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Anticipated Utility And Rational Expectations As Approximations Of Bayesian Decision Making

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  • Timothy Cogley
  • Thomas J. Sargent

Abstract

We study a Markov decision problem with unknown transition probabilities. We compute the exact Bayesian decision rule and compare it with two approximations. The first is an infinite-history, rational-expectations approximation that assumes that the decision maker knows the transition probabilities. The second is a version of Kreps' 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 probabilities. For several consumption-smoothing examples, the anticipated-utility approximation outperforms the rational expectations approximation. The rational expectations approximation misrepresents the market price of risk. Copyright 2008 by the Economics Department Of The University Of Pennsylvania And Osaka University Institute Of Social And Economic Research Association.

Suggested Citation

  • 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, February.
  • Handle: RePEc:ier:iecrev:v:49:y:2008:i:1:p:185-221
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    References listed on IDEAS

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    1. Hall, Robert E, 1978. "Stochastic Implications of the Life Cycle-Permanent Income Hypothesis: Theory and Evidence," Journal of Political Economy, University of Chicago Press, vol. 86(6), pages 971-987, December.
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    3. Abel, Andrew B., 2002. "An exploration of the effects of pessimism and doubt on asset returns," Journal of Economic Dynamics and Control, Elsevier, vol. 26(7-8), pages 1075-1092, July.
    4. Hansen, Lars Peter & Jagannathan, Ravi, 1991. "Implications of Security Market Data for Models of Dynamic Economies," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 225-262, April.
    5. Cogley, Timothy & Morozov, Sergei & Sargent, Thomas J., 2005. "Bayesian fan charts for U.K. inflation: Forecasting and sources of uncertainty in an evolving monetary system," Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 1893-1925, November.
    6. Pok-sang Lam & Stephen G. Cecchetti & Nelson C. Mark, 2000. "Asset Pricing with Distorted Beliefs: Are Equity Returns Too Good to Be True?," American Economic Review, American Economic Association, vol. 90(4), pages 787-805, September.
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    More about this item

    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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