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Noisy retrievers and the four-fold reaction to rare events


  • Davide Marchiori

    () (Department of Management, Università Ca' Foscari Venezia)

  • Sibilla Di Guida

    () (SBS-EM, ECARES, Universite Libre de Bruxelles)

  • Ido Erev

    () (Faculty of Industrial Engineering and Management, Technion)


Previous research documents two pairs of inconsistent reactions to rare events: 1) Studies of probability judgment reveal conservatism which implies overestimation of rare events, and overconfidence which implies underestimation of rare events. 2) Studies of choice behavior reveal overweighting of rare events in one-shot tasks, and the opposite bias in decisions from experience. The current analysis and experimental results demonstrate that the coexistence and relative importance of the four biases can be captured with simple models that share the assumption that judgments and decisions are made based on the information conveyed by small and noisy samples of past experiences.

Suggested Citation

  • Davide Marchiori & Sibilla Di Guida & Ido Erev, 2013. "Noisy retrievers and the four-fold reaction to rare events," Working Papers 3, Department of Management, Università Ca' Foscari Venezia.
  • Handle: RePEc:vnm:wpdman:39

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    References listed on IDEAS

    1. Itzhak Gilboa & David Schmeidler, 1995. "Case-Based Decision Theory," The Quarterly Journal of Economics, Oxford University Press, vol. 110(3), pages 605-639.
    2. Craig R. Fox & Amos Tversky, 1995. "Ambiguity Aversion and Comparative Ignorance," The Quarterly Journal of Economics, Oxford University Press, vol. 110(3), pages 585-603.
    3. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    4. Ido Erev & Ira Glozman & Ralph Hertwig, 2008. "What impacts the impact of rare events," Journal of Risk and Uncertainty, Springer, vol. 36(2), pages 153-177, April.
    5. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945, January.
    6. Gayer, Gabrielle, 2010. "Perception of probabilities in situations of risk: A case based approach," Games and Economic Behavior, Elsevier, vol. 68(1), pages 130-143, January.
    7. Wakker,Peter P., 2010. "Prospect Theory," Cambridge Books, Cambridge University Press, number 9780521765015, March.
    8. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
    9. Viscusi, W Kip, 1989. "Prospective Reference Theory: Toward an Explanation of the Paradoxes," Journal of Risk and Uncertainty, Springer, vol. 2(3), pages 235-263, September.
    10. Milton Friedman & L. J. Savage, 1948. "The Utility Analysis of Choices Involving Risk," Journal of Political Economy, University of Chicago Press, vol. 56, pages 279-279.
    11. Reinhard Selten & Thorsten Chmura, 2008. "Stationary Concepts for Experimental 2x2-Games," American Economic Review, American Economic Association, vol. 98(3), pages 938-966, June.
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    More about this item


    Black swan; prospect theory; experience-description gap; case-based decision theory; overgeneralization;

    JEL classification:

    • C79 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Other
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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