34 citations · 237 across the 46 of their papers we have counts for
6 papers · 1 filter
Stable Policy Learning
Harvey Barnhard, Giacomo Opocher, Rahul Singh
In evidence-based policymaking, typically one experimental sample is observed, then a learned policy recommendation is implemented at scale. Policies learned from the experimental…
Automatic Debiased Machine Learning for Dynamic Treatment Effects and General Nested Functionals
Victor Chernozhukov, Whitney Newey, Rahul Singh +1
Many canonical models in causal inference and structural econometrics have recursive identification formulas. In causal inference, recursion arises when identification requires bot…
Kernel methods for long term dose response curves
Rahul Singh, Hannah Zhou
A core challenge in causal inference is how to extrapolate long term effects, of possibly continuous actions, from short term experimental data. It arises in artificial intelligenc…
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…
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…
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…