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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.

Suggested Citation

  • Kesten C. Green & J. Scott Armstrong, 2004. "Value of Expertise For Forecasting Decisions in Conflicts," Monash Econometrics and Business Statistics Working Papers 27/04, Monash University, Department of Econometrics and Business Statistics.
  • Handle: RePEc:msh:ebswps:2004-27
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    File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2004/wp27-04.pdf
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    References listed on IDEAS

    as
    1. J. S. Armstrong & R. Brodie & S. McIntyre, 2005. "Forecasting Methods for Marketing:* Review of Empirical Research," General Economics and Teaching 0502023, University Library of Munich, Germany.
    2. JS Armstrong, 2004. "The Seer-Sucker Theory: The Value of Experts in Forecasting," General Economics and Teaching 0412009, University Library of Munich, Germany.
    3. 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.
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    Cited by:

    1. Green, Kesten C. & Armstrong, J. Scott, 2007. "Structured analogies for forecasting," International Journal of Forecasting, Elsevier, vol. 23(3), pages 365-376.
    2. Kesten Green & J. Scott Armstrong & Andreas Graefe, 2007. "Methods to Elicit Forecasts from Groups: Delphi and Prediction Markets Compared," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 8, pages 17-20, Fall.
    3. 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.
    4. Nikolopoulos, Konstantinos & Litsa, Akrivi & Petropoulos, Fotios & Bougioukos, Vasileios & Khammash, Marwan, 2015. "Relative performance of methods for forecasting special events," Journal of Business Research, Elsevier, vol. 68(8), pages 1785-1791.
    5. 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.
    6. António Brandão Moniz, 2012. "Avaliação participativa de tecnologia e sustentabilidade organizacional [Participative technology assessment and organisational sustainability]," IET Working Papers Series 06/2012, Universidade Nova de Lisboa, IET/CICS.NOVA-Interdisciplinary Centre on Social Sciences, Faculty of Science and Technology.
    7. 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.
    8. Edieal J. Pinker, 2007. "An Analysis of Short-Term Responses to Threats of Terrorism," Management Science, INFORMS, vol. 53(6), pages 865-880, June.
    9. Green, Kesten C., 2008. "Assessing probabilistic forecasts about particular situations," MPRA Paper 8836, University Library of Munich, Germany.

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    More about this item

    Keywords

    Bad faith; Framing; Hindsight bias; Methods; Politics.;
    All these keywords.

    JEL classification:

    • D74 - Microeconomics - - Analysis of Collective Decision-Making - - - Conflict; Conflict Resolution; Alliances; Revolutions
    • D78 - Microeconomics - - Analysis of Collective Decision-Making - - - Positive Analysis of Policy Formulation and Implementation
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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