The Effects of Socioeconomic Factors on Violent and Property CRIMES

Abstract

Due to poor socioeconomic conditions such as declining wages and high unemployment rates, unskilled young people may be drawn to the commission of crime. Several recent studies have found that worsening economic conditions cause social disorder and crime. The purpose of this study is to assess whether various socioeconomic indicators have a positive impact on both violent and property crime rates at the county level within the state of Texas in the United States. The present study hypothesizes that: 1)violent and property crime rates are higher in counties with high levels of poverty; 2)violent and property crime rates are higher in counties with high levels of unemployment; 3)violent and property crime rates are higher in counties with low levels of median household income; 4)violent and property crime rates are higher in counties with low levels of educational attainment. The data used in the analysis was collected from the Uniform Crime Report(UCR) and the United States Department of Agriculture: Economic Research Service(USDA) for the year 2015. Within the present study, the total enumeration of counties(254) located in the state of Texas(United States) was designated as the units of analysis. This study measures two dependent variables: violent crime rates and property crime rates. Four unique independent variables were chosen for the analysis based off findings in the current body of literature: (a)poverty, (b)unemployment, (c)median household income, and (d)educational attainment. An Ordinary Least Squares(OLS) regression model is employed to empirically investigate the relationships between socioeconomic indicators and crime rates. In addition, Geographic Information Systems(GIS) were employed to demonstrate the link between unemployment, violent crime, and property crime. The findings of the current study reveal that (1)violent crime rates are on average higher in counties with high levels of unemployment; (2)property crime rates are higher on average in counties with higher levels of unemployment. To clarify, a 1 Standard Deviation(SD) unit increase in unemployment predicts a 6% increase in the expected count of violent crime(p < .001). Also, a 1 SD unit increase in unemployment predicts a 29% increase in the expected count of property crime(p < .001). Unemployment is the only significant independent variable and can thus be viewed as a possible source of criminality within the counties in Texas. One method of reducing unemployment and ultimately reducing crime is by implementing a community development model. This will lead to the creation of a “community network” that draws local resources, services, and facilities together for the creation of more jobs. The contributions, limitations and suggestions for the future study were discussed in conclusion.