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Coherent Distorted Beliefs

Author

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  • Christopher P. Chambers
  • Yusufcan Masatlioglu
  • Collin Raymond
Abstract
Many models of economics assume that individuals distort objective probabilities. We propose a simple consistency condition on distortion functions, which we term distortion coherence, that ensures that the function commutes with conditioning on an event. We show that distortion coherence restricts belief distortions to have a particular function form: power-weighted distortions, where distorted beliefs are proportional to the original beliefs raised to a power and weighted by a state-specific value. We generalize our findings to allow for distortions of the probabilities assigned to both states and signals, which nests the functional forms widely used in studying probabilistic biases (e.g., Grether, 1980 and Benjamin, 2019). We show how coherent distorted beliefs are tightly related to several extant models of motivated beliefs: they are the outcome of maximizing anticipated expected utility subject to a generalized Kullback-Liebler cost of distortion. Moreover, in the domain of lottery choice, we link coherent distortions to explanations of non-expected utility like the Allais paradox: individuals who maximize subjective expected utility maximizers conditional on coherent distorted beliefs are equivalent to the weighted utility maximizers studied by Chew [1983].

Suggested Citation

  • Christopher P. Chambers & Yusufcan Masatlioglu & Collin Raymond, 2023. "Coherent Distorted Beliefs," Papers 2310.09879, arXiv.org, revised Jun 2024.
    • Handle: RePEc:arx:papers:2310.09879
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    References listed on IDEAS

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    1. Daniel J. Benjamin & Matthew Rabin & Collin Raymond, 2016. "A Model of Nonbelief in the Law of Large Numbers," Journal of the European Economic Association, European Economic Association, vol. 14(2), pages 515-544.
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    4. David M. Grether, 1980. "Bayes Rule as a Descriptive Model: The Representativeness Heuristic," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 95(3), pages 537-557.
    5. Paul R. Milgrom, 1981. "Good News and Bad News: Representation Theorems and Applications," Bell Journal of Economics, The RAND Corporation, vol. 12(2), pages 380-391, Autumn.
    6. Roland Bénabou & Jean Tirole, 2005. "Self-Confidence and Personal Motivation," International Economic Association Series, in: Bina Agarwal & Alessandro Vercelli (ed.), Psychology, Rationality and Economic Behaviour, chapter 2, pages 19-57, Palgrave Macmillan.
    7. Bracha, Anat & Brown, Donald J., 2012. "Affective decision making: A theory of optimism bias," Games and Economic Behavior, Elsevier, vol. 75(1), pages 67-80.
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    9. Roland Bénabou & Jean Tirole, 2016. "Mindful Economics: The Production, Consumption, and Value of Beliefs," Journal of Economic Perspectives, American Economic Association, vol. 30(3), pages 141-164, Summer.
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    11. Diecidue, Enrico & Schmidt, Ulrich & Zank, Horst, 2009. "Parametric weighting functions," Journal of Economic Theory, Elsevier, vol. 144(3), pages 1102-1118, May.
    12. Chew, Soo Hong, 1983. "A Generalization of the Quasilinear Mean with Applications to the Measurement of Income Inequality and Decision Theory Resolving the Allais Paradox," Econometrica, Econometric Society, vol. 51(4), pages 1065-1092, July.
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    Cited by:

    1. Konstantin von Beringe & Mark Whitmeyer, 2024. "The Perils of Overreaction," Papers 2405.08087, arXiv.org.

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