Model Validation and Learning
AbstractThis paper studies adaptive learning with multiple models. An agent operating in a self-referential environment is aware of potential model misspecification, and tries to detect it, in real-time, using an econometric specification test. If the current model passes the test, it is used to construct an optimal policy. If it fails the test, a new model is selected from a fixed set of models. As the rate of coefficient updating decreases, one model becomes dominant, and is used 'almost always'. Dominant models can be characterized using the tools of large deviations theory. The analysis is applied to Sargent's (1999) Phillips Curve model.
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Bibliographic InfoPaper provided by Department of Economics, Simon Fraser University in its series Discussion Papers with number dp12-07.
Date of creation: Apr 2012
Date of revision:
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Postal: Department of Economics, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada
Web page: http://www.sfu.ca/economics.html
More information through EDIRC
Postal: Working Paper Coordinator, Department of Economics, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- E59 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Other
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-04-17 (All new papers)
- NEP-ECM-2012-04-17 (Econometrics)
- NEP-MIC-2012-04-17 (Microeconomics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Brock,W.A. & Durlauf,S.N. & West,K.D., 2004.
"Model uncertainty and policy evaluation : some theory and empirics,"
19, Wisconsin Madison - Social Systems.
- Brock, William A. & Durlauf, Steven N. & West, Kenneth D., 2007. "Model uncertainty and policy evaluation: Some theory and empirics," Journal of Econometrics, Elsevier, vol. 136(2), pages 629-664, February.
- William Brock & Steven Durlauf & Kenneth West, 2005. "Model uncertainty and policy evaluation: some theory and empirics," Proceedings, Federal Reserve Bank of San Francisco.
- William A. Brock & Steven N. Durlauf & Kenneth D. West, 2004. "Model Uncertainty and Policy Evaluation: Some Theory and Empirics," NBER Working Papers 10916, National Bureau of Economic Research, Inc.
- Bullard, James, 1992. "Time-varying parameters and nonconvergence to rational expectations under least squares learning," Economics Letters, Elsevier, vol. 40(2), pages 159-166, October.
- Sin, Chor-Yiu & White, Halbert, 1996. "Information criteria for selecting possibly misspecified parametric models," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 207-225.
- Chu, Chia-Shang James & Stinchcombe, Maxwell & White, Halbert, 1996. "Monitoring Structural Change," Econometrica, Econometric Society, vol. 64(5), pages 1045-65, September.
- Timothy Cogley & Riccardo Colacito & Lars Peter Hansen & Thomas J. Sargent, 2008. "Robustness and U.S. Monetary Policy Experimentation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(8), pages 1599-1623, December.
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