Estimation of average treatment effects using panel data when treatment effect heterogeneity depends on unobserved fixed effects
提出一种新的面板数据方法，在允许处理效应异质性依赖于未观测固定效应的情况下，识别并估计整个总体的时变平均处理效应，并应用于研究母亲孕期吸烟对婴儿出生体重的影响。
Summary This paper proposes a new panel data approach to identify and estimate the time‐varying average treatment effect (ATE). The approach allows for treatment effect heterogeneity that depends on unobserved fixed effects. In the presence of this type of heterogeneity, existing panel data approaches identify the ATE for limited subpopulations only. In contrast, the proposed approach identifies and estimates the ATE for the entire population. The approach relies on the linear fixed effects specification of potential outcome equations and uses exogenous variables that are correlated with the fixed effects. I apply the approach to study the impact of a mother's smoking during pregnancy on her child's birth weight.