Machine Learning, Causal Inference, Programming, Data Science.
treatments, we wish to go beyond just the average treatment effects and understand how treatment effects vary across individuals. A substitute is Conditional Average Treatment Effect (CATE, τ(x)= E[D|X=x] = E[Y(1)-Y(0)|X=x]) which is the treatment effect conditional on observed covariates.