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Heterogeneous structural breaks in panel data models

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  • Okui, Ryo
  • Wang, Wendun

Abstract

This paper develops a new model and estimation procedure for panel data that allows us to identify heterogeneous structural breaks. We model individual heterogeneity using a grouped pattern. For each group, we allow common structural breaks in the coefficients. However, the number, timing, and size of these breaks can differ across groups. We develop a hybrid estimation procedure of the grouped fixed effects approach and adaptive group fused Lasso. We show that our method can consistently identify the latent group structure, detect structural breaks, and estimate the regression parameters. Monte Carlo results demonstrate the good performance of the proposed method in finite samples. An empirical application to the relationship between income and democracy illustrates the importance of considering heterogeneous structural breaks.

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  • Okui, Ryo & Wang, Wendun, 2021. "Heterogeneous structural breaks in panel data models," Journal of Econometrics, Elsevier, vol. 220(2), pages 447-473.
    • Handle: RePEc:eee:econom:v:220:y:2021:i:2:p:447-473
    DOI: 10.1016/j.jeconom.2020.04.009
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    3. Joana Almeida & Raquel M. Gaspar, 2021. "Accuracy of European Stock Target Prices," JRFM, MDPI, vol. 14(9), pages 1-27, September.
    4. Yiren Wang & Peter C B Phillips & Liangjun Su, 2023. "Panel Data Models with Time-Varying Latent Group Structures," Papers 2307.15863, arXiv.org.
    5. Weijie Cui & Yong Li, 2023. "Bicluster Analysis of Heterogeneous Panel Data via M-Estimation," Mathematics, MDPI, vol. 11(10), pages 1-19, May.
    6. Lu, Xun & Su, Liangjun, 2023. "Uniform inference in linear panel data models with two-dimensional heterogeneity," Journal of Econometrics, Elsevier, vol. 235(2), pages 694-719.
    7. Dzemski, Andreas & Okui, Ryo, 2021. "Convergence rate of estimators of clustered panel models with misclassification," Economics Letters, Elsevier, vol. 203(C).
    8. Lumsdaine, Robin L. & Okui, Ryo & Wang, Wendun, 2023. "Estimation of panel group structure models with structural breaks in group memberships and coefficients," Journal of Econometrics, Elsevier, vol. 233(1), pages 45-65.
    9. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    10. Wang, Wuyi & Su, Liangjun, 2021. "Identifying latent group structures in nonlinear panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 272-295.
    11. Yiren Wang & Liangjun Su & Yichong Zhang, 2022. "Low-rank Panel Quantile Regression: Estimation and Inference," Papers 2210.11062, arXiv.org.
    12. Varun Agiwal & Jitendra Kumar & Dahud Kehinde Shangodoyin, 2020. "A Bayesian analysis of complete multiple breaks in a panel autoregressive (CMB-PAR(1)) time series model," Statistics in Transition New Series, Polish Statistical Association, vol. 21(5), pages 133-149, December.
    13. Jiang, Peiyun & Kurozumi, Eiji, 2021. "A new test for common breaks in heterogeneous panel data models," Discussion paper series HIAS-E-107, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    14. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.

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    More about this item

    Keywords

    Panel data; Grouped patterns; Structural breaks; Grouped fixed effects; Fused Lasso;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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