By Nick Sawhney

Fare Evasion and its enforcement is an ever-more relevant issue in New York City. In this paper, a data set of fare evasion arrests and weighted census data is created and analyzed using a difference-in-differences regression model in order to understand the impact of the Manhattan District Attorney’s 2018 policy to curtail the prosecution of those arrested for fare evasion in the New York City Subway. Results suggest that, despite an overall reduction in arrests, Black and Hispanic communities still saw an increase in fare evasion policing. Income inequality is suggested as an indicator of the number of arrests as well. Furthermore, the proportion of Black arrests was found to increase following the implementation of the policy, especially in areas which contain greater Black and Hispanic populations.

Published 2020.