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.
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Sice et al. (Sun,) studied this question.
www.synapsesocial.com/papers/6994055d4e9c9e835dfd6364 — DOI: https://doi.org/10.1002/jae.70041
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:
Jack Fitzgerald Sice
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Journal of Applied Econometrics
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