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Solution-Driven Specification of DSGE Models

Author

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  • Francisco Blasques

    (VU University Amsterdam)

Abstract

This paper proposes a functional specification approach for dynamic stochastic general equilibrium (DSGE) models that explores the properties of the solution method used to approximate policy functions. In particular, the solution-driven specification takes the properties of the solution method directly into account when designing the structural model in order to deliver enhanced flexibility and facilitate parameter identification within the structure imposed by the underlying economic theory. A prototypical application reveals the importance of this method in improving the specification of functional nonlinearities that are consistent with economic theory. The solution-driven specification is also shown to have the potential to greatly improve model fit and provide alternative policy recommendations when compared to standard DSGE model designs.

Suggested Citation

  • Francisco Blasques, 2013. "Solution-Driven Specification of DSGE Models," Tinbergen Institute Discussion Papers 13-062/III, Tinbergen Institute.
  • Handle: RePEc:tin:wpaper:20130062
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    File URL: http://papers.tinbergen.nl/13062.pdf
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    References listed on IDEAS

    as
    1. Fernandez-Villaverde, Jesus & Rubio-Ramirez, Juan F., 2006. "Solving DSGE models with perturbation methods and a change of variables," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2509-2531, December.
    2. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, October.
    3. Jesus Fernandez-Villaverde & Pablo Guerron-Quintana & Juan F. Rubio-Ramirez & Martin Uribe, 2011. "Risk Matters: The Real Effects of Volatility Shocks," American Economic Review, American Economic Association, vol. 101(6), pages 2530-2561, October.
    4. Kim, Jinill & Ruge-Murcia, Francisco J., 2009. "How much inflation is necessary to grease the wheels?," Journal of Monetary Economics, Elsevier, vol. 56(3), pages 365-377, April.
    5. Diewert, Walter E & Wales, Terence J, 1987. "Flexible Functional Forms and Global Curvature Conditions," Econometrica, Econometric Society, vol. 55(1), pages 43-68, January.
    6. Ruge-Murcia, Francisco, 2012. "Estimating nonlinear DSGE models by the simulated method of moments: With an application to business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 36(6), pages 914-938.
    7. Blanchard, Olivier Jean & Kahn, Charles M, 1980. "The Solution of Linear Difference Models under Rational Expectations," Econometrica, Econometric Society, vol. 48(5), pages 1305-1311, July.
    8. 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.
    9. 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.
    10. Gourieroux, C & Monfort, A & Renault, E, 1993. "Indirect Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 85-118, Suppl. De.
    11. Judd, Kenneth L., 1992. "Projection methods for solving aggregate growth models," Journal of Economic Theory, Elsevier, vol. 58(2), pages 410-452, December.
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    Citations

    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Solution-Driven Specification of DSGE Models
      by Christian Zimmermann in NEP-DGE blog on 2013-05-08 18:34:28

    More about this item

    Keywords

    Nonlinear Model Specification; DSGE; Perturbation Solutions;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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