Multidimensional Well-Being: A Bayesian Networks Approach

被引:0
|
作者
Lidia Ceriani
Chiara Gigliarano
机构
[1] Georgetown University,School of Foreign Service
[2] Università degli Studi dell’Insubria,Department of Economics
来源
Social Indicators Research | 2020年 / 152卷
关键词
Multivariate analysis; Directed acyclic graphs; Probabilistic inference; Well-being;
D O I
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中图分类号
学科分类号
摘要
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.
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页码:237 / 263
页数:26
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