Harold D. Chiang, Antonio F. Galvao, Chia-Min Wei
arXiv 22 Feb 2026 · Econometrics
arXiv:2602.19201 · PDF · DOI · OpenAlex · Extracted main text
This paper develops an asymptotic and inferential theory for fixed-effects panel quantile regression (FEQR) that delivers inference robust to pervasive common shocks. Such shocks induce cross-sectional dependence that is central in many economic and financial panels but largely ignored in existing FEQR theory, which typically assumes cross-sectional independence and requires $T \gg N$. We show that the standard FEQR estimator remains asymptotically normal under the mild condition $(\log N)^2/T \to 0$, thereby accommodating empirically relevant regimes, including those with $T \ll N$. We further show that common shocks fundamentally alter the asymptotic covariance structure, rendering conventional covariance estimators inconsistent, and we propose a simple covariance estimator that remains consistent both in the presence and absence of common shocks. The proposed procedure therefore provides valid robust inference without requiring prior knowledge of the dependence structure, substantially expanding the applicability of FEQR methods in realistic panel data settings.
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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 | Andrews, Donald WK (2005) Cross-section regression with common shocks | 1.000 | 8 | 3 | 100% |
| 2 | Roger Koenker (2004) Quantile Regression for Longitudinal Data | 1.000 | 7 | 3 | 100% |
| 3 | Galvao, Antonio F and Gu, Jiaying and Volgushev, Stanislav (2020) On the unbiased asymptotic normality of quantile regression with fixed effects self | 1.000 | 7 | 3 | 100% |
| 4 | Kato, Kengo and Galvao, Antonio F and Montes-Rojas, Gabriel V (2012) Asymptotics for panel quantile regression models with individual effects self | 0.909 | 20 | 7 | 75% |
| 5 | Chiang, Harold D and Hansen, Bruce E and Sasaki, Yuya (2024) Standard errors for two-way clustering with serially correlated time effects self | 0.644 | 2 | 2 | 100% |
| 6 | Davezies, Laurent and D’Haultfœuille, Xavier and Guyonvarch, Yannick (2021) Empirical process results for exchangeable arrays | 0.644 | 2 | 2 | 100% |
| 7 | Jason Abrevaya and Christian M. Dahl (2008) The Effects of Birth Inputs on Birthweight: Evidence From Quantile Estimation on Panel Data | 0.405 | 1 | 1 | 100% |
| 8 | Tomohiro Ando and Jushan Bai (2020) Quantile Co-Movement in Financial Markets: A Panel Quantile Model With Unobserved Heterogeneity | 0.405 | 1 | 1 | 100% |
| 9 | Manuel Arellano and Stephane Bonhomme (2011) Nonlinear Panel Data Analysis | 0.405 | 1 | 1 | 100% |
| 10 | Manuel Arellano and Stephane Bonhomme (2016) Nonlinear Panel Data Estimation Via Quantile Regressions | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 49 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Gaussian Approximation for Maximum Score and Non-Smooth M-Estimators with Multiway Dependence | 0.405 | 1 | 1 |