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Estimation for single-index varying-coefficient spatial autoregressive model with index covariate measurement errors

Author

Listed:
  • Ke Wang

    (Liaoning University
    Changchun University of Technology)

  • Jingwen Huang

    (Liaoning University)

  • Dehui Wang

    (Liaoning University)

Abstract

This paper proposes a single-index varying coefficient spatial autoregressive model which has measurement errors in the index covariates. We combine a local-linear smoother based simulation-extrapolation (SIMEX) algorithm, the estimation equation and the profile maximum likelihood method to estimate our model. Under some regular conditions, the estimator for the nonparametric part is proved to be asymptotically normal at any fixed point, and the estimators for the parametric part are derived to be asymptotically normal as well. Some simulation studies indicate our estimation method performs well. Finally, our method is illustrated with the real dataset of Boston Housing Price.

Suggested Citation

  • Ke Wang & Jingwen Huang & Dehui Wang, 2025. "Estimation for single-index varying-coefficient spatial autoregressive model with index covariate measurement errors," Statistical Papers, Springer, vol. 66(6), pages 1-42, October.
    • Handle: RePEc:spr:stpapr:v:66:y:2025:i:6:d:10.1007_s00362-025-01750-6
    DOI: 10.1007/s00362-025-01750-6
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    References listed on IDEAS

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    1. Lixing Zhu & Liugen Xue, 2006. "Empirical likelihood confidence regions in a partially linear single‐index model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(3), pages 549-570, June.
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