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Likelihood Estimation of DSGE Models with Epstein-Zin Preferences

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Author Info

  • Ralph S.J. Koijen

    (New York University and Tilburg University)

  • Jules H. van Binsbergen

    (Duke University,)

  • Juan F. Rubio-Ramírez

    (Duke University and Federal Reserve Bank of Atlanta.)

  • Jesus Fernandez-Villaverde

    (University of Pennsylvania)

Abstract

This paper illustrates how to perform likelihood-based inference in dynamic stochastic general equilibrium (DSGE) models with Epstein-Zin preferences. This class of preferences has recently become a popular device to account for asset pricing observations and other phenomena that are challenging to address within the traditional state-separable utility framework. However, there has been little econometric work in the area, particularly from a likelihood perspective, because of the difficulty in computing an equilibrium solution to the model and in deriving the likelihood function. To fill this gap, we build a real business cycle model with Epstein-Zin preferences and long run growth, solve it with perturbation techniques, and evaluate its likelihood with the particle filter. We estimate the model using U.S. macro and yield curve data. We discuss the ability of the model to explain the business cycle, asset prices, the comovements between these two, and the implications of our point estimates for the welfare cost of the business cycle.

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Bibliographic Info

Paper provided by Society for Economic Dynamics in its series 2008 Meeting Papers with number 1099.

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Date of creation: 2008
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Handle: RePEc:red:sed008:1099

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Postal: Society for Economic Dynamics Christian Zimmermann Economic Research Federal Reserve Bank of St. Louis PO Box 442 St. Louis MO 63166-0442 USA
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  1. John Y. Campbell, 1995. "Understanding Risk and Return," Harvard Institute of Economic Research Working Papers 1711, Harvard - Institute of Economic Research.
  2. Claudio Campanale & Rui Castro & Gian Luca Clementi, 2007. "Asset Pricing in a Production Economy with ChewÐDekel Preferences," Working Paper Series 07-07, The Rimini Centre for Economic Analysis, revised Jul 2007.
  3. Manuel S. Santos & Adrian Peralta-Alva, 2005. "Accuracy of Simulations for Stochastic Dynamic Models," Econometrica, Econometric Society, vol. 73(6), pages 1939-1976, November.
  4. Jim Dolmas, 2007. "Real business cycle dynamics under first-order risk aversion," Working Papers 0704, Federal Reserve Bank of Dallas.
  5. Levine, Paul & Pearlman, Joseph G. & Pierse, Richard, 2007. "Linear-quadratic approximation, external habit and targeting rules," Working Paper Series 0759, European Central Bank.
  6. Ravi Bansal & Amir Yaron, 2004. "Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles," Journal of Finance, American Finance Association, vol. 59(4), pages 1481-1509, 08.
  7. Christopher A. Sims & Tao Zha, 2006. "Were There Regime Switches in U.S. Monetary Policy?," American Economic Review, American Economic Association, vol. 96(1), pages 54-81, March.
  8. Thomas Tallarini, . "Risk-Sensitive Real Business Cycles," GSIA Working Papers 1997-35, Carnegie Mellon University, Tepper School of Business.
  9. Caldara, Dario & Fernández-Villaverde, Jesús & Rubio-Ramirez, Juan Francisco & Yao, Wen, 2009. "Computing DSGE Models with Recursive Preferences," CEPR Discussion Papers 7312, C.E.P.R. Discussion Papers.
  10. Hansen, Lars Peter & Sargent, Thomas J & Tallarini, Thomas D, Jr, 1999. "Robust Permanent Income and Pricing," Review of Economic Studies, Wiley Blackwell, vol. 66(4), pages 873-907, October.
  11. Campbell, John Y, 1993. "Intertemporal Asset Pricing without Consumption Data," American Economic Review, American Economic Association, vol. 83(3), pages 487-512, June.
  12. Mariano M. Croce, 2006. "Welfare Costs, Long Run Consumption Risk, and a Production Economy," 2006 Meeting Papers 582, Society for Economic Dynamics.
  13. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, December.
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