Cascading Risk Propagation in Interdependent Trade Networks: A Complex-Network Model for Systemic Risk Management with Evidence from the Global Sulfur Trade

Globalized production and trade have knitted national economies into a tightly coupled interdependent network, in which a localized shock can propagate through dependency links and escalate into a systemic event. Sulfur underpins phosphate fertilizer and the clean-energy transition, yet the global sulfur trade network is concentrated, heavily import-dependent, and exposed to geopolitical chokepoints. This paper develops a data-driven complex network framework for cascading risk propagation and demonstrates it on the directed-weighted global sulfur trade network (GSTN) built from UN Comtrade over 2015–2024. A threshold-based cascading failure model propagates load redistribution until a country’s import loss exceeds its capacity buffer. Three results emerge. First, although total trade volume grew by 129%, the network contracted sharply after 2022, indicating rising systemic vulnerability. Second, avalanche sizes follow a heavy-tailed, approximately power-law distribution: Russia is the dominant systemic-risk source (nine rounds, 41% of trading countries, collapse conversion above 80%), Turkey is a secondary amplifier, while the largest exporter, the United Arab Emirates, transmits risk mainly through indirect contraction. Third, the model is calibrated against the 2022 Russia–Ukraine shock (R² = 0.8538). The framework offers an early-warning tool for identifying systemically important nodes and for stress-testing interdependent economic and financial networks.