Property Crime Clearance in Small Jurisdictions

• Date: 01 December 2018
• Published date: 01 December 2018
• DOI: 10.1177/0734016817752434
• Subject Matter: Articles

Article

Property Crime Clearance in

Small Jurisdictions: Police and

Community Factors

Jeffrey J. Roth

1

Abstract

Research on the factors that influence crime clearance rates has primarily studied violent crimes in

large cities. However, property crimes are among the most commonly occurring and least fre-

quently cleared offenses, and the majority of police departments in the United States serve small

jurisdictions. Thus, this study undertook an examination of the predictors of clearance rates for

burglary, larceny, and vehicle theft in a sample of agencies serving populations of 50,000 people or

fewer. Independent variables included both policing factors (e.g., workload, funding, broken win-

dows arrests) and social disorganization indicators (e.g., residential instability, poverty). Negative

binomial regression analyses revealed variation in the significance of the predictors across the three

crimes. Additionally, many predictors found to be influential in prior work were insignificant in this

study, which suggests differences in the nature of crime clearance between large cities and smaller

jurisdictions and a need for further research in this area.

Keywords

clearance rates, burglary, larceny, vehicle theft

In the United States, a crime is considere d cleared when an offender is arrested, char ged, and

delivered to the courts for prosecution or when there is sufficient evidence to arrest a person but

unusual circumstances (e.g., death of the suspect) prevent that from occurring (U.S. Department of

Justice, 2016). The percentage of crimes that are cleared—the clearance rate—is commonly used as

an indicator of the effectiveness of law enforcement agencies by policy makers, the media, and

criminologists (Pare & Ouimet, 2004; Worrall, 2016). Low clearance rates can have a variety of

adverse effects, including decreased trust in law enforcement, greater fear of crime, poor morale

among officers, and reduced deterrence (Lockwood, 2014; Roberts, 2008). Thus, researchers have

done much to assess the incident details, policing factors, and community traits that affect clearance

rates (Cordner, 1989; Doerner & Doerner, 2012; Jang, Hoover, & Lawton, 2008; Litwin, 2004;

Litwin & Xu, 2007; Lockwood, 2014; Ousey & Lee, 2010; Puckett & Lundman, 2003; Roberts &

Roberts, 2016; Worrall, 2016). However, the body of research on crime clearance is imbalanced in

1

Penn State University—New Kensington, New Kensington, PA, USA

Corresponding Author:

Jeffrey J. Roth, Penn State University—New Kensington, 3550 7th Street Road, New Kensington, PA 15068, USA.

Email: jjr30@psu.edu

Criminal Justice Review

2018, Vol. 43(4) 477-493

ª2018 Georgia State University

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DOI: 10.1177/0734016817752434

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two ways. One, these studies have typically focused on violent crime, especially homicide (Doerner

& Doerner, 2012; Taylor, Holleran, & Topalli, 2009). This is problematic, given the differences

between violent and property offenses. Violent crimes are more likely to have witnesses because

they require an encounter between victim and offender (Pare, Felson, & Ouimet, 2007). Addition-

ally, they tend attract publicity and so may receive greater investigative attention (Pare et al., 2007;

Puckett & Lundman, 2003). Unsurprisingly, then, violent crimes have higher clearance rates than

property offenses. Over half of homicides and aggravated assaults are cleared in the United States,

compared to less than one quarter of burglaries, larcenies, and vehicle thefts (U.S. Department of

Justice, 2016). A second shortcoming of the clearance literature is that it has typically focused on

agencies in large cities. Small and rural law departments differ in important ways from large urban

ones, such as the availability of resources and the relationship with the community (Falcone, Wells,

& Weisheit, 2002; Weisheit, Wells, & Falcone, 1995). Small departments also clear property crime

at different rates. In 2015, departments serving populations smaller than 50,000 people cleared

15.3%of burglaries, 27.6%of larcenies, and 18.3%of vehicle thefts; those figures are 9.7%,

16.2%,and8.8%for jurisdictions with populations over 250,000 (U.S. Department of Justice

2016). In light of these two weaknesses in the literature, the present study examined the predictors

of property crime clearance rates using a sample of law enforcement agencies serving small

populations.

Literature Review

Research has examined the predictors of crime clearance at the incident, neighborhood, and city

level (e.g., Cihan, Zhang, & Hoover, 2012; Lockwood, 2014; Roberts & Roberts, 2016; Wong,

2010), and each approach offers unique advantages that are considered in detail later in this article.

The reader should note that, given the different limitations of each type of research, caution is

necessary when comparing findin gs across different levels of agg regation. Since this literature

review precedes a city-level study, it focuses on other macro-level work and notes whether the

studies of property crime examined cities or neighborhoods.

Community Factors

Scholars have known for decades that the social environment of a community can influence crime

clearance (Bennett, 1982; Cordner, 1989), and social disorganization theory is one perspective that

has been applied to that relationship (Mustaine, Tewksbury, Corzine, & Huff-Corzine, 2013;

Regoeczi & Jarvis, 2013). This theory grew out of work at the University of Chicago in the early

20th century (Park, Burgess, & McKenzie, 1925/1984; Shaw & McKay, 1942). It contends that

community traits (e.g., residential instability, racial diversity, etc.) permit crime to increase because

they obstruct the development of the relationships among residents who provide a foundation for

informal social control. The body of work testing these claims has since provided “strong empirical

support” for this perspective (Pratt & Cullen, 2005, p. 405). The original formulation of the theory

focused on crime in communities as has the bulk of research testing its claims. However, since some

cities and counties experience more social disorganization than others, scholars have also tested the

theory using larger aggregate units (Barnett & Mencken, 2002; Miethe, Hughes, & McDowall, 1991;

Mosher, 2001). The possible macro-level effects of social disorganization variables have also been

considered by clearance researchers, particularly at the city level where clearance rates are com-

monly reported (Borg & Parker, 2001; Jang et al., 2008; Ousey & Lee, 2010; Roberts, 2008; Roth,

2017). There are several reasons that social disorganization may be relevant to crime clearance. One,

social disorganization is expected to increase crime and so may be related to police workload and the

number of crimes to be cleared. Two, it may be more difficult to clear crimes in cities with much

478 Criminal Justice Review 43(4)