Rejoinder: A Nonparametric Superefficient Estimator of the Average Treatment Effect

Here, a research about the rejoinder, a nonparametic superefficient estimator of the average treatment effect, is presented. Comments about the research were addressed in the larger scope of their research. Stabilization techniques that are common for inverse probability of treatment weighted (IPTW) estimators could stabilize doubly robust procedures in weakly identified settings. A proposal to use a stabilized propensity score in combination with one-step estimation or (TMLE). The resultant estimators are found through simulation have reasonable performance in the simulation settings considered in the research. The authors also highlight a potential difficulty when considering coupling this approach with machine learning or other nonparametric regression techniques.