More crime in cities? On the scaling laws of crime and the inadequacy of per capita rankings\u2014a cross-country study

Marcos Oliveira

doi:10.1186/s40163-021-00155-8

Marcos Oliveira

Open Access

https://doi.org/10.1186/s40163-021-00155-8

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Abstract

Crime rates per capita are used virtually everywhere to rank and compare cities. However, their usage relies on a strong linear assumption that crime increases at the same pace as the number of people in a region. In this paper, we demonstrate that using per capita rates to rank cities can produce substantially different rankings from rankings adjusted for population size. We analyze the population–crime relationship in cities across 12 countries and assess the impact of per capita measurements on crime analyses, depending on the type of offense. In most countries, we find that theft increases superlinearly with population size, whereas burglary increases linearly. Our results reveal that per capita rankings can differ from population-adjusted rankings such that they disagree in approximately half of the top 10 most dangerous cities in the data analyzed here. Hence, we advise caution when using crime rates per capita to rank cities and recommend evaluating the linear plausibility before doing so.

Highlights

In criminology, it is generally accepted that crime occurs more often in more populated regions
Previous works have investigated population–crime relationships extensively (Alves et al, 2013a; Bettencourt et al 2010; Chang et al 2019; Gomez-Lievano et al, 2012; Hanley et al, 2016; Yang et al, 2019), they have failed to quantify the impact of nonlinear relationships on rankings and restricted their analyses to either specific offenses or countries
We show that using crime rates to rank cities can lead to rankings that considerably differ from rankings adjusted for population size

Summary

Introduction

It is generally accepted that crime occurs more often in more populated regions. In one of the first works of modern criminology, Balbi and Guerry examined the crime distribution across France in 1825, revealing that some areas experienced more crime than others (Balbi and Guerry, 1829; Friendly, 2007) To compare these areas, they realized the need to adjust for population size and analyzed crime rates instead of raw numbers. This method eliminates the linear effect of population size on crime numbers and has been used to measure crime and compare cities almost everywhere— from academia to news outlets (Hall, 2016; Park and Katz, 2016; Siegel, 2011) This approach overlooks the potential nonlinear effects of population and, Though different criminology theories expect a relationship between population size and crime, they tend to disagree on how crime increases with population (Chamlin and Cochran, 2004; Rotolo and Tittle, 2006). Crime rates are often deemed to be a standard means of comparing crime in cities

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