IVDML

IVDML-package

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" tools:::Rd_expr_doi("10.48550/arXiv.2503.03530").

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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>.

Cyrill Scheidegger

Double Machine Learning with Instrumental Variables and
Heterogeneity

IVDML-package function

Maintainer: Cyrill Scheidegger <a href="/link/cyrill.scheidegger%40stat.math.ethz.ch?package=IVDML&version=1.0.1" data-mini-rdoc="IVDML::cyrill.scheidegger@stat.math.ethz.ch">cyrill.scheidegger@stat.math.ethz.ch</a> (<a href="https://orcid.org/0009-0005-2851-1384">ORCID</a>) [copyright holder]

Author

IVDML: Double Machine Learning with Instrumental Variables and Heterogeneity — IVDML-package

Maintainer: Cyrill Scheidegger <a href='mailto:cyrill.scheidegger@stat.math.ethz.ch'>cyrill.scheidegger@stat.math.ethz.ch</a> (<a href='https://orcid.org/0009-0005-2851-1384'>ORCID</a>) [copyright holder]

IVDML-package: IVDML: Double Machine Learning with Instrumental Variables and Heterogeneity

Description

Arguments

Author

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