City Crime Rates and Concentrated Socio-Economic Advantage and Disadvantage
*Names in bold indicate Presenter
This project uses data from the National Neighborhood Crime Study (NNCS - Peterson and Krivo, 2010), a unique data set that includes police department reported crime data and sociodemographic Census data for all tracts (N = 9593) within a representative sample of 91 major U.S. cities for 2000. This data set, released in 2010, is the first attempt to compile representative tract-level crime data for more than a few cities. Using these data, I explore the relationship between city-level socio-economic advantage and disadvantage and rates of violent crime and property crime to examine the question: does concentrated affluence and advantage explain more variation in crime rate than simply the absence of concentrated disadvantage?
The NNCS includes data at the census-tract level on the commonly used measures of “neighborhood disadvantage” as defined by Ricketts and Sawhill (1988) and Kasarada (1993): percent of high school dropouts, unemployment rate, percent of female-headed households, and per capita income. I use these “neighborhood disadvantage” measures to adapt Massey’s (2001) Index of Concentration at the Extremes (ICE) to capture the degree of concentrated advantage relative to the concentration of disadvantage in a city. Instead of the absolute level of disadvantage, the ICE captures the degree to which individuals with various levels of disadvantaged characteristics coexist. Unlike Massey, I compute indices not only using income but also unemployment rate, percent of high school dropouts, and percent of female-headed households at the tract level and evaluate their relationships to city crime rates. In addition, I compare these models to the absolute disadvantage models to determine which better explains variation in city crime rates.
This project responds to calls for a more nuanced examination of the relationship between socio-economic context and crime rates. Specifically, it moves past the focus on concentrated disadvantage to include the protective features of socio-economic advantage to contribute to the social disorganization literature. Furthermore, these results will also emphasize to policymakers looking to reduce crime rates of the need to focus not only on reducing poverty and disadvantage such as through safety net programs but also on providing communities with social and institutional resources such as high-quality schools, public spaces, and positive role models that are more prevalent in advantaged communities.