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Grouped spatial autoregressive model

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  • Huang, Danyang
  • Hu, Wei
  • Jing, Bingyi
  • Zhang, Bo

Abstract

With the development of the internet, network data with replications can be collected at different time points. The spatial autoregressive panel (SARP) model is a useful tool for analyzing such network data. However, in the traditional SARP model, all individuals are assumed to be homogeneous in their network autocorrelation coefficients, while in practice, correlations could differ for the nodes in different groups. Here, a grouped spatial autoregressive (GSAR) model based on the SARP model is proposed to permit network autocorrelation heterogeneity among individuals, while analyzing network data with independent replications across different time points and strong spatial effects. Each individual in the network belongs to a latent specific group, which is characterized by a set of parameters. Two estimation methods are studied: two-step naive least-squares estimator, and two-step conditional least-squares estimator. Furthermore, their corresponding asymptotic properties and technical conditions are investigated. To demonstrate the performance of the proposed GSAR model and its corresponding estimation methods, numerical analysis was performed on simulated and real data.

Suggested Citation

  • Huang, Danyang & Hu, Wei & Jing, Bingyi & Zhang, Bo, 2023. "Grouped spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    • Handle: RePEc:eee:csdana:v:178:y:2023:i:c:s0167947322001815
    DOI: 10.1016/j.csda.2022.107601
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    as
    1. William C. Horrace & Hyunseok Jung & Shane Sanders, 2022. "Network Competition and Team Chemistry in the NBA," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 35-49, January.
    2. Pace, R. Kelley & Barry, Ronald & Gilley, Otis W. & Sirmans, C. F., 2000. "A method for spatial-temporal forecasting with an application to real estate prices," International Journal of Forecasting, Elsevier, vol. 16(2), pages 229-246.
    3. Yu, Jihai & de Jong, Robert & Lee, Lung-fei, 2008. "Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both n and T are large," Journal of Econometrics, Elsevier, vol. 146(1), pages 118-134, September.
    4. Lee, Lung-fei & Yu, Jihai, 2010. "Estimation of spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 154(2), pages 165-185, February.
    5. Stéphane Bonhomme & Elena Manresa, 2015. "Grouped Patterns of Heterogeneity in Panel Data," Econometrica, Econometric Society, vol. 83(3), pages 1147-1184, May.
    6. LeSage, James P. & Chih, Yao-Yu, 2018. "A Bayesian spatial panel model with heterogeneous coefficients," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 58-73.
    7. Liangjun Su & Zhentao Shi & Peter C. B. Phillips, 2016. "Identifying Latent Structures in Panel Data," Econometrica, Econometric Society, vol. 84, pages 2215-2264, November.
    8. Seung C. Ahn & Alex R. Horenstein, 2013. "Eigenvalue Ratio Test for the Number of Factors," Econometrica, Econometric Society, vol. 81(3), pages 1203-1227, May.
    9. Lee, Lung-fei & Yu, Jihai, 2014. "Efficient GMM estimation of spatial dynamic panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 180(2), pages 174-197.
    10. H. Kelejian, Harry & Prucha, Ingmar R., 2001. "On the asymptotic distribution of the Moran I test statistic with applications," Journal of Econometrics, Elsevier, vol. 104(2), pages 219-257, September.
    11. Michele Aquaro & Natalia Bailey & M. Hashem Pesaran, 2021. "Estimation and inference for spatial models with heterogeneous coefficients: An application to US house prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 18-44, January.
    12. Smirnov, Oleg & Anselin, Luc, 2001. "Fast maximum likelihood estimation of very large spatial autoregressive models: a characteristic polynomial approach," Computational Statistics & Data Analysis, Elsevier, vol. 35(3), pages 301-319, January.
    13. Michael Beenstock & Daniel Felsenstein, 2019. "The Econometric Analysis of Non-Stationary Spatial Panel Data," Advances in Spatial Science, Springer, number 978-3-030-03614-0, Fall.
    14. Fan J. & Li R., 2001. "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1348-1360, December.
    15. Liangjun Su & Xia Wang & Sainan Jin, 2019. "Sieve Estimation of Time-Varying Panel Data Models With Latent Structures," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(2), pages 334-349, April.
    16. Hubert Jayet & Julie Le Gallo & Luc Anselin, 2008. "Spatial Econometrics and Panel Data Models," Post-Print hal-02389412, HAL.
    17. Nicolai Bissantz & Lutz Dümbgen & Hajo Holzmann & Axel Munk, 2007. "Non‐parametric confidence bands in deconvolution density estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(3), pages 483-506, June.
    18. Sun, Yiguo & Malikov, Emir, 2018. "Estimation and inference in functional-coefficient spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 203(2), pages 359-378.
    19. Jing Zhou & Yundong Tu & Yuxin Chen & Hansheng Wang, 2017. "Estimating Spatial Autocorrelation With Sampled Network Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 130-138, January.
    20. Zhu, Xuening & Chang, Xiangyu & Li, Runze & Wang, Hansheng, 2019. "Portal nodes screening for large scale social networks," Journal of Econometrics, Elsevier, vol. 209(2), pages 145-157.
    21. Bissantz, Nicolai & Dümbgen, Lutz & Holzmann, Hajo & Munk, Axel, 2007. "Nonparametric confidence bands in deconvolution density estimation," Technical Reports 2007,03, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    22. Lung-Fei Lee, 2004. "Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models," Econometrica, Econometric Society, vol. 72(6), pages 1899-1925, November.
    23. Atsushi Iimi & Liangzhi You & Ulrike Wood-Sichra, 2020. "Spatial Autocorrelation Panel Regression: Agricultural Production and Transport Connectivity," Networks and Spatial Economics, Springer, vol. 20(2), pages 529-547, June.
    24. Ma, Yingying & Lan, Wei & Zhou, Fanying & Wang, Hansheng, 2020. "Approximate least squares estimation for spatial autoregressive models with covariates," Computational Statistics & Data Analysis, Elsevier, vol. 143(C).
    25. 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.
    26. Xuan Yu & Manhong Shen & Weiteng Shen & Xiao Zhang, 2020. "Effects of Land Urbanization on Smog Pollution in China: Estimation of Spatial Autoregressive Panel Data Models," Land, MDPI, vol. 9(9), pages 1-16, September.
    27. Li, Kunpeng, 2017. "Fixed-effects dynamic spatial panel data models and impulse response analysis," Journal of Econometrics, Elsevier, vol. 198(1), pages 102-121.
    28. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    29. Paul Evans & Ji Uk Kim, 2016. "Convergence analysis as spatial dynamic panel regression and distribution dynamics of $$\hbox {CO}_{2}$$ CO 2 emissions in Asian countries," Empirical Economics, Springer, vol. 50(3), pages 729-751, May.
    30. 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.
    31. Beenstock, Michael & Felsenstein, Daniel, 2015. "Estimating spatial spillover in housing construction with nonstationary panel data," Journal of Housing Economics, Elsevier, vol. 28(C), pages 42-58.
    32. Yang, Kai & Lee, Lung-fei, 2017. "Identification and QML estimation of multivariate and simultaneous equations spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 196(1), pages 196-214.
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