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Semiparametric Estimation of Partially Linear Varying Coefficient Panel Data Models

An Yonghong ^a

Hsiao Cheng ^b,c

Li Dong ^d

^aDepartment of Economics, Texas A&M University, College Station, TX, USA

^bDepartment of Economics, University of Southern California, Los Angeles, CA, USA

^cWang Yanan Institute for Studies in Economics (WISE), Xiamen University, Xiamen, China

^dSchool of Economic, Political and Policy Sciences, The University of Texas at Dallas, Richardson, TX, USA

Essays in Honor of Aman Ullah

ISBN: 978-1-78560-787-5, eISBN: 978-1-78560-786-8

Publication date: 23 June 2016

Abstract

This paper considers the problem of estimating a partially linear varying coefficient fixed effects panel data model. Using the series method, we establish the root N normality for the estimator of the parametric component; and we show that the unknown function can be consistently estimated at the standard nonparametric rate. Furthermore, we extend the model to allow endogeneity in the parametric component and establish the asymptotic properties of the semiparametric instrumental variable estimators.

Keywords

Acknowledgements

The authors thank the editors and two anonymous referees for helpful comments. Hsiao acknowledges partial research support by China NSF Grant No. #71131008. Any remaining errors are our own.

Citation

Yonghong, A., Cheng, H. and Dong, L. (2016), "Semiparametric Estimation of Partially Linear Varying Coefficient Panel Data Models", Essays in Honor of Aman Ullah (Advances in Econometrics, Vol. 36), Emerald Group Publishing Limited, Leeds, pp. 47-65. https://doi.org/10.1108/S0731-905320160000036011

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