An analysis of the New York City traffic volume, vehicle collisions, and safety under COVID-19

Abstract

Introduction and Method: We use the arguably exogenous intensity of COVID-19 as an instrument in order to study the relationship between traffic volume and vehicle collisions in a large metropolitan area. We correlate data from multiple sources and consider a time interval ranging from about one year before to one year after the pandemic breakout, which allows to account for preexisting seasonal patterns as well as the disruption brought by the pandemic. Results: We identify that increased traffic volume is associated with significantly more collisions with a robust elasticity varying between 1.2 and 1.7. At the same time, higher traffic volumes are associated with a significant reduction in casualties. Conversely, low traffic volumes are associated with high speeds and with particularly dangerous collisions. In terms of social cost, we separately calculated the cost of property damage and casualties. We measured that the reduction in the per-day social cost of collisions during the COVID-19 period is approximately $453,000 in property damage. However, the increase in casualties from collisions at lower traffic volumes are worth approximately $2.6 million in injuries and fatalities, entirely offsetting any benefit from reduced collisions. Practical Applications: This research provides valuable insights that policy makers may take into consideration when shifting traffic volume in relation to social cost and safety, such as congestion taxes.