A covariate-conditional distributional bridge identifies the ATT under non-monotonic confounding and yields a Neyman-orthogonal, semiparametrically efficient estimator.
Assumption 3.1 requires Y a=0 t = h (U, t) where h is strictly increasing inU for each t = 0,
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On a Debiased and Semiparametric Efficient Changes-in-Changes Estimator
A covariate-conditional distributional bridge identifies the ATT under non-monotonic confounding and yields a Neyman-orthogonal, semiparametrically efficient estimator.