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.

     

Immigration and the Changing Nature of Homicide in US Cities, 1980–2010

Objectives

Previous research has neglected to consider whether trends in immigration are related to changes in the nature of homicide. This is important because there is considerable variability in the temporal trends of homicide subtypes disaggregated by circumstance. In the current study, we address this issue by investigating whether within-city changes in immigration are related to temporal variations in rates of overall and circumstance-specific homicide for a sample of large US cities during the period between 1980 and 2010.

Methods

Fixed-effects negative binomial and two-stage least squares (2SLS) instrumental variable regression models are used to analyze data from 156 large US cities observed during the 1980–2010 period.

Results

Findings from the analyses suggest that temporal change in overall homicide and drug homicide rates are significantly related to changes in immigration. Specifically, increases in immigration are associated with declining rates for each of the preceding outcome measures. Moreover, for several of the homicide types, findings suggest that the effects of changes in immigration vary across places, with the largest negative associations appearing in cities that had relatively high initial (i.e., 1970) immigration levels.

Conclusions

There is support for the thesis that changes in immigration in recent decades are related to changes in rates of lethal violence. However, it appears that the relationship is contingent and varied, not general.     

Seasonal Variation in Violent Victimization: Opportunity and the Annual Rhythm of the School Calendar

Objectives

This study draws on an underused source of data on seasonality—victim surveys—to assess whether violent crime occurs with greater frequency during summer months or whether it simply becomes known to police more often, and to examine the extent to which seasonal patterns in violent crime are differentiated based on victim characteristics and location of crime.

Methods

Data used come from the 1993–2008 National Crime Victimization Survey. Time series regression models are estimated to describe seasonal differences in violent crime victimization and reporting rates.

Results

Seasonal trends in youth violence stand in contrast to the trends for young and older adults, primarily due to their high risk of victimization at and near school. No evidence of seasonality is found in the extent to which serious violence becomes known to the police. However, simple assault is significantly more likely to come to the attention of the police during the summer months, primarily due to increases in the reporting of youth violence.

Conclusions

Our findings confirm some of the previous work on seasonal patterns in violent crime, but also show that these patterns vary across age groups, locations, and type of violence.     

The Effects of Immigrant Concentration on Changes in Neighborhood Crime Rates

Objectives

This study investigated the extent to which immigrant concentration is associated with reductions in neighborhood crime rates in the City of Los Angeles.

Methods

A potential outcomes model using two-stage least squares regression was estimated, where immigrant concentration levels in 1990 were used as an instrumental variable to predict immigrant concentration levels in 2000. The instrumental variables design was used to reduce selection bias in estimating the effect of immigrant concentration on changes in official crime rates between 2000 and 2005 for census tracts in the City of Los Angeles, holding constant other demographic variables and area-level fixed effects. Non-parametric smoothers were also employed in a two-stage least squares regression model to control for the potential influence of heterogeneity in immigrant concentration on changes in crime rates.

Results

The results indicate that greater predicted concentrations of immigrants in neighborhoods are linked to significant reductions in crime. The results are robust to a number of different model specifications.

Conclusions

The findings challenge traditional ecological perspectives that link immigrant settlement to higher rates of crime. Immigration settlement patterns appear to be associated with reducing the social burden of crime. Study conclusions are limited by the potential for omitted variables that may bias the observed relationship between immigrant concentration and neighborhood crime rates, and the use of only official crime data which may under report crimes committed against immigrants. Understanding whether immigrant concentration is an important dynamic of changing neighborhood patterns of crime outside Los Angeles will require replication with data from other U.S. cities.     

Gender and Age Segregation and Stratification in Criminal Collaborations

Objectives

Assess gender and age segregation and stratification among co-offenders.

Methods

The population comprises co-offenders aged 5–75 in police-reported co-offenses in Canada, 2006–2009. Segregation is indicated by observed and inbreeding homophily, measured with cross-tabulations and log-linear distance models. Stratification is assessed with elaborations by crime type. Intersectionality of gender and age status is estimated with interaction terms in the log-linear models.

Results

Female and younger offenders are over-represented among co-offenders. Co-offending exhibits gender and age status homophily: same-gender dyads are approximately twice as frequent as mixed-gender, and same-age-status dyads are almost 7 times as frequent as mixed-age-status. Gender homophily varies by crime type, being stronger in robbery, aggravated assault, common assault, and minor theft, and weaker in serious drug crime and homicide, and (especially) sex crimes against children. Age homophily is strong in all types of crime. Gender and age homophily have a negative interaction: dyads comprising a female child or youth and an adult male occur 1.4 times as frequently as predicted from the main effects of gender and age status.

Conclusions

Female and younger offenders are not excluded from co-offending per se but, consistent with expectations from Blau’s (Inequality and heterogeneity. Free Press, New York, 1977) and Steffensmeier’s (Soc Forces 6:1010–1032, 1983) theories, they are segregated from co-offending with male and (especially) adult offenders. There was limited evidence of gender stratification, and no evidence of age stratification. The interaction of gender and age status in the segregation and stratification of co-offending attenuates their individual effects, contrary to expectations from feminist intersectionality theory and consistent with Blau’s (1977) theory.

     

When Choice of Data Matters: Analyses of U.S. Crime Trends, 1973–2012

Objectives

This study uses UCR and NCVS crime data to assess which data source appears to be more valid for analyses of long-term trends in crime. The relationships between UCR and NCVS trends in violence and six factors from prior research are estimated to illustrate the impact of data choice on findings about potential sources of changes in crime over time.

Methods

Crime-specific data from the UCR and NCVS for the period 1973–2012 are compared to each other using a variety of correlational techniques to assess correspondence in the trends, and to UCR homicide data which have been shown to be externally valid in comparison with other mortality records. Log-level trend correlations are used to describe the associations between trends in violence, homicide and the potential explanatory factors.

Results

Although long-term trends in robbery, burglary and motor vehicle theft in the UCR and NCVS are similar, this is not the case for rape, aggravated assault, or a summary measure of serious violence. NCVS trends in serious violence are more highly correlated with homicide data than are UCR trends suggesting that the NCVS is a more valid indicator of long-term trends in violence for crimes other than robbery. This is largely due to differences during the early part of the time series for aggravated assault and rape when the UCR data exhibited consistent increases in the rates in contrast to general declines in the NCVS. Choice of data does affect conclusions about the relationships between hypothesized explanatory factors and serious violence. Most notably, the reported association between trends in levels of gasoline lead exposure and serious violence is likely to be an artifact associated with the reliance on UCR data, as it is not found when NCVS or homicide trend data are used.

Conclusions

The weight of the evidence suggests that NCVS data represent more valid indicators of the trends in rape, aggravated assault and serious violence from 1973 to the mid-1980s. Studies of national trends in serious violence that include the 1973 to mid-1980s period should rely on NCVS and homicide data for analyses of the covariates of violent crime trends.

     

Bayesian Spatio-Temporal Modeling for Analysing Local Patterns of Crime Over Time at the Small-Area Level

Objectives

Explore Bayesian spatio-temporal methods to analyse local patterns of crime change over time at the small-area level through an application to property crime data in the Regional Municipality of York, Ontario, Canada.

Methods

This research represents the first application of Bayesian spatio-temporal modeling to crime trend analysis at a large map scale. The Bayesian model, fitted by Markov chain Monte Carlo simulation using WinBUGS, stabilized risk estimates in small (census dissemination) areas and controlled for spatial autocorrelation (through spatial random effects modeling), deprivation, and scarce data. It estimated (1) (linear) mean trend; (2) area-specific differential trends; and (3) (posterior) probabilities of area-specific differential trends differing from zero (i.e. away from the mean trend) for revealing locations of hot and cold spots.

Results

Property crime exhibited a declining mean trend across the study region from 2006 to 2007. Variation of area-specific trends was statistically significant, which was apparent from the map of (95 % credible interval) differential trends. Hot spots in the north and south west, and cold spots in the middle and east of the region were identified.

Conclusions

Bayesian spatio-temporal analysis contributes to a detailed understanding of small-area crime trends and risks. It estimates crime trend for each area as well as an overall mean trend. The new approach of identifying hot/cold spots through analysing and mapping probabilities of area-specific crime trends differing from the mean trend highlights specific locations where crime situation is deteriorating or improving over time. Future research should analyse trends over three or more periods (allowing for non-linear time trends) and associated (changing) local risk factors.     

Long-term effects of the Moving to Opportunity residential mobility experiment on crime and delinquency

Objectives

Using data from a randomized experiment, to examine whether moving youth out of areas of concentrated poverty, where a disproportionate amount of crime occurs, prevents involvement in crime.

Methods

We draw on new administrative data from the U.S. Department of Housing and Urban Development’s Moving to Opportunity (MTO) experiment. MTO families were randomized into an experimental group offered a housing voucher that could only be used to move to a low-poverty neighborhood, a Section 8 housing group offered a standard housing voucher, and a control group. This paper focuses on MTO youth ages 15–25 in 2001 (n = 4,643) and analyzes intention to treat effects on neighborhood characteristics and criminal behavior (number of violent- and property-crime arrests) through 10 years after randomization.

Results

We find the offer of a housing voucher generates large improvements in neighborhood conditions that attenuate over time and initially generates substantial reductions in violent-crime arrests and sizable increases in property-crime arrests for experimental group males. The crime effects attenuate over time along with differences in neighborhood conditions.

Conclusions

Our findings suggest that criminal behavior is more strongly related to current neighborhood conditions (situational neighborhood effects) than to past neighborhood conditions (developmental neighborhood effects). The MTO design makes it difficult to determine which specific neighborhood characteristics are most important for criminal behavior. Our administrative data analyses could be affected by differences across areas in the likelihood that a crime results in an arrest.     

Deterrence and the Death Penalty: Partial Identification Analysis Using Repeated Cross Sections

Objectives

Researchers have used repeated cross sectional observations of homicide rates and sanctions to examine the deterrent effect of the adoption and implementation of death penalty statutes. The empirical literature, however, has failed to achieve consensus. A fundamental problem is that the outcomes of counterfactual policies are not observable. Hence, the data alone cannot identify the deterrent effect of capital punishment. This paper asks how research should proceed. We seek to make transparent how assumptions shape inference.

Methods

We study the identifying power of relatively weak assumptions restricting variation in treatment response across places and time. We perform empirical analysis using state-level data in the United States in 1975 and 1977.

Results

The results are findings of partial identification that bound the deterrent effect of capital punishment. Under the weakest restrictions, there is substantial ambiguity: we cannot rule out the possibility that having a death penalty statute substantially increases or decreases homicide. This ambiguity is reduced when we impose stronger assumptions, but inferences are sensitive to the maintained restrictions.

Conclusions

Imposing certain assumptions implies that adoption of a death penalty statute increases homicide, but other assumptions imply that the death penalty deters it. Thus, society at large can draw strong conclusions only if there is a consensus favoring particular assumptions. Without such a consensus, data on sanctions and murder rates cannot settle the debate about deterrence. However, data combined with weak assumptions can bound and focus the debate.     

Examining What Makes Violent Crime Victims Unique: Extending Statistical Methods for Studying Specialization to the Analysis of Crime Victims

Objectives

Much victimization research focuses on specific types of crime victims, which implies that the factors responsible for some victimization outcomes are distinct from others. Recent developments in victimization theory, however, take a more general approach, postulating that victimization regardless of type will share a similar basic etiology. This research examines how and whether the risk factors that are associated with violent victimization significantly differ from those that predict nonviolent victimization.

Methods

Using data from 3,682 Kentucky youth, we employ Osgood and Schreck??s (2007) Item Response Theory-based statistical approach for detecting specialization to determine the properties and predictors of tendencies for individuals to fall victim to specific types of crime.

Results

Findings show that victims typically experience varied outcomes, but some victims have a clear tendency toward violent victimization and that it is possible to predict this tendency.

Conclusions

The findings indicate that a more nuanced general approach, one that accounts for tendencies toward specific victimization outcomes, might add insight about the causes of victimization. This research also shows how statistical methods designed to examine offense specialization can add value for research on victimization.     

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.

     

The impact of two Los Angeles County Teen Courts on youth recidivism: comparing two informal probation programs

Objective

This study sought to examine the impact of two Teen Courts operating in Los Angeles County, a juvenile justice system diversion program in which youths are judged by their peers and given restorative sentences to complete during a period of supervision.

Methods

A quasi-experimental design was used to compare youths who participated in Teen Courts (n = 112) to youths who participated in another diversion program administered by the Probation Department (the 654 Contract program) (n = 194). Administrative data were abstracted from the probation records for all youths who participated in these programs between January 1, 2012 and June 20, 2014. Logistic and survival models were used to examine differences in recidivism, measured as whether the minor had any subsequent arrest or arrests for which the charge was filed.

Results

Comparison group participants had higher rates of recidivism than Teen Court participants, after controlling for age, gender, race/ethnicity, and risk level. While the magnitude of the program effects were fairly consistent across model specifications (odd ratios comparing Teen Court [referent] to school-based 654 Contract ranging from 1.95 to 3.07, hazard ratios ranging from 1.62 to 2.27), differences were not statistically significant in all scenarios.

Conclusions

While this study provides modest support for the positive impact of Teen Court, additional research is needed in order to better understand how juvenile diversion programs can improve youth outcomes.

     

Prisons and Crime, Backwards in High Heels

Objectives

Prisons reduce crime rates, but crime increases prison populations. OLS estimates of the effects of prisons on crime combine the two effects and are biased toward zero. The standard solution—to identify the crime equation by finding instruments for prison—is suspect, because most variables that predict prison populations can be expected to affect crime, as well. An alternative is to identify the prison equation by finding instruments for crime, allowing an unbiased estimate of the effect of crime on prisons. Because the two coefficients in a simultaneous system are related through simple algebra, we can then work backward to obtain an unbiased estimate of the effect of prisons on crime.

Methods

Potential instruments for crime are tested and used to identify the prison equation for the 50 U.S. states for the period 1978–2009. The effect of prisons on crime consistent with this relationship is obtained through algebra; standard errors are obtained through Monte Carlo simulation.

Results

Resulting estimates of the effect of prisons on crime are around ?0.25 ± 0.15. This is larger than biased OLS estimates, but similar in size to previous estimates based on standard instruments.

Conclusions

When estimating the effect of a public policy response on a public problem, it may be more productive to find instruments for the problem and work backward than to find instruments for the response and work forward.     

Gangs and Violence: Disentangling the Impact of Gang Membership on the Level and Nature of Offending

Objectives

To determine whether membership in youth gangs provides a unique social forum for violence amplification. This study examines whether gang membership increases the odds of violent offending over and above involvement in general delinquent and criminal behavior.

Methods

Five waves of data from a multi-site (seven cities) panel study of over 3,700 youth originally nested within 31 schools are analyzed. We estimate four level repeated measures item response theory models, which include a parameter to differentiate the difference in the log of the expected event-rate for violent offense items to the log of the expected event-rate for nonviolent offense items.

Results

Depending on the comparison group (gang youth, overall sample), periods of active gang membership were associated with a 10 or 21% increase in the odds of involvement in violent incidents. When the sample is restricted to youth who report gang membership during the study, the proportionate increase in the odds of violence associated with gangs is statistically similar for males and females. After youth reported leaving the gang their propensity for violence was not significantly different than comparison group observations, although levels of general offending remain elevated.

Conclusions

While results are limited by the school-based sampling strategy, the importance of gang prevention and intervention programming for violence reduction is highlighted. Preventing youth from gang membership or shortening the length of gang careers through interventions may reduce absolute levels of violence.     

Shared legacies,disparate outcomes: why American south border cities turned the tables on crime and their Mexican sisters did not

The article evaluates crime trends in south border American and Mexican sister cities using panel data analysis. The region offers a unique assessment opportunity since cities are characterized by shared cultural and historical legacies, institutional heterogeneity, and disparate crime outcomes. Higher homicide rates on the Mexican side seem to result from deficient law enforcement. Higher population densities in Mexican cities appear to also be a factor. Cultural differences, on the other hand, have been decreasing, and apparently do not play a substantial role. The homicide rate dynamics show opportunistic clustering of criminal activity in Mexican cities, while no clustering is found on the American side. Crime also appears to spill from Mexican cities into American cities. Homicide rates on both sides of the border have been falling faster than countrywide rates, leading, in the case of American cities, and against stereotypes, to rates below the countrywide rate in 2001.

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Place and Punishment: The Spatial Context of Mass Incarceration

Objectives

Research on race and urban poverty views incarceration as a new and important aspect of social disadvantage in inner-city neighborhoods. However, in quantitative studies of the spatial distribution of imprisonment across neighborhoods, the pattern outside urban areas has not been examined. This paper offers a unique analysis of disaggregated prison admissions and investigates the spatial concentrations and levels of admissions for the entire state of Massachusetts.

Methods

Spatial regressions estimate census tract-level prison admission rates in relation to racial demographics, social and economic disadvantage, arrest rates, and violent crime; an analysis of outlier neighborhoods examines the surprisingly high admission rates in small cities.

Findings

Regression analysis yields three findings. First, incarceration is highly spatially concentrated: census tracts covering 15% of the state’s population account for half of all prison admissions. Second, across urban and non-urban areas, incarceration is strongly related to concentrated disadvantage and the share of the black population, even after controlling for arrest and crime rates. Third, the analysis shows admission rates in small urban satellite cities and suburbs comprise the highest rates in the sample and far exceed model predictions.

Conclusion

Mass incarceration emerged not just to manage distinctively urban social problems but was characteristic of a broader mode of governance evident in communities often far-removed from deep inner-city poverty. These notably high levels and concentrations in small cities should be accounted for when developing theories of concentrated disadvantage or policies designed to ameliorate the impacts of mass incarceration on communities.

     

Lighting and Homicides: Evaluating the Effect of an Electrification Policy in Rural Brazil on Violent Crime Reduction

Introduction

This study estimates the effects of lighting on homicides in rural areas of developing countries.

Methods

We use an IV strategy by exploring the LUZ PARA TODOS or Light for All (LPT) program that was adopted by the federal government to expand electrification to rural areas in Brazilian municipalities in the 2000s as an exogenous source of variations in access to electricity.

Results

Our results indicate a significant decrease in homicide rates in municipalities the Northeast region, which is the poorest region of the country and most affected by the policy expansion. We estimate that helping a municipality increase from zero electricity coverage to full coverage reduces homicide rates by 92 per 100,000 inhabitants. This is equivalent to moving a municipality that is at the 99th percentile to the median (zero) of the crime distribution across municipalities. In addition, we perform placebo exercises using sub-samples of predominantly urban municipalities. The results increase our confidence in the IV strategy since our primary results were from areas with a larger percentage of rural population, as should be expected by the policy.

Conclusions

This study contributes to the extant literature by investigating the effects of lighting on homicides in a different context, rural areas of a developing country (Brazil).

     

Long-term impact of family group conferences on re-offending: the Indianapolis restorative justice experiment

Objectives

The purpose of the current study is to test the long-term effect of Family Group Conferences (FGCs) on recidivism prevalence and time to first re-offense for first-time youthful offenders.

Methods

The current study builds on an experiment with a reasonably large sample (n?=?782) conducted in Marion County (Indianapolis), Indiana, USA. The current study extends this work by following the cases for an additional 10?years. To examine the empirical relationships among the variables, this study employs a two-step approach. The initial analysis, employing logistic regression, measures prevalence of re-offending based on whether the youth ever was re-arrested during the follow-up period. The second step employs Cox Proportional-Hazards Regression to examine time until first re-offense.

Results

The findings revealed that when extended to a 12-year follow-up period, there were no significant differences between the FGC and control groups in re-offending prevalence or time to re-offense.

Conclusions

An earlier study suggests that treatment group youths experienced reduced risk in the short-term and there is no evidence in the present study to suggest that youths participating in FGCs were placed at greater risk for re-offending. Given these findings and the body of research suggesting improved outcomes for victims, continued experimentation with FGCs and related restorative processes seems warranted. Future studies would benefit from blocking procedures in the experimental design in order to examine whether treatment effects are moderated by gender, race, and initial type of offense. The lack of such blocking procedures represents a limitation of the current study.     

The Role of Immigration: Race/Ethnicity and San Diego Homicides Since 1970

Objectives

The temporal variation in homicide is examined by studying trends in race/ethnic specific killings (e.g. Blacks, Latinos and Whites). Two substantively important issues are also addressed—a closer examination of the role community heterogeneity plays in homicide levels and the treatment of immigration as an endogenous social process.

Methods

Data are reported homicides in the city of San Diego, California over the period 1960–2010. The address of each killing is geocoded into 341 census tracts.

Results

We find that neighborhoods experiencing increases in the foreign-born population tend to be less violent. White and Latino homicide victimization was reduced significantly as a product of increases in the neighborhood concentration of foreign-born individuals. Supplementary analyses did not find empirical evidence that the influx of foreign-born individuals could (or should) be considered a disruptive social process. Over the past five decennial census periods, the exponential increase in immigration in this border city is not associated with an increase in homicide victimization.

Conclusions

When examined through a wider temporal lens than is typically employed, and accounting for the endogeneity of immigrant residential settlement, we find no support for the claims that immigration is a crime generating social process.

     

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.