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We propose robust methods for inference on the effect of a treatment variable on a scalar outcome in the presence of very many controls. Our setting is a partially linear model with possibly non-Gaussian and heteroscedastic disturbances where the number of controls may be much larger than the...
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characterize the identified set of such densities. We obtain novel conditions for point identification, and establish that point … identification is generically weak. Given this insight, we provide a consistent nonparametric estimator that accounts for this fact …
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