Interaction Effect Between Income Inequality and Disadvantage Predicting Rural Violent Crime

• In Event: Roundtable: Advances in Research on Violence and Violent Victimization

Abstract

Using structural variables originating from Shaw and McKay’s theory (1942) as well as other ecological models, the present study examines the moderation effects of disadvantage and income inequality predicting county-level violent crime rates. The crime rate used in my analysis was calculated particularly for rural counties (N=1324) from data offered in the Uniform Crime Reports combined with county level census data for the calendar years 2010 through 2012. The independent variables are racial heterogeneity, residential mobility, disadvantage, and income inequality. This study intends to test whether the interaction effect, found by Burraston, McCutcheon and Watts (2017), between income inequality and disadvantage predicts rural county-level violent crime rates. We utilized a multilevel linear regression model to test the interaction effect for all rural counties in the USA. The interaction effect significantly predicts rural county-level violent crime rates. High disadvantaged rural counties have the highest y-intercept but the smallest inequality slope. Mean disadvantaged rural counties have the second highest y-intercept but the second smallest inequality slope. Low disadvantaged rural counties have the lowest y-intercept and the largest inequality slope.

Authors

• Karli Province, University of Memphis

• Bert Burraston, University of Memphis