Computing DSGE Models with Recursive Preferences

This paper compares,di¤erent solution methods,for computing,the equilibrium of dynamic,stochastic general equilibrium,(DSGE) models,with recursive prefer- ences such as those in Epstein and Zin (1989 and 1991). Models with these pref- erences have recently become popular, but we know little about the best ways to implement them numerically. To …ll this gap, we solve the stochastic neoclassical growth,model,with recursive preferences using four di¤erent approaches: second- and third-order perturbation, Chebyshev polynomials, and value function itera- tion. We document the performance of the methods in terms of computing time, implementation complexity, and accuracy. Our main …nding is that a third-order perturbation,is competitive,in terms,of accuracy,with Chebyshev,polynomials and value function iteration, while being an order of magnitude faster to run. Therefore, we conclude that perturbation methods are an attractive approach for computing,this class of problems. Keywords: DSGE Models, Recursive Preferences, Perturbation. JEL classi…cation Numbers: C63, C68, E37. We thank Michel Juillard for his help with computational issues and Larry Christiano, Dirk Krueger, and participants at the Penn Macro lunch for comments. Beyond the usual disclaimer, we must note that any views expressed herein are those of the authors and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. Finally, we also thank the NSF for …nancial support.