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Huber estimation for the network autoregressive model

Author

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  • Xiao, Xuan
  • Xu, Xingbai
  • Zhong, Wei

Abstract

We propose the Huber estimator for the network autoregressive model, which exhibits both robustness and efficiency under heavy-tailed errors and loses little efficiency compared to OLS under light-tailed errors.

Suggested Citation

  • Xiao, Xuan & Xu, Xingbai & Zhong, Wei, 2023. "Huber estimation for the network autoregressive model," Statistics & Probability Letters, Elsevier, vol. 203(C).
    • Handle: RePEc:eee:stapro:v:203:y:2023:i:c:s0167715223001414
    DOI: 10.1016/j.spl.2023.109917
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    References listed on IDEAS

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    1. Zhu, Xuening & Wang, Weining & Wang, Hansheng & Härdle, Wolfgang Karl, 2019. "Network quantile autoregression," Journal of Econometrics, Elsevier, vol. 212(1), pages 345-358.
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    4. Marco Avella-Medina & Heather S Battey & Jianqing Fan & Quefeng Li, 2018. "Robust estimation of high-dimensional covariance and precision matrices," Biometrika, Biometrika Trust, vol. 105(2), pages 271-284.
    5. Shin, Dong Wan & Kang, Seungho, 2006. "An instrumental variable approach for panel unit root tests under cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 134(1), pages 215-234, September.
    6. Huang, Danyang & Wang, Feifei & Zhu, Xuening & Wang, Hansheng, 2020. "Two-mode network autoregressive model for large-scale networks," Journal of Econometrics, Elsevier, vol. 216(1), pages 203-219.
    7. Qiang Sun & Wen-Xin Zhou & Jianqing Fan, 2020. "Adaptive Huber Regression," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(529), pages 254-265, January.
    8. Lung-fei Lee & Xiaodong Liu & Xu Lin, 2010. "Specification and estimation of social interaction models with network structures," Econometrics Journal, Royal Economic Society, vol. 13(2), pages 145-176, July.
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