## 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.

Original language | English (US) |
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Pages (from-to) | 185-221 |

Number of pages | 37 |

Journal | International Economic Review |

Volume | 49 |

Issue number | 1 |

DOIs | |

State | Published - Feb 2008 |

## ASJC Scopus subject areas

- Economics and Econometrics