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Taking Perturbation to the Accuracy Frontier: A Hybrid of Local and Global Solutions

Author

Listed:
  • Lilia Maliar

    (Universidad de Alicante, Hoover Institution - Hoover Institution)

  • Serguei Maliar

    (Hoover Institution - Hoover Institution, Dept. of Fundamentos del Analisis Economico - Universidad de Alicante)

  • Sébastien Villemot

    (PSE - Paris-Jourdan Sciences Economiques - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - INRA - Institut National de la Recherche Agronomique - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

Local perturbation) methods compute solutions in one point and tend to deliver far lower accuracy levels than global solution methods. We develop a hybrid method that solves for some policy functions locally (using a perturbation method) and that solves for the other policy functions globally (using closed-form expressions and a numerical solver). We applied our hybrid method to solve large-scale RBC models used in the comparison analysis of Kollmann et al. (J Econ Dyn Control 35:186-202, 2011b). We obtain more accurate solutions than those produced by any other (either local or global) solution method participating in that comparison. Our running time is a few seconds.

Suggested Citation

  • Lilia Maliar & Serguei Maliar & Sébastien Villemot, 2012. "Taking Perturbation to the Accuracy Frontier: A Hybrid of Local and Global Solutions," PSE-Ecole d'économie de Paris (Postprint) hal-00813057, HAL.
    • Handle: RePEc:hal:pseptp:hal-00813057
    DOI: 10.1007/s10614-012-9342-y
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    References listed on IDEAS

    as
    1. Kollmann, Robert & Maliar, Serguei & Malin, Benjamin A. & Pichler, Paul, 2011. "Comparison of solutions to the multi-country Real Business Cycle model," Journal of Economic Dynamics and Control, Elsevier, vol. 35(2), pages 186-202, February.
    2. Kollmann, Robert & Kim, Jinill & Kim, Sunghyun H., 2011. "Solving the multi-country Real Business Cycle model using a perturbation method," Journal of Economic Dynamics and Control, Elsevier, vol. 35(2), pages 203-206, February.
    3. Juillard, Michel & Villemot, Sébastien, 2011. "Multi-country real business cycle models: Accuracy tests and test bench," Journal of Economic Dynamics and Control, Elsevier, vol. 35(2), pages 178-185, February.
    4. Aruoba, S. Boragan & Fernandez-Villaverde, Jesus & Rubio-Ramirez, Juan F., 2006. "Comparing solution methods for dynamic equilibrium economies," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2477-2508, December.
    5. Dotsey, Michael & Mao, Ching Sheng, 1992. "How well do linear approximation methods work? : The production tax case," Journal of Monetary Economics, Elsevier, vol. 29(1), pages 25-58, February.
    6. Adjemian, Stéphane & Bastani, Houtan & Juillard, Michel & Karamé, Fréderic & Maih, Junior & Mihoubi, Ferhat & Mutschler, Willi & Perendia, George & Pfeifer, Johannes & Ratto, Marco & Villemot, Sébasti, 2011. "Dynare: Reference Manual Version 4," Dynare Working Papers 1, CEPREMAP, revised Mar 2021.
    7. Gomme, Paul & Klein, Paul, 2011. "Second-order approximation of dynamic models without the use of tensors," Journal of Economic Dynamics and Control, Elsevier, vol. 35(4), pages 604-615, April.
    8. Kenneth L. Judd & Lilia Maliar & Serguei Maliar, 2011. "Numerically stable and accurate stochastic simulation approaches for solving dynamic economic models," Quantitative Economics, Econometric Society, vol. 2(2), pages 173-210, July.
    9. Lilia Maliar & Serguei Maliar, 2003. "The Representative Consumer in the Neoclassical Growth Model with Idiosyncratic Shocks," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 6(2), pages 368-380, April.
    10. Kenneth L. Judd & Lilia Maliar & Serguei Maliar & Inna Tsener, 2017. "How to solve dynamic stochastic models computing expectations just once," Quantitative Economics, Econometric Society, vol. 8(3), pages 851-893, November.
    11. Gaspar, Jess & L. Judd, Kenneth, 1997. "Solving Large-Scale Rational-Expectations Models," Macroeconomic Dynamics, Cambridge University Press, vol. 1(1), pages 45-75, January.
    12. Lombardo, Giovanni, 2010. "On approximating DSGE models by series expansions," Working Paper Series 1264, European Central Bank.
    13. Collard, Fabrice & Juillard, Michel, 2001. "A Higher-Order Taylor Expansion Approach to Simulation of Stochastic Forward-Looking Models with an Application to a Nonlinear Phillips Curve Model," Computational Economics, Springer;Society for Computational Economics, vol. 17(2-3), pages 125-139, June.
    14. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Solving dynamic general equilibrium models using a second-order approximation to the policy function," Journal of Economic Dynamics and Control, Elsevier, vol. 28(4), pages 755-775, January.
    15. Pichler, Paul, 2011. "Solving the multi-country Real Business Cycle model using a monomial rule Galerkin method," Journal of Economic Dynamics and Control, Elsevier, vol. 35(2), pages 240-251, February.
    16. Judd, Kenneth L., 1992. "Projection methods for solving aggregate growth models," Journal of Economic Theory, Elsevier, vol. 58(2), pages 410-452, December.
    17. Maliar, Serguei & Maliar, Lilia & Judd, Kenneth, 2011. "Solving the multi-country real business cycle model using ergodic set methods," Journal of Economic Dynamics and Control, Elsevier, vol. 35(2), pages 207-228, February.
    18. Chen, Baoline & Zadrozny, Peter A., 2009. "Multi-step perturbation solution of nonlinear differentiable equations applied to an econometric analysis of productivity," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2061-2074, April.
    19. 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.
    20. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, April.
    21. Den Haan, Wouter J. & De Wind, Joris, 2012. "Nonlinear and stable perturbation-based approximations," Journal of Economic Dynamics and Control, Elsevier, vol. 36(10), pages 1477-1497.
    22. Gary S. Anderson & Andrew T. Levin & Eric T. Swanson, 2006. "Higher-order perturbation solutions to dynamic, discrete-time rational expectations models," Working Paper Series 2006-01, Federal Reserve Bank of San Francisco.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Arellano, Cristina & Maliar, Lilia & Maliar, Serguei & Tsyrennikov, Viktor, 2016. "Envelope condition method with an application to default risk models," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 436-459.
    2. Lepetyuk, Vadym & Maliar, Lilia & Maliar, Serguei, 2020. "When the U.S. catches a cold, Canada sneezes: A lower-bound tale told by deep learning," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    3. Balcilar, Mehmet & Gupta, Rangan & Kotzé, Kevin, 2015. "Forecasting macroeconomic data for an emerging market with a nonlinear DSGE model," Economic Modelling, Elsevier, vol. 44(C), pages 215-228.
    4. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    5. Mutschler, Willi, 2018. "Higher-order statistics for DSGE models," Econometrics and Statistics, Elsevier, vol. 6(C), pages 44-56.
    6. Vadym Lepetyuk & Lilia Maliar & Serguei Maliar, 2017. "Should Central Banks Worry About Nonlinearities of their Large-Scale Macroeconomic Models?," Staff Working Papers 17-21, Bank of Canada.
    7. Kenneth L. Judd & Lilia Maliar & Serguei Maliar, 2017. "Lower Bounds on Approximation Errors to Numerical Solutions of Dynamic Economic Models," Econometrica, Econometric Society, vol. 85, pages 991-1012, May.
    8. Hänsel, Matthias, 2024. "Solving the Diamond–Mortensen–Pissarides model: A hybrid perturbation approach," Economics Letters, Elsevier, vol. 236(C).

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    More about this item

    Keywords

    Dynare; Perturbation; Hybrid; Accuracy; Numerical methods; Approximation;
    All these keywords.

    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
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics

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