Publication Type

Working Paper

Publication Date

2-2015

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 approximate the unknown functional coefficients by some basis functions and estimate them by the IVQR technique. We establish the uniform consistency and asymptotic normality of the estimators of the functional coefficients. Based on the sieve estimates, we propose a nonparametric specification test for the constancy of the functional coefficients, study its asymptotic properties under the null hypothesis, a sequence of local alternatives and global alternatives, and propose a wild-bootstrap procedure to obtain the bootstrap p-values. A set of Monte Carlo simulations are conducted to evaluate the finite sample behavior of both the estimator and test statistic. As an empirical illustration of our theoretical results, we present 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

Publisher

Singapore Management University, School of Economics

City or Country

Singapore

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Comments

Working Paper No. 01-2015

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