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Decision Making with Imprecise Probabilistic Information

Author

Listed:
  • 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.)
(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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