Books

J. Scott Armstrong, ed., Principles of Forecasting, 2001. This summary of knowledge from experts and empirical studies provides guidelines that apply to economics, sociology, psychology and other fields. It addresses problems related to finance (How much is this company worth?), marketing (Will a new product be successful?), personnel (How can we identify the best job candidates?), and production (What level of inventories should be kept?). Edited by Professor J. Scott Armstrong of the Wharton School, University of Pennsylvania, this book contains contributions by 40 leading experts in forecasting. The 30 chapters cover all types of forecasting methods: judgmental methods, such as Delphi, role-playing, and intentions studies and quantitative methods, including econometric methods, expert systems, and extrapolation. Some methods, such as conjoint analysis, analogies, and rule-based forecasting, integrate quantitative and judgmental procedures. In each area, the authors identify what is known in the form of "if-then principles" and summarize evidence on these principles. The book also includes the first comprehensive forecasting dictionary. Developed over a four-year period, the book presents knowledge in the form of principles that can be used by researchers and practitioners. To ensure accuracy, the authors reviewed one another's papers. In addition, 122 external reviewers made suggestions.

J. Scott Armstrong, Long-Range Forecasting: From Crystal Ball to Computer, John Wiley and Sons, 1985 (second edition). Designed to answer the question "Which forecasting method is the best to use in a given situation?" this book covers judgmental, extrapolation, and econometric methods. It shows how to combine forecasts and describes how to evaluate and compare different forecasting methods. The conclusions are based on the author's research as well as on over 1050 books and papers on forecasting in economics, sociology, medicine, politics, weather, finance, personnel, marketing, and other areas. The book describes this vast array of literature. This second edition is out of print but is available online in a pdf of the full text.

Michael Bell and Dr. Ulrich Kustes, The Forecasting Report, IT Research, 1999. This report provides detailed knowledge about 43 systems that are used for forecasting.

Robert Fildes, et al., A Bibliography of Business and Economic Forecasting. This work is available in full text and as a searchable index on the Forecasting principles site. The authors provide keywords to describe each study allowing the reader to search for relevant studies not available on other electronic searches. It covers literature from 1965 through 1981 from over 50 journals and a number of books, describing 5,436 papers on forecasting.

Hyndman, R.J., Koehler A.B., Ord, J.K., Snyder, R.D. Forecasting with Exponential Smoothing: The State Space Approach, Springer-Verlag, 2008.. Exponential smoothing methods have been around since the 1950s, and are still the most popular forecasting methods used in business and industry. Recently, exponential smoothing has been revolutionized with the introduction of a complete modeling framework incorporating innovations state sapce models, likelihood calculation, prediction intervals and procedures for model selection. In this book, all of the important results are brought together in a coherent manner with consistent notation. In addition, many new results and extensions are introduced and several application areas are examined in detail.

Hans Levenbach and James P. Cleary, Forecasting: Practice and Process for Demand Management, Thomson/Brooks-Cole, 2006. This text introduces students to the forecasting principles, applications, and methods of demand forecasting. If you are an academic, you can receive a complimentary review copy by visiting online at http://servicedirect.thomsonlearning.com, using the promotion code 6TPST160.

L&C stress applications in their book, present­ing concepts in the context of real examples drawn from their own broad experience as forecasting practitioners in industry, consultants to organizations, and educators. It also addresses the macroeconomic forecasting procedures used by economists as well as the specific product-level forecasting techniques now widely used by corporate sales and operations planning organizations—providing comprehensive coverage of traditional and advanced forecasting tools. Throughout, the authors focus more on training students to perform accurate data analysis than on modeling sophistication. The text incorporates computing throughout the book, featuring Microsoft® Excel applications and including a free copy of anl Excel add-in, called PEERForecaster.xla and data sets on CD.

Spyros Makridakis, Steven Wheelwright and Rob Hyndman, Forecasting: methods and applications, John Wiley and Sons, 1998 (third edition). This book, sometimes known as the "Bible of forecasting", is the best-selling introductory text in business forecasting. It covers the full range of major forecasting methods and provides a complete description of their essential characteristics including the steps needed for their practical application. The book avoids getting bogged down in the theoretical details that are not essential to understanding how the various methods work, and provides a systematic comparison of the advantages and drawbacks of various methods so that the most appropriate method can be selected for each forecasting situation. It covers a comprehensive set of forecasting horizons (from the immediate to the long term) and approaches to forecasting (time series, explanatory, judgemental, mixed).

J. Holton Wilson and Barry Keating, Business Forecasting, Richard D. Irwin, Inc., 1984 (second edition). Using realistic problem sets with actual data, this applied forecasting book covers standard techniques such as exponential smoothing, regression, and ARIMA models, as well as some newer procedures such as bootstrapping and combinatorial forecasting. Special attention is paid to model selection criteria. The book includes techniques actually used by Fortune 500 companies and presents sidebar examples from several companies. 101 CitiBase data sets are included with the book as well as a sampler version of the SORITEC statistical package (on included diskette).

John and Mary Nash, Practical Forecasting for Managers, Arnold Publisher, 2001. This book is an introductory guide to business forecasting for managers and MBA students. Details about the book, as well as datasets, exercises, and forecasting links, can be found on the supporting website. It's also possible to purchase copies through the website. Inspection copies of the book are available to academics who teach relevant courses with 15 or more students. For inspection copies, please email , with your name, college address, and course details. (Please note: Inspection copies are sent to lecturers for 28 days. After this period, the lecturer may adopt the copy as a core text, return the text with no obligation, or purchase the text for personal use.)

Graham Nown, The World's Worst Predictions, London: Arrow, 1985.

George Wright and Paul Goodwin, eds., Forecasting with Judgment, John Wiley and Sons, 1998. This collection of ten papers brings together recent research on the role of judgment in forecasting and methods for improving its application.

• "Judgment: Its Role and Value for Strategy," Spyros Makridakis and Anil Gaba
• "Scenario Planning: Scaffolding Disorganized ideas about the Future," Kees van der Heijden
• "Judgmental Forecasting and the Use of Available Information", Marcus O'Connor and Michael Lawrence
• "Enhancing Judgmental Sales Forecasting: The Role of Laboratory Research," Paul Goodwin
• "Heuristics and Biases in Judgmental Forecasting," Fergus Bolger and Nigel Harvey
• "Financial Forecasting with Judgment," Dilek Ínkal-Atay
• "Reasoning with Category Knowledge in Probability Forecasting: Typicality and Perceived Variability Effects," Glenn J. Browne and Shawn P. Curley
• "The Use of Structured Groups to Improve Judgmental Forecasting," Gene Rowe
• "How Bad is Human Judgment?" Peter Ayton
• "Integration of Statistical Methods and Judgment for Time Series Forecasting: Principles from Empirical Research," J. Scott Armstrong and Fred Collopy