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A Multi-Kink quantile regression model with common structure for panel data analysis

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  • Sun, Yan
  • Wan, Chuang
  • Zhang, Wenyang
  • Zhong, Wei

Abstract

Stimulated by the analysis of a data set on financial portfolio returns, we propose a multi-kink quantile regression (MKQR) model with latent homogeneous structure for panel data analysis. The proposed model accounts for both homogeneity and heterogeneity among individuals and parameters in panel data analysis. From statistical modeling point of view, it well balances the risk of misspecification and the model parsimony. From practical point of view, it is able to reveal not only the impacts of covariates in the global sense, but also individual attributes. An estimation procedure is presented to estimate both the unknown parameters and the latent homogeneous structure in the proposed model. Computational issues with the implementation of the estimation procedure are also discussed. Asymptotic theory of the estimators is established. It shows the necessity of taking into account both homogeneity and heterogeneity in panel data analysis. Monte Carlo simulation studies are conducted to demonstrate the finite sample performance of the proposed estimation and the risk of ignoring the homogeneity or heterogeneity among individuals. Finally, we apply the proposed model and the estimation procedure to the data set which stimulates this work and reveal some interesting findings.

Suggested Citation

  • Sun, Yan & Wan, Chuang & Zhang, Wenyang & Zhong, Wei, 2024. "A Multi-Kink quantile regression model with common structure for panel data analysis," Journal of Econometrics, Elsevier, vol. 239(2).
    • Handle: RePEc:eee:econom:v:239:y:2024:i:2:s0304407622001178
    DOI: 10.1016/j.jeconom.2022.04.012
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    References listed on IDEAS

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    1. Heng Lian & Xinghao Qiao & Wenyang Zhang, 2021. "Homogeneity Pursuit in Single Index Models based Panel Data Analysis," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 386-401, March.
    2. Wei Zhong & Chuang Wan & Wenyang Zhang, 2022. "Estimation and Inference for Multi-Kink Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1123-1139, June.
    3. Stéphane Bonhomme & Elena Manresa, 2015. "Grouped Patterns of Heterogeneity in Panel Data," Econometrica, Econometric Society, vol. 83(3), pages 1147-1184, May.
    4. Wuyi Wang & Peter C. B. Phillips & Liangjun Su, 2018. "Homogeneity pursuit in panel data models: Theory and application," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 797-815, September.
    5. Liangjun Su & Zhentao Shi & Peter C. B. Phillips, 2016. "Identifying Latent Structures in Panel Data," Econometrica, Econometric Society, vol. 84, pages 2215-2264, November.
    6. Yining Chen, 2021. "Jump or kink: on super-efficiency in segmented linear regression breakpoint estimation," Biometrika, Biometrika Trust, vol. 108(1), pages 215-222.
    7. Simon N. Wood, 2001. "Minimizing Model Fitting Objectives That Contain Spurious Local Minima by Bootstrap Restarting," Biometrics, The International Biometric Society, vol. 57(1), pages 240-244, March.
    8. Zhang, Yonghui & Zhou, Qiankun & Jiang, Li, 2017. "Panel kink regression with an unknown threshold," Economics Letters, Elsevier, vol. 157(C), pages 116-121.
    9. Zhang, Yingying & Wang, Huixia Judy & Zhu, Zhongyi, 2019. "Quantile-regression-based clustering for panel data," Journal of Econometrics, Elsevier, vol. 213(1), pages 54-67.
    10. Tomohiro Ando & Jushan Bai, 2016. "Panel Data Models with Grouped Factor Structure Under Unknown Group Membership," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 163-191, January.
    11. Lin Chang-Ching & Ng Serena, 2012. "Estimation of Panel Data Models with Parameter Heterogeneity when Group Membership is Unknown," Journal of Econometric Methods, De Gruyter, vol. 1(1), pages 42-55, August.
    12. Liangjun Su & Xia Wang & Sainan Jin, 2019. "Sieve Estimation of Time-Varying Panel Data Models With Latent Structures," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(2), pages 334-349, April.
    13. Robert Tibshirani & Michael Saunders & Saharon Rosset & Ji Zhu & Keith Knight, 2005. "Sparsity and smoothness via the fused lasso," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(1), pages 91-108, February.
    14. Hidalgo, Javier & Lee, Jungyoon & Seo, Myung Hwan, 2019. "Robust inference for threshold regression models," Journal of Econometrics, Elsevier, vol. 210(2), pages 291-309.
    15. Li, Jialiang & Zhang, Wenyang & Kong, Efang, 2018. "Factor models for asset returns based on transformed factors," Journal of Econometrics, Elsevier, vol. 207(2), pages 432-448.
    16. Chaohui Guo & Jialiang Li, 2022. "Homogeneity and Structure Identification in Semiparametric Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 408-422, January.
    17. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    18. Eun Ryung Lee & Hohsuk Noh & Byeong U. Park, 2014. "Model Selection via Bayesian Information Criterion for Quantile Regression Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 216-229, March.
    19. Bruce E. Hansen, 2017. "Regression Kink With an Unknown Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 228-240, April.
    20. Zheng Tracy Ke & Jianqing Fan & Yichao Wu, 2015. "Homogeneity Pursuit," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 175-194, March.
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