Imputation is all you need: double robustness, semiparametric efficiency, and automatic covariate balance for estimating the average treatment effect

Imputation-based causal estimation is typically viewed as relying exclusively on an outcome model, in contrast to augmented inverse-probability weighting, whose consistency is protected by fitting two nuisance models. This paper argues that this view can be misleading by highlighting a hidden dual w