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Forecasts of the seasonal fractional integrated series

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Author Info
Vivien Guiraud (LAMETA|CNRS, University of Montpellier, France)
Michel Terraza (LAMETA|CNRS, University of Montpellier, France)
Olivier Darné (LAMETA|CNRS, University of Montpellier, France)

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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.

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File URL: http://hdl.handle.net/10.1002/for.907
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Publisher Info
Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 23 (2004)
Issue (Month): 1 ()
Pages: 1-17
Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Handle: RePEc:jof:jforec:v:23:y:2004:i:1:p:1-17

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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  1. John W. Galbraith & Greg Tkacz, 2007. "How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables," Working Papers 07-1, Bank of Canada. [Downloadable!]
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This page was last updated on 2008-9-24.

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