Race, the Economic Maturity Gap, and Criminal Offending in Young Adulthood

Abstract

While research has documented that racial and ethnic groups are differentially involved in juvenile and adult crime, little research has examined whether economic and employment well‐being can explain Black and White adolescents' persistence in criminal activity into young adulthood. One potential explanation emerges from Moffitt, who posits an economic maturity gap to explain Blacks' greater persistence in offending in young adulthood. To evaluate this hypothesis, we draw on three waves of data available in the National Longitudinal Survey of Adolescent Health to examine whether economic and employment well‐being in young adulthood can account for the racial gap, and persistence in offending. Findings are consistent with Moffitt's hypothesis and indicate that economic and employment well‐being in young adulthood explain Blacks' greater involvement in criminal and violent offending in young adulthood. In addition, results indicate that the greater tendency of Blacks, compared to Whites, to persist in violent offending is also driven by the reduced economic and employment well‐being that Blacks face in young adulthood.

Keywords:

• economic disadvantage
• life course
• race
• violence

Notes

1. Rare exceptions are the three OJJDP Causes and Correlates Studies in Denver, Pittsburgh, and Rochester and Wolfgang, Figlio, and Sellin's (1987) analysis of predictors of crime over the life course in the Philadelphia Birth Cohort study.

2. To be sure, Moffitt (1993) anticipates a third group of individuals, but they do not offend. She refers to them as “abstainers.” Her theory makes no explicit hypothesis about race differences among these non‐normative, non‐offenders, and our study does not focus on these individuals.

3. Moffitt also speaks to race differences in life‐course‐persistent offenders when she states: “In the United States, the crime rate for Black Americans is higher than the crime rate for Whites. The race difference may be accounted for by a relatively higher prevalence of both life‐course‐persistent and adolescence‐limited subtypes among contemporary African Americans. Life‐course‐persistent antisocials might be anticipated at elevated rates among Black Americans because the putative root causes of this type are elevated by institutionalized prejudice and by poverty. Among poor Black families, prenatal care is less available, infant nutrition is poorer, and the incidence of exposure to toxic and infectious agents is greater, placing infants at risk for the nervous system problems that research has shown to interfere with prosocial child development. To the extent that family bonds have been loosened and poor Black parents are under stress…, & to the extent that poor Black children attend disadvantaged schools …, for poor Black children the snowball of cumulative continuity may begin rolling earlier, and it may roll faster downhill. In addition, adolescence‐limited crime is probably elevated among Black youths as compared to White youths in contemporary America. If racially segregated communities provide greater exposure to life‐course‐persistent role models, then circumstances are ripe for Black teens with no prior behavior problems to mimic delinquent ways in a search for status and respect (1994, p. 39).”

4. For instance, data from the Pittsburgh Youth Survey have documented that childhood risk factors associated with life‐course‐persistent offending are similarly related to early‐onset frequent delinquent offending and physical aggression among Black and White males (Caspi et al., 1994; Lynam, Moffitt, & Stouthamer‐Loeber, 1993; Lynam et al., 2000). Only a few studies have directly compared life‐course‐persistent versus adolescence‐limited patterns across race, and they point to opposing findings. Donnellan, Ge, and Wenk (2000) designated the taxonomy groups within 2,000 California Youth Authority inmates. On several cognitive ability measures, life‐course‐persistent offenders scored below adolescence‐limited offenders among Whites and Hispanics, but not among Blacks. The opposite pattern of race differences emerged from a different study of 377 California Youth Authority inmates released on average at age 24, and followed for 12 years (Piquero, Brame, & Lynam, 2004). This study found that Non‐Whites had worse childhood poverty and lower cognitive test scores than Whites, and that Non‐Whites had longer criminal careers than Whites. Finally, a study of the Baltimore sample of the National Collaborative Perinatal Project tested for race differences in the etiological process hypothesized to underlie life‐course‐persistent offending (Piquero et al., 2005). Results showed that several variables helped to explain differences between Whites and Blacks in the frequency of offending; however, although Blacks had higher mean levels of risk factors than Whites, the developmental processes predicting frequent offending were the same across groups. Specifically, low birth weight in combination with adverse familial environments predicted frequent offending from adolescence to age 33 among Whites and Blacks alike, although the effect size reached statistical significance only among African Americans, a pattern opposite to that reported by Donnellan et al. (2000). Most, but not all, of these studies fit Moffitt's notion that the causal developmental processes are the same across racial groups, but that Blacks end up with higher levels of crime because they begin the processes with higher levels of risk factors (Moffitt, 2006).

5. Discrimination likely plays an important role in the sorting of African Americans, especially African American males, into the worst types of jobs. For instance, quasi‐experimental audit studies provide evidence of racial discrimination for entry‐level jobs (Bendick, Jackson, & Reinoso, 1999; Cross, Kenney, Mell, & Zimmerman, 1990; Turner, Fix, & Struyk, 1991) and more recent work by Pager revealed stronger effects of employment discrimination against African Americans than felons (2003).

6. Of course, a more complete analysis would examine these and other explanations. However, we focus on the “economic maturity gap” as an initial first‐step at assessing Moffitt's specific hypothesis and encourage future work to carefully examine the other hypotheses.

7. Supplementary analyses examined whether and how our sample of respondents restricted to those respondents who participated in all three waves of in‐home surveys differ from a sample of Wave 1 respondents. Findings of the attrition analyses indicate that background demographic and behavioral characteristics (e.g., delinquency, violence, substance use) of our sample are not significantly different from a sample of respondents interviewed at Wave 1. However, our restricted sample does contain slightly more Non‐White youth (49 percent compared to 47 percent).

8. We chose to dichotomize involvement in violence since a minority of respondents report engaging in any violence (10.8 percent) and of those respondents who engage in violence the majority commit fewer than two acts (87 percent).

9. Other race/ethnicity includes adolescents who self‐report their race/ethnicity as being Hispanic/Latina/o, American Indian/Native Americans, and Asians/Pacific Islanders.

10. Ideally, data would allow us to measure not only current employment status but cumulative work experience. While this is a limitation of our study, it is likely to result in conservative estimates of employment effects.

11. Add Health defines full‐time employment as working 30 or more hours.

12. The theory of labor market segmentation proposes the existence of two separate labor markets in the US Economy (Doeringer & Piore 1971). Jobs within the primary labor market are located in core industries and generally feature higher wages, comprehensive benefits, safe working conditions, on‐the‐job training, opportunities for advancement, stable employment, and due process in the enforcement of work rules (Doeringer & Piore 1971). Secondary labor market jobs, by contrast, are mostly a domain of the industrial periphery and are low paying and low in status (Averitt 1968; Gordon 1972; Osterman 1975). Work within this labor market is often performed under unsafe, or at least unpleasant, conditions. Furthermore, the lack of both internal career ladders and processes that serve to enforce work rules lead to personnel turnover rates that are significantly higher than those found within the primary labor market (Parcel & Sickmeier 1988). Research in the late 1970s and early 1980s also attempted to provide categorizations for researchers to follow (Bibb & Form 1977; Tolbert, Horan, & Beck 1980). While none of these categorizations are uniquely valid they all follow the tenets of labor market segmentation theory. More generally, it is worth pointing out that the assumption of this theory is that labor markets are highly stratified and access to certain segments of the labor market is restricted by both discrimination (noted earlier) and credentials. The role of credentials (grades, educational degrees, etc.) in the placement of individuals in jobs in the secondary sector, as well as the role of credentials in the movement of workers from jobs in the secondary to the primary sector of the labor market, are also relevant considerations.

13. Before we impute on missing data, we limit our sample to those respondents who participated in all three waves of data collection (of the 20,745 respondents interviewed at Wave 1, 19,962 were eligible for Wave III interview, and 15,170 completed the interview). Of these 15,170 respondents, 11,930 participated in Wave II, identified their race, and had sampling weights available. Among this sample, missing data on particular variables was rare and ranged between 0–2.6 percent of cases needed to be imputed for each variable. Because we do limit our sample to respondents who participated in all 3 waves of data, issues of attrition and non‐response are important to consider. In a thorough analysis of the issue of non‐response bias, Chantala, Kalsbeek, and Andraca (2004) demonstrate that total non‐response bias for many health and risk behaviors rarely exceed 1 percent in any of the three surveys.

14. In supplementary analyses we also regressed our measures of economic and employment well‐being on race and control variable to determine if there are significant race differences in the effects of the economic well‐being measures. These analyses indicated that Black respondents were significantly less likely to be employed in full‐ or part‐time employment compared to White respondents, were significantly less likely to be in skilled jobs compared to White respondents, held significantly fewer jobs than White respondents and scored significantly lower on the index of property owned compared to White respondents. Other race respondents scored significantly higher on the index of economic problems and the index of property owned compared to White respondents, were less likely to hold full‐time employment compared to White respondents, and held significantly fewer jobs than White respondents.

15. Preliminary data analyses examined the correlations among the economic and employment measures. These results showed correlation coefficients in the range of 0.10–0.38. Multicollinearity diagnostics also suggested no evidence of multicollinearity affecting estimates (VIFs less than 2).