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Value of Expertise For Forecasting Decisions in Conflicts

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  • Kesten C. Green
  • J. Scott Armstrong

Abstract

In important conflicts, people typically rely on experts' judgments to predict the decisions that adversaries will make. We compared the accuracy of 106 expert and 169 novice forecasts for eight real conflicts. The forecasts of experts using unaided judgment were little better than those of novices, and neither were much better than simply guessing. The forecasts of experts with more experience were no more accurate than those with less. Speculating that consideration of the relative frequency of decisions might improve accuracy, we obtained 89 forecasts from novices instructed to assume there were 100 similar situations and to ascribe frequencies to decisions. Their forecasts were no more accurate than 96 forecasts from novices asked to pick the most likely decision. We conclude that expert judgment should not be used for predicting decisions that people will make in conflicts. Their use might lead decision makers to overlook other, more useful, approaches.

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Bibliographic Info

Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 27/04.

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Length: 9 pages
Date of creation: Dec 2004
Date of revision:
Handle: RePEc:msh:ebswps:2004-27

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Related research

Keywords: Bad faith; Framing; Hindsight bias; Methods; Politics.;

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References

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  1. Scott Armstrong, J. & Brodie, Roderick J. & McIntyre, Shelby H., 1987. "Forecasting methods for marketing: Review of empirical research," International Journal of Forecasting, Elsevier, vol. 3(3-4), pages 355-376.
  2. J. S. Armstrong & R. Brodie & S. McIntyre, 2005. "Forecasting Methods for Marketing:* Review of Empirical Research," General Economics and Teaching 0502023, EconWPA.
  3. JS Armstrong, 2004. "The Seer-Sucker Theory: The Value of Experts in Forecasting," General Economics and Teaching 0412009, EconWPA.
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Cited by:
  1. Kesten C. Green & J. Scott Armstrong, 2004. "Structured analogies for forecasting," Monash Econometrics and Business Statistics Working Papers 17/04, Monash University, Department of Econometrics and Business Statistics.
  2. Green, Kesten C. & Armstrong, J. Scott & Graefe, Andreas, 2007. "Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared," MPRA Paper 4663, University Library of Munich, Germany.
  3. Green, Kesten C., 2005. "Game theory, simulated interaction, and unaided judgement for forecasting decisions in conflicts: Further evidence," International Journal of Forecasting, Elsevier, vol. 21(3), pages 463-472.
  4. J. Scott Armstrong & Kesten C. Green, 2005. "Demand Forecasting: Evidence-based Methods," Monash Econometrics and Business Statistics Working Papers 24/05, Monash University, Department of Econometrics and Business Statistics.
  5. Green, Kesten C., 2008. "Assessing probabilistic forecasts about particular situations," MPRA Paper 8836, University Library of Munich, Germany.
  6. Green, Kesten C. & Armstrong, J. Scott, 2011. "Role thinking: Standing in other people's shoes to forecast decisions in conflicts," International Journal of Forecasting, Elsevier, vol. 27(1), pages 69-80, January.

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