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A bi-integrative analysis of two-dimensional heterogeneous panel data models

Author

Listed:
  • Wang, Wei
  • Xiao, Zhijie
  • Ren, Yanyan
  • Yan, Xiaodong

Abstract

Heterogeneous panel data models have received more attention. This paper proposes a two- dimensional heterogeneous panel regression model that incorporate a group structure of individual dimension with cohort formation for their time-variations, which allows common coefficients between nonadjacent time points, via a doubly penalized least square is introduced. The consistency and asymptotic normality for the proposed estimators are developed. The simulations show the good finite sample performance.

Suggested Citation

  • Wang, Wei & Xiao, Zhijie & Ren, Yanyan & Yan, Xiaodong, 2023. "A bi-integrative analysis of two-dimensional heterogeneous panel data models," Economics Letters, Elsevier, vol. 230(C).
    • Handle: RePEc:eee:ecolet:v:230:y:2023:i:c:s0165176523002690
    DOI: 10.1016/j.econlet.2023.111244
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    References listed on IDEAS

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    1. Jun‐Hyung Ko & Yoshito Funashima, 2019. "On the Sources of the Feldstein–Horioka Puzzle across Time and Frequencies," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(4), pages 889-910, August.
    2. Fouquau, Julien & Hurlin, Christophe & Rabaud, Isabelle, 2008. "The Feldstein-Horioka puzzle: A panel smooth transition regression approach," Economic Modelling, Elsevier, vol. 25(2), pages 284-299, March.
    3. Stéphane Bonhomme & Elena Manresa, 2015. "Grouped Patterns of Heterogeneity in Panel Data," Econometrica, Econometric Society, vol. 83(3), pages 1147-1184, May.
    4. Liangjun Su & Zhentao Shi & Peter C. B. Phillips, 2016. "Identifying Latent Structures in Panel Data," Econometrica, Econometric Society, vol. 84, pages 2215-2264, November.
    5. Degui Li & Jia Chen & Jiti Gao, 2011. "Non‐parametric time‐varying coefficient panel data models with fixed effects," Econometrics Journal, Royal Economic Society, vol. 14(3), pages 387-408, October.
    6. Fan J. & Li R., 2001. "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1348-1360, December.
    7. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    8. 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.
    9. Qian, Junhui & Su, Liangjun, 2016. "Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso," Journal of Econometrics, Elsevier, vol. 191(1), pages 86-109.
    10. Michael Vogt & Oliver Linton, 2017. "Classification of non-parametric regression functions in longitudinal data models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(1), pages 5-27, January.
    11. Shujie Ma & Jian Huang, 2017. "A Concave Pairwise Fusion Approach to Subgroup Analysis," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 410-423, January.
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    More about this item

    Keywords

    Panel data; Bi-integration; Two-dimensional heterogeneity; Group structure; Cohort structure;
    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

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