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Local asymptotics for nonparametric quantile regression with regression splines

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  • Zhao, Weihua
  • Lian, Heng

Abstract

We consider nonparametric quantile regression using B-splines and derive local asymptotic properties of the estimator. As a by-product, we establish the convergence rate of the estimator in L∞ norm which seems to be missing in the literature. Simulations are carried out to investigate the coverage of the pointwise confidence interval.

Suggested Citation

  • Zhao, Weihua & Lian, Heng, 2016. "Local asymptotics for nonparametric quantile regression with regression splines," Statistics & Probability Letters, Elsevier, vol. 117(C), pages 209-215.
    • Handle: RePEc:eee:stapro:v:117:y:2016:i:c:p:209-215
    DOI: 10.1016/j.spl.2016.06.002
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    References listed on IDEAS

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    1. Cai, Zongwu & Xu, Xiaoping, 2009. "Nonparametric Quantile Estimations for Dynamic Smooth Coefficient Models," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 371-383.
    2. Belloni, Alexandre & Chernozhukov, Victor & Chetverikov, Denis & Kato, Kengo, 2015. "Some new asymptotic theory for least squares series: Pointwise and uniform results," Journal of Econometrics, Elsevier, vol. 186(2), pages 345-366.
    3. Chen, Xiaohong & Liao, Zhipeng, 2014. "Sieve M inference on irregular parameters," Journal of Econometrics, Elsevier, vol. 182(1), pages 70-86.
    4. Cai, Zongwu & Xiao, Zhijie, 2012. "Semiparametric quantile regression estimation in dynamic models with partially varying coefficients," Journal of Econometrics, Elsevier, vol. 167(2), pages 413-425.
    5. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
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