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Decision Making with Imprecise Probabilistic Information

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

Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL

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, applyingGilboa-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)
Date: 2004
Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00086021
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Published in Journal of Mathematical Economics, Elsevier, 2004, 40 (6), pp.647-681. ⟨10.1016/j.jmateco.2003.06.004⟩

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Journal Article: Decision making with imprecise probabilistic information (2004) Downloads
Working Paper: Decision Making with Imprecise Probabilistic Information (2003) Downloads
Working Paper: Decision Making with Imprecise Probabilistic Information (2002) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:hal:cesptp:halshs-00086021

DOI: 10.1016/j.jmateco.2003.06.004

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