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Moran's I test of spatial panel data model — Based on bootstrap method

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  • Ren, Tongxian
  • Long, Zhihe
  • Zhang, Rengui
  • Chen, Qingqing

Abstract

Under the condition of the finite sample or the unknown distributed error term, testing for spatial dependence in panel data models is an unresolved problem in spatial econometrics. In this paper, a fast double bootstrap (FDB) method is used to construct bootstrap Moran's I tests for Moran's I test in spatial panel data models, and Monte Carlo simulation experiments are used to prove the effectiveness from two aspects including size distortion and power. The experiment results show that, in asymptotic Moran's I test, there is serious size distortion, which could be rectified in bootstrap Moran's I test.

Suggested Citation

  • Ren, Tongxian & Long, Zhihe & Zhang, Rengui & Chen, Qingqing, 2014. "Moran's I test of spatial panel data model — Based on bootstrap method," Economic Modelling, Elsevier, vol. 41(C), pages 9-14.
    • Handle: RePEc:eee:ecmode:v:41:y:2014:i:c:p:9-14
    DOI: 10.1016/j.econmod.2014.04.022
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    References listed on IDEAS

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    Cited by:

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    2. Christoph Strumann, 2019. "Hodges–Lehmann Estimation of Static Panel Models with Spatially Correlated Disturbances," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 141-168, January.
    3. Marco Baudino, 2020. "Environmental Engel curves in Italy: A spatial econometric investigation," Papers in Regional Science, Wiley Blackwell, vol. 99(4), pages 999-1018, August.

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