Semiparametric variable selection for partially varying coefficient models with endogenous variables

Yuan, Jinyi; Zhao, Peixin; Zhang, Weiguo

doi:10.1007/s00180-015-0601-y

Cited by 9 publications

(1 citation statement)

References 14 publications

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“…Zhao and Xue [18] considered the interval estimation for semiparametric instrumental variable models by using the empirical likelihood method. Yuan et al [19] proposed an effective method to identify important variables by combining the SCAD penalty method and instrumental variable adjustment technique for semi-varying coefficient models with endogenous covariates. Zhao et al [20] applied the popular empirical likelihood approach to study the effective interval estimation for semi-varying coefficient instrumental variable models with the orthogonal decomposition technique.…”

Section: Introductionmentioning

confidence: 99%

Estimation in Semi-Varying Coefficient Heteroscedastic Instrumental Variable Models with Missing Responses

Zhang,

Luo,

2023

Mathematics

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This paper studies the estimation problem for semi-varying coefficient heteroscedastic instrumental variable models with missing responses. First, we propose the adjusted estimators for unknown parameters and smooth functional coefficients utilizing the ordinary profile least square method and instrumental variable adjustment technique with complete data. Second, we present an adjusted estimator of the stochastic error variance by employing the Nadaraya–Watson kernel estimation technique. Third, we apply the inverse probability-weighted method and instrumental variable adjustment technique to construct the adaptive-weighted adjusted estimators for unknown parameters and smooth functional coefficients. The asymptotic properties of our proposed estimators are established under some regularity conditions. Finally, numerous simulation studies and a real data analysis are conducted to examine the finite sample performance of the proposed estimators.

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Section: Introductionmentioning

confidence: 99%