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En busca de un modelo Benchmark univariado para predecir la tasa de desempleo

Author

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  • Javier Contreras-Reyes

    ()

  • Byron Idrovo

    ()

Abstract

En este trabajo se analiza la precisión y la estabilidad de las predicciones de la tasa de desempleo de Chile, obtenidas de una familia de modelos SARIMA, entre febrero de 1986 y febrero de 2010. Las proyecciones SARIMA son comparadas con las provenientes de modelos univariados, incluyendo los benchmarks predictivos. Simultáneamente, se ajustó un modelo ARFIMA (Autorregresive Fractionary Integrated Moving Average), debido a los signos de persistencia que muestra el indicador de desempleo en su comportamiento; sin embargo, a partir de los métodos de estimación de Reisen (1994), Geweke et al. (1983) y Whittle (1962) se obtuvieron parámetros de integración mayores que 0.5, lo que empíricamente sustenta el tratamiento de la tasa de desempleo como una serie no estacionaria. La evaluación de la capacidad predictiva de los modelos se centra en las proyecciones fuera de muestra de 1, 6 y 12 meses hacia adelante. Los resultados indican que el RECM fuera de muestra de las proyecciones SARIMA es menor que el de los métodos univariados considerados.

Suggested Citation

  • Javier Contreras-Reyes & Byron Idrovo, 2011. "En busca de un modelo Benchmark univariado para predecir la tasa de desempleo," REVISTA CUADERNOS DE ECONOMÍA, UN - RCE - CID, December.
  • Handle: RePEc:col:000093:009216
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    References listed on IDEAS

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    1. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, pages 1545-1578.
    2. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
    3. Raphael Bergoeing & Felipe Morandé & Facundo Piguillem, 2005. "Labor Market Distortions, Employment and Growth: The Recent Chilean Experience," Central Banking, Analysis, and Economic Policies Book Series,in: Rómulo A. Chumacero & Klaus Schmidt-Hebbel & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (S (ed.), General Equilibrium Models for the Chilean Economy, edition 1, volume 9, chapter 12, pages 395-414 Central Bank of Chile.
    4. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
    5. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, pages 788-829.
    6. Rómulo Chumacero & Jorge Quiroz, 1996. "La Tasa Natural de Crecimiento de la Economía Chilena: 1985-1996," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 33(100), pages 453-472.
    7. Pablo Pincheira Brown & Álvaro García Marín, 2009. "Forecasting Inflation in Chile With an Accurate Benchmark," Working Papers Central Bank of Chile 514, Central Bank of Chile.
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    Citations

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    Cited by:

    1. Idrovo Aguirre, Byron & Contreras, Javier, 2015. "Back-splicing of cement production and characterization of its economic cycle: The case of Chile (1991-2015)," MPRA Paper 67387, University Library of Munich, Germany, revised 20 Sep 2015.
    2. Pablo Pincheira B., 2014. "Predictive Evaluation of Sectoral and Total Employment Based on Entrepreneurial Confidence Indicators," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 17(1), pages 66-87, April.
    3. Javier Contreras-Reyes & Wilfredo Palma, 2013. "Statistical analysis of autoregressive fractionally integrated moving average models in R," Computational Statistics, Springer, vol. 28(5), pages 2309-2331, October.

    More about this item

    Keywords

    tasa de desempleo; SARIMA; ARFIMA; benchmarks predictivos; Chile.;

    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General

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