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Testing for a break in persistence under long-range dependencies and mean shifts

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  • Philipp Sibbertsen
  • Juliane Willert

Abstract

We show that the CUSUM-squared based test for a change in persistence by Leybourne et al. (2007) is not robust against shifts in the mean. A mean shift leads to serious size distortions. Therefore, adjusted critical values are needed when it is known that the data generating process has a mean shift. These are given for the case of one mean break. Response curves for the critical values are derived and a Monte Carlo study showing the size and power properties under this general de-trending is given
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Suggested Citation

  • Philipp Sibbertsen & Juliane Willert, 2012. "Testing for a break in persistence under long-range dependencies and mean shifts," Statistical Papers, Springer, vol. 53(2), pages 357-370, May.
    • Handle: RePEc:spr:stpapr:v:53:y:2012:i:2:p:357-370
    DOI: 10.1007/s00362-010-0342-5
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    References listed on IDEAS

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    1. Philipp Sibbertsen, 2004. "Long memory versus structural breaks: An overview," Statistical Papers, Springer, vol. 45(4), pages 465-515, October.
    2. Stephen Leybourne & Robert Taylor & Tae‐Hwan Kim, 2007. "CUSUM of Squares‐Based Tests for a Change in Persistence," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(3), pages 408-433, May.
    3. Philipp Sibbertsen & Robinson Kruse, 2009. "Testing for a break in persistence under long‐range dependencies," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(3), pages 263-285, May.
    4. Belaire-Franch, Jorge, 2005. "A Proof Of The Power Of Kim'S Test Against Stationary Processes With Structural Breaks," Econometric Theory, Cambridge University Press, vol. 21(6), pages 1172-1176, December.
    5. Philipp Sibbertsen & Juliane Willert, 2012. "Testing for a break in persistence under long-range dependencies and mean shifts," Statistical Papers, Springer, vol. 53(2), pages 357-370, May.
    6. Banerjee, Anindya & Lumsdaine, Robin L & Stock, James H, 1992. "Recursive and Sequential Tests of the Unit-Root and Trend-Break Hypotheses: Theory and International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 271-287, July.
    7. Kim, Jae-Young, 2000. "Detection of change in persistence of a linear time series," Journal of Econometrics, Elsevier, vol. 95(1), pages 97-116, March.
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    More about this item

    Keywords

    Break in persistence; Long memory; Structural break; Level shift; C12; C22;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: 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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