The Impact of Private Precautions on Home Burglary and Robbery in Brazil

Objectives

This study evaluates the effects of precaution technologies (i.e., window bars, extra locks, alarms and electric fences, CCTV, private security, dogs and combinations of these tools) on household burglary and robbery in Brazil.

Methods

Using a sample of 121,042 unique households from the Brazilian National Household Sample Survey for 2009, this study estimates a Recursive Bivariate Probit to obtain the average treatment effect of these precaution technologies in the likelihood of home burglary and robbery victimization.

Results

This study demonstrates that technology does not reduce home burglaries, but certain combinations of technologies may reduce home robberies. The combination of electric fences and alarms with private security reduces the likelihood of home robbery by 9.5 %, and when combined with a dog, these technologies reduce the likelihood of home robbery by 86 %.

Conclusions

No precaution technology is able to prevent crimes when employed independently. Occupancy combined with a set of technologies can reduce the expected victimization in crimes against property.

     

The Gains of Greater Granularity: The Presence and Persistence of Problem Properties in Urban Neighborhoods

Objectives

This study applies the growing emphasis on micro-places to the analysis of addresses, assessing the presence and persistence of “problem properties” with elevated levels of crime and disorder. It evaluates what insights this additional detail offers beyond the analysis of neighborhoods and street segments.

Methods

We used over 2,000,000 geocoded emergency and non-emergency requests received by the City of Boston’s 911 and 311 systems from 2011–2013 to calculate six indices of violent crime, physical disorder, and social disorder for all addresses (n = 123,265). We linked addresses to their street segment (n = 13,767) and census tract (n = 178), creating a three-level hierarchy that enabled a series of multilevel Poisson hierarchical models.

Results

Less than 1% of addresses generated 25% of reports of crime and disorder. Across indices, 95–99% of variance was at the address level, though there was significant clustering at the street segment and neighborhood levels. Models with lag predictors found that levels of crime and disorder persisted across years for all outcomes at all three geographic levels, with stronger effects at higher geographic levels. Distinctively, ~15% of addresses generated crime or disorder in one year and not in the other.

Conclusions

The analysis suggests new opportunities for both the criminology of place and the management of public safety in considering addresses in conjunction with higher-order geographies. We explore directions for empirical work including the further experimentation with and evaluation of law enforcement policies targeting problem properties.

     

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.

     

The Influence of Community Areas,Neighborhood Clusters,and Street Segments on the Spatial Variability of Violent Crime in Chicago

Objectives

The influence of three hierarchical units of analysis on the total spatial variability of violent crime incidents in Chicago is assessed. This analysis seeks to replicate a recent study that found street segments, rather than neighborhood units of analysis, accounted for the largest share of the total spatial variability of crime in The Hague, Netherlands (see Steenbeek and Weisburd J Quant Criminol. doi: 10.1007/s10940-015-9276-3, 2015).

Methods

We analyze violent crime incidents reported to the police between 2001 and 2014. 359,786 incidents were geocoded to 41,926 street segments nested within 342 neighborhood clusters, in turn nested within 76 community areas in Chicago. Linear mixed models with random slopes of time were estimated to observe the variance uniquely attributed to each unit of analysis.

Results

Similar to Steenbeek and Weisburd, we find 56–65 % of the total variability in violent crime incidents can be attributed to street segments in Chicago. City-wide reductions in violence over the observation period coincide with increases in the spatial variability attributed to street segments and decreases in the variability attributed to both neighborhood units.

Conclusions

Our results suggest that scholars interested in understanding the spatial variation of crime across urban landscapes should be focused on the small places that comprise larger geographic areas. The next wave of “neighborhood-effects” research should explore the role of hierarchical processes in understanding crime variation within larger areas.

     

Assessing the Validity of the Law of Crime Concentration Across Different Temporal Scales

Objectives

The present study examined if Weisburd’s (Criminology 53(2):133–157, 2015) law of crime concentration held across different theoretically relevant temporal scales.

Methods

The cumulative percentages of Philadelphia, PA USA street blocks and intersections experiencing 25 and 50 % of street robberies by hour of the day, days of the week, and seasons of the year were compared to the bandwidth percentages established by Weisburd (2015). Different analyses were used to determine the stability of the micro-places’ street robbery levels within the three temporal scales.

Results

We found that the cumulative percentages of street blocks and intersections experiencing 25 and 50 % of street robberies at each of the three temporal scales closely matched the bandwidth percentages expected from Weisburd (2015) and some micro-places experienced street robberies across all temporal periods while others had more isolated temporal concentrations.

Conclusion

Weisburd’s (2015) law of crime concentration holds across different theoretically relevant temporal scales, and future criminology of place studies should not ignore temporal crime patterns. Further, it may be possible to refine hot spots policing approaches by incorporating spatial–temporal crime concentrations.

     

A quasi-experimental evaluation of the impact of bike-sharing stations on micro-level robbery occurrence

Objectives

To examine if the implementation of bike-sharing stations is linked to robbery occurrence in micro-level street corner units in Cincinnati, OH, USA.

Methods

Propensity score matching was used to select comparison street corner units. The effect of bike-sharing station implementation on robbery occurrence across weekly, biweekly, and monthly observations was estimated using repeated measures multi-level logistic regression models.

Results

Bike-sharing stations did not statistically significantly link to robbery occurrence in immediate or nearby street corner units after implementation.

Conclusions

Numerous explanations consistent with Crime Pattern Theory may explain the null effect of bike-sharing stations on robbery occurrence. Future research should continue to examine how changes in the urban backcloth, such as bike-sharing stations, impact geographic crime patterns.

     

Educational Outcomes After Serving with Electronic Monitoring: Results from a Natural Experiment

Objectives

The paper explores the effects of electronic monitoring (EM) on young offenders’ educational outcomes and contributes to the evaluation of EM as a non-custodial sanction with a new outcome measure.

Methods

The study is based on a natural experiment exploiting a reform in Denmark in 2006 introducing electronic monitoring to all offenders under the age of 25 with a maximum prison sentence of 3 months. Information on program participation is used to estimate instrument variable models in order to assess the causal effects of EM on young offenders’ educational outcomes. The empirical analyses are based on a comprehensive longitudinal dataset (n = 1013) constructed from multiple official administrative registers and including a high number of covariates.

Results

The EM-program increases the completion rates of upper secondary education by 18 % points among program participants 3 years post-release. The EM-program includes house arrest under electronic surveillance, labor market or education participation, unannounced drug and alcohol tests and a crime preventive program. It is not possible to separate the treatment effects of the different program elements in the empirical analyses.

     

The financial implications of merging proactive CCTV monitoring and directed police patrol: a cost–benefit analysis

Objectives

This study presents a cost–benefit analysis of an intervention pairing proactive CCTV monitoring with directed police patrol in Newark, NJ. A recent randomized control trial found that the strategy generated significant crime reductions in treatment areas relative to control areas. The current study focuses on the financial implications of the experimental strategy through a cost–benefit analysis.

Methods

The study begins by measuring the costs and benefits associated with the experimental strategy, the findings of which can inform agencies with existing CCTV infrastructure. Follow-up analyses measure the costs and benefits of the intervention for agencies absent existing CCTV infrastructure, meaning a CCTV system would have to be funded in addition to the intervention outputs. Alongside overall benefits, this study presents the tangible cost savings afforded to the Criminal Justice system as well as to each of the separate criminal justice (CJ) system components: Policing, Courts, and Corrections.

Results

We found the experimental strategy to be highly cost effective for agencies with existing CCTV infrastructure. However, when the cost of the CCTV system is considered, the strategy is largely cost prohibitive. While the cumulative societal and criminal justice findings suggest some evidence of a modest cost savings, the strategy is highly cost prohibitive for each of the individual CJ system components when CCTV system costs are included.

Conclusions

Results suggest that the experimental strategy is a worthwhile investment for agencies with existing CCTV infrastructure. Agencies absent CCTV may want to consider whether funds would be better allocated towards alternate strategies.

     

Toward a Demographic Understanding of Incarceration Disparities: Race,Ethnicity, and Age Structure

Objectives

Non-Hispanic blacks and Hispanics in the United States are more likely to be incarcerated than non-Hispanic whites. The risk of incarceration also varies with age, and there are striking differences in age distributions across racial/ethnic groups. Guided by these trends, the present study examines the extent to which differences in age structure account for incarceration disparities across racial and ethnic groups.

Methods

We apply two techniques commonly employed in the field of demography, age-standardization and decomposition, to data provided by the Bureau of Justice Statistics and the 2010 decennial census to assess the contribution of age structure to racial and ethnic disparities in incarceration.

Findings

The non-Hispanic black and Hispanic incarceration rates in 2010 would have been 13–20 % lower if these groups had age structures identical to that of the non-Hispanic white population. Moreover, age structure accounts for 20 % of the Hispanic/white disparity and 8 % of the black/white disparity.

Conclusion

The comparison of crude incarceration rates across racial/ethnic groups may not be ideal because these groups boast strikingly different age structures. Since the risk of imprisonment is tied to age, criminologists should consider adjusting for age structure when comparing rates of incarceration across groups.

     

Examining the Relationship Between the Structural Characteristics of Place and Crime by Imputing Census Block Data in Street Segments: Is the Pain Worth the Gain?

Objective

The current study proposes unique methods for apportioning existing census data in blocks to street segments and examines the effects of structural characteristics of street segments on crime. Also, this study tests if the effects of structural characteristics of street segments are similar with or distinct from those of blocks.

Methods

This study compiled a unique dataset in which block-level structural characteristics are apportioned to street segments utilizing the 2010 U.S. Census data of the cities of Anaheim, Santa Ana, and Huntington Beach in Orange County, California. Negative binomial regression models predicting crime that include measures of social disorganization and criminal opportunities in street segments and blocks were estimated.

Results

The results show that whereas some of the coefficients tested at the street segment level are similar to those aggregated to blocks, a few were quite different (most notably, racial/ethnic heterogeneity). Additional analyses confirm that the imputation methods are generally valid compared to data actually collected at the street segment level.

Conclusions

The results from the street segment models suggest that the structural characteristics from social disorganization and criminal opportunities theories at street segments may operate as crucial settings for crime. Also the results indicate that structural characteristics have generally similar effects on crime in street segments and blocks, yet have some distinct effects at the street segment level that may not be observable when looking at the block level. Such differences underscore the necessity of serious consideration of the issues of level of aggregation and unit of analysis when examining the structural characteristics-crime nexus.

     

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.

     

Measuring Disorder: Observer Bias in Systematic Social Observations at Streets and Neighborhoods

Objectives

The present study focuses on Systematic Social Observation (SSO) as a method to investigate physical and social disorder at different units of analysis. The study contributes to the aggregation bias debate and to the ‘social science of ecological assessment’ in two ways: first, by presenting a new model that directly controls for observer bias in ecological constructs and second, by attempting to identify systematic sources of bias in SSO that affect the valid and reliable measurement of physical and social disorder at both street segments and neighborhoods.

Methods

Data on physical disorder (e.g., litter, cigarette butts) and social disorder (e.g., loitering adults) from 1422 street segments in 253 different neighborhoods in a conurbation of the greater The Hague area (the Netherlands) are analyzed using cross-classified multilevel models.

Results

Neighborhood differences in disorder are overestimated when scholars fail to recognize the cross-classified data structure of an SSO study that is due to allocation of street segments to observers and neighborhoods. Not correcting for observer bias and observational conditions underestimates the disorder–crime association at street segment/grid cell level, but overestimates this association at the neighborhood level.

Conclusion

Findings indicate that SSO can be used for measuring disorder at both street segment level and neighborhood level. Future studies should pay attention to observer bias prior to their data collection by selecting a minimum number of observers, offering extensive training, and collecting information on the urban background of the observers.

     

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.

     

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.

     

Recidivism in a Sample of Serious Adolescent Offenders

Objectives

A broad research literature in criminology documents key aspects of how criminal offending develops and changes over the life span. We contribute to this literature by showcasing methods that are useful for studying medium-term patterns of subsequent criminal justice system involvement among a sample of serious adolescent offenders making the transition to early adulthood.

Methods

Our approach relies on 7 years of post-enrollment follow-up from the Pathways to Desistance Study. Each person in the study was adjudicated delinquent for or convicted of one or more relatively serious offenses during adolescence. Their local jurisdiction juvenile court petition records and their adult FBI arrest records were systematically searched.

Results

We estimate in-sample 7 year recidivism rates in the 75–80 % range. Our analysis also provides recidivism rate estimates among different demographic groups within the sample. Extrapolated long-term recidivism rates are estimated to be on the order of 79–89 %.

Conclusions

The Pathways data suggest that recidivism rates of serious adolescent offenders are high and quite comparable to the rates estimated on other samples of serious offenders in the extant literature. Our analysis also reveals a pattern of heightened recidivism risk during the earliest months and years of the follow-up period followed by a steep decline.

     

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.

     

Do Crime Hot Spots Exist in Developing Countries? Evidence from India

Objectives

To determine whether concentrations of crime documented in American cities such as Boston, Jacksonville, Minneapolis, Sacramento, and Seattle generalize to unique environments such as India.

Methods

Two years of motor vehicle theft (MVT) and burglary incidents from two police stations in Jaipur, India are analyzed. The degree to which crime clusters is documented using nearest neighborhood hierarchical clustering (NNHC). These results are compared to several widely cited studies documenting concentrations in the United States.

Results

The NNHC procedure identified five MVT hot spots, which accounted for just .09 % of the two station’s land, but over 13 % of these incidents, and four burglary hot spots, which accounted for less than 1 % of its land, but nearly 23 % of the incidents.

Conclusions

Given the stark differences in the built environment and sociological makeup of Jaipur, a better understanding of the forces that cause crime to concentrate to a high degree needs to be discerned before implementing law-enforcement driven policies derived from the scholarship of American cities. Additional research should also seek to replicate not just the degree to which crime clusters in these unique environments, but also its stability over time and micro place variation.

     

Replicating Group-Based Trajectory Models of Crime at Micro-Places in Albany,NY

Objectives

Replicate two previous studies of temporal crime trends at the street block level. We replicate the general approach of group-based trajectory modelling of crimes at micro-places originally taken by Weisburd et al. (Criminology 42(2):283–322, 2004) and replicated by Curman et al. (J Quant Criminol 31(1):127–147, 2014). We examine patterns in a city of a different character (Albany, NY) than those previously examined (Seattle and Vancouver) and so contribute to the generalizability of previous findings.

Methods

Crimes between 2000 and 2013 were used to identify different trajectory groups at street segments and intersections. Zero-inflated Poisson regression models are used to identify the trajectories. Pin maps, Ripley’s K and neighbor transition matrices are used to show the spatial patterning of the trajectory groups.

Results

The trajectory solution with eight classes is selected based on several model selection criteria. The trajectory of each those groups follow the overall citywide decline, and are only separated by the mean level of crime. Spatial analysis shows that higher crime trajectory groups are more likely to be nearby one another, potentially suggesting a diffusion process.

Conclusions

Our work adds additional support to that of others who have found tight coupling of crime at micro-places. We find that the clustering of trajectories identified a set of street units that disproportionately contributed to the total level of crime citywide in Albany, consistent with previous research. However, the temporal trends over time in Albany differed from those exhibited in previous work in Seattle but were consistent with patterns in Vancouver.

     

Timing of Change in Criminal Offending Around Entrance into Parenthood: Gender and Cross-Country Comparisons for At-Risk Individuals

Objectives

This article examines the timing of change in criminal offending relative to entrance into parenthood, in light of four competing theoretical frameworks (social control, routine activities, strain and cognitive transformation). Moreover, it analyzes whether criminal developments over time are gender- or country-specific.

Methods

Using samples of men and women at risk of offending in the Netherlands and Norway, this study investigates monthly changes in offending probabilities around the time of first birth (5 years before, 5 years after). The implemented smoothing splines technique allowed for a flexible exploration of changes in offending probabilities for both pre-childbirth and post-childbirth periods.

Results

The results show that the probabilities to offend decline ahead of childbirth for all individuals analyzed. The post-childbirth period is characterized by increases in offending probabilities. However, in these overall trends, the exact timing and magnitude of change differs by gender and country of residence.

Conclusions

The results offer partial support for the cognitive transformation hypothesis because offending rates decline before childbirth. The post-childbirth period converges with assumptions of the strain theory (for males in particular) because offending probabilities increase in this period. Additional analysis investigating changes in property offending shows that economic strain does not explain the upward trend of the overall offending after childbirth.