Estimating partially linear panel data models with one-way error components
针对误差为单向误差成分结构的部分线性面板数据模型，提出可行的半参数广义最小二乘估计量，证明其渐近效率优于普通最小二乘估计量，并讨论了参数分量回归元与误差相关时的工具变量估计量。
We consider the problem of estimating a partially linear panel data model whenthe error follows an one-way error components structure. We propose a feasiblesemiparametric generalized least squares (GLS) type estimator for estimating the coefficient of the linear component and show that it is asymptotically more efficient than a semiparametric ordinary least squares (OLS) type estimator. We also discussed the case when the regressor of the parametric component is correlated with the error, and propose an instrumental variable GLS-type semiparametric estimator.