LATE With Missing or Mismeasured Treatment
提出MR-LATE估计量，能在处理变量非随机缺失时一致估计局部平均处理效应，并在处理变量测量错误时比标准LATE偏差更小，应用于印度家庭中女性资源控制对健康影响的研究。
We provide a new estimator, MR-LATE, that consistently estimates local average treatment effects when treatment is missing for some observations, not at random. If instead treatment is mismeasured for some observations, then MR-LATE usually has less bias than the standard LATE estimator. We discuss potential applications where an endogenous binary treatment may be unobserved or mismeasured. We apply MR-LATE to study the impact of women’s control over household resources on health outcomes in Indian families. This application illustrates the use of MR-LATE when treatment is estimated rather than observed. In these situations, treatment mismeasurement may arise from model misspecification and estimation errors.