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Dynamically consistent preferences under imprecise probabilistic information

Frank Riedel, Jean-Marc Tallon and Vassili Vergopoulos
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Vassili Vergopoulos: Center for Mathematical Economics, Bielefeld University

No 573, Center for Mathematical Economics Working Papers from Center for Mathematical Economics, Bielefeld University

Abstract: This paper extends decision theory under imprecise probabilistic information to dynamic settings. We explore the relationship between the given objective probabilistic information, an agent's subjective multiple priors, and updating. Dynamic consistency implies rectangular sets of priors at the subjective level. As the objective probabilistic information need not be consistent with rectangularity at the subjective level, agents might select priors outside the objective probabilistic information while respecting the support of the given set of priors. Under suitable additional axioms, the subjective set of priors belongs to the rectangular hull of the objective probabilistic information.

Keywords: Imprecise information; imprecision aversion; multiple priors; dynamic consistency (search for similar items in EconPapers)
Date: 2017-04-27
New Economics Papers: this item is included in nep-mic and nep-upt
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https://pub.uni-bielefeld.de/download/2910581/2910583 First Version, 2017 (application/x-download)

Related works:
Journal Article: Dynamically consistent preferences under imprecise probabilistic information (2018) Downloads
Working Paper: Dynamically consistent preferences under imprecise probabilistic information (2018)
Working Paper: Dynamically consistent preferences under imprecise probabilistic information (2018)
Working Paper: Dynamically consistent preferences under imprecise probabilistic information (2018)
Working Paper: Dynamically Consistent Preferences Under Imprecise Probabilistic Information (2017) Downloads
Working Paper: Dynamically Consistent Preferences Under Imprecise Probabilistic Information (2017) Downloads
Working Paper: Dynamically Consistent Preferences Under Imprecise Probabilistic Information (2017) Downloads
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