A comparative analysis of high and low homicide rate cities /

Abstract

This thesis is an analysis of the differences between high and low homicide rate cities. The specific variables that were included in the study were: the homicide rate, the unemployment rate, the gender, racial and age characteristics of offenders and victims, the percent of homicides committed with a firearm, the percent of homicides related to gang activity, drug use, alcohol use, and to drug law violations. Fifty-four cities were included in the study, twenty-seven being categorized as low homicide rate cities and twenty-seven being categorized as high homicide rate cities. Descriptive statistics were calculated for each of the aforementioned variables for each group of cities. Certain variables were selected for correlational analysis and logistic regression. Statistically significant differences were identified using descriptive statistics for the following variables: Homicide rate, unemployment rate, robbery and aggravated assault rates, percent of white, female, and male offenders, percent of white, female, and male victims, and victims age 15 to 24, percent of homicides related to alcohol, drug trafficking, gang activity, and, drug sales, and the percent of homicides committed with a handgun. Statistically significant correlations were found to exist between the following: Percent of homicides related to alcohol and the unemployment rate (for low homicide rate cities only), and percent of homicides related to gang activity and the unemployment rate (for high homicide rate cities only) The logistic regression indicated that the model used was able to predict the probability of a city being a high homicide rate city accurately for 94.44 percent of the study sample. The logistic regression model contained unemployment rate and aggravated assault rate as the predictor variables.