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Functional-coefficient quantile cointegrating regression with stationary covariates

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  • Li, Haiqi
  • Zhang, Jing
  • Zheng, Chaowen

Abstract

This study examines the estimation and inference of functional-coefficient quantile cointegrating regression. Firstly, a local linear quantile regression estimator is proposed to estimate the unknown coefficient function. Secondly, to alleviate the endogeneity problem, we propose a nonparametric fully-modified quantile regression estimator that is shown to be nh consistent and follow a mixed normal distribution asymptotically. Thirdly, we propose two Kolmogorov–Smirnov type test statistics for coefficient stability in a given quantile or across multiple quantile levels. Finally, to improve the finite sample performance, we propose a fixed regressor wild bootstrap procedure and establish its asymptotic validity. Monte Carlo simulation results confirm the merits of the proposed estimator and tests.

Suggested Citation

  • Li, Haiqi & Zhang, Jing & Zheng, Chaowen, 2025. "Functional-coefficient quantile cointegrating regression with stationary covariates," Statistics & Probability Letters, Elsevier, vol. 219(C).
    • Handle: RePEc:eee:stapro:v:219:y:2025:i:c:s0167715224003134
    DOI: 10.1016/j.spl.2024.110344
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    More about this item

    Keywords

    Quantile cointegration; Local linear smoothing; Stability tests; Fixed regressor wild bootstrap;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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