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The KPSS test with seasonal dummies

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  • Phillips, Peter C. B.
  • Jin, Sainan

Abstract

It is shown that the KPSS test for stationarity may be applied without change to regressions with seasonal dummies. In particular, the limit distribution of the KPSS statistic is the same under both the null and alternative hypotheses whether or not seasonal dummies are used.
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Suggested Citation

  • Phillips, Peter C. B. & Jin, Sainan, 2002. "The KPSS test with seasonal dummies," Economics Letters, Elsevier, vol. 77(2), pages 239-243, October.
  • Handle: RePEc:eee:ecolet:v:77:y:2002:i:2:p:239-243
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    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. Lyhagen, Johan, 2000. "The seasonal KPSS statistic," SSE/EFI Working Paper Series in Economics and Finance 354, Stockholm School of Economics.
    3. Taylor, A.M.R., 1999. "Locally Optimal Tests Against Seasonal Unit Roots," Discussion Papers 99-12, Department of Economics, University of Birmingham.
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    Cited by:

    1. Joseph Ross, 2021. "Stationarity Statistics on Rolling Windows," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 655-691, February.
    2. Haldrup, Niels & Nielsen, Morten Orregaard, 2006. "A regime switching long memory model for electricity prices," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 349-376.
    3. Halunga, Andreea G. & Osborn, Denise R. & Sensier, Marianne, 2009. "Changes in the order of integration of US and UK inflation," Economics Letters, Elsevier, vol. 102(1), pages 30-32, January.
    4. Vasilii Erokhin & Tianming Gao, 2020. "Impacts of COVID-19 on Trade and Economic Aspects of Food Security: Evidence from 45 Developing Countries," IJERPH, MDPI, vol. 17(16), pages 1-28, August.
    5. Natasha Kang & Vadim Marmer, 2020. "Modeling Long Cycles," Papers 2010.13877, arXiv.org, revised Sep 2023.
    6. Lujia Bai & Weichi Wu, 2021. "Detecting long-range dependence for time-varying linear models," Papers 2110.08089, arXiv.org, revised Mar 2023.
    7. Choudhry, Taufiq, 2003. "Stock market volatility and the US consumer expenditure," Journal of Macroeconomics, Elsevier, vol. 25(3), pages 367-385, September.
    8. Andrew Harvey & Stephen Thiele, 2021. "Cointegration and control: Assessing the impact of events using time series data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 71-85, January.
    9. Matei Demetrescu & Uwe Hassler, 2007. "Effect of neglected deterministic seasonality on unit root tests," Statistical Papers, Springer, vol. 48(3), pages 385-402, September.
    10. Josep Carrion-i-Silvestre & Andreu Sansó, 2006. "A guide to the computation of stationarity tests," Empirical Economics, Springer, vol. 31(2), pages 433-448, June.

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    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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