Baysian Model Averaging, Learning and Model Selection

Kaushik Mitra, George Evans and Seppo Honkapohja

No 2012-11, SIRE Discussion Papers from Scottish Institute for Research in Economics (SIRE)

Abstract: 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: Learning dynamics; Bayesian model averaging; grain of truth; self-referential systems (search for similar items in EconPapers)
Date: 2012
New Economics Papers: this item is included in nep-for and nep-mic
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Working Paper: Bayesian Model Averaging, Learning and Model Selection (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:edn:sirdps:314

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