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The fragility of the KPSS stationarity test

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  • Nunzio Cappuccio

    ()

  • Diego Lubian

    ()

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.

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File URL: http://hdl.handle.net/10.1007/s10260-010-0130-3
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Bibliographic Info

Article provided by Springer in its journal Statistical Methods and Applications.

Volume (Year): 19 (2010)
Issue (Month): 2 (June)
Pages: 237-253

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Handle: RePEc:spr:stmapp:v:19:y:2010:i:2:p:237-253

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Related research

Keywords: KPSS stationarity test; Size distortion; Nearly-white noise nearly integrated model;

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References

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  1. Denis Kwiatkowski & Peter C.B. Phillips & Peter Schmidt, 1991. "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?," Cowles Foundation Discussion Papers 979, Cowles Foundation for Research in Economics, Yale University.
  2. Newey, Whitney K & West, Kenneth D, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," Review of Economic Studies, Wiley Blackwell, vol. 61(4), pages 631-53, October.
  3. 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.
  4. 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 157-66, April.
  5. Nunzio Cappuccio & Diego Lubian, 2006. "Local Asymptotic Distributions of Stationarity Tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(3), pages 323-345, 05.
  6. Lanne, Markku & Saikkonen, Pentti, 2000. "Reducing size distortions of parametric stationarity tests," SFB 373 Discussion Papers 2000,12, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  7. Donald W.K. Andrews & Christopher J. Monahan, 1990. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Cowles Foundation Discussion Papers 942, Cowles Foundation for Research in Economics, Yale University.
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Cited by:
  1. Tadeusz Bednarski, 2010. "Fr├ęchet differentiability in statistical inference for time series," Statistical Methods and Applications, Springer, vol. 19(4), pages 517-528, November.
  2. Majid Al-Sadoon, 2014. "A General Theory of Rank Testing," Working Papers 750, Barcelona Graduate School of Economics.

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