Estimating Heterogeneous Causal Effects of High-Dimensional Treatments: Application to Conjoint Analysis
高维处理的异质性因果效应估计:联合分析应用
Estimation of heterogeneous treatment effects is an active area of research. Most of the existing methods, however, focus on estimating the conditional average treatment effects of a single, binary treatment given a set of pre-treatment covariates. In this paper, we propose a method to estimate the heterogeneous causal effects of high-dimensional treatments, which poses unique challenges in terms of estimation and interpretation. The proposed approach finds maximally…