Double/debiased machine learning for treatment and structural parameters

Double/debiased machine learning for treatment and structural parameters

We revisit the classic semi-parametric 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 (e.g. Donsker properties) t...

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Bibliographic Details
Main Authors: Chetverikov, Denis (Author), Hansen, Christian (Author), Robins, James (Author), Chernozhukov, Victor V (Contributor), Demirer, Mert (Contributor), Duflo, Esther (Contributor), Newey, Whitney K (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Economics (Contributor), Massachusetts Institute of Technology. School of Humanities, Arts, and Social Sciences (Contributor)
Format: Article
Language:English
Published: Wiley-Blackwell, 2018-03-01T21:22:20Z.
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