Using a regional CGE model for rapid assessments of the economic implications of terrorism: creating GRAD-ECAT (Generalized, Regional And Dynamic Economic Consequence Analysis Tool

Peter Dixon, Michael Jerie, Maureen Rimmer and Glyn Wittwer

No 332900, Conference papers from Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project

Abstract: The Terrorism Risk Assessment (TRA) groups in the Department of Homeland Security assess millions of terrorism scenarios defined by location, agent (e.g. nuclear device), and delivery method (e.g. car bomb). For each scenario they estimate deaths, injuries, property damage, clean-up and health expenses, visitor discouragement, and other damage dimensions. The TRA groups translate damages into economic measures, e.g. loss of GDP. Previously they used an input-output (I-O) model. Here we replace I-O with computable general equilibrium (CGE). Solving CGE models is computationally time-consuming and requires specialist skills. For the TRA groups this creates two challenges: feasibility and security. A model that cannot be solved in less than a fraction of a second is infeasible for analyzing millions of scenarios. The TRAs can rely only on people with high security clearances, limiting the possibilities for obtaining specialist advice. Our approach to these challenges was to use a CGE model to estimate elasticities that connect economic implication variables with damage or driving variables. We supplied these elasticities for use in the equation: v=Sum(s, E(s,d,v)*s ) where v and s are the percentage changes in an implication variable and a driving variable. E(s,d,v) is a CGE-estimated elasticity that we supplied. It is the elasticity of v to a terrorism shock s perpetrated in target region d, e.g. the percentage effect on national welfare of destruction of 1 per cent of the capital stock in congressional district NY14. Our elasticity approach solves both challenges. First, for any given terrorism scenario specified by a location and a vector of s variables, the elasticity equation can be computed in nanoseconds to evaluate a range of implication variables, v. Second, as outside contractors, we had no need for access to sensitive information on specific shock vectors s and target regions d.

Keywords: Research; Methods/Statistical; Methods (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:ags:pugtwp:332900

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