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Tests for time-varying coefficient spatial autoregressive panel data model with fixed effects

Author

Listed:
  • Lingling Tian

    (Beijing University of Technology)

  • Yunan Su

    (Minzu University of China)

  • Chuanhua Wei

    (Minzu University of China)

Abstract

As an extension of the spatial autoregressive panel data model and the time-varying coefficient panel data model, the time-varying coefficient spatial autoregressive panel data model is useful in analysis of spatial panel data. While research has addressed the estimation problem of this model, less attention has been given to hypotheses tests. This paper studies two tests for this semiparametric spatial panel data model. One considers the existence of the spatial lag term, and the other determines whether some time-varying coefficients are constants. We employ the profile generalized likelihood ratio test procedure to construct the corresponding test statistic, and the residual-based bootstrap procedure is used to derive the p-value of the tests. Some simulations are conducted to evaluate the performance of the proposed test method, the results show that the proposed methods have good finite sample properties. Finally, we apply the proposed test methods to the provincial carbon emission data of China. Our findings suggest that the partially linear time-varying coefficients spatial autoregressive panel data model provides a better fit for the carbon emission data.

Suggested Citation

  • Lingling Tian & Yunan Su & Chuanhua Wei, 2024. "Tests for time-varying coefficient spatial autoregressive panel data model with fixed effects," Statistical Papers, Springer, vol. 65(9), pages 5481-5501, December.
    • Handle: RePEc:spr:stpapr:v:65:y:2024:i:9:d:10.1007_s00362-024-01607-4
    DOI: 10.1007/s00362-024-01607-4
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    References listed on IDEAS

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    1. Chunrong Ai & Yuanqing Zhang, 2017. "Estimation of partially specified spatial panel data models with fixed-effects," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 6-22, March.
    2. Xuan Liang & Jiti Gao & Xiaodong Gong, 2022. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1784-1802, October.
    3. Ruiqin Tian & Miaojie Xia & Dengke Xu, 2024. "Profile quasi-maximum likelihood estimation for semiparametric varying-coefficient spatial autoregressive panel models with fixed effects," Statistical Papers, Springer, vol. 65(8), pages 5109-5143, October.
    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. Baltagi, Badi H. & Song, Seuck Heun & Koh, Won, 2003. "Testing panel data regression models with spatial error correlation," Journal of Econometrics, Elsevier, vol. 117(1), pages 123-150, November.
    6. Baltagi, Badi H. & Liu, Long, 2008. "Testing for random effects and spatial lag dependence in panel data models," Statistics & Probability Letters, Elsevier, vol. 78(18), pages 3304-3306, December.
    7. Wei, Chuanhua & Guo, Shuang & Zhai, Shufen, 2017. "Statistical inference of partially linear varying coefficient spatial autoregressive models," Economic Modelling, Elsevier, vol. 64(C), pages 553-559.
    8. Li, Deng-Kui & Mei, Chang-Lin & Wang, Ning, 2019. "Tests for spatial dependence and heterogeneity in spatially autoregressive varying coefficient models with application to Boston house price analysis," Regional Science and Urban Economics, Elsevier, vol. 79(C).
    9. J. Paul Elhorst, 2003. "Specification and Estimation of Spatial Panel Data Models," International Regional Science Review, , vol. 26(3), pages 244-268, July.
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