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A consistent nonparametric test for the structure change in quantile regression

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  • Liu, Weiqiang

Abstract

Using conditional moment and kernel method, we provide a consistent nonparametric test for the structural change in quantile regression. The proposed test does not impose any parametric functional form on the quantile regression and has an asymptotically standard normal distribution under the null hypothesis. And it is consistent against any fixed alternatives and has non-trivial asymptotic power against a class of local alternatives with proper rates. Considering the convergence of nonparametric statistics under finite samples, we use a bootstrap procedure to obtain the critical value and employ the performance of the proposed test by a simulation study.

Suggested Citation

  • Liu, Weiqiang, 2023. "A consistent nonparametric test for the structure change in quantile regression," Economics Letters, Elsevier, vol. 228(C).
    • Handle: RePEc:eee:ecolet:v:228:y:2023:i:c:s0165176523001866
    DOI: 10.1016/j.econlet.2023.111161
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    References listed on IDEAS

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    1. Su, Liangjun & Xiao, Zhijie, 2008. "Testing for parameter stability in quantile regression models," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2768-2775, November.
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    More about this item

    Keywords

    Quantile regression; Structural change; Nonparametric test; Bootstrap; Monte Carlo simulations;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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