Willis Henry H, LaTourrette Tom
RAND Corporation, Pittsburgh, PA 15213, USA.
Risk Anal. 2008 Apr;28(2):325-39. doi: 10.1111/j.1539-6924.2008.01022.x.
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.
本文提出了一个在监管分析中使用概率性恐怖主义风险建模的框架。我们通过一个示例应用展示了该框架,该示例应用涉及一项正在审议的法规——西半球陆地环境旅行倡议(WHTI-L)。首先,我们使用风险管理解决方案(RMS)概率性恐怖主义模型估计恐怖袭击的年化损失。然后,我们估计关键风险降低量,即WHTI-L为了使其在美国减少恐怖主义损失方面的收益超过其成本所需的风险降低效果。我们的分析表明,关键风险降低量不仅强烈依赖于恐怖主义风险水平的不确定性,还依赖于监管成本的不确定性以及伤亡如何货币化。对于基于RMS标准风险估计的恐怖主义风险水平、WHTI-L的基线监管成本估计以及基于支付意愿方法的一系列伤亡成本估计,我们对恐怖主义预期年化损失的估计范围为27亿美元至52亿美元。对于这个年化损失范围,WHTI-L的关键风险降低量范围为7%至13%。基于使年化恐怖主义损失减半的较低风险水平得出结果,将使关键风险降低量翻倍(14%-26%),而基于使年化恐怖主义损失翻倍的较高风险水平得出结果,将使关键风险降低量减半(3.5%-6.6%)。理想情况下,关于恐怖主义安全法规和政策的决策应以真正的效益成本分析为依据,即将估计的效益与成本进行比较。此类针对恐怖主义安全工作的分析面临重大障碍,这些障碍源于恐怖主义威胁的巨大不确定性以及大型袭击的极低复发间隔。可以使用几种方法来估计恐怖主义安全计划或法规如何减少其旨在管理的风险分布。但是,持续开展研究以开发更多工具和数据对于支持这些方法的应用是必要的。这些工作包括完善模型和模拟、让主题专家参与、实施项目评估以及估计恐怖主义事件造成的伤亡成本。