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The Fragility of the KPSS Stationarity Test

Author

Listed:
  • Nunzio Cappuccio

    () (Department of Economics and Management, University of Padova)

  • Diego Lubian

    () (Department of Economics (University of Verona))

Abstract

Stationarity tests exhibit extreme size distortions if the observable process is stationary yet highly persistent. In this paper we provide a theoretical explanation for the size distortion of the KPSS test for DGPs with a broad range of first order autocorrelation coefficient. Considering a near-integrated, nearly stationary process we show that the asymptotic distribution of the test contains an additional term, which can potentially explain the amount of size distortion documented in previous simulation studies.

Suggested Citation

  • Nunzio Cappuccio & Diego Lubian, 2009. "The Fragility of the KPSS Stationarity Test," Working Papers 67/2009, University of Verona, Department of Economics.
  • Handle: RePEc:ver:wpaper:67/2009
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    File URL: http://dse.univr.it//workingpapers/fragility_kpss.pdf
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    References listed on IDEAS

    as
    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. Nunzio Cappuccio & Diego Lubian, 2006. "Local Asymptotic Distributions of Stationarity Tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(3), pages 323-345, May.
    3. Whitney K. Newey & Kenneth D. West, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," Review of Economic Studies, Oxford University Press, vol. 61(4), pages 631-653.
    4. Markku Lanne & Pentti Saikkonen, 2003. "Reducing size distortions of parametric stationarity tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 423-439, July.
    5. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-966, July.
    6. Leybourne, S J & McCabe, B P M, 1994. "A Consistent Test for a Unit Root," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 157-166, April.
    7. Bart Hobijn & Philip Hans Franses & Marius Ooms, 2004. "Generalizations of the KPSS-test for stationarity," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(4), pages 483-502.
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    Cited by:

    1. Majid M. Al-Sadoon, 2014. "A general theory of rank testing," Economics Working Papers 1411, Department of Economics and Business, Universitat Pompeu Fabra, revised Feb 2015.
    2. Tadeusz Bednarski, 2010. "Fréchet differentiability in statistical inference for time series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(4), pages 517-528, November.
    3. repec:kap:compec:v:50:y:2017:i:1:d:10.1007_s10614-016-9586-z is not listed on IDEAS

    More about this item

    Keywords

    KPSS stationarity test; size distortion; nearly white noise nearly integrated model;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • 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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