Computing DSGE Models with Recursive Preferences and Stochastic Volatility
Institute for International Economic Studies
University of Pennsylvania - Department of Economics; National Bureau of Economic Research (NBER)
Juan Francisco Rubio-Ramirez
Duke University - Department of Economics; Federal Reserve Bank of Atlanta - Research Department
University of Pennsylvania - Department of Economics
January 10, 2012
FEDS Working Paper No. 2012-04
This paper compares different solution methods for computing the equilibrium of dynamic stochastic general equilibrium (DSGE) models with recursive preferences such as those in Epstein and Zin (1989 and 1991) and stochastic volatility. Models with these two features have recently become popular, but we know little about the best ways to implement them numerically. To fill this gap, we solve the stochastic neoclassical growth model with recursive preferences and stochastic volatility using four different approaches: second- and third-order perturbation, Chebyshev polynomials, and value function iteration. We document the performance of the methods in terms of computing time, implementation complexity, and accuracy. Our main finding is that perturbations are competitive in terms of accuracy with Chebyshev polynomials and value function iteration while being several orders of magnitude faster to run. Therefore, we conclude that perturbation methods are an attractive approach for computing this class of problems.
Number of Pages in PDF File: 44
Keywords: DSGE models, recursive preferences, perturbation
JEL Classification: C63, C68, E32working papers series
Date posted: February 1, 2012
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