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Factor-Augmented Panel Regressions and Variance-Weighted Treatment Effects

Artūras Juodis, Martin Weidner

arXiv 20 Apr 2026 · Econometrics

arXiv:2604.18078 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We revisit panel regressions with unobserved heterogeneity through the lens of variance-weighted average treatment effects. Building on established results for cross-sectional OLS and one-way fixed effects panels, we show that two-way panel estimators with latent factors, specifically the principal components estimator of Greenaway-McGrevy, Han and Sul (2012) and the interactive fixed effects estimator of Bai (2009), also converge to interpretable estimands under fully nonparametric assumptions. Both estimators consistently estimate the same variance-weighted average of unit-time-specific treatment effects, where the weights are proportional to the conditional variance of the regressor given the unobserved heterogeneity. The result requires the number of estimated factors to grow with the sample size and applies to the single regressor case. We discuss the challenges that arise when extending to multiple regressors and to inference.

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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
1Bai, J (2009) Panel data models with interactive fixed effects1.00075100%
2Goldsmith-Pinkham, P., P. Hull, and M. Kolesár (2024) Contamination bias in linear regressions1.00053100%
3Pesaran, M. H (2006) Estimation and inference in large heterogeneous panels with a multifactor error structure0.9416483%
4Greenaway-McGrevy, R., C. Han, and D. Sul (2012) Asymptotic distribution of factor augmented estimators for panel regression0.92844100%
5Lu, X. and L. Su (2023) Uniform inference in linear panel data models with two-dimensional heterogeneity0.92843100%
6Chernozhukov, V., C. Hansen, Y. Liao, and Y. Zhu (2019) Inference for heterogeneous effects using low-rank estimation of factor slopes0.92843100%
7Beyhum, J. and M. Mugnier (2024) Inference after discretizing unobserved heterogeneity0.87482100%
8Westerlund, J. and J.-P. Urbain (2015) Cross-sectional averages versus principal components0.84333100%
9Freeman, H. and M. Weidner (2023) Linear panel regressions with two-way unobserved heterogeneity0.76911545%
10Juodis, A (2025) This shock is different: Estimation and inference in misspecified two-way fixed effects regressions self0.7374350%

Showing the top 10 of 101 scored citations.