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 dierent dimension of well-being. Moreover, Bayesian Networks are useful to understand the eectiveness of policies directed to one or more dimensions, as well as to design more eective interventions to improve well-being. The new approach is illustrated with an empirical application for a selection of Western and Eastern European countries.

Multidimensional Well-Being: A Bayesian Networks Approach

Chiara Gigliarano
Secondo
2020-01-01

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 dierent dimension of well-being. Moreover, Bayesian Networks are useful to understand the eectiveness of policies directed to one or more dimensions, as well as to design more eective interventions to improve well-being. The new approach is illustrated with an empirical application for a selection of Western and Eastern European countries.
2020
Ceriani, Lidia; Gigliarano, Chiara
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2099337
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