IDEAS home Printed from https://ideas.repec.org/a/wly/quante/v9y2018i2p903-944.html
   My bibliography  Save this article

Solution methods for models with rare disasters

Author

Listed:
  • Jesús Fernández‐Villaverde
  • Oren Levintal

Abstract

This paper compares different solution methods for computing the equilibrium of dynamic stochastic general equilibrium (DSGE) models with rare disasters along the lines of those proposed by Rietz (1988), Barro (2006), Gabaix (2012), and Gourio (2012). DSGE models with rare disasters require solution methods that can handle the large nonlinearities triggered by low‐probability, high‐impact events with accuracy and speed. We solve a standard New Keynesian model with Epstein–Zin preferences and time‐varying disaster risk with perturbation, Taylor projection, and Smolyak collocation. Our main finding is that Taylor projection delivers the best accuracy/speed tradeoff among the tested solutions. We also document that even third‐order perturbations may generate solutions that suffer from accuracy problems and that Smolyak collocation can be costly in terms of run time and memory requirements.

Suggested Citation

  • Jesús Fernández‐Villaverde & Oren Levintal, 2018. "Solution methods for models with rare disasters," Quantitative Economics, Econometric Society, vol. 9(2), pages 903-944, July.
  • Handle: RePEc:wly:quante:v:9:y:2018:i:2:p:903-944
    as

    Download full text from publisher

    File URL: https://doi.org/10.3982/QE744
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Fernández-Villaverde, Jesús & Gordon, Grey & Guerrón-Quintana, Pablo & Rubio-Ramírez, Juan F., 2015. "Nonlinear adventures at the zero lower bound," Journal of Economic Dynamics and Control, Elsevier, vol. 57(C), pages 182-204.
    2. Isoré, Marlène & Szczerbowicz, Urszula, 2017. "Disaster risk and preference shifts in a New Keynesian model," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 97-125.
    3. Gourio, François & Siemer, Michael & Verdelhan, Adrien, 2013. "International risk cycles," Journal of International Economics, Elsevier, vol. 89(2), pages 471-484.
    4. Martin M Andreasen & Jesús Fernández-Villaverde & Juan F Rubio-Ramírez, 2018. "The Pruned State-Space System for Non-Linear DSGE Models: Theory and Empirical Applications," Review of Economic Studies, Oxford University Press, vol. 85(1), pages 1-49.
    5. Jerry Tsai & Jessica A. Wachter, 2015. "Disaster Risk and its Implications for Asset Pricing," NBER Working Papers 20926, National Bureau of Economic Research, Inc.
    6. Jessica A. Wachter, 2013. "Can Time-Varying Risk of Rare Disasters Explain Aggregate Stock Market Volatility?," Journal of Finance, American Finance Association, vol. 68(3), pages 987-1035, June.
    7. Judd, Kenneth L. & Maliar, Lilia & Maliar, Serguei & Valero, Rafael, 2014. "Smolyak method for solving dynamic economic models: Lagrange interpolation, anisotropic grid and adaptive domain," Journal of Economic Dynamics and Control, Elsevier, vol. 44(C), pages 92-123.
    8. Martin Andreasen, 2012. "On the Effects of Rare Disasters and Uncertainty Shocks for Risk Premia in Non-Linear DSGE Models," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 15(3), pages 295-316, July.
    9. Xavier Gabaix, 2012. "Variable Rare Disasters: An Exactly Solved Framework for Ten Puzzles in Macro-Finance," The Quarterly Journal of Economics, Oxford University Press, vol. 127(2), pages 645-700.
    10. repec:eee:macchp:v2-527 is not listed on IDEAS
    11. Epstein, Larry G & Zin, Stanley E, 1989. "Substitution, Risk Aversion, and the Temporal Behavior of Consumption and Asset Returns: A Theoretical Framework," Econometrica, Econometric Society, vol. 57(4), pages 937-969, July.
    12. Malin, Benjamin A. & Krueger, Dirk & Kubler, Felix, 2011. "Solving the multi-country real business cycle model using a Smolyak-collocation method," Journal of Economic Dynamics and Control, Elsevier, vol. 35(2), pages 229-239, February.
    13. Marlène Isoré & Urszula Szczerbowicz, 2013. "Disaster Risk in a New Keynesian Model," Working Papers 2013-12, CEPII research center.
    14. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, Elsevier.
    15. repec:eee:dyncon:v:80:y:2017:i:c:p:1-16 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Robert J. Barro & Jesús Fernández-Villaverde & Oren Levintal & Andrew Mollerus, 2014. "Safe Assets," NBER Working Papers 20652, National Bureau of Economic Research, Inc.
      • Barro, Robert J. & Fern�ndez-Villaverde, Jes�s & Levintal, Oren & Mollerus, Andrew, 2017. "Safe Assets," CEPR Discussion Papers 12043, C.E.P.R. Discussion Papers.
      • Robert Barro & Jesus Fernandez-Villaverde & Oren Levintal & Andrew Mollerus, 2017. "Safe Assets," PIER Working Paper Archive 17-008, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 10 May 2017.
    2. Giorgio Fagiolo & Andrea Roventini, 2017. "Macroeconomic Policy in DSGE and Agent-Based Models Redux: New Developments and Challenges Ahead," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(1), pages 1-1.
    3. repec:eee:macchp:v2-527 is not listed on IDEAS
    4. Isoré, Marlène & Szczerbowicz, Urszula, 2017. "Disaster risk and preference shifts in a New Keynesian model," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 97-125.
    5. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, Elsevier.
    6. repec:eee:dyncon:v:80:y:2017:i:c:p:1-16 is not listed on IDEAS
    7. Sergey Ivashchenko & Semih Emre Çekin & Kevin Kotzé & Rangan Gupta, 2018. "Forecasting with Second-Order Approximations and Markov Switching DSGE Models," Working Papers 201862, University of Pretoria, Department of Economics.
    8. Giovanni Dosi & Andrea Roventini, 2019. "More is different ... and complex! the case for agent-based macroeconomics," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 1-37, March.

    More about this item

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    Statistics

    Access and download statistics

    Corrections

    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:wly:quante:v:9:y:2018:i:2:p:903-944. 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: (Wiley Content Delivery). General contact details of provider: http://edirc.repec.org/data/essssea.html .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.