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Tests on Fractional Cointegration Comparison of a Finite M— and ML—test on Fractional Cointegration

In: Developments in Robust Statistics

Author

Listed:
  • A. Peters

    (University of Erlangen—Nuremberg, Department of Medical Informatics, Biometry and Epidemiology)

  • P. Sibbertsen

    (University of Dortmund, Department of Statistics)

Abstract

Summary Cointegration describes the pattern that pairs of time series keep together in long run, although they diverge in short run. A generalisation of this behaviour is the fractional cointegration. Two statistical tests, the M— and ML—test are formulated for fractional cointegration in different situations. It turns out that the robust M—test reaches almost the same power as the maximum likelihood test under certain assumptions. In contrast to this, the power of the M—test is much higher compared with the ML—test if the examined time series is contaminated following the general replacement model.

Suggested Citation

  • A. Peters & P. Sibbertsen, 2003. "Tests on Fractional Cointegration Comparison of a Finite M— and ML—test on Fractional Cointegration," Springer Books, in: Rudolf Dutter & Peter Filzmoser & Ursula Gather & Peter J. Rousseeuw (ed.), Developments in Robust Statistics, pages 307-316, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-57338-5_27
    DOI: 10.1007/978-3-642-57338-5_27
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