From the 1 of 10 linked papers with an AI index.
10 papers
Linear Estimation of Structural and Causal Effects for Nonseparable Panel Data
Victor Chernozhukov, Ben Deaner, Ying Gao +2
The paper proposes linear sieve estimators with bias‑corrected ridge regressions to identify structural and causal effects in nonseparable panel data models that feature time‑varyi…
Higher-Order Neyman Orthogonality in Moment-Condition Models
Stéphane Bonhomme, Koen Jochmans, Whitney K. Newey +1
We construct moment functions that are Neyman-orthogonal to a chosen order in parametric moment condition models. These moment functions reduce sensitivity to nuisance estimation e…
Semiparametric Efficient Empirical Higher Order Influence Function Estimators
Lin Liu, Rajarshi Mukherjee, Whitney K. Newey +1
Robins et al. (2008, 2017) applied the theory of higher order influence functions (HOIFs) to derive an estimator of the mean of an outcome Y in a missing data model with Y mis…
Automatic Debiased Machine Learning for Covariate Shifts
Victor Chernozhukov, Michael Newey, Whitney K Newey +2
We present machine learning estimators for causal and predictive parameters under covariate shift, where covariate distributions differ between training and target populations. One…
Minimax Semiparametric Learning With Approximate Sparsity
Jelena Bradic, Victor Chernozhukov, Whitney K. Newey +1
Estimating linear, mean-square continuous functionals is a pivotal challenge in statistics. In high-dimensional contexts, this estimation is often performed under the assumption of…
Welfare Analysis in Dynamic Models
Victor Chernozhukov, Whitney Newey, Vira Semenova
This paper introduces metrics for welfare analysis in dynamic models. We develop estimation and inference for these parameters even in the presence of a high-dimensional state spac…