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econ.EM2021
Generalized Kernel Ridge Regression for Causal Inference with Missing-at-Random Sample Selection
Rahul Singh
I propose kernel ridge regression estimators for nonparametric dose response curves and semiparametric treatment effects in the setting where an analyst has access to a selected sa…
econ.EM2021★ 1 cited
Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy
Anish Agarwal, Rahul Singh
The US Census Bureau will deliberately corrupt data sets derived from the 2020 US Census, enhancing the privacy of respondents while potentially reducing the precision of economic…
econ.EM2021
Adversarial Estimation of Riesz Representers
Victor Chernozhukov, Whitney Newey, Rahul Singh +1
Many causal parameters are linear functionals of an underlying regression. The Riesz representer is a key component in the asymptotic variance of a semiparametrically estimated lin…