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On a Generalized Non-compensatory Composite Index for Measuring Socio-economic Phenomena

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  • Matteo Mazziotta

    (Italian National Institute of Statistics)

  • Adriano Pareto

    (Italian National Institute of Statistics)

Abstract

Composite indices for measuring multidimensional phenomena have become very popular in a variety of economic, social and policy domains. The literature offers a wide range of aggregation methods, all with their pros and cons. The most used are additive methods, but they imply requirements and properties which are often not desirable or difficult to meet. For example, they assume a full substitutability among the components of the index: a deficit in one dimension can be compensated by a surplus in another. In this paper, we consider a non-compensatory composite index for spatial comparisons and its variant for spatio-temporal comparisons. A study of the aggregation function is, for the first time, presented and its main properties are formally defined. As an example of application, a set of individual indicators of well-being for OECD countries is considered and a comparison between the two approaches is provided, in order to show what they offer and how they work.

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  • Matteo Mazziotta & Adriano Pareto, 2016. "On a Generalized Non-compensatory Composite Index for Measuring Socio-economic Phenomena," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 127(3), pages 983-1003, July.
    • Handle: RePEc:spr:soinre:v:127:y:2016:i:3:d:10.1007_s11205-015-0998-2
    DOI: 10.1007/s11205-015-0998-2
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    17. Gianni Onesti & Eleonora Monaco & Riccardo Palumbo, 2022. "Assessing the Italian Innovative Start-Ups Performance with a Composite Index," Administrative Sciences, MDPI, vol. 12(4), pages 1-18, December.
    18. Giorgio Calzolari & Maria Gabriella Campolo & Antonino Pino & Laura Magazzini, 2023. "Assessing individual skill influence on housework time of Italian women: an endogenous-switching approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(2), pages 659-679, June.
    19. Alessandro Crociata & Iacopo Odoardi & Massimiliano Agovino & Pier Luigi Sacco, 2020. "A missing link? Cultural capital as a source of human capital: evidence from Italian regional data," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(1), pages 79-109, February.
    20. Matheus Pereira Libório & Petr Iakovlevitch Ekel & Carlos Augusto Paiva Martins, 2023. "Economic analysis through alternative data and big data techniques: what do they tell about Brazil?," SN Business & Economics, Springer, vol. 3(1), pages 1-16, January.
    21. de Castro-Pardo, Mónica & Cabello, José Manuel & Martín, José María & Ruiz, Francisco, 2023. "A multi reference point based index to assess and monitor European water policies from a sustainability approach," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    22. Ferraro, Aniello & Cerciello, Massimiliano & Agovino, Massimiliano & Garofalo, Antonio, 2021. "Do public policies reduce social exclusion? The role of national and supranational economic tools," Structural Change and Economic Dynamics, Elsevier, vol. 57(C), pages 165-181.
    23. Francesco Maria Chelli & Barbara Ermini & Mauro Gallegati & Andrea Gentili, 2023. "Investigating Regional Disparities in Italy’s Well-Being Since Unification (1871–2011)," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(2), pages 697-722, July.
    24. Fusco, Elisa, 2023. "Potential improvements approach in composite indicators construction: The Multi-directional Benefit of the Doubt model," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).

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