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Decision Making with Imprecise Probabilistic Information

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  • Thibault Gadjos

    (Crest)

  • Jean-Marc Tallon

    (Crest)

  • Jean-Christophe Vergnaud

    (Crest)

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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Thibault Gadjos & Jean-Marc Tallon & Jean-Christophe Vergnaud, 2002. "Decision Making with Imprecise Probabilistic Information," Working Papers 2002-33, Center for Research in Economics and Statistics.
    • Handle: RePEc:crs:wpaper:2002-33
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    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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