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Seasonal and Long Run Fractional Integration in the Industrial Production Index of Some Latin Americ

Author

Listed:
  • Luis A. Gil-Alana

    (School of Economics and Business Administration, University of Navarra)

  • Bertrand Candelon

Abstract

In this article we propose a new approach that permits us to simultaneously test unit and fractional roots at the long run and the seasonal frequencies. We examine the industrial production indexes in four Latin American countries (Brazil, Argentina, Colombia and Mexico), using new statistical tools based on seasonal and non-seasonal long memory processes. Results show that the root at the long run or zero frequency plays a much more important role than the seasonal one. Nevertheless, in the cases of Brazil and Argentina a component of long memory behaviour is also present at the seasonal structure, indicating that shocks modify the seasonal structure for a long period. Policy makers should thus pay attention to this result in choosing the optimal economic policy.

Suggested Citation

  • Luis A. Gil-Alana & Bertrand Candelon, 2004. "Seasonal and Long Run Fractional Integration in the Industrial Production Index of Some Latin Americ," Faculty Working Papers 08/04, School of Economics and Business Administration, University of Navarra.
  • Handle: RePEc:una:unccee:wp0804
    as

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    File URL: http://www.unav.edu/documents/10174/6546776/1132583774_wp0804.pdf
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    References listed on IDEAS

    as
    1. Joseph Beaulieu, J. & Miron, Jeffrey A., 1993. "Seasonal unit roots in aggregate U.S. data," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 305-328.
    2. L. A. Gil-Alana & P. M. Robinson, 2001. "Testing of seasonal fractional integration in UK and Japanese consumption and income," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(2), pages 95-114.
    3. 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.
    4. Dickey, David A & Pantula, Sastry G, 2002. "Determining the Order of Differencing in Autoregressive Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 18-24, January.
    5. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, March.
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    Cited by:

    1. Alagidede, Paul & Coleman, Simeon & Cuestas, Juan Carlos, 2012. "Inflationary shocks and common economic trends: Implications for West African monetary union membership," Journal of Policy Modeling, Elsevier, vol. 34(3), pages 460-475.
    2. Guglielmo Maria Caporale & Luis Alberiko Gil-Alana & Carlos Poza & Alvaro Baños Izquierdo, 2023. "Persistence and Seasonality in the US Industrial Production Index," CESifo Working Paper Series 10756, CESifo.

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    More about this item

    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

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