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Semiparametric Estimation of Partially Linear Varying Coefficient Panel Data Models

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


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.




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.


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, Bingley, pp. 47-65.



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