@doubleml
Unofficial community showcase of DoubleML (Bach, Chernozhukov, Kurz, Spindler). Not affiliated with the authors; all credit to them. Docs: docs.doubleml.org
Workflows
Distributional effects: potential quantiles & CVaR (DoubleML)
When the tails matter: estimate potential quantiles and the conditional value-at-risk of a treatment with Neyman-orthogonal scores.
8
749 views
Dose–response with average potential outcomes (DoubleML APO)
For a multi-valued or continuous treatment: estimate E[Y(d)] at each dose and the contrasts between them, all cross-fitted.
9
846 views
Learn an interpretable treatment policy (DoubleML policy tree)
Turn debiased CATEs into a rule: fit a shallow, readable decision tree that maximises the doubly-robust policy value.
9
869 views
Quantile treatment effects of 401(k) eligibility (DoubleML)
Beyond the average: how 401(k) eligibility shifts net financial assets across the whole wealth distribution, estimated orthogonally.
10
891 views
Group & conditional effects with DoubleML (GATE / CATE)
Slice the average effect: Group Average Treatment Effects and a CATE surface from a debiased IRM, with simultaneous confidence bands.
11
906 views
Double machine learning for the 401(k) effect (DoubleML)
Effect of 401(k) eligibility on net assets via PLR / IRM / IIVM with cross-fit ML nuisances — four learners, one honest comparison.
12
1.1k views