Anticipated Utility and Rational Expectations as Approximations of Bayesian Decision Making
AbstractFor a Markov decision problem in which unknown transition probabilities serve as hidden state variables, we study the quality of two approximations to the 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 the transition probabilities. The second approximation is a version of Kreps’ (1998) anticipated utility model in which decision makers update using Bayes’ law but optimize in a way that is myopic with respect to their updating of probabili- ties. For a range of consumption smoothing examples, the anticipated utility approximation outperforms the rational expectations approximation. The an- ticipated utility and Bayesian models augment market prices of risk relative to the rational expectations approximation.
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Bibliographic InfoPaper provided by University of California, Davis, Department of Economics in its series Working Papers with number 523.
Date of creation: 01 Mar 2005
Date of revision:
Rational expectations; Bayes’ Law; anticipated utility; market price ofrisk;
Other versions of this item:
- Timothy Cogley & Thomas J. Sargent, 2008. "Anticipated Utility And Rational Expectations As Approximations Of Bayesian Decision Making," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 49(1), pages 185-221, 02.
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
- D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
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