GRESHAM’S LAW OF MODEL AVERAGING

Inkoo Cho and Kenneth Kasa

Discussion Papers from Department of Economics, Simon Fraser University

Abstract: A decision maker doubts the stationarity of his environment. In response, he uses two models, one with time-varying parameters, and another with constant parameters. Forecasts are then based on a Bayesian Model Averaging strategy, which mixes forecasts from the two models. In reality, structural parameters are constant, but the (unknown) true model features expectational feedback, which the reduced form models neglect. This feedback permits fears of parameter instability to become self-confirming. Within the context of a standard linear present value asset pricing model, we use the tools of large deviations theory to show that even though the constant parameter model would converge to the (constant parameter) Rational Expectations Equilibrium if considered in isolation, the mere presence of an unstable alternative drives it out of consideration.

Keywords: model averaging; asset pricing (search for similar items in EconPapers)
JEL-codes: C63 D84 (search for similar items in EconPapers)
Pages: 39
Date: 2016-04
New Economics Papers: this item is included in nep-ecm, nep-pr~ and nep-mic
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Related works:
Journal Article: Gresham's Law of Model Averaging (2017)
Working Paper: Gresham's Law of Model Averaging (2015)
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