Enhancing Interdependency Analysis with the CFS

摘要

Our modern era is characterized by a large-scale web of interconnected and interdependent economic and infrastructure sectors, coupled with threats of terrorism. This research demonstrates the value of integrating the Commodity Flow Survey (CFS) databases with the Inoperability Input-Output Model (IIM) to enable the analysis of interdependencies among connected economic and infrastructure sectors spanning various regions of the United States. The IIM estimates the cascading inoperability and economic losses that result from interdependencies within large-scale economic and infrastructure systems in a specified region (1). It has been applied in various studies for the Commission on High-Altitude Electromagnetic Pulse (2), the U.S. Department of Homeland Security (3), and the Defense Threat Reduction Agency. Derived from Bureau of Economic Analysis (BEA) data and a Nobel Prize-winning W. Leontief macroeconomic model, the IIM is a quick, inexpensive, holistic method for estimating economic impacts. The integration of the CFS databases with the IIM to enhance the capability and performance of the model is presented in three applications. First, we have used CFS databases to quantify direct disruptions resulting from an attack to a transportation asset (e.g., bridge), which prohibits or delays commodities from reaching their destinations. Second, we employ the CFS databases to enable interregional analyses and estimate how a disruption cascades across regions. Third, we plan future work that involves integrating CFS databases into a geographic information systems framework for spatial interdependency analysis.