Quantitative Methods for Systemic Risk in Sustainability

Systemic risk in sustainability arises from the intricate interplay between environmental, economic, and social systems. Addressing these risks requires a multidimensional approach: mapping the architecture of risk data, analyzing interconnections that transmit shocks, and applying quantitative models to understand underlying dynamics. By exploring scenario analysis, stress testing, and lifecycle-based assessments, it becomes possible to anticipate how disruptions propagate across value chains and financial networks. Advanced analytics, including machine learning and network theory, further reveal hidden vulnerabilities and emerging threats. Together, these perspectives illuminate the pathways through which sustainability risks evolve, enabling a deeper understanding of both the fragility and resilience inherent in complex global systems.
Systemic Risk in Sustainability
Risk Taxonomy and Data Architecture
Network Analysis and Systemic Interconnection
Econometric and Statistical Modeling of Systemic Risk
Scenario Analysis and Stress Testing for Sustainability
Lifecycle and Impact-Based Risk Assessment
Quantitative Methods for Systemic Risk in Sustainability Dashboard
Predictive Analytics for Systemic Risk Dashboard
References