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Método numérico para la calibración de un modelo DSGE

Author

Listed:
  • Pietro Bonaldi
  • Andrés González
  • Juan David Prada
  • Diego A. Rodríguez

Abstract

En este artículo se propone un método numérico para la calibración de un modelode equilibrio general dinámico y estocástico (DSGE). Esencialmente, éste consisteen utilizar un algoritmo híbrido de optimización, primero para encontrar un estadoestacionario del modelo, y luego para minimizar una función objetivo que se definesegún cuál sea el propósito del investigador con el proceso de calibración. El algoritmopropuesto consiste en una aplicación del Simulated Annealing seguida de métodostradicionales de optimización. Las bondades del algoritmo se analizan mediante simulacionesde Monte Carlo usando un modelo de economía cerrada cuyo estado estacionariono tiene solución analítica. Los resultados de este ejercicio muestran que el algoritmopropuesto genera resultados más precisos utilizando menos recursos computacionalesque alternativas tradicionales. Por último se presentan los resultados de la calibraciónde un modelo para la economía colombiana que consta de 179 ecuaciones y que seajusta a 50 razones con 50 parámetros. La máxima desviación porcentual entre lasrazones del modelo y los valores correspondientes de la economía colombiana es de7;9% y en 29 de los 50 casos, esta desviación es menor o igual al 1%.

Suggested Citation

  • Pietro Bonaldi & Andrés González & Juan David Prada & Diego A. Rodríguez, 2009. "Método numérico para la calibración de un modelo DSGE," Borradores de Economia 5265, Banco de la Republica.
  • Handle: RePEc:col:000094:005265
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    References listed on IDEAS

    as
    1. Andrés González & Lavan Mahadeva & Juan D. Prada & Diego Rodríguez, 2011. "Policy Analysis Tool Applied to Colombian Needs: Patacon Model Description," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 29(66), pages 222-245, December.
    2. 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.
    3. Juan Carlos Parra Alvarez, 2008. "Hechos Estilizados de la Economía Colombiana:Fundamentos Empíricos para la Construcción y Evaluación de un Modelo DSGE," Borradores de Economia 4602, Banco de la Republica.
    4. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-1370, November.
    5. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
    6. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
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    Cited by:

    1. Sergio Ocampo Díaz, 2011. "Agentes no ricardianos y rigideces nominales: su efecto sobre el principio de Taylor," Vniversitas Económica 8302, Universidad Javeriana - Bogotá.
    2. Ramiro Rodríguez Revilla, 2011. "Modelos de equilibrio general dinámicos y estocásticos para Colombia 1995-2011," Revista Ecos de Economía, Universidad EAFIT, December.
    3. Gomez Ospina, Monica A., 2023. "Optimal monetary policy in developing countries: The role of informality," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
    4. Andres Gonzalez & Alexander Guarin & Diego A. Rodriguez-Guzman & Hernando Vargas-Herrera, 2020. "4GM: A New Model for the Monetary Policy Analysis in Colombia," Borradores de Economia 1106, Banco de la Republica de Colombia.

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    More about this item

    Keywords

    Simulated Annealing; calibración; DSGE; estado estacionario.;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General

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