Heteroskedasticity-Robust Standard Errors for Fixed Effects Panel Data Regression
指出传统异方差稳健标准误在固定T时对固定效应估计量不一致，提出一种偏误调整的估计量，在n和/或T趋于无穷时一致，并可扩展处理固定阶序列相关。
The conventional heteroskedasticity-robust (HR) variance matrix estimator for cross-sectional regression (with or without a degrees-of-freedom adjustment), applied to the fixed-effects estimator for panel data with serially uncorrelated errors, is inconsistent if the number of time periods T is fixed (and greater than 2) as the number of entities n increases. We provide a bias-adjusted HR estimator that is √nT-consistent under any sequences (n T ) in which n and/or T increase to ∞. This estimator can be extended to handle serial correlation of fixed order.