TY  - RPRT
        AU  - Ahrens, Achim
AU  - Hansen, Christian B.
AU  - Schaffer, Mark E
AU  - Wiemann, Thomas
        TI  - ddml: Double/Debiased Machine Learning in Stata
        PY  - 2023/Feb/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 15963
        UR  - https://www.iza.org/publications/dp15963
        AB  - We introduce the package ddml for Double/Debiased Machine Learning (DDML) in Stata. Estimators of causal parameters for five different econometric models are supported, allowing for flexible estimation of causal effects of endogenous variables in settings with unknown functional forms and/or many exogenous variables. ddml is compatible with many existing supervised machine learning programs in Stata. We recommend using DDML in combination with stacking estimation which combines multiple machine learners into a final predictor. We provide Monte Carlo evidence to support our recommendation.
        KW  - doubly-robust estimation
KW  - machine learning
KW  - causal inference
KW  - st0001
        ER  -