Bayesian Model Averaging, Learning and Model Selection
George W. Evans
University of Oregon - Department of Economics; University of St. Andrews - School of Economics and Finance
Bank of Finland; Centre for Economic Policy Research (CEPR); CESifo (Center for Economic Studies and Ifo Institute for Economic Research)
Thomas J. Sargent
New York University (NYU) - Department of Economics, Leonard N. Stern School of Business; National Bureau of Economic Research (NBER)
Princeton University - Department of Economics; National Bureau of Economic Research (NBER)
CEPR Discussion Paper No. DP8917
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.
Number of Pages in PDF File: 27
Keywords: grain of truth, rational expectations equilibrium, Time-varying perceptions
JEL Classification: D83, D84, E37
Date posted: April 4, 2012
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