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

Author

Listed:
  • Qu Zhongjun

    (Department of Economics, Boston University, Boston, USA)

  • Oka Tatsushi

    (Department of Economics, Keio University, Minato, Japan)

  • Messer Samuel

    (Department of Economics, Boston University, Boston, USA)

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.

Suggested Citation

  • Qu Zhongjun & Oka Tatsushi & Messer Samuel, 2025. "QR.break: An R Package for Structural Breaks in Quantile Regression," Journal of Econometric Methods, De Gruyter, vol. 14(1), pages 21-34.
    • Handle: RePEc:bpj:jecome:v:14:y:2025:i:1:p:21-34:n:1004
    DOI: 10.1515/jem-2025-0010
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    Keywords

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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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