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

Chaohua Dong (), Jiti Gao and Bin Peng ()

No 7/15, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

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 established 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. (search for similar items in EconPapers)
JEL-codes: C13 C14 C23 C51 (search for similar items in EconPapers)
Date: 2015
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (4)

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