Proposes nonparametric tests for treatment effect heterogeneity that avoid sample splitting, incorporate structured assumptions, and target policy-relevant alternatives comparing personalized vs. covariate-ignoring rules.
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Nonparametric tests of treatment effect homogeneity for policy-makers
Proposes nonparametric tests for treatment effect heterogeneity that avoid sample splitting, incorporate structured assumptions, and target policy-relevant alternatives comparing personalized vs. covariate-ignoring rules.