Author(s)

Tamaraubibibogha Manfred Gunuboh

Public Administration of Mississippi State University, Starkville, MI, USA.

This paper examines the effect of parental poverty and neighborhood conditions on juvenile crime rates. It employs two distinct regression models: OLS linear regression model and negative binomial regression model to test for several hypotheses. The OLS is used to explore the correlational relationship between the dependent and independent variables, while the negative binomial regression model is used to make prediction about the relationship between the dependents and independent variables. The findings in the first regression (OLS) results indicated a significantly positive relationship between parental poverty and juvenile violent crime rates; it shows that a percent increase in parental poverty in a county will cause juvenile crime rate to increase by about 0.53 percent. Likewise, the incidence rate ratio of the negative binomial regression model (1st NBRM) indicates that if the percentage of families in a county who are living in poverty increases by a unit, the number of juvenile arrest counts for violent crimes is likely to increase by a factor of 1.48, while holding all other variables constant. Hence, this paper directs government officials to see beyond traditional approach to juvenile crime and begin to address specific factors such as parental poverty that have proven to increase the rate of juvenile crime.

Parental Poverty, Juvenile Crime, Racial Disparity, Education, Neighborhood Conditions

Gunuboh, T. (2023) Parental Poverty and Neighborhood Conditions as Predictors of Juvenile Crime Rates. Open Journal of Social Sciences, 11, 287-318. doi: 10.4236/jss.2023.117021.