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Defund or Reform?
New Work Looks at What Investors (and Economists) Expect for the Future of US Policing
How do social uprisings against police brutality affect police vendors? The authors of a new NBER WP investigate and raise pointed questions for their colleagues about whether economists are well placed to understand the mechanisms at work.
How resilient is the US policing industry to mass uprisings against police brutality? In a new NBER working paper, economists Bocar Ba, Roman Rivera, and Alexander Whitefield tackle this question within the context of the historic racial uprisings in response to the police killing of George Floyd in 2020. After Floyd’s murder, a resurgent wave of prison and police abolitionists and decarceral feminists came together under the banner of the Black Lives Matter (BLM) movement and issued demands to “defund the police.” But what did investors and police vendors make of their calls?
Ba, Rivera, and Whitefield find both a substantial increase in stock market valuations and an improvement in firm fundamentals for firms involved in police contracting in the aftermath of the George Floyd and several other BLM-led uprisings. Their work suggests that firms contracting with police departments seize on the reformist urges fanned by social uprisings against police violence to increase the size of the policing sector. Ba and co-authors also compare the stock impacts of BLM-led uprisings to that of white supremacist or mass shooting incidents and find no such effect for firms contracting with the police, indicating a racialized dimension to the stock market responses to social uprisings.
After Floyd’s murder, a resurgent wave of prison and police abolitionists and decarceral feminists came together under the banner of the Black Lives Matter (BLM) movement and issued demands to “defund the police.”
The critical role of on-the-ground knowledge
One of the more interesting among the plethora of compelling elements in the paper is that Ba and authors turn their scrutiny inward to the economics discipline. To derive some intuition on the expected direction of the stock market effects, the authors conducted a survey of economists, asking them to forecast how the events of the summer of 2020 would impact policing–connected firms. On average, respondents believed that the uprisings after Floyd’s death would actually lead to a decrease in valuations for firms contracting with the police.What accounts for the misalignment of economists’ beliefs with the firms’ actual stock performance? According to Ba, one reason might be economists’ lack of engagement with activists “on the ground.” Despite the surge in visibility of the Defund movement, many activists also predicted that the popular preference for police reform (involving, e.g., greater use of body-worn cameras, predictive policing, surveillance, etc.) over abolitionism would actually lead to an increase in the size of the policing sector despite the inefficacy of many policing technologies in reducing police violence [1]. Ba’s experience listening to and talking with activists directly involved in the BLM uprisings led him to ask questions and pose hypotheses that economists otherwise may have found counterintuitive.
Figure: Economic Expert Predictions and Explanations of the Impact of George Floyd’s Murder
Notes: The figure presents economic experts’ forecasts on the impact of George Floyd’s murder on the stock performance of firms contracting with police. Each respondent provided a forecast for a portfolio of firms with ties to policing in the 21 days after the killing of George Floyd, where the pre-uprising price=100. The figure presents the average probabilities assigned to each forecast bin. Source: Ba, Rivera, and Whitefield (2023).
Seeing like the police
For early-career researchers, Ba’s experiences with data collection for the paper show the importance of collecting data from the perspective of the subject of study. Constructing a dataset on publicly traded firms contracting with the police was a demanding project: Ba combed through police magazines, websites, and police conferences to generate a dataset of publicly traded contractors of police departments. Rather than attempting to guess at which sorts of firms might be involved in police contracting, Ba simply let the police and the firms involved with the policing industry speak for themselves. This sort of inductive discovery process stands in contrast to many contemporary forms of scientific discovery in which researchers may start with a model of how they believe the world to operate. Instead, by going directly to the fora in which police and police contractors communicate and disseminate information among themselves, Ba, Rivera, and Whitefield were able to overcome a massive data collection challenge that could otherwise have impeded researchers from even producing a study of this kind.Econometrics as a rhetorical tool
In many respects, the results of this study may not seem novel. Activists have predicted that reformist impulses tend to lead to expansions in the policing industry, with police themselves tending to agree with that assessment. Considering that fellow economists are the primary audience for his research, though, Ba uses state-of-the-art empirical techniques such as synthetic difference-in-differences and synthetic control methods to causally demonstrate the stock impacts of the BLM uprisings in the wake of George Floyd’s murder at the hands of the police. Ba argues that his work shows how arguments grounded in econometrics and causal inference can be used as a rhetorical device to help persuade economists–an intellectual group with increasing influence over policing policy–about the promises and pitfalls of police reform.Note: Parts of this piece are informed by correspondence with Bocar Ba. The views in this article are those of the post author and should not necessarily be attributed to Standard Error or the authors of the working paper.
[1] For more on the ways in which police reform tends to generate policing expansion, see Naomi Murakawa (2014), The First Civil Right: How Liberals Built Prison America. On the inefficacy of technological solutions to policing such as body-worn cameras, see David Yokum, Anita Ravishankar, and Alexander Coppock (2019), “A Randomized Control Trial Evaluating the Effects of Police Body-worn Cameras,” Proceedings of the National Academy of Sciences. On the inefficacy of artificial intelligence technologies as they relate to policing, see Sankin, Aaron, and Surya Mattu (2023), “Predictive Policing Software Terrible at Predicting Crimes.” Wired.
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