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

TL;DR

This study examines how crime scales with city population size across 12 countries, revealing that per capita crime rates can misrepresent actual risks and suggesting the need for population-adjusted analyses.

Contribution

It demonstrates that per capita crime rankings can be misleading and advocates for population-adjusted measures based on empirical scaling laws across multiple countries.

Findings

Theft increases superlinearly with city size in most countries.

Burglary increases linearly with population.

Per capita rankings often disagree with population-adjusted rankings in top dangerous cities.

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 analysed here. Hence, we advise caution when using crime rates per capita to rank cities and recommend evaluating the linear plausibility before doing so.