Identification and estimation in quantile varying-coefficient models with unknown link function

Lili Yue, Gaorong Li () and Heng Lian
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Lili Yue: Beijing University of Technology
Gaorong Li: Beijing University of Technology
Heng Lian: City University of Hong Kong

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2019, vol. 28, issue 4, No 14, 1275 pages

Abstract: Abstract In this paper, we consider the estimation problem of quantile varying-coefficient models when the link function is unspecified, which significantly expands the existing works on varying-coefficient models with unspecified link function focusing only on mean regression. We provide new identification conditions which are weaker than existing ones. Under these identification conditions, we use polynomial splines to estimate both the varying coefficients and the link functions and establish the convergence rate of the estimator. Our simulation studies and a real data application illustrate the finite sample performance of the estimators.

Keywords: Asymptotic property; B-splines; Check loss minimization; Single-index models; Quantile regression; 62G08; 62G20; 62G35 (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s11749-019-00638-6

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