Police officers often claim to be searching motorists so as to deter crime rather than to
catch as many criminals as possible. According to a new study by economists Jeff
Dominitz and John Knowles , published in the November 2006 issue of the
Economic Journal , if this is the case, unbiased police will focus their searches on
groups that would be most deterred by the threat of higher search rates. What's more,
unbiased policing no longer implies that guilt rates of motorists will be equalised
across racial groups.
Public outrage and legal retribution over racial profiling by police officers usually
revolves around the apparent injustice implied by motor vehicle search rate statistics.
When the rate at which a motorist is singled out by police turns out to be far higher
for black motorists than for whites, both the press and the courts see evidence of racist
police practices.
But according to a recent line of economic research, the public may be barking up the
wrong tree, statistically speaking: these studies argue that racially imbalanced search
rates do not imply racist policing. A far better indicator of racism may be the fraction
of searched motorists who police find carrying contraband, usually drugs and guns.
The study by Professors Dominitz and Knowles shows how this approach can be
applied in cases where the police claim to be searching motorists in order to minimise
crime.
The original work in this line – by Knowles, Nicola Persico and Petra Todd – argued
that if the job of the police is to catch as many guilty motorists as possible, then
racism against black people would be signalled by lower find rates when the police
searched black motorists. Unbiased police would see that they could catch more guilty
drivers by spending less time searching black motorists and searching more whites
instead.
When these researchers examined the court-mandated collection of search statistics by
Maryland state troopers, they found that although black people were three times as
likely as white people to be searched, the find rates were the same for blacks and
whites. They argued that this finding indicates the police were not racially biased, and
that black motorists had a higher tendency to carry contraband. (This is because the
threat of search deters motorists from carrying contraband; black motorists, if
searched at a higher rate, would respond by carrying drugs or guns less often.)
Equality of find rates appears, however, to be the exception rather than the rule. More
generally, find rates are substantially lower for minority motorists. Recent examples
include Missouri and Florida, where state-wide hit rates on Hispanic motorists were
about half that of white motorists; Minneapolis, where these searches were just over
one-third as successful; and Pennsylvania, where these searches were less than twothirds
as successful.
Less extreme but still substantial disparities are found when comparing searches of
black motorists to those of white motorists in these jurisdictions. If police officers
were indeed supposed to be maximising find rates, then these statistics would indicate
widespread discrimination against black motorists.
In the new study, Dominitz and Knowles argue that in many cases the police claim to
be searching motorists in order to deter crime, rather than to catch as many criminals
as possible. In such cases, unbiased police focus their searches on the group that
would be most deterred by the threat of higher search rates. Unbiased policing no
longer implies that guilt rates of motorists will be equalised across groups, so the
question becomes a matter of finding conditions under which a lower find rate for
black motorists still indicates racism.
The analysis by Dominitz and Knowles reveals an interesting implication: the ‘crimeminimisation'
defence hinges on how similar members of a given group are to each
other in their tendency to be deterred from crime. If the police search black motorists
at a higher rate, and these searches result in lower find rates, then racism can be
inferred if the white motorists are more similar to each other than are black motorists.
The reason is that the more similar are members of a group, the more effective will be
drug interdiction efforts targeted towards that group – so unbiased, crime-minimising
police would never choose to search more intensely a group that is more disparate in
terms of crime tendency unless that group was carrying contraband at a higher rate
than the rest of the population.
Similarity can be measured using characteristics that predict crime but are not
immediately visible to the police, such as income, marital status and employment.
While the new study does not take a stand on whether crime-minimisation is more
prevalent than arrest-maximisation, the results imply that the new find-rate approach
may be more widely applicable than the previous research suggests.
ENDS
Notes for editors : ‘Crime Minimisation and Racial Bias: What Can We Learn from
Police Search Data?' by Jeff Dominitz and John Knowles is published in the
November 2006 issue of the Economic Journal .
Jeff Dominitz is a senior economist at the RAND Corporation in Arlington, Virginia.
John Knowles is an assistant professor in the department of economics at the
University of Pennsylvania.
For further information : contact Jeff Dominitz on +1-703-413-1100 (email:
dominitz@rand.org ); John Knowles on +1-215-888-6530 (email:
jknowles@econ.sas.upenn.edu ); or Romesh Vaitilingam on 07768-661095 (email:
romesh@compuserve.com).