Decision Making with Imprecise Probabilistic Information
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, applyingGilboaSchmeidler [1989] maxmin criterion to the initial set of priors amounts to assuming extreme pessimism.
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Date of creation:  2004 
Date of revision:  
Publication status:  Published in Journal of Mathematical Economics, Elsevier, 2004, 40 (6), pp.647681. <10.1016/j.jmateco.2003.06.004> 
Handle:  RePEc:hal:cesptp:halshs00086021 
DOI:  10.1016/j.jmateco.2003.06.004 
Note:  View the original document on HAL open archive server: https://halshs.archivesouvertes.fr/halshs00086021 
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