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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Weiwei Zhang & Jingxuan Luo & Shengyun Ma, 2023. "Estimation in Semi-Varying Coefficient Heteroscedastic Instrumental Variable Models with Missing Responses," Mathematics, MDPI, vol. 11(23), pages 1-20, December.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:23:p:4853-:d:1293007
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    References listed on IDEAS

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