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Cumulative sum estimator for change-point in panel data

Author

Listed:
  • Zhuoheng Chen

    (Wuhan University
    Huaqiao University)

  • Yijun Hu

    (Wuhan University)

Abstract

We propose a new estimator for the common change-point in means for panel data. Cumulative sum method is used for estimating the common change-point. We establish the consistency of the estimated change-point, and provide the rate of convergence. Comparison with the existing results is made in a simulation study via Monte Carlo method, which shows that our proposed method is more efficient.

Suggested Citation

  • Zhuoheng Chen & Yijun Hu, 2017. "Cumulative sum estimator for change-point in panel data," Statistical Papers, Springer, vol. 58(3), pages 707-728, September.
    • Handle: RePEc:spr:stpapr:v:58:y:2017:i:3:d:10.1007_s00362-015-0722-y
    DOI: 10.1007/s00362-015-0722-y
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    References listed on IDEAS

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    1. Michele Aquaro & Pavel Čížek, 2014. "Robust estimation of dynamic fixed-effects panel data models," Statistical Papers, Springer, vol. 55(1), pages 169-186, February.
    2. Kokoszka, Piotr & Leipus, Remigijus, 1998. "Change-point in the mean of dependent observations," Statistics & Probability Letters, Elsevier, vol. 40(4), pages 385-393, November.
    3. Bai, Jushan, 2010. "Common breaks in means and variances for panel data," Journal of Econometrics, Elsevier, vol. 157(1), pages 78-92, July.
    4. Hariz, Samir Ben & Wylie, Jonathan J., 2005. "Rates of convergence for the change-point estimator for long-range dependent sequences," Statistics & Probability Letters, Elsevier, vol. 73(2), pages 155-164, June.
    5. Terence Chong, 2001. "Estimating the locations and number of change points by the sample-splitting method," Statistical Papers, Springer, vol. 42(1), pages 53-79, January.
    6. Lawrence Joseph & David Wolfson, 1993. "Maximum likelihood estimation in the multi-path change-point problem," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 45(3), pages 511-530, September.
    7. 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.
    8. Achim Zeileis, 2004. "Alternative boundaries for CUSUM tests," Statistical Papers, Springer, vol. 45(1), pages 123-131, January.
    9. Karavias, Yiannis & Tzavalis, Elias, 2014. "Testing for unit roots in short panels allowing for a structural break," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 391-407.
    10. Bischoff, W. & Gegg, A., 2011. "Partial sum process to check regression models with multiple correlated response: With an application for testing a change-point in profile data," Journal of Multivariate Analysis, Elsevier, vol. 102(2), pages 281-291, February.
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    Cited by:

    1. Haoran Lu & Dianpeng Wang, 2024. "Grouped Change-Points Detection and Estimation in Panel Data," Mathematics, MDPI, vol. 12(5), pages 1-20, March.
    2. Gabriela Ciuperca, 2022. "Real-time detection of a change-point in a linear expectile model," Statistical Papers, Springer, vol. 63(4), pages 1323-1367, August.

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