Macro-level Research on Immigration and Crime in the Contemporary USA: Problems and Simple Solutions

Abstract

Extant research uses regression analysis with macro-level data to study the effect of immigration on crime in the contemporary USA. These studies have found mostly null or negative associations between the two variables. I point out three problems with these analyses. (i) Some studies use negative binomial regression inappropriately, in effect measuring determinants of frequencies rather than rates; (ii) all existing estimates arguably suffer from severe undercontrol, overcontrol, or both and cannot establish the direction of causality (if any) between immigration and crime; (iii) all studies present estimates that give equal weight to areas of differing population size. Taken together, these limitations render the research inconclusive. I show how to avoid these problems in a regression analysis of the effect of recent immigration on homicide rates in a sample of 91 US cities in 2000. Estimates point to a negative effect of immigration on homicide, but are not statistically significant.