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Learning under Ambiguity: An Experimental Investigation
[Apprentissage en présence d'incertitude ambigue]

Author

Listed:
  • M. Abdellaoui

    (HEC Paris - Ecole des Hautes Etudes Commerciales, CNRS - Centre National de la Recherche Scientifique)

  • B. Hill

    (HEC Paris - Recherche - Hors Laboratoire - HEC Paris - Ecole des Hautes Etudes Commerciales, CNRS - Centre National de la Recherche Scientifique, GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique)

  • E. Kemel

    (HEC Paris - Ecole des Hautes Etudes Commerciales, CNRS - Centre National de la Recherche Scientifique)

  • H. Maafi

    (UP8 - Université Paris 8)

Abstract

We investigate learning in ambiguous situations where subjects bet on a winning event whose probability depends on an unknown proportion of winning chips in an urn. Varying the number of draws prior to choice allows us to "scan" ambiguity attitudes across differing amounts of information. By separately eliciting posterior beliefs in addition to matching probabilities, we disentangle the impact of learning on ambiguity attitude from its impact on beliefs, including divergences from Bayesian update. Both "raw data" and smooth ambiguity model-based analyses show that learning affects ambiguity attitude in the direction of ambiguity neutrality. Moreover, at small sample sizes, the impact of these changes on preferences is comparable to that of the divergence from Bayesian update.

Suggested Citation

  • M. Abdellaoui & B. Hill & E. Kemel & H. Maafi, 2025. "Learning under Ambiguity: An Experimental Investigation [Apprentissage en présence d'incertitude ambigue]," Post-Print hal-05541433, HAL.
    • Handle: RePEc:hal:journl:hal-05541433
    DOI: 10.1016/j.jet.2025.106093
    Note: View the original document on HAL open archive server: https://hal.science/hal-05541433v1
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    References listed on IDEAS

    as
    1. Mohammed Abdellaoui & Han Bleichrodt & Olivier L’Haridon, 2008. "A tractable method to measure utility and loss aversion under prospect theory," Journal of Risk and Uncertainty, Springer, vol. 36(3), pages 245-266, June.
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    5. Machina, Mark J & Schmeidler, David, 1992. "A More Robust Definition of Subjective Probability," Econometrica, Econometric Society, vol. 60(4), pages 745-780, July.
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    JEL classification:

    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • 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
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • 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

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