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The Effect of Private Sector Work Opportunities in Prison on Labor Market Outcomes of the Formerly Incarcerated

Abstract

This paper examines the effects of a private-sector prison work program called the Prison Industry Enhancement Certification Program (PIECP) on formal unemployment duration, duration of formal employment, and earnings of men and women released from various state prisons between 1996 and 2001. It also investigates the labor market dynamics of formerly incarcerated men and women. The program is found to increase reported earnings and formal employment on the extensive margin, with a stronger impact on the formal employment of women. There is little evidence that it increases formal employment along the intensive margin (i.e., duration of formal employment). Contrary to segmented labor market theories, superior employment (i.e., higher-paying jobs) does not lead to increased job stability. Roughly 92 % of individuals who obtained formal employment in the sample experienced job loss; however, reincarceration rates are too low to explain this fact. An evaluation of labor market dynamics reveals that traditional human capital variables, criminogenic factors, and a few demographic characteristics determine job loss. In addition, black women, single women, and women with more extensive criminal histories face greater barriers in the labor market than their male counterparts.

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Notes

  1. Machin and Meghir (2004) also find the same result in England and Wales.

  2. Although the use of prison labor has been opposed by labor and human rights activists, this research focuses solely on the rehabilitative aspect of prison work programs and seeks to understand whether receiving vocational skills training and work experience while incarcerated improves postrelease labor market outcomes. For a detailed historical discussion of prison labor and the Prison Industry Enhancement Certification Program, please see Cox (2009).

  3. Retrieved from the Federal Justice Statistics Program (http://www.bjs.gov/fjsrc/), and West and Sabol (2008).

  4. Normalized differences for each variable are calculated by dividing the difference in the mean values of each group by the average standard deviation of the groups.

  5. Likewise, due to the availability of additional control variables, a broader range of demographic characteristics of the PIECP sample can be compared to national estimates to explore the extent to which external validity is traded for greater interval validity. A detailed comparison of the PIECP sample to a nationally representative sample of prisoners can be found in Cox (2015).

  6. Please see Appendix A for a more detailed description of OTW, TI, and PIECP jobs.

  7. Please see Cox (2009) for the legislative history and an in-depth analysis of PIECP.

  8. Please see Cox (2009) for a complete listing of certificate holders during that time.

  9. According to the BJA (1999), “Certificate Holder refers to a department of corrections, or an alternate umbrella authority, which is approved by BJA for PIECP Project Certification. Certificate Holders assume monitoring and designation responsibilities with respect to their designated Cost Accounting Centers (CAC). All PIECP prisoner-made goods are produced within (a CAC) that a certificate holder designates within itself, private prisons located in the same state or jurisdiction or, in the case of an umbrella authority within its membership agencies. … Umbrella Authority refers to a type of Certificate Holder which is authorized by law to administer a PIECP Project and which consists of state and/or local departments of correction located within the same state. A certified umbrella authority may designate CACs within its membership agencies, as well as within members’ private prisons, and assumes responsibility for monitoring CAC compliance” (pp. 17007–17009)

  10. Delaware, Missouri, and the Texas Red River County Department of Corrections no longer hold certificates. On May 13, 2004, the Washington State Supreme Court found employing inmates in Class 1 free venture industries to be unconstitutional. However, the legislature proposed an amendment to the constitution that would allow the state to employ such labor. This amendment passed in November 2007. Using a logistic regression in a public choice model, Gallagher and Edwards (1997) attempted to explain the likelihood that a state would participate in PIECP using data from 1985 to 1992. They find that “states with stronger union membership, democratic governors, and high unemployment rates will be less likely to allow PIE projects” (p. 97). However, states with a rehabilitative view of prisons are more likely to participate in PIECP.

  11. According to the BJA (1999), “Cost Accounting Center (CAC) refers to a distinct PIECP goods production unit of the industries system that is managed as a separate accounting entity under the authority of a Certificate Holder. All PIECP production activities are conducted within the context of a designated CAC which, generally is structured either as a customer or employer model for purposes of determining PIECP inmate benefits” (p. 17007).

  12. Note that the type of model the private sector uses will determine the benefit structure to the inmate. According to the BJA’s (1999) PIECP federal guidelines, “PIECP projects must provide inmate workers appropriate benefits comparable to those made available by the Federal or State Government to private sector employees, including workers’ compensation and, under certain circumstances, Social Security” (p. 17011). Nonetheless, some states prohibit inmates from receiving workers’ compensation. However, “provision of comparable workers’ compensation benefits is acceptable as long as the CAC can demonstrate comparability of such benefits with those secured by the Federal or State Government for private sector employees” (BJA 1999, p. 17011). Moreover, if the employer model is used, then Social Security benefits must be provided to the prisoner. However, if the customer model is used, then “the BJA recognizes the applicability of other provisions of Federal law which may operate to preclude the provision of PIECP inmates with certain benefits, including Social Security” (BJA 1999, p. 17011).

  13. I am grateful to Cindy Smith for her guidance and willingness to share the data.

  14. Segmented labor market theory (SLM) is often referred to as a theory of dual labor markets because it argues that there are two distinct labor markets: the primary labor market and the secondary labor market. The primary labor market consists of “jobs in large firms and/or unionized jobs, which tend to be better jobs—higher paying, more promotion possibilities, better working conditions, and more stable work. The secondary labor market, which roughly overlaps large sections of the external labor market, contains the low-paid jobs that are held by workers who are discriminated against and who have unstable working patterns” (Cain 1976, p. 1222). Traditionally, economists view preferences for work as exogenous variables that help to explain an individual’s labor market achievements. However, SLM theorists argue that preferences are actually endogenous and can be determined by success in the labor market. In particular, discrimination and other systematic or random influences that cause individuals to enter the secondary labor market can trigger antiwork sentiments among low-income workers, thereby keeping them in a position of hardship (Cain 1976). Theoretically, this implies that employment can help to rehabilitate an offender; however, it would take a decent (i.e., in the primary labor market) job to draw individuals out of a life of crime.

  15. There are originally 1,309 observations. However, one observation is dropped due to having a negative value for time served and 91 observations with a recorded race of minority other are excluded. Moreover, there are two observations in which time from release to formal employment and time from formal employment to job loss indicated the ex-offender was employed during the follow-up period. However, the censored employment variable was coded to the contrary. Because all of the other employment variables indicated employment was obtained, the censored variable was corrected to match the rest of the data. A descriptive analysis comparing this sample to the Smith (2009) data determined that individuals in these data are about the same age at release and incur roughly the same number of disciplinary reports during incarceration as the superset to the data (i.e., the Smith 2009 data). However, the individuals in the smaller sample seem to be worse off than those in the superset to the data as measured by criminal history, marital status, preincarceration employment, and preincarceration earnings. In particular, the individuals in the data utilized in this study have on average greater prior arrests, more prior convictions, more previous incarcerations, have a larger proportion that have no formal employment prior to incarceration, have a greater proportion of individuals that earned wages less than $20,234 prior to confinement, and have a larger percentage of individuals that are single.

  16. The other than work (OTW) and traditional industries (TI) groups comprise the control group and (as previously mentioned) could also perform the same tasks as PIECP participants depending on how the state classifies the work performed by TI and OTW workers. Moreover, OTW participants could earn wages comparable to TI participants. TI workers could be classified as those who perform work similar to PIECP workers (however, unlike PIECP, they may earn a nominal wage or nothing at all) and those who perform institutional maintenance. Finally, PIECP tasks can vary from habitual and labor intensive to very skilled.

  17. Even though there is no official cutoff to determine when normalized differences are too large, Imbens (2013) suggests that variables with a normalized difference greater than .5 should be considered too large to be adequately controlled for using regression analysis.

  18. Assuming the unconfoundedness assumption holds.

  19. Tied data occurs when multiple failures happen at the same point in time (Cameron and Trivedi 2005).

  20. This assumes φ(x,β) > 0.

  21. Incarceration wages and wages after release are indirectly controlled for through PIECP. These variables are not included in the analysis to avoid overcontrolling for the effects of PIECP. In other words, if PIECP is beneficial because it increases postincarceration wages, then including this variable in the analysis will eliminate the effect of PIECP.

  22. However, because the data are measured in quarters and don’t indicate how many times an individual changes jobs in a quarter, this is an imperfect measure of job stability because it only shows whether the individual maintained employment, not the number of changes in employment during the observation period.

  23. A complete list of covariates can be found in the footnotes to Tables 2 and 3.

  24. Please see Cox (2015) for a detailed discussion of the imputation procedure.

  25. To recapture these observations, the Cox model is reestimated by assigning observations that have a time from release to formal employment of zero (i.e., obtaining a job at discharge from prison) with the smallest recognizable number that is close to zero but not equal to zero. This can be done for the Cox estimator because it is the ranking of the numbers that is most important when estimating the coefficients.

  26. It should be noted that type of release (supervised release, work release, etc.) cannot be controlled for in the model. Thus, an alternative explanation is that PIECP workers are more likely to participate in work release, suggesting that work release is a mediator variable through which part of the effect of PIECP occurs. Controlling for work release, therefore, might attenuate the effect of PIECP on the duration of formal unemployment.

  27. Thanks to an anonymous referee for pointing this out.

  28. Anyone with a previous occupation is hypothesized to have a shorter duration of unemployment, a greater duration of formal employment, and greater earnings than those who were unemployed or out of the labor force prior to prison.

References

  • Angrist JD, Pischke JS (2009) Mostly harmless econometrics: an empiricist’s companion. Princeton University Press, Princeton

    Google Scholar 

  • Auerbach BJ (2001) Emerging practices: wage policies and practices for the Prison Industries Enhancement Certification Program (PIECP). Bureau of Justice Assistance, Washington, DC

    Google Scholar 

  • Bayer P, Hjalmarsson R, Pozen D (2009) Building criminal capital behind bars: peer effects in juvenile corrections. Q J Econ 124(1):105–147

    Article  Google Scholar 

  • Bureau of Justice Assistance (1999) Prison industry enhancement certification program guideline (RIN 1121–AA36). Fed Regist 64(66):17000–17014

    Google Scholar 

  • Bureau of Justice Assistance (2004) Prison industry enhancement certification program (NCJ 203483). U.S. Department of Justice. http://www.ncjrs.gov/pdffiles1/bja/203483.pdf.

  • Bushway S, Reuter P (2002) Labor markets and crime risk factors. In: Farrington DP, McKenzie DL, Sherman L, Welsh BC (eds) Evidenced-based crime prevention. Routledge, London, pp 198–240

    Google Scholar 

  • Bushway SD, Stoll MA, Weiman D (eds) (2007) Barriers to reentry? the labor market for released prisoners in post-industrial America. Russell Sage, New York

    Google Scholar 

  • Cain GG (1976) The challenge of segmented labor market theories to orthodox theory: a survey. J Econ Lit 14(4):1215–1257

    Google Scholar 

  • Cameron AC, Trivedi PK (2005) Microeconometrics: methods and applications. Cambridge University Press, New York

    Book  Google Scholar 

  • Card D, Chetty R, Feldstein M, Saez E (2010) Expanding access to administrative data for research in the United States. Soc Sci Res Netw. doi:10.2139/ssrn.1888586

    Google Scholar 

  • Carson EA (2015) Prisoners in 2014 (NCJ 248955). U.S. Department of Justice. http://www.bjs.gov/content/pub/pdf/p14.pdf

  • Cox R (2009) An economic analysis of prison labor (doctoral dissertation). Economics Dissertations. http://works.bepress.com/robynn_cox/1

  • Cox R (2010) Crime, incarceration, and employment in light of the great recession. Rev Black Polit Econ 37(3–4):283–294

    Article  Google Scholar 

  • Cox R (2012) The impact of mass incarceration on the lives of African American women. Rev Black Polit Econ 39(2):203–215

    Article  Google Scholar 

  • Cox R (2015) The effect of private sector work opportunities in prison on labor market outcomes of the formerly incarcerated (Working Paper No. 2015–014). USC Center for Economic and Social Research and Schaeffer Center for Health Policy and Economics. http://dx.doi.org/10.2139/ssrn.2628780

  • Gallagher DJ, Edwards ME (1997) Prison industries and the private sector. Atl Econ J 25(1):91–98

    Article  Google Scholar 

  • Gould ED, Weinberg BA, Mustard DB (2002) Crime rates and local labor market opportunities in the United States: 1979–1997. Rev Econ Stat 84(1):45–61

    Article  Google Scholar 

  • Grubb F (2001) The market evaluation of criminality: evidence from the auction of British convict labor in America, 1767–1775. Am Econ Rev 91(1):295–304

    Article  Google Scholar 

  • Heckman JJ, Hotz VJ (1989) Choosing among alternative nonexperimental methods for estimating the impact of social programs: the case of manpower training. J Am Stat Assoc 84(408):862–874

    Article  Google Scholar 

  • Heckman JJ, Stixrud J, Urzua S (2006) The effects of cognitive and noncognitive abilities on labor market outcomes and social behavior. J Labor Econ 24(3):411–482

    Article  Google Scholar 

  • Holzer HJ (2007) Collateral costs: the effects of incarceration on the employment and earnings of young workers. Institute for the Study of Labor, Bonn

    Google Scholar 

  • Holzer HJ, Raphael S, Stoll MA (2004) How willing are employers to hire ex-offenders? Focus 23(2):40–43

    Google Scholar 

  • Hughes TA, Wilson DJ (2003) Reentry trends in the United States. U.S. Department of Justice. http://www.bjs.gov/content/pub/pdf/reentry.pdf

  • Imben, G, Rubin D (2012) Causal inference in statistics and social sciences (unpublished manuscript)

  • Imbens G (2013) Lectures on evaluation methods. Lecture resented at the 2013 main causal inference workshop. Northwestern University, Chicago

    Google Scholar 

  • Jung H (2011) Increase in the length of incarceration and the subsequent labor market outcomes: evidence from men released from Illinois state prisons. J Policy Anal Manage 30(3):499–533

    Article  Google Scholar 

  • Lalonde RJ, Cho RM (2008) The impact of incarceration in state prison on the employment prospects of women. J Quant Criminol 24(3):243–265

    Article  Google Scholar 

  • Langan PA, Levin DJ (2002) Recidivism of prisoners released in 1994 (NCJ 193427). U.S. Department of Justice. http://bjs.ojp.usdoj.gov/content/pub/pdf/rpr94.pdf

  • Machin S, Meghir C (2004) Crime and economic incentives. J Hum Resour 39(4):958–979

    Article  Google Scholar 

  • Maltz MD (2001) Recidivism. Academic Press, Orlando. http://www.uic.edu/depts/lib/forr/pdf/crimjust/recidivism.pdf

  • Mocan HN, Billups SC, Overland J (2005) A dynamic model of differential human capital and criminal activity. Economica 72(288):655–681

    Article  Google Scholar 

  • Myers SL Jr (1983) Estimating the economic model of crime: employment versus punishment effects. Q J Econ 98(1):157–166

    Article  Google Scholar 

  • Pencavel J (1986) Labor supply of men: a survey. In: Layard R (ed) Handbook of labor economics, vol 1. Elsevier Science, Amsterdam, pp 3–102

    Google Scholar 

  • Pettit B, Lyons CJ (2007) Status and the stigma of incarceration: the labor-market effects of incarceration, by race, class, and criminal involvement. In: Bushway SD, Stoll MA, Weiman D (eds) Barriers to reentry? The labor market for released prisoners in post-industrial America. Russell Sage, New York, pp 203–226

    Google Scholar 

  • Piehl A (2003) Crime, work, and reentry. Paper presented at the Urban Institute Reentry Roundtable. New York University Law School. http://www.urban.org/UploadedPDF/410856_Piehl.pdf

  • Piehl A (2009) Preparing prisoners for employment: the power of small rewards (Civic Report No. 57). Manhattan Institute for Policy Research, New York

    Google Scholar 

  • Raphael S, Winter‐Ebmer R (2001) Identifying the effect of unemployment on crime. J Law Econ 44(1):259–283

    Article  Google Scholar 

  • Roman CG, Travis J (2006) Where will I sleep tomorrow? Housing, homelessness, and the returning prisoner. Hous Policy Debate 17(2):389–418

    Article  Google Scholar 

  • Saylor WG, Gaes GG (1997) Training inmates through industrial work participation and vocational and apprenticeship instruction. Correct Manag Q 1(2):32–43

    Google Scholar 

  • Schmidt P, Witte AD (1984) An economic analysis of crime and justice. Academic, Orlando

    Google Scholar 

  • Smith CJ (2009) National Evaluation of Prison Industry Enhancement Certification Program (PIECP), 1996–2003 [United States]. ICPSR20740-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor]

  • Smith CJ, Bechtel J, Patrick A, Smith RR, Wilson-Gentry L (2006) Correctional industries preparing inmates for re-entry: recidivism & post-release employment. U.S. Department of Justice. http://www.ncjrs.gov/pdffiles1/nij/grants/214608.pdf

  • Tyler JH, Kling JR (2007) Prison-based education and re-entry into the mainstream labor market. In: Bushway SD, Stoll MA, Weiman D (eds) Barriers to reentry? The labor market for released prisoners in post-industrial America. Russell Sage, New York, pp 227–256

    Google Scholar 

  • Uggen C (2000) Work as a turning point in the life course of criminals: a duration model of age, employment, and recidivism. Am Sociol Rev 65(4):529–246

    Article  Google Scholar 

  • Waldfogel J (1994) The effect of criminal conviction on income and the trust “reposed in the workmen.”. J Hum Resour 29(1):62–81

    Article  Google Scholar 

  • West HC, Sabol WJ (2008) Prisoners in 2007 (NCJ 224280). U.S. Department of Justice. http://www.bjs.gov/content/pub/pdf/p07.pdf

  • Western B, Kling JR, Weiman DF (2001) The labor market consequences of incarceration. Crime Delinq 47(3):410–427

    Article  Google Scholar 

  • Wilson DB, Gallagher CA, MacKenzie DL (2000) A meta-analysis of corrections-based education, vocation, and work programs for adult offenders. J Res Crime Delinq 37(4):347–368

    Article  Google Scholar 

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Correspondence to Robynn Cox.

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Conflict of Interest

I volunteered to assist Dr. Cindy Smith with data management of the supplementary data to the National Evaluation of the Prison Industry Enhancement Certification Program (Smith 2009), which was used in this study. Dr. Smith also served on my dissertation committee. Additionally, I serve as a program evaluator for Correction Enterprises, the North Carolina Department of Public Safety’s prison industrial work program. I am unaware of additional (potential) conflicts of interest.

Appendices

Appendix A: Definitions of PIECP, TI, and OTW (Smith et al. 2006, pp. 28–31)

Other than work (OTW)

Individuals involved in other prison activities (e.g., education or drug treatment programs) but not industry work. Those classified as OTW are not necessarily inactive while incarcerated. In addition, individuals classified as OTW and TI could perform the same task (i.e., laundry). However, one state may classify the task as OTW and the other as TI. OTW can be classified into two groups: (1) prisoner who decide not to work and (2) those located in compulsory work states (which require the prisoner to provide labor or go to school) that select jobs that demand minimal exertion and time. Some receive a nominal wage comparable to TI (e.g., $0.25 per hour).

Traditional Industries (TI)

There are two kinds of TI workers. One group performs work comparable to PIECP; however, the prisoner does not earn a market wage and the manufactured goods cannot be purchased in the private sector. For instance, the inmate may not earn anything or could make a nominal amount, such as a minimum of $0.25 per hour up to about $1.25 per hour. The second group of workers does institutional maintenance (e.g., semiskilled maintenance, administrative support, etc.). Each state determines what is considered a traditional industry in that state.

Prison Industry Enhancement Certification Program

Tasks range from habitual manual labor (e.g., assembly line) to highly skilled labor (e.g., sheet metal welding). Prisoners who work in facilities featuring the employer and manpower models have normal dealings with and are managed by a free-world employee. This could transform the corrections atmosphere to an employment setting during the workday. This program is explained in detail in the body of the article; thus, the reader is referred to the section on PIECP for a more detailed discussion of the program.

Appendix B

Fig. 1
figure 1

Kaplan-Meier recidivism survival curves

Fig. 2
figure 2

Kaplan-Meier survival curves formal employment versus incarceration

Table 4 Probability of recidivism estimates: PIECP sample compared to national estimates

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Cox, R. The Effect of Private Sector Work Opportunities in Prison on Labor Market Outcomes of the Formerly Incarcerated. J Labor Res 37, 412–440 (2016). https://doi.org/10.1007/s12122-016-9229-0

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Keywords

  • Prison labor
  • Incarceration
  • Prisoner reentry
  • Unemployment duration
  • Employment duration
  • Formerly incarcerated
  • Earnings
  • Prison industry enhancement certification program
  • Job training programs

JEL Classification

  • J30
  • J31
  • J64
  • J68
  • K42
  • K49