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Change Point Estimation in Panel Data without Boundary Issue

Author

Listed:
  • Barbora Peštová

    (Department of Medical Informatics and Biostatistics, Institute of Computer Science, The Czech Academy of Sciences, Pod Vodárenskou věží 271/2, 18207 Prague 8, Czech Republic
    These authors contributed equally to this work.)

  • Michal Pešta

    (Department of Probability and Mathematical Statistics, Faculty of Mathematics and Physics, Charles University, Sokolovská 83, 18675 Prague 8, Czech Republic
    These authors contributed equally to this work.)

Abstract

Panel data of our interest consist of a moderate number of panels, while the panels contain a small number of observations. An estimator of common breaks in panel means without a boundary issue for this kind of scenario is proposed. In particular, the novel estimator is able to detect a common break point even when the change happens immediately after the first time point or just before the last observation period. Another advantage of the elaborated change point estimator is that it results in the last observation in situations with no structural breaks. The consistency of the change point estimator in panel data is established. The results are illustrated through a simulation study. As a by-product of the developed estimation technique, a theoretical utilization for correlation structure estimation, hypothesis testing and bootstrapping in panel data is demonstrated. A practical application to non-life insurance is presented, as well.

Suggested Citation

  • Barbora Peštová & Michal Pešta, 2017. "Change Point Estimation in Panel Data without Boundary Issue," Risks, MDPI, vol. 5(1), pages 1-22, January.
    • Handle: RePEc:gam:jrisks:v:5:y:2017:i:1:p:7-:d:88504
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    References listed on IDEAS

    as
    1. Bai, Jushan, 2010. "Common breaks in means and variances for panel data," Journal of Econometrics, Elsevier, vol. 157(1), pages 78-92, July.
    2. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2016. "Estimation of heterogeneous panels with structural breaks," Journal of Econometrics, Elsevier, vol. 191(1), pages 176-195.
    3. Dukpa Kim, 2014. "Common breaks in time trends for large panel data with a factor structure," Econometrics Journal, Royal Economic Society, vol. 17(3), pages 301-337, October.
    4. Marie Hušková & Claudia Kirch, 2012. "Bootstrapping sequential change-point tests for linear regression," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(5), pages 673-708, July.
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