Racial bias in police shooting

23 Jul, 2016 at 18:23 | Posted in Politics & Society, Statistics & Econometrics | 3 Comments

roland-fryerRoland Fryer, an economics professor at Harvard University, recently published a working paper at NBER on the topic of racial bias in police use of force and police shootings. The paper gained substantial media attention – a write-up of it became the top viewed article on the New York Times website. The most notable part of the study was its finding that there was no evidence of racial bias in police shootings, which Fryer called “the most surprising result of [his] career”. In his analysis of shootings in Houston, Texas, black and Hispanic people were no more likely (and perhaps even less likely) to be shot relative to whites.

Fryer’s analysis is highly flawed, however … Fryer was not comparing rates of police shootings by race. Instead, his research asked whether these racial differences were the result of “racial bias” rather than merely “statistical discrimination”. Both terms have specific meanings in economics. Statistical discrimination occurs when an individual or institution treats people differently based on racial stereotypes that ‘truly’ reflect the average behavior of a racial group. For instance, if a city’s black drivers are 50% more likely to possess drugs than white drivers, and police officers are 50% more likely to pull over black drivers, economic theory would hold that this discriminatory policing is rational …

Once explained, it is possible to find the idea of “statistical discrimination” just as abhorrent as “racial bias”. One could point out that the drug laws police enforce were passed with racially discriminatory intent, that collectively punishing black people based on “average behavior” is wrong, or that – as a self-fulfilling prophecy – bias can turn into statistical discrimination (if black people’s cars are searched more thoroughly, for instance, it will appear that their rates of drug possession are higher) …

Even if one accepts the logic of statistical discrimination versus racial bias, it is an inappropriate choice for a study of police shootings. The method that Fryer employs has, for the most part, been used to study traffic stops and stop-and-frisk practices. In those cases, economic theory holds that police want to maximize the number of arrests for the possession of contraband (such as drugs or weapons) while expending the fewest resources. If they are acting in the most cost-efficient, rational manner, the officers may use racial stereotypes to increase the arrest rate per stop. This theory completely falls apart for police shootings, however, because officers are not trying to rationally maximize the number of shootings …

Economic theory aside, there is an even more fundamental problem with the Houston police shooting analysis. In a typical study, a researcher will start with a previously defined population where each individual is at risk of a particular outcome. For instance, a population of drivers stopped by police can have one of two outcomes: they can be arrested, or they can be sent on their way. Instead of following this standard approach, Fryer constructs a fictitious population of people who are shot by police and people who are arrested. The problem here is that these two groups (those shot and those arrested) are, in all likelihood, systematically different from one another in ways that cannot be controlled for statistically … Properly interpreted, the actual result from Fryer’s analysis is that the racial disparity in arrest rates is larger than the racial disparity in police shootings. This is an unsurprising finding, and proves neither a lack of bias nor a lack of systematic discrimination.

Justin Feldman

3 Comments

  1. The notion of statistical discrimination seems weird. If crime statistics show that group A has more often been found in possession than group B, it is tempting to focus on group A. But if the statistic was generated by police already focussing on group A, one has some positive feedback between expectation and the statistic. Alternatively one might wish to establish the ‘true’ rates, but this is very difficult.

    In the UK, I would say that if indeed group A were more often in possession than others it would be best to try and develop more precise indicators. Personally, I would also draw a distinction between initial suspicion and stopping. Thus in some cities I might think it reasonable for a police patrol to follow a group A car for a short while, but not to stop them unless there were some actual sign, such as driving erratically.

    • Yes, indeed, ‘statistical discrimination’ is in many regards ‘weird.’ Not the least because when using it, you can more or less conjure away a lot of ‘real’ discrimination by defining it as ‘statistical’ (I had a couple of blog posts on this some years ago). E. g. — Women are not wage discrimnated against, it just so happens that they work in sectors where ‘average’ wages are low …

  2. The choice of drug possession statistics is unfortunate, because Blacks are not more likely to possess or use drugs than Whites. The fictitious example follows racial stereotypes.

    Also, Feldman ignores the tension between the interest of the individual policeman to make arrests and the ideals of civil rights and equality before the law.

    And, something he does not mention, but seems significant to me, in the encounters studied, white suspects were more likely to attack the policeman than black suspects. One reason, perhaps, might be that black males are more docile in their interactions with police because of their rational fear of being shot or abused.


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