Estimation in a semiparametric panel data model with nonstationarity

In this paper, we consider a partially linear panel data model with nonstationarity and certain cross-sectional dependence. Accounting for the explosive feature of the nonstationary time series, we particularly employ Hermite orthogonal functions in this study. Under a general spatial error dependence structure, we then establish some consistent closed-form estimates for both the unknown parameters and the unknown functions for the cases where N and T go jointly to infinity. Rates of convergence and asymptotic normalities are established for the proposed estimators. Both the finite sample performance and the empirical applications show that the proposed estimation methods work well.

本文针对一类兼具非平稳性与特定截面相关性的部分线性面板数据模型展开研究。考虑到非平稳时间序列的爆炸性特征，本文特别采用埃尔米特（Hermite）正交函数开展分析。在一般化空间误差相关性结构下，针对截面个体数N与时期数T联合趋于无穷的情形，本文推导得到未知参数与未知函数的一致闭式估计量，并确立了所提估计量的收敛速度与渐近正态性。有限样本仿真性能与实证应用均表明，本文提出的估计方法表现良好。