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Computing DSGE Models with Recursive Preferences and Stochastic Volatility

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Author Info

  • Dario Caldara

    (Federal Reserve Board)

  • Jesus Fernandez-Villaverde

    (University of Pennsylvania)

  • Juan Rubio-Ramirez

    (Duke University)

  • Wen Yao

    (University of Pennsylvania)

Abstract

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. (Copyright: Elsevier)

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Bibliographic Info

Article provided by Elsevier for the Society for Economic Dynamics in its journal Review of Economic Dynamics.

Volume (Year): 15 (2012)
Issue (Month): 2 (April)
Pages: 188-206

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Handle: RePEc:red:issued:11-123

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Keywords: DSGE models; Recursive preferences; Perturbation;

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References

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Cited by:
  1. Mennuni, Alessandro, 2013. "Labor Force Composition and Aggregate Fluctuations," Discussion Paper Series In Economics And Econometrics, Economics Division, School of Social Sciences, University of Southampton 1302, Economics Division, School of Social Sciences, University of Southampton.
  2. Francesco Bianchi & Cosmin L. Ilut & Martin Schneider, 2014. "Uncertainty Shocks, Asset Supply and Pricing over the Business Cycle," NBER Working Papers 20081, National Bureau of Economic Research, Inc.
  3. Juan Carlos Parra-Alvarez, 2013. "A comparison of numerical methods for the solution of continuous-time DSGE models," CREATES Research Papers 2013-39, School of Economics and Management, University of Aarhus.
  4. Jules van Binsbergen & Jesús Fernández-Villaverde & Ralph S.J. Koijen & Juan F. Rubio-Ramírez, 2010. "The Term Structure of Interest Rates in a DSGE Model with Recursive Preferences," NBER Working Papers 15890, National Bureau of Economic Research, Inc.
  5. Matthew Smith & Rhys Bidder, 2013. "Robust Animal Spirits," 2013 Meeting Papers, Society for Economic Dynamics 265, Society for Economic Dynamics.
  6. Jang, Tae-Seok, 2012. "Structural estimation of the New-Keynesian Model: a formal test of backward- and forward-looking expectations," MPRA Paper 39669, University Library of Munich, Germany.
  7. Echevarría Olave, Cruz Angel & Iza Padilla, María Amaya, . "Income Taxation and Growth in an OLG Economy: Does Aggregate Uncertainty Play any Role?," DFAEII Working Papers DFAEII;2013-06, University of the Basque Country - Department of Foundations of Economic Analysis II.
  8. Jang, Tae-Seok, 2012. "Structural estimation of the New-Keynesian Model: a formal test of backward- and forward-looking expectations," MPRA Paper 40278, University Library of Munich, Germany.
  9. Nikolay Gospodinov & Damba Lkhagvasuren, 2014. "A Moment‐Matching Method For Approximating Vector Autoregressive Processes By Finite‐State Markov Chains," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 29(5), pages 843-859, 08.
  10. Jang, Tae-Seok, 2012. "Structural estimation of the New-Keynesian model: A formal test of backward- and forward-looking behavior," Economics Working Papers, Christian-Albrechts-University of Kiel, Department of Economics 2012-07, Christian-Albrechts-University of Kiel, Department of Economics.
  11. Neil Shephard, 2013. "Martingale unobserved component models," Economics Papers 2013-W01, Economics Group, Nuffield College, University of Oxford.
  12. Cesa-Bianchi, Ambrogio & Fernandez-Corugedo, Emilio, 2014. "Uncertainty in a model with credit frictions," Bank of England working papers, Bank of England 496, Bank of England.

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