Exploring the effects of urban rail on the survival of nearby businesses

This study investigates the spatiotemporal impacts of urban rail on business survival. Urban rail projects can increase accessibility and foot traffic, benefiting nearby businesses, but may also lead to higher rents and commercial gentrification, potentially displacing small or local businesses. However, little is known about how transit investments affect business survival over time. To address this gap, we employ a quasi-experimental design and estimate Extended Cox Hazards models using historical business microdata from Data Axle, covering a 21-year period from 1998 to 2019. Our analysis compares businesses located within 0.5 miles of light rail stations with those in a carefully selected control area, while also examining heterogeneous impacts by distance to stations and by TOD district characteristics. Our empirical application focuses on the LYNX Blue Line in Charlotte, NC. Our findings indicate that the effects of light rail on business survival are sector-specific. Specialty retailers (NAICS code 45) located between 0.125 and 0.25 miles from a station experience a 58% reduction in closure risk five to ten years after the beginning of light rail operation. Accommodation and food services (NAICS code 72) located between 0.25 and 0.5 miles from stations experience decreases of 66% in the probability of closure during the same time period. Moreover, service establishments and specialty retailers operating in TOD zones exhibit reductions in closure risk of approximately 50% compared to their counterparts in the control group. Our results demonstrate that overall, proximity to transit and TOD environments that encourage pedestrian traffic through parking restrictions and higher development density do not negatively impact retail and service establishments and in some cases significantly support the longevity of businesses. However, more research is needed to improve our understanding of transit’s impacts on nearby businesses and to design relevant and effective policies. • Extended Cox Hazards models on survival of retail and service businesses near transit. • Analysis of historical business microdata over a 21-year period. • Quasi-experimental design isolates transit impact on firm survival. • TOD districts and distance from stations shape the effects on business survival. • Higher probability of survival for specialty retailers and service establishments close to transit.