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Bayesian Analysis of DSGE Models

Listed author(s):
  • Sungbae An
  • Frank Schorfheide

This paper reviews Bayesian methods that have been developed in recent years to estimate and evaluate dynamic stochastic general equilibrium (DSGE) models. We consider the estimation of linearized DSGE models, the evaluation of models based on Bayesian model checking, posterior odds comparisons, and comparisons to vector autoregressions, as well as the non-linear estimation based on a second-order accurate model solution. These methods are applied to data generated from correctly specified and misspecified linearized DSGE models and a DSGE model that was solved with a second-order perturbation method.

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Article provided by Taylor & Francis Journals in its journal Econometric Reviews.

Volume (Year): 26 (2007)
Issue (Month): 2-4 ()
Pages: 113-172

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Handle: RePEc:taf:emetrv:v:26:y:2007:i:2-4:p:113-172
DOI: 10.1080/07474930701220071
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