dml-sensitivity-experiment

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Python research code for sensitivity analysis in double machine learning. A twin design, in which the hidden confounder copies an observed benchmark covariate, tests a benchmark-calibrated omitted-variable-bias bound when the benchmark is itself estimated, with an application to 401(k) eligibility and a mathematical supplement.

causal-infer... double-machi... sensitivity-... omitted-vari... econometrics monte-carlo Python reproducible...

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Created on

October 04, 2026

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