Social Trust and Support Networks: A Regional Analysis of Italy

Massimo Arnone (), Angelo Leogrande, Carlo Drago and Alberto Costantiello ()
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Massimo Arnone: Unict - Università degli studi di Catania = University of Catania

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Abstract: This research explores how regional socioeconomic variables affect the perception of social trust and support networks (PYCC) in Italian regions, and examines the implications for public policy designed to strengthen social cohesion. This study examines the variable "People You Can Count On" (PYCC) from the ISTAT-BES dataset, focusing on its distribution across Italian regions between 2013 and 2022. Using clustering through a k-Means algorithm optimized with the Silhouette coefficient and the Elbow method, three distinct clusters of regions emerged, highlighting significant differences in social support networks. An econometric model was employed to estimate the PYCC variable, factoring in socioeconomic indicators such as employment rates, income inequality, and social participation. The results indicate a complex interplay between socioeconomic conditions and social trust, with regions in the South and Islands showing increased community support, while many Northern regions experienced declines. The study suggests that areas with lower economic conditions often foster stronger social networks, driven by necessity. These findings underline the importance of targeted public policies aimed at fostering social cohesion, particularly in regions facing economic challenges. Policy implications include enhancing education, supporting small enterprises, and promoting social housing and welfare initiatives. Strengthening community participation and volunteering are also highlighted as critical strategies to build resilient support networks. Overall, the research provides valuable insights into the regional disparities of social trust and the role of socioeconomic factors in shaping community support across Italy.

Keywords: Altruism Social Trust k-Means Machine-Learning Silhouette Coefficient Elbow Method Panel Data Regional Disparities. JEL Classification: D6 D64 D9 J21 D63; Altruism; Social Trust; k-Means; Machine-Learning; Silhouette Coefficient; Elbow Method; Panel Data; Regional Disparities. JEL Classification: D6; D64; D9; J21; D63 (search for similar items in EconPapers)
Date: 2024-09-15
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Working Paper: Social Trust and Support Networks: A Regional Analysis of Italy (2024)
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