Raúl Pezoa, Louis de Grange, Rodrigo Troncoso & Hugo Contreras
Abstract
This paper examines how factors linked to perceived insecurity – such as crime exposure, payment method, and customer familiarity – affect the likelihood that a female driver serves a ride request. Using a dataset of over ten million Uber trips in Chile, we estimate binary logit models that incorporate trip-level attributes, area-level socioeconomic characteristics, and a control function approach to address potential endogeneity in crime rates. Our findings show that female drivers are less likely to serve trips originating from or destined to high-crime areas, especially when paid in cash. They are also less likely to be involved in trips occurring at night, requested by infrequent customers, or involving longer distances. These patterns suggest that personal safety-related factors may influence female drivers’ participation in the ride-hailing market and could limit the flexibility that this type of work is expected to offer.
