Journal of Quantitative Criminology 31(2)

Journal of Quantitative Criminology, June 2015: Volume 31, Issue 2

Risky Lifestyles, Low Self-control, and Violent Victimization Across Gendered Pathways to Crime
Jillian J. Turanovic, Michael D. Reisig & Travis C. Pratt

Objectives: 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. Methods: 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. Results: 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. Conclusions: 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.

The Absorbing Status of Incarceration and its Relationship with Wealth Accumulation
Michelle Lee Maroto

Objectives: 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. Methods: 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. Results: 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. Conclusions: 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.

How Far to Travel? A Multilevel Analysis of the Residence-to-Crime Distance
Jeffrey M. Ackerman & D. Kim Rossmo

Objectives: This study investigates whether individual- and area-level factors explain variation in the residence-to-crime distances (RC distance) for 10 offense types. Methods: Five years of police data from Dallas, Texas, are analyzed using multilevel models (hierarchical-linear/multi-level modeling). Results: 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. Conclusions: 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.

Monetary Benefits and Costs of the Stop Now And Plan Program for Boys Aged 6–11, Based on the Prevention of Later Offending
David P. Farrington & Christopher J. Koegl

Objectives: 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. Methods: 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. Results: 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. Conclusions: 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.

On the Importance of Treatment Effect Heterogeneity in Experimentally-Evaluated Criminal Justice Interventions
Chongmin Na, Thomas A. Loughran & Raymond Paternoster

Objectives: 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. Methods: 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. Results: 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. Conclusions: 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.

Broken Neighborhoods: A Hierarchical Spatial Analysis of Assault and Disability Concentration in Washington, DC
Paul D. C. Bones & Trina L. Hope

Objective: 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? Methods: 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. Results: 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 %. Conclusions: 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.

The Effect of Commuting on City-Level Crime Rates
Brian J. Stults & Matthew Hasbrouck

Objective: 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. Methods: 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. Results: 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. Conclusions: 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.