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Measurement of well-being has been a highly debated topic since the end ofthe last century. While some specific aspects are still open issues, amultidimensional approach as well as the construction of shared and well-rootedsystems of indicators are now accepted as the main route to measure thiscomplex phenomenon. A meaningful effort, in this direction, is that of theItalian "Equitable and Sustainable Well-being" (BES) system of indicators,developed by the Italian National Institute of Statistics (ISTAT) and theNational Council for Economics and Labour (CNEL). The BES framework comprises anumber of atomic indicators measured yearly at the regional level andreflecting the different domains of well-being (e.g. Health, Education, Work \&Life Balance, Environment,...). In this work we aim at dealing with themultidimensionality of the BES system of indicators and try to answer threemain research questions: I) What is the structure of the relationships amongthe BES atomic indicators; II) What is the structure of the relationships amongthe BES domains; III) To what extent the structure of the relationshipsreflects the current BES theoretical framework. We address these questions byimplementing Bayesian Networks (BNs), a widely accepted class of multivariatestatistical models, particularly suitable for handling reasoning withuncertainty. Implementation of a BN results in a set of nodes and a set ofconditional independence statements that provide an effective tool to exploreassociations in a system of variables. In this work, we also suggest twostrategies for encoding prior knowledge in the BN estimating algorithm so thatthe BES theoretical framework can be represented into the network.

Modeling "Equitable and Sustainable Well-being" (BES) using Bayesian Networks: A Case Study of the Italian regions