Rapid Assessments of the Economic Implications of Terrorism Events Using a Regional CGE Model: Creating GRAD-ECAT (Generalized, Regional and Dynamic Economic Consequence Analysis Tool)

The Department of Homeland Security (DHS) considers the effects of hypothetical terrorism scenarios distinguished by many dimensions including: perpetrator; target; location; weapon; and delivery method. For each scenario, DHS requires a computationally rapid, in-house (secure) tool for translating impact effects or “driving variables” (e.g. capital destruction, clean-up expenditures, etc.) into economic implication variables (e.g. GDP in the short and long run, regional output in the short and long run, and economic welfare). We use a detailed, dynamic, multi-regional CGE model to generate elasticities E(s,d,v) of 9 implication variables (v) with respect to 14 driving variables (s) occurring as a result of incidents in any of the US’s 436 congressional districts (d). Equipped with these elasticities, DHS can apply trivial calculations to estimate the national and regional economic implications of an enormous variety of scenarios. Rose et al. (Economic consequence analysis tool (E-CAT), Springer, Tokyo, 2017) also propose a CGE-based rapid calculation tool for translating terrorism-related driving variables into economic implication variables. They refer to this tool as E-CAT (Economic Consequence Analysis Tool). Compared with E-CAT, our tool has a more general coverage of economic variables (both driving and implication variables) and introduces regional and dynamic dimensions. In view of the similarities and differences between our approach and E-CAT, we title the tool created here as GRAD-E-CAT (Generalized, Regional And Dynamic Economic Consequence Analysis Tool).