Multidimensional Well-Being: A Bayesian Networks Approach

Lidia Ceriani () and Chiara Gigliarano ()
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Chiara Gigliarano: Università degli Studi dell’Insubria

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2020, vol. 152, issue 1, No 9, 237-263

Abstract: Abstract The study of multidimensional well-being has long recognized the importance of formalizing the interaction between dimensions, but came short of treating this formally. In this paper, we show that the statistical technique of Bayesian Networks is an intuitive and powerful instrument that allows to model the dependence structure among the different dimension of well-being. Moreover, Bayesian Networks are useful to understand the effectiveness of policies directed to one or more dimensions, as well as to design more effective interventions to improve well-being. The new approach is illustrated with an empirical application for a selection of Western and Eastern European countries.

Keywords: Multivariate analysis; Directed acyclic graphs; Probabilistic inference; Well-being (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (5)

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Working Paper: Multidimensional well-being: A Bayesian Networks approach (2016)
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DOI: 10.1007/s11205-020-02432-6

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