  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.
