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Modeling Local BES Indicators by Copula-Based Bayesian Networks

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  • Pierpaolo D’Urso

    (Sapienza Università di Roma)

  • Vincenzina Vitale

    (Sapienza Università di Roma)

Abstract

In Italy, the measure of the Equitable and Sustainable Well-being is provided by the Italian Institute of Statistics by means of a dashboard of basic and composite indicators. To investigate the dependence structure between the different domains of well-being, we propose the use of Non-Parametric Bayesian Networks based on the normal copula distribution, that allow to explore the conditional independence relationships between the composite indicators. The main advantage of the non-parametric models is that, as opposed to the parametric approach, they do not require any assumption on the marginal distributions of the variables. The proposed model is applied to the Equitable and Sustainable Well-being indicators measured at the provincial level and enriches the analysis of well-being by inspecting similarities and differences between Italian urban areas and territories.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:soinre:v:153:y:2021:i:3:d:10.1007_s11205-020-02530-5
    DOI: 10.1007/s11205-020-02530-5
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    1. Hanea, A.M. & Kurowicka, D. & Cooke, R.M. & Ababei, D.A., 2010. "Mining and visualising ordinal data with non-parametric continuous BBNs," Computational Statistics & Data Analysis, Elsevier, vol. 54(3), pages 668-687, March.
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    6. Francesco M. Chelli & Mariateresa Ciommi & Alessandra Emili & Chiara Gigliarano & Stefania Taralli, 2016. "Measuring Local Well-Being: A Comparison Among Aggregative Methods For The Equitable And Sustainable Well-Being," 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. 70(4), pages 91-102, October-D.
    7. Pierpaolo D’Urso & Vincenzina Vitale, 2020. "Bayesian Networks Model Averaging for Bes Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 151(3), pages 897-919, October.
    8. 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.
    9. 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.
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    Cited by:

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    2. Rossi, Luca & Pasca, Maria Giovina & Arcese, Gabriella & Poponi, Stefano, 2024. "Innovation, researcher and creativity: A complex indicator for territorial evaluation capacity," Technology in Society, Elsevier, vol. 77(C).

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