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I nvestigate D iscuss E stimate A ggregate for structured expert judgement

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  • Hanea, A.M.
  • McBride, M.F.
  • Burgman, M.A.
  • Wintle, B.C.
  • Fidler, F.
  • Flander, L.
  • Twardy, C.R.
  • Manning, B.
  • Mascaro, S.

Abstract

This study presents the results of an approach to the prediction of the outcomes of geopolitical events, which we term the IDEA protocol. The participants investigate the background and causal factors behind a question, predict the outcome, and discuss their thinking with others. They then make a second, private and anonymous judgement of the probability of the event, which is subsequently aggregated mathematically. The method performed well relative to both an equally weighted linear pool and a prediction market, and is relatively simple to implement. The results indicate the value of discussion for removing arbitrary linguistic uncertainty and for sharing and debating knowledge, thereby improving the judgements. Weighting individual judgements based on prior performance using Cooke’s method improved group judgements. Even though some of the results are not statistically significant, the study may not have had sufficient power to detect some important effects. Nevertheless, the results help us to formulate conjectures, which can then be investigated further.

Suggested Citation

  • Hanea, A.M. & McBride, M.F. & Burgman, M.A. & Wintle, B.C. & Fidler, F. & Flander, L. & Twardy, C.R. & Manning, B. & Mascaro, S., 2017. "I nvestigate D iscuss E stimate A ggregate for structured expert judgement," International Journal of Forecasting, Elsevier, vol. 33(1), pages 267-279.
  • Handle: RePEc:eee:intfor:v:33:y:2017:i:1:p:267-279
    DOI: 10.1016/j.ijforecast.2016.02.008
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    1. Graefe, Andreas & Armstrong, J. Scott, 2011. "Comparing face-to-face meetings, nominal groups, Delphi and prediction markets on an estimation task," International Journal of Forecasting, Elsevier, vol. 27(1), pages 183-195, January.
    2. Willy Aspinall, 2010. "A route to more tractable expert advice," Nature, Nature, vol. 463(7279), pages 294-295, January.
    3. Schultze, Thomas & Mojzisch, Andreas & Schulz-Hardt, Stefan, 2012. "Why groups perform better than individuals at quantitative judgment tasks: Group-to-individual transfer as an alternative to differential weighting," Organizational Behavior and Human Decision Processes, Elsevier, vol. 118(1), pages 24-36.
    4. Robin Hanson, 2003. "Combinatorial Information Market Design," Information Systems Frontiers, Springer, vol. 5(1), pages 107-119, January.
    5. Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 107-126, Spring.
    6. Lyon, Aidan & Wintle, Bonnie C. & Burgman, Mark, 2015. "Collective wisdom: Methods of confidence interval aggregation," Journal of Business Research, Elsevier, vol. 68(8), pages 1759-1767.
    7. Simon French, 2012. "Expert Judgment, Meta-analysis, and Participatory Risk Analysis," Decision Analysis, INFORMS, vol. 9(2), pages 119-127, June.
    8. Weiss, David J & Shanteau, James, 2012. "Decloaking the privileged expert," Journal of Management & Organization, Cambridge University Press, vol. 18(3), pages 300-310, May.
    9. Jonathan Baron & Barbara A. Mellers & Philip E. Tetlock & Eric Stone & Lyle H. Ungar, 2014. "Two Reasons to Make Aggregated Probability Forecasts More Extreme," Decision Analysis, INFORMS, vol. 11(2), pages 133-145, June.
    10. Robin Hanson, 2007. "Logarithmic Market Scoring Rules for Modular Combinatorial Information Aggregation," Journal of Prediction Markets, University of Buckingham Press, vol. 1(1), pages 3-15, February.
    11. Cooke, Roger M. & Goossens, Louis L.H.J., 2008. "TU Delft expert judgment data base," Reliability Engineering and System Safety, Elsevier, vol. 93(5), pages 657-674.
    12. Murphy, Allan H. & Winkler, Robert L., 1992. "Diagnostic verification of probability forecasts," International Journal of Forecasting, Elsevier, vol. 7(4), pages 435-455, March.
    13. Yates, J. Frank & Price, Paul C. & Lee, Ju-Whei & Ramirez, James, 1996. "Good probabilistic forecasters: The 'consumer's' perspective," International Journal of Forecasting, Elsevier, vol. 12(1), pages 41-56, March.
    14. Wei Sun & Robin Hanson & Kathryn Blackmond Laskey & Charles Twardy, 2012. "Probability and Asset Updating using Bayesian Networks for Combinatorial Prediction Markets," Papers 1210.4900, arXiv.org.
    15. McKenzie, Craig R.M. & Liersch, Michael J. & Yaniv, Ilan, 2008. "Overconfidence in interval estimates: What does expertise buy you?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 107(2), pages 179-191, November.
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    Cited by:

    1. Bolger, Fergus & Wright, George, 2017. "Use of expert knowledge to anticipate the future: Issues, analysis and directions," International Journal of Forecasting, Elsevier, vol. 33(1), pages 230-243.
    2. Ling Cao & Benjamin S. Halpern & Max Troell & Rebecca Short & Cong Zeng & Ziyu Jiang & Yue Liu & Chengxuan Zou & Chunyu Liu & Shurong Liu & Xiangwei Liu & William W. L. Cheung & Richard S. Cottrell & , 2023. "Vulnerability of blue foods to human-induced environmental change," Nature Sustainability, Nature, vol. 6(10), pages 1186-1198, October.
    3. repec:cup:judgdm:v:15:y:2020:i:5:p:783-797 is not listed on IDEAS
    4. Di, Chen & Dimitrov, Stanko & He, Qi-Ming, 2019. "Incentive compatibility in prediction markets: Costly actions and external incentives," International Journal of Forecasting, Elsevier, vol. 35(1), pages 351-370.
    5. Michael C. Runge & Clark S. Rushing & James E. Lyons & Madeleine A. Rubenstein, 2023. "A Simplified Method for Value of Information Using Constructed Scales," Decision Analysis, INFORMS, vol. 20(3), pages 220-230, September.
    6. David R. Mandel & Robert N. Collins & Evan F. Risko & Jonathan A. Fugelsang, 2020. "Effect of confidence interval construction on judgment accuracy," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 15(5), pages 783-797, September.

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