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Instrumental variable estimation of a spatial dynamic panel model with endogenous spatial weights when T is small

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  • Xi Qu
  • Xiaoliang Wang
  • Lung‐fei Lee

Abstract

The spatial dynamic panel data (SDPD) model is a standard tool for analysing data with both spatial correlation and dynamic dependences among economic units. Conventional estimation methods rely on the key assumption that the spatial weight matrix is exogenous, which would likely be violated in some empirical applications where spatial weights are determined by economic factors. In this paper, we propose an SDPD model with individual fixed effects in a short time dimension, where the spatial weights can be endogenous and time‐varying. We establish the consistency and asymptotic normality of the two‐stage instrumental variable (2SIV) estimator and we investigate its finite sample properties using a Monte Carlo simulation. When applying this model to study government expenditures in China, we find strong evidence of spatial correlation and time dependence in making spending decisions among China's provincial governments.

Suggested Citation

  • Xi Qu & Xiaoliang Wang & Lung‐fei Lee, 2016. "Instrumental variable estimation of a spatial dynamic panel model with endogenous spatial weights when T is small," Econometrics Journal, Royal Economic Society, vol. 19(3), pages 261-290, October.
    • Handle: RePEc:wly:emjrnl:v:19:y:2016:i:3:p:261-290
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    File URL: http://hdl.handle.net/10.1111/ectj.12069
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    Cited by:

    1. Qu, Xi & Lee, Lung-fei & Yang, Chao, 2021. "Estimation of a SAR model with endogenous spatial weights constructed by bilateral variables," Journal of Econometrics, Elsevier, vol. 221(1), pages 180-197.
    2. Sophie Béreau & Nicolas Debarsy & Cyrille Dossougoin & Jean-Yves Gnabo, 2022. "Contagion in the Banking Industry: a Robust-to-Endogeneity Analysis," Working Papers halshs-03513049, HAL.
    3. Sebastian Langer, 2019. "Expenditure interactions between municipalities and the role of agglomeration forces: a spatial analysis for North Rhine-Westphalia," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 62(3), pages 497-527, June.
    4. Li, Liyao & Yang, Zhenlin, 2021. "Spatial dynamic panel data models with correlated random effects," Journal of Econometrics, Elsevier, vol. 221(2), pages 424-454.
    5. Bera, Anil K. & Doğan, Osman & Taşpınar, Süleyman, 2018. "Simple tests for endogeneity of spatial weights matrices," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 130-142.
    6. Bera Anil K. & Doğan Osman & Taşpınar Süleyman, 2019. "Testing Spatial Dependence in Spatial Models with Endogenous Weights Matrices," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-33, January.
    7. Lee, Jiyon, 2018. "A spatial latent class model," Economics Letters, Elsevier, vol. 162(C), pages 62-68.
    8. Massimiliano Cerciello, 2021. "Spatial patterns in food waste at the local level. A preliminary analysis for Italian data," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 83-101, February.
    9. T. M. Tonmoy Islam, 2020. "The impact of population agglomeration of an area on its neighbors: evidence from the USA," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 65(1), pages 1-26, August.
    10. Huijuan Xiao & Sheng Bao & Jingzheng Ren & Zhenci Xu & Song Xue & Jianguo Liu, 2024. "Global transboundary synergies and trade-offs among Sustainable Development Goals from an integrated sustainability perspective," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    11. Chen, Xin & Xuan, Chao & Qiu, Rui, 2021. "Understanding spatial spillover effects of airports on economic development: New evidence from China’s hub airports," Transportation Research Part A: Policy and Practice, Elsevier, vol. 143(C), pages 48-60.
    12. Ioannis Skevas, 2023. "A novel modeling framework for quantifying spatial spillovers on total factor productivity growth and its components," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(4), pages 1221-1247, August.

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