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cyrillsch
IVDML:Double Machine Learning with Instrumental Variables and Heterogeneity
Instrumental variable (IV) estimators for homogeneous and heterogeneous treatment effects with efficient machine learning instruments. The estimators are based on double/debiased machine learning allowing for nonlinear and potentially high-dimensional control variables. Details can be found in Scheidegger, Guo and Bühlmann (2025) "Inference for heterogeneous treatment effects with efficient instruments and machine learning" <doi:10.48550/arXiv.2503.03530>.
Maintained by Cyrill Scheidegger. Last updated 4 days ago.
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