27 Pages Posted: 4 Apr 2012
Date Written: March 2012
Agents 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.
Keywords: grain of truth, rational expectations equilibrium, Time-varying perceptions
JEL Classification: D83, D84, E37
Suggested Citation: Suggested Citation
Evans, George W. and Honkapohja, Seppo and Sargent, Thomas J. and Williams, Noah, Bayesian Model Averaging, Learning and Model Selection (March 2012). CEPR Discussion Paper No. DP8917. Available at SSRN: https://ssrn.com/abstract=2034135
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