Bayesian Analysis of DSGE Models

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 a reference model, as well as the estimation of second-order accurate solutions of DSGE models. These methods are applied to data generated from a linearized DSGE model, a vector autoregression that violates the cross-coefficient restrictions implied by the linearized DSGE model, and a DSGE model that was solved with a second-order perturbation method.