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On the power of durbin-watson statistic against fractionally integrated processes

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  • W. Tsay

Abstract

This paper provides the theoretical explanation and Monte Carlo experiments of using a modified version of Durbin-Watson ( D W ) statistic to test an 1 ( 1 ) process against I ( d ) alternatives, that is, integrated process of order d, where d is a fractional number. We provide the exact order of magnitude of the modified D W test when the data generating process is an I ( d ) process with d E (0. 1.5). Moreover, the consistency of the modified DW statistic as a unit root test against I ( d ) alternatives with d E ( 0 , l ) U ( 1 , 1.5) is proved in this paper. In addition to the theoretical analysis, Monte Carlo experiments show that the performance of the modified D W statistic reveals that it can be used as a unit root test against I ( d ) alternatives.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:emetrv:v:17:y:1998:i:4:p:361-386
    DOI: 10.1080/07474939808800423
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    Cited by:

    1. Hsiao, James Po-Hsun & Jaw, Chyi & Huan, Tzung-Cheng, 2009. "Information diffusion and new product consumption: A bass model application to tourism facility management," Journal of Business Research, Elsevier, vol. 62(7), pages 690-697, July.
    2. 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.
    3. 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.
    4. 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.

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