Analyzing Pennsylvania’s Economic Resilience Considering Interdependent Infrastructures and Economic Sectors

Open Access
- Author:
- Clayman, Scott
- Graduate Program:
- Computer Science and Engineering
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- November 07, 2019
- Committee Members:
- Mohamad Darayi, Thesis Advisor/Co-Advisor
Raghu Sangwan, Committee Member
Satish Mahadevan Srinivasan, Committee Member
Youakim Badr, Committee Member
Colin Neill, Program Head/Chair - Keywords:
- economic
disruption
input-output model
inoperability input-output model
multi-regional inoperability input-output model
I-O model
IIM model
MRIIM model
infrastructure
critical infrastructure
economic resilience
economic sectors
industry sectors
bayesian vector autoregression
network
clustering
centrality
components
GDP
forecasting
vulnerability - Abstract:
- This research studies Pennsylvania and 22 other states that are its largest trading partners to determine the economic loss caused by infrastructure disruptions both in 2012 and as forecast by Bayesian vector autoregression in the year 2040. This analysis of economic loss is based on an analysis of the interdependent infrastructure and economic sectors in these 23 states using the multi-regional inoperability input-output model (MRIIM). A data-driven analysis of this 23 state network to study the critical elements of the network has allowed for a measure of importance to be developed for the network as well. Based on the economic sectors and states that have the greatest projected economic loss in both 2012 and 2040, as well as those that are of the greatest importance to the network, it is possible for stakeholders to plan for the hardening of critical infrastructure that serves the states and economic sectors that are of the greatest importance. The measure of importance is derived by calculating the vulnerability of the network before a node is removed from the network and comparing it to the vulnerability after it is removed, with a more vulnerable network after removal indicating that node or economic sector is of greater importance to the network. The four different projections by disruption scenario in both 2012 and 2040, varying based on which modes of transportation are disrupted, allow for stakeholders to weigh the economic loss in each scenario against the limited budgets for infrastructure hardening. Among the largest sectors by economic loss caused by Disruption Scenario 1, 40% of railways and 45% of waterways being disrupted, in 2012 are primary metals, petroleum and coal products, and chemical products. The disruption scenario causing the greatest economic loss in both 2012 and 2040 was Disruption Scenario 3, 60% of truckways being disrupted. In 2040, Disruption Scenario 3 also had the largest percentage gain in economic loss for that scenario compared to 2012, but the disruption scenarios were closer to one another in the percentage change in total economic loss from 2012 to 2040. This outcome likely reflects marginal changes in each scenario’s proportionate impact on the economy, with the exception of Disruption Scenario 4, 100% of waterways being disrupted, having a smaller percentage increase than the others. Meanwhile, the measure of importance indicates that the top four industry sectors are wholesale trade, chemical products, food and beverage and tobacco products, and primary metals. This research shows that the economic impact of a disruption can be quantified for industry sectors in multiple states that are in trade with Pennsylvania. Each disruption scenario allows stakeholders to determine the infrastructure that serves the modes of transportation with the greatest economic loss, while the measure of importance also allows the economic sectors that are of the highest importance to the entire network to be determined. These results show how the projected economic loss from disruption scenarios and importance of each node to the entire network can enable more informed decisions for stakeholders involved in infrastructure development studies and infrastructure hardening strategies.