1. Introduction, J. Scott Armstrong, Wharton School, University of Pennsylvania, pp. 1-12.

2. Role-Playing

   • "Role Playing: A Method to Forecast Decisions," J. Scott Armstrong, Wharton School, University of Pennsylvania, pp. 15-30 – Abstract

3. Intentions

   • "Methods for Forecasting from Intentions Data," Vicki G. Morwitz, Stern School, New York University, pp. 33-56 – Abstract

4. Expert Opinions

   • "Improving Judgmental Forecasts," Nigel Harvey, Department of Psychology, University College London, pp. 59-80 – Abstract

   • "Improving Reliability of Judgmental Forecasts," Thomas R. Stewart, Center for Policy Research, State University of New York at Albany, pp. 81-106 – Abstract – Corrections (PDF)

   • "Decomposition for Judgmental Forecasting and Estimation," Donald G. MacGregor, Decision Research, Eugene, Oregon, pp. 107-123 – Abstract

   • "Expert Opinions in Forecasting: Role of the Delphi Technique," Gene Rowe, Institute of Food Research, and George Wright, University of Strathclyde, pp. 125-144 – Abstract

5. Conjoint Analysis

   • "Forecasting with Conjoint Analysis," Dick R. Wittink, Yale University and Trond Bergestuen, Johnson Graduate School of Management, Cornell University, pp. 147-167 – Abstract

6. Judgmental Bootstrapping

   • "Judgmental Bootstrapping: Inferring Experts' Rules for Forecasting," J. Scott Armstrong, Wharton School, University of Pennsylvania, pp. 171-192 – Abstract

7. Analogies

   • "Forecasting Analogous Time Series," George T. Duncan, Wilpen L. Gorr, and Janusz Szczypula, School of Public Policy, Carnegie Mellon University, pp. 195-213 – Abstract

8. Extrapolation

   • "Extrapolation of Time Series and Cross-Sectional Data," J. Scott Armstrong, The Wharton School, University of Pennsylvania, pp. 217-243 – Abstract

   • "Neural Networks for Time Series Forecasting" William Remus, College of Business Administration, U. of Hawaii and Marcus O'Connor, Univ. of New South Wales, pp. 245-256 – Abstract

9. Rule-based Forecasting

   • "Rule-based Forecasting: Using Judgment in Time-Series Extrapolation," J. Scott Armstrong, The Wharton School, University of Pennsylvania, Monica Adya, Dept. of Management, DePaul University, and Fred Collopy, The Weatherhead School, Case Western Reserve University, pp. 259-282 – Abstract

10. Expert Systems

    • "Expert Systems for Forecasting," Fred Collopy, The Weatherhead School, Case Western Reserve University, J. Scott Armstrong, The Wharton School, University of Pennsylvania and Monica Adya, Dept. of Management, DePaul University, pp. 285-300 – Abstract

11. Econometric Models

    • "Econometric Forecasting," P. Geoffrey Allen, Department of Resource Economics, University of Massachusetts and Robert Fildes, The Management School, Lancaster University, pp. 303-362 – Abstract and see Appendix below

12. Selecting Methods

    • "Selecting Forecasting Methods," J. Scott Armstrong, The Wharton School, University of Pennsylvania, pp. 365-386 – Abstract

13. Integrating, Adjusting, and Combining Procedures

    • "Judgmental Time Series Forecasting Using Domain Knowledge," Richard Webby, Marcus O'Connor, and Michael Lawrence, University of South Wales, pp. 389-403 – Abstract

    • "Judgmental Adjustments of Statistical Forecasts," Nada R. Sanders, Department of Management Science, Wright State University and Larry P. Ritzman, Operations and Strategic Management, Boston College, pp. 405-416 – Abstract

    • "Combining Forecasts," J. Scott Armstrong, The Wharton School, University of Pennsylvania, pp. 417-439 – Abstract

14. Evaluating Methods

    • "Evaluating Forecasting Methods," J. Scott Armstrong, The Wharton School, University of Pennsylvania, pp. 443-472 – Abstract

15. Assessing Uncertainty

    • "Prediction Intervals for Time Series," Chris Chatfield, Department of Mathematical Sciences, University of Bath, pp. 475-494 – Abstract

    • "Overconfidence in Judgmental Forecasting," Hal R. Arkes, Department of Psychology, Ohio State University, pp. 495-515 – Abstract

16. Gaining Acceptance

    • "Scenarios and Acceptance of Forecasts," W. Larry Gregory and Anne Duran, Department of Psychology, New Mexico State University, pp. 519-541 – Abstract

17. Monitoring Forecasts

    • "Learning from Experience: Coping with Hindsight Bias and Ambiguity," Baruch Fischhoff, Department of Social and Decision Sciences, Carnegie-Mellon University, pp. 543-554 – Abstract

18. Applications of Principles

    • "Population Forecasting," Dennis A. Ahlburg, University of Minnesota, and Department of Social Statistics, University of Southampton, pp. 557-575 – Abstract

    • "Forecasting the Diffusion of Innovations: Implications for Time Series Extrapolation," Nigel Meade and Towhidul Islam, The Management School, Imperial College, London, pp. 577-595 – Abstract

    • "Econometric Models for Forecasting Market Share," Roderick J. Brodie and Peter Danaher, Department of Marketing, University of Auckland, V. Kumar, University of Houston, and Peter Leeflang, Gröningen University, pp. 597-611 – Abstract

    • "Forecasting Trial Sales of New Consumer Packaged Goods," Peter S. Fader, The Wharton School, University of Pennsylvania and Bruce Hardie, London Business School, pp. 613-630 – Abstract

19. Diffusion of Principles

    • "Diffusion of Forecasting Principles through Books," James E. Cox, Jr. and David G. Loomis, Illinois State University, pp. 633-649 – Abstract; List of Books

    • "Diffusion of Forecasting Principles: An Assessment of Forecasting Software Programs," Leonard J. Tashman, University of Vermont, and Jim Hoover, U.S. Navy, pp. 651-676 – Abstract – Tables (PDF – published by permission of Kluwer Academic Publishers) – Corrections to Table 7 (PDF)

20. Summary

    • "Standards and Practices for Forecasting," J. Scott Armstrong, The Wharton School, University of Pennsylvania, pp. 679-738 – Abstract

Appendix

Supporting Materials:
Tables on which econometric methods work best, by Geoff Allen

Reviewers,
People Index
Subject Index (PDF, 49kb)

The Forecasting Dictionary