Prediction of default risk in Italian municipalities

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This study addresses the growing phenomenon of financial default among Italian municipalities, focusing on early detection and predictive analysis. Although more than 350 municipalities have entered default since 2001 — especially concentrated in Southern Italy — no institutional early warning systems are currently in place. The research combines a systematic literature review (SLR) and an econometric analysis to identify the main drivers of fiscal distress and to develop a predictive model based on official administrative data. Using a dataset covering all Italian municipalities from 2014 to 2024, the study applies a weighted logistic regression model corrected through post-stratification to account for population structure imbalances. Results highlight the importance of variables such as tax pressure, financial autonomy, and population size in predicting default risk. The model achieves excellent predictive performance, validated through real-world case studies. These findings suggest that the proposed approach can serve as a reliable early warning tool for national and local authorities, enabling a shift from reactive crisis management to preventive governance. Future research will extend the model to other national contexts, including the U.S., to foster fiscal resilience in decentralized government systems.

Keywords: Municipal Default, Predictive Model, Logistic Regression, Post-Stratification, Fiscal Risk, Local Governments

JEL Classification: H72, H74, H83, M41, M48

Received: 17.10.2025
Accepted: 29.10.2025

How to cite: Ciurleo, E., Gallo, A. M., & Comite, U. (2026). Prediction of default risk in Italian municipalities. In A. Celentano, A. Kostyuk, S. Dell’Atti, & G. Giovando (Eds.), Corporate governance: Multidisciplinary research (pp. 47–52). Virtus Interpress. https://doi.org/10.22495/cgmrp10