Methods to Estimate Dynamic Stochastic General Equilibrium Models

Serie

• 2004 Meeting Papers

Resumen

• This paper employs the one-sector Real Business Cycle model as a testing ground for four different procedures to estimate Dynamic Stochastic General Equilibrium (DSGE) models. The procedures are: 1) Maximum Likelihood, with and without measurement errors and incorporating Bayesian priors, 2) Generalized Method of Moments, 3) Simulated Method of Moments, and 4) Indirect Inference. Monte Carlo analysis indicates that all procedures deliver reasonably good estimates under the null hypothesis. However, there are substantial differences in statistical and computational efficiency in the small samples currently available to estimate DSGE models. GMM and SMM appear to be more robust to misspecification than the alternative procedures. The implications of the stochastic singularity of DSGE models for each estimation method are fully discussed.

autores

• Ruge-Murcia, Francisco Javier

fecha de publicación

• 2004

Área temática

• C11 - Análisis bayesiano: generalidades
• C13 - Estimación: generalidades
• C15 - Métodos de simulación estadística: generalidades
• C32 - Modelos de series temporales; Regresiones cuantiles dinámicas; Modelos dinámicos de tratamiento; procesos de difusión; representación de espacios de estados
• E13 - Neoclásicos

Enfoque geográfico

• Colombia  Country
• Monaco  Country

Líneas de investigación

• DSGE Models
• Estimation Methods
• Monte Carlo Analysis
• Montercarlo
• Stochastic Singularity

Issue

• 83