Crime and Inflation: Preliminary
Cross-National Evidence
Richard Rosenfeld
University of Missouri – St. Louis
USA
Inflation is the cruelest tax.
Anon
New Consensus?
• Recent US research reveals robust effects
of changing economic conditions on
crime rates
• Beyond the unemployment rate: GDP,
wages, consumer sentiment
• Direct effects limited to property crime;
indirect effects on violent crime
Great Recession
• Unemployment rose, economic growth
stalled, consumer sentiment plunged
during 2008-09 recession
• Crime rates fell
• Resurgence of the “consensus of doubt”
Was the Great Recession Different?
• Unlike in previous recessions, inflation rates at
historic lows
– Prices dropped in 2009 for first time in over 50 years
• Anecdotal evidence of inflation – crime
connection
–
–
–
–
1930s: price deflation
1950s: low inflation
1960s: rising inflation
1970s: stagflation
Falling crime rates
Rising crime rates
Prior Research
• Scattered US studies of inflation effects
on crime
• All show significant positive effect
• Little theoretical development
• No cross-national research
Inflation vs. Other Indicators of
Economic Adversity
• More widespread
• More immediate
• Closer relationship to demand for stolen
goods
Logic Model: Inflation and the Market
for Stolen Goods
• Supply
– Offenders sell or trade goods they do not consume or
give away
– Offenders respond to incentives, including demand for
stolen goods
• Demand
– Consumers “trade down” as prices rise
– Stolen goods are “inferior goods”: demand increases
as prices rise (or aggregate income falls)
– Acquisitive crime rises with increases in demand for
stolen goods
Inflation and Violent Crime
• Trafficking stolen goods risky business
• Underground markets “stateless”
locations
• Violence potent enforcement mechanism
Research Issues
• Are year-over-year changes in crime related to
inflation?
• Is the relationship between crime and inflation
nonlinear?
• Do former communist nations affect the
relationship between inflation and crime?
• Are the effects of inflation on crime independent
of those of GDP and unemployment?
• Does inflation condition the effect of
unemployment on crime?
Data and Methods
• DVs: Homicide, Robbery, and Burglary Rates for 20
Nations, 1990 – 2010
– European Sourcebook of Crime and Criminal Justice
Statistics
– Eurostat (2008-10)
• IVs: Inflation, unemployment, GDP per cap, nation and
period effects
– World Bank
– International Monetary Fund
• Fixed effects panel models with panel corrected
standard errors
– Variables first-differenced, except where noted
Sample
Austria
Bulgaria
Denmark
England & Wales
Estonia
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Netherlands
Northern Ireland
Norway
Poland
Scotland
Sweden
Switzerland
United States
Summary Descriptive and Bivariate
Results
Homicide and Inflation Rates for 20 Nations,
1990 - 2010 (Z Scores)
2.50
Homicide
2.00
Mean
Sd
1.50
Inflation
2.49
.60
Mean
Sd
2.46
.98
1.00
0.50
0.00
-0.50
-1.00
-1.50
r = .41
-2.00
-2.50
-3.00
1990
1995
2000
2005
2010
Figure 2. Robbery and Inflation Rates for 20 Nations,
1990 - 2010 (Z Scores)
2.50
Robbery
Mean
110
Sd
21
2.00
1.50
Inflation
Mean
Sd
2.46
.98
1.00
0.50
0.00
-0.50
-1.00
-1.50
r = .68
-2.00
-2.50
-3.00
1990
1995
2000
2005
2010
Figure 3. Domestic Burglary and Inflation Rates for 20
Nations, 1990 - 2010 (Z Scores)
2.50
Burglary
Mean
398
Sd
63
2.00
1.50
Inflation
Mean
2.46
Sd
.98
1.00
0.50
0.00
-0.50
-1.00
-1.50
r = .61
-2.00
-2.50
-3.00
1990
1995
2000
2005
2010
Table 1. Regression Results for Yearly Change in Homicide, Robbery,
a
and Burglary Rates in 20 Nations, 1990 – 2010
___________________________________________________________
Homicide
Robbery
Burglary
___________________________________________________________
b
Inflation
.021
.033**
.046**
(.013)
(.012)
(.014)
2
R
.105
.197
.177
Obs.
400
400
397
___________________________________________________________
a
Fixed effects panel models. Nation and year effects suppressed. Variables in natural
logs. Panel corrected standard errors in parentheses.
b
Yearly percentage change in consumer prices.
** p < .01 * p < .05
Table 2. Regression Results for Residual Change in Homicide, Robbery,
a
and Burglary Rates in 20 Nations, 1990 – 2010
___________________________________________________________
Homicide
Robbery
Burglary
________________________________ ___________________________
Crime rate t-1
.630**
.918**
.746**
(.069)
(.040)
(.048)
Inflationb
.029*
.032**
.034**
(.012)
(.012)
(.013)
2
R
.946
.954
.932
Obs.
400
400
397
___________________________________________________________
a
Fixed effects panel models. Nation and year effects suppressed. Variables in natural
logs. Panel corrected standard errors in parentheses.
b
Yearly percentage change in consumer prices.
** p < .01 * p < .05
Crime as a Non-Linear Function of
Inflation
Burglary Example
Estimated Yearly Change in Burglary Rate in 20 Nations by
Values and Percentiles of Inflation Rate, 1990 - 2010
2
28.1
0
-2
-4
10.5
-6
Inflation Rate
4.1
-8
-10
-12
.5
.9
5th
10th
1.6
25th
2.4
Inflation Percentile
50th
75th
90th
95th
Multivariate Results by Crime Type
Table 3. Regression Results for Yearly Change in Homicide Rates in 20 Nations,
a
1990 – 2010
_________________________________________________________ ______________
Model 1
Model 2
Model 3
Model 4
________________________________________________________ _______________
Former communist
-.048
-.007
-.019
-.076
nation
(.037)
(.057)
(.058)
(.042)
b
Inflation
.021
-.006
-.008
-.015
(.013)
(.018)
(.018)
(.018)
Inflationsqu
--.008*
.008*
.006
--(.003)
(.003)
(.003)
GDPpercap
----.229*
.260**
----(.107)
(.098)
Unemployment
----.057
-.050
----(.063)
(.080)
Inflation x
------.062**
unemployment
------(.022)
2
R
.105
.121
.130
.145
Obs.
400
400
400
400
_____________________________________________________ __________________
a
Fixed effects panel models. Nation and year effects suppressed. All variables in natural
logs except former communist nations. Panel corrected standard errors in parentheses.
b
Yearly percentage change in consumer prices.
** p < .01 * p < .05
Table 4. Regression Results for Yearly Change in Robbery Rates in 20 Nations,
a
1990 – 2010
_______________________________________________________________________
Model 1
Model 2
Model 3
Model 4
_____________________________________________________ __________________
Former communist
-.074
-.011
.014
-.078
nation
(.046)
(.045)
(.042)
(.049)
b
Inflation
.033**
-.005
-.002
-.008
(.012)
(.013)
(.013)
(.013)
Inflationsqu
--.011**
.009**
.007*
--(.003)
(.003)
(.003)
GDPpercap
-----.258**
-.235**
----(.092)
(.088)
Unemployment
----.094
.012
----(.049)
(.062)
Inflation x
------.048**
unemployment
------(.018)
2
R
.197
.240
.270
.282
Obs.
400
400
400
400
_______________________________________________________________________
a
Fixed effects panel models. Nation and year effects suppressed. All variables in natural
logs except former communist nations. Panel corrected standard errors in parentheses.
b
Yearly percentage change in consumer prices.
** p < .01 * p < .05
Table 5. Regression Results for Yearly Change in Burglary Rates in 20 Nations,
a
1990 – 2010
_______________________________________________________________________
Model 1
Model 2
Model 3
Model 4
_______________________________________________________________________
Former communist
-.043
-.107
-.092
-.096
nation
(.090)
(.075)
(.070)
(.071)
b
Inflation
.046**
-.007
-.004
-.002
(.014)
(.016)
(.016)
(.016)
Inflationsqu
--.016**
.013**
.014**
--(.004)
(.004)
(.004)
GDPpercap
-----.341**
-.350**
----(.109)
(.108)
Unemployment
----.078
.109
----(.055)
(.062)
Inflation x
-------.017
unemployment
------(.023)
2
R
.177
.251
.286
.287
Obs.
397
397
397
397
_______________________________________________________________________
a
Fixed effects panel models. Nation and year effects suppressed. All variables in natural
logs except former communist nation. Panel corrected standard errors in parentheses.
b
Yearly percentage change in consumer prices.
** p < .01 * p < .05
Discussion
• Crime is a nonlinear function of inflation
• Inflation effects are small but robust
• Inflation conditions the effect of
unemployment on homicide and robbery, but
not burglary
• Economic growth has sizable and robust
effects on crime
– Positive effect of growth on homicide needs
further exploration
Next Steps
• Add other economic indicators
– Consumer sentiment
– Poverty, inequality
• Add other controls
– Age composition
– Divorce rate
– Urbanization