The purpose of this study is to extend research on communities and crime by assessing neighborhood variation in mortgage fraud.
We use proprietary data to generate a measure of mortgage fraud for 2005 through 2008 for 793 census tracts in Chicago. We estimate maximum likelihood spatial regression models to assess the impact of tract-level structural variables and lending market characteristics on mortgage fraud.
We find that concentrated disadvantage, percent black, and immigrant concentration are associated with greater levels of mortgage fraud. However, the impact of these factors is largely mediated by subprime lending. In addition, we find mortgages purchased by private entities also lead to greater levels of mortgage fraud. Contrary to expectations, changing loan values are unrelated to mortgage fraud.
The findings suggest the relationship between neighborhood structural characteristics and mortgage fraud is partially due to a lack of public social control in disadvantaged minority neighborhoods. Future research should build on this study and examine a wider variety of crimes than are traditionally studied at the neighborhood level.
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.
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.
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.
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.
We used multilevel data from the National Crime Victimization Survey (NCVS) to identify factors that account for differences in risk of violent victimization among young Latino adults in new and traditional settlement areas.
Area-identified NCVS data (2008–2012) were linked with census tract data from the decennial census and American Community Survey to study individual and community contributions to the risk of violent victimization. We analyzed total violence and violence specific to offense types and victim-offender relationship. The analyses were performed adjusting for the complex survey design.
Young Latino adults in new settlement areas have higher victimization rates than their counterparts in traditional areas for total violence and for the majority of violence types studied. Holding constant individual and other contextual factors, Latino population density is a key neighborhood characteristic that explains the observed area differences in victimization, yielding evidence for the hypothesis that co-ethnic support in a community helps protect young Latino adults and contributes to differences in victimization across areas. Also there is evidence that the protective role of Latino population density is stronger for violence involving non-strangers than it is for violence involving strangers. Moreover, we find that the concentration of Latino immigrants, which indicates the neighborhood potential for immigrant revitalization, is another neighborhood factor that protects young Latino adults in both new and traditional settlement areas. However, there is some but limited evidence that the neighborhood-revitalizing role of immigration might be smaller in some contexts (such as some new areas outside central cities), possibly because those areas are heterogeneous in their ability to promote the integration of immigrants.
Our analysis of the NCVS shows the importance of neighborhood factors for the risk of violence among young Latino adults. It provides evidence consistent with co-ethnic support and immigrant revitalization theories. The findings also suggest that the effects of those neighborhood factors may be contingent upon violence type and the context in which they occur. These findings help us understand the difference in the safety of young Latino adults in new and traditional areas.
To assess the impact of schools on crime in neighborhoods.
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.
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.
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 Welfare Act of 1996 banned welfare and food stamp eligibility for felony drug offenders and gave states the ability to modify their use of the law. Today, many states are revisiting their use of this ban, searching for ways to decrease the size of their prison populations; however, there are no empirical assessments of how this ban has affected prison populations and recidivism among drug offenders. Moreover, there are no causal investigations whatsoever to demonstrate whether welfare or food stamp benefits impact recidivism at all.
This paper provides the first empirical examination of the causal relationship between recidivism and welfare and food stamp benefits
Using a survival-based estimation, we estimated the impact of benefits on the recidivism of drug-offending populations using data from the National Corrections Reporting Program. We modeled this impact using a difference-in-difference estimator within a regression discontinuity framework.
Results of this analysis are conclusive; we find no evidence that drug offending populations as a group were adversely or positively impacted by the ban overall. Results apply to both male and female populations and are robust to several sensitivity tests. Results also suggest the possibility that impacts significantly vary over time-at-risk, despite a zero net effect.
Overall, we show that the initial passage of the drug felony ban had no measurable large-scale impacts on recidivism among male or female drug offenders. We conclude that the state initiatives to remove or modify the ban, regardless of whether they improve lives of individual offenders, will likely have no appreciable impact on prison systems.
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.
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.
It is found that increasing the tertiary education eligibility rate decreases both property and violent crime substantially.
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.
An important indicator of discrimination in the criminal justice system is the degree to which race differences in arrest account for racial disproportionality in prisons (“accountability”). A recent National Academy of Sciences (NAS) study raised concerns by reporting low and declining estimates of accountability. Our improved measure accounts for unreported Hispanic arrestees. We measure accountability at intermediate stages, including commitments to prison and time served. We also use victim reports to extend accountability from arrest to differential involvement in violent crimes.
Our methods utilize information on self-reported racial identity of Hispanic prisoners to provide more accurate comparison with the race of arrestees. We also assess accountability for 42 individual states and 4 regions.
Our national estimate of accountability is close to previous estimates and much higher than those in the NAS report. Accountability is high for the serious violent crimes of murder and rape, and low for drug trafficking, drug possession, weapons, and aggravated assault, which involve more discretion in arrest, labeling and charging.
Our more accurate accountability results contradict the NAS report of low and declining accountability. Regional accountability estimates show no consistently stronger or weaker region. We also show a corrected national estimate of the ratio of black-to-white incarceration-rates has dropped from 6.8 in 1990 to 4.7 in 2011, an important correction to concerns of increasing discrimination. Reports of offenders’ race by victims and arrestees’ race are found to be close, supporting use of arrest as an indicator of involvement in violent crimes.
To examine the extent to which there are differences in the developmental course of offending among individuals with maltreatment histories, compared to nonmaltreated controls, and whether these patterns vary for males and females.
This paper uses data from a longitudinal study in which abused and neglected children (N = 908) were matched with non-maltreated children (N = 667) and followed prospectively into adulthood. Group-based trajectory modeling was conducted using official criminal history records collected through mean age 51. Patterns of criminal offending were first considered for the whole sample, with abuse status and sex included as time-stable covariates, and then separately by subgroup (control females, maltreated females, control males and maltreated males).
Analyses revealed that a three-group model provided the best fit (nonoffenders, low-level chronic offenders, mid-level chronic offenders) for the overall sample. Child maltreatment and sex were significant predictors, with offenders more likely to be male and abused/neglected, compared to non-offenders. Separate analyses for the four subgroups revealed some similarities across groups in the characterization of offending trajectories, although trajectories for abused/neglected females differed significantly from trajectories for control females. Additional analyses suggest that desistance from offending may be largely a function of incapacitation due to early death, rather than imprisonment.
These new analyses provide evidence that child maltreatment affects patterns of offending and that there is an impact on females and males, although the impact differs by gender. Future research should build on this work by examining the mechanisms through which child maltreatment leads to differential patterns of offending throughout the life course.
The study extends previous literature (Cochran in J Crim Justice 40:433–440, 2012, J Res Crime Delinq 51(2):200–229, 2014) by simultaneously examining two margins: the probability of receiving a visit and the number of visits a prisoner receives conditional on receiving any visits; adding a level of nuance to the exploration of prison visits.
A random sample of New York State prisoners admitted between 2000 and 2013 who served at least 24 months and had basic admission, release, and transfer data (N = 22,975) were selected. Visit patterns were derived using group-based trajectory models with a zero-inflated Poisson specification and up to a cubic polynomial on probability and count parameters.
The best fitting model had seven groups that displayed wide variation in the probability of a visit (in both directions). By contrast, the number of visits, conditional on receiving a visit, is relatively constant over time. Subsequent dual trajectory modeling of prison visits with distance from home county demonstrates that the dynamic patterns of probability of visit correspond with dynamic patterns of distance from home county.
We demonstrate that time variation in visitation occurs along the prevalence margin. Researchers interested in studying the longitudinal relationship between visits and outcomes should be attentive to this result. Additionally, characteristics of prisoners assigned to the trajectory groups using Posterior Probabilities of Assignment suggest that pre-prison factors (i.e. criminal record) and in-prison policy decisions (i.e. custody level) are associated with particular patterns of visits over time; highlighting the challenge to understanding the effect of visitation in studies without explicit causal identification strategies.
Conventional statistical modeling in criminology assumes proper model specification. Very strong and unrebutted criticisms have existed for decades. Some respond that although the criticisms are correct, there is for observational data no alternative. In this paper, we provide an alternative.
We draw on work in econometrics and statistics from several decades ago, updated with the most recent thinking to provide a way to properly work with misspecified models.
We show how asymptotically, unbiased regression estimates can be obtained along with valid standard errors. Conventional statistical inference can follow.
If one is prepared to work with explicit approximations of a “true” model, defensible analyses can be obtained. The alternative is working with models about which all of the usual criticisms hold.
This study seeks to determine the extent to which Tittle’s control balance (CB) theory (CBT: 1995) accurately predicts different types of deviance within a corporate setting (in this case, a financial services corporation). CB theory contends that deviance is the result of a control imbalance between the amount of control a person exerts and the amount to which they are subject. Control deficits result in repressive deviance (including most types of predatory crime). Control surpluses result in autonomous deviance (including many types of white collar offending).
We exploit a unique dataset consisting of the internal investigations of fraud conducted by a large United States-based financial services company to explore these concepts in the corporate sales environment.
Consistent with the theory, we find that a control surplus predicts certain autonomous deviance while a control deficit explained some repressive forms of criminality. Results also indicate that a control imbalance is incremental in nature and not simply a balanced/non-balanced condition. Further discussion revolves around implications, limitations, and future research.
The advent of mass incarceration has reinvigorated calls for a deeper understanding of how the “quality of relationships” is shaped by imprisonment (Travis J, Western B, Redburn S (eds), The growth of incarceration in the United States: exploring causes and consequences, National Academies Press, Washington DC, 2014). We address this issue by describing how imprisonment relates to four dimensions of tie strength in a sample of South Bronx residents.
We draw on a series of survey-based multilevel models to examine how tie strength relates to characteristics of respondents and their self-reported contacts (N1 = 585 ties, N2 = 97 egos) regarding (a) frequency, (b) duration, (c) multiplexity, and (d) reciprocity.
Ties of formerly-incarcerated persons are of shorter duration and exhibit less overlap relative to other respondents. However, markers of general association across the sample to currently/formerly incarcerated persons correlate with alter-ego ties that are more frequent, long-lasting, and multi-dimensional.
There is some support for the notion that direct exposure to incarceration is linked to a weakening of ties akin to a “knifing-off” process (Maruna and Roy, J Contemp Crim Justice 23(1):104–124, 2007). Indirect exposure to incarceration may follow an inverse pattern, strengthening the ties among those “left behind”.
We analyze the contribution of changes in the black–white racial disparity in imprisonment to changes in the black incarceration rate. We also describe the behavior of the racial disparity across states and across time.
We use state level incarceration data for non-Hispanic black and white males to perform a decomposition of the black incarceration rate. This allows us to attribute changes in black incarceration to changes in the racial disparity and changes in the overall incarceration rate. We use a Fourier approximation to identify structural change points for the racial disparity at both the state and national level.
The large increase in black imprisonment between 1978 and 1999 was driven by increases in the overall rate of imprisonment, while the smaller decrease which occurred between 1999 and 2014 was driven by reductions in the black–white racial disparity. For many states, the racial disparity increased starting in the mid-1980s, where this increase may have been linked to the crack epidemic. Many states experienced a downturn in the racial disparity starting in the 1990s. Whatever its other effects, this suggests that the 1994 crime bill did not aggravate the preexisting racial disparity in imprisonment. California’s experience has been strongly counter to national trends with a large increase in the racial disparity beginning in the early 1990s and continuing until near the end of our sample.
While the racial disparity in imprisonment has been falling since 1996, it remains quite high as of 2014. Future work is required to better understand the policy determinants of this disparity.
This cohort study explores the prevalence and effect of suspected outcome reporting bias in clinical trials on substance use disorders.
Protocols on the ClinicalTrials.gov registry are compared with the corresponding trial reports for 95 clinical trials across 3,162 outcomes. Variation in average effect size is examined by completeness and accuracy of reporting using ordinary least squares regression with robust standard errors (Eicker-Huber-White sandwich estimator).
Trials reports are frequently incomplete and inconsistent with their protocol. The most commonly practiced biased reporting practices are added outcomes not prespecified on the protocol, insufficiently pre-specifying outcomes, and omitting outcomes that were pre-specified on the protocol. There is a linear trend between the number of different biased reporting practices the trialist(s) engaged in and mean study-level Cohen’s d (+ 0.214 with each additional type of biased reporting practice). Trials with omitted pre-specified outcomes have a significantly higher Cohen’s d on average when compared to trials that did not omit such outcomes (+ 0.315). Added outcomes have a Cohen’s d that is 0.385 higher in comparison to reported outcomes that were pre-specified on the protocol.
The magnitude of outcome reporting bias raises considerable concern regarding inflated type I error rates. Implications for clinical trials on substance abuse, and randomized experiments in criminology, more generally, are discussed.
A key issue is how to interpret t-statistics when publication bias is present. In this paper we propose a set of rough rules of thumb to assist readers to interpret t-values in published results under publication bias. Unlike most previous methods that utilize collections of studies, our approach evaluates the strength of evidence under publication bias when there is only a single study.
We first re-interpret t-statistics in a one-tailed hypothesis test in terms of their associated p-values when there is extreme publication bias, that is, when no null findings are published. We then consider the consequences of different degrees of publication bias. We show that under even moderate levels of publication bias adjusting one’s p-values to insure Type I error rates of either 0.05 or 0.01 result in far higher t-values than those in a conventional t-statistics table. Under a conservative assumption that publication bias occurs 20 percent of the time, with a one-tailed test at a significance level of 0.05, a t-value equal or greater than 2.311 is needed. For a two-tailed test the appropriate standard would be equal or above 2.766. Both cutoffs are far higher than the traditional ones of 1.645 and 1.96. To achieve a p-value less than 0.01, the adjusted t-values would be 2.865 (one-tail) and 3.254 (two-tail), as opposed to the traditional values 2.326 (one-tail) and 2.576 (two-tail). We illustrate our approach by applying it to evaluate the hypothesis tests in recent issues of Criminology and Journal of Quantitative Criminology (JQC).
Under publication bias much higher t-values are needed to restore the intended p-value. By comparing the observed test scores with the adjusted critical values, this paper provides a rough rule of thumb for readers to evaluate the degree to which a reported positive result in a single publication reflects a true positive effect. Further measures to increase the reporting of robust null findings are needed to ameliorate the issue of publication bias.
Criminologists have long questioned how fragile our statistical inferences are to unobserved bias when testing criminological theories. This study demonstrates that sensitivity analyses offer a statistical approach to help assess such concerns with two empirical examples—delinquent peer influence and school commitment.
Data from the Gang Resistance Education and Training are used with models that: (1) account for theoretically-relevant controls; (2) incorporate lagged dependent variables and; (3) account for fixed-effects. We use generalized sensitivity analysis (Harada in ISA: Stata module to perform Imbens’ (2003) sensitivity analysis, 2012; Imbens in Am Econ Rev 93(2):126–132, 2003) to estimate the size of unobserved heterogeneity necessary to render delinquent peer influence and school commitment statistically non-significant and substantively weak and compare these estimates to covariates in order to gauge the likely existence of such bias.
Unobserved bias would need to be unreasonably large to render the peer effect statistically non-significant for violence and substance use, though less so to reduce it to a weak effect. The observed effect of school commitment on delinquency is much more fragile to unobserved heterogeneity.
Questions over the sensitivity of inferences plague criminology. This paper demonstrates the utility of sensitivity analysis for criminological theory testing in determining the robustness of estimated effects.
This paper investigates the influence of case characteristics and investigative resources on homicide clearance rates.
We extend a previous evaluation of a problem-oriented policing project intended to improve homicide clearance rates in Boston. Data were collected on N = 465 homicide incidents that occurred between January 1, 2007 and December 31, 2014. Confirmatory factor analyses are used to identify latent variables representing investigative resources, initial crime scene results, and subsequent investigative actions and forensic testing. The effects of these investigative factors on homicide clearances net other covariates were estimated using mixed effects logistic regression models. Mediation analysis was then used to decompose the total, direct, and indirect effect of investigative resources on homicide clearances. Exploratory group comparisons were examined to distinguish investigative differences in gang and drug homicides relative to non-gang and non-drug homicides.
Investigative resources, crime scene results, and subsequent investigative actions and forensic testing were found to increase the likelihood of homicide case clearance controlling for other covariates. Investigative resources were found to produce both direct and indirect impacts on homicide clearances mediated through its positive influence on initial crime scene results and subsequent investigative actions and forensic testing. Clearance through follow-up investigation was more difficult for gang and drug homicide cases when compared to other homicide cases.
While inherited case characteristics matter, enhanced investigative resources and improved practices increase homicide clearances. Beyond investments to improve investigations, gang and drug homicides remain particularly difficult to clear due to a lack of physical evidence and witness cooperation.
We test a serial multiple mediation model in which the relationship between ethnicity and antisocial behavior is sequentially mediated by disadvantaged neighborhoods and impaired neuropsychological functioning.
Parental and self-report measures of antisocial behavior were assessed in a community sample of 341 adolescent males and females. Neighborhood disadvantage was assessed from census data. Neuropsychological functioning was evaluated using a computerized battery. Separate serial multiple mediation models were tested using non-executive functioning and executive functioning.
The serial mediation model for executive functioning was supported, with the pathway from race to antisocial behavior through neighborhood disadvantage and executive functioning in serial accounting for 10.8% of the total effect of race on antisocial behavior.
Findings support social neurocriminology theory by integrating neighborhood disadvantage and executive functioning as sequential mediators of the race–antisocial relationship. To our knowledge, these are the first findings to explain the race–antisocial relationship in terms of connected social and neuropsychological processes. While this pathway is significant, the effect is still relatively small and thus should be understood as one of many mechanisms through which race may affect antisocial behavior. From a translational science standpoint, the identification of neurocognitive mechanisms by which neighborhood disadvantage predisposes to antisocial behavior suggests the potential benefits of cognitive enhancement techniques to remediate the negative effects of adverse neighborhoods on brain functioning in at-risk minority groups.
A substantial body of literature indicates that certain forms of media consumption may increase anxiety about crime and support for social controls. However, few studies have examined whether Internet news consumption is positively associated with such attitudes. The void is significant given the public’s increasing use of online news sources. This study addresses this research gap.
We draw on data from four national surveys conducted between 2007 and 2013, which collectively include interviews with more than 13,000 Americans. Using OLS and logistic regression, we assess the relationships between exposure to traditional and online media and perceptions of victimization risk, support for punitive crime policies, and views about police powers.
Consistent with prior work, we find positive relationships between exposure to traditional forms of media—television news and crime programming—and anxiety about victimization and support for harsh crime policies. In contrast, Internet news exposure is generally not associated with anxieties about crime or support for getting tough on criminals. However, there is evidence of an interactive relationship between political ideology and Internet news exposure.
The results provide little support for cultivation theory in the context of Internet news consumption. We discuss the import of our findings, and suggest new lines of research to explore the correlates and the effects of exposure to online news sources.
Crime continuity is one of the best documented and least understood aspects of criminal behavior. Psychological inertia, the notion that cognitive variables mediate the relationship between earlier and later expressions of the same behavior, was tested as a possible explanation for crime continuity.
The cognitive mediation and additive postulates of the psychological inertia theorem were tested in a path analysis using self-report data from 1170 male delinquent members of the Pathways to Desistance study (Mulvey in Paper presented at the American Society of Criminology Annual Meeting, Chicago, IL, 2012). Wave 1 delinquency served as the independent variable, Wave 3 delinquency served as the dependent variable, Wave 2 outcome expectancies for crime, self-efficacy, general criminal thinking, and social capital served as the mediator variables, and 12 different baseline measures from criminological theory served as control variables in this study.
General criminal thinking and low self-efficacy successfully mediated the relationship between past and future offending after age, race, early behavioral problems, peer criminality, family criminality, parental knowledge and monitoring, parental hostility, routine activities, measured intelligence, and precursors for each of the mediators were controlled. Social capital (cumulative disadvantage), by comparison, failed to mediate crime continuity in this study.
Effective cognitive mediation of the relationship between Wave 1 offending and Wave 3 offending and evidence that the effect may be additive offer preliminary support for the cognitive mediation and additive postulates of the psychological inertia theorem. Practical implications of these results include the need to routinely assess cognitive factors in criminal populations and target these factors for intervention.
Effects of place-based criminal justice interventions extend across both space and time, yet methodological approaches for evaluating these programs often do not accommodate the spatiotemporal dimension of the data. This paper presents an example of a bivariate spatiotemporal Ripley’s K-function, which is increasingly employed in the field of epidemiology to analyze spatiotemporal event data. Advantages of this technique over the adapted Knox test are discussed.
The study relies on x–y coordinates of the exact locations of stop-question-frisk (SQF) and crime incident events in New York City to assess the deterrent effect of SQFs on crime across space at a daily level.
The findings suggest that SQFs produce a modest reduction in crime, which extends over a three-day period. Diffusion of benefits is observed within 300 feet from the location of the SQF, but these effects decay as distance from the SQF increases.
A bivariate spatiotemporal Ripley’s K-function is a promising approach to evaluating place-based crime prevention interventions, and may serve as a useful tool to guide program development and implementation in criminology.
This study tests the generality of Tyler’s process-based model of policing by examining whether the effect of procedural justice and competing variables (i.e., distributive justice and police effectiveness) on police legitimacy evaluations operate in the same manner across individual and situational differences.
Data from a random sample of mail survey respondents are used to test the “invariance thesis” (N = 1681). Multiplicative interaction effects between the key antecedents of legitimacy (measured separately for obligation to obey and trust in the police) and various demographic categories, prior experiences, and perceived neighborhood conditions are estimated in a series of multivariate regression equations.
The effect of procedural justice on police legitimacy is largely invariant. However, regression and marginal results show that procedural justice has a larger effect on trust in law enforcement among people with prior victimization experience compared to their counterparts. Additionally, the distributive justice effect on trust in the police is more pronounced for people who have greater fear of crime and perceive higher levels of disorder in their neighborhood.
The results suggest that Tyler’s process-based model is a “general” theory of individual police legitimacy evaluations. The police can enhance their legitimacy by ensuring procedural fairness during citizen interactions. The role of procedural justice also appears to be particularly important when the police interact with crime victims.
This study explores preference variation in location choice strategies of residential burglars. Applying a model of offender target selection that is grounded in assertions of the routine activity approach, rational choice perspective, crime pattern and social disorganization theories, it seeks to address the as yet untested assumption that crime location choice preferences are the same for all offenders.
Analyzing detected residential burglaries from Brisbane, Australia, we apply a random effects variant of the discrete spatial choice model to estimate preference variation between offenders across six location choice characteristics. Furthermore, in attempting to understand the causes of this variation we estimate how offenders’ spatial target preferences might be affected by where they live and by their age.
Findings of this analysis demonstrate that while in the aggregate the characteristics of location choice are consistent with the findings from previous studies, considerable preference variation is found between offenders.
This research highlights that current understanding of choice outcomes is relatively poor and that existing applications of the discrete spatial choice approach may underestimate preference variation between offenders.
We seek evidence for economic and social mechanisms that aim to explain the relationship between employment and crime. We use the distinctive features of social welfare for identification.
We consider a sample of disadvantaged males from The Netherlands who are observed between ages 18 and 32 on a monthly time scale. We simultaneously model the offending, employment and social welfare variables using a dynamic discrete choice model, where we allow for state dependence, reciprocal effects and time-varying unobserved heterogeneity.
We find significant negative bi-directional structural effects between employment and property crime. Robustness checks show that only regular employment is able to significantly reduce the offending probability. Further, a significant uni-directional effect is found for the public assistance category of social welfare on property offending.
The results highlight the importance of economic incentives for explaining the relationship between employment and crime for disadvantaged individuals. For these individuals the crime reducing effects from the public assistance category of social welfare are statistically equivalent to those from employment, which suggests the importance of financial gains. Further, the results suggest that stigmatizing effects from offending severely reduce future employment probabilities.
This study tracked the behavior of male inmates housed in the general inmate populations of 70 different prison units from a large southern state. Each of the inmates studied engaged in violent misconduct at least once during the first 2 years of incarceration (n = 3,808). The goal of the study was to isolate the effect of exposure to short-term solitary confinement (SC) as a punishment for their initial act of violent behavior on the occurrence and timing of subsequent misconduct.
This study relied upon archival longitudinal data and employed a multilevel counterfactual research design (propensity score matching) that involved tests for group differences, event history analyses, and trajectory analyses.
The results suggest that exposure to short-term solitary confinement as a punishment for an initial violence does not appear to play a role in increasing or decreasing the probability, timing, or development future misconduct for this particular group on inmates.
Upon validation, these findings call for continued research and perhaps a dialog regarding the utility of solitary confinement policies under certain contexts. This unique study sets the stage for further research to more fully understand how solitary impacts post-exposure behavior.
This study examines UCR and NCVS serious violence crime trends in urban, suburban, and rural areas, and assesses the extent to which discrepancies in the two data series are due to victim reporting or police crime-recording practices. Particular attention is paid to the dynamics of the rural data series.
NCVS data for 1973–2010 are used to estimate subnational rates of serious violence and comparable rates for crimes that victims said were reported to police, and these estimates are compared to subnational UCR data. Time-series cointegration analysis is used to assess convergence in the NCVS and UCR series along with descriptive comparative analyses.
The degree of convergence in UCR and NCVS trends was found to vary across areas; however this was not due to differences in rates of reporting to police. Suburban and urban UCR and NCVS trends converged with and without adjustment for police reporting. Little evidence of NCVS/UCR series convergence was found in rural areas even after victim reporting was taken into account.
The recording and production of crime data by the police appears to contribute to subnational differences in the convergence between the UCR and NCVS series. The findings suggest rural crime trend analysis should not be based solely on UCR data. To illustrate the difference between conclusions based on UCR and NCVS rural violence trends, we find that poverty rates have a large, significant association with rural violence as measured in the NCVS, but are unrelated to UCR rates.
A key question in the general deterrence literature has been the extent to which the police reduce crime. Definitive answers to this statement, however, are difficult to come by because while more police may reduce crime, higher crime rates may also increase police levels, by triggering the hiring of more police. One way to help overcome this problem is through the use of instrumental variables (IV). Levitt, for example, has employed instrumental variables regression procedures, using mayoral and gubernatorial election cycles and firefighter hiring as instruments for police strength, to address the potential endogeneity of police levels in structural equations of crime due to simultaneity bias.
We assess the validity and reliability of the instruments used by Levitt for police hiring using recently-developed specification tests for instruments. We apply these tests to both Levitt’s original panel dataset of 59 US cities covering the period 1970–1992 and an extended version of the panel with data through 2008.
Results indicate that election cycles and firefighter hiring are “weak instruments”—weak predictors of police growth that, if used as instruments in an IV estimation, are prone to result in an unreliable estimate of the impact of police levels on crime.
Levitt’s preferred instruments for police levels—mayoral and gubernatorial election cycles and firefighter hiring—are weak instruments by current econometric standards and thus cannot be used to address the potential endogeneity of police in crime equations.
Drawing from a social disorganization perspective, this research addresses the effect of immigration on crime within new destinations—places that have experienced significant recent growth in immigration over the last two decades.
Fixed effects regression analyses are run on a sample of n = 1252 places, including 194 new destinations, for the change in crime from 2000 to the 2005–2007 period. Data are drawn from the 2000 Decennial Census, 2005–2007 American Community Survey, and the Uniform Crime Reports. Places included in the sample had a minimum population of 20,000 as of the 2005-07 ACS. New destinations are defined as places where the foreign-born have increased by 150 % or more since 1990 and with a minimum foreign-born population of 1000 in 2007.
Results indicate new destinations experienced greater declines in crime, relative to the rest of the sample. Moreover, new destinations with greater increases in foreign-born experienced greater declines in their rates of crime. Additional predictors of change in crime include change in socioeconomic disadvantage, the adult-child ratio, and population size.
Results fail to support a disorganization view of the effect of immigration on crime in new destinations and are more in line with the emerging community resource perspective. Limitations and suggestions for future directions are discussed.
This study revisits the relationship between property crime and economic conditions with the latter being represented by a collective economic perception variable in the form of the Index of Consumer Confidence (ICC). The present work takes this application to assess the severity of cross-sectional dependence and nonstationarity, two issues that are deemed pervasive in macro panels but have not been given sufficient consideration in previous research.
The dataset comprises information for five Canadian regions over a time period of 24 years from 1982 to 2005. The study compares the parameter estimates and residual properties of the commonly used two-way fixed effects (2FE) model and the augmented mean group (AMG) estimator where the latter can accommodate nonstationarity and cross-sectional dependence that potentially arise from unobserved common factors.
In contrast to the 2FE approach, when using the AMG estimator one can reject the null hypothesis that the current ICC has no impact on crime. Some of the effects still hold when an alternative economic indicator, the unemployment rate of young males, is added to the model. Diagnostic tests confirm that the commonly used 2FE estimator yields nonstationary and cross-sectional dependent residuals, whereas the heterogeneous parameter model produces more favorable diagnostic results.
The findings provide evidence supporting the hypothesis that subjective measures of economic conditions are linked to financially-motivated crime rates. Through this application, the study demonstrates the importance of examining underlying data properties and regression residuals in empirical work to ensure the validity of estimates.
Because of the merging of immigration control and criminal justice, or “crimmigration,” state and local police increasingly drive interior immigration enforcement through the routine policing of crime. At the same time, growing evidence indicates that immigration is an ethnicity-coded issue that allows for the veiled expression of broader anti-Latino sentiments. Yet little research has examined whether public perceptions of either immigrants or Latinos influence support for police policies and practices that, in the context of crimmigration, may significantly shape immigration enforcement and, more broadly, may contribute to the subordination of Latinos. The current study addresses this research question.
The study draws on data from a recent nationally representative telephone survey and employs multivariate regression methods to evaluate whether perceptions of Latino economic and political threat are associated with support for granting police greater latitude in stopping, searching, and using force against suspects.
This study provides the first evidence that, at least among Whites, perceived Latino threat is positively associated with support for expanding police investigative powers, especially the power to stop suspects based only on the way they look.
The results suggest that by increasing public support for aggressive policing, or, at minimum, by reducing opposition to discriminatory social controls such as police profiling, Latino threat perceptions may increase the political attractiveness and viability of crimmigration as a “solution” to the “Latino problem.”
Research indicates respondents overestimate the similarity between their own deviance and that of their peers. Extending Rebellon and Modecki’s (J Quant Criminol 30:163–186, 2014) study, we examine if item-level error correlations in structural models reduce bias for non-peer-based, theoretically derived covariates such as self-control. Our specific interest lies in investigating the theoretical implications and practical value of using the correlated error technique in ‘everyday’ structural equation modeling.
Using dyadic data and multiple constructs of deviance, we present three sets of structural equation analyses. The first assesses the relationship between peer behavior and deviance via perceptual measures. The second uses identical constructs, but estimates item-level error correlations between perceptual and deviance items. The third replaces perceptions of peer deviance with items measuring peers’ self-reported behavior.
Self-control and demographic variables have equivalent effects in perceptually-based correlated error models and models controlling peer self-reported deviance. However, latent variable adjustments to perceptions of peer behavior fail to bring perceived peer deviance coefficients into line with corresponding coefficients from models using peer self-reports, indicating that perceptions and peer self-reports are distinct constructs.
Researchers cannot use item-level error-correlations to model peer effects without collecting data from peers. They may, however, use these correlations to control for peer effects even when peer self-reports are not available. Because we find strong effects of self-control while maintaining social learning theory’s emphasis on perceptions, we argue that the technique is a form of theoretical reconciliation and recommend criminologists adopt the use of correlated errors in all social influence-based structural models.
To evaluate with an ex post facto quasi-experimental design the impact of tactical police response on residential theft from vehicle crime in micro-time hot spots as well as whether spatial displacement occurs.
The evaluation uses 5 years of data from one police agency that responded to micro-time hot spots as part of its normal crime reduction efforts. To determine the experimental comparison group, propensity scores were computed using logistic regression. Cases were matched using greedy 1–1 matching with a caliper of 0.10 of the standard deviation of the logit of the propensity score and resulted in 86 pairs. t Tests were used to examine the effect of the treatment and whether spatial displacement of crime occurred as a result.
Results showed that when police responded with about seven responses per day and for between 2 and 3 weeks, there was nearly a 20 % reduction in residential theft from vehicle crimes, and the micro-time hot spots with response did not last as long as those that did not. Results also showed no spatial displacement of crime as a result of the response.
This evaluation is first to examine tactical police strategies for property crimes occurring at micro-places in micro-time. Findings support the hypothesis that micro-time hot spots are less severe and “cool off” more quickly after a response. Thus, police should consider responding to property crime occurring in micro-places at a smaller temporal unit. Future research should further explore this unit of police response to corroborate these results.
There is a misspelling of one of the author’s names. The fourth author’s last name should be “Ribeaud”, instead of “Ribaud”.
The following text should be added immediately after the end of the last paragraph of “Socio-psychological characteristics” section:
An additional item that rated whether the respondent was bullied was not included in this scale due to the overlap with the dependent variable (i.e., victimization). Therefore, we re-labeled the scale ‘negative peer relations.’Also, the authors would like to add an acknowledgment to the paper as follows:
Recent evidence suggests that typifying violent juvenile delinquency as a Black phenomenon may increase support for punitive juvenile justice policies. However, the research to date has not yet explored various theoretical explanations for this relationship. In particular, theory suggests that racialized punitiveness may be explained by (1) the adoption of dispositional attributions toward delinquency, (2) the failure to empathetically identify with delinquents, and (3) the belief that juveniles possess adult criminal intent and lack childhood naivety. The current study addresses this gap to determine the mediating associations between each of these factors and the racial stereotypes-punitiveness link.
Path analysis is conducted to determine the direct and indirect associations of each of the proposed mediators. In deriving the measures for the analyses, we also make the first attempt at operationalizing empathy specifically toward offenders.
The findings suggest that those who racially typify violent delinquency are more likely to attribute juvenile crime to dispositional causes, empathize less with violent juvenile offenders, and believe young violent offenders possess adult criminal intentions, which in turn, leads to increased punitiveness.
The findings provide support for three theoretical predictions of racialized punitiveness. Empathy emerges as the strongest predictor of punitive attitudes and accounts for the largest proportion of the relationship between racial typification and support for punitive delinquency policies.
Neighborhood youth organizations are a salient community-level resource in the lives of children and adolescents, but empirical research on the aggregate-level relationship between neighborhood crime rates and neighborhood organizations is mixed. This study attempts to clarify and extend prior research by examining (1) whether there is a contextual effect of neighborhood youth organizations on individual violent offending, and (2) whether neighborhood youth organizations have conditioning, beneficial effects that extend beyond the youths who participate in these organizations.
Data from two components of the Project on Human Development in Chicago Neighborhoods were utilized in this study: the Community Survey and the Longitudinal Cohort Study. A three-level logistic item response model nested 15,242 violent crime item responses within 1,912 subjects from cohorts aged 9, 12, and 15 years; subjects were nested within 79 neighborhoods across the city of Chicago.
Neighborhood youth organizations did not have a direct, contextual effect on adolescent violent offending. But, the effects of neighborhood youth organizations were heterogeneous in that they reduced the effects of low self-control on violent crime. Moreover, the conditioning role of neighborhood youth organizations operated partly through child-centered informal social control.
Neighborhood organizations matter in the etiology of youthful offending, but the ways in which these organizations are relevant are nuanced. Research must continue to grapple with the various mechanisms through which neighborhood organizations operate. Illuminating these processes may hold key insights for designing and implementing neighborhood organizations to prevent adolescent violent offending.
There is a widespread belief among criminologists, judges and the like that criminals are better off serving non-custodial sentences instead of going to prison. However, empirical evidence of the effects of such other types of sentences is scarce. To help fill the gap, this paper assesses the causal effect of community service on post-sentence income, dependency on social benefits, and crime.
For the empirical analyses I exploit a policy reform that implemented the use of community service as punishment among specific groups of criminals, Danish administrative data, and difference-in-difference matching
The results show that community service participants have higher long-run income levels and lower long-run levels of social benefit dependency compared to offenders who serve custodial sentences. However, while community service lowers recidivism among offenders convicted of violent crime, other traffic offences and misdemeanor, there are no overall effects of community service on crime committed after the serving of a sentence.
Serving a sentence through community services rather than in prison, causally improves offenders’ post-sentencing outcomes, particularly with regards to their labor market situation. Through this, the offender contributes not only to himself but also to society, and an increased use of non-custodial sentences is then beneficial on several levels. Importantly, my results apply to the Danish legal system, and may not be immediately applicable to other legal contexts.
Disentangle self-control from its elements and provide several new insights into the self-control dimensionality debate including: the proportion explained variance in scale items attributed to self-control and its elements, the viability of using total and individual scores to measure self-control and its elements in observed variable analyses, and the unique effects of general (self-control) and specific (elements) latent factors on crime and victimization.
The current study utilizes bifactor measurement and structural equation models to address the research objectives. The sample consists of Florida jail inmates and self-control and its elements are measured with the Grasmick et al. scale.
Results indicate the elements exist above and beyond the general factor of self-control, and that these specific factors collectively account for nearly one-third of the total proportion explained variance in the scale items. Findings from omega reliability analyses provide evidence supporting the use of a total score to measure self-control, but discouraging the use of subscales to measure the individual elements, when measurement error is not taken into account. Results from a bifactor structural equation model predicting crime and victimization reveal that the effects of three latent specific factors (temper, risk-seeking, and self-centeredness) are substantially larger than the effects of the general factor (self-control).
Bifactor methods placed self-control and the elements on equal conceptual footing and found both to explain variation in Grasmick et al. item responses and both to influence crime and victimization. Future work should examine the origins and stability of self-control vis-à-vis the individual elements.
Use a unique dataset to pair probation and parole officers and their clients in Denmark in 2002–2009 to identify causal effects of these officers on labor market outcomes and recidivism.
To identify these effects, we rely on data from all probationers and parolees in Copenhagen, where a rotational assignment process randomizes clients to officers. We apply OLS models to test whether the inclusion of probation and parole officer fixed effects improves model fit, and we show the impact of officer fixed effects by generating predicted values for one individual, varying only the officer.
The first stage of the analysis shows that the assignment of a probation or parole officer is indeed random in Copenhagen—at least in regards to the vast majority of background characteristics—suggesting that we are able to identify causal effects of probationer and parolee assignment on labor market outcomes and recidivism. The second stage of our analysis shows that although to a lower degree than common sense might suggest, probation and parole officers do matter for their clients’ dependency on public benefit transfers (around 10 percentage points) and criminal recidivism (around 30 percentage points), whereas earnings are unaffected.
As no study has yet to identify causal effects of probation and parole officer assignment, this study makes a novel contribution to the literature on the effects of criminal justice contact on subsequent life-course outcomes. Although generalizability to the US context is uncertain because we rely on Danish data, our findings nonetheless point in interesting directions for future research.
Provide insight into the victim-offender overlap and role differentiation by examining to what extent socio-psychological characteristics, risky lifestyles/routine activities and immersion in a violent subculture explain differences between victims, offenders and victim-offenders. Specifically, we measure to what extent anxiety and depression, negative peer relations, dominance, and self-control account for differences in adolescents’ inclination towards (violent) offending, victimization or both, over and above risky lifestyles/routine activities or immersion in a violent subculture.
Building on the method proposed by Osgood and Schreck (Criminology 45:273–311, 2007), we use two waves of panel data from the Zurich Project on the Social Development of Children and Youths, a prospective longitudinal study of adolescents in Switzerland.
Incorporating socio-psychological characteristics provides a more encompassing view of both the victim-offender overlap and victim versus offender role differentiation than routine activities/risky lifestyles and subcultural theory alone. Specifically, socio-psychological characteristics in particular differentiate between those who take on predominantly offender roles versus those who are predominantly victims.
Unpacking the victim-offender overlap and examining differences in socio-psychological characteristics furthers our understanding of the etiology of the victim-offender overlap.
The juvenile court was envisioned as a system of justice that would rehabilitate and punish young offenders. However, studies have not directly measured or examined support for “balanced” juvenile justice—that is, support for simultaneously employing juvenile rehabilitation and punishment to sanction youth—or how beliefs central to the creation of the court influence support for balanced justice. Drawing on scholarship on juvenile justice and theoretical accounts of views about sanctioning, the study tests hypotheses about such support.
The study employs multinomial logistic regression, using data from 866 college students enrolled in criminology and criminal justice classes, to examine support for different approaches to sanctioning violent juvenile offenders.
Analyses indicate that a majority of respondents supported balanced justice for violent delinquents, approximately one-third supported a primarily rehabilitation-focused approach to sanctioning, and the remainder supported a primarily punishment-oriented approach. Individuals who believed that youth could be reformed and deserved treatment were more likely to support balanced justice or a primarily rehabilitation-oriented approach to sanctioning youth.
The findings underscore the nuanced nature of public views about sanctioning youth, the salience of philosophical beliefs to support different sanctioning approaches, and the importance of research that accounts for beliefs central to the juvenile court’s mission.
To test the hypothesis that the spatial distribution of residential burglary is shaped by the configuration of the street network, as predicted by, for example, crime pattern theory. In particular, the study examines whether burglary risk is higher on street segments with higher usage potential.
Residential burglary data for Birmingham (UK) are examined at the street segment level using a hierarchical linear model. Estimates of the usage of street segments are derived from the graph theoretical metric of betweenness, which measures how frequently segments feature in the shortest paths (those most likely to be used) through the network. Several variants of betweenness are considered. The geometry of street segments is also incorporated—via a measure of their linearity—as are several socio-demographic factors.
As anticipated by theory, the measure of betweenness was found to be a highly-significant predictor of the burglary victimization count at the street segment level for all but one of the variants considered. The non-significant result was found for the most localized measure of betweenness considered. More linear streets were generally found to be at lower risk of victimization.
Betweenness offers a more granular and objective means of measuring the street network than categorical classifications previously used, and its meaning links more directly to theory. The results provide support for crime pattern theory, suggesting a higher risk of burglary for streets with more potential usage. The apparent negative effect of linearity suggests the need for further research into the visual component of target choice, and the role of guardianship.
Police use-of-force continues to be a major source of international concern, inviting interest from academics and practitioners alike. Whether justified or unnecessary/excessive, the exercise of power by the police can potentially tarnish their relationship with the community. Police misconduct can translate into complaints against the police, which carry large economic and social costs. The question we try to answer is: do body-worn-cameras reduce the prevalence of use-of-force and/or citizens’ complaints against the police?
We empirically tested the use of body-worn-cameras by measuring the effect of videotaping police–public encounters on incidents of police use-of-force and complaints, in randomized-controlled settings. Over 12 months, we randomly-assigned officers to “experimental-shifts” during which they were equipped with body-worn HD cameras that recorded all contacts with the public and to “control-shifts” without the cameras (n = 988). We nominally defined use-of-force, both unnecessary/excessive and reasonable, as a non-desirable response in police–public encounters. We estimate the causal effect of the use of body-worn-videos on the two outcome variables using both between-group differences using a Poisson regression model as well as before-after estimates using interrupted time-series analyses.
We found that the likelihood of force being used in control conditions were roughly twice those in experimental conditions. Similarly, a pre/post analysis of use-of-force and complaints data also support this result: the number of complaints filed against officers dropped from 0.7 complaints per 1,000 contacts to 0.07 per 1,000 contacts. We discuss the findings in terms of theory, research methods, policy and future avenues of research on body-worn-videos.
This paper presents a new quasi-experimental approach to assessing place based policing to encourage the careful evaluation of policing programs, strategies, and operations for researchers to conduct retrospective evaluations of policing programs.
We use a synthetic control model to reduce the bias introduced by models using non-equivalent comparison groups to evaluate High Point’s Drug Market Intervention and demonstrate the method and its versatility for evaluating programs retrospectively.
The synthetic control method was able to identify a very good match across all socio-demographic and crime data for the intervention and comparison area. Using a variety of statistical models, the impact of High Point Drug Market Intervention on crime was estimated to be larger than previous evaluations with little evidence of displacement.
The synthetic control method represents a significant improvement over the earlier retrospective evaluations of crime prevention programs, but there is still room for improvement. This is particularly important in an age where rigorous scientific research is being used more and more to guide program development and implementation.
This exploratory study examines if causal mechanisms highlighted by criminology theories work in the same way to explain both ideologically motivated violence (i.e., terrorism) and regular (non-political) homicides. We study if macro-level hypotheses drawn from deprivation, backlash, and social disorganization frameworks are associated with the likelihood that a far-right extremist who committed an ideologically motivated homicide inside the contiguous US resides in a particular county. To aid in the assessment of whether criminology theories speak to both terrorism and regular violence we also apply these hypotheses to far-right homicide and regular homicide incident location and compare the results.
We use data from the US Extremist Crime Database (ECDB) and the FBI’s SHR to create our dependent variables for the 1990–2012 period and estimated a series of logistic regression models.
The findings are complex. On the one hand, the models we estimated to account for the odds of a far-right perpetrator residing in a county found that some hypotheses were significant in all, or almost all, models. These findings challenge the view that terrorism is completely different from regular crime and argues for separate causal models to explain each. On the other hand, we estimated models that applied these same hypotheses to account for the odds that a far-right homicide incident occurred in a county, and that a county had very high regular homicide rate. Our comparison of the results found a few similarities, but also demonstrated that different variables were generally significant for each outcome variable. In other words, although criminology theory accounts for some of the odds for both outcomes, different causal mechanisms also appear to be at play in each instance. We elaborate on both of these points and highlight a number of important issues for future research to address.
While the economic model of crime suggests that improving post-prison labor market prospects should reduce recidivism, evaluations of previous employment-oriented re-entry programs have mixed results, possibly due to the multi-faceted challenges facing prisoners at the time of their release. We present an evaluation of an experiment that combines enhanced employment opportunities with wrap around services before and after release.
This paper presents what we believe is the first randomized controlled trial (RCT) of a re-entry program that combines post-release subsidized work with “reach-in” social services provided prior to release. The sample was 236 high-risk offenders in Milwaukee with a history of violence or gang involvement.
We observe increased employment rates and earnings during the period when ex-offenders are eligible for subsidized jobs, and these gains persist throughout the year. The intervention has significant effects (p < 0.01) in reducing the likelihood of rearrest. The likelihood that the treatment group is re-imprisoned during the first year after release is lower than for controls (22 vs. 26 %) but the difference is not statistically significantly different from zero.
The results of our RCT suggest that “reach-in” services to help improve human capital of inmates prior to release, together with wrap around services following release, boosts employment and earnings, although whether there is sufficient impact on recidivism for the intervention to pass a benefit-cost test is more uncertain. Average earnings for both treatment and control groups were very low; legal work simply does not seem that important in the economic lives of released prisoners.
The decision to carry a gun by drug market participants involves consideration of the potential for conflict with other market actors, the need for self-protection, and the desire for reputation and status, among other factors. The objective of this study is to investigate the motives, contingencies, and situational factors that influence criminal gun possession among drug market participants.
Using data on drug offenders from the 2004 Survey of Inmates in State and Federal Correctional Facilities, we estimate design-based logistic regression models within a multiple imputation framework to investigate the influence of drug market features and participant characteristics on gun carrying behavior.
Overall, 7 % of the drug offenders in our sample carried a firearm during the offense for which they were incarcerated. Our multivariate findings indicate that a number of factors condition drug market participants’ propensity for gun carrying, including individual psychopharmacological, economic-compulsive, and systemic factors as well as broader features of the marketplace, including the type of drug market, the value of the drugs, and certain structural characteristics.
Our findings have a number of implications for designing drug market interventions. Directing enforcement resources against emerging, expanding, or multi-commodity drug markets could deter lethal violence more than interventions targeting stable, single-commodity markets. In addition to open-air street markets, targeting higher-level and closed market segments could realize meaningful gun violence reductions. Finally, the expansion of promising focused deterrence strategies that combine deterrence and support initiatives could further deescalate gun violence.
To examine the effect of commuting rates on crime rate estimates in US cities, and to observe potential changes in the effects of other common crime rate correlates after accounting for commuting.
Crimes evaluated include homicide, aggravated assault, robbery, burglary, larceny, and auto theft. The sample includes US cities with a population of at least 100,000. The analysis first compares crime rankings using a rate based on the residential population and an alternative rate that takes into account daytime population changes due to commuting. Next, multivariate random effects panel models are used to evaluate the effect of commuting on crime rates, and to examine the extent to which the effects of other predictors change after controlling for commuting.
A city’s ranking can vary considerably depending on which denominator is used. Multivariate findings suggest that daily commuting rates are a significant, strong predictor of crime rates, and that controlling for commuting yields important changes in the effects of concentrated disadvantage, concentrated affluence, racial composition and residential instability.
The impact of the commuting population on crime rate rankings underscores the importance of viewing crime rankings with great caution. Specifically, the residential crime rate overestimates relative risk for cities that attract a large daily population from outside the city limits. Findings provide support for the routine activities perspective, and suggest that future research examining city-level crime rates should control for commuting. Limitations to the study and directions for future research are discussed.
The present study addresses whether unique or general processes lead to victimization across gendered pathways to crime. Specifically, the effects of low self-control and risky lifestyles—specified as various forms of offending and substance abuse—on violent victimization across developmental typologies for both men and women are examined.
Using data from three waves of the National Longitudinal Study of Adolescent Health, a two-stage cluster analysis is used to identify taxonomic groups for males and females that represent different pathways to crime. Multivariate negative binomial regression models are estimated to assess whether both self-control and risky lifestyles (e.g., criminal offending) are significant predictors of general forms of violent victimization across each identified cluster.
Low self-control and risky lifestyles significantly predict violent victimization across each of the taxonomic groups identified in the data, suggesting that these causal processes are universal rather than unique to any particular gendered pathway.
Although inferences cannot be made for types of victimization beyond those observed in the study (e.g., intimate partner violence and sexual assault), the findings lend credence to the notion that self-control and risky lifestyles are critical to the study of violent victimization among men and women following different gendered pathways.
To assess the monetary benefits and costs of the Stop Now And Plan-Under 12 Outreach Project (SNAP-ORP), a cognitive–behavioral skills training and self-control program, in preventing later offending by boys.
We assess the effect size of the SNAP-ORP program and convert this into a percentage reduction in convictions. We apply this reduction to the number and types of offenses committed by a sample of 376 boys between ages 12 and 20, taking account of co-offending, to estimate the crimes saved by the program. Based on the cost of each type of crime, we estimate the cost savings per boy and compare this with the cost of the SNAP-ORP program for low, moderate and high risk boys. We also scale up from convictions to undetected crimes.
Based on convictions, we estimate that between $2.05 and $3.75 are saved for every $1 spent on the program. Scaling up to undetected offenses, between $17.33 and $31.77 are saved for every $1 spent on the program. The benefit-to-cost ratio was greatest for the low risk boys and smallest for the high-risk boys. However, there were indications that the program was particularly effective for high risk boys who received intensive treatment.
Our benefit-to-cost ratios are underestimates. On any reasonable assumptions, the monetary benefits of the SNAP-ORP program greatly exceed its monetary costs. It is desirable to invest in early prevention programs such as SNAP-ORP to reduce crime and save money.
This study extends our knowledge on the negative effects of incarceration to the accumulation of wealth by examining whether, how, and how much incarceration affects home ownership and net worth. It also investigates how these outcomes vary with the time since a person was incarcerated and the number of incarceration periods, along with addressing potential mechanisms behind this relationship.
I apply hybrid mixed effects models that disaggregate within- and between person variation to investigate incarceration’s relationship with home ownership and net worth, using National Longitudinal Study of Youth data from 1985 to 2008. I also incorporate a set of mediation models in order to test for indirect effects of incarceration on wealth through earnings, health, and family formation.
My results show that incarceration limits wealth accumulation. Compared to never-incarcerated persons, ex-offenders are less likely to own their homes by an average of 5 percentage points, and their probability of home ownership decreases by an additional 28 percentage points after incarceration. Ex-offenders’ net worth also decreases by an average of $42,000 in the years after incarceration.
When combined with previous research on incarceration, my findings show that incarceration acts as an absorbing status, potentially leading to the accumulation of disadvantage. Although incarceration’s negative effects on wealth accumulation were partially mediated by its relationship with earnings and family formation, incarceration directly affected home ownership and net worth. In most cases, former inmates began with flatter wealth trajectories and experienced additional losses after incarceration.
This study investigates whether individual- and area-level factors explain variation in the residence-to-crime distances (RC distance) for 10 offense types.
Five years of police data from Dallas, Texas, are analyzed using multilevel models (hierarchical-linear/multi-level modeling).
Residence-to-crime distances for Dallas offenders varied notably across offense types. Although several area characteristics such as residential instability and concentrated immigration were associated with the overall variance in RC distance, neither these nor the individual-level characteristics used in our models explained the offense-type variance in the RC distance.
Although individual- and neighborhood-level factors did not explain substantial variation in RC distance across the various offenses, neighborhood-level factors explained a significant portion of neighborhood-level variance. Other finding included a curvilinear effect of age on RC distance. The salience of these findings and their implications for future research and offender travel theory are discussed.
This paper aims to suggest a framework to think of a more practical way to consider the broader impact of a program intervention beyond just its average, by considering the concept of treatment effect heterogeneity—how the same intervention may produce differential effects for different subgroups of individuals.
Using an application of data on an experimental intervention from the Johns Hopkins Prevention Intervention Research Center, the current study demonstrates the contribution of more general growth mixture modeling approaches, such as Group-Based Trajectory Model (Nagin in Group-based modeling of development. Harvard University Press, Cambridge, 2005) and growth mixture modeling (Muthén in New developments and techniques in structural equation modeling. Lawrence Erlbaum Associates, Mahwah, pp 1–33, 2001) for assessing meaningful heterogeneous effects of a treatment across clusters or classes of individuals following distinct patterns of development over time.
The findings demonstrate how population-averaged treatment effects might underestimate substantively meaningful localized effects among more theoretically and policy relevant subgroups of individuals such as those with non-normative growth (high–low) and those with more room for improvement (low–low) in the development of self-control.
We are calling for the assessment of a program in terms of both average and localized effects because we might wrongfully conclude that a given program is not effective when it in fact has a great impact, but only on the segments of population who need it the most.
This study seeks to better understand the relationship between neighborhood disability concentration and police calls for assault with a deadly weapon. Is this relationship the result of neighborhood concentrated disadvantage, or does disability act independently of other ecological characteristics associated with high crime rates?
The authors combine Census and other neighborhoodlevel data from Washington, DC to test a one-level random intercept hierarchical multiple regression model using Census tracts as a grouping variable. Disability concentration is measured by the percent of disabled residents living in a block group. Concentrated disadvantage is a composite measure including percent households below poverty line, percent families on public assistance, percent African American, percent female-headed households with children, and percent unemployed. Assault with a deadly weapon is a rate per 1,000 of police calls for assault in 2005–2006.
The effect of disability concentration is partially mediated by other ecological factors, but remains a significant predictor of neighborhood rates of reported assault. Each one-unit increase in percent disabled increased police calls for assault by 0.14 %.
The results of the analyses suggest that although concentrated disadvantage does affect the relationship between disability concentration and crime, it exerts an independent effect on neighborhood rates of assault with a deadly weapon.
To test the generalizability of previous crime and place trajectory analysis research on a different geographic location, Vancouver BC, and using alternative methods.
A longitudinal analysis of a 16-year data set using the street segment as the unit of analysis. We use both the group-based trajectory model and a non-parametric cluster analysis technique termed k-means that does not require the same degree of assumptions as the group-based trajectory model.
The majority of street blocks in Vancouver evidence stable crime trends with a minority that reveal decreasing crime trends. The use of the k-means has a significant impact on the results of the analysis through a reduction in the number of classes, but the qualitative results are similar.
The qualitative results of previous crime and place trajectory analyses are confirmed. Though the different trajectory analysis methods generate similar results, the non-parametric k-means model does significantly change the results. As such, any data set that does not satisfy the assumptions of the group-based trajectory model should use an alternative such as k-means.
Ascertaining the effect of treatment on recidivism is a core area of investigation in criminology and corrections research. The two objectives of the current analysis are: (1) to determine the true effect of treatment regimen completion on time to recidivism controlling for propensity to complete treatment; and (2) to examine the sensitivity of results under various propensity score methods.
Drawing on the population (n = 1,270) of parolees residing in a Midwestern state, we examine the effect of completing a treatment regimen on days to recidivism (using two failure outcomes) over a 2-year period using proportional hazard models. We adjust for the propensity to complete a treatment regimen using the covariate adjustment, inverse weighting, case matching, and strata methods.
Completing a treatment regimen has a sizable effect at reducing recidivism risk, which grows stronger the longer offenders are on parole. This effect is consistent across treatment propensity methods. It is driven mainly by completion of alcohol and drug treatment regimens. Treatment effects are stable across two measures of recidivism (arrest/prison-return and prison-return only).
Discussion centers on the implications for assessing treatment success in the parole population as well as on methodological implications for researchers conducting similar research. In the current analysis propensity scores produce stable results regardless of propensity method. Guidance is provided on selecting propensity methods based on data distortion, technical expertise, and presentation of results. We conclude that the covariate adjustment method is best suited for novice researchers, and the case matching method for expert researchers. The strata method is recommended for supplemental analyses. Future research should examine treatment effects reporting at least two propensity methods.
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We investigate the potential for preventing crimes at temporary hot spots in addition to chronic hot spots. Using data on serious violent crimes from Pittsburgh, Pennsylvania, we investigate an early warning system (EWS) for starting/stopping police deployments at temporary hot spots in coordination with constant prevention work at chronic hot spots.
We estimate chronic hot spots using kernel density smoothing. We use simple rules for detecting flare-ups of temporary hot spots, predicting their persistence, deploying police, and stopping deployments. We also consider a combination program including the hottest chronic hot spots, with EWS applied to remaining areas. Using 2000–2010 data, we run computational experiments varying the size of chronic hot spots and varying rule thresholds to tune the EWS. Tradeoff curves with percentage of crimes exposed to prevention versus percentage area of the city with crime prevention workload provide tools for coordinating chronic and temporary hot spot programs.
The combination program is the most efficient, equitable, and responsive program. After first allocating police prevention resources to the hottest chronic hot spots, the marginal benefits of adding more chronic hot spot area is not as high as adding temporary hot spots. Chronic hot spots are limited to large commercial and adjoining residential areas. Temporary hot spots are widely scattered throughout Pittsburgh.
Temporary hot spots exist outside of chronic hot spots and are targets for prevention as supplements to chronic hot spots. A combination program targeting both chronic and temporary hot spots is recommended.
This paper synthesizes the effects on repeat offending reported in ten eligible randomized trials of face-to-face restorative justice conferences (RJCs) between crime victims, their accused or convicted offenders, and their respective kin and communities.
After an exhaustive search strategy that examined 519 studies that could have been eligible for our rigorous inclusion criteria, we found ten that did. Included studies measured recidivism by 2 years of convictions after random assignment of 1,880 accused or convicted offenders who had consented to meet their consenting victims prior to random assignment, based on “intention-to-treat” analysis.
Our meta-analysis found that, on average, RJCs cause a modest but highly cost-effective reduction in the frequency of repeat offending by the consenting offenders randomly assigned to participate in such a conference. A cost-effectiveness estimate for the seven United Kingdom experiments found a ratio of 3.7–8.1 times more benefit in cost of crimes prevented than the cost of delivering RJCs.
RJCs are a cost-effective means of reducing frequency of recidivism.
Prior theoretical scholarship makes strong assumptions about the invariance of the age-crime relationship by sex. However, scant research has evaluated this assumption. This paper asks whether the age-crime curve from age 12–30 is invariant by sex using a contemporary, nationally representative sample of youth, the National Longitudinal Survey of Youth 1997 cohort (NLSY97).
To address the limitations of the existing empirical literature, a novel localized modeling approach is used that does not require a priori assumptions about the shape of the age-crime curve. With a non-parametric method—B-spline regression, the study models self-report criminal behavior and arrest by sex using age as the independent variable, and its cubic spline terms to accommodate different slopes for different phases of the curve.
The study shows that males and females have parallel age-crime curves when modeled with self-report criminal behavior variety score but they have unique age-crime in the frequency of self-report arrest. Group-based trajectory analysis is then used to provide a deeper understanding of heterogeneity underlying the average trends. The onset patterns by sex are quite similar but the post-peak analyses using the early onset sample reveal different patterns of desistance for arrest by sex.
The study found evidence of relatively early and faster desistance of arrest among females but little difference exists for the variety of criminal behaviors. Implications and future directions are discussed.
We test several principal hypotheses regarding individual criminal behavior derived from the integrated theory of Differential Coercion/Social Support (DCSS).
We use random sample household survey data from 1,000 respondents in two major cities, one in Bangladesh and one in Ukraine. In our site-specific analyses, we examine bivariate associations to estimate relations between global and domain-specific social support and coercion. We use negative binomial regressions with robust standard errors to assess separate, simultaneous, and interactive effects of social support and coercion on criminal probability, and, where appropriate, mediating effects of self-control and anger.
Consistent with the theory, coercion and social support are found to be independent rather than being opposite ends of a single continuum, although their inverse relationship is found to be substantially weaker than the theory implies. The data also support the idea that coercion has a crime generative effect, although they provide little confirmation of hypotheses about social support and criminal probability or about social support’s interrelationship with coercion. The results do suggest that beneficial effects of social support may be more pronounced and detrimental effects of coercion weakened in the more supportive context of Bangladesh, suggesting that their effects are sensitive to macro-level socio-cultural influences. Furthermore, the effects of both social support and coercion vary across different life domains. Finally, the results provide partial support for mediation hypotheses, with anger and sometimes self-control emerging as significant mediators of relationships between coercion and violence in the Ukrainian sample.
Our findings highlight the explanatory potential of DCSS, though the coercion part of the theory appears to be more viable than the social support part. The results suggest specific areas where theoretical refinement and clarification are needed, and they point toward some important policy implications.
The study of gang members is closely linked to the self-nomination method. It is timely to revisit the criterion validity of self-nomination, as recent theoretical and empirical advancements in gang disengagement necessitate further differentiating current from former gang members. This study assessed differences in gang embeddedness—a construct that taps individual immersion within deviant social networks—across three groups: current gang members, former gang members, and those individuals who have never joined a gang.
Data gathered in 2011 from a high-risk sample of 621 individuals in five cities were used to assess the validity of the self-nomination method. Standardized differences in a mixed graded response model of gang embeddedness were evaluated across the three statuses of gang membership.
Self-nomination was strongly related to embeddedness in gangs, even after controlling for demographic, theoretical, and gang-related factors. The strongest predictor of gang embeddedness was self-nomination as a current or a former gang member, although current gang members maintained levels of gang embeddedness about one standard deviation greater than former gang members. Self-nomination was also the primary determinant of gang embeddedness for males, females, whites, blacks, and Hispanics.
The results of this study provide strong evidence in support of the use of self-nomination to differentiate between non-gang and gang members as well as current and former gang members, adding to a body of research demonstrating that self-nomination is a valid measure of gang membership.
Prior research indicates that public assessments of the manner in which the police exercise their authority are a key antecedent of judgments about the legitimacy of the police. In this study, the importance of context in influencing people’s assessment of police wrongdoing is examined.
A randomized factorial experiment was used to test how respondents perceive and evaluate police–citizens interactions along a range of types of situations and encounters. 1,361 subjects were surveyed on factors hypothesized to be salient influences on how citizens perceive and evaluate citizen interactions with police. Subjects viewed videos of actual police–citizen encounters and were asked for their evaluations of these observed encounters. Contextual primes were used to focus subjects on particular aspects of the context within which the encounter occurs.
Structural equation models revealed that social contextual framing factors, such as the climate of police–community relations and the legality of the stop that led to the encounter, influence citizen appraisals of police behavior with effects comparable in size to and even larger than demographic variables such as education, race, and income.
These results suggest that the understandings and perceptions that people bring to a situation are important determinants of their assessment of police fairness. The police can positively influence citizen interpretations of police actions by striving to create a climate of positive police–community relationships in cities.
Criminological researchers want people to reveal considerable private information when utilizing self-report surveys, such as involvement in crime, subjective attitudes and expectations, and probability judgments. Some of this private information is easily accessible for subjects and all that is required is for individuals to be honest, while other information requires mental effort and cognitive reflection. Though researchers generally provide little or no incentive to be honest and thoughtful, it is generally assumed that subjects do provide honest and accurate information. We assess the accuracy of deterrence measures by employing a scoring rule known as the Bayesian truth serum (BTS)—that incentivizes honesty and thoughtfulness among respondents.
Individuals are asked to report on self-report offending and estimates of risk after being assigned to one of two conditions: (1) a group where there is a financial incentive just for participation, and (2) a BTS financial incentive group where individuals are incentivized to be honest and thoughtful.
We find evidence that there are some important differences in the responses to self-reporting offending items and estimates of the probability of getting arrested between the groups. Individuals in the BTS condition report a greater willingness to offend and lower estimates of perceived risk for drinking and driving and cheating on exams. Moreover, we find that the negative correlation between perceived risk and willingness to offend that is often observed in scenario-based deterrence research does not emerge in conditions where respondents are incentivized to be accurate and thoughtful in their survey responses.
The results raise some questions about the accuracy of survey responses in perceptual deterrence studies, and challenge the statistical relationship between perceived risk and offending behavior. We suggest further exploration within criminology of both BTS and other scoring rules and greater scrutiny of the validity of criminological data.
Has the Mexican government’s policy of removing drug-trafficking organization (DTO) leaders reduced or increased violence? In the first 4 years of the Calderón administration, over 34,000 drug-related murders were committed. In response, the Mexican government captured or killed 25 DTO leaders. This study analyzes changes in violence (drug-related murders) that followed those leadership removals.
The analysis consists of cross-sectional time-series negative binomial modeling of 49 months of murder counts in 32 Mexican states (including the federal district).
Leadership removals are generally followed by increases in drug-related murders. A DTO’s home state experiences more subsequent violence than the state where the leader was removed. Killing leaders is associated with more violence than capturing them. However, removing leaders for whom a $30m peso bounty was offered is associated with a smaller increase than other removals.
DTO leadership removals in Mexico were associated with an estimated 415 additional deaths during the first 4 years of the Calderón administration. Reforming Mexican law enforcement and improving career prospects for young men are more promising counter-narcotics strategies. Further research is needed to analyze how the rank of leaders mediates the effect of their removal.
The development and application of methods to assess consistency in sentencing before and after the 2011 England and Wales assault guideline came into force.
We use the Crown Court Sentencing Survey to compare the goodness of fit of two regression analyses of sentence length on a set of legal factors before and after the assault guideline came into force. We then monitor the dispersion of residuals from these regressions models across time. Finally, we compare the variance in sentence length of equivalent types of offences using exact matching.
We find that legal factors can explain a greater portion of variability in sentencing after the guideline was implemented. Furthermore, we detect that the unexplained variability in sentencing decreases steadily during 2011, while results from exact matching point to a statistically significant average reduction in the variance of sentence length amongst same types of offences.
We demonstrate the relevance of two new methods that can be used to produce more robust assessments regarding the evolution of consistency in sentencing, even in situations when only observational non-hierarchical data is available. The application of these methods showed an improvement in consistency during 2011 in England and Wales, although this positive effect cannot be conclusively ascribed to the implementation of the new assault guideline.
This work further examines the functional form of the self-control–delinquency relationship as an extension of recent work by Mears et al. (J Quant Criminol, 2013). Given the importance of the authors’ conclusions regarding the nonlinear relationship between these two variables and the recognition that there are some potential limitations in the sample and assumptions required for the analytic methods used, we apply both similar and alternative techniques with a data set comprised of serious youthful offenders to determine whether key findings can be replicated.
Data from the Pathways to Desistance study, which comprise extensive individual and social history interviews with 1,354 offenders over multiple waves spread out over 84 months, is utilized in this analysis. These data are well-suited to investigating the questions of interest as the target population comprises youth with offending histories that are more extensive than those likely to be found in general surveys of adolescents. The analyses consider the self-control–delinquency relationship in an alternative sample with the previously used Generalized Propensity Score (GPS) procedure, which requires strong assumptions, as well as nonparametric regression which requires far weaker assumptions to consider the functional form of the self-control–delinquency relationship.
The results generally show that the identified functional form of the self-control–delinquency relationship seems to be at least partly dependent on aspects of the modeling of dose–response associated with GPS procedures. When nonparametric general additive models are used with the same data, the relationship between self-control and delinquency seems to be approximately linear.
Identifying functional form relationships has importance for many criminological theories, but it is a task that requires that the balance of model assumptions to exploratory data analysis falls toward the latter. Nonparametric approaches to such questions may be a necessary first step in learning about the nature of mechanisms presumed to be at work in important explanations for crime and criminality.
Prior research suggests racial differences in violent victimization reflect differences in severity and not frequency. The current study proposes and tests hypotheses regarding the sources of racial variation in the nature of violent victimization.
A person-incident data file is employed to examine theoretical mechanisms that purportedly explain the effects of race on the nature of violent victimization. Data are analyzed with multinomial logistic regression models. Mediation processes are examined using a decomposition model that simultaneously adjusts for parameter rescaling and confounding.
Descriptive statistics reveal larger proportions of black males compared to whites experience gun violence, yet higher percentages of white males suffer unarmed violence. Differential exposure variables explain a larger quantity of racial differences in the likelihood of gun versus unarmed violence compared to behavioral attributes variables. Still, race remains a robust predictor of firearm victimization controlling for the full array of study variables.
It appears that black males are more likely than whites to suffer serious forms of violence and not minor forms due more to their exposure to risky settings than to their behavioral characteristics. Nonetheless, there is some evidence that stereotypes also partially account for the higher rates of gun victimization among black males. This study advances research on race and interpersonal violence. Moreover, the study demonstrates the importance of specifying the proper dependent variable when testing theories of interpersonal violence and victimization.
This study examines whether radical eco-groups have been deterred by legal sanctions. From a rational choice framework, I argue that members of these groups weigh costs and benefits. I measure an increase in costs, or an objective deterrence effect, through four federal sentencing acts targeted at reducing the criminal behavior of these groups [the tree-spiking clause of the Anti-Drug Abuse Act (ADA), the Animal Enterprise Protection Act (AEPA), the Anti-Terrorism and Effective Death Penalty Act (AEDPA), and the Animal Enterprise Terrorism Act (AETA)] and hypothesize that this legislation decreased the hazard of subsequent attacks.
This research is a quasi-experimental design utilizing the 1,068 illegal incidents perpetrated in the name of the environment, animal, or both as extracted from the Eco-Incidents Database. Using series hazard modeling, I examine the time until the next incident, serious incident, and ideologically specific incident in relation to dummy variables operationalizing the enactment dates of the above legislation.
All in all, the results are somewhat consistent with a rational choice framework and my hypotheses. The ADA decreased the hazard of another attack (11 %) and environment-only attack (15 %), while at the same time increasing the hazard of a terrorist, damage, and animal-related attack. AETA decreased the hazard of all (47 %), damage (42 %), and the behavior it was aimed at, that of animal-only incidents (52 %). However, neither the AEPA, nor AEDPA had a significant effect on any of the outcomes.
Overall, radical eco-groups were deterred by legal sanctions, but these findings are legislation and outcome specific in addition to including displacement effects.
The present study examines how individuals’ sanction risk perceptions are shaped by neighborhood context.
Using structural equation modeling on data from waves 6 and 7 of the National Youth Survey, we assess the direct and indirect relationships between adverse neighborhood conditions and two dimensions of sanction risk perceptions: the certainty of punishment and perceived shame. In addition, the role of shame as a mediator between neighborhood context and certainty of punishment is also investigated.
The results indicate that adverse neighborhood conditions indirectly affect both forms of sanction risk perceptions, and additional results show that perceived shame fully mediates the effect of neighborhood conditions on perceptions of the certainty of punishment.
The perceptual deterrence/rational choice perspective will need to be revised to accommodate more explicitly the role of neighborhood context in shaping sanction risk perceptions.
Examine relationships between routine activities, character contests in the form of “signifying,” and general delinquency and fighting in a street gang context.
Samejima’s (Estimation of latent ability using a response pattern of graded scores. Psychometrika monograph supplement 17. Psychometric Society, Richmond, VA, Retrieved 10 Aug 2011, from http://www.psychometrika.org/journal/online/MN17.pdf, 1969) graded response models and multilevel ordinal logistic regression models are estimated using data from Short and Strodtbeck (Group process and gang delinquency. University of Chicago Press, Chicago, 1965) study of street gangs in Chicago, 1959–1962. The primary sample consists of 490 boys representing 10 black gangs, 4 white gangs, 9 black lower-class groups, 4 white lower-class groups, 2 black middle-class groups, and 2 white middle-class groups.
Unstructured and unsupervised socializing with peers significantly increased the likelihood of delinquency among the boys and explained a significant portion of the group-level gang effect. In addition, the more time the boys spent hanging in the streets and attending parties, the more likely they were to participate in signifying, which, in turn, increased their risk of fighting.
Findings provide evidence that gangs contribute to delinquency partly through their effect on the routine activities of members. Findings also suggest that signifying is an important mechanism by which unstructured and unsupervised socializing with peers leads to violence.
Egocentric measures of peer delinquency, obtained through a census of a social network, have become the preferred operationalization for examining the relationships between social influence and delinquency. Studies regressing ego’s delinquency on the delinquency of nominated friend/s (i.e. alter/s) conclude that a statistically significant coefficient provides evidence of social influence. However, the inferences drawn from these studies may be biased by the introduction of artificial statistical dependence as a consequence of using social network data in a regression framework. Recent work (Shalizi and Thomas Sociol Methods Res 40:211–239, 2011) shows that latent homophily, or unmeasured confounding of observables, may lead to nonzero estimates of social influence, even if there is no causal significance. To examine this possibility, sensitivity analyses have been created (e.g. VanderWeele and Arah Epidemiology 22:42–52, 2011; VanderWeele Sociol Methods Res 40:240–255, 2011) to determine the robustness of an estimated coefficient to latent homophily.
In this research note, I examine the robustness of estimates for social influence from two articles (Haynie Am J Sociol 106:1013–1057, 2001; Meldrum et al. J Res Crime Delinq 46:353–376, 2009) using egocentric measures of peer delinquency.
Findings indicate that for large, precise point estimates, highly improbable conditions are needed to explain away the effects of social influence. However, less precise point estimates (i.e. large standard errors) are more sensitive to latent homophily.
The analyses indicate that studies using egocentric measures should conduct sensitivity tests, particularly when the estimated effect is weak and/or has a relatively large standard error. Scripts written in the free programming language R (R Core Team R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, 2012) are provided for researchers to conduct such analyses.
To undertake the first exploration of the nature of the relationship between internal crime (those that happen within facilities) and external crime (those occurring outside but in the nearby locale of facilities). The following questions are addressed. Do those localities that suffer high volumes of crime internally within their facilities also suffer high levels of crime in their immediate external environment? How is this influenced by the distribution of internal theft across facilities? What are the likely mechanisms for any relationship found?
Spatial regression is used to explore these relationships using data for 30,144 incidents of theft from a Metropolitan area of the UK arranged into small 50 × 50 m grid squares. Variables used in the analysis include counts of external and internal theft, counts of victimized and ‘risky’ facilities, indicators of land-use and a proxy for the on-street population.
There is found to be a strong positive relationship between internal and external theft that appears to be strengthened by the existence of facilities suffering particularly high crime volumes. Results suggest that internal theft problems precede external ones and that the physical concentration of chronically risky facilities is a particularly strong predictor of external theft problems.
An argument is made that risky facilities act as crime ‘radiators’, causing crime in the immediate environment as well as internally. This has implications for crime prevention policy in terms of facility placement and management.
Introduce and test the relative efficacy of two methods for modeling the impact of cumulative ‘exposure’ to drinking facilities on violent crime at street segments.
One method, simple count, sums the number of drinking places within a distance threshold. The other method, inverse distance weighted count, weights each drinking place within a threshold based on its distance from the street segment. Closer places are weighted higher than more distant places. Distance is measured as the street length from a street segment to a drinking place along the street network. Seven distance thresholds of 400, 800, 1,200, 1,600, 2,000, 2,400 and 2,800 feet are tested. A negative binomial regression model controlling for socio-economic characteristics, opportunity factors and spatial autocorrelation is used to evaluate which of the measure/threshold combinations produce a better fit as compared to a model with no exposure measures.
Exposure measured as an inverse distance weighted count produces the best fitting model and is significantly related to violent crime at longer distances than simple count (from 400 to 2,800 feet). Exposure to drinking places using a simple count is significantly related to violent crime up to 2,000 feet. Both models indicate the influence of drinking places is highest at shorter distance thresholds.
Both researchers and practitioners can more precisely quantify the influence of drinking places in multivariate models of street segment level violent crime by incorporating proximity in the development of a cumulative exposure measure. The efficacy of using exposure measures to quantify the influence of other types of facilities on crime patterns across street segments should be explored.
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.
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.
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.
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.
The federal sentencing guidelines constrain decision makers’ discretion to consider offenders’ life histories and current circumstances, including their histories of drug use and drug use at the time of the crime. However, the situation is complicated by the fact that judges are required to take the offender’s drug use into account in making bail and pretrial detention decisions and the ambiguity inherent in decisions regarding substantial assistance departures allows consideration of this factor. In this paper we build upon and extend prior research examining the impact of an offender’s drug use on sentences imposed on drug trafficking offenders.
We used data from three U.S. District Courts and a methodologically sophisticated approach (i.e., path analysis) to test for the direct and indirect (i.e., through pretrial detention and receipt of a substantial assistance departure) effects of an offender’s drug use history and use of drug at the time of the crime, to determine if the effects of drug use varies by the type of drug, and to test for the moderating effect of type of crime.
We found that although the offender’s history of drug use did not affect sentence length, offenders who were using drugs at the time of the crime received longer sentences both as a direct consequence of their drug use and because drug use at the time of the crime increased the odds of pretrial detention and increased the likelihood of receiving a substantial assistance departure. We also found that the effects of drug use varied depending on whether the offender was using crack cocaine or some other drug and that the type of offense for which the offender was convicted moderated these relationships.
Our findings illustrate that there is a complex array of relationships between drug use and key case processing decisions in federal courts.
Despite the dramatic expansion of the US correctional system in recent decades, little is known about the relative effectiveness of commonly used sanctions on recidivism. The goal of this paper is to address this research gap, and systematically examine the relative impacts on recidivism of four main types of sanctions: probation, intensive probation, jail, and prison.
Data on convicted felons in Florida were analyzed and propensity score matching analyses were used to estimate relative effects of each sanction type on 3-year reconviction rates.
Estimated effects suggest that less severe sanctions are more likely to reduce recidivism.
The findings raise questions about the effectiveness of tougher sanctioning policies for reducing future criminal behavior. Implications for future research, theory, and policy are also discussed.
Motivated by the reorientation of gang membership into a life-course framework and concerns about distinct populations of juvenile and adult gang members, this study draws from the criminal career paradigm to examine the contours of gang membership and their variability in the life-course.
Based on nine annual waves of national panel data from the NLSY97, this study uses growth curve and group-based trajectory modeling to examine the dynamic and cumulative prevalence of gang membership, variability in the pathways into and out of gangs, and the correlates of these pathways from ages 10 to 23.
The cumulative prevalence of gang membership was 8 %, while the dynamic age-graded prevalence of gang membership peaked at 3 % at age 15. Six distinct trajectories accounted for variability in the patterning of gang membership, including an adult onset trajectory. Gang membership in adulthood was an even mix of adolescence carryover and adult initiation. The typical gang career lasts 2 years or less, although much longer for an appreciable subset of respondents. Gender and racial/ethnic disproportionalities in gang membership increase in magnitude over the life-course.
Gang membership is strongly age-graded. The results of this study support a developmental research agenda to unpack the theoretical and empirical causes and consequences of gang membership across stages of the life-course.
To assess the role of selection in the observed association between residential mobility and delinquency among adolescents.
This study draws on a sample of adolescents from the National Longitudinal Study of Adolescent Health (Add Health). We first examine whether adjusting regression models for several well-established determinants of moving attenuates the association between mobility and delinquency. We then employ propensity score methods to estimate the effect of residential mobility on delinquency among a sub-sample of movers and non-movers who had similar likelihoods of moving.
The association between mobility and delinquency is significant and positive in regression models, although it is somewhat attenuated by additional control variables that are rarely considered in prior work. However, the distribution of mobility determinants differs substantially across movers and non-movers, potentially biasing these estimates. After covariate balance is achieved using a propensity score approach, we observe no differences in delinquency between groups.
Results suggest that certain adolescents are more likely to move than others, explaining the observed association between mobility and delinquency. Future research should therefore be mindful of selection when trying to account for differential outcomes between mobile and non-mobile adolescents.
To test whether individuals differ in deterrability by studying whether the effect of criminal experiences on perceived detection risk varies by criminal propensity.
Data from the British “Offending, Crime and Justice Survey”, a four-wave panel study on criminal behavior and victimization, are analyzed. Two subsamples for analyses are constructed: one of non-offenders at first measurement, to analyze the effect of gaining first offending experiences during the time of study (n = 1,279) and one sample of individuals who have committed offenses within the past year (n = 567), to analyze the effect of police contact among active offenders. Fixed-effects regressions of perceived detection risk on criminal experiences and interactions between criminal experiences and measures of criminal propensity (risk-affinity, impulsivity) are estimated.
Analyses support learning models for the formation and change of risk perceptions, but individual differences by criminal propensity are present in the deterrence process: After gaining first offending experiences, impulsive individuals as well as risk-averse individuals are more likely to lower their perceptions about the probability of detection than less impulsive or risk-affine individuals are. A positive effect of police contact on expected detection risk is restricted to risk-averse individuals.
Findings support claims that deterrence works differently for crime-prone individuals. The differential effects of impulsivity and risk-affinity underline the importance of not combining constituent characteristics of criminal propensity in composite indices, because they might have differential effects on deterrence.
Projection effects have been shown to bias respondent perceptions of peer delinquency, but network data required to measure peer delinquency directly are unavailable in most existing datasets. Some researchers have therefore attempted to adjust perceived peer behavior measures for bias via latent variable modeling techniques. The present study tested whether such adjustments render perceived peer coefficients equal to direct peer coefficients, using original data collected from 538 young adults (269 dyads).
After first replicating projection effects in our own data and examining the degree to which measures of personal, perceived peer, and direct peer violence represent empirically distinct constructs, we compared coefficients derived from two alternative models of personal violence. The first model included an error-adjusted latent measure of perceived peer violence as a predictor, whereas the second substituted a latent measure of directly-assessed, peer-reported violence.
Results suggest that personal, perceived peer, and direct peer measures each reflect fundamentally separate constructs, but call into question whether latent variable techniques used by prior researchers to correct for respondent bias are capable of rendering perceived peer coefficients equal to direct peer coefficients.
Research cannot bypass the collection of direct peer delinquency measures via latent variable modeling adjustments to perceived peer measures, nor should models of deviance view perceived peer and direct peer measures as alternative measures of the same underlying construct. Rather, theories of peer influence should elaborate and test models that simultaneously include both peer measures and, further, should attempt to identify those factors that account for currently unexplained variance in perceptions of peer behavior.
Drawing on prior theoretical and empirical work on survey participation, this study develops one potential method for increasing response rates and response quality in correctional surveys. Specifically, we hypothesize that providing inmates with a superficial survey choice (SSC)—that is, a choice between completing either of two voluntary surveys that are actually differently ordered versions of the same questionnaire—will increase their motivation both to participate in a given survey and to respond thoughtfully to the questions asked therein.
We test the effectiveness of this method by evaluating its impact on unit nonresponse, item nonresponse, and answer reliability. To do this, we analyze experimental data from a recent survey of male inmates incarcerated in a medium security, private prison.
Findings indicate that the overall response rate is higher among inmates who are provided a survey choice. In addition, the evidence shows that the SSC method increases the percentage of individual items completed, the number of demanding questions completed, and the reliability of reported responses.
The results from the analyses are consistent with the hypotheses that motivated this study and suggest that the SSC method holds promise as a tool for correctional researchers.
Despite the popularity of closed circuit television (CCTV), evidence of its crime prevention capabilities is inconclusive. Research has largely reported CCTV effect as “mixed” without explaining this variance. The current study contributes to the literature by testing the influence of several micro-level factors on changes in crime levels within CCTV areas of Newark, NJ.
Viewsheds, denoting the line-of-sight of CCTV cameras, were units of analysis (N = 117). Location quotients, controlling for viewshed size and control-area crime incidence, measured changes in the levels of six crime categories, from the pre-installation period to the post-installation period. Ordinary least squares regression models tested the influence of specific micro-level factors—environmental features, camera line-of-sight, enforcement activity, and camera design—on each crime category.
First, the influence of environmental features differed across crime categories, with specific environs being related to the reduction of certain crimes and the increase of others. Second, CCTV-generated enforcement was related to the reduction of overall crime, violent crime and theft-from-auto. Third, obstructions to CCTV line-of-sight caused by immovable objects were related to increased levels of auto theft and decreased levels of violent crime, theft from auto and robbery.
The findings suggest that CCTV operations should be designed in a manner that heightens their deterrent effect. Specifically, police should account for the presence of crime generators/attractors and ground-level obstructions when selecting camera sites, and design the operational strategy in a manner that generates maximum levels of enforcement.
To better understand the workings of illicit gun markets by identifying the characteristics of buyers, sellers, firearms, and transactions that predict whether a gun is used in crime or obtained by an illegal possessor subsequent to purchase.
The study employed multivariate survival analysis utilizing data on nearly 72,000 guns sold in the Baltimore metropolitan area from 1994 through 1999 and subsequent recoveries of over 1,800 of those guns by police in Baltimore through early 2000.
Adjusting for exposure time, guns sold in the Baltimore area had a 3.2 % chance of being recovered by police in Baltimore within 5 years. Guns were more likely to be recovered if: they were semiautomatic, medium to large caliber, easily concealable, and cheap; the buyers were black, young, female, living in or close to the city, and had previously purchased guns that were recovered by police; the dealer making the sale was, most notably, in or near the city and had made prior sales of crime guns; and the gun was purchased in a multiple gun transaction. The adoption of a law regulating secondhand gun sales in Maryland did not appear to affect the likelihood of a gun’s recovery, though the extent of the law’s enforcement is unclear.
Risk factors identified in this study could be used to guide gun trafficking investigations, regulation of gun dealers, and the development of prevention efforts for high-risk actors and areas. The results also provide some support for policies that regulate particular types of firearms and transactions. Limitations to the study and directions for future research are discussed.
Place-based policing experiments have led to encouraging findings regarding the ability of the police to prevent crime, but sample sizes in many of the key studies in this area are small. Farrington and colleagues argue that experiments with fewer than 50 cases per group are not likely to achieve realistic pre-test balance and have excluded such studies from their influential systematic reviews of experimental research. A related criticism of such studies is that their statistical power under traditional assumptions is also likely to be low. In this paper, we show that block randomization can overcome these design limitations.
Using data from the Jersey City Drug Market Analysis Experiment (N = 28 per group) we conduct simulations on three key outcome measures. Simulations of simple randomization with 28 and 50 cases per group are compared to simulations of block randomization with 28 cases. We illustrate the statistical modeling benefits of the block randomization approach through examination of sums of squares in GLM models and by estimating minimum detectable effects in a power analysis.
The block randomization simulation is found to produce many fewer significantly unbalanced samples than the naïve randomization approaches both with 28 and 50 cases per group. Block randomization also produced similar or smaller absolute mean differences across the simulations. Illustrations using sums of squares show that error variance in the block randomization model is reduced for each of the three outcomes. Power estimates are comparable or higher using block randomization with 28 cases per group as opposed to naïve randomization with 50 cases per group.
Block randomization provides a solution to the small N problem in place-based experiments that addresses concerns about both equivalence and statistical power. The authors also argue that a 50 case rule should not be applied to block randomized place-based trials for inclusion in key reviews.
Drawing from lifestyle-routine activity and self-control perspectives, the causal mechanisms responsible for repeat victimization are explored. Specifically, the present study investigates: (1) the extent to which self-control influences the changes victims make to their risky lifestyles following victimization, and (2) whether the failure to make such changes predicts repeat victimization.
Two waves of panel data from the Gang Resistance Education and Training program are used (N = 1,370) and direct measures of change to various risky lifestyles are included. Two-stage maximum likelihood models are estimated to explore the effects of self-control and changes in risky lifestyles on repeat victimization for a subsample of victims (n = 521).
Self-control significantly influences whether victims make changes to their risky lifestyles post-victimization, and these changes in risky lifestyles determine whether victims are repeatedly victimized. These changes in risky lifestyles are also found to fully mediate the effects of self-control on repeat victimization.
Findings suggest that future research should continue to measure directly the intervening mechanisms between self-control and negative life outcomes, and to conceptualize lifestyles-routine activities as dynamic processes.
Test the hypothesis that dispositional self-control and morality relate to criminal decision making via different mental processing modes, a ‘hot’ affective mode and a ‘cool’ cognitive one.
Structural equation modeling in two studies under separate samples of undergraduate students using scenarios describing two different types of crime, illegal downloading and insurance fraud. Both self-control and morality are operationalized through the HEXACO model of personality (Lee and Ashton in Multivariate Behav Res 39(2):329–358, 2004).
In Study 1, negative state affect, i.e., feelings of fear and worry evoked by a criminal prospect, and perceived risk of sanction were found to mediate the relations between both dispositions and criminal choice. In Study 2, processing mode was manipulated by having participants rely on either their thinking or on their feelings prior to deciding on whether or not to make a criminal choice. Activating a cognitive mode strengthened the relation between perceived risk and criminal choice, whereas activating an affective mode strengthened the relation between negative affect and criminal choice.
In conjunction, these results extend research that links stable individual dispositions to proximal states that operate in the moment of decision making. The results also add to dispositional perspectives of crime by using a structure of personality that incorporates both self-control and morality. Contributions to the proximal, state, perspectives reside in the use of a new hot/cool perspective of criminal decision making that extends rational choice frameworks.
Recent legislation in Pennsylvania mandates that forecasts of "future dangerousness" be provided to judges when sentences are given. Similar requirements already exist in other jurisdictions. Research has shown that machine learning can lead to usefully accurate forecasts of criminal behavior in such setting. But there are settings in which there is insufficient IT infrastructure to support machine learning. The intent of this paper is provide a prototype procedure for making forecasts of future dangerousness that could be used to inform sentencing decisions when machine learning is not practical. We consider how classification trees can be improved so that they may provide an acceptable second choice.
We apply an version of classifications trees available in R, with some technical enhancements to improve tree stability. Our approach is illustrated with real data that could be used to inform sentencing decisions.
Modest sized trees grown from large samples can forecast well and in a stable fashion, especially if the small fraction of indecisive classifications are found and accounted for in a systematic manner. But machine learning is still to be preferred when practical.
Our enhanced version of classifications trees may well provide a viable alternative to machine learning when machine learning is beyond local IT capabilities.
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.
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.
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.
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.
The relatively weak quasi-experimental evaluation design of the original Boston Operation Ceasefire left some uncertainty about the size of the program’s effect on Boston gang violence in the 1990s and did not provide any direct evidence that Boston gangs subjected to the Ceasefire intervention actually changed their offending behaviors. Given the policy influence of the Boston Ceasefire experience, a closer examination of the intervention’s direct effects on street gang violence is needed.
A more rigorous quasi-experimental evaluation of a reconstituted Boston Ceasefire program used propensity score matching techniques to develop matched treatment gangs and comparison gangs. Growth-curve regression models were then used to estimate the impact of Ceasefire on gun violence trends for the treatment gangs relative to comparisons gangs.
This quasi-experimental evaluation revealed that total shootings involving Boston gangs subjected to the Operation Ceasefire treatment were reduced by a statistically-significant 31 % when compared to total shootings involving matched comparison Boston gangs. Supplementary analyses found that the timing of gun violence reductions for treatment gangs followed the application of the Ceasefire treatment.
This evaluation provides some much needed evidence on street gang behavioral change that was lacking in the original Ceasefire evaluation. A growing body of scientific evidence suggests that jurisdictions should adopt focused deterrence strategies to control street gang violence problems.
To present and test an opportunity perspective on prison inmate victimization.
Stratified random samples of inmates (n 1 = 5,640) were selected from Ohio and Kentucky prisons (n 2 = 46). Bi-level models of the prevalence of assaults and thefts were estimated. Predictors included indicators of inmate routines/guardianship, target antagonism, and target vulnerability at the individual level, and several indicators of guardianship at the facility level.
Assaults were more common among inmates with certain routines and characteristics that might have increased their odds of being victimized (e.g., less time spent in recreation; committed violence themselves during incarceration), and higher levels of assaults characterized environments with lower levels of guardianship (e.g., architectural designs with more “blind spots”, larger populations, and less rigorous rule enforcement as perceived by correctional officers). Similar findings emerged for thefts in addition to stronger individual level effects in prisons with weaker guardianship (e.g., ethnic group differences in the risk of theft were greater in facilities with larger populations and less rigorous rule enforcement).
The study produced evidence favoring a bi-level opportunity perspective of inmate victimization, with some unique differences in the relevance of particular concepts between prison and non-prison contexts.
This paper uses a “local average treatment effect” (LATE) framework in an attempt to disentangle the separate effects of criminal and noncriminal gun prevalence on violence rates. We first show that a number of previous studies have failed to properly address the problems of endogeneity, proxy validity, and heterogeneity in criminality. We demonstrate that the time series proxy problem is severe; previous panel data studies have used proxies that are essentially uncorrelated in time series with direct measures of gun relevance.
We adopt instead a cross-section approach: we use US county-level data for 1990, and we proxy gun prevalence levels by the percent of suicides committed with guns, which recent research indicates is the best measure of gun levels for crosssectional research. We instrument gun levels with three plausibly exogenous instruments: subscriptions to outdoor sports magazines, voting preferences in the 1988 Presidential election, and numbers of military veterans. In our LATE framework, the estimated impact of gun prevalence is a weighted average of a possibly negative impact of noncriminal gun prevalence on homicide and a presumed positive impact of criminal gun prevalence.
We find evidence of a significant negative impact, and interpret it as primarily “local to noncriminals”, i.e., primarily determined by a negative deterrent effect of noncriminal gun prevalence. We also demonstrate that an ATE for gun prevalence that is positive, negative, or approximately zero are all entirely plausible and consistent with our estimates of a significant negative impact of noncriminal gun prevalence.
The policy implications of our findings are perhaps best understood in the context of two hypothetical gun ban scenarios, the first more optimistic, the second more pessimistic and realistic. First, gun prohibition might reduce gun ownership equiproportionately among criminals and noncriminals, and the traditional ATE interpretation therefore applies. Our results above suggest that plausible estimates of the causal impact of an average reduction in gun prevalence include positive, nil, and negative effects on gun homicide rates, and hence no strong evidence in favor of or against such a measure. But it is highly unlikely that criminals would comply with gun prohibition to the same extent as noncriminals; indeed, it is virtually a tautology that criminals would violate a gun ban at a higher rate than noncriminals. Thus, under the more likely scenario that gun bans reduced gun levels more among noncriminals than criminals, the LATE interpretation of our results moves the range of possible impacts towards an increase in gun homicide rates because the decline in gun levels would primarily occur among those whose gun possession has predominantly negative effects on homicide.
Tests the idea that the frequency distribution typically observed in crosssectional crime victimization data sampled from surveys of general populations is a heterogeneously distributed result of the mixing of two latent processes associated, respectively, with each of the tails of the distribution.
Datasets are assembled from a number of samples taken from the British Crime Survey and the Scottish Crime Victimization Survey. Latent class analysis is used to explore the probable, latent distributions of individual property crime and personal crime victimization matrices that express the frequency and type of victimization that are self-reported by respondents over the survey recall period.
The analysis obtains broadly similar solutions for both types of victimization across the respective datasets. It is demonstrated that a hypothesized mixing process will produce a heterogeneous set of local sub-distributions: a large sub-population that is predominantly not victimized, a very small ‘chronic’ sub-population that is frequently and consistently victimized across crime-type, and an ‘intermediate’ sub-population (whose granularity varies with sample size) to whom the bulk of victimization occurs. Additionally, attention is paid to the position of very high frequency victimization within these sub-populations.
The analysis supports the idea that crime victimization may be a function of two propensities: for immunity, and exposure. It demonstrates that zero-inflation is also a defining feature of the distribution that needs to be set alongside the significance that has been attached to the thickness of its right tail. The results suggest a new baseline model for investigating population distributions of crime victimization.
This paper uses a sample of convicted offenders from Pennsylvania to estimate the effect of incarceration on post-release criminality.
To do so, we capitalize on a feature of the criminal justice system in Pennsylvania—the county-level randomization of cases to judges. We begin by identifying five counties in which there is substantial variation across judges in the uses of incarceration, but no evidence indicating that the randomization process had failed. The estimated effect of incarceration on rearrest is based on comparison of the rearrest rates of the caseloads of judges with different proclivities for the use of incarceration.
Using judge as an instrumental variable, we estimate a series of confidence intervals for the effect of incarceration on one year, two year, five year, and ten year rearrest rates.
On the whole, there is little evidence in our data that incarceration impacts rearrest.
The logic of incapacitation is the prevention of crime via the forced removal of known offenders from the community. The challenge is to provide a plausible estimate of how many crimes an incarcerated individual would have committed, were s/he free in the community rather than confined in prison. The objective of this study is to provide estimates of the incapacitation effect of first-time imprisonment from a sample of convicted offenders.
The data are official criminal records of all individuals convicted in The Netherlands in 1997. Two different analytical strategies are used to estimate an incapacitation effect. First, the offending rate of the imprisoned individuals prior to their confinement in 1997 provides a “within-person counterfactual”. Second, imprisoned offenders are paired with comparable non-imprisoned offenders using the method of propensity score matching in order to estimate a “between-person counterfactual”. Incapacitation estimates are provided separately for juvenile imprisonment (ages 12–17) as well as adult imprisonment (ages 18–50), and for male and female offenders.
The best estimate is that 1 year of incarceration prevents between 0.17 and 0.21 convictions per year. The use of additional data sources indicates that this corresponds to between roughly 2.0 and 2.5 criminal offenses recorded by the police.
The current results suggest that, insofar as imprisonment is used with the primary goal of reducing crime through incapacitation, a general increase in the use of incarceration as the sanction of choice is not likely to yield major crime control benefits.
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.
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.
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.
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.
Current ‘geographical offender profiling’ methods that predict an offender’s base location from information about where he commits his crimes have been limited by being based on aggregate distributions across a number of offenders, restricting their responsiveness to variations between individuals as well as the possibility of axially distorted distributions. The efficacy of five ideographic models (derived only from individual crime series) was therefore tested.
A dataset of 63 burglary series from the UK was analysed using five different ideographic models to make predictions of the likely location of an offenders home/base: (1) a Gaussian-based density analysis (kernel density estimation); (2) a regression-based analysis; (3) an application of the ‘Circle Hypothesis’; (4) a mixed Gaussian method; and (5) a Minimum Spanning Tree (MST) analysis. These tests were carried out by incorporating the models into a new version of the widely utilised Dragnet geographical profiling system DragNetP. The efficacy of the models was determined using both distance and area measures.
Results were compared between the different models and with previously reported findings employing nomothetic algorithms, Bayesian approaches and human judges. Overall the ideographic models performed better than alternate strategies and human judges. Each model was optimal for some crime series, no one model producing the best results for all series.
Although restricted to one limited sample the current study does show that these offenders vary considerably in the spatial distribution of offence location choice. This points to important differences between offenders in the morphology of their crime location choice. Mathematical models therefore need to take this into account. Such models, which do not draw on any aggregate distributions, will improve geographically based investigative decision support systems.
Sentencing guidelines, statutory presumptive sentencing, determinate sentencing, truth in sentencing, and three strikes are important components of the criminal justice system. The main purpose behind a relatively-fixed sentence is to remove judicial discretion by insuring that convicted felons receive a reasonably-assumed sentence depending on the crime committed. The current study assessed shifts in year-to-year changes in incarceration rates within all 50 states from the years 1965–2008 due to the adoption of sentencing reforms.
The study tests two competing theories, a normative theory and critical theory of the expected effects of reforms on imprisonment. Data was analyzed using panel regression with unit-specific fixed effects, conditional change scores, panel corrected standard errors, and a new measure of reforms.
This study, possibly due to differences in model specification, ran counter to a number of previous studies and suggests some “front-end” sentencing reforms and “back-end” release changes are, on average, related to changes in imprisonment.
The study concluded, that when significant, reforms increased more than decreased prison growth in comparison to indeterminate sentencing. Additionally, the analysis concludes that changes in release mechanisms and parole decision structures are driving increased growth more than changes in sentencing structures.
Social control theory assumes that the ability of social constraints to deter juvenile delinquency will be invariant across individuals. This paper tests this hypothesis and examines the degree to which there are differential effects of parental controls on adolescent substance use.
Analyses are based on self-reported data from 7,349 10th-grade students and rely on regression mixture models to identify latent classes of individuals who may vary in the effects of parental controls on drug use.
All parental controls were significantly related to adolescent drug use, with higher levels of control associated with less drug use. The effects of instrumental parental controls (e.g., parental management strategies) on drug use were shown to vary across individuals, while expressive controls (e.g., parent/child attachment) had uniform effects in reducing drug use. Specifically, poor family management and more favorable parental attitudes regarding children’s drug use and delinquency had stronger effects on drug use for students who reported greater attachment to their neighborhoods, less acceptance of adolescent drug use by neighborhood residents, and fewer delinquent peers, compared to those with greater community and peer risk exposure. Parental influences were also stronger for Caucasian students versus those from other racial/ethnic groups, but no differences in effects were found based on students’ gender or commitment to school.
The findings demonstrate support for social control theory, and also help to refine and add precision to this perspective by identifying groups of individuals for whom parental controls are most influential. Further, they offer an innovative methodology that can be applied to any criminological theory to examine the complex forces that result in illegal behavior.
This paper examines Gottfredson and Hirschi’s (A general theory of crime. Stanford University Press, Stanford, 1990) self-control theory and develops theoretical arguments for why self-control may have a differential effect on offending depending on the level of self-control.
We test the argument that the association between self-control and violent offending (n = 5,681) and non-violent offending (5,672) is nonlinear by using generalized propensity score analyses of data from the National Longitudinal Study of Adolescent Health.
The results indicate that self-control and offending are nonlinearly related in a manner that involves two thresholds. Specifically, among individuals at the high end of the self-control spectrum, there was little evidence of an association between variation in self-control and offending. However, among individuals in the middle part of the self-control spectrum, a positive association obtained—that is, the greater the level of low self-control, the greater the likelihood of offending. Finally, among individuals at the low end of the self-control spectrum, there was, once again, little evidence of an association.
A nonlinear association between self-control and offending may exist and have implications for self-control theory and tests of it. Studies are needed to investigate further the possibility of a nonlinear association and to test empirically the mechanisms that give rise to it.
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.
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.
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.
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.
Drawing from general strain and self-control perspectives, the role of maladaptive coping (i.e., substance use) in the causal pathway between victimization and offending is explored. Specifically, the present study investigates: (1) the extent to which self-control influences substance use in response to victimization, and (2) whether victims with low self-control and who engage in substance use are more likely to commit violent offenses in the future.
Three waves of panel data from the Gang Resistance Education and Training program are used (N = 1,463), and negative binomial regression models are estimated to explore the interactive effects of low self-control, victimization, and substance use on violent offending.
Victims with low self-control are more likely to engage in substance use post-victimization, and low self-control and substance use are found to exert significant conditional effects on the pathway between victimization and offending. These results remained robust even after controlling for prior violent offending, peer influences, prior substance use, and other forms of offending.
The causal pathway between victimization and offending can be explained by drawing upon key concepts drawn from self-control (i.e., how self-control shapes coping responses) and general strain (i.e., how those responses influence offending above and beyond self-control) theories, indicating that these two perspectives can and should be integrated more explicitly to explain the dynamics of victimization and offending.
Using data from a nationally representative survey of adolescents in Finland this research examined the influence of spending time in public settings on the risk of physical assault and robbery victimization.
Binary and multinomial regression models were estimated to disaggregate associations between hours spent in public settings and characteristics of the victimization incident. The amount of causality/spuriousness in the association was examined using a method of situational decomposition.
Our findings indicate that: (1) an active night life (any time after 6 pm) has a strong effect on victimization for boys, whereas much of the association between night life and victimization is spurious for girls; (2) after-school activity is not a risk factor; (3) adolescents who frequent public places at night increase their risk of victimization by people they know as well as strangers; and (4) much of the risk of night time activity in public settings is alcohol-related.
Our research suggests that a good deal of the risk associated with spending time in public settings is a function of the victim’s own risky behavior rather than inadvertent physical contact with motivated offenders in the absence of capable guardians. In addition, this lifestyle is significantly more victimogenic for males.
This study investigated the extent to which immigrant concentration is associated with reductions in neighborhood crime rates in the City of Los Angeles.
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.
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.
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.
This study examines the relationship between delinquent behavior and gang involvement in China. We assess the feasibility of self-report methodology in China and whether established findings in US and European settings on the relationship between gang involvement, violence specialization, and delinquent behavior extend to the Chinese context.
Data were gathered from 2,245 members of a school-based sample in Changzhi, a city of over 3 million people in Northern China. Drawing from a detailed survey questionnaire that measures prominent theoretical constructs, multi-level item response theory modeling was used to examine the association of gang involvement with general and specific forms of delinquency, notably violence specialization.
Over half of the sample engaged in some form of delinquency over the prior year. Eleven percent of the sample reported gang involvement. Large bivariate differences in overall delinquency and violence specialization between gang and non-gang youth were observed. Multivariate analyses with measures of low self-control, household strains, family and school attachment, parental monitoring, and peer delinquency reduced the bivariate effect sizes, but current and former gang members had higher log odds of overall delinquency and violence specialization.
In helping fill gaps of knowledge on gangs and delinquency in the world’s most populous country, this study observed self-reported rates of delinquency and gang involvement not unlike Western countries. Findings on the relationship between gangs and delinquency, particularly violence, are consistent with the current literature and support the invariance hypothesis of gang involvement.
This article explores patterns of terrorist activity over the period from 2000 through 2010 across three target countries: Indonesia, the Philippines and Thailand.
We use self-exciting point process models to create interpretable and replicable metrics for three key terrorism concepts: risk, resilience and volatility, as defined in the context of terrorist activity.
Analysis of the data shows significant and important differences in the risk, volatility and resilience metrics over time across the three countries. For the three countries analysed, we show that risk varied on a scale from 0.005 to 1.61 “expected terrorist attacks per day”, volatility ranged from 0.820 to 0.994 “additional attacks caused by each attack”, and resilience, as measured by the number of days until risk subsides to a pre-attack level, ranged from 19 to 39 days. We find that of the three countries, Indonesia had the lowest average risk and volatility, and the highest level of resilience, indicative of the relatively sporadic nature of terrorist activity in Indonesia. The high terrorism risk and low resilience in the Philippines was a function of the more intense, less clustered pattern of terrorism than what was evident in Indonesia.
Mathematical models hold great promise for creating replicable, reliable and interpretable “metrics” to key terrorism concepts such as risk, resilience and volatility.
Develop the concept of differential institutional engagement and test its ability to explain discrepant findings regarding the relationship between the age structure and homicide rates across ecological studies of crime. We hypothesize that differential degrees of institutional engagement—youths with ties to mainstream social institutions such as school, work or the military on one end of the spectrum and youths without such bonds on the other end—account for the direction of the relationship between homicide rates and age structure (high crime prone ages, such as 15–29).
Cross sectional, Ordinary Least Squares regression analyses using robust standard errors are conducted using large samples of cities characterized by varying degrees of youths’ differential institutional engagement for the years 1980, 1990 and 2000. The concept is operationalized with the percent of the population enrolled in college and the percent of 16–19 year olds who are simultaneously not enrolled in school, not in the labor market (not in the labor force or unemployed), and not in the military.
Consistent and invariant results emerged. Positive effects of age structure on homicide rates are found in cities that have high percentages of disengaged youth and negative effects are found among cities characterized with high percentages of youth participating in mainstream social institutions.
This conceptualization of differential institutional engagement explains the discrepant findings in prior studies, and the findings demonstrate the influence of these contextual effects and the nature of the age structure-crime relationship.
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.
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.
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.
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.
Using household survey data from three major cities in foreign countries, we add to research concerning General Strain Theory (GST) by focusing on aspects that have been ignored or under-researched. First, we address questions concerning SES variations in the operation of the processes of GST, with particular focus on whether various relationships specified by the theory are more likely in the lower SES group. Second, we explore the extent to which prior coping strategies influence subsequent coping choices. Finally, we seek to determine the links between SES, coping histories, and subsequent coping choices.
The study analyzes the effects of past and contemporaneous strain/negative emotions and prior coping efforts on various coping strategies across three SES groupings using negative binomial, ordered logit, and OLS regression.
We find that, with some variations, the basic processes of GST are operative across all SES categories. However, whereas strain appears to have a moderate association with alcohol-related and criminal coping strategies, avoidant coping appears to be largely irrelevant for anybody who faces strain. Our data also demonstrate that specific forms of prior coping partially influence the types of coping employed later. But, with few exceptions, these effects are not more pronounced among those of lower SES.
In sum, our findings suggest that individuals in various SES groupings may prefer certain types of coping, whereas different types of attempted coping may predispose individuals to specific forms of subsequent adaptation.
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.
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.
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.
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.
We provide a critical review of empirical research on the deterrent effect of capital punishment that makes use of state and, in some instances, county-level, panel data.
We present the underlying behavioral model that presumably informs the specification of panel data regressions, outline the typical model specification employed, discuss current norms regarding “best-practice” in the analysis of panel data, and engage in a critical review.
The connection between the theoretical reasoning underlying general deterrence and the regression models typically specified in this literature is tenuous. Many of the papers purporting to find strong effects of the death penalty on state-level murder rates suffer from basic methodological problems: weak instruments, questionable exclusion restrictions, failure to control for obvious factors, and incorrect calculation of standard errors which in turn has led to faulty statistical inference. The lack of variation in the key underlying explanatory variables and the heavy influence exerted by a few observations in state panel data regressions is a fundamental problem for all panel data studies of this question, leading to overwhelming model uncertainty.
We find the recent panel literature on whether there is a deterrent effect of the death penalty to be inconclusive as a whole, and in many cases uninformative. Moreover, we do not see additional methodological tools that are likely to overcome the multiple challenges that face researchers in this domain, including the weak informativeness of the data, a lack of theory on the mechanisms involved, and the likely presence of unobserved confounders.
Investigate how different model assumptions have driven the conflicting findings in the literature on the deterrence effect of capital punishment.
The deterrence effect of capital punishment is estimated across different models that reflect the following sources of model uncertainty: (1) the uncertainty about the probability model generating the aggregate murder rate equation, (2) the uncertainty about the determinants of an individual’s choice of committing a murder or not, (3) the uncertainty about state level heterogeneity, and (4) the uncertainty about the exchangeability between observations with zero murder case and those with positive murder cases.
First, the estimated deterrence effects exhibit great dispersion across models. Second, a particular subset of models—linear models with constant coefficients—always predict a positive deterrence effect. All other models predict negative deterrence effects. Third, the magnitudes of the point estimates of deterrence effects differ mainly because of the choice of linear versus logistic specifications.
The question about the deterrence effect of capital punishment cannot be answered independently from substantive assumptions on what determines individual behavior. The need for judgment cannot be escaped in empirical work.