Online Estimation of Average Treatment Effects
This chapter develops a one-pass, doubly robust estimator for average treatment effects in large observational datasets. It updates both the treatment effect and its uncertainty using fixed memory. Simulations show that a learned warm start closely matches conventional pooled estimates while reducing computation and storage. Applied to more than 13 million Medicaid-paid births, the method finds that prenatal WIC participation is associated with improved infant health outcomes.