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Modeling the Change of Paradigm: Non-Bayesian Reactions to Unexpected News

Ortoleva, Pietro (2010) Modeling the Change of Paradigm: Non-Bayesian Reactions to Unexpected News. Social Science Working Paper, 1320. California Institute of Technology , Pasadena, CA. (Unpublished) http://resolver.caltech.edu/CaltechAUTHORS:20170726-155556701

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Abstract

Despite its normative appeal and widespread use, Bayes’ rule has two well-known limitations: first, it does not predict how agents should react to an information to which they assigned probability zero; second, a sizable empirical evidence documents how agents systematically deviate from its prescriptions by overreacting to information to which they assigned a positive but small probability. By replacing Dynamic Consistency with a novel axiom, Dynamic Coherence, we characterize an alternative updating rule that is not subject to these limitations, but at the same time coincides with Bayes’ rule for “normal” events. In particular, we model an agent with a utility function over consequences, a prior over priors ρ, and a threshold. In the first period she chooses the prior that maximizes the prior over priors ρ--a’ la maximum likelihood. As new information is revealed: if the chosen prior assigns to this information a probability above the threshold, she follows Bayes’ rule and updates it. Otherwise, she goes back to her prior over priors ρ, updates it using Bayes’ rule, and then chooses the new prior that maximizes the updated ρ. We also extend our analysis to the case of ambiguity aversion.


Item Type:Report or Paper (Working Paper)
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http://resolver.caltech.edu/CaltechAUTHORS:20121126-103347996Related ItemPublished Version
Additional Information:I would like to thank Kim Border, Paolo Ghirardato, Federico Echenique, Leeat Yariv, Leonardo Pejsachowicz, Gil Riella, and the participants at seminars at ASU, Caltech, Collegio Carlo Alberto, and SWET 2010 for useful comments and discussions. Published in American Economic Review, 102(6). pp. 2410-2436.
Group:Social Science Working Papers
Subject Keywords:Bayes’ Rule, Updating, Dynamic Consistency, Ambiguity Aversion
Classification Code:JEL: D81, C61
Record Number:CaltechAUTHORS:20170726-155556701
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20170726-155556701
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:79459
Collection:CaltechAUTHORS
Deposited By: Jacquelyn Bussone
Deposited On:07 Aug 2017 21:54
Last Modified:07 Aug 2017 21:54

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