This study explains variation in urban crime incidence
as a function of a number of socio-economic variables, including income, education, and urban blight. Ordinary
least squares regression analysis is applied to cross-section
data from the 60 largest Standard Metropolitan Statistical
Areas, for 19 70. Various extensions of the basic model are
presented, using log variables, a lagged endogenous variable,
and indices derived from factor analysis of a large matrix
of socio-economic variables.