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use a large-scale dynamic regional computable general equilibrium (CGE)
model of the Los Angeles economy to perform an economic consequence
analysis of a terrorist attack with chlorine gas. We divide the event's direct
effects into resource losses (injuries, BI) and behavioral reactions stemming
from fear. We provide a decomposition of aggregate economic effects in terms
of these various loss components, allowing us to elucidate the relative sizes of
potential loss channels. We also discuss the effect of geographic shifts of
economic activity within the affected region and in neighboring regions in
estimating the losses. Our analysis can assist risk managers in developing
plans for pre-event mitigation and post-event resilience.
16.1
Introduction
By elucidating the benefits of threat reduction and post-event response, economic
consequence analysis can be an important input to the contingency planning of
emergency management decision makers. In this paper we show how dynamic
regional CGE modeling can elucidate behavioral and dynamic elements relevant to
such planning. We considered several modeling approaches to perform our analy-
sis. Methodologies for analysing the regional economic consequences of specific
threats have developed from the use of regional input-output models to investigate
the direct and indirect effects of physical destruction, transport disruption and BI
(Gordon et al.
1998
) to applications of regional CGE models to also analyse the
consequences of behavioral responses (Rose et al.
2009
).
Input-output models are practical tools but lack behavioral content, the crux of
the issue at hand. They also lack the ability to effectively model the workings of
markets through factor and product price changes. Econometric models are a
valuable approach, especially for forecasting but less so for simulation. They are
highly dependent on time series or cross-sectional data, and less conducive to the
incorporation of simulation results. Moreover, econometric models typically are
based on aggregate relationships, as opposed to micro behavioral responses of
consumers, firms, and providers of factor services. Agent-based modeling on the
other hand is especially adept at analyzing individual decision-makers and their
interactions. However, they are not yet able to scale up to the macro level and to
analyze the full effects of the workings of markets. As we expand upon below, CGE
models have behavioral content, are able to mimic the role of markets and prices,
and can readily be recalibrated with simulation data. Moreover, they have been
successfully applied to topics such as the focus of this chapter [see, e.g., Giesecke
et al.
2012
)].
Regional CGE models embody much detail describing economic structure
(e.g. production technologies, and regional resource constraints); the behavior of
economic agents (e.g. household preferences, and investor return requirements);
and policy variables (e.g. the instruments of government taxing and spending). This
detail has allowed these models to be applied to a wide range of issues relating to
the structural, behavioral and policy drivers of regional growth and decline and the
