Larger cities, more commuters, more crime? The role of inter-city commuting in the scaling of urban crime

Abstract

Cities attract a daily influx of non-resident commuters, reflecting their roles within wider urban networks -- not as isolated places. However, it remains unclear how this interconnectivity shapes the way crime scales with population, given that larger cities tend to receive more commuters and experience more crime. In this work, we investigate how inter-city commuting relates to the population-crime relationship. We find that larger cities receive proportionately more commuters, which in turn is associated with higher levels of burglary, drug possession, robbery, shoplifting, and theft. For example, each 1% increase in inbound commuters corresponds to a 0.32% rise in theft and 0.20% rise in burglary, holding population size constant. We demonstrate that models incorporating both population size and commuter inflows explain variation in these offenses better than population-only models. Our findings underscore the importance of considering how cities are connected -- not just their population size -- in disentangling the population-crime relationship.

Figures (3)

• Figure 1: The inter-city commuting network.(a) We construct a commuting network where nodes represent cities, and directed edges indicate the number of individuals traveling between them for work. In the plot, edge color shows direction, and thickness reflects the number of commuters (only flows above 500 are shown). Most commuting flows are spatially constrained, occurring between nearby areas, but some cities attract disproportionately large inflows, (b) leading to a distribution of inbound commuters with broad variance. While most cities receive a moderate number of workers, a few attract substantially more, forming a long right tail. (c) This attraction is tied to city size: more populated cities receive more commuters, and this relationship is approximately linear.
• Figure 2: The role of inter-city commuting on the crime--population relationship.(a, b) Theft and burglary both scale superlinearly with population: as city size increases, these crimes rise faster than proportionally. Some of the variation in crime not captured by population alone can be explained by (c, d) incorporating commuter inflows. In the plots, dots are the prediction of the population-only model, whereas their color represents the percentile of inbound commuters (given population size). (e, f) We find that a population-and-commuter model yields more parsimonious and better-fitting explanation than the population-only model.
• Figure 3: The role of inter-city commuting across crime types. We estimate population and inbound commuter coefficients for each offense using the population-and-commuter model. This model explains variation in burglary, drug possession, robbery, shoplifting, and theft; in contrast, drug trafficking and homicide show no evidence of association with inbound commuting. The asterisks indicate where the population-and-commuter model offers a better fit than the population-only specification, whereas the bars denote 95% confidence intervals.