Bayesian Model Averaging, Learning and Model Selection
George Evans (),
Seppo Honkapohja (),
Thomas Sargent () and
Noah Williams ()
No 8917, CEPR Discussion Papers from C.E.P.R. Discussion Papers
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 (search for similar items in EconPapers)
JEL-codes: D83 D84 E37 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dge and nep-for
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Working Paper: Baysian Model Averaging, Learning and Model Selection (2012)
Working Paper: Bayesian Model Averaging, Learning and Model Selection (2012)
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