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Nonparametric time-varying panel data models with heterogeneity

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Abstract

Since Bai (2009, Econometrica 77, 1229-1279), considerable extensions have been made to panel data models with interactive fixed effects (IFEs). However, little work has been conducted to understand the associated iterative algorithm, which, to the best of our knowledge, is the most commonly adopted approach in this line of research. In this paper, we refine the algorithm of panel data models with IFEs using the nuclear-norm penalization method and duple least-squares (DLS) iterations. Meanwhile, we allow the regression coefficients to be individual-specific and evolve over time. Accordingly, asymptotic properties are established to demonstrate the theoretical validity of the proposed approach. Furthermore, we show that the proposed methodology exhibits good finite-sample performance using simulation and real data examples.

Original languageEnglish
Pages (from-to)302-325
Number of pages24
JournalEconometric Theory
Volume41
Issue number2
Early online date23 Oct 2023
DOIs
Publication statusPublished - 1 Apr 2025

Acknowledgements

The author would like to thank the Editor (Peter C.B. Phillips), the Co-Editor (Liangjun Su), and two referees for their constructive comments and suggestions. An earlier version of this paper was a chapter of the author’s PhD thesis at Monash University under the supervision of Jiti Gao and Yanrong Yang. The author would like to acknowledge their guidance and helpful comments. Thanks also go to Badi H. Baltagi, Oliver Linton, Bin Peng, and Robin Sickles for their comments on early versions of this paper. Address correspondence to Fei Liu, School of Finance, Nankai University, Tianjin, China; e-mail: [email protected].

Funding

This research is financially supported by the National Natural Science Foundation of China under Grant No. 72203114.

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Economics and Econometrics

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