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Grouped Patterns of Heterogeneity in Panel Data

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  • Stéphane Bonhomme
  • Elena Manresa

Abstract

This paper introduces time‐varying grouped patterns of heterogeneity in linear panel data models. A distinctive feature of our approach is that group membership is left unrestricted. We estimate the parameters of the model using a “grouped fixed‐effects” estimator that minimizes a least squares criterion with respect to all possible groupings of the cross‐sectional units. Recent advances in the clustering literature allow for fast and efficient computation. We provide conditions under which our estimator is consistent as both dimensions of the panel tend to infinity, and we develop inference methods. Finally, we allow for grouped patterns of unobserved heterogeneity in the study of the link between income and democracy across countries.

Suggested Citation

  • Stéphane Bonhomme & Elena Manresa, 2015. "Grouped Patterns of Heterogeneity in Panel Data," Econometrica, Econometric Society, vol. 83(3), pages 1147-1184, May.
  • Handle: RePEc:wly:emetrp:v:83:y:2015:i:3:p:1147-1184
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    Cited by:

    1. Guner, Nezih & Kulikova, Yuliya & Llull, Joan, 2018. "Marriage and health: Selection, protection, and assortative mating," European Economic Review, Elsevier, vol. 104(C), pages 138-166.
    2. Carlos Vladimir Rodríguez-Caballero, 2016. "Panel Data with Cross-Sectional Dependence Characterized by a Multi-Level Factor Structure," CREATES Research Papers 2016-31, Department of Economics and Business Economics, Aarhus University.
    3. repec:wly:hlthec:v:26:y:2017:i:9:p:1146-1161 is not listed on IDEAS
    4. Lisa Oberlander & Anne‐Célia Disdier & Fabrice Etilé, 2017. "Globalisation and national trends in nutrition and health: A grouped fixed‐effects approach to intercountry heterogeneity," Health Economics, John Wiley & Sons, Ltd., vol. 26(9), pages 1146-1161, September.
    5. Hansen, Christian & Liao, Yuan, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," MPRA Paper 75313, University Library of Munich, Germany.
    6. Jiti Gao & Kai Xia, 2017. "Heterogeneous panel data models with cross-sectional dependence," Monash Econometrics and Business Statistics Working Papers 16/17, Monash University, Department of Econometrics and Business Statistics.
    7. Christian Hansen & Yuan Liao, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," Papers 1611.09420, arXiv.org, revised Dec 2016.
    8. Ryo Okui & Takahide Yanagi, 2018. "Kernel Estimation for Panel Data with Heterogeneous Dynamics," Papers 1802.08825, arXiv.org, revised Mar 2018.
    9. repec:taf:gnstxx:v:29:y:2017:i:1:p:108-136 is not listed on IDEAS
    10. Ryo Okui & Takahide Yanagi, 2014. "Panel Data Analysis with Heterogeneous Dynamics," KIER Working Papers 906, Kyoto University, Institute of Economic Research.
    11. Bräuning, Falk & Koopman, Siem Jan, 2016. "The dynamic factor network model with an application to global credit risk," Working Papers 16-13, Federal Reserve Bank of Boston.
    12. Ruiqi Liu & Anton Schick & Zuofeng Shang & Yonghui Zhang & Qiankun Zhou, 2018. "Identification and estimation in panel models with overspecified number of groups," Departmental Working Papers 2018-03, Department of Economics, Louisiana State University.
    13. Christian Hansen & Yuan Liao, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," Departmental Working Papers 201610, Rutgers University, Department of Economics.
    14. Chu, Ba, 2017. "Composite Quasi-Maximum Likelihood Estimation of Dynamic Panels with Group-Specific Heterogeneity and Spatially Dependent Errors," MPRA Paper 79709, University Library of Munich, Germany.
    15. repec:eee:ecolec:v:142:y:2017:i:c:p:249-256 is not listed on IDEAS
    16. Francesco Bravo & Ba M. Chu & David T. Jacho-Chávez, 2017. "Semiparametric estimation of moment condition models with weakly dependent data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(1), pages 108-136, January.
    17. Bo Pieter Johannes Andree & Francisco Blasques & Eric Koomen, 2017. "Smooth Transition Spatial Autoregressive Models," Tinbergen Institute Discussion Papers 17-050/III, Tinbergen Institute.

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