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Factor-Augmented Machine Learning Panel Regressions

Andrii Babii, Luca Barbaglia, Eric Ghysels, Jonas Striaukas

arXiv 7 Jul 2026 · Econometrics

arXiv:2607.06368 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper develops the asymptotic theory for high-dimensional panel data regressions in settings with cross-sectionally dependent errors driven by common shocks. We consider a factor-augmented sparse-group LASSO estimator that combines MIDAS aggregation with latent factors. The estimator can take advantage of the mixed-frequency group structure in the time-series dimension. Theory shows that it can outperform the standard LASSO estimator both for prediction and estimation while allowing for cross-sectional dependence.

Citation extraction

24
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35
in-text mentions
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distinct cited
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main-text words

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Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Babii, Andrii and Ghysels, Eric and Striaukas, Jonas (2022) Machine learning time series regressions with an application to nowcasting self0.81142100%
2Beyhum, Jad and Striaukas, Jonas (2026) Factor-augmented sparse MIDAS regressions with an application to nowcasting self0.81142100%
3Babii, Andrii and Ball, Ryan T and Ghysels, Eric and Striaukas, Jonas (2023) Machine learning panel data regressions with heavy-tailed dependent data: Theory and application self0.64422100%
4Cai, T Tony and Zhang, Anru R and Zhou, Yuchen (2022) Sparse group LASSO: Optimal sample complexity, convergence rate, and statistical inference0.64422100%
5Babii, Andrii and Ghysels, Eric and Pan, Junsu (2025) Tensor PCA for factor models self0.51121100%
6Andreou, Elena and Ghysels, Eric and Kourtellos, Andros (2010) Regression Models with Mixed Sampling Frequencies self0.40511100%
7Bai, Jushan (2003) Inferential theory for factor models of large dimensions0.40511100%
8Bellec, Pierre C and Lecué, Guillaume and Tsybakov, Alexandre B (2018) Slope meets LASSO: improved oracle bounds and optimality0.40511100%
9Belloni, Alexandre and Chernozhukov, Victor and Hansen, Christian (2014) Inference on Treatment Effects after Selection among High-Dimensional Controls0.40511100%
10Beyhum, Jad and Gautier, Eric (2023) Factor and factor loading augmented estimators for panel regression with possibly nonstrong factors0.40511100%

Showing the top 10 of 24 scored citations.