Evolution of Threats in the Global Risk Network

TL;DR

This paper models the evolution of global risks using a Cascading Alternating Renewal Process, providing insights into long-term risk levels and inter-risk influences to better understand vulnerabilities in the global network.

Contribution

It introduces a novel application of the Cascading Alternating Renewal Process to analyze the dynamics and evolution of the global risk network over time.

Findings

Identifies long-term risk levels in the global network.

Analyzes influence among different global risks.

Provides a framework for monitoring risk evolution.

Abstract

With a steadily growing population and rapid advancements in technology, the global economy is increasing in size and complexity. This growth exacerbates global vulnerabilities and may lead to unforeseen consequences such as global pandemics fueled by air travel, cyberspace attacks, and cascading failures caused by the weakest link in a supply chain. Hence, a quantitative understanding of the mechanisms driving global network vulnerabilities is urgently needed. Developing methods for efficiently monitoring evolution of the global economy is essential to such understanding. Each year the World Economic Forum publishes an authoritative report on the state of the global economy and identifies risks that are likely to be active, impactful or contagious. Using a Cascading Alternating Renewal Process approach to model the dynamics of the global risk network, we are able to answer critical questions regarding the evolution of this network. To fully trace the evolution of the network we analyze the asymptotic state of risks (risk levels which would be reached in the long term if the risks were left unabated) given a snapshot in time, this elucidates the various challenges faced by the world community at each point in time. We also investigate the influence exerted by each risk on others. Results presented here are obtained through either quantitative analysis or computational simulations.