arXiv 17 Dec 2025 · Econometrics
arXiv:2512.15965 · PDF · DOI · OpenAlex · Extracted main text
The double machine learning (DML) method combines the predictive power of machine learning with statistical estimation to conduct inference about the structural parameter of interest. This paper presents the R package `xtdml`, which implements DML methods for partially linear panel regression models with low-dimensional fixed effects, high-dimensional confounding variables, proposed by Clarke and Polselli (2025). The package provides functionalities to: (a) learn nuisance functions with machine learning algorithms from the `mlr3` ecosystem, (b) handle unobserved individual heterogeneity choosing among first-difference transformation, within-group transformation, and correlated random effects, (c) transform the covariates with min-max normalization and polynomial expansion to improve learning performance. We showcase the use of `xtdml` with both simulated and real longitudinal data.
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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 | Clarke, Paul S and Polselli, Annalivia (2025) Double machine learning for static panel models with fixed effects self | 0.928 | 4 | 3 | 100% |
| 2 | Chernozhukov, Victor and Chetverikov, Denis and Demirer, Mert and Du… (2018) Double/debiased machine learning for treatment and structural parameters | 0.811 | 4 | 2 | 100% |
| 3 | P. Bach and V. Chernozhukov and M. S. Kurz and M. Spindler and Sven… (2024) DoubleML – An Object-Oriented Implementation of Double Machine Learning in R | 0.644 | 2 | 2 | 100% |
| 4 | Chang, Neng-Chieh (2020) Double/debiased machine learning for difference-in-differences models | 0.511 | 2 | 1 | 100% |
| 5 | Haddad, Michel FC and Huber, Martin and Zhang, Lucas Z (2024) Difference-in-Differences with Time-varying Continuous Treatments using Double/Debiased Machine Learning | 0.511 | 2 | 1 | 100% |
| 6 | Philipp Bach and Malte S. Kurz and Victor Chernozhukov and Martin Sp… (2024) DoubleML: Double Machine Learning in R | 0.405 | 1 | 1 | 100% |
| 7 | R Core Team (2025) R: A Language and Environment for Statistical Computing | 0.405 | 1 | 1 | 100% |
| 8 | Winston Chang (2025) R6: Encapsulated Classes with Reference Semantics | 0.405 | 1 | 1 | 100% |
| 9 | Rebecca Sela and Jeffrey Simonoff and Wenbo Jing (2025) REEMtree: Regression Trees with Random Effects for Longitudinal (Panel) Data | 0.405 | 1 | 1 | 100% |
| 10 | Victor Chernozhukov and Ivan Fernandez-Val and Chen Huang and Weinin… (2025) ablasso: Arellano-Bond LASSO Estimator for Dynamic Linear Panel Models | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 43 scored citations.