Recent studies have examined racial disparities in stop-and-frisk, a widely employed but controversial policing tactic. The statistical evidence, though, has been limited and contradictory. We investigate by analyzing three million stops in New York City over five years, focusing on cases where officers suspected the stopped individual of criminal possession of a weapon (CPW). For each CPW stop, we estimate the ex-ante probability that the detained suspect would have a weapon. We find that in 44% of cases, the likelihood of finding a weapon was less than 1%, raising concerns that the legal requirement of "reasonable suspicion" was often not met. We further find that blacks and Hispanics were disproportionately stopped in these low hit rate contexts, a phenomenon largely attributable to lower thresholds for stopping individuals in high-crime, predominately minority areas, particularly public housing. Even after adjusting for location effects, however, we find that stopped blacks and Hispanics were still less likely than similarly situated whites to possess weapons, indicative of racial bias in stop decisions. We demonstrate that by conducting only the 6% ex-ante highest hit rate stops, one can both recover the majority of weapons and mitigate racial disparities. Finally, we develop stop heuristics that can be implemented as a simple scoring rule, and have comparable accuracy to our full statistical models.
This work is joint with Justin Rao (Microsoft) and Ravi Shroff (NYU).A draft of the paper can be downloaded here: https://5harad.com/papers/frisky.pdf