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Abstract
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VioLit summary:
OBJECTIVE:
The goal of this study by Harer and Steffensmeier was to test the relationship between economic inequality and rates of violent crimes disaggregated by race for Standard Metropolitan Statistical Areas (SMSAs).
METHODOLOGY:
A quasi-experimental method was employed for this study. Secondary analysis was performed on data obtained for the 125 largest SMSAs in the United States in 1980. Arrest data (transformed into natural logs) for 1980 were taken from the FBI's Uniform Crime Reports. These data were aggregated by SMSA, year, and race. Analyses were also done with estimates of "offending" (see article for further details on computations). Income inequality was measured in several ways. A measure of total inequality was defined as an overall societal measure (Gini coefficient) for all families. A measure of white to black income difference was used and was defined as the difference between the logged means of white and black family income. Within-race inequality was calculated for both whites and blacks and consisted of Gini coefficients of income among black or white families. Control variables included poverty, percent black, age, police per capita, population size, and geographic region. Poverty was disaggregated by race. Age was disaggregated by percentage of race aged 15-24. Multiple regression was used to analyze the data.
FINDINGS/DISCUSSION:
The offense rates were found to be strongly correlated with the corresponding arrest rate. Total inequality was found to be strongly correlated with each of the violent crime categories for both offense and arrest data. White to black inequality was less strongly correlated. Overall poverty and percent black were strongly correlated with all the violent crimes. Regression was done for aggregate offense rates for 1980. Total inequality and percent black were significantly and positively related to homicide (p<.001). Overall poverty (p<.025), age (p<.025), total inequality (p<.001), and percent black (p<.001) were significantly and positively related to rape. Total inequality (p<.001) and percent black (p<.025) were significantly and positively related to assault. total inequality, percent black, police, population, and South were all positively and significantly (p<.001 for all) related to robbery. When arrest rates were considered, only total inequality was significantly (p<.025) related to homicide arrest rates. Total inequality (p<.025) and age were significantly and positively related to rape arrest rates. Total inequality was the only significantly related variable for assault arrest rates (p<.001). Total inequality and police were significantly and positively related to robbery arrest rates (p<.025). When the income inequality measures were considered on race-disaggregated arrest rates, total inequality was found to be highly significant (p<.001) for white homicide, rape, assault, and robbery rates but only significant for black assault arrest rates (p<.025). The white to black income difference was insignificant for black and white arrest rates. White to white inequality was significantly (p<.001) related to white homicide, rape, assault, and robbery arrest rates, but black to black inequality was insignificant when applied to black arrest rates. White arrest rates were regressed on inequality measures and the other independent variables. White to white inequality was highly positive and significant for all four arrest rates: homicide, assault, robbery (all three at p<.001), and rape (p<.025). Additionally, age (percent of the population 15-24) was significant and positive for rape (p<.025). When black arrest rates were regressed on the inequality measures and other independent variables, a different pattern emerged. Black to black inequality was insignificant for any of the four arrest rates. The age group 15-24 was significantly (p<.025) and positively related to rape and robbery rates. Percent black was significantly and negatively related to rape, assault )p<.025), and robbery (p<.001). Police was significantly (P,.025) related to black robbery arrest rates. The authors concluded by stating the importance of disaggregating both arrest rates and inequality indicators; the relationships observed would have been masked with a consideration of total rates. While overall inequality was seen to have strong relationships with overall inequality, this relationship only held for white arrest rates. The explanation offered by the authors for the differential effect of inequality by race was that whites may have a poorer articulation between structural and cultural contingencies than blacks. In other words, blacks were thought to possibly see success of self in particularistic terms rather than on universalistic norms. It was also said that inequality may have indirect effects on blacks through reducing formal and informal community controls, undermining family stability, by fostering subcultural adaptations that promote deviant lifestyles, and by altering patterns of criminal opportunity and routine activities.
AUTHORS' RECOMMENDATIONS:
The authors stated that more theoretical work needs to be done considering the way inequality contributes to exceptionally high levels of black violence in urban areas. Other structural or community sources of variation in black rates of violence should be investigated, the authors argued.
EVALUATION:
The design of this study is of high quality, and its findings are as solid as the data from which they come. There is a lot to be said for analysis of disaggregated data and the closer examination of variables applied to specific groups which may differ. However, there are a couple of cautions to be taken. First, while the data are taken from the FBI and represent the best available data, the authors' claims that there is virtually no bias in the data disregards the problems of data collection which are dependent on police observation of offenses and citizen reporting for offense rates and police arrest behavior for arrest rates. These have not been shown to be completely bias free. More troubling are the authors' conclusions that there may still be this subculture of violence among blacks, although their own data do not even address this. The question for these authors comes back to black violence, although their study shows the clear connection between inequality and white violence rates. I would have liked to seen a more thorough discussion of the issue at hand rather than the speculation about subcultures of black violence.
(CSPV Abstract - Copyright © 1992-2007 by the Center for the Study and Prevention of Violence, Institute of Behavioral Science, Regents of the University of Colorado)
Crime Rates
Socioeconomic Factors
Caucasian Offender
Caucasian Violence
African American Violence
African American Offender
Violence Rates
Income Inequality
Poverty
Socioeconomic Status
Black-White Comparison
Racial Comparison
Racial Differences
Racial Factors
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