Partially Linear Panel Data Models with Cross-Sectional Dependence and Nonstationarity
51 Pages Posted: 27 Mar 2015
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
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