Tianyin Yu, University of New Haven
According to data from the U.S. Bureau of Justice Statistics (BJS), 67.8% of released state prisoners were arrested for a new crime within three years, and 76.7% were arrested within five years (Durose, Cooper, & Snyder, 2014). Reducing recidivism not only protects society at large, but also improves the life quality of individual ex-prisoners. Employment has long been recognized as having a negative correlation with crime (Uggen, 1999; Uggen et al., 2005). However, ex-prisoners face tremendous difficulties in obtaining employment opportunities post-release. Such a disadvantaged situation may be attributable to multiple reasons. First, most of the offenders may simply lack the necessary job skills for specific positions, keeping them from those usually higher paid and more stable jobs. Second, many employers are reluctant to hire these people due to the stigma imposed by their previous criminal records.
This review aims to explore the general effect of employment on recidivism, the gender effect of employment on recidivism, and the role of job characteristics play in deterring crime, as well as to examine how incarceration may affect ex-prisoners in their pursuit of jobs. Policy implications based on the extant research and future research directions also will be discussed.
Studies on the association between employment and crime have never been lacking (Lageson & Uggen, 2013). Most of the studies have focused exclusively on men (Laub & Sampson, 2003; Skardhamar & Savolainen, 2014; van der Geest, Bijleveld, & Blokland, 2011). Theories such as social control and rational choice assume employment should have a crime deterrent effect. Many service programs are in place to help offenders to build job skills. However, evaluations of these programs have yielded mixed results. Some have found positive effects on recidivism (e.g., Redcross, Millenky, Rudd, & Levshin, 2012), while others have found little or no effect (e.g., Bushway & Apel, 2012; Cook et al., 2015).
One longitudinal study consisted of a large sample from Norwegian prisons (Skardhamar & Telle, 2012) and used a wide range of individual information (offense type, post-release education, post-release social benefits, drug use/possession, time served, immigrant background, family type, education, parents’ education, previous earnings from work, etc.). The researchers found that employment is associated with reduced recidivism, with the association “strongest for those who were sentenced for property and economic offenses and least strong for those who were sentenced for violent and traffic offenses” (Skardhamar & Telle, 2012, p.646-647). Their measure of post-release employment, though, “is based on being registered in the central employee register,” which does not include characteristics of the job.
Some studies do incorporate characteristics of the job. One such example is by Uggen (1999). In this study, it was found that job quality had a strong and robust effect on economic and non-economic criminal behavior (Uggen, 1999). Another longitudinal study by van der Geest and colleagues (2011) also considered both job quality and stability. They found a significant relationship between employment and delinquent development among most offender groups.
Others have focused on the timing of the employment (Skardhamar & Savolainen, 2014) and the effect of social ties on employment and recidivism (Berg & Huebner, 2011). Offenders with stronger family ties were more likely to be employed, and those who were employed and had strong ties to family were less likely to recidivate (Berg & Huebner, 2011). In terms of timing, Skardhamar and Savolainen (2014) asked specifically the question of whether employment promotes desistance from crime by testing two contradicting hypotheses – the turning point hypothesis (reductions in offending after job entries) and the hook-for-change hypothesis (desistance occurring before successful transitions to legitimate work). Interestingly, they found that “most offenders had desisted prior to the employment transition and that becoming employed was not associated with further reductions in criminal behavior” (Skardhamar & Savolainen, 2014, p. 263). Nevertheless, there seem to be a tiny portion (less than 2%) of the sample that became employed while engaging in active criminal activity, and subsequently decreased their criminal activity (Skardhamar & Savolainen, 2014).
Contemporary Research and Findings
A study by Ramakers and colleagues (2016) used observational longitudinal Dutch data from the Prison Project to measure ex-prisoners’ recidivism risk in relation to employment and its characteristics. Specifically, the researchers investigated whether “job duration, returning to pre-prison employer, working as an employee versus self-employed, hours, and occupational level” have any effect on recidivism outcomes. Because of the design, one cannot rule out the possibility that the recidivism outcomes are due to factors other than employment and its characteristics (education, marital status, offender type, etc.), as people with various recidivism risks may self-select themselves into jobs of different qualities. To address this issue, the authors controlled for a wide range of individual characteristics and life domains in multivariate analyses. Separate propensity score models were used for each of the six independent variables (employed, employee, job retention, full-time job, higher occupational level, return job), with 34 potential confounding factors.
Results from the bivariate analyses indicated that overall, unemployed ex-prisoners were more likely to re-offend than those employed, and that “a higher occupational level seems to be related to a lower risk of reoffending” (Ramakers et al., 2016, p. 15). Meanwhile, it was found that working as an employee or being self-employed and work intensity do not seem to affect recidivism. Multivariate analyses, however, revealed that after controlling for the confounding factors, employment did not seem to affect recidivism, while “type of job remains significantly related to reoffending” (Ramakers et al., 2016, p. 17).
This study advanced our knowledge of the relationship between types of job and recidivism, by incorporating multiple independent variables on job characteristics and careful design to minimize selection bias. Nonetheless, a few aspects are still waiting to be explored by future studies. First, a universal problem in many quasi-experimental studies is that, however many variables are controlled, there will be selection bias to some extent. Second, one important job characteristic, wage, was not included in this study. As one would imagine, being able to pay off monthly bills by using their wages would mean a lot to ex-prisoners. On the other hand, if they could hardly make ends meet, it would likely pull them toward yet another criminal event. Link and Roman (2017) provided some insights into the financial aspects by studying the relationship between child support debt, employment, and recidivism following incarceration. It was found that “higher child support debt significantly reduced employment” in a 15-month follow up period, indicating the strain of financial burden may have an impact on employment, thus further affecting recidivism (Link and Roman, 2017). Third, the authors also acknowledged they used a relatively short follow-up period (6 months). Had the study extended its duration, could it have yielded different outcomes? Finally, as was mentioned earlier, studies in this area tend to focus on male criminals. Although women account for a small portion of the total criminal population, research to date has shown varying (un)employment effects for the two genders (Verbruggen, Blokland, & van der Geest, 2012).
Concerning the gender question, a recent study by Denver and colleagues (2017) advanced our knowledge by focusing on a sample of nursing home and home health-care job applicants, of which the majority (two-thirds) were women with criminal records. Specifically, Denver and colleagues (2017) examined “how a criminal background check affects subsequent criminal justice involvement for individuals with records” (p. 177). In this study, to conquer the selection bias, they used “an instrumental variable (IV) approach” and controlled virtually every aspect (candidate’s criminal history, demographic and geographic characteristics, etc.) on which the decision of background clearance is made. Theoretically, as the authors argued, the leftover variation should be “as good as random.” In addition to gender, they also examined the age effect on recidivism.
Results show that gender and age do matter. Overall, “older individuals experience smaller treatment effects … on subsequent arrest” (p. 197). Particularly, older women “experienced an almost null effect” of background clearance, whereas men (young and old) “seem to be responsive to the background check decision” (p. 197). It is worth noting that the fact that older women being irresponsive to the background check decision does not necessarily mean they are callous about being able to get a job. As the authors point out, it may simply be that they are less likely to recidivate in the first place. In addition to the background clearance effect on subsequent arrest, the authors went a step further to examine the impact of overall employment on recidivism. In general, results showed that while “women still have a low-to null effect,” men “experience a substantial impact,” a sizeable portion of which can only be attributable to increased employment opportunities. Such a result is not surprising, given that gender differences in offending have long been recognized by scholars (Daly, 1992; Fagan, 2015; Liu, 2015).
What is worth mentioning is that this sample consists of ex-offenders who are motivated to seek a job, which is different than most of the previous studies examining the employment effect on recidivism. It thus makes it possible to control for motivation and examine precisely the effect of allowing one to work on recidivism. Labeling theory (Becker, 1963) posits that people with criminal records receive negative impressions from others. In other words, given two persons who have everything else equal (age, education, gender, personality, etc.), the one with a criminal record would experience a negative impact of the legal sentencing beyond legal sentencing per se. Employment being a crucial step following releasing, and a good indicator of recidivism, certainly warrants closer examination.
Previous studies have probed the impact of incarceration on employment (Apel & Sweeten, 2010; Raphael, 2007; Fagan and Freeman, 1999; Western, Kling, and Weiman, 2001). In general, results show the effect of incarceration tend to differ across time (Western & Beckett, 1999), and age (Fagan & Freeman, 1999). In an article by van der Geest and colleagues (2016), the authors examined “the effects of incarceration on longitudinal trajectories of employment” by using “observational data on the employment careers from age 23 up to age 32 in 270 high-risk makes” (p. 107). As most of the studies of this kind, random assignment was difficult to implement, so the authors chose to use trajectory models to control for heterogeneity. Four employment trajectories were identified: normative, delayed onset, dropouts, and non-participating. For the non-participating group, after controlling for the characteristics, it was found that incarceration did not affect employment in this category, which is not surprising. As the authors speculated, it may be mainly due to their already poor job skills, social skills, and personality traits, which would have made this group not competent to employment anyway. Meanwhile, a greater negative impact was found among those who were more regularly employed than those who had limited work experience. However, the effect was found to be temporary (van der Geest and colleagues, 2016).
One of the advantages of this study lies in its longitudinal nature (from age 23 to 32), which enables observation of long-term effects of incarceration. The shortcoming, though, is the small sample size (270). As the authors also acknowledged, had the sample size been large enough, it would be possible to control other factors and test exclusively for the effects of incarceration on employment. Also, this study used data from the Netherlands. What would the result look like if it was conducted in the United States? That would leave the need for future research.
Policy Implications and Future Research
Based on the extant research findings, we know that the effect of employment does not apply equally to everyone of different ages, gender, and background. The fact that many of the evaluation studies on employment-oriented reentry programs have failed to yield solid positive results should trigger the question of – why not? As evidence indicates, not every type of job, but jobs of higher quality, will influence recidivism (Ramakers et al., 2016). Therefore, employment-oriented programs should focus on building technical skills and knowledge of the ex-prisoners and help them to get jobs that are of higher quality. Meanwhile, scarce resources need to be focused on those who are most likely to be affected by (un)employment – younger men. As evidence shows, women of older age are the least likely to be influenced by work (Denver et al., 2017). It is possible that their recidivism rates are low in the first place, or (un)employment may simply mean little to them. Either way, programs other than employment training should be utilized for this specific population. Because research in this area is rare, future research should look to verify findings of gender differences.
Meanwhile, there is evidence showing that ex-offenders do face extra obstacles than people who do not have criminal records while seeking for jobs, and that the negative impact is most prominent for those who are regularly employed (van der Geest et al., 2016). One needs to keep in mind that the Netherlands, when compared to the United States, has relatively shorter prison sentences and more lenient laws (van der Geest et al., 2016). Therefore, when it comes to the United States, one would assume that ex-prisoners in the United States may face greater obstacles. The question of how to balance public safety and provide reentry support for individual ex-offenders is always a difficult one. However, a blanket ban on job opportunities by employers certainly is not the best solution. It is encouraging that during the past few years, efforts have been put in place to promote the hiring of people with records (Avery & Hernandez, 2017). Future research should investigate how to best balance public safety and individual ex-offender’s wellbeing, by probing into why ex-offenders who hold jobs re-offend and considering their offense types, as well as how to reduce risk factors.
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