Attitude toward information and learning under multiple priors

Robert Kast (1) , André Lapied (2) , Pascal Toquebeuf (2)

1 LAMETA - Laboratoire Montpelliérain d'Économie Théorique et Appliquée
2 GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille

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.

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

Domains: Economics and Finance

Robert Kast, André Lapied, Pascal Toquebeuf. Attitude toward information and learning under multiple priors. 2009. ⟨halshs-00409368⟩