Working Paper: CEPR ID: DP9442
Authors: Martin M. Andreasen; Jess Fernández-Villaverde; Juan F. Rubio-Ramirez
Abstract: This paper studies the pruned state-space system for higher-order approximations to the solutions of DSGE models. For second- and third-order approximations, we derive the statistical properties of this system and provide closed-form expressions for first and second unconditional moments and impulse response functions. Thus, our analysis introduces GMM estimation for DSGE models approximated up to third-order and provides the foundation for indirect inference and SMM when simulation is required. We illustrate the usefulness of our approach by estimating a New Keynesian model with habits and Epstein-Zin preferences by GMM when using first and second unconditional moments of macroeconomic and financial data and by SMM when using additional third and fourth unconditional moments and non-Gaussian innovations.
Keywords: Epstein-Zin Preferences; Higher-Order Perturbation Approximation; Non-Gaussian Innovations; Yield Curve
JEL Codes: C15; C53; E30
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| pruned state space system (C69) | estimation of DSGE models (C51) |
| estimation of DSGE models (C51) | capturing nonlinear dynamics of economic models (C22) |
| GMM estimation based on first and second unconditional moments (C51) | efficient parameter estimates (C51) |
| GMM estimation (C51) | sizable habits (E21) |
| GMM estimation (C51) | low Frisch elasticity of labor supply (J49) |
| GMM estimation (C51) | high relative risk aversion (D11) |
| GMM estimation (C51) | high price stickiness (E31) |
| SMM with third and fourth unconditional moments (C29) | nominal term premium (E43) |
| nominal term premium (E43) | implications for monetary policy (E52) |
| pruning method (C24) | ensures that explosive sample paths do not occur almost surely (C41) |