  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 and leisure and hospitality
sectors. 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 also 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.

Econometrics;Atmospheric and Oceanic Physics