Grigory Franguridi, Bulat Gafarov, Kaspar Wuthrich
arXiv 5 Nov 2020 · Econometrics · publishedJournal of Econometrics (2025) · 1 citations (OpenAlex)
arXiv:2011.03073 · PDF · DOI · OpenAlex · Extracted main text
We study the bias of classical quantile regression and instrumental variable quantile regression estimators. While being asymptotically first-order unbiased, these estimators can have non-negligible second-order biases. We derive a higher-order stochastic expansion of these estimators using empirical process theory. Based on this expansion, we derive an explicit formula for the second-order bias and propose a feasible bias correction procedure that uses finite-difference estimators of the bias components. The proposed bias correction method performs well in simulations. We provide an empirical illustration using Engel's classical data on household food expenditure.
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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 | Chernozhukov, V. and C. Hansen (2006) Instrumental quantile regression inference for structural and treatment effect models | 0.928 | 4 | 3 | 100% |
| 2 | Koenker, R. and G. Bassett (1978) Regression Quantiles | 0.843 | 3 | 3 | 100% |
| 3 | Chen, L.-Y. and S. Lee (2018) Exact computation of GMM estimators for instrumental variable quantile regression models | 0.737 | 4 | 3 | 50% |
| 4 | Zhu, Y (2019) Learning non-smooth models: instrumental variable quantile regressions and related problems | 0.737 | 3 | 3 | 67% |
| 5 | Kaplan, D. M. and Y. Sun (2017) Smoothed estimating equations for instrumental variables quantile regression | 0.737 | 3 | 2 | 100% |
| 6 | Koenker, R. and K. F. Hallock (2001) Quantile Regression | 0.737 | 3 | 2 | 100% |
| 7 | Nagar, A. L (1959) The Bias and Moment Matrix of the General k-Class Estimators of the Parameters in Simultaneous Equations | 0.737 | 3 | 2 | 100% |
| 8 | Ota, H., K. Kato, and S. Hara (2019) Quantile regression approach to conditional mode estimation | 0.693 | 12 | 5 | 33% |
| 9 | Angrist, J., V. Chernozhukov, and I. Fernández-Val (2006) Quantile regression under misspecification, with an application to the US wage structure | 0.644 | 4 | 2 | 50% |
| 10 | Engel, E (1857) Die Produktions- und Konsumptionsverhältnisse des Königreichs Sachsen | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 48 scored citations.