Double LASSO: Replication and Practical Insights
ABSTRACT The rise of machine learning (ML) is one of the most prominent developments in applied econometrics in the past decade. The focus of much economic analysis is causal, rather than prediction, and Belloni et al. (2014) demonstrate how ML methods can be used in causal inference. This paper undertakes a narrow and wide replication of the Monte Carlo and empirical examples presented by Belloni et al. (2014). We discuss practical implications of this replication for the use of double ML methods in applied econometric research.
Authors
- Jack Fitzgerald Sice
- Tim Robinson
- Finn Lattimore
- Anna Zhu
Institutions
- The University of Melbourne (AU)
- Reserve Bank of Australia (AU)
- Gradient (United States) (US)
- RMIT University (AU)
Publication Details
- Journal
- Journal of Applied Econometrics
- Published
- 2026-02-15
- DOI
- https://doi.org/10.1002/jae.70041
- Primary Topic
- Advanced Causal Inference Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00