The BES–GDP Nexus: A Panel Econometric and Machine Learning Analysis of Italian Regions

The study investigates the interrelationship between the performance of the regional economy in Italy and the multidimensionality of wellbeing, as defined by the ISTAT Benessere Equo e Sostenibile (BES) model. Based on panel data from 19 Italian regions and 2 autonomous provinces—Trentino and Bolzano (2012–2023)—the research aims to explore whether there is a link between regional GDP and the three BES dimensions: Benessere (B), Equità (E), and Sostenibilità (S). The innovative contribution of this paper is not the creation of a novel theoretical model, but a multilayered empirical approach that combines panel data methods, machine learning, and clustering. This approach makes it possible to reveal nonlinearities, complex interactions, and regional heterogeneity in BES–GDP relationships. The analysis of the Benessere dimension based on k-Nearest Neighbors reveals nonlinear dynamics related to health, mobility, security, digital access, and socio-economic conditions. Furthermore, cluster analysis identifies territorial development regimes according to the Benessere dimension. The Equità dimension is estimated using boosting regression and clustering models that emphasize the role of income, poverty risk, healthcare pressure, labour-market participation, youth exclusion, deprivation, and access to essential services. Finally, the Sostenibilità dimension is explored using boosting regression and random forest models to estimate interactions among environmental quality, climate stress, energy transition, innovation, digital skills, service reliability, and regional economic performance. The findings demonstrate a structural connection between well-being, equity, sustainability, and the economic performance of Italian regions. The results also confirm the hypothesis that Italy has multiple development regimes that differ geographically.