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Subjective–Objective Method of Maximizing the Average Variance Extracted From Sub-indicators in Composite Indicators

Author

Listed:
  • Matheus Pereira Libório

    (Pontifical Catholic University of Minas Gerais)

  • Alexandre Magno Alvez Diniz

    (Pontifical Catholic University of Minas Gerais)

  • Douglas Alexandre Gomes Vieira

    (Federal Technological Education Centre of Minas Gerais)

  • Petr Iakovlevitch Ekel

    (Pontifical Catholic University of Minas Gerais)

Abstract

This research presents an innovative method for constructing composite indicators: the Subjective–objective method of maximizing extracted variance (Sommev). Sommev’s hybrid weighting approach fills an important gap within a highly controversial area of the composite indicators’ literature, which criticizes the statistical assignment of weights disconnected from theory and the errors and judgmental biases inherent in the expert opinion-based weighting approach. These innovations contribute to a more coherent and consistent operationalization of the theoretical framework of multidimensional phenomena, reconciling the non-compensability between sub-indicators and the maximum retention of original information through statistically defined weights, in which the expert’s opinion is considered, but does not determine the sub-indicator’s weights. Twenty simulations were carried out to analyze the application of the method in representing social exclusion in a Brazilian city. Composite indicators constructed by Sommev retain twice as much information as those constructed with equal weights or weights defined by experts. This increased informational capacity favors a more comprehensive representation of the multidimensional phenomenon, having a high potential for application in solving problems of a multidimensional nature in the social, economic, and environmental areas.

Suggested Citation

  • Matheus Pereira Libório & Alexandre Magno Alvez Diniz & Douglas Alexandre Gomes Vieira & Petr Iakovlevitch Ekel, 2024. "Subjective–Objective Method of Maximizing the Average Variance Extracted From Sub-indicators in Composite Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 175(2), pages 613-637, November.
    • Handle: RePEc:spr:soinre:v:175:y:2024:i:2:d:10.1007_s11205-024-03385-w
    DOI: 10.1007/s11205-024-03385-w
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