Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2502.12980

Quantitative, Data-driven Network Model for Global Cascading Financial Failure

Łukasz G. Gajewski·Michael Hinge·David Denkenberger
View original source ↗Read source document ↗Export metadata ↓

Abstract

Global catastrophic risk events, such as nuclear war, pose a severe threat to the stability of international financial systems. As evidenced by even less severe scenarios like the Great Recession, an economic failure can propagate through the world trade network, wreaking havoc on the global economy. While the contemporary literature on cascading failure models addresses this issue qualitatively, a simple and intuitive quantitative estimation that could be used in integrated assessment frameworks is missing. In this study, we introduce a quantitative network model of global financial cascading failure. Our proposal is a fast, efficient, single free parameter model, following a straightforward logic of propagating failures. We fit the model to the Great Recession and test it against historical examples and commercial analysis. We also provide predictions for a hypothetical armed conflict between India and Pakistan. Our aim is to introduce a quantitative approach that could inform policy decisions by contextualising global catastrophic scenarios regarding financial losses and assessing the effectiveness of resilience strategies, complementing existing models and frameworks for broader risk assessment.

Explore related subjects

physics.soc-ph

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Łukasz G. Gajewski, Michael Hinge, David Denkenberger. 2025-02-18. Quantitative, Data-driven Network Model for Global Cascading Financial Failure. https://arxiv.org/abs/2502.12980

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Assessment of Latent Pedestrian-Vehicle Interaction Risk Profiles at Midblock Crossing in VR

Pedestrian safety at midblock crossings is a critical concern in mixed traffic environments where autonomous vehicles (AVs) and human-driven vehicles (HDVs) share the road. Pedestrians often infer intent from vehicle motion in AV encounters, making them vulnerable to small shifts in conflict margins. This study investigates whether virtual reality (VR) crossing sessions separate into distinct interaction risk profiles and whether AV-only sessions shift profile prevalence compared to HDV-only sessions. Using large-scale immersive VR experiments from Toronto, Canada, and Newcastle, England, we compute surrogate safety measures (SSMs) and apply latent profile analysis (LPA) to identify distinct pedestrian crossing stances, ranging from risk-accepting to highly cautious. Key findings show that Newcastle exhibits a higher prevalence of high-urgency risk profiles in AV-only sessions, indicating that AVs contribute to higher-risk encounters. In contrast, Toronto shows no significant difference between AV-only and HDV-only sessions, suggesting that contextual factors influence the impact of AVs on pedestrian safety.

physics.soc-ph↗
arXiv2026

Unused power surge compromises U.S. road vehicles sustainability

Material and energy flows underpin sociotechnical metabolism. However, despite growing sustainability concerns over expanding material stocks and declining stock productivity, the link between material use and energy consumption remains poorly understood. This gap reflects a limited distinction between structures and the activity they enable, and the lack of quantification of the installed power of energy consuming structures. Here we reconstruct the long-term growth dynamics of U.S. road vehicles, distinguishing professional and consumer assets. We show that installed power, mass, and fuel energy use follow divergent patterns within and across vehicle categories. By introducing the usage factor as a metric linking structure to activity, we quantify decoupling mechanisms such as engine oversizing and fleet redundancy, which drive up material immobilization. As electrification requires large-scale fleet replacement, our findings highlight that avoiding power oversized vehicles could reduce material demand, emphasizing the need to account for structure-activity decoupling in energy transition policies.

physics.soc-ph↗
arXiv2026

Environmental sustainability in basic research: a perspective from HECAP+

The climate crisis and the degradation of the world's ecosystems require humanity to take immediate action. The international scientific community has a responsibility to limit the negative environmental impacts of basic research. The HECAP+ communities (High Energy Physics, Cosmology, Astroparticle Physics, and Hadron and Nuclear Physics) make use of common and similar experimental infrastructure, such as accelerators and observatories, and rely similarly on the processing of big data. Our communities therefore face similar challenges to improving the sustainability of our research. This document aims to reflect on the environmental impacts of our work practices and research infrastructure, to highlight best practice, to make recommendations for positive changes, and to identify the opportunities and challenges that such changes present for wider aspects of social responsibility.

physics.soc-ph↗