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Alternatives to Bayesian Updating

Author

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  • Pietro Ortoleva

    (Department of Economics and School of Public and International Affairs, Princeton University, Princeton, New Jersey, USA)

Abstract

We discuss models of updating that depart from Bayes’ rule even when it is well-defined. After reviewing Bayes’ rule and its foundations, we begin our analysis with models of non-Bayesian behavior arising from a bias, a pull toward suboptimal behavior due to a heuristic or a mistake. Next, we explore deviations caused by individuals questioning the prior probabilities they initially used. We then consider non-Bayesian behavior resulting from the optimal response to constraints on perception, cognition, or memory, as well as models based on motivated beliefs or distance minimization. Finally, we briefly discuss models of updating after zero probability events.

Suggested Citation

  • Pietro Ortoleva, 2024. "Alternatives to Bayesian Updating," Annual Review of Economics, Annual Reviews, vol. 16(1), pages 545-570, August.
    • Handle: RePEc:anr:reveco:v:16:y:2024:p:545-570
    DOI: 10.1146/annurev-economics-100223-050352
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    More about this item

    Keywords

    hypothesis testing; cognitive noise; conservatism; non-Bayesian behavior; Bayes’ rule; base-rate neglect;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D9 - Microeconomics - - Micro-Based Behavioral Economics
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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