Learning and Model Validation
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 âalmost alwaysâ. 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 Society for Economic Dynamics in its series 2011 Meeting Papers with number 1086.
Date of creation: 2011
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Postal: Society for Economic Dynamics Christian Zimmermann Economic Research Federal Reserve Bank of St. Louis PO Box 442 St. Louis MO 63166-0442 USA
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Other versions of this item:
- 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
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