A New Look at Racial Profiling: Evidence from the Boston Police Department

Abstract

This paper provides new evidence on the role of preference-based versus statistical discrimination in racial profiling using a unique data set that includes the race of both the driver and the officer. We first generalize the model presented in Knowles, Persico and Todd (2001) and show that the fundamental insight that allows them to distinguish between statistical discrimination and preference-based discrimination depends on the specialized shapes of the best response functions in their model. Thus, the test that they employ is not robust to a range of alternative modeling assumptions. However, we also show that if statistical discrimination alone explains differences in the rate at which the vehicles of drivers of different races are searched, then search decisions should be independent of officer race. We then test this prediction using data from the Boston Police Department. Consistent with preference-based discrimination, our baseline results demonstrate that officers are more likely to conduct a search if the race of the officer differs from the race of the driver. We then investigate and rule out two alternative explanations for our findings: race-based informational asymmetries between officers and the assignment of officers to neighborhoods.