Working Paper: CEPR ID: DP5207
Authors: Sungbae An; Frank Schorfheide
Abstract: 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.
Keywords: Bayesian analysis; DSGE models; Model evaluation; Vector autoregressions
JEL Codes: C11; C32; C51; C52
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| monetary policy shocks (E39) | inflation (E31) |
| monetary policy shocks (E39) | output growth (O40) |
| Bayesian estimation techniques (C11) | posterior distributions for model parameters (C46) |
| posterior distributions for model parameters (C46) | causal interpretations of structural shocks (E32) |
| first-order and second-order accurate solutions (C69) | estimation of parameters related to price stickiness and monetary policy response (C54) |
| Bayesian methods (C11) | credibility of DSGE models in informing policy decisions (E13) |