Comparing dynamic equilibrium models to data: A Bayesian approach
Abstract
This paper studies the properties of the Bayesian approach to estimation and comparison
of dynamic equilibrium economies. Both tasks can be performed even if the models are
nonnested, misspecified, and nonlinear. First, we show that Bayesian methods have
a classical interpretation: asymptotically, the parameter point estimates converge
to their pseudotrue values, and the best model under the Kullback-Leibler distance
will have the highest posterior probability. Second, we illustrate the strong small
sample behavior of the approach using a well-known application: the U.S. cattle cycle.
Bayesian estimates outperform maximum likelihood results, and the proposed model is
easily compared with a set of BVARs. © 2003 Elsevier B.V. All rights reserved.
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https://hdl.handle.net/10161/1903Published Version (Please cite this version)
10.1016/j.jeconom.2003.10.031Publication Info
Fernández-Villaverde, J; & Rubio-Ramírez, JF (2004). Comparing dynamic equilibrium models to data: A Bayesian approach. Journal of Econometrics, 123(1). pp. 153-187. 10.1016/j.jeconom.2003.10.031. Retrieved from https://hdl.handle.net/10161/1903.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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