Characteristics and Predictive Modeling of Short-term Impacts of Hurricanes on the US Employment

This study examines the short-term employment changes in the US after hurricane impacts. An analysis of hurricane events during 1990-2021 suggests that county-level employment changes in the initial month are small on average, though large employment losses (>30%) can occur after extreme cyclones. The overall small changes partly result from compensation among opposite changes in employment sectors, such as the construction and leisure and hospitality sectors. An analysis of these extreme cases highlights concentrated employment losses in the service-providing industries and delayed, robust employment gains related to reconstruction activities. The overall employment shock is negatively correlated with the metrics of cyclone hazards (e.g., extreme wind and precipitation) and geospatial details of impacts (e.g., cyclone-entity distance). Additionally, non-cyclone factors such as county characteristics also strongly affect short-term employment changes. The findings inform predictive modeling of short-term employment changes and help deliver promising skills for service-providing industries and high-impact cyclones. Specifically, the Random Forests model, which can account for nonlinear relationships, greatly outperforms the multiple linear regression model commonly used by economics studies. Overall, our findings may help improve post-cyclone aid programs and the modeling of hurricanes socioeconomic impacts in a changing climate.