Before revision: We propose the orthogonal random forest, an algorithm that incorporates double machine learning--a method of using Neyman-orthogonal moments to reduce sensitivity with respect to nuisance parameters to estimate the target parameter--with generalized random forests (Athey et al., 2017)--a flexible non-parametric method for statistical estimation of conditional moment models using random forests.
After revision: We propose the orthogonal random forest, an algorithm that combines Neyman-orthogonality to reduce sensitivity with respect to nuisance parameters to estimate the target parameter--with generalized random forests (Athey et al., 2017)--a flexible non-parametric method for statistical estimation of conditional moment models using random forests.