Data and Code for: Two-way fixed effects estimators with heterogeneous treatment effects

Linear regressions with period and group fixed effects are widely used to estimate treatment effects. We show that they estimate weighted sums of the average treatment effects (ATE) in each group and period, with weights that may be negative. Due to the negative weights, the linear regression coefficient may for instance be negative while all the ATEs are positive. We propose another estimator that solves this issue. In the two applications we revisit, it is significantly different from the linear regression estimator.

纳入时期固定效应与组固定效应的线性回归模型，被广泛应用于处理效应（treatment effects）的评估。本文研究表明，此类模型实际估计的是各分组与时期下平均处理效应（Average Treatment Effects，简称ATE）的加权和，且权重可取值为负值。由于负权重的存在，线性回归系数可能出现所有平均处理效应均为正，但系数本身为负的反常情形。本文提出一种可解决该问题的替代估计量。在本文重新审视的两项实证应用中，该估计量与线性回归估计量存在显著差异。