% This file was created with JabRef 2.5. % Encoding: UTF8 @ARTICLE{Oeller08, author = {Lars-Erik {\"O}ller}, title = {Thomas B. Fomby and Dek Terrell, Editors, Econometric analysis of financial and economic time series, Advances in Econometrics, Volume 20, Part 2, Elsevier Ltd. (2006) 352 pages, Price, \$105, ISBN-10: 0-7623-1273-4, ISBN-13: 978-0-7623-1273-3.}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {179-183}, number = {1}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.11.001}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Oeller06, author = {Lars-Erik {\"O}ller}, title = {Michael P. Clements, Evaluating Econometric Forecasts of Economic and Financial Variables, Palgrave Texts in Econometrics, 2005, 173 pp, ISBN 1-4039-0173-2 (paperback), �19.99, ISBN 1-4039-0172-4 (hardback), �50.}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {196-198}, number = {1}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.06.004}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Oeller06a, author = {Lars-Erik {\"O}ller}, title = {Arnold Zellner, Statistics, Econometrics and Forecasting. The Stone Lectures in Economics, Cambridge University Press (2004) 163 pp, ISBN 0 521 54044 5 (paperback), \$24.99, ISBN 0 521 83287 X (hardback), \$70.}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {408-409}, number = {2}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.06.003}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Oeller03, author = {Lars-Erik {\"O}ller}, title = {Nonlinear Econometric Modeling in Time Series: Proceedings of the Eleventh International Symposium in Economic Theory,: Edited by W.A. Barnett, D.F. Hendry, S. Hylleberg, T. Ter{\"a}svirta, D. Tj{\o}stheim, and A.W. W{\"u}rtz, Cambridge University Press, 2000. ISBN: 0-521- 59424-3, pp. 227, �42.50, US\$70 (hardback).}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {756-758}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00057-8}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Oeller01, author = {Lars-Erik {\"O}ller}, title = {Forecasting Non-stationary Economic Time Series: Michael P. Clements, and David F. Hendry, The MIT Press, Cambridge, Massachusetts, 1999, ISBN 0-262-03272-4, US\$35 (Hardback)}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {133-134}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00092-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Oeller00, author = {Lars-Erik {\"O}ller}, title = {Forecasting Economic Time Series, Clements, Michael P. and Hendry, David, F., Cambridge University Press, Cambridge, England, 1998, HB US\$69.95, ISBN 0-521-63242-0, PB US\$25.95, ISBN 0-521-63242-0.}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {425-426}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00043-1}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{98i, author = {Lars-Erik {\"O}ller}, title = {Book Review (Brockwell and Davis)}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {300-301}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00021-1}, issn = {0169-2070}, key = {tagkey1998300}, keywords = {bookrev} } @ARTICLE{Oeller94, author = {Lars-Erik {\"O}ller}, title = {Modelling nonlinear economic relationships : C.W.J. Granger and T. Ter{\"a}svirta, 1993, (Oxford University Press, New York,) 187 pp., hardback \$30, ISBN 0-19-877319-6; paperback \$14.95, ISBN 0-19-877320-X}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {169-171}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90064-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Oeller92, author = {Lars-Erik {\"O}ller}, title = {Statistical analysis and forecasting of economic structural change : Peter Hackl (ed.), (Springer-Verlag, Berlin, 1989) pp. 489, \$106.00}, journal = {International Journal of Forecasting}, year = {1992}, volume = {7}, pages = {536-538}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90040-G}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Oeller90, author = {Lars-Erik {\"O}ller}, title = {Forecasting the business cycle using survey data}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {453-461}, number = {4}, abstract = {Regular business survey data are published as percentages of firms predicting higher, equal or lower values of some reference variable. Time series of such percentages do not fit production data too well. Univariate models often produce forecasts which are just as accurarate. Still, surveys contain anticipative judgement which, when combined with univariate modeling and proper filtering, may produce a good indicator for business cycle turning points. The way survey data are transformed so as to fit statistics on production seems not to be of much importance. A case study of the Finnish forest industry is offered as an example.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90021-3}, issn = {0169-2070}, keywords = {Turning point prediction, Carlson-Parking transform, Exponential smoothing, Combining forecasts, regart} } @ARTICLE{Oeller85, author = {Lars-Erik {\"O}ller}, title = {How far can changes in general business activity be forecasted?}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {135-141}, number = {2}, abstract = {An F test [Nelson, 1976] of Parzen's prediction variance horizon [Parzen, 1982] of an ARMA model yields the number of steps ahead that forecasts contain information (short memory). A special 10 year pattern in Finnish GDP is introduced as a `seasonal' in an ARMA-model. Forecasts three years ahead are statistically informative but exploiting the complete 10 year pattern raises doubts both about model memory and model validity.}, doi = {http://dx.doi.org/10.1016/0169-2070(85)90018-4}, issn = {0169-2070}, keywords = {Forecasts of business activity, Prediction variance horizon, ARMA memory, ARRM forecasts, regart} } @ARTICLE{Oeller85a, author = {Lars-Erik {\"O}ller}, title = {Macroeconomic forecasting with a vector arima model : A case study of the finnish economy}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {143-150}, number = {2}, abstract = {The vector ARIMA (VARIMA) model is a multivariate generalization of the univariate ARIMA model. VARIMA can accomodate assumptions on exogeneity and on contemporaneous relationships. Exogeneous forecasts and non-zero future shocks make it possible to generate alternative forecasts. In a case study VARIMA well describes developments in the 1970's and successfully competes with judgemental methods and ARIMA in providing a general outlook of the early 1980's.}, doi = {http://dx.doi.org/10.1016/0169-2070(85)90019-6}, issn = {0169-2070}, keywords = {VARIMA, Macroeconomic forecasts, Causal assumptions, Adjustment of forecasts, regart} } @ARTICLE{OeS08, author = {Lars-Erik {\"O}ller and P{\"a}r Stockhammar}, title = {Nicolas Carnot, Vincent Koen and Bruno Tissot, Economic Forecasting , Palgrave Macmillan (2005) ISBN 1-4039-3653-6 (hardback), �65, ISBN 1-4039-3653-4 (paperback), \$22.50, 315pp..}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {183-184}, number = {1}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.12.005}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{OeT96, author = {Lars-Erik {\"O}ller and Christer Tallbom}, title = {Smooth and timely business cycle indicators for noisy Swedish data}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {389-402}, number = {3}, abstract = {Noise in statistical time series is often overlooked when selecting the best forecasting model by minimizing forecast errors. An error implies that one knows the true (noise-free) outcome. Instead of merely trying to forecast a noisy outcome, we construct entirely new indicators, based on business tendency survey data and statistical time series. False turning point signals are avoided by exponential smoothing. A special trigger is found in the joint behavior of model generated smoothed and unsmoothed forecasts, by which smoothing can be switched off in sharp turns, and this avoids late turning point signals that would occur with smoothed data.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00614-1}, issn = {0169-2070}, keywords = {Business cycle indicators, Business tendency surveys, Noisy data, Exponential smoothing, Kalman filter, regart} } @ARTICLE{OeT07, author = {Lars-Erik {\"O}ller and Alex Teterukovsky}, title = {Quantifying the quality of macroeconomic variables}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {205-217}, number = {2}, abstract = {Methods to quantify the quality of a macroeconomic statistical time series are presented. The integrated measures are based on a combination of how predictable the series is and how much its statistics need to be revised. An informationwindow based on signal-to-noise ratios provides a snapshot of the quality. A formulation of information in terms of entropy is also considered. Our approach allows testing of whether a forecast or a preliminary value is informative. Concavity and monotonic convergence of information accrual are discussed.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.01.006}, issn = {0169-2070}, keywords = {Statistical quality, Forecast errors, Revisions, Information measures, Entropy, regart} } @ARTICLE{OeWH+96, author = {Lars-Erik {\"O}ller and Anders Westlund and Peter Hackl and Kajal Lahiri}, title = {Forecasting in the manufacturing industry}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {325-326}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(96)00667-X}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Oenkal09, author = {Dilek {\"O}nkal}, title = {Comments on Effective forecasting and judgmental adjustments: An empirical evaluation and strategies forimprovement in supply-chain planning}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {30-31}, number = {1}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.09.003}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{OeM96, author = {Dilek {\"O}nkal and G{\"u}lnur Muradoglu}, title = {Effects of task format on probabilistic forecasting of stock prices}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {9-24}, number = {1}, abstract = {This study aims to explore the differences in various dimensions of forecasting accuracy that may result from the task format used to elicit the probabilistic forecasts. In particular, we examine the effects of using multiple-interval and dichotomous formats on the performance of portfolio managers' probabilistic forecasts of stock prices. Probabilistic forecasts of these experts are compared with those provided by semi-experts comprised of other banking professionals trained in portfolio management, as well as with forecasts provided by a novice group. The results suggest that the task format used to elicit the probabilistic forecasts has a differential impact on the performance of experts, semi-experts, and novices. The implications of these findings for financial forecasting are discussed and directions for future research are given.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00633-8}, issn = {0169-2070}, keywords = {Subjective probability, Probability forecasting, Judgmental forecasting, Stock-price forecasting, Task format, regart} } @ARTICLE{AJ87, author = {David A. Aaker and Robert Jacobson}, title = {The sophistication of `naive' modeling}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {449-451}, number = {3-4}, abstract = {The relatively high predictive power of a naive market share model is due to (1) its similarity to the reduced form representation of the underlying model and (2) the comparison with forecasts generated from structural models that are likely to be misspecified.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90039-2}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{Abberger07, author = {Klaus Abberger}, title = {Qualitative business surveys and the assessment of employment -- A case study for Germany}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {249-258}, number = {2}, abstract = {Business tendency surveys are a commonly accepted instrument for the assessment of the current business cycle course. Most of these surveys rely on qualitative questions about the current situation of the firms and about their expectations for the coming months. This paper analyzes whether qualitative questions about employment expectations are useful to assessing actual employment changes. In Germany the Ifo Institute specialises in business surveys. The German Ifo data are investigated using three different approaches: smoothing techniques are used to help in dating turning points in the course of the series; error correction models are used to analyze the general lead/lag relationships and Probit models are used to estimate a threshold for the survey-based indicator which helps to differentiate between an increase and a decrease in employment. All three methods indicate that the employment expectations are a leading indicator of actual employment changes.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.10.002}, issn = {0169-2070}, keywords = {Business tendency surveys, Employment, Employment expectations, Turning points, Granger-causality, Error correction models, regart} } @ARTICLE{99c, author = {Gerald W. Abbott}, title = {Book Review}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {206-207}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00080-6}, issn = {0169-2070}, key = {tagkey1999206}, keywords = {bookrev} } @ARTICLE{AF98, author = {Ahmed Abdi and Robert Fildes}, title = {Product Review}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {151-153}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00011-9}, issn = {0169-2070}, key = {tagkey1998151}, keywords = {prodrev} } @ARTICLE{Abeele85, author = {P. Vanden Abeele}, title = {P. Vanden Abeele, The index of consumer sentiment: predictability and predictive power in the EEC, Journal of Economic Psychology 3 (1983), pp. 1-17.}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {309-309}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(85)80051-0}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Abeysinghe00, author = {Tilak Abeysinghe}, title = {Modeling variables of different frequencies}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {117-119}, number = {1}, abstract = {The transformation introduced in Abeysinghe (1998: International Journal of Forecasting 14, 505-513) to model dynamic regressions with variables of different frequencies creates an autocorrelation problem when applied to flow variables. This exercise shows that the magnitude of the autocorrelation is rather small and offers a solution to the problem.}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00028-X}, issn = {0169-2070}, keywords = {Flow variables, Autocorrelation, IV estimator, regart} } @ARTICLE{Abeysinghe98, author = {Tilak Abeysinghe}, title = {Forecasting Singapore's quarterly GDP with monthly external trade}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {505-513}, number = {4}, abstract = {In this paper we suggest a methodology to formulate a dynamic regression with variables observed at different time intervals. This methodology is applicable if the explanatory variables are observed more frequently than the dependent variable. We demonstrate this procedure by developing a forecasting model for Singapore's quarterly GDP based on monthly external trade. Apart from forecasts, the model provides a monthly distributed lag structure between GDP and external trade, which is not possible with quarterly data.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00038-7}, issn = {0169-2070}, keywords = {Variables observed at different time intervals, Non-linear dynamic regression, regart} } @ARTICLE{Abramowitz08, author = {Alan I. Abramowitz}, title = {It's about time: Forecasting the 2008 presidential election with the time-for-change model}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {209-217}, number = {2}, abstract = {The popular vote for president can be predicted accurately before the national nominating conventions based on three factors: the incumbent president's approval rating at mid-year, the growth rate of the economy during the first half of the election year, and the length of time that the president's party has controlled the White House. Regardless of who wins the Democratic and Republican nominations, 2008 will be a time-for-change presidential election. Based on President Bush's approval rating in June of 2007, the recent growth rate of the economy, and the fact that the Republican Party will have controlled the White House for eight years, the Democratic nominee would be predicted to win the national popular vote by a comfortable margin. For the Republican nominee to have a reasonable chance of winning the 2008 presidential election, there would have to be a dramatic improvement in President Bush's approval rating during the next 12 months.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.02.002}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{ABE+96, author = {Bruce Abramson and John Brown and Ward Edwards and Allan Murphy and Robert L. Winkler}, title = {Hailfinder: A Bayesian system for forecasting severe weather}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {57-71}, number = {1}, abstract = {Hailfinder is a Bayesian system that combines meteorological data and model with expert judgment, based on both experience and physical understanding, to forecast severe weather in Northeastern Colorado. The system is based on a model, known as a belief network (BN), that has recently emerged as the basis of some powerful intelligent systems. Hailfinder is the first such system to apply these Bayesian models in the realm of meteorology, a field that has served as the basis of many past investigations of probabilistic forecasting. The design of Hailfinder provides a variety of insights to designers of other BN-based systems, regardless of their fields of application.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00664-8}, issn = {0169-2070}, keywords = {Bayesian, Belief networks, Meteorology, System design, Weather forecasting, Intelligent systems, Elicitation, regart} } @ARTICLE{AC95, author = {Bruce Abramson and Robert Clemen}, title = {Probability forecasting}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {1-4}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(94)02000-F}, issn = {0169-2070} } @ARTICLE{AF95, author = {Bruce Abramson and Anthony Finizza}, title = {Probabilistic forecasts from probabilistic models: A case study in the oil market}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {63-72}, number = {1}, abstract = {Probabilistic forecasts, probabilistic models, and contingent policy recommendations are inextricably intertwined. This article describes a case study in the use of inherently probabilistic belief network models to produce probabilistic forecasts of average annual oil prices. Belief networks are flexible enough to capture both standard, data-driven economic variables, and quantified expert judgements about the politics of the oil market (particularly the production and capacity policies of key OPEC members). These variables are interrelated by a combination of algebraic formulas, conditional probabilities, and econometric relations. The resultant network is used to test the impact of a variety of different scenarios. The probabilistic forecasts generated by running Monte Carlo analyses on these scenario networks provide corporate decision-makers with useful insights and recommendations.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)02004-9}, issn = {0169-2070}, keywords = {Probability, Decision analysis, Behavioral forecasting, Modeling, System design, Artificial Intelligence, Influence diagrams, Politics, Economics, Energy, regart} } @ARTICLE{AF91, author = {Bruce Abramson and Anthony Finizza}, title = {Using belief networks to forecast oil prices}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {299-315}, number = {3}, abstract = {Belief networks are knowledge-based models, developed by segments of the artificial intelligence and decision analysis communities, that have the potential to become important forecasting tools. ARCO1, currently under development at the Atlantic Richfield Company (ARCO) and the University of Southern California (USC), is the most advanced implementation of these models in a financial forecasting setting. ARCO1's underlying belief network is an artificial intelligence knowledge base; it models all variables believed to have an impact on the crude oil market. Decision analytic elicitation techniques collect information about the market's variables, their value ranges, and their interrelationsships. A pictorial market model - developed on a MAC II - facilitates consensus among the members of the forecasting team. The system forecasts crude oil prices via Monte Carlo analyses of the network. Several different models of the oil market have been developed; the system's ability to be updated quickly in light of recent events in the Persian Gulf highlights its flexibility.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90004-F}, issn = {0169-2070}, keywords = {Belief networks, Influence diagrams, Simulation, Artificial intelligence, Decision analysis, Judgement, Energy forecasting, Oil markets, regart} } @ARTICLE{AAM91, author = {Gail Adams and P. Geoffrey Allen and Bernard J. Morzuch}, title = {Probability distributions of short-term electricity peak load forecasts}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {283-297}, number = {3}, abstract = {Electric companies schedule generator maintenance so as to equalize the risks of capacity shortfall. Distributions of peak loads for given future weeks, months and seasons provide information on the probability that a critical load level will be exceeded in the given time period. Day-to-day fluctuations in peak loads were assumed to be directly caused by weather variables whose distributions vary by week throughout the year. Forecast distributions of weekly peak loads were computed by non-parametric simulation and re-estimation for three regression models: (1) weekly peak loads dependent on time trend and dummy variables, (2) weekly peak loads dependent on socioeconomic and weather variables, and (3) a daily version of (2). Comparisons of actual peak loads against within-sample and post-sample forecast distributions of peak loads showed that (1) and (2) were statistically equivalent but (3) was significantly worse.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90003-E}, issn = {0169-2070}, keywords = {Forecast distributions, Bootstrap method, Electricity demand, Extreme valuesregart} } @ARTICLE{AD97, author = {Philip D. Adams and Peter B. Dixon}, title = {Generating detailed commodity forecasts from a computable general equilibrium model}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {223-236}, number = {2}, abstract = {The largest computable general equilibrium (CGE) models currently in operation produce forecasts for about 100 commodities (goods and services). This level of detail may seem overwhelming to macroeconomists but is often inadequate for micro planning. For example, a forecast for business services (a typical commodity at the 100-level) is of marginal interest in planning educational programs for sub-categories of business services such as accountancy, advertising and architecture. As a step towards generating information for micro planning, this paper describes a tops-down method for disaggregating CGE forecasts. The method relies on detailed sales data often collected by input-output sections of statistical agencies. An application is reported in which forecasts from a 114-commodity CGE model are disaggregated into forecasts for 780 commodities. Within each of the 114 core commodities, differences in prospects are forecast for sub-commodities reflecting differences in their sales patterns and in the degree to which they face import competition.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00713-3}, issn = {0169-2070}, keywords = {Computable general equilibrium models, Disaggregated economic forecasting, Input-output data, Microeconomic forecasting, regart} } @ARTICLE{ADM+94, author = {Philip D. Adams and Peter B. Dixon and Daina McDonald and G. A. Meagher and Brian R. Parmenter}, title = {Forecasts for the Australian economy using the MONASH model}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {557-571}, number = {4}, abstract = {This paper describes annual forecasts for the period 1990-1991 to 1996-1997 made with a new CGE model of the Australian economy called MONASH. Using MONASH, we project the implications for the structure of the economy of macroeconomic forecasts made by conventional, less formal methods. MONASH has enough dynamics to enable it to track, at the micro level, business-cycle phenomena which are assumed in the macro forecasts. The CGE model is very detailed, distinguishing 112 industries, 6 regions and up to 283 labour-force occupations. Apart from the level of detail, the strength of our MONASH forecasting system is that it produces forecasts which can be interpreted fully in terms of the model's theory, data and the assumptions underlying the exogenous input.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90024-8}, issn = {0169-2070}, keywords = {Forecasting, Sectors, Regions, Occupations, Economic models, Australiaregart} } @ARTICLE{Adcock95, author = {Chris Adcock}, title = {Non-linear dynamics chaos and econometrics : M Hashem Pesaran and Simon M Potter, (Wiley, Chichester), 244 pp., hardback, \$39.95, ISBN 04719 39420.}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {599-601}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(95)90003-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Adcock94, author = {Chris Adcock}, title = {Modelling reality and personal modelling : Richard Flavell, (ed.), 1993, Contributions to Management Science, (Physica-Verlag, Heidelberg), 407 pp., paperback, DM120, ISBN 3-7908-0682-X}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {466-469}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90078-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{98d, author = {C. J. Adcock}, title = {Book Review}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {148-149}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00054-X}, issn = {0169-2070}, key = {tagkey1998148}, keywords = {bookrev} } @ARTICLE{Adya02, author = {Monica Adya}, title = {Research on Forecasting}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {481-482}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00005-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Adya00, author = {Monica Adya}, title = {Corrections to rule-based forecasting: findings from a replication}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {125-127}, number = {1}, abstract = {Rule-Based Forecasting (RBF) is an expert system that combines forecasts from simple extrapolation methods based on features of time series. In this study, we provide corrections to ten of the 99 rules contained in RBF. These corrections were identified during a replication of RBF. Empirical comparisons indicate that the corrections did not lead to a noticeable improvement in accuracy when tested against some of the original data. However, in light of the fact that several studies are extending the work on RBF, it is important to report on these corrections to RBF.}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00034-5}, issn = {0169-2070}, keywords = {Calibration, Validation, Rule-based systems, regart} } @ARTICLE{AAC+00, author = {Monica Adya and J. Scott Armstrong and Fred Collopy and Miles Kennedy}, title = {An application of rule-based forecasting to a situation lacking domain knowledge}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {477-484}, number = {4}, abstract = {Rule-based forecasting (RBF) uses rules to combine forecasts from simple extrapolation methods. Weights for combining the rules use statistical and domain-based features of time series. RBF was originally developed, tested, and validated only on annual data. For the M3-Competition, three major modifications were made to RBF. First, due to the absence of much in the way of domain knowledge, we prepared the forecasts under the assumption that no domain knowledge was available. This removes what we believe is one of RBF's primary advantages. We had to re-calibrate some of the rules relating to causal forces to allow for this lack of domain knowledge. Second, automatic identification procedures were used for six time-series features that had previously been identified using judgment. This was done to reduce cost and improve reliability. Third, we simplified the rule-base by removing one method from the four that were used in the original implementation. Although this resulted in some loss in accuracy, it reduced the number of rules in the rule-base from 99 to 64. This version of RBF still benefits from the use of prior findings on extrapolation, so we expected that it would be substantially more accurate than the random walk and somewhat more accurate than equal weights combining. Because most of the previous work on RBF was done using annual data, we especially expected it to perform well with annual data.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00074-1}, issn = {0169-2070}, keywords = {Causal forces, Expert systems, Feature identification, Heuristics, Seasonality, Time series, regart} } @ARTICLE{ACA+01, author = {Monica Adya and Fred Collopy and J. Scott Armstrong and Miles Kennedy}, title = {Automatic identification of time series features for rule-based forecasting}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {143-157}, number = {2}, abstract = {Rule-based forecasting (RBF) is an expert system that uses features of time series to select and weight extrapolation techniques. Thus, it is dependent upon the identification of features of the time series. Judgmental coding of these features is expensive and the reliability of the ratings is modest. We developed and automated heuristics to detect six features that had previously been judgmentally identified in RBF: outliers, level shifts, change in basic trend, unstable recent trend, unusual last observation, and functional form. These heuristics rely on simple statistics such as first differences and regression estimates. In general, there was agreement between automated and judgmental codings for all features other than functional form. Heuristic coding was more sensitive than judgment and consequently, identified more series with a certain feature than judgmental coding. We compared forecast accuracy using automated codings with that using judgmental codings across 122 series. Forecasts were produced for six horizons, resulting in a total of 732 forecasts. Accuracy for 30% of the 122 annual time series was similar to that reported for RBF. For the remaining series, there were as many that did better with automated feature detection as there were that did worse. In other words, the use of automated feature detection heuristics reduced the costs of using RBF without negatively affecting forecast accuracy.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00079-6}, issn = {0169-2070}, keywords = {Changing trend, Extrapolation, Functional form, Heuristics, Level discontinuities, Outliers, RBF, Unstable trend, Unusual last observation, regart} } @ARTICLE{AKO09, author = {P. Ager and M. Kappler and S. Osterloh}, title = {The accuracy and efficiency of the Consensus Forecasts: A further application and extension of the pooled approach}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {167-181}, number = {1}, abstract = {This paper analyses the performance of consensus forecasts, published by Consensus Economics, for 12 countries over the period from 1996 to 2006 regarding bias and information efficiency. A pooled approach is employed which permits the evaluation of all forecasts for each target variable over 24 horizons simultaneously. It is shown how the pooled approach needs to be set up in order to accommodate the forecasting scheme of the consensus forecasts. Furthermore, the pooled approach is extended by a sequential test for detecting the critical horizon after which the forecast should be regarded as biased. Moreover, heteroscedasticity in the form of target-year-specific variances of macroeconomic shocks is taken into account. The results show that in the analysed period, which was characterised by pronounced macroeconomic shocks, several countries show biased forecasts, especially with forecast horizons of more than 12 months. In addition, information efficiency has to be rejected in almost all cases.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.11.008}, issn = {0169-2070}, keywords = {Evaluating forecasts, Business cycle forecasting, Inflation forecasting, Consensus forecasts, Bias and efficiency, regart} } @ARTICLE{Ahlburg92, author = {Dennis A. Ahlburg}, title = {Predicting the job performance of managers: What do the experts know?}, journal = {International Journal of Forecasting}, year = {1992}, volume = {7}, pages = {467-472}, number = {4}, abstract = {US personnel experts, like their New Zealand, UK, and French colleagues, do not know or apply the research base of their profession when selecting managers. Students do know which are the most valid predictors but do not apply them to their work. Nor does it appear that predictors are chosen on the grounds of technical feasibility, cost, or legal defensibility. It seems that practitioners do not believe the research evidence, or are prevented from using it by established practices in their organizations, or they consider other issues more important than validity in the choice of methods for selecting managers.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90030-D}, issn = {0169-2070}, keywords = {Selection, Prediction, Job performance, Validity, regart} } @ARTICLE{Ahlburg92a, author = {Dennis A. Ahlburg}, title = {Error measures and the choice of a forecast method}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {99-100}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90010-7}, issn = {0169-2070}, keywords = {othercom,} } @ARTICLE{Ahlburg87, author = {Dennis A. Ahlburg}, title = {World population projections 1985: Short- and long-term estimates by age and sex with related demographic statistics : Myel Vu, (Johns Hopkins University Press for the World Bank, Baltimore, MD, 1985) pp. 451, \$50.00}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {336-338}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90018-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Ahlburg85, author = {Dennis A. Ahlburg}, title = {Alternative forecasts of U.S. school enrollments to 2050 when will a trend bend?}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {37-47}, number = {1}, abstract = {This paper presents alternative forecasts of enrollments in grades K-12 for the period 1980-2050. The forecasts suggest that enrollments will continue to decline in the short run, perhaps by more than is currently recognized. The long-run position is, however, different. By 1995, K-8 enrollment should approximate its 1969 maximum, while by 2000 enrollment in grades 9-12 should be within 5% of its 1976 maximum. These increases will not be uniform across the nation. The most significant increases will occur in the South and West, with enrollments in the Northeast and Atlantic regions at least stabilizing.}, doi = {http://dx.doi.org/10.1016/S0169-2070(85)80069-8}, issn = {0169-2070}, keywords = {Enrollment forecasts -- national, regional, School planners, Cyclical enrollments, regart} } @ARTICLE{AL92, author = {Dennis A. Ahlburg and Kenneth C. Land}, title = {Population forecasting: Guest editors' introduction}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {289-299}, number = {3}, note = {Population Forecasting}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90048-E}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{AL07, author = {Dennis Ahlburg and Thomas Lindh}, title = {Long-run income forecasting}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {533-538}, number = {4}, abstract = {The papers in this collection show that the growing body of knowledge on economic growth can be used to improve forecasts of future economic performance and other variables related to economic growth. The papers also show that assumptions matter and that the sectoral sources and the determinants of growth matter, and that not all members of the population benefit equally from economic growth.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.10.003}, issn = {0169-2070}, keywords = {Long-term forecasting, Economic growth, Age structure, Convergence, Demography, regart} } @ARTICLE{AL09, author = {Katja Ahoniemi and Markku Lanne}, title = {Joint modeling of call and put implied volatility}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {239-258}, number = {2}, abstract = {This paper exploits the fact that implied volatilities calculated from identical call and put options have often been empirically found to differ, although they should be equal in theory. We propose a new bivariate mixture multiplicative error model and show that it is a good fit to Nikkei 225 index call and put option implied volatility (IV). A good model fit requires two mixture components in the model, allowing for different mean equations and error distributions for calmer and more volatile days. Forecast evaluation indicates that, in addition to jointly modeling the time series of call and put IV, cross effects should be added to the model: put-side implied volatility helps forecast call-side IV, and vice versa. Impulse response functions show that the IV derived from put options recovers faster from shocks, and the effect of shocks lasts for up to six weeks.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2009.01.012}, issn = {0169-2070}, keywords = {Implied volatility, Option markets, Volatility forecasting, MEM models, Impulse responses, regart} } @ARTICLE{AG92, author = {Celal Aksu and Sevket I. Gunter}, title = {An empirical analysis of the accuracy of SA, OLS, ERLS and NRLS combination forecasts}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {27-43}, number = {1}, abstract = {Theoretically, the efficiency of OLS combination forecasts can be improved by imposing linear equality or nonnegativity restrictions on the combination weights. In Equality Restricted Least Squares (ERLS) combinations, the weights are restricted to sum to unity, whereas in Nonnegativity Restricted Least Squares (NRLS) combinations, the weights are constrained to be nonnegative. There is little empirical evidence on the relative peformance of OLS, ERLS and NRLS combination forecasts. In this study, we provide empirical results on the relative accuracy of OLS, ERLS, NRLS and Simple Average (SA) ex ante combined forecasts using three macroeconomic and thirty-seven firm specific series. The empirical results reveal that combined forecasts are not always more accurate. NRLS and SA combinations almost always outperform OLS and ERLS combinations, while NRLS combinations are at least as robust and accurate as SA combinations. On average, ERLS combination models without a constant term produce more accurate forecasts than OLS combination models.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90005-T}, issn = {0169-2070}, keywords = {Combining forecasts, Accuracy of forecasts, Simple average, Ordinary least squares, Equality restricted least squares, Inequality restricted least squares, Gross national product, Money supply, Treasury bill rates, Accounting earnings, regart} } @ARTICLE{AN91, author = {Celal Aksu and Jack Y. Narayan}, title = {Forecasting with vector ARMA and state space methods}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {17-30}, number = {1}, abstract = {The theory and practice of modeling with vector and state space methods are reviewed. Currently available computer software packages for these techniques are discussed and compared. Further, the model identification and estimation procedures employed by these packages are illustrated in detail using a data set consisting of monthly observations of `90-day treasury bill rates' and `changes in money supply'. In addition, the usefulness of the vector and state space methods are tested empirically by evaluating the out-of-sample one-step-ahead forecasting performance of the univariate and bivariate models of treasury bill rates obtained from each method/package.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90029-U}, issn = {0169-2070}, keywords = {Forecast evaluation, Vector methods, State space methods, Forecast accuracy, Vector and state space software, regart} } @ARTICLE{Alba93, author = {Enrique de Alba}, title = {Constrained forecasting in autoregressive time series models: A Bayesian analysis}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {95-108}, number = {1}, abstract = {A Bayesian approach is used to derive constrained and unconstrained forecasts in an autoregressive time series model. Both are obtained by formulating an AR(p) model in such a way that it is possible to compute numerically the predictive distribution for any number of forecasts. The types of constraints considered are that a linear combination of the forecasts equals a given value. This kind of restriction is applied to forecasting quarterly values whose sum must be equal to a given annual value. Constrained forecasts are generated by conditioning on the predictive distribution of unconstrained forecasts. The procedures are applied to the Quarterly GNP of Mexico, to a simulated series from an AR(4) process and to the Quarterly Unemployment Rate for the United States.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90057-T}, issn = {0169-2070}, keywords = {Conditional, Predictive, Monte Carlo, regart} } @ARTICLE{AA03, author = {Kevin Albertson and Jonathan Aylen}, title = {Forecasting the behaviour of manufacturing inventory}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {299-311}, number = {2}, abstract = {Forecasting levels of stocks held by manufacturing industry is problematic. Stocks are the most volatile component of GDP. The data itself is subject to chronic revision. Yet, forecasting inventory changes in the supply chain is crucial for firms trying to manage output. The paper reports a successful approach to forecasting UK manufacturing stock behaviour sponsored by a leading European metals manufacturer. The model exploits the seasonality of stock build-ups and run-downs. (Existing econometric approaches rely on seasonally adjusted data.) The forecasting performance of our model is compared to alternative time series approaches. Use of raw, unadjusted data implies markedly different specifications from those in the established literature. In particular, we find no significant evidence of a structural break in UK stockholding behaviour in our sample period and the absence of cointegration between stocks and output suggests the conventional error correction approach is spurious, as well as giving poor forecasts.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00147-9}, issn = {0169-2070}, keywords = {Inventory behaviour, Manufacturing, Econometric models, Time series, Seasonality, ADL, ECM, Periodicity, regart} } @ARTICLE{AA99, author = {Kevin Albertson and Jonathan Aylen}, title = {Forecasting using a periodic transfer function: with an application to the UK price of ferrous scrap}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {409-419}, number = {4}, abstract = {The familiar concept of cointegration enables us to determine whether or not there is a long-run relationship between two integrated time series. However, this may not capture short-run effects such as seasonality. Two series which display different seasonal effects can still be cointegrated. Seasonality may arise independently of the long-run relationship between two time series or, indeed, the long-run relationship may itself be seasonal. The market for recycled ferrous scrap displays these features: the US and UK scrap prices are cointegrated, yet the local markets exhibit different forms of seasonality. The paper addresses the problem of using both cointegrating and seasonal relationships in forecasting time series through the use of periodic transfer function models. We consider the problems of testing for cointegration between series with differing seasonal patterns and develop a periodic transfer function model for the US and UK scrap markets. Forecast comparisons with other time series models suggest that forecasting efficiency may be improved by allowing for periodicity but that such improvement is by no means guaranteed. The correct specification of the periodic component of the model is critical for forecast accuracy.}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00020-5}, issn = {0169-2070}, keywords = {Cointegration, Ferrous scrap, Forecasting competition, Periodic transfer function, Seasonality, Recycling, regart} } @ARTICLE{AA96, author = {Kevin Albertson and Jonathan Aylen}, title = {Modelling the Great Lakes freeze: forecasting and seasonality in the market for ferrous scrap}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {345-359}, number = {3}, abstract = {The paper offers a methodology for modelling seasonality in a volatile commodity market. It gives a practical example of the way seasonal factors can be incorporated into industrial forecasts. Recycled ferrous scrap is a widely traded commodity used in the steel and foundry industries. This paper considers the problems of forecasting scrap prices in the US market. Scrap prices display seasonal behaviour as a result of weather and patterns of industrial production. We consider various ways of modelling this seasonality, use of seasonal vector autoregression, the concept of seasonal integration and the use of dummy variables. A seasonal vector autoregression (VAR) is developed. Here the quarterly series is decomposed into four annual series, one for each quarter. We regress each of these resultant series on its own lags and lags of other series, so developing a periodic autoregressive model. A series of tests enables us to determine the type of seasonality exhibited by the data. The simplest form of seasonal adjustment using seasonal dummy variables turns out to be the best for forecasting US scrap prices. Use of the test procedure suggests that employing seasonal dummies is the correct specification in this case. Inclusion of seasonal effects usually improves the estimation and forecasting performance of time series models. Comparison of a range of alternative forecasting models suggests a periodic autoregression only forecasts satisfactorily in the short run. ARIMA models with seasonal dummies show the best performance. A long lag length is necessary to capture long run cyclical effects.}, doi = {http://dx.doi.org/10.1016/0169-2070(96)00669-3}, issn = {0169-2070}, keywords = {Autoregressive modelling, ARIMA forecasting, Ferrous scrap, Seasonality, Sector modellingregart} } @ARTICLE{Alexander85, author = {Don Alexander}, title = {Gary Giroux and Peter Rose, Financial Forecasting and Banking, UMI Research Press, London (1981), p. 196. \$39.95}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {316-317}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(85)80061-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{ABT87, author = {Don Alexander and Richard T. Baillie and Lee Thomas}, title = {Introduction}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {1-1}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90074-4}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{AT87, author = {Don Alexander and Lee R. Thomas}, title = {Monetary/asset models of exchange rate determination : How well have they performed in the 1980's?}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {53-64}, number = {1}, abstract = {This study compares the performance of various structural exchange rate models based on the methodology developed by Meese and Rogoff (1983 a,b, 1985). means of improving forecast performance.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90078-1}, issn = {0169-2070}, keywords = {Exchange rates, Forecasting accuracy, Kalman filter, Random walk, regart} } @ARTICLE{Alho08, author = {Juha Alho}, title = {Aggregation across countries in stochastic population forecasts}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {343-353}, number = {3}, abstract = {Stochastic methods of multi-state population modeling are less developed than methods for single states for two reasons. First, the structure of a multi-state population is inherently more complex than that of a single state because of state-to-state transitions. Second, estimates of cross-state correlations of the vital processes are a largely uncharted territory. Unlike multi-state lifetable theory, in forecasting applications the role of directed flows from state to state is often less important than the overall coherence of the assumptions concerning the vital processes. This is the case in the context of the European Union. Thus, a simplified approach is feasible, in which migration is represented by state-specific net numbers of migrants. This allows the use of existing single-state software, when simulations are suitably organized, in a multi-state setting. To address the second problem, we provide empirical estimates of cross-country covariances in the forecast uncertainty of fertility, mortality, and net migration. Together with point forecasts of these parameters that are coherent across countries, this produces coherent forecasts for aggregates of countries. The finding is that models for intermediate correlations are necessary for a proper accounting of forecast uncertainty at the aggregate level, in this case the European Union.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.05.003}, issn = {0169-2070}, keywords = {Correlations, Demography, Multi-state, Principal components, regart} } @ARTICLE{Alho91, author = {J. Alho}, title = {Uncertainty in national population forecasting: Issues, backgrounds, analyses, recommendations : N.C. Keilman, (Swets \& Zeitlinger, 1990) pp. 211}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {392-393}, number = {3}, doi = {DOI:10.1016/0169-2070(91)90018-Q}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Alho92, author = {Juha M. Alho}, title = {The magnitude of error due to different vital processes in population forecasts}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {301-314}, number = {3}, abstract = {The propagation of error in stochastic cohort-component forecasts of population is discussed. The uncertainty of the forecasts is due to uncertain estimates of the jump-off population, and to errors in the forecasts of the vital rates: fertility, mortality, and migration. Empirically based (ex post) estimates of each source are presented and propagated first through a simplified analytical model of population growth. Being analytic, the model readily permits the assessment of the role of each component in the total error. Then, we consider numerical estimates based on the (ex ante) errors of an actual vector ARIMA forecast of the vital rates and propagate them through a forecast of the US female population. The results agree in broad outline with those of the analytical model. In particular, the uncertainty in the forecasts of fertility is shown to be so much higher than that in the other sources that the latter can be ignored in the propagation of error calculations for those cohorts that are born after the jump-off year of the forecast. This simplifies the propagation of error calculations considerably. However, both the uncertainty of the jump-off population, migration, and mortality needs to be considered in the propagation of error for those alive at the jump-off time of the forecast.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90049-F}, issn = {0169-2070}, keywords = {Fertility, Migration, Mortality, Propagation of Error, regart} } @ARTICLE{Alho90, author = {Juha M. Alho}, title = {Stochastic methods in population forecasting}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {521-530}, number = {4}, abstract = {This paper presents a stochastic version of the demographic cohort-component method of forecasting future population. In this model the sizes of future age-sex groups are non-linear functions of random future vital rates. An approximation to their joint distribution can be obtained using linear approximations or simulation. A stochastic formulation points to the need for new empirical work on both the autocorrelations and the cross-correlations of the vital rates. Problems of forecasting declining mortality and fluctuating fertility are contrasted. A volatility measure for fertility is presented. The model can be used to calculate approximate prediction intervals for births using data from deterministic cohort-component forecasts. The paper compares the use of expert opinion in mortality forecasting with simple extrapolation techniques to see how useful each approach has been in the past. Data from the United States suggest that expert opinion may have caused systematic bias in the forecasts.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90030-F}, issn = {0169-2070}, keywords = {Cohort-component, Expert opinion, Fertility, Mortality, Volatility, regart} } @ARTICLE{AV06, author = {Juha M. Alho and Reijo Vanne}, title = {On predictive distributions of public net liabilities}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {725-733}, number = {4}, abstract = {The analysis of the sustainability of public sector finances requires an accounting of all future revenues and all future spending that we would expect, under current tax laws and current entitlements. The classical calculation does not acknowledge the inherent uncertainty of the future economic and demographic developments, so the results can be misleading. Our aim is to produce a more robust summary of the sustainability of the public sector than the one currently available. By taking a forecasting point of view, our formulation takes into account the uncertainty of future productivity, stock and bond markets, and demography. Methodological complications that arise in the stochastic setting are discussed. Estimates of the relative roles of economics and demographics in the uncertainty of public net liabilities are presented.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.11.005}, issn = {0169-2070}, keywords = {Demography, Discounting, Fiscal sustainability, Generational accounting, Population forecasting, Stochastic methods, regart} } @ARTICLE{Alien94, author = {P. Geoffrey Alien}, title = {Economic forecasting in agriculture: Reply}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {601-602}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90028-0}, issn = {0169-2070} } @ARTICLE{Allen97, author = {Geoff Allen}, title = {Model selection and forecasting ability of theory-constrained food demand systems : T.L. Kastens and G.W. Brester, 1996, American journal of agricultural economics, 78, 301-312}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {150-151}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00723-6}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Allen09, author = {P. Geoffrey Allen}, title = {Richard S. Markovits , Truth or Economics: On the Definition, Prediction, and Relevance of Economic Efficiency, Yale University Press, New Haven (2008), p. x+507 pp..}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {629 - 630}, number = {3}, note = {Special Section: Time Series Monitoring}, doi = {10.1016/j.ijforecast.2009.02.004}, issn = {0169-2070} } @ARTICLE{Allen09a, author = {P. Geoffrey Allen}, title = {Comments on 'Forecasting economic and financial variables with global VARs'}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {676 - 679}, number = {4}, note = {Special section: Decision making and planning under low levels of predictability}, doi = {10.1016/j.ijforecast.2009.05.018}, issn = {0169-2070} } @ARTICLE{Allen08, author = {P. Geoffrey Allen}, title = {Peter G.M. Swann, Putting econometrics in its place: A new direction in applied economics , Edward Elgar, Cheltenham (2006) ISBN 978 1 85898 305 9 xiv + 250 pp..}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {177-179}, number = {1}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.09.004}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Allen04, author = {P. Geoffrey Allen}, title = {Environmental Foresight and Models: A Manifesto: Edited by M.B. Beck, Elsevier Science, Oxford, 2003. 473 pp.; \$120, ISBN 0-080-44086-X}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {144-148}, number = {1}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.11.002}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Allen03, author = {P. Geoffrey Allen}, title = {Maddala, G.S., 'Econometrics in the 21st Century,' pp. 265-284}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {763-764}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00061-X}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Allen01, author = {P. Geoffrey Allen}, title = {Diebold, F.X. and Kilian, L. (2000) Unit-root tests are useful for selecting forecasting models. Journal of Business and Economic Statistics, 18, 265-273.}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {323-325}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00095-9}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Allen94, author = {P. Geoffrey Allen}, title = {Economic forecasting in agriculture}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {81-135}, number = {1}, abstract = {Forecasts of agricultural production and prices are intended to be useful for farmers, governments, and agribusiness industries. Because of the special position of food production in a nation's security, governments have become both principal suppliers and main users of agricultural forecasts. They need internal forecasts to execute policies that provide technical and market support for the agricultural sector. Government publications routinely provide private decision makers with commodity price and output forecasts at regional and national levels and at various horizons. Routine forecasts are not found in the agricultural economics journals that are the sources for most of this review. The review emphasizes methodological contributions and changes. Short-term output or `outlook' forecasting uses a unique form of leading indicator. Because the production process has long been well understood, production forecasts are based on the quantifiable features of livestock or a growing crop. Price forecasts are largely made by conventional econometric methods, with time series approaches occupying minor roles. Because of the dominance of agricultural economists, there has been an overemphasis on explanation, and little interest in the predictive power of models. In recent years, some agricultural economists have begun to compare forecasts from different methods. Findings generally conform to widely held beliefs. For short-term forecasting, combining leads to more accurate forecasts, better than those produced by vector autoregression, which surprisingly is the best single method. Also surprising is that econometric models and univariate methods both do badly compared with naive models.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90052-3}, issn = {0169-2070}, keywords = {Agricultural prices, Agricultural production, Forecast comparisons, Econometric forecasting, Judgmental forecasting, Meta-analysis, Sector modelingregart} } @ARTICLE{AM06, author = {P. Geoffrey Allen and Bernard J. Morzuch}, title = {Twenty-five years of progress, problems, and conflicting evidence in econometric forecasting. What about the next 25 years?}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {475-492}, number = {3}, abstract = {In the early 1940s, the Cowles Commission for Research (later, the Cowles Foundation) fostered the development of statistical methodology for application in economics and paved the way for large-scale econometric models to be used for both structural estimation and forecasting. This approach stood for decades. Vector autoregression (VAR), appearing in the 1980s, was a clear improvement over early Cowles Foundation models, primarily because it paid attention to dynamic structure. As a way of imposing long-run equilibrium restrictions on sets of variables, cointegration and error-correction modeling (ECM) gained popularity in the 1980s and 1990s, though ECMs have so far failed to deliver on their early promise. ARCH and GARCH modeling have been used with great success in specialized financial areas to model dynamic heteroscedasticity, though in mainstream econometrics, evidence of their value is limited and conflicting. Concerning misspecification tests, any model will inevitably fail some of them for the simple reason that there are many possible tests. Which failures matter? The root of the difficulty regarding all issues related to modeling is that we can never know the true data generating process. In the next 25 years, what new avenues will open up? With ever greater computational capacity, more complex models with larger data sets seem the way to the future. Will they require the automatic model selection methods that have recently been introduced? Preliminary evidence suggests that these methods can do well. The quality of aggregate data is no better than it was. Will greater use of more disaggregated data be sufficient to provide better forecasts? That remains an open question.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.03.003}, issn = {0169-2070}, keywords = {VAR, Cointegration, Error correction, Dynamic stochastic general equilibrium, Leading indicators, ARCH, GARCH, Automatic model selection, regart} } @ARTICLE{AM95, author = {P. Geoffrey Allen and Bernard J. Morzuch}, title = {Comparing probability forecasts derived from theoretical distributions}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {147-157}, number = {1}, abstract = {Using the wrong forecast error distribution (typically the normal distribution) has been suggested as one reason why prediction intervals are too narrow. Extreme values are especially likely to be drawn from non-normal distributions. A simple way of selecting the appropriate theoretical distribution is to estimate parameters using historical data, transformed if necessary, to make them stationary. The method is demonstrated using daily electricity peak loads, a set of extreme values. Parameters for four specific distributions, the normal, gamma, Cauchy and Weibull, were estimated and used to make probabilistic forecasts. Although none of the distributions produced well-calibrated post-sample forecasts, the Weibull showed the most promise. Probability forecasts calculated from Chebychev's inequality were the worst-calibrated.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)02005-A}, issn = {0169-2070}, keywords = {Probability forecast, Weibull distribution, Gamma distribution, Cauchy distribution, Chebychev's inequality, Electricity demand, regart} } @ARTICLE{AL94, author = {Karel Jan Alsem and Peter S. H. Leeflang}, title = {Predicting advertising expenditures using intention surveys}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {327-337}, number = {2}, abstract = {In this article we study the use of intention surveys to predict the effects of a possible entrant. The case under investigation deals with the introduction of private broadcasting in the Netherlands. Several predictions of the advertising expenditures in various media are given which depend on a number of scenarios. These scenarios are used to reduce the discrepancies between behavioural intentions and actual behaviour. The predictions of the most realistic scenario are compared with their realizations, and the differences are analyzed. To this end the prediction error is decomposed into an intention error and a sampling error. This decomposition offers good opportunities to analyze discrepancies between intentions and actual behaviour.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90011-6}, issn = {0169-2070}, keywords = {Intention survey, Scenarios, Industrial market, Validation, regart} } @ARTICLE{ASS08, author = {Luiz Felipe Amaral and Reinaldo Castro Souza and Maxwell Stevenson}, title = {A smooth transition periodic autoregressive (STPAR) model for short-term load forecasting}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {603-615}, number = {4}, abstract = {This paper compares the short-term load performance of several forecasting models, including a new class of nonlinear models known as smooth transition periodic autoregressive (STPAR) models. A model building procedure is developed for the STPAR model, along with a linearity test against smooth transition periodic autoregressive behaviour. The predictive ability of the STPAR model is evaluated against alternative load forecasting models using load data from the Australian electricity market.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.08.006}, issn = {0169-2070}, keywords = {Time series, Periodic and autoregressive models, STAR model, Load forecast, regart} } @ARTICLE{Anderson95, author = {Elizabeth A. Anderson}, title = {Judgmental and statistical methods of peak electric load management}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {295-305}, number = {2}, abstract = {This paper presents the results of a study comparing two computerized peak-shaving systems for an electricity distributing utility company. A judgmentally-based system was designed to replicate an actual human expert in the field, while a statistically-based system was developed to incorporate statistically-based decision rules to replace some of the purely judgmental rules of the expert. These peak management systems were tested against each other, and then tested against the human expert for periods in which data on his actual decisions were available. The results show that when the objective is to correctly predict peaks, and the number of false alarms is not important, the human expert should be used. Alternatively, when the objective is to reduce system nervousness by limiting the number of false alarms, the statistically-based peak management system should be used.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00589-I}, issn = {0169-2070}, keywords = {Judgmental forecasting, Decision-making systems, Electric utility planning, Demand-side management, regart} } @ARTICLE{Anderson03, author = {Scott Anderson}, title = {Practical Business Forecasting: Michael K. Evans, Blackwell Publishing, Oxford, 2003, pp. 483, ISBN 0-631-22065-8, \$69.95.}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {330-332}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00017-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Andersson00, author = {Michael K. Andersson}, title = {Do long-memory models have long memory?}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {121-124}, number = {1}, abstract = {This paper examines the predictability memory of fractionally integrated ARMA processes. Very long memory is found for positively fractionally integrated processes with large positive AR parameters. However, negative AR parameters absorb, to a great extent, the memory generated by a positive fractional difference. An MA parameter may also reduce the predictability memory substantially, even if the parameter alone provides hardly any memory.}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00040-0}, issn = {0169-2070}, keywords = {ARMA, Fractional integration, Prediction horizon, regart} } @ARTICLE{AEE05, author = {Patric Andersson and Jan Edman and Mattias Ekman}, title = {Predicting the World Cup 2002 in soccer: Performance and confidence of experts and non-experts}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {565-576}, number = {3}, abstract = {This paper investigates the forecasting performance and confidence of experts and non-experts. 251 participants with four different levels of knowledge of soccer (ranging between expertise and almost ignorance) took part in a survey and predicted the outcome of the first round of World Cup 2002. The participating experts (i.e., sport journalists, soccer fans, and soccer coaches) and the non-experts were found to be equally accurate and better than chance. A simple prediction rule that followed world rankings outperformed most participants. Experts overestimated their performance and tended to be overconfident, while the opposite tendency was observed for the participants with limited knowledge. Providing non-experts with information did not improve their performance, but increased their confidence.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.03.004}, issn = {0169-2070}, keywords = {Experts, Judgmental forecasting, Overconfidence, Sports forecasting, regart} } @ARTICLE{Ando09, author = {Tomohiro Ando}, title = {Bayesian portfolio selection using a multifactor model}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {550 - 566}, number = {3}, note = {Special Section: Time Series Monitoring}, doi = {10.1016/j.ijforecast.2009.01.005}, issn = {0169-2070}, keywords = {Bayesian methods, Decision making,Finance,Model selection} } @ARTICLE{Andreassen89, author = {Paul B. Andreassen}, title = {Judgmental forecasting : George Wright and Peter Ayton, eds., (Wiley, Chichester, UK, 1987), pp. 293, �29.95}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {616-617}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90024-1}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{AO91, author = {Soon Ang and Marcus O'Connor}, title = {The effect of group interaction processes on performance in time series extrapolation}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {141-149}, number = {2}, abstract = {This study explores the ability of groups to forecast and establish judgmental confidence intervals in time series extrapolation. Thirty-six three-person groups were used to evaluate four different group interaction processes. In addition to staticized, nominal group technique and consensus processes, the study utilizes a modified consensus process, where a selected group member completes the task prior to group discussion and interaction. Using real life time series, subjects produced forecasts and related confidence intervals for six periods. Groups in the modified-consensus structuring process exhibited significantly greater forecast accuracy than all other experimental conditions (p < 0.001). The superiority was most pronounced for series of high forecast difficulty. These results are discussed in relation to the contribution of the initial estimates as an anchor on which the modified-consensus group can focus.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90048-Z}, issn = {0169-2070}, keywords = {Group judgment, Forecast accuracyregart} } @ARTICLE{Antzoulatos96, author = {Angelos A. Antzoulatos}, title = {Consumer credit and consumption forecasts}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {439-453}, number = {4}, abstract = {Recent advances in the theory of consumer behavior indicate that consumption may exhibit non-linear dynamics characterized by occasional surges. Building upon them, and taking explicitly into account the forward-looking nature of consumption, this paper argues that rising consumer debt can signal such surges, as well as the consumption underprediction which will occur if they are not taken sufficiently into account in forecasting. This insight is tested with and strongly confirmed by the Organization of Economic Cooperation and Developments forecasts for the USA. The results should be of interest not only to professional forecasters and policy-makers, but also to theoretical economists and econometricians who study non-linear dynamic models.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00687-5}, issn = {0169-2070}, keywords = {Borrowing constraints, Consumption, Forecasts, regart} } @ARTICLE{Antzoulatos94, author = {Angelos A. Antzoulatos}, title = {The rationality of the OECD foreign-balance forecasts for the USA}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {435-443}, number = {3}, abstract = {A recent study has documented that the OECD forecasts of the USA foreign balance are biased. This paper, in the spirit of intertemporal models of the current account, advances the hypothesis that the bias is due to the tendency to underpredict the surge in demand which follows periods of rising consumer indebtedness. The empirical results are consistent with this hypothesis. They also indicate that the bias is more severe than originally thought, but, on the positive side, associated with some easily identifiable periods. Both the theoretical and the empirical analysis should be of interest to economists who study the impact of exchange rate changes on a country's balance of payments, and to policy makers and market participants who condition their decisions on expectations about future developments.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90072-8}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{Arafa92, author = {Hazem Arafa}, title = {Oil and gas forecasting: Reflections of a petroleum geologist : Lawrence J. Drew, (Oxford University Press, New York, 1990) \$45.00}, journal = {International Journal of Forecasting}, year = {1992}, volume = {7}, pages = {540-541}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90043-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Archibald90, author = {Blyth C. Archibald}, title = {Parameter space of the Holt-winters' model}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {199-209}, number = {2}, abstract = {In the additive Holt-Winters' seasonal exponential smoothing model, it is theoretically possible for smoothing parameters in the usual (0, 1) interval to produce `non-invertible' models. A sample of 406 monthly series reveal that this is a real concern. In the multiplicative model, reasonable estimation procedures produce smoothing constants outside the additive invertible region. When this occurs, the impact on forecasts of values in the distant past is much larger than for recent values and forecasts are poor. Results from the 406 series show that the problem can be avoided and forecasts improved if a subset of the additive invertible region is used as the parameter space.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90005-V}, issn = {0169-2070}, keywords = {Exponential smoothing, Seasonal, Coefficients choice, Stability, Evaluationregart} } @ARTICLE{AK03, author = {Blyth C. Archibald and Anne B. Koehler}, title = {Normalization of seasonal factors in Winters' methods}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {143-148}, number = {1}, abstract = {In Winters' seasonal exponential smoothing methods, a time series is decomposed into: level, trend and seasonal components, that change over time. The seasonal factors are initialized so that their average is 0 in the additive version or 1 in the multiplicative version. Usually, only one seasonal factor is updated each period, and the average of the seasonal factors is no longer 0 or 1; the `seasonal factors' no longer meet the usual meaning of seasonal factors. We provide an equivalent reformulation of previous equations for renormalizing the components in the additive version. This form of the renormalization equations is then adapted to new renormalization formulas for the multiplicative Winters' method. For both the standard and renormalized equations we make a minor change to the seasonal equation. Predictions from our renormalized smoothing values are the same as for the original smoothed values. The formulas can be applied every period, or when required. However, we recommend renormalization every time period. We show in the multiplicative version that the level and trend should be adjusted along with the seasonal component.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00117-0}, issn = {0169-2070}, keywords = {Winters' method, Exponential smoothing, Renormalization, Seasonal indexes, regart} } @ARTICLE{AKV+97, author = {Bart Van Arem and Howard R. Kirby and Martie J. M. Van Der Vlist and Joe C. Whittaker}, title = {Recent advances and applications in the field of short-term traffic forecasting}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {1-12}, number = {1}, abstract = {Frequent road traffic congestion is now a global issue. One of the proposed solutions to this problem is dynamic traffic management (DTM): the management of traffic flows, vehicles and traffic demand based on data representing the current and near expected traffic situation. A key ingredient for DTM is accurate network-wide short-term traffic forecasts. This article gives a general overview of the state of the art together with some recent advances and applications derived from a number of field trials conducted as part of the DRIVE-II programme of the Commission of the European Communities. The article gives an introduction to DTM, and reviews the nature of traffic demand and supply and the traffic measurement process. The statistical methodology of short-term forecasts applied in transport is discussed and the articles in this issue are introduced. Mention is made of as yet unresolved problems. The article concludes that a great deal of work still remains to be done before the current methodology can consistently provide the desired level of accuracy needed for DTM. In the near future, more research will be needed and carried out, both with respect to methods already available, to methods available but not yet applied and perhaps to develop new methodology.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00695-4}, issn = {0169-2070}, keywords = {Short-term traffic prediction, Dynamic traffic management, Statistical forecasting, Physical traffic models, Behavioural traffic modelsregart} } @ARTICLE{AVM+97, author = {Bart Van Arem and Martie J. M. Van Der Vlist and M. (Rik) Muste and Stef A. Smulders}, title = {Travel time estimation in the GERDIEN project}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {73-85}, number = {1}, abstract = {In order to produce traffic predictions up to 1 h ahead for a motorway network, it is essential to produce reliable estimates for the travel time over motorway sections. This article describes a model for estimating travel times on motorway sections 3-5 km in length. The model uses measurements from inductive loop detectors and is based on a linear input--output ARMA model representation. The model is evaluated using results from a field study. The evaluation data set covers traffic situations with both `normal' congestion and congestion due to accidents or incidents. The observed and estimated travel times are very close in cases of normal congestion. Travel time estimates in cases concerning accidents showed large deviations, but in these cases there were no travel time observations to verify their accuracy.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00702-9}, issn = {0169-2070}, keywords = {Short-term traffic prediction, ARMA model, Evaluation, Travel timesregart} } @ARTICLE{AF00, author = {Miguel A. Ari{\~n}o and Philip Hans Franses}, title = {Forecasting the levels of vector autoregressive log-transformed time series}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {111-116}, number = {1}, abstract = {In this paper we give explicit expressions for the forecasts of levels of a vector time series when such forecasts are generated from (possibly cointegrated) vector autoregressions for the corresponding log-transformed time series. We also show that simply taking exponentials of forecasts for logged data leads to substantially biased forecasts. We illustrate this using a bivariate cointegrated vector series containing US GNP and investments.}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00025-4}, issn = {0169-2070}, keywords = {VAR time series, Log-transformation, Forecasting, regart} } @ARTICLE{02a, author = {Armstrong}, title = {The International Institute of Forecasting Award for the Best Paper in the IJF in the Period 1998 to 1999}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {315-316}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00014-6}, issn = {0169-2070}, key = {tagkey2002315}, keywords = {pubnote} } @ARTICLE{Armstrong07, author = {J. Scott Armstrong}, title = {Statistical significance tests are unnecessary even when properly done and properly interpreted: Reply to commentaries}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {335-336}, number = {2}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.01.010}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Armstrong07a, author = {J. Scott Armstrong}, title = {Significance tests harm progress in forecasting}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {321-327}, number = {2}, abstract = {I briefly summarize prior research showing that tests of statistical significance are improperly used even in leading scholarly journals. Attempts to educate researchers to avoid pitfalls have had little success. Even when done properly, however, statistical significance tests are of no value. Other researchers have discussed reasons for these failures. I was unable to find empirical evidence to support the use of significance tests under any conditions. I then show that tests of statistical significance are harmful to the development of scientific knowledge because they distract the researcher from the use of proper methods. I illustrate the dangers of significance tests by examining a re-analysis of the M3-Competition. Although the authors of the re-analysis conducted a proper series of statistical tests, they suggested that the original M3-Competition was not justified in concluding that combined forecasts reduce errors, and that the selection of the best method is dependent on the selection of a proper error measure. I show that the original conclusions were correct. Authors should avoid tests of statistical significance; instead, they should report on effect sizes, confidence intervals, replications/extensions, and meta-analyses. Practitioners should ignore significance tests and journals should discourage them.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.03.004}, issn = {0169-2070}, keywords = {Accuracy measures, Combining forecasts, Confidence intervals, Effect size, M-Competition, Meta-analysis, Null hypothesis, Practical significance, Replications, regart} } @ARTICLE{Armstrong07b, author = {J. Scott Armstrong}, title = {Forecasting of software development work effort: Introduction}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {447-447}, number = {3}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.05.014}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Armstrong06, author = {J. Scott Armstrong}, title = {Findings from evidence-based forecasting: Methods for reducing forecast error}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {583-598}, number = {3}, abstract = {Empirical comparisons of reasonable approaches provide evidence on the best forecasting procedures to use under given conditions. Based on this evidence, I summarize the progress made over the past quarter century with respect to methods for reducing forecasting error. Seven well-established methods have been shown to improve accuracy: combining forecasts and Delphi help for all types of data; causal modeling, judgmental bootstrapping and structured judgment help with cross-sectional data; and causal models and trend-damping help with time series data. Promising methods for cross-sectional data include damped causality, simulated interaction, structured analogies, and judgmental decomposition; for time series data, they include segmentation, rule-based forecasting, damped seasonality, decomposition by causal forces, damped trend with analogous data, and damped seasonality. The testing of multiple hypotheses has also revealed methods where gains are limited: these include data mining, neural nets, and Box-Jenkins methods. Multiple hypotheses tests should be conducted on widely used but relatively untested methods such as prediction markets, conjoint analysis, diffusion models, and game theory.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.04.006}, issn = {0169-2070}, keywords = {Box-Jenkins, Causal forces, Causal models, Combining forecasts, Complex series, Conjoint analysis, Contrary series, Damped seasonality, Damped trend, Data mining, Delphi, Diffusion, Game theory, Judgmental decomposition, Multiple hypotheses, Neural nets, Prediction markets, Rule-based forecasting, Segmentation, Simulated interaction, Structured analogies, regart} } @ARTICLE{Armstrong04, author = {J. Scott Armstrong}, title = {Damped seasonality factors: Introduction}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {525-527}, number = {4}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.03.001}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Armstrong03, author = {J. Scott Armstrong}, title = {Predicting Presidential Elections and Other Things,: Ray C. Fair. Stanford University Press: Stanford, CA, 2002, 168 pp., Hardback, ISBN 0-8047-4509-9, \$26.00.}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {760-761}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00053-0}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong02, author = {J. Scott Armstrong}, title = {Assessing game theory, role playing, and unaided judgment}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {345-352}, number = {3}, abstract = {Green's study [Int. J. Forecasting (forthcoming)] on the accuracy of forecasting methods for conflicts does well against traditional scientific criteria. Moreover, it is useful, as it examines actual problems by comparing forecasting methods as they would be used in practice. Some biases exist in the design of the study and they favor game theory. As a result, the accuracy gain of game theory over unaided judgment may be illusory, and the advantage of role playing over game theory is likely to be greater than the 44% error reduction found by Green. The improved accuracy of role playing over game theory was consistent across situations. For those cases that simulated interactions among people with conflicting roles, game theory was no better than chance (28% correct), whereas role-playing was correct in 61% of the predictions.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00024-9}, issn = {0169-2070}, keywords = {Forecasting, Role playing, Simulated interactions, regart} } @ARTICLE{Armstrong02a, author = {J. Scott Armstrong}, title = {How useful are the forecasts of intergovernmental agencies? The IMF and OECD versus the consensus: Batchelor, Roy (2001), Applied Economics, 33, pp. 225-235. E-mail address: R.A.Batchelor@city.bc.uk}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {482-483}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00006-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong97, author = {J. Scott Armstrong}, title = {The impact of empirical accuracy studies on time series analysis and forecasting : R. Fildes and S. Makridakis, 1995, International Statistical Review, 63, 289-308}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {151-153}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00724-8}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong96, author = {J. Scott Armstrong}, title = {Journal of economic literature : Clifford Winston, 1993, Economic deregulation: Days of reckoning for microeconomists, 31, 1263-1289.}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {183-184}, number = {1}, note = {Probability Judgmental Forecasting}, doi = {http://dx.doi.org/10.1016/0169-2070(96)88197-0}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong96a, author = {J. Scott Armstrong}, title = {Journal of business forecasting : John Hanke and Pam Weigand, 1994, What are business schools doing to educate forecasters, Fall, 10-12.}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {185-186}, number = {1}, note = {Probability Judgmental Forecasting}, doi = {http://dx.doi.org/10.1016/0169-2070(96)88199-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong96b, author = {J. Scott Armstrong}, title = {The validity of employment interviews: A comprehensive review and meta-analysis : Michael A. McDaniel, D.L. Whetzel, F.L. Schmidt and S.D. Maurer, 994, Journal of Applied Psychology, 79, 599-615}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {317-318}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00653-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong96c, author = {J. Scott Armstrong}, title = {Validity of an honeesty test in predicting theft among convenience store employees : H. John Bernardin and D.K. Cooke, 1993 Academy of Management Journal, 36, 1097-1108}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {318-319}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00654-0}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong96d, author = {J. Scott Armstrong}, title = {Heuristics, biases and improvement strategies in judgmental time series : P. Goodwin and G. Wright, 1994, Omega, 22, 553-568}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {319-321}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00655-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong96e, author = {J. Scott Armstrong}, title = {Factors affecting new product forecasting accuracy in new firms : William B. Gartner, and Robert J. Thomas, 1993, Journal of Productive Innovation Management, 10, 35-52}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {321-322}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00656-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong96f, author = {J. Scott Armstrong}, title = {Predicting insurance agent turnover using a video-based judgement test : Anthony T. Dalessio, 1994, Journal of Business an Psychology, 9, 23-32}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {322-323}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00657-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong96g, author = {J. Scott Armstrong}, title = {Publication of research on controversial topics: The early acceptance procedure}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {299-302}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00626-5}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Armstrong94, author = {J. Scott Armstrong}, title = {The fertile field of meta-analysis: Cumulative progress in agricultural forecasting}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {147-149}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90056-6}, issn = {0169-2070} } @ARTICLE{Armstrong94a, author = {J. Scott Armstrong}, title = {Forecasting practices in US corporations: Survey results : Nada Sanders and Karl B. Manrodt, 1994, interfaces, 24, 92-100}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {471-472}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90079-5}, issn = {0169-2070}, keywords = {revart} } @ARTICLE{Armstrong94b, author = {J. Scott Armstrong}, title = {Omega 21: G.L. Riddington, (1993), Time varying coefficient models and their forecasting performance, 573-583}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {647-649}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90038-8}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Armstrong94c, author = {J. Scott Armstrong}, title = {Marketing letters : Barry L., Bayus, (1992), Have diffusion rates been accelerating over time? 3 215-226}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {647-647}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90037-X}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Armstrong94d, author = {J. Scott Armstrong}, title = {The indexes of consumer sentiment and cofidence: Leading or misleading guides to future buyer behavior : William L. Huth, D.R. Eppright and P.M. Taube, 1994, Journal of business research, 29, 199-206}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {472-473}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90080-9}, issn = {0169-2070}, keywords = {revart} } @ARTICLE{Armstrong94e, author = {J. Scott Armstrong}, title = {An analysis of the accuracy ot trial heat polls during the 1992 presidential election : Richard R. Lau, 1994, Public opinion quarterly, 58, 2-20}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {473-474}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90081-7}, issn = {0169-2070}, keywords = {revart} } @ARTICLE{Armstrong93, author = {J. Scott Armstrong}, title = {Finding public opinion data: A guide to sources : Tom W. Smith and Frederick D. Weil, Public Opinion Quarterly, 54 (1990), 609-626}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {137-138}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90066-V}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Armstrong93a, author = {J. Scott Armstrong}, title = {Municipal forecasting practice: 'Demand' and 'supply' side perspectives: Howard A. Frank and Jane McCollough, International Journal of Public Administration, 15 (1992) 1669-1696}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {137-137}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90065-U}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Armstrong93b, author = {J. Scott Armstrong}, title = {Forecasting output with the composite leading index: A real time analysis : Francis X. Diebold, and Glenn D. Rudebusch, Journal of the American Statistical Association, 86 (1991), 603-610}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {283-284}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90018-I}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Armstrong93c, author = {J. Scott Armstrong}, title = {Accuracy of judgmental forecasts: A comparison : R. Nada Sanders, Omega, 20 (1992) 353-364}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {429-430}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90036-M}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Armstrong93d, author = {J. Scoot Armstrong}, title = {The uses and abuses of consensus forecasts : Stephen K. McNees,Journal of forecasting, 11 (1992) 703-710}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {431-432}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90039-P}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Armstrong93e, author = {J. Scott Armstrong}, title = {A case study of expert judgment: Economists probabilities versus base-rate model forecasts : Phillip A. Braun and Ilan Yaniv, Journal of behavioral decision making, 5 (1992), 217-231}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {431-431}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90038-O}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Armstrong92, author = {J. Scott Armstrong}, title = {Public opinion quarterly : Tom W. Smith and Frederick D. Weil, Finding public opinion data: A guide to sources 54 (1990) 609-626}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {279-279}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90129-W}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong92a, author = {J. Scott Armstrong}, title = {Editorial policies for the publication of controversial findings}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {543-544}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90064-G}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Armstrong91, author = {J. Scott Armstrong}, title = {The obsession to forecast: Pre-election polls in the Israeli press : Gabriel Weimann, Public opinion Quarterly, 54 (1990) 396-408.}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {254-254}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90071-3}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Armstrong89, author = {J. Scott Armstrong}, title = {Editorial: Reflections on forecasting in the 1980's}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {467-468}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90001-0}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Armstrong89a, author = {J. Scott Armstrong}, title = {Combining forecasts: The end of the beginning or the beginning of the end?}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {585-588}, number = {4}, abstract = {Research from over 200 studies demonstrates that combining forecasts produces consistent but modest gains in accuracy. However, this research does not define well the conditions under which combining is most effective nor how methods should be combined in each situation. Rule-based forecasting can be used to define these conditions and to specify more effective combinations.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90013-7}, issn = {0169-2070}, keywords = {Combining forecasts, Meta-analysis, Realistic simulations, Rule-based forecasting, regart} } @ARTICLE{Armstrong88, author = {J. Scott Armstrong}, title = {Communication of research on forecasting: The journal}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {321-324}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90099-4}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Armstrong88a, author = {J. Scott Armstrong}, title = {The great depression of 1990 : Ravi Batra, (Simon and Schuster, New York, 1985) pp. 235, \$14.95}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {493-495}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90113-6}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong88b, author = {J. Scott Armstrong}, title = {Organizational behavior and human decision processes: Wagenaar, Willem A. and G.B. Keren, The seat belt paradox: Effect off accepted roles on information seeking, 38 (1986), 1-6}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {513-513}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90125-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong88c, author = {J. Scott Armstrong}, title = {Journal of personality and social psychology : Osberg, Timothy M. and J. Sidney Shrauger, Self-prediction: Exploring the parameters of accuracy, 51 (1986), 1044-1057}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {514-514}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90126-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong88d, author = {J. Scott Armstrong}, title = {Research needs in forecasting}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {449-465}, number = {3}, abstract = {The demand for research on forecasting is strong. This conclusion is based on the high number of citations to papers published about research on forecasting, and upon the number of subscriptions for journals devoted to forecasting. The supply of research papers is also large, following a rapid growth in the 1960s and 1970s. This research has produced important findings. Despite this, a comparison of published research versus the needs expressed in two surveys of academics and practitioners showed that numerous gaps still exist. A review of the literature also supported this conclusion that the research being produced does not match up well against the research desired. Suggestions are made as to what research is needed and how it should be conducted.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90111-2}, issn = {0169-2070}, keywords = {Acceptance of forecasts, Forecasting audit, Legal aspects, Survey of forecasters, regart} } @ARTICLE{Armstrong86, author = {J. Scott Armstrong}, title = {Naive vs. sophisticated methods of forecasting public library circulations : Terrence Brooks, Library and Information Science Research 6 (1984) 215-217}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {115-115}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90034-8}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong86a, author = {J. Scott Armstrong}, title = {Quantitative forecasting -- The state of the art: Econometric models}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {238-239}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90115-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong86b, author = {J. Scott Armstrong}, title = {Forecasting presidential elections}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {248-249}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90122-6}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Armstrong85, author = {J. Scott Armstrong}, title = {J. Scott Armstrong, Forecasting by extrapolation: Conclusions from 25 years of research, Interfaces 14 (1984), pp. 52-66.}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {309-310}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(85)80052-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{ABM87, author = {J. Scott Armstrong and Roderick J. Brodie and Shelby H. McIntyre}, title = {Forecasting methods for marketing: Review of empirical research}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {355-376}, number = {3-4}, abstract = {This paper reviews the empirical research on forecasting in marketing. In addition, it presents results from some small scale surveys. We offer a framework for discussing forecasts in the area of marketing, and then review the literature in light of that framework. Particular emphasis is given to a pragmatic interpretation of the literature and findings. Suggestions are made on what research is needed.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90029-X}, issn = {0169-2070}, keywords = {Bootstrapping, Econometric models, Expert systems, Intentions, Judgment, Market forecasting, Market share, Uncertainty, regart} } @ARTICLE{AB88, author = {J. Scott Armstrong and Lance Eliot Brouthers}, title = {International journal of public administration : Lance Eliot Brouthers, parties, ideology and elections: The politics of federal revenues and expenditures forecasting, 8 (1986) 289-314}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {161-162}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90017-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{AB88a, author = {J. Scott Armstrong and William Buchanan}, title = {Public opinion quarterly : William Buchanan, election predictions: An empirical assessment, 50 (1986) 222-227}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {162-164}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90018-0}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{AC92, author = {J. Scott Armstrong and Fred Collopy}, title = {Error measures for generalizing about forecasting methods: Empirical comparisons}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {69-80}, number = {1}, abstract = {This study evaluated measures for making comparisons of errors across time series. We analyzed 90 annual and 101 quarterly economic time series. We judged error measures on reliability, construct validity, sensitivity to small changes, protection against outliers, and their relationship to decision making. The results lead us to recommend the Geometric Mean of the Relative Absolute Error (GMRAE) when the task involves calibrating a model for a set of time series. The GMRAE compares the absolute error of a given method to that from the random walk forecast. For selecting the most accurate methods, we recommend the Median RAE (MdRAE) when few series are available and the Median Absolute Percentage Error (MdAPE) otherwise. The Root Mean Square Error (RMSE) is not reliable, and is therefore inappropriate for comparing accuracy across series.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90008-W}, issn = {0169-2070}, keywords = {Forecast accuracy, M-Competition, Relative absolute error, Theil's U, regart} } @ARTICLE{ACY05, author = {J. Scott Armstrong and Fred Collopy and J. Thomas Yokum}, title = {Decomposition by causal forces: a procedure for forecasting complex time series}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {25-36}, number = {1}, abstract = {Causal forces are a way of summarizing forecasters' expectations about what will happen to a time series in the future. Contrary to the common assumption for extrapolation, time series are not always subject to consistent forces that point in the same direction. Some are affected by conflicting causal forces; we refer to these as complex time series. It would seem that forecasting these time series would be easier if one could decompose the series to eliminate the effects of the conflicts. We hypothesized that a time series could be effectively decomposed when (1) uncertainty is high, (2) forecasters can use domain knowledge to decompose the problem such that different forces can be identified for two or more component series, (3) the causal forces imply trends that differ in direction, and (4) it is possible to obtain forecasts for each component that are more accurate than the forecast for the global series. Forecast accuracy for the components can be assessed by testing how well they can be forecast on early hold-out data. When such data are not available, historical variability may be an adequate substitute. We tested decomposition by causal forces on 12 complex annual time series for automobile accidents, airline accidents, personal computer sales, airline revenues, and cigarette production. The length of these series ranged from 16 years for airline revenues to 56 years for highway safety data. We made forecasts for one to ten horizons, obtaining 800 forecasts through successive updating. For nine series in which the conditions were completely or partially met, the forecast error (median absolute percentage error, MdAPE) was reduced by more than half. For three series in which the conditions were not met, decomposition by causal forces had little effect on accuracy.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.05.001}, issn = {0169-2070}, keywords = {Airline accidents, Extrapolation, Holt's exponential smoothing, Model formulation, Personal computers, Revenue forecasting, Transportation safety, regart} } @ARTICLE{ADF+86, author = {J. Scott Armstrong and Estela Bee Dagum and Robert Fildes and Spyros Makridakis}, title = {Editorial: Publishing standards for research on forecasting}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {133-137}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(86)99001-1}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{AF06, author = {J. Scott Armstrong and Robert Fildes}, title = {Making progress in forecasting}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {433-441}, number = {3}, abstract = {Twenty-five years ago, the International Institute of Forecasters was established tobridgethegapbetweentheoryandpractice. Its primary vehicle was the Journal of Forecasting and is now the International Journal of Forecasting. The Institute emphasizes empirical comparisons of reasonable forecasting approaches. Such studies can be used to identify the best forecasting procedures to use under given conditions, a process we call evidence-based forecasting. Unfortunately, evidence-based forecasting meets resistance from academics and practitioners when the findings differ from currently accepted beliefs. As a consequence, although much progress has been made in developing improved forecasting methods, the diffusion of useful forecasting methods has been disappointing. To bridge the gap between theory and practice, we recommend a stronger emphasis on the method of multiple hypotheses and on invited replications of important research. It is then necessary to translate the findings into principles that are easy to understand and apply. The Internet and software provide important opportunities for making the latest findings available to researchers and practitioners. Because researchers and practitioners believe that their areas are unique, we should organise findings so that they are relevant to each area and make them easily available when people search for information about forecasting in their area. Finally, progress depends on our ability to overcome organizational barriers.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.04.007}, issn = {0169-2070}, keywords = {Barriers to implementation, Evidence-based forecasting, Forecasting practice, Forecasting software, Freeware, Replication, regart} } @ARTICLE{AFD+88, author = {J. Scott Armstrong and Robert Fildes and Estela B. Dagum and Allan H. Murphy}, title = {Editorial}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {1-2}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90004-0}, issn = {0169-2070}, key = {tagkey19881}, keywords = {editorial} } @ARTICLE{AG88, author = {J. Scott Armstrong and David M. Georgoff}, title = {Harvard Business Review : David M. Georgoff and Robert G. Murdick, manager's guide to forecasting, 64 (Jan-Feb.) (1986) 110-120}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {164-165}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90019-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{AKF+98, author = {J. Scott Armstrong and A.B. Koehler and R. Fildes and M. Hibon and S. Makridakisd and N. Meadee}, title = {Commentaries on ��Generalizing about univariate forecasting methods: further empirical evidence��}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {359-366}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00007-7}, issn = {0169-2070}, key = {tagkey1998359}, keywords = {othercom} } @ARTICLE{AL88, author = {J. Scott Armstrong and James B. Lemert}, title = {Public opinion quarterly : James B. Lemert, picking the winners: Politician vs. voter predictions of two controversial ballot measures, 50 (1986) 208-221}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {165-166}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90020-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{AM87, author = {J. Scott Armstrong and Shelby McIntyre}, title = {Editorial}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {351-351}, number = {3-4}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90027-6}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{AMK00, author = {J. Scott Armstrong and Vicki G. Morwitz and V. Kumar}, title = {Sales forecasts for existing consumer products and services: Do purchase intentions contribute to accuracy?}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {383-397}, number = {3}, abstract = {Purchase intentions are routinely used to forecast sales of existing products and services. While past studies have shown that intentions are predictive of sales, they have only examined the absolute accuracy of intentions, not their accuracy relative to other forecasting methods. For example, no research has been able to demonstrate that intentions-based forecasts can improve upon a simple extrapolation of past sales trends. We examined the relative accuracy of four methods that forecast sales from intentions. We tested these methods using four data sets involving different products and time horizons; one of French automobile sales, two of US automobile sales, and one of US wireless services. For all four products and time horizons, each of the four intentions-based forecasting methods was more accurate than an extrapolation of past sales. Combinations of these forecasting methods using equal weights lead to even greater accuracy, with error rates about one-third lower than extrapolations of past sales. Thus, it appears that purchase intentions can provide better forecasts than a simple extrapolation of past sales trends. While the evidence from the current study contradicts the findings of an earlier study, the consistency of the results in our study suggest that intentions are a valuable input to sales forecasts.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00058-3}, issn = {0169-2070}, keywords = {Combining, Expectations, Extrapolation, Intentions, Purchase probabilities, regart} } @ARTICLE{AR88, author = {J. Scott Armstrong and Steven J. Rosenstone}, title = {Public opinion quarterly : Steven J. Rosenstone, John Mark Hansen, and Donald R. Kinder, measuring change in personal economic well-being, 50 (1986) 176-192}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {166-167}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90021-0}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{AS88, author = {J. Scott Armstrong and Jacob Shamir}, title = {Public opinion quarterly : Jacob Shamir, preelection polls in Israel: Structural constraints on accuracy, 50 (1986) 62-75}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {167-167}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90022-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{AS90, author = {Harjit K. Arora and David J. Smyth}, title = {Forecasting the developing world : An accuracy analysis of the IMF's forecasts}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {393-400}, number = {3}, abstract = {The accuracy of the forecasts for the developing world made by the International Monetary Fund from 1980 to 1988 is analyzed in this paper. The forecasts are for the growth in real output, exports and imports, the inflation rate, long-term debt, the current account balance and the ratio of reserves to imports. The developing world is divided into five regions, Africa, Asia, Europe, the Middle East and the Western Hemisphere, and the forecasts are for each region. Overall the IMF's forecasts are inferior to those generated by a naive model, a simple random walk, although the differences are not usually significant. When allowance is made for changes in forecasting difficulty (measured by the performance of the naive model) the IMF's forecasting accuracy does not improve significantly over time and for somew series it deteriorates. The results suggest that there is no reason to prefer the IMF forecasts for the developing world over those that can be obtained by assuming a simple random walk.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90065-J}, issn = {0169-2070}, keywords = {Forecasting accuracy, Developing world, International Monetary Fund, Naive model, Random walk, regart} } @ARTICLE{AM09, author = {Javier Arroyo and Carlos Mat{\'e}}, title = {Forecasting histogram time series with k-nearest neighbours methods}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {192-207}, number = {1}, abstract = {Histogram time series (HTS) describe situations where a distribution of values is available for each instant of time. These situations usually arise when contemporaneous or temporal aggregation is required. In these cases, histograms provide a summary of the data that is more informative than those provided by other aggregates such as the mean. Some fields where HTS are useful include economy, official statistics and environmental science. This article adapts the k-Nearest Neighbours (k-NN) algorithm to forecast HTS and, more generally, to deal with histogram data. The proposed k-NN relies on the choice of a distance that is used to measure dissimilarities between sequences of histograms and to compute the forecasts. The Mallows distance and the Wasserstein distance are considered. The forecasting ability of the k-NN adaptation is illustrated with meteorological and financial data, and promising results are obtained. Finally, further research issues are discussed.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.07.003}, issn = {0169-2070}, keywords = {Density forecast, Finance, Nonlinear time series models, Non-parametric forecasting, Symbolic data analysis, Weather forecastregart} } @ARTICLE{AZ90, author = {M. J. Artis and W. Zhang}, title = {BVAR forecasts for the G-7}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {349-362}, number = {3}, abstract = {The paper provides forecasts, derived from Bayesian vector autoregressive models, for the output growth, inflation and balance of payments of the G-7 countries. In constructing the models, particular attention is paid to the determination of the prior and to the choice of lag length and vector content. The forecasts derived from the models are compared with those published by the International Monetary Fund on alternative assumptions about the information set available to the forecaster. The results indicate that BVAR methods can provide a highly effective standard of comparison for forecasts produced by more traditional methods.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90062-G}, issn = {0169-2070}, keywords = {Forecasts, Bayesian vector autoregression, International Monetary Fund, regart} } @ARTICLE{AE10, author = {Kai Arzheimer and Jocelyn Evans}, title = {Bread and butter a la francaise: Multiparty forecasts of the French legislative vote (1981-2007)}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {19 - 31}, number = {1}, note = {Special Section: European Election Forecasting}, doi = {10.1016/j.ijforecast.2009.05.025}, issn = {0169-2070}, keywords = {Election forecasting, France,Economic voting,Regression,Time series} } @ARTICLE{AM08, author = {Manabu Asai and Michael McAleer}, title = {A Portfolio Index GARCH model}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {449-461}, number = {3}, abstract = {This paper develops the structure of a parsimonious Portfolio Index (PI) GARCH model. Unlike the conventional approach to Portfolio Index returns, which employs the univariate ARCH class, the PI-GARCH approach incorporates the effects on individual assets, leading to a better understanding of portfolio risk management, and achieves greater accuracy in forecasting Value-at-Risk (VaR) thresholds. For various asymmetric GARCH models, a Portfolio Index Composite News Impact Surface (PI-CNIS) is developed to measure the effects of news on the conditional variances. The paper also investigates the finite sample properties of the PI-GARCH model. The empirical example shows that the asymmetric PI-GARCH-t model outperforms the GJR-t model and the filtered historical simulation with a t distribution in forecasting VaR thresholds.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.06.006}, issn = {0169-2070}, keywords = {Risk management, Portfolio Index model, Multivariate volatility, Asymmetry, Composite news, Value-at-Risk thresholds, Monte Carlo simulations, regart} } @ARTICLE{Ascher93, author = {William Ascher}, title = {The ambiguous nature of forecasts in project evaluation: Diagnosing the over-optimism of rate-of-return analysis}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {109-115}, number = {1}, abstract = {Development projects often have low economic rates of return, despite high ex ante forecasts. By reviewing several sets of project appraisals undertaken by the World Bank, this paper isolates the technical/methodological sources of this bias. There are several types of failures to account for the fact that unforeseen conditions are more likely to reduce rather than enhance the true rate of return, but the ambiguity in the status of `predictions' in project evaluation allows unreasonably conditional, optimistic forecasts to be used where usually more pessimistic absolute forecasts would be appropriate.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90058-U}, issn = {0169-2070}, keywords = {Development projects, Forecast bias, Project evaluation, regart} } @ARTICLE{Ascher89, author = {William Ascher}, title = {Beyond accuracy}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {469-484}, number = {4}, abstract = {Long-range, political-economic forecasting cannot be appraised in terms of empirically demonstrated accuracy. Yet as `scientific research programs', futures studies can be assessed in terms of methodological dependability and progressive problem shifts. The methodology of developmental constructs meets these criteria; policy debates and international conflicts can be viewed as competitions among developmental sequences, which progress best, if cast as provisional rather than as general laws. Developmental constructs can incorporate historical lessons without the rigidity of single, dominant analogies. The approach applies with equal robustness to long-term economic growth futures studies and international conflict and mediation.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90002-2}, issn = {0169-2070}, keywords = {Developmental constructs, Forecast accuracy, Forecast evaluation, Future studies, Scientific progress, regart} } @ARTICLE{Ascher85, author = {William Ascher}, title = {An Assessment of Simon's methodology of natural resource forecasting}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {95-103}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(85)90013-5}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{ASH98, author = {J. C. K. Ash and D. J. Smyth and S. M. Heravi}, title = {Are OECD forecasts rational and useful?: a directional analysis}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {381-391}, number = {3}, abstract = {Tests of direction are employed to evaluate the rationality and usefulness of a large data set of semi-annual forecasts for the G7 economies made by the OECD. Changes in the main components of aggregate demand and output, inflation and the balance of payments are predicted up to three half-years ahead. In total, we inspect the signs of 14[punctuation space]184 pairs of forecasts and outcomes. The results indicate that all these forecasts are rational and, looking ahead 6 months, generally useful. However, there is no evidence that longer term forecasts - with a 1 year or 18-month horizon - are valuable. With very few exceptions, they are no better than a naive model that always predicted the same direction of change.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00035-1}, issn = {0169-2070}, keywords = {Macroeconomic forecasts, OECD, Forecast evaluation, Rationality, regart} } @ARTICLE{ASH90, author = {J. C. K. Ash and D. J. Smyth and S. M. Heravi}, title = {The accuracy of OECD forecasts of the international economy : Demand, output and prices}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {379-392}, number = {3}, abstract = {This paper examines the accuracy of forecasts of the international economy made by the OECD. Our large data set, comprising over 7,000 pairs of forecasts and outcomes, includes one-, two-, and three-step ahead semi-annual forecasts of the main components of demand, output and prices for Canada, France, Germany, Italy, Japan, the U.K. and the U.S.A. over the twenty-year period 1968-1987. Various measures of accuracy are computed; also a comparison is made with competing naive and time-series predictions. The analysis includes a full range of diagnostic checks on forecast performance, including rationality tests for unbiasedness, efficiency and consistency. Although there is considerable variation in the accuracy of these forecasts, they are generally superior to the naive and time-series predictions. Error is predominantly non-systematic. However, our analysis exposes exceptions, particularly forecasts of government consumption, and in some of the forecasts of fixed and inventory investment, the foreign balance and inflation. Accuracy in these cases could be improved by a simple linear correction, or by incorporating information contained in recent, known forecast errors. At least half the OECD forecasts fail one or more of the rationality tests.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90064-I}, issn = {0169-2070}, keywords = {International economy, Forecasting accuracy, Error analysis, Rational expectations, OECD, Comparative methods - naive and time-series prediction, regart} } @ARTICLE{Ashiya06, author = {Masahiro Ashiya}, title = {Forecast accuracy and product differentiation of Japanese Institutional Forecasters}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {395-401}, number = {2}, abstract = {This paper investigates whether some forecasters consistently outperform others using real GDP forecast data of 53 Japanese institutions over the past 24 years. It finds that the accuracy rankings are not significantly different from those that might be expected if all institutions had equal forecasting ability. On the other hand, their rankings of the relative forecast levels are significantly different from a random one. These results suggest that the macroeconomic forecasting business is competitive and each institution chooses the degree of productdifferentiation of its forecast so that accuracy and publicity are optimally balanced.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.07.003}, issn = {0169-2070}, keywords = {Economic forecasts, Forecast evaluation, Forecast accuracy, regart} } @ARTICLE{Ashley03, author = {Richard Ashley}, title = {Statistically significant forecasting improvements: how much out-of-sample data is likely necessary?}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {229-239}, number = {2}, abstract = {Testing the out-of-sample forecasting superiority of one model over another requires an a priori partitioning of the data into a model specification/estimation (`training') period and a model comparison/evaluation (`out-of-sample' or `validation') period. How large a validation period is necessary for a given mean square forecasting error (MSFE) improvement to be statistically significant at the 5% level? If the forecast errors from each model are NIID and these errors are independent of one another, then the 5% critical points for theF distribution provide the answer to this question. But even optimal forecast errors from well-specified models can be serially correlated. And forecast errors are typically substantially crosscorrelated. For such errors, a validation period in excess of 100 observations long is typically necessary in order for a 20% MSFE reduction to be statistically significant at the 5% level. Illustrative applications using actual economic data are given.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00139-X}, issn = {0169-2070}, keywords = {Postsample forecasting, Statistical testing, regart} } @ARTICLE{Ashley88, author = {Richard Ashley}, title = {On the relative worth of recent macroeconomic forecasts}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {363-376}, number = {3}, abstract = {The accuracy of recent forecasts of key macroeconomic variables by a variety of forecasters is analyzed over the period 1980II to 1985I. With the exception of the Bayesian VAR forecasts of cumulative growth rates in some real variables, most of these forecasts are so inaccurate that the forecast MSE exceeds the variance of the variable being forecast. This implies that substituting such a projection into a forecasting model estimated using one of these variables as an explanatory variable will provide inferior forecasts relative to a naive model (incorrectly) dropping the explanatory variable altogether. Put another way: most of these forecasts are so inaccurate that simple extrapolation of historical trends is superior for forecasts more than a couple of quarters ahead.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90104-5}, issn = {0169-2070}, keywords = {Forecasting, Accuracy, Mean Square Errors (MSE), Macroeconomic, regart} } @ARTICLE{AK92, author = {Vassilis Assimakopoulos and Alexandra Konida}, title = {An object oriented approach to forecasting}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {175-185}, number = {2}, abstract = {This paper introduces the use of object oriented design techniques in the area of forecasting. It focuses on representing the knowledge underlying the forecasting process using classes, objects and properties organized in a tree structure. Three major classes have been identified: time-series, quantitative forecasting tools, and results. Objects constitute specific instances of these classes, while properties represent their characteristics perceived as decisive in the forecasting process. Reasoning is performed by rules that act upon the three basic structures of representation mentioned above and determine the inference relations that exist among them. In the working applications developed, knowledge bases corresponding to specific forecasting methodologies were integrated with the proposed object oriented representation.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90117-R}, issn = {0169-2070}, keywords = {Forecasting, Knowledge base, Object oriented design, regart} } @ARTICLE{AN00, author = {V. Assimakopoulos and K. Nikolopoulos}, title = {The theta model: a decomposition approach to forecasting}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {521-530}, number = {4}, abstract = {This paper presents a new univariate forecasting method. The method is based on the concept of modifying the local curvature of the time-series through a coefficient `Theta' (the Greek letter [theta]), that is applied directly to the second differences of the data. The resulting series that are created maintain the mean and the slope of the original data but not their curvatures. These new time series are named Theta-lines. Their primary qualitative characteristic is the improvement of the approximation of the long-term behavior of the data or the augmentation of the short-term features, depending on the value of the Theta coefficient. The proposed method decomposes the original time series into two or more different Theta-lines. These are extrapolated separately and the subsequent forecasts are combined. The simple combination of two Theta-lines, the Theta=0 (straight line) and Theta=2 (double local curves) was adopted in order to produce forecasts for the 3003 series of the M3 competition. The method performed well, particularly for monthly series and for microeconomic data.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00066-2}, issn = {0169-2070}, keywords = {M3-Competition, Time series, Univariate forecasting method, regart} } @ARTICLE{AWW97, author = {T. Astatkie and D. G. Watts and W. E. Watt}, title = {Nested threshold autoregressive (NeTAR) models}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {105-116}, number = {1}, abstract = {A class of Nested Threshold Autoregressive (NeTAR) model is proposed to describe non-linear time series whose non-linearity is caused by two sources. For example, the most important sources of non-linearity in daily streamflows are the state of basin storage and air temperature. The NeTAR modeling procedure, which involves forming zones defined by two threshold varuables, estimating threshold parameters and subset selection, is illustrated using an Icelandic streamflow series that was used in other non-linear time-series models. The NeTAR model gave an easily interpretable and final model and performed better than Tong's TARSO, and Chen and Tsay's NAARX models in describing and forecasting the Icelandic streamflow.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00716-9}, issn = {0169-2070}, keywords = {Threshold time series, Non-linearity, Streamflow, Supersmoother, Forecasting, regart} } @ARTICLE{AAH09, author = {George Athanasopoulos and Roman A. Ahmed and Rob J. Hyndman}, title = {Hierarchical forecasts for Australian domestic tourism}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {146-166}, number = {1}, abstract = {In this paper we explore the hierarchical nature of tourism demand time series and produce short-term forecasts for Australian domestic tourism. The data and forecasts are organized in a hierarchy based on disaggregating the data according to geographical regions and purposes of travel. We consider five approaches to hierarchical forecasting: two variations of the top-down approach, the bottom-up method, a newly proposed top-down approach where top-level forecasts are disaggregated according to the forecasted proportions of lower level series, and a recently proposed optimal combination approach. Our forecast performance evaluation shows that the top-down approach based on forecast proportions and the optimal combination method perform best for the tourism hierarchies we consider. By applying these methods, we produce detailed forecasts of the Australian domestic tourism market.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.07.004}, issn = {0169-2070}, keywords = {Australia, Exponential smoothing, Hierarchical forecasting, Innovations state space models, Optimal combination forecasts, Top-down method, Tourism demand, regart} } @ARTICLE{Author99, author = {A. Author}, title = {Research note}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {225-226}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00078-8}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Author99a, author = {A. Author}, title = {Book review}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {341-342}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00008-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Author99b, author = {A. Author}, title = {Book review}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {345-346}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00010-2}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Author99c, author = {A. Author}, title = {The International Institute of Forecasters Award for the Best Forecasting Paper}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {347-348}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00017-5}, issn = {0169-2070} } @ARTICLE{Author99d, author = {A. Author}, title = {Introduction to paper and commentaries on the Delphi technique}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {351-352}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00012-6}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Author99e, author = {A. Author}, title = {Book review}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {379-380}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00016-3}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Author99f, author = {A. Author}, title = {Book reviews}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {447-447}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00021-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Author99g, author = {A. Author}, title = {Book review}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {449-450}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00022-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Author99h, author = {A. Author}, title = {Software review}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {451-459}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00011-4}, issn = {0169-2070}, keywords = {prodrev} } @ARTICLE{AC05, author = {Basel M.A. Awartani and Valentina Corradi}, title = {Predicting the volatility of the S\&P-500 stock index via GARCH models: the role of asymmetries}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {167-183}, number = {1}, abstract = {In this paper, we examine the relative out of sample predictive ability of different GARCH models, with particular emphasis on the predictive content of the asymmetric component. First, we perform pairwise comparisons of various models against the GARCH(1,1) model. For the case of nonnested models, this is accomplished by constructing the [Diebold, F.X., & Mariano, R.S., 1995. Comparing predictive accuracy. Journal of Business and Economic Statistics, 13, 253-263 test statistic.]. For the case of nested models, this is accomplished via the out of sample encompassing tests of [Clark, T.E., & McCracken, M.W., 2001. Tests for equal forecast accuracy and encompassing for nested models. Journal of Econometrics, 105, 85-110.]. Finally, a joint comparison of all models against the GARCH(1,1) model is performed along the lines of the reality check of [White, H., 2000, A reality check for data snooping. Econometrica, 68, 1097-1126.]. Our findings can be summarized as follows: for the case of one-step ahead pairwise comparison, the GARCH(1,1) is beaten by the asymmetric GARCH models. The same finding applies to different longer forecast horizons, although the predictive superiority of asymmetric models is not as striking as in the one-step ahead case. In the multiple comparison case, the GARCH(1,1) model is beaten when compared against the class of asymmetric GARCH, while it is not beaten when compared against other GARCH models that do not allow for asymmetries.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.08.003}, issn = {0169-2070}, keywords = {Asymmetric, Bootstrap P-values, Forecast evaluation, GARCH, Volatility, regart} } @ARTICLE{Ayres87, author = {Robert Ayres}, title = {World futures: A critical analysis of alternatives : Barry Hughes, (Johns Hopkins University Press, Baltimore, MD, 1985) pp. 243, \$25.00, \$10.95 paperback}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {331-331}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90014-8}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{AFS99, author = {Peter Ayton and William R. Ferrell and Thomas R. Stewart}, title = {Commentaries on The Delphi technique as a forecasting tool: issues and analysis by Rowe and Wright}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {377-379}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00013-8}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Bachmeier04, author = {Lance Bachmeier}, title = {The State of Macroeconomic Forecasting: Robert Fildes and Herman Stekler, Journal of Macroeconomics, 2002 24, 435-468. Corresponding author: hstekler@gwu.edu}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {737-738}, number = {4}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.01.001}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{BGP04, author = {Alberto Baffigi and Roberto Golinelli and Giuseppe Parigi}, title = {Bridge models to forecast the euro area GDP}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {447-460}, number = {3}, abstract = {Quantitative information on the current state of the economy is crucial to economic policy-making and to early understanding of the economic situation, but the quarterly national account (NA) data for GDP in the euro area are released with a substantial delay. The aim of the paper is to examine the forecast ability of bridge models (BM) for GDP growth in the euro area. BM `bridge the gap' between the information content of timely updated indicators and the delayed (but more complete) NA. In this paper, BM are estimated for aggregate GDP and components both area-wide and for the three main countries of the euro area. Their short-term (one- and two-quarter ahead) forecasting performance is assessed with respect to benchmark univariate/multivariate statistical models, and a small structural model. The paper shows that national BM fare better than benchmark models. In addition, euro area GDP and its components are more precisely predicted by aggregating national forecasts.}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00067-0}, issn = {0169-2070}, keywords = {Short-term GDP forecast for the euro area, Bridge model, Out-of-sample forecasting accuracy, regart} } @ARTICLE{Bailey94, author = {R. Clifton Bailey}, title = {Forecasting the health of elderly populations : Kenneth G. Manton, Burton H. Singer, Richard M. Suzman (editors), 1993, (Springer-Verlag, New York), 371 pp., \$59.00, ISBN 0-387-97953-0}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {168-169}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90063-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{BCR02, author = {R. Baillie and N. Crato and B. K. Ray}, title = {Introduction}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {163-165}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00150-9}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Baillie86, author = {Richard T. Baillie}, title = {Handbook of econometrics : Zvi Griliches and Michael D. Intriligator, eds., vol. 1 (North Holland, Amsterdam, 1983) pp. 771}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {393-394}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90062-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{BC02, author = {Richard T. Baillie and Sang-Kuck Chung}, title = {Modeling and forecasting from trend-stationary long memory models with applications to climatology}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {215-226}, number = {2}, abstract = {This paper considers the estimation of both univariate and multivariate trend-stationary ARFIMA models, which generate a long memory autocorrelated process around a deterministic time trend. The model is found to be remarkably successful at representing annual temperature and width of tree ring time series data. Forecasts using this model are found to generally be superior to those from AR models. The results indicate an upward trend in temperature that is consistent with global warming; the results for the tree ring series are ambiguous.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00154-6}, issn = {0169-2070}, keywords = {Climatic change, Dendrochronology, Hurst effect, Long memory, Multivariate ARFIMA, Tree rings, regart} } @ARTICLE{BS87, author = {Richard T. Baillie and David D. Selover}, title = {Cointegration and models of exchange rate determination}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {43-51}, number = {1}, abstract = {The application of new techniques in testing for cointegration indicate the inappropriate- ness of the pure monetary model to explain movements in the nominal exchange rate. In general the fundamental variables are found to be integrated of different orders and there is a lack of cointegration between the exchange rate variables in the monetary model and relative prices. Estimation of other dynamic models are found to give rise to parameter estimates which do not support the monetary model. The results are broadly consistent across five countries. These results imply that it is not worthwhile to forecast from the monetary model and its main variants.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90077-X}, issn = {0169-2070}, keywords = {Monetary model, Non-stationarity, Cointegration, Purchasing power parity, Tests for unit roots, regart} } @ARTICLE{Bails86, author = {Dale Bails}, title = {Sales forecasting: Timesaving and profit-making strategies that work}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {250-251}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90125-1}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Balkin01, author = {Sandy Balkin}, title = {On Forecasting Exchange Rates Using Neural Networks: P.H. Franses and P.V. Homelen, 1998, Applied Financial Economics, 8, 589-596}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {139-140}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00047-9}, issn = {0169-2070} } @ARTICLE{BO00, author = {Sandy D. Balkin and J. Keith Ord}, title = {Automatic neural network modeling for univariate time series}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {509-515}, number = {4}, abstract = {Artificial neural networks (ANNs) are an information processing paradigm inspired by the way the brain processes information. Using neural networks requires the investigator to make decisions concerning the architecture or structure used. ANNs are known to be universal function approximators and are capable of exploiting nonlinear relationships between variables. This method, called Automated ANNs, is an attempt to develop an automatic procedure for selecting the architecture of an artificial neural network for forecasting purposes. It was entered into the M-3 Time Series Competition. Results show that ANNs compete well with the other methods investigated, but may produce poor results if used under certain conditions.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00072-8}, issn = {0169-2070}, keywords = {Artificial neural networks, Automated ANNs, Architecture, regart} } @ARTICLE{BBR95, author = {Sati P. Bandyopadhyay and Lawrence D. Brown and Gordon D. Richardson}, title = {Analysts' use of earnings forecasts in predicting stock returns: Forecast horizon effects}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {429-445}, number = {3}, abstract = {Little attention has been paid to a principal decision context in which analysts' earnings forecasts are prepared, namely, as an input to their recommendations. We use two data sets, Value Line, USA, and Research Evaluation Service, Canada, and examine the importance of analysts' earnings forecasts for their stock price forecasts via three hypotheses: (1) analysts' earnings forecasts are important for their stock price forecasts; (2) analysts' long-term earnings forecasts are more important than their short-term earnings forecasts for their predictions of stock prices over a particular stock price forecast horizon; (3) the importance of analysts' earnings forecasts for their stock price forecasts rises as the joint earnings and stock price forecast horizon increases. We show that: (1) when the earnings forecast horizon is the next fiscal year, forecasted earnings explain only 30% of the variation in forecasted price; (2) the importance of forecasted earnings for forecasted price rises as the earnings forecast horizon increases; (3) in the long run, (i.e. three to five years hence), forecasted earnings explain about 60% of the variation in forecasted price. Decision usefulness is an ex ante concept, but tests regarding the usefulness of earnings for stock price generally have used actual (not expectational) data. Our evidence suggests that earnings expectations are decision useful, where the decision context is sell-side analysts' stock price forecasts. Our results are potentially important to users of sell-side analyst research reports. When a stock recommendation is accompanied only by short-run earnings forecasts, investors need to closely examine estimates of non-earnings variables to assess the quality of stock recommendations. In contrast, when stock recommendations are accompanied by both short-run and long-run earnings forecasts, investors need to examine estimates of non-earnings information variables less closely.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00593-0}, issn = {0169-2070}, keywords = {Analysts, Earnings forecasts, Stock price forcasts, Value line (USA), Research evaluation service (Canada), regart} } @ARTICLE{BM06, author = {Anindya Banerjee and Massimiliano Marcellino}, title = {Are there any reliable leading indicators for US inflation and GDP growth?}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {137-151}, number = {1}, abstract = {In this paper, we evaluate the relative merits of three alternative approaches to extracting information from a large data set for forecasting, namely, the use of an automated model selection procedure, the adoption of a factor model, and the adoption of single-indicator-based forecast pooling. The comparison is conducted using a large set of indicators for forecasting US inflation and GDP growth. We also compare our large set of leading indicators with purely autoregressive models, using an evaluation procedure that is particularly relevant for policy making. The evaluation is conducted both ex post and in a pseudo-real-time context, for several forecast horizons, and using both recursive and rolling estimation. The results indicate a preference for simple forecasting tools, with a good relative performance of pure autoregressive models, and substantial instability in the characteristics of the leading indicators. A pseudo real-time analysis provides a useful guide to the selection of the best leading indicator, in particular for GDP growth.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.03.005}, issn = {0169-2070}, keywords = {Leading indicator, Factor model, Model selection, GDP growth, Inflation, regart} } @ARTICLE{BH01, author = {Anirvan Banerji and Lorene Hiris}, title = {A framework for measuring international business cycles}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {333-348}, number = {3}, abstract = {The classical measurement of business cycles, growth cycles, and growth rate cycles lies at the foundation for the understanding of macroeconomic dynamics in open market economies. This essay presents a framework for analyzing and forecasting cyclical behavior in economic activity, employment, and inflation. The framework is extended to foreign trade and important domestic sectors of an economy such as manufacturing, services, and construction. This multidimensional framework, which allows for a more in-depth analysis, serves as a model to be developed on a comparable basis across countries. Business cycle and growth rate cycle reference chronologies, which have been determined for the major economies, are presented in this context.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00089-9}, issn = {0169-2070}, keywords = {Business cycles, Growth rate cycles, International reference cycles, International reference chronologies, International cycle dates, Turning points, Cyclical analysis, Forecasting, Leading indexes, Long leading indexes, Short leading indexes, Economic sectors, Inflation cycles, Employment cycles, Foreign trade, Exports, Imports, regart} } @ARTICLE{Barbera85, author = {Anthony J. Barbera}, title = {Estimation and simulation of industry factor demand equations}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {273-286}, number = {3}, abstract = {A factor demand model derived from the Generalized Leontief Cost Function is outlined. The model is estimated for 53 U.S. industries which together make up the entire U.S. economy. The purpose of the model is to provide long-run forecasts of equipment investment and labor productivity within the context of an input-output forecasting model. Extensive discussion is devoted to selection of functional form, modeling of dynamics, and estimation technique, with special emphasis upon the considerations which uniquely confront the forecaster. An array of a priori constraints are imposed upon the estimation, reflecting a body of empirical evidence and theoretical requirements. In addition, elasticity estimates are reported, as well as evidence on the short-run simulation performance of the mode.}, doi = {http://dx.doi.org/10.1016/0169-2070(85)90007-X}, issn = {0169-2070}, keywords = {Forecasting, Duality theory, Econometrics, regart} } @ARTICLE{Barnett88, author = {Arnold Barnett}, title = {Prediction and criminology : David P. Farrington and Roger Tarling, eds. (State University of New York Press, 1985) pp. 218, \$49.50}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {292-294}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90086-6}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{BS89, author = {Sonia M. Bartolomei and Arnold L. Sweet}, title = {A note on a comparison of exponential smoothing methods for forecasting seasonal series}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {111-116}, number = {1}, abstract = {Additive seasonal models and multiplicative seasonal models can be forecast using general exponential smoothing and Winters' methods. The two forecasting methods were compared using 47 of the 1001 time series which were used in the M-competition. Values of the optimal smoothing constants found when fitting the models are shown. Although Winters' models always resulted in a better squared error fit, these models gave a better forecast in only 55% of the series.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90068-X}, issn = {0169-2070}, keywords = {Comparative methods -- exponential smoothing, Exponential smoothing -- higher order, Winters, regart} } @ARTICLE{Bass87, author = {Frank M. Bass}, title = {Misspecification and the inherent randomness of the model are at the heart of the Brodie and de Kluyver enigma}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {441-444}, number = {3-4}, abstract = {This comment provides an explanation of why econometric market share models with explanatory variables do not always dominate `naive' models that simply predict that future share will equal current share. The empirical evidence cited by Brodie and de Kluyver and others is used as a framework to illustrate how short-term forecasts suffer from (1) misspecification and (2) variance, while long-term forecasts of market share are biased.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90037-9}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{Batchelor07, author = {Roy Batchelor}, title = {Bias in macroeconomic forecasts}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {189-203}, number = {2}, abstract = {This paper documents the presence of systematic bias in the real GDP and inflation forecasts of private sector forecasters in the G7 economies in the years 1990-2005. The data come from the monthly Consensus Economics forecasting service, and bias is measured and tested for significance using parametric fixed effect panel regressions and nonparametric tests on accuracy ranks. We examine patterns across countries and forecasters to establish whether the bias reflects the inefficient use of information, or whether it reflects a rational response to financial, reputational and other incentives operating for forecasters. In several G7 countries - Japan, Italy, Germany and France - there is evidence of a change in the trend growth rate. In these circumstances, standard tests for rationality are inappropriate, and a bias towards optimism in the consensus forecast is inevitable as rational forecasters learn about the new trend. In all countries there is evidence that individual forecasters converge on the consensus forecast too slowly. However, the persistent optimism of some forecasters, and the persistent pessimism of others, is not consistent with the predictions of models of rationalbias that have become popular in the finance and economics literature.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.01.004}, issn = {0169-2070}, keywords = {Macroeconomic forecasts, Judgmental forecasting, Bias, regart} } @ARTICLE{BD90, author = {Roy A. Batchelor and Pami Dua}, title = {Product differentiation in the economic forecasting industry}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {311-316}, number = {3}, abstract = {This paper tests whether economic forecasters differentiate their products, either by making forecasts which are consistently more optimistic or pessimistic than the industry average, or by developing comparative advantages in forecasting some variables at the expense of others. Application of nonpara-metric tests to the track records of 19 U.S. forecasters shows that the first strategy is followed, but not the second. These results imply that many forecasters may have found it optimal to produce forecasts which are technically irrational.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90058-J}, issn = {0169-2070}, keywords = {Economic forecasting, Accuracy of forecasts, Rational expectations, regart} } @ARTICLE{BAV07, author = {Roy Batchelor and Amir Alizadeh and Ilias Visvikis}, title = {Forecasting spot and forward prices in the international freight market}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {101-114}, number = {1}, abstract = {This paper tests the performance of popular time series models in predicting spot and forward rates on major seaborne freight routes. Shipping is a nonstorable service, so the forward price is not tied to the spot by any arbitrage relationship. The developing forward market is dominated by hedgers, and it is an empirical question whether forward rates contain information about future spot rates. We find that vector equilibrium correction (VECM) models give the best in-sample fit, but implausibly suggest that forward rates converge strongly on spot rates. In out-of-sample forecasting all models easily outperform a random walk benchmark. Forward rates do help to forecast spot rates, suggesting some degree of speculative efficiency. However, in predicting forward rates, the VECM is unhelpful, and ARIMA or VAR models forecast better. The exercise illustrates the dangers of forecasting with equilibrium correction models when the underlying market structure is evolving, and coefficient estimates conflict with sensible priors.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.07.004}, issn = {0169-2070}, keywords = {Forecasting, Freight market, Commodity market: Vector equilibrium correction model, ARIMA model, regart} } @ARTICLE{BD98, author = {Roy Batchelor and Pami Dua}, title = {Improving macro-economic forecasts: The role of consumer confidence}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {71-81}, number = {1}, abstract = {The failure of economic forecasters to predict the most recent US recession has renewed interest in the idea of supplementing model-based forecasts with information from other, more qualitative, indicators. This paper tests whether one such variable, the consumer confidence index, could have improved these forecasts; and whether improvements are greatest for forecasts generated by econometric models with little judgmental adjustment. We find that consumer confidence would have been helpful in predicting the 1991 recession. But the result does not generalize to other years, and appears to reflect the special nature of the recession rather than a persistent weakness in forecasting technique.}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00052-6}, issn = {0169-2070}, keywords = {Forecasting, Consumer confidence, Rational expectations, regart} } @ARTICLE{BK07, author = {Roy Batchelor and Tai Yeong Kwan}, title = {Judgemental bootstrapping of technical traders in the bond market}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {427-445}, number = {3}, abstract = {In many domains the decisions of experts are inferior to the decisions of statistical models of experts. The aim of this paper is to test this proposition in the financial markets, where genuine expertise is hard to find and the drivers of success are unclear. We exploit a unique database containing the recommended trading positions of technical analysts following the German bond market, and questionnaires revealing the technical indicators they used. The analysts have only average directional forecasting ability, but make consistent profits through superior market timing. Ordered-response models describing their positions in each market, driven by a subset of the technical indicators they claim to use, make even more profits. Models based on pooled data from several markets do better still. However, the pattern of model based trades is different from, and more risky than, the pattern of analyst trades. So it cannot be claimed that the models mimic the judgement process, or that the outcomes clearly dominate those from expert judgement.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.05.007}, issn = {0169-2070}, keywords = {judgemental bootstrapping, Technical analysis, Forecasting, regart} } @ARTICLE{BD90a, author = {Roy Bathcelor and Pami Dua}, title = {Forecaster ideology, forecasting technique, and the accuracy of economic forecasts}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {3-10}, number = {1}, abstract = {This paper uses a survey of US economic forecasters to assess the impact of their theories and forecasting methods on the accuracy of their predictions for a number of macroeconomic variables. Forecasters who give more weight to Keynesian ideology and econometric modelling dominate predominantly atheoretical times series forecasters for most variables. Although Keynesianism is the most popular ideology in practice, most forecasters place more weight on judgment than on any formal modelling technique.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90093-Q}, issn = {0169-2070}, keywords = {Economic forecasting, Survey of forecasters, Econometric forecasting, Time series forecasting, Judgmental forecasting, regart} } @ARTICLE{Baum04, author = {Christopher F. Baum}, title = {A review of Stata 8.1 and its time series capabilities}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {151-161}, number = {1}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.11.007}, issn = {0169-2070}, keywords = {prodrev} } @ARTICLE{BGG+04, author = {Luc Bauwens and Pierre Giot and Joachim Grammig and David Veredas}, title = {A comparison of financial duration models via density forecasts}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {589-609}, number = {4}, abstract = {Using density forecast evaluation techniques, we compare the predictive performance of econometric specifications that have been developed for modeling duration processes in intra-day financial markets. The model portfolio encompasses various variants of the Autoregressive Conditional Duration (ACD) model and recently proposed dynamic factor models. The evaluation is conducted on time series of trade, price and volume durations computed from transaction data of NYSE listed stocks. The results show that simpler approaches perform at least as well as more complex methods. With respect to modeling trade duration processes, standard ACD models successfully account for duration dynamics while none of the models provides an acceptable specification for the conditional duration distribution. We find that the Logarithmic ACD, if based on a flexible innovation distribution, provides a quite robust and useful framework for the modeling of price and volume duration processes.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.09.014}, issn = {0169-2070}, keywords = {Duration processes, Transactions data, Intra-day financial markets, Density forecast evaluation, regart} } @ARTICLE{Beaumont88, author = {Chris Beaumont}, title = {Cash flow forecasting : G.R. Kaye and K.N. Bhaskar, Report No. 211, Planning with personal computers 1 (The Economist Publications, 1985) pp. 98, �55}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {300-300}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90091-X}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Beaumont86, author = {Chris Beaumont}, title = {Understanding management software : A. Leigh, (Macmillan, London, 1985) �11.50, pp. 286}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {505-506}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90104-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{BC08, author = {Ralf Becker and Adam E. Clements}, title = {Are combination forecasts of S\&P 500 volatility statistically superior?}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {122-133}, number = {1}, abstract = {Forecasting volatility has received a great deal of research attention, with the relative performances of econometric model based and option implied volatility forecasts often being considered. While many studies find that implied volatility is the pre-ferred approach, a number of issues remain unresolved, including the relative merit of combining forecasts and whether the relative performances of various forecasts are statistically different. By utilising recent econometric advances, this paper considers whether combination forecasts of S&P 500 volatility are statistically superior to a wide range of model based forecasts and implied volatility. It is found that a combination of model based forecasts is the dominant approach, indicating that the implied volatility cannot simply be viewed as a combination of various model based forecasts. Therefore, while often viewed as a superior volatility forecast, the implied volatility is in fact an inferior forecast of S&P 500 volatility relative to model-based forecasts.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.09.001}, issn = {0169-2070}, keywords = {Implied volatility, Volatility, Forecasts, Volatility models, Combination forecasts, Model confidence sets, regart} } @ARTICLE{BOe10, author = {Meredith Beechey and Par Osterholm}, title = {Forecasting inflation in an inflation-targeting regime: A role for informative steady-state priors}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {248 - 264}, number = {2}, note = {Special Issue: Bayesian Forecasting in Economics}, doi = {10.1016/j.ijforecast.2009.10.006}, issn = {0169-2070}, keywords = {Monetary policy, Central bank preferences} } @ARTICLE{Beenstock88, author = {Michael Beenstock}, title = {The performance of UK exchange rate forecasters : David Blake, Michael Beenstock and Valerie Brasse, Economic Journal 96 (1986) 986-999}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {627-629}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90146-X}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{BS04, author = {S{\'e}bastien Van Bellegem and Rainer von Sachs}, title = {Forecasting economic time series with unconditional time-varying variance}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {611-627}, number = {4}, abstract = {The classical forecasting theory of stationary time series exploits the second-order structure (variance, autocovariance, and spectral density) of an observed process in order to construct some prediction intervals. However, some economic time series show a time-varying unconditional second-order structure. This article focuses on a simple and meaningful model allowing this nonstationary behaviour. We show that this model satisfactorily explains the nonstationary behaviour of several economic data sets, among which are the U.S. stock returns and exchange rates. The question of how to forecast these processes is addressed and evaluated on the data sets.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.10.002}, issn = {0169-2070}, keywords = {Covariance nonstationarity, Rescaled time, Time-modulated process, Nonparametric estimation, Forecasting, regart} } @ARTICLE{Bellucci10, author = {Paolo Bellucci}, title = {Election cycles and electoral forecasting in Italy, 1994-2008}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {54 - 67}, number = {1}, note = {Special Section: European Election Forecasting}, doi = {10.1016/j.ijforecast.2009.09.004}, issn = {0169-2070}, keywords = {Italian government approval, Vote and popularity functions,Election forecasting,Electoral cycle,Italian 2nd Republic} } @ARTICLE{Belsley88, author = {David A. Belsley}, title = {Modelling and forecasting reliability}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {427-447}, number = {3}, abstract = {Four (counter) examples are used to estblish the proposition that good forecasting requires a meaningful and proper model, particularly when forecasting into situations that differ greatly from those that characterize the data upon which the model estimates are based. It is also argued that, contrary to much current opinion, it is this latter activity that is the real art of forecasting. The central notion of a `meaningful and proper' model is defined, and the process leading to its construction is examined.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90110-0}, issn = {0169-2070}, keywords = {Prediction, Model-building, Model-evaluation, Model-interpretation, Model-specification, Model-testing, regart} } @ARTICLE{Belsley86, author = {David A. Belsley}, title = {Model selection in regression analysis, regression diagnostics and prior knowledge : A book review article with comments from Anthony C. Atkinson, D.R. Cox And John McDonald}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {41-52}, number = {1}, abstract = {Model selection of a regression model typically includes both selecting which variables to include in a model and the functional form of the relationship between the variables. In recent years regression diagnostics (a catch-all phrase that includes such topics as identifying influential observations) have been increasingly used as an aid in selecting a regression model. In evaluating the recent book Residuals and influence in regression, by Cook and Weisberg, Belsley argues that such analyses, while extremely useful, should not be used in a theoretical vacuum. Effective model building requires the analyst to make substantial use of any prior information relevant to the problem in hand. The commentators, while accepting the general thrust of Belsley's comments, are on the whole more sceptical -- perhaps the prior knowledge is poor and in conflict with the data; perhaps the use of a wrong theory is more dangerous than `letting the data speak for themselves'.}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90029-4}, issn = {0169-2070}, keywords = {Regression, model choice, review, Specification error, tests, model selection, Regression, diagnostics, Prior information, Evaluation, ex post models, Comparative methods, regression, non-linear, regart} } @ARTICLE{BG96, author = {Valerie Belton and Paul Goodwin}, title = {Remarks on the application of the analytic hierarchy process to judgmental forecasting}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {155-161}, number = {1}, abstract = {The analytical hierarchy process (AHP) has been proposed as a method for improving judgmental forecasts. This paper argues that some applications of the method are ill founded because they involve the inappropriate weighting of the factors which will influence the forecast variable and do not permit the modelling of situations where these factors operate to their fullest extent at the same time. Modifications to the method are proposed.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00643-5}, issn = {0169-2070}, keywords = {Judgmental forecasting, Decomposition, AHP, regart} } @ARTICLE{BCP06, author = {Pilar Bengoechea and Maximo Camacho and Gabriel Perez-Quiros}, title = {A useful tool for forecasting the Euro-area business cycle phases}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {735-749}, number = {4}, abstract = {Based on a novel extension of existing multivariate Markov-switching models, we provide the reader with a useful tool for analyzing current business conditions and making predictions about the future state of the Euro-area economy in real time. Apart from the Industrial Production Index, we find that the European Commission Industrial Confidence Indicator, which is issued with no delay, is very useful for constructing the real-time predictions.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.01.002}, issn = {0169-2070}, keywords = {Business cycles, Confidence indicators, Markov switching, Turning points, regart} } @ARTICLE{BOe92, author = {P. George Benson and Dilek{\"O}nkal}, title = {The effects of feedback and training on the performance of probability forecasters}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {559-573}, number = {4}, abstract = {An experiment examined the effects of outcome feedback and three types of performance feedback-calibration feedback, resolution feedback, and covariance feedback - on various aspects of the performance of probability forecasters. Subjects made 55 forecasts in each of four sessions, receiving feedback prior to making their forecasts in each of the last three sessions. The provision of calibration feedback was effective in improving both the calibration and overforecasting of probability forecasters, but the improvement was not gradual; it occurred in one step, between the second and third sessions. Simple outcome feedback had very little effect on forecasting performance. Neither resolution nor covariance feedback affected forecasters' performances much differently than outcome feedback. However, unlike outcome feedback, the provision of performance feedback caused subjects to manage their use of the probability scale. Subjects switched from two-digit probabilities to one-digit probabilities, and those receiving calibration and resolution feedback also reduced the number of different probabilities they used.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90066-I}, issn = {0169-2070}, keywords = {Probability forecasting, Judgmental forecasting, Subjective probability, Outcome feedback, Performance feedback, Scoring rules, Calibration, Resolution, Covariance decomposition, regart} } @ARTICLE{BFG+02, author = {Jan Beran and Yuanhua Feng and Sucharita Ghosh and Philipp Sibbertsen}, title = {On robust local polynomial estimation with long-memory errors}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {227-241}, number = {2}, abstract = {Prediction in time series models with a trend requires reliable estimation of the trend function at the right end of the observed series. Local polynomial smoothing is a suitable tool because boundary corrections are included implicitly. However, outliers may lead to unreliable estimates, if least-squares regression is used. In this paper, local polynomial smoothing based on M-estimation is considered for the case where the error process exhibits long-range dependence. In contrast to the iid case, all M-estimators are asymptotically equivalent to the least-square solution, under the (ideal) Gaussian model. The potential usefulness of the proposal for forecasting is illustrated by practical and simulated examples. A simulation study shows that outliers have a major effect on nonrobust bandwidth selection, in particular due to the change of the dependence structure.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00155-8}, issn = {0169-2070}, keywords = {Local polynomial, Long memory, M-estimator, SEMIFAR model, Forecasting, regart} } @ARTICLE{BNR08, author = {Joyce E. Berg and Forrest D. Nelson and Thomas A. Rietz}, title = {Prediction market accuracy in the long run}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {285-300}, number = {2}, abstract = {'Prediction markets' are designed specifically to forecast events such as elections. Though election prediction markets have been being conducted for almost twenty years, to date nearly all of the evidence on efficiency compares election eve forecasts with final pre-election polls and actual outcomes. Here, we present evidence that prediction markets outperform polls for longer horizons. We gather national polls for the 1988 through 2004 U.S. Presidential elections and ask whether either the poll or a contemporaneous Iowa Electronic Markets vote-share market prediction is closer to the eventual outcome for the two-major-party vote split. We compare market predictions to 964 polls over the five Presidential elections since 1988. The market is closer to the eventual outcome 74% of the time. Further, the market significantly outperforms the polls in every election when forecasting more than 100 days in advance.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.03.007}, issn = {0169-2070}, keywords = {Combining forecasts, Evaluating forecasts, Financial markets, Election forecasting, Polls, Comparative methods, Automatic forecasting, Calibration, Comparative studies, Long-term forecasting, Election market, Political stock market, regart} } @ARTICLE{Bergstroem95, author = {Reinhold Bergstr{\"o}m}, title = {The relationship between manufacturing production and different business survey series in Sweden 1968-;1992}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {379-393}, number = {3}, abstract = {The relationship between production in total manufacturing measured as an ordinary volume series and various barometer series from the Swedish Business Tendency Surveys is investigated using data from the period 1968-;1992. Models are constructed using a systematic strategy aiming at parsimonious models within the Autoregressive-Distributed Lag (ADL) class. Autoprojective models that serve as a baseline in the comparisons are estimated. The performance of these models is compared with models that include barometer series. In the main, seasonally unadjusted series are used and models formulated both in terms of quarter-to-quarter and annual changes are considered. As regards immediate ease of interpretation, the latter have an advantage, but there is not much difference between the quality of the two types of models. The best barometer series is found to be volume of production and a model including this series is a significant improvement on the best autoprojective model. There is a close relationship between the barometer production series and the annual change in the volume series. About twenty-five other barometer series are also considered, but they are not found to provide additional information. In order to come closer to a forecasting model, ex ante variables are also considered. The connection between each ex ante and the corresponding ex post variable is investigated including a study of possible lagged and seasonal effects. Finally models based on the information set available at time-point t-1 are obtained.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00601-7}, issn = {0169-2070}, keywords = {Forecasting, business survey data, ex ante/ex postregart} } @ARTICLE{Berliner92, author = {L. Mark Berliner}, title = {Journal of the American statistics association: Likelihood and bayesian prediction of chaotic systems, 86 (1991) 938-952.}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {650-651}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90084-M}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Bernstein88, author = {Jeffrey I. Bernstein}, title = {Multiple outputs, adjustment costs and the structure of production for Bell Canada}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {207-219}, number = {2}, abstract = {A dynamic model of production is developed and estimated for Bell Canada. Dynamic models are forward- looking so that forecasts are required of the exogenous variables. Equations are specified which define these expectations-generating processes. In this model, output is disaggregated into local and toll categories. The dynamics arise from adjustment costs associated with changes to the capital stock. It is estimated that for $1.00 of marginal capital costs there are additional adjustment costs of $0.40. Price, output and scale elasticities are estimated. The existence of adjustment costs shows that the effects of price and output changes on factor demands are each significantly different from the effects obtained from static models without adjustment costs. Thus substantial forecast errors with respect to input requirements will he made if adjustment costs are ignored. The disaggregation of output into local and toll categories allows for the differential effects on production cost. The relatively small effect that toll output exerts on variable cost is the reason that Bell Canada exhibits increasing returns to scale.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90078-7}, issn = {0169-2070}, keywords = {Adjustment cost, Capital stock, Expectations, Output, Production, Telecommunications, Variable cost, regart} } @ARTICLE{Bessler94, author = {David A. Bessler}, title = {Economic forecasting in agriculture: Discussion}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {137-138}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90053-1}, issn = {0169-2070} } @ARTICLE{Bewley00, author = {Ronald Bewley}, title = {Mr Henri Theil:: an interview with the International Journal of Forecasting}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {1-16}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00031-X}, issn = {0169-2070}, keywords = {revart} } @ARTICLE{Bewley97, author = {Ronald Bewley}, title = {The forecast process and academic research}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {433-437}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00047-2}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{BF88, author = {Ronald Bewley and Denzil G. Fiebig}, title = {A flexible logistic growth model with applications in telecommunications}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {177-192}, number = {2}, abstract = {In this paper, we develop a four-parameter generalization of the logistic growth curve, the flexible-logistic (FLOG) model. It is shown that the FLOG model is sufficiently general to locate its point of inflection anywhere between its upper and lower bounds: it can offer wide variation in its degree of symmetry for a given point of inflection. Although additional parameters always produce a better within-sample fit. the specific flexibility introduced by the FLOG class of models emphasises the forecast properties by controlling the saturation level and the approach to that level. The model is subjected to a number of theoretical and empirical tests and is applied to three sets of telecommunications data.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90076-3}, issn = {0169-2070}, keywords = {Box-Cox transformation, Forecasting, Saturation levels, S-shaped growth curves, Stochastic specification, Telecommunications, regart} } @ARTICLE{BG03, author = {Ronald Bewley and William E. Griffiths}, title = {The penetration of CDs in the sound recording market: issues in specification, model selection and forecasting}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {111-121}, number = {1}, abstract = {Annual data on the market penetration of music CDs in 12 countries are used to consider two issues in a forecasting comparison of 12 model specifications and three sample sizes. Firstly, particular attention is paid to the impact of stochastic specification of the models on the estimation of the saturation levels and forecasts. Secondly, the issue of model complexity and sample size is addressed by including two four-parameter models with various specialisations, other three-parameter models, and three different sample sizes. There is reasonably strong support for one particular model which is a member of Bewley and Fiebig's (Int. J. Forecasting 4 (1988) 177) flexible logistic class.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00133-9}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{BK02, author = {R. J. Bhansali and P. S. Kokoszka}, title = {Computation of the forecast coefficients for multistep prediction of long-range dependent time series}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {181-206}, number = {2}, abstract = {Three different linear methods, called the truncation, type-II plug-in and type-II direct, for constructing multistep forecasts of a long-range dependent time series are discussed, all three methods being based on a stochastic model fitted to the time series for characterizing its long-memory as well as short-memory components. However, while the forecast coefficients for the truncation method may be obtained from the model equation itself, those for the type-II plug-in and type-II direct methods involve the autocorrelation function of the fitted stochastic model, analytic exact expressions for which may be cumbersome to evaluate. A numerical quadrature procedure, based on the fast Fourier transform algorithm, for computing the autocorrelation function of a long-memory process, as well as the forecast coefficients for the truncation method, is suggested and the computational accuracy of the approximations is investigated for several ARFIMA models. The three methods of constructing the forecasts of a long-memory time series apply when the innovations, [epsilon]t, of the fitted model are postulated to follow a Gaussian distribution, and, also, when they follow an infinite variance stable distribution with characteristic exponent [tau], 1<[tau]<2. A comparison of the multistep forecasts produced by these three methods is carried out by simulating several ARFIMA models with both Gaussian and stable innovations, and two FEXP models with Gaussian innovations. In addition, their relative behaviour with an actual time series, namely, the mean temperature in England, 1659-1976, is examined.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00152-2}, issn = {0169-2070}, keywords = {Long memory, Prediction, regart} } @ARTICLE{BT08, author = {Prasad S. Bhattacharya and Dimitrios D. Thomakos}, title = {Forecasting industry-level CPI and PPI inflation: Does exchange rate pass-through matter?}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {134-150}, number = {1}, abstract = {We show that incorporating the effects of exchange rate pass-through into a model can help in obtaining superior forecasts of domestic, industry-level inflation. Our analysis is based on a multivariate system of domestic inflation, import prices and exchange rates that incorporates restrictions from economic theory. These are restrictions on the transmission channels of the exchange rate pass-through to domestic prices, and are presented as testable hypotheses that lead to model reduction. We provide the results of various tests, including causality and prior restrictions, which support the underlying economic arguments and the model we use. The forecasting results for our model suggest that it has a superior performance overall, jointly producing more accurate forecasts of domestic inflation.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.06.002}, issn = {0169-2070}, keywords = {Causality, Direction of change, Econometric model, Exchange rates, Forecasting, Inflation, Model reduction, Pass-through, VAR model, VARMA model, regart} } @ARTICLE{BCB87, author = {Carlo Bianchi and Giorgio Calzolari and Jean-Louis Brillet}, title = {Measuring forecast uncertainty : A review with evaluation based on a macro model of the French economy}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {211-227}, number = {2}, abstract = {Five alternative techniques have been applied to measure the degree of uncertainty associated with the forecasts produced by a macro-model of the French economy, the Mini-DMS developed at INSEE. They are bootstrap, analytic simulation on coefficients, Monte Carlo on coefficients, parametric stochastic simulation and re-estimation, a residual-based procedure. Due to the complexity and the size of the model (nonlinear and with more than 200 equations), several associated technical problems had to be solved. The remarkable convergence of results which has been obtained for all the main endogenous variables suggests that forecast confidence intervals are likely to be quite reliable for this model.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90003-3}, issn = {0169-2070}, keywords = {Simultaneous system; Confidence intervals; Macro model-France; Macro models-methodology; Monte Carlo; Bootstrapping; Analytic simulation; Stochastic simulation; Residual-based procedures, revart} } @ARTICLE{BJH98, author = {Lisa Bianchi and Jeffrey Jarrett and R. Choudary Hanumara}, title = {Improving forecasting for telemarketing centers by ARIMA modeling with intervention}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {497-504}, number = {4}, abstract = {In this study we analyze existing and improved methods for forecasting incoming calls to telemarketing centers for the purposes of planning and budgeting. We analyze the use of additive and multiplicative versions of Holt-Winters (HW) exponentially weighted moving average models and compare it to Box-Jenkins (ARIMA) modeling with intervention analysis. We determine the forecasting accuracy of HW and ARIMA models for samples of telemarketing data. Although there is much evidence in recent literature that simplemodels such as Holt-Winters perform as well as or better than more complex models, we find that ARIMA models with intervention analysis perform better for the time series studied.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00037-5}, issn = {0169-2070}, keywords = {Holt-Winters models, Intervention Analysis, Box-Jenkins (ARIMA) modeling, Time Series, regart} } @ARTICLE{Bidarkota98, author = {Prasad V. Bidarkota}, title = {The comparative forecast performance of univariate and multivariate models: an application to real interest rate forecasting}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {457-468}, number = {4}, abstract = {Does the use of information on the past history of the nominal interest rates and inflation entail improvement in forecasts of the ex ante real interest rate over its forecasts obtained from using just the past history of the realized real interest rates? To answer this question we set up a univariate unobserved components model for the realized real interest rates and a bivariate model for the nominal rate and inflation which imposes cointegration restrictions between them. The two models are estimated under normality with the Kalman filter. It is found that the error-correction model provides more accurate one-period ahead forecasts of the real rate within the estimation sample whereas the unobserved components model yields forecasts with smaller forecast variances. In the post-sample period, the forecasts from the bivariate model are not only more accurate but also have tighter confidence bounds than the forecasts from the unobserved components model.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00036-3}, issn = {0169-2070}, keywords = {Unobserved components models, ARIMA models, Cointegration, Kalman filtering, Forecast evaluation, regart} } @ARTICLE{BY95, author = {Vicki M. Bier and Woojune Yi}, title = {A Bayesian method for analyzing dependencies in precursor data}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {25-41}, number = {1}, abstract = {Past Bayesian methods for analyzing accident precursor data have rested on unreasonable simplifying assumptions; in particular, the assumption that successive stages of each accident sequence (e.g. successive system failures) are independent. However, obtaining information on intersystem dependencies is one of the greatest benefits of precursor analysis. With such dependencies, each system may have not one but several conditional failure probabilities; for example, one under normal or test conditions, and another during accident conditions (e.g. after other systems have already failed). These probabilities, while not identical, may be correlated, since the system will contain the same components (with the same inherent reliability levels) regardless of whether other systems have already failed. In this paper, extended natural conjugate distributions are used in a Bayesian method to analyze pairs of correlated probabilities. While motivated by applications to precursor analysis, the method is in fact quite general.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)02011-D}, issn = {0169-2070}, keywords = {Accident precursors, Bayesian analysis, Natural conjugate distributions, Dependence, regart} } @ARTICLE{BKS+06, author = {Baki Billah and Maxwell L. King and Ralph D. Snyder and Anne B. Koehler}, title = {Exponential smoothing model selection for forecasting}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {239-247}, number = {2}, abstract = {Applications of exponential smoothing to forecasting time series usually rely on three basic methods: simple exponential smoothing, trend corrected exponential smoothing and a seasonal variation thereof. A common approach to selecting the method appropriate to a particular time series is based on prediction validation on a withheld part of the sample using criteria such as the mean absolute percentage error. A second approach is to rely on the most appropriate general case of the three methods. For annual series this is trend corrected exponential smoothing: for sub-annual series it is the seasonal adaptation of trend corrected exponential smoothing. The rationale for this approach is that a general method automatically collapses to its nested counterparts when the pertinent conditions pertain in the data. A third approach may be based on an information criterion when maximum likelihood methods are used in conjunction with exponential smoothing to estimate the smoothing parameters. In this paper, such approaches for selecting the appropriate forecasting method are compared in a simulation study. They are also compared on real time series from the M3 forecasting competition. The results indicate that the information criterion approaches provide the best basis for automated method selection, the Akaike information criteria having a slight edge over its information criteria counterparts.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.08.002}, issn = {0169-2070}, keywords = {Model selection, Exponential smoothing, Information criteria, Prediction, Forecast validation, regart} } @ARTICLE{BC85, author = {Robert Bilongo and Robert Carbone}, title = {Adaptive model-based seasonal adjustment of time series : An Empirical Comparison with XII-ARIMA and SIGEX}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {165-177}, number = {2}, abstract = {Several model-based approaches have been proposed in recent years for adjusting and decomposing time series data. Using real world data, this paper presents results of a large scale empirical comparison of the XII-ARIMA and SIGEX procedures to DESAEP, a new adaptive model-based method that combines stochastic and deterministic effects. The comparison reveals no substantial inconsistencies in seasonally adjusted values produced by the 3 methods. As for the magnitude in revisions in both concurrent and forecasted seasonally adjusted values, an overall reduction by a factor of 2 to 3 was obtained with DESAEP depending on the level of variability in the data.}, doi = {http://dx.doi.org/10.1016/0169-2070(85)90021-4}, issn = {0169-2070}, keywords = {Seasonal adjustment, Empirical comparison, SIGEX, XII-ARIMA, DESAEP, regart} } @ARTICLE{BH87, author = {John F. O. Bilson and David A. Hsieh}, title = {The profitability of currency speculation}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {115-130}, number = {1}, abstract = {This paper presents the results of a post-sample simulation of a speculative strategy using a portfolio of foreign currency forward contracts. The main new features of the speculative strategy are (a) the use of Kalman filters to updata the forecasting equation, (b) the allowance for transactions costs and margin requirements and (c) the endogeneous determination of the leveraging of the portfolio. While the forecasting model tended to overestimate profit and underestimate risk, the strategy was still profitable over a three year period and it was possible to reject the hypothesis that the sum of profits was zero.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90082-3}, issn = {0169-2070}, keywords = {Exchange rates, Speculation, Ex ante, Loss functions, regart} } @ARTICLE{BCD00, author = {David C. Black and Paul R. Corrigan and Michael R. Dowd}, title = {New dogs and old tricks: do money and interest rates still provide information content for forecasts of output and prices?}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {191-205}, number = {2}, abstract = {Out-of-sample forecasting experiments are used as an alternative to looking at F-statistics when examining whether money, interest rates or the commercial paper/T-bill spread provide information content for subsequent movements in output, real and nominal personal income, the CPI and the PPI. Here, a variable provides information if it improves the forecast of the explained variable. Employing this procedure we find that the paper-bill spread but not monetary aggregates provide information content for industrial production or real personal income when using data over the 1980-1997 period. In contrast, we find that monetary aggregates provide information content for the CPI and nominal personal income but not the PPI.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00035-2}, issn = {0169-2070}, keywords = {Macroeconomic forecasting: industrial production, personal income, inflation, Time series, regart} } @ARTICLE{BF95, author = {Gail Blattenberger and Richard Fowles}, title = {Road closure to mitigate avalanche danger: a case study for Little Cottonwood Canyon}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {159-174}, number = {1}, abstract = {Avalanche forecasters make decisions to close the Little Cottonwood Canyon Highway to vehicular traffic in the case of avalanche danger. A statistical model improves forecasting performance. Conditions do not vary simply by day as implied in the statistical model, but the development of the snowpack varies substantially among seasons. There are persistent features of a snowpack which affect avalanche danger within each season. Forecasters' performance also varies substantially over seasons. This paper attempts to incorporate this feature into an operational method to develop seasonal weights to combine data and expert opinion.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)02008-D}, issn = {0169-2070}, keywords = {Decision making under risk, forecasting, regart} } @ARTICLE{BCF+07, author = {David E. Bloom and David Canning and G{\"u}nther Fink and Jocelyn E. Finlay}, title = {Does age structure forecast economic growth?}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {569-585}, number = {4}, abstract = {Increases in the proportion of the working age population can yield a demographicdividend that enhances the rate of economic growth. We estimate the parameters of an economic growth model using a cross section of countries over the period 1960 to 1980, and investigate whether the inclusion of age structure improves the model's forecasts for the period 1980 to 2000. We find that including the age structure improves the forecast, although there is evidence of parameter instability between periods with an unexplained growth slowdown in the second period. We use the model to generate growth forecasts for the period 2000 to 2020.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.07.001}, issn = {0169-2070}, keywords = {Economic growth, Demography, Forecast evaluation, Error decomposition, regart} } @ARTICLE{BG92, author = {David E. Bloom and Sherry Glied}, title = {Projecting the number of new AIDS cases in the United States}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {339-365}, number = {3}, abstract = {This paper reviews the two leading methods used to project the number of AIDS cases: back calculation and extrapolation. These methods are assessed in light of key features of the HIV/AIDS epidemic and of data on the epidemic; they are also assessed in terms of the quality of the projections they yield. Our analysis shows that both methods have tended to overproject, often by sizable amounts, the number of AIDS cases in the United States, especially among homosexual/bisexual males and users of blood and blood products. Our results provide no evidence that the use of AZT and other prophylaxis accounts for these projection errors. Rather, the overprojections appear to be mainly the result of a considerable reduction in the rate of new HIV infection among the gay community starting in 1983-1985. A new method for projecting AIDS cases is proposed that exploits knowledge about the process generating AIDS cases and that incorporates readily available information about rates of new HIV infection. This method is far less sensitive to estimates of the incubation distribution than the method of back calculation and is shown, for the two transmission categories studied, to generate far more accurate AIDS case projections through 1990 than those based on the method of extrapolation. Relative to the method of extrapolation, this method projects 22000 fewer new AIDS cases for 1995 (a 36% difference). This method also projects that intravenous drug users will replace homosexual/bisexual men as the dominant transmission category for AIDS.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90052-B}, issn = {0169-2070}, keywords = {AIDS, Projection, Forecastingregart} } @ARTICLE{BS87a, author = {Giorgio Bodo and Luigi Federico Signorini}, title = {Short-term forecasting of the industrial production index}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {245-259}, number = {2}, abstract = {A correct and timely assessment of the cyclical situation is essential for policy-making One of the most commonly used indicators is the industrial production index. In Italy a preliminary value of the index is only published 40-50 days after the end of the reference month. The authors present several methods for obtaining earlier estimates, including (a) simple univariate models, (b) an OLS model that employs data on electric power input, corrected for the effects of temperature and (indirectly) of the manufacturing output mix, (c) a transfer-function model based on business surveys. The results are satisfactory. The best single forecasts are those based on the electric power input, but combining these with business surveys gives even better predictions.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90006-9}, issn = {0169-2070}, keywords = {Industrial production, Estimation, Time series methods, Forecasts, Leading indicators, regart} } @ARTICLE{Boehm93, author = {Ernst A. Boehm}, title = {Business cycles: Theory, history, indicators, and forecasting : Victor Zarnowitz, 1992, (University of Chicago Press, Chicago), xvii + 593 pp., \$70.00, ISBN 0-226-97890-7}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {275-277}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90014-E}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{BM91, author = {Ernst A. Boehm and Geoffrey H. Moore}, title = {Financial market forecasts and rates of return based on leading index signals}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {357-374}, number = {3}, abstract = {This report describes and analyzes a practical system which will assist financial analysts and portfolio managers to maximize the annual rate of return in their asset-allocation program when choosing between stocks, short-term bills and long-term bonds. The level and stability of the total rates of return (from capital gain or loss and dividends or interest) are compared for various investment strategies. Our objective is achieved by developing, with the aid of new long-leading indexes, a method of forecasting the beginning and end of major bull markets in stock prices. During bear-market periods the choice between short-term bills and long-term bonds is governed by signals from a leading index of inflation. The paper reports the findings for Australia, Japan, the United Kingdom, the United States and West Germany.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90010-S}, issn = {0169-2070}, keywords = {Annual rate of return, Signalled bull- and bear-market periods, Stocks, Short-term bills, Long-term bonds, Capital gain (loss), Investment strategies, Market timing, Long-leading index, Leading inflation index, regart} } @ARTICLE{BM04, author = {Gianna Boero and Emanuela Marrocu}, title = {The performance of SETAR models: a regime conditional evaluation of point, interval and density forecasts}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {305-320}, number = {2}, abstract = {The aim of this paper is to analyse the out-of-sample performance of SETAR models relative to a linear AR and a GARCH model using daily data for the euro effective exchange rate (euro-EER). The evaluation is conducted on point, interval and density forecasts, unconditionally, over the whole forecast period, and conditional on specific regimes. The results show that overall the GARCH model is better able to capture the distributional features of the series and to predict higher-order moments than the SETAR models. However, from the results there is also a clear indication that the performance of the SETAR models improves significantly conditional on being on specific regimes.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.09.011}, issn = {0169-2070}, keywords = {SETAR models, Forecasting accuracy, Point forecasts, MSFEs, Interval forecasts, Density forecasts, Euro effective exchange rate, regart} } @ARTICLE{BSW08, author = {Gianna Boero and Jeremy Smith and Kenneth F. Wallis}, title = {Evaluating a three-dimensional panel of point forecasts: The Bank of England Survey of External Forecasters}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {354-367}, number = {3}, abstract = {This article provides a first analysis of the forecasts of inflation and GDP growth obtained from the Bank of England's Survey of External Forecasters, considering both the survey average forecasts published in the quarterly Inflation Report, and the individual survey responses, recently made available by the Bank. These comprise a conventional incomplete panel dataset, with an additional dimension arising from the collection of forecasts at several horizons; both point forecasts and density forecasts are collected. The inflation forecasts show good performance in tests of unbiasedness and efficiency, albeit over a relatively calm period for the UK economy, and there is considerable individual heterogeneity. For GDP growth, inaccurate real-time data and their subsequent revisions are seen to cause serious difficulties for forecast construction and evaluation, although the forecasts are again unbiased. There is evidence that some forecasters have asymmetric loss functions.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.04.003}, issn = {0169-2070}, keywords = {Forecast surveys, Point forecasts, Density forecasts, Forecast efficiency, Asymmetric loss functions, regart} } @ARTICLE{BOe04, author = {Fergus Bolger and Dilek {\"O}nkal-Atay}, title = {The effects of feedback on judgmental interval predictions}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {29-39}, number = {1}, abstract = {The majority of studies of probability judgment have found that judgments tend to be overconfident and that the degree of overconfidence is greater the more difficult the task. Further, these effects have been resistant to attempts to `debias' via feedback. We propose that under favourable conditions, provision of appropriate feedback should lead to significant improvements in calibration, and the current study aims to demonstrate this effect. To this end, participants first specified ranges within which the true values of time series would fall with a given probability. After receiving feedback, forecasters constructed intervals for new series, changing their probability values if desired. The series varied systematically in terms of their characteristics including amount of noise, presentation scale, and existence of trend. Results show that forecasts were initially overconfident but improved significantly after feedback. Further, this improvement was not simply due to `hedging', i.e. shifting to very high probability estimates and extremely wide intervals; rather, it seems that calibration improvement was chiefly obtained by forecasters learning to evaluate the extent of the noise in the series.}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00009-8}, issn = {0169-2070}, keywords = {Judgmental forecasting, Calibration, Feedback, Overconfidence, Confidence intervals, regart} } @ARTICLE{Bolton02, author = {Gary E. Bolton}, title = {Game theory's role in role-playing}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {353-358}, number = {3}, abstract = {Green (International Journal of Forecasting, 18, 321-344) considers one method of testing the predictive value of game theory for conflict situations, and finds that role-playing does better. I discuss a second method, one that combines game theory and role-playing. This method has already been used with success to solve practical business problems. I argue game theory will have to play a critical part if role-playing is to be reliable for forecasting conflict outcomes. Existing research that combines game theory and experimental economics holds important lessons for the design of role-playing exercises.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00027-4}, issn = {0169-2070}, keywords = {Game theory, Role-playing, regart} } @ARTICLE{Bon86, author = {Ranko Bon}, title = {Comparative stability analysis of demand-side and supply-side input-output models}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {231-235}, number = {2}, abstract = {This paper presents the results of a comparison of technical coefficient stability in demand-side and supply-side input-output models using a seven-sector aggregation of the 1947, 1958, 1963, 1967, 1972, and 1977 U.S. input-output tables. Sectoral and total output forecasts of the two models, generated with known final demand and value added figures from all subsequent tables, are compared to known output figures. Although the demand-side model performs somewhat better in terms of total output forecasts, the supply-side model provides better forecasts for a larger number of sectors. This analysis suggests that both models should be used in order to determine the extent to which an economy or a sector are demand- or supply-driven.}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90112-3}, issn = {0169-2070}, keywords = {Demand-side input-output models, Supply-side input-output models, Comparative stability analysis, Interplay of demand and supply forces, regart} } @ARTICLE{Bondt93, author = {Werner P. M. De Bondt}, title = {Betting on trends: Intuitive forecasts of financial risk and return}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {355-371}, number = {3}, abstract = {Based on nearly 38 000 forecasts of stock prices and exchange rates, it appears that non-experts expect the continuation of apparent past `trends' in prices. Thus, they are optimistic in bull markets and pessimistic in bear markets. Interestingly, the subjects hedge their forecasts, i.e. their subjective probability distributions are skewed in the opposite direction. As a result, perceived risk also depends on prior performance.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90030-Q}, issn = {0169-2070}, keywords = {Investor psychology, Noise traders, Overreaction, Confidence intervals, regart} } @ARTICLE{BGZ09, author = {Carl Bonham and Byron Gangnes and Ting Zhou}, title = {Modeling tourism: A fully identified VECM approach}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {531 - 549}, number = {3}, note = {Special Section: Time Series Monitoring}, doi = {10.1016/j.ijforecast.2008.11.014}, issn = {0169-2070}, keywords = {Cointegration, Vector error correction model,Identification,Tourism demand and supply analysis,Tourism forecasting,Hawaii} } @ARTICLE{Booth06, author = {Heather Booth}, title = {Demographic forecasting: 1980 to 2005 in review}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {547-581}, number = {3}, note = {Twenty five years of forecasting}, abstract = {Approaches and developments in demographic and population forecasting since 1980 are reviewed. Three approaches to forecasting demographic processes are extrapolation, expectation (individual-level birth expectations or population-level opinions of experts), and theory-based structural modelling involving exogenous variables. Models include 0-3 factors (age, period and cohort). Decomposition and disaggregation are also used in multistate models, including macrosimulation and microsimulation. Forecasting demographic change is difficult; accuracy depends on the particular situation or trends, but it is not clear when a method will perform best. Estimates of uncertainty (model-based ex ante error, expert-opinion-based ex ante error, and ex post error) differ; uncertainty estimation is highly uncertain. Probabilistic population forecasts are based on stochastic population renewal or random scenarios. The approaches to population forecasting, demographic process forecasting and error estimation are closely linked. Complementary methods that combine approaches are increasingly employed. The paper summarises developments, assesses progress and considers the future.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.04.001}, issn = {0169-2070}, keywords = {Demographic modelling; Population forecasting; Mortality; Fertility; Migration; Extrapolation; Expectations; Causal models; Disaggregation, revart} } @ARTICLE{BG87, author = {Paul Boothe and Debra Glassman}, title = {Comparing exchange rate forecasting models : Accuracy versus profitability}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {65-79}, number = {1}, abstract = {In this paper we compare the rankings of alternative exchange rate forecasting models using two different evaluation criteria: forecast accuracy and profitability in forward market speculation. Either or both of these criteria may be useful to the practitioner depending on the forecasting application. We use both time-series and static and dynamic structural models to construct forecasts for the Canadian dollar/U.S. dollar and German mark/U.S. dollar exchange rates over the period 1976 :12-1984: 9. Our results confirm earlier findings that simple time-series models such as the random walk rank highest in forecast accuracy. The random walk also ranks high in terms of profitability for the German mark, but for the Canadian dollar the profitability rankings are quite different than the accuracy results. For both currencies we find that some models are very profitable in forward speculation, which is evidence against the speculative efficiency hypothesis but may be consistent with the existence of risk premia in foreign exchange markets.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90079-3}, issn = {0169-2070}, keywords = {Exchange rates, Forecast comparisons, Forecast accuracy, Profitability, regart} } @ARTICLE{Bos04, author = {Charles S Bos}, title = {Time Series Modelling using TSMod 3.24}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {515-522}, number = {3}, abstract = {Time Series Modelling (TSMod) is an interactive program which allows the user to estimate a broad range of univariate models. This review describes the possibilities of the package, from a user's perspective and with a secondary focus on the numerical accuracy of the program.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.12.001}, issn = {0169-2070}, keywords = {Time series; Software; Econometrics, othercom} } @ARTICLE{BFO02, author = {Charles S. Bos and Philip Hans Franses and Marius Ooms}, title = {Inflation, forecast intervals and long memory regression models}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {243-264}, number = {2}, abstract = {We examine recursive out-of-sample forecasting of monthly postwar US core inflation and log price levels. We use the autoregressive fractionally integrated moving average model with explanatory variables (ARFIMAX). Our analysis suggests a significant explanatory power of leading indicators associated with macroeconomic activity and monetary conditions for forecasting horizons up to 2 years. Correcting for the effect of explanatory variables, we still find fractional integration and structural breaks in the mean and variance of inflation in the 1970s and 1980s. We compare the forecasts of ARFIMAX models and ARIMAX models over the period 1984-1999. The ARIMAX(1, 1, 1) model provides the best forecasts, but its multi-step forecast intervals are too large. The multi-step forecast intervals of the ARFIMAX(0, d, 0) model prove to be more realistic.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00156-X}, issn = {0169-2070}, keywords = {Long memory, Inflation, Time series, Recursive estimation, Multi-step forecasting, regart} } @ARTICLE{BJ05, author = {Charles S. Bos and Ana Justel}, title = {On model selection criteria as a starting point for sequential detection of non-linearity}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {749-754}, number = {4}, note = {Nonlinearities, Business Cycles and Forecasting}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.04.007}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{BB92, author = {Eduard Bos and Rodolfo A. Bulatao}, title = {The demographic impact of AIDS in sub-Saharan Africa: Short- and long-term projections}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {367-384}, number = {3}, abstract = {This paper describes the methodology used to incorporate AIDS mortality in recently revised World Bank population projections, and compares resulting demographic indicators with those constructed if AIDS is not incorporated, as in previous editions of the World Bank's projections. The paper first reviews different approaches for projecting AIDS and its demographic consequences. This is followed by a summary of an epidemiological model that simulates the spread of HIV used in this analysis, and a demographic model that translates mortality from AIDS into population outcomes. These models are then used in a set of simulations, from which the effect of current HIV prevalence on projected future mortality is extracted. Finally, the extracted equations linking current HIV prevalence with future mortality indicators are applied to sub-Saharan countries with a measurable level of current HIV prevalence.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90053-C}, issn = {0169-2070}, keywords = {HIV/AIDS modelling, Population projections, Sub-Sahara Africa, regart} } @ARTICLE{Bottomley90, author = {Paul Bottomley}, title = {Effect of price on the demand for durables: Modelling, estimation and findings : D.C. Jain and R.C. Rao, Journals of Business and Economics Statistics 8, no. 2 (1990) 163-170}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {583-584}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90046-E}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Bottomley90a, author = {Paul Bottomley}, title = {A meta-analysis of applications of diffusion models : F. Sultan, J.U. Farley and D.R. Lehmann, Journal of marketing research 27 (1990) 70-77}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {584-585}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90047-F}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{BT90, author = {Jamel Boucelham and Timo Ter{\"a}svirta}, title = {Use of preliminary values in forecasting industrial production}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {463-468}, number = {4}, abstract = {The first preliminary values of the monthly index of Finnish industrial production undergo a major revision once a year. The problem discussed in this paper is how to take this into account when forecasting the index using a transfer function model based on quick indicators. The preliminary values may be interpreted as measurements with error and handled in the state space framework as proposed in the literature. However, if one forecasts beyond the period for which preliminary values are available, this does not lead to any significant improvements in prediction accuracy compared to the case in which the preliminary values are treated as final values without any error. This outcome simplifies the forecasting procedure in this specific example, and has to do with improved quality of the preliminary values of the index over time.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90022-4}, issn = {0169-2070}, keywords = {ARIMA model, Data revisions, Kaiman filter, Time series analysis, Transfer function model, regart} } @ARTICLE{BSC+10, author = {Bryan L. Boulier and H.O. Stekler and Jason Coburn and Timothy Rankins}, title = {Evaluating National Football League draft choices: The passing game}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {589 - 605}, number = {3}, note = {Sports Forecasting}, doi = {10.1016/j.ijforecast.2009.10.009}, issn = {0169-2070}, keywords = {Sports forecasts, Personnel forecasts,National football league,Sports economics} } @ARTICLE{BS03, author = {Bryan L. Boulier and H. O. Stekler}, title = {Predicting the outcomes of National Football League games}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {257-270}, number = {2}, abstract = {Rankings have predictive value for determining the outcomes of basketball games and tennis matches. Rankings, based on power scores, are also available for NFL teams. This paper evaluates power scores as predictors of the outcomes of NFL games for the 1994-2000 seasons. The evaluation involves a comparison of forecasts generated from probit regressions based on power scores published in The New York Times with those of a naive model, the betting market, and the opinions of the sports editor of The New York Times. We conclude that the betting market is the best predictor followed by the probit predictions based on power scores. We analyze the editor's predictions and find that his predictions were comparable to a bootstrapping model of his forecasts but were inferior to those based on power scores and even worse than naive forecasts.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00144-3}, issn = {0169-2070}, keywords = {Sports forecasting, Expert predictions, Bootstrapping, regart} } @ARTICLE{BS99, author = {Bryan L. Boulier and H. O. Stekler}, title = {Are sports seedings good predictors?: an evaluation}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {83-91}, number = {1}, abstract = {Very little attention has been given to predicting outcomes of sporting events. While studies have examined the accuracy of alternative methods of predicting the outcomes of thoroughbred horse races, some obvious predictors of the outcomes of other sporting events have not been examined. In this paper, we evaluate whether rankings (seedings) are good predictors of the actual outcomes in two sports: (1) US collegiate basketball and (2) professional tennis. In this analysis we use statistical probit regressions with the difference in rankings as the predictor of the outcome of games and/or matches. We evaluate both the ex post and ex ante predictions using base rate forecasts and Brier scores. We conclude that the rankings, by themselves, are useful predictors and that the probits improve on this performance.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00067-3}, issn = {0169-2070}, keywords = {Probability forecasts, Probits, Sports forecasts, regart} } @ARTICLE{BKP+08, author = {Marek Brabec and Ondrej Kon{\'a}r and Emil Pelik{\'a}n and Marek Mal{\'y}}, title = {A nonlinear mixed effects model for the prediction of natural gas consumption by individual customers}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {659-678}, number = {4}, abstract = {This study deals with the description and prediction of the daily consumption of natural gas at the level of individual customers. Unlike traditional group averaging approaches, we are faced with the irregularities of individual consumption series posed by inter-individual heterogeneity, including zeros, missing data, and abrupt consumption pattern changes. Our model is of the nonlinear regression type, with individual customer-specific parameters that, nevertheless, have a common distribution corresponding to the nonlinear mixed effects model framework. It is advantageous to build the model conditionally. The first condition, whether a particular customer has consumed or not, is modeled as a consumption status in an individual fashion. The prediction performance of the proposed model is demonstrated using a real dataset of 62 individual customers, and compared with two more traditional approaches: ARIMAX and ARX.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.08.005}, issn = {0169-2070}, keywords = {Individual gas consumption, Nonlinear mixed effects model, ARIMAX, ARX, Generalized linear mixed model, Conditional modeling, regart} } @ARTICLE{BJ04, author = {Michael D. Bradley and Dennis W. Jansen}, title = {Forecasting with a nonlinear dynamic model of stock returns and industrial production}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {321-342}, number = {2}, abstract = {We model stock returns and industrial production as nonlinear and state-dependent, with dynamics depending on the sign and magnitude of past realization of returns and the growth of industrial production. We estimate various nonlinear models including smooth transition autoregressive models and examine their in-sample properties. We also conduct an out-of-sample forecasting exercise and compare the forecasting performance of the various nonlinear models with that of a linear model. For stock returns, we find that the linear model generally does as well or better than any of our nonlinear models, while for growth in industrial production, two of our nonlinear models outperformed the linear model.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.09.007}, issn = {0169-2070}, keywords = {Forecasting, Stock return, Industrial production, regart} } @ARTICLE{Brandon85, author = {Charles Brandon}, title = {Charles Brandon, Richard Fritz and James Xander, Econometric forecasts: Evaluation and revision, Applied Economics 15 (1983), pp. 187-201.}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {310-311}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(85)80053-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Breece92, author = {James H. Breece}, title = {Business forecasting and economic cycles : S.G. Karsten, (University Press of America, Inc., Lanham, 1990) pp. 293 including index, \$41.25}, journal = {International Journal of Forecasting}, year = {1992}, volume = {7}, pages = {533-535}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90038-B}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{BH02, author = {F. Jay Breidt and Nan-Jung Hsu}, title = {A class of nearly long-memory time series models}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {265-281}, number = {2}, abstract = {We consider an autoregressive regime-switching model for the dynamic mean structure of a univariate time series. The model allows for a variety of stationary and nonstationary alternatives, and includes the possibility of approximate long-memory behavior. The proposed model includes as special cases white noise, first-order autoregression, and random walk models as well as regime-switching models and the random level-shift model proposed by Chen and Tiao, Journal of Business and Economic Statistics, 8 (1990) p. 83. We describe properties of the model, focusing on its resemblance to long-memory under a certain asymptotic parameterization. We develop a reversible-jump Markov chain Monte Carlo method for Bayesian inference on unknown model parameters and apply the methodology to the Nile River data.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00157-1}, issn = {0169-2070}, keywords = {Hurst phenomenon, Regime switching, regart} } @ARTICLE{Bretschneider86, author = {Stuart Bretschneider}, title = {Estimating forecast variance with exponential smoothing Some new results}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {349-355}, number = {3}, abstract = {This note compares MAD and MSE smoothing approaches to estimating the forecast variance for the simple exponential smoothing forecast model. Using simulation techniques, the MSE approach is found to be more efficient than the MAD approach. These results hold for a wide assortment of cases in which both the mean and variance of the underlying demand series are potentially non-stationary. The results are found to be robust even in the presence of outliers. Several heuristic rules are developed for selection of a smoothing coefficient for the variance term, the most significant one being based on an inverse relationship between the optimal smoothing coefficient for the mean and the optimal coefficient for the variance.}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90053-1}, issn = {0169-2070}, keywords = {Exponential smoothing - monitoring, Forecast variance, Confidence interval - predictions, time series, Data - simulation, Data errors - outliers, regart} } @ARTICLE{BG92a, author = {Stuart Bretschneider and Wilpen Gorr}, title = {Economic, organizational, and political influences on biases in forecasting state sales tax receipts}, journal = {International Journal of Forecasting}, year = {1992}, volume = {7}, pages = {457-466}, number = {4}, abstract = {This paper investigates factors influencing fixed bias in forecasting state sales taxes revenues. By extending an existing model used to explain forecast accuracy to include a series of complex interactions related to the potential political and policy use of revenue forecasts, the paper extends our understanding of the forecasting process in government. Exploratory empirical analysis based on survey data is used to provide evidence that bias in forecasting results, at least in part, from political and policy manipulation. There is also evidence that institutional reforms associated with `good management' practices affect forecast bias, but in complex ways depending upon the extent to which political competition exists within the state.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90029-9}, issn = {0169-2070}, keywords = {Forecast bias, Political and institutional influences, Economic uncertainty, regart} } @ARTICLE{BS88, author = {Stuart Bretschneider and Larry Schroeder}, title = {Evaluation of commercial economic forecasts for use in local government budgeting}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {33-43}, number = {1}, abstract = {Using a decision-making under uncertainty framework, this paper proposes an approach to evaluating commercial macroeconomic forecasts as used by local governments in forecasting revenues. The approach is applied to a case study of Kansas City. Forecasts of GNP and CPI provided by DRI, Chase and Wharton Econometrics are evaluated along with simple time series extrapolations as inputs to the revenue forecasting process. The results indicate that the variance of forecasts errors is minimized by either extrapolating exogenous variables using time series methods, or relying directly on time series extrapolation methods to forecast revenues.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90008-8}, issn = {0169-2070}, keywords = {Government budgeting, Value of information, Risk analysis, Forecast evaluation, Government revenue forecasting, regart} } @ARTICLE{BG89, author = {Stuart I. Bretschneider and Wilpen L. Gorr}, title = {Special issue on public sector forecasting}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {303-304}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90033-2}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{BG89a, author = {Stuart I. Bretschneider and Wilpen L. Gorr}, title = {Forecasting as a science}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {305-306}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90034-4}, issn = {0169-2070}, key = {tagkey1989305}, keywords = {editorial} } @ARTICLE{BGG+89, author = {Stuart I. Bretschneider and Wilpen L. Gorr and Gloria Grizzle and Earle Klay}, title = {Political and organizational influences on the accuracy of forecasting state government revenues}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {307-319}, number = {3}, abstract = {This paper tests a general theory of the factors influencing the accuracy of state government revenue forecasts. Besides the more familiar hypotheses on forecasting techniques and randomness of dependent variable time series, our theory includes hypotheses on the political environment and organizational procedures used in forecasting. The primary data are from three surveys of state governments and include percentage forecasts errors for total and sales tax revenues. The analysis uses two measures of forecast accuracy, the mean and median absolute percentage errors. These are estimated in a linear model that uses ordinary least squares and least absolute value regressions. The results confirm most parts of the theoretical model, subject to the caveats of field data. Forecast accuracy increases when there are independent forecasts from competing agencies. It increases even more when formal procedures exist to combine competing forecasts. It decreases when outside expert advisors are used and when there is a dominant political party or ideology. Finally, it increases when simple regression models and judgmental methods are used as opposed to univariate time series methods or econometric models.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90035-6}, issn = {0169-2070}, keywords = {Field study, Government forecasting, Revenue forecasting, regart} } @ARTICLE{BCK91, author = {Eileen Bridges and Anne T. Coughlan and Shlomo Kalish}, title = {New technology adoption in an innovative marketplace: Micro- and macro-level decision making models}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {257-270}, number = {3}, abstract = {Innovative markets are those which are undergoing rapid development due to changing customer needs or improving technological capability. Because these markets are so dynamic, new products are introduced frequently, and there is a high degree of uncertainty regarding their potential for success. We review literature relevant to firm decision-making, including such topics as timing the adoption of a technological innovation, determining optimal spending on an innovative technology, and predicting the success of a class of products which are based on a particular innovative technology. We consider these problems both at the micro (individual firm) and macro (aggregate) levels.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90001-C}, issn = {0169-2070}, keywords = {Innovation, Diffusion, Technology, Adoption, regart} } @ARTICLE{BEN93, author = {Eileen Bridges and Katherine B. Ensor and John A. Norton}, title = {Forecasting the number of competing products in high-technology markets}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {399-405}, number = {3}, abstract = {Firm decisions to enter a high-tech product category or to extend an existing product line depend in part on the intensity of competition anticipated in the marketplace at the planned introduction time. We develop and empirically test three models that may be used to forecast the number of products competing in a developing marketplace as a function of time. By helping managers to predict the degree of competition they will face at alternative introduction times, these models may be used, in conjunction with demand growth models, to assess efforts to commercialize new products.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90033-J}, issn = {0169-2070}, keywords = {Marketing, Competition, Technology, regart} } @ARTICLE{BW92, author = {G. Briscoe and R. Wilson}, title = {Forecasting economic activity rates}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {201-217}, number = {2}, abstract = {This paper develops a new set of models for projecting labour market activity rates for the UK economy. The Department of Employment currently publishes annual projections with a 10-15 year time horizon. The present research was aimed at improving the methodology used for these forecasts. The models developed attempt to reflect, as fully as possible, the behavioural relationships which are involved in the decision to actively participate in the workforce. As such, they draw on current theoretical contributions to the literature on labour supply. Additionally, account is taken of recent advances in the economic analysis of time series to obtain forecasting equations, which are derived from a set of co-integrated equilibrium relationships. The newly derived equations are applied to forecast activity rates, for a number of male and female age cohorts, over the period 1990-2000. Continuation of trend or an assumption of no change are used for establishing future values of the key determining variables. The results are compared against existing models which rely heavily on trend and dummy variables. The new models developed here are found to produce projections which, whilst broadly comparable to these generated from the existing equations, nevertheless show some important differences.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90119-T}, issn = {0169-2070}, keywords = {Labour market, Participation, Labour supply, Economic activity rates, Time series modelsregart} } @ARTICLE{BH92, author = {P. J. Brockwell and R. J. Hyndman}, title = {On continuous-time threshold autoregression}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {157-173}, number = {2}, abstract = {The use of non-linear models in time series analysis has expanded rapidly in the last ten years, with the development of several useful classes of discrete-time non-linear models. One family of processes which has been found valuable is the class of self-exciting threshold autoregressive (SETAR) models discussed extensively in the books of Tong (1983, 1990). In this paper we consider problems of modelling and forecasting with continuous-time threshold autoregressive (CTAR) processes. Techniques for analyzing such models have been proposed by Tong and Yeung (1991) and Brockwell, Hyndman and Grunwald (1991). In this paper we define a CTAR(p) process X(t) with boundary width 2[delta]>0 as the first component of a p-dimensional Markov process X(t), defined by a stochastic differential equation. We are primarily concerned with the problems of model-fitting and forecasting when observations are available at times 1, 2, ..., N; however, the techniques considered apply equally well to irregularly spaced observations. For practical computations with CTAR processes we approximate the process X(t) by a linearly interpolated discrete-time Markov process whose transitions occur at times jn/n,j = 1, 2, ..., with n large. This model is used to fit `narrow boundary' CTAR models to both simulated and real data.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90116-Q}, issn = {0169-2070}, keywords = {Non-linear forecasting, Threshold autoregression, State-space representation, Maximum likelihood estimation, Continuous-time autoregression, regart} } @ARTICLE{BGL85, author = {R. Brodie and A. Ghosh and P.S.H. Leeflang}, title = {R. Brodie and C.A. Kluyver, Attraction versus linear and multiplicative market share models: An empirical evaluation, Journal of Marketing Research 21 (1984), pp. 194-201.A. Ghosh, S. Neslin and R. Shoemaker, A comparison of market share models and estimation procedures, Journal of Marketing Research 21 (1984), pp. 202-210.P.S.H. Leeflang and J.L. Reuyl, On the predictive power of market share attraction models and estimation procedures, Journal of Marketing Research 21 (1984), pp. 211-215.}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {311-312}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(85)80054-6}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{BA91, author = {Roderick J. Brodie and J. Scott Armstrong}, title = {The forecasting accuracy of market share models using predicted values of competitive marketing behavior : Karel J. Alsem, Peter S.H. Leeflang and Jan C. Reuyl, International Journal of Research in Marketing 6 (1989) 183-198.}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {117-118}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90041-S}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{BB94, author = {Roderick J. Brodie and Andre Bonfrer}, title = {Conditions when market share models are useful for forecasting: further empirical results}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {277-285}, number = {2}, abstract = {The increased availability of data and access to computers has meant that econometric methods are readily available to model and forecast market share. However, controversy exists over their usefulness. For example R. Brodie and C.A. de Kluyver's (International Journal of Forecasting, 1987, 3, 423-437) review of empirical studies revealed that the predictive accuracy of causal market share models was not consistently better than that of a naive model. In contrast, V. Kumar and T.B. Heath (International Journal of Forecasting, 1990, 6, 163-174) found that causal models consistently outperformed the naive model when using aggregated weekly scanner data which allowed for more observations. This paper reports the results of a replication and extension study which confirms Kumar and Heath's findings. However, the increased accuracy from using the causal model is diminished considerably when the more realistic situation of forecasting competitive action is included. The paper concludes by outlining a research agenda aimed at further clarifying the conditions when market share models are useful for forecasting.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90007-8}, issn = {0169-2070}, keywords = {Empirical study, Forecasting accuracy, Market share models, Naive models, regart} } @ARTICLE{BCK87, author = {Roderick J. Brodie and A. Cornelis and de Kluyver}, title = {Reply to the commentary}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {461-462}, number = {3-4}, abstract = {Our conclusion that econometric market share models may not be consistently more accurate than naive models was not surprising to the commentators. The comments they made help clarify the research that is needed to identify when econometric market share models are likely to be useful for forecasting.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90042-2}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{BK87, author = {Roderick J. Brodie and Cornelis A. De Kluyver}, title = {A comparison of the short term forecasting accuracy of econometric and naive extrapolation models of market share}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {423-437}, number = {3-4}, abstract = {Empirical evaluation of econometric market share models has shown that they are useful as descriptive tools. This use of the models has led to a number of generalizations about the effectiveness and relative importance of advertising, price, and other elements of the marketing mix. However, little is known about whether these models are useful for prediction. This paper examines the published empirical evidence about the predictive performance of econometric market share models and uses data for fifteen brands from three markets to examine the predictive ability of the models in more detail. Three conclusions are reached: (1) Econometric market share models were not consistently more accurate than simple extrapolation (time series) methods for short-term forecasting. (2) Market share models did not usually capture enough of the important features of the market to be used by themselves as `stand alone' forecasting instruments. (3) Apart from differences between markets there did not appear to be circumstances which indicated where econometric market share models are likely to be more accurate at short-term forecasting. Surprisingly the face validity of the estimated models did not appear to be a good indicator of forecasting accuracy. The final section of the paper poses a number of research questions which need to be resolved before any final judgment can be made about the usefulness of econometric models for prediction.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90035-5}, issn = {0169-2070}, keywords = {Forecasting sales, Forecasting market share, Market share models, Evaluating forecasts, Causal methods versus naive extrapolation (time series), Accuracy, Empirical studyregart} } @ARTICLE{BN94, author = {Noel Brodsky and Paul Newbold}, title = {Late forecasts and early revisions of United States GNP}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {455-460}, number = {3}, abstract = {We consider a sequence of four-monthly predictions and estimates of quarterly U.S. real gross national product. The late forecasts are released in the final month of a quarter, and an initial estimate and two subsequent revisions are published in the following three months. The question of efficiency is analyzed through considering the earlier figures as forecasts of this last number. The strongest indication of inefficiency appears in a nonlinear relationship between the third published number and each of the two previously reported estimates.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90074-4}, issn = {0169-2070}, keywords = {Conditional efficiency, Data revisions, Nonlinearity, regart} } @ARTICLE{BBP01, author = {Chris Brooks and Simon P. Burke and Gita Persand}, title = {Benchmarks and the accuracy of GARCH model estimation}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {45-56}, number = {1}, abstract = {This paper reviews nine software packages with particular reference to their GARCH model estimation accuracy when judged against a respected benchmark. We consider the numerical consistency of GARCH and EGARCH estimation and forecasting. Our results have a number of implications for published research and future software development. Finally, we argue that the establishment of benchmarks for other standard non-linear models is long overdue.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00070-4}, issn = {0169-2070}, keywords = {GARCH; EGARCH; Benchmarks; Accuracy, prodrev} } @ARTICLE{BP01, author = {Chris Brooks and Gita Persand}, title = {The trading profitability of forecasts of the gilt-equity yield ratio}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {11-29}, number = {1}, abstract = {Research has highlighted the usefulness of the Gilt-Equity Yield Ratio (GEYR) as a predictor of UK stock returns. This paper extends recent studies by endogenising the threshold at which the GEYR switches from being low to being high or vice versa, thus improving the arbitrary nature of the determination of the threshold employed in the extant literature. It is observed that a decision rule for investing in equities or bonds, based on the forecasts from a regime switching model, yields higher average returns with lower variability than a static portfolio containing any combinations of equities and bonds. A closer inspection of the results reveals that the model has power to forecast when investors should steer clear of equities, although the trading profits generated are insufficient to outweigh the associated transaction costs.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00060-1}, issn = {0169-2070}, keywords = {GEYR, Markov switching, Regime model, Forecasting, Equity and bond returns, Trading rule, regart} } @ARTICLE{BRR01, author = {Chris Brooks and Alistair G. Rew and Stuart Ritson}, title = {A trading strategy based on the lead-lag relationship between the spot index and futures contract for the FTSE 100}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {31-44}, number = {1}, abstract = {This paper examines the lead-lag relationship between the FTSE 100 index and index futures price employing a number of time series models. Using 10-min observations from June 1996-1997, it is found that lagged changes in the futures price can help to predict changes in the spot price. The best forecasting model is of the error correction type, allowing for the theoretical difference between spot and futures prices according to the cost of carry relationship. This predictive ability is in turn utilised to derive a trading strategy which is tested under real-world conditions to search for systematic profitable trading opportunities. It is revealed that although the model forecasts produce significantly higher returns than a passive benchmark, the model was unable to outperform the benchmark after allowing for transaction costs.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00062-5}, issn = {0169-2070}, keywords = {Stock index futures, FTSE 100, Error correction model, Trading rules, Forecasting accuracy, Cost of carry model, regart} } @ARTICLE{BC99, author = {Lloyd B. Brown and Henry W. Chappell}, title = {Forecasting presidential elections using history and polls}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {127-135}, number = {2}, abstract = {We develop a method for efficiently using current poll data to update election forecasts based on historical relationships. The method is applied on an ex post basis to forecast Republican and Democratic shares of the national vote in U.S. Presidential elections from 1952 to 1992. Using poll data substantially improves the performance of forecasting models that rely solely on historical fundamentals. Moreover, when poll data are used appropriately, their information content dominates in the calculation of an optimal forecast. The method has also been applied on an ex ante basis to forecast the 1996 presidential election, producing a series of highly accurate predictions over the 2 month period before the election.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00059-4}, issn = {0169-2070}, keywords = {Election forecasting, Polls, Presidential elections, regart} } @ARTICLE{Brown03, author = {Lawrence D. Brown}, title = {Small negative surprises: frequency and consequence}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {149-159}, number = {1}, abstract = {Using a large sample of quarterly observations for the 16 years, 1984-99, I present four types of related temporal evidence: (1) a decrease in the tendency of managers to report quarterly earnings that fall slightly short of analyst estimates [small negative surprises of no more than three cents]; (2) the temporal decrease in the tendency of managers to report small negative surprises pertains more to growth than to value firms; (3) the adverse valuation consequence of reporting small negative surprises has increased in severity in recent years; and (4) the temporal increase in the adverse valuation consequence of reporting small negative surprises pertains more to growth than to value firms. My frequency results are robust to alternative definitions of small negative surprises, and my valuation results are robust to including median surprises as a potential correlated omitted variable and are not due to temporal changes in the frequency of losses.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00061-4}, issn = {0169-2070}, keywords = {Temporal trend, Earnings, Analysts, Small negative surprises, Frequency, Valuation consequences, Growth versus value, regart} } @ARTICLE{Brown96, author = {Lawrence D. Brown}, title = {Forecasting profit : M. Metcalf, 1995, (Kluwer Academic Publishers, Boston), US\$110, ISBN 0-7923-9482-8.}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {176-177}, number = {1}, note = {Probability Judgmental Forecasting}, doi = {http://dx.doi.org/10.1016/0169-2070(96)88192-1}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Brown93, author = {Lawrence D. Brown}, title = {Earnings forecasting research: its implications for capital markets research}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {295-320}, number = {3}, abstract = {Since the early 1980s, earnings forecasting research has become much more closely aligned with capital markets research. Capital markets research requires a proxy for the (unobservable) market earnings expectation and earnings forecasting research has provided such proxy measures. Questions considered in this paper include: (1) if annual earnings follow a random walk or an IMA (1,1) model, does this mean that earnings changes cannot be predicted? (2) Do stock prices act as if quarterly earnings follow a seasonal random walk with drift process? (3) Is the predictive model which is best on the forecast accuracy dimension also best on the market association dimension? (4) How do analysts formulate their earnings expectations? (5) What is the role of earnings forecasting in `earnings response coefficient' and `post-earnings announcement drift' studies? (6) What is the likely role of earnings forecasting research in future capital market studies?}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90023-G}, issn = {0169-2070}, keywords = {Earnings forecasting, Forecast accuracy, Market association, Post-earnings announcement drift, Future research, regart} } @ARTICLE{Brown93a, author = {Lawrence D. Brown}, title = {Reply to commentaries on Earnings forecasting research: its implications for capital markets research}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {343-344}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90028-L}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Brown91, author = {Lawrence D. Brown}, title = {Forecast selection when all forecasts are not equally recent}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {349-356}, number = {3}, abstract = {Little is known about which forecasts to select when all forecasts are not equally recent. This paper uses security analysts' annual earnings forecasts to examine this issue. The comparative predictive accuracy of the mean and three timely composites is examined, where the three timely composites are the most recent forecast, the average of the three most recent forecasts, and the 30-day average. The mean is shown to be less accurate than all three timely composites, and the 30-day average is shown to be the most accurate timely composite. The findings suggest that tradeoffs exist between recency and aggregation, and that these tradeoffs are related to firm size.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90009-K}, issn = {0169-2070}, keywords = {Recency, Aggregation, Timely composites, Earnings forecasts, regart} } @ARTICLE{Brown88, author = {Lawrence D. Brown}, title = {Comparing judgmental to extrapolative forecasts: It's time to ask why and when}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {171-173}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90074-X}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Brown85, author = {Lawrence D. Brown}, title = {Robert E. Jensen, Review of Forecasts: Scaling \& Analysis of Expert Judgements Regarding Cross-Impacts of Assumptions on Business Forecasts \& Accounting Measures, American Accounting Association, Amsterdam (1983), p. 235. \$15.00}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {320-321}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(85)80063-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{98f, author = {L. D. Brown and Guerard, Jr., J. B.}, title = {Editorial}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {157-160}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00023-5}, issn = {0169-2070}, key = {tagkey1998157}, keywords = {editorial} } @ARTICLE{Brown93b, author = {Philip Brown}, title = {Comments on `Earnings forecasting research: its implications for capital markets research' by L. Brown}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {331-335}, number = {3}, abstract = {Research on the linkage between earnings forecasts and stock market behaviour dates from the 1960s. Larry Brown's latest survey focuses on more recent work and shows that, despite the intense activity over the last decade, much remains to be done. His suggestions, if pursued, are sure to keep research on earnings forecasts very much alive for at least the next 10 years.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90026-J}, issn = {0169-2070}, keywords = {Earnings forecasts; Returns-earnings relation; Security analysts, othercom} } @ARTICLE{Brown08, author = {Stephen J. Brown}, title = {Elusive return predictability: Discussion}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {19-21}, number = {1}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.08.003}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Browne00, author = {Glenn J. Browne}, title = {Griffin, D., Buehler, R. (1999). Frequency, Probability, and Prediction: Easy Solutions to Cognitive Illusions? Cognitive Psychology, 38, 48-78.}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {140-142}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00037-0}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Braennaes95, author = {Kurt Br{\"a}nn{\"a}s}, title = {Prediction and control for a time-series count data model}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {263-270}, number = {2}, abstract = {Time series of count data are becoming more widely available. In a recently suggested class of models, the serial correlation between counts can conveniently be accounted for. In this paper, an easily calculated linear predictor is introduced. Control solutions for average count and for probabilities of specified events are given. An illustration based on a road accident frequency model for a Swedish county is included.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)00569-X}, issn = {0169-2070}, keywords = {Count data, Serial correlation, Overdispersion, Prediction, Control, Road accidents, regart} } @ARTICLE{BHN02, author = {Kurt Br{\"a}nn{\"a}s and J{\"o}rgen Hellstr{\"o}m and Jonas Nordstr{\"o}m}, title = {A new approach to modelling and forecasting monthly guest nights in hotels}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {19-30}, number = {1}, abstract = {Starting from a day-to-day model on hotel specific guest nights we obtain an integer-valued moving average model by cross-sectional and temporal aggregation. The two parameters of the aggregate model reflect mean check-in and the check-out probability. Letting the parameters be functions of dummy and economic variables we demonstrate the potential of the approach in terms of interesting interpretations. Empirical results are presented for a series of Norwegian guests in Swedish hotels. The results indicate strong seasonal patterns in both mean check-in and in the check-out probability. Models based on differenced series are preferred in terms of goodness-of-fit. In a forecast comparison the improvements due to economic variables are small.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00104-2}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{BM08, author = {Ruijun Bu and Brendan McCabe}, title = {Model selection, estimation and forecasting in INAR(p) models: A likelihood-based Markov Chain approach}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {151-162}, number = {1}, abstract = {This paper considers model selection, estimation and forecasting for a class of integer autoregressive models suitable for use when analysing time series count data. Any number of lags may be entertained, and estimation may be performed by likelihood methods. Model selection is enhanced by the use of new residual processes that are defined for each of the p + 1 unobserved components of the model. Forecasts are produced by treating the model as a Markov Chain, and estimation error is accounted for by providing confidence intervals for the probabilities of each member of the support of the count data variable. Confidence intervals are also available for more complicated event forecasts such as functions of the cumulative distribution function, e.g., for probabilities that the future count will exceed a given threshold. A data set of Australian counts on medical injuries is analysed in detail.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.11.002}, issn = {0169-2070}, keywords = {Time Series of Counts, INAR(p) models, Maximum Likelihood Estimation, Markov Chain, Transition Probability, Transition Matrix, Delta Method, regart} } @ARTICLE{Bucken-Knapp00, author = {Gregg Bucken-Knapp}, title = {Trouble in Paradise? Europe in the 21st Century: Steven Philip Kramer and Irene Kyriakopoulos (Washington, DC: National Defense University Press, 1996)}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {289-291}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00041-8}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Bunn85, author = {Derek W. Bunn}, title = {Statistical efficiency in the linear combination of forecasts}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {151-163}, number = {2}, abstract = {In seeking an efficient combination of forecasts which minimises the forecast error variance, many methods have been suggested. Through analysis, simulation and case studies, this paper seeks to develop insights into the statistical circumstances which influence the relative accuracy of six of these methods. The six methods chosen have all been advocated in various publications and consist of `equal weighting' (i.e., pooled average), `optimal' (i.e., error variance minimising), `optimal with independence assumption' (i.e., error variance minimising assuming zero correlation between individual forecast errors) and three variations on the formulation of a Bayesian combination based upon posterior probabilities. The statistical circumstances reflected varying conditions of relative forecast errors, error correlations and outliers.}, doi = {http://dx.doi.org/10.1016/0169-2070(85)90020-2}, issn = {0169-2070}, keywords = {Combining forecasts, Methodology, Combining forecasts, Time series, Dependence of forecasts, Bayesian methods, Combining, Robustness, Data, Small samples, Data errors, Outliers, Data, Simulation, regart} } @ARTICLE{BS96, author = {Derek W. Bunn and Ahti A. Salo}, title = {Adjustment of forecasts with model consistent expectations}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {163-170}, number = {1}, abstract = {This paper provides a practical procedure to support the judgemental adjustment of statistical forecasts, for the class of problems where judgement is necessary to compensate for omitted variables in the model. The analysis suggests that many casual adjustments in practice may be prone to a double-counting bias, and that the use of model-consistent expectations, for the omitted variables, should provide a basis for judgemental adjustments free of such bias. The procedure is applied to a real case study, from the petroleum industry, based upon capital cost forecasting for major offshore facilities.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00660-5}, issn = {0169-2070}, keywords = {Forecasting, Judgement, Adjustment, Bias, Expectations, Capital costs, Inflation, regart} } @ARTICLE{BT01, author = {Derek W. Bunn and James W. Taylor}, title = {Setting accuracy targets for short-term judgemental sales forecasting}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {159-169}, number = {2}, abstract = {Traditionally, the quality of a forecasting model is judged by how it compares, in terms of accuracy, to alternative models. However, by providing a relative measure, no indication is given as to how much scope there might be for improvements beyond the benchmark model. When judgemental methods are used alongside simple forecasting models, the scope for such improvements is considerable and difficult to benchmark. Derivation of targets for forecasting quality is thus not straightforward. The approach taken in this paper is to consider forecast error as consisting of irreducible error due to intrinsic unpredictable uncertainty, and error due to less than perfect modelling, estimation and forecasting. As the intrinsic uncertainty presents a bound on forecast accuracy, our derivation of an accuracy target is based on the measurement of this irreducible uncertainty. The motivation and data for this case-study was taken from the short-term sales forecasting process of a major, international high-technology manufacturer.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00090-X}, issn = {0169-2070}, keywords = {Accuracy targets, Judgemental forecasting, regart} } @ARTICLE{BV99, author = {Derek W. Bunn and Angelos I. Vassilopoulos}, title = {Comparison of seasonal estimation methods in multi-item short-term forecasting}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {431-443}, number = {4}, abstract = {This paper addresses the issue of estimating seasonal indices for multi-item, short-term forecasting, based upon both individual time series estimates and groups of similar time series. This development of the joint use of individual and group seasonal estimation is extended in two directions. One class of methods is derived from the procedures developed for combining forecasts. The second employs the general class of Stein Rules to obtain shrinkage estimates of seasonal components. A comparative evaluation has been undertaken of several versions of these methods, based upon a sample of retail sales data. The results favour these newly developed methods and provide some interesting insights for practical implementation.}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00005-9}, issn = {0169-2070}, keywords = {Combining, Forecasting, Product lines, Seasonality, regart} } @ARTICLE{BV93, author = {Derek W. Bunn and A. I. Vassilopoulos}, title = {Using group seasonal indices in multi-item short-term forecasting}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {517-526}, number = {4}, abstract = {Methods for dealing with seasonal patterns of product sales can be categorized into two groups: those that forecast the demand for seasonal products by estimating the individual seasonal components for each product, and those that estimate the seasonal component by combining `similar' products into a product line. An approach is proposed for the latter case, based on a synthesis of time series decomposition techniques and cluster analysis. Some initial experiments on a sample of retail sales data demonstrate its feasibility and give some comparative insights into this and alternative methods.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90078-2}, issn = {0169-2070}, keywords = {Forecasting, Seasonality, Multivariate, Product lines, Retailing, regart} } @ARTICLE{Buongiorno96, author = {Joseph Buongiorno}, title = {Forest sector modeling: a synthesis of econometrics, mathematical programming, and system dynamics methods}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {329-343}, number = {3}, abstract = {Quantitative analysis and forecasting of forest product markets began in the 1950s, based almost exclusively on pure time-series analysis. Since then, considerable improvements have been made in the theoretical basis of the models, the statistical methods of estimation, and the coverage of the data. Especially noteworthy is the exploitation of panel data in the analysis of demand for final products. To model the industry supply of intermediate and final products, however, activity analysis seems more promising than econometrics. It allows for a detailed description of the techniques of production, and, therefore, a better modeling of technical change than the econometric approach. This paper presents a class of models, currently used for policy analysis and forecasting, that present a blend of econometric and mathematical programming, with a dash of system dynamics. Econometrically estimated demand and supply functions are combined with activity analysis of production and transportation, into optimizers to calculate spatial equilibria in multi-product markets. The shadow prices of the optimization are then the key inputs in predicting capacity change by region and process, in system dynamics fashion, and based on Tobin's q theory of investments.}, doi = {http://dx.doi.org/10.1016/0169-2070(96)00668-1}, issn = {0169-2070}, keywords = {Industry forecasting, Forest industry, Econometrics, Demand equations -- system of, Price forecasting, System dynamics, Input-output, Comparative methods, evaluation, Long-term forecasting, Mathematical programming, Modeling, Natural resources, Technological change - effect of, regart} } @ARTICLE{Butler97, author = {Nick Butler}, title = {World index of economic forecasts : edited by Rob Fildes, Gower Publishing Ltd, 672 pp., �125.00, ISBN 0566 074885}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {295-296}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00729-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Byers91, author = {David Byers}, title = {Econometric modelling of agricultural commodity markets : David Hallam, (Routledge, London, UK, 1990), �35.00, ISBN 0-415-00405-5.}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {248-249}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90064-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{CKY+96, author = {Jeffrey L. Callen and Clarence C. Y. Kwan and Patrick C. Y. Yip and Yufei Yuan}, title = {Neural network forecasting of quarterly accounting earnings}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {475-482}, number = {4}, abstract = {This study uses an artificial neural network model to forecast quarterly accounting earnings for a sample of 296 corporations trading on the New York stock exchange. The resulting forecast errors are shown to be significantly larger (smaller) than those generated by the parsimonious Brown-Rozeff and Griffin-Watts (Foster) linear time series models, bringing into question the potential usefulness of neural network models in forecasting quarterly accounting earnings. This study confirms the conjecture by Chatfield and Hill et al. that neural network models are context sensitive. In particular, this study shows that neural network models are not necessarily superior to linear time series models even when the data are financial, seasonal and non-linear.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00706-6}, issn = {0169-2070}, keywords = {Artificial neural networks, Quarterly earnings, Comparative forecast performance, regart} } @ARTICLE{CP90, author = {Giorgio Calzolari and Lorenzo Panattoni}, title = {Mode predictors in nonlinear systems with identities}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {317-326}, number = {3}, abstract = {For a nonlinear system of simultaneous equations, the mode of the joint distribution of the endogenous variables in the forecast period is proposed as an alternative to the more usual deterministic or mean predictors. A first method follows from maximizing the joint density of a subset of the endogenous variables, corresponding to stochastic equations only (analogously to FIML estimation, where identities are first substituted into stochastic equations). Then a more general approach is developed, which maintains the identities. The model with identities is viewed as a mapping between the space of the random errors and a hypersurface in the space of the endogenous variables; the probability density is defined, and maximization is performed on such a hypersurface. Experimental results on these two mode predictors (and comparisons with deterministic and mean predictors) are provided for a macro model of the Italian economy.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90059-K}, issn = {0169-2070}, keywords = {Nonlinear econometric models, Simultaneous equations, Deterministic predictor, Mean predictor, Joint density function, regart} } @ARTICLE{Campbell08, author = {James E. Campbell}, title = {Evaluating U.S. presidential election forecasts and forecasting equations}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {259-271}, number = {2}, abstract = {This article examines four problems with past evaluations of presidential election forecasting and suggests one aspect of the models that could be improved. Past criticism has had problems with establishing an overall appraisal of the forecasting equations, in assessing the accuracy of both the forecasting models and their forecasts of individual election results, in identifying the theoretical foundations of forecasts, and in distinguishing between data-mining and learning in model revisions. I contend that overall assessments are innately arbitrary, that benchmarks can be established for reasonable evaluations of forecast accuracy, that blanket assessments of forecasts are unwarranted, that there are strong (but necessarily limited) theoretical foundations for the models, and that models should be revised in the light of experience, while remaining careful to avoid data-mining. The article also examines the question of whether current forecasting models grounded in retrospective voting theory should be revised to take into account the partial-referendum nature of non-incumbent, open-seat elections such as the 2008 election.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.03.001}, issn = {0169-2070}, keywords = {Evaluating forecasts, Data mining, Econometric models, Forecasting criticism, Voting, Presidential incumbency, Open-seat elections, regart} } @ARTICLE{CL08, author = {James E. Campbell and Michael S. Lewis-Beck}, title = {US presidential election forecasting: An introduction}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {189-192}, number = {2}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.02.003}, issn = {0169-2070}, keywords = {Approval ratings, Elections, Forecast accuracy, Forecasting, Preference polls, Presidents, Retrospective voting} } @ARTICLE{CCI97, author = {Roberto Camus and Giulio E. Cantarella and Domenico Inaudi}, title = {Real-time estimation and prediction of origin--destination matrices per time slice}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {13-19}, number = {1}, abstract = {As part of the DRIVE-II project DYNA (Dynamic Network Assignment), an approach for the real-time estimation and prediction of origin--destination (OD) matrices per time slice has been developed. This method is useful to support real-time traffic management of a freeway network. The proposed indirect approach combines historical information with traffic counts at on-ramps. It has been tested on the Italian freeway A4, where the existing pay toll system enables us to measure the real origin-destination matrices. The results show that these prediction procedures can perform almost as well as direct prediction methods based on knowledge of the demand.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00696-6}, issn = {0169-2070}, keywords = {Freeway traffic, Traffic-flow prediction, Origin-destination matrices estimation, regart} } @ARTICLE{CEG08, author = {Jos{\'e} Ram{\'o}n Cancelo and Antoni Espasa and Rosmarie Grafe}, title = {Forecasting the electricity load from one day to one week ahead for the Spanish system operator}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {588-602}, number = {4}, abstract = {This paper discusses the building process and models used by Red El{\'e}ctrica de Espa{\~n}a (REE), the Spanish system operator, in short-term electricity load forecasting. REE's forecasting system consists of one daily model and 24 hourly models with a common structure. There are two types of forecasts of special interest to REE, several days ahead predictions for daily data, and one day ahead hourly forecasts. Accordingly, the forecast accuracy is assessed in terms of their errors. To do this, we analyse historical, real time forecasting errors for daily and hourly data for the year 2006, and report the forecasting performance by day of the week, time of the year and type of day. Other aspects of the prediction problem, like the influence of the errors in predicting the temperature on forecasting the load several days ahead, or the need for an adequate treatment of special days, are also investigated.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.07.005}, issn = {0169-2070}, keywords = {Energy forecasting, Hourly and daily models, Time series, Forecasting practice, regart} } @ARTICLE{CS99, author = {Liangyue Cao and Abdol S. Soofi}, title = {Nonlinear deterministic forecasting of daily dollar exchange rates}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {421-430}, number = {4}, abstract = {We perform out-of-sample predictions on several dollar exchange rate returns by using time-delay embedding techniques and a local linear predictor. We compared our predictions with those by a mean value predictor. Some of our predictions of the exchange rate returns outperform the predictions of the same series by the mean value predictor. However, these improvements were not statistically significant. Another interesting result in this paper which was obtained by using a recently developed technique of nonlinear dynamics is that all exchange rate return series we tested have a very high embedding dimension. Additionally, evidence indicates that these series are likely generated by high dimensional systems with measurement noise or by high dimensional nonlinear stochastic systems, that is, nonlinear deterministic systems with dynamic noise.}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00024-2}, issn = {0169-2070}, keywords = {Exchange rates, Time series, Embedding dimension, Nonlinear forecasting, regart} } @ARTICLE{CH85, author = {Noel Capon and James M. Hulbert}, title = {The integration of forecasting and strategic planning}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {123-133}, number = {2}, abstract = {The paper analyzes the use of information in companies planning strategically versus those which are not. This contrast is used to build the case for developing strategic forecasting capability which focuses on a variety of environments, is proactive and interactive, and creates a need for different kinds of data bases and forecasting techniques.}, doi = {http://dx.doi.org/10.1016/0169-2070(85)90017-2}, issn = {0169-2070}, keywords = {Strategic planning, Forecasting, Environment, Performance, Strategic forecasting system, regart} } @ARTICLE{CP94, author = {Noel Capon and Peter Palij}, title = {Strategic marketing forecasting, market segment selection and firm performance}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {339-352}, number = {2}, abstract = {In this study we investigate several hypotheses relating strategic forecasting to market segment selection and firm performance. In the context of a strategic marketing simulation, subjects in 14 competitive industries made strategic forecasts for market segment size and benchmark prices. Our results show that firms differentially select those segments with attractive characteristics; that some strategic forecasts for these targeted segments are more accurate than for non-targeted segments; that strategic forecasts are more accurate the higher the level of competition; and that superior forecasting performance is positively associated with superior firm performance. Implications and limitations of the study are discussed.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90012-4}, issn = {0169-2070}, keywords = {Strategic marketing forecasting, Market forecasting, Market segment selection, MARKSTRAT, regart} } @ARTICLE{Cappelen93, author = {A. Cappelen}, title = {Konjunkturprognoser och konjunkturpolitikk--Ekonomiska r{\aa}dets {\aa}rsbok 1992 (Business cycle forecasting and stabilization policies--Economic council yearbook 1992 : (Allmanna Forlaget, Stockholm, 1993), pp. 116, ISBN 91-3812586-X, ISSN 1100-3413.}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {578-579}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90082-X}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{CJB+03, author = {Thomas A. Carnes and Jefferson P. Jones and Timothy B. Biggart and Katherine J. Barker}, title = {Just-in-time inventory systems innovation and the predictability of earnings}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {743-749}, number = {4}, abstract = {Firms that adopt just-in-time (JIT) inventory practices do so in order to realize cost savings and improve product quality, but an unexpected benefit to such firms could be a more predictable earnings stream. We examine the relationship between implementation of just-in-time inventory practices and the predictability of future quarterly earnings for a matched-pair sample of 82 firms, half of which have publicly announced that they have adopted JIT inventory practices. We find that one- and four-step-ahead forecasts of quarterly earnings, using either a Brown-Rozeff [Journal of Accounting Research (1979) 179-189] ARIMA or a seasonal random walk expectation model, are more accurate for the firms that have adopted JIT.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00079-1}, issn = {0169-2070}, keywords = {Just-in-time, Inventory utilization, Quarterly earnings forecasts, regart} } @ARTICLE{CH94, author = {Gregory S. Carpenter and Dominique M. Hanssens}, title = {Market expansion, cannibalization, and international airline pricing strategy}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {313-326}, number = {2}, abstract = {We analyze market response and pricing of air travel on the Paris-Abidjan, Ivory Coast route operated by a French airline, Union des Transports Aeriens (UTA). We measure the impact of price on the overall size of the market, and examine the nature, pattern, and extent of cannibalization using a set of econometric models for overall passenger volume and for each fare class share. Our analysis shows that (1) only one class of fares expands the market; (2) cannibalization is very significant and highly asymmetric; (3) even small deviations from optimal prices substantially reduce profit. Based on these estimated models, we forecast demand for air travel and calculate optimal fares. We discuss how these models and results were used by UTA and the impact they had on pricing strategy.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90010-8}, issn = {0169-2070}, keywords = {Pricing, Market response, Air travel, Optimization, regart} } @ARTICLE{CM90, author = {Jose Juan Carreno and Jesus Madinaveitia}, title = {A modification of time series forecasting methods for handling announced price increases}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {479-484}, number = {4}, abstract = {This paper deals with a modification of exponential smoothing forecasting methods to allow for announced price increases. Such price increases occur frequently and at irregular intervals of time. We suggest a procedure that consists basically of an adjustment to sales plus exponential smoothing, moving indices to normalize the original sales data, and modification of the forecast. Numerical results are reported for several time series. The approach is particulary useful for forecasting in an economy with a high inflation rate.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90024-6}, issn = {0169-2070}, keywords = {Effect of price increases, Forecasting, Time series, regart} } @ARTICLE{CKM09, author = {A. Carriero and G. Kapetanios and M. Marcellino}, title = {Forecasting exchange rates with a large Bayesian VAR}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {400-417}, number = {2}, abstract = {Models based on economic theory have serious problems forecasting exchange rates better than simple univariate driftless random walk models, especially at short horizons. Multivariate time series models suffer from the same problem. In this paper, we propose to forecast exchange rates with a large Bayesian VAR (BVAR), using a panel of 33 exchange rates vis-a-vis the US Dollar. Since exchange rates tend to co-move, a large set of them can contain useful information for forecasting. In addition, we adopt a driftless random walk prior, so that cross-dynamics matter for forecasting only if there is strong evidence of them in the data. We produce forecasts for all 33 exchange rates in the panel, and show that our model produces systematically better forecasts than a random walk for most of the countries, and at all forecast horizons, including 1-step-ahead.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2009.01.007}, issn = {0169-2070}, keywords = {Exchange rates, Forecasting, Bayesian VAR, regart} } @ARTICLE{CM07, author = {Andrea Carriero and Massimiliano Marcellino}, title = {A comparison of methods for the construction of composite coincident and leading indexes for the UK}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {219-236}, number = {2}, abstract = {In this paper, we provide an overview of recent developments in the methodology for the construction of composite coincident and leading indexes, and apply them to the UK. In particular, we evaluate the relative merits of factor based models and Markov switching specifications for the construction of coincident and leading indexes. For the leading indexes, we also evaluate the performance of probit models and pooling. The results indicate that alternative methods produce similar coincident indexes, while there are more marked differences in the leading indexes.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.01.005}, issn = {0169-2070}, keywords = {Forecasting, Business cycles, Leading indicators, Coincident indicators, Turning points, regart} } @ARTICLE{Carter98, author = {Lawrence R. Carter}, title = {Combining probabilistic and subjective assessments of error to provide realistic appraisals of demographic forecast uncertainty: Alho's approach}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {523-526}, number = {4}, abstract = {With increasing interest in forecast uncertainty, there is an evolving concern with assessing the degree of certainty we can attach to uncertainty itself. This concern is the subject of recent work by Juha Alho. This paper reviews his approach to tackling this problem. Alho focuses on conditional forecasts - conditional on the possible future policies feeding into the forecasts. This approach combines simple statistical methods with expert judgement to generate an overall predictive distribution for the future world population from 1994 to 2030. I examine the approach systematically and draw general conclusions about its efficacy. Suggestions for improvement are made.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00057-0}, issn = {0169-2070}, keywords = {Demographic forecast uncertainty, Alho's approach, Probabilistic and subjective, regart} } @ARTICLE{CL92, author = {Lawrence R. Carter and Ronald D. Lee}, title = {Modeling and forecasting US sex differentials in mortality}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {393-411}, number = {3}, abstract = {This paper examines forecasted differentials in age-sex-specific mortality in the United States, 1990-2065. A non-linear model,mx,t = exp(ax+bxkt+ex,t), is fitted for each sex age-specific US death rates, 1933-1988, using SVD to derive a single time-varying index of mortality,kt. Box-Jenkins techniques are used to estimate and forecastkt. These forecasts are used to generate age-specific mortality rates and life expectancies to 2065. Independent forecasts of male and femalee0's are 82.0 and 90.4, respectively, for 2065, a difference of 8.4 years. These forecasts are substantially higher with narrower confidence intervals than those prepared regularly by the Actuary of the Social Security Administration [Wade (1989)]. Thesekt, generated forecasts ofe0 appear more plausible than direct forecasts ofe0 Life expectancies derived from jointly estimated and forecastedkt are competitive with the independent sex forecasts, but have some problems. Joint forecasts ofkt are juxtaposed to co-integration speculatively as a direction for future research into linkages between male and female mortality.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90055-E}, issn = {0169-2070}, keywords = {Age-sex-specific mortality, Life-table functions, Non-linear Demographic Model, Forecasting, Forecast accuracy, Co-integration, regart} } @ARTICLE{86a, author = {Phillip A. Cartwright}, title = {Time series analysis: Theory and practice 4: O.D. Anderson, ed., (North-Holland, Amsterdam, 1983) Dfl. 170.00, pp. × + 352}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {249-250}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90123-8}, issn = {0169-2070}, key = {tagkey1986249}, keywords = {bookrev} } @ARTICLE{Cartwright86, author = {Phillip A. Cartwright}, title = {Time series analysis: Theory and practice 5}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {249-250}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90124-X}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{CH05, author = {Vasco M. Carvalho and Andrew C. Harvey}, title = {Growth, cycles and convergence in US regional time series}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {667-686}, number = {4}, abstract = {This article reports the results of fitting unobserved components (structural) time series models to data on real income per capita in eight regions of the United States. The aim is to establish stylised facts about cycles and convergence. It appears that while the cycles are highly correlated, the two richest regions have been diverging from the others in recent years. A new model is developed in order to characterise the converging behaviour of the six poorest regions. The model combines convergence components with a common trend and cycles. These convergence components are formulated as a second-order error correction mechanism which allows temporary divergence while imposing eventual convergence. After fitting the model, the implications for forecasting are examined. Finally, the use of unit root tests for testing convergence is critically assessed in the light of the stylised facts obtained from the fitted models.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.04.017}, issn = {0169-2070}, keywords = {Balanced growth, Error correction mechanism, Kalman filter, Signal extraction, Unobserved components, regart} } @ARTICLE{CJS00, author = {Jos{\'e} Casals and Miguel Jerez and Sonia Sotoca}, title = {Exact smoothing for stationary and non-stationary time series}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {59-69}, number = {1}, abstract = {In this work we derive an analytical relationship between exact fixed-interval smoothed moments and those obtained from an arbitrarily initialized smoother. Combining this result with a conventional smoother we obtain an exact algorithm that can be applied to stationary, non-stationary or partially non-stationary systems. Other advantages of our method are its computational efficiency and numerical stability. Its extension to forecasting, filtering, fixed-point and fixed-lag smoothing is immediate, as it only requires modification of a conditioning information set. Three examples illustrate the adverse effect of an inadequate initialization on smoothed estimates.}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00030-8}, issn = {0169-2070}, keywords = {Smoothing, Forecasting, State-space models, Unit roots, Kalman filter, regart} } @ARTICLE{Caselles-Moncho86, author = {Antonio Caselles-Moncho}, title = {An empirical comparison of cross-impact models for forecasting sales}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {295-303}, number = {3}, abstract = {This paper compares a set of four cross-impact models: (1) additive, (2) likelihood multiplier, (3) R-space, and (4) a model constructed by the author. This is done by examining a forecasting problem encountered by an industrial firm. The forecasting problem was to study the market trend in order to decide whether to expand the production capacity of a ceramics plant. In spite of their different theoretical premises, the models yielded similar results. However, only the R-space model produced results that differed from the others. The paper also suggests a method that should avoid some internal contradictions of the cross-impact models.}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90049-X}, issn = {0169-2070}, keywords = {Cross-impact, Forecasting sales, Ceramics, Market trend, regart} } @ARTICLE{CKN89, author = {Glenn Cassidy and Mark S. Kamlet and Daniel S. Nagin}, title = {An empirical examination of bias in revenue forecasts by state governments}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {321-331}, number = {3}, abstract = {This analysis examines the influence of economic forecast errors and political and institutional factors on the general fund revenue forecast errors of 23 states for the period 1978 to 1987. During this period states in the sample underestimated their revenue by only 0.5%. This modest tendency toward conservative forecasting is further reduced after controlling for economic uncertainty. Moreover, the analysis reveals no systematic relationship between revenue forecast errors and state political and institutional factors. Thus, the results cast substantial doubt on the prevailing belief as found in the literature, that state revenue forecasts have a pronounced conservative bias.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90036-8}, issn = {0169-2070}, keywords = {Economic uncertainty, Forecasting accuracy and bias, Political and institutional influences, State revenue forecasting, regart} } @ARTICLE{Cataquet89, author = {Harold Cataquet}, title = {Macroeconomic uncertainty: International risks and opportunities for the corporation : L. Oxelheim and C. Wihlborg, (Wiley, Chichester, UK, 1987) pp. 272, �29.50/\$58.45 (hardcover) and �12.95/\$29.95 (paperback)}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {617-619}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90025-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Caudill03, author = {Steven B. Caudill}, title = {Predicting discrete outcomes with the maximum score estimator: the case of the NCAA men's basketball tournament}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {313-317}, number = {2}, abstract = {Seedings as a predictor of winning in the men's NCAA basketball tournament have recently been examined by Boulier and Stekler [Int. J. Forecast. 15 (1999) 83]. BS estimate a probit model to establish a relationship between seedings and the probability of winning. This study discusses the merits of a maximum score estimator for the prediction of discrete outcomes. Unlike the probit model, the maximum score estimator maximizes the number of correct predictions. The maximum score estimator is applied to updated data on the men's NCAA basketball tournament. The score estimator has better in-sample performance than the probit model used by BS. When out-of-sample predictions are examined using a series of rolling or recursive regressions, the maximum score estimator performs slightly better than the probit/maximum likelihood models. These results illustrate the potential advantages of using the maximum score estimator when predicting discrete outcomes.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00008-0}, issn = {0169-2070}, keywords = {Maximum score, Discrete choice, Forecasting, regart} } @ARTICLE{Caulkins01, author = {Jonathan P. Caulkins}, title = {A Study of Recidivism of Serious and Persistent Offenders Among Adolescents: Brent B. Benda and Connie L. Tollett, 1999; Journal of Criminal Justice, Vol. 27, No. 2, pp. 111-126}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {135-139}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00049-2}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{CE96, author = {A. Aydin Cecen and Cahit Erkal}, title = {Distinguishing between stochastic and deterministic behavior in high frequency foreign exchange rate returns: Can non-linear dynamics help forecasting?}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {465-473}, number = {4}, abstract = {This paper investigates the dynamic properties of high frequency foreign exchange rate returns. Using hourly data for four exchanges rates, the British Pound, the Deutschemark, the Japanese Yen and Swiss Franc, we attempt to differentiate between stochastic and deterministic behavior in hourly rates of returns. While the autocorrelation coefficients and the Brock-Dechert-Scheinkman test point to the presence of some non-linear dependence, correlation dimension estimates reveal little evidence in favor of low-dimensional chaos. The analysis appears to support the view that although it is not possible to exploit deterministic non-linear dependence in exchange rate time series in order to improve short-term forecasting, non-linear stochastic models can be used for conditional volatility forecasts.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00686-3}, issn = {0169-2070}, keywords = {Low-dimensional chaos, Correlation dimension, GARCH model, regart} } @ARTICLE{Chacko87, author = {George K. Chacko}, title = {Forecasting use of health services: A provider's guide : R.S. MacStravic, (Aspen Systems, Rockville, MD, 1984) 281 pp.}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {338-339}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90019-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{CT89, author = {Wilkie W. Chaffin and Wayne K. Talley}, title = {Diffusion indexes and a statistical test for predicting turning points in business cycles}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {29-36}, number = {1}, abstract = {This paper presents a non-econometric statistical procedure for testing the significance of turning points in a sample diffusion index of leading indicators, allowing one to make inferences with respect to turning points of the corresponding business cycle. The procedure is applied utilizing 30 leading indicators in the prediction of peaks and troughs in the U.S. business cycle between 1969 and 1982. For this time period, the procedure correctly predicts the four peaks and the four troughs in the U.S. business cycle with a lead time range of from zero to twelve months, although false turns with respect to the prediction of peaks were recorded. This procedure compares very favorable with the Neftci non-econometric statistical test approach for predicting turning points in business cycles. Further, this procedure may be used in conjunction with smoothing and weighting techniques for improving predictions from leading indicators.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90061-7}, issn = {0169-2070}, keywords = {Business cycle-prediction, Business indicators-application, Index numbers-methodology, Time series-hypothesis tests, Turning points-forecasting, regart} } @ARTICLE{CB89, author = {Saade N. Chami and David W. Butterfield}, title = {The implications of myopic policy-making for macroeconomic performance}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {49-58}, number = {1}, abstract = {This paper evaluates the implications of myopic behaviour in policy-making on intertemporal economic performance by applying an optimal control approach to Canada. Myopia is characterized in two ways; first by the rate at which the future is discounted and second by the policy maker's planning horizon. The optimal decision rules, which correspond to various degrees of time preference and different time horizons, generate an intertemporal tradeoff curve of economic performance. This tradeoff tends to disappear with an excessive preoccupation on the present vis à vis the future. That is, an extremely myopic policy results in poor economic perfomance in the future without any improvement in the present.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90063-0}, issn = {0169-2070}, keywords = {Macroeconomic policy, Time preference, Time horizon, Interemporal tradeoff, regart} } @ARTICLE{CG06, author = {Kam Fong Chan and Philip Gray}, title = {Using extreme value theory to measure value-at-risk for daily electricity spot prices}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {283-300}, number = {2}, abstract = {The recent deregulation in electricity markets worldwide has heightened the importance of risk management in energy markets. Assessing Value-at-Risk (VaR) in electricity markets is arguably more difficult than in traditional financial markets because the distinctive features of the former result in a highly unusual distribution of returns--electricity returns are highly volatile, display seasonalities in both their mean and volatility, exhibit leverage effects and clustering in volatility, and feature extreme levels of skewness and kurtosis. With electricity applications in mind, this paper proposes a model that accommodates autoregression and weekly seasonals in both the conditional mean and conditional volatility of returns, as well as leverage effects via an EGARCH specification. In addition, extreme value theory (EVT) is adopted to explicitly model the tails of the return distribution. Compared to a number of other parametric models and simple historical simulation based approaches, the proposed EVT-based model performs well in forecasting out-of-sample VaR. In addition, statistical tests show that the proposed model provides appropriate interval coverage in both unconditional and, more importantly, conditional contexts. Overall, the results are encouraging in suggesting that the proposed EVT-based model is a useful technique in forecasting VaR in electricity markets.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.10.002}, issn = {0169-2070}, keywords = {Extreme value theory, Value-at-risk, Electricity, EGARCH, Conditional interval coverage, regart} } @ARTICLE{CGC08, author = {Kam Fong Chan and Philip Gray and Bart van Campen}, title = {A new approach to characterizing and forecasting electricity price volatility}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {728-743}, number = {4}, abstract = {There is a growing need to model the dynamics of electricity spot prices. While many studies have adopted the jump-diffusion model used successfully in traditional financial markets, the distinctive features of energy prices present non-trivial challenges. In particular, electricity price series feature extreme jumps of magnitudes rarely seen in financial markets, and occurring at greater frequency. Standard parametric approaches to estimating jump-diffusion models struggle to disentangle the jump and non-jump variation. This paper explores a recently-developed approach to separating the total variation into jump and non-jump components. Using quadratic variation theory, we non-parametrically estimate jump parameters for five power markets which are known to feature some important physical differences. The unique characteristics of the jump and non-jump components of the total variation are studied for each market. Given the evidence that the two sources of variation in spot prices have distinct dynamics, the paper explores whether volatility forecasts can be improved by explicitly incorporating the jump and non-jump components of the total variation.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.08.002}, issn = {0169-2070}, keywords = {Realized volatility, Bipower variation, Quadratic variation, Jumps, Volatility forecast, regart} } @ARTICLE{Chatfield06, author = {Chris Chatfield}, title = {`Modelling non-stationary economic time series'}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {819-819}, number = {4}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.12.003}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Chatfield02, author = {Chris Chatfield}, title = {Book reviews: Time Series: Data Analysis and Theory, Classics Edition, David R. Brillinger, SIAM, Philadelphia, USA, 2001, Paperback, 540pp, ISBN 0-89871-501-6, \$59, �51.95.}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {461-461}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00148-0}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Chatfield95, author = {Chris Chatfield}, title = {Positive or negative?}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {501-502}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(96)83105-0}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Chatfield94, author = {Chris Chatfield}, title = {Developments in time series analysis : T. Subba Rao, ed., 1993, (Chapman \& Hall, London, UK), 433 pp., hardback �49.95, ISBN 0-412-49260-1}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {171-172}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90065-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Chatfield94a, author = {Chris Chatfield}, title = {Elements of multivariate time series analysis : Gregory C. Reinsel, 1993, (Springer-Verlag, New York), xiv + 263 pp., DM 88 hardback, ISBN 0-387-94063-4}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {381-382}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90014-0}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Chatfield93, author = {Chris Chatfield}, title = {Neural networks: Forecasting breakthrough or passing fad?}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {1-3}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90043-M}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Chatfield93a, author = {Chris Chatfield}, title = {A personal view of the M2-competition}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {23-24}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90045-O}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Chatfield93b, author = {Chris Chatfield}, title = {Rule-based forecasting: Development and validation of an expert systems approach to combining time series extrapolations: Fred Collopy and J. Scott Armstrong, Management science, 38 (1992) 1394-1414}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {284-285}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90019-J}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Chatfield92, author = {Chris Chatfield}, title = {A commentary on error measures}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {100-102}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90011-W}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Chatfield91, author = {Chris Chatfield}, title = {Non-linear time series : Howell Tong, (Clarendon Press, Oxford, UK, 1990), pp. 564, �50.00.}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {249-249}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90065-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Chatfield90, author = {Chris Chatfield}, title = {Confidence intervals for non-stationary forecast errors, by P. Lefran{\c c}ois}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {559-559}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90035-A}, issn = {0169-2070}, keywords = {Confidence intervals, othercom} } @ARTICLE{Chatfield89, author = {Chris Chatfield}, title = {Business forecasting methods : Jeffrey Jarrett: (Basil Blackwell Ltd., Oxford, U.K., 1987) pp. 346, \$15.00}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {285-286}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90100-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Chatfield89a, author = {Chris Chatfield}, title = {Non-linear and non-stationary time series analysis : M.B. Priestley, (Academic Press, London, 1988), �25.00, pp. 237}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {428-429}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90048-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Chatfield88, author = {Chris Chatfield}, title = {The future of the time-series forecasting}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {411-419}, number = {3}, abstract = {Time-series forecasting methids may be classified into univariate (projection) methods and multivariate methids. The choice amongst methods depends on a variety of considerations including the objectives, the type of data, and whether an automatic or unautomatic approach is to be used. The value of forecasting competitions is reviewed and suggestions are made regarding the forthcoming M2-competition. Various unsolved research problems relating to different univariate and multivariate methods are outlined. The difficulties of fitting multivariate models to economic data are discussed and it is suggested that univariate procedures will continue to have wide use in practice. The impact of proliferating computer software is considered and some desirable features of `good' packages are listed.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90108-2}, issn = {0169-2070}, keywords = {Forecasting competitions, M-competition, FORSYS, ARARMA, Holt-Winters, Structural models, Transfer function models, VARIMA, Econometrica model, M2-competition, Computer software, regart} } @ARTICLE{Chatfield88a, author = {Chris Chatfield}, title = {Apples, oranges and mean square error}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {515-518}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90127-6}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Chatfield86, author = {Chris Chatfield}, title = {Simple is best?}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {401-402}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90086-5}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{CK91, author = {Christopher Chatfield and Anne B. Koehler}, title = {On confusing lead time demand with h-period-ahead forecasts}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {239-240}, number = {2}, abstract = {The forecast of cumulative demand over the next h periods should obviously not be confused with the single-period forecast for h-steps ahead. However, an approximate formula for the standard deviation of the error in cumulative demand (given by s[radical sign]h, where s is the standard deviation of one-step-ahead errors) has unfortunately been used for single-period forecasts, and this confusion clearly needs to be rectified.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90057-3}, issn = {0169-2070}, keywords = {Cumulative demand, Lead time, Confidence interval, regart} } @ARTICLE{CW94, author = {Chris Chatfield and Andreas S. Weigend}, title = {Time series prediction: Forecasting the future and understanding the past : Neil A. Gershenfeld and Andreas S. Weigend, 1994, `The future of time series', in: A.S. Weigend and N.A. Gershenfeld, eds., (Addison-Wesley, Reading, MA), 1-70.}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {161-163}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90058-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{CY91, author = {Chris Chatfield and Mohammed Yar}, title = {Prediction intervals for multiplicative Holt-Winters}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {31-37}, number = {1}, abstract = {Yar and Chatfield (1990) have proposed a method of constructing prediction intervals for the additive Holt-Winters forecasting procedure and this companion paper extends the results to the multiplicative seasonal case. In contrast to the additive case, it is shown that the width of `multiplicative' prediction intervals will depend on the time origin of the forecasts and may decrease (near a seasonal trough) as well as increase with lead time. This key result follows from the form of the Holt-Winters updating equations, and applies whatever assumption is made about the error variance, although more self-consistent results are obtained if the (one-step-ahead) error variance is assumed to be proportional to the seasonal effect rather than constant. An example is presented to compare the proposed prediction intervals, calculated under two different error assumptions, with those obtained using an empirical procedure, which effectively assumes additive errors with constant variance, and those obtained with an `approximate' procedure. Some general recommendations are made.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90030-Y}, issn = {0169-2070}, keywords = {Holt-Winters, Prediction intervals, Exponential smoothing, regart} } @ARTICLE{CY88, author = {C. Chatfield and M. Yar}, title = {Software reviews}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {503-508}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90120-3}, issn = {0169-2070}, keywords = {prodrev} } @ARTICLE{Chen97, author = {Chunhang Chen}, title = {Robustness properties of some forecasting methods for seasonal time series: A Monte Carlo study}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {269-280}, number = {2}, abstract = {Most statistical time series forecasting methods are based upon some assumptions on the data generating processes. These assumptions, however, may not be satisfied in practical situations. In this research, we investigate robustness properties of four major forecasting methods for seasonal time series, using Monte Carlo simulations. We ask the question as to whether the various methods have reasonably good forecasting performances for a wide class of time series to which the methods are likely to be used. We discuss some reasons why a forecasting method is (or is not) robust.}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00014-9}, issn = {0169-2070}, keywords = {Time series, Seasonality, Trend, Forecasting, ARIMA models, Regression models, Structural component models, Holt-Winters method, Robustness, regart} } @ARTICLE{CS06, author = {Cathy W.S. Chen and Mike K.P. So}, title = {On a threshold heteroscedastic model}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {73-89}, number = {1}, abstract = {This paper proposes a threshold heteroscedastic model which integrates threshold nonlinearity and GARCH-type conditional variance for modeling mean and volatility asymmetries in financial markets. The main feature of this model is that the threshold variable for regime switching is formulated as a weighted average of important auxiliary variables. Estimation and diagnostic checks are performed using Markov chain Monte Carlo methods. Forecasts of volatility and value at risk can also be generated from predictive distributions. The proposed methodology is illustrated using both simulated and actual international market index data. Empirical results show higher average volatility and more persistent volatility when bad news arrives. While the domestic return is the major determinant of the regimes, both the SP 500 and Nikkei 225 indices also impact the dynamic structure of domestic market returns.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.08.001}, issn = {0169-2070}, keywords = {Asymmetry, Auxiliary variables, GARCH model, Markov chain Monte Carlo, Model diagnostics, Stock returns, regart} } @ARTICLE{Chen94, author = {Dean T. Chen}, title = {Economic forecasting in agriculture: Comment}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {597-599}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90027-2}, issn = {0169-2070} } @ARTICLE{CB90, author = {Dean T. Chen and David A. Bessler}, title = {Forecasting monthly cotton price: Structural and time series approaches}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {103-113}, number = {1}, abstract = {This paper examines the predictive performance of structural and vector autorregressive models for forecasting monthly cotton prices. Two distinct time periods were selected for testing: a period of major policy shock, and a period of more normal market conditions. The study also investigates a composite approach, using vector autoregressions to determine the future values of exogenous variables of the structural model. Multi-dimensional testing procedures were adopted to evaluate the accuracy of forecasts. Simulation results demonstrate the superior performance of the structural model in handling major policy changes, while the time series approach shows greater accuracy in forecasting normal price movement. Although the composite approach failed to show improvement in forecasting accuracy, a joint specification of the structural model and the time series properties of exogenous variables may merit further investigations.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90101-G}, issn = {0169-2070}, keywords = {Composite approach, Cotton price forecast, Multi-dimensional evaluation, Structural model, Vector autoregression, regart} } @ARTICLE{CB08, author = {Huijing Chen and John E. Boylan}, title = {Empirical evidence on individual, group and shrinkage seasonal indices}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {525-534}, number = {3}, abstract = {This paper provides empirical evidence on forecasting seasonal demand using both individual and group seasonal indices methods. The findings show that the group seasonal indices methods outperform the individual seasonal indices method. This paper also offers empirical results from comparing two shrinkage methods with the group seasonal indices methods. The theoretical rules developed by the authors for choosing between group seasonal indices and individual seasonal indices produce more accurate forecasts than do published rules for choosing between shrinkage methods, when measured by the MSE, and are competitive when measured by the symmetric MAPE.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.02.005}, issn = {0169-2070}, keywords = {Forecasting, Seasonality, Grouping, Shrinkage, regart} } @ARTICLE{Chen93, author = {Rong Chen}, title = {Nonlinear modeling and forecasting : Martin Casdagli and Stephen Eubank (eds.), 1992, (Addison-Wesley, Reading, MA), 533 pp., paper-back \$34.50, ISBN 0-201-58788-2}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {273-274}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90012-C}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{CS06a, author = {Shyh-Wei Chen and Chung-Hua Shen}, title = {When Wall Street conflicts with Main Street--The divergent movements of Taiwan's leading indicators}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {317-339}, number = {2}, abstract = {This paper argues that the simultaneous use of all leading indicators may result in the blending of two different sets of information, which could lead to less accurate predictions of a future recession. We divide six of Taiwan's leading indicators into two different sectors, the real and financial sectors, and distinctly demonstrate that the two sectors may very well reveal different information. Three inconsistent, or even divergent, movements are found for 1988, 1991 and 1994, implying that the factor extracted from the real side may be different from that from the financial side. Thus, in contrast to the one-factor model typically used, we suggest a two-factor model. We compare four Markov Switching models, and it is evident that the predicted recessions based on the two-factor one-state model seem to outperform other models. The second best is the one-factor model which is only based on the real side variables, followed by the one-factor model with four variables. The worst model is that which simply uses financial variables. The results support our argument to use the two-factor model.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.09.005}, issn = {0169-2070}, keywords = {Wall Street, Main Street, Business cycle, Markov Switching model, regart} } @ARTICLE{CKW94, author = {Youhua Chen and Vinay Kanetkar and Doyle L. Weiss}, title = {Forecasting market shares with disaggregate or pooled data: a comparison of attraction models}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {263-276}, number = {2}, abstract = {The objective of this paper is to compare market share forecasts using parameter estimates from three different arrangements of single source scanner data. The data arrangements are coupled with two different attraction models and a well known naive model. Each attraction model is specified with either autocorrelated errors or with a lagged attraction term on the right hand side. Forecasts are compared using data aggregated across stores and disaggregated by store. In the later case, parameters for each store are estimated and a composite (average) share forecast is formed or the data are pooled and a single set of estimated parameters provide the forecast. The study finds that the full cross effects model with an autocorrelated error structure fits the data better than alternative models. However, the differential effects model with an autocorrelated error structure provides the best forecasts. With respect to the alternative data arrangements, the data aggregated across stores (i.e. chain level data) provides the best forecasts.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90006-X}, issn = {0169-2070}, keywords = {Aggregate data, Disaggregate data, Empirical study, Predictive accuracy, Market share models, Pooling data, Scanner dataregart} } @ARTICLE{CDH+04, author = {Timothy Chenoweth and Karen Dowling and Robert Hubata and Robert St. Louis}, title = {Distance and prediction error variance constraints for ARMA model portfolios}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {41-52}, number = {1}, abstract = {Poskitt and Tremayne 74 (1987) present a posterior odds ratio () portfolio selection strategy for ARMA models. This paper makes the range of prediction error variances that are implicit in more explicit. Model closeness is quantified using a distance function in a Hilbert space. The relationship between distance and the posterior odds ratio is demonstrated. This provides a distance interpretation of the posterior odds ratio. The distance function also makes it possible to develop a prediction error variance (p.e.v.) criterion for identifying models to include in an ARMA model portfolio. A simulation experiment shows that the p.e.v. criterion provides forecasters with both a measure for assessing the likelihood that the models in an ARMA model portfolio yield practically equivalent forecasts, and a measure for assessing the usefulness of alternative criteria for identifying the order of an ARMA model.}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00006-2}, issn = {0169-2070}, keywords = {Distance, Information criteria, Misspecification error, Order determination, Posterior odds ratio, Prediction error variance, regart} } @ARTICLE{Chevillon09, author = {Guillaume Chevillon}, title = {Multi-step forecasting in emerging economies: An investigation of the South African GDP}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {602 - 628}, number = {3}, note = {Special Section: Time Series Monitoring}, doi = {10.1016/j.ijforecast.2008.12.004}, issn = {0169-2070}, keywords = {Multi-step forecasting, Intercept correction,Structural breaks} } @ARTICLE{CH05a, author = {Guillaume Chevillon and David F. Hendry}, title = {Non-parametric direct multi-step estimation for forecasting economic processes}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {201-218}, number = {2}, abstract = {We evaluate the asymptotic and finite-sample properties of direct multi-step estimation (DMS) for forecasting at several horizons. For forecast accuracy gains from DMS in finite samples, mis-specification and non-stationarity of the DGP are necessary, but when a model is well-specified, iterating the one-step ahead forecasts may not be asymptotically preferable. If a model is mis-specified for a non-stationary DGP, in particular omitting either negative residual serial correlation or regime shifts, DMS can forecast more accurately. Monte Carlo simulations clarify the nonlinear dependence of the estimation and forecast biases on the parameters of the DGP, and explain existing results.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.08.004}, issn = {0169-2070}, keywords = {Adaptive estimation, Multi-step estimation, Dynamic forecasts, Model mis-specification, regart} } @ARTICLE{Cho02, author = {Dong W. Cho}, title = {Do revisions improve forecasts?}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {107-115}, number = {1}, abstract = {This study examines the effects of forecast revisions on accuracy using economic forecast survey data. Forecasts on the GDP growth rate and the short-term bond yield have been more extensively revised than forecasts on the inflation rate, the long-term bond yield, and the yen/dollar exchange rate. This study finds that revision produces significantly better forecasts for the short-term interest rate and the exchange rate, but not for the GDP growth or inflation rates. For the latter, the additional information available since the original forecasts appears to make little difference. The results on macroeconomic forecasting are in disagreement with an earlier finding that recently revised forecasts are superior to the originals.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00107-8}, issn = {0169-2070}, keywords = {Forecast revision, Fixed horizon forecasts, Revision effectiveness, Economic and financial rate forecasts, regart} } @ARTICLE{CW95, author = {Seungmook Choi and Mark E. Wohar}, title = {The expectations theory of interest rates: Cointegration and factor decomposition}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {253-262}, number = {2}, abstract = {This paper empirically re-examines the expectations theory of the term structure by using the decomposition procedures developed by Stock and Watson (1988, Journal of the American Statistical Association 83, 1097-1107), Park (1990, Working paper, Dept. of Economics, Cornell University) and Gonzalo and Granger (1991, Working paper, University of California-San Diego). Three- and six-month interest rates for four sub-periods between 1910 and 1989 are decomposed into permanent and transitory components. The results of the decomposition technique indicate that the failure of the spread between three- and six-month US Treasury bill rates to predict future short-rates during the post-1979 period results from the fact that the variation in the permanent components of interest rates dominates relative to the variation of the transitory components. The spread is found to provide predictive power during the 1979-1989 period when the permanent component is removed from the short-rate.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00590-M}, issn = {0169-2070}, keywords = {Cointegration, Expectations theory, Term structure, Stationarity, Permanant component, Transitory component, regart} } @ARTICLE{CK05, author = {{Hwan-sik} Choi and Nicholas M. Kiefer}, title = {Software evaluation: EasyReg International}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {609-616}, number = {3}, abstract = {Herman J. Bierens' EasyReg International is a convenient and efficient tool for researchers, teachers and students. It is free of charge, easy to use and offers many popular econometric tools. We reviewed the most recent (October 6, 2004) version. We present the evaluation according to Berk's (1987) [Berk, K., 1987. Effective microcomputer statistical software, The American Statistician, 41, 222-228] list of criteria for statistical software. We also discuss the numerical accuracy of EasyReg International.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.02.003}, issn = {0169-2070}, keywords = {Software evaluation; Econometric software; EasyReg International; Berk's criteria; Numerical accuracy, prodrev} } @ARTICLE{CL86, author = {Pierre A. Cholette and Robert Lamy}, title = {Mutivariate ARIMA forecasting of irregular time series}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {201-216}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(86)99004-7}, issn = {0169-2070} } @ARTICLE{CC06, author = {Hwee Kwan Chow and Keen Meng Choy}, title = {Forecasting the global electronics cycle with leading indicators: A Bayesian VAR approach}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {301-315}, number = {2}, abstract = {Developments in the global electronics industry are typically monitored by tracking indicators that span a whole spectrum of activities in the sector. However, these indicators invariably give mixed signals at each point in time, thereby hampering attempts at prediction. In this paper, we propose a unified framework for forecasting the global electronics cycle by constructing a VAR model that captures the economic interactions between putative leading indicators representing expectations, orders, inventories and prices. The ability of the indicators to presage world semiconductor sales is first examined by Granger causality tests. Subsequently, an impulse response analysis confirms the leading qualities of the selected indicators. Finally, out-of-sample forecasts of global chip sales are generated from two parsimonious variants of the VAR model, viz., the Bayesian VAR (BVAR) and Bayesian ECM (BECM), and compared with predictions from a bivariate model which uses a composite index of the leading indicators and a univariate autoregressive model. An evaluation of their relative accuracy suggests that the BVAR's forecasting performance is superior to the other models. The BVAR is also able to predict the turning points of the recent IT boom-and-bust cycle.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.07.002}, issn = {0169-2070}, keywords = {Leading indicators, Global electronics cyle, VAR, Forecasting, regart} } @ARTICLE{CP89, author = {Thana Chrissanthaki and Jenifer Piesse}, title = {Software reviews : The international journal of forecasting policy}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {147-150}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90080-0}, issn = {0169-2070}, keywords = {prodrev} } @ARTICLE{Christofides91, author = {Louis N. Christofides}, title = {In-sample and out-of-sample forecasts of wage adjustment in indexed and non-indexed labour contracts}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {171-181}, number = {2}, abstract = {This paper adopts an econometric framework which makes it possible to analyse the determi- nants of total as well as non-contingent wage adjustment, the elasticity of indexation and contract duration. A sample of Canadian labour contracts arrived at in the non-controlled private sector is used and detailed in-sample wage adjustment predictions by indexation status are presented. The model predicts wage change in indexed and non-indexed contracts satisfactorily and, consistent with the actual data and particular time period used, indicates that non-indexed contracts do better in general and particularly so in periods of decelerating inflation. Out-of-sample wage adjustment predictions appear reasonable. The in- and out-of-sample behaviour of the ex ante elasticity of indexation and contract duration are also considered.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90052-W}, issn = {0169-2070}, keywords = {Indexation, Contract duration, Wage adjustment, Forecasts, In-sample, Out-of-sample, Nelson and Olson estimator, regart} } @ARTICLE{CST96, author = {Costas Christou and P. A. V. B. Swamy and George S. Tavlas}, title = {Modelling optimal strategies for the allocation of wealth in multicurrency investments}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {483-493}, number = {4}, abstract = {This paper analyzes rates of return on financial assets denominated in five major currencies and provides a framework for the determination of optimal strategies for the allocation of wealth in multicurrency investments. Three models are estimated: a univariate autoregressive conditional heteroskedasticity (ARCH) model, an extended ARCH model using the random coefficient (RC) procedure, and a pure RC model. A comparison of the forecasts of these models with those generated by a random walk model demonstrates that forecasts based on the RC/extended ARCH procedure are superior to those based on the random walk model and those based on direct ARCH estimation. These results could be useful for both international investors for the allocation of their wealth among fixed-income investment securities and central banks for the management of their external reserve assets.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00673-5}, issn = {0169-2070}, keywords = {ARCH models, Random coefficient models, Forecasting, Optimal portfolios, regart} } @ARTICLE{CC96, author = {Keith B. Church and Stephen P. Curram}, title = {Forecasting consumers' expenditure: A comparison between econometric and neural network models}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {255-267}, number = {2}, abstract = {This paper is motivated by the difficulties faced by forecasters in predicting the decline in the growth rate of consumers' expenditure in the late 1980s. The econometric specifications of four competing explanations are replicated and the static forecasts compared with the actual outturns. The same data are then used to estimate neural network models. The main issue is whether the neural network technology can extract any more from the data sets provided than the econometric approach. It is found that the neural network models describe the decline in the growth of consumption since the late 1980s as well as, but no better than, the econometric specifications included in the exercise, and are shown to be robust when faced with a small number of data points. However, whichever approach is adopted, it is the skill of choosing the menu of explanatory variables which determines the success of the final results.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00631-1}, issn = {0169-2070}, keywords = {Consumers' expenditure, Econometric modelling, Neural networks, Forecasting, regart} } @ARTICLE{CPR07, author = {Oscar Claveria and Ernest Pons and Raúl Ramos}, title = {Business and consumer expectations and macroeconomic forecasts}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {47-69}, number = {1}, abstract = {Business and consumer surveys have become an essential tool for gathering information about different economic variables. While the fast availability of the results and the wide range of variables covered have made them very useful for monitoring the current state of the economy, there is no consensus on their usefulness for forecasting macroeconomic developments. The objective of this paper is to analyse the possibility of improving forecasts for selected macroeconomic variables for the euro area using the information provided by these surveys. After analyzing the potential presence of seasonality and the issue of quantification, we tested whether these indicators provide useful information for improving forecasts of the macroeconomic variables. With this aim, different sets of models have been considered (AR, ARIMA, SETAR, Markov switching regime models and VAR) to obtain forecasts for the selected macroeconomic variables. Then, information from surveys has been considered for forecasting these variables in the context of the following models: autoregressive, VAR, Markov switching regime and leading indicator models. In all cases, the root mean square error (RMSE) has been computed for different forecast horizons. The comparison of the forecasting performance of the two sets of models permits us to conclude that, in most cases, models that include information from the surveys have lower RMSEs than the best model without survey information. However, this reduction is only significant in a limited number of cases. In this sense, the results obtained extend the results of previous research that has included information from business and consumer surveys to explain the behaviour of macroeconomic variables, but are not conclusive about its role.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.04.004}, issn = {0169-2070}, keywords = {Macroeconomic forecasts, Forecast competition, Business and consumer surveysregart} } @ARTICLE{Clemen89, author = {Robert T. Clemen}, title = {Combining forecasts: A review and annotated bibliography}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {559-583}, number = {4}, abstract = {Considerable literature has accumulated over the years regarding the combination of forecasts. The primary conclusion of this line of research is that forecast accuracy can be substantially improved through the combination of multiple individual forecasts. Furthermore, simple combination methods often work reasonably well relative to more complex combinations. This paper provides a review and annotated bibliography of that literature, including contributions from the forecasting, psychology, statistics, and management science literatures. The objectives are to provide a guide to the literature for students and researchers and to help researchers locate contributions in specific areas, both theoretical and applied. Suggestions for future research directions include (1) examination of simple combining approaches to determine reasons for their robustness, (2) development of alternative uses of multiple forecasts in order to make better use of the information they contain, (3) use of combined forecasts as benchmarks for forecast evaluation, and (4) study of subjective combination procedures. Finally, combining forecasts should become part of the mainstream of forecasting practice. In order to achieve this, practitioners should be encouraged to combine forecasts, and software to produce combined forecasts easily should be made available.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90012-5}, issn = {0169-2070}, keywords = {Forecast combination, Composite models, Forecast aggregation, Consensus, Forecast synthesis, regart} } @ARTICLE{CG89, author = {Robert T. Clemen and John B. Guerard}, title = {Econometric GNP forecasts: Incremental information relative to naive extrapolation}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {417-426}, number = {3}, abstract = {Recent studies of macroeconomic forecasts have focused primarily on the relative performance of individual forecasts and combinations thereof. We suggest that these forecasts be evaluated in terms of the incremental information that they provide relative to a simple extrapolation forecast. Using a Bayesian approach, we measure the incremental information contained in econometric forecasts of U.S. GNP relative to a random-walk-with-drift time series forecast. The results indicate that (1) substantial incremental gains can be obtained from econometric GNP forecasts for the current quarter, but that these gains decrease rapidly as the forecast horizon increases, and (2) after one econometric forecast has been consulted, subsequent such forecasts add little information.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90045-9}, issn = {0169-2070}, keywords = {Forecast evaluation, Combination of forecasts, GNP forecasts, Econometric models, regart} } @ARTICLE{CMW95, author = {Robert T. Clemen and Allan H. Murphy and Robert L. Winkler}, title = {Screening probability forecasts: contrasts between choosing and combining}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {133-145}, number = {1}, abstract = {In many forecasting situations, forecasts can be produced by several different methods. The ultimate objective of considering multiple methods may be to select a single method (the choosing scenario) or to aggregate the multiple forecasts into a single forecast (the combining scenario). Procedures for screening candidate forecasts--sufficiency in the choosing scenario and extraneousness in the combining scenario--are described here. Screening can identify forecasting methods that are dominated in the sense that their forecasts are clearly inferior to those of other methods or do not add any information to the combination of forecasts. These evaluation procedures are illustrated and contrasted by considering prototypical examples and an application involving precipitation probability forecasts. The value of screening is that it can reduce the set of candidate forecasting methods to a manageable number, which can then be evaluated in greater detail.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)02007-C}, issn = {0169-2070}, keywords = {Probability forecasts, Combining, Sufficiency, Screening, Extraneousness, regart} } @ARTICLE{Clements09, author = {Michael P. Clements}, title = {Comments on 'Forecasting economic and financial variables with global VARs'}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {680 - 683}, number = {4}, note = {Special section: Decision making and planning under low levels of predictability}, doi = {10.1016/j.ijforecast.2009.05.007}, issn = {0169-2070} } @ARTICLE{Clements08, author = {Michael P. Clements}, title = {Consensus and uncertainty: Using forecast probabilities of output declines}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {76-86}, number = {1}, abstract = {A number of studies have addressed the relationship between intra-personal uncertainty and inter-personal disagreement about the future values of economic variables such as output growth and inflation using the SPF. By making use of the SPF respondents' probability forecasts of declines in output, we are able to construct a quarterly series of output growth uncertainty to supplement the annual series that are often used in such analyses. We also consider the relationship between disagreement and uncertainty for probability forecasts of declines in output.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.06.003}, issn = {0169-2070}, keywords = {Disagreement, Uncertainty, Output declines, SPF, regart} } @ARTICLE{Clements03, author = {Michael P. Clements}, title = {Some possible directions for future research}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {1-3}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00037-7}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{CFS04, author = {Michael P. Clements and Philip Hans Franses and Norman R. Swanson}, title = {Forecasting economic and financial time-series with non-linear models}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {169-183}, number = {2}, abstract = {In this paper we discuss the current state-of-the-art in estimating, evaluating, and selecting among non-linear forecasting models for economic and financial time series. We review theoretical and empirical issues, including predictive density, interval and point evaluation and model selection, loss functions, data-mining, and aggregation. In addition, we argue that although the evidence in favor of constructing forecasts using non-linear models is rather sparse, there is reason to be optimistic. However, much remains to be done. Finally, we outline a variety of topics for future research, and discuss a number of areas which have received considerable attention in the recent literature, but where many questions remain.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.10.004}, issn = {0169-2070}, keywords = {Economic, Financial, Non-linear models, regart} } @ARTICLE{CG04, author = {Michael P. Clements and Ana Beatriz Galv{\~ a}o}, title = {A comparison of tests of nonlinear cointegration with application to the predictability of US interest rates using the term structure}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {219-236}, number = {2}, abstract = {We test whether there are nonlinearities in the response of short- and long-term interest rates to the spread in interest rates, and assess the out-of-sample predictability of interest rates using linear and nonlinear models. We find strong evidence of nonlinearities in the response of interest rates to the spread. Nonlinearities are shown to result in more accurate short-horizon forecasts, especially of the spread.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.09.001}, issn = {0169-2070}, keywords = {Threshold nonlinearities, Cointegration, Term structure, Forecasting, regart} } @ARTICLE{CH98, author = {Michael P. Clements and David F. Hendry}, title = {Forecasting economic processes}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {111-131}, number = {1}, abstract = {When the assumption of constant parameters fails, the in-sample fit of a model may be a poor guide to ex-ante forecast performance. We expound a number of models, methods, and procedures that illustrate the impacts of structural breaks on forecast accuracy, and evaluate ways of improving forecast performance. We argue that a theory of economic forecasting which allows for model mis-specification and structural breaks is feasible, and may provide a useful basis for interpreting and circumventing systematic forecast failure in macroeconomics. The empirical time series of consumers' expenditure, and Monte Carlo simulations, illustrate the analysis.}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00057-5}, issn = {0169-2070}, keywords = {Forecasting, Structural change, Intercept corrections, Consumers' nondurable expenditure, Monte Carlo, regart} } @ARTICLE{CH98a, author = {Michael P. Clements and David F. Hendry}, title = {Forecasting economic processes��A reply}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {139-143}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00005-3}, issn = {0169-2070}, key = {tagkey1998139}, keywords = {othercom} } @ARTICLE{CH97, author = {Michael P. Clements and David F. Hendry}, title = {An empirical study of seasonal unit roots in forecasting}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {341-355}, number = {3}, abstract = {We assess the usefulness of pre-testing for seasonal roots, based on the HEGY approach, for out-of-sample forecasting. It is shown that if there are shifts in the deterministic seasonal components then the imposition of unit roots can partially robustify sequences of rolling forecasts, yielding improved forecast accuracy. The analysis is illustrated with two empirical examples where more accurate forecasts are obtained by imposing more roots than is warranted by HEGY. The issue of assessing forecast accuracy when predictions of any one of a number of linear transformations may be of interest is also addressed.}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00022-8}, issn = {0169-2070}, keywords = {Seasonality, Structural breaks, Unit roots, Forecasting, regart} } @ARTICLE{CMD09, author = {Michael P. Clements and Costas Milas and Dick van Dijk}, title = {Forecasting returns and risk in financial markets using linear and nonlinear models}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {215-217}, number = {2}, note = {Forecasting Returns and Risk in Financial Markets using Linear and Nonlinear Models}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2009.01.003}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{CMD09a, author = {Michael P. Clements and Costas Milas and Dick van Dijk}, title = {Forecasting returns and risk in financial markets using linear and nonlinear models}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {215-217}, number = {2}, note = {Forecasting Returns and Risk in Financial Markets using Linear and Nonlinear Models}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2009.01.003}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{CS02, author = {Michael P. Clements and Jeremy Smith}, title = {Evaluating multivariate forecast densities: a comparison of two approaches}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {397-407}, number = {3}, abstract = {We consider methods of evaluating multivariate density forecasts. A recently proposed method is found to lack power when the correlation structure is mis-specified. Tests that have good power to detect mis-specifications of this sort are described. We also consider the properties of the tests in the presence of more general mis-specifications.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00126-1}, issn = {0169-2070}, keywords = {Multivariate density forecasts, Point forecasts, regart} } @ARTICLE{CS97, author = {Michael P. Clements and Jeremy Smith}, title = {The performance of alternative forecasting methods for SETAR models}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {463-475}, number = {4}, abstract = {We compare a number of methods that have been proposed in the literature for obtaining h-step ahead minimum mean square error forecasts for self-exciting threshold autoregressive (SETAR) models. These forecasts are compared to those from an AR model. The comparison of forecasting methods is made using Monte Carlo simulation. The Monte-Carlo method of calculating SETAR forecasts is generally at least as good as that of the other methods we consider. An exception is when the disturbances in the SETAR model come from a highly asymmetric distribution, when a Bootstrap method is to be preferred. An empirical application calculates multi-period forecasts from a SETAR model of US gross national product using a number of the forecasting methods. We find that whether there are improvements in forecast performance relative to a linear AR model depends on the historical epoch we select, and whether forecasts are evaluated conditional on the regime the process was in at the time the forecast was made.}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00017-4}, issn = {0169-2070}, keywords = {Threshold model, Forecasting, Simulationsregart} } @ARTICLE{CT01, author = {Michael P. Clements and Nick Taylor}, title = {Bootstrapping prediction intervals for autoregressive models}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {247-267}, number = {2}, abstract = {Methods of improving the coverage of Box-Jenkins prediction intervals for linear autoregressive models are explored. These methods use bootstrap techniques to allow for parameter estimation uncertainty and to reduce the small-sample bias in the estimator of the models' parameters. In addition, we also consider a method of bias-correcting the non-linear functions of the parameter estimates that are used to generate conditional multi-step predictions.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00079-0}, issn = {0169-2070}, keywords = {Prediction intervals, Bootstrapping, Bias-correction, regart} } @ARTICLE{04d, author = {Clive W. J. Granger, Yongil Jeon}, title = {Corrigendum to 'Comparing forecasts of inflation using time distance' [International Journal of Forecasting 19 (2003) 339��349]}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {739-740}, number = {4}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.09.003}, issn = {0169-2070}, key = {tagkey2004739}, keywords = {othercom} } @ARTICLE{CT92, author = {Carlos Henrique Motta Coelho and Moyses Tenenblat}, title = {Trading days, seasonal unit root, and variance change}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {61-67}, number = {1}, abstract = {A time series model is developed for the Brazilian index of total industrial production, including a trading days effect well accounted for by only one variable. Estimation using the exact likelihood function produces a unitary MA seasonal root and thus a common factor in the equation. This is dealt with first by using dummies and later by transforming the original data using difference equation solution properties to obtain a simplified model. The residuals show a variance change at a well defined point and this is confirmed with an F test. A new simplified model is built that allows for a variance change, and after a suitable data transformation it is reestimated and its forecasting performance tested.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90007-V}, issn = {0169-2070}, keywords = {Trading days, Seasonal time series, Seasonal unit root, Common factor, Variance change, Transfer function, regart} } @ARTICLE{Cogger88, author = {Kenneth O. Cogger}, title = {Proposals for research in time series forecasting}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {403-410}, number = {3}, abstract = {This paper reviews to developing lines of forecasting research which have received limited attention in the past and which appear to promise significant improvements in modeling ability and forecasting accuracy. Previous work is summarized, some new results are presented, and suggestions are given for fruitful new avenues of investigation.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90107-0}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{CGG09, author = {Jacqueline Cohen and Samuel Garman and Wilpen Gorr}, title = {Empirical calibration of time series monitoring methods using receiver operating characteristic curves}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {484 - 497}, number = {3}, note = {Special Section: Time Series Monitoring}, doi = {10.1016/j.ijforecast.2008.11.007}, issn = {0169-2070}, keywords = {Time series monitoring, ROC curve,Average run length statistic,Exponential smoothing,Structural breaks,Step jumps,Outliers} } @ARTICLE{Cole88, author = {Sam Cole}, title = {The electronic Oracle computer models and social decisions : Donella H. Meadows and J.M. Robinson, (Wiley, 1985) pp. 462, \$48.95, �29.95}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {616-617}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90142-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Collopy07, author = {Fred Collopy}, title = {Difficulty and complexity as factors in software effort estimation}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {469-471}, number = {3}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.05.011}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{04c, author = {Fred Collopy}, title = {Research on Forecasting}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {731-732}, number = {4}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.12.002}, issn = {0169-2070}, key = {tagkey2004731}, keywords = {othercom} } @ARTICLE{Collopy00, author = {Fred Collopy}, title = {Judgmental forecasts of time series affected by special events: Does providing a statistical forecast improve accuracy?: Paul Goodwin and Robert Fildes (1999) Journal of Behavioral Decision Making 12(1), 37-53.}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {143-144}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00044-8}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Collopy96, author = {Fred Collopy}, title = {Journal of computing in civil engineering : Paul Teicholz, 1993, Forecasting final cost and budget of construction projects, 7, 511-529.}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {186-187}, number = {1}, note = {Probability Judgmental Forecasting}, doi = {http://dx.doi.org/10.1016/0169-2070(96)88200-8}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Collopy95, author = {Fred Collopy}, title = {Journal of economic psychology : Fred D. Davis, Gerald L. Loshe, and Jeffrey E. Kottemann, 1944, Harmful effects of seemingly helpful information on forecasts of stock earnings}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {354-355}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(95)90069-1}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Collopy94, author = {Fred Collopy}, title = {Forecasting final cost and budget of construction projectsPaul Teicholz, Journal of computing in civil engineering, 7 (1993), 511-529}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {474-475}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90082-5}, issn = {0169-2070}, keywords = {revart} } @ARTICLE{Collopy94a, author = {Fred Collopy}, title = {A world-wide information system for forecasters}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {491-494}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90017-5}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Collopy91, author = {Fred Collopy}, title = {Innocents in the forest: Forecasting and research methods : P. Narayan Pant and William H. Starbuck, Journal of Management 16 (1990) 433-460}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {400-401}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90022-N}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{CA92, author = {Fred Collopy and J. Scott Armstrong}, title = {Generalization and communication issues in the use of error measures: A reply}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {107-109}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90015-2}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{CA92a, author = {Fred Collopy and J. Scott Armstrong}, title = {Management science : D. Bunn and G. Wright, Interaction of Judgmental and Statistical Forecasting Methods: Issues and Analysis, 37 (1991) 501-518}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {277-279}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90128-V}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{CA92b, author = {Fred Collopy and J. Scott Armstrong}, title = {Expert opinions about extrapolation and the mystery of the overlooked discontinuities}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {575-582}, number = {4}, abstract = {We report on the opinions of 49 forecasting experts on guidelines for extrapolation methods. They agreed that seasonality, trend, aggregation, and discontinuities were key features to use for selecting extrapolation methods. The strong agreement about the importance of discontinuities was surprising because this topic has been largely ignored in the forecasting literature.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90067-J}, issn = {0169-2070}, keywords = {Discontinuities, Forecasting guidelines, Selection criteria, Time series features, regart} } @ARTICLE{CCE+05, author = {Antonio J. Conejo and Javier Contreras and Rosa Esp{\'i}nola and Miguel A. Plazas}, title = {Forecasting electricity prices for a day-ahead pool-based electric energy market}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {435-462}, number = {3}, abstract = {This paper considers forecasting techniques to predict the 24 market-clearing prices of a day-ahead electric energy market. The techniques considered include time series analysis, neural networks and wavelets. Within the time series procedures, the techniques considered comprise ARIMA, dynamic regression and transfer function. Extensive analysis is conducted using data from the PJM Interconnection. Relevant conclusions are drawn on the effectiveness and flexibility of any one of the considered techniques. Furthermore, they are exhaustively compared among themselves.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.12.005}, issn = {0169-2070}, keywords = {Electricity market, Day-ahead price forecasting, Time series models, Neural networks, Wavelet models, regart} } @ARTICLE{CHP98, author = {Robert M. Conroy and Robert S. Harris and Young S. Park}, title = {Fundamental information and share prices in Japan: evidence from earnings surprises and management predictions}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {227-244}, number = {2}, abstract = {Over the period 1985-1993, company-specific earnings fundamentals play a significant role in the pricing of Japanese equities. Moreover, the information content of management forecasts of future earnings is far larger than that conveyed by announcements of current earnings. Despite this base in fundamentals, the dramatic surge and crash of the Japanese market show a changing role for earnings information. During the market run up, price responses to earnings information are lower. In addition, market reactions to good versus bad news change over time. The patterns are broadly consistent with the view that the Japanese market did pay less attention to earnings fundamentals (and especially to bad news) in the alleged bubble period of the late 1980's.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00029-6}, issn = {0169-2070}, keywords = {Stock prices, Management forecasts, Earnings forecast, Japanese equity markets, regart} } @ARTICLE{CHL90, author = {Roger K. Conway and James Hrubovcak and Michael LeBlanc}, title = {A forecast evaluation of capital investment in agriculture}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {509-519}, number = {4}, abstract = {A stochastic coefficients model developed by Swamy and Tinsley is used to forecast agricultural investment. In two sets of out-of-sample forecasts, one for 5 years, the other for 10 years, the Swamy-Tinsley stochastic coefficients model outperforms competing fixed and stochastic coefficients empirical models of agricultural investment for a wide array of risk functions. The Swamy-Tinsley stochastic coefficients investment model forecasts continued declines in net investment for farm machinery, with greater declines toward the end of the forecast period. The Swamy-Tinsley method produced better predictions than both stochastic and fixed-coefficients competitors.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90029-B}, issn = {0169-2070}, keywords = {Agricultural investment, Evaluation, Forecast, Stochastic coefficients, regart} } @ARTICLE{Coomes92, author = {Paul A. Coomes}, title = {A Kalman filter formulation for noisy regional job data}, journal = {International Journal of Forecasting}, year = {1992}, volume = {7}, pages = {473-481}, number = {4}, abstract = {A problem of great concern to regional economic forecasters is how to know the current local economic status given the delays and noise in provisional data. In this paper the structure of revisions to one of the most important regional data sets, local jobs by industry, is analyzed. A Kalman filter formulation is presented that can be used to improve the monthly estimates of jobs in local industries where large subsequent data revisions are most likely. Two data sets, one for the State of Virginia and one for the Louisville MSA, are used to illustrate the technique. The results, while not conclusive, suggest that the technique may be of practical importance in the monitoring and forecasting of employment activity in mining, construction and other industries for which provisional estimates are subject to the greatest later revision.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90031-4}, issn = {0169-2070}, keywords = {Data revisions, Regional employment, Kalman filter, regart} } @ARTICLE{Copeland02, author = {Laurence Copeland}, title = {Exchange Rate Forecasting. Techniques and Applications: Imad A. Moosa, Macmillan Business, London, 2000, ISBN: 0-333-73644-3, pp. 448, �120 (Hardback)}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {153-154}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00127-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Copulsky91, author = {William Copulsky}, title = {A managerial guide to business forecasting : Dennis Ellis and Jay Nathan, (Graceway Publishing Co., Flushing, NY, 1990), paperback, pp. 162.}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {241-241}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90058-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Copulsky91a, author = {William Copulsky}, title = {A short history of the future : W. Warren Wager, (The University of Chicago Press, Chicago, IL, 1989), pp. 323.}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {242-242}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90059-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Copulsky88, author = {William Copulsky}, title = {A guide to forecasting for planners and managers : Raymond E. Willis (Prentice-Hall, Englewood Cliffs, New Jersey , 1987) pp. 404, \$36.63}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {501-502}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90119-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{CWW03, author = {Jonathan J. Corcoran and Ian D. Wilson and J. Andrew Ware}, title = {Predicting the geo-temporal variations of crime and disorder}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {623-634}, number = {4}, abstract = {Traditional police boundaries--precincts, patrol districts, etc.--often fail to reflect the true distribution of criminal activity and thus do little to assist in the optimal allocation of police resources. This paper introduces methods for crime incident forecasting by focusing upon geographical areas of concern that transcend traditional policing boundaries. The computerised procedure utilises a geographical crime incidence-scanning algorithm to identify clusters with relatively high levels of crime (hot spots). These clusters provide sufficient data for training artificial neural networks (ANNs) capable of modelling trends within them. The approach to ANN specification and estimation is enhanced by application of a novel and noteworthy approach, the Gamma test (GT).}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00095-5}, issn = {0169-2070}, keywords = {Crime forecasting, Cluster analysis, Geographic information system, Artificial neural networks, Gamma test, Autoregressive model, regart} } @ARTICLE{98g, author = {Joseph J. Cordes}, title = {Book Review}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {299-300}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00020-X}, issn = {0169-2070}, key = {tagkey1998299}, keywords = {bookrev} } @ARTICLE{CHE86, author = {R. J. Corker and S. Holly and R. G. Ellis}, title = {Uncertainty and forecast precision}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {53-53}, number = {1}, abstract = {Macroeconomic forecasters typically report a single estimate per time period for each macroeconomic variable. But they rarely provide consumers of forecasts with information about the degree of confidence there is in the forecast or the likely range of dispersion of the actual outcome relative to the conditional forecast. Partly this is due to the non-linearity of the model and thus the cost of producing standard error bands. But there is also the problem that a mechanical stochastic simulation may misrepresent the degree of forecast uncertainty because forecasters use non-model information to produce a forecast which is more precise, at least for the immediate future, than the model alone. In this paper we propose a method for generating standard error bands which gives a truer reflection of the forecaster's uncertainty.}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90030-0}, issn = {0169-2070}, keywords = {Macroeconomic models, methodology, adjustments, Confidence intervals, predictions of simultaneous system/exogenous variables, Stochastic forecasting, Forecast error bands, Prior uncertainty, regart} } @ARTICLE{CS04, author = {Valentina Corradi and Norman R. Swanson}, title = {Some recent developments in predictive accuracy testing with nested models and (generic) nonlinear alternatives}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {185-199}, number = {2}, abstract = {Forecasters and applied econometricians are often interested in comparing the predictive accuracy of nested competing models. A leading example of nestedness is when predictive ability is equated with out-of-sampleGrangercausality. In particular, it is often of interest to assess whether historical data from one variable are useful when constructing a forecasting model for another variable, and hence our use of terminology such as out-of-sampleGrangercausality (see, e.g., Ashley, Granger, and Schmalensee [Econometrica 48 (1980) 1149]). In this paper, we examine and discuss three key issues one is faced with when constructing predictive accuracy tests, namely: the contribution of parameter estimation error (PEE), the choice of linear versus nonlinear models, and the issue of (dynamic) misspecification, with primary focus on the latter of these issues. One of our main conclusions is that there are a number of easy-to-apply statistics constructed using out-of-sample conditional moment conditions which are robust to the presence of dynamic misspecification under both hypothesis. We provide some new Monte Carlo findings and empirical evidence based on the use of such tests. In particular, we analyze the finite sample properties of the consistent out-of-sample test of Corradi and Swanson [J. Econ. 110 (2002)] using data generating processes calibrated with US money and output, and we empirically investigate the (non)linear marginal predictive content of money for output. Our Monte Carlo evidence suggests that the tests perform adequately in finite samples, and our empirical evidence suggests that there is no useful (non)linear information in money growth that is not already contained in lags of output growth, when the objective is output growth prediction.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.09.008}, issn = {0169-2070}, keywords = {Conditional p value, Bootstrap, Forecasting, Out-of-sample predictive accuracy, Parameter estimation error, regart} } @ARTICLE{CP10, author = {Julio del Corral and Juan Prieto-Rodriguez}, title = {Are differences in ranks good predictors for Grand Slam tennis matches?}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {551 - 563}, number = {3}, note = {Sports Forecasting}, doi = {10.1016/j.ijforecast.2009.12.006}, issn = {0169-2070}, keywords = {Sports forecasting, Probit models,Prediction intervals,Tennis,Brier scores,Bootstrapping} } @ARTICLE{Cowan02, author = {Adrian M. Cowan}, title = {Data Mining in Finance: Advances in Relational and Hybrid Methods: Boris Kovalerchuk and Evgenii Vityaev (Eds.), Kluwer Academic Publishers, Norwell, Massachusetts, 2000, HB US \$120, ISBN 0-7923-7804-0}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {155-156}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00128-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Cox87, author = {James E. Cox}, title = {An assessment of books relevant to forecasting in marketing}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {515-527}, number = {3-4}, abstract = {A systematic evaluation was done of thirteen books that have relevance for forecasting in marketing. Each book was assessed on several dimensions including: readability, comprehensiveness, organization, mathematical complexity, appropriateness as a textbook, and appropriateness as a reference. Additionally, a comparison was made with respect to depth of coverage for different forecasting methods and for major forecasting concepts.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90049-5}, issn = {0169-2070}, keywords = {Forecasting books, Forecasting book evaluation, regart} } @ARTICLE{Cox86, author = {James E. Cox}, title = {Business forecasting : Charles S. Gross and Robin T. Peterson, 2nd ed. (Houghton Mifflin Company, Boston 1983) pp. 400}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {391-393}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90061-0}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{CJL06, author = {Cox, Jr., Louis A. and David G. Loomis}, title = {Improving forecasting through textbooks -- A 25 year review}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {617-624}, number = {3}, abstract = {In celebration of the International Institute of Forecasters' 25th anniversary, this paper reviews the improvement in forecasting by looking at changes in forecasting textbooks over the last 25 years. Today, more texts are available than ever before to both introductory students and seasoned forecasters and many of these are increasingly specialized. Today's textbook authors are standing on the shoulders of the previous authors while adding original ideas and discussing innovations contained in the more recent forecasting literature. This paper reviews books that should be considered milestones within the forecasting profession. This paper also details changes in the length, presentation, organization, content and pedagogy of forecasting textbooks during the past 25 years. In addition, we review the changes due to the diffusion of forecasting literature into textbooks.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.12.004}, issn = {0169-2070}, keywords = {Forecasting education, Forecasting practice, Forecasting profession, Forecasting textbooks, regart} } @ARTICLE{Cox2002, author = {Cox, Jr., Louis A. and Douglas A. Popken}, title = {A hybrid system-identification method for forecasting telecommunications product demands}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {647-671}, number = {4}, abstract = {A crucial challenge for telecommunications companies is how to forecast changes in demand for specific products over the next 6 to 18 months--the length of a typical short-range capacity-planning and capital-budgeting planning horizon. The problem is especially acute when only short histories of product sales are available. This paper presents a new two-level approach to forecasting demand from short-term data. The lower of the two levels consists of adaptive system-identification algorithms borrowed from signal processing, especially, Hidden Markov Model (HMM) methods [Hidden Markov Models: Estimation and Control (1995) Springer Verlag]. Although they have primarily been used in engineering applications such as automated speech recognition and seismic data processing, HMM techniques also appear to be very promising for predicting probabilities of individual customer behaviors from relatively short samples of recent product-purchasing histories. The upper level of our approach applies a classification tree algorithm to combine information from the lower-level forecasting algorithms. In contrast to other forecast-combination algorithms, such as weighted averaging or Bayesian aggregation formulas, the classification tree approach exploits high-order interactions among error patterns from different predictive systems. It creates a hybrid, forecasting algorithm that out-performs any of the individual algorithms on which it is based. This tree-based approach to hybridizing forecasts provides a new, general way to combine and improve individual forecasts, whether or not they are based on HMM algorithms. The paper concludes with the results of validation tests. These show the power of HMM methods to forecast what individual customers are likely to do next. They also show the gain from classification tree post-processing of the predictions from lower-level forecasts. In essence, these techniques enhance the limited techniques available for new product forecasting.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00069-9}, issn = {0169-2070}, keywords = {Classification, Markov-models, Telecommunications, Combining forecasts, Market forecasting, State-space models, Transition probabilities, regart} } @ARTICLE{CK95, author = {David Cracknell and Michael Knott}, title = {The measurement of price elasticities--the BT experience}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {321-329}, number = {2}, abstract = {The telephony market in the UK has been subject to substantial structural change over the last five years. Examples of this change include the growth of competition, the availability of volume related price discounts, and the introduction of special offers. Under these conditions, the assessment of market response to price changes using elasticities obtained from traditional time series econometric methods becomes invalid, rendering forecasts potentially inaccurate. This paper explores three alternative techniques for estimating price elasticities: the cross-sectional technique, the calculation of implied price sensitivity to special offers, and the calculation of price elasticities of various market segments. Price elasticities will be shown to vary substantially, depending on the method of analysis and situational characteristics (broadly categorised as simple, structural, and special offer). The authors conclude that elasticities should be viewed by managers as instruments one can try to manipulate rather than as fixed parameters.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00587-G}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Crato05, author = {Nuno Crato}, title = {A mild skepticism on nonlinear forecasting: Some comments on the paper by Harvill and Ray}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {729-730}, number = {4}, note = {Nonlinearities, Business Cycles and Forecasting}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.04.003}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Crawford96, author = {Peggy Crawford}, title = {The distortion theory of macro-economic forecasting : Steven Marquard, 1994, (Quorum Books, Westport, CT), US\$59.95, ISBN 0-89930-910-0.}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {180-181}, number = {1}, note = {Probability Judgmental Forecasting}, doi = {http://dx.doi.org/10.1016/0169-2070(96)88195-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{CDL07, author = {David de la Croix and Fr{\'e}d{\'e}ric Docquier and Philippe Li{\'e}geois}, title = {Income growth in the 21st century: Forecasts with an overlapping generations model}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {621-635}, number = {4}, abstract = {We forecast income growth over the period 2000-2050 in the US, Canada, and France. To ground the forecasts on relationships that are as robust as possible to changes in the environment, we use a quantitative theoretical approach which involves calibrating and simulating a general equilibrium model. Compared to existing studies, we allow for life uncertainty and migrations, use generational accounting studies to link taxes and public expenditures to demographic changes, and take into account the interaction between education and work experience. Forecasts show that growth will be weaker over the period 2010-2040. The gap between the US and the two other countries is increasing over time. France will catch-up and overtake Canada in 2020. Investigating alternative policy scenarios, we show that increasing the effective retirement age to 63 would be most profitable for France, reducing the gap between it and the US by one third. A decrease in social security benefits would slightly stimulate growth but would have no real impact on the gap between the countries.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.07.003}, issn = {0169-2070}, keywords = {Aging, Forecast, Computable general equilibrium, Education, Experience, regart} } @ARTICLE{Crone09, author = {Sven F. Crone}, title = {Mining the past to determine the future: Comments}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {456 - 460}, number = {3}, note = {Special Section: Time Series Monitoring}, doi = {10.1016/j.ijforecast.2009.05.022}, issn = {0169-2070} } @ARTICLE{Cullity93, author = {John P. Cullity}, title = {Monitoring business conditions at the CIBCR}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {39-48}, number = {1}, abstract = {In 1981, Geoffrey Moore delivered a keynote address to the First International Symposium on Forecasting in which he made comparisons between the monitoring and forecasting approaches to the business cycle. This paper re-examines the subject: in the following ways. (1) It examines the differences and similarities between the two approaches. (2) It provides information about an ex post test of the forecasting usefulness of an early set of leading indicators. (3) It discusses the use of CIBCR leading and coinciding indexes for countries around the world. (4) It examines the accuracy of forecasts of magnitudes of change in real output made with a long-leading index. (5) It looks at the development of a sequential signal system. (6) It comments on the forecasting of Globescope consensus forecasts.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90052-O}, issn = {0169-2070}, keywords = {Leading index, Coincident index, Six month smoothed, Sequential signals, regart} } @ARTICLE{Cullity88, author = {John P. Cullity}, title = {The business forecasting revolution : F. Gerald Adams, (Oxford University Press, New York, 1986) pp. 265, \$18.95, �9.68}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {287-289}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90083-0}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{CG85, author = {J. David Cummins and Gary L. Griepentrog}, title = {Forecasting automobile insurance paid claim costs using econometric and ARIMA models}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {203-215}, number = {3}, abstract = {Automobile insurance companies in the United States currently utilize simple exponential trend models to forecast paid claim costs, an important variable in ratemaking. This paper tests the performance of econometric and ARIMA models, as well as the current insurance industry method, in forecasting two paid claim cost series. The experiments encompass eight forecast periods ranging from 1974 through early 1983. The results indicate that automobile insurers could significantly improve their forecasts of property damage liability claim costs by adopting econometric models. For bodily injury liability claim costs, the accuracy of the econometric and insurance industry methods is approximately the same, and both outperform the ARIMA models. Overall, a net gain in accuracy could be achieved by adopting econometric models.}, doi = {http://dx.doi.org/10.1016/0169-2070(85)90003-2}, issn = {0169-2070}, keywords = {Automobile insurance, General insurance, Actuarial models, Insurance, Forecasting, ARIMA models, regart} } @ARTICLE{CB97, author = {Justine Cutler and Roderick Brodie}, title = {Comptrack: A competitive tracking software : Hubert Gatignon and Piet Vanden Abeele, 1993, (Scientific Management Systems, Scientific Press) ISBN 0-89426-247-5. The software is supplied with this book}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {137-139}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00685-1}, issn = {0169-2070}, keywords = {prodrev} } @ARTICLE{Dagum89, author = {Estela Bee Dagum}, title = {The future of the forecasting profession}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {155-157}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90082-4}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{DGH+95, author = {P. Dagum and A. Galper and E. Horvitz and A. Seiver}, title = {Uncertain reasoning and forecasting}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {73-87}, number = {1}, abstract = {We develop a probability forecasting model through a synthesis of Bayesian belief-network models and classical time-series analysis. By casting Bayesian time-series analyses as temporal belief-network problems, we introduce dependency models that capture richer and more realistic models of dynamic dependencies. With richer models and associated computational methods, we can move beyond the rigid classical assumptions of linearity in the relationships among variables and of normality of their probability distributions. We apply the methodology to the difficult problem of predicting outcome in critically ill patients. The nonlinear, dynamic behavior of the critical-care domain highlights the need for a synthesis of probability forecasting and uncertain reasoning.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)02009-E}, issn = {0169-2070}, keywords = {Uncertainty, Probability forecasting, Bayesian belief networks, Critical careregart} } @ARTICLE{DHS09, author = {Christian M. Dahl and Henrik Hansen and John Smidt}, title = {The cyclical component factor model}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {119-127}, number = {1}, abstract = {Forecasting using factor models based on large data sets has received ample attention due to the models' ability to increase forecast accuracy with respect to a range of key macroeconomic variables in the US and the UK. However, forecasts based on such factor models do not uniformly outperform the simple autoregressive model when using data from other countries. In this paper we propose to estimate the factors based on the pure cyclical components of the series entering the large data set. Monte Carlo evidence and an empirical illustration using Danish data shows that this procedure can indeed improve on pseudo real time forecast accuracy.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.11.011}, issn = {0169-2070}, keywords = {Factor model, Cyclical components, Estimation, Real time forecasting, regart} } @ARTICLE{DH04, author = {Christian M. Dahl and Svend Hylleberg}, title = {Flexible regression models and relative forecast performance}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {201-217}, number = {2}, abstract = {In this paper, four alternative flexible nonlinear regression model approaches are reviewed and their performance evaluated based on various measures of out-of-sample forecast accuracy. The class of flexible regression model considered includes Neural Networks, Projection Pursuit models and the Random Field regression model approach recently suggested by Hamilton [Econometrica 69 (2001) 537-573]. An empirical illustration is provided, showing that linear models for the US unemployment rate and the growth rate in US industrial production cannot outperform the best flexible nonlinear regression models in terms of out-of-sample forecast accuracy. The results indicate a possible presence of a nonlinear component in the conditional mean function of both time series.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.09.002}, issn = {0169-2070}, keywords = {Flexible regression models, Real-time forecast accuracy, regart} } @ARTICLE{DA89, author = {Stephen Dakin and J. Scott Armstrong}, title = {Predicting job performance: A comparison of expert opinion and research findings}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {187-194}, number = {2}, abstract = {A survey was conducted of New Zealand personnel consultants. Their beliefs about the validity of various selection tools and their claimed usage of these tools was then compared with the validities in a previously published meta-analysis. The experts claimed to use the predictors they believed to be most valid. However, their beliefs about validity were unrelated to empirically demonstrated validities (Spearman's RHO = -0.06). Suggestions were made on the types of research that are needed to improve predictive ability in selection and on the ways in which practitioners can use existing research.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90086-1}, issn = {0169-2070}, keywords = {Employee selection, Forecasting, Job performance, Predictor validity, Research vs. expert opinion, regart} } @ARTICLE{Dalrymple87, author = {Douglas J. Dalrymple}, title = {Sales forecasting practices: Results from a United States survey}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {379-391}, number = {3-4}, abstract = {The paper presents the results of a survey designed to discover how business firms prepare sales forecasts, what methods they prefer, and the accuracy of their predictions. The survey showed that subjective, extrapolation and naive techniques are widely used by American business firms in various forecasting situations. Also, some business firms are reducing forecasting errors by making greater use of computers and seasonal adjustments.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90031-8}, issn = {0169-2070}, keywords = {Accuracy, Business survey of forecasting methods, Computer forecasting, regart} } @ARTICLE{Dana07, author = {Jason Dana}, title = {Is task complexity an exception to the superiority of mechanized judgement, or a barrier to it?}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {463-464}, number = {3}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.05.010}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Danaher94, author = {Peter J. Danaher}, title = {Comparing naive with econometric market share models when competitors' actions are forecast}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {287-294}, number = {2}, abstract = {While econometric market share models have been shown to be useful to managers as descriptive tools, controversy exists over their use in forecasting. As a result, a criterion as been developed which can be used to assess whether or not a naive model will outperform an econometric model for market share forecasting. However, this criterion ignored the effects of having to forecast competitors' actions, as would be demanded in a real-life market share forecasting application. In this paper previous results by the author are extended to cover the situation where competitors' actions must also be forecast. The results show that having to forecast competitors' actions is very demanding for econometric models. Consequently, the naive model is likely to be preferred in most market share forecasting situations where competitors' actions are forecast. Econometric models will be preferred only when they fit the data extremely well for all brands in the market.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90008-6}, issn = {0169-2070}, keywords = {Competition, Econometric model, Forecasting, Market share, Mean squared error, Naive modelregart} } @ARTICLE{DB92, author = {Peter J. Danaher and Roderick J. Brodie}, title = {Predictive accuracy of simple versus complex econometric market share models: Theoretical and empirical results}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {613-626}, number = {4}, abstract = {While econometric market share models have been shown to be useful to managers as descriptive tools, controversy exists over their use in forecasting. For instance, Brodie and de Kluyver (1987) showed, using data for 15 brands in three markets, that naive forecasting will often do better than econometric models when predicting market share. In the discussion of the paper Hagerty (1987) showed theoretically that these results were not surprising. This paper extends the analysis of Hagerty (1986, 1987) by deriving conditions under which naive econometric models are expected to do better than complex models when predicting market share. The results show that the naive model is preferred when the number of parameters used in the econometric model is too large or when the number of points used to fit the models is too small. We also show that the decision to go for the naive or econometric model is not greatly influenced by the number of points withheld for model validation, under the assumption of similarity of correlations between predictor variables in the estimation and validation data.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90070-P}, issn = {0169-2070}, keywords = {Econometric model, Forecasting, Market share, Mean squared error, Naive modelregart} } @ARTICLE{DM92, author = {Byron J. Dangerfield and John S. Morris}, title = {Top-down or bottom-up: Aggregate versus disaggregate extrapolations}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {233-241}, number = {2}, abstract = {Two approaches have been suggested for forecasting items in a product line. The top-down (TD) approach uses an aggregate forecast model to develop a summary forecast, which is then allocated to individual items on the basis of their historical relative frequency. The bottom-up (BU) approach employs an individual forecast model for each of the items in the family. The present study compares these two approaches by using over 15,000 aggregate series constructed by combining individual series from the M-competition database. The effects of correlation between individual items and the relative frequency of individual items in the family are examined. In most situations, BU forecasting of family items produces more accurate forecasts.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90121-O}, issn = {0169-2070}, keywords = {Family forecasts, Top-down forecasts, Aggregate forecasts, M-competition, regart} } @ARTICLE{DS00, author = {Georges A. Darbellay and Marek Slama}, title = {Forecasting the short-term demand for electricity: Do neural networks stand a better chance?}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {71-83}, number = {1}, abstract = {We address a problem faced by every supplier of electricity, i.e. forecasting the short-term electricity consumption. The introduction of new techniques has often been justified by invoking the nonlinearity of the problem. Our focus is directed to the question of deciding whether the problem is indeed nonlinear. First, we introduce a nonlinear measure of statistical dependence. Second, we analyse the linear and the nonlinear autocorrelation functions of the Czech electric consumption. Third, we compare the predictions of nonlinear models (artificial neural networks) with linear models (of the ARMA type). The correlational analysis suggests that forecasting the short-term evolution of the Czech electric load is primarily a linear problem. This is confirmed by the comparison of the predictions. In the light of this case study, the conditions under which neural networks could be superior to linear models are discussed.}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00045-X}, issn = {0169-2070}, keywords = {Energy forecasting, Time series, Nonlinearity, Artificial neural networks, ARIMA models, regart} } @ARTICLE{DDG94, author = {Chanda Ghose Dasgupta and Gary S. Dispensa and Sanjoy Ghose}, title = {Comparing the predictive performance of a neural network model with some traditional market response models}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {235-244}, number = {2}, abstract = {The study compares the performance of two statistical market response models (a logistic regression model and a discriminant analysis model) to that of a back propagation neural network model. The comparative performances of these models are evaluated with respect to their ability to identify consumer segments based upon their willingness to take financial risks and to purchase a non-traditional investment product. The empirical analysis is conducted using two different real-world individual level cross-sectional data sets related to the marketing of financial services. If we rank order the performance of these models, we find that the neural network model performs better than the other two models. However, the level of performance is not significantly higher than those of the other models. This is in contradiction to the findings in the financial industry applications in the literature, where neural network models have, in general, significantly outperformed traditional statistical response models. We believe that our study is one of the first applications of neural network models using individual level cross-sectional survey data for predicting market response and that our findings have opened the doors to further research about the applicability of neural network modelling using individual level cross-sectional data, as opposed to using aggregate company level data.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90004-3}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{Davidson01, author = {James Davidson}, title = {Econometric Modelling: Techniques and Applications,: Sean Holly and Martin Weale (Eds.) (2000), Cambridge: Cambridge University Press, x+296 pages. ISBN 0 521 65069 0 Hardback �45, \$74.95.}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {302-303}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00086-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Davies06, author = {Antony Davies}, title = {A framework for decomposing shocks and measuring volatilities derived from multi-dimensional panel data of survey forecasts}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {373-393}, number = {2}, abstract = {This work applies previously published frameworks developed for analyzing multi-dimensional panel data of survey forecasts to IPD forecasts from the Survey of Professional Forecasters. The paper expands on these frameworks, demonstrates that the frameworks imply the existence of new and richer measures of shocks and volatilities, and shows how these measures can be extracted from multi-dimensional forecast panels. Three distinct types of economic shocks (cumulative shocks, cross-sectional shocks, and discrete shocks) and implied volatility measures based on these shocks are calculated for IPD inflation over the period 1969 through 2004. GMM tests for forecaster biases are conducted using the expanded framework.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.09.007}, issn = {0169-2070}, keywords = {Panel data, Shocks, Volatility, Multidimensional, Survey of Professional Forecasters, Inflation, Rationality, Error measures, Evaluating forecasts, Inflation forecasting, Volatility forecasting, regart} } @ARTICLE{DM07, author = {Donna F. Davis and John T. Mentzer}, title = {Organizational factors in sales forecasting management}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {475-495}, number = {3}, abstract = {Over the past three decades, significant advances have been made in developing sales forecasting techniques that more accurately reflect marketplace conditions. However, surveys of sales forecasting practice continue to report only marginal gains in sales forecasting performance. This gap between theory and practice has been identified as a significant issue for sales forecasting research. The forecasting literature suggests that the issue should be addressed by examining organizational factors in sales forecasting management. In this paper, we propose a theory-based framework of organizational factors in sales forecasting management that integrates research on organizational climate, organizational capabilities, organizational learning and sales forecasting. Empirical evidence of the fit between sales forecasting practice and the conceptual framework is provided by a content analysis of interview texts from an extensive field study of sales forecasting management that involved 516 practitioners at 18 global manufacturing firms.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.02.005}, issn = {0169-2070}, keywords = {Sales forecasting practice, Sales forecasting capability, Organizational behavior, Performance measurement, Sales forecasting climate, Content analysis, regart} } @ARTICLE{DFL+94, author = {Robyn Dawes and Robert Fildes and Michael Lawrence and Keith Ord}, title = {The past and the future of forecasting research}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {151-159}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90057-4}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Dawes86, author = {Robyn M. Dawes}, title = {Forecasting one's own preference}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {5-14}, number = {1}, abstract = {This paper compares two methods of making preference judgments based on multi-attribute inputs: (i) an intuitive global evaluation of each input in its totality, (ii) a separate evaluation of each input attribute weighted intuitively to form a linear composite. When judges in psychological, medical and business settings have been asked to make predictive judgments on the basis of multi-attribute input, method (ii) has proved to be superior -- with unerring consistency. People are quite poor at making intuitive global judgments based on psychologically incomparable attributes and much poorer than they believe themselves to be. Nevertheless, for various illusiory reasons (e.g., biased feedback, overestimation of the predictability inherent in the situation), people prefer method (i). A preference judgment can be conceptualized as a predictive judgment of one's future `state of mind.' Thus, the research findings strongly suggest that when making preference judgments method (ii) is superior, but will remain less popular than method (i).}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90027-0}, issn = {0169-2070}, keywords = {Forecasting, Preference, Intuition, Linear models, Random weights, Ad hoc weights, Ben Franklin, Decision, regart} } @ARTICLE{Deadman03, author = {Derek Deadman}, title = {Forecasting residential burglary}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {567-578}, number = {4}, abstract = {Following the work of Dhiri et al. [Modelling and predicting property crime trends. Home Office Research Study 198 (1999). London: HMSO] at the Home Office predicting recorded burglary and theft for England and Wales to the year 2001, econometric and time series models were constructed for predicting recorded residential burglary to the same date. A comparison between the Home Office econometric predictions and the less alarming econometric predictions made in this paper identified the differences as stemming from the particular set of variables used in the models. However, the Home Office and one of our econometric models adopted an error correction form which appeared to be the main reason why these models predicted increases in burglary. To identify the role of error correction in these models, time series models were built for the purpose of comparison, all of which predicted substantially lower numbers of residential burglaries. The years 1998-2001 appeared to offer an opportunity to test the utility of error correction models in the analysis of criminal behaviour. Subsequent to the forecasting exercise carried out in 1999, recorded outcomes have materialised, which point to the superiority of time series models compared to error correction models for the short-run forecasting of property crime. This result calls into question the concept of a long-run equilibrium relationship for crime.}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00091-8}, issn = {0169-2070}, keywords = {Residential burglary, Error correction, Time series forecasting, regart} } @ARTICLE{Dennis85, author = {Robin L. Dennis}, title = {Forecasting and mediation: Colorado and the clean air act}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {297-306}, number = {3}, abstract = {This paper presents an analysis of discussions designed to resolve technical differences, a process known as data mediation, between originators of divergent forecasts. Differing forecasts of future urban air quality by several agencies led to debate over revisions to the 1977 Clean Air Act proposed during the 97th Congress. Researchers for General Motors, the U.S. Environmental Protection Agency, and the State of Colorado disagreed over the ability of Denver, Colorado ever to attain the health standards for carbon monoxide if automobile emission for high altitude were relaxed. Data mediation led to resolution of some differences. The search for disconfirming evidence was a key element of the successful data mediation. In examining the process of that mediation, it was found that the search for disconfirming evidence requires: (1) balance of scientific expertise and credibility; (2) explicitness of assumptions; and (3) segmenting and bounding of the problem.}, doi = {http://dx.doi.org/10.1016/0169-2070(85)90009-3}, issn = {0169-2070}, keywords = {Air quality forecasts, Conflicting forecasts, Resolving forecast differences, Carbon monoxide forecasts, regart} } @ARTICLE{DeRoeck91, author = {Richard DeRoeck}, title = {Is there a gap between forecasting theory and practice? A personal view}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {1-2}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90027-S}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Deschamps04, author = {Elaine Deschamps}, title = {The impact of institutional change on forecast accuracy: A case study of budget forecasting in Washington State}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {647-657}, number = {4}, abstract = {This paper explores the relationship between institutional change and forecast accuracy via an analysis of the entitlement caseload forecasting process in Washington State. This research extends the politics of forecasting literature beyond the current area of government revenue forecasting to include expenditure forecasting and introduces an in-depth longitudinal study to the existing set of cross-sectional studies. Employing a fixed-effects model and ordinary least squares regression analysis, this paper concludes that the establishment of an independent forecasting agency and subsequent formation of technical workgroups improve forecast accuracy. Additionally, this study finds that more frequent forecast revisions and structured domain knowledge improve forecast accuracy.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.11.009}, issn = {0169-2070}, keywords = {Forecast accuracy, Politics of forecasting, Judgmental forecasting, Government forecasting, Institutional change, regart} } @ARTICLE{DGT94, author = {Melinda Deutsch and Clive W. J. Granger and Timo Ter{\"a}svirta}, title = {The combination of forecasts using changing weights}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {47-57}, number = {1}, abstract = {This paper considers the combination of forecasts using changing weights derived from switching regression models or from smooth transition regression models. The regimes associated with the switches may not be known to the forecaster and thus need to be estimated. Several approaches to this problem are considered. In two empirical examples, these time-varying combining procedures produced smaller, in some cases substantially smaller, out-of-sample squared forecast errors than those obtained using the simple linear combining model.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90049-3}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{DHC95, author = {Aaron R. Dewispelare and L. Tandy Herren and Robert T. Clemen}, title = {The use of probability elicitation in the high-level nuclear waste regulation program}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {5-24}, number = {1}, abstract = {Expert judgement elicitation is expected to be used in the performance assessments (PA) of the long-term behavior of high-level waste (HLW) geologic repositories. As a preparation for an effective review of the U.S. Department of Energy (DOE) PA, the Nuclear Regulatory Commission (NRC) is evaluating the mechanics of eliciting expert judgements. One of the objectives of this evaluation is to explore techniques for generating and aggregating probabilistic judgements of future conditions at the proposed HLW repository at Yucca Mountain, Nevada. An actual elicitation was conducted as an aid to these evaluations. This paper documents this probabilistically centered elicitation and subsequent activities to explore aggregation of opinion techniques. Future climate in the Yucca Mountain, Nevada vicinity was selected as the topic for elicitation. Personnel from the NRC and Center for Nuclear Waste Regulatory Analyses (CNWRA) defined the climatic parameters of interest in conjunction with a panel of five expert climatologists. Individual elicitations were performed with each climatologist to produce probabilistic estimates of each parameter at seven points of time in the future. The elicitations employed the fractile technique to generate cumulative probability distributions representing the uncertainty in the predictions. After the individual elicitations, a group session was conducted to explore aggregation and consensus methods.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)02006-B}, issn = {0169-2070}, keywords = {Expert elicitation, Expert judgement, Subjective probability assessment, Climate, Uncertainty, Opinion aggregation, regart} } @ARTICLE{Dhrymes89, author = {Phoebus J. Dhrymes}, title = {Handbook of econometrics : Z. Griliches and M.D. Intriligator, eds., Vol. 2 (North Holland, Amsterdam, 1984) �67.19, �64.56, pp. 686}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {143-144}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90078-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Dhrymes88, author = {Phoebus J. Dhrymes}, title = {Handbook of econometrics : Z. Griliches and M.D. Intrilligator, eds. vol. 2 (North Holland, Amsterdam, 1984) pp. 686 + xxvi. �67.19, XXX65.00}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {298-300}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90090-8}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{DP88, author = {Phoebus J. Dhrymes and Stavros C. Peristiani}, title = {A comparison of the forecasting performance of WEFA and ARIMA time series methods}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {81-101}, number = {1}, abstract = {This paper examines the forecasting performance of the Wharton model (MARK III) over the period 1973 through 1975 and compares it with that of ARIMA models' performance over the same period. Despite strong intimation in the literature to the contrary, we find that this econometric model, at least, exhibits greater accuracy in every respect relative to ARIMA methods, in terms of its forecasts cum constant adjustments. When constant adjustments are disallowed then its forecasts are still more accurate than ARIMA forecasts over a 4- and 8-quarter forecasting horizon, but less accurate over a 1-quarter horizon. The comparison was carried out over twenty three macrovariables, under a slight handicap for the Wharton Model, in that the latter's parameters were estimated over a sample ending in 1969.3 while the ARIMA models were reidentified and reestimated as of the quarter immediately preceding the forecast.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90011-8}, issn = {0169-2070}, keywords = {Forecasting accuracy, Wharton model, Forecasting horizon, Exogenous variables, Parametric stability, Comparative accuracy, causal, time series, regart} } @ARTICLE{DT98, author = {Phoebus J. Dhrymes and Dimitrios D. Thomakos}, title = {Structural VAR, MARMA and open economy models}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {187-198}, number = {2}, abstract = {In this paper we examine a number of issues in the context of structural VAR and MARMA open economy macro models. In particular, we examine whether VAR or MARMA is the more appropriate specification; whether expectations are forward or backward looking, and whether a number of restrictions imposed on such models are supported by empirical evidence. Prior restrictions are imposed by means of Lagrange multipliers, which makes many of the tests noted above routine.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00026-0}, issn = {0169-2070}, keywords = {Structural VAR, Structural MARMA, Open economy macro, Rational expectations, Just- and over-identification, Lagrange multipliers, regart} } @ARTICLE{Diamantopoulos02, author = {A. Diamantopoulos}, title = {Research on Forecasting}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {479-480}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00003-1}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{DW99, author = {Adamantios Diamantopoulos and Heidi Winklhofer}, title = {The impact of firm and export characteristics on the accuracy of export sales forecasts: evidence from UK exporters}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {67-81}, number = {1}, abstract = {The empirical literature on forecasting practice has hardly distinguished between export and domestic sales forecasting. This is surprising given the importance of exporting for companies and the additional difficulties involved in preparing export as opposed to home market forecasts. Drawing from the forecasting and export literatures, this study examines several linkages between firm and export characteristics and the accuracy of short- and medium-term export sales forecasts (as captured by self-reported MAPEs). Using survey data derived from UK exporters in the manufacturing sector and a multivariate analytical framework, the results indicate that export experience (as reflected in the firm's stage in the export life cycle), export diversity (as reflected in the number of export markets served) and the turbulence of the export environment are the key variables affecting export sales forecast accuracy. The implications for the study of export sales forecasting practice are considered and future research directions suggested.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00069-7}, issn = {0169-2070}, keywords = {Exporting, Sales forecasting, Surveys, regart} } @ARTICLE{Diebold89, author = {Francis X. Diebold}, title = {Forecast combination and encompassing: Reconciling two divergent literatures}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {589-592}, number = {4}, abstract = {The relationship of forecast combination to recent developments in the theory and practice of model selection (in particular, the encompassing literature) is explored, the pragmatic virtues of forecast combination are argued, and a synthesis is attempted. Promising areas for future research, particularly exploration and development of forecast combination methodologies that facilitate `shrinkage' of estimated combining weights toward a measure of central tendency, are also discussed.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90014-9}, issn = {0169-2070}, keywords = {Forecasting, Prediction, Pooling, Model selection, Shrinkage estimation, regart} } @ARTICLE{DP90, author = {Francis X. Diebold and Peter Pauly}, title = {The use of prior information in forecast combination}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {503-508}, number = {4}, abstract = {Simple averages often, but not always, outperform more sophisticated optimal forecast composites. We used Bayesian shrinkage techniques to allow the incorporation of prior information into the estimation of combining weights; the estimated combining weights were coaxed or shrunken toward equality but were not forced to be exactly equal. The least-squares and prior (i.e., arithmetic average) weights then emerged as polar cases for the posterior mean; the exact location depended on prior precision, which was estimated from the data. In a simple example involving U.S. GNP forecasts, a large amount of shrinkage was found to be optimal.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90028-A}, issn = {0169-2070}, keywords = {Bayesian, Pooling, Prediction, Shrinkage, regart} } @ARTICLE{Dielman86, author = {Terry E. Dielman}, title = {The theory and practice of econometrics}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {245-246}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90119-6}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{DR94, author = {Terry E. Dielman and Elizabeth L. Rose}, title = {Forecasting in least absolute value regression with autocorrelated errors: a small-sample study}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {539-547}, number = {4}, abstract = {Least absolute value (LAV) regression is a robust alternative to ordinary least squares (OLS) and is particularly useful when model disturbances follow distributions that are nonnormal and subject to outliers. The performance of the OLS estimator when the disturbances are autocorrelated has been studied extensively, but the performance of the LAV estimator in the presence of serial correlation is less well established. In this research, we study the forecasting performances of OLS- and LAV-based models for simple time series regression when the errors are autocorrelated. Monte Carlo simulation methods are used to compare the forecasting accuracies of the different models. A least absolute value analogue of the Prais-Winsten correction possesses an appealing robustness for the context under consideration.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90022-1}, issn = {0169-2070}, keywords = {Robust regression, L1 regression, Least absolute deviations, Serial correlation, Prais-Winsten correction, regart} } @ARTICLE{Dijk06, author = {Dick Van Dijk}, title = {Paul D. McNelis, Neural networks in finance--gaining predictive edge in the market, Elsevier Academic Press (2005) ISBN 0-12-485967-4 hardcover, 243 pages.}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {407-408}, number = {2}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.10.001}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{OeM95, author = {Dilek{\"O}nkal and Gulnur Muradoglu}, title = {Effects of feedback on probabilistic forecasts of stock prices}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {307-319}, number = {2}, abstract = {This paper reports the results of an experiment in stock-price forecasting that investigated the effects of feedback on various dimensions of probability forecasting accuracy. Three types of feedback were used: (1) simple outcome feedback, (2) outcome feedback presented in the task format, and (3) performance feedback in the form of an overall accuracy score in addition to detailed calibration information. While calibration improved for all the feedback groups, forecasters' skill was found to improve only for the task-formated outcome feedback and performance feedback groups (but not for the simple outcome feedback group). Finally, the forecasters in the performance feedback group also improved their mean slope and mean probability scores, an effect not observed in the other feedback groups. It is suggested that, in a dynamic environment like the stock market, probability forecasting offers distinct advantages by providing an important channel of communication between the forecasters and the users of financial information.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)00572-T}, issn = {0169-2070}, keywords = {Probability forecasting, Judgmental forecasting, Stock-price forecasting, Outcome feedback, Performance feedback, Calibration, regart} } @ARTICLE{DP04, author = {Mark J. Dixon and Peter F. Pope}, title = {The value of statistical forecasts in the UK association football betting market}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {697-711}, number = {4}, abstract = {In this paper, we evaluate the economic significance of statistical forecasts of UK Association Football match outcomes in relation to betting market prices. We present a detailed comparison of odds set by different bookmakers in relation to forecast model predictions, and analyse the potential for arbitrage across firms. We also examine extreme odds biases. A detailed re-examination of match result odds and a new examination of correct score odds for the period 1993 to 1996 suggest that the market is inefficient.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.12.007}, issn = {0169-2070}, keywords = {Statistical forecast, Score odd, Firm, regart} } @ARTICLE{DC88, author = {Robert H. Doktor and Susan M. Chandler}, title = {Limits of predictability in forecasting in the behavioral sciences}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {5-14}, number = {1}, abstract = {A series of methodological problems in forecasting which arise out of the humanness of the predictor and/or predictee are reviewed. These include (1) perceptual disordering, in which the imperfect nature of data collected by human sensation is investigated, (2) model disordering, in which the imperfect nature of models and theories arising out of human information processing limitations is investigated, and lastly, (3) obtrusive reactive disordering, in which the human tendencies of the predictee, to guess the forecast, and to alter his or her behavior so as to reinforce or interfere with the forecast, are explored. The implications of these methodological dilemmas for forecasting are discussed.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90006-4}, issn = {0169-2070}, keywords = {Behavioral forecasting, Reflexive prediction, Perceptual disordering, Model disordering, Human information processing, Judgement under uncertainty, regart} } @ARTICLE{DO08, author = {Jurgen A. Doornik and Marius Ooms}, title = {Multimodality in GARCH regression models}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {432-448}, number = {3}, abstract = {It is shown empirically that mixed autoregressive moving average regression models with generalized autoregressive conditional heteroskedasticity (Reg-ARMA-GARCH models) can have multimodality in the likelihood that is caused by a dummy variable in the conditional mean. Maximum likelihood estimates at the local and global modes are investigated and turn out to be qualitatively different, leading to different model-based forecast intervals. In the simpler GARCH(p,q) regression model, we derive analytical conditions for bimodality of the corresponding likelihood. In that case, the likelihood is symmetrical around a local minimum. We propose a solution to avoid this bimodality.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.06.002}, issn = {0169-2070}, keywords = {ARIMA models, Dummy variable, Forecasting practice, GARCH models, Inflation forecasting, Intervention analysis, Multimodality, Outliers, regart} } @ARTICLE{DKO+08, author = {V. Dordonnat and S.J. Koopman and M. Ooms and A. Dessertaine and J. Collet}, title = {An hourly periodic state space model for modelling French national electricity load}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {566-587}, number = {4}, abstract = {We present a model for hourly electricity load forecasting based on stochastically time-varying processes that are designed to account for changes in customer behaviour and in utility production efficiencies. The model is periodic: it consists of different equations and different parameters for each hour of the day. Dependence between the equations is introduced by covariances between disturbances that drive the time-varying processes. The equations are estimated simultaneously. Our model consists of components that represent trends, seasons at different levels (yearly, weekly, daily, special days and holidays), short-term dynamics and weather regression effects, including nonlinear functions for heating effects. The implementation of our forecasting procedure relies on the multivariate linear Gaussian state space framework, and is applied to the national French hourly electricity load. The analysis focuses on two hours, 9 AM and 12 PM, but forecasting results are presented for all twenty-four hours. Given the time series length of nine years of hourly observations, many features of our model can be estimated readily, including yearly patterns and their time-varying nature. The empirical analysis involves an out-of-sample forecasting assessment up to seven days ahead. The one-day ahead forecasts from forty-eight bivariate models are compared with twenty-four univariate models, one for each hour of the day. We find that the implied forecasting function depends strongly on the hour of the day.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.08.010}, issn = {0169-2070}, keywords = {Kalman filter, Maximum likelihood estimation, Seemingly Unrelated Regression Equations, regart} } @ARTICLE{DC97, author = {Mark S. Dougherty and Mark R. Cobbett}, title = {Short-term inter-urban traffic forecasts using neural networks}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {21-31}, number = {1}, abstract = {Back-propagation neural networks were trained to make short-term forecasts of traffic flow, speed and occupancy in the Utrecht/Rotterdam/Hague region of The Netherlands. A problem which had to be faced when designing the system was the vast number of possible input parameters. Whilst neural networks which utilised all available inputs performed well, their size made them impractical for implementation. A technique of stepwise reduction of network size was developed by elasticity testing the large neural networks, showing a way of overcoming this difficulty. Results for occupancy and flow forecasts by this method show some promise, but do not out-perform naive predictors. Forecasts of vehicle speed were much less successful, perhaps because of the distorting effect of slow moving vehicles, particularly in low flow conditions. The elasticity tests were found to be useful, not only as a means of enabling network size reduction, but as a means of interpreting the neural network model.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00697-8}, issn = {0169-2070}, keywords = {Neural networks, Back-propagation, Traffic, Elasticity, regart} } @ARTICLE{DL97, author = {Michael R. Dowd and James P. LeSage}, title = {Analysis of spatial contiguity influences on state price level formation}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {245-253}, number = {2}, abstract = {Economists frequently ignore the spatial dimension of market activity, especially in macroeconomic analysis which tends to focus on aggregate variables. Using annual implicit price deflator time series for the 48 continental states, we carry out tests for the importance of geographic location in price-level determination. Spatial contiguity relationships between the states (geographic location) are shown to provide significant power in explaining historical variation in prices across states. The policy implications for local businesses trying to draw inferences regarding future price levels are that aggregate national information on the implicit price deflator (inflation) can be greatly enhanced by taking into account regional price-level information.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00714-5}, issn = {0169-2070}, keywords = {Bayesian methods, Time series, VAR, Prior information, regart} } @ARTICLE{DB07, author = {Ning Du and David V. Budescu}, title = {Does past volatility affect investors' price forecasts and confidence judgements?}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {497-511}, number = {3}, abstract = {This study investigates the influence of past volatility on individual investors' forecasting behavior. We conducted two experiments in which we used real stock prices to construct low- and high-volatility time series, and asked participants to make both point estimates and interval forecasts of future values. We focus on two main aspects of investors' future expectations: (1) forecasts of future price, and (2) subjective confidence of future stock price, which includes 50%, 70% and 90% confidence intervals. Past volatility has a weak effect on future forecasts that are sensitive to minor changes in the characteristics of price series. We found strong evidence that low past volatility increases participants' confidence and improves forecast accuracy. The calibration of the confidence intervals was not affected by the stocks' volatility. However, most confidence intervals were skewed, suggesting that participants use asymmetric confidence intervals to hedge their price forecasts.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.03.003}, issn = {0169-2070}, keywords = {Calibration, Judgemental forecasting, Overconfidence, Investment, Volatility, regart} } @ARTICLE{DH03, author = {Agustin Duarte and Ken Holden}, title = {The business cycle in the G-7 economies}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {685-700}, number = {4}, abstract = {In this paper the Hodrick-Prescott filter is used to decompose real GDP for the G7 countries into cyclical and trend components. The resulting series of cyclical components are then examined for static relationships, using correlations and graphs; long-run relationships using autoregressive-distributed lag models; and short-run relationships, using error-correction models. The main result is that the patterns of cyclical behaviour changed following the oil price shocks in the 1970s. Since 1980, cyclical fluctuations have been smaller as a result of a decline in synchronisation of the cycles in the G7. Two separate cycles seem to be developing since 1990. One is for Germany, Italy and France, whilst the other is for the US, UK and Canada. Within each of these groups there are both long-run and short-run relationships between the cyclical components of GDP.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00074-2}, issn = {0169-2070}, keywords = {Business cycle, Hodrick-Prescott filter, Error-correction model, Autoregressive-distributed lag models, regart} } @ARTICLE{DVP05, author = {Agustin Duarte and Ioannis A. Venetis and Ivan Paya}, title = {Predicting real growth and the probability of recession in the Euro area using the yield spread}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {261-277}, number = {2}, abstract = {Although the spread has been established as a leading indicator of economic activity, recent studies in US and European Union (EU) countries have documented, theoretically and empirically, that the term spread-output growth relationship may not be stable over time and it may be subjected to nonlinearities. Using aggregate data for the Euro area over the period 1970:1-2000:4, we applied linear regression as well as nonlinear models to examine the predictive accuracy of the term spread-output growth relationship. Our results confirm the ability of the yield curve as a leading indicator. Moreover, significant nonlinearity with respect to time and past annual growth is detected, outperforming the linear model in out-of-sample forecasts of 1-year-ahead annual growth. Furthermore, probit models that use the EMU and US yield spreads are successful in predicting EMU recessions.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.09.008}, issn = {0169-2070}, keywords = {Term spread and real growth, Threshold models, Recession, Forecasting accuracy, regart} } @ARTICLE{DF88, author = {Donald H. Dutkowsky and William G. Foote}, title = {Forecasting discount window borrowing}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {593-603}, number = {4}, abstract = {This paper compares the predictive performance of five recent models of banks' demand for borrowed reserves using post-sample simulation. The findings indicate that models which incorporate observed nonlinearity and switching in the borrowings-interest rate spread relationship outperform the linear nonswitching model. However, the best performance is obtained from the model in which switching and aggregation are considered in the theoretical derivation. Forecasting the level of borrowed reserves is critical to the FOMC reserve targeting procedure. Hence, a comparison of model robustness and stability using post-sample simulation provides useful information to the FOMC in its search for a reliable borrowed reserves demand model.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90136-7}, issn = {0169-2070}, keywords = {Discount window borrowing, Switching regression, Post-sample simulation, Nonlinear forecasting models, regart} } @ARTICLE{Doepke01, author = {J{\"o}rg D{\"o}pke}, title = {Macroeconomic forecasts and the nature of economic shocks in Germany}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {181-201}, number = {2}, abstract = {The paper elaborates on the sources of macroeconomic forecast errors in Germany covering a time period ranging from 1963 to 1999. The joint predictions of the so-called `six leading' research institutes are analyzed. The forecast errors are discussed within an aggregate demand/supply scheme. Structural vector autoregressive models are estimated to identify the shocks underlying the business cycle. The empirical results suggest that, in general, the shocks are helpful in explaining the forecast errors. However, the correlations are rather weak. In addition, lagged shocks help also to explain the forecast errors of the institutes. This is in line with previous evidence that forecasters' expectations are not rational.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00080-2}, issn = {0169-2070}, keywords = {Forecast error evaluation, Structural VARs, Business cycles, regart} } @ARTICLE{DF06, author = {J{\"o}rg D{\"o}pke and Ulrich Fritsche}, title = {When do forecasters disagree? An assessment of German growth and inflation forecast dispersion}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {125-135}, number = {1}, abstract = {Based on a panel of German professional forecasts for 1970-2004 we analyse the dispersion of growth and inflation forecasts. Forecast dispersion varies over time and is particularly high before and during recessions. There is no clear link between forecast dispersion and the subsequent forecast error. Forecast dispersion is positively correlated with the volatility of macroeconomic variables, but not necessarily with the level of the same variables. We interpret this finding to be evidence in favour of the notion that forecasters do not share a common belief about what is an adequate model of the economy. In particular, the assessment of the effects of monetary policy seems to be the prime suspect for diverging beliefs regarding an appropriate model of the economy.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.05.006}, issn = {0169-2070}, keywords = {Consensus forecast, Disagreement, Uncertainty, Germany, regart} } @ARTICLE{EH04, author = {Joshy Z. Easaw and Saeed M. Heravi}, title = {Evaluating consumer sentiments as predictors of UK household consumption behavior: Are they accurate and useful?}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {671-681}, number = {4}, abstract = {This paper investigates empirically whether consumer sentiments indices, based on surveys complied by GfK, forecast household consumption types for the UK. Firstly, we use a quantitative equation approach to assess whether the indices are able to forecast household consumption growth in addition to traditional variables, which are included as control variables. Subsequently, using qualitative directional analysis, we investigate whether the indices are accurate and useful predictors as well. We find that, broadly speaking, both the headline, or aggregate, and the major purchasing indices have some predictive powers in addition to the control variables and are also directionally accurate and useful.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.12.006}, issn = {0169-2070}, keywords = {Consumer sentiments, Survey data, Forecastability, Household consumption behavior, Directional analysis, regart} } @ARTICLE{Easingwood89, author = {Christopher J. Easingwood}, title = {An analogical approach to the long term forecasting of major new product sales}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {69-82}, number = {1}, abstract = {This article shows that new product sales follow a wide variety of diffusion patterns. However, some new products may exhibit diffusions that are characteristic of a particular group of products. If this is so, then the sales of a new product may be unfolding along a predictable path. This hypothesis was tested using sales of color television sets among Western European countries. Forecasts for three-and five-years-ahead were made using just the first four or six years' data. The bases of the projections were pre-forecast simulated estimates of diffusion `shape'. The results obtained were encouraging. It is shown that the methodology approaches the best achievable using trend-based projections of this kind.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90065-4}, issn = {0169-2070}, keywords = {Diffusion, Long term forecasting, Consumer durables, Analogy, Diffusion model, regart} } @ARTICLE{EU10, author = {Stephen Easton and Katherine Uylangco}, title = {Forecasting outcomes in tennis matches using within-match betting markets}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {564 - 575}, number = {3}, note = {Sports Forecasting}, doi = {10.1016/j.ijforecast.2009.10.004}, issn = {0169-2070}, keywords = {Prediction markets, Market efficiency,Market microstructure,Betting exchange,Betfair} } @ARTICLE{EV87, author = {Hali J. Edison and Erling V{\aa}rdal}, title = {Optimal currency basket in a world of generalized floating : An application to the Nordic countries}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {81-96}, number = {1}, abstract = {This paper derives optimal weights for a currency basket taking into consideration the objective of policymakers in the Nordic countries. The analysis is based on the work of Branson and Katseli and Lipschitz and Sundararajan. This paper derives both export share weights by using a simple multi-country model and basket weights by assuming that the objective of the policymakers is to minimize fluctuations in the production of exports. The results show that only under special circumstances are the two weights the same. The basket weights tend to be functions of export weights and other factors such as the covariances of relative prices and exchange rate. Using the formulas derived in the paper, various optimal basket calculations are made for Norway, Finland, and Sweden.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90080-X}, issn = {0169-2070}, keywords = {Exchange rates, Currency baskets, Effective exchange rates, regart} } @ARTICLE{EK93, author = {Per-Olov Edlund and Sune Karlsson}, title = {Forecasting the Swedish unemployment rate VAR vs. transfer function modelling}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {61-76}, number = {1}, abstract = {The Swedish unemployment rate is forecast using three time series methods: the ARIMA, transfer function and Vector Autoregressive (VAR) models. Within this context, the choice of modelling strategy is discussed. It is found that the forecasting performance of VAR models is improved by explicitly taking account of cointegration between the variables in the model, despite the fact that unemployment is not cointegrated. However, the more parsimonious ARIMA and transfer function models have lower RMSE for all forecasting horizons. It is also found that the additional variables in the VAR models are important for predicting the turning points in the unemployment rate.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90054-Q}, issn = {0169-2070}, keywords = {Cointegration, Forecast evaluation, Model selection, Seasonal unit roots, Turning points, regart} } @ARTICLE{EP92, author = {Barry Edmonston and Jeffrey S. Passel}, title = {Immigration and immigrant generations in population projections}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {459-476}, number = {3}, abstract = {This paper proposes a new model for population projections. This model projects an initial population under conditions of fertility, mortality, and international migration (like standard cohortcomponent models), but considers the population arrayed by generation. The model incorporates four generations: a foreign-born first generation (the immigrants), a second generation (sons and daughters of immigrants), a third generation (grandsons and granddaughters of immigrants), and fourth-and-higher generations. The model requires fertility, mortality, and migration equations by generation, which take a somewhat different form than in conventional cohort-component population projection. Consideration of the model also makes apparent that assignment of births to generations may not follow a simple form; the paper presents a method for including the empirical description of intergenerational births within the generational framework. As an example, we examine the next century of population growth for the Asian, Black, Hispanic, and White non-Hispanic populations in the United States, comparing their growth rates and their composition within the total US population. With annual net immigration of 950000, the total US population of 249 million in 1990 will top 400 million in 2070 and reach about 432 million in 2090. Thus, the level of immigration and emigration assumed in these projections suggests considerable population growth for the next hundred years. The racial/ethnic composition of the United States will shift markedly during the next century, as described in the paper.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90058-H}, issn = {0169-2070}, keywords = {Foreign-born population, Racial and ethnic composition, Generationsregart} } @ARTICLE{Egginton99, author = {Don M. Egginton}, title = {Testing the efficiency and rationality of City forecasts}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {57-66}, number = {1}, abstract = {This paper examines the accuracy of city forecasts of UK data releases as collected by Standard and Poor's MMS. It finds that the median forecast calculated by MMS are, for the majority of series, biased and inefficient. The numerical size of these deviations is found to be small, unlike in some other studies. Evidence is presented that revisions may take place during the period between the collection of the forecast and the publication of the data. If significant forecast revisions take place this would compromise the usefulness of forecast surveys in the estimation of `news' effects on financial asset prices. Regression analysis does not suggest that revisions can be systematically measured by changes in current dated variables or by news from other variables. News effects therefore measure the direct effect of the forecast error rather than also including the effects of revisions to forecasts of, as yet, unpublished data.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00068-5}, issn = {0169-2070}, keywords = {Macroeconomic forecasting, Rationality, Surveys, regart} } @ARTICLE{EFO99, author = {Rob Eisinga and Philip Hans Franses and Marius Ooms}, title = {Forecasting long memory left-right political orientations}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {185-199}, number = {2}, abstract = {This paper considers out-of-sample forecasting of left-right political orientations of party affiliates in the Netherlands, using weekly data from 973 independent national Dutch surveys conducted between 1978 and 1996. The orientations of left-wing and right-wing party affiliates tend to converge over time in the sense that the differences between the average positions tend to decline. The left-right series also reveal long-memory properties in the sense that shocks appear to be highly persistent. We develop forecasting models that account for these data features and we derive the relevant forecast intervals.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00064-8}, issn = {0169-2070}, keywords = {Left-right political orientation, Fractional integration, Convergence, regart} } @ARTICLE{Eliashberg86, author = {Jehoshua Eliashberg}, title = {Business competitor intelligence, methods for collecting, organizing, and using information : William L. Sammon, Mark A. Kurland and Robert Spitainic, (Wiley, New York, 1984) \$29,95, pp. 357}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {506-506}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90105-6}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{EK93a, author = {M. A. Elkhafif and A. A. Kubursi}, title = {The demand for gasoline: a two stage approach}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {457-465}, number = {4}, abstract = {The demand for gasoline has typically been estimated using a reduced-form equation model. The simplicity of the approach is attractive, but has proven to be costly in terms of the insights lost as to the nature of the processes governing the interdependence between fuel efficiency and the overall demand for gasoline. On the other hand, disaggregating the overall demand for gasoline into all of its components produces an enormous amount of detail and many insights, but increases commensurately the complexity of the system and reduces its usefulness in forecasting. A two stage simple demand equation is used which first involves an estimation of the level of fuel efficiency of the fleet stock in terms of price induced technical change. In the second stage, the first equation is coupled with other typical demand variables to determine the overall demand for gasoline. The procedure provides an excellent forecasting equation of both the short-and long-term demand for gasoline.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90073-V}, issn = {0169-2070}, keywords = {Demand for gasoline, Price elasticity, Fuel efficiency, Gasoline forecasting modelregart} } @ARTICLE{Elkhafif93, author = {Mahmoud A. T. Elkhafif}, title = {Energy forecasting models, simulations and price sensitivity: New formulation}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {203-210}, number = {2}, abstract = {The top-down, two-stage optimization approach provides energy analysts with a powerful tool for both policy analysis and forecasting. This approach assumes that energy is weakly separable from other inputs to the production process. An aggregate energy Divisia Price Index (DPI) links the two stages. Although the DPI is necessary for the model estimation, it can distort the outcomes of price sensitivity analysis and forecasting exercises when the model is used for forecasting and simulations without adjusting the DPI. This deprives the two-stage optimization procedure of some of its virtues. The present study attempts to explain the reason for these distortions and to show that, by reformulating the same set of estimated coefficients, the simulation module will correct the shortcomings of the conventional formulation.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90005-8}, issn = {0169-2070}, keywords = {Energy demand forecast, Price sensitivity, Divisia Price Index, Fuel substitution, Out-of- sample simulation, Two-stage optimization, regart} } @ARTICLE{Elliott09, author = {Graham Elliott}, title = {Sir Clive W. J. Granger (1934-2009)}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {639 - 641}, number = {4}, note = {Special section: Decision making and planning under low levels of predictability}, doi = {10.1016/j.ijforecast.2009.09.002}, issn = {0169-2070} } @ARTICLE{EF98, author = {Walter Enders and Barry Falk}, title = {Threshold-autoregressive, median-unbiased, and cointegration tests of purchasing power parity}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {171-186}, number = {2}, abstract = {We use Dickey-Fuller tests, threshold autoregressive unit-root tests, median unbiased estimators, and cointegration tests for I(1) and I(2) variables to examine the validity of Purchasing Power Parity (PPP). The within-sample tests generally lead to the rejection of long-run PPP. Long-term out-of-sample forecasts assuming various forms of long-run PPP are not especially better than those assuming that real rates contain a unit-root. We show that no one method emerges as the best in the sense that it provides the smallest out-of-sample forecast errors.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00025-9}, issn = {0169-2070}, keywords = {Comparative Methods, Exchange Rates, Unit Roots, Threshold Model, regart} } @ARTICLE{EHP05, author = {J. Engel and D. Haugh and A. Pagan}, title = {Some methods for assessing the need for non-linear models in business cycle analysis}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {651-662}, number = {4}, abstract = {It is often suggested that non-linear models are needed to capture business cycle features. In this paper, we subject this view to some critical analysis. We examine two types of non-linear models designed to capture the bounce-back effect in US expansions. This means that these non-linear models produce an improved explanation of the shape of expansions over that provided by linear models. But this is at the expense of making expansions last much longer than they do in reality. Interestingly, the fitted models seem to be influenced by a single point in 1958 when a large negative growth rate in GDP was followed by good positive growth in the next quarter. This seems to have become embedded as a population characteristic and results in overly long and strong expansions. That feature is likely to be a problem for forecasting if another large negative growth rate was observed.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.04.013}, issn = {0169-2070}, keywords = {Threshold model, Business cycle, Non-linearity, Evaluation, Markov models, regart} } @ARTICLE{Engsted96, author = {Tom Engsted}, title = {The predictive power of the money market term structure}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {289-295}, number = {2}, abstract = {The term structure of interest rates is analyzed using weekly data from the Danish money market. Using the methods from Campbell and Shiller (1991, Review of Economic Studies 58, 495-514) it turns out that interest rate spreads are much more powerful predictors of future interest rates in perinds with relative volatile interest rates than in periods with relative smooth interest rates. However, also in the latter case spreads significantly predict future short rate changes. This implies, among other things, that the slope of the term structure may be used by the monetary authorities as a useful indicator of the tightness of monetary policy.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00624-9}, issn = {0169-2070}, keywords = {Term structure, Expectations hypothesis, Predictive power, regart} } @ARTICLE{Entorf93, author = {Horst Entorf}, title = {Constructing leading indicators from non-balanced sectoral business survey series}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {211-225}, number = {2}, abstract = {This paper considers the construction of leading indicators based on monthly survey data from the Ifo Institute, Munich. The three main points covered in the paper are: (a) The use of survey data at the sectoral level results in a longer leading indicator. By taking a non-balanced form of the survey answers and exploiting the information contained in `no change' responses through the use of canonical coherence, regressions on certain wave lengths lead to higher cross-spectral coherencies between the survey data and the actual business cycle, (b) Comparisons of frequency domain and time domain results for lead-lag relationships highlight the roles of seasonal and business cycles, (c) Out of sample forecasts reveal that the traditional balance concept is dominated by a weighted average of `worse' and `equal' responses. Surprisingly, the best results come from using the `worse' share.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90006-9}, issn = {0169-2070}, keywords = {Survey data, Business cycle, Leading indicator, Spectral methods, regart} } @ARTICLE{EFC87, author = {J. E. Epperson and S. M. Fletcher and M. F. Collins}, title = {Price forecasting and trigger price probability estimation}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {281-287}, number = {2}, abstract = {This paper shows how probability estimation, incorporated within price prediction from a single equation, will enhance the usefulness of forecast information and will have greater intuitive appeal. The estimated probability is the probability that the price will cross some predetermined threshold of importance, a trigger price. This procedure is likely to be more useful in economic decision making than the application of prediction interval estimates since the latter approach does not convey threshold probability information. Empirical application encompasses forecasting in the watermelon production industry to demonstrate the power and appeal of the approach. All probability estimates were more precise than a 0.5 probability of occurence.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90009-4}, issn = {0169-2070}, keywords = {Predicted price, Threshold price, Threshold probability, Single equation model, Probability estimation, regart} } @ARTICLE{ERS+02, author = {Ido Erev and Alvin E. Roth and Robert L. Slonim and Greg Barron}, title = {Predictive value and the usefulness of game theoretic models}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {359-368}, number = {3}, abstract = {Green [Int. J. Forecasting (2002)] reports that in certain settings predictions made by game theorists can be outperformed by the outcome of a short role playing exercise. Goodwin [Int. J. Forecasting (2002)] argues that this does not imply that game theoretic analysis cannot be useful. The current paper discusses two types of observations that support this assertion. First, there are many important settings in which game theoretic models have high forecasting power. Two examples: the aggregate outcome of entry job markets, and the outcome of repeated interactions are summarized here. The second observation concerns the possibility of objectively forecasting the predictive value of specific models (and methods) on particular domains. To increase our understanding of the value of role playing, we suggest that future research focus on estimating the predictive value of this method using a random selection of problems from a well defined set.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00023-7}, issn = {0169-2070}, keywords = {Predictive value, Role playing, regart} } @ARTICLE{Erickson87, author = {Gary M. Erickson}, title = {Marketing managers need more than forecasting accuracy}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {453-455}, number = {3-4}, abstract = {In theory, time series models can provide more accurate predictions than econometric models. However, time series models do so by introducing bias. To marketing managers who are interested in planning as well as forecasting, lack of bias is more important than accuracy.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90040-9}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{EW08, author = {Robert S. Erikson and Christopher Wlezien}, title = {The economy and the presidential vote: What leading indicators reveal well in advance}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {218-226}, number = {2}, abstract = {Everybody knows that theeconomy matters in presidential elections, but how can one incorporate economic information in an early forecasting equation? Our economic forecasting tool is the cumulative growth of leading indicators during a presidential term--weighting recent growth most heavily--which provides an early warning, as early as quarter 1 of the election year, about the Election Day economy. To control for other, non-economic factors, our model also includes presidential approval or trial-heat polls. In this paper we show how cumulative leading indicators measured early in the election year actually reveal as much about the final vote as cumulative income growth observed on the eve of the election. That is, voters respond at least as much to economic change that is predicted well in advance of elections as to economic surprises that are felt during the course of the campaign. Approval judgments incorporate these effects over the course of the election year. Very late economic shocks matter, to be sure, but they are not known until well after the campaign. The findings are informative about how the economy matters on Election Day, and have implications for our ability to forecast the outcome well in advance.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.02.001}, issn = {0169-2070}, keywords = {Forecasting, Elections, Approval, Polls, Time series, regart} } @ARTICLE{EC10, author = {Cuneyt Eroglu and Keely L. Croxton}, title = {Biases in judgmental adjustments of statistical forecasts: The role of individual differences}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {116 - 133}, number = {1}, note = {Special Section: European Election Forecasting}, doi = {10.1016/j.ijforecast.2009.02.005}, issn = {0169-2070}, keywords = {Judgmental forecasting, Adjusting forecasts,Sales forecasting,Motivation,Personality,Locus of control,Cognition} } @ARTICLE{Espasa05, author = {Antoni Espasa}, title = {Comments on The Marshallian macroeconomic model: A progress report by Arnold Zellner and Guillermo Israilevich}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {647-650}, number = {4}, note = {Nonlinearities, Business Cycles and Forecasting}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.04.005}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{EI10, author = {Jocelyn Evans and Gilles Ivaldi}, title = {Comparing forecast models of Radical Right voting in four European countries (1973-2008)}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {82 - 97}, number = {1}, note = {Special Section: European Election Forecasting}, doi = {10.1016/j.ijforecast.2009.04.001}, issn = {0169-2070}, keywords = {Electoral forecast, Radical Right,Evaluating forecasts,Regression,Time series} } @ARTICLE{EA10, author = {Heiner Evanschitzky and J. Scott Armstrong}, title = {Replications of forecasting research}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {4 - 8}, number = {1}, note = {Special Section: European Election Forecasting}, doi = {10.1016/j.ijforecast.2009.09.003}, issn = {0169-2070}, keywords = {Replication research, Research policy,Census study} } @ARTICLE{Falk99, author = {Barry Falk}, title = {Fitting autoregressive trend stationary models with finite samples}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {11-25}, number = {1}, abstract = {Sims (Journal of Applied Econometrics, 6, 423-434) conjectured that the conditional maximum likelihood estimator of autoregressive trend stationary models of macroeconomic time series will tend to place initial observations relatively far from the estimated trend line, explaining early sample behavior as transient behavior as these series move from their extreme initial positions back toward the trend path. This can be misleading if the entire sample has been generated by the same data generating process and there is nothing unusual about the initial observations. We use Monte Carlo methods and the extended Nelson-Plosser data set to evaluate Sims' conjecture. We also study the behavior of the weighted symmetric estimator developed by Park and Fuller (Unpublished manuscript, 1993, Department of Statistics, Iowa State University, Ames, Iowa) as an estimator of autoregressive trend stationary models.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00054-5}, issn = {0169-2070}, keywords = {Trend-stationary models, Weighted symmetric estimator, Conditional maximum, Likelihood estimator, regart} } @ARTICLE{FR05, author = {Barry Falk and Anindya Roy}, title = {Forecasting using the trend model with autoregressive errors}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {291-302}, number = {2}, abstract = {This paper is concerned with forecasting time series generated by the linear trend model with autoregressive errors, allowing for a possible unit root (UR). Time series of this sort play an important role in economics, particularly macroeconomics. We consider a variety of estimators of the model and use simulation methods to compare the forecast errors that result from applying each of these estimators. Our main conclusion is that no single estimation procedure emerges as a dominant procedure, but we are able to provide some potentially useful results regarding the circumstances under which certain estimation procedures work better than the alternatives. We then apply the estimators to produce real time, out-of-sample forecasts of six macroeconomic time series. In these applications, the Roy-Fuller bias-corrected Prais-Winsten (PW) estimator emerges as the best procedure in five of the six cases.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.08.001}, issn = {0169-2070}, keywords = {Forecasting, Trend model, Autoregressive errors, Unit root, Bias correction, regart} } @ARTICLE{Fang03, author = {Yue Fang}, title = {Forecasting combination and encompassing tests}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {87-94}, number = {1}, abstract = {In this paper we demonstrate that forecast encompassing tests are valuable tools in getting an insight into why competing forecasts may be combined to produce a composite forecast which is superior to the individual forecasts. We also argue that results from forecast encompassing tests are potentially useful in model specification. We illustrate this using forecasts of quarterly UK consumption expenditure data from three classes of models: ARIMA, DHSY and VAR models.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00121-2}, issn = {0169-2070}, keywords = {ARIMA, Econometric model, Forecast encompassing, Forecast combination, VAR, regart} } @ARTICLE{FX03, author = {Yue Fang and Daming Xu}, title = {The predictability of asset returns: an approach combining technical analysis and time series forecasts}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {369-385}, number = {3}, abstract = {We investigate predictability of asset returns by developing an approach that combines technical analysis and conventional time series forecasts. While exploiting predictable components as functions of past prices or returns, technical trading rules and time series forecasts capture different aspects of market predictability: the former tends to identify periods to be in the market when returns are positive and the latter is capable of identifying periods to be out when returns are negative. Applied to daily Dow Jones Averages over the first 100 years, the combined strategies outperform both technical trading rules and time series forecasts. The predictability can be explained largely by non-trivial low-order serial correlations in returns and is not mainly attributable to measurement errors arising from non-synchronous trading.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00013-4}, issn = {0169-2070}, keywords = {AR-GARCH models, Combining forecasts, Excess returns, Predictability, Technical trading rules, regart} } @ARTICLE{Farebrother86, author = {R.W. Farebrother}, title = {Recent advances in regression methods}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {246-246}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90120-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Farebrother86a, author = {R. W. Farebrother}, title = {Nonlinear regression modelling: A unified practical approach : David A. Ratkowsky, (Dekker, New York, 1983) \$39.00, pp. 276}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {125-125}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90042-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Faria02, author = {Alvaro E. Faria}, title = {Forecasting: Methods and Applications, by Spyros Makridakis, Steven C. Wheelwright and Rob J. Hyndman. Third edition. John Wiley and Sons, 1998, 642pp, ISBN 0-471-53233-9. �29.95, \$90.65.}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {158-159}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00130-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Faucheux96, author = {Claude Faucheux}, title = {Comments on Forecasting: its role and value forplanning and strategy by Spyros Makridakis}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {539-546}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00680-2}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Feldman89, author = {Maryann P. Feldman}, title = {Theory of population and economic growth : Julian L. Simon, (Basil Blackwell, New York, 1986) \$45.00 pp. 215}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {142-143}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90077-0}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{FP03, author = {Marcus Felson and Erika Poulsen}, title = {Simple indicators of crime by time of day}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {595-601}, number = {4}, abstract = {Crime varies greatly by hour of day--more than by any other variable. Yet numbers of cases declines greatly when fragmented into hourly counts. Summary indicators are needed to conserve degrees of freedom, while making hourly information available for description and analysis. This paper describes some new indicators that summarize hour-of-day variations. A basic decision is to pick the first hour of the day, after which summary indicators are easily defined. These include the median hour of crime, crime quartile minutes, crime's daily timespan, and the 5-to-5 share of criminal activity; namely, that occurring between 5:00 AM and 4:59 PM. Each summary indicator conserves cases while offering something suitable to forecast.}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00093-1}, issn = {0169-2070}, keywords = {Hour-of-day periodicity, Crime series data, regart} } @ARTICLE{Fernandez-Macho05, author = {Javier Fern{\'a}ndez-Macho}, title = {Comments on Combining filter design with model-based filtering}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {711-715}, number = {4}, note = {Nonlinearities, Business Cycles and Forecasting}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.04.008}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{FSA99, author = {Fernando Fern{\'a}ndez-Rodr{\'i}guez and Sim{\'o}n Sosvilla-Rivero and Juli{\'a}n Andrada-F{\'e}lix}, title = {Exchange-rate forecasts with simultaneous nearest-neighbour methods: evidence from the EMS}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {383-392}, number = {4}, abstract = {In this paper we extend nearest-neighbour predictors to allow for information content in a wider set of simultaneous time series. We apply these simultaneous nearest-neighbour (SNN) predictors to nine EMS currencies, using daily data for the 1st January 1978-31st December 1994 period. When forecasting performance is measured by Theil's U statistic, the (nonlinear) SNN predictors perform marginally better than both a random walk and the traditional (linear) ARIMA predictors. Furthermore, the SNN predictors outperform the random walk and the ARIMA models when producing directional forecasts.When formally testing for forecast accuracy, in most of the cases the SNN predictor outperforms the random walk at the 1% significance level, while outperforming the ARIMA model in three of the nine cases. On the other hand, our results suggest that the probability of correctly predicting the sign of change is higher for the SNN predictions than the ARIMA case.}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00003-5}, issn = {0169-2070}, keywords = {Nearest-neighbours, Exchange rates, regart} } @ARTICLE{Fields92, author = {Paul J. Fields}, title = {Forecasting systems for operations management: Stephen A. Delurgio and Carl D. Bhame, 1991, (Business One Irwin, Homewood, IL), pp. 648, hardback, US\$49.95}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {644-646}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90079-O}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes10, author = {Robert Fildes}, title = {Book review}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {208 - 209}, number = {1}, note = {Special Section: European Election Forecasting}, doi = {10.1016/j.ijforecast.2009.09.007}, issn = {0169-2070} } @ARTICLE{Fildes08, author = {Robert Fildes}, title = {Diebold Francix X., Elements of Forecasting (4th ed.), Thomson, South-Western: Ohio, US (2007) ISBN 978-0-324-35904-6 458 Hardcover.}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {552-553}, number = {3}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.05.004}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes07, author = {Robert Fildes}, title = {Thomas F. Wallace and Robert A. Stahl , Sales Forecasting: A New Approach, T.F. Wallace \& Co. (2006) ISBN: 0-9674884-1-9 (paper), \$44.95, 166 pages.}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {719-720}, number = {4}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.08.002}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes06, author = {Robert Fildes}, title = {The forecasting journals and their contribution to forecasting research: Citation analysis and expert opinion}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {415-432}, number = {3}, abstract = {In 1982, the International Institute of Forecasters set up the Journal of Forecasting, followed in 1985 by the International Journal of Forecasting. The primary aim of their foundation, laid out in the first issues, was to take a 'multi-disciplinary perspective'; all types of forecasting methods were of interest. Of particular importance were 'papers that compare[d] different approaches to actual forecasting situations', the multiple hypotheses approach. This paper evaluates the success of the two journals in meeting their objectives and in setting the research agenda in forecasting. The approach taken is through citation analysis and the identification of influential forecasting articles using both citations and expert analysis. The two approaches identified the same themes as particularly important, with the econometric advances of Engle and Granger outstanding. A content analysis of the journals was also undertaken, showing that the comparative approach to establishing improved forecasting methods through examining multiple hypotheses has been successfully adopted and is unusual when compared to other journals. Few articles examined the conditions under which one approach outperformed its competitors. By examining the highly cited articles in the forecasting journals compared to other journals in the business, economics, and management area, I conclude that the forecasting journals have covered all areas of forecasting research; however, many influential articles are published across a wide range of other journals. There was little cross-fertilisation between journals. There remain, however, topics which have been widely neglected. In particular, organisational issues and the effects of forecast error, highlighted as important areas when the journals were founded, have been ignored. These two issues directly impact the gap between theoretical contributions and forecasting practice, a gap that remains unbridged. In short, the journals have made progress in meeting the objectives set by the founders, but there still remains much important research to be done.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.03.002}, issn = {0169-2070}, keywords = {Citation analysis, Diffusion of research, Expert opinion, Forecasting practice, Multiple hypotheses, regart} } @ARTICLE{Fildes05, author = {Robert Fildes}, title = {The IJF, the Institute and forecasting software}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {199-200}, number = {2}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.01.002}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Fildes03, author = {Robert Fildes}, title = {New-Product Diffusion Models: V. Mahajan, E. Muller and Y. Wind (Eds.), Kluwer Academic Press, Boston \& Dordrecht, 2000, ISBN 0-7923-7751-6. 115.50 EUR/99.95 USD/70.00 GBP.}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {327-328}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00016-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes03a, author = {Robert Fildes}, title = {Corrigendum to 'Telecommunications demand forecasting--a review': [International Journal of Forecasting 18 (2002) 489-522]}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {337-337}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00039-6}, issn = {0169-2070}, keywords = {errata} } @ARTICLE{02c, author = {Robert Fildes}, title = {Book reviews}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {697-698}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00072-9}, issn = {0169-2070}, key = {tagkey2002697}, keywords = {bookrev} } @ARTICLE{01, author = {Robert Fildes}, title = {Book reviews}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {129-130}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00091-1}, issn = {0169-2070}, key = {tagkey2001129}, keywords = {bookrev} } @ARTICLE{Fildes94, author = {Robert Fildes}, title = {Journal of econometrics : Chung-ki Min and Arnold Zellner, 1993, Bayesian and non-Bayesian methods for combining models and forecasts with applications to forecasting international growth rates}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {163-164}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90059-0}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Fildes94a, author = {Robert Fildes}, title = {Journal of Business and Economic Statistics: Rick L. Andrews, 1994, Forecasting performance of structural time series models, 12, 129-133}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {649-649}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90039-6}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Fildes94b, author = {Robert Fildes}, title = {Applied Statistics: L.S.-Y. Wu, J.R.M. Hosking and N. Ravishankar, 1993, Reallocation outliers in time series, 42, 301-313}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {650-650}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90040-X}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Fildes93, author = {Robert Fildes}, title = {A critique of recent papers on 'Trends, random walks, and break points in macroeconomic time series'}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {281-283}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90017-H}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Fildes93a, author = {Robert Fildes}, title = {A simple nonparameteric test of predictive performance: M. Hashem Pesaran and Allan Timmerman, Journal of business and economic statistics, 10 (1992) 461-465}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {285-285}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90020-N}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Fildes93b, author = {Robert Fildes}, title = {Management science : George Duncan, Wilpen Gorr and Janusz Szczypula, 1993, Bayesian forecasting for seemingly unrelated time series: an application to local government forecasting 39, 275-293.}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {585-586}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90087-4}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Fildes93c, author = {Robert Fildes}, title = {Journal of the Royal Statistical Society (B) : Gary K. Grunwald, Adrian E. Raftery and Peter Guttorp, 1993, Time series of continuous proportions, 55, 103-116.}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {586-587}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90088-5}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Filde92, author = {Robert Fildes}, title = {Influencing forecasting practice}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {1-2}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90002-Q}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Filders92, author = {Robert Fildes}, title = {American economic review : Gordon Leitch and J. Ernest Tanner, Economic forecast evaluation: Profit versus the conventional error measures, 81 (1991) 580-590}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {279-282}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90130-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes92, author = {Robert Fildes}, title = {The practice of econometrics: Classical and contemporary : Ernst R. Berndt, (Addison-Wesley Publishing company, Reading, Mass., 1991), pp. 702, \$18.95}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {269-270}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90124-R}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes92a, author = {Robert Fildes}, title = {Forecasting structural time series models and the kalman filter: Andrew Harvey, 1989, (Cambridge University Press), 554 pp., ISBN 0-521-32196-4}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {635-635}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90072-H}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes92b, author = {Robert Fildes}, title = {Bayesian forecasting and dynamic models: Mike West and Jeff Harrison, 1989,(Springer), 704 pp., ISBN 0-387-97025-8}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {635-637}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90073-I}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes92c, author = {Robert Fildes}, title = {On error measures: A response to the commentators -- the best error measure?}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {109-111}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90016-3}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Fildes92d, author = {Robert Fildes}, title = {The evaluation of extrapolative forecasting methods}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {81-98}, number = {1}, abstract = {Extrapolative forecasting methods are widely used in production and inventory decisions. Typically many hundreds of series are forecast and the cost-effectiveness of the decisions depends on the accuracy of the forecasting method(s) used. This paper examines how a forecasting method should be chosen based on analyzing alternative loss functions. It is argued that a population of time series must be evaluated by time period and by series. Of the alternative loss functions considered, only the geometric root mean squared error is well-behaved and has a straightforward interpretation. The paper concludes that exponential smoothing and `naive' models, previously thought to be `robust' performers, forecast poorly for the particular set of time series under analysis, whatever error measure is used. As a consequence, forecasters should carry out a detailed evaluation of the data series, as described in the paper, rather than relying on a priori analysis developed from earlier forecasting competitions.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90009-X}, issn = {0169-2070}, keywords = {Evaluation, time series methods, Evaluation, methodology, Comparative methods, time series, Robust estimation, Outliers, effect of, Loss functions, evaluation, Ex ante, regart} } @ARTICLE{Fildes91, author = {Robert Fildes}, title = {Evaluating forecast performance in an inventory control system : Everette S. Gardner Jr., Management Science 36 (1990) 490-499.}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {118-118}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90042-T}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes91a, author = {Robert Fildes}, title = {Sliding simulation: A new approach to time series forecasting : Spyros Makridakis, Management Science 36 (1990) 505-512.}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {119-119}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90044-V}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes91b, author = {Robert Fildes}, title = {Database models and managerial intuition: 50% model +50% manager : Robert C. Blattberg and Stephen J. Hoch, Management Science 36 (1990) 887-899.}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {251-252}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90066-5}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Fildes91c, author = {Robert Fildes}, title = {Combining forecasts: Operational adjustments to theoretical optimal rules : David C. Schmittlein, Jinho Kim and Donald G. Morrison, Management Science 36 (1990) 1044-1056.}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {253-254}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90069-8}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Fildes91d, author = {Robert Fildes}, title = {Prelaunch forecasting of new automobiles : Glen L. Urban, John R. Hauser and John H. Roberts, Management Science 36 (1990) 401-421.}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {254-254}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90070-C}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Fildes91e, author = {Robert Fildes}, title = {The lead and accuracy of macroeconomic forecasts : R.A. Kolb, and H.O. Stekler, Journal of Macroeconomics 12 (1990) 111-123}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {400-400}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90021-M}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Fildes90, author = {Robert Fildes}, title = {The price elasticity of selective demand: A meta-analysis of econometric models of sales : Gerald J. Tellis, Journal of marketing research 25 (1988) 331-341}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {586-586}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90049-H}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Fildes89, author = {Robert Fildes}, title = {Journal of forecasting 7 : Robert F. Engle, Scott J. Brown and Gary Stern, A comparison of adaptive structural forecasting methods for electricity sales, (1988) 149-172}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {293-294}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90105-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes89a, author = {Robert Fildes}, title = {Journal of the American Statistical Association : William S. Cleveland, Marylyn E. McGill and Robert McGill, The shape parameter for a two variable graph 83 (1988) 289-300}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {294-294}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90106-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes89b, author = {Robert Fildes}, title = {Journal of the American Statistical Association : Stanley K. Smith,Tests of forecast accuracy and bias for country population projections (with discussion), 82 (1987) 991-1012}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {294-295}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90107-6}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes89c, author = {Robert Fildes}, title = {The important forecasting problems that we are not researching}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {1-1}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90057-5}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Fildes89d, author = {Robert Fildes}, title = {Research on forecasting}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {151-153}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90081-2}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Fildes88, author = {Robert Fildes}, title = {Model reliability : David A. Belsley and Edwin Kuh, eds. (Massachusetts Institute of Technology Press, Cambridge, MA 1986) pp. 244, \$30.00, �29.95}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {297-298}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90089-1}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes88a, author = {Robert Fildes}, title = {Journal of business and economic statistics 5 : Garcia-Ferrer, A. et al., `Macroeconomic forecasting using pooled international data', (1987), 53-67}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {509-510}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90121-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes88b, author = {Robert Fildes}, title = {Management science : Lawrence, M.J., R.H. Edmunson and M.J. O'Connor, The accuracy of combining judgmental and statistical forecasts, 32 (1986), 1521-1532}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {510-511}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90122-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes88c, author = {Robert Fildes}, title = {Journal of business : Lupoletti, William M. and Roy H. Webb, 1986, `Defining and improving the accuracy of macroeconomic forecasts; contributions from a VAR model', 59, 263-284}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {511-512}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90123-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes88d, author = {Robert Fildes}, title = {Journal of business and economic statistics : L{\"u}tkepohl, Helmut, `Forecasting vector ARMA processes with systematically missing observations', 4 1986, 375-390.}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {513-513}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90124-0}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes86, author = {Robert Fildes}, title = {Long-Term Forecasting and the Experts}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {3-4}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90026-9}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Fildes86a, author = {Robert Fildes}, title = {Diagnostic checking in practice : Walter Kramer, Harald Sonnberger, Johann Maurer and Peter Havlik, Review of Economics and Statistics 67 (1985) 118-123}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {115-116}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90035-X}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes86b, author = {Robert Fildes}, title = {The role of linear recursive estimators in time series forecasting. : D.J. Pack, D.H. Pike and D.J. Downing, Management Science 31 (1985) 188-199}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {116-117}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90036-1}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes86c, author = {Robert Fildes}, title = {Time series analysis : Adrian E. Raftery, European Journal of Operations Research 20 (1985) 127-137}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {117-117}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90037-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes86d, author = {Robert Fildes}, title = {Sensitivity analyses would help}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {237-238}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90114-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes86e, author = {Robert Fildes}, title = {Computer Modeling for Business and Industry : Bruce L. Bowerman and Richard T. O'Connell, (Marcel Dekker, New York, 1984) pp. 219}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {501-501}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90102-0}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fildes86f, author = {Robert Fildes}, title = {Combining economic forecasts : Robert T. Clemen and Robert L. Winkler, Journal of Business and Economic Statistics 4 (1986) 39-46}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {384-384}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90057-9}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Fildes86g, author = {Robert Fildes}, title = {Methods for determining the order of an autoregressive-moving average process: a survey : Jan G. De Gooijer, Bovas Abraham, Ann Gould and Lecily Robinson, International Statistical Review 53 (1985) 301-329}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {384-385}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90058-0}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Fildes86h, author = {Robert Fildes}, title = {Forecasting trends in time series : Everette S. Gardner Jr. and Ed. McKenzie, Management Science 31 (1985) 1237-1246}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {383-384}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90056-7}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Fildes86i, author = {Robert Fildes}, title = {What will take the con out of econometrics: Michael McAleer, Adrian R. Pagan and Paul A. Volker,American Economic Review 75 (1985) 293-307}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {237-238}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90113-5}, issn = {0169-2070}, key = {tagkey1986237}, keywords = {othercom} } @ARTICLE{FBC+03, author = {Robert Fildes and Stuart Bretschneider and Fred Collopy and Michael Lawrence and Doug Stewart and Heidi Winklhofer and John T. Mentzer and Mark A. Moon}, title = {Researching Sales Forecasting Practice: Commentaries and authors' response on Conducting a Sales Forecasting Audit by M.A. Moon, J.T. Mentzer \& C.D. Smith}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {27-42}, number = {1}, abstract = {Sales forecasting is a common activity in most companies affecting operations, marketing and planning. Little is known about its practice. Mentzer and his colleagues have developed a research programme over twenty years aimed at rectifying the gap in knowledge. Most recently, in the Mentzer et al. (2002) paper they have demonstrated with supporting evidence the use of a sales forecasting audit to establish the dimensions of best practice. In this commentary on the paper, the methodology underlying their approach is examined from a number of different perspectives. The commentaries examine how convincing and complete has been the choice of audit dimensions as well as how this new research fits with evidence from other sources. Both commentators and respondents agree that the topic is important to organisational practice and more research is needed to gain a complete picture of the sales forecasting function and the systems that support it. Clarifying the audit function is particularly important since sales forecasting often has a low organisational profile until events turn sour with damaging consequences to organisational viability.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00033-X}, issn = {0169-2070}, keywords = {Forecasting practice, Audit, Forecasting management, Performance measurement, Forecasting systems, Supply chain, Research methodology, Forecasting support systems, regart} } @ARTICLE{FGL+09, author = {Robert Fildes and Paul Goodwin and Michael Lawrence and Konstantinos Nikolopoulos}, title = {Effective forecasting and judgmental adjustments: an empirical evaluation and strategies for improvement in supply-chain planning}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {3-23}, number = {1}, abstract = {Demand forecasting is a crucial aspect of the planning process in supply-chain companies. The most common approach to forecasting demand in these companies involves the use of a computerized forecasting system to produce initial forecasts and the subsequent judgmental adjustment of these forecasts by the company's demand planners, ostensibly to take into account exceptional circumstances expected over the planning horizon. Making these adjustments can involve considerable management effort and time, but do they improve accuracy, and are some types of adjustment more effective than others? To investigate this, we collected data on more than 60,000 forecasts and outcomes from four supply-chain companies. In three of the companies, on average, judgmental adjustments increased accuracy. However, a detailed analysis revealed that, while the relatively larger adjustments tended to lead to greater average improvements in accuracy, the smaller adjustments often damaged accuracy. In addition, positive adjustments, which involved adjusting the forecast upwards, were much less likely to improve accuracy than negative adjustments. They were also made in the wrong direction more frequently, suggesting a general bias towards optimism. Models were then developed to eradicate such biases. Based on both this statistical analysis and organisational observation, the paper goes on to analyse strategies designed to enhance the effectiveness of judgmental adjustments directly.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.11.010}, issn = {0169-2070}, keywords = {Forecasting accuracy, Judgment, Heuristics and biases, Supply chain, Forecasting support systems, Practice, Combining, Forecast adjustment, regart} } @ARTICLE{FGL+09a, author = {Robert Fildes and Paul Goodwin and Michael Lawrence and Konstantinos Nikolopoulos}, title = {Reply to Commentaries by Flores,{\"O}nkal and Sanders}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {32-34}, number = {1}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.09.006}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{FHM+98, author = {Robert Fildes and Michèle Hibon and Spyros Makridakis and Nigel Meade}, title = {Generalising about univariate forecasting methods: further empirical evidence}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {339-358}, number = {3}, abstract = {This paper extends the empirical evidence on the forecasting accuracy of extrapolative methods. The robustness of the major conclusions of the M-Competition data is examined in the context of the telecommunications data of Fildes (1992). The performance of Robust Trend, found to be a successful method for forecasting the telecommunications data by Fildes, is compared with that of other successful methods using the M-Competition data. Although it is established that the structure of the telecommunications data is more homogeneous than that of the M-Competition data, the major conclusions of the M-Competition continue to hold for this new data set. In addition, while the Robust Trend method is confirmed to be the best performing method for the telecommunications data, for the 1001 M-Competition series, this method is outperformed by methods such as Single or Damped Smoothing. The performance of smoothing methods depended on how the smoothing parameters are estimated. Optimisation at each time origin was more accurate than optimisation at the first time origin, which in turn is shown to be superior to arbitrary (literature based) fixed values. In contrast to the last point, a data based choice of fixed smoothing constants from a cross-sectional study of the time series was found to perform well.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00009-0}, issn = {0169-2070}, keywords = {Comparative methods-Time series: Univariate, Time series-univariate: ARIMA, Estimation-robust, Time series-univariate: exponential smoothing, M-Competition, regart} } @ARTICLE{FK02, author = {Robert Fildes and V. Kumar}, title = {Telecommunications demand forecasting--a review}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {489-522}, number = {4}, abstract = {The last decade has seen rapid advances in telecommunications technology in an increasingly deregulated and competitive market place. Companies operating in these various markets have relied on demand forecasts to justify the considerable investment needed to ensure capacity availability at the right time. These new markets are typically composed of new consumers taking up a product or service for the first time, established users changing their usage patterns, users of competing services shifting to the alternative service and those exiting from this segment of the market altogether. This paper describes various models that have been used to understand market dynamics. Markets discussed include both established and new: mobile, the internet, and PSTN (public switched telephony network). Cross-sectional choice models of the mode of accessing the service are discussed along with models for usage in established markets. These models typically include price (and perceived price) differentials and use standard econometric methods, focusing on price elasticity estimation. Forecasting accuracy has been neglected. New product models may include additional `drivers' such as aspects of service quality and the attributes of the products themselves. Both choice models of adoption of new products and Bass-type diffusion models have been used in forecasting. Because of the complexity of the `drivers' of the adoption process, the successful modelling of these new markets has been limited, not least by inadequate data. Simulation models have been proposed to structure the problem more completely and overcome these inadequacies. Both these classes of model have not been effectively validated, researchers having been content just to propose a new approach without thoroughly testing it against alternatives. The only class of telecommunications forecasting problem that has been more thoroughly analysed are those needed to support operations such as call centres. This review paper describes the research that has been carried out on the three problem areas of established products, new products and operations, highlighting areas where further research is needed. The paper also serves as an introduction to the Special Issue on Telecoms Forecasting by describing how the papers contribute to the developing research agenda.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00064-X}, issn = {0169-2070}, keywords = {Telecommunications, New products--evaluation, Call centre, Price elasticity estimation, Forecasting practice, Choice models--evaluation, Diffusion models, System dynamics, Internet, Simulation, regart} } @ARTICLE{FK02a, author = {Robert Fildes and V. Kumar}, title = {Telecommunications Forecasting}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {487-488}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00063-8}, issn = {0169-2070}, key = {tagkey2002487}, keywords = {editorial} } @ARTICLE{FM88, author = {Robert Fildes and Spyros Makridakis}, title = {Forecasting and loss functions}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {545-550}, number = {4}, abstract = {This paper considers two problems of interpreting forecasting competition error statistics. The first problem is concerned with the importance of linking the error measure (loss function) used in evaluating a forecasting model with the loss function used in estimating the model. It is argued that because the variety of uses of any single forecast, such matching is impractical. Secondly, there is little evidence that matching would have any impact on comparative forecast performance, however measured. As a consequence the results of forecasting competitions are not affected by this problem. The second problem is concerned with the interpreting performance, when evaluated through M(ean) S(quare) E(rror). The authors show that in the Makridakis Competition, good MSE performance is solely due to performance on a small number of the 1001 series, and arises because of the effects of scale. They conclude that comparisons of forecasting accuracy based on MSE are subject to major problems of interpretation.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90131-8}, issn = {0169-2070}, keywords = {M-competition, Bayesian forecasting, Loss functions - interpretation, Loss functions - evaluation, Estimation - evaluation, Time series - transformations, evaluation, regart} } @ARTICLE{FWM04, author = {David F. Findley and Kellie C. Wills and Brian C. Monsell}, title = {Seasonal adjustment perspectives on Damping seasonal factors: shrinkage estimators for the X-12-ARIMA program}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {551-556}, number = {4}, abstract = {We examined the shrinkage methods of Miller and William from the perspective of seasonal adjustment rather than forecasting, restricting attention to their performance on the approximately 500 of the 1428 M3 series that are seasonal and have multiplicative seasonality. Local shrinkage improved the quality of the seasonal adjustment of enough of these series that almost 50% have acceptable automatic X-12-ARIMA adjustments, instead of 40% with no shrinkage. For a few series, global shrinkage produced demonstrably incorrect results, and for some of these series and also others improved by local shrinkage, the SEATS seasonal adjustment provided by an experimental version of X-12-ARIMA offered still greater improvements. No benefits were observed from global shrinkage.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.03.008}, issn = {0169-2070}, keywords = {Seasonal adjustment quality, othercom} } @ARTICLE{FLK09, author = {Waltraud Fink and Vilen Lipatov and Martin Konitzer}, title = {Diagnoses by general practitioners: Accuracy and reliability}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {784 - 793}, number = {4}, note = {Special section: Decision making and planning under low levels of predictability}, doi = {10.1016/j.ijforecast.2009.05.023}, issn = {0169-2070}, keywords = {Primary care, Risk management,Medical diagnosis} } @ARTICLE{FS99, author = {David Fintzen and H. O. Stekler}, title = {Why did forecasters fail to predict the 1990 recession?}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {309-323}, number = {3}, abstract = {This paper examines the forecasts that were prepared prior to and during the early stages of the recession that occurred in 1990 in the United States. It examines the characteristics of those forecasts, the data that were available and attempts to determine why the forecast errors occurred. Private sector and public sector predictions are compared and the possibility of rational forecast bias is investigated. We conclude that data problems might have contributed to the forecast errors and suggest that individuals might have been able to predict this recession.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00072-7}, issn = {0169-2070}, keywords = {Recession, Forecast errors, Rational forecast bias, Macroeconomic forecasting, regart} } @ARTICLE{Fiordaliso98, author = {Antonio Fiordaliso}, title = {A nonlinear forecasts combination method based on Takagi-Sugeno fuzzy systems}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {367-379}, number = {3}, abstract = {In this paper, we investigate the use of a special class of fuzzy systems, namely first order Takagi-Sugeno fuzzy systems to combine a set of individual forecasts. Such systems can be interpreted as local linear approximation models and have been used mainly as such in this study. The inference produced by these models can be seen as a new kind of piecewise linear regression with softened transitions between the pieces. By comparing our combining system with traditional linear combining models, we have shown the possible advantage of the nonlinear approach as well as the flexibility of our system.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00010-7}, issn = {0169-2070}, keywords = {Takagi-Sugeno systems, Combining forecasts, Gradient-based algorithms, Pruning, Self-structuring fuzzy systems, Function approximation, regart} } @ARTICLE{FH99, author = {Ilan Fischer and Nigel Harvey}, title = {Combining forecasts: What information do judges need to outperform the simple average?}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {227-246}, number = {3}, abstract = {Previous work has shown that combinations of separate forecasts produced by judgment are inferior to those produced by simple averaging. However, in that research judges were not informed of outcomes after producing each combined forecast. Our first experiment shows that when they are given this information, they learn to weight the separate forecasts appropriately. However, their judgments, though improved, are still not significantly better than the simple average because they contain a random error component. Bootstrapping can be used to remove this inconsistency and produce results that outperform the average. In our second and third experiments, we provided judges with information about errors made by the individual forecasters. Results show that providing information about their mean absolute percentage errors updated each period enables judges to combine their forecasts in a way that outperforms the simple average.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00073-9}, issn = {0169-2070}, keywords = {Judgment, Forecasting, Feedback, Information integration, Combining forecasts, regart} } @ARTICLE{Fischhoff94, author = {Baruch Fischhoff}, title = {What forecasts (seem to) mean}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {387-403}, number = {3}, abstract = {A forecast is just the set of probabilities attached to a set of future events. In order to understand a forecast, all one needs to do is to interpret those two bits of information. Unfortunately, there are pitfalls to communicating each element, so that the user of a forecast understands what its producer means. One source of potential problems is ambiguity regarding the event being predicted and what exactly is being said about it. Another is the difficulty of determining the relevance of the problem that the forecaster has solved for the problem that the user is facing. Problems can also arise out of epistemological and sociological issues of trust and context. A simple framework is offered for considering these communication problems and is then illustrated with a mixture of systematic data and anecdotal observation. The criticality of these different problems is considered, along with procedures that might reduce them.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90069-8}, issn = {0169-2070}, keywords = {Forecasting, Ambiguity, Risk communication, Uncertainty, Subjective probability, regart} } @ARTICLE{Fischhoff88, author = {Baruch Fischhoff}, title = {Judgmental aspects of forecasting : Needs and possible trends}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {331-339}, number = {3}, abstract = {Judgment permeates any forecasting process. It is also subject to systematic study. Considering judgment as an understandable phenomenon allows access to the research literature examining judgments in other contexts and to the research methodologies needed to study the judgments needed for specific forecasting tasks. Such research can clarify how much forecasts are to be trusted and how forecasts might be improved (by evaluating and improving their judgmental component). Indeed, just identifying where judgment enters a forecast can make it more useful. The approach outlined here offers a complement both to seeing `judgmental forecasting' as an irreducible whole and to focusing primarily on a few judgmental subtasks (e.g., assessing confidence intervals). It argues that such focused empirical study can be profitably performed on other subtasks, creating a more comprehensive picture of judgment.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90101-X}, issn = {0169-2070}, keywords = {Forecasting, Judgment, Expert judgment, Decision support, Elicitation, Subjective probabilities, regart} } @ARTICLE{Fisher91, author = {Joseph L. Fisher}, title = {What futurists believe : Joseph F. Coates and Jennifer Jarrett, (Lomond Publication, Inc., Mt. Airy, MD and The World Future Society, Bethesda, MD, 1989).}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {245-246}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90062-Z}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Fisher91a, author = {Paul Fisher}, title = {Economic forecasting: an introduction : K. Holden, D.A. Peel and J.L. Thompson,(Cambridge University Press, Cambridge, UK, 1991) ISBN 0521 356121, 0521 35692x. h/b �30.00, \$44.5; p/b �10.95, \$16.95}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {388-389}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90014-M}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Flavell92, author = {Richard Flavell}, title = {Japanese financial market research : W.T. Ziemba, W. Bailey and Y. Hamao, eds., (Elsevier, Amsterdam, 1991), pp. 616, \$69.50, Dfl 175.00}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {270-271}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90125-S}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Flavell88, author = {R. Flavell}, title = {Predicting corporate collapse : A. Bathory (Financial Times Business Information, 1984) pp. 159, �65, \$110}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {300-301}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90092-1}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Flavell87, author = {R. B. Flavell}, title = {Corporate failure, prediction, panacea and prevention : O.P. Kharbanda and E.A. Stallworthy, (McGraw-Hill, New York, NY, 1985) �16.50}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {345-346}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90024-0}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Flores89, author = {Benito Flores}, title = {The handbook of forecasting: A manager's guide : S. Makridakis and S.C. Wheelwright, eds., Second edition, 1987, J. Wiley and Sons, New York., \$58.50, �52.50, p. 638}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {138-141}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90075-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Flores09, author = {Benito E. Flores}, title = {Comments on Effective forecasting and judgmental adjustments: An empirical evaluation and strategies for improvement in supply-chain planning}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {27-29}, number = {1}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.09.002}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Flores89a, author = {Benito E. Flores}, title = {The utilization of the Wilcoxon test to compare forecasting methods: A note}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {529-535}, number = {4}, abstract = {The selection of forecasting methods is a complicated issue. The situation is created by the need to identify the best method for a time series. Criteria for selection must be defined. If the sole criterion is accuracy, then a comparison of two forecasting methods can be made by testing them ex post while utilizing the time series. Care should be exercised in the selection of the accuracy metric. A statistical test should be made to determine if the results are significantly different. The test recommended is the Wilcoxson test since it is less restrictive to the nature of the error and less susceptible to outliers.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90008-3}, issn = {0169-2070}, keywords = {Forecasting methods, Decision making, Comparing forecasting methods, regart} } @ARTICLE{Flores86, author = {Benito E. Flores}, title = {Use of the sign test to supplement the percentage better statistic}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {477-489}, number = {4}, abstract = {The utilization of an accuracy measure such as Percentage Better can be made more meaningful if it is supplemented with a statistical test of the significance of the results. For the Percentage Better, the Sign Test can be useful. In this paper, some of the results of the Makridakis competition are re-analyzed to illustrate this point. The results make for a clearer interpretation and easier use to identify the best forecasting method in a pairwise fashion}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90093-2}, issn = {0169-2070}, keywords = {Comparative methods, Forecasting evaluation, Accuracy measures, regart} } @ARTICLE{FOW92, author = {Benito E. Flores and David L. Olson and Christopher Wolfe}, title = {Judgmental adjustment of forecasts: A comparison of methods}, journal = {International Journal of Forecasting}, year = {1992}, volume = {7}, pages = {421-433}, number = {4}, abstract = {Attention has recently been given to combinations of subjective and objective forecasts to improve forecast accuracy. This research offers an extension on this theme by comparing two methods that can be used to adjust an objective forecast. Wolfe and Flores (1990) show that forecasts can be judgmentally adjusted by analysts using a structured approach based on Saaty's analytic hierarchy process (AHP). In this study, the centroid method is introduced as a vehicle for forecast adjustment and is compared to the AHP. While the AHP allows for finer tuning in reflecting decision maker judgement, the centroid method produces very similar results and is much simpler to use in the forecast adjustment process.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90027-7}, issn = {0169-2070}, keywords = {Earnings forecasts, Judgmental adjustment, Analytic hierarchy Process (AHP), Centroid method, regart} } @ARTICLE{FP00, author = {Benito E. Flores and Stephen L. Pearce}, title = {The use of an expert system in the M3 competition}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {485-496}, number = {4}, abstract = {The Expert System that one of the authors had developed during his dissertation was tried on the data set of the M3 Competition. The expert system was originally designed to forecast monthly demand for industrial products in a distribution environment and was modified to run the data. The results of the application of the system were mixed as in some of the time series the results were statistically undistinguishable with the exception of the monthly series. In general, the intervention did not improve the accuracy and the effort required to do it was substantial.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00068-6}, issn = {0169-2070}, keywords = {Competition, Expert systems, regart} } @ARTICLE{FLW94, author = {Eijte W. Foekens and Peter S. H. Leeflang and Dick R. Wittink}, title = {A comparison and an exploration of the forecasting accuracy of a loglinear model at different levels of aggregation}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {245-261}, number = {2}, abstract = {We compare the * model of retail promotion effects, at different levels of aggregation. The alternative model specifications are: (1) store-level models with homogeneous or heterogeneous response parameters across retail chains, and with or without weekly indicator variables, (2) chain-level models with homogeneous or heterogeneous response parameters across retail chains, and (3) a market-level model. Based on scanner data, we show comparisons between the models in terms of relative frequencies of statistically significant parameter estimates in the expected range of values. Sales forecasts are compared at two levels viz. chain and market level. We find that a comparison of the relative frequencies favors the homogeneous store models (with or without weekly indicators), while the forecasting accuracy examined at both the chain and market levels is superior for chain-specific store models without weekly indicator variables. We also examine differences in the mean squared error between the estimation and validation samples.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90005-1}, issn = {0169-2070}, keywords = {Loglinear model, Aggregate and disaggregate scanner data, Empirical study, Forecasting accuracy at aggregate levelregart} } @ARTICLE{FDF05, author = {Dennis Fok and Dick van Dijk and Philip Hans Franses}, title = {Forecasting aggregates using panels of nonlinear time series}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {785-794}, number = {4}, abstract = {Macroeconomic time series such as total unemployment or total industrial production concern data which are aggregated across regions, sectors, or age categories. In this paper we examine whether forecasts for these aggregates can be improved by considering panel models for the disaggregate series. As many macroeconomic variables have nonlinear properties, we specifically focus on panels of nonlinear time series. We discuss the representation of such models, parameter estimation and a method for generating forecasts. We illustrate the usefulness of our approach for simulated data and for the US coincident index, making use of state-specific component series.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.04.015}, issn = {0169-2070}, keywords = {Data aggregation, Forecasting, Panel of time series, Business cycle, Nonlinearity, Multi-level models, regart} } @ARTICLE{FF01, author = {Dennis Fok and Philip Hans Franses}, title = {Forecasting market shares from models for sales}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {121-128}, number = {1}, abstract = {Dividing forecasts of brand sales by a forecast of category sales, when they are generated from brand specific sales-response models, renders biased forecasts of the brands' market shares. In this note we propose as an alternative a simulation-based method which results in unbiased forecasts of market shares. An application of this forecasting technique to a five brand tuna fish market illustrates its practical relevance.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00075-3}, issn = {0169-2070}, keywords = {Sales models, Market shares, Forecasting, regart} } @ARTICLE{FGS05, author = {David Forrest and John Goddard and Robert Simmons}, title = {Odds-setters as forecasters: The case of English football}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {551-564}, number = {3}, abstract = {Sets of odds issued by bookmakers may be interpreted as incorporating implicit probabilistic forecasts of sporting events. Employing a sample of nearly 10 000 English football (soccer) games, we compare the effectiveness of forecasts based on published odds and forecasts made using a benchmark statistical model incorporating a large number of quantifiable variables relevant to match outcomes. The experts' views, represented by the published odds, are shown to be increasingly effective over a 5-year period. Bootstraps performed on the statistical model fail to outperform the expert judges. The trend towards odds-setters displaying greater expertise as forecasters coincided with a period during which intensifying competition is likely to have increased the financial penalties for bookmakers of imprecise odds-setting. In the context of a financially pressured environment, the main findings of this paper challenge the consensus that subjective forecasting by experts will normally be inferior to forecasts from statistical models.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.03.003}, issn = {0169-2070}, keywords = {Football, Odds, Ordered probit, Comparative forecasting--causal, judgement, Bootstrap-evaluation, regart} } @ARTICLE{FST10, author = {David Forrest and Ismael Sanz and J.D. Tena}, title = {Forecasting national team medal totals at the Summer Olympic Games}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {576 - 588}, number = {3}, note = {Sports Forecasting}, doi = {10.1016/j.ijforecast.2009.12.007}, issn = {0169-2070}, keywords = {Sports forecasting, Olympic Games,Medals} } @ARTICLE{FS00, author = {David Forrest and Robert Simmons}, title = {Forecasting sport: the behaviour and performance of football tipsters}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {317-331}, number = {3}, abstract = {Professional advice is available in several forecasting contexts, such as share prices, sales and the weather. English newspaper tipsters offer professional advice on the outcomes of English and Scottish football (soccer) matches. Such advice could potentially inform selections of bettors in fixed odds or pools betting. This paper investigates the effectiveness of the guidance given by newspaper tipsters. Employing a sample of three tipsters and 1694 English league games, we find that tipster success rates are higher than would follow from random forecasting methods. We identify some differences between the processes by which actual results and tipster forecasts are determined. Likelihood-ratio tests imply that the tipsters fail adequately to utilise easily obtainable public information on teams' strength. Further tests show that only one of three tipsters appears to make successful use of other unspecified information relevant to game outcomes. A consensus forecast across the three tipsters appears to outperform any single tipster.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00050-9}, issn = {0169-2070}, keywords = {Football, Newspaper tipsters, Logit, regart} } @ARTICLE{Forsyth93, author = {Jay D. Forsyth}, title = {Guide to forecasts and projections : Don Pallais and Stephen D. Holton, 1992, (Practitioners Publishing, Fort Worth, TX), 2 vols., \$120.00}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {277-278}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90015-F}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{FVN10, author = {Egon Franck and Erwin Verbeek and Stephan N�esch}, title = {Prediction accuracy of different market structures -- bookmakers versus a betting exchange}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {448 - 459}, number = {3}, note = {Sports Forecasting}, doi = {10.1016/j.ijforecast.2010.01.004}, issn = {0169-2070}, keywords = {Prediction accuracy, Betting,Bookmaker,Bet exchange,Probit regression} } @ARTICLE{Franses08, author = {Philip Hans Franses}, title = {Merging models and experts}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {31-33}, number = {1}, abstract = {It is argued that for specific forecast settings there must exist an optimally-sized model with forecasts that only need occasional adjustments by experts. The argument is built on recent evidence on the interaction between models and experts. A consequence of this is that the future research agenda should involve more interaction between researchers in model-based forecasting and those who are engaged in judgemental forecasting research.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.12.002}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{Franses91, author = {Philip Hans Franses}, title = {Seasonality, non-stationarity and the forecasting of monthly time series}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {199-208}, number = {2}, abstract = {We focus on two forecasting models for a monthly time series. The first model requires that the variable is first order and seasonally differenced. The second model considers the series only in its first differences, while seasonality is modeled with a constant and seasonal dummies. A method to distinguish empirically between these two models is presented. The relevance of this method is established by simulation results as well as empirical evidence, which show, first, that conventional autocorrelation checks are often not discriminative and, second, that considering the first model while the second is more appropriate yields a deterioration of forecasting performance.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90054-Y}, issn = {0169-2070}, keywords = {Monthly time series, Non-stationarity, Seasonality, Seasonal unit roots, Seasonal differencing, Forecasting performance, regart} } @ARTICLE{FD05, author = {Philip Hans Franses and Dick van Dijk}, title = {The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {87-102}, number = {1}, abstract = {Seasonality often accounts for the major part of short-run movements in quarterly or monthly macro economic time series. In addition, business cycle nonlinearity is a prominent feature of many such series. A forecaster can nowadays consider a wide variety of time series models that describe seasonal variation and nonlinear regime-switching behavior. In this paper we examine the forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production series of 18 OECD countries. We find that the accuracy of point forecasts varies widely across series, across forecast horizons and across seasons. However, in general, linear models with fairly simple descriptions of seasonality outperform nonlinear at short forecast horizons, whereas nonlinear models with more elaborate seasonal components dominate at longer horizons. Finally, none of the models is found to render efficient forecasts and hence, forecast combination is worthwhile.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.05.005}, issn = {0169-2070}, keywords = {Nonlinearity, Seasonality, Forecasting, Forecast evaluation, regart} } @ARTICLE{FG99, author = {Philip Hans Franses and Hendrik Ghijsels}, title = {Additive outliers, GARCH and forecasting volatility}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {1-9}, number = {1}, abstract = {The Generalized Autoregressive Conditional Heteroskedasticity [GARCH] model is often used for forecasting stock market volatility. It is frequently found, however, that estimated residuals from GARCH models have excess kurtosis, even when one allows for conditional t-distributed errors. In this paper we examine if this feature can be due to neglected additive outliers [AOs], where we focus on the out-of-sample forecasting properties of GARCH models for AO-corrected returns. We find that models for AO-corrected data yield substantial improvement over GARCH and GARCH-t models for the original returns, and that this improvement holds for various samples, two forecast evaluation criteria and four stock markets.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00053-3}, issn = {0169-2070}, keywords = {GARCH, Additive outlier, Forecasting volatility, regart} } @ARTICLE{FK96, author = {Philip Hans Franses and Frank Kleibergen}, title = {Unit roots in the Nelson-Plosser data: Do they matter for forecasting?}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {283-288}, number = {2}, abstract = {In this paper we compare two univariate time series models, i.e. one with and one without an imposed unit root, in a forecasting experiment for the fourteen annually observed US data analyzed by Nelson and Plosser (1982, Journal of Monetary Economics 10, 139-162). Our main result is that the unit root model is regularly preferred. This result holds for a variety of sample sizes and forecast horizons as well as for one-step and multi-step ahead forecasts.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00629-X}, issn = {0169-2070}, keywords = {Unit roots, Forecasting, regart} } @ARTICLE{FK98, author = {Philip Hans Franses and Anne B. Koehler}, title = {A model selection strategy for time series with increasing seasonal variation}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {405-414}, number = {3}, abstract = {We propose a model selection strategy for time series with increasing seasonal variation. This strategy amounts to a selection of the most appropriate differencing filter to obtain a stationary time series without using a Box-Cox transformation. Hence, it is based on a sequence of tests for nonseasonal and seasonal unit roots. Through Monte Carlo replications, we provide new tables of critical values for the various test statistics. We apply our methods, which can be automated, to six example series and find that the results compare favorably to those of an expert.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00041-7}, issn = {0169-2070}, keywords = {Model selection strategy, Time series, seasonal variation, regart} } @ARTICLE{FL09, author = {Philip Hans Franses and Rianne Legerstee}, title = {Properties of expert adjustments on model-based SKU-level forecasts}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {35-47}, number = {1}, abstract = {The recent literature on expert adjustment of model-based forecasts at the SKU level suggests that such adjustments occur quite frequently. Second, over-optimism of experts is found to cause adjustments to be upwards more often than downwards. We analyze a unique database containing one-step-ahead model-based forecasts adjusted by many experts, who are located in 37 countries, and are making forecasts for pharmaceutical products within 7 distinct categories. Our results are consistent with earlier findings that the experts make frequent adjustments and that these tend to be upward. Next, and this is new to the literature, we document the fact that expert adjustment itself is largely predictable, where the weight of a forecaster's own earlier adjustment is about three times as large as the weight of past model-based forecast errors. We also show that expert adjustment is not independent of the model-based forecasts, and we argue that this affects the way we should evaluate the contribution of expert adjustment to the overall forecast quality.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.11.009}, issn = {0169-2070}, keywords = {Adjusting forecasts, Automatic forecasting, Decision making, Evaluating forecasts, Judgemental forecasting, regart} } @ARTICLE{FO97, author = {Philip Hans Franses and Marius Ooms}, title = {A periodic long-memory model for quarterly UK inflation}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {117-126}, number = {1}, abstract = {We consider an extension of the fractionally integrated ARIMA(0, d, 0) model for quarterly UK inflation, where we allow the fractional integration parameter d to vary with the season s. This periodic ARFIMA(0, d, 0) model does not only provide an informative in-sample description, it may also be useful for out-of-sample forecasting. The main result is that the integration parameter in the first two quarters is significantly larger than that in the last two quarters.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00715-7}, issn = {0169-2070}, keywords = {Fractional integration, Seasonal time series, Periodic models, regart} } @ARTICLE{FPV04, author = {Philip Hans Franses and Richard Paap and Bj{\"o}rn Vroomen}, title = {Forecasting unemployment using an autoregression with censored latent effects parameters}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {255-271}, number = {2}, abstract = {Monthly observed unemployment typically displays explosive behavior in recessionary periods, while there seems to be stationary behavior in expansions. Allowing parameters in an autoregression to vary across regimes, and hence over time, can capture this feature. In this paper, we put forward a new autoregressive time series model with time-varying parameters, where this variation depends on a linear indicator variable. When the value of this variable exceeds a stochastic threshold level, the parameters change. We discuss representation, estimation and interpretation of the model. Also, we analyze its forecasting performance for unemployment series of three G-7 countries, and we compare it with various related models.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.09.004}, issn = {0169-2070}, keywords = {Nonlinear time series, Unemployment, Censored regression, regart} } @ARTICLE{FR93, author = {Philip Hans Franses and Gerbert Romijn}, title = {Periodic integration in quarterly UK macroeconomic variables}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {467-476}, number = {4}, abstract = {This paper presents empirical evidence on the seasonal patterns in several UK macroeconomic variables, additional to related evidence reported in Osborn (International Journal of Forecasting (1990), 6, 327-336). The method used is a test procedure for seasonal unit roots that allows parameters to vary over the seasons. This extension of currently applied procedures can select between seasonal and periodic integration. In a small Monte Carlo experiment, this new method is evaluated with respect to two rival procedures. The empirical results for the UK variables indicate that many of these are periodically integrated. The implications of this outcome on modelling and forecasting are discussed. One of the implications is that a periodic error correction model for the univariate series can outperform non-periodic models with respect to forecasting.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90074-W}, issn = {0169-2070}, keywords = {Seasonality, Periodic processes, Unit roots, Forecasting, regart} } @ARTICLE{Franses00, author = {P. H. B. F. Franses}, title = {The Econometric Modelling of Financial Time Series: Second Edition, Terence C. Mills, (Cambridge: Cambridge University Press, 1999) 380 pages, Paperback; ISBN 0521-62492-4 (\$27.95). Hardback: ISBN 0521-62413-4 (\$80.00)}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {426-427}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00046-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Freebairn94, author = {John Freebairn}, title = {The agricultural commodity market forecasting game}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {139-142}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90054-X}, issn = {0169-2070} } @ARTICLE{Freedman09, author = {David A. Freedman}, title = {Diagnostics cannot have much power against general alternatives}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {833 - 839}, number = {4}, note = {Special section: Decision making and planning under low levels of predictability}, doi = {10.1016/j.ijforecast.2009.05.004}, issn = {0169-2070}, keywords = {Specification error, Specification tests,Model testing,Forecast uncertainty,Causal inference} } @ARTICLE{FM04, author = {R. K. Freeland and B. P. M. McCabe}, title = {Forecasting discrete valued low count time series}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {427-434}, number = {3}, abstract = {In the past, little emphasis has been placed on producing data coherent forecasts for discrete valued processes. In this paper the conditional median is suggested as a general method for producing coherent forecasts and is in contrast to the conventional conditional mean. When counts are low we suggest that the emphasis of the forecast method be changed from forecasting future values to forecasting the k-step-ahead conditional distribution. In practice, this usually depends on unknown parameters. We modify the distribution to account for estimation error in a coherent way. The ideas are exemplified by an analysis of Poisson Autoregressive model and of wage loss claims data.}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00014-1}, issn = {0169-2070}, keywords = {Birth and death process, Data coherence, Forecasting, Maximum likelihood, Poisson autoregression, Queuing process, regart} } @ARTICLE{FM04a, author = {Edward W. Frees and Thomas W. Miller}, title = {Sales forecasting using longitudinal data models}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {99-114}, number = {1}, abstract = {This paper shows how to forecast using a class of linear mixed longitudinal, or panel, data models. Forecasts are derived as special cases of best linear unbiased predictors, also known as BLUPs, and hence are optimal predictors of future realizations of the response. We show that the BLUP forecast arises from three components: (1) a predictor based on the conditional mean of the response, (2) a component due to time-varying coefficients, and (3) a serial correlation correction term. The forecasting techniques are applicable in a wide variety of settings. This article discusses forecasting in the context of marketing and sales. In particular, we consider a data set of the Wisconsin State Lottery, in which 40 weeks of sales are available for each of 50 postal codes. Using sales data as well as economic and demographic characteristics of each postal code, we forecast sales for each postal code.}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00005-0}, issn = {0169-2070}, keywords = {Panel data models, Unobserved effects, Random coefficients, Heterogeneity, regart} } @ARTICLE{FIK09, author = {Ana-Maria Fuertes and Marwan Izzeldin and Elena Kalotychou}, title = {On forecasting daily stock volatility: The role of intraday information and market conditions}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {259-281}, number = {2}, abstract = {Several recent studies advocate the use of nonparametric estimators of daily price variability that exploit intraday information. This paper compares four such estimators, realised volatility, realised range, realised power variation and realised bipower variation, by examining their in-sample distributional properties and out-of-sample forecast ranking when the object of interest is the conventional conditional variance. The analysis is based on a 7-year sample of transaction prices for 14 NYSE stocks. The forecast race is conducted in a GARCH framework and relies on several loss functions. The realized range fares relatively well in the in-sample fit analysis, for instance, regarding the extent to which it brings normality in returns. However, overall the realised power variation provides the most accurate 1-day-ahead forecasts. Forecast combination of all four intraday measures produces the smallest forecast errors in about half of the sampled stocks. A market conditions analysis reveals that the additional use of intraday data on day t-1 to forecast volatility on day t is most advantageous when day t is a low volume or an up-market day. These results have implications for option pricing, asset allocation and value-at-risk.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2009.01.006}, issn = {0169-2070}, keywords = {Conditional variance, Realised volatility, Nonparametric estimators, Intraday prices, Superior predictive ability, regart} } @ARTICLE{FK07, author = {Ana-Maria Fuertes and Elena Kalotychou}, title = {Optimal design of early warning systems for sovereign debt crises}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {85-100}, number = {1}, abstract = {This paper tackles the design of an optimal early warning system (EWS) for sovereign default from two distinct angles: the choice of the econometric methodology and the evaluation of the EWS itself. It compares K-means clustering of macrodata, a logit regression for macrodata, a logit regression for credit ratings, and the combined forecasts from all three methods. The optimal choice of forecast method is shown to depend on the desired trade-off between missed defaults and false alarms. Hence, it is crucial to account for the decision-maker's preferences which are characterized through a loss function and risk-aversion parameter. Recursive forecast combining generally yields a better balance of type I and type II errors than any of the individual forecasting methods, and outperforms the naïve predictions.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.07.001}, issn = {0169-2070}, keywords = {Country risk analysis, Clustering, Default prediction, Emerging markets, Forecast combining, Logit forecast, Loss function, regart} } @ARTICLE{FO01, author = {{Shin-ichi} Fukuda and Takashi Onodera}, title = {A new composite index of coincident economic indicators in Japan: how can we improve forecast performances?}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {483-498}, number = {3}, abstract = {The purpose of this paper is to construct a new composite index of coincident economic indicators in Japan and to demonstrate their usefulness in forecasting short-run economic fluctuations in the 1990s. The method of construction is based on the single-index dynamic factor model. Our two types of indexes are highly correlated with the traditional composite index compiled by the EPA over business-cycle horizons. However, standard leading indicators, which failed to forecast the traditional composite index, make a satisfactory performance in forecasting our indexes in the 1990s. In addition, lagged values of our indexes help to improve the leading indicators performance in forecasting the traditional composite index in the 1990s. The result is noteworthy because several research institutes in Japan made serious errors in forecasting business cycles and prolonged recessions in the 1990s.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00090-5}, issn = {0169-2070}, keywords = {Business cycles, Composite Indicators, Macroeconomic forecasting, Kalman filter, regart} } @ARTICLE{Fullerton89, author = {Thomas M. Fullerton}, title = {A composite approach to forecasting state government revenues: Case study of the Idaho sales tax}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {373-380}, number = {3}, abstract = {Fiscal problems have led to increased reliance on economic and revenue forecasting by state governments in recent years. As a means of improving accuracy, many forecasters use alternative outlooks. Composite modeling goes a step further and allows analysts to systematically combine two or more forecasts. This paper examines the effectiveness of composite forecasting of sales tax revenues in Idaho. Base line projections are provided by an econometric model and a univariate time series model. The composite forecasts are found to outperform both base line forecasts. The combined forecasts are also found to be more accurate than the executive branch forecasts actually utilized from 1982 through 1985.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90040-X}, issn = {0169-2070}, keywords = {Composite forecasting, Econometric modeling, State revenue forecasting, Univariate ARIMA analysis, regart} } @ARTICLE{FLW01, author = {Thomas M. Fullerton and Mika M. Laaksonen and Carol T. West}, title = {Regional multi-family housing start forecast accuracy}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {171-180}, number = {2}, abstract = {This paper extends earlier research regarding the predictability of residential construction activity in regional markets. Because of their implications for overall business conditions, housing start forecasts traditionally represent one of the most important components of regional prediction efforts. Quarterly frequency data are assembled from previously published econometric forecasts for Florida and its six largest metropolitan economies. The sample simulation period covers 1985:1-1996:2 and includes all three business cycle phases: expansion, recession, and recovery. Multi-family housing start forecasts are compared to univariate time series and random walk alternatives. Results indicate that structural model forecasts of multi-family regional housing activity are comparatively less reliable than those for nonagricultural employment, but superior to those for single-family residential construction.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00082-0}, issn = {0169-2070}, keywords = {Econometric forecasting analysis, Regional multi-family housing activity, regart} } @ARTICLE{Funke97, author = {Michael Funke}, title = {Supply potential and output gaps in West German manufacturing}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {211-222}, number = {2}, abstract = {Data on West Germany manufacturing output and producer prices are analysed to extract information on underlying demand and supply shocks. Identification is achieved using long-run restrictions, based on a theoretical model. The main results are that both demand and supply shocks are important in explaining German business cycles from 1965 to 1993. Finally, the structural VAR gap measures are compared with alternative univariate gap measures and it is shown that the predictability range of inflation could be enhanced when alternative output gap measures are combined.}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00717-6}, issn = {0169-2070}, keywords = {VAR models, Inflation, regart} } @ARTICLE{Funke90, author = {Michael Funke}, title = {Assessing the forecasting accuracy of monthly vector autoregressive models : The case of five OECD countries}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {363-378}, number = {3}, abstract = {Vector autoregressions have been proposed as good forecasting models in the recent past. This paper presents five different VAR specifications of the level of industrial production in five major industrial countries estimated on monthly data. The forecasting performance of the various specifications is analysed and compared with the accuracy of univariate time-series models. In general, the VAR forecasts perform better than the alternative procedures. Their performance in forecasting the calender outcome 1988:1-1988:12 (on an ex ante basis after the stock market crash in October 1987) reveals, however, that all VAR's have underestimated the growth rates in industrial production.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90063-H}, issn = {0169-2070}, keywords = {Multivariate time-series methods, Univariate time-series methods, Forecast evaluation, regart} } @ARTICLE{Gagnon97, author = {Joseph E. Gagnon}, title = {Predicting external imbalances for the United States and Japan}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {300-300}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00012-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Galbraith03, author = {John W. Galbraith}, title = {Content horizons for univariate time-series forecasts}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {43-55}, number = {1}, abstract = {This paper investigates the maximum horizon at which conditioning information can be shown to have value for univariate time series forecasts. In particular, we consider the problem of determining the horizon beyond which forecasts from univariate time series models of stationary processes add nothing to the forecast implicit in the unconditional mean. We refer to this as the content horizon for forecasts, and provide a formal definition of the corresponding forecast content function at horizons s=1,... S. This function depends upon parameter estimation uncertainty as well as on autocorrelation structure of the process. We show that for autoregressive processes it is possible to give an asymptotic expression for the forecast content function, and show by simulation that the expression gives a good approximation even at modest sample sizes. The results are applied to the growth rate of GDP and to inflation, using US and Canadian data.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00124-8}, issn = {0169-2070}, keywords = {Autoregression, Forecast horizon, Long term forecasting, Macroeconomic forecasting, Time series, regart} } @ARTICLE{GK05, author = {John W. Galbraith and Turgut K?s?nbay}, title = {Content horizons for conditional variance forecasts}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {249-260}, number = {2}, abstract = {Using realized variance to estimate daily conditional variance of financial returns, we compare forecasts of daily variance from standard GARCH and FIGARCH models estimated by Quasi-Maximum Likelihood (QML), and from projections on past realized volatilities obtained from high-frequency data. We consider horizons extending to 30 trading days. The forecasts are compared with the unconditional sample variance of daily returns treated as a predictor of daily variance, allowing us to estimate the maximum horizon at which conditioning information has exploitable value for variance forecasting. With foreign exchange return data (DM/$US and Yen/$US), we find evidence of forecasting power at horizons of up to 30 trading days, on each of two financial returns series. We also find some evidence that the result of (e.g.) Bollerslev and Wright [Bollerslev, T., & Wright, J. H. (2001) High-frequency data, frequency domain inference, and volatility forecasting. Review of Economics and Statistics, 83, 596-602], that projections on past realized variance provide better one-step forecasts than the QML-GARCH and -FIGARCH forecasts, appears to extend to longer horizons up to around 10 to 15 trading days. At longer horizons, there is less to distinguish the forecast methods, but the evidence does suggest positive forecast content at 30 days for various forecast types.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.10.002}, issn = {0169-2070}, keywords = {GARCH, High-frequency data, Integrated variance, Realized variance, regart} } @ARTICLE{Garcia-Ferrer96, author = {Antonio Garcia-Ferrer}, title = {Dynamic econometrics : David F. Hendry, 1995, (Oxford University Press, Oxford), 904 pp., paperback, �25.00, ISBN 0-19-828316-4, hardback, �50.00, ISBN 0-19-828317-2.}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {306-308}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00646-X}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Garcia-Ferrer03, author = {Antonio Garc{\'i}a-Ferrer}, title = {Macroeconomics and the Real World. Volume 1: Econometric Techniques and Macroeconomics,: Roger E. Backhouse and Andrea Salanti (Eds.), Oxford University Press, New York, 2001, Paperback, 301 pages, ISBN 0199242046, \$26.95.}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {525-527}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00024-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Garcia-Ferrer03a, author = {Antonio Garc{\'i}a-Ferrer}, title = {A Course in Time Series Analysis,: Daniel Pe{\~n}a, George C. Tiao and Ruey S. Tsay (Eds.), John Wiley, New York, 2001. ISBN:0-471-36164-X, pp. 460, \$75.00.}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {527-530}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00023-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Garcia-Ferrer00, author = {Antonio Garc{\'i}a-Ferrer}, title = {Business Cycles: Durations, Dynamics and Forecasting: Francis X. Diebold and Glenn D. Rudebusch, Princeton University Press, Princeton 1999. Hardcover, 420 pages. ISBN: 0-691-01218-0, \$49.50}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {283-286}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00039-X}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Garcia-Ferrer00a, author = {Antonio Garc{\'i}a-Ferrer}, title = {Econometric Business Cycle Research: Jan Jacobs, Kluwer Academic Publishers, Boston, 1997. Hardcover, 228 pages. ISBN; 0-7923-8254-4, \$100}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {286-288}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00042-X}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Garcia-Ferrer98, author = {Antonio Garc{\'i}a-Ferrer}, title = {Professor Zellner: An interview for the International Journal of Forecasting}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {303-312}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00046-6}, issn = {0169-2070}, keywords = {revart} } @ARTICLE{GB00, author = {Antonio Garc{\'i}a-Ferrer and Marcos Bujosa-Brun}, title = {Forecasting OECD industrial turning points using unobserved components models with business survey data}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {207-227}, number = {2}, abstract = {The approach followed in this paper stresses the importance of timing in signalling turning points. This is done in two stages; first a signal that a turning point is likely to occur, and later a statement of when it will occur. We use Young's trend derivative method, adding leading qualitative survey data. We find high coherence between its low frequency component and that of the corresponding economic variable. We study industrial production in six OECD countries with special emphasis on France and Spain. Inclusion of survey data improves forecast accuracy.}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00049-7}, issn = {0169-2070}, keywords = {Turning point forecasting, Unobserved components and qualitative survey data, regart} } @ARTICLE{GGP+05, author = {Antonio Garc{\'i}a-Ferrer and Jan G. De Gooijer and Pilar Poncela and Esther Ruiz}, title = {Introduction to nonlinearities, business cycles, and forecasting}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {623-625}, number = {4}, note = {Nonlinearities, Business Cycles and Forecasting}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.04.001}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{GJP06, author = {A. Garc{\'i}a-Ferrer and A. de Juan and P. Poncela}, title = {Forecasting traffic accidents using disaggregated data}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {203-222}, number = {2}, abstract = {Traffic accidents, measured monthly, present different characteristics when the aggregate is compared to its individual components. When disaggregated data are used, the effects of policy variables, calendar events, and different seasonal behaviors should be clearly understood and their coefficients properly estimated. In this paper, we compare the empirical performance of various models in assessing the effects of policy variables, legal changes, and traffic security campaigns. In addition, aggregated versus disaggregated forecasts of the main accident variables are compared in order to examine the robustness of the forecasting improvement from using disaggregated data. In particular, we test the robustness of this improvement against the specification of the model, information set, type of measure of forecasting accuracy, and forecast year. Overall, we conclude that forecast combinations based on disaggregated models display better performance.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.11.001}, issn = {0169-2070}, keywords = {Accuracy criteria, Disaggregation, Forecast combination, Time series, Traffic accidents, regart} } @ARTICLE{GQ98, author = {Antonio Garc{\'i}a-Ferrer and Ricardo A. Queralt}, title = {Can univariate models forecast turning points in seasonal economic time series?}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {433-446}, number = {4}, abstract = {Based on a particular class of recently developed unobserved component models with, time varying parameters, the objectives of this paper are two-fold. On the one hand, we propose an alternative measure of underlying growth based on our estimated trend derivative with no need for any further transformations. Additionally, using the information embedded on the trend derivative, we provide a simple method for improving quantitative point forecasts in the vicinity of turning points. Empirical applications are presented for a set of seasonal monthly economic indicators of the Spanish economy.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00043-0}, issn = {0169-2070}, keywords = {Unobserved components, Underlying growth estimator, Turning point forecasting, regart} } @ARTICLE{GQ97, author = {Antonio Garc{\'i}a-Ferrer and Ricardo A. Queralt}, title = {A note on forecasting international tourism demand in Spain}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {539-549}, number = {4}, abstract = {This paper considers the extent to which price and income proxy variables help in forecasting tourist demand in Spain. Contrary to some recent studies, we found that the inputs' contribution in terms of fitting and forecasting is nil when compared with alternative univariate models. Whether these findings are the results of the restrictions embedded in building the proxy inputs or in a poor specification of the dynamics of these models remains to be seen. We also contend that when dealing with medium, long-term forecasting comparisons, the use of the traditional aggregate accuracy measures like RMSE and MAPE help very little in discriminating among competing models. In these situations, predicted annual growth rates may be a better alternative.}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00033-2}, issn = {0169-2070}, keywords = {Tourism demand, Unobserved components models, Forecasting accuracy measures, regart} } @ARTICLE{GQB01, author = {Antonio Garc{\'i}a-Ferrer and Ricardo Queralt and Cristina Blazquez}, title = {A growth cycle characterisation and forecasting of the Spanish economy: 1970-1998}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {517-532}, number = {3}, abstract = {In contrast to classical cycles, growth cycles are more likely to represent the present stage of economic activity. This paper analyzes the growth cycle chronology of the Spanish economy from 1970 to 1998, based on the official rules depicted by the Spanish Statistical Institute. Alternatively, we propose a simple method that not only anticipates such reference cycle but can also be used as a forecasting tool in predicting turning points. Given these good properties, the method is also used in computing the so-called `stylized facts' among the main economic aggregates.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00097-8}, issn = {0169-2070}, keywords = {Detrending, Growth cycles, Filters, Turning points, regart} } @ARTICLE{Gardner93, author = {Everette S. Gardner}, title = {Forecasting the failure of component parts in computer systems: A case study}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {245-253}, number = {2}, abstract = {This paper is an applied study in forecasting the failure of component parts in computer systems to aid in production planning and inventory control. The aim is to develop a reasonably simple forecasting system that can be operated by managers rather than statisticians. Monthly failures of components are shown to be related to cumulative shipments from the factory after a time lag of several months. This relationship is modelled using discounted-least-squares regression, a methodology that appears to be rare in practice. Simulated forecast accuracy is then compared with two alternatives, exponential smoothing and a combination of regression and smoothing forecasts. Discounted regression proves to be the most accurate and is therefore implemented.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90008-B}, issn = {0169-2070}, keywords = {Regression analysis, Combining forecasts, Monitoring forecasts, Exponential smoothing, regart} } @ARTICLE{GA97, author = {Everette S. Gardner and Elizabeth A. Anderson}, title = {Focus forecasting reconsidered}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {501-508}, number = {4}, abstract = {Focus Forecasting is a popular heuristic methodology for production and inventory control although there has never been a rigorous test of accuracy using real time series. We compare Focus Forecasting to damped-trend, seasonal exponential smoothing using five time series of cookware demand in a production planning application. We also make comparisons using 91 time series from the M-Competition study of forecast accuracy. Exponential smoothing was more accurate in both cases.}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00035-6}, issn = {0169-2070}, keywords = {Exponential smoothing, Forecasting, Focus forecasting, Inventory control systems, regart} } @ARTICLE{GAW01, author = {Everette S. Gardner and Elizabeth A. Anderson-Fletcher and Angela M. Wicks}, title = {Further results on focus forecasting vs. exponential smoothing}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {287-293}, number = {2}, abstract = {In an earlier paper, we found that damped-trend, seasonal exponential smoothing was more accurate than a simple version of Focus Forecasting, based on Flores and Whybark [Production and Inventory Management Journal, (1986), 14, 339-366]. This note tests Demand Solutions, a more sophisticated version of Focus Forecasting. As in the earlier paper, we used five time series of cookware demand from a production planning application and 91 time series from the M-Competition study of forecast accuracy. Results are much the same as in our earlier paper. Exponential smoothing is substantially more accurate than Demand Solutions. This is perhaps not surprising in that Demand Solutions' forecasting rules are arbitrary, with no statistical rationale. Users of Focus Forecasting have much to gain by adopting statistical forecasting methods.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00098-4}, issn = {0169-2070}, keywords = {Exponential smoothing, Focus forecasting, Comparative forecasting methods - time series, Production and operations planning, regart} } @ARTICLE{GD02, author = {Everette S. Gardner and Joaquin Diaz-Saiz}, title = {Seasonal adjustment of inventory demand series: a case study}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {117-123}, number = {1}, abstract = {This paper analyzes procedures for seasonal adjustment of inventory demand series at a large US auto parts distributor, BPX Holding Corporation of Houston, TX. The company's forecasting system made no attempt to classify demand series as seasonal or nonseasonal. All demand series were assumed to be seasonal. They were seasonally-adjusted using a multiplicative decomposition procedure, then forecasted with exponential smoothing. We show that simple methods of identifying seasonal series, coupled with an additive decomposition procedure, can make significant reductions in forecast errors and safety stock investment. We also discuss forecasting implementation problems in inventory control systems.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00108-X}, issn = {0169-2070}, keywords = {Forecasting, Time series, Seasonal adjustment, Inventory, Distribution, regart} } @ARTICLE{GM88, author = {Everette S. Gardner and Spyros Makridakis}, title = {The future of forecasting}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {325-330}, number = {3}, abstract = {This paper discusses our aims in organizing this special issue. We believe that a synthesis of the field is needed to resolve the many conflicts between theory and empirical evidence and between advocates of the various forecasting methods. One step toward synthesis is to agree on the major problems in the field, the goal of this issue. Another step is to establish standards for both practice and research and some proposals are made to this end. We also give some personal opinions on the most important research opportunities in the field.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90100-8}, issn = {0169-2070}, keywords = {Forecasting-general, judgment, time series, econometrics, regart} } @ARTICLE{GJ06, author = {Gardner, Jr., Everette S.}, title = {Exponential smoothing: The state of the art--Part II}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {637-666}, number = {4}, abstract = {In Gardner [Gardner, E. S., Jr. (1985). Exponential smoothing: The state of the art. Journal of Forecasting 4, 1-28], I reviewed the research in exponential smoothing since the original work by Brown and Holt. This paper brings the state of the art up to date. The most important theoretical advance is the invention of a complete statistical rationale for exponential smoothing based on a new class of state-space models with a single source of error. The most important practical advance is the development of a robust method for smoothing damped multiplicative trends. We also have a new adaptive method for simple smoothing, the first such method to demonstrate credible improved forecast accuracy over fixed-parameter smoothing. Longstanding confusion in the literature about whether and how to renormalize seasonal indices in the Holt-Winters methods has finally been resolved. There has been significant work in forecasting for inventory control, including the development of new predictive distributions for total lead-time demand and several improved versions of Croston's method for forecasting intermittent time series. Regrettably, there has been little progress in the identification and selection of exponential smoothing methods. The research in this area is best described as inconclusive, and it is still difficult to beat the application of a damped trend to every time series.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.03.005}, issn = {0169-2070}, keywords = {Time series--ARIMA, exponential smoothing, state-space models, identification, stability, invertibility, model selection, Comparative methods--evaluation, Intermittent demand, Inventory control, Prediction intervals, Regression--discount weighted, kernel, regart} } @ARTICLE{GJ85, author = {Gardner, Jr., Everette S.}, title = {Everette S. Gardner Jr., The strange case of the lagging forecasts, Interfaces 14 (1984), pp. 47-50.}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {312-312}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(85)80055-8}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Gardner2008, author = {Gardner, Jr., Everette S. and Joaquin Diaz-Saiz}, title = {Exponential smoothing in the telecommunications data}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {170-174}, number = {1}, abstract = {Exponential smoothing methods gave poor forecast accuracy in Fildes et al.'s study of telecommunications time series. We reexamine this study and show that the accuracy of the Holt and damped trend methods can be improved by trimming the time series to eliminate irrelevant early data, fitting the methods to minimize the MAD rather than the MSE, and optimizing the parameters. Contrary to Fildes et al., we show that the damped trend is more accurate than Holt's method. Because most of the telecommunications series display steady trends, we test the Theta method of forecasting and a closely related method, simple exponential smoothing with drift. The Theta method proves disappointing, but simple exponential smoothing with drift is the best smoothing method for this data, giving about the same accuracy as the robust trend.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.05.002}, issn = {0169-2070}, keywords = {Comparative methods -- evaluation, Time series -- exponential smoothing, Robust trend, Theta method, regart} } @ARTICLE{GJK05, author = {Gardner, Jr., Everette S. and Anne B. Koehler}, title = {Comments on a patented bootstrapping method for forecasting intermittent demand}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {617-618}, number = {3}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.04.021}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Garman87, author = {Mark B. Garman}, title = {Perpetual currency options}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {179-184}, number = {1}, abstract = {This paper explores the properties of perpetual currency options and their uses. Perpetual currency options could be highly useful in controlling the uncertainties of foreign currency flows of unknown timing. Yet they are not traded in any market at the time of the present writing. Nonetheless, they have several interesting uses in both theoretical and trading environments. As American-style options, perpetual options provide boundary conditions as the limiting cases of short-lived traded options. They possess the theoretical advantage that valuation equations, hedge ratios, and related quantities may be written down, in contrast to their shorter-term American currency option counterparts. Due to their relative simplicity, there is also a nomogram which graphically depicts their exercise boundaries. By replication techniques, perpetual currency options may be produced even in the absence of actual markets in the instrument.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90087-2}, issn = {0169-2070}, keywords = {Currency options, Foreign exchange, Perpetual, Option exercise boundary, regart} } @ARTICLE{GLM+09, author = {Anthony Garratt and Kevin Lee and Emi Mise and Kalvinder Shields}, title = {Real time representation of the UK output gap in the presence of model uncertainty}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {81-102}, number = {1}, abstract = {We undertake an empirical analysis of the UK output gap using real-time data and an approach that accommodates, in a coherent way, three types of uncertainty when measuring the gap. These are model uncertainty (associated with the choice of model and de-trending technique), estimation uncertainty (with a given model) and measurement uncertainty (associated with the reliability of the data). The approach employs VAR models, along with Bayesian-style `model averaging' procedures, to jointly explain and forecast real-time measures and realisations of output series. A comprehensive representation of the UK output gap and the associated uncertainties are provided in real time by probability forecasts over 1961q2-2005q4.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.11.005}, issn = {0169-2070}, keywords = {Output gap, Real time data, Revisions, Output trends, Model uncertainty, Probability forecasts, regart} } @ARTICLE{GM03, author = {William T. Gavin and Rachel J. Mandal}, title = {Evaluating FOMC forecasts}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {655-667}, number = {4}, abstract = {Monetary policy outcomes have improved since the early 1980s. One factor contributing to the improvement is that Federal Reserve policymakers began reporting economic forecasts to Congress in 1979. These forecasts indicate what the Federal Open Market Committee (FOMC) members think will be the likely consequence of their policies. We evaluate the accuracy of the FOMC forecasts relative to private sector forecasts, the forecasts of the Research Staff at the Board of Governors, and a naïve alternative. We find that the FOMC output forecasts were better than the naïve model and at least as good as those of the private sector and the Fed staff. The FOMC inflation forecasts were more accurate than the private sector forecasts and the naïve model; for the period ending in 1996, however, they were not as accurate as Fed staff inflation forecasts.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00075-4}, issn = {0169-2070}, keywords = {Federal Reserve, Forecast evaluation, Monetary policy, regart} } @ARTICLE{Gemmill88, author = {Gordon Gemmill}, title = {Modelling financial time series : Stephen Taylor, (Wiley, 1986) pp. 268, \$34.95, �19.95}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {496-497}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90115-X}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Gemmill86, author = {Gordon Gemmill}, title = {A complete guide to the futures markets: Fundamental analysis, technical analysis, trading, spreads and options}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {251-252}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90127-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Gemmill86a, author = {Gordon Gemmill}, title = {Handbook of futures markets: Commodity, financial stock index and options: Perry J. Kaufman, ed., (Wiley-Interscience, New York, 1984) \$75.00/�86.95, pp. 1500 approx.}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {251-252}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90126-3}, issn = {0169-2070}, key = {tagkey1986251}, keywords = {bookrev} } @ARTICLE{GS04, author = {Ramazan Gen{\c c}ay and Faruk Sel{\c c}uk}, title = {Extreme value theory and Value-at-Risk: Relative performance in emerging markets}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {287-303}, number = {2}, abstract = {In this paper, we investigate the relative performance of Value-at-Risk (VaR) models with the daily stock market returns of nine different emerging markets. In addition to well-known modeling approaches, such as variance-covariance method and historical simulation, we study the extreme value theory (EVT) to generate VaR estimates and provide the tail forecasts of daily returns at the 0.999 percentile along with 95% confidence intervals for stress testing purposes. The results indicate that EVT-based VaR estimates are more accurate at higher quantiles. According to estimated Generalized Pareto Distribution parameters, certain moments of the return distributions do not exist in some countries. In addition, the daily return distributions have different moment properties at their right and left tails. Therefore, risk and reward are not equally likely in these economies.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.09.005}, issn = {0169-2070}, keywords = {Value-at-Risk, Financial risk management, Extreme value theory, Nonlinear tail forecasts, regart} } @ARTICLE{GS01, author = {Ramazan Gen{\c c}ay and Faruk Sel{\c c}uk}, title = {Software reviews}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {305-317}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00084-X}, issn = {0169-2070}, keywords = {prodrev} } @ARTICLE{GO91, author = {Pamela Texter Geriner and J. Keith Ord}, title = {Automatic forecasting using explanatory variables: A comparative study}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {127-140}, number = {2}, abstract = {Automatic model selection techniques can be an effective and efficient method of forecasting in certain business situations. The purpose of this study is to examine the potential of these automated methods for developing multivariate forecasting models; univariate models are utilized as benchmarks by which to evaluate the performance of the multivariate schemes. For the multivariate cases, ex ante and ex post forecasts for the input series are compared. Ten pairs of selected indicator, industry, and international macroeconomic series are used to evaluate forecasting performance. The results of this research show that overall the Box-Jenkins transfer function models perform more accurately. Also, it is found that misspecification of the transfer function component often produces poorer forecasts than simple univariate methods that ignore the explanatory variables altogether.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90047-Y}, issn = {0169-2070}, keywords = {Automatic forecasting, Time series analysis, Multivariate forecasting methods, regart} } @ARTICLE{GT06, author = {Richard Gerlach and Frank Tuyl}, title = {MCMC methods for comparing stochastic volatility and GARCH models}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {91-107}, number = {1}, abstract = {This paper presents Markov chain Monte Carlo and importance sampling techniques for volatility estimation, model misspecification testing and comparisons for general volatility models, including GARCH and stochastic volatility formulations. Integrated model likelihoods are estimated and employed to compare among competing classes of volatility model. The performance of some GARCH and stochastic volatility models, incorporating fat-tailed errors and Markov switching, is compared for the S&P500 daily return index and the US/Canadian dollar exchange rate. The comparison is made using integrated likelihoods and residuals, incorporating parameter uncertainty and some model uncertainty. Simulation studies are carried out to confirm that the Bayesian approach is reliable for these models.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.04.020}, issn = {0169-2070}, keywords = {Regime switching, Bayes factors, Importance sampling, regart} } @ARTICLE{GIL93, author = {Mary E. Gerlow and Scott H. Irwin and Te-Ru Liu}, title = {Economic evaluation of commodity price forecasting models}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {387-397}, number = {3}, abstract = {Price forecasts are typically evaluated on the basis of statistical criteria, such as mean error, mean absolute error, or root mean squared error. An alternative approach for evaluating price forecasts is to analyze them using economic criteria. Four types of economic criteria are applied to five quarterly hog price forecasting models over the period 1976:I-1985:IV. In general, model evaluations under the different economic criteria are consistent with one another. However, the economic evaluations are not consistent with those found using traditional statistical evaluation.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90032-I}, issn = {0169-2070}, keywords = {Forecasting, Commodity prices, Economic, Evaluation, Market timing, regart} } @ARTICLE{GMB+07, author = {Tony Van Gestel and David Martens and Bart Baesens and Daniel Feremans and Johan Huysmans and Jan Vanthienen}, title = {Forecasting and analyzing insurance companies' ratings}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {513-529}, number = {3}, abstract = {Insurance companies sell protection to policy holders against many types of risks: property damage or loss, health and casualties, financial losses, etc. In return for this risk protection, insurance companies receive a premium from the policy holder, which is used to cover expenses and the expected risk. For longer-term risk protections, part of the premiums are invested to get higher yields. Although the protection buyer mitigates the individual risk to the large and better diversified portfolio of the insurer, it does not mean that the risk is completely reduced since the insurer may default his obligations. Insurers need to have sufficient equity or buffer capital to meet their obligations in adverse conditions when their losses on the diversified portfolio exceed the expected losses. Ratings provide an assessment of the ability of the insurer to meet its obligations to policy holders and debt holders. In this paper, the relationship between financial ratios and the rating is analyzed for different types of insurance companies using advanced statistical techniques that are able to detect non-linear relationship. The resulting rating model approach is similar to the approach for a low default portfolio, which uses a common set of explanatory variables (such as capitalization, profitability, leverage and size) which is generally applicable for all insurance types, and is complemented with insurance type specific ratios. The resulting model is found to yield a good accuracy, with 75% of the model ratings differing at most one notch from the external rating.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.05.001}, issn = {0169-2070}, keywords = {Credit scoring, Internal rating system, Insurance companies, regart} } @ARTICLE{Geurts87, author = {Michael D. Geurts}, title = {Practical techniques of business forecasting : George Kress, (Quorum, Westport, CT, 1985) pp. 259, \$39.95.}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {532-533}, number = {3-4}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90052-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{GK90, author = {Michael D. Geurts and J. Patrick Kelly}, title = {In defense of ARIMAmodeling, by D.J. Pack}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {497-499}, number = {4}, abstract = {The comparative accuracy of ARIMA modeling remains a controversial issue. In the International Journal of Forecasting, Pack (1990, pp. 211-218) argued that some of the criticisms are misplaced, and in particular criticized a study by Geurts and Kelly that compared the accuracy of exponential smoothing with that achieved by ARIMA modeling when applied to departmental store sales. Here Geurts and Kelly respond to Pack's criticism. Pack adds a final rejoinder.*}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90026-8}, issn = {0169-2070}, keywords = {ARIMA models; Calendar variation; Comparative forecasting accuracy; Time series, othercom} } @ARTICLE{GK86, author = {Michael D. Geurts and J. Patrick Kelly}, title = {Forecasting retail sales using alternative models}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {261-272}, number = {3}, abstract = {This paper explores the issues associated with adapting forecasting techniques used by manufacturers to produce accurate forecasts for retail sales. A case study is presented that is developed using a retail situation because retailers often view their sales forecasting problems as being very different from a manufacturer's problems. Sales volumes are dramatically impacted by competitor promotional actions, discounts, store promotions and weather. Finally, consumption holidays like Christmas, Easter, Mother's day, have a large impact on sales as well as back to school shopping. The findings in this paper indicate that forecasting retail sales can be accomplished with a high degree of accuracy.}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90046-4}, issn = {0169-2070}, keywords = {Retail sales forecasting, Exponential smoothing, Forecasting, Trading days, Box-Jenkins, regart} } @ARTICLE{Geweke10, author = {John Geweke}, title = {Comment}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {435 - 438}, number = {2}, note = {Special Issue: Bayesian Forecasting in Economics}, doi = {10.1016/j.ijforecast.2010.01.006}, issn = {0169-2070} } @ARTICLE{GA10, author = {John Geweke and Gianni Amisano}, title = {Comparing and evaluating Bayesian predictive distributions of asset returns}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {216 - 230}, number = {2}, note = {Special Issue: Bayesian Forecasting in Economics}, doi = {10.1016/j.ijforecast.2009.10.007}, issn = {0169-2070}, keywords = {Forecasting, GARCH,Inverse probability transformation,Markov mixture,Predictive likelihood,S&P 500 returns,Stochastic volatility} } @ARTICLE{GSZ05, author = {M. Ghiassi and H. Saidane and D.K. Zimbra}, title = {A dynamic artificial neural network model for forecasting time series events}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {341-362}, number = {2}, abstract = {Neural networks have shown to be an effective method for forecasting time series events. Traditional research in this area uses a network with a sequential iterative learning process based on the feed-forward, back-propagation approach. In this paper we present a dynamic neural network model for forecasting time series events that uses a different architecture than traditional models. To assess the effectiveness of this method, we forecasted a number of standard benchmarks in time series research from forecasting literature. Results show that this approach is more accurate and performs significantly better than the traditional neural network and autoregressive integrated moving average (ARIMA) models.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.10.008}, issn = {0169-2070}, keywords = {Artificial neural networks, Forecasting, Time series, ARIMA, Back-propagation, regart} } @ARTICLE{GD02a, author = {Sucharita Ghosh and Dana Draghicescu}, title = {Predicting the distribution function for long-memory processes}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {283-290}, number = {2}, abstract = {Nonparametric kernel estimation of quantiles for time-dependent transformations of stationary Gaussian processes with long-memory was considered in Ghosh, Beran and Innes [Student 2 (1997) 109-117]. In this paper, we consider the problem of predicting the future distribution function for such processes. In particular, an expanded logistic transformation is used. Prediction intervals are obtained by using the asymptotic distribution of the predicted distribution function at future time points. Simulations and a data example illustrate the findings.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00158-3}, issn = {0169-2070}, keywords = {Kernel smoothing, Logistic transformation, Long range dependence, Nonparametric methods, Prediction, Probability, Time series, regart} } @ARTICLE{GR09, author = {Domenico Giannone and Lucrezia Reichlin}, title = {Comments on 'Forecasting economic and financial variables with global VARs'}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {684 - 686}, number = {4}, note = {Special section: Decision making and planning under low levels of predictability}, doi = {10.1016/j.ijforecast.2009.06.003}, issn = {0169-2070} } @ARTICLE{Gill95, author = {Len Gill}, title = {Handbook of statistics, volume 11, econometrics : G.S. Maddala, C.R. Rao and H.D. Vinod, eds., 1993, (North Holland, Amsterdam), 800 pp., US\$180.00 D[latin small letter f with hook]340.00, ISBN 0-444-89577-9.}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {189-191}, number = {1}, note = {Probability Forecasting}, doi = {http://dx.doi.org/10.1016/0169-2070(95)90021-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{GV10, author = {Paolo Giordani and Mattias Villani}, title = {Forecasting macroeconomic time series with locally adaptive signal extraction}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {312 - 325}, number = {2}, note = {Special Issue: Bayesian Forecasting in Economics}, doi = {10.1016/j.ijforecast.2009.12.011}, issn = {0169-2070}, keywords = {Bayesian inference, Forecast evaluation,Regime switching,State space modeling,Dynamic mixture models} } @ARTICLE{GP07, author = {Pierre Giot and Mikael Petitjean}, title = {The information content of the Bond-Equity Yield Ratio: Better than a random walk?}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {289-305}, number = {2}, abstract = {Since the 1990s run up in stock prices and the subsequent crashes, the financial community has taken a dim view of the traditional valuation ratios and has instead turned its attention to a new valuation ratio: the Bond-Equity Yield Ratio (BEYR). In this paper we provide the first comprehensive statistical assessment, both in-sample and out-of-sample, of the fundamental short-term reversion dynamics of the BEYR towards its long-term mean. Using cointegrated VAR models, we show that the BEYR can depart from its long-term relationship for an extended period of time before the reversion process finally brings it back to equilibrium. The out-of-sample forecasting analysis, based on both equally and superior predictive ability tests, shows that the cointegrated VAR model does not perform better than a naïve random walk. As such, we cast doubt on the ability of the BEYR to predict monthly stock returns.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.02.004}, issn = {0169-2070}, keywords = {Valuation ratio, Cointegration, Random walk, Predictive ability, Reversion, regart} } @ARTICLE{GSW90, author = {Rashi Glazer and Joel H. Steckel and Russell S. Winer}, title = {Judgmental forecasts in a competitive environment: Rational vs. adaptive expectations}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {149-162}, number = {2}, abstract = {In a competitive environment, judgmental forecasts or expectations affect not only a firm's own decisions but also those of its competitors. They also influence ultimate market outcomes which, in turn, are then used to form new forecasts. In this paper, we use data from a simulated competitive marketing environment to examine the expectations formation process for key micro variables of interest to marketing managers. These include market size, number of competing products, and average industry price. In particular, we test two alternative hypotheses - rational and adaptive expectations - that are used to study how effective and efficient managers are in using information to form forecasts. We find no support for adaptive expectations, but partial support for rational expectations in that decision makers' forecasts tend to be efficient but biased. We discuss the implications of our results for both the relationship between industry competitiveness and forecast efficiency and for improving forecasts within a competitive setting.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90001-R}, issn = {0169-2070}, keywords = {Adaptive expectations, MARKSTRAT, Rational expectations, regart} } @ARTICLE{Glenn96, author = {Jerome C. Glenn}, title = {Futurehype: The tyranny of prophecy : Max Dublin, 1991, (Dutton Books, New York), 304pp., ISBN 0452-26800-1, US\$12.00.}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {181-182}, number = {1}, note = {Probability Judgmental Forecasting}, doi = {http://dx.doi.org/10.1016/0169-2070(96)88196-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{GLJ87, author = {Dennis Glennon and Julia Lane and Stanley Johnson}, title = {Regional econometric models that reflect labor market relations}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {299-312}, number = {2}, abstract = {Regional economic forecasting is often hampered by a lack of reliable data. This study attempts to improve the efficiency of forecasts by incorporating interindustry linkages in wage and employment determination into an econometric model. Prior information of historical linkages is utilized in the form of restricted least squares and applied to the Louisville metropolitan area. We provide a step toward the specification of reliable models that reflect the local institutional framework which is often ignored in neoclassical, labor market-based model specifications. Comparisons on forecast accuracy with other structural models found in the literature favor the use of local institutional factors, though univariate time series models still tend to outperform the econometric approach.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90011-2}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{GG97, author = {Stuart M. Glosser and Lonnie Golden}, title = {Average work hours as a leading economic variable in US manufacturing industries}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {175-195}, number = {2}, abstract = {This paper examines the role of the average workweek as a leading indicator of output and employment in US manufacturing industries. A separate VAR system is estimated for the aggregate, durable, and non-durable manufacturing sectors as well as for 16 of the 20 two-digit SIC detailed manufacturing industries. Each VAR system is comprised of hours, employment, output, and real wages for that sector or industry. Tests conducted for structural change show a structural break occurred after the late 1970s. Granger causality tests and impulse response analysis show that the impact of a given change in average hours on employment and output weakened considerably after the structural break point in 1979. Our results imply that the average workweek in US manufacturing has become less associated with the entire business cycle in both output and employment.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00725-X}, issn = {0169-2070}, keywords = {Average weekly hours, Granger causality, Impulse response functions, Leading indicators, Labor market, Manufacturing workweek, Overtime hours, VAR, regart} } @ARTICLE{Goddard05, author = {John Goddard}, title = {Regression models for forecasting goals and match results in association football}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {331-340}, number = {2}, abstract = {In the previous literature, two approaches have been used to model match outcomes in association football (soccer): first, modelling the goals scored and conceded by each team; and second, modelling win-draw-lose match results directly. There have been no previous attempts to compare the forecasting performance of these two types of model. This paper aims to fill this gap. Bivariate Poisson regression is used to estimate forecasting models for goals scored and conceded. Ordered probit regression is used to estimate forecasting models for match results. Both types of models are estimated using the same 25-year data set on English league football match outcomes. The best forecasting performance is achieved using a `hybrid' specification, in which goals-based team performance covariates are used to forecast win-draw-lose match results. However, the differences between the forecasting performance of models based on goals data and models based on results data appear to be relatively small.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.08.002}, issn = {0169-2070}, keywords = {Bivariate Poisson, Ordered probit, Football match results, regart} } @ARTICLE{Goitein89, author = {Bernard J. Goitein}, title = {Judgment and choice: The psychology of decision : Robin M. Hogarth, Second edition (Wiley, New York, 1987) \$24.95, �17.50, pp. 311}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {135-137}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90072-1}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Goitein89a, author = {Bernard J. Goitein}, title = {New directions in research on decision making : Berndt Brehmer, Helmut Jungermann, Peter Laurens and Guje Sevon, eds. (Elsevier Science Publishers, Amsterdam, 1986) pp. 443, \$105}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {286-288}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90101-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{GG09, author = {Daniel G. Goldstein and Gerd Gigerenzer}, title = {Fast and frugal forecasting}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {760 - 772}, number = {4}, note = {Special section: Decision making and planning under low levels of predictability}, doi = {10.1016/j.ijforecast.2009.05.010}, issn = {0169-2070}, keywords = {Heuristics, Fast and frugal heuristics,Unit weighting,Robustness,Overfitting,Cross-validation} } @ARTICLE{GP08, author = {Roberto Golinelli and Giuseppe Parigi}, title = {Real-time squared: A real-time data set for real-time GDP forecasting}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {368-385}, number = {3}, abstract = {This paper uses real-time data to mimic real-time GDP forecasting activity. Through automatic searches for the best indicators for predicting GDP one and four steps ahead, we compare the out-of-sample forecasting performance of adaptive models using different data vintages, and produce three main findings. First, despite data revisions, the forecasting performance of models with indicators is better, but this advantage tends to vanish over longer forecasting horizons. Second, the practice of using fully updated datasets at the time the forecast is made (i.e., taking the best available measures of today's economic situation) does not appear to bring any effective improvement in forecasting ability: the first GDP release is predicted equally well by models using real-time data as by models using the latest available data. Third, although the first release is a rational forecast of GDP data after all statistical revisions have taken place, the forecast based on the latest available GDP data (i.e. the temporarilybest measures) may be improved by combining preliminary official releases with one-step-ahead forecasts.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.05.001}, issn = {0169-2070}, keywords = {Short-term GDP forecasting, Bridge model, Real-time data-set, Automatic forecasting, First release, Final GDP prediction, regart} } @ARTICLE{GM95, author = {Pilar Gonz{\'a}lez and Paz Moral}, title = {An analysis of the international tourism demand in Spain}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {233-251}, number = {2}, abstract = {In this paper the external demand for Spanish tourist services is analysed within the framework of Structural Time Series Models. The estimated structural model includes as explanatory variables an income index, two price indexes (one with respect to client countries and another with respect to competitor countries), a stochastic trend, representing the changes in tourist tastes, and a stochastic seasonal component. The results show that both price indexes are the more relevant of the variables that determine tourist demand and that the contribution of the trend component has been decisive in the rapid rates of growth of the tourist sector during recent years. The forecasting performance of the estimated structural model compares well with the forecasting performance of two alternative dynamic models, the transfer function and error correction models.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)00570-3}, issn = {0169-2070}, keywords = {Tourism demand, Structural time series models, Stochastic trends, Kalman Filter, Transfer function, Error correction mechanism, regart} } @ARTICLE{GLM04, author = {Gloria Gonz{\'a}lez-Rivera and Tae-Hwy Lee and Santosh Mishra}, title = {Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {629-645}, number = {4}, abstract = {We analyze the predictive performance of various volatility models for stock returns. To compare their performance, we choose loss functions for which volatility estimation is of paramount importance. We deal with two economic loss functions (an option pricing function and an utility function) and two statistical loss functions (a goodness-of-fit measure for a value-at-risk (VaR) calculation and a predictive likelihood function). We implement the tests for superior predictive ability of White [Econometrica 68 (5) (2000) 1097] and Hansen [Hansen, P. R. (2001). An unbiased and powerful test for superior predictive ability. Brown University]. We find that, for option pricing, simple models like the Riskmetrics exponentially weighted moving average (EWMA) or a simple moving average, which do not require estimation, perform as well as other more sophisticated specifications. For a utility-based loss function, an asymmetric quadratic GARCH seems to dominate, and this result is robust to different degrees of risk aversion. For a VaR-based loss function, a stochastic volatility model is preferred. Interestingly, the Riskmetrics EWMA model, proposed to calculate VaR, seems to be the worst performer. For the predictive likelihood-based loss function, modeling the conditional standard deviation instead of the variance seems to be a dominant modeling strategy.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.10.003}, issn = {0169-2070}, keywords = {ARCH, Data snooping, Option pricing, Predictive likelihood, Reality check, Superior predictive ability, Utility function, VaR, Volatility, regart} } @ARTICLE{Goodrich00, author = {Robert L. Goodrich}, title = {The Forecast Pro methodology}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {533-535}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00086-8}, issn = {0169-2070}, keywords = {prodrev} } @ARTICLE{Goodwin09, author = {Paul Goodwin}, title = {Book review}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {208-209}, number = {1}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.11.015}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Goodwin08, author = {Paul Goodwin}, title = {,The Black Swan. The impact of the highly improbable .Nassim Nicholas Taleb and Allen Lane, Editors, Hardcover (2007) 366 pages, ISBN: 978-0713-99995-2, �20, Paperback, ISBN 978-0141-03459-1, �8.99.}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {551-552}, number = {3}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.03.006}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Goodwin07, author = {Paul Goodwin}, title = {Should we be using significance tests in forecasting research?}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {333-334}, number = {2}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.01.008}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Goodwin03, author = {Paul Goodwin}, title = {Practical Forecasting for Managers,: John C. Nash \& Mary Nash (2001), London: Arnold and New York: Oxford University Press, 296 pages. ISBN 0 340 76238 1 Paperback �24.99, \$40.00.}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {532-534}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00021-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Goodwin03a, author = {Paul Goodwin}, title = {International Marketing Forecasts (2002),: London: Euromonitor Books, 606 pages. ISBN 0 84264-152-2, Paperback, \$1250, �625, [euro]1250.}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {753-754}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00055-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Goodwin02, author = {Paul Goodwin}, title = {Forecasting games: can game theory win?}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {369-374}, number = {3}, abstract = {I present evidence to suggest that studying the use of game theory in prediction is a legitimate area of research and suggest ways in which game theory might be used to make or support predictions. Green's study predominately assesses the accuracy of predictions by game theorists (who may have made informal use of game theory concepts) rather than predictions obtained from formal game theory models. I argue that the accuracy of predictions derived from such models is likely to be contingent on the characteristics of the conflict and provide a partial taxonomy of these characteristics, together with their hypothesised effects. I also argue that it would be worth investigating the potential use of game theory as an aid to obtaining probabilistic predictions.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00022-5}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{Goodwin02a, author = {Paul Goodwin}, title = {How to Forecast: A Guide for Business: James Morrell (2001), Aldershot: Gower, xii+201 pages. ISBN 0 566 08363 0. Hardback �55.}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {463-464}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00004-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Goodwin00, author = {Paul Goodwin}, title = {Correct or combine? Mechanically integrating judgmental forecasts with statistical methods}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {261-275}, number = {2}, abstract = {A laboratory experiment and two field studies were used to compare the accuracy of three methods that allow judgmental forecasts to be integrated with statistical methods. In all three studies the judgmental forecaster had exclusive access to contextual (or non time-series) information. The three methods compared were: (i) statistical correction of judgmental biases using Theil's optimal linear correction; (ii) combination of judgmental forecasts and statistical time-series forecasts using a simple average and (iii) correction of judgmental biases followed by combination. There was little evidence in any of the studies that it was worth going to the effort of combining judgmental forecasts with a statistical time-series forecast - simply correcting judgmental biases was usually sufficient to obtain any improvements in accuracy. The improvements obtained through correction in the laboratory experiment were achieved despite its effectiveness being weakened by variations in biases between periods.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00038-8}, issn = {0169-2070}, keywords = {Judgmental forecasting, Combining forecasts, regart} } @ARTICLE{Goodwin00a, author = {Paul Goodwin}, title = {Judgment and Decision Making: An Interdisciplinary Reader: Second edition, Terry Connolly, Hal R. Arkes and Kenneth R. Hammond (Eds.), Cambridge University Press, 2000. Paperback: ISBN 0-521-62602-1, �24.95 (\$34.95); Hardback: ISBN: 0-521-62355-3, �60.00 (\$84.95).}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {429-430}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00055-8}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Goodwin00b, author = {Paul Goodwin}, title = {Improving the voluntary integration of statistical forecasts and judgment}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {85-99}, number = {1}, abstract = {When regular time series patterns are disturbed by foreseeable special events, judgmental modifications of statistical forecasts may improve accuracy by allowing the estimated effects of these events to be incorporated into the forecast. However, previous research has found that judgmental forecasters use statistical forecasts inefficiently -- they make unnecessary changes to reliable forecasts and ignore forecasts that form an ideal base-line for adjustment. An experiment was conducted to test the effectiveness of three simple methods that were designed to improve the use of statistical forecasts by judgmental forecasters: (a) making the statistical forecast the default and requiring an explicit request to change this forecast, (b) requiring the judge to record a reason for changing the statistical forecast and (c) eliciting adjustments to the statistical forecast, rather than revised forecasts. The first two methods led to improvements in the utilisation of statistical forecasts and improved accuracy. The third method was less successful.}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00026-6}, issn = {0169-2070}, keywords = {Judgmental forecasting, Forecast adjustment, regart} } @ARTICLE{Goodwin97, author = {Paul Goodwin}, title = {A psychological approach to decision support systems : S.J. Hoch and D.A. Schkade, 1996, Management science, 42, 51-64}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {149-150}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00722-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Goodwin96, author = {Paul Goodwin}, title = {Journal of behavioral decision making : J.S. Lim and M. O'Connor, 1995, Judgemental adjustment of initial forecasts: its effectiveness and biases, 8, 149-168.}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {184-185}, number = {1}, note = {Probability Judgmental Forecasting}, doi = {http://dx.doi.org/10.1016/0169-2070(96)88198-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Goodwin92, author = {Paul Goodwin}, title = {Prediction, projection and forecasting : Thomas L. Saaty and Luis G. Vargas, (Kluwer, Norwell, MA, 1991), pp. 251, \$57.50}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {118-119}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90020-A}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{GFL+07, author = {Paul Goodwin and Robert Fildes and Michael Lawrence and Konstantinos Nikolopoulos}, title = {The process of using a forecasting support system}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {391-404}, number = {3}, abstract = {The actions of individual users of an experimental demand forecasting support system were traced and analyzed. Users adopted a wide variety of strategies when choosing a statistical forecasting method and deciding whether to apply a judgmental adjustment to its forecast. This was the case, despite the users reporting similar levels of familiarity with statistical methods. However, the analysis also revealed that users were very consistent in the strategies that they applied across twenty different series. In general, the study found that users did not emulate mechanical forecasting systems, in that they often did not choose the forecasting method that provided the best fit to past data. They also tended to examine only a small number of methods before making a selection, though they were likely to examine more methods when they perceived the series to be difficult to forecast. Individuals who were relatively unsuccessful in identifying a well fitting statistical method tended to compensate for this by making large judgmental adjustments to the statistical forecasts. However, this generally led to forecasts that were less accurate than those produced by people who selected well fitting methods in the first place. These results should be of particular interest to designers of forecasting support systems, who will typically have some stylised representation of the way that users employ their systems to generate forecasts.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.05.016}, issn = {0169-2070}, keywords = {Judgmental forecasting, Forecasting support system, Forecaster behaviour, Forecasting tasks, regart} } @ARTICLE{GL03, author = {Paul Goodwin and Richard Lawton}, title = {Debiasing forecasts: how useful is the unbiasedness test?}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {467-475}, number = {3}, abstract = {A number of studies have demonstrated the improvements in accuracy that can result from correcting judgmental forecasts to remove systematic bias. It has been suggested that the `unbiasedness test', based on the F-distribution, should be employed to determine when to apply correction to forecasts. The effectiveness of using the test for this purpose was investigated under conditions where its underlying assumptions were valid. The results suggest that, even under these conditions, the use of the test is unlikely to be advisable in most practical contexts and that a policy of always correcting forecasts is preferable.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00059-6}, issn = {0169-2070}, keywords = {Forecast correction, Bias, Judgmental forecasting, Significance testing, regart} } @ARTICLE{GL99, author = {Paul Goodwin and Richard Lawton}, title = {On the asymmetry of the symmetric MAPE}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {405-408}, number = {4}, abstract = {Several authors have suggested that the use of the mean absolute percentage error (MAPE) as a measure of forecast accuracy should be avoided because they argue it treats forecast errors above the actual observation differently from those below this value. To counter this, the use of a symmetric (or modified) MAPE has been proposed. This paper shows that, in its treatment of negative and positive errors, the proposed modification is far from symmetric, particularly where these errors have large absolute values. It also shows that, under some circumstances, a non-monotonic relationship can occur between the symmetric MAPE and the absolute forecast errors.}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00007-2}, issn = {0169-2070}, keywords = {Forecasting, Error measures, regart} } @ARTICLE{GOOe+02, author = {Paul Goodwin and J. Keith Ord and Lars-Erik{\"O}ller and Janet A. Sniezek and Mike Leonard}, title = {Principles of Forecasting: A Handbook for Researchers and Practitioners: J. Scott Armstrong (Ed.), (2001), Boston: Kluwer Academic Publishers, 849 pages. Hardback: ISBN: 0-7923-7930-6; \$190, �133, [euro]210.00, Paperback: ISBN: 07923-7401-0; \$95; �66.50, [euro]105.}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {468-478}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00034-1}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{GW93, author = {Paul Goodwin and George Wright}, title = {Improving judgmental time series forecasting: A review of the guidance provided by research}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {147-161}, number = {2}, abstract = {This study reviews the research literature on judgmental time series forecasting in order to assess: (i) the quality of inferences about judgmental forecasting in practice which can be drawn from this research; (ii) what is currently known about the processes employed by people when producing judgmental forecasts; (iii) the current evidence that certain strategies can lead to more accurate judgmental forecasts. A key focus of the paper is the identification of areas where further research is needed.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90001-4}, issn = {0169-2070}, keywords = {Judgmental forecasting, Time series, Decomposition, Quality of judgement, regart} } @ARTICLE{Gooijer93, author = {Jan G. de Gooijer}, title = {Nonlinear dynamics, chaos, and instability : William A. Brock, David A. Hsieh and Blake LeBaron, 1991, (MIT Press, Cambridge) 328, pp. �29.25. ISBN 0-262-02329-6}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {134-135}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90063-S}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Gooijer90, author = {Jan G. de Gooijer}, title = {System identification : Torsten S{\"o}derstr{\"o}m and Petre Stoica, Prentice-Hall, New York, 1989) pp. 612 including index, \$75.95}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {256-258}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90013-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Gooijer90a, author = {Jap G. de Gooijer}, title = {The role of time series analysis in forecasting: A personal view}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {449-451}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90020-C}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{GK92, author = {Jan G. de Gooijer and Andr{\'e} Klein}, title = {On the cumulated multi-step-ahead predictions of vector autoregressive moving average processes}, journal = {International Journal of Forecasting}, year = {1992}, volume = {7}, pages = {501-513}, number = {4}, abstract = {When a time series model is used for making predictions, then it is often meaningful to evaluate its performance on the basis of cumulated multi-step-ahead prediction errors. In this paper some theoretical properties of cumulated multi-step-ahead predictors and cumulated multi-step-ahead prediction errors for vector autoregressive moving average processes are considered. A general expression for the optimal cumulated multi-step-ahead predictor is derived. The predictors are based on the Kalman filter algorithm. To determine the maximum prediction horizon of cumulated multi-step-ahead predictions, two information measures are introduced. For univariate (p, q) processes with p < 3 and q < 3, these measures are evaluated analytically as well as numerically. It is shown that the information content of cumulated multi-step-ahead predictions depends on the prediction horizon and the location of the roots of the AR and MA polynomials.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90034-7}, issn = {0169-2070}, keywords = {Cumulated predictions, Kullback-Leibler information measure, Multi-step-ahead predictions, R{\'e}nyi's information measure, Vector autoregressive moving average processes, regart} } @ARTICLE{Gooijer04, author = {Jan G. De Gooijer}, title = {Editorial Announcement}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {523-524}, number = {4}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.09.009}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{02, author = {Jan G. De Gooijer}, title = {Editorial transition}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {1-3}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00142-X}, issn = {0169-2070}, key = {tagkey20021}, keywords = {editorial} } @ARTICLE{Gooijer02, author = {Jan G. De Gooijer}, title = {Introduction to forecasting decisions in conflict situations}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {319-320}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00026-2}, issn = {0169-2070} } @ARTICLE{98, author = {Jan G. De Gooijer}, title = {Editorial (Thank you Robert Fildes)}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {1-2}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00012-0}, issn = {0169-2070}, key = {tagkey19981}, keywords = {editorial} } @ARTICLE{98h, author = {Jan G. De Gooijer}, title = {Erratum}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {3-3}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00014-4}, issn = {0169-2070}, key = {tagkey19983}, keywords = {errata} } @ARTICLE{Gooijer93a, author = {Jan G. De Gooijer}, title = {On predictive least squares principles : C.Z. Wei, The Annals of Statistics 20 (1992), 1-42}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {138-139}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90068-X}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{GV04, author = {Jan G. De Gooijer and Antoni Vidiella-i-Anguera}, title = {Forecasting threshold cointegrated systems}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {237-253}, number = {2}, abstract = {The cointegration literature suggests that forecast errors may be reduced by incorporating the knowledge of cointegrating relationships into linear models to generate forecasts. We show that the long-term (one- to sixty-steps ahead) forecasting performance can further be enhanced by applying nonlinear equilibrium correction models. In particular, we focus on a bivariate threshold vector equilibrium correction model with the same unknown cointegrating parameter vector in both regimes (TVECM), and a bivariate cointegration model with regime-specific cointegration vectors (LTVECM). Based on simulation experiments as well as two real data sets, and using a variety of evaluation measures, we find that the forecasting performance of the LTVECM outperforms the TVECM and the usual linear specification of the equilibrium correcting mechanism. This result holds for forecasts generated by bootstrapping and Monte Carlo simulation.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.09.006}, issn = {0169-2070}, keywords = {Cointegration, Forecasting performance, Maximum likelihood, Multivariate forecast densities, Vector equilibrium correction model, regart} } @ARTICLE{GF97, author = {Jan G. De Gooijer and Philip Hans Franses}, title = {Forecasting and seasonality}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {303-305}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00018-6}, issn = {0169-2070} } @ARTICLE{GH06, author = {Jan G. De Gooijer and Rob J. Hyndman}, title = {25 years of time series forecasting}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {443-473}, number = {3}, abstract = {We review the past 25 years of research into time series forecasting. In this silver jubilee issue, we naturally highlight results published in journals managed by the International Institute of Forecasters (Journal of Forecasting 1982-1985 and International Journal of Forecasting 1985-2005). During this period, over one third of all papers published in these journals concerned time series forecasting. We also review highly influential works on time series forecasting that have been published elsewhere during this period. Enormous progress has been made in many areas, but we find that there are a large number of topics in need of further development. We conclude with comments on possible future research directions in this field.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.01.001}, issn = {0169-2070}, keywords = {Accuracy measures, ARCH, ARIMA, Combining, Count data, Densities, Exponential smoothing, Kalman filter, Long memory, Multivariate, Neural nets, Nonlinearity, Prediction intervals, Regime-switching, Robustness, Seasonality, State space, Structural models, Transfer function, Univariate, VAR, regart} } @ARTICLE{93, author = {Jan G. De Gooijer and Kuldeep Kumar}, title = {Corrigendum}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {145-145}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90071-T}, issn = {0169-2070}, key = {tagkey1993145}, keywords = {errata} } @ARTICLE{GK92a, author = {Jan G. De Gooijer and Kuldeep Kumar}, title = {Some recent developments in non-linear time series modelling, testing, and forecasting}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {135-156}, number = {2}, abstract = {Most of the recent work in time series analysis has been done on the assumption that the structure of the series can be described by linear time series models. However, there are occasions when subject-matter, theory or data suggest that linear models are unsatisfactory. In those cases it is desirable to look at non-linear alternatives. This paper gives an overview of the most recent developments in this area. Particular attention is paid to the strengths and weaknesses (advantages and disadvantages) of a large number of models and tests for non-linearity, focusing on `ready-to-use' issues rather than discussing technical details. Various problems in forecasting from non-linear models are discussed. Some guidelines for practical non-linear time series modelling and forecasting are also included.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90115-P}, issn = {0169-2070}, keywords = {ARCH, Bilinear, CUSUMS, Exponential AR, Identification, Invertibility, Lagrange-multiplier test, Multi-step-ahead forecasting, Order selection, Thresho, regart} } @ARTICLE{GH03, author = {Wilpen Gorr and Richard Harries}, title = {Introduction to crime forecasting}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {551-555}, number = {4}, abstract = {This short paper introduces the six papers comprising the Special Section on Crime Forecasting. A longer title for the section could have been Forecastingcrimeforpolicyandplanningdecisionsandinsupportoftacticaldeploymentofpoliceresources. Crime forecasting for police is relatively new. It has been made relevant by recent criminological theories, made possible by recent information technologies including geographic information systems (GIS), and made desirable because of innovative crime management practices. While focused primarily on the police component of the criminal justice system, the six papers provide a wide range of forecasting settings and models including UK and US jurisdictions, long- and short-term horizons, univariate and multivariate methods, and fixed boundary versus ad hoc spatial cluster areal units for the space and time series data. Furthermore, the papers include several innovations for forecast models, with many driven by unique features of the problem area and data.}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00089-X}, issn = {0169-2070}, keywords = {Crime forecasting, regart} } @ARTICLE{GOT03, author = {Wilpen Gorr and Andreas Olligschlaeger and Yvonne Thompson}, title = {Short-term forecasting of crime}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {579-594}, number = {4}, abstract = {The major question investigated is whether it is possible to accurately forecast selected crimes 1 month ahead in small areas, such as police precincts. In a case study of Pittsburgh, PA, we contrast the forecast accuracy of univariate time series models with naïve methods commonly used by police. A major result, expected for the small-scale data of this problem, is that average crime count by precinct is the major determinant of forecast accuracy. A fixed-effects regression model of absolute percent forecast error shows that such counts need to be on the order of 30 or more to achieve accuracy of 20% absolute forecast error or less. A second major result is that practically any model-based forecasting approach is vastly more accurate than current police practices. Holt exponential smoothing with monthly seasonality estimated using city-wide data is the most accurate forecast model for precinct-level crime series.}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00092-X}, issn = {0169-2070}, keywords = {Crime forecasting, Time series, Small area estimation, regart} } @ARTICLE{Gorr09, author = {Wilpen L. Gorr}, title = {Forecast accuracy measures for exception reporting using receiver operating characteristic curves}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {48-61}, number = {1}, abstract = {The exception principle of management reporting suggests that, under ordinary conditions, operational staff persons make decisions, but that the same staff refer decisions to upper-level managers under exceptional conditions. Forecasts of large changes or extreme values in product or service demand are potential triggers for such reporting. Seasonality estimates in univariate forecast models and leading independent variables in multivariate forecast models are among the approaches to forecasting exceptional demand, a forecast activity that this paper identifies as requiring new accuracy measures based on the tails of sampled forecast error distributions, rather than conventional measures which use the central tendency. For this purpose, the paper introduces the application of the receiver operating characteristic (ROC) framework, which has been used for the assessment of exceptional behavior in many fields. In a case study on serious violent crime in Pittsburgh, Pennsylvania, the simplest, non-naïve univariate forecast method is best for forecasting ordinary conditions using conventional forecast accuracy measures, but the most complex multivariate model is best for forecasting exceptional conditions using ROC forecast accuracy measures.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.11.013}, issn = {0169-2070}, keywords = {Forecast accuracy measures, Exception reporting, ROC curves, Crime forecasting, regart} } @ARTICLE{Gorr94, author = {Wilpen L. Gorr}, title = {Editorial: Research prospective on neural network forecasting}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {1-4}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90044-2}, issn = {0169-2070} } @ARTICLE{GNS94, author = {Wilpen L. Gorr and Daniel Nagin and Janusz Szczypula}, title = {Comparative study of artificial neural network and statistical models for predicting student grade point averages}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {17-34}, number = {1}, abstract = {This paper compares linear regression; stepwise polynomial regression; and fully-connected, single middle layer artificial neural network models with an index used by an admissions committee for predicting student GPAs in professional school. It also provides methods for implementing, interpreting, and evaluating artificial neural networks, including an optimization of model structure for simple neural networks. While the neural network identifies additional model structure over the regression models, none of the empirical methods was statistically significantly better than the practitioners' index.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90046-9}, issn = {0169-2070}, keywords = {Artificial neural networks, Prediction forecasting, Comparative forecast performance, regart} } @ARTICLE{GO09, author = {Wilpen L. Gorr and J. Keith Ord}, title = {Introduction to time series monitoring}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {463 - 466}, number = {3}, note = {Special Section: Time Series Monitoring}, doi = {10.1016/j.ijforecast.2009.04.005}, issn = {0169-2070} } @ARTICLE{GS90, author = {Patricia Grambsch and Werner A. Stahel}, title = {Forecasting demand for special telephone services: A case study}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {53-64}, number = {1}, abstract = {Future demand for services or goods is usually forecasted by fitting ARIMA models and using the optimal rules based on the squared error criterion. When analyzing a large number of time series describing Special Services in the telephone business, we found that a model with independent increments with stable distributions was more suitable and led to better predictions. It also described forecast errors adequately. This paper discusses the model, compares it with a state space model which is currently used for the problem, and applies several data analytic procedures to assess how well the model fits the data. A few remarks on the use of estimated forcast error size conclude the paper.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90097-U}, issn = {0169-2070}, keywords = {Forecasting, Stable distribution, Forecast error, Robust estimation, regart} } @ARTICLE{GFC88, author = {Peter J. Grandstaff and Mark E. Ferris and Shuh S. Chou}, title = {Forecasting competitive behavior : An assessment of AT\&T's incentive to extend its U.S. network}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {521-533}, number = {4}, abstract = {Competitive analysis is used to forecast how, where and when AT&T will integrate backward into the production of its own local access. By using a net present value framework to model AT&T's decision on whether to create additional capacity for collecting and distributing its long-distance traffic, a realistic assessment of the scope and timing of such action is achieved. Thus, a technique outside the usual class of those used in U.S. telecommunications demand forecasting is applied. The effects of two local exchange company rate structures for switched access are compared. Revenue at risk to a local exchange company totaled approximately $267 million for rates in effect, as compared to $100 million under a flattened rate structure.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90129-X}, issn = {0169-2070}, keywords = {Competitive analysis, Competitive forecasting, Demand, Pricing, Telecommunications, regart} } @ARTICLE{Granger09, author = {Clive W.J. Granger}, title = {Comments on 'Forecasting economic and financial variables with global VARs'}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {687 - 688}, number = {4}, note = {Special section: Decision making and planning under low levels of predictability}, doi = {10.1016/j.ijforecast.2009.05.017}, issn = {0169-2070} } @ARTICLE{GJ07, author = {Clive W.J. Granger and Yongil Jeon}, title = {Long-term forecasting and evaluation}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {539-551}, number = {4}, abstract = {Looking ahead thirty years is a difficult task, but is not impossible. In this paper we illustrate how to evaluate such long-term forecasts. Long-term forecasting is likely to be dominated by trend curves, particularly the simple linear and exponential trends. However, there will certainly be breaks in their parameter values at some unknown points, so that eventually the forecasts will be unsatisfactory. We investigate whether or not simple methods of long-run forecasting can ever be successful, after one takes into account the uncertainty level associated with the forecasts.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.07.002}, issn = {0169-2070}, keywords = {Long-term trend fitting, Forecasting evaluation, Density forecasting, regart} } @ARTICLE{Granger92, author = {Clive W. J. Granger}, title = {Forecasting stock market prices: Lessons for forecasters}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {3-13}, number = {1}, abstract = {In recent years a variety of models which apparently forecast changes in stock market prices have been introduced. Some of these are summarised and interpreted. Nonlinear models are particularly discussed, with a switching regime, from forecastable to non-forecastable, the switch depending on volatility levels, relative earnings/price ratios, size of company, and calendar effects. There appear to be benefits from disaggregation and for searching for new causal variables. The possible lessons for forecasters are emphasised and the relevance for the Efficient Market Hypothesis is discussed.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90003-R}, issn = {0169-2070}, keywords = {Forecastability, Stock returns, Non-linear models, Efficient markets, regart} } @ARTICLE{GJ03, author = {Clive W. J. Granger and Yongil Jeon}, title = {Corrigendum to 'Comparing forecasts of inflation using time distance' [International Journal of Forecasting 19 (2003) 339-349]}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {767-767}, number = {4}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.10.001}, issn = {0169-2070}, keywords = {errata} } @ARTICLE{GJ03a, author = {Clive W. J. Granger and Yongil Jeon}, title = {A time-distance criterion for evaluating forecasting models}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {199-215}, number = {2}, abstract = {In modeling series with leading or lagging indicators, it is useful to compare models in terms of time-distance. This paper formalizes the concept of time-distance in terms of various metrics, and investigates their behavior. For evaluating forecasts, time-distance metrics are shown to be more useful than standard measures (such as mean squared forecasting errors) under some circumstances and some time-distance metrics outperform others. An application to business cycle leading indicators is provided.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00030-4}, issn = {0169-2070}, keywords = {Forecasting evaluation, Time-distance, Leading indicators, regart} } @ARTICLE{GJ03b, author = {Clive W. J. Granger and Yongil Jeon}, title = {Comparing forecasts of inflation using time distance}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {339-349}, number = {3}, abstract = {When considering the relative quality of forecasts the method of comparison is relevant: should we use vertical measures, such as mean square forecasting error, or the recently developed horizontal measure time distance. Four models for inflation in the US are considered based on univariate time series, a leading indicator, a univariate model combining with the specifications of the two models, and a bivariate model. According to the mean squared forecast errors an AR(1) model is superior, but it performs much less well than models using a leading indicator when considered in terms of time distance. These results hold for both standard procedures and for the bootstrap reality check.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00029-8}, issn = {0169-2070}, keywords = {Time distance, Core inflation, Stochastic dominance, Bootstrap reality check, regart} } @ARTICLE{GOS98, author = {Clive W. J. Granger and Paul Ormerod and Ron Smith}, title = {Comments on ��Forecasting Economic Processes�� by Michael P. Clements and David F. Hendry}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {133-137}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00019-3}, issn = {0169-2070}, key = {tagkey1998133}, keywords = {othercom} } @ARTICLE{GJ10, author = {Andrew Grant and David Johnstone}, title = {Finding profitable forecast combinations using probability scoring rules}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {498 - 510}, number = {3}, note = {Sports Forecasting}, doi = {10.1016/j.ijforecast.2010.01.002}, issn = {0169-2070}, keywords = {Probability scoring rule, Kelly betting,Kelly probability score,Combining probability forecasts,Economic forecast evaluation,Probability football} } @ARTICLE{Green05, author = {Kesten C. Green}, title = {Game theory, simulated interaction, and unaided judgement for forecasting decisions in conflicts: Further evidence}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {463-472}, number = {3}, abstract = {When people in conflicts can accurately forecast how others will respond, they should be able to make better decisions. Contrary to expectations, earlier research found game theorists' forecasts were less accurate than forecasts from student role players. To assess whether game theorists had been disadvantaged by the selection of conflicts, I obtained forecasts for three new conflicts of types preferred by game theory experts. As before, role-players in simulated interactions were students, and other students forecast using their judgement. Game theorists did better than previously. However, when the three new and five earlier conflicts are combined, 101 forecasts by 23 game theorists were no more accurate (31%) than 354 forecasts by students who used unaided judgement (31%). Experienced game theorists were not more accurate. Neither were those who spent more time on the task. Of 105 simulated-interaction forecasts, 62% were accurate: an average error reduction of 47% over game-theorist forecasts and a halving of error relative to the current method. Forecasts can sometimes have value without being strictly accurate. Assessing the usefulness of forecasts led to the same conclusions about the relative merits of the methods. Finally, by combining simulated interaction forecasts, accurate forecasts were obtained for seven of the eight situations.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.02.006}, issn = {0169-2070}, keywords = {Accuracy, Methods, Role playing, Strategy, Usefulness, regart} } @ARTICLE{Green02, author = {Kesten C. Green}, title = {Forecasting decisions in conflict situations: a comparison of game theory, role-playing, and unaided judgement}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {321-344}, number = {3}, abstract = {Can game theory aid in forecasting the decision making of parties in a conflict? A review of the literature revealed diverse opinions but no empirical evidence on this question. When put to the test, game theorists' predictions were more accurate than those from unaided judgement but not as accurate as role-play forecasts. Twenty-one game theorists made 99 forecasts of decisions for six conflict situations. The same situations were described to 290 research participants, who made 207 forecasts using unaided judgement, and to 933 participants, who made 158 forecasts in active role-playing. Averaged across the six situations, 37 percent of the game theorists' forecasts, 28 percent of the unaided-judgement forecasts, and 64 percent of the role-play forecasts were correct.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00025-0}, issn = {0169-2070}, keywords = {Conflict, Expert opinion, Forecasting, Game theory, Judgement, Role-playing, Simulation, regart} } @ARTICLE{Green02a, author = {Kesten C. Green}, title = {Embroiled in a conflict: who do you call?}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {389-395}, number = {3}, abstract = {I address commentators' concerns about the research reported in my paper. These concerns do not threaten the conclusion that role-playing should be preferred ahead of game theory and unaided judgement for forecasting decisions in conflicts. I provide additional evidence and argument that the relative forecasting accuracy of game theory is a legitimate subject for research. I discuss non-forecasting uses for game theory and suggest that, without forecasting validity, such applications may be ill-founded. Replication of the Green research (Green, K. C. (2002) International Journal of Forecasting 18, 321-344) by game-theory advocates would be valuable. Extending the research with forecasts for more conflicts would allow greater confidence in recommendations to managers. Extensions should aim to increase the variety of conflicts so that managers can match research findings with their own forecasting problems. More data may allow researchers to identify conditions that favour particular forecasting methods and to estimate the effects of variations in conflict descriptions and decision options.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00020-1}, issn = {0169-2070}, keywords = {Conflict, Evaluation, Expert opinion, Forecasting, Game theory, Judgement, Prediction, Role-playing, Simulated interaction, Simulation, regart} } @ARTICLE{GA07, author = {Kesten C. Green and J. Scott Armstrong}, title = {Structured analogies for forecasting}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {365-376}, number = {3}, abstract = {People often use analogies when forecasting, but in an unstructured manner. We propose a structured judgmental procedure whereby experts list analogies, rate their similarity to the target, and match outcomes with possible target outcomes. An administrator would then derive a forecast from the information. When predicting decisions made in eight conflict situations, unaided experts' forecasts were little better than chance, at 32% accurate. In contrast, 46% of structured-analogies forecasts were accurate. Among experts who were able to think of two or more analogies and who had direct experience with their closest analogy, 60% of forecasts were accurate. Collaboration did not help.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.05.005}, issn = {0169-2070}, keywords = {Availability, Case-based reasoning, Comparison, Decision, Method, regart} } @ARTICLE{GAS09, author = {Kesten C. Green and J. Scott Armstrong and Willie Soon}, title = {Validity of climate change forecasting for public policy decision making}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {826 - 832}, number = {4}, note = {Special section: Decision making and planning under low levels of predictability}, doi = {10.1016/j.ijforecast.2009.05.011}, issn = {0169-2070}, keywords = {Climate model, Ex ante forecasts,Out-of-sample errors,Predictability,Public policy,Relative absolute errors,Unconditional forecasts} } @ARTICLE{Greenberg89, author = {Jerome Greenberg}, title = {Fashion forecasting : Rita Perna, (Fairchild Publications, N.Y, 1987) \$18.50, pp. 327}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {144-145}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90079-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Greer03, author = {Mark Greer}, title = {Directional accuracy tests of long-term interest rate forecasts}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {291-298}, number = {2}, abstract = {The one-year forecasts for long-term interest rates issued by The Wall Street Journal's panel of economic forecasters are tested for directional accuracy. A binomial test reveals that few of the forecasters correctly predicted the direction of change in long-term interest rates so well that pure chance could be rejected, at a five percent significance level, as the source of their success. However, the pooled directional accuracy outcome for the panel as a whole was significant at five percent. The Henriksson-Merton and Pesaran-Timmermann tests for forecast value show that the pooled forecasts would be of value to a user. A chi-square goodness-of-fit test reveals no statistically significant difference between the abilities of business economists and academic economists to predict correctly the direction of change in long-term interest rates.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00141-8}, issn = {0169-2070}, keywords = {Forecast tests, Evaluation procedures, Directional errors, regart} } @ARTICLE{GS87, author = {Allan W. Gregory and Michael Sampson}, title = {Testing the independence of forecast errors in the forward foreign exchange market using Markov chains : A cross-country comparison}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {97-113}, number = {1}, abstract = {In this paper, we apply the theory of finite state Markov chains to test the cross-country and temporal independence of forecast errors in the forward foreign exchange market. Specifically, we consider the month-end thirty day foreign exchange data for Canada, France, Italy, Japan, United Kingdom and West Germany for the period 1974-1981. Using pairwise comparisons for the various countries, we find that except for Canada, the hypothesis that the probability distribution of the forecast error of one country is independent of the forecast error of another is rejected. Further tests indicate that the temporal independence for most countries is also rejected. Based upon these results, we conclude that for these six countries, there is current information available which is `useful' in predicting the future forward exchange forecast errors.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90081-1}, issn = {0169-2070}, keywords = {Independence, Forecast errors, Markov chains, regart} } @ARTICLE{GY04, author = {Allan W. Gregory and James Yetman}, title = {The evolution of consensus in macroeconomic forecasting}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {461-473}, number = {3}, abstract = {When professional forecasters repeatedly forecast macroeconomic variables, their forecasts may converge over time towards a consensus. The evolution of consensus is analysed with Blue Chip data under a parametric polynomial decay function that permits flexibility in the decay path. For the most part, this specification fits the data. We test whether forecast differences decay to zero at the same point in time for a panel of forecasters, and discuss possible explanations for this, along with its implications for studies using panels of forecasters.}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00064-5}, issn = {0169-2070}, keywords = {Forecasting revisions, Macroeconomic forecasting, regart} } @ARTICLE{GG91, author = {Noel P. Greis and C. Zachary Gilstein}, title = {Empirical Bayes methods for telecommunications forecasting}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {183-197}, number = {2}, abstract = {Data-dependent shrinkage techniques such as empirical Bayes methods have been of great interest to statisticians for a number of years but have not been widely used by applied statisticians facing real-world forecasting problems. In this paper, empirical Bayes methods are used to forecast circuit activity, or churn, on a telecommunications network. A combination of shrinking and smoothing is shown to provide better forecasts than maximum likelihood estimates, especially in the case of noisy time series. These methods can be easily implemented in a mechanized forecasting system.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90053-X}, issn = {0169-2070}, keywords = {Empirical Bayes, Telecommunications forecasting, Time series, Cross-sectional methods, regart} } @ARTICLE{GNO10, author = {William E. Griffiths and Lisa S. Newton and Christopher J. O'Donnell}, title = {Predictive densities for models with stochastic regressors and inequality constraints: Forecasting local-area wheat yield}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {397 - 412}, number = {2}, note = {Special Issue: Bayesian Forecasting in Economics}, doi = {10.1016/j.ijforecast.2009.12.008}, issn = {0169-2070}, keywords = {Bayesian forecasting, Inequality restrictions,Random regressors,Rainfall distributions,Truncated distributions} } @ARTICLE{Grigoletto98, author = {Matteo Grigoletto}, title = {Bootstrap prediction intervals for autoregressions: some alternatives}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {447-456}, number = {4}, abstract = {A new method is proposed to obtain interval forecasts for autoregressive models taking into account the variability due to the estimation of the order and the parameters. The procedure improves that introduced by Masarotto (1990), allows a substantial reduction of the variance of the predictive distribution percentile estimators and should thus be considered as a useful alternative to the classic Box and Jenkins interval forecast. The method uses the bootstrap technique and is distribution-free. An empirical application is considered.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00004-1}, issn = {0169-2070}, keywords = {Interval forecasts, Autoregressive models, Bootstrap, regart} } @ARTICLE{Grillenzoni98, author = {Carlo Grillenzoni}, title = {Forecasting unstable and nonstationary time series}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {469-482}, number = {4}, abstract = {Many time series are asymptotically unstable and intrinsically nonstationary, i.e. satisfy difference equations with roots greater than one (in modulus) and with time-varying parameters. Models developed by Box-Jenkins solve these problems by imposing on data two transformations: differencing (unit-roots) and exponential (Box-Cox). Owing to the Jensen inequality, these techniques are not optimal for forecasting and sometimes may be arbitrary. This paper develops a method for modeling time series with unstable roots and changing parameters. In particular, the effectiveness of recursive estimators in tracking time-varying unstable parameters is shown with applications to data-sets of Box-Jenkins. The method is useful for forecasting time series with trends and cycles whose pattern changes over time.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00039-9}, issn = {0169-2070}, keywords = {Adaptive forecasting, Airline series, IBM stock prices, Recursive estimators, Time-varying parameters, Unstable roots, regart} } @ARTICLE{Grinyer96, author = {Peter H. Grinyer}, title = {Comments on Forecasting: its role and for planning and strategy by Spyros Makridakis}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {546-550}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00679-6}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{GKP09, author = {Jan J.J. Groen and George Kapetanios and Simon Price}, title = {A real time evaluation of Bank of England forecasts of inflation and growth}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {74-80}, number = {1}, abstract = {We compare the Bank of England's Inflation Report quarterly forecasts for growth and inflation to real-time benchmark forecasts. The results reveal the well-known difficulty of forecasting in a stable macroeconomic environment, and the Inflation Report forecasts of GDP growth are generally inferior to forecasts from linear and non-linear univariate models. However, for the inflation forecast the Inflation Report is clearly dominant.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.09.005}, issn = {0169-2070}, keywords = {Real-time data, Forecast performance, Inflation, Growth, regart} } @ARTICLE{Grubb90, author = {Howard Grubb}, title = {Software reviews}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {573-581}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90045-D}, issn = {0169-2070}, key = {tagkey1990573}, keywords = {prodrev} } @ARTICLE{GM01, author = {Howard Grubb and Alexina Mason}, title = {Long lead-time forecasting of UK air passengers by Holt-Winters methods with damped trend}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {71-82}, number = {1}, abstract = {Planning decisions for air transport infrastructure require forecasts of air passenger traffic at relatively long lead-times-of the order of ten years. The Civil Aviation Authority (CAA) has collected data on air transport, including a long time series of monthly total UK passenger numbers, from 1949 to the present day, which we analyse in this paper. This series exhibits strong, regular growth and pronounced, approximately multiplicative seasonality. We estimate the historical growth using Holt-Winters decomposition and produce long lead-time forecasts. The long data series allows us to evaluate the out-of-sample forecasting performance of this and other forecasting procedures - a modification to the Holt-Winters method greatly improves forecasting performance for long lead-times. An assessment of uncertainty in the predictions is essential for planning decisions. The trend is the most important component to forecast for long lead-time prediction. The modification to the Holt-Winters procedure allows us to vary the trend used for these predictions, and so estimate the sensitivity of our forecasts to assumptions about the future trend. Persistent extreme growth is required for the most extreme forecasts, and the historical trend suggests that this is unlikely to continue for the length of time required.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00053-4}, issn = {0169-2070}, keywords = {Transport - air, Data - aggregate, Planning: capacity, Holt-Winters, Long term forecasting, Uncertainty, Scenarios, regart} } @ARTICLE{Guerard09, author = {Guerard, John B., Jr.}, title = {Fleeing the Nazis, surviving the Gulag, and arriving in the free world: My life and times}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {435 - 440}, number = {3}, note = {Special Section: Time Series Monitoring}, doi = {10.1016/j.ijforecast.2009.05.009}, issn = {0169-2070} } @ARTICLE{GJB+98, author = {Guerard, Jr., John B. and John Blin and Steve Bender}, title = {Forecasting earnings composite variables, financial anomalies, and efficient Japanese and U.S. portfolios}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {255-259}, number = {2}, abstract = {In this study we address the creation of efficient portfolios with particular emphasis on earnings forecast and value strategies in Japan and the U.S. We show that market-neutral portfolios produce much higher returns for a given level of risk than merely creating efficient (long) portfolios. Thus use of a multi-factor risk model is useful for the 1988-1997 period for creating market-neutral portfolios and one can create the market-neutral equity selection and portfolio construction models. We find that the inclusion of consensus I/B/E/S forecasts, revisions, and momentum substantially increases the market-neutral portfolio average annual returns of Japanese and U.S. portfolios. A value-only model works quite well in a Japanese market-neutral strategy and the use of I/B/E/S forecasts significantly enhances the returns; however, in the U.S., we find that the I/B/E/S forecasts are necessary for an effective market-neutral strategy.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00031-4}, issn = {0169-2070}, keywords = {Portfolio optimization, Earnings forecasting, regart} } @ARTICLE{GH02, author = {Cherif Guermat and Richard D. F. Harris}, title = {Forecasting value at risk allowing for time variation in the variance and kurtosis of portfolio returns}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {409-419}, number = {3}, abstract = {A common approach to forecasting the value at risk (VaR) of a portfolio is to assume a parametric density function for portfolio returns, and to estimate the parameters of the density function by maximum likelihood using historical data. In order to allow for volatility clustering in short horizon returns, this approach is typically combined with a conditional variance model such as EWMA or GARCH. However, these models implicitly assume that while the volatility of returns may be time-varying, the kurtosis of the return distribution is constant, at least over the estimation sample. In this paper, we show that the EWMA variance estimator can be obtained as a special case of a more general, exponentially weighted maximum likelihood (EWML) procedure that potentially allows for time-variation not only in the variance of the return distribution, but also in its higher moments. We use EWML to forecast VaR allowing for time-variation in both the variance and the kurtosis of daily equity returns. Our results show that the EWML based VaR forecasts are generally more accurate than those generated by both the EWMA and GARCH models, particularly at high VaR confidence levels.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00122-4}, issn = {0169-2070}, keywords = {Value-at-risk, Time-varying variance and kurtosis, Exponentially weighted maximum likelihood, regart} } @ARTICLE{Guerrero91, author = {Victor M. Guerrero}, title = {ARIMA forecasts with restrictions derived from a structural change}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {339-347}, number = {3}, abstract = {Some time series models, which account for a structural change either in the deterministic or in the stochastic part of an model are presented. The structural change is assumed to occur during the forecast horizon of the series and the only available information about this change, besides the time point of its occurrence, is provided by only one or two linear restrictions imposed on the forecasts. Formulas for calculating the variance of the restricted forecasts as well as some other statistics are derived. The methods here suggested are illustrated by means of empirical examples.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90008-J}, issn = {0169-2070}, keywords = {Deterministic change, Intervention, Minimum mean-square error, Stochastic change, Time series models, regart} } @ARTICLE{Guerrero93, author = {V{\'i}ctor M. Guerrero}, title = {Combining historical and preliminary information to obtain timely time series data}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {477-485}, number = {4}, abstract = {A method is presented to improve the precision of timely data, which are published when final data are not yet available. Explicit statistical formulae, equivalent to Kalman filtering, are derived to combine historical with preliminary information. The application of these formulae is validated by the data, through a statistical test of compatibility between sources of information. A measure of the share of precision of each source of information is also derived. An empirical example with Mexican economic data serves to illustrate the procedure.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90075-X}, issn = {0169-2070}, keywords = {ARIMA models, Compatibility statistic, Forecast combination, Optimal forecast, Precision share, regart} } @ARTICLE{GV01, author = {Debashis Guha and Dimitra Visviki}, title = {What determines inflation in the US, job growth or unemployment?}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {447-458}, number = {3}, abstract = {An empirical investigation of postwar US data reveals that movements in inflation are much more strongly associated with job growth than the unemployment rate. Job growth is found to be strongly related to inflation even after accounting for the effect of the unemployment rate. The residual influence of the unemployment rate on inflation is small, however, after accounting for the effect of job growth. The data shows that in the past inflation has tended to decline when job growth is weak even if unemployment is low. This suggests that the relatively slow job growth of recent years may partly explain the puzzle that, during much of the current expansion, the US economy has experienced little inflation in spite of low unemployment.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00100-5}, issn = {0169-2070}, keywords = {Inflation, Growth, Unemployment, United States, Phillips curve, regart} } @ARTICLE{GHM+09, author = {Massimo Guidolin and Stuart Hyde and David McMillan and Sadayuki Ono}, title = {Non-linear predictability in stock and bond returns: When and where is it exploitable?}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {373-399}, number = {2}, abstract = {We systematically examine the comparative predictive performance of a number of linear and non-linear models for stock and bond returns in the G7 countries. Besides Markov switching, threshold autoregressive (TAR), and smooth transition autoregressive (STAR) regime switching models, we also estimate univariate models in which conditional heteroskedasticity is captured by GARCH and in which predicted volatilities appear in the conditional mean function. We find that capturing non-linear effects may be key to improving forecasting. In contrast to other G7 countries, US and UK asset return data are 'special,' requiring that non-linear dynamics be modeled, especially when using a Markov switching framework. The results appear to be remarkably stable over time, robust to changes in the loss function used in statistical evaluations as well as to the methodology employed to perform pair-wise comparisons.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2009.01.002}, issn = {0169-2070}, keywords = {Non-linearities, Regime switching, Threshold predictive regressions, Forecasting, regart} } @ARTICLE{Gunter92, author = {Sevket I. Gunter}, title = {Nonnegativity restricted least squares combinations}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {45-59}, number = {1}, abstract = {In combining reasonably efficient forecasts of a time series, nonnegative weights are intuitively meaningful and their constrained least squares estimators are known to have desirable theoretical properties. It is analytically shown that whether such inequality (or equality) constraints will result in gains in efficiency depends on the number of observations in the fit sample and the mean level of the fit set. Next, the performances of the combination forecasts of a macroeconomic time series obtained using Nonnegativity Restricted Least Squares (NRLS) and other combination methods are exhaustively compared. It is shown that NRLS combination models are more efficient, more robust, and less sensitive to sample size than Ordinary Least Squares, Equality Restricted Least Squares, minimum-variance, and outperformance models. They are more efficient than historical weighting and equal weighting methods only for large samples. Two heuristic NRLS algorithms are shown to yield equally accurate and robust combined forecasts.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90006-U}, issn = {0169-2070}, keywords = {Combining forecasts, Accuracy of forecasts, Restricted least squares, Robustness, Non-sample information, Gross National Product, regart} } @ARTICLE{Gupta87, author = {Satyadev Gupta}, title = {Testing causality : Some caveats and a suggestion}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {195-209}, number = {2}, abstract = {The Granger concept of causality is defined within the framework of dynamic economic systems in terms of the predictability criterion. The concept has however been often wrongly applied to static systems. The test procedures for Granger causality due to Granger, Sims, Haugh and Pierce provide grossly inconclusive and often conflicting if not misleading results. These problems are illustrated with the data on profits and investment for Canada and the U.S.A. Further, it is suggested that the predictability criterion, if interpreted in terms of conventional forecasting methods, would enable us to provide more conclusive results. The problems assume added importance as the recent vintage of econometric modelling techniques heavily rely on these causality tests.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90002-1}, issn = {0169-2070}, keywords = {Causality, Forecasting, Time series analysis, regart} } @ARTICLE{GL93, author = {Ren{\'e} G{\'e}linas and Pierre Lefran{\c c}ois}, title = {On the estimation of time-series quantiles using smoothed order statistics}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {227-243}, number = {2}, abstract = {This paper describes how smoothed order statistics can be used to estimate time-series quantiles in a stationary and non-stationary context. The approach proposed, termed a Smoothed Order Statistics quantile estimation (SOS) does not rely on assumptions about the distribution of the fitting errors of a time-series model. The approach is based on a recursive estimation mechanism and the order statistics obtained from a time-varying window-sample of the observations of a time-series. An illustrative example of the application of the model is presented along with experimental results based on its application to a sample of simulated and real time-series; a comparison is provided with three alternative quantile estimation procedures. The results show that the SOS quantiles compare favorably overall and are robust to changes in a time-series generating process.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90007-A}, issn = {0169-2070}, keywords = {Quantiles, Order statistics, Time-series, regart} } @ARTICLE{GG06, author = {Nicol{\'a}s G{\'o}mez and V{\'i}ctor M. Guerrero}, title = {Restricted forecasting with VAR models: An analysis of a test for joint compatibility between restrictions and forecasts}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {751-770}, number = {4}, abstract = {A restricted forecasting compatibility test for Vector Autoregressive Error Correction models is analyzed in this work. It is shown that a variance-covariance matrix associated with the restrictions can be used to cancel out model dynamics and interactions between restrictions. This allows us to interpret the joint compatibility test as a composition of the corresponding single restriction compatibility tests. These tests are useful for appreciating the contribution of each and every restriction to the joint compatibility between the whole set of restrictions and the unrestricted forecasts. An estimated process adjustment for the test is derived and the resulting feasible joint compatibility test turns out to have better performance than the original one. An empirical illustration of the usefulness of the proposed test makes use of Mexican macroeconomic data and the targets proposed by the Mexican Government for the year 2003.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.12.002}, issn = {0169-2070}, keywords = {Cointegration, Compatibility test, Economic targets, Finite sample adjustment, Multiple time series, regart} } @ARTICLE{HS89, author = {R. W. Hafer and Richard G. Sheehan}, title = {The sensitivity of VAR forecasts to alternative lag structures}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {399-408}, number = {3}, abstract = {Although numerous articles examine the effect on VAR forecasts from changes in the variables included in a model, little has been done to examine the effect that changing the lag structure has on forecasting accuracy. The latter analysis is made difficult by the fact that no overriding rule exists for ex ante selection of lag length in such models. This paper examines the sensitivity of forecasts from a VAR model using different lag structures. Holding constant the variables included and the time period studied, different lag structures are used. For example, we use simple ad hoc rules as well as statistical criteria, such as mean square error and Bayesian rules. Our results indicate that the accuracy of VAR forecasts varies dramatically across alternative lag structures. Moreover, our results show relatively short-lagged models to be more accurate, on average, than longer-lagged specifications.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90043-5}, issn = {0169-2070}, keywords = {Forecast accuracy, Lag structure, VAR, regart} } @ARTICLE{Hagerty87, author = {Michael R. Hagerty}, title = {Conditions under which econometric models will outperform naive models}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {457-460}, number = {3-4}, abstract = {Brodie and de Kluyver have reported empirical results in which simple naive models have produced forecasts as accurate as those derived from econometric models. I apply some recent theoretical results to show that these findings are plausible. I also suggest some general conditions under which econometric models will outperform naive models.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90041-0}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{Halal92, author = {William E. Halal}, title = {Encyclopedia of world problems and human potential: Union of international associations, 1991, (K.G. Saur, Munich), Vol. 1, 950 pp; Vol. 2, 1188 pp., hardcover, ISBN 3-598-10842-7, US\$400.00}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {639-641}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90076-L}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Hall86, author = {Peter Hall}, title = {Cities in the 21st century : Gary Gappert and Richard V. Knight, (Urban Affairs Annual Reviews, vol. 23) (Sage, Beverley Hills, CA and London, 1982) \$28.00/�19.50 (hard)/�9.75 (paper), pp. 320}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {124-125}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90041-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Hall86a, author = {Peter Hall}, title = {Eurofutures: The challenges of innovation (The FAST Report)}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {244-244}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90118-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Hall98, author = {Stephen Hall}, title = {Book Review}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {147-148}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00053-8}, issn = {0169-2070}, key = {tagkey1998147}, keywords = {bookrev} } @ARTICLE{HHP+86, author = {Stephen Hall and Brian Henry and Judith Payne and Simon Wren-Lewis}, title = {Forecasting employment : The role of forward-looking behaviour}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {435-445}, number = {4}, abstract = {Manufacturing output per head rose at an unprecedented rate in the UK in 1981/2, and conventional econometric relationships failed to forecast the associated falls in employment. In this paper we estimate manufacturing employment equations in which output expectations play a central role. These compare fabourably with alternative models, and are able to predict most of the large falls in employment over this period.}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90090-7}, issn = {0169-2070}, keywords = {Manufacturing employment, Productivity, Optimisation, Adjustment costs, Forward looking expectations, regart} } @ARTICLE{Hall90, author = {S. G. Hall}, title = {Challenges for macroeconomic modelling : W. Driehuis, M.M.G. Fase and H. den Hartog, eds., Contributions to Economic Analysis, Vol. 178 (North-Holland, Amsterdam, 1988) pp. 487, Dfl 185.00 (\$97.25).}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {442-443}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90070-R}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{HM07, author = {Stephen G. Hall and James Mitchell}, title = {Combining density forecasts}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {1-13}, number = {1}, abstract = {This paper brings together two important but hitherto largely unrelated areas of the forecasting literature, density forecasting and forecast combination. It proposes a practical data-driven approach to the direct combination of density forecasts by taking a weighted linear combination of the competing density forecasts. The combination weights are chosen to minimize the `distance', as measured by the Kullback-Leibler information criterion, between the forecasted and true but unknown density. We explain how this minimization both can and should be achieved but leave theoretical analysis to future research. Comparisons with the optimal combination of point forecasts are made. An application to simple time-series density forecasts and two widely used published density forecasts for U.K. inflation, namely the Bank of England and NIESR fan charts, illustrates that combination can but need not always help.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.08.001}, issn = {0169-2070}, keywords = {Density forecasts, Uncertainty, Combining forecasts, Evaluating forecasts, Inflation forecasting, regart} } @ARTICLE{Hallahan03, author = {Charlie Hallahan}, title = {STAMP 6.0: STAMP 6.0 Structural Time Series Analyser, Modeller and Predictor by Siem Jan Koopman, Andrew C. Harvey, Jurgen A. Doornik and Neil Shephard. London: Timberlake Consultants Ltd, 2000. Prices for the package, which includes GiveWin and one set of books and 1 CD, are: Single user: $850+$50sh, 5-user: $1700+sh, 10-user: $2250+sh, 20-user: $3400+sh, Unlimited: $4250+sh. Prices vary when STAMP bought in combination with other OxMetrics products. Academic discounts are also available. Head office is Timberlake Consultants Limited, Unit B3, Broomsleigh Business Park, Worsley Bridge Road, London, SE26 SBN, UK. Tel.: +44 (0)20 86973377, Fax: +44 (0)20 86973388. Email: info@timberlake.co.uk. Websites: http://www.timberlake.co.uk and (in the U.S.) http://www.timberlake-consultancy.com. Main website for STAMP is: www.STAMP-software.com.}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {319-325}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00029-3}, issn = {0169-2070}, keywords = {prodrev} } @ARTICLE{Hallahan97, author = {Charles Hallahan}, title = {SAS/ETS�}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {578-582}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00041-1}, issn = {0169-2070}, keywords = {prodrev} } @ARTICLE{Hallett93, author = {Andrew Hughes Hallett}, title = {Scanning the future: A long term scenario study of the world economy 1990-2015 : Central Planning Bureau, 1992, (Sdu Publishers, The Hague), 246 pp., ISBN 9039902046}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {133-134}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90062-R}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Hallett86, author = {Andrew Hughes Hallett}, title = {Prediction and regulation by linear least-square methods : Peter Whittle, (Blackwell, Oxford, 1983) second revised ed., �17.50, pp. XV + 187}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {125-127}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90043-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Hallett90, author = {A. J. Hughes Hallett}, title = {By how much would exchange rate stabilisation improve macroeconomic performance? : An exercise in forecasting alternative histories for the industrial economies}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {407-419}, number = {3}, abstract = {Evaluations of the Target Zone proposal for stabilising exchange rates have compared their results to historical policy performances. This does not allow us to distinguish the contribution of the target zone mechanism from the gains which are due to simply using the existing policy instruments to improve on the historical policy choices. Introducing suitable control solutions shows that the majority of the gains would in fact come from increasing the effectiveness of conventional policies, but that exchange rate targetting is a simple but effective way of preventing inefficient (uncoordinated) policy choices. These results appear to be insensitive to changes in the problem specification.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90067-L}, issn = {0169-2070}, keywords = {Exchange rate targetting, Policy coordination, regart} } @ARTICLE{Hamrick96, author = {Karen S. Hamrick}, title = {Bibliography on forecasting and planning: Kwok Keung (Kern) Kwong, Cheng Li, Vladimir Simunek and Chaman L. Jain, 1995, (Graceway Publishing Company, Inc.), 332 pp., paperback, \$56.95, ISBN 0-932126-16-2.}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {437-438}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(96)00693-0}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Hamrick93, author = {Karen S. Hamrick}, title = {Selling the story: The layman's guide to collecting and communicating demographic information : William Dunn, 1992, (American Demographic Books, Ithaca, NY), 245 pp., paperback \$27.50, hardback \$39.95, ISBN 0-936889-14-4}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {278-279}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90016-G}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Hand09, author = {David J. Hand}, title = {Mining the past to determine the future: Rejoinder}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {461 - 462}, number = {3}, note = {Special Section: Time Series Monitoring}, doi = {10.1016/j.ijforecast.2009.02.002}, issn = {0169-2070} } @ARTICLE{Hand09a, author = {David J. Hand}, title = {Mining the past to determine the future: Problems and possibilities}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {441 - 451}, number = {3}, note = {Special Section: Time Series Monitoring}, doi = {10.1016/j.ijforecast.2008.09.004}, issn = {0169-2070}, keywords = {Empirical models, Iconic models,Data mining,Model search,Large datasets,Selection bias} } @ARTICLE{Hanke89, author = {John Hanke}, title = {Forecasting in business schools: A follow-up survey}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {259-262}, number = {2}, abstract = {This article reports the results of a follow-up survey designed to determine whether changes have occurred in the area of forecasting education since 1983. The survey instrument was sent to member institutions of the American Assembly of Collegiate Schools of Business (AACSB). The results of this survey were similar to those for the 1983 study. Differences were found in computer usage and the number of schools planning to offer forecasting courses in the future.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90093-9}, issn = {0169-2070}, keywords = {Business school courses, Computer packages, Forecasting methods, regart} } @ARTICLE{HJL05, author = {Jesper Hansson and Per Jansson and M{\aa}rten L{\"o}f}, title = {Business survey data: Do they help in forecasting GDP growth?}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {377-389}, number = {2}, abstract = {In this paper we examine whether data from business tendency surveys are useful for forecasting GDP growth in the short run. The starting point is a so-called dynamic factor model (DFM), which is used both as a framework for dimension reduction in forecasting and as a procedure for filtering out unimportant idiosyncratic noise in the underlying survey data. In this way, it is possible to model a rather large number of noisy survey variables in a parsimoniously parameterised vector autoregression (VAR). To assess the forecasting performance of the procedure, comparisons are made with VARs that either use the survey variables directly, use macro variables only, or use other popular summary indices of economic activity. Our DFM-based procedure turns out to outperform the competing alternatives in most cases.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.11.003}, issn = {0169-2070}, keywords = {Business survey data, Dynamic factor models, Macroeconomic forecasting, regart} } @ARTICLE{Hapka86, author = {Alexander R. Hapka}, title = {Comparative models for electrical load forecasting : D.W. Bunn and E.D. Farmer, (Wiley, Belfast, 1985) pp. 232, �24.95}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {501-505}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90103-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Harries02, author = {Clare Harries}, title = {Forecasting with Judgment: George Wright and Paul Goodwin (Eds.) (1998) Chichester: Wiley. 297 pages. ISBN 0 471 97014 X Hardback: �55.00, \$165.00.}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {159-161}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00131-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Harries03, author = {Richard Harries}, title = {Modelling and predicting recorded property crime trends in England and Wales--a retrospective}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {557-566}, number = {4}, abstract = {In 1999 the Home Office published, for the first time ever, 3-year ahead projections of property crime in England and Wales. The projections covered the period 1999-2001 and indicated strong upward pressure after five full years of falling crime. This pressure was generated by three factors: the number of young men in the general population, the state of the economy and the fact that property crime appeared to be well below its underlying trend level. The projections received a mixed response, with some agreeing that crime was set to rise while questioning the scale of any increase, to others who doubted the value of this type of econometric modelling. In fact, property crime did increase in 1999, although not at the rate suggested by the models--and indeed levels of burglary continued to fall. This paper addresses some of the reasons for this disparity as well as considering various criticisms of the Home Office approach.}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00090-6}, issn = {0169-2070}, keywords = {Cointegration, Error-correction models, Routine activities theory, Crime forecasting, regart} } @ARTICLE{Harriff97, author = {Richard B. Harriff}, title = {Chaos and nonlinear dynamics in the financial markets: Theory, evidence, and applications : Robert R. Trippi (ed.), Irwin Professional Publishing Company, Burr Ridge, IL, 1996, 528 pages, \$85, ISBN 1-55738-857-7}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {146-147}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00727-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{HL93, author = {John L. Harris and Lon-Mu Liu}, title = {Dynamic structural analysis and forecasting of residential electricity consumption}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {437-455}, number = {4}, abstract = {This paper studies the dynamic relationships between electricity consumption and several potentially relevant variables, such as weather, price, and consumer income. Monthly data from January 1969 to December 1990 for all-electric residences in the southeast United States are used for this study. Because of the nature of the annual weather cycle, several of these time series are highly seasonal. Multiple-input transfer function models are employed to analyze the data for their dynamic structure and to evaluate future levels of electricity consumption. The linear transfer function (LTF) method is employed in the identification of transfer function models for structural analysis and forecasting. A major finding is that price plays a major role in explaining conservation behavior by electricity consumers. This result has important implications for forecasting the consumption of electric energy. This paper also demonstrates the appropriate construction of models for economic time series with strong seasonality.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90072-U}, issn = {0169-2070}, keywords = {Transfer function models, ARIMA models, Seasonality, Electricity consumption, Electricity prices, Energy conservation, Weather conditions, regart} } @ARTICLE{HY10, author = {Richard D.F. Harris and Fatih Yilmaz}, title = {Estimation of the conditional variance-covariance matrix of returns using the intraday range}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {180 - 194}, number = {1}, note = {Special Section: European Election Forecasting}, doi = {10.1016/j.ijforecast.2009.02.009}, issn = {0169-2070}, keywords = {Conditional variance-covariance matrix of returns, Exponentially weighted moving average (EWMA),Intraday range} } @ARTICLE{HKY05, author = {Richard Harrison and George Kapetanios and Tony Yates}, title = {Forecasting with measurement errors in dynamic models}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {595-607}, number = {3}, abstract = {In this paper, we explore the consequences for forecasting of the following two facts: first, that over time statistics agencies revise and improve published data, so that observations on more recent events are those that are least well measured. Second, that economies are such that observations on the most recent events contain the largest signal about the future. We discuss a variety of forecasting problems in this environment, and present an application using a univariate model of the quarterly growth of UK private consumption expenditure.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.03.002}, issn = {0169-2070}, keywords = {Forecasting, Data revisions, Dynamic models, regart} } @ARTICLE{HS90, author = {Andrew Harvey and Ralph D. Snyder}, title = {Structural time series models in inventory control}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {187-198}, number = {2}, abstract = {Exponential smoothing methods are often used to forecast demand in computerized inventory control systems. These methods, by themselves, are rather ad hoc, but they can be given a proper statistical foundation by setting up a class of structural time series models. The purpose of the paper is to highlight the potential role of these models in inventory control. In particular they are used as the basis for deriving formulae for estimating the mean and variance of the lead time demand distribution under both constant and stochastic lead time assumptions.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90004-U}, issn = {0169-2070}, keywords = {Exponential smoothing, Kalman filtering, Inventory control, Forecasting, Lead times, regart} } @ARTICLE{HT94, author = {Andrew Harvey and Sabine Toulson}, title = {Review of `4thought'}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {35-41}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90047-7}, issn = {0169-2070} } @ARTICLE{HLN97, author = {David Harvey and Stephen Leybourne and Paul Newbold}, title = {Testing the equality of prediction mean squared errors}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {281-291}, number = {2}, abstract = {Given two sources of forecasts of the same quantity, it is possible to compare prediction records. In particular, it can be useful to test the hypothesis of equal accuracy in forecast performance. We analyse the behaviour of two possible tests, and of modifications of these tests designed to circumvent shortcomings in the original formulations. As a result of this analysis, a recommendation for one particular testing approach is made for practical applications.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00719-4}, issn = {0169-2070}, keywords = {Comparing forecasts, Correlated forecast errors, Evaluation of forecasts, Non-normality, regart} } @ARTICLE{HN03, author = {David I. Harvey and Paul Newbold}, title = {The non-normality of some macroeconomic forecast errors}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {635-653}, number = {4}, abstract = {This paper investigates the distributional properties of individual and consensus time series macroeconomic forecast errors, using data from the Survey of Professional Forecasters. The degree of autocorrelation and the presence of ARCH in the consensus errors is also determined. We find strong evidence of leptokurtic forecast errors as well as evidence of skewness, suggesting that an assumption of error normality is inappropriate; many of the forecast error series are found to have non-zero mean, and we find widespread evidence of consensus error ARCH. Properties of the distribution of cross-sectional forecast errors are also examined.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00076-6}, issn = {0169-2070}, keywords = {Survey data, Forecast error distribution, Non-normality, regart} } @ARTICLE{HM88, author = {Edward B. Harvey and K. S. R. Murthy}, title = {Forecasting manpower demand and supply : A model for the accounting profession in Canada}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {551-562}, number = {4}, abstract = {Manpower forecasting, while being an important tool for decision makers such as potential entrants, employers and policy makers, is still in its infancy. The most notable problem in this area is not the lack of sophisticated models but the absence of reliable time series data. For this reason, the forecaster is forced to use the available data in conjunction with a suitable model framework and some judgemental decision. In this paper, we have used such an approach to forecast the possible aggregate manpower imbalances in the accounting profession. Along with the basic primary sources of data from the profession itself, the model uses the outputs of a major Canadian macro econometric model for aggregate industry-based labour requirements. In case of vital data gaps, we were forced to use judgemental estimates based on available qualitative information. The overall approach employed in this exercise emphasizes the efficient use of available data in the design of the model. We consider this method preferable to the alternative, this is, to have a sophisticated model and make adjustments for missing (or unsuitable) data. The basic objective of this paper is mainly to illustrate the mixing of judgemental considerations within a model framework.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90132-X}, issn = {0169-2070}, keywords = {Manpower forecasting, Accounting, Judgemental adjustment, Macroeconometric model - Canada, Model design, Validating assumptions, regart} } @ARTICLE{HB96, author = {Nigel Harvey and Fergus Bolger}, title = {Graphs versus tables: Effects of data presentation format on judgemental forecasting}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {119-137}, number = {1}, abstract = {We report two experiments designed to study the effect of data presentation format on the accuracy of judgemental forecasts. In the first one, people studied 44 different 20-point time series and forecast the 21st and 22nd points of each one. Half the series were presented graphically and half were in tabular form. Root mean square error (RMSE) in forecasts was decomposed into constant error (to measure bias) and variable error (to measure inconsistency). For untrended data, RMSE was somewhat higher with graphical presentation: inconsistency and an overforecasting bias were both greater with this format. For trended data, RMSE was higher with tabular presentation. This was because underestimation of trends with this format was so much greater than with graphical presentation that it overwhelmed the smaller but opposing effects that were observed with untrended series. In the second experiment, series were more variable but very similar results were obtained.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00634-6}, issn = {0169-2070}, keywords = {Judgement, Time series, Graphs, Forecasting, regart} } @ARTICLE{HH04, author = {Nigel Harvey and Clare Harries}, title = {Effects of judges' forecasting on their later combination of forecasts for the same outcomes}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {391-409}, number = {3}, abstract = {In a first experiment, we show that judges' ability to combine forecasts that they receive from more knowledgeable advisors is impaired when they have previously made their own forecasts for the same outcomes. It appears that they implicitly include their own forecasts among those that have to be combined. In a second experiment, we demonstrate that people combining forecasts put more weight on forecasts that are their own (whether or not they are labelled as such) or are labelled as their own (when they are not) than on equivalent forecasts that are neither their own nor labelled as such. We argue that the cognitive mechanisms responsible for these effects are better characterized as a type of conservatism rather than as an example of anchoring. Our results imply that people responsible for integrating forecasts from more knowledgeable advisors should not explicitly include their own forecasts among those that they combine and should consider avoiding making their own forecasts altogether.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.09.012}, issn = {0169-2070}, keywords = {Judgment, Forecasting, Information integration, Combining forecasts, regart} } @ARTICLE{HR05, author = {Jane L. Harvill and Bonnie K. Ray}, title = {A note on multi-step forecasting with functional coefficient autoregressive models}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {717-727}, number = {4}, abstract = {This paper presents and evaluates alternative methods for multi-step forecasting using univariate and multivariate functional coefficient autoregressive (FCAR) models. The methods include a simple plug-in approach, a bootstrap-based approach, and a multi-stage smoothing approach, where the functional coefficients are updated at each step to incorporate information from the time series captured in the previous predictions. The three methods are applied to a series of U.S. GNP and unemployment data to compare performance in practice. We find that the bootstrap-based approach out-performs the other two methods for nonlinear prediction, and that little forecast accuracy is sacrificed using any of the methods if the underlying process is actually linear.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.04.012}, issn = {0169-2070}, keywords = {Bootstrap prediction, Multi-step prediction, Smoothing, Vector nonlinear time series, regart} } @ARTICLE{HHZ09, author = {Hossein Hassani and Saeed Heravi and Anatoly Zhigljavsky}, title = {Forecasting European industrial production with singular spectrum analysis}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {103-118}, number = {1}, abstract = {In this paper, the performance of the Singular Spectrum Analysis (SSA) technique is assessed by applying it to 24 series measuring the monthly seasonally unadjusted industrial production for important sectors of the German, French and UK economies. The results are compared with those obtained using the Holt-Winters' and ARIMA models. All three methods perform similarly in short-term forecasting and in predicting the direction of change (DC). However, at longer horizons, SSA significantly outperforms the ARIMA and Holt-Winters' methods.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.09.007}, issn = {0169-2070}, keywords = {Singular spectrum analysis, ARIMA, Holt-Winters' method, Forecasting, European industrial production series, regart} } @ARTICLE{Heaney02, author = {Richard Heaney}, title = {Does knowledge of the cost of carry model improve commodity futures price forecasting ability?: A case study using the London Metal Exchange lead contract}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {45-65}, number = {1}, abstract = {The use of futures prices to predict commodity cash prices is important both to practitioners and researchers yet the literature provides conflicting results on the ability of futures prices to predict cash prices. Brenner and Kroner [Journal of Financial and Quantitative Analysis 30 (1995) 23] argue that if the cost of carry model applies to commodity futures pricing then current futures prices may not accurately predict subsequent cash prices. Inventory, cash price return variance, cash price return first order auto-correlation and interest rates are used to proxy carrying costs in a test of the ability of commodity futures prices to predict cash prices. Various predictive models relating futures price to cash price are described, including univariate and multivariate error correction models. London Metal Exchange (LME) lead cash prices, lead futures prices, lead inventory and UK treasury bill rates are collected over the period 1964 to 1995. Analysis of this data confirms the importance of the cost of carry model elements as well as futures price in forecasting cash prices.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00106-6}, issn = {0169-2070}, keywords = {Error correction model, Cost of carry model, Forecasting, regart} } @ARTICLE{HDG08, author = {Christiaan Heij and Dick van Dijk and Patrick J.F. Groenen}, title = {Macroeconomic forecasting with matched principal components}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {87-100}, number = {1}, abstract = {This article proposes an improved method for the construction of principal components in macroeconomic forecasting. The underlying idea is to maximize the amount of variance of the original predictor variables that is retained by the components in order to reduce the variance involved in estimating the forecast model. This is achieved by matching the data window used for constructing the components with the estimation window. Extensive Monte Carlo simulations, using dynamic factor models, clarify the relationship between the achieved reduction in forecast variance and various design parameters, such as the observation length, the number of predictors, and the length of the forecast horizon. The method is also used in an empirical application to forecast eight key US macroeconomic time series over various horizons, where the components are constructed from a large set of predictors. The results show that the proposed modification leads, on average, to more accurate forecasts than previously used principal component regression methods.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.08.005}, issn = {0169-2070}, keywords = {Time series forecasting, Long term forecasting, Forecast evaluation, Simulation, Dynamic factor model, Factor construction, regart} } @ARTICLE{Heilemann02, author = {Ullrich Heilemann}, title = {Increasing the transparency of macroeconometric forecasts: a report from the trenches}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {85-105}, number = {1}, abstract = {The acceptance of macroeconometric model results suffers from the procedures of model builders/users that are often opaque. This paper describes in detail the production of a macroeconomic forecast with a macroeconometric model for the German economy. The model used is the RWI-business cycle model, a medium sized macroeconometric model (41 stochastic equations, 86 identities). It has been used since the late 1970s in the RWI and in the biannual `Joint Diagnosis' of German economic research institutes. The paper starts with a presentation of the analytical foundations of econometric model forecasting in general and of various ways and forms of incorporating outside-model information in particular. The presentation of the main features of the model is followed by the detailed description of the various stages of forecast production. The paper ends with suggesting a more intensive use of the analytical possibilities of the models and their forecast.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00113-3}, issn = {0169-2070}, keywords = {Macro models, Forecast evaluation, Forecast comparison, add-factoring, regart} } @ARTICLE{HS07, author = {Ullrich Heilemann and Herman Stekler}, title = {Introduction to The future of macroeconomic forecasting}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {159-165}, number = {2}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.01.001}, issn = {0169-2070}, keywords = {editorial}, keywordss = {Forecast bias} } @ARTICLE{HS88, author = {Scott E. Hein and Raymond E. Spudeck}, title = {Forecasting the daily federal funds rate}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {581-591}, number = {4}, abstract = {This paper compares two alternative one-day-ahead forecasts of tomorrow's federal funds rate. The first forecast is a simple random walk forecast in which the forecast of tomorrow's federal funds rate is taken to be today's federal funds rate. The second forecast is an ARIMA model forecast that was allowed to vary with changes in the Federal Reserve System's operating procedures. These two forecasts are compared in terms of their general forecast accuracy and the decision support they provide to a financial institution hypothesized to be borrowing $7 million a week in the federal funds market. Even in cases felt to be most favorable to the ARIMA forecasts, the degree of forecast accuracy and decision support superiority of the ARIMA forecasts is found to be quite small.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90135-5}, issn = {0169-2070}, keywords = {Federal funds rate, ARIMA, Random walk, Forecast accuracy, Decision support, regart} } @ARTICLE{Heitmann91, author = {George Heitmann}, title = {Introductory business forecasting : Paul Newbold and Theodore Bos, (South-western, Cincinnati, OH,1990), pp. 497.}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {243-245}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90061-Y}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{HR08, author = {David F. Hendry and J. James Reade}, title = {Elusive return predictability: Discussion}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {22-28}, number = {1}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.09.003}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Henry92, author = {Brian Henry}, title = {Seasonal adjustment as a practical problem : F.A.G. den Butter and M.M.G. Fase, Elsevier, Amsterdam, 1991), pp. iv + 226, US\$94.50, Dfl 165.00}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {271-274}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90126-T}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Henry89, author = {SGB Henry}, title = {Models of the UK economy: A fourth review by the ESRC Macroeconomic Modelling Bureau : K.F. Wallis, ed, P.G. Fisher, J.A. Longbottom, D.S. Turner and J.D. Whitley, (Oxford University Press, Oxford, U.K., 1987) �22.50/\$36.00, pp. 152}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {141-142}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90076-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Henry90, author = {S. G. B. Henry}, title = {Investment and factor demand : Patrick Artus and Pierre-Alain Muet, Contributions to Economic Analysis, Vol. 193 (North-Holland, Amsterdam, 1990) pp. 308, Dfl 175.00 (\$69.50)}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {441-442}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90069-N}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Henry89a, author = {S. G. B. Henry}, title = {Advances in econometrics : Truman F. Bewley, ed.,Vol. I (Cambridge University Press, 1988), �27.50 (\$34.50)}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {612-614}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90021-6}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Henry88, author = {S. G. B. Henry}, title = {Business cycle surveys in the assessment of economic activity : Karl Heinrich Oppenl{\"a}nder and G{\"u}nter Poser, eds. (Gower Aldershot, UK, 1986) pp. 674, �35. \$50.00}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {291-292}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90085-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Henry87, author = {S. G. B. Henry}, title = {Structural sensitivity in econometric models : Edwin, Kuh, John W. Neese and Peter Hollinger, (Wiley, New York and Chichester, 1985) 324 pp., 38.00}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {343-344}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90022-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Henry86, author = {S. G. B. Henry}, title = {Specification, Estimation and analysis of macroeconomic models : Ray C. Fair, Specification, (Harvard University Press, Cambridge, MA, 1984) \$35.00/�28.00, pp. 479}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {122-124}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90040-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{HH90, author = {S. G. B. Henry and K. Holden}, title = {Macroeconomic forecasting}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {283-284}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90054-F}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{HH90a, author = {S. G. B. Henry and K. Holden}, title = {Introduction}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {285-286}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90055-G}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{HOB04, author = {Saeed Heravi and Denise R. Osborn and C. R. Birchenhall}, title = {Linear versus neural network forecasts for European industrial production series}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {435-446}, number = {3}, abstract = {The value of neural network models in forecasting economic time series has been established for North America, but little work has been undertaken for Europe. This paper considers 24 series measuring the annual change in monthly seasonally unadjusted industrial production for important sectors of the German, French and UK economies. Preliminary testing indicates relatively little evidence of nonlinearity in most series. According to root mean-square error (RMSE), linear models generally produce more accurate post-sample forecasts than neural network models at horizons of up to a year. This applies overall and also to the sub-group of series with substantial sample period evidence of nonlinearity. In contrast, the neural network models dominate linear ones in predicting the direction of change. Therefore, the model chosen by users should depend on the type of forecasts they require.}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00062-1}, issn = {0169-2070}, keywords = {Neural networks, Forecasting, Industrial production, regart} } @ARTICLE{Herwartz01, author = {Helmut Herwartz}, title = {Investigating the JPY/DEM-rate: arbitrage opportunities and a case for asymmetry}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {231-245}, number = {2}, abstract = {Deviations from the triangular equality are observed on foreign exchange (FX) markets when the respective rates are sampled at very high frequencies. Within the framework of nonstationary but cointegrated time series the triangular equation may be regarded as a long-run equilibrium. A time invariant and symmetric vector error correction model seems appropriate to explain the evolution of FX-returns depending on recent returns and on lagged deviations from the triangular equality. High frequency FX-rates are typically unequally spaced. Kalman recursions cope with the issue of missing values making (Quasi-) Maximum-Likelihood estimation feasible. The in-sample and out-of-sample forecasting performance of the common vector error correction model is compared to that of alternative specifications including a moving average process, periodic autoregressions, and asymmetric generalizations of the symmetric vector autoregression. For the actual JPY/DEM-rate the employed asymmetric time series models yield superior forecasting results compared to the remaining empirical models. Time dependent processes allowing for intra-day seasonality provide only minor improvements compared to time invariant models of corresponding autoregressive order.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00097-2}, issn = {0169-2070}, keywords = {Foreign exchange, High frequency data, Time-dependent vs. time invariant models, Smooth transition models, Market timing ability, regart} } @ARTICLE{Herwartz97, author = {Helmut Herwartz}, title = {Performance of periodic error correction models in forecasting consumption data}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {421-431}, number = {3}, abstract = {Periodic time series models have become an appealing tool for the analysis of seasonal time series. Since these models condition the data-generating process on the season they are able to cope with periodic generalisations of economic models with seasonal preferences and seasonal technologies. This paper examines the forecasting performance of alternative specifications of a periodic error-correction model for the relation between consumption and income. Estimation and forecasting exercises are performed for data from the United Kingdom, Sweden, Germany and Japan.}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00028-9}, issn = {0169-2070}, keywords = {Forecasting, Error-correction, Periodic models, Seasonality, regart} } @ARTICLE{HB88, author = {R. M. J. Heuts and J. H. J. M. Bronckers}, title = {Forecasting the Dutch heavy truck market : A multivariate approach}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {57-79}, number = {1}, abstract = {In this paper it is investigated whether multivariate time series models can improve the forecasting performance of Holt-Winters models and univariate `naive' ARIMA-models, which are easier to construct, but do not take into account lead-lag relationships. This research deals with the Dutch truck market performance in the light of overall economic developments. A 5-variate model is built, containing two truck sales series and three economic indicators. It is found that a substantial reduction in residual variance can be found by using a multivariate model. In the case of one truck series (rigids) this leads to uniformly better forecasts. For the other output series (artics), no improvement in forecasting accuracy was found. Holt-Winters models do not seem to improve any of the sophisticated models.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90010-6}, issn = {0169-2070}, keywords = {Uni- and multivariate ARIMA-models, Holt-Winters, Truck market modelling, Alignment, Forecasting performance, regart} } @ARTICLE{Hewins88, author = {R. D. Hewins}, title = {Exchange rate theory and practice : John F. Bilson and Richard C. Marston, eds. (The University of Chicago Press, Chicago and London, 1984) pp. 528, �53.25, \$66.75}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {302-302}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90093-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Hibon93, author = {Michèle Hibon}, title = {Computational aspects and a personal view of the M2-competition}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {24-25}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90046-P}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{HE05, author = {Michèle Hibon and Theodoros Evgeniou}, title = {To combine or not to combine: selecting among forecasts and their combinations}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {15-24}, number = {1}, abstract = {Much research shows that combining forecasts improves accuracy relative to individual forecasts. In this paper we present experiments, using the 3003 series of the M3-competition, that challenge this belief: on average across the series, the best individual forecasts, based on post-sample performance, perform as well as the best combinations. However, this finding lacks practical value since it requires that we identify the best individual forecast or combination using post sample data. So we propose a simple model-selection criterion to select among forecasts, and we show that, using this criterion, the accuracy of the selected combinations is significantly better and less variable than that of the selected individual forecasts. These results indicate that the advantage of combining forecasts is not that the best possible combinations perform better than the best possible individual forecasts, but that it is less risky in practice to combine forecasts than to select an individual forecasting method.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.05.002}, issn = {0169-2070}, keywords = {Combined forecasts, M3-competition, Forecasting accuracy, Model selection, regart} } @ARTICLE{HCA91, author = {R. Carter Hill and Phillip A. Cartwright and Julia F. Arbaugh}, title = {The use of biased predictors in marketing research}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {271-282}, number = {3}, abstract = {Marketing data are often collinear. Multicollinearity can pose serious problems for estimation of models such as those generally specified for the analysis of price and promotions. In this paper, we analyze the relative performance of several biased estimators under an in-sample and out-of-sample mean squared error criterion. We consider the alternative estimators from the standpoint of addressing the problem of estimating models with collinear data.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90002-D}, issn = {0169-2070}, keywords = {Price-promotion models, Biased estimators, Multicollinearity, regart} } @ARTICLE{HMO+94, author = {Tim Hill and Leorey Marquez and Marcus O'Connor and William Remus}, title = {Artificial neural network models for forecasting and decision making}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {5-15}, number = {1}, abstract = {Some authors advocate artificial neural networks as a replacement for statistical forecasting and decision models; other authors are concerned that artificial neural networks might be oversold or just a fad. In this paper we review the literature comparing artificial neural networks and statistical models, particularly in regression-based forecasting, time series forecasting, and decision making. Our intention is to give a balanced assessment of the potential of artificial neural networks for forecasting and decision making models. We survey the literature and summarize several studies we have performed. Overall, the empirical studies find artificial neural networks comparable with their statistical counterparts. We note the need to consider the many mathematical proofs underlying artificial neural networks to determine the best conditions for their use in forecasting and decision making.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90045-0}, issn = {0169-2070}, keywords = {Artificial neural networks, Regression, Forecasting, Decision making, Time seriesregart} } @ARTICLE{Hillmer88, author = {Steven C. Hillmer}, title = {Software reviews}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {143-159}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90016-7}, issn = {0169-2070}, keywords = {prodrev} } @ARTICLE{HBS05, author = {H.S. Hippert and D.W. Bunn and R.C. Souza}, title = {Large neural networks for electricity load forecasting: Are they overfitted?}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {425-434}, number = {3}, abstract = {Neural networks have apparently enjoyed considerable success in practice for predicting short-term daily electricity load profiles. Most of these applications have utilised very large neural network specifications, which raises the methodological question of over-fitting. This paper examines this issue by comparing several forecasting methods on a sample of hourly electricity demands, including both large neural networks and conventional regression-based methods. We find good performance for the large neural networks, and offer some analysis of why forecasting the 24 element vector of daily electricity demands may be particularly conducive to this approach.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.12.004}, issn = {0169-2070}, keywords = {Neural networks, Electricity demand, regart} } @ARTICLE{Hogarth07, author = {Robin M. Hogarth}, title = {Information asymmetry and aggregation rules: A comment on J{\o}rgensen (2007)}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {465-467}, number = {3}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.05.012}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Hogarth89, author = {Robin M. Hogarth}, title = {On combining diagnostic `forecasts': Thoughts and some evidence}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {593-597}, number = {4}, abstract = {The combining of forecasts involves more than issues of statistical aggregation. This comment focuses on situations where people have to combine forecasts in the form of diagnostic opinions concerning different states of nature. Taking a descriptive or psychological viewpoint, it is argued that people act upon the information they obtain and engage in considerable interpretation and imagination. Three specific problems are discussed: (1) the level at which opinions are aggregated; (2) the effects of redundancy and credibility of different sources; and (3) the manner in which the structure of information from multiple sources can lead to different diagnostic interpretations. The discussions are illustrated with experimental data.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90015-0}, issn = {0169-2070}, keywords = {Combining forecasts, Diagnosis, Imagination, regart} } @ARTICLE{HD99, author = {Thomas M. Holbrook and Jay A. DeSart}, title = {Using state polls to forecast presidential election outcomes in the American states}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {137-142}, number = {2}, abstract = {This paper presents a simple forecasting model for state-level presidential outcomes, based on statewide preference polls and a lagged vote variable. The analysis illustrates two important points. First, the candidate who is leading in a state in September usually goes on to win that state in the November election. Second, the combination of pre-election preference polls and a lagged dependent variable generates highly accurate estimates of presidential election outcomes in the states. The limits of using statewide preference polls are also discussed.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00060-0}, issn = {0169-2070}, keywords = {State polls, Presidential elections, Forecasting, America, regart} } @ARTICLE{Holden97, author = {Ken Holden}, title = {Microsimulation modelling of the corporate firm : F.W. van Tongeren, 1995, Springer-Verlag, Berlin, 275 pp., DM 82.00, ISBN 3-540-59443-4}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {143-144}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00721-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Holden97a, author = {Ken Holden}, title = {Economies in transition and the world economy: Models, forecasts and scenarios : Wladyslaw Welfe (ed.) (Peter Lang, Frankfurt am Main, 1997) 528 pp., �52.00, ISBN 3-631-49335-5}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {586-587}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00045-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Holden96, author = {Ken Holden}, title = {Testing exogeneity : N. R. Ericsson and J. S. Irons, Editors, 1994, (Oxford University Press, Oxford), 422 pp. �18.95, ISBN 0-19-8774044.}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {303-304}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(96)00665-6}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Holden95, author = {Ken Holden}, title = {Macroeconomic modelling vols I and II : Kenneth F. Wallis, Editor, 1944, (Edward Elgar, Aldershot), Vol. I: 460 pp., Vol. II: 475 PP., �175.00, ISBN 1-85278-664-7}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {334-335}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(95)90063-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Holden93, author = {Kenneth Holden}, title = {Leading economic indicators: New approaches and forecasting records : Kajal Lahiri and Geoffrey H. Moore, eds. 1992 (Cambridge University Press, Cambridge, UK), 464 pp., paperback �15.95, US\$22.95, ISBN 0-521-43858-6}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {271-272}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90010-K}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Holden92, author = {Ken Holden}, title = {Economic structural change: Analysis and forecasting : Peter Hackl and Anders H. Westlund (eds.), (Springer-Verlag, Berlin, 1991) pp. 385, DM 148}, journal = {International Journal of Forecasting}, year = {1992}, volume = {7}, pages = {538-539}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90041-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Holden91, author = {Ken Holden}, title = {Economic modelling in the OECD countries : Homa Motamen, ed., (Chapman and Hall, London, U.K., 1988), pp. 746, �89.00.}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {242-243}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90060-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Holden89, author = {Ken Holden}, title = {Employment forecasting: The employment problem in industrialized countries : M.J.D. Hopkins, ed., (Pinter Publishers, New York and London, 1988)}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {429-430}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90049-6}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Holden89a, author = {Ken Holden}, title = {The computation and modelling of economic equilibria : A. Talman and G. van der Laan, eds., (North-Holland, Amsterdam, 1987) pp. 229, Dfl 120.00}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {612-612}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90020-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Holden88, author = {Kenneth Holden}, title = {Centre for economic forecasting, economic and financial review : London Business School, volume 2, 1986 (Gower Aldershot, UK.) pp. 116. �9.60. \$17.50}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {290-291}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90084-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Holden87, author = {K. Holden}, title = {Economic forecasting and policy: The international dimension : J. Llewellyn, S. Potter and L. Samuelson, (Routledge and Kegan Paul, London, UK, 1985 288 pp., 12.95}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {342-343}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90021-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Holden86, author = {K. Holden}, title = {Models of the UK economy: A review by the ESRC Macroeconomic Modelling Bureau}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {242-243}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90117-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{HB90, author = {K. Holden and A. Broomhead}, title = {An examination of vector autoregressive forecasts for the U.K. economy}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {11-23}, number = {1}, abstract = {The vector autoregressive (VAR) approach to forecasting is applied to economic variables for the U.K. Unrestricted VAR and Bayesian VAR models are contructed using the data available in November 1981. Forecasts for 1981-1984 are compared with forecasts from four economic models and also from simple AR and ARIMA models. The economic models give the best forecasts for the growth of output and inflation but the other methods perform well for the remaining variables. The accuracy of VAR forecasts varies with the data used for fitting the models and the prior assumptions made. Finally, forecasts for 1987-1992 are presented, using the data available in November 1987.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90094-R}, issn = {0169-2070}, keywords = {Economic forecasting, Vector autoregresive (VAR) models, Time series models, Bayesian forecasting, regart} } @ARTICLE{HKL01, author = {Ken Holden and Philip A. Klein and Kajal Lahiri}, title = {Introduction}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {329-332}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00101-7}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Holloway89, author = {Thomas M. Holloway}, title = {Measuring the cyclical sensitivity of federal receipts and expenditures: Simplified estimation procedures}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {347-360}, number = {3}, abstract = {It is well known that the federal budget automatically responds to cyclical fluctuations in economic activity. For this reason, economists are often interested in removing these temporary cyclical changes in the budget to permit the analysis of fiscal trends and impacts. Cyclically adjusted budgets (e.g., the full-employment budget, the high-employment budget, etc.) emerge after removing the automatic cyclical responses and are frequently used in these fiscal studies. Further, forecasts of the cyclically adjusted budget often appear in policy discussions. This paper presents simple procedures to estimate automatic cyclical responses and the cyclically adjusted budget. The first section discusses some of the issues surrounding the measurement of automatic cyclical responses and the cyclically adjusted budget. The most controversial issue, the selection of trend GNP (e.g., potential GNP), is highlighted. The second section describes a relatively large structural model used by the Bureau of Economic Analysis to measure the cyclical responses and the cyclically adjusted budget. The third section presents several stochastic equations that approximate the results from the structural model. The final section uses the results from the stochastic equations to produce two equations - one for receipts, one for expenditures - that can be used to estimate the automatic cyclical responses and the cyclically adjusted budget. A comparison of the results from the two equations with those from the structural model and a post-sample analysis suggest that the two equations capture most of the variation in the estimates from the larger model, and can be used by forecasters to produce reasonable approximations of what `official' cyclically adjusted budget estimates would be.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90038-1}, issn = {0169-2070}, keywords = {Fiscal trend analysis, Cyclical adjustments, Structural modeling, Post-sample evaluation, regart} } @ARTICLE{Holmen87, author = {Jay S. Holmen}, title = {A note on the value of combining short-term earnings forecasts : A test of Granger and Ramanathan}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {239-243}, number = {2}, abstract = {This paper conducts an empirical analysis of the approaches to obtaining linear combinations of forecasts. Simulated quarterly earnings were modeled using three ARIMA models. One-quarter ahead forecasts were then developed. These forecasts were combined using alternative approaches. The most accurate forecasts were obtained by adding a constant term and not constraining the weights to add up to one. The differences in the accuracy rankings were found to be statistically significant. The results are similar to those obtained by Granger and Ramanathan (1984).}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90005-7}, issn = {0169-2070}, keywords = {Combining forecasts, ARIMA models, regart} } @ARTICLE{Holmes86, author = {R. A. Holmes}, title = {Leading indicators of industrial employment in British Columbia}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {87-100}, number = {1}, abstract = {Leading indicators employing a new weighting procedure are developed and tested in this study. The weighting procedure used produces a leading indicator which is tailored to forecasts of a specific series. The application of our methodology which is presented in this study is to forecasts of industrial employment in British Columbia (BCEI). In this application, our leading indicators are shown to provide substantial improvement over the best available alternative increasing explanatory power from 15 to 92 percent at 6-months lead, and from 38 to 79 percent at 12-months lead. Moreover, our leading indicators provide an average lead of about 12 months at the 6 major turning points in BCEI over the 1973 to 1985 period. Further testing is provided by employing our leading indicators in decomposition and transfer function models designed to forecast BCEI, and comparing results with forecasts from Holt's exponential smoothing model. The transfer function models are found to perform best yielding out-of-sample forecast errors of about 3 percent in 6-month forecasts and about 5 to 6 percent in 12-month forecasts. We conclude that our approach has produced leading indicators which yield substantially improved forecasts of BCEI, and that our methodology which is more generally applicable, warrants consideration in forecasts of other series. Results from some of our other work indicate that our approach will provide improved forecasts in applications to other time periods and other countries.}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90032-4}, issn = {0169-2070}, keywords = {Leading indicator, Industrial employment, Forecasts, Turning points, Decomposition models, Transfer function models, regart} } @ARTICLE{HS93, author = {Richard A. Holmes and Abul F. M. Shamsuddin}, title = {Evaluation of alternative leading indicators of British Columbia industrial employment}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {77-83}, number = {1}, abstract = {Leading indicators based on principal components and weighted r2 values are evaluated in this study. The tests are based on out-of-sample forecasts of British Columbia employment. Overall, the principal component approach is found to be superior in tests conducted separately by forecast horizons ranging from 1 to 12 months, and in tests conducted in the months immediately following the 1984-1992 turning point. This finding is explained in the study by the methodological superiority of the leading indicator based on principal components of the input series.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90055-R}, issn = {0169-2070}, keywords = {Leading indicator, Forecasts, Turning points, ARIMA models, Transfer function models, regart} } @ARTICLE{Holmes92, author = {William M. Holmes}, title = {Time Series : Sir Maurice Kendall and J. Keith Ord, third edition (Edward Arnold, Great Britain, 1990) pp. 296}, journal = {International Journal of Forecasting}, year = {1992}, volume = {7}, pages = {532-533}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90037-A}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Holroyd89, author = {P. Holroyd}, title = {Information horizons : Miles, Rush, Turner and Bessant, Edward Elgar, 1988}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {614-615}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90023-X}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Holt04, author = {Charles C. Holt}, title = {Author's retrospective on 'Forecasting seasonals and trends by exponentially weighted moving averages'}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {11-13}, number = {1}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.09.017}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Holt04a, author = {Charles C. Holt}, title = {Forecasting seasonals and trends by exponentially weighted moving averages}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {5-10}, number = {1}, abstract = {The paper provides a systematic development of the forecasting expressions for exponential weighted moving averages. Methods for series with no trend, or additive or multiplicative trend are examined. Similarly, the methods cover non-seasonal, and seasonal series with additive or multiplicative error structures. The paper is a reprinted version of the 1957 report to the Office of Naval Research (ONR 52) and is being published here to provide greater accessibility.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.09.015}, issn = {0169-2070}, keywords = {Exponential smoothing, Forecasting, Local seasonals, Local trends, regart} } @ARTICLE{HD10, author = {Lennart Hoogerheide and Herman K. van Dijk}, title = {Bayesian forecasting of Value at Risk and Expected Shortfall using adaptive importance sampling}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {231 - 247}, number = {2}, note = {Special Issue: Bayesian Forecasting in Economics}, doi = {10.1016/j.ijforecast.2010.01.007}, issn = {0169-2070}, keywords = {Value at Risk, Expected Shortfall,Numerical standard error,Importance sampling,Mixture of Student-t distributions,Variance reduction technique} } @ARTICLE{HNR08, author = {Vincent J. Hooper and Kevin Ng and Jonathan J. Reeves}, title = {Quarterly beta forecasting: An evaluation}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {480-489}, number = {3}, abstract = {Ever since the inception of betas as a measure of systematic risk, the forecast error in relation to this parameter has been a major concern to both academics and practitioners in finance. In order to reduce forecast error, this paper compares a series of competing models to forecast beta. Realized measures of asset return covariance and variance are computed and applied to forecast beta, following the advances in methodology of Andersen, Bollerslev, Diebold and Wu [Andersen, T. G., Bollerslev, T., Diebold, F. X., & Wu, J. (2005). A framework for exploring the macroeconomic determinants of systematic risk. American Economic Review, 95, 398-404; and Andersen, T. G., Bollerslev, T., Diebold, F. X., & Wu, J. (2006). Realized beta: Persistence and Predictability. In T. Fomby & D. Terrell (Eds.), Advances in Econometrics, vol 20B: Econometric Analysis of Economic and Financial Times Series., JAI Press, 1-40.]. This approach is compared with the constant beta model (the industry standard) and a variant, the random walk model. It is shown that an autoregressive model with two lags produces the lowest or close to the lowest error for quarterly stock beta forecasts. In general, the AR(2) model has a mean absolute forecast error half that of the constant beta model. This reduction in forecast error is a dramatic improvement over the benchmark constant model.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.03.005}, issn = {0169-2070}, keywords = {Portfolio management, Realized beta, Systematic risk, regart} } @ARTICLE{Horowitz96, author = {Ira Horowitz}, title = {Decision making and forecasting: with emphasis on model building and policy analysis: Kneale T. Marshall and Robert Oliver, 1995, (McGraw-Hill Co., New York), 432 pp., \$69.78 ISBN 0-07-048027-3}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {433-435}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(96)00690-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Hotta93, author = {Luiz Koodi Hotta}, title = {The effect of additive outliers on the estimates from aggregated and disaggregated ARIMA models}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {85-93}, number = {1}, abstract = {Assume that the observed series follows an ARIMA process, and that the forecaster is only interested in predicting aggregated values. In this case the aggregate series also follows an ARIMA process and the prediction could be done using either the disaggregate or the aggregate models. We derive the approximate expected values of the estimates of the model coefficients and of the innovation variances in the presence of a single additive outlier. The approximations are also checked through simulations. Our conclusion is that the approximation is good, provided the size of the series is not too small, and that the additive outlier can have a stronger effect on the disaggregate model than on the aggregate model. An empirical analysis is presented using the international airline passengers series.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90056-S}, issn = {0169-2070}, keywords = {Estimating aggregated models, Additive outliers, Effect of additive outliers, Forecasting aggregated observation, regart} } @ARTICLE{HI97, author = {Nick B. Hounsell and Saeed Ishtiaq}, title = {Journey time forecasting for dynamic route guidance systems in incident conditions}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {33-42}, number = {1}, abstract = {New in-vehicle systems for route guidance require optimum routes in a network to be calculated based on current and forecast journey times. Following a brief review of forecasting methods developed for normal traffic conditions, this article describes a new method for the more difficult but particularly important situation of traffic incidents which occur in variety of forms in urban networks, e.g. an accident, a vehicle breakdown, illegal parking/ stopping and so on. In such conditions journey times may be increased not only on the incident link, but also on the links which are the upstream links of the incident location, this could lead to serious congestion, a rise in energy consumption and environmental nuisance. The prediction of the effects of traffic incidents is therefore an important issue for better efficiency and for on-line dynamic route guidance (DRG) systems and other traffic control systems. In this study an incident data base was compiled, based on modelling of several incident/ network/ traffic scenarios using a simulation tool. Generalised statistical models were then developed for predicting the spread of congestion effects following an incident and the required travel time modifications on the incident link and on affected links. The aim was to provide a reasonably robust process for on-line applications, to improve on current ad-hoc methods. The main application of the developed models is in incident management for dynamic route guidance systems particularly in low penetration level (i.e. where the proportion of guided drivers is relatively low).}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00698-X}, issn = {0169-2070}, keywords = {Traffic incidents, Journey time, Dynamic route guidance, Network modelling, Urban traffic control, regart} } @ARTICLE{Howell90, author = {Sydney D. Howell}, title = {Parameter instability in learning curve models : Invited comments on papers by Towill and by Sharp and Price}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {541-547}, number = {4}, abstract = {Towill, and Sharp and Price, have confirmed that the Time Constant/Wiltshire learning curve model is relevant to wider aspects of learning, and over longer time horizons, than it was designed for. However in many contexts the model shows paradoxical properties; it is non-robust in estimation, due to instability in its parameter estimates, but robustly good at forecasting, whether the parameters are unstable or not. Researchable causes and estimation remedies are suggested, but it is also pointed out that this model should not converge in all circumstances, and failure to converge can be informative.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90032-7}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Hoyo05, author = {J. del Hoyo}, title = {Comments on Fok, van Dijk and Franses's paper: Forecasting aggregates using panels of nonlinear time series}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {795-797}, number = {4}, note = {Nonlinearities, Business Cycles and Forecasting}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.04.006}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{HM86, author = {Wu-ron Hsu and Allan H. Murphy}, title = {The attributes diagram A geometrical framework for assessing the quality of probability forecasts}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {285-293}, number = {3}, abstract = {In two-event situations, a reliability diagram provides a geometrical framework for evaluating this attribute of probability forecasts. However, reliability is only one of several important attributes of such forecasts. This paper describes an extension of the reliability diagram - the attributes diagram - in which the accuracy, resolution, and skill, as well as the reliability, of probability forecasts can be depicted. Moreover, these geometrical representations are shown to be directly related to quantitative measures of the respective attributes. The interpretation and use of the attributes diagram is illustrated by considering samples of probabilistic quantitative precipitation forecasts. Some possible extensions of this diagram to multiple-event situations are briefly discussed.}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90048-8}, issn = {0169-2070}, keywords = {Evaluation of probability forecasts, Attributes of probability forecasts, Geometrical interpretations of attributes of probability forecasts, Attributes diagram, Evaluation measures for probability forecasts, Quadratic score, Probability forecasts, regart} } @ARTICLE{Hubbard04, author = {Raymond Hubbard}, title = {Reaping benefits from management research: Lessons from the forecasting principles project, J. Scott Armstrong and Ruth A. Pagell, 2003, Interfaces 33 (6) 89-111.}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {740-741}, number = {4}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.04.002}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Hubrich05, author = {Kirstin Hubrich}, title = {Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {119-136}, number = {1}, abstract = {Monitoring and forecasting price developments in the euro area is essential in light of the two-pillar framework of the ECB's monetary policy strategy. This study analyses whether the accuracy of forecasts of aggregate euro area inflation can be improved by aggregating forecasts of subindices of the Harmonized Index of Consumer Prices (HICP) as opposed to forecasting the aggregate HICP directly. The analysis includes univariate and multivariate linear time series models and distinguishes between different forecast horizons, HICP components and inflation measures. Various model selection procedures are employed to select models for the aggregate and the disaggregate components. The results indicate that aggregating forecasts by component does not necessarily help forecast year-on-year inflation 12 months ahead.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.04.005}, issn = {0169-2070}, keywords = {Euro area inflation, HICP subindex forecast aggregation, Linear time series models, regart} } @ARTICLE{Hughes88, author = {Kirsty Hughes}, title = {R\&D, patents and productivity : Zvi Griliches, ed. (National Bureau of Economic Research, University of Chicago Press, 1984) pp. 528, �47.25, \$53.00}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {303-303}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90094-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{HA94, author = {Ken Hung and Frank B. Alt}, title = {The approximation of the one-step ahead forecast error covariance for vector ARMA models}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {59-64}, number = {1}, abstract = {A vector case parallel to that described by Ledolter and Abraham (Technometrics, 23 (1981) 411-414) is extended for an approximation of one-step ahead forecast error covariance for vector ARMA models.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90050-7}, issn = {0169-2070}, keywords = {Vector ARMA models, Forecast error covariance, One-step ahead, regart} } @ARTICLE{Hurvich02, author = {Clifford M. Hurvich}, title = {Multistep forecasting of long memory series using fractional exponential models}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {167-179}, number = {2}, abstract = {We develop forecasting methodology for the fractional exponential (FEXP) model. First, we devise algorithms for fast exact computation of the coefficients in the infinite order autoregressive and moving average representations of a FEXP process. We also describe an algorithm to accurately approximate the autocovariances and to simulate realizations of the process. Next, we present a fast frequency-domain cross validation method for selecting the order of the model. This model selection method is designed to yield the model which provides the best multistep forecast for the given lead time, without assuming that the process actually obeys a FEXP model. Finally, we use the infinite order autoregressive coefficients of a fitted FEXP model to construct multistep forecasts of inflation in the United Kingdom. These forecasts are substantially different than those from a fitted ARFIMA model.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00151-0}, issn = {0169-2070}, keywords = {Fractional integration, Long-range dependence, Spectral factorization, regart} } @ARTICLE{Huss88, author = {William R. Huss}, title = {A move toward scenario analysis}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {377-388}, number = {3}, abstract = {Since the 1960s, tremendous emphasis has been placed on developing more sophisticated forecasting techniques which can process large quantities of historical data and produce extrapolations for predicting the future. These techniques, however, have failed in a number of respects including their ability to consider systematically quantitative variables, predict turning points, provide an internal communications tool, and serve as a link between forecasting planning and decision making. This paper discusses a relatively new approach to forecasting, called scenario analysis, and recommends further research to develop this technique. A scenario is a narrative description of a consistent set of factors which define in a probabilistic sense alternative sets of future business conditions. Scenario analysis addresses many of the weaknesses of traditional extrapolative forecasts mentioned above. Several techniques are discussed including intuitive logics (SRI International and Royal Dutch Shell), trend-impact analysis (the Future Group), and cross-impact analysis (INTERAX and BASICS).}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90105-7}, issn = {0169-2070}, keywords = {Scenarios, Energy, Judgemental forecasts, Strategic planning simulations, Trend-impact anaysis, Cross-impact analysis, Econometrics, regart} } @ARTICLE{Huss85, author = {William R. Huss}, title = {Comparative analysis of company forecasts and advanced time series techniques using annual electric utility energy sales data}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {217-239}, number = {3}, abstract = {This article describes the results of a study of load forecasting at 49 of the 75 largest electric utilities in the United States. Historical forecasts and actual energy sales data were obtained from each participating utility along with descriptions of the technique or techniques used in the forecast preparation. Comparisons are made between techniques for forecasts with two, four, six, and eleven year horizons and vintages of 1972, 1976, 1978, 1980, and 1982. In addition, one multivariate and four univariate time series techniques were tested using annual sales data supplied by the utilities. The techniques tested were Univariate Adaptive Estimation Procedure (UNIAEP), Linear Regression, Holt's Exponential Smoothing, a combination technique which weights each of the previous approaches by one third, and a multiple regression approach where total electricity sales are forecast from state real per capita income, state population, and national real electricity price. The results show that the utility forecasts, especially end-use models, perform extremely well for the two year horizons but deteriorate over the longer term. Of the time series techniques tested, the combination technique and the Univariate Adaptive Estimation Procedure perform best over all horizons. Holt's Exponential Smoothing performs reasonably well in the short term while linear extrapolation performs fairly well over longer horizons. The results of the multivariate technique are disappointing in the short term but show some improvement for the longer horizons.}, doi = {http://dx.doi.org/10.1016/0169-2070(85)90004-4}, issn = {0169-2070}, keywords = {Load forecasting, Electric utilities, Multivariate, Univariate, Linear regression, Holt, regart} } @ARTICLE{HCH+86, author = {G. Huyot and Kim Chiu and John Higginson and Nazira Gait}, title = {Analysis of Revisions in the Seasonal Adjustment of Data Using X-11-Arima Model-Based filters}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {217-229}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(86)80112-1}, issn = {0169-2070} } @ARTICLE{HA10, author = {Lars Magnus Hvattum and Halvard Arntzen}, title = {Using ELO ratings for match result prediction in association football}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {460 - 470}, number = {3}, note = {Sports Forecasting}, doi = {10.1016/j.ijforecast.2009.10.002}, issn = {0169-2070}, keywords = {Sports forecasting, Loss function,Evaluating forecasts,Rating,Ordered logit} } @ARTICLE{HP97, author = {S. Hylleberg and A. R. Pagan}, title = {Seasonal integration and the evolving seasonals model}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {329-340}, number = {3}, abstract = {The paper uses a model of seasonality popular in the 1960s, the evolving seasonals model, to explore issues relating to testing for unit roots in seasonal time series. The model is used to show how data can be transformed in such a way that tests for seasonal integration simply become those for regular unit roots. Once this connection is established it becomes obvious that there are many possible ways of constructing a test for seasonal integration, only a few of which have appeared in the literature. A byproduct of the approach is the separation of the existence of a seasonal pattern from its nature allowing one to place developments such as fractionally integrated and periodic seasonality within the same framework as regular integration.}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00021-6}, issn = {0169-2070}, keywords = {Seasonal integration, Harmonic regression, Evolving seasonals, Unobserved components, HEGY test, Canova, Hansen test, Periodic seasonality, Fractional integration, regart} } @ARTICLE{Hyndman10, author = {Rob J. Hyndman}, title = {Changing of the guard}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {1 - 1}, number = {1}, note = {Special Section: European Election Forecasting}, doi = {10.1016/j.ijforecast.2009.12.002}, issn = {0169-2070} } @ARTICLE{Hyndman10a, author = {Rob J. Hyndman}, title = {Encouraging replication and reproducible research}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {2 - 3}, number = {1}, note = {Special Section: European Election Forecasting}, doi = {10.1016/j.ijforecast.2009.12.003}, issn = {0169-2070} } @ARTICLE{07, author = {Rob J Hyndman}, title = {Note from the editor}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {727-727}, number = {4}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.09.002}, issn = {0169-2070}, key = {tagkey2007727}, keywords = {pubnote} } @ARTICLE{Hyndman05, author = {Rob J. Hyndman}, title = {Editorial}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {1-1}, number = {1}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.11.004}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Hyndman04, author = {Rob J. Hyndman}, title = {The interaction between trend and seasonality}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {561-563}, number = {4}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.03.005}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{HB03, author = {Rob J. Hyndman and Baki Billah}, title = {Unmasking the Theta method}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {287-290}, number = {2}, abstract = {The `Theta method' of forecasting performed particularly well in the M3-competition and is therefore of interest to forecast practitioners. The original description of the method given by Assimakopoulos and Nikolopoulos [International Journal of Forecasting 16 (2000) 521] involves several pages of algebraic manipulation. We show that the method can be expressed much more simply and that the forecasts obtained are equivalent to simple exponential smoothing with drift.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00143-1}, issn = {0169-2070}, keywords = {Exponential smoothing, Forecasting competitions, State space models, regart} } @ARTICLE{HB08, author = {Rob J. Hyndman and Heather Booth}, title = {Stochastic population forecasts using functional data models for mortality, fertility and migration}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {323-342}, number = {3}, abstract = {Age-sex-specific population forecasts are derived through stochastic population renewal using forecasts of mortality, fertility and net migration. Functional data models with time series coefficients are used to model age-specific mortality and fertility rates. As detailed migration data are lacking, net migration by age and sex is estimated as the difference between historic annual population data and successive populations one year ahead derived from a projection using fertility and mortality data. This estimate, which includes error, is also modeled using a functional data model. The three models involve different strengths of the general Box-Cox transformation chosen to minimise out-of-sample forecast error. Uncertainty is estimated from the model, with an adjustment to ensure that the one-step-forecast variances are equal to those obtained with historical data. The three models are then used in a Monte Carlo simulation of future fertility, mortality and net migration, which are combined using the cohort-component method to obtain age-specific forecasts of the population by sex. The distribution of the forecasts provides probabilistic prediction intervals. The method is demonstrated by making 20-year forecasts using Australian data for the period 1921-2004. The advantages of our method are: (1) it is a coherent stochastic model of the three demographic components; (2) it is estimated entirely from historical data with no subjective inputs required; and (3) it provides probabilistic prediction intervals for any demographic variable that is derived from population numbers and vital events, including life expectancies, total fertility rates and dependency ratios.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.02.009}, issn = {0169-2070}, keywords = {Fertility forecasting, Functional data, Mortality forecasting, Net migration, Nonparametric smoothing, Population forecasting, Principal components, Simulation, regart} } @ARTICLE{HK06, author = {Rob J. Hyndman and Anne B. Koehler}, title = {Another look at measures of forecast accuracy}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {679-688}, number = {4}, abstract = {We discuss and compare measures of accuracy of univariate time series forecasts. The methods used in the M-competition as well as the M3-competition, and many of the measures recommended by previous authors on this topic, are found to be degenerate in commonly occurring situations. Instead, we propose that the mean absolute scaled error become the standard measure for comparing forecast accuracy across multiple time series.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.03.001}, issn = {0169-2070}, keywords = {Forecast accuracy, Forecast evaluation, Forecast error measures, M-competition, Mean absolute scaled error, regart} } @ARTICLE{HKS+02, author = {Rob J. Hyndman and Anne B. Koehler and Ralph D. Snyder and Simone Grose}, title = {A state space framework for automatic forecasting using exponential smoothing methods}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {439-454}, number = {3}, abstract = {We provide a new approach to automatic forecasting based on an extended range of exponential smoothing methods. Each method in our taxonomy of exponential smoothing methods provides forecasts that are equivalent to forecasts from a state space model. This equivalence allows: (1) easy calculation of the likelihood, the AIC and other model selection criteria; (2) computation of prediction intervals for each method; and (3) random simulation from the underlying state space model. We demonstrate the methods by applying them to the data from the M-competition and the M3-competition. The method provides forecast accuracy comparable to the best methods in the competitions; it is particularly good for short forecast horizons with seasonal data.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00110-8}, issn = {0169-2070}, keywords = {Automatic forecasting, Exponential smoothing, Prediction intervals, State space models, regart} } @ARTICLE{HO06, author = {Rob J. Hyndman and J. Keith Ord}, title = {Twenty-five years of forecasting}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {413-414}, number = {3}, note = {Twenty five years of forecasting}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.06.001}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Ilmakunnas96, author = {Pekka Ilmakunnas}, title = {Use of macroeconomic forecasts in corporate forecasting: a note on aggregation problems}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {383-388}, number = {3}, abstract = {The use of corporate sales forecasting models is simplified, if the forecasting models have such explanatory variables for which published macroeconomic forecasts are easily available. However, if the macroeconomic forecast is not accurate enough it may not be useful for forecasting the corporate level sales. In addition, aggregation problems arise in the use of this kind of model. There is, first, the traditional aggregation error when product subgroup forecasting models are aggregated to a total sales forecasting model. Secondly, when the product group composition of sales differs from the composition of consumer expenditure, there is a composition bias. This remains even when perfect aggregation is possible. Similar problems arise e.g. in regional and industry forecasting. These effects should be judgmentally taken into account when using such models.}, doi = {http://dx.doi.org/10.1016/0169-2070(96)00672-3}, issn = {0169-2070}, keywords = {Adjusting forecasts, Company forecasting, Forecast-aggregation, regart} } @ARTICLE{Ingene87, author = {Charles A. Ingene}, title = {Store location and store assessment research : R.L. Davies and D.S. Rogers, (John Wiley, New York, 1981) pp. 375.}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {529-530}, number = {3-4}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90050-1}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Ioannides95, author = {Chris Ioannides}, title = {Population growth, income distribution and economic development (Theory, methodology, and empirical results) : Nico Heerink, 1994, (Springer, Berlin, Heidelberg), 401 pp., DM 168, ISBN 3-540-57323-2 (Springer, Berlin, Heidelberg), 401 pp., DM 168, ISBN 3-540-57323-2}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {333-334}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(95)90061-6}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{99, author = {Christos Ioannidis}, title = {Book Review}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {121-122}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00070-3}, issn = {0169-2070}, key = {tagkey1999121}, keywords = {bookrev} } @ARTICLE{Ioannidis97, author = {C. Ioannidis}, title = {The econometrics of panel data. A handbook of the theory with applications, second revised edition : by Laszlo Matyas and Patrick Sevestre (Editors), 1996, (Kluwer Academic Publishers, Dordrecht), Dfl275.00; US\$150.00; �106.00; ISBN 0792337875}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {588-589}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00003-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Ioannidis09, author = {John P.A. Ioannidis}, title = {Limits to forecasting in personalized medicine: An overview}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {773 - 783}, number = {4}, note = {Special section: Decision making and planning under low levels of predictability}, doi = {10.1016/j.ijforecast.2009.05.003}, issn = {0169-2070}, keywords = {Prediction, Prognosis,Personalized medicine,Individualized medicine,Bias,Reporting} } @ARTICLE{IL07, author = {Gultekin Isiklar and Kajal Lahiri}, title = {How far ahead can we forecast? Evidence from cross-country surveys}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {167-187}, number = {2}, abstract = {Using monthly GDP forecasts from Consensus Economics, Inc. for 18 developed countries, reported over 24 different forecast horizons during the period 1989-2004, we find that the survey forecasts do not have much value when the horizon goes beyond 18 months. Using two alternative approaches to measure the flow of new information in fixed-target survey forecasts, we find that the biggest improvement in forecasting performance comes when the forecast horizon is around 14 months. The dynamics of information accumulation over forecast horizons can provide both the forecasters and their clients with an important clue in their selection of the timing and frequency in the use of forecasting services. The limits to forecasting that these private market forecasters exhibit are indicative of the current state of macroeconomic foresight.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.01.003}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{IFM02, author = {Towhidul Islam and Denzil G. Fiebig and Nigel Meade}, title = {Modelling multinational telecommunications demand with limited data}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {605-624}, number = {4}, abstract = {Forecasting the diffusion of innovations in the telecommunications sector is a constantly recurring problem for national providers. The problem is characterised by short data series making the estimation of model parameters unreliable. However, the same innovation will be diffusing simultaneously in other national markets, although with a different start date. The use of this cross-sectional data in constructing innovation diffusion models is investigated here. Four models for pooling the cross-sectional data are described and two diffusion models are discussed although only one, the Gompertz model is used throughout. Three innovation data sets are used in the evaluation of the models: digital cellular telephones, ISDN connections and fax connections. The pooled diffusion forecasts proved to be more accurate in several comparisons relative to a naïve benchmark and to individual forecasts when available.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00073-0}, issn = {0169-2070}, keywords = {Diffusion, Cross-sectional data, Telecommunications, Gompertz, Bass, regart} } @ARTICLE{ILS00, author = {Detelina Ivanova and Kajal Lahiri and Franz Seitz}, title = {Interest rate spreads as predictors of German inflation and business cycles}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {39-58}, number = {1}, abstract = {We have studied the comparative performance of a number of interest rate spreads as predictors of the German inflation and business cycle in the post-Bretton Woods era. The two-regime Markov-switch model that we used as a nonlinear filter allows the dynamic behavior of the economy to vary between expansions and recessions in terms of duration and volatility. We found that the bank term structure, the public term structure, and the spread based on the call rate predicted all recessions with a comfortable lead, although they lagged some of the recoveries by a few months. The bank-public spread generates a series of false signals, and missed completely the upturn in the mid-1970s, but detected the last two recoveries with an average lead of nearly 12 months. The source of the predictive power of interest rate spreads lies in the information they contain not only about monetary policy, but also about an assortment of general macroeconomic shocks. The filter probabilities from three of the interest rate differentials also foreshadowed the long swings in the German inflation rate remarkably well, with a lead time of 2-4 years without any false signals.}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00029-1}, issn = {0169-2070}, keywords = {Turning-point forecasts, Markov-switch model, Bundesbank policy, Term structure, Germany, regart} } @ARTICLE{JC05, author = {Shabbar Jaffry and Nick Capon}, title = {Alternative methods of forecasting risks in Naval manpower planning}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {73-85}, number = {1}, abstract = {This paper compares qualitative and quantitative methods to incorporate risk in manpower planning, using the case study of UK Naval Services. The methods provide complementary insights in forecasting risk, and thus, offer an improvement over the use of a single method. Qualitative methods alone overstate impacts that lead to inaccurate ranking of risks, resulting in a management response of compliance rather than action. The qualitative analyses support the quantitative analyses in identifying the range of potential explanatory variables and suggest appropriate management interventions. The quantitative method of risk forecasting using an Error Correction framework identifies more accurately the range of possible outcomes for which management must prepare. The quantitative approach also helps to identify significant explanatory factors in risk management. Its use may be limited due to non-availability of historical data, and could place too much emphasis on a limited set of explanatory factors. A staged approach of mixed methods is recommended. A higher weight should be given to past observations than to experts' subjective opinions. Periodic repeated validations by qualitative methods should help effective working of quantitative methods.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.05.003}, issn = {0169-2070}, keywords = {Forecasting, Forecast comparison, Manpower forecasts, Risk, Error correction mechanism, Qualitative judgement, regart} } @ARTICLE{JE85, author = {Tom Janz and Lois Etherington}, title = {Using forecasted net benefits in designing improved recruitment and selection systems}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {287-296}, number = {3}, abstract = {This paper extends the post hoc application of utility formulae to designing improved recruitment and selection systems. It emphasizes interactive tradeoffs from spending to (I) increase the size of the applicant pool, and (2) increase the accuracy of applicant selection. First, the paper reviews the utility formula. Then it applies the formula towards improving the design of recruitment strategies. Next, the paper examines the dollar costs and benefits of different selection strategies. Finally, it examines the dual impact of recruitment and selection taken together. In short, while recruitment has been both under and overfunded in specific environments, selection has been uniformly underfunded, resulting in substantial opportunity costs to organizations.}, doi = {http://dx.doi.org/10.1016/0169-2070(85)90008-1}, issn = {0169-2070}, keywords = {Use-Personnel selection, Forecasting-Value ofregart} } @ARTICLE{Jarrett91, author = {Jeffrey Jarrett}, title = {Time series: A biostatistical introduction : Peter Diggle, (Oxford University Press, Oxford, England and Cary, NC, 1990) pp. 257 including index, \$75.00}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {390-391}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90016-O}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{JCS05, author = {Miguel Jerez and Jos{\'e} Casals and Sonia Sotoca}, title = {Growth, cycles, and convergence in US regional time series: A personal point of view}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {687-689}, number = {4}, note = {Nonlinearities, Business Cycles and Forecasting}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.04.009}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{JJ10, author = {Bruno Jer�me and V�ronique Jer�me-Speziari}, title = {Forecasting partisan dynamics in Europe}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {98 - 115}, number = {1}, note = {Special Section: European Election Forecasting}, doi = {10.1016/j.ijforecast.2009.03.001}, issn = {0169-2070}, keywords = {Economic voting, Elections,Europe,Forecasting,Political business cycle,Partisan cycle} } @ARTICLE{Jex91, author = {Colin Jex}, title = {Business forecasting in a Lotus 1-2-3 environment : Colin Lewis, (Wiley, Chichester, UK, 1989), pp. 98 (software included), �19.95.}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {108-108}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90038-W}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Jex94, author = {Colin F. Jex}, title = {Recursive estimation as an aid to exploratory data analysis: an application to market share models}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {445-453}, number = {3}, abstract = {Recursive estimation methods are often adopted in order to allow for parameter changes in a model. They can also be used to explore data in the time domain before embarking upon traditional estimation methods. A case study using the data from Brodie and de Kluyver (Journal of Marketing Research, 1984, 21, 194-201), whilst only marginally improving upon forecast accuracy, sheds some light on the problem of why explanatory models have difficulty in outperforming `naive' models on some data sets. In contrast to the common assumption that model parameters are constant in time, we show that there is considerable evidence for time-dependent behaviour in the Brodie and de Kluyver data. This is particularly critical for evaluation of forecasting performance, since it occurs predominantly during the holdout period of that study.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90073-6}, issn = {0169-2070}, keywords = {Market share models, Recursive estimation, Kalman filter, Discount weighted regression, regart} } @ARTICLE{JKS10, author = {Markus Jochmann and Gary Koop and Rodney W. Strachan}, title = {Bayesian forecasting using stochastic search variable selection in a VAR subject to breaks}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {326 - 347}, number = {2}, note = {Special Issue: Bayesian Forecasting in Economics}, doi = {10.1016/j.ijforecast.2009.11.002}, issn = {0169-2070}, keywords = {Vector autoregressive model, Predictive density,Over-parameterization,Structural break,Shrinkage} } @ARTICLE{Johnes98, author = {Geraint Johnes}, title = {Book Review}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {536-536}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00056-9}, issn = {0169-2070}, key = {tagkey1998536}, keywords = {bookrev} } @ARTICLE{JB96, author = {F. R. Johnston and J. E. Boylan}, title = {Forecasting intermittent demand: A comparative evaluation of croston's method. Comment}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {297-298}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00642-7}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Jones89, author = {Randall J. Jones}, title = {The politics of energy forecasting: A comparative study of energy forecasting in western Europe and north America : (Oxford University Press, New York, 1987) \$67.00, �32.50, pp.314}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {133-135}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90071-X}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Jones2008, author = {Jones, Randall J, Jr.}, title = {The state of presidential election forecasting: The 2004 experience}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {310-321}, number = {2}, abstract = {This paper assesses the current state of U. S. presidential election forecasting, describing forecast methods and their predictive accuracies for the most recent election, 2004. Three types of forecasts were made for the election using the methods noted: 1) point forecasts of the popular vote (by campaign polls, futures contracts on candidates' performance, regression models, Delphi expert surveys, and a combination of forecasts from these methods); 2) point forecasts of the electoral vote (by regression models, probability models based on state polls, a compilation of median polls in states, and exit polls); and 3) dichotomous forecasts of the popular-vote winner (by a multi-indicator index, cut-points for single indicators, and bellwether states). Candidate futures provided the most accurate popular-vote forecasts. A state probability model and the median state poll technique were the most accurate electoral vote methods. All three dichotomous techniques successfully predicted the election winner.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.03.002}, issn = {0169-2070}, keywords = {Bellwethers, Combining forecasts, Cut-points, Delphi, Election forecasting, Evaluating forecasts, Indexes, Polls, Prediction markets, Probability forecasting, Regression, regart} } @ARTICLE{Jonsson94, author = {Bo Jonsson}, title = {Prediction with a linear regression model and errors in a regressor}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {549-555}, number = {4}, abstract = {The subject under study is prediction with a simple linear regression model in the presence of errors in variables. The paper focuses on the case of a non-stochastic true regressor (x). For a wide range of true x-values around the mean of x in the estimation period, predictions based on OLS on the observed variables is to be preferred in terms of MSE to a predictor based on consistent estimation of the parameters. This can be so also when x follows a trend and predictions are made for the next observation. When the error variance of the regressor in the prediction period differs from the mean error variance in the estimation period sample, a predictor based on a modified OLS estimator, adjusted for that difference, behaves like the OLS predictor in the case of equal error variances.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90023-X}, issn = {0169-2070}, keywords = {Errors in variables, Regression models, Prediction, regart} } @ARTICLE{JW08, author = {Victor Richmond R. Jose and Robert L. Winkler}, title = {Simple robust averages of forecasts: Some empirical results}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {163-169}, number = {1}, abstract = {An extensive body of literature has shown that combining forecasts can improve forecast accuracy, and that a simple average of the forecasts (the mean) often does better than more complex combining schemes. The fact that the mean is sensitive to extreme values suggests that deleting such values or reducing their extremity might be worthwhile. We study the performance of two simple robust methods, trimmed and Winsorized means, which are easy to use and understand. For the data sets we consider, they provide forecasts which are slightly more accurate than the mean, and reduce the risk of high errors. Our results suggest that moderate trimming of 10-30% or Winsorizing of 15-45% of the forecasts can provide improved combined forecasts, with more trimming or Winsorizing being indicated when there is more variability among the individual forecasts. There are some differences in the performance of the trimmed and Winsorized means, but overall such differences are not large.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.06.001}, issn = {0169-2070}, keywords = {Combining forecast, Robustness, Trimming, Winsorizing, M3 Competition, regart} } @ARTICLE{Joseph03, author = {Nathan Lael Joseph}, title = {Predicting returns in U.S. financial sector indices}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {351-367}, number = {3}, abstract = {This study focuses on: (i) the responsiveness of the U.S. financial sector stock indices to foreign exchange (FX) and interest rate changes; and, (ii) the extent to which good model specification can enhance the forecasts from the associated models. Three models are considered. Only the error-correction model (ECM) generated efficient and consistent coefficient estimates. Furthermore, a simple zero lag model in differences which is clearly mis-specified, generated forecasts that are better than those of the ECM, even if the ECM depicts relationships that are more consistent with economic theory. In brief, FX and interest rate changes do not impact on the return-generating process of the stock indices in any substantial way. Most of the variation in the sector stock indices is associated with past variation in the indices themselves and variation in the market-wide stock index. These results have important implications for financial and economic policies.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00012-2}, issn = {0169-2070}, keywords = {Interest rates, Foreign exchange rates, Cointegration, Error-correction model, Forecast accuracy, regart} } @ARTICLE{JO88, author = {Heather Joshi and Elizabeth Overton}, title = {Forecasting the female labour force in Britain}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {269-285}, number = {2}, abstract = {Official labour force projections for Britain until 1991 are now based on a regression model which is described in this paper. The model was derived from an econometric study of employment by single years of age during the period 1950-1974. Our labour force projections take the past and projected child-bearing of British women together with cohort-specific constant terms to synthesize, for any age group specified between 20 and 59, the proportion of women who would he in paid employment at a given level of demand. The results predict a slackening of the growth in aggregate labour force participation during the 1980s as the underlying rates approach their limit. When not responsible for children, women in the most recent cohorts display participation rates similar to those recorded for men.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90082-9}, issn = {0169-2070}, keywords = {Labour force, Women, Projections, Cohort, Fertility, regart} } @ARTICLE{Joutz96, author = {Fred Joutz}, title = {Testing of macroeconometric models : Ray C. Fair, 1994, (Harvard University Press, Cambridge, MA), 421 pp., ISBN 0-674-87503-6}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {559-561}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00694-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{JS00, author = {Fred Joutz and H. O. Stekler}, title = {An evaluation of the predictions of the Federal Reserve}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {17-38}, number = {1}, abstract = {To successfully implement monetary policy, the Federal Reserve System (FED) must make forecasts about the future state of the economy. This paper examines some of the characteristics of these forecasts. The analysis presents the usual error measures and tests for rationality. The paper compares these predictions with those generated by ARIMA models and the ASA/NBER surveys. In addition, we analyze (1) the relationship between accuracy and the length of the forecast horizon, (2) whether accuracy has improved over time, and (3) the accuracy of the forecasts in the vicinity of turning points. We conclude that the FED predictions tended to yield the same type of errors that private forecasters have displayed: in some periods either real GNP or inflation had systematic errors; turning point errors occurred prior to recessions; the forecasts were unbiased, but showed evidence of inefficiency. However, the FED forecasts were not significantly different from the predictions of the ARIMA models or ASA/NBER surveys.}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00046-1}, issn = {0169-2070}, keywords = {Forecasting, Macroeconomic forecasting, Evaluation procedures, Federal Reserve, regart} } @ARTICLE{JT92, author = {Frederick Joutz and Robert Trost}, title = {Using stochastic simulation to test the effect of seasonal adjustment on forecast standard errors of motor gasoline demand}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {219-231}, number = {2}, abstract = {Most government agencies and private forecasting firms using large econometric models construct ad hoc confidence intervals with a base case forecast followed by a high and low case forecast. These do not provide a true measure of confidence in the predictions; rather, they represent different states of the world. Forecast standard errors represent a way of incorporating uncertainty into forecasts. In the complicated models the theoretical forecast standard errors are not easily computed. In our paper we estimate forecast standard errors using stochastic simulation and are able to inflate the standard errors if model misspecification is suspected. We compare the results using different seasonal adjustment filtering techniques on econometric models and time series models.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90120-X}, issn = {0169-2070}, keywords = {Forecast confidence intervals stochastic simulation, Seasonal adjustment techniques, regart} } @ARTICLE{Joutz10, author = {Frederick L. Joutz}, title = {Interview with Herman O. Stekler}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {195 - 203}, number = {1}, note = {Special Section: European Election Forecasting}, doi = {10.1016/j.ijforecast.2009.12.001}, issn = {0169-2070} } @ARTICLE{Joutz03, author = {Frederick L. Joutz}, title = {20/20 Foresight Crafting Strategy in an Uncertain World,: by Hugh Courtney, Harvard Business School Press, Boston, Massachusetts, 2001. ISBN 1-57851-266-2.}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {539-541}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00033-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Joutz98, author = {Frederick L. Joutz}, title = {Book Review}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {535-536}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00048-X}, issn = {0169-2070}, key = {tagkey1998535}, keywords = {bookrev} } @ARTICLE{JKP+02, author = {Duk B. Jun and Seon K. Kim and Yoon S. Park and Myoung H. Park and Amy R. Wilson}, title = {Forecasting telecommunication service subscribers in substitutive and competitive environments}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {561-581}, number = {4}, abstract = {The telecommunications market is expanding rapidly and becoming more substitutive and competitive. In this environment, demand forecasting is very difficult, yet important for both practitioners and researchers. In this paper, we adopt the modeling approach proposed by Jun and Park [Technological Forecasting and Social Change 61 (1999)]. The basic premise is that demand patterns result from choice behavior, where customers choose a product to maximize their utility. We apply a choice-based substitutive diffusion model to the Korean mobile telecommunication service market where digital service has completely replaced analog service. A choice-based competitive diffusion model is also formulated and applied to the case where two digital services compete. In comparison with Bass-type models, these two models provide superior fitting and forecasting performance. Finally, we suggest a new choice-based diffusion model to describe an environment in which substitution and competition occur simultaneously and show the application results. The choice-based model is useful in that it enables the description of such complicated environments and provides the flexibility to include marketing mix variables such as price and advertising in the regression analysis.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00067-5}, issn = {0169-2070}, keywords = {Marketing--new products, price, advertising, Comparative methods--choice-based multigeneration diffusion model, diffusion models, regart} } @ARTICLE{JT06, author = {Robert C. Jung and A.R. Tremayne}, title = {Coherent forecasting in integer time series models}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {223-238}, number = {2}, abstract = {Our principal focus is on forecasting methods suitable for a certain class of observation-driven time series models for counts. Integer-valued autoregressive (INAR) models may be attractive when the data exhibit a significant serial dependence structure. Having briefly reviewed the familiar first order Markov model, we give an account of the extension of the method of moments estimation procedures to higher order INAR models, concentrating on the second order case. We provide means of obtaining estimated standard errors which are not easily found by analytical methods. Throughout the paper the methods are illustrated using a well known test data set. These models seem particularly useful in the context of forecasting, especially if the integer nature of the data is to be acknowledged in the modelling exercise. A computer intensive method for generating coherent, integer out-of-sample predictions is proposed and used in the context of the data. Distributions are generated for multi-step and also for sequences of one-step rolling/recursive forecasts. Block-of-blocks bootstrap techniques are used for estimating asymptotic standard errors and the results of the exercise are central in allowing for parameter uncertainty in the forecast distributions.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.07.001}, issn = {0169-2070}, keywords = {Time series of counts, INAR-models, Integer prediction, Monte Carlo, Block-of-blocks bootstrap, Forecast distribution, Parameter uncertainty, regart} } @ARTICLE{Junttila01, author = {Juha Junttila}, title = {Structural breaks, ARIMA model and Finnish inflation forecasts}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {203-230}, number = {2}, abstract = {Via the use of the rolling regression technique and a specific procedure for analysing strong structural breaks in a univariate time series model, we forecast the rate of future inflation in Finland for the time period of unregulated financial markets since the beginning of 1987. The identified structural changes in the data generating process (DGP) of inflation are labelled with both economic events and changes in the main leading inflation indicators. The final intervention model yields, in some cases, better forecasts than the pure rolling regression technique without identification of the strong breaks. When comparing the obtained forecasts with certain noncontinuous time series based on inflation expectation surveys with respect to actual future inflation, we find that the comparable point forecasts from our rolling regressions perform better than the corresponding point expectation proxies from questionnaires. When compared with the performance of the forecasts by the Research Institute of the Finnish Economy, the recursive procedure also produces more accurate forecasts.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00080-7}, issn = {0169-2070}, keywords = {AR(I)MA models, Structural breaks, Time variation, Forecasting, regart} } @ARTICLE{JR08, author = {Ren{\'e} Jursa and Kurt Rohrig}, title = {Short-term wind power forecasting using evolutionary algorithms for the automated specification of artificial intelligence models}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {694-709}, number = {4}, abstract = {Wind energy is having an increasing influence on the energy supply in many countries, but in contrast to conventional power plants, it is a fluctuating energy source. For its integration into the electricity supply structure, it is necessary to predict the wind power hours or days ahead. There are models based on physical, statistical and artificial intelligence approaches for the prediction of wind power. This paper introduces a new short-term prediction method based on the application of evolutionary optimization algorithms for the automated specification of two well-known time series prediction models, i.e., neural networks and the nearest neighbour search. Two optimization algorithms are applied and compared, namely particle swarm optimization and differential evolution. To predict the power output of a certain wind farm, this method uses predicted weather data and historic power data of that wind farm, as well as historic power data of other wind farms far from the location of the wind farm considered. Using these optimization algorithms, we get a reduction of the prediction error compared to the model based on neural networks with standard manually selected variables. An additional reduction in error can be obtained by using the mean model output of the neural network model and of the nearest neighbour search based prediction approach.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.08.007}, issn = {0169-2070}, keywords = {Variable selection, Multivariate time series, Neural networks, Nearest neighbour search, Evolutionary optimization, Comparative studies, Wind energy, regart} } @ARTICLE{Juselius85, author = {Katarina Jus{\'e}lius}, title = {Modelling short- and long-term effects in the aggregate demand for soft drinks}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {253-272}, number = {3}, abstract = {A dynamic regression model for non-durable commodity demand is specified based on the additive unobserved components seasonal model with causal variables. The seasonal component which includes retailer stock effects is modelled as a seasonal ARMA process with fixed temperature effects. The non-seasonal component incorporates both short-run consumer responses and long-run adaptation to steady-state growth paths. Aggregation effects on per capita demand caused by the increase of new consumers as real income grows are investigated and the resulting growth trends accounted for. It is shown that neglecting these trends in the long-run adaptation process is likely to produce biased predictions and misleading estimates of crucial response parameters.}, doi = {http://dx.doi.org/10.1016/0169-2070(85)90006-8}, issn = {0169-2070}, keywords = {Application-sector, Consumer nondurables, Food, Dynamic regression, Model selection, Effect of income distribution seasonality, estimation, Unobserved components, Long-run adaptation, Growth trends, Comparative methods, Models, Simple, complex, regart} } @ARTICLE{JJL99, author = {Bruno J{\'e}{\'e}rôme and V{\'e}ronique J{\'e}rôme and Michael S. Lewis-Beck}, title = {Polls fail in France: forecasts of the 1997 legislative election}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {163-174}, number = {2}, abstract = {In France, political observers and politicians pay considerable attention to public opinion polls, using them as indicators of who will win the upcoming election. Before the 1997 French legislative contest, the polls consistently forecast a win for the ruling Right party coalition. To almost everyone's surprise, they were wrong. We document the extent of their error, then speculate on why it occurred. Finally, we propose a political economy model as an alternative, and more accurate, means of forecasting French legislative elections.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00065-X}, issn = {0169-2070}, keywords = {Opinion polls, Political economy, Election forecasting, French elections, regart} } @ARTICLE{Joergensen07, author = {Magne J{\o}rgensen}, title = {Forecasting of software development work effort: Evidence on expert judgement and formal models}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {449-462}, number = {3}, abstract = {The review presented in this paper examines the evidence on the use of expert judgement, formal models, and a combination of these two approaches when estimating (forecasting) software development work effort. Sixteen relevant studies were identified and reviewed. The review found that the average accuracy of expert judgement-based effort estimates was higher than the average accuracy of the models in ten of the sixteen studies. Two indicators of higher accuracy of judgement-based effort estimates were estimation models not calibrated to the organization using the model, and important contextual information possessed by the experts not included in the formal estimation models. Four of the reviewed studies evaluated effort estimates based on a combination of expert judgement and models. The mean estimation accuracy of the combination-based methods was similar to the best of that of the other estimation methods.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.05.008}, issn = {0169-2070}, keywords = {Judgemental forecasting, Combining forecasts, Comparative studies, Evaluating forecasts, Forecasting practice, regart} } @ARTICLE{Joergensen07a, author = {Magne J{\o}rgensen}, title = {How should we compare forecasting models with expert judgement?}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {473-474}, number = {3}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.05.013}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Kaboudan96, author = {M. A. Kaboudan}, title = {Chaos and forecasting : Howell Tong (Editor), 1995, (World Scientific, Singapore), 345 pp., �38, ISBN 981-02-2126-6.}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {304-306}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(96)00666-8}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{KM05, author = {Regina Kaiser and Agust{\'i}n Maravall}, title = {Combining filter design with model-based filtering (with an application to business-cycle estimation)}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {691-710}, number = {4}, abstract = {Filters used to estimate unobserved components in time series are often designed on a priori grounds, so as to capture the frequencies associated with the component. A limitation of these filters is that they may yield spurious results. The danger can be avoided if the so-called ARIMA-model-based (AMB) procedure is used to derive the filter. However, parsimony of ARIMA models typically implies little resolution in terms of the detection of hidden components. It would be desirable to combine a higher resolution with consistency of the structure of the observed series. We show first that for a large class of a priori designed filters, an AMB interpretation is always possible. Using this result, proper convolution of AMB filters can produce richer decompositions of the series that incorporate a priori desired features of the components and fully respect the ARIMA model for the observed series (hence no additional parameter needs to be estimated). The procedure is discussed in detail in the context of business-cycle estimation by means of the Hodrick-Prescott filter applied to a seasonally adjusted series or a trend-cycle component.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.04.016}, issn = {0169-2070}, keywords = {Time series, Filtering and smoothing, ARIMA models, Trend and cycle estimation, Hodrick-Prescott filterregart} } @ARTICLE{Kalton85, author = {Graham Kalton}, title = {Part 1Graham Kalton and Howard Schuman, The effect of the question on survey responses: A review, Journal of the Royal Statistical Society:A 145 (1982), pp. 42-73.}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {312-312}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(85)80056-X}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{KMB06, author = {Wagner A. Kamakura and Jos{\'e} Afonso Mazzon and Arnaud De Bruyn}, title = {Modeling voter choice to predict the final outcome of two-stage elections}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {689-706}, number = {4}, abstract = {Most election forecasting research to date has been conducted in the context of single-round elections. However, more than 40 countries in the world employ a two-stage process, where actual voting data are available between the first and the second rounds to help politicians understand their position in relation to each other and to voter preferences and to help them predict the final outcome of the election. In this study we take advantage of the theoretical foundation on voter behavior from the political science literature and the recent methodological advances in choice modeling to develop a Nested Logit Factor Model of voter choice which we use to predict the final outcome of two stage elections and gain insights about the underlying political landscape. We apply the proposed model to data from the first stage and predict the final outcome of two stage elections based on the inferences made from the first stage results. We demonstrate how our proposed model can help politicians understand their competitive position immediately after the first round of actual voting and test its predictive accuracy in the run-off election across 11 different state governorship elections.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.04.002}, issn = {0169-2070}, keywords = {Voter choice, Election forecasting, Political marketing, Nested Logit model, regart} } @ARTICLE{KK98, author = {Mark Kamstra and Peter Kennedy}, title = {Combining qualitative forecasts using logit}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {83-93}, number = {1}, abstract = {This paper introduces a computationally-convenient means of combining qualitative forecasts, through use of logit regression applied to training set data, applicable in dichotomous, polychotomous and ordered polychotomous contexts. It can be employed in the cases of combining probability forecasts, combining qualitative forecasts which have no associated probability forecasts, and combining both of these types of forecasts, a case for which no combining method currently exists. This methodology offers insights into the suitability of equal-weight averaging of probability forecasts, yields an existing method as a special case, and facilitates associated hypothesis testing.}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00056-3}, issn = {0169-2070}, keywords = {Probability forecasting, Event forecasting, Logit model, Ordinal data, regart} } @ARTICLE{Kanetkar00, author = {Vinay Kanetkar}, title = {Bayesian Inference in Dynamic Econometric Models: Luc Bauwens, Michel Lubrano and Jean-Francois Richard, Oxford University Press, Oxford, 1999, Hardback ISBN 0-19-877312-9, �45.00, Paperback ISBN 0-19-877313-7, �19.95.}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {427-429}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00054-6}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Kang90, author = {Heejoon Kang}, title = {A composite model for deterministic and stochastic trends}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {175-186}, number = {2}, abstract = {Nonstationary time series are typically either detrended or differenced to achieve stationarity in forecasting analyses. Detrending assumes the presence of a deterministic trend and differencing assumes the presence of a stochastic trend. A composite model, which is needed when a time series contains both trends, is a special case of a transfer function analysis. A transfer function with linear or quadratic trend variables as inputs can be used to forecast nonstationary time series with trends. Forecasts of 14 macroeconomic series for the United States show that these series are better represented and forecastable by these transfer function models than by a univariate ARIMA analysis. Comparisons between forecasts from a univariate analysis through detrending or differencing and those from a transfer function analysis for artificially generated data in a series of Monte Carlo experiments show that either detrending or differencing alone does not effectively account for the presence of trend as well as the transfer function model does.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90003-T}, issn = {0169-2070}, keywords = {Univariate analysis, Transfer Function analysis, Trend-stationarity, Difference-stationarity, Detrending, regart} } @ARTICLE{Kang03, author = {In-Bong Kang}, title = {Multi-period forecasting using different models for different horizons: an application to U.S. economic time series data}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {387-400}, number = {3}, abstract = {Most time series forecasters have used a single forecasting model at multiple forecast horizons. This practice is still largely in place, despite various suggestions that using different forecasting models for different horizons could improve forecast accuracy. Using monthly data on various U.S. economic time series, we investigate empirically whether the procedure of using a multi-period-ahead forecasting autoregressive model selected separately for each horizon (instead of using a single autoregressive model for all horizons) may or may not improve forecast accuracy for economic time series. We find that the forecast performance of the procedure appears to depend on, among other things, optimal order selection criteria, forecast origins, forecast horizons, and the time series to be forecasted.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00010-9}, issn = {0169-2070}, keywords = {Multi-period forecasting, Forecast accuracy, regart} } @ARTICLE{KB08, author = {Nektaria V. Karakatsani and Derek W. Bunn}, title = {Forecasting electricity prices: The impact of fundamentals and time-varying coefficients}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {764-785}, number = {4}, abstract = {This paper investigates the day-ahead forecasting performance of fundamental price models for electricity spot prices, intended to capture: (i) the impacts of economic, technical, strategic and risk factors on intra-day prices; and (ii) the dynamics of these effects over time. A time-varying parameter (TVP) regression model allows for a continuously adaptive price structure, due to agent learning, regulatory and market structure changes. A regime-switching regression model allows for discontinuities in pricing due to temporal irregularities and scarcity effects. The models that invoke market fundamentals and time-varying coefficients exhibit the best predictive performance among various alternatives, in the British market.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.09.008}, issn = {0169-2070}, keywords = {Electricity prices, Forecasting, Time-varying effects, Regime-switching, regart} } @ARTICLE{Karlsson93, author = {Sune Karlsson}, title = {Introduction to multiple time series : H. L{\"u}tkepohl, 1991, (Springer, New York), 552 pp., paperback US\$59.00, ISBN 0-387-53194-7.}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {577-578}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90081-W}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{KLT96, author = {Eija Kauppi and Jukka Lassila and Timo Ter{\"a}svirta}, title = {Short-term forecasting of industrial production with business survey data: experience from Finland's great depression 1990-1993}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {373-381}, number = {3}, abstract = {The severe Finnish recession in the early 90s provides an interesting testing ground for forecasting models specified and estimated before the recession. We use recent data to evaluate some short-term forecasting models for industrial production. The main explanatory variables are from business surveys and the models themselves are based on the use of the Kalman filter. The recession years present difficulties for forecasting especially in the textile industry and metal industry. In the food industry and to some extent in the forest industry the forecasting performance during the recession is actually better than in earlier periods. Mechanical re-estimation of the models yields better forecasting results in four out of six branches studied. The importance of business survey information, however, seems to have increased during the recession. The improvement in prediction accuracy after taking account of relevant business survey information is statistically significant in the forest industry and in manufacturing of non-metallic products when the precision of autoprojective forecasts is used as a baseline.}, doi = {http://dx.doi.org/10.1016/0169-2070(96)00671-1}, issn = {0169-2070}, keywords = {Autoprojective forecasts, Forecast comparison, Forecast updating, Kalman filter, Predictive accuracy, regart} } @ARTICLE{KMS90, author = {Sunder Kekre and Thomas E. Morton and Timothy L. Smunt}, title = {Forecasting using partially known demands}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {115-125}, number = {1}, abstract = {Most forecasting models for building a master schedule do not use information from orders that have been received for future delivery. We propose two basic algorithms that forecast the total demand by making use of information on orders already received. We test these algorithms using actual demand data from a printing firm. The behavior of the algorithms under special conditions like price promotions and shocks is also illustrated. We conclude that the proposed algorithms perform relatively better than exponential smoothing when partially known demand data is available.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90102-H}, issn = {0169-2070}, keywords = {Forecasting, Smoothing technologies, Production/operation management, Management information systems, regart} } @ARTICLE{Kennedy92, author = {Peter Kennedy}, title = {Forecasting with dynamic regression models: Alan Pankratz, 1991, (John Wiley and Sons, New York), ISBN 0-471-61528-5, �47.50}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {647-648}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90081-J}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Kennedy91, author = {Peter Kennedy}, title = {Comparing classification techniques}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {403-406}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90024-P}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Kennedy90, author = {Peter Kennedy}, title = {An exercise in computing the variance of the forecast error}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {275-276}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90017-6}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Ketkar90, author = {Kusum W. Ketkar}, title = {A log-linear approach to disaggregated micro-level population forecasts}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {241-251}, number = {2}, abstract = {This paper proposes the use of a log-linear model to obtain long-range micro-level population projections from the aggregative projections. The proposed model is tested using U.S. data. The total population of households is decomposed into 120 subgroups on the basis of the household's region of location, age, size and the female's employment status. The estimated number of households from the log-linear technique is compared against the random-walk and time-trend methods. A comparison of the size of the observed and estimated subgroups for the years 1960 and 1980 suggests that the log-linear technique is superior to the other two methods. Five different measures of errors are used to evaluate the projections.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90009-Z}, issn = {0169-2070}, keywords = {Population projections, Age, Region of location, Family size, Female employment, Log-linear model, Accuracy, regart} } @ARTICLE{KY05, author = {Konstantin A. Kholodilin and Vincent W. Yao}, title = {Measuring and predicting turning points using a dynamic bi-factor model}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {525-537}, number = {3}, abstract = {In this paper a dynamic bi-factor model with Markov-switching is developed to measure and predict turning points. Both common factors, namely composite leading index (CLI) and composite coincident index (CCI) respectively, have their own cyclical dynamics, and their lead-lag relationships are reflected in the transition probabilities matrix. The model is applied to four coincident and four selected leading indicators for the US economy. The bi-factor model estimates that, on average, CLI leads CCI by 7-8 months at both peaks and troughs. The model-derived recession probabilities of CCI and those of CLI with a lag of 9 months capture the NBER business cycle chronology very well. The out-of-sample forecast using CLI successfully detected the latest recession from March to December 2001. This allows the measurement and prediction of turning points in a precise and timely fashion.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.02.002}, issn = {0169-2070}, keywords = {Forecasting turning points, Composite coincident indicator, Composite leading indicator, Dynamic bi-factor model, Markov-switching, regart} } @ARTICLE{Kim04, author = {Jae H. Kim}, title = {Bootstrap prediction intervals for autoregression using asymptotically mean-unbiased estimators}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {85-97}, number = {1}, abstract = {The use of asymptotically mean-unbiased parameter estimation is considered as a means of bias-correction, when bootstrap prediction interval is constructed for the autoregressive (AR) model with unknown lag order. Its computational efficiency facilitates application of the endogenous lag order bootstrap algorithm. Extensive Monte Carlo experiments are conducted using a number of stationary and near unit-root AR models. It is found that bias-correction based on asymptotically mean-unbiased estimation substantially improves small sample properties of bootstrap prediction intervals. In particular, the endogenous lag order bootstrap interval shows highly desirable small sample performances. These features are evident, especially when the sample size is small; when the model is near unit-root non-stationary; and for high order AR models where the range of order estimation is wide.}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00007-4}, issn = {0169-2070}, keywords = {Autoregression, Bias-correction, Bootstrapping, Endogenous lag order bootstrap algorithm, Prediction interval, regart} } @ARTICLE{Kim03, author = {Jae H. Kim}, title = {Forecasting autoregressive time series with bias-corrected parameter estimators}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {493-502}, number = {3}, abstract = {The parameter estimators of autoregressive (AR) models are biased in small samples, and these biases can adversely affect their forecast accuracy. The purpose of this paper is to evaluate the effect of bias-correction for AR parameter estimators on forecast accuracy. The bias-corrected parameter estimators considered include a bootstrap mean bias-corrected estimator similar to [The Review of Economics and Statistics, 80 (1998) 218], the bootstrap approximately median bias-corrected estimator, the modified estimator of [Journal of Business & Economic Statistics, 19(4) (2001) 482], and the approximately median-unbiased estimator of [Journal of Business & Economic Statistics, 12 (1994) 187]. Monte Carlo simulations are conducted for AR models with linear time trend. It is found that all bias-corrected estimators can deliver a substantial gain of forecast accuracy for unit root or near-unit root AR models, especially when the sample size is small. Overall, the bootstrap mean bias-corrected estimator is found to provide more accurate forecasts than the other alternatives over a wider range of the parameter space.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00062-6}, issn = {0169-2070}, keywords = {Bias-correction, Autoregressive model, Forecasting, Bootstrapping, Unit root, regart} } @ARTICLE{Kim99, author = {Jae H. Kim}, title = {Asymptotic and bootstrap prediction regions for vector autoregression}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {393-403}, number = {4}, abstract = {Small sample properties of asymptotic and bootstrap prediction regions for VAR models are evaluated and compared. Monte Carlo simulations reveal that the bootstrap prediction region based on the percentile-t method outperforms its asymptotic and other bootstrap alternatives in small samples. It provides the most accurate assessment of future uncertainty under both normal and non-normal innovations. The use of an asymptotic prediction region may result in a serious under-estimation of future uncertainty when the sample size is small. When the model is near non-stationary, the use of the bootstrap region based on the percentile-t method is recommended, although extreme care should be taken when it is used for medium to long-term forecasting.}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00006-0}, issn = {0169-2070}, keywords = {VAR model, Prediction regions, Bootstrap, Backward VAR model, regart} } @ARTICLE{KC98, author = {Steven H. Kim and Se Hak Chun}, title = {Graded forecasting using an array of bipolar predictions: application of probabilistic neural networks to a stock market index}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {323-337}, number = {3}, abstract = {To an increasing extent over the past decade, software learning methods including neural networks have been used for prediction in financial markets and other areas. By far the most popular type of neural network has been backpropagation. However, the advantages of other learning techniques such as the swift response of the probabilistic neural network (PNN) suggest the desirability of adapting other models to the predictive function. Unfortunately, the conventional architecture for probabilistic neural networks yields only a bipolar output corresponding to Yes or No; Up or Down. This limitation may be circumvented in part by using a graded forecast of multiple discrete values. More specifically, the approach involves an architecture comprising an array of elementary PNNs with bipolar output. This paper explores a number of interrelated topics: (1) presentation of a new architecture for graded forecasting using an arrayed probabilistic network (APN); (2) use of a mistakechart to compare the accuracy of learning systems against default performance based on a constant prediction; and (3) evaluation of several backpropagation models against a recurrent neural network (RNN) as well as PNN, APN, and case based reasoning. These concepts are investigated against the backdrop of a practical application involving the prediction of a stock market index.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00003-X}, issn = {0169-2070}, keywords = {Forecasting system, Artificial intelligence, Financial market forecasting, regart} } @ARTICLE{KWD97, author = {Howard R. Kirby and Susan M. Watson and Mark S. Dougherty}, title = {Should we use neural networks or statistical models for short-term motorway traffic forecasting?}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {43-50}, number = {1}, abstract = {This article discusses the relative merits of neural networks and time series methods for traffic forecasting and summarises the findings from a comparative study of their performance for motorway traffic in France. Whilst it was possible to get a good performance with both neural networks and traditional Auto-Regressive Integrated Moving Average (ARIMA) models when forecasting up to an hour ahead using data supplied in 30-min intervals, a purpose-built pattern based forecasting model known as ATHENA, developed by INRETS, out-performed both these methods somewhat. The ways in which these models relate to the structure of traffic data are discussed and alternative paradigms are proposed.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00699-1}, issn = {0169-2070}, keywords = {Traffic forecasting, ARIMA models, Neural networks, ATHENA model, Motorway flows, regart} } @ARTICLE{Kirkendall86, author = {Nancy J. Kirkendall}, title = {Microeconomic modeling and policy analysis: Studies in residential energy demand : Tomas G. Cowing and Daniel L. McFadden, (Academic Press, Orlando, FL, 1984)}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {499-501}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90101-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Kjaerulff95, author = {Uffe Kj{\ae}rulff}, title = {dHugin: a computational system for dynamic time-sliced Bayesian networks}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {89-111}, number = {1}, abstract = {A computational system for reasoning about dynamic time-sliced systems using Bayesian networks is presented. The system, called dHugin, may be viewed as a generalization of the inference methods of classical discrete time-series analysis in the sense that it allows description of non-linear, discrete multivariate dynamic systems with complex conditional independence structures. The paper introduces the notions of dynamic time-sliced Bayesian networks, a dynamic time window, and common operations on the time window. Inference, pertaining to the time window and time slices preceding it, are formulated in terms of the well-known message passing scheme in junction trees. Backward smoothing, for example, is performed efficiently through inter-tree message passing. Further, the system provides an efficient Monte-Carlo algorithm for forecasting; i.e. inference pertaining to time slices succeeding the time window. The system has been implemented on top of the Hugin shell.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)02003-8}, issn = {0169-2070}, keywords = {Bayesian belief network, Junction tree, Time series analysis, Discrete Markov chain, Non-linear multivariate dynamic system, Monte-Carlo algorithm, regart} } @ARTICLE{KH00, author = {Daniel Klapper and Helmut Herwartz}, title = {Forecasting market share using predicted values of competitive behavior: further empirical results}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {399-421}, number = {3}, abstract = {Forecasting is an important marketing activity for evaluating the expected performance of alternative marketing plans, especially in order to predict earnings, sales or market shares. The purpose of this paper is fourfold. Firstly, we develop and evaluate alternative econometric approaches to predict competitors' future actions. Secondly, the forecasting performance of attraction models is compared to those of linear and multiplicative market share models not only if competitors' actions are known a priori but also if competitors' actions are forecasts. Thirdly, the effects of alternative structural specifications of attraction models on the forecasting accuracy are investigated. Finally, we reinvestigate the impact of OLS estimation versus GLS estimation on the forecasting performance. The adopted empirical methods account for the interdependence of marketing instruments. We also allow for competitive reactions up to 10 periods ago and introduce a new approach concentrating on so-called marketing events characterizing directly the contemporaneous choice of several promotional activities within a brand. Analyzing weekly scanner data from three markets we find that attraction models outperform the share predictions of the linear and multiplicative models even if competitors' actions are forecast. This result is valid on the market and brand level. In addition, response models outperform the naive model on the market level irrespective of whether competitors' actions are known a priori or if they are forecasts. On the brand level the superiority of response models over naive models diminishes though it still exists. With respect to the best method of predicting competitors' actions it turns out that parsimonious specifications like autoregressive price predictions or binary logit models perform conveniently.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00052-2}, issn = {0169-2070}, keywords = {Forecasting competitors'actions, Market share models, Naive models, Market level forecasting, Brand level forecasting, Forecasting accuracy, regart} } @ARTICLE{98j, author = {Hans Klein}, title = {Book Review}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {301-303}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00022-3}, issn = {0169-2070}, key = {tagkey1998301}, keywords = {bookrev} } @ARTICLE{Klein09, author = {Philip A. Klein}, title = {Victor Zarnowitz 1919-2009}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {432 - 434}, number = {3}, note = {Special Section: Time Series Monitoring}, doi = {10.1016/j.ijforecast.2009.05.021}, issn = {0169-2070} } @ARTICLE{Klein02, author = {Philip A. Klein}, title = {Victor Zarnowitz: An interview with the International Journal of Forecasting}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {131-151}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00084-4}, issn = {0169-2070}, keywords = {revart} } @ARTICLE{Klein96, author = {Philip A. Klein}, title = {Is the economic cycle still alive? : Mario Baldassarri and Paolo Annunziato, eds., 1994, (St. Martin, New York), US\$79.95, ISBN 0-312-10380-8.}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {177-179}, number = {1}, note = {Probability Judgmental Forecasting}, doi = {http://dx.doi.org/10.1016/0169-2070(96)88193-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Klein93, author = {Philip A. Klein}, title = {Geoffrey H. Moore and dynamic statistical methods}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {31-37}, number = {1}, abstract = {Geoffrey H. Moore's professional life has been devoted to ongoing research in the development of a variety of statistically innovative techniques applied to business cycle research. His approach is convincing proof that constant reassessment of statistical measures is a prerequisite for improving our techniques for monitoring and for forecasting aggregate economic performance.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90051-N}, issn = {0169-2070}, keywords = {Business cycle indicators, Diffusion index, Business cycle surveys, Statistical and smoothing composite index, regart} } @ARTICLE{Klein87, author = {Philip A. Klein}, title = {Expectations: Theory and evidence : K. Holden, D.A. Peel and J.L. Thompson, NY, 1985. (St. Martin's Press, New York, NY, 1985), \$25.00}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {340-341}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90020-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Klein86, author = {Philip A. Klein}, title = {Leading indicators of inflation in market economies}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {403-412}, number = {4}, abstract = {Inflation rates are cyclical in major market-oriented economies. Recently Geoffrey H. Moore and Stanley Kaish applied the well-known leading indicator approach to the development of a leading index of inflation cycles for the United States. Their index was based on measures of tightness in the labor market, and a measure of tightness in total credit markets, along with a measure of changes in industrial commodity prices. They found that this composite index reflects changes in inflation rate cycles reasonably well, and that it was more reliable than any of the three components taken alone. The present study broadens their study by attempting to duplicate the leading inflation index for forecasting changes in inflation rates in Canada, the United Kingdom, West Germany, France, Italy, and Japan. In general we find that the leading index is useful in anticipating changes in inflation rates in all these countries with the exception of France and Italy. As such we find that the forecasting properties of this index are often as promising in other countries as they have been in the U.S. Where they are not we conclude that there is a need for further research.}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90087-7}, issn = {0169-2070}, keywords = {Leading indicator, Composite index, Inflation cycles, Forecasting inflation, regart} } @ARTICLE{Kling88, author = {John L. Kling}, title = {The modern forecaster: The forecasting process through data analysis : Hans Levenbach and James P. Cleary, (Van Nostrand Reinhold, 1984) pp. 450, \$36.95}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {498-499}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90117-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{KB85, author = {John L. Kling and David A. Bessler}, title = {A comparison of multivariate forecasting procedures for economic time series}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {5-24}, number = {1}, abstract = {In the recent decade several multivariate time-series methods have become available for forecasting. As with univariate methods, choices must be made as to which methods to use in practice. This paper reports the results of out-of-sample forecasts for several well-known procedures. Three interesting sets of data are used, and the forecasts are made over a five-year period. The data and model specifications are available upon request, so that the statistics presented in this paper can be used as a basis of comparison for future research.}, doi = {http://dx.doi.org/10.1016/S0169-2070(85)80067-4}, issn = {0169-2070}, keywords = {Forecasting evaluation, Factor autoregressive methods, Multivariate time-series methods, Accuracy, Empirical study, regart} } @ARTICLE{Kluyver96, author = {Cornelis A. de Kluyver}, title = {Forecasting and market analysis techniques -- A practical approach : George J. Kress and John Snyder, 1994, (Quorum Books, Westport, CT), US\$65.00, ISBN 0-59930-835-X.}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {179-180}, number = {1}, note = {Probability Judgmental Forecasting}, doi = {http://dx.doi.org/10.1016/0169-2070(96)88194-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Koehler06, author = {Anne Koehler}, title = {Discussion}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {667-670}, number = {4}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.07.002}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Koehler95, author = {Anne Koehler}, title = {Software review}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {337-337}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(95)90065-9}, issn = {0169-2070} } @ARTICLE{KDG+96, author = {Anne Koehler and Francis X. Diebold and Lorenzo Giogianni and Atsushi Inoue}, title = {Software review}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {309-315}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(96)00683-8}, issn = {0169-2070}, keywords = {prodrev} } @ARTICLE{KN95, author = {Anne Koehler and Nicholas R. Noble}, title = {Software review}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {497-499}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(95)90037-3}, issn = {0169-2070}, keywords = {prodrev} } @ARTICLE{Koehler04, author = {Anne B. Koehler}, title = {Comments on damped seasonal factors and decisions by potential users}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {565-566}, number = {4}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.03.004}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Koehler01, author = {Anne B. Koehler}, title = {Time Series Analysis and Forecasting with Applications of SAS and SPSS: Robert Yaffee and Monnie McGee (contributor), (2000) San Diego: Academic Press. 496 pages. ISBN 0 127 67870 0 Hardback: �29.95, \$69.95.}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {301-302}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00087-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Koehler95a, author = {Anne B. Koehler}, title = {Journal of the American Statistical Association : Carlo Grillenzoni, 1994, Optimal recursive estimation of dynamic models, 89, 777-787}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {353-354}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(95)90067-5}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Koehler90, author = {Anne B. Koehler}, title = {An inappropriate prediction interval}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {557-558}, number = {4}, abstract = {This paper discusses a point of confusion in the literature of applied forecasting. There is a misconception that multiplying s, the standard deviation of one-period-ahead forecast errors, by the square root of h gives a valid standard deviation for h-period-ahead forecast errors. This standard deviation and the interval forecasts produced with it are theoretically correct only for a random walk model.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90034-9}, issn = {0169-2070}, keywords = {Interval forecast, Prediction interval, regart} } @ARTICLE{Koehler89, author = {Anne B. Koehler}, title = {Forecasting economic time series : C.W.J. Granger and Paul Newbold, Second edition (Harcourt Brace Jovanovich, New York, 1986) hard cover \$49.50/paperback \$24.95, �37.50 pp. 337}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {137-138}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90073-3}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Koehler85, author = {Anne B. Koehler}, title = {Simple vs. complex extrapolation models: An evaluation in the food processing industry}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {63-68}, number = {1}, abstract = {This paper describes an empirical study of time series data for consumer products in the food processing industry at the stockkeeping unit level. The focus is on whether or not simple forecasting models adequately fit this type of data. The Box-Jenkins methodology is used to select forecasting models. The results show that simple models are identified by this procedure. In particular, two types of models prevail: (1) models that require information from only the previous time period and (2) simple seasonal models. The forecasting results reinforce the choice of simple models and show that better fitting models do not, in general, give better forecasts. Finally, the simple exponential smoothing model is shown to be a robust forecasting model for data of this type.}, doi = {http://dx.doi.org/10.1016/S0169-2070(85)80071-6}, issn = {0169-2070}, keywords = {Forecasting, Time series, Box-Jenkins, Empirical study, Stockkeeping unit, Extrapolative method, regart} } @ARTICLE{KM88, author = {Anne B. Koehler and Emily S. Murphree}, title = {A comparison of results from state space forecasting with forecasts from the Makridakis Competition}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {45-55}, number = {1}, abstract = {State space models are fit to a subset of the time series modelled by the Box-Jenkins method in the Makridakis Competition. The state space approach to time series analysis is outlined, as is the use of a modelling package on a personal computer. Forecasts from one to 18 months beyond the fit set of each series are computed from the fitted models. Box-Jenkins forecasts and deseasonalized single exponential smoothing (final forecasts are reasonalized) forecasts for the same series are extracted from the M-Competition data tape. All three sets of forecasts are compared to the actual series values withheld in the check sets; forecasting accuracy is calculated on the basis of mean absolute percentage error and median absolute percentage error. The automatic procedure of single exponential smoothing and the semi-automatic procedure of the state space package produce forecasts which, in most cases, are as accurate or more accurate than those developed by an expert using the Box-Jenkins method.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90009-X}, issn = {0169-2070}, keywords = {Forecasting accuracy, Univariate time series methods, Extrapolation, Empirical study, State space, Box-Jenkins, Exponential smoothing, regart} } @ARTICLE{KSO01, author = {Anne B. Koehler and Ralph D. Snyder and J. Keith Ord}, title = {Forecasting models and prediction intervals for the multiplicative Holt-Winters method}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {269-286}, number = {2}, abstract = {A new class of models for data showing trend and multiplicative seasonality is presented. The models allow the forecast error variance to depend on the trend and/or the seasonality. It is shown that each of these models has essentially the same updating equations and forecast functions as the multiplicative Holt-Winters method, whether or not the error variation in the model is constant. Although the different models produce identical updating relationships for the point forecast, the prediction intervals, of course, depend on the structure of the error variance and so it is essential to be able to choose the most appropriate form of model. Two methods for model selection are presented and examined by simulation. For the most common case of series with an upward trend, we recommend using a model with variance dependent on both the trend and seasonal elements.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00081-4}, issn = {0169-2070}, keywords = {Holt-Winters method, Exponential smoothing, State space models, Prediction intervals, Model selection, regart} } @ARTICLE{KZ88, author = {Eduard Kofler and Peter Zweifel}, title = {Exploiting linear partial information for optimal use of forecasts : With an application to U.S. economic policy}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {15-32}, number = {1}, abstract = {Traditionally, the link between forecasting and decision making rests on the assumption of a known distribution for the future values of predicted variables. In practice, however, forecasts tend to offer little more than Linear Partial Information (LPI), typically of the form, `State 1 is more likely to prevail than state 2, and state 2 more likely to prevail than state 3, among five possible states'. This paper shows how such fuzzy LPI statements can be exploited in decision making. For an illustration, LPI analysis is used for determining (ex post) the optimal economic policy to be followed by the Carter Administration with a view to ensuring reelection in 1980. An optimal adaption of that policy occasioned by the fallible 1980 forecasts made by the Council of Economic Advisors is also derived.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90007-6}, issn = {0169-2070}, keywords = {Decision rules methodology, Partial information, Policy evaluation methodology, regart} } @ARTICLE{KS96, author = {R. A. Kolb and H. O. Stekler}, title = {Is there a consensus among financial forecasters?}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {455-464}, number = {4}, abstract = {This paper examines the interest rate forecasts of a cross-section of financial forecasters to determine whether these analysts make predictions which have the characteristics of a consensus. The forecasts are published semi-annually in The Wall Street Journal. The techniques for determining whether a consensus exists are developed and are applied to the predictions of the interest rates of the 90-day T-bill and the 30-year Treasury bond. The methodology provides bounds on the number of distributions which may be classified as consensus and the results indicate that central moments should not be used as consensus predictions.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00675-9}, issn = {0169-2070}, keywords = {Financial forecasting, Interest rate forecasting, Consensus, Distribution of forecasts, regart} } @ARTICLE{KS93, author = {R. A. Kolb and H. O. Stekler}, title = {Are economic forecasts significantly better than naive predictions? An appropriate test}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {117-120}, number = {1}, abstract = {Most forecast evaluations do not test whether the predictions are statistically significantly better than naive forecasts. This note describes how an existing test can be used to test the hypothesis that predictions are superior to naive forecasts.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90059-V}, issn = {0169-2070}, keywords = {Error comparisons; Hypothesis test; Naive model, othercom} } @ARTICLE{KFH+05, author = {Alex J. Koning and Philip Hans Franses and Michèle Hibon and H.O. Stekler}, title = {The M3 competition: Statistical tests of the results}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {397-409}, number = {3}, abstract = {The main conclusions of the M3 competition were derived from the analyses of descriptive statistics with no formal statistical testing. One of the commentaries noted that the results had not been tested for statistical significance. This paper undertakes such an analysis by examining the primary findings of that competition. We introduce a new methodology that has not previously been used to evaluate economic forecasts: multiple comparisons. We use this technique to compare each method against the best and against the mean. We conclude that the accuracy of the various methods does differ significantly, and that some methods are significantly better than others. We confirm that there is no relationship between complexity and accuracy but also show that there is a significant relationship among the various measures of accuracy. Finally, we find that the M3 conclusion that a combination of methods is better than that of the methods being combined was not proven.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.10.003}, issn = {0169-2070}, keywords = {Forecasting competitions, M3 competition, Multiple comparisons, Analysis of ranks, regart} } @ARTICLE{Kontzalis92, author = {Panos Kontzalis}, title = {Identification of key attributes, gap analysis and simulation techniques in forecasting market potential of ethical pharmaceutical products}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {243-249}, number = {2}, abstract = {This paper describes a model used to forecast the potential market share of a new pharmaceutical product. It was developed specifically for Sandoz Pharma AG but it can be applied to other pharmaceutical companies. The model takes into account the customers' (i.e. physicians') decision-making process, their attitudes/needs as well as the product's clinical profile. The model development consists of the following major steps: 1. (1) Identification of key attributes physicians consider important in selecting products for the treatment of a certain condition. 2. (2) Measurement of the relative importance of each attribute vs. all others (trade-off utility score). 3. (3) Association of leading existing therapies with the attributes (product profiling and gap analysis). 4. (4) Product usage simulation based on the mean scores of the competitors and the actual clinical profile of the new product. The model predicts the overall market share likety to be attained by the new product in each of the major markets (i.e. key countries) and its impact on the market share of the leading competitive products. Besides pharmaceuticals, the model can also be used to forecast the market potential of other industrial products such as cars, cigarettes, and consumer goods.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90122-P}, issn = {0169-2070}, keywords = {Forecasting market share, Trade-off utility scores, Conjoint analysis, Correspondence analysis, Gap analysis, Simulation model, Forecasting pharmaceutical productsregart} } @ARTICLE{KP98, author = {Sergio G. Koreisha and Tarmo Pukkila}, title = {A two-step approach for identifying seasonal autoregressive time series forecasting models}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {483-496}, number = {4}, abstract = {One of the most powerful and widely used methodologies for forecasting economic time series is the class of models known as seasonal autoregressive processes. In this article we present a new approach not only for identifying seasonal autoregressive models, but also the degree of differencing required to induce stationarity in the data. The identification method is iterative and consists in systematically fitting increasing order models to the data, and then verifying that the resulting residuals behave like white noise using a two stage autoregressive order determination criterion. Once the order of the process is determined the identified structure is tested to see if it can be simplified. The identification performance of this procedure is contrasted with other order selection procedures for models with `gaps.' We also illustrate the forecast performance of the identification method using monthly and quarterly economic data.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00044-2}, issn = {0169-2070}, keywords = {Forecast performance, Identification, Order determination criterion, Residual white noise test, Seasonal models, regart} } @ARTICLE{KD88, author = {John F. Kottas and Jack Dittrick}, title = {Simulated solutions plus : (Version 1.3 - $295: demo $25) Enfin Software Corp., 6920 Miramar Rd., Suite 106-A, San Diego, CA 92121, (619) 549-6606. Requirements: Lutos 123 version 2 or 2.01, or symphony versions 1 through 1.2. Not copy-protected}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {621-623}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90144-6}, issn = {0169-2070}, keywords = {prodrev} } @ARTICLE{Krause02, author = {Andreas Krause}, title = {Book review: Developments in Forecast Combination and Portfolio Choice, edited by Christian Dunis, Allan Timmermann and John Moody, Wiley, New York, 2001, Hardback, 330pp. ISBN 0-47152-165-5, \$95.}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {462-463}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00149-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{KRT02, author = {Donald J. Kridel and Paul N. Rappoport and Lester D. Taylor}, title = {IntraLATA long-distance demand: carrier choice, usage demand and price elasticities}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {545-559}, number = {4}, abstract = {Competition in the long-distance market in the US continues to intensify; the 1996 Telecommunications Act has led to increased competition in long-distance telephony especially as the Regional Bell Operating Companies have begun to gain entry to long-haul, long-distance markets. In order to better understand the implications of having increased service offerings, models of how customers choose between carriers (and the impact of this choice on subsequent usage) will be useful. We develop the first publicly available models that simultaneously estimate choice and usage for intraLATA long-distance in the US. Utilizing a generalized Tobit model, the price responsiveness of usage and carrier choice are estimated. The results are generally consistent with expectations both in terms of theory and of practical experience in the industry.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00065-1}, issn = {0169-2070}, keywords = {Telecommunications, Econometric models, Consumer demand, Probits, regart} } @ARTICLE{KNR89, author = {Lakshman Krishnamurthi and Jack Narayan and S. P. Raj}, title = {Intervention analysis using control series and exogenous variables in a transfer function model: A case study}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {21-27}, number = {1}, abstract = {This paper presents a case study to show how a control group can be used to obtain more accurate estimates of the impact of interventions. Intervention analysis using the ARIMA time series method is applied in an experimental design context using multiple input transfer function analysis. The study combines the analytic rigor of time series analysis with the careful controls provided by an experiment involving a test and control series. The data are from a field experiment with test and control panels connected to a split-cable TV system.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90060-5}, issn = {0169-2070}, keywords = {Intervention analysis, Control groups, Multiple transfer function models, Experimental design, regart} } @ARTICLE{Krishnan04, author = {Murugappa Krishnan}, title = {Earnings skewness and analyst forecast bias: Gu Zhaoyang and Joanna Shuang Wu, 2003, Journal of Accounting and Economics, 35, 5-29}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {734-736}, number = {4}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.04.004}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{KT07, author = {Libor Krkoska and Utku Teksoz}, title = {Accuracy of GDP growth forecasts for transition countries: Ten years of forecasting assessed}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {29-45}, number = {1}, abstract = {The paper analyses the accuracy of GDP growth forecasts prepared by the EBRD for 25 transition countries between 1994 and 2004. It provides the first comprehensive statistical analysis of the accuracy of output growth forecasts for transition countries in central and eastern Europe and the former Soviet Republics. We find that EBRD forecasts are mostly unbiased and efficient, i.e., forecast errors are not autocorrelated and do not depend on the value of the forecasted variable. In addition, we show that forecast accuracy improves with progress in transition as well as with the expansion in the information domain. We have also identified the Russian crisis as the only clear structural break in the available time series. Finally, we show that the EBRD forecast accuracy for late within-year GDP forecasts is better than the forecast accuracy of other institutions by 0.4 percentage points.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.08.002}, issn = {0169-2070}, keywords = {Macroeconomic forecasting, Forecast evaluation, GDP growth, Bias and efficiency, Transition, EBRD, regart} } @ARTICLE{Krolzig01, author = {Hans-Martin Krolzig}, title = {Business cycle measurement in the presence of structural change: international evidence}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {349-368}, number = {3}, abstract = {By generalizing Hamilton's model of the US business cycle to a three-regime Markov-switching vector autoregressive model, this paper analyzes regime shifts in the stochastic process of economic growth in the US, Japan and Europe over the last four decades. Empirical evidence is established for the presence of a structural break in the expansionary GDP growth for the US and Japan based on an output-employment MS vector equilibrium correction model, and a structural break in the context of a common European business cycle. For the United States the long expansions of recent years signify basic changes in the business cycles pattern. In the case of Japan we identify long episodes of rapid economic expansions (existing until the mid 1970s) and long economic recessions (as in the 1990s). In Europe we find after an episode of catching-up in the 1970s, convergence in the business cycle pattern which suggests the notion of a European business cycle. The multi-regime Markov-switching VARs proposed are profoundly checked for their economic content and statistical congruency, and are found to provide a sound statistical framework for a comprehensive analysis of the business cycle.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00099-1}, issn = {0169-2070}, keywords = {Business cycles, Regime shifts, Markov switching, Structural change, Employment, Impulse-response analysis, Cointegration, European Union, Time series analysis, regart} } @ARTICLE{KL91, author = {Roman Krzysztofowicz and Dou Long}, title = {Forecast sufficiency characteristic: Construction and application}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {39-45}, number = {1}, abstract = {The binary relation of sufficiency induces a quasi order among alternative forecast systems, consistent with their order in terms of economic values, yet independent of the prior distribution and the loss function. This invariance across decision problems makes the sufficiency relation an attractive tool for comparing forecasts serving multiple users. The existence of the sufficiency relation between discrete probabilistic forecasts of binary events may be verified graphically by plotting Forecast Sufficiency Characteristics (FSC). The article presents a general algorithm for constructing FSC and illustrates the concept with an application to real meteorologic forecasts.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90031-P}, issn = {0169-2070}, keywords = {Sufficiency, Forecast, Bayesian method, Meteorology, regart} } @ARTICLE{KL91a, author = {Roman Krzysztofowicz and Dou Long}, title = {Beta likelihood models of probabilistic forecasts}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {47-55}, number = {1}, abstract = {A class of parametric likelihood models for continuous probabilistic forecasts of binary states is formulated based on the beta family of densities. Characteristics of the models deemed useful for applications are derived. These include: (i) parametric conditions for verifying the calibration and semicalibration properties of forecasts, (ii) procedures for constructing Forecast Sufficiency Characteristics (FSC) that enable one to establish the sufficiency relation between forecasts prepared by different forecasters, and (iii) parametric conditions (stronger than ) for verifying the sufficiency relation. The models are illustrated with an application to real meteorologic forecasts.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90032-Q}, issn = {0169-2070}, keywords = {Likelihood, Beta distribution, Forecast, Bayesian method, Calibration, Sufficiency, Meteorology, regart} } @ARTICLE{KK97, author = {N. Kulendran and Maxwell L. King}, title = {Forecasting international quarterly tourist flows using error-correction and time-series models}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {319-327}, number = {3}, abstract = {This paper compares a range of forecasting models in the context of predicting quarterly tourist flows into Australia from the major tourist markets of USA, Japan, UK and New Zealand. Models considered include the error-correction model, the autoregressive model, the autoregressive integrated moving average model, the basic structural model and a regression based time series model. Seasonality is an important feature of these series that requires careful handling. The relative performance of each model varies from country to country. The main conclusion is that relative to the time-series models, the error correction models perform poorly. This may be caused by the way in which decisions on how best to model nonstationarity and seasonality are made.}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00020-4}, issn = {0169-2070}, keywords = {Unit roots, Seasonality, Tourism demand, Cointegration, Forecast comparison, regart} } @ARTICLE{Kumar94, author = {V. Kumar}, title = {Forecasting performance of market share models: an assessment, additional insights, and guidelines}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {295-312}, number = {2}, abstract = {The research provides an assessment of the relevant literature on market share models and identifies the need for further research. Additional insights are generated in this study by using point-of-sale scanners for evaluating the forecasting performance of market share models under various conditions. Specifically, weekly store-level scanner data for four frequently purchased product categories-saltine crackers, baking chips, diapers and toilet tissue, and simulated data are used in this study. Consistent with theoretical expectations, the attraction models estimated by GLS produce the best forecasts even (1) at the brand level, and (2) when competitors' actions are predicted. However, the superiority of the attraction models is diminished when systematic errors are introduced to the values of the competitors' predictor variables in the holdout sample. In fact, naive models outperform all types of econometric models when large errors are present in the competitors' predictor variables, and among the econometric models, linear models produce better forecasts than attraction models. The need for estimating the models with GLS (as opposed to OLS) with the use of cross-sectional time-series data is also illustrated. Finally, guidelines are developed for practitioners and researchers on the usefulness of market share models for forecasting.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90009-4}, issn = {0169-2070}, keywords = {Scanner data, Forecasting competitors' actions, Brand level forecasting, Market share models, Forecasting promotional (dummy) variables, Evaluating forecasting performance, Systematic error in competitors' actions, regart} } @ARTICLE{KH90, author = {V. Kumar and Timothy B. Heath}, title = {A comparative study of market share models using disaggregate data}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {163-174}, number = {2}, abstract = {Prior research assessing the predictive validity of alternate market share models produced conflicting results and often found that econometric models performed worse than naive extrapolations. However, contributors to IJF's recent issue on market share models suggested that such models are often misspecified, in part because they exclude promotional variables and are estimated on aggregate data. Thus, we used weekly scanner data to assess full, reduced, and naive forms of linear, multiplicative, and attraction specifications across different levels of parameterization. Consistent with specification-based arguments, (1) econometric models were superior to naive models, (2) GLS estimates of attraction models were superior when models were fully specified, (3) OLS estimates of linear models were superior when models omitted important variables, and (4) attraction models predicted best overall. Moreover, in general, unconstrained models yielded superior forecasts relative to constrained models because brand-specific parameters were heterogeneous for the product category tested.}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90002-S}, issn = {0169-2070}, keywords = {Empirical study, Evaluating forecast accuracy, Market share models, Scanner data, Theoretical explanation, regart} } @ARTICLE{KLG95, author = {V. Kumar and Robert P. Leone and John N. Gaskins}, title = {Aggregate and disaggregate sector forecasting using consumer confidence measures}, journal = {International Journal of Forecasting}, year = {1995}, volume = {11}, pages = {361-377}, number = {3}, abstract = {The usefulness of the combination of Katona's abilityandwillingnesstobuy framework and Bayesian vector autoregression for business forecasting was examined. Models were estimated with and without a measure of consumer confidence and with either a vector autoregression model with lag structure determined by a stepwise (VAR) or a Bayesian (BVAR) approach. Additionally, Katona's framework was tested at different levels of aggregation of consumer expenditures. Unlike in past research, monthly data were used in the operationalization of the framework. It was found that the BVAR, along with the consumer confidence measure, performed the best across three forecasting horizons and three performance measures. Any degradation of model performance at lower levels of aggregation across expenditure categories was only modest. The findings suggest that the use of BVAR, with consumer confidence index as a predictor should be considered in business forecasting.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00594-2}, issn = {0169-2070}, keywords = {Katona's framework, Business forecasting, VAR, BVAR, Index of consumer sentiment, regart} } @ARTICLE{KNV02, author = {V. Kumar and Anish Nagpal and Rajkumar Venkatesan}, title = {Forecasting category sales and market share for wireless telephone subscribers: a combined approach}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {583-603}, number = {4}, abstract = {The ability to forecast market share remains a challenge for many managers especially in dynamic markets, such as the telecommunications sector. In order to accommodate the unique dynamic characteristics of the telecommunications market, we use a multi-component model, called MSHARE. Our method involves a two-phase process. The first phase consists of three components: a projection method, a ring down survey methodology and a purchase intentions survey. The predictions from these components are combined to forecast category sales for the wireless subscribers market. In the second phase, market shares for the various brands are generated using the forecast of the number of subscribers that are obtained in Phase 1 and the share predictions from the ring down methodology. The proposed methodology produces the minimum Relative Absolute Error for each market as compared to the forecasts from each individual component in the first phase. The value of the proposed model is illustrated by its application to a real world scenario. The managerial implications of the proposed model are also discussed.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00068-7}, issn = {0169-2070}, keywords = {Forecasting, Category sales, Wireless telephone subscribers, Combined approach, Market share, regart} } @ARTICLE{KH86, author = {Kiyonori Kunisawa and Yasuichi Horibe}, title = {Forecasting international telecommunications traffic by the data translation method}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {427-434}, number = {4}, abstract = {In forecasting the future international telecommunications traffic for individual countries, a global international view may provide a better long-range view of future trends rather than one based on observing individual countries separately. We propose a data translation method to achieve this. The method properly translates the traffic data per person for a group of countries along the time axis and `joins' them together to form a single logistic or exponential forecasting curve. A necessary and sufficient mathematical condition for the method to be applied is given. Estimation of these curves is then considered. Forecasts are briefly shown for the telephone and telex examples, which demonstrate the improved accuracy that can be achieved relative to simple models based on individual country's trends.}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90089-0}, issn = {0169-2070}, keywords = {International telecommunications traffic, Data translation method, Logistic curve, Exponential curve, regart} } @ARTICLE{KN86, author = {Robert Kunst and Klaus Neusser}, title = {A forecasting comparison of some var techniques}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {447-456}, number = {4}, abstract = {Higher dimensional multivariate time series models suffer from the problem of over-parametrisation which impairs their forecasting performance. Starting from such unrestricted vector autoregressive models the paper discusses two ways to cope with this difficulty. The first approach reduces the number of free parameters by applying a subset modelling strategy. The second approach takes a Bayesian point of view by formulating `priors' which are then combined with sample information, but leaving the original specification unaltered. Using Austrian quarterly macroeconomic time series a comparative study is undertaken by running alternative forecasting exercises. Both methods improve out-of-sample forecasting performance substantially at the cost of some bias in ex-post simulations. Comparing the ex-ante predictions of the two approaches, the former does better at short horizons whereas the latter gains as the forecast horizon lengthens.}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90091-9}, issn = {0169-2070}, keywords = {Multivariate time-series methods, Forecasting evaluation, Empirical study, Subset modeling, Bayesian analysis, regart} } @ARTICLE{91, author = {Gerard H. Kuper}, title = {Software reviews}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {111-115}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90040-3}, issn = {0169-2070}, key = {tagkey1991111}, keywords = {prodrev} } @ARTICLE{KMB06a, author = {Ulrich K{\"u}sters and B.D. McCullough and Michael Bell}, title = {Forecasting software: Past, present and future}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {599-615}, number = {3}, abstract = {We present an overview of the history of forecasting software over the past 25 years, concentrating especially on the interaction between computing and software. Initially we create a framework by describing important developments of computing technology in terms of hardware and software environments. We then concentrate on two different application areas of forecasting software: (1) research oriented forecasting software often used to analyze a small number of series (for example, in market research); and (2) forecasting modules in planning environments which are often partially automated due to the large number of time series involved. Finally we make some suggestions as to where forecasting software has room for improvement.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.03.004}, issn = {0169-2070}, keywords = {Forecasting software, Demand planning, Econometric analysis systems, History of computing, Statistical software packages, Operational planning, Sales planning, Software development, Supply chain management, regart} } @ARTICLE{98o, author = {Pamela Labadie and}, title = {Book Review}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {533-535}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00047-8}, issn = {0169-2070}, key = {tagkey1998533}, keywords = {bookrev} } @ARTICLE{LS88, author = {Charles J. Lacivita and Terry G. Seaks}, title = {Forecasting accuracy and the choice of first difference or percentage change regression models}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {261-268}, number = {2}, abstract = {Regression models used by forecasters are often formulated in terms of the first differences or percentage changes of the variables. A recently developed maximum likelihood procedure permits the researcher to determine whether the first difference or percentage change model is superior. In this paper we apply this new method to several forecasting models from the literature and then determine whether or not the correct functional form improves forecasting accuracy. Results indicate that when either the first difference or percentage change model can he rejected in favor of the other, then superior forecasts can be obtained by using the correct form.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90081-7}, issn = {0169-2070}, keywords = {Forecasting accuracy, Regression, model choice, Evaluation, Transformed variables, regart} } @ARTICLE{LQ04, author = {Dominique Ladiray and Benoit Quenneville}, title = {Implementation issues on shrinkage estimators for seasonal factors within the X-11 seasonal adjustment method}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {557-560}, number = {4}, abstract = {This commentary on Miller and Williams [Intl. J. Forecast. 20 (2004)S29-49] discusses how shrinkage can be implemented within X12-ARIMA. We discuss how the seasonal factors are estimated in X12-ARIMA, how shrinkage can be translated into a moving average, if this is compatible with the philosophy behind the X12-ARIMA method, and suggest possible improvements.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.03.003}, issn = {0169-2070}, keywords = {Shrinkage estimators; Seasonal factors; X-11 seasonal adjustment method, othercom} } @ARTICLE{LS09, author = {A. Lahiani and O. Scaillet}, title = {Testing for threshold effect in ARFIMA models: Application to US unemployment rate data}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {418-428}, number = {2}, abstract = {Macroeconomic time series often involve a threshold effect in their ARMA representation, and exhibit long memory features. In this paper we introduce a new class of threshold ARFIMA models to account for this. The threshold effect is introduced in the autoregressive and/or fractional integration parameters, and can be tested for using LM tests. Monte Carlo experiments show the desirable finite sample size and the power of the test with an exact maximum likelihood estimator of the long memory parameter. Simulations also show that a model selection strategy is available to discriminate between the competing threshold ARFIMA models. The methodology is applied to US unemployment rate data, where we find a significant threshold effect in the ARFIMA representation, and a better forecasting performance relative to TAR and symmetric ARFIMA models.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2009.01.004}, issn = {0169-2070}, keywords = {Threshold ARFIMA, LM test, Asymmetric time series, regart} } @ARTICLE{Lahiri09, author = {Kajal Lahiri}, title = {Comments on 'Forecasting economic and financial variables with global VARs'}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {689 - 692}, number = {4}, note = {Special section: Decision making and planning under low levels of predictability}, doi = {10.1016/j.ijforecast.2009.05.006}, issn = {0169-2070} } @ARTICLE{Lahiri92, author = {Kajal Lahiri}, title = {Leading economic indicators: A leading iindicator of inflation based on interest rates}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {649-650}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90083-L}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Lahiri90, author = {Kajal Lahiri}, title = {Optimal control, expectations and uncertainty : Sean Holly and Andrew Hughes Hallett, (Cambridge University Press, Cambridge, UK, 1989) pp. 244}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {255-256}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90012-Z}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{LM10, author = {Kajal Lahiri and Gael Martin}, title = {Bayesian forecasting in economics}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {211 - 215}, number = {2}, note = {Special Issue: Bayesian Forecasting in Economics}, doi = {10.1016/j.ijforecast.2010.02.003}, issn = {0169-2070} } @ARTICLE{LS10, author = {Kajal Lahiri and Xuguang Sheng}, title = {Learning and heterogeneity in GDP and inflation forecasts}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {265 - 292}, number = {2}, note = {Special Issue: Bayesian Forecasting in Economics}, doi = {10.1016/j.ijforecast.2009.12.009}, issn = {0169-2070}, keywords = {Bayesian learning, Public information,Panel data,Forecast disagreement,Forecast horizon,Forecast efficiency,GDP,Inflation targeting} } @ARTICLE{LT87, author = {Kajal Lahiri and Christie Teigland}, title = {On the normality of probability distributions of inflation and GNP forecasts}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {269-279}, number = {2}, abstract = {This study analyzes mean probability distributions reported by ASA-NBER forecasters on two macroeconomic variables, GNP and the GNP implicit price deflator. In the derivation of expectations, a critical assertion has been that the aggregate average expectation can be regarded as coming from a normal distribution. We find that, in fact, this assumption should be rejected in favor of distributions which are more peaked and skewed. For IPD, they are mostly positively skewed, and for nominal GNP the reverse is true. We then show that a non-central scaled t-distribution fit the empirical distributions remarkably well. The practice of using the degree of consensus across a group of predictions as a measure of a typical forecasters' uncertainty about the prediction is called to question.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90008-2}, issn = {0169-2070}, keywords = {Macroeconomic forecasting, Distribution of forecasts, Non-normality, Non-central scaled t-distribution, regart} } @ARTICLE{Lai91, author = {T. H. Lai}, title = {Time series analysis univariate and multivariate methods : William W.S. Wei, (Addison-Wesley, Reading, MA, 1990)}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {389-390}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90015-N}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{LV02, author = {J. -P. Lam and M. R. Veall}, title = {Bootstrap prediction intervals for single period regression forecasts}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {125-130}, number = {1}, abstract = {The prediction interval formula for the forecast of a regression-dependent variable conditional upon known future values for the independent variables and normally distributed disturbances is commonly taught and used. This pedagogic note illustrates how badly this standard formula can fail when the disturbances are nonnormal, with the degree of failure increasing rather than decreasing with sample size. A small Monte Carlo experiment emphasizes the point for some asymmetric distributions and some seldom-tried symmetric distributions and shows how poorly the standard formula performs, even in large samples. Bootstrap prediction intervals based on either the percentile principle or the percentile-t principle perform substantially better.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00112-1}, issn = {0169-2070}, keywords = {Prediction error with non-normal disturbances, Percentile bootstrap, Percentile-t bootstrap, regart} } @ARTICLE{Land88, author = {Kenneth Land}, title = {Methods for national population forecasting: A review : Land, Kenneth, Journal of the American Statistical Association 81 (1986) 888-901}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {631-632}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90149-5}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Landsberg85, author = {Hans H. Landsberg}, title = {An assessment of Simon's methodology of natural resource forecasting}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {103-105}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(85)90014-7}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{LD89, author = {Wayne R. Landsman and Aswath Damodaran}, title = {A comparison of quarterly earnings per share forecasts using James-Stein and unconditional least squares parameter estimators}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {491-500}, number = {4}, abstract = {This study provides evidence which suggests that the use of the James-Stein shrinkage estimator of parameters from multiple ARIMA models of quarterly earnings per share results in forecasts of earnings with lower mean square percentage forecast error (MSPFE) than can be obtained using the unconditional least square estimator. Moreover, this reduction in MSPFE is available at low marginal computational cost.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90004-6}, issn = {0169-2070}, keywords = {Earnings per share (EPS) forecasts, James-Stein (J-S) estimator, regart} } @ARTICLE{Lanne07, author = {Markku Lanne}, title = {Forecasting realized exchange rate volatility by decomposition}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {307-320}, number = {2}, abstract = {We compare forecasts of the realized volatility of the exchange rate returns of the Euro against the U.S. Dollar and the Japanese Yen obtained both directly and through decomposition. Decomposing the realized volatility into its continuous sample path and jump components, and modeling and forecasting them separately instead of directly forecasting the realized volatility, is shown to lead to improved out-of-sample forecasts. Moreover, the gains in forecast accuracy are fairly robust with respect to the details of the decomposition, but the jump component should probably not be defined too tightly.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.02.001}, issn = {0169-2070}, keywords = {Realized volatility, Mixture of distributions, Aggregation, Jumps, Exchange rates, regart} } @ARTICLE{Law04, author = {Rob Law}, title = {Leading indicator tourism forecasts,: Kulendran, Nada and Stephen F. Witt, Tourism Management, 2003, 24, 503-510. Corresponding author: J.Nash@surrey.ac.uk}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {733-734}, number = {4}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2003.12.003}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Lawrence03, author = {K. D. Lawrence}, title = {The impact of forecasting model selection on the value of information sharing in a supply chain: Zhao, X., J. Xie, and Leung, J. (Eds.), European Journal of Operational Research, 2002, Vol. 142, pp. 321-344.}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {765-765}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00060-8}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Lawrence93, author = {Kenneth D. Lawrence}, title = {Market research using forecasting in business : Peter Clifton, Hai Nguyen and Susan Nutt, 1991, (Butterworth and Heinemann, Stoneham, MA), 294 pp., paperback, US\$29.95, ISBN 0-7506-0153-1.}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {579-580}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90083-Y}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{04b, author = {Michael Lawrence}, title = {Commentary on: A new approach to forecasting intermittent demand for service parts inventories}, journal = {International Journal of Forecasting}, year = {2004}, volume = {20}, pages = {389-390}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00034-7}, issn = {0169-2070}, key = {tagkey2004389}, keywords = {editorial} } @ARTICLE{Lawrence00, author = {Michael Lawrence}, title = {What does it take to achieve adoption in sales forecasting?}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {147-148}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00032-1}, issn = {0169-2070}, keywords = {editorial} } @ARTICLE{Lawrence99, author = {Michael Lawrence}, title = {Book Review}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {342-343}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00009-6}, issn = {0169-2070}, key = {tagkey1999342}, keywords = {bookrev} } @ARTICLE{Lawrence94, author = {Michael Lawrence}, title = {The rise and fall of strategic planning : Henry Mintzberg, 1994, (Prentice Hall, Englewood Cliffs, NJ, USA), 458 pp., �19.95 ISBN 0137818246}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {645-646}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90036-1}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Lawrence93a, author = {Michael Lawrence}, title = {The M2-competition: Some personal views}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {25-26}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90047-Q}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{LGO+06, author = {Michael Lawrence and Paul Goodwin and Marcus O'Connor and Dilek{\"O}nkal}, title = {Judgmental forecasting: A review of progress over the last 25 years}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {493-518}, number = {3}, abstract = {The past 25 years has seen phenomenal growth of interest in judgemental approaches to forecasting and a significant change of attitude on the part of researchers to the role of judgement. While previously judgement was thought to be the enemy of accuracy, today judgement is recognised as an indispensable component of forecasting and much research attention has been directed at understanding and improving its use. Human judgement can be demonstrated to provide a significant benefit to forecasting accuracy but it can also be subject to many biases. Much of the research has been directed at understanding and managing these strengths and weaknesses. An indication of the explosion of research interest in this area can be gauged by the fact that over 200 studies are referenced in this review.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.03.007}, issn = {0169-2070}, keywords = {Judgement, Forecasting, Review, Improving judgement forecasts, Probability forecasts, Domain knowledge, Prediction intervals, regart} } @ARTICLE{LO05, author = {Michael Lawrence and Marcus O'Connor}, title = {Judgmental forecasting in the presence of loss functions}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {3-14}, number = {1}, abstract = {Many practicing forecasters operate in an environment where there are either implicit or explicit biases favouring under- or over-forecasting. For example some marketing executives may be rewarded for exceeding the forecast which operates, in effect, as a sales target. In other organizations, the forecast may be set high to encourage greater effort. Previous studies show that most practical forecasts are indeed significantly biased, with some organizations biased one way and some the other. One of the possible reasons for this bias is the rational reaction to asymmetry in the loss function faced by the forecaster. This paper reports a laboratory study on the reactions of forecasters to different types of loss functions. The subjects were given a cover story that they were the production manager in an organization with an asymmetric loss function. This was diagrammatically displayed, and operationalised in the experiment by paying money bonuses to the subjects. Two shapes of loss function were used differing in their kindness, and two directions of bias, one favouring over- and one under-forecasting. The results show that the subjects responded appropriately to the differing directions of the asymmetry and to the differing kindness shapes of the loss functions. These results support the field research showing that forecast biases can be the result of deliberate and rational decision making behaviour on the part of the forecasters.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.02.003}, issn = {0169-2070}, keywords = {Judgmental forecasting, Loss functions, Asymmetric loss, Tolerance zone, regart} } @ARTICLE{LO00, author = {Michael Lawrence and Marcus O'Connor}, title = {Sales forecasting updates: how good are they in practice?}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {369-382}, number = {3}, abstract = {Both theory and the opinions of practising forecasters expect that, as the lead time before an event reduces, updates to the forecast will efficiently incorporate more recent information and so be more accurate and less biased. However, in practice, it may be anticipated that there will be some inefficiency due to excessive anchoring on the last forecast, leading to positive correlations in forecast revisions. This study tests these expectations using a large sample drawn from judgementally estimated sales forecasts from 10 manufacturing organisations. The results suggest that forecast accuracy does not improve as much as anticipated as the lead time reduces, and that the forecast revisions display negative not positive first-order autocorrelations. The inefficiency of the fixed-event forecast revisions does not appear to be related to the rolling-event forecast accuracy. This is in distinction to the one period ahead forecast errors where efficiency was strongly related to forecast accuracy performance. Some reasons for the findings are discussed.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00059-5}, issn = {0169-2070}, keywords = {Forecast updates, Fixed-event forecasts, Sales forecasting accuracy, regart} } @ARTICLE{LO92, author = {Michael Lawrence and Marcus O'Connor}, title = {Exploring judgemental forecasting}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {15-26}, number = {1}, abstract = {Most of our knowledge of the accuracy or goodness of human judgement has been gained from studies carried out in a setting of multivariate non-serially correlated cues. This is not representative of the task of time series forecasting where there is typically a single series of serially correlated cues. As judgement is widely used in this setting, this study seeks to investigate the extent to which some of the widely documented judgemental biases and heuristics apply to time series forecasting. The research design varied the series presentation, series length and the type of series to investigate the influences of presentation scale, length of series, recency and anchoring and adjustment in estimating a judgemental forecast. The time series used were modelled from a stationary ARMA process. The study found that while scale did not influence accuracy, series length and the most recent segment slope did influence it. Subjects' forecasts could be modelled as exponential smoothing or anchoring and adjustment, where the anchor point corresponded to the long term average of the stationary series.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90004-S}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{LEO85, author = {Michael J. Lawrence and Robert H. Edmundson and Marcus J. O'Connor}, title = {An examination of the accuracy of judgmental extrapolation of time series}, journal = {International Journal of Forecasting}, year = {1985}, volume = {1}, pages = {25-35}, number = {1}, abstract = {Recent studies of forecasting accuracy have neglected to include the most commonly used technique of judgmental extrapolative forecasting, perhaps reflecting the widely held view that this approach is inferior to statistical techniques. This paper reports on a study of the accuracy of judgmental extrapolation of time series. Three alternative judgmental forecasting approaches were used and their accuracy compared to that of the quantitatively-based forecasts developed by experts in the course of a competition. The paper concludes that judgmental extrapolation is on average no less accurate than statistical forecasting and, in a number of subgroups of the time series, was the most accurate. Further, one of the judgmental approaches appeared to provide more robust forecasts than the statistical techniques.}, doi = {http://dx.doi.org/10.1016/S0169-2070(85)80068-6}, issn = {0169-2070}, keywords = {Judgmental forecasting, Forecasting accuracy, Extrapolation, regart} } @ARTICLE{Lawton06, author = {Richard Lawton}, title = {Discussion}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {677-677}, number = {4}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.07.003}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Lawton03, author = {Richard Lawton}, title = {Statistics in the 21st Century,: Edited by Adrian E. Rafferty, Martin A. Tanner and Martin T. Wells, Monographs on Statistics and Applied Probability, Chapman and Hall/CRC (2002), Paperback, �24.99, \$39.95, ISBN 1-58488-272-7.}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {534-535}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00020-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Lawton01, author = {Richard Lawton}, title = {Time Series Analysis and its Applications: Robert H. Shumway and David S. Stoffer; Springer Texts in Statistics; 2000, Springer-Verlag; �55, US\$79.95, ISBN 0-387-98950-1}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {299-301}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00083-8}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Lawton98, author = {Richard Lawton}, title = {How should additive Holt-Winters estimates be corrected?}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {393-403}, number = {3}, abstract = {An important by-product of a good forecasting procedure is to gain some understanding of how the series behaves. This paper looks primarily at how well the Additive Holt-Winters method succeeds in this task. Additive Holt-Winters is a widely used technique which has had some success in forecasting competitions. The paper shows that the basic form of the method does not give good estimates for the level and seasonal features of a time series. The paper then looks at various ways of correcting the estimates, looks at their performance and recommends a particular approach.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00040-5}, issn = {0169-2070}, keywords = {Seasonality, Holt-Winters, Renormalisation, regart} } @ARTICLE{Layton98, author = {Allan P. Layton}, title = {A further test of the influence of leading indicators on the probability of US business cycle phase shifts}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {63-70}, number = {1}, abstract = {In earlier work Filardo (1994) used a variable transition probability Markov regime-switching model to investigate the usefulness of a number of leading indicators in anticipating phase changes in the business cycle. Filardo used Industrial Production as a proxy for the business cycle and found the leading indicators were not only statistically significant determinants of the transition probabilities but that they also substantially improved the dating of the business cycle. However, Industrial Production is a very narrow proxy for the business cycle and represents a relatively small and decreasing component of economic activity. Here a broader, more comprehensive proxy for the business cycle is employed to test the usefulness of leading indicators in forecasting the likelihood of future business cycle phase shifts. Specifically, the Economic Cycle Research Institute's (ECRI) coincident composite index is employed as a summative measure of the business cycle. Then, following Diebold et al. (1994), the transition probability parameters are allowed to vary. In particular, the ECRI leading and long leading indexes are used as putative determinants of these transition probabilities.}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00051-4}, issn = {0169-2070}, keywords = {Business cycles, Leading indicators, Markov-models, regart} } @ARTICLE{Layton96, author = {Allan P. Layton}, title = {Dating and predicting phase changes in the U.S. business cycle}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {417-428}, number = {3}, abstract = {Hamilton's quasi-Bayesian, Markovian, regime-switching model is applied to monthly growth rates of leading, long-leading and coincident indexes of the US economy. A simple rule applied to regime probabilities for each data point of the coincident index produces a phase chronology which exactly reproduces the turning points of the index produced by the Bry-Boschan method. The chronology is also therefore almost identical to the officially recognised US business cycle chronology. To gain some insight into how quickly the last eight business cycle turning points could have been identified, the dating algorithm is applied to the data sequentially, augmenting the sample period one monthly observation at a time. The regime-switching model is also applied to the leading and long-leading indexes. The application of a simple rule to the regime probabilities is found to result in a very reliable advance signalling system for the US business cycle.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00663-X}, issn = {0169-2070}, keywords = {Bayesian, Markov, Regime-switching, Business cycle, Coincident index, Leading index, regart} } @ARTICLE{LDZ86, author = {Allan P. Layton and Lorraine V. Defris and Ben Zehnwirth}, title = {An international comparison of economic leading indicators of telecommunications traffic}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {413-425}, number = {4}, abstract = {The purpose of this paper is to draw international comparisons of the coherence of indexes of leading economic indicators with selected telecommunications traffic series. The traffic series under consideration are total Australian telephone outgoing and U.S. outgoing telephone to Australia with data consisting of monthly observations spanning the period 1970-1983. The response of the telecommunications traffic to these indexes is analysed using cross-spectral techniques. Additionally, a dynamic regression forecasting model for Australian traffic is estimated using the Australian index as an explanatory variable. In comparison to an ARIMA model for the telecommunications data this model reduces post-sample MSE by 19 percent.}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90088-9}, issn = {0169-2070}, keywords = {Australian telecommunications, Cross-spectral analysis, Dynamic regression forecasting model, Leading indicators, regart} } @ARTICLE{LK01, author = {Allan P. Layton and Masaki Katsuura}, title = {Comparison of regime switching, probit and logit models in dating and forecasting US business cycles}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {403-417}, number = {3}, abstract = {Three non-linear model specifications are tested for their efficacy in dating and forecasting US business cycles, viz. a probit specification, a logit specification -- both binomial and multinomial alternatives -- and a markov, regime-switching specification. The models employ leading indicators compiled by the Economic Cycle Research Institute as putative explanators. They are tested within sample to determine their relative abilities to produce a business cycle chronology similar to the official NBER chronology. They are also tested in a post-sample context to test their relative abilities in anticipating future turning points with the result that the regime-switching model with time-varying transition probabilities performs the best.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00096-6}, issn = {0169-2070}, keywords = {Business cycles, Regime switching model: logit and probit model, Quadratic probability score, regart} } @ARTICLE{LeBaron03, author = {Blake LeBaron}, title = {Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, \$33, �22.95, [euro]36.18, Hardback, ISBN 0-521-770416-0, \$90, �60, [euro]89.03.}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {751-752}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00054-2}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{LS01, author = {James H. Lebovic and Lee Sigelman}, title = {The forecasting accuracy and determinants of football rankings}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {105-120}, number = {1}, abstract = {Numerous models vie to explain the extent to which and the manner in which people use new information to reconsider existing beliefs. We analyze week-to-week changes in the rankings of big time college football teams to test predictions based on these models. We test logistic regression models of whether Top 25 teams moved up a certain number of places in the rankings following victories, using data on weekly movement in the AP rankings, 1985-95. The predictors in these models are indicators of inertia and constraint, rank elevators, and the passage of time. Lower-ranked teams move up faster after a victory than do higher-ranked teams, but moving up in the rankings after a victory is an incremental process -- much more incremental than moving down after a loss. All the focal predictors in the models perform as expected in influencing a team's chances of moving up following a win. That is, the odds of moving up are greater: the fewer prior losses a team has suffered; the lower the team's rank before the victory; if an opening has occurred higher in the rankings; if the victory is over a ranked opponent, and especially a higher-ranked opponent; and if the standing of opponents played earlier in the season has risen. These results are most compatible with a model that combines what are often treated as contradictory ideas -- that people are `naive scientists' or `intuitive statisticians', on the one hand, and that they are extremely conservative information processors, on the other.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00064-9}, issn = {0169-2070}, keywords = {Information-processing, Football rankings, regart} } @ARTICLE{Ledolter07, author = {Johannes Ledolter}, title = {Increase in mean square forecast error when omitting a needed covariate}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {147-152}, number = {1}, abstract = {Mean square errors of ex-post and ex-ante forecasts from transfer function (regression) models are compared with mean square forecast errors of univariate time series models that ignore the covariate. We show that forecasts from the univariate ARMA models are never better, and are usually worse, than the forecasts from the transfer function model.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.10.001}, issn = {0169-2070}, keywords = {ARMA model, Ex-ante forecast, Ex-post forecast, Transfer function model, regart} } @ARTICLE{Ledolter89, author = {Johannes Ledolter}, title = {The effect of additive outliers on the forecasts from ARIMA models}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {231-240}, number = {2}, abstract = {Assume that a time series of length n = T+k includes an additive outlier at time T and suppose this fact is ignored in the estimation of the coefficients and the calculation of the forecasts. In this paper we derive the resulting increase in the mean square of the l-step-ahead forecast error. We show that this increase is due to (i) a carry-over effect of the outlier on the forecast, and (ii) a bias in the estimates of the autoregressive and moving average coefficients. Looking at several special cases we find that this increase is rather small provided that the outlier occurs not too close to the forecast origin. In such cases the point forecasts are largely unaffected. Our conclusion concerning the width of the prediction intervals is different, however. Since outliers in a time series inflate the estimate of the innovation variance, we find that the estimated prediction intervals are quite sensitive to additive outliers.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90090-3}, issn = {0169-2070}, keywords = {ARIMA model, Forecasting, Mean square forecast error, Outliers, Prediction intervals, Time series, regart} } @ARTICLE{LeeSigelmana99, author = {Lee Sigelmana, Roy Batchelor, Herman Stekler}, title = {Editorial (Political forecasting)}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {125-126}, number = {2}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00058-2}, issn = {0169-2070}, key = {tagkey1999125}, keywords = {editorial} } @ARTICLE{LS97, author = {Hahn Shik Lee and Pierre L. Siklos}, title = {The role of seasonality in economic time series reinterpreting money-output causality in U.S. data}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {381-391}, number = {3}, abstract = {While empirical evidence on the relationship between money and income has mainly been presented using seasonally adjusted data, seasonally unadjusted data are used in this paper to examine the time series behaviour of money, real GNP and industrial production, at both the seasonal and zero frequencies, based on tests of cointegration and seasonal cointegration. Two important conclusions are reached in the paper. First, although the univariate time series properties of M1 and real GNP appear to be very similar at both the seasonal and zero frequencies, seasonal comovements of M1 and real GNP turn out to be different from long-run comovements. Second, when seasonally unadjusted data are used, there appears to be no long-run relationship between money (M1 or M2) and output in the sense that the null of no cointegration cannot be rejected. Moreover, there is evidence of some feedback from output to money so that money is not necessarily exogenous. Consequently, as we might lose a possibly important chain of causation from money to income by ignoring the information concerning seasonal fluctuations, this paper provides further evidence that researchers should use raw data instead of seasonally adjusted data for inference and forecasting purposes.}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00025-3}, issn = {0169-2070}, keywords = {Seasonality, Causality, Seasonal cointegration, Error-correction model, regart} } @ARTICLE{LS02, author = {Junsoo Lee and Mark C. Strazicich}, title = {ITSM 2000 Professional Version 6.0, developed by Peter J. Brockwell and Richard A. Davis, B\&D Enterprises, Inc., Copyright 1999. The Student Version is included in Introduction to Time Series and Forecasting, 1996, Springer-Verlag New York Inc. (ISBN: 0387947191). The Professional Version is obtainable from pbrockwell@compuserve.com. Web Page of the author: http://www.stat.colostate.edu/~pjbrock/}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {455-460}, number = {3}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00138-8}, issn = {0169-2070}, keywords = {prodrev} } @ARTICLE{Lee88, author = {Jack C. Lee}, title = {Nested Rotterdam model : Applications to marketing research with special reference to telecommunications demand}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {193-206}, number = {2}, abstract = {The Rotterdam model is a highly structured econometric model that can be used to model and forecast market demand in a system-wide manner. Since marketing researchers are primarily interested in a subset of consumer goods, the application of the Rotterdam model to marketing research requires the assumption of some separability conditions such as preference independence or block independence on the utility function. If the consumer's preferences for consumer goods can be characterized by a utility function which is the sum of individual utility functions for all goods, it is called preference independence. Similarly, block independence refers to the situation where the consumer's preferences for consumer goods can he expressed by a utility function which is additive in the groups of goods. Under these separability assumptions, it is possible to restrict attention to a subset of goods. Such a model is called a conditional form of the Rotterdam model. This is in contrast to the unconditional form of the Rotterdam model which deals with the consumption of all goods and services as a whole. This paper discusses an embedding procedure that has been developed for linking the conditional and unconditional forms of the Rotterdam model and several statistical issues associated with use of the model. The resulting unconditional model can be used for forecasting the market demand at a future time. The data required for estimating the Rotterdam model are usually a time series of goods and services being studied.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90077-5}, issn = {0169-2070}, keywords = {Conditional form, Embedding, Marketing research, Rotterdam models, Telecommunications demand, Unconditional form, regart} } @ARTICLE{LES97, author = {Myung-Soo Lee and B. Elango and Steven P. Schnaars}, title = {The accuracy of the Conference Board's buying plans index: A comparison of judgmental vs. extrapolation forecasting methods}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {127-135}, number = {1}, abstract = {This paper compares the Conference Board's buying intentions for consumer durable goods with forecasts constructed using simple time-series extrapolation over 177 months. The results show that simple time-series extrapolations provide more accurate forecasts than the judgmental approach. Very little support is found for using buying intentions as a forecasting tool for predicting the sales of durable goods.}, doi = {http://dx.doi.org/10.1016/S0169-2070(96)00711-X}, issn = {0169-2070}, keywords = {Buying intentions, Forecasting, Naive approach, Six-month moving average, Mean absolute percentage error (MAPE), regart} } @ARTICLE{Lee93, author = {Ronald D. Lee}, title = {Modeling and forecasting the time series of US fertility: Age distribution, range, and ultimate level}, journal = {International Journal of Forecasting}, year = {1993}, volume = {9}, pages = {187-202}, number = {2}, abstract = {To develop high-low bounds for population projections, traditional demographic forecasts assume fertility is always high or always low. Such bounds are related to bounds on average annual fertility up to year t rather than to individual year bounds in time series forecasts, and so the autocorrelation of time series forecast errors is important in practical applications. This paper develops methods for using time series methods to make constrained long term forecasts of fertility. Specifically, age-time variations in fertility are modeled with a single time-varying parameter, or fertility index; upper and lower bounds on the total fertility rate are imposed by forecasting an inverse logistic transform of the fertility index; the long run level of the fertility forecast is also constrained to equal a prespecified level. The principal interest is in the variance and the autocorrelation structure of the forecast errors. Based on these for the USA we conclude: (1) the probability interval for average fertility up to time t begins to contract after about 50 years, but only very slightly: (2) the probability interval for average fertility up to year 2065 is about three-fifths as wide as that for single year fertility in 2065, but is still far wider than the band for official forecasts; (3) realizations of the simple ARMA (1,0,1) forecast model exhibit long fluctuations something like actual fertility in industrial nations; (4) the model of fertility age patterns fits poorly at older ages, but may be adequate for present purposes.}, doi = {http://dx.doi.org/10.1016/0169-2070(93)90004-7}, issn = {0169-2070}, keywords = {Fertility, Demographic, Projection, Forecasts, Constrained, regart} } @ARTICLE{Lee92, author = {Ronald D. Lee}, title = {Stochastic demographic forecasting}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {315-327}, number = {3}, abstract = {This paper describes a particular approach to stochastic population forecasting, which is implemented for the USA through 2065. Statistical time series methods are combined with demographic models to produce plausible long run forecasts of vital rates, with probability distributions. The resulting mortality forecasts imply gains in future life expectancy that are roughly twice as large as those forecast by the Office of the Social Security Actuary. The method for forecasting fertility is useful mainly for providing estimates of the variance and autocorrelation in fertility forecast errors, and not for making stand-alone point forecasts. The forecasts of the probability distributions of the vital rates can then be used in a stochastic Leslie matrix to produce stochastic population forecasts. These provide probability distributions for the quantities forecast, reflecting lower bound estimates of uncertainty. Resulting stochastic forecasts of the elderly population, elderly dependency ratios, and payroll tax rates for health, education and pensions are presented.}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90050-J}, issn = {0169-2070}, keywords = {Population, Forecasting, Aging, Dependency, Mortality, Fertility, Projection, Social Security, regart} } @ARTICLE{LM07, author = {Sang-Hyop Lee and Andrew Mason}, title = {Who gains from the demographic dividend? Forecasting income by age}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {603-619}, number = {4}, abstract = {Changes in the population age structure are known to influence the total income per person, but little is known about whether the changes are equally shared across the population or are concentrated on particular age groups and/or birth cohorts. The answer to this question has potentially important implications for income inequality, human capital investment, and fertility decision-making. We propose a new model of intergenerational transfers which distinguishes between the effects of changes in population structure and the effects of changes in family age structure. Using age-specific data from annual income and expenditure surveys of Taiwan between 1978 and 1998, we show that changes in age structure have had a very favorable effect on Taiwan's income growth. The gains are not equally shared by all age groups, however. Children and young adults have benefited the most, while the elderly have benefited the least. The population and family age structures have independent effects on per capita income; the effect of the population age structure is most important. Generational differences in per capita income are closely related to intergenerational differences in earnings, suggesting only a weak form of altruism. Finally, we predict that, on average, population aging will adversely influence the per capita income growth in Taiwan in the coming decades.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.07.004}, issn = {0169-2070}, keywords = {Demographic dividend, Intergenerational transfers, Income forecasts, regart} } @ARTICLE{LGF+07, author = {Wing Yee Lee and Paul Goodwin and Robert Fildes and Konstantinos Nikolopoulos and Michael Lawrence}, title = {Providing support for the use of analogies in demand forecasting tasks}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {377-390}, number = {3}, abstract = {Management judgment is widely used to adjust statistical forecasts in order to take into account special events, such as sales promotions. There is evidence that forecasters often use information from analogous events from the past to help to estimate the effects of an anticipated special event. Unaided forecasters using such an approach may suffer from errors in recall, difficulties in making judgments about similarity, and difficulties in adapting the information from analogous events to match the attributes of the anticipated event. We conducted an experiment to investigate whether a forecasting support system (FSS), which provided users with guidance on similarity judgments and support for adaptation judgments, could lead to more accurate forecasts of the effects of sales promotions. The experiment suggested that a simple, easily implemented form of adaptation support could significantly improve forecast accuracy under some conditions. The support is also likely to be acceptable to potential users.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.02.006}, issn = {0169-2070}, keywords = {Judgmental forecasting, Forecasting by analogy, Forecasting support system, Sales promotions, regart} } @ARTICLE{Leffrancois89, author = {Pierre Leffran{\c c}ois}, title = {Allowing for asymmetry in forecast errors : Results from a Monte-Carlo study}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {99-110}, number = {1}, abstract = {The paper presents an heuristic to estimate the distribution of future values in a forecasting process. The heuristic is based on the split-normal density used as a proxy for the expected distribution of future values. The approach is novel in that it allows for asymmetric non-stationary distributions of future values. Results of Monte-Carlo tests in a context of inventory control indicate that the heuristic may significantly reduce costs.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90067-8}, issn = {0169-2070}, keywords = {Forecasting, Statistics, Inventory systems, regart} } @ARTICLE{Lefrancois90, author = {Pierre Lefran{\c c}ois}, title = {Comments by C. Chatfield}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {561-561}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90036-B}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Lefrancois89, author = {Pierre Lefran{\c c}ois}, title = {Confidence intervals for non-stationary forecast errors : Some empirical results for the series in the M-competition}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {553-557}, number = {4}, abstract = {This paper investigates the effectiveness of generating confidence intervals from an adaptive estimate of the variance of forecast errors. The investigation is performed on the sample of 1001 series first analyzed by Makridakis et al. It is shown that the accuracy of the intervals is improved and that the type of series and the forecasting model used are among the factors explaining the accuracy of forecast intervals.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90011-3}, issn = {0169-2070}, keywords = {Forecasting, Time-series, regart} } @ARTICLE{LZH10, author = {Christoph Leitner and Achim Zeileis and Kurt Hornik}, title = {Forecasting sports tournaments by ratings of (prob)abilities: A comparison for the EURO 2008}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {471 - 481}, number = {3}, note = {Sports Forecasting}, doi = {10.1016/j.ijforecast.2009.10.001}, issn = {0169-2070}, keywords = {Sports forecasting, EURO 2008,Bookmakers odds,Elo rating,Abilities} } @ARTICLE{Leitz92, author = {Scott Leitz}, title = {Future demographic trends in Europe and North America: What can we assume today?.Lutz Wolfgang, Editor, Academic Press, Inc., San Diego, CA (1991), p. 585 including index, \$107.50. ISBN 0-12-460445-5.}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {541-542}, number = {3}, note = {Population Forecasting}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90063-F}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{LK10, author = {Bertrand Lemennicier and Honorine Katir-Lescieux}, title = {Testing the accuracy of the Downs' spatial voter model on forecasting the winners of the French parliamentary elections in May-June 2007}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {32 - 41}, number = {1}, note = {Special Section: European Election Forecasting}, doi = {10.1016/j.ijforecast.2009.03.002}, issn = {0169-2070}, keywords = {Median voter, Elections,Two round ballot,Electoral system,Party competition,Forecasting errors,Elections forecasts} } @ARTICLE{LCD08, author = {Aur{\'e}lie Lemmens and Christophe Croux and Marnik G. Dekimpe}, title = {Measuring and testing Granger causality over the spectrum: An application to European production expectation surveys}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {414-431}, number = {3}, abstract = {Decomposing Granger causality over the spectrum allows us to disentangle potentially different Granger causality relationships over different frequencies. This may yield new and complementary insights compared to traditional versions of Granger causality. In this paper, we compare two existing approaches in the frequency domain, proposed originally by Pierce [Pierce, D. A. (1979). R-squared measures for time series. Journal of the American Statistical Association, 74, 901-910] and Geweke [Geweke, J. (1982). Measurement of linear dependence and feedback between multiple time series. Journal of the American Statistical Association, 77, 304-324], and introduce a new testing procedure for the Pierce spectral Granger causality measure. To provide insights into the relative performance of this test, we study its power properties by means of Monte Carlo simulations. In addition, we apply the methodology in the context of the predictive value of the European production expectation surveys. This predictive content is found to vary widely with the frequency considered, illustrating the usefulness of not restricting oneself to a single overall test statistic.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.03.004}, issn = {0169-2070}, keywords = {Business surveys, Granger causality, Government forecasting, Production expectations, Spectral analysis, regart} } @ARTICLE{LCD05, author = {Aur{\'e}lie Lemmens and Christophe Croux and Marnik G. Dekimpe}, title = {On the predictive content of production surveys: A pan-European study}, journal = {International Journal of Forecasting}, year = {2005}, volume = {21}, pages = {363-375}, number = {2}, abstract = {For over 40 years, Business Tendency Surveys have been collected in multiple member states of the European Union. Previous research has studied the predictive content of the expectation variables included in those surveys through bivariate, within-country, Granger-causality tests. These tests have resulted in mixed conclusions. We extend previous research in various ways, as we (i) explicitly allow for cross-country influences, and (ii) do so using both bivariate and multivariate Granger-causality tests. Specifically, the multivariate El Himdi-Roy (HR) test is adapted to jointly test the forecasting value of multiple production expectation series, to assess whether part of this joint effect is indeed due to cross-country influences, and to determine which countries' expectation series have the most clout in predicting the production levels in the other member countries, or have the highest receptivity, in that their production levels are Granger caused by the other countries' expectations.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2004.10.004}, issn = {0169-2070}, keywords = {Business surveys, Cross-correlations, Production expectations, Granger causality, regart} } @ARTICLE{Leone87, author = {Robert P. Leone}, title = {Forecasting the effect of an environmental change on market performance: An intervention time-series approach}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {463-478}, number = {3-4}, abstract = {Forecasting the effects of changes in advertising or pricing strategies on a company's sales or market share is an important task faced by marketing managers. This paper applies a time series approach, intervention analysis, to several marketing policy applications illustrating the flexibility and value of the method for testing hypotheses and providing forecasts. Empirical evidence is presented for two different marketing situations, one that involves a change in advertising and another that involves offering price specials.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90043-4}, issn = {0169-2070}, keywords = {Analysis, Box-Jenkins analysis, Intervention, regart} } @ARTICLE{Lesage90, author = {James P. Lesage}, title = {System-theoretic methods in economic modelling I : Stefan Mittnik, ed., (Pergamon Press, Oxford, 1989), pp. 184, \$39.50}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {566-568}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90040-I}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Lesage89, author = {James P. Lesage}, title = {Incorporating regional wage relations in local forecasting models with a Bayesian prior}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {37-47}, number = {1}, abstract = {A Bayesian vector autoregressive technique is used to incorporate intercity wage relations into a local model of wage formation. This technique requires that a simple prior distribution be specified for the likely values of the coefficients for the variables that represent the intercity relations. The Bayesian model provides out-of-sample forecasts superior to those from both unconstrained vector autoregressive and univariate autoregressive models. This suggests that intercity linkages provide useful information that can be effectively incorporated in local forecasting models.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90062-9}, issn = {0169-2070}, keywords = {Accuracy, Empirical study, Forecasting evaluation, Multivariate time-series methods, regart} } @ARTICLE{LM91, author = {James P. LeSage and Michael Magura}, title = {Using interindustry input-output relations as a Bayesian prior in employment forecasting models}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {231-238}, number = {2}, abstract = {This paper presents the results of using input-output tables as a source of Bayesian prior information in a national employment forecasting model. A Bayesian vector autoregressive (BVAR) estimation technique is used to incorporate the interindustry input-output table relationships into the labor market forecasting model. This technique requires that a simple translation of the direct use coefficients from the input-output table be used as prior weighting elements to depict the interindustry relations. The Bayesian model provides out-of-sample forecasts superior to those from unconstrained vector autoregressive, univariate autoregressive, a block recursive bvar model and a naive BVAR model based on the Minnesota random walk prior. This suggests that interindustry input-output table linkages provide useful information that can be effectively incorporated into labor market forecasting models.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90056-2}, issn = {0169-2070}, keywords = {Empirical study, Forecasting evaluation, Ridge regression, Vector autoregression, regart} } @ARTICLE{LSJ10, author = {Stefan Lessmann and Ming-Chien Sung and Johnnie E.V. Johnson}, title = {Alternative methods of predicting competitive events: An application in horserace betting markets}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {518 - 536}, number = {3}, note = {Sports Forecasting}, doi = {10.1016/j.ijforecast.2009.12.013}, issn = {0169-2070}, keywords = {Probability forecasting, Classification,Random forest,Sports forecasting} } @ARTICLE{Levenbach00, author = {Hans Levenbach}, title = {The Practice of Data Analysis: Essays in Honor of John W. Tukey: D.R. Brillinger, L.T. Fernholz and S. Morgenthaler (Eds.); Princeton, NJ: Princeton University Press, 1997, 337pp.; ISBN 0-691-05782-6}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {130-132}, number = {1}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00042-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Levenbach00a, author = {Hans Levenbach}, title = {The PP (Autocast) System}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {536-536}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00088-1}, issn = {0169-2070}, keywords = {prodrev} } @ARTICLE{Lewis86, author = {Colin D. Lewis}, title = {Advanced service parts inventory control : Robert Goodell Brown, (Materials Management Systems Inc., Norwich, VT, 1982) \$42.50, pp. 436}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {122-122}, number = {1}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90039-7}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{LJ10, author = {Michael S. Lewis-Beck and Bruno Jerome}, title = {European election forecasting: An introduction}, journal = {International Journal of Forecasting}, year = {2010}, volume = {26}, pages = {9 - 10}, number = {1}, note = {Special Section: European Election Forecasting}, doi = {10.1016/j.ijforecast.2009.08.008}, issn = {0169-2070} } @ARTICLE{LT08, author = {Michael S. Lewis-Beck and Charles Tien}, title = {Forecasting presidential elections: When to change the model}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {227-236}, number = {2}, abstract = {Here, we address the issue of forecasting from statistical models, and how they might be improved. Our real-world example is the forecasting of US presidential elections. First, we ask whether a model should be changed. To illustrate problems and opportunities, we examine the forecasting history of different models, in particular our own, which has tried to foresee presidential selection since 1984. We apply what we learn to the question of whether our Jobs model, which offered an accurate ex ante point estimate for 2004, should be changed for 2008. We conclude there is room for judicious, theory-driven adjustment, but also raise a caution about inadvertent curve-fitting. Some evidence is offered that simple core models, based on strong theory, may perform almost as well as more stretched models.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.02.008}, issn = {0169-2070}, keywords = {Adjusting forecasts, Econometric models, Evaluating forecasts, Model selection, Regression, regart} } @ARTICLE{LT99, author = {Michael S. Lewis-Beck and Charles Tien}, title = {Voters as forecasters: a micromodel of election prediction}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {175-184}, number = {2}, abstract = {Much presidential election forecasting research employs macromodels based on national economic and political fluctuations. Micromodels based on surveys of individuals exist, but they are almost entirely pre-election explorations of vote intention. What has been neglected are micromodels derived from vote expectations. We show, by analysis of the American National Election Surveys 1956-1996, that voters themselves can forecast who will win the presidential election. We go on to explain some of sources of this forecasting ability, and to evaluate its precision. Voter forecasting models emerge as a useful alterative to current approaches.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00063-6}, issn = {0169-2070}, keywords = {Election forecasting, Election surveys, Presidential elections, Presidential polls, regart} } @ARTICLE{LSW06, author = {Gang Li and Haiyan Song and Stephen F. Witt}, title = {Time varying parameter and fixed parameter linear AIDS: An application to tourism demand forecasting}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {57-71}, number = {1}, abstract = {This study develops time varying parameter (TVP) linear almost ideal demand system (LAIDS) models in both long-run (LR) static and short-run error correction (EC) forms. The superiority of TVP-LAIDS models over the original static version and the fixed-parameter EC counterparts is examined in an empirical study of modelling and forecasting the demand for tourism in Western European destinations by UK residents. Both the long-run static and the short-run EC-LAIDS models are estimated using the Kalman filter algorithm. The evolution of demand elasticities over time is illustrated using the Kalman filter estimation results. The remarkably improved forecasting performance of the TVP-LAIDS relative to the fixed-parameter LAIDS is illustrated by a one-year- to four-years-ahead forecasting performance assessment. Both the unrestricted TVP-LR-LAIDS and TVP-EC-LAIDS outperform their fixed-parameter counterparts in the overall evaluation of demand level forecasts, and the TVP-EC-LAIDS is also ranked ahead of most other competitors when demand changes are concerned.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2005.03.006}, issn = {0169-2070}, keywords = {Linear almost ideal demand system (LAIDS), Error correction, Time varying parameter (TVP), Kalman filter, Tourism demand, Forecasting, regart} } @ARTICLE{Li06, author = {Jing Li}, title = {Testing Granger Causality in the presence of threshold effects}, journal = {International Journal of Forecasting}, year = {2006}, volume = {22}, pages = {771-780}, number = {4}, abstract = {This paper proposes a Granger Causality test allowing for threshold effects. The proposed test can be conducted on the basis of the threshold autoregressive distributed lag model or the augmented logistic smooth transition autoregressive model. The proposed test is applied to the U.S. civilian unemployment rate, and it is shown that real investment, real GDP and real interest rate are helpful for improving the in-sample fit of unemployment.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2006.01.003}, issn = {0169-2070}, keywords = {Granger Causality, Threshold autoregressive model, Smooth transition autoregressive model, Time series, Unemployment, regart} } @ARTICLE{Lichtman08, author = {Allan J. Lichtman}, title = {The keys to the white house: An index forecast for 2008}, journal = {International Journal of Forecasting}, year = {2008}, volume = {24}, pages = {301-309}, number = {2}, abstract = {The Keys to the White House are an index-based prediction system that retrospectively accounts for the popular-vote winners of every American presidential election from 1860 to 1980, and prospectively forecast the winners of every presidential election from 1984 through 2004 well ahead of time. The Keys give specificity to the theory that presidential election results turn primarily on the performance of the party controlling the White House. The Keys include no polling data and consider a much wider range of performance indicators than economic concerns. Already, the Keys are lining up for 2008, showing how changes in the structure of politics will produce a Democratic victory, in a dramatic reversal from 2004. The Keys also suggest that candidates need not follow the empty scripted campaigns of the recent past, but should instead be liberated to offer forthright discussions of the issues and ideas that will shape America's future.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.02.004}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{LO96, author = {Joa Sang Lim and Marcus O'Connor}, title = {Judgmental forecasting with time series and causal information}, journal = {International Journal of Forecasting}, year = {1996}, volume = {12}, pages = {139-153}, number = {1}, abstract = {Although contextual or causal information has been emphasised in forecasting, few empirical studies have been conducted on this issue in controlled conditions. This study investigates the way people adjust statistical forecasts in the light of contextual/causal information. Results indicate that people appeared to reasonably incorporate extra-model causal information to make up for what the statistical time-series model lacks. As expected, the effectiveness of causal adjustment was contingent upon the reliability of the causal information. While adjustment of forecasts using causal information of low reliability did not lead to significant improvement, adjustment using highly reliable causal information produced forecasts more accurate than the best statistical models. However, people relied too heavily on their initial forecasts compared with the optimal model. Moreover, people did not seem to learn over time to modify this conservative behaviour. People also seemed to prefer statistical forecasts in favour of causal information.}, doi = {http://dx.doi.org/10.1016/0169-2070(95)00635-4}, issn = {0169-2070}, keywords = {Judgemental adjustment, Causal information, regart} } @ARTICLE{Lin89, author = {Winston T. Lin}, title = {Modeling and forecasting hospital patient movements: Univariate and multiple time series approaches}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {195-208}, number = {2}, abstract = {The purpose of this paper is two-fold: it recognizes the importance of modeling and forecasting as a future-oriented decision-making process in the field of health care by proposing to model and forecast monthly patient movements in individual hospitals by means of the Box-Jenkins univariate and Tiao-Box multiple time series approaches; and it attempts to determine the choice between the univariate method and the multivariate approach in the case of hospital patient data. The forecasting performance of the resulting models is evaluated against the Holt-Winters exponential smoothing model using the mean squared error, mean absolute deviation, and mean absolute percentage error, for five non-overlapping time periods. The test results suggest that the proper choice of time series techniques to be applied to hospital admissions and discharges has an important and direct bearing on the reliability of forecasting results. Therefore, the practical implications and usefulness of time series techniques and models are discussed.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90087-3}, issn = {0169-2070}, keywords = {Hospital patient movements - admissions, discharges, and gains, Univariate ARIMA and vector ARMA processes, Holt-Winters exponential smoothing, Unidirectional causality, Relationships - feedback and contemporaneous, regart} } @ARTICLE{Lin86, author = {Winston T. Lin}, title = {Modeling and forecasting U.S. public construction}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {319-331}, number = {3}, abstract = {This paper extends Lin's flexible accelerator model of dynamic investment behavior of U.S. public construction by relaxing two of the underlying basic assumptions: (1) the coefficient of adjustment is allowed to vary with the level of government expenditure and (2) the regression coefficients are treated as randomly changing over time rather than being viewed as fixed. The new models afford a better explanation of the behavior of U.S. public construction. Importantly, the forecasting ability of the variable-coefficient-of-adjustment model is tested for the three-year period beyond the sample period and compared to both the Lin's original and ARIMA models. It is found that this new model gives better forecasts of public construction for ten quarters ahead. On the basis of the chi-square test of model stability and the mean squared error, it is concluded that the model with variable adjustment coefficients is a better abstraction of economic reality and improves forecasting accuracy.}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90051-8}, issn = {0169-2070}, keywords = {Theory - investment, Variable coefficient of adjustment, Regression - random coefficients, Evaluation, Comparative methods, ARIMA, Causal, Ex ante, regart} } @ARTICLE{LM07a, author = {Thomas Lindh and Bo Malmberg}, title = {Demographically based global income forecasts up to the year 2050}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {553-567}, number = {4}, abstract = {Demographic projections of age structure provide the best information available on long-term future human resources and demand. Fairly robust correlations between age structure, GDP and GDP growth have been discovered in current data. In this paper we use these two facts to study the forecasting properties of demographically based models. Extending the forecasts to 2050 suggests that, due to projected fertility decreases, the poor countries of today will start to catch up with developed economies, in which the growth process will stagnate due to the growth of the elderly population. This remains the case whether or not indications of positive longevity effects are taken into account.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.07.005}, issn = {0169-2070}, keywords = {Long-term forecasting, Panel data, Life expectancy, Catch-up, Age effects, regart} } @ARTICLE{Linstone87, author = {Harold A. Linstone}, title = {Contrasts: Soviet and American thinkers discuss the future : Wiktor Osiatynski, (Macmillan Co., New York, NY, 1984) pp. 208, \$19.95}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {333-334}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90016-1}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Lippens87, author = {Robert E. Lippens}, title = {Multimaturity efficient market hypotheses : Sorting out rejections in international interest and exchange rate markets}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {149-158}, number = {1}, abstract = {This paper is concerned with econometric testing of multimaturity efficient market hypotheses for Canadian and Japanese foreign exchange and Eurocurrency deposit rates. A multimaturity efficient market hypothesis is developed and it is demonstrated that for the null hypothesis of multimarket efficiency to hold in the forward exhange market, rational expectations of the term structure of the matching Eurocurrency deposit rates must hold.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90084-7}, issn = {0169-2070}, keywords = {Multimaturity efficient market, Source of rejection, regart} } @ARTICLE{LM97, author = {Francesco Lisi and Alfredo Medio}, title = {Is a random walk the best exchange rate predictor?}, journal = {International Journal of Forecasting}, year = {1997}, volume = {13}, pages = {255-267}, number = {2}, abstract = {The paper discusses short-term exchange rate prediction, using the random walk hypothesis (RWH) as a benchmark to compare performances. After surveying some recent results in this field, the authors suggest a filtering-prediction method inspired by recent developments in nonlinear dynamical systems theory. The filtering of presumably noisy data is realized by means of a technique derived from Singular Spectrum Analysis (SSA) conveniently adapted to a nonlinear dynamics context. In particular, the authors develop a multichannel version of SSA. Filtered data are then used to perform an out-of-sample, short-term prediction, by means of a nonlinear (locally linear) method. This method is applied to exchange rate series of the major currencies and the predictions thus obtained are shown to outperform neatly those derived from the RWH. Finally, the application of a test recently developed by Mizrach confirms the statistical significance of the results.}, doi = {http://dx.doi.org/10.1016/S0169-2070(97)00001-0}, issn = {0169-2070}, keywords = {Time series, Nonlinearity, Forecasting comparison, Exchange rates, regart} } @ARTICLE{LJ07, author = {Dandan Liu and Dennis W. Jansen}, title = {Macroeconomic forecasting using structural factor analysis}, journal = {International Journal of Forecasting}, year = {2007}, volume = {23}, pages = {655-677}, number = {4}, abstract = {The use of a small number of underlying factors to summarize the information from a much larger set of information variables is one of the new frontiers in forecasting. In prior work, the estimated factors have not usually had a structural interpretation and the factors have not been chosen on a theoretical basis. In this paper we propose several variants of a general structural factor forecasting model, and use these to forecast certain key macroeconomic variables. We make the choice of factors more structurally meaningful by estimating factors from subsets of information variables, where these variables can be assigned to subsets on the basis of economic theory. We compare the forecasting performance of the structural factor forecasting model with that of a univariate AR model, a standard VAR model, and some non-structural factor forecasting models. The results suggest that our structural factor forecasting model performs significantly better in forecasting real activity variables, especially at short horizons.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2007.03.001}, issn = {0169-2070}, keywords = {Macroeconomic forecasting, Forecast evaluation, Principal components, Time series, Econometric models, regart} } @ARTICLE{LB03, author = {Hua Liu and Donald E. Brown}, title = {Criminal incident prediction using a point-pattern-based density model}, journal = {International Journal of Forecasting}, year = {2003}, volume = {19}, pages = {603-622}, number = {4}, abstract = {Law enforcement agencies need crime forecasts to support their tactical operations; namely, predicted crime locations for next week based on data from the previous week. Current practice simply assumes that spatial clusters of crimes or hotspots observed in the previous week will persist to the next week. This paper introduces a multivariate prediction model for hot spots that relates the features in an area to the predicted occurrence of crimes through the preference structure of criminals. We use a point-pattern-based transition density model for space-time event prediction that relies on criminal preference discovery as observed in the features chosen for past crimes. The resultant model outperforms the current practices, as demonstrated statistically by an application to breaking and entering incidents in Richmond, VA.}, doi = {http://dx.doi.org/10.1016/S0169-2070(03)00094-3}, issn = {0169-2070}, keywords = {Point-pattern methods, Crime forecasting, Spatial transition density model, Hot spot prediction model, regart} } @ARTICLE{Liu86, author = {Lon-Mu Liu}, title = {Identification of time series models in the presence of calendar variation}, journal = {International Journal of Forecasting}, year = {1986}, volume = {2}, pages = {357-372}, number = {3}, abstract = {Monthly time series data are frequently subject to calendar variation, such as trading day and holiday effects. Calendar variation effects often make model identification difficult, even in single time series analysis. This paper presents a comprehensive and easy-to-use method for the identification of the degree of differencing and appropriate ARMA model in univariate ARIMA modeling when these effects are present. The method can be readily applied to the identification of intervention and transfer function models which may also be subject to calendar variation.}, doi = {http://dx.doi.org/10.1016/0169-2070(86)90054-3}, issn = {0169-2070}, keywords = {ARIMA models, Model identification, Calendar variation, Holiday effects, Trading day effects, regart} } @ARTICLE{LL91, author = {Lon-Mu Liu and Maw-Wen Lin}, title = {Forecasting residential consumption of natural gas using monthly and quarterly time series}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {3-16}, number = {1}, abstract = {This paper studies the consumption of natural gas in Taiwan within the residential sector. In this study, we explore the dynamic relationships among several potentially relevant time series variables and develop appropriate models for forecasting. It is apparent that the temperature of service areas and the price of natural gas are important factors in forecasting the residential consumption of natural gas. Because of the government price control policy, however, we find that the price variable employed in modeling and forecasting of natural gas consumption needs to be used judiciously. Otherwise, inappropriate models and poor forecasts may occur. We also study the inclusion of the price variable using an intervention model and an outlier detection and adjustment method. We find both approaches provide more accurate forecasts and reveal useful information on the dynamics of the controlled variable. Both monthly and quarterly time series of the data are studied. We find it is easier to obtain appropriate models using quarterly data. However, the performance of quarterly models may not be as good as that of monthly models. In this study, however, we find the loss of performance efficiency in using quarterly data is not too great. This is probably due to the fact that the consumption of natural gas is subjected to moving holiday effects and the use of quarterly data may conveniently avoid such systematic disturbances. Both the traditional method and the method for transfer function model identification are employed in this study, we find the method is more efficient and easier to use than the method.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90028-T}, issn = {0169-2070}, keywords = {ARIMA models, Transfer function models, Aggregation, Linear transfer function method, Natural gas consumption, Service area temperature, Natural gas price, regart} } @ARTICLE{LGI94, author = {Te-Ru Liu and Mary E. Gerlow and Scott H. Irwin}, title = {The performance of alternative VAR models in forecasting exchange rates}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {419-433}, number = {3}, abstract = {The purpose of this research is to analyze the forecasting accuracy of full vector autoregressive (FVAR), mixed vector autoregressive (MVAR), and Bayesian vector autoregressive (BVAR) models of the US dollar/yen, US dollar/Canadian dollar, and US dollar/Deutsche mark exchange rates. The VAR specifications are based on a monetary/asset model of exchange rate determination. Out-of-sample results (1983:1-1989:12) indicate that the forecasting performance of restricted VARs (MVARs and BVARs) is substantially better than that of unrestricted VARs (FVARs). Overall, the results show that a monetary/asset model in a VAR representation does have forecasting value for some exchange rates.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90071-X}, issn = {0169-2070}, keywords = {Vector autoregression, Forecasting, Exchange rates, regart} } @ARTICLE{Lobo92, author = {Gerald J. Lobo}, title = {Journal of business research : Analysis and comparison of financial analysts', time series, and combined forecast of annual earnings, 24 (1992) 269-280.}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {649-649}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90082-K}, issn = {0169-2070}, keywords = {othercom} } @ARTICLE{Lobo91, author = {Gerald J. Lobo}, title = {Alternative methods of combining security analysts' and statistical forecasts of annual corporate earnings}, journal = {International Journal of Forecasting}, year = {1991}, volume = {7}, pages = {57-63}, number = {1}, abstract = {This study provides empirical evidence on the accuracy of alternative methods of combining security analysts' and statistical forecasts of annual corporate earnings. Linear cross-sectional least squares regression models with and without constant terms, and constrained and unconstrained forecast weights, are used to form combination forecasts in addition to equally weighted combinations. The empirical analysis indicates that combination forecasts formed using a linear model with no constant term and no constraints on the forecast weights are superior to forecasts generated using the other combination methods. Additionally, improvement in the accuracy of security analysts' earnings forecasts is obtained by combining them with forecasts generated from statistical models fitted to past earnings series.}, doi = {http://dx.doi.org/10.1016/0169-2070(91)90033-R}, issn = {0169-2070}, keywords = {Annual corporate earnings, Forecast combination, Security analysts' earnings forecasts, Statistical earnings forecasts, regart} } @ARTICLE{99i, author = {Marten Lof and Lars-Erik{\"O}nkal}, title = {Book reviews}, journal = {International Journal of Forecasting}, year = {1999}, volume = {15}, pages = {445-446}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(99)00015-1}, issn = {0169-2070}, key = {tagkey1999445}, keywords = {bookrev} } @ARTICLE{Lothian87, author = {James R. Lothian}, title = {The behavior of real exchange rates}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {17-42}, number = {1}, abstract = {Dominating the behavior of real exchange rates for the dollar during the course of the past two and a half decades have been two substantial and for many countries largely offsetting movements. In the years surrounding the breakdown of Bretton Woods most exchange rates fell precipitously and throughout the 1970s remained low. Near the start of the 1980s they began a rise that continued more or less unabated until early 1985. Any explanation of exchange rate behavior over this period, therefore, has to account for both of these movements, not simply the increase in real exchange rates for the dollar in the 1980s that has been the topic of so much discussion in the financial press. The explanation offered in this paper attributes these movements to the two important changes in monetary policy that occurred during these years.}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90076-8}, issn = {0169-2070}, keywords = {Exchange rates, Purchasing power parity, Real exchange rates, Monetary policy, regart} } @ARTICLE{LS09a, author = {Thomas H. Lotze and Galit Shmueli}, title = {How does improved forecasting benefit detection? An application to biosurveillance}, journal = {International Journal of Forecasting}, year = {2009}, volume = {25}, pages = {467 - 483}, number = {3}, note = {Special Section: Time Series Monitoring}, doi = {10.1016/j.ijforecast.2008.11.012}, issn = {0169-2070}, keywords = {Biosurveillance, Control charts,Anomaly detection,Sensitivity,Specificity,Timeliness} } @ARTICLE{Loungani01, author = {Prakash Loungani}, title = {How accurate are private sector forecasts? Cross-country evidence from consensus forecasts of output growth}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {419-432}, number = {3}, abstract = {The performance of Consensus Forecasts of real GDP growth is evaluated for a large number of industrialized and developing countries for the time period 1989 to 1998. Two key findings emerge. First, the record of failure to predict recessions is virtually unblemished. Second, there is a high degree of similarity between private sector growth forecasts and those of international organizations (the IMF, OECD and the World Bank). The paper also provides preliminary evidence on the efficiency of, and extent of bias in, these forecasts.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00098-X}, issn = {0169-2070}, keywords = {Forecast accuracy, Turning points, Forecast comparisons, regart} } @ARTICLE{Loungani90, author = {Prakash Loungani}, title = {Applied time series analysis for business and economic forecasting : Sufi M. Nazem, (Marcel Dekker, Inc., New York and Basel, 1988), pp. 431, \$89.75}, journal = {International Journal of Forecasting}, year = {1990}, volume = {6}, pages = {565-566}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(90)90039-E}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Luchino89, author = {Anatoly I. Luchino}, title = {Forecasting in the social and natural sciences : K.C. Land and S.H. Schneider, eds.,(1987), \$78.00, pp. 381}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {431-432}, number = {3}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90051-4}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{LE00, author = {Jorge Ludlow and Walter Enders}, title = {Estimating non-linear ARMA models using Fourier coefficients}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {333-347}, number = {3}, abstract = {Linear time-series models are often inadequate to capture the presence of asymmetric adjustment and/or conditional volatility. Parametric models of asymmetric adjustment and ARCH-type models necessitate specifying the nature of the non-linear coefficient. If there is little a priori information concerning the actual form of the non-linearity, the estimated model can suffer from a misspecification error. We show that a non-linear time-series can be represented by a deterministic time-dependent coefficient model without first specifying the nature of the non-linearity. The methodology is applied to real GDP and the NYSE Transportation Index.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00048-0}, issn = {0169-2070}, keywords = {Asymmetric adjustment, Fourier approximation, Non-linear model, regart} } @ARTICLE{LF01, author = {M{\aa}rten L{\"o}f and Philip Hans Franses}, title = {On forecasting cointegrated seasonal time series}, journal = {International Journal of Forecasting}, year = {2001}, volume = {17}, pages = {607-621}, number = {4}, abstract = {We analyze periodic and seasonal cointegration models for bivariate quarterly observed time series in an empirical forecasting study. We include both single equation and multiple equation methods for those two classes of models. A VAR model in first differences, with and without cointegration restrictions, and a VAR model in annual differences are also included in the analysis, where they serve as benchmark models. Our empirical results indicate that the VAR model in first differences without cointegration is best if one-step ahead forecasts are considered. For longer forecast horizons however, the VAR model in annual differences is better. When comparing periodic versus seasonal cointegration models, we find that the seasonal cointegration models tend to yield better forecasts. Finally, there is no clear indication that multiple equations methods improve on single equation methods.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00085-1}, issn = {0169-2070}, keywords = {Periodic cointegration, Seasonal cointegration, Forecasting, regart} } @ARTICLE{LL02, author = {M{\aa}rten L{\"o}f and Johan Lyhagen}, title = {Forecasting performance of seasonal cointegration models}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {31-44}, number = {1}, abstract = {Forecasts from two different seasonal cointegration specifications are compared in an empirical forecasting example and in a Monte Carlo study. The two seasonal cointegration specifications are the one proposed by Lee [Journal of Econometrics 54 (1992) 1], with a parameter restriction included at the annual frequency, and the model proposed by Johansen and Schaumburg [Journal of Econometrics 88 (1998) 301], with a general specification for the complex root frequency, respectively. In the empirical forecasting example we also include a standard cointegration model based on first differences and seasonal dummies and analyze the effects of restricting or not restricting seasonal dummies in the seasonal cointegration models. While the Monte Carlo results favor the specification suggested by Johansen and Schaumburg, and definitely so if larger sample sizes are considered, we do not find such clear cut evidence in the empirical example.}, doi = {http://dx.doi.org/10.1016/S0169-2070(01)00105-4}, issn = {0169-2070}, keywords = {Seasonal cointegration, Monte Carlo, regart} } @ARTICLE{Loeffler98, author = {Gunter L{\"o}ffler}, title = {Biases in analyst forecasts: cognitive, strategic or second-best?}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {261-275}, number = {2}, abstract = {Financial analysts act in a complex environment, and the incentives they face may make them issue forecasts which appear to be inconsistent with rational expectations. In order to test several explanations for biases, I analyze a large sample of individual analyst earnings forecasts of German companies. The evidence supports the conjecture that biases in point estimates can be useful for communicating information about forecast precision. When analysts believe their clients misconceive the true precision of the forecast, they distort their estimates in a way which gives them a more appropriate weight in the clients' decision process. Game-theoretical models, on the other hand, which rationalize biases by arguing that they are strategic lack support from the data. Violations of forecast rationality are more likely to stem from underreaction and overconfidence, two types of bias discussed in the psychological literature. Judging from the results of simulations, however, these cognitive errors do not seem to be of major economic significance.}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00032-6}, issn = {0169-2070}, keywords = {Earnings forecasting, Rationality, Forecasting process, Statistical tests, regart} } @ARTICLE{MA94, author = {Donald G. MacGregor and J. Scott Armstrong}, title = {Judgmental decomposition: when does it work?}, journal = {International Journal of Forecasting}, year = {1994}, volume = {10}, pages = {495-506}, number = {4}, abstract = {We hypothesized that multiplicative decomposition would improve accuracy only in certain conditions. In particular, we expected it to help for problems involving extreme and uncertain values. We first reanalyzed results from two published studies. Decomposition improved accuracy for nine problems that involved extreme and uncertain values, but for six problems with target values that were not extreme and uncertain, decomposition was not more accurate. Next, we conducted experiments involving 10 problems with 280 subjects making 1078 estimates. As hypothesized, decomposition improved accuracy when the problem involved the estimation of extreme and uncertain values. Otherwise, decomposition often produced less accurate predictions.}, doi = {http://dx.doi.org/10.1016/0169-2070(94)90018-3}, issn = {0169-2070}, keywords = {Decision Analysis, Estimation, Extreme Values, Forecasting, Multiplicative Decomposition, Uncertainty, regart} } @ARTICLE{MS98, author = {Joseph A. Machak and W. Allen Spivey}, title = {Product Review}, journal = {International Journal of Forecasting}, year = {1998}, volume = {14}, pages = {527-530}, number = {4}, doi = {http://dx.doi.org/10.1016/S0169-2070(98)00049-1}, issn = {0169-2070}, key = {tagkey1998527}, keywords = {prodrev} } @ARTICLE{MSC02, author = {Gary Madden and Scott J. Savage and Grant Coble-Neal}, title = {Forecasting United States-Asia international message telephone service}, journal = {International Journal of Forecasting}, year = {2002}, volume = {18}, pages = {523-543}, number = {4}, abstract = {This study compares forecasts of US international message telephone service (IMTS) traffic using several relative mean squared error statistics. The forecasts are obtained from time-series extrapolation, univariate autoregressive integrated moving average (ARIMA), error correction and vector autoregressive models. The models are estimated on annual US IMTS outgoing traffic data for six US-Asia bilateral markets for the period 1964 to 1993. No single approach provides best forecasts. However, forecast evaluation statistics indicate that econometric models generally outperform the alternatives.}, doi = {http://dx.doi.org/10.1016/S0169-2070(02)00066-3}, issn = {0169-2070}, keywords = {US-Asia telephone service markets, Forecast comparisons, regart} } @ARTICLE{Mady00, author = {M. Tawfik Mady}, title = {Sales forecasting practices of Egyptian public enterprises: survey evidence}, journal = {International Journal of Forecasting}, year = {2000}, volume = {16}, pages = {359-368}, number = {3}, abstract = {The sales forecasting practices of Egyptian public manufacturing companies are reported on and discussed in this paper. The survey revealed the major drawbacks in conducting the forecasting function in Egypt. It shows that few qualified forecasting personnel are available and computers are not used in sales forecasting by most companies. Egyptian companies tend to prepare individual-products forecasts in both monetary and physical units; forecasting is mainly used for the domestic market, and they are reluctant to produce long-term forecasts. Egyptian practitioners are less familiar with the objective than the subjective techniques. The more statistically sophisticated the forecast technique, the lower reported level of usage. Both production planning and budgeting were the major area of use. The lack of top management support and the turbulence change of the company's market were among the top sales forecasting implementation problems in Egypt. Some recommendations are provided to improve forecasting practices in Egyptian industry.}, doi = {http://dx.doi.org/10.1016/S0169-2070(00)00033-9}, issn = {0169-2070}, keywords = {Forecasting practice, Forecasting techniques, Familiarity and usage, Implementation problems, Egyptian manufacturing firms, regart} } @ARTICLE{MW88, author = {Vijay Mahajan and Yoram Wind}, title = {New product forecasting models : Directions for research and implementation}, journal = {International Journal of Forecasting}, year = {1988}, volume = {4}, pages = {341-358}, number = {3}, abstract = {Given the importance of forecasting the performance of new products and services in the marketplace, numerous new product forecasting models have been developed over the years, both in industry and academia. This paper evaluates strengths and weaknesses of these models and outlines a research agenda to enhance their implementation and further development.}, doi = {http://dx.doi.org/10.1016/0169-2070(88)90102-1}, issn = {0169-2070}, keywords = {regart} } @ARTICLE{Mahmoud92, author = {Essam Mahmoud}, title = {Modeling and forecasting demand in tourism: Stephen F. Witt and Christine A. Witt, 1992, (Academic Press, London), pp. 195, ISBN 0-127-60740-4, �35.00}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {643-644}, number = {4}, doi = {http://dx.doi.org/10.1016/0169-2070(92)90078-N}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Mahmoud89, author = {Essam Mahmoud}, title = {Time series forecasting, unified concepts and computer implementation : Bruce L. Bowerman and Richard T. O'Connell, 2nd ed. (Duxbury Press, Boston, 1987) pp. 540}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {282-283}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90098-8}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{Mahmoud89a, author = {Essam Mahmoud}, title = {Combining forecasts: Some managerial issues}, journal = {International Journal of Forecasting}, year = {1989}, volume = {5}, pages = {599-600}, number = {4}, abstract = {The amount of research on combining forecasts is substantial. Yet, relatively little is known about when and how managers combine forecasts. Important managerial issues that require further study include managerial adjustment of quantitative forecasts, the use of expert systems in combining forecasts, and analyses of the costs of combining forecasts.}, doi = {http://dx.doi.org/10.1016/0169-2070(89)90016-2}, issn = {0169-2070}, keywords = {Combining, Accuracy, Forecasting methods, regart} } @ARTICLE{Mahmoud87, author = {Essam Mahmoud}, title = {Time series and forecasting with IDA : Harry V. Roberts, (Scientific Press/McGraw-Hill, New York, NY, 1984)}, journal = {International Journal of Forecasting}, year = {1987}, volume = {3}, pages = {344-345}, number = {2}, doi = {http://dx.doi.org/10.1016/0169-2070(87)90023-9}, issn = {0169-2070}, keywords = {bookrev} } @ARTICLE{MDB+92, author = {Essam Mahmoud and Richard DeRoeck and Robert Brown and Gillian Rice}, title = {Bridging the gap between theory and practice in forecasting}, journal = {International Journal of Forecasting}, year = {1992}, volume = {8}, pages = {251-267}, number = {2}, abstract = {The successful implementation of forecasting in many organizations is hampered by gaps in communication and understanding between forecast preparers and forecast users. Different individuals in organizations may have varying political agendas which impact the forecasting process. Advances in forecasting can be limited because of the gap between forecasting theorists and practitioners. This paper discusses these issues. In particular, it reports on a series of roundtable discussions on the gap between theory and practice which took place at the 1991 International Symposium on Forecasti