Realized Random Graphs: A New Econometric Methodology for the Inference of Dynamic Network

This project develops scalable econometric tools to study how financial and social networks evolve in response to shocks and policy interventions. Bringing together the University of Verona and Scuola Normale Superiore, it builds on the Realized Random Graphs (RRG) methodology, which simplifies the analysis of complex dynamic networks while preserving flexibility.

The research follows three main directions. First, it extends the theoretical framework to sparse networks, improving its applicability to real-world systems. Second, it develops methods to identify evolving communities in financial networks and examines how economic shocks and policy interventions influence market behavior and systemic risk. Third, it introduces statistical tools to investigate the emergence and evolution of cooperation in social networks, exploring how interaction patterns and incentives shape cooperative behavior.

Expected outputs include methodological advances, empirical analyses and publicly available software. The project aims to help researchers and policymakers identify financial vulnerabilities, assess policy effectiveness and better understand cooperation in social and organisational settings.