Proceedings of the 9th International Conference on Research in Social Sciences
Year: 2024
DOI:
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Unequal Spaces: Socio-Economic and Demographic Drivers of Violent Crime Across U.S. Counties
Yifei Gao
ABSTRACT:
This study explores the socio-economic and demographic factors that influence violent crime rates at the county level across the United States. Using data from 51 states for 2022, we employed a multivariate regression model to examine variables including population density, poverty levels, police expenditure, unemployment rates, youth population percentage, and racial composition. Our findings indicate that violent crime rates are significantly affected by multiple factors, with results showing that higher population density correlates with lower crime rates, suggesting that urban density may contribute to enhanced community oversight and policing. Conversely, poverty levels and racial composition exhibit positive associations with violent crime rates, aligning with prior research indicating socio-economic disparities’ impact on crime. The model explains roughly 40.71% of the variance in crime rates, with an adjusted R-squared of 0.33, suggesting that while our variables capture key relationships, additional factors—such as social cohesion, law enforcement effectiveness, and cultural dynamics—may also be influential. The inclusion of robust standard errors helps account for heteroscedasticity in cross-sectional data, enhancing the reliability of our estimates. Despite data limitations, this study advances the understanding of violent crime’s determinants and highlights the complex interplay of economic and demographic variables. Future research should consider broader socio-economic interactions and alternative models to capture the nuanced influences on violent crime, potentially offering deeper insights for policy development aimed at reducing crime and promoting community well-being.
keywords: Demographic Factors, Public Safety, Racial Composition, Regression Analysis, Structural Inequality