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Prueba de hipótesis sobre la existencia de una raíz fraccional en una serie de tiempo no estacionaria

Author

Listed:
  • Lemus Polanía, Diego Fernando
  • Castaño Vélez, Elkin Argemiro

Abstract

RESUMEN: En este trabajo se propone una modificación de la prueba de hipótesis propuesta por Castano, Gómez y Gallón (2008) para determinar la existencia de memoria larga en un proceso ARFIMA(p,d,q) estacionario e invertible. En el caso puntual de los procesos ARFIMA(p,d,q), esta modificación permite determinar la existencia de una raíz fraccional en una serie de tiempo no estacionaria cuyo componente ARMA de corto plazo es indeterminado o desconocido. Vía simulaciones de Monte Carlo, se validan los resultados analíticos obtenidos en el trabajo y se demuestra el buen comportamiento de la prueba propuesta, en términos de potencia y tamano, en comparación con otras metodologías disponibles en la literatura.

Suggested Citation

  • Lemus Polanía, Diego Fernando & Castaño Vélez, Elkin Argemiro, 2013. "Prueba de hipótesis sobre la existencia de una raíz fraccional en una serie de tiempo no estacionaria," Revista Lecturas de Economía, Universidad de Antioquia, CIE, issue 78, pages 151-184, March.
  • Handle: RePEc:col:000174:014811
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    Cited by:

    1. Mateo Isoardi & Luis A. Gil-Alana, 2019. "Inflation in Argentina: Analysis of Persistence Using Fractional Integration," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 45(2), pages 204-223, April.

    More about this item

    Keywords

    Series de tiempo de memoria larga; parámetro de diferenciación fraccional; aproximación autorregresiva; proceso ARFIMA no estacionario;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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