Local GMM Estimation of Semiparametric Panel Data with Smooth Coefficient Models
提出一类简单易行的局部广义矩估计方法，用于估计半参数面板数据平滑系数模型，证明估计量的一致性和渐近正态性，并通过蒙特卡洛模拟和英国企业面板数据验证其有限样本表现。
In this article, we consider the estimation of semiparametric panel data smooth coefficient models. We propose a class of local generalized method of moments (LGMM) estimators that are simple and easy to implement in practice. We show that the proposed LGMM estimators are consistent and asymptotically normal. Monte Carlo simulations suggest that our proposed estimator performs quite well in finite samples. An empirical application using a large panel of U.K. firms is also presented.