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Modified Kpss Tests For Near Integration

Author

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  • Harris, David
  • Leybourne, Stephen
  • McCabe, Brendan

Abstract

This note suggests a simple modification to the Kwiatkowski, Phillips, Schmidt, and Shin (1992, Journal of Econometrics, 54, 159–178) test (KPSS test) so that it is applicable to testing the null hypothesis of near integration against a unit root alternative. The modified KPSS test is shown not to suffer from the asymptotic size distortion problems of the original KPSS test that are described by Müller (2005, Journal of Econometrics 128, 195–213). The test also has good asymptotic and finite-sample properties relative to the point optimal tests of Müller (2005) and Elliott and Müller (2006, Journal of Econometrics 135, 285–310).

Suggested Citation

  • Harris, David & Leybourne, Stephen & McCabe, Brendan, 2007. "Modified Kpss Tests For Near Integration," Econometric Theory, Cambridge University Press, vol. 23(2), pages 355-363, April.
    • Handle: RePEc:cup:etheor:v:23:y:2007:i:02:p:355-363_07
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    Citations

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    Cited by:

    1. Anton Skrobotov, 2013. "Local Structural Trend Break in Stationarity Testing," Working Papers 0074, Gaidar Institute for Economic Policy, revised 2013.
    2. Anton Skrobotov, 2013. "On GLS-detrending for deterministic seasonality testing," Working Papers 0073, Gaidar Institute for Economic Policy, revised 2014.
    3. David O. Cushman, 2012. "Mankiw vs. DeLong and Krugman on the CEA's Real GDP Forecasts in Early 2009: What Might a Time Series Econometrician Have Said?," Econ Journal Watch, Econ Journal Watch, vol. 9(3), pages 309-349, September.
    4. Cho, Cheol-Keun & Amsler, Christine & Schmidt, Peter, 2015. "A test of the null of integer integration against the alternative of fractional integration," Journal of Econometrics, Elsevier, vol. 187(1), pages 217-237.
    5. Anton Skrobotov, 2015. "Trend and Initial Condition in Stationarity Tests: The Asymptotic Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(2), pages 254-273, April.
    6. Lujia Bai & Weichi Wu, 2021. "Detecting long-range dependence for time-varying linear models," Papers 2110.08089, arXiv.org, revised Mar 2023.
    7. Ferrer-Pérez, H. & Ayuda, M.I. & Aznar, A., 2017. "A comparison of two modified stationarity tests. A Monte Carlo study," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 134(C), pages 28-36.
    8. Eiji Kurozumi & Shinya Tanaka, 2010. "Reducing the size distortion of the KPSS test," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 415-426, November.

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