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
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  maxmin criterion to the initial set of priors amounts to assuming extreme pessimism.
Keywords: Uncertainty; Decision; Multiple Priors (search for similar items in EconPapers)
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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)
Working Paper: Decision Making with Imprecise Probabilistic Information (2003)
Working Paper: Decision Making with Imprecise Probabilistic Information (2002)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:cesptp:halshs-00086021
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