Long Story Short: Omitted Variable Bias in Causal Machine Learning

arXiv:2112.13398 · econ.EM, cs.LG, stat.ME, stat.ML · Submitted 2021-12-26 · Read on arXiv

econ.EM, cs.LG, stat.ME, stat.ML

Submitted: 2021-12-26

Updated: 2026-09-21

Comments: This is an extended version of the paper was prepared for the NeurIPS-2021 Workshop "Causal Inference & Machine Learning: Why now?"; 55 pages; 10 figures

Journal ref: Victor Chernozhukov, Carlos Cinelli, Whitney K. Newey, Amit Sharma, Vasilis Syrgkanis. Long Story Short: Omitted Variable Bias in Causal Machine Learning. The Review of Economics and Statistics, 2026

DOI: 10.1162/REST.a.1705

Code: https://github.com/carloscinelli/dml.sensemakr

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Robustness — 12× in this paper · explained in 5 episodes
• Benchmarking — 9× in this paper · explained in 3 episodes
• Causal Inference — 7× in this paper · explained in 4 episodes
• Hilbert Space — 5× in this paper · explained in 2 episodes
• Covariate Shift — 4× in this paper · explained in 2 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Elias — 2× in this paper · explained in 2 episodes
• National Household Travel Survey — 2× in this paper
• Additivity — 1× in this paper · explained in 1 episode
• Directed Acyclic Graph — 1× in this paper
• Generalization — 1× in this paper · explained in 13 episodes
• Influence Functions — 1× in this paper · explained in 2 episodes
• Score Function — 1× in this paper · explained in 4 episodes
• Selection Bias — 1× in this paper · explained in 4 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Double/Debiased Machine Learning for Treatment and Causal Parameters
• De-Biased Machine Learning of Global and Local Parameters Using Regularized Riesz Representers
• Adversarial Estimation of Riesz Representers
• Automatic Debiased Machine Learning via Riesz Regression
• Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
• Confounding-Robust Policy Improvement
• Semiparametric sensitivity analysis: unmeasured confounding in observational studies
• Bounds on the conditional and average treatment effect with unobserved confounding factors

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