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Effect of sub-indicator weighting schemes on the spatial dependence of multidimensional phenomena

Author

Listed:
  • Matheus Pereira Libório

    (Pontifical Catholic University of Minas Gerais)

  • João Francisco Abreu

    (Pontifical Catholic University of Minas Gerais)

  • Petr Iakovlevitch Ekel

    (Pontifical Catholic University of Minas Gerais
    Federal University of Minas Gerais)

  • Alexei Manso Correa Machado

    (Pontifical Catholic University of Minas Gerais
    Federal University of Minas Gerais)

Abstract

The weighting of sub-indicators is widely debated in the composite indicator literature. However, these weighting schemes’ effects on the composite indicator’s spatial dependence property are still little known. This research reveals a direct relationship between the weighting scheme of sub-indicators and the spatial autocorrelation of the composite indicator. The Global Moran's Index (I) of composite indicators built using Data-driven (Moran’s I = 0.636) and Hybrid (Moran’s I = 0.597) weighting schemes is, on average, eleven percent higher than in the Equal-weights (Moran's I = 0.549) and Expert opinion (Moran's I = 0.560) weighting schemes. The average score of the composite indicator is higher when they are built by weighting schemes that better describe the spatial dependence. The spatial dependence of sub-indicators and composite indicators are not related. All fifteen sub-indicators show lower spatial autocorrelation than the composite indicators built by Expert opinion, Hybrid, and Data-driven weighting schemes. The spatial weighting matrix influences the spatial autocorrelation but does not change the robustness and quality parameters of the composite indicator. The research develops a Data-driven weighting scheme that allows individually or simultaneously considering the opinion of experts and parameters of quality and robustness of the composite indicator. It also offers the means to reduce judgment errors and evaluation biases in Expert opinion sub-indicator weighting schemes.

Suggested Citation

  • Matheus Pereira Libório & João Francisco Abreu & Petr Iakovlevitch Ekel & Alexei Manso Correa Machado, 2023. "Effect of sub-indicator weighting schemes on the spatial dependence of multidimensional phenomena," Journal of Geographical Systems, Springer, vol. 25(2), pages 185-211, April.
    • Handle: RePEc:kap:jgeosy:v:25:y:2023:i:2:d:10.1007_s10109-022-00401-w
    DOI: 10.1007/s10109-022-00401-w
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    More about this item

    Keywords

    Composite indicators; Spatial dependence; Sub-indicators weighting; Moran's Index;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • D6 - Microeconomics - - Welfare Economics
    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty

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