Bayesian Model Averaging, Learning, and Model Selection*

George W. Evans, Seppo Honkapohja, Thomas J. Sargent and Noah Williams

in Macroeconomics at the Service of Public Policy

Published in print February 2013 | ISBN: 9780199666126
Published online May 2013 | e-ISBN: 9780191749278 | DOI:
Bayesian Model Averaging, Learning, and Model Selection*

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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 longrun. A key structural parameter governing outcomes measures the degree of expectations feedback in Muth’s model of price determination.

Keywords: forecasting models; time varying parameters; rational expectations equilibria; Bayesian updating; self‐referential system; model selection

Chapter.  8722 words.  Illustrated.

Subjects: Macroeconomics and Monetary Economics

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