Comparing dynamic equilibrium models to data: A Bayesian approach

Published

Journal Article

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.

Full Text

Cited Authors

  • Fernández-Villaverde, J; Rubio-Ramírez, JF

Published Date

  • November 1, 2004

Published In

Volume / Issue

  • 123 / 1

Start / End Page

  • 153 - 187

International Standard Serial Number (ISSN)

  • 0304-4076

Digital Object Identifier (DOI)

  • 10.1016/j.jeconom.2003.10.031

Citation Source

  • Scopus