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Fixed-effects dynamic spatial panel data models and impulse response analysis

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  • Li, Kunpeng

Abstract

Real data often have complicated correlations over cross section and time. Such correlations are of particular interests in empirical studies. This paper considers using high order spatial lags and high order time lags to model complicated correlations over cross section and time. We propose to use the quasi maximum likelihood (QML) method to estimate the model. We establish the asymptotic theory of the quasi maximum likelihood estimator (QMLE), including the consistency and limiting distribution, under large N and large T setup, where N denotes the number of individuals and T the number of time periods. We investigate the problem of estimating impulse response functions and the associated (1−α)-confidence intervals. Average direct, indirect and total impacts are defined along the same spirits of LeSage and Pace (2009) under the dynamic spatial panel data setup. The estimation and inferential theory for the three impacts are studied. Model selection issue is also considered. Monte Carlo simulations confirm our theoretical results and show that the QMLE after bias correction has good finite sample performance.

Suggested Citation

  • Li, Kunpeng, 2017. "Fixed-effects dynamic spatial panel data models and impulse response analysis," Journal of Econometrics, Elsevier, vol. 198(1), pages 102-121.
    • Handle: RePEc:eee:econom:v:198:y:2017:i:1:p:102-121
    DOI: 10.1016/j.jeconom.2017.02.001
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    2. Anil K. Bera & Osman Doğan & Süleyman Taşpınar & Monalisa Sen, 2020. "Specification tests for spatial panel data models," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-39, December.
    3. Huang, Danyang & Hu, Wei & Jing, Bingyi & Zhang, Bo, 2023. "Grouped spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    4. Jakub Olejnik & Alicja Olejnik, 2017. "Improved asymptotic analysis of Gaussian QML estimators in spatial models," Lodz Economics Working Papers 9/2017, University of Lodz, Faculty of Economics and Sociology.
    5. 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.
    6. Jakub Olejnik & Alicja Olejnik, 2020. "QML estimation with non-summable weight matrices," Journal of Geographical Systems, Springer, vol. 22(4), pages 469-495, October.
    7. Bai, Jushan & Li, Kunpeng, 2021. "Dynamic spatial panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 224(1), pages 134-160.
    8. Gupta, Abhimanyu, 2023. "Efficient closed-form estimation of large spatial autoregressions," Journal of Econometrics, Elsevier, vol. 232(1), pages 148-167.
    9. 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.
    10. Li, Kunpeng, 2022. "Threshold spatial autoregressive model," MPRA Paper 113568, University Library of Munich, Germany.
    11. Shiwei Yu & Xing Hu & Xuejiao Zhang & Zhenxi Li, 2019. "Convergence of per capita carbon emissions in the Yangtze River Economic Belt, China," Energy & Environment, , vol. 30(5), pages 776-799, August.
    12. Xuan Liang & Jiti Gao & Xiaodong Gong, 2019. "Time-Varying Coefficient Spatial Autoregressive Panel Data Model with Fixed Effects," Monash Econometrics and Business Statistics Working Papers 26/19, Monash University, Department of Econometrics and Business Statistics.
    13. Li, Kunpeng, 2018. "Spatial panel data models with structural change," MPRA Paper 85388, University Library of Munich, Germany.
    14. Yang, Kai & Lee, Lung-fei, 2021. "Estimation of dynamic panel spatial vector autoregression: Stability and spatial multivariate cointegration," Journal of Econometrics, Elsevier, vol. 221(2), pages 337-367.
    15. Xueqian Song & Yongping Wei & Wei Deng & Shaoyao Zhang & Peng Zhou & Ying Liu & Jiangjun Wan, 2019. "Spatio-Temporal Distribution, Spillover Effects and Influences of China’s Two Levels of Public Healthcare Resources," IJERPH, MDPI, vol. 16(4), pages 1-18, February.

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    More about this item

    Keywords

    Dynamic spatial models; Panel data models; Quasi maximum likelihood estimation; Impulse response analysis; Confidence intervals; Model selection;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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