Gresham’s Law of model averaging

In Koo Cho, Kenneth Kasa

Research output: Contribution to journalReview articlepeer-review


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 asset-pricing model, we use the tools of large deviations theory to show that even though the constant parameter model would converge to the rational expectations equilibrium if considered in isolation, the mere presence of an unstable alternative drives it out of consideration.

Original languageEnglish (US)
Pages (from-to)3589-3616
Number of pages28
JournalAmerican Economic Review
Issue number11
StatePublished - Nov 2017

ASJC Scopus subject areas

  • Economics and Econometrics


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