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A note on the size of the KPSS unit root test


  • Su, Jen-Je
  • Amsler, Christine
  • Schmidt, Peter


The KPSS unit root test with lags is asymptotically valid and the fixed-b asymptotic distribution predicts its critical values well. A small positive number of lags improves the size of the test, without much loss in power.

Suggested Citation

  • Su, Jen-Je & Amsler, Christine & Schmidt, Peter, 2012. "A note on the size of the KPSS unit root test," Economics Letters, Elsevier, vol. 117(3), pages 697-699.
  • Handle: RePEc:eee:ecolet:v:117:y:2012:i:3:p:697-699 DOI: 10.1016/j.econlet.2012.08.019

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    References listed on IDEAS

    1. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    2. Shin, Yongcheol & Schmidt, Peter, 1992. "The KPSS stationarity test as a unit root test," Economics Letters, Elsevier, vol. 38(4), pages 387-392, April.
    3. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 33(1), pages 125-132.
    4. Breitung, Jorg, 2002. "Nonparametric tests for unit roots and cointegration," Journal of Econometrics, Elsevier, vol. 108(2), pages 343-363, June.
    5. Amsler Christine & Schmidt Peter & Vogelsang Timothy J, 2009. "The KPSS Test Using Fixed-b Critical Values: Size and Power in Highly Autocorrelated Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 1(1), pages 1-44, December.
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    More about this item


    KPSS test; Unit root; Fixed-b asymptotics;

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • 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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