A general framework derives exact outcome weights for double machine learning and generalized random forest estimators, showing that standard implementations are only scale-normalized rather than fully-normalized.
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Treatment Effect Estimators as Weighted Outcomes
A general framework derives exact outcome weights for double machine learning and generalized random forest estimators, showing that standard implementations are only scale-normalized rather than fully-normalized.