Measuring Marginal Crime Concentration: A New Solution to an Old Problem

• Author: Jacob Kaplan,Aaron Chalfin,Maria Cuellar
• Published date: 01 July 2021
• Date: 01 July 2021
• DOI: 10.1177/0022427820984213
• Subject Matter: Articles

Article

Measuring

Marginal Crime

Concentration:

A New Solution

to an Old Problem

Aaron Chalfin

1

, Jacob Kaplan

1

, and Maria Cuellar

1

Abstract

Objectives: In his 2014 Sutherland address to the American Society of Crim-

inology,DavidWeisburddemonstratedthattheshareofcrime thatis

accounted for by the most crime-ridden street segments is notably high

and strikingly similar across cities, an empirical regularity referred to as the

“law of crime concentration.” In the large literature that has since prolifer-

ated, there remains considerable debate as to how crime concentration

should be measured empirically. We suggest a measure of crime concen-

tration that is simple, accurate and easily interpreted. Methods: Using data

from three of the largest cities in the United States, we compare observed

crime concentration to a counterfactual distribution of crimes generated by

randomizing crimes to street segments. We show that this method avoids a

key pitfall that causes a popular method of measuring crime concentration

to considerably overstate the degree of crime concentration in a city.

Results: While crime is significantly concentrated in a statistical sense and

while some crimes are substantively concentrated among hot spots, the

1

University of Pennsylvania, Philadelphia, PA, USA

Corresponding Author:

Aaron Chalfin, University of Pennsylvania, Philadelphia, PA, USA.

Email: achalfin@sas.upenn.edu

Journal of Research in Crime and

Delinquency

2021, Vol. 58(4) 467-504

ªThe Author(s) 2021

Article reuse guidelines:

sagepub.com/journals-permissions

DOI: 10.1177/0022427820984213

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precise relationship is considerably weaker than has been documented in

the empirical literature. Conclusions: The method we propose is simple and

easily interpretable and compliments recent advances which use the Gini

coefficient to measure crime concentration.

Keywords

criminology of place, hot spots, microgeography, law of crime

concentration

Introduction

A large and growing literature in criminology documents the importance of

place—in particular, microgeographic places like street segments—one of

the two faces of a standard city block—in explaining crime. Across a large

number of places and in a variety of contexts, crime is found to be highly

concentrated (Andresen, Curman, and Linning 2017; Eck, Clarke, and

Guerette 2007; Haberman, Sorg, and Ratcliffe 2017; Sherman, Gartin, and

Buerger 1989; Weisburd 2015) and persistent over time (Gorr and Lee

2015; Weisburd et al., 2009). Taken as a whole, the substantial geographic

concentration of crime suggests that the social and physical features of the

urban landscape might potentially play an important role in the crime pro-

duction function and therefore that crime hot spots are an appropriate target

over which a social planner can focus resources and ultimately intervene.

1

However, the efficiency with which resources can be targeted to crime hot

spots depends critically on the extent to which crime is, in fact, concen-

trated. Consequently, an over-emphasis on place may crowd out other pro-

mising approaches to crime control (e.g., social service-based strategies) if

the evidence on spatial crime concentration is misleading.

In his 2014 Edmund H. Sutherland address to the American Society of

Criminology, David Weisburd summarized the research on the importance

of place and noted that places have been studied far less by criminologists

than other natural units of analysis (Weisburd 2015). Weisburd further notes

the extent to which crime is concentrated among the most crime-ridden

street segments is remarkably consistent across cities and proposes that this

empirical regularity is sufficiently strong to be characterized as a “law of

crime concentration.”

2

Across eight cities of varyi ng sizes, the top one

percent of street segments, ranked by crime incidence, accounted for

approximately 25 percent of crimes in that city and the top 5 percent of

468 Journal of Research in Crime and Delinquency 58(4)

street segments accounted for h alf of the crimes. The stabili ty of these

estimates is noteworthy and forms the basis for the claim that this pattern

can be characterized as a law.

Despite the abundance of research inspired by the law of crime concen-

tration, recent scholarship has raised a number of key measurement issues in

how crime concentration should actually be measured (Bernasco and Steen-

beek 2017; Hipp and Kim 2017; Levin, Rosenfeld, and Deckard 2017;

Mohler et al. 2019; Obrien 2019; Prieto Curiel 2019). In particular, prior

research notes that the fact that a small share of street segments accounts for

a large share of the crime over a given time period does not necessarily mean

that crime is substantively concentrated. To see this, consider that even in

the cities with most the challenging crime problems, the number of street

segments can far exceed the number of crimes known to law enforcement

over any reasonable time window. For instance, consider a city like New

York in which there are approximately 120,000 street segments and 300

homicides annually. In this case, it is trivial to see that, even if each homi-

cide occurs on a different street segment (thus, by definition, there would be

no concentration of crime), 0.25 percent of the street segments would

account for 100 percent of the homicides.

3

Thus, using the standard metric

of crime concentration, the extent to which at least some types of crimes are

concentrated will be biased upward. Similarly, the standard metric does not

allow for a comparative analysis of concentration among different types of

crimes since rarer crimes will, for mechanical reasons, appear to be more

concentrated than more common crimes (Hipp and Kim 2017).

Recent scholarship has proposed several modifications to the measure-

ment of crimeconcentration that address theseconcerns (Bernasco and Steen-

beek 2017; Curiel, Delmar, and Bishop 2018; Hipp and Kim 2017; Levin

et al. 2017; Mohler et al. 2019; Obrien 2019). A particularly common

approach that is advanced by Levin et al. (2017) and which can be found

in abundancein the recent literature (see e.g. Steenbeekand Weisburd (2016),

Andresen et al. (2017), Schnell, Braga, and Piza (2017) and Umar, Johnson,

and Cheshire (2020)) is to measure crime concentration only among street

segmentsthat experienced at least one crime. The ideabehind this approach is

that crimes can only be concentrated where they, in fact, occur. This mod-

ification to the measurement of crime concentration does tend to reduce the

degree of the bias in the standardmeasure but, as we show, in most empirical

applications, removing crime-free street segments will continue to lead to a

substantial overestimate of the extent to which crimes are concentrated.

In this article, we propose a different way to measure crime concentra-

tion that is simple, easily interpreted and which fully addresses the concerns

Chalfin et al. 469