Distribution of Losses from Large Terrorist Attacks Under the Terrorism Risk Insurance Act

Carroll, Stephen J.; LaTourrette, Tom; Chow, Brian G.; Jones, Gregory S.; Martin, Craig

doi:10.7249/mg427

Cited by 9 publications

(6 citation statements)

References 7 publications

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“…For example, in the United States following the terrorist attack of September 11, 2001, the US Congress passed the Terrorism Risk Insurance Act (TRIA), which requires all US insurance firms to offer terrorism coverage as a rider to their standard coverage for commercial buildings. The quid pro quo is that the government provides reinsurance for the highest layer of risk, although, as shown in Carroll, LaTourrette, Chow, Jones, and Martin (2005), the actual subsidy is very small. Thus, the primary force of TRIA is that it requires a coordinated equilibrium in which all insurers must offer terrorism coverage.…”

Section: The Role Of a Central Agencymentioning

confidence: 99%

Nondiversification Traps in Catastrophe Insurance Markets

2008

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We develop a model for markets for catastrophic risk. The model explains why insurance providers may choose not to offer insurance for catastrophic risks and not to participate in reinsurance markets, even though there is a large enough market capacity to reach full risk sharing through diversification in a reinsurance market. This is a "nondiversification trap." We show that nondiversification traps may arise when risk distributions have heavy left tails and insurance providers have limited liability. When they are present, there may be a coordination role for a centralized agency to ensure that risk sharing takes place.

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Section: The Role Of a Central Agencymentioning

confidence: 99%

Nondiversification Traps in Catastrophe Insurance Markets

2008

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“…The quid pro quo is that the government provides reinsurance for the highest layer of risk, although, as shown in Carroll et al (2005), the actual subsidy is very small. Thus, the primary force of TRIA is that it requires a coordinated equilibrium in which all insurers must offer terrorism coverage.…”

Section: The Role Of a Central Agencymentioning

confidence: 99%

Heavy-Tailed Distributions and Robustness in Economics and Finance

Ibragimov

Ибрагимов

Waldén

2015

Lecture Notes in Statistics

116

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“…Applications of risk analysis to terrorism security have used many different methods and approaches. Examples of methods that have been applied include agent‐based models (N‐ABLE, 2006; Tsvetovat & Carley, 2002), game theory (Kunreuther, 2005; Bier et al , 2005), economic input‐output models (Haimes et al , 2005; Gordon et al , 2006), probabilistic risk analysis (Rosoff & von Winterfeldt, 2006; ASME, 2007), operations research approaches drawing upon queuing theory and decision analysis (Martonosi et al , 2005; Wein et al , 2006), and probabilistic models developed and used in the insurance industry (Willis et al , 2005; Willis, 2007; Carroll et al , 2005; Doherty et al , 2005).…”

Section: Using Risk Modeling In Regulatory Benefit‐cost Analysismentioning

confidence: 99%

Using Probabilistic Terrorism Risk Modeling for Regulatory Benefit‐Cost Analysis: Application to the Western Hemisphere Travel Initiative in the Land Environment

Willis

LaTourrette

2008

Risk Analysis

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This article presents a framework for using probabilistic terrorism risk modeling in regulatory analysis. We demonstrate the framework with an example application involving a regulation under consideration, the Western Hemisphere Travel Initiative for the Land Environment, (WHTI-L). First, we estimate annualized loss from terrorist attacks with the Risk Management Solutions (RMS) Probabilistic Terrorism Model. We then estimate the critical risk reduction, which is the risk-reducing effectiveness of WHTI-L needed for its benefit, in terms of reduced terrorism loss in the United States, to exceed its cost. Our analysis indicates that the critical risk reduction depends strongly not only on uncertainties in the terrorism risk level, but also on uncertainty in the cost of regulation and how casualties are monetized. For a terrorism risk level based on the RMS standard risk estimate, the baseline regulatory cost estimate for WHTI-L, and a range of casualty cost estimates based on the willingness-to-pay approach, our estimate for the expected annualized loss from terrorism ranges from $2.7 billion to $5.2 billion. For this range in annualized loss, the critical risk reduction for WHTI-L ranges from 7% to 13%. Basing results on a lower risk level that results in halving the annualized terrorism loss would double the critical risk reduction (14-26%), and basing the results on a higher risk level that results in a doubling of the annualized terrorism loss would cut the critical risk reduction in half (3.5-6.6%). Ideally, decisions about terrorism security regulations and policies would be informed by true benefit-cost analyses in which the estimated benefits are compared to costs. Such analyses for terrorism security efforts face substantial impediments stemming from the great uncertainty in the terrorist threat and the very low recurrence interval for large attacks. Several approaches can be used to estimate how a terrorism security program or regulation reduces the distribution of risks it is intended to manage. But, continued research to develop additional tools and data is necessary to support application of these approaches. These include refinement of models and simulations, engagement of subject matter experts, implementation of program evaluation, and estimating the costs of casualties from terrorism events.

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Distribution of Losses from Large Terrorist Attacks Under the Terrorism Risk Insurance Act

Cited by 9 publications

References 7 publications

Nondiversification Traps in Catastrophe Insurance Markets

Nondiversification Traps in Catastrophe Insurance Markets

Heavy-Tailed Distributions and Robustness in Economics and Finance

Using Probabilistic Terrorism Risk Modeling for Regulatory Benefit‐Cost Analysis: Application to the Western Hemisphere Travel Initiative in the Land Environment

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