% This file was created with JabRef 2.4.2. % Encoding: UTF8 @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{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 = {In Press, Corrected Proof}, pages = {-}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2009.02.004}, issn = {0169-2070}, keywords = {bookrev} } @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 = {In Press, Corrected Proof}, pages = {-}, abstract = {This article develops a new portfolio selection method using Bayesian theory. The proposed method accounts for the uncertainties in estimation parameters and the model specification itself, both of which are ignored by the standard mean-variance method. The critical issue in constructing an appropriate predictive distribution for asset returns is evaluating the goodness of individual factors and models. This problem is investigated from a statistical point of view; we propose using the Bayesian predictive information criterion. Two Bayesian methods and the standard mean-variance method are compared through Monte Carlo simulations and in a real financial data set. The Bayesian methods perform very well compared to the standard mean-variance method.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2009.01.005}, issn = {0169-2070}, keywords = {Bayesian methods, Decision making, Finance, Model selection, regart} } @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{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{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{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 = {In Press, Corrected Proof}, pages = {-}, abstract = {System-based cointegration methods have become popular tools for economic analysis and forecasting. However, the identification of structural relationships is often problematic. Using a theory-directed sequential reduction method suggested by Hall, Henry and Greenslade [Hall, S. G., Henry, S., & Greenslade, J. (2002). On the identification of cointegrated systems in small samples: A modelling strategy with an application to UK wages and prices. Journal of Economic Dynamics and Control, 26, 1517-1537], we estimate a vector error correction model of Hawaii tourism, where both demand and supply-side influences are important. We identify reasonable long-run equilibrium relationships, and Diebold-Mariano tests for forecast accuracy demonstrate satisfactory forecasting performance.}, doi = {http://dx.doi.org/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, regart} } @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{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 = {In Press, Corrected Proof}, pages = {-}, abstract = {To forecast at several, say h, periods into the future, a modeller faces a choice between iterating one-step-ahead forecasts (the IMS technique), or directly modeling the relationship between observations separated by an h-period interval and using it for forecasting (DMS forecasting). It is known that structural breaks, unit-root non-stationarity and residual autocorrelation may improve DMS accuracy in finite samples, all of which occur when modelling the South African GDP over the period 1965-2000. This paper analyzes the forecasting properties of 779 multivariate and univariate models that combine different techniques of robust forecasting. We find strong evidence supporting the use of DMS and intercept correction, and attribute their superior forecasting performance to their robustness in the presence of breaks.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2008.12.004}, issn = {0169-2070}, keywords = {Multi-step forecasting, Intercept correction, Structural breaks, regart} } @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{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{CGG08, 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 = {2008}, volume = {In Press, Corrected Proof}, pages = {-}, abstract = {Time series monitoring methods, such as the Brown and Trigg methods, have the purpose of detecting pattern breaks (or signals) in time series data reliably and in a timely fashion. Traditionally, researchers have used the average run length (ARL) statistic on results from generated signal occurrences in simulated time series data to calibrate and evaluate these methods, with a focus on timeliness of signal detection. This paper investigates the receiver operating characteristic (ROC) framework, well-known in the diagnostic decision making literature, as an alternative to ARL analysis for time series monitoring methods. ROC analysis traditionally uses real data to address the inherent tradeoff in signal detection between the true and false positive rates when varying control limits. We illustrate ROC analysis using time series data on crime at the patrol district level in two cities, and use the concept of Pareto frontier ROC curves and reverse functions for methods such as Brown's and Trigg's that have parameters affecting signal-detection performance. We compare the Brown and Trigg methods to three benchmark methods, including one commonly used in practice. The Brown and Trigg methods collapse to the same simple method on the Pareto frontier and dominate the benchmark methods under most conditions. The worst method is the one commonly used in practice.}, doi = {http://dx.doi.org/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, regart} } @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{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{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{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{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{EC09, 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 = {2009}, volume = {In Press, Corrected Proof}, pages = {-}, abstract = {Judgmental adjustments of statistical forecasts are widely used for improving forecast accuracy. Despite the overall effectiveness of this method, it may allow forecasters to introduce biases in statistical forecasts when they judgmentally adjust them. This paper considers three types of bias: (1) optimism bias, (2) anchoring bias, and (3) overreaction bias. We explore the effects of particular individual differences, specifically personality, motivational orientation, and work locus of control, on forecasting biases. The results indicate that a forecaster's personality and motivational orientation have significant effects on forecasting biases, whereas work locus of control has no effect on forecasting biases. Our analysis further indicates that experience, work locus of control and motivational orientation drive a forecaster's willingness to judgmentally adjust a statistical forecast.}, doi = {http://dx.doi.org/10.1016/j.ijforecast.2009.02.005}, issn = {0169-2070}, keywords = {Judgmental forecasting, Adjusting forecasts, Sales forecasting, Motivation, Personality, Locus of control, Cognition, regart} } @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{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{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 p