Abstract:

This paper investigates the differential response to the MeToo movement across areas with varying levels of sexism in the United States. Measuring the local sexist attitude toward women by the Google search index and a machine learning technique, we show that the number of documented sexual crimes increases in areas with lower sexism. This finding is robust to including a host of controls that account for the demographic, socioeconomic, and ideological differences across these areas. Our finding still holds for individuals with differential tolerance toward inappropriate behaviors in workplaces. Suggestive evidence indicates that the surge in documented sexual crimes in low sexism areas is primarily sourced from reporting rather than actual incidents.