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Sieve instrumental variable quantile regression estimation of functional coefficient models

Liangjun Su and Tadao Hoshino ()

Journal of Econometrics, 2016, vol. 191, issue 1, 231-254

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 (search for similar items in EconPapers)
JEL-codes: C12 C13 C14 C21 C23 C26 (search for similar items in EconPapers)
Date: 2016
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Working Paper: Sieve Instrumental Variable Quantile Regression Estimation of Functional Coefficient Models (2015) Downloads
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DOI: 10.1016/j.jeconom.2015.10.006

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Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

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