Introduces covariate-adjustment with sample-splitting for finite-sample valid inference on points of the treatment effect distribution, applied to five microcredit RCTs revealing heterogeneous effects despite null averages.
Then, there exists¯θL,Pn, ¯θU,Pn with ¯θL,Pn ≤ θ∗ L,Pn ≤ θPn ≤ θ∗ U,Pn ≤ ¯θU,Pn such that √n " bθL − ¯θL,Pn bθU − ¯θU,Pn # d → N 0 0 , σ2 L σL,U σL,U σ2 U Proof of Theorem A.1
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Predicting the Distribution of Treatment Effects: A Covariate-Adjustment Approach
Introduces covariate-adjustment with sample-splitting for finite-sample valid inference on points of the treatment effect distribution, applied to five microcredit RCTs revealing heterogeneous effects despite null averages.