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Robust tests on fractional cointegration

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  • Peters, Andrea
  • Sibbertsen, Philipp

Abstract

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 than that of the ML–test if the examined time series is contaminated following the general replacement model.

Suggested Citation

  • Peters, Andrea & Sibbertsen, Philipp, 2001. "Robust tests on fractional cointegration," Technical Reports 2001,29, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    • Handle: RePEc:zbw:sfb475:200129
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    References listed on IDEAS

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    1. Hauser, Michael A, 1997. "Semiparametric and Nonparametric Testing for Long Memory: A Monte Carlo Study," Empirical Economics, Springer, vol. 22(2), pages 247-271.
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    3. Granger, Clive W J, 1986. "Developments in the Study of Cointegrated Economic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 213-228, August.
    4. Cheung, Yin-Wong & Lai, Kon S, 1993. "A Fractional Cointegration Analysis of Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 103-112, January.
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    Cited by:

    1. Banerjee, Anindya & Urga, Giovanni, 2005. "Modelling structural breaks, long memory and stock market volatility: an overview," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 1-34.

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