Description:
<jats:title>Abstract</jats:title><jats:p>Economic consequence analysis is one of many inputs to terrorism contingency planning. Computable general equilibrium (CGE) models are being used more frequently in these analyses, in part because of their capacity to accommodate high levels of event‐specific detail. In modeling the potential economic effects of a hypothetical terrorist event, two broad sets of shocks are required: (1) physical impacts on observable variables (e.g., asset damage); (2) behavioral impacts on unobservable variables (e.g., investor uncertainty). Assembling shocks describing the physical impacts of a terrorist incident is relatively straightforward, since estimates are either readily available or plausibly inferred. However, assembling shocks describing behavioral impacts is more difficult. Values for behavioral variables (e.g., required rates of return) are typically inferred or estimated by indirect means. Generally, this has been achieved via reference to extraneous literature or <jats:italic>ex ante</jats:italic> surveys. This article explores a new method. We elucidate the magnitude of CGE‐relevant structural shifts implicit in econometric evidence on terrorist incidents, with a view to informing future <jats:italic>ex ante</jats:italic> event assessments. <jats:italic>Ex post</jats:italic> econometric studies of terrorism by Blomberg <jats:italic>et al</jats:italic>. yield macro econometric equations that describe the response of observable economic variables (e.g., GDP growth) to terrorist incidents. We use these equations to determine estimates for relevant (unobservable) structural and policy variables impacted by terrorist incidents, using a CGE model of the United States. This allows us to: (i) compare values for these shifts with input assumptions in earlier <jats:italic>ex ante</jats:italic> CGE studies; and (ii) discuss how future <jats:italic>ex ante</jats:italic> studies can be informed by our analysis.</jats:p>