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Attitude toward information and learning under multiple priors

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Author Info
Robert Kast () (LAMETA - Laboratoire Montpellierain d'économie théorique et appliquée - CNRS : UMR5474 - INRA : UR1135 - CIHEAM - Université Montpellier I - Montpellier SupAgro)
André Lapied () (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - Université de la Méditerranée - Aix-Marseille II - Université Paul Cézanne - Aix-Marseille III - Ecole des Hautes Etudes en Sciences Sociales - CNRS : UMR6579)
Pascal Toquebeuf () (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - Université de la Méditerranée - Aix-Marseille II - Université Paul Cézanne - Aix-Marseille III - Ecole des Hautes Etudes en Sciences Sociales - CNRS : UMR6579)

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Abstract

This paper studies learning under multiple priors by characterizing the decision maker's attitude toward information. She is incredulous if she integrates new information with respect to only those measures that minimizes the likelihood of the new information and credulous if she uses the maximum likelihood procedure to update her priors. Both updating rules expose her to dynamic inconsistency. We explore different ways to resolve this problem. One way consists to assume that the decision maker's attitude toward information is not relevant to characterize conditional preferences. In this case, we show that a necessary and sufficient condition, introduced by [Epstein L. and Schneider M., 2003. Recursive multiple priors. Journal of Economic Theory 113, 1-31], is the rectangularity of the set of priors. Another way is to extend optimism or pessimism to a dynamic set-up. A pessimistic (max-min expected utility) decision maker will be credulous when learning bad news but incredulous when learning good news.Conversely, an optimistic (max-max expected utility) decision maker will be credulous when learning good news but incredulous when learning bad news. It allows max-min (or max-max) expected utility preferences to be dynamically consistent but it violates consequentialism because conditioning works with respect to counterfactual outcomes. The implications of our findings when the set of priors is the core of a non-additive measure are explored.

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Paper provided by HAL in its series Working Papers with number halshs-00409368_v1.

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Date of creation: 07 Aug 2009
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Handle: RePEc:hal:wpaper:halshs-00409368_v1

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Related research
Keywords: Multiple priors ; Learning ; Dynamic consistency ; Consequentialism ; Attitude toward information;

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This page was last updated on 2009-12-17.


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