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Méthodes de simulation des modèles stochastiques d'équilibre général

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  • Tarik Ocaktan
  • Michel Juillard

Abstract

[eng] This paper presents the numerical methods commonly used today to solve dynamic stochastic general equilibrium (DSGE) models. We begin by introducing a canonical model of dynamic optimization, which is the crucial element in this approach. We then review value-function iteration, the projection method, the parameterized expectation approach (PEA), and the perturbation method. Linearization, a very popular method in the literature, is presented as a special case of the perturbation method. [fre] Ce chapitre introduit les méthodes de simulation utilisées aujourd’hui pour résoudre les modèles d’équilibre général. Après la présentation d’un modèle canonique d’optimisation dynamique qui est au coeur de cette problématique, nous passons en revue les méthodes d’itération sur la fonction valeur, de projection, de paramétrisation des anticipations (PEA) et la méthode des perturbations. La linéarisation, très populaire dans cette littérature, est présentée comme un cas particulier de la méthode des perturbations.

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  • Tarik Ocaktan & Michel Juillard, 2008. "Méthodes de simulation des modèles stochastiques d'équilibre général," Économie et Prévision, Programme National Persée, vol. 183(2), pages 115-126.
  • Handle: RePEc:prs:ecoprv:ecop_0249-4744_2008_num_183_2_7809
    DOI: 10.3406/ecop.2008.7809
    Note: DOI:10.3406/ecop.2008.7809
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    1. Christiano, Lawrence J. & Fisher, Jonas D. M., 2000. "Algorithms for solving dynamic models with occasionally binding constraints," Journal of Economic Dynamics and Control, Elsevier, vol. 24(8), pages 1179-1232, July.
    2. Christiano, Lawrence J, 2002. "Solving Dynamic Equilibrium Models by a Method of Undetermined Coefficients," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 21-55, October.
    3. King, Robert G & Watson, Mark W, 2002. "System Reduction and Solution Algorithms for Singular Linear Difference Systems under Rational Expectations," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 57-86, October.
    4. Christiano, Lawrence J, 1990. "Linear-Quadratic Approximation and Value-Function Iteration: A Comparison," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 99-113, January.
    5. McGrattan, Ellen R., 1996. "Solving the stochastic growth model with a finite element method," Journal of Economic Dynamics and Control, Elsevier, vol. 20(1-3), pages 19-42.
    6. Anderson, Evan W. & McGrattan, Ellen R. & Hansen, Lars Peter & Sargent, Thomas J., 1996. "Mechanics of forming and estimating dynamic linear economies," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 4, pages 171-252, Elsevier.
    7. Tauchen, George, 1990. "Solving the Stochastic Growth Model by Using Quadrature Methods and Value-Function Iterations," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 49-51, January.
    8. Miranda, Mario J, 1998. "Numerical Strategies for Solving the Nonlinear Rational Expectations Commodity Market Model," Computational Economics, Springer;Society for Computational Economics, vol. 11(1-2), pages 71-87, April.
    9. Wright, Brian D & Williams, Jeffrey C, 1982. "The Economic Role of Commodity Storage," Economic Journal, Royal Economic Society, vol. 92(367), pages 596-614, September.
    10. Gaspar, Jess & L. Judd, Kenneth, 1997. "Solving Large-Scale Rational-Expectations Models," Macroeconomic Dynamics, Cambridge University Press, vol. 1(1), pages 45-75, January.
    11. Fabrice Collard & Patrick Feve & Corinne Perraudin, 2000. "Solving and Estimating Dynamic Models under Rational Expectations," Computational Economics, Springer;Society for Computational Economics, vol. 15(3), pages 201-221, June.
    12. 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.
    13. Albert Marcet & David A. Marshall, 1994. "Solving nonlinear rational expectations models by parameterized expectations: convergence to stationary solutions," Discussion Paper / Institute for Empirical Macroeconomics 91, Federal Reserve Bank of Minneapolis.
    14. Collard, Fabrice & Juillard, Michel, 2001. "Accuracy of stochastic perturbation methods: The case of asset pricing models," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 979-999, June.
    15. 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.
    16. Rust, John, 1996. "Numerical dynamic programming in economics," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 14, pages 619-729, Elsevier.
    17. 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.
    18. Klein, Paul, 2000. "Using the generalized Schur form to solve a multivariate linear rational expectations model," Journal of Economic Dynamics and Control, Elsevier, vol. 24(10), pages 1405-1423, September.
    19. Miranda, Mario J & Helmberger, Peter G, 1988. "The Effects of Commodity Price Stabilization Programs," American Economic Review, American Economic Association, vol. 78(1), pages 46-58, March.
    20. Burkhard Heer & Alfred Maußner, 2024. "Dynamic General Equilibrium Modeling," Springer Texts in Business and Economics, Springer, edition 3, number 978-3-031-51681-8, June.
    21. Judd, Kenneth L. & Guu, Sy-Ming, 1997. "Asymptotic methods for aggregate growth models," Journal of Economic Dynamics and Control, Elsevier, vol. 21(6), pages 1025-1042, June.
    22. 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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    2. Nicolas Maggiar & Antoine Devulder & Christophe Cahn & Stéphane Adjemian, 2008. "Variantes en univers incertain," Économie et Prévision, Programme National Persée, vol. 183(2), pages 223-238.
    3. Tsasa Vangu, Jean-Paul Kimbambu, 2014. "Diagnostic de la politique monétaire en Rép. Dém. Congo – Approche par l’Equilibre Général Dynamique Stochastique," Dynare Working Papers 38, CEPREMAP.

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