Data Police

13 Mar

In a new paper, Chohlas-Wood et al. present three interesting points:

  1. Some of the major policing strategies have scant empirical support:
    • The impact of “pulling over drivers for minor traffic violations” (for the alleged purpose of “[preventing] criminal activity by intercepting individuals driving to and from the scene of a crime”) in Nashville was ~ 0 on serious crimes. (See Figures 1 and 2). To get a sense of the scale of the intervention: “In 2012, the MNPD conducted traffic stops up to ten times more frequently per capita than police departments in similar U.S. cities.”
    • The impact of stop and frisk in NYC on serious crime was also ~ 0. Again, to get a sense of the scale of the policy: “NYPD officers reported conducting nearly 700,000 Terry stops in 2011 alone, nearly 90% of which involved Black or Hispanic pedestrians.”
    • GS: None of this is terribly surprising. All over the world, very few policies are chosen as a result of careful data analysis. Why would policing be any different? My other prior based on looking at a fair bit of US crime data is that to a first approximation, all trends are national. When policing is local and trends are national, it suggests that the way policing is done is perhaps not the most important factor in preventing crime.
  2. Racial bias in who is stopped:
    • “[A]t any given level of risk Black and Hispanic individuals were frisked considerably more often than white individuals.” (NYC, 2011-2012)
    • “[T]he rates at which frisks recover weapons are significantly lower for frisked Black individuals (3.8%) and Hispanic individuals (3.4%) compared to white individuals (5.7%).” (From the Chicago Police Department (CPD) in 2017)
    • Contraband recovery rate for Blacks = 17%, Hispanics = 20%, Whites = 27% (Chicago 2014–2019, traffic stops.)
    • Contraband recovery rate for Blacks = 24%, Hispanics = 23%, Whites = 34% (Philadelphia 2014–2019; traffic stops.)
    • GS: I am impressed by the contraband recovery rates. Either the base rate of ‘contraband’ is super high or the police is very good. My hunch is the former but would love to see data. (See below.)
    • GS: If police select who to stop based on observable characteristics (conditional on location; what else can they rely on?), criminals may be incentivized to game that reducing the value of observables over time.
  3. Whack-a-mole nature of policing policies
    • “The settlement agreement with the ACLU took effect on January 1, 2016.85 For 2016, the CPD reported a total of approxi-mately 100,000 pedestrian stops, a sharp drop from the roughly 600,000 stops reported for 2015 (Figure 9).86 At the same time, the number of traffic stops made by the CPD began to rise. The CPD reported around 100,000 traffic stops in 2014 and a similar amount in 2015, but by 2019, the CPD reported nearly 600,000 traffic stops, with large increases occurring each year from 2016 to 2019. These traffic stops came to closely resemble the pedestrian stops that the CPD was contemporaneously under pressure to curtail. …”
    • Following a consent decree and settlement in 2011, pedestrian stops fell from more than 200,000 reported stops in 2014 (the earliest year for which we have data released publicly by the city) to fewer than 100,000 reported stops in each of 2018 and 2019, while traffic stops almost doubled in the same period”

p.s. Graham sends this:

“Back in the 1990s, it looked like the Supreme Court was going to run drug checkpoints, so Indianapolis started doing one. Drivers were stopped completely at random until the Supreme Court put an end to it.

The city conducted six such roadblocks between August and November that year, stopping 1,161 vehicles and arresting 104 motorists. Fifty-five arrests were for drug-related crimes, while 49 were for offenses unrelated to drugs. The overall “hit rate” of the program was thus approximately nine percent.

If you take this as a baseline, police are twice as good at finding contraband as random selection. If “contraband” just means drugs, then probably four times as good. So the baseline rate of contraband is high (a surprising number of people have warrants, drugs, and weapons) but police are also beating the odds.”

Chicago is not Indianapolis and 2015 is not 2000 but still valuable.

p.p.s. Graham also highlights an issue with Figure 2. Chohlas-Wood et al. plot the murder rate per 1k on the same graphs as vehicle stops per 1k. This naturally squishes the variation in the murder rate. The general rule is that you should avoid plotting variables that vary by orders of magnitude on the same graph. At any rate, doing so gives the appearance that the authors are putting a thumb on the scale.