IDEAS home Printed from https://ideas.repec.org/p/zbw/sfb475/200415.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/49321/1/384011888.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. King, Maxwell L., 1985. "A point optimal test for autoregressive disturbances," Journal of Econometrics, Elsevier, vol. 27(1), pages 21-37, January.
    4. 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.
    5. Kramer, Walter & Zeisel, Helmut, 1990. "Finite sample power of linear regression autocorrelation tests," Journal of Econometrics, Elsevier, vol. 43(3), pages 363-372, March.
    6. Bartels, Robert, 1992. "On the power function of the Durbin-Watson test," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 101-112.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wan, Alan T.K. & Zou, Guohua & Banerjee, Anurag, 2007. "The power of autocorrelation tests near the unit root in models with possibly mis-specified linear restrictions," Economics Letters, Elsevier, vol. 94(2), pages 213-219, February.
    2. Wan, Alan & Zou, Guohua & Banerjee, Anurag, 2004. "The limiting power of autocorrelation tests in regression models with linear restrictions," Discussion Paper Series In Economics And Econometrics 0405, Economics Division, School of Social Sciences, University of Southampton.
    3. Preinerstorfer, David & Pötscher, Benedikt M., 2017. "On The Power Of Invariant Tests For Hypotheses On A Covariance Matrix," Econometric Theory, Cambridge University Press, vol. 33(1), pages 1-68, February.
    4. Wan, Alan & Zou, Guohua & Banerjee, Anurag, 2004. "The limiting power of autocorrelation tests in regression models with linear restrictions," Discussion Paper Series In Economics And Econometrics 405, Economics Division, School of Social Sciences, University of Southampton.
    5. Banerjee, Anurag N. & Magnus, Jan R., 1999. "The sensitivity of OLS when the variance matrix is (partially) unknown," Journal of Econometrics, Elsevier, vol. 92(2), pages 295-323, October.
    6. Martellosio, Federico, 2008. "Power Properties of Invariant Tests for Spatial Autocorrelation in Linear Regression," MPRA Paper 7255, University Library of Munich, Germany.
    7. 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.
    8. Maxwell L. King & Sivagowry Sriananthakumar, 2015. "Point Optimal Testing: A Survey of the Post 1987 Literature," Monash Econometrics and Business Statistics Working Papers 5/15, Monash University, Department of Econometrics and Business Statistics.
    9. Banerjee, A.N. & Magnus, J.R., 1996. "Testing the Sensitivity of OLS when the Variance Maxtrix is (Partially) Unknown," Other publications TiSEM e942b349-586c-4201-9228-0, Tilburg University, School of Economics and Management.
    10. Cappuccio, Nunzio & Lubian, Diego & Mistrorigo, Mirko, 2015. "The power of unit root tests under local-to-finite variance errors," Chaos, Solitons & Fractals, Elsevier, vol. 76(C), pages 205-217.
    11. Dufour, Jean-Marie & Neifar, Malika, 2004. "Méthodes d’inférence exactes pour un modèle de régression avec erreurs AR(2) gaussiennes," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(4), pages 593-618, Décembre.
    12. King, Maxwell L. & Zhang, Xibin & Akram, Muhammad, 2020. "Hypothesis testing based on a vector of statistics," Journal of Econometrics, Elsevier, vol. 219(2), pages 425-455.
    13. Phillips, Peter C. B. & Loretan, Mico, 1991. "The Durbin-Watson ratio under infinite-variance errors," Journal of Econometrics, Elsevier, vol. 47(1), pages 85-114, January.
    14. GONZALO , Jesus & PITARAKIS , Jean-Yves, 1995. "On the Exact Moments of Non-Standard Asymptotic Distributions in Non Stationary Autoregressions with Dependent Errors," LIDAM Discussion Papers CORE 1995034, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Franco Bevilacqua & Adriaan van Zon, 2004. "Random walks and non-linear paths in macroeconomic time series: some evidence and implications," Chapters, in: John Foster & Werner Hölzl (ed.), Applied Evolutionary Economics and Complex Systems, chapter 3, Edward Elgar Publishing.
    16. Tsay, Wen-Jen & Chung, Ching-Fan, 2000. "The spurious regression of fractionally integrated processes," Journal of Econometrics, Elsevier, vol. 96(1), pages 155-182, May.
    17. Mehdi Hosseinkouchack & Uwe Hassler, 2016. "Powerful Unit Root Tests Free of Nuisance Parameters," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(4), pages 533-554, July.
    18. Sanchez, Ismael, 1998. "Testing for Unit Roots with Prediction Errors," University of California at San Diego, Economics Working Paper Series qt8pc6n1j8, Department of Economics, UC San Diego.
    19. Banerjee, Anurag N. & Magnus, Jan R., 2000. "On the sensitivity of the usual t- and F-tests to covariance misspecification," Journal of Econometrics, Elsevier, vol. 95(1), pages 157-176, March.
    20. Zeng-Hua Lu & Maxwell King, 2002. "Improving The Numerical Technique For Computing The Accumulated Distribution Of A Quadratic Form In Normal Variables," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 149-165.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:sfb475:200415. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/isdorde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.