Partially Linear Panel Data Models with Cross-Sectional Dependence and Nonstationarity

51 Pages Posted: 27 Mar 2015

See all articles by Chaohua Dong

Chaohua Dong

Zhongnan University of Economics and Law

Jiti Gao

Monash University - Department of Econometrics & Business Statistics

Bin Peng

Monash University - Department of Econometrics and Business Statistics

Date Written: March 26, 2015

Abstract

In this paper, we consider a partially linear panel data model with cross-sectional dependence and non-stationarity. Meanwhile, we allow fixed effects to be correlated with the regressors to capture unobservable heterogeneity. Under a general spatial error dependence structure, we then establish some consistent closed-form estimates for both the unknown parameters and the unknown function for the case where N and T go jointly to infinity. Rates of convergence and asymptotic normality results are established for the proposed estimators. Both the finite-sample performance and the empirical applications show that the proposed estimation method works well when the cross-sectional dependence exists in the data set.

Keywords: Asymptotic theory; closed-form estimate; orthogonal series method; partially linear panel data model.

JEL Classification: C13, C14, C23, C51

Suggested Citation

Dong, Chaohua and Gao, Jiti and Peng, Bin, Partially Linear Panel Data Models with Cross-Sectional Dependence and Nonstationarity (March 26, 2015). Available at SSRN: https://ssrn.com/abstract=2585334 or http://dx.doi.org/10.2139/ssrn.2585334

Chaohua Dong

Zhongnan University of Economics and Law ( email )

182 Nanhu Avenue
Wuhan, Hubei 430073
China

Jiti Gao (Contact Author)

Monash University - Department of Econometrics & Business Statistics ( email )

900 Dandenong Road
Caulfield East, Victoria 3145
Australia
61399031675 (Phone)
61399032007 (Fax)

HOME PAGE: http://www.jitigao.com

Bin Peng

Monash University - Department of Econometrics and Business Statistics ( email )

900 Dandenong Road
Caulfield East, VIC 3145
Australia

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