Assessing the impact of economic and demographic change on property crime rates in Western Canada

This research investigates the links between economic, demographic, and crime rate changes in Western Canada. The study finds that increases in household incomes and alcohol sales per capita, and decreases in unemployment rates, coincide with decreases in rates of property crime. Increases in migration turnover and changes in police reporting methods also affect property crime rates. The recent rise in property crime rates in the west is linked to the economic slowdown following the drop in oil and resource prices.

52
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ORIGINAL RESEARCH
Assessing the impact of economic and
demographic change on property crime rates
in Western Canada
Stuart Wilson*
ABSTRACT
Western provinces have experienced tremendous change over the last few decades, with oil booms and busts, with larg
international and interprovincial movement of workers and families, and with rising and declining property cri
rates. What are the links between these economic, demographic, and crime rate changes? I investigate these links for
Western Canada over the period from 1968 to 2015. Empirical results suggest that increases in household incomes and
alcohol sales per capita, and decreases in unemployment rates, all signs of improved economic prosperity, coincided
with decreases in rates of property crime. Increases in migration turnover (both inward and outward migration) put
upward pressure on rates of property crime. In addition, changes in police reporting methods and categorization have
had dramatic effects on official rates of property crime: the change from UCR1 to UCR2 reporting methodology caused
rates of property crime to rise by between 18 per cent and 30 per cent in 1998, and changes in police reporting method
2003 caused property crime rates to rise again, by between 5 per cent and 16 per cent in 2003, for the western provinc
The recent rise in rates of property crime in the west is closely linked to the economic slowdown following the drop in
oil and resource prices, and should migration turnover rates remain high as people move seeking better opportunities,
property crime rates will remain high. Policymakers and criminal justice professionals may be advised and reminded
of the effect of these economic and demographic changes, as well as the effect of reporting changes, on official rates
property crime.
Key Words Crime rate trends; economic growth; demographic change; police reporting.
Journal of CSWB. 2018 Oct;3(2):52-58 www.journalcswb.ca
INTRODUCTION
Crime rates trended downwards from 2003 to 2013 in western
Canada, coinciding with an international resource boom.
In particular, Saskatchewan experienced sharp increases
in resource development, household income, and large in-
migration movements, from both other provinces and nations,
during a period termed the “Saskaboom”. Rapid economic
and demographic change can have various effects on crime.
Newcomers may have different behaviours and propensities
to commit certain types of crimes. Improved employment
outcomes of young males may reduce criminal activity.
Inequalities in employment, incomes, and housing may lead
to increased crime. Over the past few years with the decline
in oil prices and revenues, some western Canadian provinces
have experienced poor economic growth and increasing
unemployment rates. What influence have demographic and
economic changes had on crime rate patterns in the western
Canadian provinces?
The economic factors that have been found to influence
crime include changes in unemployment, in incomes, in
inflation, in inequality, and in alcohol consumption (Cook
& Zarkin, 1985; Raphael & Winter-Ebmer, 2001; Savoie, 2008;
Pernanen, Cousineau, Brochu et al., 2002; Bunge, Johnson,
& Balde, 2005, Andresen, 2013 among others). Research
investigating the demographic factors that influence crime
have tended to concentrate on the youth and migrant popu-
lations (Butcher & Piehl, 1998; Bunge et al., 2005; Kitchen,
2007; Stevens, Odynak, Brazil et al, 2011; Plecas, Evans, &
Dandurand, n.d.). For more extensive reviews of the influ-
ences on crime, readers are encouraged to refer to Levitt
(2004), Albertson & Fox (2012), Farrell, Tilley & Tseloni (2014),
Tonry (2014), and Wilson, Sagynbekov, Pardy et al. (2015).
Tonry (2014) wrote that overall, there may be a role for
economic and demographic forces in explaining property
crime rate patterns over time, but little support for their influ-
ence on violent crime rate patterns. Recent work by Wilson
(2017) supported this assessment by showing that economic
Correspondence to: Stuart Wilson, Department of Economics, University of Regina, 3737 Wascana Parkway, Regina, SK S4S 0A2, Canada.
E-mail: [e-mail]
Journal of
COMMUNITY SAFETY & WELL-BEING

IMPACTS OF ECONOMIC/DEMOGRAPHIC CHANGE ON PROPERTY CRIME RATES, Wilson
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and demographic change could help explain only minor
changes in rates of violent crime, but may help explain up to
40 per cent of the changes in rates of property crime in west-
ern Canadian provinces over the last five decades. This article
further focuses on assessing the economic and demographic
influences on property crime in western Canada.
METHODS
Police-reported crime data are available for Canadian prov-
inces starting in 1962. The rates of property crime from 1962
to 2015 are depicted in Figure 1. Bunge et al. (2005) conducted
time-series analyses on the influences on crime over 1962 to
2003 for Canada as a whole. This study serves as an extension
of their work, with a larger time period, and with a larger
dataset by pooling together data for the five provinces west
of Quebec in a panel analysis.1 This study also serves as an
extension of Wilson (2017) in three ways: (i) some explanatory
variables, including inflation, were dropped due to statistical
insignificance; (ii) the model allows for a singular focused
effect of migration turnover on property crime, motivated
by results which suggested that increases in interprovincial
and international migrant movement, both inward and out-
ward, had similarly positive impacts on property crime, and;
(iii) the analysis incorporates data from the more recent
period characterized by low resource prices.
The relationship between rates of property crime and
the economic and demographic variables for the panel of
five provinces (British Columbia, Alberta, Saskatchewan,
Manitoba, and Ontario) is investigated using a linear panel
model. The set of provincial economic and demographic
variables used in the analysis are described in Table 1. These
variables are real household disposable income per capita,
the unemployment rate, per capita alcohol sales, the youth
share of the population, and the migration turnover rate
(the sum of both in- and out-migration, as a proportion of
the total population). Provincial data for unemployment
rates are only available starting in 1967. These variables all
exhibit the property of nonstationarity, and therefore require
transformation using logarithmic first differences to allow for
estimation to overcome the problems of stochastic trends and
spurious regressions; as such, this study may not be directly
compared to that of Andresen (2013), which presented results
from a panel study with variables in their undifferenced
logarithmic forms.2 In addition, a set dummy variables was
used to account for additional province-specific trends and
shifts in rates of property crime. The effective time period of
the study is from 1968 to 2015.
RESULTS
The results from the panel regressions for the growth in the
rates of property crime over the study period are presented in
Table 2. The first regression model includes contemporaneous
and lagged independent variables, and a common constant
term but with no other dummy variables. The estimates
from that model are presented in Column 2, are identified as
Model 1, and indicate how much variation may be accounted
for solely by variation in the independent variables. The
estimated fit of this first model is relatively low, with an
overall R2 of 0.18, indicating that the explanatory variables
used in this regression may account for a small portion of
the variation in the growth of the rates of property crime
over the sample. Only one variable, the unemployment rate,
was statistically significant in the regression. The second
regression model includes province-specific constant terms,
and province-specific one-period and trend shift dummies
which allow for trend changes that occurred around 1990, for
an upward shift in 1998 with the movement to UCR2 report-
ing, and also for changes around 2003 (see notes to Table 2).
The estimates from this model are identified in Column 3
as Model 2. This second regression performed much better
in terms of the R2 statistic. The inclusion of these province-
specific dummy variables allows the model to measure the
impact of economic and demographic changes on property
crime rates with better precision, and all of the economic and
demographic variables have statistically significant effects on
property crime rates, either contemporaneously, with lagged
effects, or both. This model indicates how important it is to
include these province- and time-specific effects to better
identify the relationship between economic and demographic
change, and changes in rates of property crime.
Influence of Economic and Demographic Change on
Rates of Property Crime
The estimates provided in Table 2 for Model 2, of the impact
of economic and demographic changes on rates of property
crime, will first be explained using a few illustrative exam-
ples. The coefficient estimates of -0.1214 and -0.2232 for Δyt
and Δyt-1 suggest that for every one percentage point increase
in the growth rate of real disposable household income per
capita, the growth rate of the rate of property crime decreased
by 0.12 percentage points, and the growth rate of the rate of
property crime decreased by 0.22 percentage points in the
following period, all else equal. The coefficient estimates of
1.1038 and 0.1322 for Δyouth-sharet and Δyouth-sharet-1suggest
1 Panel dataset estimation provides several advantages over individual
time series estimation, including “more informative data, more variabil-
ity, less collinearity among the variables, more degrees of freedom and
more efficiency” (Baltagi, 2005, p. 5).
2 Nonstationary series, including the undifferenced series in this analy-
sis, exhibit stochastic trends which may lead such series to appear to
be related over the long run when they aren’t, resulting in a spurious
regression. For more information on issues regarding nonstationar-
ity and spurious regressions, please refer to Stock and Watson (2003,
pp. 460–462).
FIGURE 1Rates of property crime, four western provinces and Ontario,
1962–2015.
- ‐
1,000.00
2,000.00
3,000.00
4,000.00
5,000.00
6,000.00
7,000.00
8,000.00
9,000.00
10,000.00
1962
1965
1968
1971
1974
1977
1980
1983
1986
1989
1992
1995
1998
2001
2004
2007
2010
2013
Incidents per 100,000 residents
British Columbia
Alberta
Saskatchewan
Manitoba
Ontario

IMPACTS OF ECONOMIC/DEMOGRAPHIC CHANGE ON PROPERTY CRIME RATES, Wilson
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that for every one percentage point decrease in the growth
rate of the share of youth aged 15 to 24 years to the total
population, the growth rate of the rate of property crime
decreased by 1.10 percentage points, and the growth rate of
the rate of property crime decreased by 0.13 percentage points
in the following period, all else equal. While the other specific
estimates themselves are of importance, it is appropriate and
convenient to continue the analysis focusing on the direction
of the influences of these variables on rates of property crime
for the purpose of simplicity and ease of presentation.
As noted in one of the illustrative examples above, the
empirical results indicate that there were negative contem-
poraneous and lagged relationships between changes in
disposable income and changes in rates of property crime.
In addition, there was a strong positive contemporaneous
link between unemployment rates and property crime rates;
however, that impact was partially muted with a counter-
acting negative effect of lagged unemployment rates. These
results strongly suggest that improvements in the economy
coincided with declines in rates of property crime, and that
increases in property crime rates occurred during poor
economic conditions, supporting a motivational effect of the
economy on crime. Rates of property crime were also found
to be negatively linked with contemporaneous and lagged
changes in per capita alcohol sales. This result runs counter
to the hypothesis that alcohol consumption and crime are
positively linked, given a high proportion of crime is com-
mitted by individuals dependent and under the influence of
alcohol and drugs (Pernanen et al., 2002). However, alcohol
sales were positively correlated with disposable income, and
are more likely a sign of increasing wealth and responsible
alcohol consumption, so that these results reinforce the infer-
ence that increasing prosperity leads to declines in the rate
of property crime.
Demographic change also had an influence on rates of
property crime. Changes in the proportion of youth in the
population and in the rate of migration turnover (both of
inward and outward migration) were positively linked to
changes in property crime. These results reinforce the age–
crime link with adolescents committing a high proportion
of crime in society (Gannon, Mihorean, Beattie et al., 2005;
Brennan, 2012), and over the past decade while property
crime rates have been falling, the proportion of youth in the
population has also been in decline. While much international
work has focused on the impact of immigrant populations on
crime rates, in the Canadian context there is only suggestive
TABLE IData description
Variable
Symbol for
Logarithmic Form Description Sources
Property Crime Rate pcr Provincial rate of property crime, incidents per
100,000 residents as of July 1.a
CANSIM Tables 252-0001 (1962-1997);
252-0051 (1998-2015); 051-0026 (1962-
1970),- 0001 (1971-2015)
Per Capita Income y Real provincial household disposable income
per capita.
CANSIM Tables 384-5000 (1962-2013);
384-0040 and 051-0051 (2014-2015)b
Unemployment Rate ur The provincial unemployment rate. CANSIM I CHASS I CHASS Labels
D45076,45097,45118, 45139, 45160
(1967-1975)
CANSIM Table 282-0002 (1976-2015)
Per Capita Alcohol
Sales
alcohol_sales Real value of provincial alcohol sales per capita,
by March 31 fiscal year endc
CANSIM Tables 183-0006; 183-0023
(2014-2015 - see Note 3); 051-0026
(1962-1970), 051-0001 (1971-2015)
Youth Population
Share
youth_share The provincial ratio of the population aged 15 to
24 as of July 1 that year divided by the
population as of July 1 of that year.
CANSIM Tables 051-0026 (1962-1970),
051-0001 (1971-2015)
Migration Turnover
Rate
mig_turnover Migration Turnover Rate: The provincial ratio of the
number of international immigrants plus emigrants
plus interprovincial in-migrants plus interprovincial
out-migrants that year divided by the
population as of July 1.
CANSIM Tables 051-0017 and 051-0037
(1962-2015); 051-0026 (1962-1970),
-0001 (1971-2015)
a Police-reported crime data are available starting in 1962, using the Uniform Crime Reporting Survey UCR1 definitions and crime categori
made available by Statistics Canada from 1962 to 2003. Statistics Canada currently releases police-reported crime data under UCR2 cod
from the UCR1 coding include more detailed offense categories, expanding from the three-digit coding in UCR1 to the four-digit coding in
offenses which were previously categorized in the “Other Criminal Code violations” category were re-categorized under UCR2 as violent o
crimes. The UCR2 data go back to 1998 and are considered as the official crime statistics. Statistics Canada has also released more comp
data using UCR1 methodology for the period from 1977 to 1997, with series similar to those released after 1997. For the purpose of this
UCR1 data was used from 1962 to 1997, and the UCR2 data was used from 1998 to 2014. The change in methodology at 1998, with a su
jump in many police-reported crime rates in 1998 compared to 1997, is important to note and to treat appropriately in the econometric a
b The two different data sources resulted in series discontinuities in 2014. Since the data for the 2014-15 period included earlier data, the s
differences was spliced starting in 2014 rather than the series in levels.
c Data is for fiscal years ending on March 31 of the given year. Since the data contain nine months of data from the previous year, regressi
conducted using the lead (t+1) which would contain nine months of data from that calendar year along with data from three additional m
following year, but did not yield statistically significant coefficients for these leads.

IMPACTS OF ECONOMIC/DEMOGRAPHIC CHANGE ON PROPERTY CRIME RATES, Wilson
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evidence that, over time, an increasing share of immigrants
may decrease rates of property crime (Zhang, 2014). Results
presented herein indicate that the migration turnover rate,
which measures the sum of inward and outward migration
movements, had an impact on the rate of property crime,
so that increasing migration turnover over the past decade
put upward pressure on rates of property crime. This raises
the question as to whether increasing migration turnover
presents criminals with increased opportunities for prop-
erty crime as people and their goods move in and out of the
community, or whether the migrants themselves commit
these acts.
Trend Changes and Jumps in Rates of Property Crime
Significant changes in the pattern of property crime rates
occurred around 1990, 1998, and 2003. The quantitative
impact of these changes is highlighted in Table 3. Up to
the late 1980s, rates of property crime in the five provinces
grew by between four per cent (Ontario) and seven per cent
(Saskatchewan) per year (the result of the combined impact of
the common constant identified in the second row of Table 3
and the additional province-specific constant term in the
third row). The growth trend in the rates of property crime
in all five provinces fell significantly around 1990, by between
seven and eight percentage points from previous rates of
growth (as indicated by the period- and province-specific
additions to the growth trend indicated in row four). This
was a major turning point in the evolution of property crime,
and coincided with the drop in the rate of total criminal code
violations in Canada which occurred after the peak in 1991.
The figures in the next row of Table 3 indicate the extent of
special one-period changes (jumps) in the growth rates of
property crime which occurred at the beginning of the trend
decline. These identify a significant one-period drop in the
rate of property crime for Manitoba in 1988 from a peak in
1987, and significant increases in the rates of property crime
for Ontario, Alberta, and British Columbia to peaks in 1991,
prior to the model-predicted trend decline in the rates.
Of particular interest are the one-period jumps in 1998
and 2003. The predicted rates of property crime for the five
provinces jumped by approximately 20 per cent in 1998. This
substantial change is attributed to the change in reporting
methodology, from UCR1 to UCR2 in 1998. Many offense
categories expanded in detail, and some offenses were re-
categorized from the “Other Criminal Code” category to
either of the property crime or violent crime categories under
UCR2 coding. Significant one-period, model-predicted jumps
in property crime rates above the trend decline also occurred
in 2003 in Manitoba (16%), Saskatchewan (16%), Alberta (9%),
and in British Columbia (11%), as indicated in the last row of
Table 3, and in Figure 1. This increase in rates of property
crime in 2003 has been attributed to changes in reporting
procedures “which make it easier for the public to report
minor crimes to the police” (Wallace, 2004:4). As an example,
the major increase of minor thefts in Winnipeg in 2003, and
of auto thefts in particular, was tied to the introduction of a
telephone reporting system by the Winnipeg Police Service
(Wallace, 2004:11). These types of reporting changes were
TABLE IIPanel estimates of the growth in the rate of property crimea
Δpcr
1968–2015
Δpcr
1968–2015
Regressors/Statistics Model 1b Model 2b
Δyt 0.0050 (0.1620) -0.1214 (0.0967)
Δyt-1 -0.0979 (0.1546) -0.2232 (0.0988)**
Δurt 0.1303 (0.0450)*** 0.1103 (0.0264)***
Δurt-1 -0.0396 (0.0458) -0.0589 (0.0266)**
Δalcohol_salest -0.1512 (0.1450) -0.1882 (0.0881)**
Δalcohol_salest-1 -0.1288 (0.1413) -0.1965 (0.0847)**
Δyouth_sharet 0.8700 (0.7869) 1.1038 (0.4644)**
Δyouth_sharet-1 0.4810 (0.7809) 0.1322 (0.457)
Δmig_turnovert 0.0387 (0.1019) 0.0798 (0.0561)
Δmig_turnovert-1 0.1388 (0.1020) 0.1275 (0.0554)**
ρˆ (ON; MB; SK; AB; BC) 0.26; 0.12; 0.11; 0.38; 0.24 0.10; -0.02; 0.13; 0.43; 0.16
Province-specific deterministic dummiesc No (only a common constant term) Yes (25)
R2 0.1843 0.6246
Test for significance of second lags
(t-2 variables)
χ2 (6) =7.93
(p-value= 0.1602)
χ2 (6) = 7.20
(p-value = 0.2063)
a The xtpcse command in STATA was used to produce these results, and allows for panel-corrected standard errors for the estimates, for h
for first order autocorrelation, and for correlation of errors across panels at a given point in time; the generalized least squares method in
was also used and yielded similar results to those presented herein, but does not produce a convenient and universally understood R2 statistic.
b Panel-corrected standard errors in parentheses; **, and *** denote coefficient is statistically significantly different from zero at the 95% a
confidence levels (two-tailed tests), respectively.
c Province-specific deterministic dummies include: province-specific constants, one-period dummies for 1988 (Saskatchewan, Manitoba), fo
British Columbia, Ontario), for 1998 and for 2003 (for all five provinces); period dummies for 1988–2015 (Saskatchewan, Manitoba), and f
(Alberta, British Columbia, Ontario).

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also experienced elsewhere. Tonry (2014) indicated that many
countries have changed how they report crime incidents, by
moving from an “output” system in which crime is officially
reported after police screening, to “input” systems, where
crime is officially reported with less police screening and
investigation. In 2002/03, the police-reported crime rate in
England and Wales rose by 10 per cent as a result of the shift
from an output to input system (Simmons & Dodd, 2003).
DISCUSSION
The empirical results suggest that rates of property crime
will decline with improvements in economic conditions and
increasing prosperity, with reductions in the share of youth
in the total population, and with reductions in migration
turnover, in the short term. Rates of property crime have risen
in Manitoba, Saskatchewan, Alberta, and British Columbia
over the past two years, and this corresponds to the drop in
oil prices and pause in the commodity boom, and a rise in
unemployment. If economic conditions continue to weaken
and if the unemployment rate continues to rise, then the prop-
erty crime rate is expected to continue to rise. If the degree
of migration turnover remains high as people move to seek
opportunities, it is expected that rates of property crime will
remain high relative to the rates in the early part of the last
decade. Policies that can strengthen the economy, in both
resource and non-resource sectors, and that provide busi-
nesses with a favourable climate to create jobs and decrease
unemployment, are especially welcome in difficult times,
given policymakers have limited influence over international
resource price changes. Policymakers and justice officials also
have limited influence over migrants’ decisions to relocate,
but they may be better prepared and able to formulate and
target additional crime prevention measures knowing that
population movements and economic slowdowns tend to
increase crime rates. The results presented herein also indi-
cate how crucial it is to incorporate relevant province- and
time-specific effects into the analysis to show that changes in
the economic and demographic variables are important, yet
incomplete, predictors for changes in rates of property crime.
The one-period growth rate changes which occurred in
1998 and in 2003 were substantial, leading to large upward
shifts in the rates of property crime in 1998, and again in
2003, as shown in Figure 1. These large and lasting increases
in rates of property crime have been attributed to changes in
crime categorization in the UCR2 coding, and to recording
practices as police have moved from output to input systems
of recording. Policymakers and justice professionals may be
advised and reminded of how changes in recording practices
and methods may have substantial effects on police-reported
crime rates, and to exercise caution when examining trends
over time. Comparisons of crime rates, between those in
the 1990s and those in the 2010s as an example, are not
advisable without taking into account these changes in
reporting methodology.
The shift from growing to falling rates of property crime
occurred in the late 1980s in Saskatchewan and Manitoba,
and in the early 1990s in British Columbia, Alberta, and
Ontario. This long-run trend shift has also been experienced
in most developed countries, and has yet to be conclusively
explained. Levitt (2004) examined the recent crime decline in
the US, and provided evidence to discredit some prominent
explanations and to conclude that the increased number
of police, the increase in incarceration, the diminished
crack cocaine problem, and the legalization of abortion
and reduction in unwanted births and child poverty were
the prominent causes of the US decline in crime since the
early 1990s. These explanations are not particularly useful,
however, for other nations experiencing similar transitions
in crime rate trends, but dissimilar changes in policing and/
or incarceration, and differing drug and abortion environ-
ments. Mishra & Lalumiere (2009) added to the literature by
suggesting that a decrease in risky behaviour among youth
contributed to the crime drop in the US and Canada, while
van Dijk, Tseloni & Farrell (2012) pointed also to the influence
of situational crime prevention initiatives as a possible factor
to the decline in crime. Farrell et al. (2014) tested the major
hypotheses proposed to explain the recent drop in crime
in industrialized nations, including those of Levitt (2004),
and concluded that the timing and patterns of the drop in
TABLE IIIProvince-specific deterministic dummiesa
Ontario Manitoba Saskatchewan Alberta British Columbia
Common constant (initial
growth rate trend)
0.0436 (0.0091)***
Additional constant term
(addition to the initial
growth trend)
N/A 0.0208
(0.0131)
0.0255
(0.0133)*
0.0129
(0.0178)
0.0109
(0.0093)
Period-specific addition
to growth trend
1991-2015
-0.0808 (0.0117)***
1988-2015
-0.0836 (0.0160)***
1988-2015
-0.0746 (0.0151)***
1991-2015
-0.0697 (0.0245)***
1991-2015
-0.0787 (0.0146)***
One-period additional
growth (1988 or 1991)
1991
0.1212 (0.0370)***
1988
-0.1316 (0.0538)**
1988
0.0016 (0.0446)
1991
0.1068 (0.0473)**
1991
0.1225 (0.0418)***
One-period additional
growth in 1998
1998
0.2066 (0.0370)***
1998
0.2969 (0.0537)***
1998
0.2175 (0.0428)***
1998
0.2350 (0.0461)***
1998
0.1740 (0.0461)***
One-period additional
growth in 2003
2003
0.0521 (0.0353)
2003
0.1559 (0.0534)***
2003
0.1573 (0.0423)***
2003
0.0850 (0.0465)*
2003
0.1086 (0.0412)***
a Panel-corrected standard errors in parentheses; *, **, and *** denote coefficient is statistically significantly different from zero at the 90%
99% confidence levels (two-tailed tests), respectively.

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crime in various countries could be best tied to the timing
and patterns of security improvements, and these security
improvements may have contributed to declines in many
crime types through spillover effects. Research continues
to better understand this important recent Canadian and
international long-run trend decline in crime.
CONCLUSIONS
This article provides an empirical assessment of the changes
in rates of property crime over the period from 1968 to 2015,
to uncover the impact of economic and demographic change
on rates of property crime in British Columbia, Alberta,
Saskatchewan, Manitoba, and Ontario. The results suggest
that increasing incomes and alcohol sales per capita, and
decreasing unemployment rates, all indicative of improved
economic conditions, coincided with declines in rates of
property crime. The results also suggest that a declining share
of youth to the total population coincided with decreases in
rates of property crime, while increasing migration turnover
(both inwards and outwards migration) put upward pres-
sure on rates of property crime. Both of these demographic
changes are typically experienced during times of improved
employment opportunities with counteracting effects on
property crime.
These findings help to explain how resource and eco-
nomic booms in the west helped bring down rates of property
crime, as well as to inform policymakers how the more recent
resource and economic slowdown has put upward pressure
on rates of property crime. In addition, the results presented
herein indicate the strong role changes in reporting practices
and methodology have had on official police-reported crime
statistics, of which policymakers and analysts must be aware
before characterizing crime rates in different periods, and in
considering policy changes. Lastly, while this article helps to
identify the quantitative nature of the change from growing
to declining rates of property crime that occurred in the late
1980s and early 1990s, the causes have not yet been fully iden-
tified. More research is needed to explore long-run trends in
rates of property crime, including the exploration of a role for
the timing and patterns of security improvements in Canada,
as well as for differences in the patterns of—and influences
over—the sub-categories of property crime.
ACKNOWLEDGMENTS
This work has been supported by resources and funding from
the Collaborative Centre for Justice and Safety, the Saskatchewan
Ministry of Corrections and Policing, and the Royal Canadian
Mounted Police F Division. This work is related to a project on
the economics of crime and corrections with financial assistance
from the Saskatchewan Ministry of Corrections and Policing, and
to a project on the impact of economic and demographic change
on crime and policing supported by and with financial assistance
from the Collaborative Centre for Justice and Safety and the RCMP
F Division. The author acknowledges encouragement and assistance
from Steve Palmer of the Collaborative Centre for Justice and Safety,
Brian Rector of the Research and Evidence-Based Excellence Branch
of the Saskatchewan Ministry of Corrections and Policing, and
from Nina Sahasrabuddhe of the RCMP F Division. Material in this
article was presented at the 13th WEA International Conference in
Santiago Chile, January 2017, and the author acknowledges feedback
from conference participants. The author also gratefully thanks the
editor and the anonymous reviewers of this Journal who provided
very helpful comments. Any errors of fact or interpretation remain
solely those of the author.
CONFLICT OF INTEREST DISCLOSURES
The author acknowledges funding support, but no editorial involve-
ment, from the Saskatchewan Ministry of Corrections and Policing
and the RCMP F Division. The content reflects the author’s sole
opinions and do not reflect those of the Saskatchewan Government
nor those of the RCMP. The author states that there are no known
conflicts of interest.
AUTHOR AFFILIATIONS
*Department of Economics, University of Regina, Regina, SK, Canada.
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