Collaborative Research: An Integrated Approach to Measuring Dynamic Economic Resilience Following Disasters

2011年，美国经历了创纪录的14次与天气有关的灾害，损失达10亿美元。 第二年，超级风暴桑迪，这项研究的重点，造成了估计680亿美元的损失，使其成为第二个最昂贵的风暴在我们的历史。 这些损失表明，了解国家如何在灾害面前变得更具弹性至关重要。 该项目将动态弹性定义为在经历灾难后“反弹”的能力，被广泛视为减少灾难造成的破坏和控制成本的一种方式，包括由个人业主承担的成本。S.财政部以灾害援助的形式，以及保险/再保险部门。 灾害和灾后恢复援助造成的财政损失减少了可用于其他生产性投资的资源供应。 因此，这个项目与NSF的使命是一致的，特别是关注如何“促进国家健康、繁荣和福利”的方面。“在这项研究中，我们将探索弹性的一个方面-动态经济弹性-通过更好地了解纽约市地区受影响的企业如何应对桑迪以及他们能够恢复的程度。 我们寻求以综合的方式了解企业主的决策和更广泛的经济条件如何有助于恢复力。我们将建立灾后恢复投资决策模型;对具有代表性的企业样本进行调查，以了解更多有关其恢复决策的信息;并研究社区水平条件（如就业率，劳动力特征和社区经济多样性）对经济弹性和恢复的影响。该项目将采用几种分析战略，提供一个全面和综合的模型，其中包括影响灾后经济复原力的微观、中观和宏观因素。将制定一个微观经济投资框架，以考虑到企业所有人对灾后恢复投资的决定。 将建立一个数据库，其中包括对区域经济复苏具有重要意义的社区一级因素。 我们还将开发一个动态可计算的一般非均衡模型，以分析宏观经济层面的弹性。

In 2011, the nation experienced a record fourteen, billion-dollar weather-related disasters. The next year, Superstorm Sandy, the focus of this study, caused an estimated $68 billion in losses, making it the second-costliest storm in our history. These losses show why it is critical to understand how the nation can become more resilient in the face of disasters. Dynamic resilience, defined in this project as the ability to "bounce back" after experiencing a disaster, is widely seen as a way of reducing the disruption disasters cause and of containing costs, including those borne by individual property owners, the U. S. Treasury in the form of disaster aid, and the insurance/reinsurance sector. The financial losses that result from disasters and post-disaster recovery assistance reduce the supply of resources available for other productive investment. This project is thus consistent with the mission of NSF, particularly aspects of that focus on understanding how to "advance national health, prosperity, and welfare." In this study, we will explore one dimension of resilience - dynamic economic resilience - by developing a better understanding of how affected businesses in the New York City area coped following Sandy and the extent to which they were able to recover. We seek to understand in an integrated way how both business owners' decisions and broader economic conditions contribute to resilience. We will model post-disaster recovery investment decisions; conduct a survey with a representative sample of businesses to learn more about their recovery decision making; and examine the effects of community-level conditions such as employment rates, labor force characteristics, and community economic diversity on dimensions of economic resilience and recovery. The project will employ several analytic strategies to provide a holistic and integrated model that incorporates micro-, miso-, and macro-level factors affecting economic resilience following disasters. A microeconomic investment framework will be developed to take into account business owners' decisions to invest in post-disaster recovery. A database will be developed consisting of community-level factors important for regional economic recovery. We will also develop a dynamic computable general disequilibrium model to analyze resilience at the macroeconomic level.