Drivers of Race Crime and the Impact of Bridging Gaps: A Dynamic Empirical Analysis - Chan, Kitty Kay (Race and social problems, 2023)
Hate crimes in the US have reached their highest recorded levels in more than a decade. Greater understanding of the factors contributing to violence toward minority groups is needed to support evidence-based policies to curb race crime. This study analyzes the causes of race crime in the US using a state-level dynamic empirical model derived from the combination of well-recognized criminological theories. To our knowledge, the study provides the only empirical analyses of race crimes across the US. The paper applies a dynamic panel model to better use crime data at the aggregate level by taking advantage of the longitudinal data structure to account for unobservable factors across states. It also draws upon the dynamic panel structure to integrate the theoretical framework of social learning of crime, together with strain theory and theory of doing difference, to identify potential causal factors. The findings confirm implications derived from strain theory, theories of doing difference, and social learning theory of crime, respectively, indicating the value of an integrated framework. The results suggest “closing gaps” is key in deterring race crime. Over the recent decade, a 1% annual change in key factors that would close the economic gap, increase understanding of cultural difference, incorporate seniors into communities, and stop cascading effects of race crime would, individually, have lowered the 2019 race crime rate by an estimated 12–21% and, in combination, by approximately 28%. Potential policy interventions that merit testing include increasing cultural awareness education, improving access to credit, supporting inter-generational community programs, and appropriate training and resources to support law enforcement personnel to collect, manage, and report race crime data.