no code implementations • 20 Jul 2022 • Jinyong Hahn, David W. Hughes, Guido Kuersteiner, Whitney K. Newey
In particular, we find that for a variety of estimators the straightforward bootstrap bias correction gives the same higher-order variance as more complicated analytical or jackknife bias corrections.
1 code implementation • 6 Oct 2021 • Victor Chernozhukov, Whitney K. Newey, Victor Quintas-Martinez, Vasilis Syrgkanis
We also propose a Random Forest method which learns a locally linear representation of the Riesz function.
no code implementations • 31 May 2021 • Victor Chernozhukov, Whitney K. Newey, Rahul Singh
Debiased machine learning is a meta algorithm based on bias correction and sample splitting to calculate confidence intervals for functionals, i. e. scalar summaries, of machine learning algorithms.
no code implementations • 4 Sep 2020 • Whitney K. Newey, Sami Stouli
Multidimensional heterogeneity and endogeneity are important features of models with multiple treatments.
no code implementations • 27 Dec 2019 • Jelena Bradic, Victor Chernozhukov, Whitney K. Newey, Yinchu Zhu
This paper is about the feasibility and means of root-n consistently estimating linear, mean-square continuous functionals of a high dimensional, approximately sparse regression.