Intercontinental trade and transport patterns do not normally change overnight. But the networks that support them can when catastrophes destroy key links. A USC-based study group is creating a model to predict the economic results of transport disasters on a state-by-state, sector-by-sector basis. The hope is the model will help authorities better prepare, better decide, and better respond.
The group leader, Professor James Moore of the USC Viterbi School’s Epstein Department of Industrial and Systems Engineering, prepared an overview of the work, entitled “TransNIEMO: An Operational Model of Interregional Trade with Explicit Consideration of Highway Network Effects” for the Viterbi School’s Integrated Media Systems Center (IMSC), work he has also presented internationally in South Korea and China.
The 1-35 bridge collapse in Minneapolis impacted the economy across the country. The new TransNIEMO system can estimate the economic impact of such disasters to help planners prepare and respond.
He began with an existing model that his group developed, called the National Interstate Economic Model (NIEMO). It is an extremely detailed state-by-state accounting of production and shipping activity across many economic sectors. The group then modeled the “Trans”, the transport side that enables trade, by calculating the changes in shipping times and costs resulting from major network failures, such as the August 1, 2007 collapse of the I-35 bridge over the Mississippi River in Minneapolis, Minn.
The TransNIEMO estimates are based on a model of economic interconnections and impact feedbacks, starting with predicting and mapping alternative paths for national freight movements, and then analyzing the consequences in time, cost, lost production and other factors.
These damage scenario estimates come out of the U.S. Department of Transportation’s detailed national database of 114 freight zones. The model computes an economic centroid for each
zone, and each centroid is connected to a web of network intersections leading in and out of each centroid. Then the model calculates freight demands between each pair of these centroids – a total of 12,882 demand calculations in all — which are then applied to NIEMO data to estimate changes in shipping costs, commodity prices, consumption, and demand.
James Moore
The group ran exercises to estimate the economic losses resulting from the closure of two major bridges over the lower Mississippi River, a region in which river crossings are sparse. The annual economic loss totaled $316 million on a national level. The losses varied widely from state to state, with some states (such as Indiana, Louisiana and Ohio) much more vulnerable to economic impacts than others (such as Arkansas and Vermont).
This general model can be focused on specific scenarios. The team hopes to expand TransNIEMO to include passenger traffic and other networks such as air and rail, and also to take better account of changes that might be improvised in the face of such emergencies.
In addition to Moore, the other USC members of the team included Department of Industrial and Systems Engineering graduate student Joongkoo Cho, and Professors Peter Gordon and Harry Richardson, and graduate student Eunha Jun, of the Price School of Public Policy.
The team also included SungHo Ryu of the Southern California Association of Governments, Professor Qisheng Pan of Texas Southern University, and Professor Jiyoung Park of the State University of New York, Buffalo. Pan and Park are doctoral graduates of USC. Research sponsors included the California and U.S. Departments of Transportation, through the National Center for Metropolitan Transportation Research (METRANS); and the Department of Homeland Security, through the USC Center for Risk and Economic Analysis of Terrorism Events (CREATE).
