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Decision Making with Imprecise Probabilistic Information

  • Thibault Gadjos

    (Crest)

  • Jean-Marc Tallon

    (Crest)

  • Jean-Christophe Vergnaud

    (Crest)

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.

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Paper provided by Centre de Recherche en Economie et Statistique in its series Working Papers with number 2002-33.

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Date of creation: 2002
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Handle: RePEc:crs:wpaper:2002-33
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