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 storms. The overall small changes are partly a result of compensation among different employment sectors, such as the construction sector and the leisure and hospitality sector. Employment losses tend to be relatively pronounced in the service-providing industries. The post-storm employment shock is negatively correlated with the metrics of storm hazards (e.g., extreme wind and precipitation) and geospatial details of impacts (e.g., storm-entity distance). Additionally, non-storm factors such as county characteristics strongly affect short-term employment changes. The findings inform predictive modeling of short-term employment changes, which shows promising skills for service-providing industries and high-impact storms. The Random Forests model, which can account for nonlinear relationships, greatly outperforms the multiple linear regression model commonly used by economics studies. These findings may help improve post-storm aid programs and the modeling of hurricanes' socioeconomic impacts in a changing climate.