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We propose generalized random forests, a method for non-parametric statistical estimation based on random forests (Breiman, 2001) that can be used to fit any quantity of interest identified as the solution to a set of local moment equations.
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[author] Athey, SusanS. and Imbens, GuidoG. (2016). Recursive partitioning for heterogeneous causal effects. Proceedings of the National Academy of Sciences 113 7353–7360
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[author] Wager, StefanS. and Athey, SusanS. (2018). Estimation and inference of heterogeneous treatment effects using random forests. JASA just-accepted
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