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

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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.