Decision making with imprecise probabilistic information |
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| Institution: | 1. CNRS-CREST and ICER, France;2. EUREQua, CNRS-Université Paris I Panthéon-Sorbonne, 106–112 bd de l’Hôpital, 75647 Paris Cedex 13, France;1. Department of Economics, University of St. Gallen, Switzerland;2. Department of Economics, Bar-Ilan University, Israel;1. Tecnológico de Monterrey, EGADE Business School, San Pedro Garza García, NL, Mexico;2. KU Leuven, Department of Biosystems, Leuven, Belgium;3. Department of Industrial and Systems Engineering, School of Engineering and Sciences, Tecnológico de Monterrey, E. Garza Sada 2501 Sur, Monterrey C.P. 64849, NL, Mexico;1. Department of Economics, University College London, UK;2. CNRS – École Polytechnique, France;3. Department of Mathematics, London School of Economics, UK;4. Department of Economics, Brown University, USA;1. Department of Economics, Yale University, New Haven CT 06511, United States;2. Department of Economics, Princeton University, Princeton NJ 08544, United States |
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| 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, applying Gilboa and Schmeidler J. Math. Econ. 18 (1989) 141] maxmin criterion to the initial set of priors amounts to assuming extreme pessimism. |
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