Paul Hünermund, Beyers Louw, Itamar Caspi
arXiv 25 Aug 2021 · Econometrics · publishedJournal of Causal Inference (2023) · 23 citations (OpenAlex)
arXiv:2108.11294 · PDF · DOI · OpenAlex · Extracted main text
Double machine learning (DML) has become an increasingly popular tool for automated variable selection in high-dimensional settings. Even though the ability to deal with a large number of potential covariates can render selection-on-observables assumptions more plausible, there is at the same time a growing risk that endogenous variables are included, which would lead to the violation of conditional independence. This paper demonstrates that DML is very sensitive to the inclusion of only a few "bad controls" in the covariate space. The resulting bias varies with the nature of the theoretical causal model, which raises concerns about the feasibility of selecting control variables in a data-driven way.
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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 | Belloni, A., V. Chernozhukov, and C. Hansen (2014) Inference on treatment effects after selection among high-dimensional controls | 0.874 | 5 | 2 | 100% |
| 2 | Blau, F. D. and L. M. Kahn (2017) The gender wage gap: Extent, trends, and explanations | 0.874 | 5 | 2 | 100% |
| 3 | Chernozhukov, V., D. Chetverikov, M. Demirer, E. Duflo, C. Hansen, W… (2018) Double/debiased machine learning for treatment and structural parameters | 0.811 | 4 | 2 | 100% |
| 4 | Cinelli, C., A. Forney, and J. Pearl (2022) A crash course in good and bad controls | 0.737 | 3 | 2 | 100% |
| 5 | Pearl, J (1995) Causal diagrams for empirical research | 0.737 | 3 | 2 | 100% |
| 6 | Pearl, J (2009) Causality: Models, Reasoning, and Inference\/ (2nd ed.) | 0.693 | 5 | 1 | 100% |
| 7 | Bareinboim, E., J. D. Correa, D. Ibeling, and T. Icard (2022, Februa… (2022) On pearl’s hierarchy and the foundations of causal inference | 0.644 | 2 | 2 | 100% |
| 8 | Hünermund, P. and E. Bareinboim (2023) Causal inference and data fusion in econometrics | 0.585 | 3 | 1 | 100% |
| 9 | Vanneste, B. S. and R. Gulati (2021) Generalized trust, external sourcing, and firm performance in economic downturns | 0.585 | 3 | 1 | 100% |
| 10 | Angrist, J. D. and B. Frandsen (2022) Machine labor | 0.511 | 2 | 1 | 100% |
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