More on random utility models with bounded ambiguity

Charles Manski

Theory and Decision, 2018, vol. 84, issue 2, No 4, 205-213

Abstract: Abstract Econometric analysis of discrete choice has made considerable use of random utility models to interpret observed choice behavior. Much empirical research concerns choice problems in which persons act with partial knowledge of the utilities of the feasible actions. Economists use random expected utility models to analyze such choice problems. A common practice is to specify fully the expectations that persons hold, in which case choice analysis reduces to inference on preferences alone. However, the expectations assumptions made in empirical research rarely have much foundation. To enable more credible research, this paper considers inference when one specifies a set of expectations that decision makers may plausibly hold. I first pose the idea in abstraction and then specialize to binary response with linear utilities, where the analysis is particularly straightforward. I initially assume that decision makers possess unique subjective probability distributions on the states of nature and make choices that maximize expected utility. I later consider the possibility that persons place only partial probabilistic structure on the states of nature and make undominated choices.

Keywords: Discrete choice analysis; Decisions under ambiguity; Partial identification (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s11238-017-9620-1

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