By Ash Ahmed
The murders of George Floyd and Breonna Taylor have put police departments across the country under unprecedented scrutiny; calls to reform, defund, and abolish the police have been at the forefront of protests and national media. Americans are beginning to rethink law enforcement's role in society, including many practices within departments that have gone unquestioned for decades.
Regardless of what changes are made, conversations regarding the future of policing must analyze the economics of policing. While policing is most commonly linked to the criminal justice system, it plays a significant role in the economy. From departments' budgets to economic inequality in communities, there are many important areas for research that can inform future decisions.
Police departments garner funds from multiple sources, including federal, state, and local governments. However, the vast majority of funding comes from local governments, composing 86% of total funding in 2017. Funds from the state tend to focus on highway patrols, while local funding is directed to departments (salaries, operations, equipment, etc.). Most data concerning police funding focuses on the general funds for cities and towns.
Where do those funds come from? The primary sources of revenue for general funds at both the local and state levels are taxes, with sales taxes and property taxes being the top two sources. However, a growing portion of revenue comes from fees and fines generated from "traffic stops, jaywalking… appearances in court," and other sources. For example, in Minneapolis, "other revenues, aids, and user fees" composed 33.6% of the 2016 general fund budget. Police departments, in particular, have increasingly relied on fees and fines as a result of uncertainty regarding tax cuts; unsurprisingly, this can result in a change in policing practices, where even minor offenses, such as not wearing a seat belt or speeding, can accumulate thousands of dollars in fees and fines. These charges are not distributed equally, with Black and low-income individuals paying the brunt of them. The result can be a vicious cycle where police forces prioritize money over justice, and fees and fines hamper individuals who were already in bad economic situations.
When comparing the police budgets of major cities, it is important to remember what specific measurements can and cannot tell us; the crime rate in a city, for example, cannot be reliably predicted based on local police expenditure per capita (this can vary significantly due to average salaries in a state). It is also inaccurate to compare cities based on total dollars spent on policing, as budget sizes vary considerably. One possible way to compare cities is by the percentage of their general fund spent on policing. The Center for Popular Democracy has gathered data from 2017 and 2020 outlining the discretionary funds that major cities allocated to police departments (this data was also used in a Statistica report). Although there was an increase in dollars spent on policing between 2017 and 2020, the percentage of the general fund spent on policing remained consistent for most cities.
Past reforms have largely avoided the question of reducing police budgets, opting instead for increased accountability in the form of body cameras and new training practices. Understanding the source of funds and their uses will be a critical step in future changes to policing.
Law enforcement and systemic racism are inextricably tied. While this can be seen from tragedies such as the deaths of unarmed Black Americans, discrimination is also prevalent in economic opportunities.
Disparities in incarceration rates, police stops, and many other areas between white Americans and Black Americans contribute to economic inequality, with Black Americans facing generational wealth gaps and wage gaps. In particular, policing can hinder communities from gaining many skills, jobs, and assets that can improve their economic situations.
What specific tools are to blame? Predictive policing algorithms have taken law enforcement agencies by storm in recent years; over 60 major departments contract companies to implement algorithms. However, multiple studies have found that the data sets used to predict which individuals are likely to commit a crime or what location a crime will be committed are filled with racial bias. Models rely on arrest rates, information regarding the socioeconomic background of individuals, and other factors informed by the racist actions of officers and institutions rather than actual crime reports. This creates a feedback loop when machine learning models base future predictions on flawed historical data, constantly reinforcing biases in the algorithms.
At a larger scale, "taste-based racial discrimination" in policing, which includes predictive policing algorithms, can create a cycle of economic inequality. When individuals are in bad financial situations, they live in neighborhoods with low-quality schools, a lack of public services, and higher pollution, all of which decrease economic opportunity and strengthen racial profiling amongst police officers.
Activists, police watchdog groups and legal experts have all proposed solutions to combat police violence and discrimination. In the case of predictive policing, a community organizer named Hamid Khan called out the LAPD for relying on problematic data sets. Liability insurance companies, who insure many departments for police brutality claims, could raise premiums or end coverage. Rather than having taxpayers pay for police misconduct, payouts could come directly from department budgets.
As the nation grapples with police brutality, understanding the economic impact of policing will help us formulate effective solutions. Policing is a complicated and multi-faceted issue, but further research can provide much-needed information to guide future decisions.