Standard Errors for Two-Way Clustering with Serially Correlated Time Effects
提出了改进的标准误和渐近理论，适用于存在序列相关时间效应的双向聚类面板数据，证明OLS渐近正态且方差估计一致，对实证研究者有用。
Abstract We propose improved standard errors and an asymptotic theory for two-way clustered panels. Our theory allow for arbitrary serial dependence in the common time effects, which is excluded by existing two-way methods. Our asymptotic distribution theory is the first which allows for this level of inter-dependence. Under weak conditions, we demonstrate that OLS is asymptotically normal, our proposed variance estimator is consistent, and t-ratios are asymptotically standard normal. The results extend to two-way fixed-effect models; we argue that two-way clustering is still necessary even if two-way fixed effects are included. Simulation and empirical illustration are provided.