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Finite sample of the Durbin-Watson test against fractionally integrated disturbances

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  • Kleiber, Christian
  • Krämer, Walter

Abstract

We consider the finite sample power of various tests against serial correlation in the disturbances of a linear regression when these disturbances follow a stationary long memory process. It emerges that the power depends on the form of the regressor matrix and that, for the Durbin-Watson test and many other tests that can be written as ratios of quadratic forms in the disturbances, the power can drop to zero for certain regressors. We also provide a means to detect this zero-power trap. Our results depend solely on the correlation structure and allow for fairly arbitrary nonlinearities.

Suggested Citation

  • Kleiber, Christian & Krämer, Walter, 2004. "Finite sample of the Durbin-Watson test against fractionally integrated disturbances," Technical Reports 2004,15, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    • Handle: RePEc:zbw:sfb475:200415
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    References listed on IDEAS

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    1. Kramer, W., 1985. "The power of the Durbin-Watson test for regressions without an intercept," Journal of Econometrics, Elsevier, vol. 28(3), pages 363-370, June.
    2. W. Tsay, 1998. "On the power of durbin-watson statistic against fractionally integrated processes," Econometric Reviews, Taylor & Francis Journals, vol. 17(4), pages 361-386.
    3. Kleiber, Christian, 2001. "Finite sample efficiency of OLS in linear regression models with long-memory disturbances," Economics Letters, Elsevier, vol. 72(2), pages 131-136, August.
    4. Kramer, Walter & Zeisel, Helmut, 1990. "Finite sample power of linear regression autocorrelation tests," Journal of Econometrics, Elsevier, vol. 43(3), pages 363-372, March.
    5. Bartels, Robert, 1992. "On the power function of the Durbin-Watson test," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 101-112.
    6. King, M. L., 1981. "The alternative Durbin-Watson test : An assessment of Durbin and Watson's choice of test statistic," Journal of Econometrics, Elsevier, vol. 17(1), pages 51-66, September.
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    8. Kariya, Takeaki, 1988. "The Class of Models for which the Durbin-Watson Test is Locally Optimal," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 29(1), pages 167-175, February.
    9. King, Maxwell L. & Evans, Merran A., 1988. "Locally Optimal Properties of the Durbin-Watson Test," Econometric Theory, Cambridge University Press, vol. 4(3), pages 509-516, December.
    10. Hisamatsu, Hiroyuki & Maekawa, Koichi, 1994. "The distribution of the Durbin-Watson statistic in integrated and near-integrated models," Journal of Econometrics, Elsevier, vol. 61(2), pages 367-382, April.
    11. Nakamura, Shisei & Taniguchi, Masanobu, 1999. "Asymptotic Theory For The Durbin–Watson Statistic Under Long-Memory Dependence," Econometric Theory, Cambridge University Press, vol. 15(6), pages 847-866, December.
    12. Nabeya, Seiji & Tanaka, Katsuto, 1990. "Limiting power of unit-root tests in time-series regression," Journal of Econometrics, Elsevier, vol. 46(3), pages 247-271, December.
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    Cited by:

    1. Anurag Banerjee, 2004. "Sensitivity of OLS estimates against ARFIMA error process as small sample Test for long memory," Econometric Society 2004 Australasian Meetings 159, Econometric Society.

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    More about this item

    Keywords

    Durbin-Watson test; power; autocorrelation; long memory;
    All these keywords.

    JEL classification:

    • 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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