Brainstorming the Cost-Benefit Analysis of Policing

© NY Photographic (, content modified and licensed under  Creative Commons

© NY Photographic (, content modified and licensed under Creative Commons

What is the psychological cost of being stopped by a police officer? What are the potential privacy costs of using license-pla­­te readers?

Elsewhere in government, questions like these would be a standard part of cost-benefit analysis (CBA) — a common procedure that attempts to identify and weigh the full range of positive and negative consequences produced by a particular policy or program.

But despite its wide use in almost all areas of government, and its proven ability to help us better understand the effectiveness and impact of certain practices, CBA has only rarely been applied to policing.

To address this shortcoming, the Policing Project kicked off its efforts to bring cost-benefit analysis (CBA) to policing by hosting a roundtable discussion at NYU Law School in May 2016.

More than twenty academics, from a wide range of disciplines – including psychology, economics, criminology, political science, law, and sociology – gathered to discuss the best approach to changing this status quo. Specifically, the attendees brainstormed about ways to tackle the various methodological and practical obstacles to using CBA in the analysis of policing practices.

Attendees considered the following important questions: 1) what kinds of costs or benefits are typically overlooked when evaluating policing practices?; 2) how can we fairly and accurately put a dollar figure on difficult-to-quantify aspects of policing?; and 3) what research designs should we use to evaluate the effects of policing on society?

This roundtable was held as a prelude to further work the Policing Project will be doing in this area. With the generous support of the Laura and John Arnold Foundation, and partnership with the Police Foundation, we will be embarking on a two-year initiative to bring CBA to policing and to tackle some of the most complicated questions.