Baysian Model Averaging, Learning and Model Selection
AbstractAgents have two forecasting models, one consistent with the unique rational expectations equilibrium, another that assumes a time-varying parameter structure. When agents use Bayesian updating to choose between models in a self-referential system, we find that learning dynamics lead to selection of one of the two models. However, there are parameter regions for which the non-rational forecasting model is selected in the long-run. A key structural parameter governing outcomes measures the degree of expectations feedback in Muth's model of price determination.
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Bibliographic InfoPaper provided by Scottish Institute for Research in Economics (SIRE) in its series SIRE Discussion Papers with number 2012-11.
Date of creation: 2012
Date of revision:
Learning dynamics; Bayesian model averaging; grain of truth; self-referential systems;
Other versions of this item:
- Evans, George W. & Honkapohja, Seppo & Sargent, Thomas J & Williams, Noah, 2012. "Bayesian Model Averaging, Learning and Model Selection," CEPR Discussion Papers 8917, C.E.P.R. Discussion Papers.
- George W. Evans & Seppo Honkapohja & Thomas Sargent & Noah Williams, 2012. "Bayesian Model Averaging, Learning and Model Selection," CDMA Working Paper Series 201203, Centre for Dynamic Macroeconomic Analysis.
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
- D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-06-25 (All new papers)
- NEP-FOR-2012-06-25 (Forecasting)
- NEP-MIC-2012-06-25 (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.:
- Thomas J. Sargent & Noah William, 2005.
"Impacts of Priors on Convergence and Escapes from Nash Inflation,"
Review of Economic Dynamics,
Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 360-391, April.
- Thomas J. Sargent & Noah Williams, 2003. "Impacts of priors on convergence and escapes from Nash inflation," Working Paper 2003-14, Federal Reserve Bank of Atlanta.
- 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.
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