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Testing Spatial Autocorrelation in Weighted Networks: The Modes Permutation Test

In: Spatial Econometric Interaction Modelling

Author

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  • François Bavaud

    (University of Lausanne)

Abstract

Permutation tests of spatial autocorrelation are justified under exchangeability, that is the premise that the observed scores follow a permutation-invariant joint distribution. Yet, in the frequently encountered case of geographical data collected on regions differing in importance, the variance of a regional score is expected to decrease with the size of the region, in the same way that the variance of an average is inversely proportional to the size of the sample in elementary statistics: heteroscedasticity holds in effect, already under spatial independence, thus weakening the rationale of the celebrated spatial autocorrelation permutation test (e.g. Cliff and Ord 1973; Besag and Diggle 1977) in the case of a weighted network.

Suggested Citation

  • François Bavaud, 2016. "Testing Spatial Autocorrelation in Weighted Networks: The Modes Permutation Test," Advances in Spatial Science, in: Roberto Patuelli & Giuseppe Arbia (ed.), Spatial Econometric Interaction Modelling, chapter 0, pages 67-83, Springer.
    • Handle: RePEc:spr:adspcp:978-3-319-30196-9_4
    DOI: 10.1007/978-3-319-30196-9_4
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    Citations

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    Cited by:

    1. Burris, Courtney & Nikolaev, Alexander & Zhong, Shiran & Bian, Ling, 2021. "Network effects in influenza spread: The impact of mobility and socio-economic factors," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    2. Arbia, Giuseppe & Bramante, Riccardo & Facchinetti, Silvia & Zappa, Diego, 2018. "Modeling inter-country spatial financial interactions with Graphical Lasso: An application to sovereign co-risk evaluation," Regional Science and Urban Economics, Elsevier, vol. 70(C), pages 72-79.

    More about this item

    Keywords

    Bootstrap; Local variance; Markov and semi-Markov processes; Moran’s I; Permutation test; Spatial autocorrelation; Spatial filtering; Weighted networks;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • 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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