IDEAS home Printed from
   My bibliography  Save this paper

Computing Models with Recursive Preferences


  • Wen Yao

    (University of Pennsylvania)

  • Juan Rubio Ramirez

    (Duke University)

  • Jesus Fernandez Villaverde

    (University of Pennsylvania)

  • Dario Caldara

    (Institute for International Economic Studies)


This paper compares different solution methods for the computation of the equilibrium of dynamic stochastic general equilibrium (DSGE) models with recursive preferences. Over the last decade, a growing number of researchers have investigated models with recursive preferences of the type first proposed by Kreps and Porteus (1978) and later generalized by Epstein and Zin, (1989 and 1991) and Weil (1990). These economist have been attracted by the extra flexibility of separating risk aversion and intertemporal elasticity of substitution and some for the intuitive appealing of having preferences for early or later resolution of uncertainty. Despite a large manifold of papers using recursive preferences, little is known about the numerical properties of the different solution methods that solve models with these type of preferences. This paper attempts at filling this gap in the literature. We solve the model using three different approaches: value function iteration, Chebyshev polynomials, and perturbation. This paper complements a previous paper by Aruoba, Fernández-Villaverde, and Rubio-Ramírez (2006), where a similar exercise is performed with the neoclassical growth model with CRRA utility function.

Suggested Citation

  • Wen Yao & Juan Rubio Ramirez & Jesus Fernandez Villaverde & Dario Caldara, 2009. "Computing Models with Recursive Preferences," 2009 Meeting Papers 1162, Society for Economic Dynamics.
  • Handle: RePEc:red:sed009:1162

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Olaf Posch & Timo Trimborn, 2010. "Numerical solution of continuous-time DSGE models under Poisson uncertainty," Economics Working Papers 2010-08, Department of Economics and Business Economics, Aarhus University.
    2. Boons, Martijn & Duarte, Fernando M. & de Roon, Frans & Szymanowska, Marta, 2013. "Time-varying inflation risk and the cross section of stock returns," Staff Reports 621, Federal Reserve Bank of New York, revised 01 Nov 2017.
    3. Francois Gourio, 2012. "Disaster Risk and Business Cycles," American Economic Review, American Economic Association, vol. 102(6), pages 2734-2766, October.

    More about this item


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:red:sed009:1162. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christian Zimmermann). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.