Anticipated utility and rational expectations as approximations of Bayesian decision making

Arbeitspapier

For 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 anticipated utility and Bayesian models augment market prices of risk relative to the rational expectations approximation.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Working Paper ; No. 05-23

Classification and Topics

• Classification: Wirtschaft

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Cogley, Timothy W. ; Sargent, Thomas J.
• Event: Veröffentlichung
• (who): University of California, Department of Economics
• (where): Davis, CA
• (when): 2005

Further information

• Handle: http://hdl.handle.net/10419/31318
• Last update: 10.03.2025, 11:41 AM CET