Sieve instrumental variable quantile regression estimation of functional coefficient models

• Main Authors: SU, Liangjun, HOSHINO, Tadao
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2016
• Subjects: Endogeneity; Functional coefficient; Heterogeneity; Instrumental variable; Panel data; Sieve estimation; Specification test; Structural quantile function; Econometrics
• Online Access: https://ink.library.smu.edu.sg/soe_research/2133; https://ink.library.smu.edu.sg/context/soe_research/article/3133/viewcontent/SieveInstrumentalVariableQuantileRegressionEstimation_pp.pdf
• Institution: Singapore Management University

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.