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Abstract:
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In his 2014 Sutherland address to the American Society of Criminology, David Weisburd demonstrated empirically that the share of crime that is accounted for by the most crime-ridden street segments is notably high and strikingly similar across cities, an empirical regularity that Weisburd refers to as the “law of crime concentration.” We build upon recent work in this area that points out that the concentration of a large share of crime amongst a small number of street segments can, in some cases, be a mechanical artifact of the degree of crime density in a city rather than the signature of an empirical law. Using data from three of the largest cities in the United States, we identify crime concentration by comparing observed crime concentration to a counterfactual distribution of crimes generated by randomizing crimes to street segments. We further show that, within a city, crime is least concentrated in the neighborhoods that experience the largest number of crimes. Accordingly, the law of crime concentration sometimes holds only tenuously in the communities in which crimes are most prevalent. We conclude that the law of crime concentration requires some qualification.
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