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Un Modelo Estadístico Flexible para la Estructura Intertemporal de Tasas en Chile

Author

Listed:
  • Dante Jara

    (Corporacion Financiera de Desarrollo)

Abstract

El presente trabajo plantea un modelo estadístico flexible que captura paramétricamente la compleja condicionalidad y desvíos de normalidad que caracteriza a la estructura intertemporal de tasas de interés en la economía chilena entre los años 1992 y 2003. El modelo general consiste en una aproximación SemiNoParamétrica a la densidad condicional del proceso conjunto que siguen las tasas a 6 meses y 5 años. Este trabajo realiza el ejercicio de elección del mejor modelo, escogiendo el grado de flexibilidad necesario para capturar los hechos estilizados, por lo que son los datos los que indican la forma funcional específica para su densidad conjunta. Se implementa un algoritmo de simulación del modelo estadístico estimado, lo cual permite simular series artificiales de estructura de tasas a fin de verificar sus principales regularidades empíricas. El modelo SNP estimado puede ser utilizado como métrica para discriminar entre modelos alternativos de equilibrio general que pretendan dar cuenta de los hechos estilizados de estructura de tasas en la economía chilena.

Suggested Citation

  • Dante Jara, 2004. "Un Modelo Estadístico Flexible para la Estructura Intertemporal de Tasas en Chile," Econometrics 0412010, EconWPA.
  • Handle: RePEc:wpa:wuwpem:0412010
    Note: Type of Document - pdf; pages: 29
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    References listed on IDEAS

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    1. Gallant, Ronald & Tauchen, George, 1989. "Seminonparametric Estimation of Conditionally Constrained Heterogeneous Processes: Asset Pricing Applications," Econometrica, Econometric Society, vol. 57(5), pages 1091-1120, September.
    2. Ronald Gallant, A. & Tauchen, George, 1999. "The relative efficiency of method of moments estimators1," Journal of Econometrics, Elsevier, vol. 92(1), pages 149-172, September.
    3. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1993. "Nonlinear Dynamic Structures," Econometrica, Econometric Society, vol. 61(4), pages 871-907, July.
    4. White, Halbert, 1980. "Using Least Squares to Approximate Unknown Regression Functions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(1), pages 149-170, February.
    5. Fenton, Victor M. & Gallant, A. Ronald, 1996. "Qualitative and asymptotic performance of SNP density estimators," Journal of Econometrics, Elsevier, vol. 74(1), pages 77-118, September.
    6. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1992. "Stock Prices and Volume," Review of Financial Studies, Society for Financial Studies, vol. 5(2), pages 199-242.
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    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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