Estimation in a semiparametric panel data model with nonstationarity
研究了带有非平稳性和截面依赖的部分线性面板数据模型，使用Hermite正交函数进行估计，给出了参数和非参数函数的闭式估计量及其渐近性质，适用于N和T同时趋于无穷的情况。
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.