Modeling Local BES Indicators by Copula-Based Bayesian Networks

Pierpaolo D’Urso () and Vincenzina Vitale ()
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Pierpaolo D’Urso: Sapienza Università di Roma
Vincenzina Vitale: Sapienza Università di Roma

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2021, vol. 153, issue 3, No 3, 823-847

Abstract: 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.

Keywords: Non-Parametric Bayesian Networks; Normal copula; Equitable and Sustainable Well-being; Model selection (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11205-020-02530-5

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