Robust Inference for the Direct Average Treatment Effect with Treatment Assignment Interference
处理分配存在干扰时直接平均处理效应的稳健推断
This paper develops methods for uncertainty quantification in causal inference settings with random network interference. We study the large-sample distributional properties of the classical difference-in-means Hajek treatment effect estimator, and propose a robust inference procedure for the (conditional) direct average treatment effect. Our framework allows for cross-unit interference in both the outcome equation and the treatment assignment mechanism. Drawing from…