The Law of Crime Concentration: An Application and Recommendations for Future Research

Objective

We address four outstanding empirical questions related to the “law of crime concentration” (Weisburd in Criminology 53:133–157, 2015): (1) Is the spatial concentration of crime stable over time? (2) Do the same places consistently rank among those with the highest crime counts? (3) How much crime concentration would be observed if crimes were distributed randomly over place? (4) To what degree does the spatial concentration of crime depend on places that are crime free?

Methods

The data are annual counts of violent and property crimes in St. Louis between 2000 and 2014. Temporal stability in the spatial inequality of crime is measured by computing the fraction of crimes that occur in the 5% of street segments with the highest crime frequencies each year. The spatial mobility of crime is measured by computing the number of years each street segment appears in the top 5% of street segments. Poisson simulations are used to estimate the fraction of crimes that could appear in the top 5% of street segments on the basis of chance alone. The impact of crime-free locales on the spatial concentration of crime is evaluated by comparing results from analyses that include and exclude crime-free street segments from the crime distributions.

Results

The concentration of crime is highly unequal and stable over time. The specific street segments with the highest crime frequencies, however, change over time. Nontrivial fractions of street segments may appear among the 5% with the highest crime frequencies on the basis of chance. Spatial concentration of crime is reduced when crime-free street segments are excluded from the crime distributions.

Conclusions

The law of crime concentration is not a measurement artifact. Its substantive significance, however, should be assessed in future longitudinal research that replicates the current study across diverse social settings.

     

Measuring Crime Concentration Across Cities of Varying Sizes: Complications Based on the Spatial and Temporal Scale Employed

Objectives

We argue that assessing the level of crime concentration across cities has four challenges: (1) how much variability should we expect to observe; (2) whether concentration should be measured across different types of macro units of different sizes; (3) a statistical challenge for measuring crime concentration; (4) the temporal assumption employed when measuring high crime locations.

Methods

We use data for 42 cities in southern California with at least 40,000 population to assess the level of crime concentration in them for five different Part 1 crimes and total Part 1 crimes over 2005–2012. We demonstrate that the traditional measure of crime concentration is confounded by crimes that may simply spatially locate due to random chance. We also use two measures employing different temporal assumptions: a historically adjusted crime concentration measure, and a temporally adjusted crime concentration measure (a novel approximate solution that is simple for researchers to implement).

Results

There is much variability in crime concentration over cities in the top 5 % of street segments. The standard deviation across cities over years for the temporally adjusted crime concentration measure is between 10 and 20 % across crime types (with the average range typically being about 15–90 %). The historically adjusted concentration has similar variability and typically ranges from about 35 to 100 %.

Conclusions

The study provides evidence of variability in the level of crime concentration across cities, but also raises important questions about the temporal scale when measuring this concentration. The results open an exciting new area of research exploring why levels of crime concentration may vary over cities? Either micro- or macro- theories may help researchers in exploring this new direction.

     

Where the Action is in Crime? An Examination of Variability of Crime Across Different Spatial Units in The Hague, 2001–2009

Objectives

To identify how much of the variability of crime in a city can be attributed to micro (street segment), meso (neighborhood), and macro (district) levels of geography. We define the extent to which different levels of geography are important in understanding the crime problem within cities and how those relationships change over time.

Methods

Data are police recorded crime events for the period 2001–2009. More than 400,000 crime events are geocoded to about 15,000 street segments, nested within 114 neighborhoods, in turn nested within 44 districts. Lorenz curves and Gini coefficients are used to describe the crime concentration at the three spatial levels. Linear mixed models with random slopes of time are used to estimate the variance attributed to each level.

Results

About 58–69 % of the variability of crime can be attributed to street segments, with most of the remaining variability at the district level. Our findings suggest that micro geographic units are key to understanding the crime problem and that the neighborhood does not add significantly beyond what is learned at the micro and macro levels. While the total number of crime events declines over time, the importance of street segments increases over time.

Conclusions

Our findings suggest that micro geographic units are key to understanding the variability of crime within cities—despite the fact that they have received little criminological focus so far. Moreover, our results raise a strong challenge to recent focus on such meso geographic units as census block groups.

     

Court Sentencing Patterns for Environmental Crimes: Is There a “Green” Gap in Punishment?

Objectives

This study examines sentencing patterns for environmental crimes and tests the assumption that “green” offenders receive more lenient treatment from criminal courts than non-environmental offenders.

Methods

We present two sets of analyses. First, we present an empirical portrait of environmental felony offenses convicted in a single state (Florida) over a fifteen-year period and the resulting criminal sanctions. Second, we use a precision matching analysis to assess whether environmental offenders receive more lenient treatment when compared to non-environmental offenders with the same characteristics and offense severity scores.

Results

Findings indicate that an overall small percentage of felony convictions in state courts stem from environmental crimes. We also find that punishments for environmental crimes are more lenient than sanctions assigned to comparable non-environmental offenses when the environmental crime is ecological, but that punishments are sometimes harsher when the environmental crime involves animals.

Conclusions

The findings provide general support for the argument that courts and other formal institutions of social control treat environmental crimes more leniently than non-environmental crimes. This paper also raises important questions about citizen and state actors’ perceptions of crimes against the environment and, more generally, about the ways in which theories of court sentencing behaviors apply to environmental crime sanctioning decisions.

     

Acquisitive Crime and Inflation in the United States: 1960–2012

Objectives

Inflation is conspicuous by its absence from recent research on crime and the economy. We argue that price inflation increases the rate of crimes committed for monetary gain by fueling demand for cheap stolen goods.

Methods

The study includes inflation along with indicators of unemployment, GDP, income, consumer sentiment, and controls in error correction models of acquisitive crime covering the period from 1960 to 2012. Both short- and long-run effects of the predictors are estimated.

Results

Among the economic indicators, only inflation has consistent and robust short- and long-run effects on year-over-year change in the offense types under consideration. Low inflation helps to explain why acquisitive crime did not increase during the 2008–2009 recession. Imprisonment rates also have robust long-run effects on change in acquisitive crime rates.

Conclusions

Incorporating inflation into studies of crime and the economy can help to reduce the theoretical and empirical uncertainty that has long characterized this important research area in criminology.

     

Crimes by Visitors Versus Crimes by Residents: The Influence of Visitor Inflows

Objectives

To disaggregate the crime impact of visitor inflows. There is increasing evidence that visitors can make a major contribution to levels of crime in a given neighbourhood: crimes by visiting offenders may add to those committed by local offenders, while visitors (and their property) may provide local offenders with additional opportunities for crime.

Methods

Using police-recorded crime data for a large Eastern Canadian city we determined whether individuals charged or chargeable for property and violent crimes were visitors or residents of census tracts (CT) where crimes had been committed. This information was combined with data from a large transportation survey, allowing us to estimate daily population flows into each CT for four purposes (work, shopping, recreation, and education). Negative binomial regression models including spatial lags were used.

Results

An increase in visitor inflow not only increases the number of visitors charged with crimes but also the number of local residents charged. These effects vary significantly by visit purpose: more infractions are committed in tracts where visits are for recreation and, to a lesser extent, for shopping. Findings for work and education are mixed.

Conclusions

One important implication of our results is that, because most studies of aggregate crime counts or rates fail to account for whether crimes have been committed by visitors or residents, previous research may have provided hasty, partial, or even erroneous explanations for crime concentrations.

     

The Murder Mystery: Police Effectiveness and Homicide

Objective

Previous aggregate analyses of the effect of police on crime show that increases in police staffing are especially effective at preventing homicide. This conflicts with evidence that suggests standard police methods should be more effective at preventing robbery, auto theft, and other property crimes. My objective is to reconcile the two.

Methods

Regression of crime rates on uniformed police staffing and other economic and demographic covariates, for a panel of 59 US cities for the period 1970–2013.

Results

Lagged crime rates are strong and statistically significant predictors of both policing staffing and crime rates, particularly homicide. When lags are included in the specification, the apparent effect of police on homicide drops by more than 70 %; there is little change in the effect of police on other crimes. Findings are robust with respect to specification and method.

Conclusions

Previous studies omitted lags and overstated the effectiveness of police on homicide. Because murder accounts for almost 40 % of all costs of crime in US cities, it is no longer clear whether increasing police force size is a cost-effective way to cut crime. Improving police tactics is more likely to work and less expensive.

     

Do Schools Cause Crime in Neighborhoods? Evidence from the Opening of Schools in Philadelphia

Objectives

To assess the impact of schools on crime in neighborhoods.

Methods

We utilize data of charter and public schools in Philadelphia to estimate the effect of school openings on neighborhood crime patterns between 1998 and 2010. We estimate the change in crime in areas surrounding schools before and after their opening compared to areas where schools were always open with Poisson regression models. We also estimate changes in crime in census tracts as schools are added compared to census tracts that never had schools. Finally, we compare estimates from Poisson regression models to those derived from permutation tests where schools are randomly assigned different opening dates.

Results

We find no evidence that school openings increase crime relative to locations where schools were always open or never had schools. The models generally produce null effects, though there is some evidence for a reduction in property crimes for public school openings and a reduction in violent crimes for charter school openings within certain distances. Estimates at the census tract level show that changes in the number of schools are not associated with any changes in crime relative to tracts with no schools.

Conclusions

Contrary to a large theoretical and empirical literature, the results suggest that school locations play a minimal role in neighborhood crime production in Philadelphia. Future research should investigate specific contexts and mechanisms, such as land-use characteristics and travel patterns to schools, which may interact with specific school settings in ways that are related to crime production.

     

The Trajectories of Crime at Places: Understanding the Patterns of Disaggregated Crime Types

Objectives

Investigate the spatial concentrations and the stability of trajectories for disaggregated crime types on street segments and intersections in Vancouver, Canada.

Methods

A longitudinal analysis of 16 years of crime data using street segments and intersections as the units of analysis. We use the k-means non-parametric cluster analysis technique considering eight crime types: assault, burglary, robbery, theft, theft of vehicle, theft from vehicle, other, and total crime.

Results

The overall results for the individual crime types versus overall crime are similar: crime is highly concentrated regardless of crime type, most street segment and intersection trajectories are stable over time with the others decreasing, and most decreasing trajectories are in the same general areas. However, there are notable differences across crime types that need to be considered when attempting to understand spatial pattern changes and implement crime prevention initiatives.

Conclusions

The law of crime concentration at places holds in Vancouver, Canada for disaggregated crime types in the context of spatial concentrations and their stability over time. However, notable differences exist across crime types that should be accounted for when developing theory or policy.

     

Testing the “Law of Crime Concentration at Place” in a Suburban Setting: Implications for Research and Practice

Objective

To assess whether the “law of crime concentration at place” applies in a non-urban context. We test whether longitudinal trends in crime concentration, stability, and variability apply in a suburban setting.

Methods

We use group-based trajectory analysis to examine trends in recorded crime incidents on street segments in Brooklyn Park, a suburban city outside Minneapolis, Minnesota, over a 15-year period from 2000 to 2014.

Results

Consistent with the law of crime concentration at place, crime in Brooklyn Park is highly concentrated at a small percentage of micro-places. Two percent of street segments produced 50 % of the crime over the study period and 0.4 % of segments produced 25 % of the crime. The patterns of concentration are highly stable over time. However, the concentration of crime is substantially higher and there is much less street-by-street variability in Brooklyn Park compared to urban areas.

Conclusions

We find strong support for the application of the law of crime concentration at place to a non-urban setting, suggesting that place-based policing approaches tested in cities can also be applied to suburbs. However, there are also important differences in the concentration and variability of crime hot spots in suburbs that require further examination. Our study is based on a single setting that may not be representative of other suburban and rural areas. Finally, the clustering of hot spots raises questions about the use of street segments to analyze crime at suburban micro-places.

     

Measuring the Distribution of Crime and Its Concentration

Objectives

Generally speaking, crime is, fortunately, a rare event. As far as modelling is concerned, this sparsity of data means that traditional measures to quantify concentration are not appropriate when applied to crime suffered by a population. Our objective is to develop a new technique to measure the concentration of crime which takes into account its low frequency of occurrence and its high degree of concentration in such a way that this measure is comparable over time and over different populations.

Methods

This article derives an estimate of the distribution of crime suffered by a population based on a mixture model and then evaluates a new and standardised measurement of the concentration of the rates of suffering a crime based on that distribution.

Results

The new measure is successfully applied to the incidence of robbery of a person in Mexico and is able to correctly quantify the concentration crime in such a way that is comparable between different regions and can be tracked over different time periods.

Conclusions

The risk of suffering a crime is not uniformly distributed across a population. There are certain groups which are statistically immune to suffering crime but there are also groups which suffer chronic victimisation. This measure improves our understanding of how patterns of crime can be quantified allowing us to determine if a prevention policy results in a crime reduction rather than target displacement. The method may have applications beyond crime science.

     

Expanding the focus of correctional evaluations beyond recidivism: the impact of halfway houses on public safety

Objective

This article reports the findings of a quasi-experimental evaluation of the impact of residential halfway houses (HHs) on public safety in the immediate vicinity of the facilities.

Methods

Instead of focusing on recidivism reduction or cost effectiveness, as is common, outcome measures for this study are limited to the impact on community crime rates, here defined as offenses committed within 1/8 and 1/4 mi radii around a subject facility. A set of fixed effect Poisson regression models were employed to assess the changes in monthly crime counts associated with the opening or closing of an HH (N =?19). A second difference-in-differences analysis (DiD) compares HHs that ceased operation to HHs that remained consistently open for the duration of the study period. A series of robustness checks were conducted.

Results

We find the presence of an active HH is associated with an increase in crime within the immediate vicinity. We identify significant increases in monthly counts of overall crimes reported to law enforcement, as well as in counts for specific crimes of violence, including assaults and robberies with a firearm; property offenses, such as burglary; and in minor and misdemeanor offenses. A closing of an HH is associated with a decrease in reported crimes.

Conclusions

The location of a community-based correctional facility can have a significant and negative impact on public health, largely through decreased levels of local public safety. Evaluations of residential correctional programs should include indicators of community-level impact in addition to individual-level measures of recidivism, particularly when such programs are clustered in at-risk or vulnerable communities.

     

Crime Clearance and Temporal Variation in Police Investigative Workload: Evidence from National Incident-Based Reporting System (NIBRS) Data

Objectives

Police workload’s relationship with crime clearance has been studied widely. In the challenging environment now facing police, even small and possibly temporary changes in investigative workload could harm clearance. However existing workload-clearance research either used only a yearly average that obscures temporal variability in caseload, or explored proxy rather than direct measures of workload’s short-term variation. Our improved workload measures capture caseload’s daily changes as crimes are reported, cleared, or remain uncleared but reach the end of active investigation. We examine relationships between clearance and both long- and short-term variability in workload.

Methods

Using NIBRS and LEMAS data, we calculated between-agency (typical or long-term) and time-varying, within-agency (daily fluctuating or short-term) workload measures. We used these and other agency/jurisdiction- and incident-level variables in multi-level survival analysis of clearance by arrest for serious violent incidents from 2007 NIBRS.

Results

Both workload measures were significantly and negatively related to the clearance hazard rate; higher long- and short-term workloads are associated with reduced chance of a case being cleared. The estimated relationship between longterm workload and clearance became progressively stronger (more negative) as the crime incident’s legal seriousness decreased. However, estimates indicated greater sensitivity of the clearance hazard to short-term workload fluctuations for more serious crimes, though the workload-clearance relationship remained negative for all crime types.

Conclusion

Crime clearance should be considered by police agency planners when addressing workload through staffing decisions. Refinement of our workload measures will require additional information, and should be considered in future agency- and incident-level data collection.

     

Predictive Crime Mapping: Arbitrary Grids or Street Networks?

Objectives

Decades of empirical research demonstrate that crime is concentrated at a range of spatial scales, including street segments. Further, the degree of clustering at particular geographic units remains noticeably stable and consistent; a finding that Weisburd (Criminology 53:133–157, 2015) has recently termed the ‘law of crime concentration at places’. Such findings suggest that the future locations of crime should—to some extent at least—be predictable. To date, methods of forecasting where crime is most likely to next occur have focused either on area-level or grid-based predictions. No studies of which we are aware have developed and tested the accuracy of methods for predicting the future risk of crime at the street segment level. This is surprising given that it is at this level of place that many crimes are committed and policing resources are deployed.

Methods

Using data for property crimes for a large UK metropolitan police force area, we introduce and calibrate a network-based version of prospective crime mapping [e.g. Bowers et al. (Br J Criminol 44:641–658, 2004)], and compare its performance against grid-based alternatives. We also examine how measures of predictive accuracy can be translated to the network context, and show how differences in performance between the two cases can be quantified and tested.

Results

Findings demonstrate that the calibrated network-based model substantially outperforms a grid-based alternative in terms of predictive accuracy, with, for example, approximately 20 % more crime identified at a coverage level of 5 %. The improvement in accuracy is highly statistically significant at all coverage levels tested (from 1 to 10 %).

Conclusions

This study suggests that, for property crime at least, network-based methods of crime forecasting are likely to outperform grid-based alternatives, and hence should be used in operational policing. More sophisticated variations of the model tested are possible and should be developed and tested in future research.

     

Improving forensic responses to residential burglaries: results of a randomized controlled field trial

Objectives

Residential burglaries (or break and enters) can cause great concern to the public but are typically a routine police job. The present study sought to evaluate an enhanced police approach to this high-volume crime by emphasizing police–victim interactions and more thorough forensic examinations.

Methods

Scenes of crime officers (forensic examiners) were randomly assigned to either a control (business-as-usual) or experimental condition. Officers in the experimental condition received additional training and resources to upskill them in DNA and fingerprint evidence collection and crime scene evaluation. Experimental officers also received additional training on procedurally just approaches to dealing with victims and were encouraged to be more thorough and spend more time at these high-volume crime scenes.

Results

The trial revealed that the enhanced, experimental, approach offered a number of benefits, including greater evidence collection, identification, and incidents solved. Further, this enhanced approach boosted victims’ perceptions of officers’ procedural justice and satisfaction with the procedures used. However, this approach was more costly in relation to time, and the additional collection of extra DNA evidence did not greatly add to the crime solvability of these incidents.

Conclusions

High-volume crimes such as break and enters have a significant impact on the victims and often go unsolved. This study provides causal evidence that enhancing officers’ attendance and attention to victims and evidence at these scenes can increase solvability and enhance victim experiences.

     

Consequences of legal risk communication for sanction perception updating and white-collar criminality

Objectives

Scholars have long emphasized that communicating, or “advertising”, information about legal sanction risk is necessary for the success of deterrence-based crime policies. However, scant research has evaluated whether direct communications about legal risk can cause sanction perception updating, the updating of ambiguity in sanction perceptions, or changes in persons’ willingness to offend. No prior studies have evaluated sanction perception updating for white-collar crimes.

Methods

To address this research void, the current study analyzes data from an experiment embedded in a recent national survey (N?=?878). Multivariate regression models estimate the effect of providing participants with information about the “objective” arrest risk for white-collar offenses on their sanction perceptions.

Results

The findings provide the first evidence that such information, when it is inconsistent with individuals’ prior beliefs, causes them to update: (1) their perceptions of the certainty of arrest; (2) their ambiguity about arrest risk; and, indirectly, (3) their willingness to commit white-collar crimes.

Conclusions

The results imply that individuals are willing to incorporate relevant information into their subjective beliefs about sanction risks. Importantly, however, they also make meaningful distinctions about the value of new information for understanding criminal risks.

     

Effect of emergency winter homeless shelters on property crime

Objective

To evaluate the effect of emergency winter homeless shelters on property crimes in the nearby communities.

Methods

Every winter between 2009 and 2016, the City of Vancouver, Canada opened shelters to protect the homeless from harsh winter conditions. The city opened 19 shelters, but only five to nine of them were open in any one winter. Using the variation in timing and placement of the shelters, we contrast crime rates in the surrounding areas when the shelters are open and closed.

Results

The presence of a shelter appears to cause property crime to increase by 56% within 100 m of that shelter, with thefts from vehicles, other thefts, and vandalism driving the increase. However, when a homeless shelter opened, rates of breaking and entering commercial establishments were 34% lower within 100 m of that shelter. The observed effects are concentrated close to shelters, within 400 m, and dissipate beyond 400 m. Consistent with a causal effect, we find a decreasing effect of shelters with increasing distance from the shelter.

Conclusions

While homeless shelters are a critical social service, in Vancouver, they appear to impact property crime in the surrounding community. Shelters may warrant greater security to control property crime, but the data suggest that any increase in security need not extend beyond 400 m, about two to three blocks, from the shelters.

     

Does Eligibility for Tertiary Education Affect Crime Rates? Quasi-Experimental Evidence

Objectives

This paper estimates the effect of tertiary education eligibility on crime in Sweden. The hypothesis tested is that continuing to higher education decreases crime rates since it allows young people to escape inactivity and idleness, which are known to trigger crime. However, to qualify for tertiary education, individuals have to meet the eligibility requirements in upper-secondary school. Tertiary education eligibility may therefore affect crime rates.

Methods

This paper uses a panel data set of 287 Swedish municipalities over the period 1998–2010 to estimate the tertiary education eligibility effect on crime. However, estimating educational effects on crime is challenging, because investment in education is an endogenous decision. In Sweden, substantial grade inflation, increased tertiary education eligibility by more than 6% points between 1998 and 2003. Thus, since the eligibility increase is exogenous to the educational achievements of a student cohort, i.e. not accompanied by a corresponding knowledge increase, we can use the increase to identify the effect of tertiary education eligibility on crime.

Results

It is found that increasing the tertiary education eligibility rate decreases both property and violent crime substantially.

Conclusions

The results show that when young people have the opportunity to attend tertiary education, and thus escape unemployment or inactivity, their propensity to commit crime decreases.

     

Measuring the Spatial and Temporal Patterns of Police Proactivity

Objectives

To measure where officers engage in proactive, self-initiated activities, how much time they spend being proactive, and whether their proactive activities coincide with crime patterns.

Methods

This study uses Andresen’s Spatial Point Pattern Test to compare the spatial similarity between police proactivity and crime, as well as regression modeling to explore the relationship between proactivity and crime and the time spent on proactivity and crime.

Results

In the jurisdiction examined, high levels of proactivity are noted. This proactive activity is more likely to occur in places where crime is most concentrated. Additionally, the number of proactive calls and the proactive time spent per crime-and-disorder call remain high and stable across spatial scales. For each crime call received at a street block, police initiated 0.7 proactive activities and spent approximately 28 min carrying out proactive works.

Conclusions

This study develops a way of measuring proactive activity by patrol officers using calls for service data. We find that not only do officers in this jurisdiction exhibit higher levels of proactivity to prevent crime (compared to reacting to crime), but they also do so in targeted, micro-place ways. Agencies may consider using similar techniques to gauge the levels of proactivity in their agencies if proactive activity is a goal.