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Testing for Spatial Correlation under a Complete Bipartite Network

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Abstract

This note shows that for a spatial regression with a weight matrix depicting a complete bipartite network, the Moran I test for zero spatial correlation is never rejected when the alternative is positive spatial correlation no matter how large the true value of the spatial correlation coefficient. In contrast, the null hypothesis of zero spatial correlation is always rejected (with probability one asymptotically) when the alternative is negative spatial correlation and the true value of the spatial correlation coefficient is near -1.

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  • Badi H. Baltagi & Long Liu, 2024. "Testing for Spatial Correlation under a Complete Bipartite Network," Center for Policy Research Working Papers 264, Center for Policy Research, Maxwell School, Syracuse University.
    • Handle: RePEc:max:cprwps:264
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    File URL: https://surface.syr.edu/cpr/489/
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    1. Martellosio, Federico, 2010. "Power Properties Of Invariant Tests For Spatial Autocorrelation In Linear Regression," Econometric Theory, Cambridge University Press, vol. 26(1), pages 152-186, February.
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    More about this item

    Keywords

    Spatial Error Model; Moran I Test; Complete Bipartite Network.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • 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

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