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Power of Moran’s I Test for Spatial Dependence in Panel Data Models with Time Varying Spatial Weights Matrices

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  • Ou Bianling

    (School of Management Science and Engineering, Central University of Finance and Economics, Beijing102206, China)

  • Zhao Xin

    (School of Management Science and Engineering, Central University of Finance and Economics, Beijing100081, China)

  • Wang Mingxi

    (School of International Trade and Economics, University of International Business and Economics, Beijing100029, China)

Abstract

The spatial weights matrix is usually specified to be time invariant. However, when it are constructed with economic/socioeconomic distance, trade /demographic/climatic characteristics, these characteristics might be changing over time, and then the spatial weights matrix substantially varies over time. This paper focuses on power of Moran’s I test for spatial dependence in panel data models with where spatial weights matrices can be time varying (TV-Moran). Compared with Moran’s I test with time invariant spatial weights matrices (TI-Moran), the empirical power of TV-Moran test for spatial dependence are evaluated. Our extensive Monte Carlo simulation results indicate that Moran’s I test with misspecified time invariant spatial weights matrices is questionable; Instead, TV-Moran test has shown superiority in higher power, especially for cases with negative spatial correlation parameters and the large time dimension.

Suggested Citation

  • Ou Bianling & Zhao Xin & Wang Mingxi, 2015. "Power of Moran’s I Test for Spatial Dependence in Panel Data Models with Time Varying Spatial Weights Matrices," Journal of Systems Science and Information, De Gruyter, vol. 3(5), pages 463-471, October.
    • Handle: RePEc:bpj:jossai:v:3:y:2015:i:5:p:463-471:n:7
    DOI: 10.1515/JSSI-2015-0463
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    References listed on IDEAS

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