Estimating and comparing economic consequences of multiple threats: A reduced-form computable general equilibrium approach☆
Introduction
Research on the economic consequences of disasters is generally conducted on a threat-by-threat basis, yet public and private risk managers must allocate resources across multiple threats. Combining results from single-threat studies is problematic when the analyses use different economic consequence models, employ unique sets of assumptions and parameters, and present results in terms of different economic indicators. This study improves upon this threat-by-threat approach by developing an economic consequence analysis tool that can be applied across multiple threats to facilitate comparisons and provide a holistic approach to disaster risk management.
The Economic Consequence Analysis Tool (E-CAT) outlined below is capable of providing consistent results across various types of hazards given its standardized application of a comprehensive modeling framework and comparable types of assumptions, parameters and impact indicators. The E-CAT approach improves the understanding of the mechanisms of hazard events as it enables researchers to decompose the economic impacts across multiple threats according to the relative influence of causal factors.
Behavioral linkages and resilience effects are of particular interest because they are not covered in much of the literature and yet can have a significant impact on the overall economic impacts. Behavioral linkages refer to the changes in everyday practices of individuals in response to an extreme event, while economic resilience refers to the ways in which economic systems can bounce back from the shock of an extreme event and either recover losses or reach a new normal. The lack of attention to behavioral linkages and resilience effects has been highlighted in recent studies by Prager et al. [30] in an analysis of influenza outbreaks, [7] for aviation system disruptions, and [12], [39] for a variety of threats. For example, Prager et al. showed that behavioral factors, such as individuals avoiding workplaces or public spaces, could significantly augment the economic impacts of an influenza outbreak, while resilience factors, such as employees working overtime and other business recapture activities, could significantly reduce the economic impacts.
In addition, the empirical basis for the E-CAT approach, beginning with an enumeration of a comprehensive set of threat characteristics, can often allow for more accurate overall estimation than can be achieved by the in-depth estimation of a smaller number of direct impact categories. For example, a study of the economic impacts of an influenza outbreak focusing only on detailed workforce participation and medical expenditure impacts would be less accurate overall than a study considering a broader range of factors. This broader range would include factors such as behavioral linkages (e.g. staying home from work or school for fear of infection or to care for infected family, avoiding public gatherings or transportation use) and resilience effects (such as the ability to recapture lost work). Moreover, a “reduced-form” extension of the analysis – based on linear regressions of GDP and employment CGE outputs on Monte Carlo-generated CGE inputs (“drivers”) – renders the complex modeling accessible to a broad range of potential users (see, e.g., [39]) and facilitates improved decision-making for resource allocation in emergency planning and management.
Section snippets
Literature review
Two methods are prevalent in estimating the total economic consequences of disasters. Input-Output (I-O) and computable general equilibrium (CGE) modeling analyses have been conducted for numerous individual threats types1 [22],
Methods and data
This analysis uses CGE modeling in the Center for Risk and Economic Analysis of Terrorism Events (CREATE) ECA framework [32] and applies it to multiple threat types, creating a reduced-form model with a probabilistic element that can be interpreted easily by decision makers through a user-friendly software tool. The E-CAT research framework is the standardized application of the ECA framework to a broad range of extreme events using CGE modeling, which is then condensed into an
Results
Table 4, Table 5 present results for the economic impacts of five threats, with respect to CGE results and decompositions (Table 4), based on the regression results illustrated in Table 5. Table 4 presents the least and the most impactful scenarios for each threat in order to illustrate the relative impacts of different policy-relevant variables on total GDP results. Unsurprisingly, disaster events usually lead to significant negative economic impacts. The Magnitude column represents those
Conclusions
This paper introduces an economic modeling system that improves the analytical ability, accuracy and consistency of economic consequence analyses. It first decomposes the direct impacts of numerous threats into their constituent CGE input factors (drivers). This multi-threat decomposition approach allows for analysis of the relative prominence of numerous drivers and how they are impacted in the general equilibrium stages.
Such a decomposition also allows for impact assessment of different
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This study was based on work supported by the U.S. Department of Homeland Security under Grant Award Number 2010-ST-061-RE0001-05. The authors wish to thank to Sam Chatterjee, Dan Wei, Nat Heatwole, Eric Warren, Noah Miller, and Joshua Banks for their helpful assistance on the research contained in this paper. Any remaining errors or omissions are solely those of the authors.