Achim Ahrens, Victor Chernozhukov, Christian Hansen, Damian Kozbur, Mark Schaffer, Thomas Wiemann
arXiv 11 Apr 2025 · Econometrics · 3 citations (OpenAlex)
arXiv:2504.08324 · PDF · DOI · OpenAlex · Extracted main text
This paper provides a practical introduction to Double/Debiased Machine Learning (DML). DML provides a general approach to performing inference about a target parameter in the presence of nuisance parameters. The aim of DML is to reduce the impact of nuisance parameter estimation on estimators of the parameter of interest. We describe DML and its two essential components: Neyman orthogonality and cross-fitting. We highlight that DML reduces functional form dependence and accommodates the use of complex data types, such as text data. We illustrate its application through three empirical examples that demonstrate DML's applicability in cross-sectional and panel settings.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Dube, Arindrajit, Jacobs, Jeff, Naidu, Suresh, Suri, Siddharth (2020) Monopsony in Online Labor Markets | 1.000 | 12 | 3 | 100% |
| 2 | Chernozhukov, Victor, Chetverikov, Denis, Demirer, Mert, Duflo, Esth… (2018) Double/debiased machine learning for treatment and structural parameters self | 0.974 | 13 | 7 | 92% |
| 3 | Ahrens, Achim, Hansen, Christian B., Schaffer, Mark E., Wiemann, Tho… (2025) Model averaging and double machine learning self | 0.928 | 4 | 3 | 100% |
| 4 | Sun, Liyang, Abraham, Sarah (2021) Estimating dynamic treatment effects in event studies with heterogeneous treatment effects | 0.874 | 7 | 2 | 100% |
| 5 | Dobkin, Carlos, Finkelstein, Amy, Kluender, Raymond, Notowidigdo, Ma… (2018) The economic consequences of hospital admissions | 0.874 | 6 | 2 | 100% |
| 6 | Callaway, Brantly, Sant'Anna, Pedro H. C (2021) Difference-in-differences with multiple time periods | 0.874 | 5 | 2 | 100% |
| 7 | Chernozhukov, Victor, Escanciano, Juan Carlos, Ichimura, Hidehiko, N… (2022) Locally robust semiparametric estimation self | 0.843 | 4 | 4 | 75% |
| 8 | Newey, Whitney K (1994) The asymptotic variance of semiparametric estimators | 0.843 | 4 | 4 | 75% |
| 9 | Kennedy, Edward H (2023) Semiparametric doubly robust targeted double machine learning: a review | 0.737 | 3 | 3 | 67% |
| 10 | Angrist, Joshua D., Imbens, Guido W., Krueger, Alan B (1999) Jackknife Instrumental Variables Estimation | 0.737 | 3 | 2 | 100% |
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