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Forecasts of the seasonal fractional integrated series

Author

Listed:
  • Vivien Guiraud

    (LAMETA|CNRS, University of Montpellier, France)

  • Michel Terraza

    (LAMETA|CNRS, University of Montpellier, France)

  • Olivier Darné

    (LAMETA|CNRS, University of Montpellier, France)

Abstract

We study the probability of rejecting the seasonal unit root tests developed by Hylleberg et al. when they are applied to fractionally integrated seasonal time series. We find that these tests have quite low power and that they lead to a risk of over-differencing. The forecasting performance of fractionally integrated seasonal models is also examined. This approach is compared with the traditional approaches from Box-Jenkins methodology, and the HEGY-type test procedure. Forecasting results obtained from simulated series and quarterly economic time series show that the fractional approach improves the forecasting accuracy with regard to the other approaches. Copyright © 2004 John Wiley & Sons, Ltd.

Suggested Citation

  • Vivien Guiraud & Michel Terraza & Olivier Darné, 2004. "Forecasts of the seasonal fractional integrated series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(1), pages 1-17.
    • Handle: RePEc:jof:jforec:v:23:y:2004:i:1:p:1-17
    DOI: 10.1002/for.907
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    Cited by:

    1. Laurent Ferrara & Dominique Guegan & Zhiping Lu, 2008. "Testing fractional order of long memory processes: a Monte Carlo study," Documents de travail du Centre d'Economie de la Sorbonne b08012, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    2. Laurent Ferrara & Dominique Guegan, 2006. "Fractional seasonality: Models and Application to Economic Activity in the Euro Area," Post-Print halshs-00185370, HAL.
    3. Laurent Ferrara & Dominique Guegan & Zhiping Lu, 2008. "Testing fractional order of long memory processes : a Monte Carlo study," Post-Print halshs-00259193, HAL.
    4. John Galbraith & Greg Tkacz, 2007. "How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables," Staff Working Papers 07-1, Bank of Canada.

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