Globally Efficient Non-Parametric Inference of Average Treatment Effects by Empirical Balancing Calibration Weighting
通过经验平衡校准加权实现平均处理效应的全局有效非参数推断
Summary The estimation of average treatment effects based on observational data is extremely important in practice and has been studied by generations of statisticians under different frameworks. Existing globally efficient estimators require non-parametric estimation of a propensity score function, an outcome regression function or both, but their performance can be poor in practical sample sizes. Without explicitly estimating either function, we consider a wide class of…