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NONPARAMETRIC TIME-VARYING PANEL DATA MODELS WITH HETEROGENEITY

Published online by Cambridge University Press:  23 October 2023

Fei Liu Open the ORCID record for Fei Liu [Opens in a new window]
Fei Liu*
Affiliation:
Nankai University
*
Address correspondence to Fei Liu, School of Finance, Nankai University, Tianjin, China; e-mail: fei.liu@nankai.edu.cn.
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Abstract

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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.

Information

Type
ARTICLES
Information
Econometric Theory , Volume 41 , Issue 2 , April 2025 , pp. 302 - 325
Copyright
© The Author(s), 2023. Published by Cambridge University Press

Footnotes

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

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