Differential Risks: Which Groups Get Robbed the Most and the Least Often?
To discover patterns in robberies, researchers must sort through data collected each year about various groupings of people and households that participated in the NCVS survey. According to the NCVS for 2013, the robbery rate was 2.4 per 1,000. That means just about 2 individuals out of every 1,000 residents over the age of 11 got robbed that year. But, just as with murder rates, sharp differences in robbery risks become evident when the odds facing
the average American are disaggregated or decon- structed. Breaking down the NCVS sample into subcategories, certain demographic groupings were robbed much more often than others. Patterns that prevailed when robbery was a huge problem in 1993 and patterns that still persisted when the robbery rate was dramatically lower in 2013 can be discerned from the data assembled in Table 4.4.
To put the issue bluntly, although everyone might be apprehensive about being robbed at a cer- tain time and place, particular groups of people have a lot more to fear on a regular basis than
B O X 4.2 “Your Money or Your Life!”
Using both the UCR and the NCVS, it is possible to derive rough estimates of how many robbery victims get killed each year, and whether that percentage is growing or shrinking.
The number of robberies committed annually can be estimated from NCVS figures. However, the NCVS excludes robberies of establishments like convenience stores and banks and thereby unavoidably undercounts commercial robberies where some employee or bystander might get slain. UCR figures are always smaller because they represent only the robberies known to the police. The SHRs’ annual number of slayings that were felony murders starting out as robberies is surely an undercount because homicide detectives are unable to determine the motive and solve the crime in around one-third of all cases. Also, in certain murders, the killer might have robbed the deceased person’s corpse as an afterthought, according to a study of robbery-related homi- cides in Baltimore during 1983 (see Loftin, 1986).
Acknowledging these methodological caveats, rough calculations can be performed to derive ballpark estimates of how often targeted individuals—whether they are cooperat- ing or resisting—are murdered by robbers. (See the data assembled in Table 4.3.)
Several tentative conclusions can be reached from this statistical evidence drawn from official sources: The nationwide annual death toll is disturbing but at least it is diminishing. Nearly 2,500 people died at the hands of rob- bers in 1980, and about 685 perished in 2013. But, thank- fully, slayings committed during the course of holdups are rare, considering the huge numbers of confrontations (well over a million in 1980, nearly 370,000 in 2013) in which a life could have been taken along with money or possessions. In 2013, the proportion of robbery victims who were slain— less than two-tenths of 1 percent, was within the same range as during the past 33 years. So predators these days are not more inclined to snuff out the lives of their prey while trying to relieve them of their valuables before making their escape.
And yet, this advice remains sound: When accosted by an armed offender who growls, “Your money or your life!” statistics confirm that the correct response is to hand over the money and hang on to your life, according to a detailed study of more than 100 solved homicides that occurred in Chicago during 1983 (Zimring and Zuehl, 1986).
T A B L E 4.3 Yearly Estimates of Murders Committed During Robberies
1980 1990 2000 2010 2013
Number of persons murdered (from the UCR) 23,040 23,438 15,586 14,748 12,253 Number of persons murdered during a robbery (from the UCR)
2,488 2,156 1,077 780 686
Total number of robbery victims (from the NCVS) 1,179,000 1,150,000 732,000 480,750 369,000 Murdered victims as a percentage of all robbery victims 0.21% 0.19% 0.14% 0.16% 0.19%
SOURCE: FBI’s UCR, 1980, 1990, 2000, 2010, 2013; BJS’s NCVS, 1980, 1990, 2000, 2010, 2013.
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others. The differential risks vary dramatically by demographic characteristics.
Starting with sex, the first pattern that stands out is that males are singled out more often than females. The rate for males was 11 per 1,000 in
1993, compared to 6 for females. By 2013, boys and men were getting robbed a lot less frequently than in 1993 (down sharply to just 3 per 1,000) but they still tangled more often with robbers than girls and women (down substantially to just 2 per 1,000).
With regard to race and ethnicity, in 1993 blacks and Hispanics were accosted several times as often as whites and others (mostly Americans of Asian ancestry). By 2013, the rates for all four racial and ethnic groups had tumbled and the differences had nearly disappeared, although whites still enjoyed lower risks than blacks, Hispanics, and others.
As for age, the analysis of the survey’s findings for 1993 revealed that younger people (between the ages of 15 and 34) were confronted much more often than older people. Individuals in their late teens faced the gravest risks of all. After those peak years, risks decline steadily with advancing age. In other words, an inverse relationship prevails: As age increases, the dangers of being robbed decrease. In 2013, the differences in victimization rates had narrowed dramatically but the overall pattern persisted: People younger than 35 were targeted more often than those who were older. Contrary to the impression that robbers prefer to prey upon the elderly and frail, the statistics dem- onstrate that senior citizens are singled out the least often of any age group.
Family income also appeared to be negatively correlated with robbery rates. As income increased, the chances of being robbed generally decreased, with just one exception. In 1993, the differences between the lowest and highest income groups were dramatic. Twenty years later, the gap had narrowed considerably, but the pattern persisted: The desperately poor were robbed of their meager possessions much more often than others with higher household incomes. Clearly, robbers are no Robin Hoods.
Robbery is thought to be a big-city problem, and that perception is supported by the data.
In 1993, residents of urban areas were targeted much more often than suburbanites, while inhabi- tants of small towns and rural areas led safer lives. Inhabitants of the largest cities with populations of
T A B L E 4.4 Robbery Rates for Various Groups, 1993 and 2013
Victim Characteristics 1993 Rate 2013 Rate
Overall rate 8 per 1,000 2 per 1,000 Sex
Male 11 3 Female 6 2
Race and Ethnicity White 7 2 Black 21 3 Other 9 4* Hispanic 14 3
Age 15–17 13 3* 18–20 16 3* 21–24 11 4 25–34 11 4 35–49 6 2 50–64 2 2 65 and older 2 0.4*
Family income** Less than $7,500 15 10 $7,500–$14,999 12 8 $15,000–$24,999 10 5 $25,000–$34,999 6 2 $35,000–$49,999 6 3 $50,000–$74,999 7 1 $75,000 or more 5 0.6 Location of the Incident
Urban 15 3 Cities with more than 1 million residents
34** 4
Suburban 7 2 Rural 4 2*
Marital status** Married 3 0.8 Widowed 2 3* Divorced 12 4 Separated 19 9* Never married 17 4
NOTES: Rates are per 1,000 people with these characteristics per year. All rates are rounded off to the nearest whole number, except for those smaller than 1.0. *Estimate is based on very few cases and could be unreliable. **Figure is for 1995, not 1993.
SOURCE: BJS’s Victimization Analysis Tool, 2014.
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over 1,000,000 suffered a shockingly high victimi- zation rate of 33 per 100,000. Two decades later, city people still faced higher risks and country peo- ple still enjoyed lower odds, but the dangers of get- ting robbed in all areas had tumbled, especially in the nation’s largest cities.
In addition to sex, age, race and ethnicity, income, and area of residence, marital status made a big difference: In 1993, individuals who had never been married or who were separated or divorced endured much higher robbery rates than either married or widowed people (who generally were older and tended to be female). By 2013, risks were lower for all groups (except for the widowed, but that statistic was based on very few cases), but the pattern persisted: Those who were not married were more likely to find themselves in trouble. Chances are that most robbers don’t check for wed- ding rings before striking; lifestyle choices may explain the disparate rates. This pattern provides an important clue that will be cited later to explain differential risks.
To sum up the patterns gleaned from Table 4.5, in both the early 1990s and on the safer streets dur- ing 2013, higher robbery risks were faced by men rather than women; minorities than whites; younger people than middle-aged or elderly people; single individuals than married couples; poor people than those who are better off financially; and city residents than those living in suburbs or small towns. Com- bining these factors, the profile of the person facing the gravest dangers of all is an impoverished, young, black or Hispanic man living in an inner-city neigh- borhood. Affluent, elderly white ladies living in rural areas lead the safest lives.
Unfortunately, the NCVS does not calculate a victimization rate for comparison purposes for an individual who falls into all of the high-risk or all of the low-risk subcategories. However, the sur- vey findings cited in Table 4.4 indicated that black teenage boys living in low-income families and residing in the biggest cities (thereby falling into all five of the high-risk categories) must have suf- fered a robbery victimization rate in the “bad old days” of the early 1990s that was off the charts compared with persons from other backgrounds.
However, two decades later, people falling into this highest risk grouping faced dramatically improved odds of avoiding a sharply reduced number of robbers on the prowl.
One additional variable is worthy of consideration—occupation. Robbery rates differ substantially depending on the nature of a person’s work. Statistics from the NCVS indicated that peo- ple holding the following (generally less desirable) jobs were much more likely to be robbed: taxi dri- vers, gardeners, busboys, dishwashers, carnival and amusement park workers, car wash attendants, mes- sengers, newspaper carriers, peddlers, and certain construction workers. However, musicians and composers, painters and sculptors, and photogra- phers also were victimized at above-average rates. Least likely to be accosted were inspectors, line workers, bank tellers, opticians, farmers, profes- sional athletes, elementary school teachers, engi- neers, and psychologists (Block, Felson, and Block, 1985). Another study determined that retail sales workers, especially clerks at convenience stores and liquor stores, were robbed the most, along with cab drivers. College professors faced the lowest risks of being accosted (Warchol, 1998).
Differential risks also show up clearly when a particular kind of robbery—carjacking—is the focus of attention. Some people are more likely than others to have their vehicles taken from them by robbers, as the information assembled from official sources in Box 4.3 indicates.
In general, it appears that the daily activities of individuals as well as the behavior patterns of entire groups—such as poor young men living in cities— determine, to some degree, whether or not robbers will single them out as possible prey.
The takeaway message in the graphs depicted in Figures 4.2 and 4.3 confirm that the rates of these three violent crimes have fallen dramatically, even crashed, from their historically high levels that were socially as well as politically intolerable. In general, Americans have been getting along much better with each other since the early 1990s, even during the hard times of the Great Recession that devel- oped during 2008 and persisted for several years. The dramatic downward trends in murders,
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aggravated assaults, and robberies (see above) through 2013 indicate that even the nation’s mean- est streets have become substantially safer. But to conclude from these very positive developments that began during the early 1990s that the “worst is over” might be overly optimistic. No criminolo- gist or victimologist knows for sure why crime rates rise and fall, or what the future holds. Predictions about upcoming crime waves or crashes must be based on projected changes in a number of
underlying variables. Developments in some of these root causes are very hard to anticipate. Another crime wave could break out, or the unan- ticipated but much welcomed improvement in America’s crime problem might continue for an additional number of years. But it is safe to con- clude that the ranks of victims were not growing during the twenty-first century as rapidly as they were during the 1960s, 1970s, 1980s, and 1990s, when pessimists made dire predictions that violence