Comparing US state resident IQ, socioeconomic status, and racial-ethnic composition as predictors of state violent crime rates

This study examined the extent to which state resident IQ, socioeconomic status (SES), and five racial-ethnic composition variables can independently account for differences in violent crime rates across the 48 contiguous American states using correlation and multiple regression strategies focused on 2019. Pearson correlations indicated that state violent crime rates significantly correlated − .69 with IQ, − .54 with SES, .39 with a racial-ethnic diversity composite, − .52 with White population percent, .30 with Black population percent, and .39 with Hispanic population percent. One set of five sequential multiple regression equations indicated that a state racial-ethnic diversity composite, White population percent, and Black population percent, still were significant predictors of state violent crime rates with socioeconomic status controlled. A second set of five equations showed none of the five racial-ethnic variables was a significant predictor of crime rates with IQ controlled. A third set of five equations showed that neither SES nor any of the racial-ethnic variables was a significant predictor with IQ controlled, and that IQ remained a significant predictor with SES and each of the five racial-ethnic variables in turn controlled. The findings persisted with multicollinearity and spatial autocorrelation considered. The results demonstrate the large and predominant negative relation of state resident IQ to state violent crime rates and its capacity to eliminate the relations of SES and racial-ethnic variables to those crime rates. Generally, the results underline the importance of evaluating potential crime rate predictors in a multiple regression model rather than testing their predictive capacities only as single variables.