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Decision Making with Imprecise Probabilistic Information

Thibault Gajdos (), Jean-Marc Tallon () and Jean-Christophe Vergnaud ()

ICER Working Papers - Applied Mathematics Series from ICER - International Centre for Economic Research

Abstract: We develop an axiomatic approach to decision under uncertainty that explicitly takes into account the information available to the decision maker. The information is described by a set of priors and a reference prior. We define a notion of imprecision for this informational setting and show that a decision maker who is averse to information imprecision maximizes the minimum expected utility computed with respect to a subset of the set of initially given priors. The extent to which this set is reduced can be seen as a measure of imprecision aversion. This approach thus allows a lot of flexibility in modelling the decision maker attitude towards imprecision. In contrast, applying Gilboa and Schmeidler (1989) maxmin criterion to the initial set of priors amounts to assuming extreme pessimism.

Keywords: Uncertainty; Decision; Multiple Priors (search for similar items in EconPapers)
JEL-codes: D81 (search for similar items in EconPapers)
Pages: 41 pages
Date: 2002-06, Revised 2003-05
New Economics Papers: this item is included in nep-mic
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Citations: View citations in EconPapers (20) Track citations by RSS feed

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Related works:
Journal Article: Decision making with imprecise probabilistic information (2004) Downloads
Working Paper: Decision Making with Imprecise Probabilistic Information (2004) Downloads
Working Paper: Decision Making with Imprecise Probabilistic Information (2002) Downloads
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