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Adjusted empirical likelihood inferences for varying coefficient partially non linear models with endogenous covariates

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  • Xinrong Tang
  • Peixin Zhao
  • Yiping Yang
  • Weiming Yang

Abstract

In this article, based on empirical likelihood method and instrumental variable adjustment technique, we propose an adjusted empirical likelihood based statistical inference procedure for varying coefficient partially non linear models with endogenous covariates. Under some mild conditions, the constructed empirical log-likelihood ratio is shown to be asymptotically chi-squared, and then the confidence intervals for the parameter and non parametric components are constructed. Some simulation studies are conducted to examine the finite sample performance of the proposed methods.

Suggested Citation

  • Xinrong Tang & Peixin Zhao & Yiping Yang & Weiming Yang, 2022. "Adjusted empirical likelihood inferences for varying coefficient partially non linear models with endogenous covariates," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 51(4), pages 953-973, February.
    • Handle: RePEc:taf:lstaxx:v:51:y:2022:i:4:p:953-973
    DOI: 10.1080/03610926.2020.1747078
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    Cited by:

    1. 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.

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