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Multivariate spatial autoregressive model for large scale social networks

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  • Zhu, Xuening
  • Huang, Danyang
  • Pan, Rui
  • Wang, Hansheng

Abstract

The rapid growth of social network platforms generates a large amount of social network data, where multivariate responses are frequently collected from users. To statistically model such type of data, the multivariate spatial autoregressive (MSAR) model is studied. To estimate the model, the quasi maximum likelihood estimator (QMLE) is obtained under certain technical conditions. However, it is found that the computational cost of QMLE is expensive. To fix this problem, a least squares estimator (LSE) is developed. The corresponding identification conditions and asymptotic properties are investigated. To gauge the finite sample performance of various estimators, a number of simulation studies are conducted. Lastly, a Sina Weibo dataset is analyzed for illustration purpose.

Suggested Citation

  • Zhu, Xuening & Huang, Danyang & Pan, Rui & Wang, Hansheng, 2020. "Multivariate spatial autoregressive model for large scale social networks," Journal of Econometrics, Elsevier, vol. 215(2), pages 591-606.
    • Handle: RePEc:eee:econom:v:215:y:2020:i:2:p:591-606
    DOI: 10.1016/j.jeconom.2018.11.018
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    Cited by:

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    3. Bofei Xiao & Bo Lei & Wei Lan & Bin Guo, 2022. "A blockwise network autoregressive model with application for fraud detection," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(6), pages 1043-1065, December.
    4. Dong, Ruipeng & Li, Daoji & Zheng, Zemin, 2021. "Parallel integrative learning for large-scale multi-response regression with incomplete outcomes," Computational Statistics & Data Analysis, Elsevier, vol. 160(C).
    5. Gupta, Abhimanyu, 2023. "Efficient closed-form estimation of large spatial autoregressions," Journal of Econometrics, Elsevier, vol. 232(1), pages 148-167.
    6. Valentin Courgeau & Almut E. D. Veraart, 2022. "Likelihood theory for the graph Ornstein-Uhlenbeck process," Statistical Inference for Stochastic Processes, Springer, vol. 25(2), pages 227-260, July.
    7. Ando, Tomohiro & Li, Kunpeng & Lu, Lina, 2023. "A spatial panel quantile model with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 232(1), pages 191-213.
    8. Xuan Liang & Tao Zou, 2023. "Quasi-Score Matching Estimation for Spatial Autoregressive Model with Random Weights Matrix and Regressors," Papers 2305.19721, arXiv.org.
    9. Christis Katsouris, 2024. "Robust Estimation in Network Vector Autoregression with Nonstationary Regressors," Papers 2401.04050, arXiv.org.
    10. Wu, Shihao & Li, Zhe & Zhu, Xuening, 2023. "A distributed community detection algorithm for large scale networks under stochastic block models," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).

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    More about this item

    Keywords

    Least squares estimator; Quasi maximum likelihood estimator; Multivariate responses; Social network; Network autoregression;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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