Arbeitspapier
ddml: Double/Debiased Machine Learning in Stata
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.
- Language
-
Englisch
- Bibliographic citation
-
Series: IZA Discussion Papers ; No. 15963
- Classification
-
Wirtschaft
Semiparametric and Nonparametric Methods: General
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Econometric Software
- Subject
-
st0001
causal inference
machine learning
doubly-robust estimation
- Event
-
Geistige Schöpfung
- (who)
-
Ahrens, Achim
Hansen, Christian B.
Schaffer, Mark E
Wiemann, Thomas
- Event
-
Veröffentlichung
- (who)
-
Institute of Labor Economics (IZA)
- (where)
-
Bonn
- (when)
-
2023
- Handle
- Last update
-
10.03.2025, 11:41 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Ahrens, Achim
- Hansen, Christian B.
- Schaffer, Mark E
- Wiemann, Thomas
- Institute of Labor Economics (IZA)
Time of origin
- 2023
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