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A Choice Prediction Competition: Choices From Experience and From Description

Author

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  • Roth, Alvin E.
  • Herzog, Stefan
  • Hau, Robin
  • Hertwig, Ralph
  • Erev, Ido
  • Ert, Eyal
  • Haruvy, Ernan
  • Stewart, Terrence
  • West, Robert
  • Lebiere, Christian

Abstract

Erev, Ert, and Roth organized three choice prediction competitions focused on three related choice tasks: one shot decisions from description (decisions under risk), one shot decisions from experience, and repeated decisions from experience. Each competition was based on two experimental datasets: An estimation dataset, and a competition dataset. The studies that generated the two datasets used the same methods and subject pool, and examined decision problems randomly selected from the same distribution. After collecting the experimental data to be used for estimation, the organizers posted them on the Web, together with their fit with several baseline models, and challenged other researchers to compete to predict the results of the second (competition) set of experimental sessions. Fourteen teams responded to the challenge: the last seven authors of this paper are members of the winning teams. The results highlight the robustness of the difference between decisions from description and decisions from experience. The best predictions of decisions from descriptions were obtained with a stochastic variant of prospect theory assuming that the sensitivity to the weighted values decreases with the distance between the cumulative payoff functions. The best predictions of decisions from experience were obtained with models that assume reliance on small samples. Merits and limitations of the competition method are discussed.

Suggested Citation

  • Roth, Alvin E. & Herzog, Stefan & Hau, Robin & Hertwig, Ralph & Erev, Ido & Ert, Eyal & Haruvy, Ernan & Stewart, Terrence & West, Robert & Lebiere, Christian, 2009. "A Choice Prediction Competition: Choices From Experience and From Description," Scholarly Articles 5343169, Harvard University Department of Economics.
    • Handle: RePEc:hrv:faseco:5343169
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    References listed on IDEAS

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    Cited by:

    1. Stefano DellaVigna & Devin Pope, 2018. "Predicting Experimental Results: Who Knows What?," Journal of Political Economy, University of Chicago Press, vol. 126(6), pages 2410-2456.
    2. Takemi Fujikawa, 2009. "On the relative importance of the hot stove effect and the tendency to rely on small samples," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 4(5), pages 429-435, August.
    3. Zhihua Li & Julia Müller & Peter P. Wakker & Tong V. Wang, 2018. "The Rich Domain of Ambiguity Explored," Management Science, INFORMS, vol. 64(7), pages 3227-3240, July.
    4. Stefano DellaVigna & Devin Pope, 2018. "What Motivates Effort? Evidence and Expert Forecasts," Review of Economic Studies, Oxford University Press, vol. 85(2), pages 1029-1069.
    5. Kim, Younjun, 2015. "Essays on firm location decisions, regional development and choices under risk," ISU General Staff Papers 201501010800005579, Iowa State University, Department of Economics.
    6. Laudenbach, Christine & Loos, Benjamin & Pirschel, Jenny & Wohlfart, Johannes, 2020. "The trading response of individual investors to local bankruptcies," SAFE Working Paper Series 272, Leibniz Institute for Financial Research SAFE.
    7. repec:cup:judgdm:v:4:y:2009:i:5:p:429-435 is not listed on IDEAS
    8. Christine Laudenbach & Benjamin Loos & Jenny Pirschel & Johannes Wohlfart, 2020. "The Trading Response of Individual Investors to Local Bankruptcies," CESifo Working Paper Series 8191, CESifo.
    9. Ido Erev & Alvin E. Roth & Robert Slonim, 2016. "Minimax across a population of games," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 2(2), pages 144-156, November.

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