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Composite Indices Construction: The Performance Interval Approach

Author

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  • Matteo Mazziotta

    (Italian National Institute of Statistics)

  • Adriano Pareto

    (Italian National Institute of Statistics)

Abstract

In the last years, there has been a growing interest in composite indices, whether they be social, socio-economic or environmental indices. In this paper, we propose a new approach to the composite indices construction which consists in computing an interval of possible values, for each statistical unit, rather than a single value. The interval is called ‘performance interval’ and it is constructed depending on the level of compensability of individual indicators. As an example of application, we considered a set of indicators of well-being in Italy and we constructed the performance intervals for the Italian Regions. Finally, we compared the midpoint of the performance intervals with the geometric mean, a classic partially compensatory aggregation function.

Suggested Citation

  • Matteo Mazziotta & Adriano Pareto, 2022. "Composite Indices Construction: The Performance Interval Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(2), pages 541-551, June.
  • Handle: RePEc:spr:soinre:v:161:y:2022:i:2:d:10.1007_s11205-020-02336-5
    DOI: 10.1007/s11205-020-02336-5
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    References listed on IDEAS

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    1. P. Zhou & B. Ang & D. Zhou, 2010. "Weighting and Aggregation in Composite Indicator Construction: a Multiplicative Optimization Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 96(1), pages 169-181, March.
    2. Matteo Mazziotta & Adriano Pareto, 2019. "Use and Misuse of PCA for Measuring Well-Being," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(2), pages 451-476, April.
    3. Enrico Casadio Tarabusi & Giulio Guarini, 2013. "An Unbalance Adjustment Method for Development Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 112(1), pages 19-45, May.
    4. Leonardo S. Alaimo & Filomena Maggino, 2020. "Sustainable Development Goals Indicators at Territorial Level: Conceptual and Methodological Issues—The Italian Perspective," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(2), pages 383-419, January.
    5. Salvatore Greco & Alessio Ishizaka & Menelaos Tasiou & Gianpiero Torrisi, 2019. "On the Methodological Framework of Composite Indices: A Review of the Issues of Weighting, Aggregation, and Robustness," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(1), pages 61-94, January.
    6. M. Saisana & A. Saltelli & S. Tarantola, 2005. "Uncertainty and sensitivity analysis techniques as tools for the quality assessment of composite indicators," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 307-323, March.
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    2. Daniela Madrazo-Ortega & Maria Molinos-Senante, 2023. "Quantifying Progress Made in Achieving Sustainable Development Goal 6 in Chile: A Holistic and Local Approach," Sustainability, MDPI, vol. 15(5), pages 1-18, February.

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