Author

V. Chernozhukov

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Preprint Oct 2026

Pragmatic DML with AI-Learned Representations

Text, images, and other rich covariates are increasingly compressed into AI-learned representations and then used as controls in causal analysis. We study when this approach is valid and develop a practical framework for causal inference with learned representations. For a broad class of estimands, an imperfect represe...

Andrés Fernández, V. Chernozhukov, Carlos Cinelli et al. · 0 citations

Preprint Sep 2026

Omitted Variable Bias in Difference-in-Differences Designs

We study the omitted variable bias (OVB) problem in canonical difference-in-differences (DiD) designs when unobserved confounding induces departures from the parallel trends assumption. Our results provide a novel characterization of the OVB formula for the average treatment effect on the treated (ATT), which is of ind...

Jue-Jue Wang, Pedro H. C. Sant'Anna, V. Chernozhukov et al. · 0 citations