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

Weiwei Zhang, Jingxuan Luo and Shengyun Ma ()
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Weiwei Zhang: College of Science, Inner Mongolia Agricultural University, Hohhot 010018, China
Jingxuan Luo: School of Statistics, Beijing Normal University, Beijing 100875, China
Shengyun Ma: College of Science, Inner Mongolia Agricultural University, Hohhot 010018, China

Mathematics, 2023, vol. 11, issue 23, 1-20

Abstract: 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.

Keywords: adaptive-weighted adjusted estimation; heteroscedastic; Nadaraya–Watson kernel estimation; semi-varying coefficient instrumental variable models (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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