Objective

To examine the effect of commuting rates on crime rate estimates in US cities, and to observe potential changes in the effects of other common crime rate correlates after accounting for commuting.

Methods

Crimes evaluated include homicide, aggravated assault, robbery, burglary, larceny, and auto theft. The sample includes US cities with a population of at least 100,000. The analysis first compares crime rankings using a rate based on the residential population and an alternative rate that takes into account daytime population changes due to commuting. Next, multivariate random effects panel models are used to evaluate the effect of commuting on crime rates, and to examine the extent to which the effects of other predictors change after controlling for commuting.

Results

A city’s ranking can vary considerably depending on which denominator is used. Multivariate findings suggest that daily commuting rates are a significant, strong predictor of crime rates, and that controlling for commuting yields important changes in the effects of concentrated disadvantage, concentrated affluence, racial composition and residential instability.

Conclusions

The impact of the commuting population on crime rate rankings underscores the importance of viewing crime rankings with great caution. Specifically, the residential crime rate overestimates relative risk for cities that attract a large daily population from outside the city limits. Findings provide support for the routine activities perspective, and suggest that future research examining city-level crime rates should control for commuting. Limitations to the study and directions for future research are discussed.