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Abstract

Quantile regression for panel data has become a common model of interest for econometricians and statisticians. The theoretical literature has addressed important questions, including identification, estimation, and statistical inference. Although recent advances have enabled practitioners to estimate flexible models under a wide range of assumptions, practical issues have not been fully addressed. In this paper, we offer a guide to empirical practice intended to help applied researchers navigate the challenges of estimation and inference for panel quantile models. We also present a series of practical recommendations and illustrations, emphasizing both “why” and the “how” to help researchers with the implementation of existing approaches.

Document Type

Article

Publication Date

2026

Notes/Citation Information

© 2026 The Author(s). Published with license by Taylor & Francis Group, LLC This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

Digital Object Identifier (DOI)

https://doi.org/10.1080/07474938.2026.2642065

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