What drives resilience for states in the United States? This thesis seeks to answer this question and addresses the absence of quantitative metrics for efforts to increase resilience. We used a literature review to create a framework of indicators, a Delphi review to validate the framework, and statistical techniques to create a composite indicator from the framework. Knowing that all models are false but some are useful, the intent was not to perfectly predict resilience, but simply to create a tool to help practitioners understand which programs most affect resilience. Our results showed that even programs assumed to have a strong link with resilience such as strong building codes actually had little relation with increased resilience, as measured by weather-related fatalities and economic losses. Some conclusions are that state-level measurement masks granular differences that are important in understanding weather-related deaths. In most states, for instance, weather-related deaths happen infrequently, yet most federal and state programs aim to increase resilience in catastrophic events, which makes it challenging to validate resilience measurement tools using data on day-to-day deaths. Recommendations include that FEMA should continue to build on improvements to the Threat and Hazard Identification and Risk Assessment and that agencies should determine and consistently measure the dependent variable (i.e., deaths and damage or other measures of well-being).
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