This post originally appeared on the Fraser Institute Blog, February 7th.
Crime rates and severity, as well as policing resources per person,
can differ substantially across Ontario municipalities. Naturally,
Ontarians want to know the relationship between crime and police
resources, particularly when police forces are asking for more money.
The
first chart below plots the number of police officers per 100,000
against the Crime Severity Index (CSI) in Ontario’s 30 largest
municipalities. As illustrated, there’s a positive relationship between
crime severity and police levels, which some might find counterintuitive
as one would think that more police means less crime. However, as has
been noted,
it’s sometimes difficult to sort out if more police officers result in
less crime or whether more crime leads to a call for more police
resources and an increase in police officers. Or even if more officers
and more crime are positively related because of more effective
reporting and control of crime.
While one could interpret this as evidence that more crime requires
more police, it remains that we must account for the aforementioned
bidirectional nature of the relationship and this ultimately requires
controlling for confounding factors before attempting to answer the
question as to whether the crime severity in these communities supports
the policing numbers.
The table below presents regression
estimates of the determinants of crime severity and policing using data
for the 30 largest Ontario municipalities in 2021 and with a methodology
similar to other studies. The regression models first estimate a
regression of the CSI on police officers per 100,000, average household
income in the municipality, and regional variables placing the
municipalities in either Northern, Eastern, Western, Central/GTA or the
Niagara Peninsula (with Central/GTA as the omitted regional comparison
variable). Northern municipalities are Thunder Bay and Sudbury. Eastern
municipalities are Ottawa and Kingston. Western municipalities include
London, Windsor and Chatham-Kent. The Niagara peninsula includes
Hamilton, St. Catharines and Niagara Falls. The remainder are in the
Central/GTA region.
To account for bidirectional or simultaneous effects, this regression
was used to estimate a fitted CSI from the estimated coefficients, and
it was then used in the police officers per 100,000 regression as the
crime variable. The remaining determinants in the police regression were
average residential property taxes for a three-bedroom bungalow as a
measure of potential community resources, population density (persons
per square kilometre), and then again, the set of regional variables,
which are included to capture regional differences that might uniquely
affect not only crime rates and severity but also the operation of
police services. For example, Indigenous peoples comprise a larger
population share of Northern Ontario and according to self-reported
information from the 2009 General Social survey (GSS), aboriginal
people were two times more likely than non-aboriginal people to
experience violent victimization
such as an assault, sexual assault or robbery (232 versus 114 incidents
per 1,000 population). The approach is essentially a simultaneous
equations technique and also uses weighted regression where observations
were weighted by municipal population size thereby providing greater
weight to larger population size municipalities.
The results show
that variables significantly affecting crime severity positively include
police officers per 100,000 population and the regional variable with
Northern and Western Ontario demonstrating higher crime rates relative
to the Central/GTA municipalities. As well, crime severity is negatively
and significantly related to average household incomes in the
municipality. Crime severity is also positively and significantly
related to police officers per 100,000, which can be interpreted either
as having more police officers per person results in more crime being
reported and dealt with, or more crime requires more police officers.
In
the police determinants regression, police officers per 100,000 is
positively and significantly related to crime severity (fitted) and
population density. The only regional variable that’s significant here
is Western Ontario and that variable shows that Western Ontario has
fewer police officers per 100,000 in relation to the Central/GTA region,
all other things given. Both regressions explain a high proportion of
the variation in the dependent variables.
Having established a
statistical relationship between policing resources and crime rates
after accounting for a number of confounding factors, the next step (in
the fourth and final post of this blog series) is to use these results
to see what predicted police staffing levels are like and how they
compare to actual levels.
