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Computing DSGE Models with Recursive Preferences

  • Dario Caldara

    ()

    (Institute of International Economic Studies, Stockholm University)

  • Jesus Fernandez-Villaverde

    ()

    (Department of Economics, University of Pennsylvania)

  • Juan F. Rubio-Ramirez

    ()

    (Department of Economics, Duke University)

  • Wen Yao

    ()

    (Department of Economics, University of Pennsylvania)

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). Models with these preferences 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 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 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.

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Paper provided by Penn Institute for Economic Research, Department of Economics, University of Pennsylvania in its series PIER Working Paper Archive with number 09-018.

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Length: 41 pages
Date of creation: 25 May 2009
Date of revision:
Handle: RePEc:pen:papers:09-018
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