A Few Bad Apples? Racial Bias in Policing

By Felipe M. Goncalves, Steven Mello. The American Economic Review, 2017

165 citations recorded by the source corpus.

We estimate the degree to which individual police officers practice racial discrimination. Using a bunching estimation design and data from the Florida Highway Patrol, we show that minorities are less likely to receive a discount on their speeding tickets than White drivers. Disaggregating this difference to the individual police officer, we estimate that 42 percent of officers practice discrimination. We then apply our officer- level discrimination measures to various policy-relevant questions in the literature. In particular, reassigning officers across locations based on their lenience can effectively reduce the aggregate disparity in treatment (JEL H76, J15, K42)

Subfields: Law, Political Science and International Relations, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/dfcf8552bdb2429e99da92e7fd8e450e6e4fecb0

Citations in the corpus

• Impossible inference in econometrics: Theory and applications (2016, unknown): “…rely on the existence of bunching on “reported income” at the boundary of tax brackets to identify the elasticity of reported income wrt tax rates; Goncalves and Mello (2018) use bunching on “charged speed in traffic tickets” to separate lenient from non-lenient police officers and identify racial…”
• Racial Bias in Bail Decisions ⇤ (2018, unknown): “[36] Goncalves, Felipe, and Steven Mello, “A Few Bad Apples? Racial Bias in Policing.”
• Inaccurate Statistical Discrimination: An Identification Problem (2019, unknown): “To the first point, in some cases the underlying measures may be inaccurately recorded; for example, biased police officers are less likely to record a minority driver at a discounted speed than a white driver (Goncalves and Mello 2019).”