Double/Debiased Machine Learning for Treatment and Structural Parameters

@article{Chernozhukov2017DoubleDebiasedML,
title={Double/Debiased Machine Learning for Treatment and Structural Parameters},
author={Victor Chernozhukov and Denis Chetverikov and Mert Demirer and Esther Duflo and Christian Hansen and Whitney Newey and James M. Robins},
journal={Econometrics: Econometric \& Statistical Methods - General eJournal},
year={2017}
}
• V. Chernozhukov, +4 authors J. Robins
• Published 2017
• Mathematics
• Econometrics: Econometric & Statistical Methods - General eJournal
We revisit the classic semiparametric problem of inference on a low dimensional parameter θ_0 in the presence of high-dimensional nuisance parameters η_0. We depart from the classical setting by allowing for η_0 to be so high-dimensional that the traditional assumptions, such as Donsker properties, that limit complexity of the parameter space for this object break down. To estimate η_0, we consider the use of statistical or machine learning (ML) methods which are particularly well-suited to… Expand
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