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Confidence Models of Incomplete Preferences

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  • McClellon, M.

Abstract

This paper introduces and axiomatizes a new class of representations for incomplete preferences called confi dence models. Con fidence models describe decision makers who behave as if they have probabilistic uncertainty over their true preferences, and are only willing to express a binary preference if it is sufficiently likely to hold. Confi dence models are flexible enough to model behavior on a variety of domains, and they are general enough to nest the popular multi-utility models of incomplete preferences. Most importantly, they provide a natural way to connect incomplete preferences with stochastic choice. This connection is characterized by a simple condition that serves to identify the behavioral content of incomplete preferences.

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  • McClellon, M., 2014. "Confidence Models of Incomplete Preferences," Working Paper 144976, Harvard University OpenScholar.
  • Handle: RePEc:qsh:wpaper:144976
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