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Two-mode network autoregressive model for large-scale networks

Author

Listed:
  • Huang, Danyang
  • Wang, Feifei
  • Zhu, Xuening
  • Wang, Hansheng

Abstract

A two-mode network refers to a network where the nodes are classified into two distinct types, and edges can only exist between nodes of different types. In analysis of two-mode networks, one important objective is to explore the relationship between responses of two types of nodes. To this end, we propose a network autoregressive model for two-mode networks. Different network autocorrelation coefficients are allowed. To estimate the model, a quasi-maximum likelihood estimator is developed with high computational cost. To alleviate the computational burden, a least squares estimator is proposed, which is applicable in large-scale networks. The least squares estimator can be viewed as one particular type of generalized methods of moments estimator. The theoretical properties of both estimators are investigated. The finite sample performances are assessed through simulations and a real data example.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:econom:v:216:y:2020:i:1:p:203-219
    DOI: 10.1016/j.jeconom.2020.01.014
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    Cited by:

    1. Alex Centeno, 2022. "A Structural Model for Detecting Communities in Networks," Papers 2209.08380, arXiv.org, revised Oct 2022.
    2. Huang, Danyang & Hu, Wei & Jing, Bingyi & Zhang, Bo, 2023. "Grouped spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    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. Xiao, Xuan & Xu, Xingbai & Zhong, Wei, 2023. "Huber estimation for the network autoregressive model," Statistics & Probability Letters, Elsevier, vol. 203(C).
    5. Fan, Xinyan & Fang, Kuangnan & Pu, Dan & Qin, Ruixuan, 2024. "Generalized latent space model for one-mode networks with awareness of two-mode networks," Computational Statistics & Data Analysis, Elsevier, vol. 193(C).
    6. Xuan Liang & Tao Zou, 2023. "Quasi-Score Matching Estimation for Spatial Autoregressive Model with Random Weights Matrix and Regressors," Papers 2305.19721, arXiv.org.
    7. Christis Katsouris, 2024. "Robust Estimation in Network Vector Autoregression with Nonstationary Regressors," Papers 2401.04050, arXiv.org.
    8. Wu, Yujia & Lan, Wei & Fan, Xinyan & Fang, Kuangnan, 2024. "Bipartite network influence analysis of a two-mode network," Journal of Econometrics, Elsevier, vol. 239(2).

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    More about this item

    Keywords

    Two-mode network; Quasi-maximum likelihood estimator; Least squares estimator; Network autoregressive model; Large-scale network;
    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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