shown in this Table, property crime fell quite considerably over 2001–2006.
6
The criminology literature has not reached a consensus on the factors that explain this
drop, though possible explanations include changes in the age structure, shifts in heroin supply, reduced availability of fi rearms, and improved antitheft devices in new
motor vehicles. See, for example, Moffatt and Poynton 2006; Brickell 2008. Violent crime shows no such pattern.
The next four rows of Table 1 present the fraction of respondents that were victim- ized during the quarter before the interview and or during the two to four quarters
prior to the interview. Roughly 0.6 percent of our observations are violent crime vic- timization incidents within the previous quarter. 1.1 percent are victims two to four
quarters before the interview. Property crime is more prevalent with 2.1 percent of individuals having suffered a property crime in the previous quarter and 3.9 percent
in the two to four quarters before the interview. The identifying variation for these variables is roughly equally divided between cross- section and time, and the crime
rate from these self- reported surveys is of a similar magnitude to police- reported crime rates.
C. Data on Individual Characteristics
In Table 2 we summarize the individual characteristics of the respondents in our data, where we report in the fi rst column means and standard deviations for individuals
in the sample that are never victimized. We then distinguish between those who are victims of violent or property crime not necessarily mutually exclusive at some point
during 2001–2006. For the last two columns, all demographic and mental health mea- sures apply to previctimization periods—that is, using only the data prior to becoming
a victim as we consider mental health endogenous to victimization status.
The table entries suggest that, generally speaking, nonvictims and victims differ on a number of dimensions. Nonvictims are more likely to be older, have children
between 5–24 and are less likely to move out of their LGA. When breaking victims down into violent and property it becomes clearer that victims of violent crimes differ
much more from nonvictims than do victims of property crimes. This is particularly true for the mental well- being variables. Victims of violent crimes have, on average,
lower mental well- being. We can also see that there are signifi cant differences be- tween the two types of victims. Victims of violent crimes are younger, less educated,
have fewer children and lower mental and physical well- being than victims of prop- erty crimes. This table illustrates the importance of controlling for demographics in the
empirical analysis as well as focusing on changes in mental health rather than cross- sectional differences.
Our analysis also accounts for other time- varying characteristics known to affect mental well- being: the local area unemployment rate, local area average total income,
and the share of rainy days. The unemployment rate is included in order to capture the possibility that local economic booms or busts may affect both crime and mental well-
being. See, for example, Kapuscinski, Braithwaite, and Chapman 1998; Raphael and Winter Ebmer 2001. Average incomes may capture degrees of fi nancial stress as well
6. This stands in contrast to the United States, where property crime over this period did not change substantially.
Corna gl
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119
Table 2 Summary Statistics
Variable Nonvictims
Victim of Violent Crime
Victim of Property Crime
Description Age
43.72 33.52
38.69† Age in years
17.83 14.80
15.99 Female
0.54 0.51
0.51 Male = 0, Female=1
0.50 0.50
0.50 Education
Low 0.50
0.55 0.47†
= 1 if maximum education is Certifi cate I II or High 0.50
0.50 0.50
School Diploma, 0 otherwise. Medium
0.26 0.25
0.27 = 1 if maximum education is Certifi cate III IV or
0.44 0.44
0.44 Advanced diploma, 0 otherwise.
Children Age 0–4
0.12 0.12
0.15 = 1 if there are children between 0–4 years old in the
0.32 0.33
0.35 household, zero otherwise.
Age 5–14 0.20
0.15 0.20†
= 1 if there are children between 5–14 years old in the 0.40
0.36 0.40
household, zero otherwise. Age 15–24
0.15 0.10
0.12 = 1 if there are children between 15–24 years old in the
0.35 0.30
0.32 household, zero otherwise.
Mover 0.10
0.16 0.14
= 1 if moved from one LGA to another, 0 otherwise 0.24
0.32 0.31
continued
T he
J ourna
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an Re sourc
es 120
Table 2
continued Variable
Nonvictims Victim of
Violent Crime Victim of
Property Crime Description
Mental health MCS
49.02 43.98
48.33† See
Table 1
10.00 12.09
10.39 Vitality
61.13 55.89
60.84† See
Table 1
19.30 20.22
19.33 Social functioning
83.59 75.62
83.76† See Table 1
22.47 26.32
22.08 Role emotional
84.41 71.54
83.59† See Table 1
31.44 37.72
31.28 Mental health
74.55 67.25
74.35† See Table 1
16.71 19.64
16.33 Physical health
Physical functioning 84.06
84.91 87.62†
See Table 1 22.58
22.15 19.23
Raw physical 81.14
76.24 83.59†
See Table 1 34.30
36.34 32.01
VCR 908.00
977 988
See Table 1 576
664 674
PCR 5664.00
6497 7186†
See Table 1 2966
3441 3769
Corna gl
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121 Rainy days
0.33 0.33
0.33 The fraction of rainy days over the previous year.
.04 .04
.04 Unemployment rate
5.50 6.25
6.34 The unemployment rate over the previous year.
2.71 2.91
3.18 Average total income
19441.00 18726
18323† LGA level average total income labor plus other
2949 2967
2895 sources
per fi scal year July–June. Includes
nonworkers. Interview month
modal response
September September
September Observations
25,408 465
1682
Notes: different from column 1 at a minimum 5 percent level of signifi cance. † different from Column 2 at a minimum 5 percent level of signifi cance. Education: Certifi cate I II provides basic vocational skills and knowledge 6–12 months of secondary education. Certifi cate III IV provides training in more advanced skills and knowledge. A
Certifi cate IV is generally accepted by universities to be the equivalent of six to 12 months of a Bachelor’s degree, and credit towards studies may be granted accordingly. Courses at diploma, advanced diploma level take between two to three years to complete, and are generally considered to be equivalent to one to two years of study at degree
level. The excluded education category is “High” that is equal to one for a Bachelor degree or above, zero otherwise. Source: HILDA except for crime rates, rainy days and unemployment rate. See data appendix.
as being correlated with crime. Finally, the number of rainy days is included on the basis that good or bad weather may have a direct impact on both crime and mental
well- being. See, for example, Cohn 1990; Jacob, Lefgren, and Moretti 2007. The unemployment rate and rainy days are measured over the same period as the crime
rate the 12 months prior to the interview whereas average income is measured over the calendar year due to data availability.
7
As Table 2 shows, both property and violent crime victims live in LGAs with higher unemployment, lower average earnings, and
higher violent and property crime rates.
IV. Empirical Methodology
