Statistical indicators for the analysis of social inequalities in Italy

Abstract

The analysis of social inequalities is a topic of growing academic and policy interest, recognized as a key dimension in assessing individual and collective well-being. A fundamental prerequisite for any rigorous statistical assessment of inequality is the adoption of a shared, multidimensional definition that captures the complex nature of social disadvantage. This study addresses the need to identify small-area territorial units or population subgroups affected by hardship or severe exclusion. A fuzzy logic approach (Totally Fuzzy and Relative) and a spatial clustering algorithm (DBSCAN) are adopted to construct and interpret indicators of social disadvantage. The analysis draws on 2024 data from the “Equitable and Sustainable Well-being” (BES) framework published by ISTAT, focusing on three domains: socio-demography, employment, and personal safety at the provincial level. This integrated methodology enables the detection of both the intensity and spatial configuration of disadvantage across Italian territories. It provides a robust foundation for evidence-based and place-sensitive policy interventions.