Abstract

The official Italian well-being measuring system (“Equitable and Sustainable Well-being—BES”) is probably the worldwide most advanced attempt to pursue the beyond GDP perspective effectively. In it, well-being is described in terms of 12 domains and a complex multi-indicator system of around 130 indicators, drawn mainly from Istat (official Italian statistical bureau) surveys and administrative archives. In order to get a more synthetic view of well-being, in the last four BES reports Istat employed aggregative procedures providing composite indicators for each well-being domain. The aggregative road to synthesis is however problematic, when complex and non-highly correlated indicator systems are to be summarized, mainly due to its compensative nature and interpretational difficulties. As a valuable alternative, in this paper we adopt a non-aggregative approach to synthesis, based on Partially Ordered Set Theory (Poset Theory) and show how it can be used to provide more “complexity-preserving”insights into well-being. In particular, we describe each well-being domain as a partially ordered set and compute synthetic indicators for well-being rankings at regional level for year 2017, getting more robust and interpretable results than with mainstream aggregative procedures.

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