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Anticipated Utility and Rational Expectations as Approximations of Bayesian Decision Making

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  • Tim W. Cogley
  • Thomas J. Sargent

    (Department of Economics, University of California Davis)

Abstract

For a Markov decision problem in which unknown transition probabilitiesserve as hidden state variables, we study the quality of two approximations tothe decision rule of a Bayesian who each period updates his subjective distribu-tion over the transition probabilities by Bayes? law. The first is the usual ratio-nal expectations approximation that assumes that the decision maker knows thetransition probabilities. The second approximation is a version of Kreps? (1998)anticipated utility model in which decision makers update using Bayes? law butoptimize in a way that is myopic with respect to their updating of probabili-ties. For a range of consumption smoothing examples, the anticipated utilityapproximation outperforms the rational expectations approximation. The an-ticipated utility and Bayesian models augment market prices of risk relative tothe rational expectations approximation.

Suggested Citation

  • Tim W. Cogley & Thomas J. Sargent, 2005. "Anticipated Utility and Rational Expectations as Approximations of Bayesian Decision Making," Working Papers 68, University of California, Davis, Department of Economics.
    • Handle: RePEc:cda:wpaper:68
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    Keywords

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    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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