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A Quantile Composite-Indicator Approach for the Measurement of Equitable and Sustainable Well-Being: A Case Study of the Italian Provinces

Author

Listed:
  • Cristina Davino

    (University of Macerata)

  • Pasquale Dolce

    (University of Naples Federico II)

  • Stefania Taralli

    (Istat, Italian National Institute of Statistics)

  • Vincenzo Esposito Vinzi

    (ESSEC Business School)

Abstract

An interesting measure for equitable and sustainable well-being has been proposed recently by the National Institute of Statistics in Italy and the National Council for Economy and Labour. It is called BES (from the Italian Benessere Equo e Sostenibile). A set of indicators, partitioned into several domains and themes, is used for measuring the BES. Taking into account prior knowledge of both the structure of this set of indicators and the relationships among them, the paper proposes a hierarchical composite model for measuring and modeling the BES of the Italian provinces. This hierarchical model allows us to synthesize individual indicators into single indexes in order to construct composite indicators at a global and a partial level. Moreover, we analyze the relationships among the different domains and themes as well as the effects of these on equitable and sustainable well-being, in order to search for strongly influential factors. In order to estimate the parameters of the model, we use both Partial Least Squares path modeling and a new method, called Quantile Composite-based path modeling. In particular, Partial Least Squares path modeling is used to estimate average effects in the network of relationships between variables, while with Quantile Composite-based path modeling we investigate whether the magnitude of these effects changes across different parts of the variable distributions, providing a more complete picture and uncovering specific local leveraging factors for improvement. A final ranking of the Italian provinces, according to the BES composite indicator, is also provided at the national level and for different geographic areas of Italy.

Suggested Citation

  • Cristina Davino & Pasquale Dolce & Stefania Taralli & Vincenzo Esposito Vinzi, 2018. "A Quantile Composite-Indicator Approach for the Measurement of Equitable and Sustainable Well-Being: A Case Study of the Italian Provinces," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(3), pages 999-1029, April.
    • Handle: RePEc:spr:soinre:v:136:y:2018:i:3:d:10.1007_s11205-016-1453-8
    DOI: 10.1007/s11205-016-1453-8
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    References listed on IDEAS

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    1. Francesco M. Chelli & Mariateresa Ciommi & Alessandra Emili & Chiara Gigliarano & Stefania Taralli, 2015. "Comparing Equitable And Sustainable Well-Being (Bes) Across The Italian Provinces. A Factor Analysis-Based Approach," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 69(3), pages 61-72, July-Sept.
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    6. Cristina Davino & Vincenzo Esposito Vinzi, 2016. "Quantile composite-based path modeling," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(4), pages 491-520, December.
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    8. Stefania Taralli & Chiara Capogrossi & Giampietro Perri, 2015. "Measuring Equitable and Sustainable Well-Being (BES) for Policy-making at Local Level (Nuts3)," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 69(3), pages 95-106, July-Sept.
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    1. Pasquale Dolce & Cristina Davino & Domenico Vistocco, 2022. "Quantile composite-based path modeling: algorithms, properties and applications," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(4), pages 909-949, December.
    2. Cantone, Giulio Giacomo & Tomaselli, Venera, 2024. "On the Coherence of Composite Indexes: Multiversal Model and Specification Analysis for an Index of Well-Being," MetaArXiv d5y26, Center for Open Science.
    3. Rajko Tomaš, 2022. "Measurement of the Concentration of Potential Quality of Life in Local Communities," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 163(1), pages 79-109, August.
    4. Immacolata Di Napoli & Pasquale Dolce & Caterina Arcidiacono, 2019. "Community Trust: A Social Indicator Related to Community Engagement," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 145(2), pages 551-579, September.
    5. Venera Tomaselli & Mario Fordellone & Maurizio Vichi, 2021. "Building Well-Being Composite Indicator for Micro-Territorial Areas Through PLS-SEM and K-Means Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(2), pages 407-429, January.
    6. Idiano D’Adamo & Cristina Di Carlo & Massimo Gastaldi & Edouard Nicolas Rossi & Antonio Felice Uricchio, 2024. "Economic Performance, Environmental Protection and Social Progress: A Cluster Analysis Comparison towards Sustainable Development," Sustainability, MDPI, vol. 16(12), pages 1-24, June.
    7. Matheus Pereira Libório & Oseias da Silva Martinuci & Sandro Laudares & Renata de Mello Lyrio & Alexei Manso Correa Machado & Patrícia Bernardes & Petr Ekel, 2020. "Measuring Intra-Urban Inequality with Structural Equation Modeling: A Theory-Grounded Indicator," Sustainability, MDPI, vol. 12(20), pages 1-18, October.
    8. Cristina Davino & Pasquale Dolce & Stefania Taralli & Domenico Vistocco, 2022. "Composite-Based Path Modeling for Conditional Quantiles Prediction. An Application to Assess Health Differences at Local Level in a Well-Being Perspective," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(2), pages 907-936, June.
    9. Hao Cheng, 2023. "Composite quantile estimation in PLS-SEM for environment sustainable development evaluation," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6249-6268, July.
    10. Hao Cheng, 2023. "Environmental Effect Evaluation: A Quantile-Type Path-Modeling Approach," Sustainability, MDPI, vol. 15(5), pages 1-21, March.
    11. Hao Cheng, 2024. "Inverse Probability-Weighted Estimation for Dynamic Structural Equation Model with Missing Data," Mathematics, MDPI, vol. 12(19), pages 1-20, September.
    12. Rosanna Cataldo & Corrado Crocetta & Maria Gabriella Grassia & Natale Carlo Lauro & Marina Marino & Viktoriya Voytsekhovska, 2021. "Methodological PLS-PM Framework for SDGs System," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 701-723, August.
    13. Ilyes Boumahdi & Nouzha Zaoujal, 2023. "Regional Well-Being Disparities in Morocco and its OECD Partners," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 167(1), pages 183-211, June.
    14. Pierpaolo D’Urso & Vincenzina Vitale, 2021. "Modeling Local BES Indicators by Copula-Based Bayesian Networks," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(3), pages 823-847, February.

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