Before revision: We develop a general class of two-step algorithms for heterogeneous treatment effect estimation in observational studies.
After revision: Flexible estimation of heterogeneous treatment effects lies at the heart of many statistical challenges, such as personalized medicine and optimal resource allocation. In this paper, we develop a general class of two-step algorithms for heterogeneous treatment effect estimation in observational studies.