Publication Type
Journal Article
Version
submittedVersion
Publication Date
3-2016
Abstract
In this paper we consider sieve instrumental variable quantile regression (IVQR) estimation of functional coefficient models where the coefficients of endogenous regressors are unknown functions of some exogenous covariates. We estimate the functional coefficients by the sieve-IVQR technique and establish the uniform consistency and asymptotic normality of the estimators. Based on the sieve estimates, we propose a nonparametric specification test for the constancy of the functional coefficients and study its asymptotic. We conduct simulations to evaluate the finite sample behavior of our estimator and test statistic, and apply our method to study the estimation of quantile Engel curves.
Keywords
Endogeneity, Functional coefficient, Heterogeneity, Instrumental variable, Panel data, Sieve estimation, Specification test, Structural quantile function
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Econometrics
Volume
191
Issue
1
First Page
231
Last Page
254
ISSN
0304-4076
Identifier
10.1016/j.jeconom.2015.10.006
Publisher
Elsevier: 24 months
Citation
SU, Liangjun and HOSHINO, Tadao.
Sieve instrumental variable quantile regression estimation of functional coefficient models. (2016). Journal of Econometrics. 191, (1), 231-254.
Available at: https://ink.library.smu.edu.sg/soe_research/2133
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1016/j.jeconom.2015.10.006