Division of the Humanities and Social Sciences California Institute of Technology Pasadena, California 91125 Bayesian Consistent Prior Selection
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چکیده
A subjective expected utility agent is given information about the state of the world in the form of a set of possible priors. She is allowed to condition her prior on this information. A set of priors may be updated according to Bayes’ rule, prior-by-prior, upon learning that some state of the world has not obtained. We show that there exists no decision maker who obeys Bayes’ rule, conditions her prior on the available information (by selecting a prior in the announced set), and who updates the information prior-byprior using Bayes’ rule. The result implies that at least one of several familiar decision theoretic “paradoxes” is a mathematical necessity. JEL classification numbers: C11, D01, D80, D81
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Op-scan120058 341..350
Peter Sokol-Hessner, Colin F. Camerer, and Elizabeth A. Phelps Division of the Humanities and Social Sciences (HSS), California Institute of Technology, Division of the Humanities and Social Sciences (HSS) and Computational and Neural Systems (CNS), California Institute of Technology, 1200 E. California Blvd., Pasadena, CA 91125, USA, and Department of Psychology, New York University, 6 Washing...
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تاریخ انتشار 2005