QR.break: An R Package for Structural Breaks in Quantile Regression

Qu Zhongjun (), Tatsushi Oka and Messer Samuel ()
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Qu Zhongjun: Department of Economics, Boston University, Boston, USA
Messer Samuel: Department of Economics, Boston University, Boston, USA

Journal of Econometric Methods, 2025, vol. 14, issue 1, 21-34

Abstract: The QR.break package provides methods for detecting, estimating, and conducting inference on multiple structural breaks in linear quantile regression models, based on one or multiple quantiles and applicable to both time series and repeated cross-sectional data. The main function, rq.break(), returns testing and estimation results based on user specifications of the quantiles of interest, the maximum number of breaks allowed, and the minimum length of a single regime. This note outlines the underlying methods and explains how to use the main function with two datasets: a time series dataset on U.S. real GDP growth rates and a repeated cross-sectional dataset on youth drinking and driving behavior. Both datasets are included in the package available on CRAN.

Keywords: structural break, quantile regression; time series; repeated cross-sections; software (search for similar items in EconPapers)
JEL-codes: C21 C22 C31 C52 C63 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1515/jem-2025-0010

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