mlsanityData to 7 Oct 2026

xtdml: Double Machine Learning Estimation to Static Panel Data Models with Fixed Effects in R

arXiv 2512.15965 ↗First posted 17 Dec 2025econ.EM stat.ME stat.MLcited by 0

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 11 of its 39 references that are in the map. First posted on arXiv 17 Dec 2025.

Builds on

11 of 39 references.

References · 11

  1. 2020Double/Debiased Machine Learning for Dynamic Treatment Effects via g-Estimationcited by 27
  2. 2021DoubleML -- An Object-Oriented Implementation of Double Machine Learning in Rcited by 13
  3. 2024Hyperparameter Tuning for Causal Inference with Double Machine Learning: A Simulation Studycited by 11
  4. 2020Double machine learning for sample selection modelscited by 8
  5. 2017Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in Indiacited by 4
  6. 2023Robustness of Algorithms for Causal Structure Learning to Hyperparameter Choicecited by 4
  7. 2023Double Machine Learning for Static Panel Models with Fixed Effectscited by 4
  8. 2022How causal machine learning can leverage marketing strategies: Assessing and improving the performance of a coupon campaigncited by 2
  9. 2022Local Projection Inference in High Dimensionscited by 2
  10. 2024Difference-in-Differences with Time-varying Continuous Treatments using Double/Debiased Machine Learningcited by 1
  11. 2025Weak instrumental variables due to ignored nonlinearities in panel data: A Super Learner Control Function estimatorcited by 1

Built on by

Not cited yet.