Alternatives to Bayesian Updating

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

Annual Review of Economics, 2024, vol. 16, issue 1, 545-570

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.

Keywords: hypothesis testing; cognitive noise; conservatism; non-Bayesian behavior; Bayes’ rule; base-rate neglect (search for similar items in EconPapers)
JEL-codes: D81 D84 D9 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:anr:reveco:v:16:y:2024:p:545-570

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DOI: 10.1146/annurev-economics-100223-050352

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