Nonparametric Estimation in Large Panels with Cross-Sectional Dependence
研究在截面依赖的多因子结构下，对面板数据进行非参数估计，使用局部线性回归过滤未观测的截面因子并估计条件均值，蒙特卡洛模拟显示估计量有良好的有限样本性质。
In this paper we consider nonparametric estimation in panel data under cross-sectional dependence. Both the number of cross-sectional units (N) and the time dimension of the panel (T) are assumed to be large, and the cross-sectional dependence has a multifactor structure. Local linear regression is used to filter the unobserved cross-sectional factors and to estimate the nonparametric conditional mean. A Monte Carlo simulation study shows that the proposed estimator yields good finite sample properties.