Before revision:  The recent literature on statistical learning methods for heterogeneous treatment effects demonstrates the utility of estimating the marginal conditional average treatment effect (MCATE), i.e., the average treatment effect for a subpopulation of respondents who share a particular subset of covariates. However, each proposed method makes its own set of restrictive assumptions about the intervention's effects , the underlying data generating processes, and which subpopulations (MCATEs) to explicitly estimate.
After revision:  The recent literature on statistical learning methods for heterogeneous treatment effects , each proposed method makes its own set of restrictive assumptions about the intervention's effects , the underlying data generating processes, and which subpopulations (MCATEs) to explicitly estimate.