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Correctional industries (program costs include expenditures only)

Adult Criminal Justice
Benefit-cost methods last updated December 2024.  Literature review updated May 2024.
Correctional industries (CI) programming combines training, workforce development, and jobs with the aim of developing marketable job skills, promoting positive work ethics, and offering enhanced opportunities for post-release employment and opportunity. Often, individuals work for a private sector employer, a non-profit, or in institutional industries within the prison. CI participants obtain work through an application process, which commonly includes work in metal fabrication, laundry, furniture assembly, and textile manufacturing.

In Washington State, CI participants are expected to complete a 20-hour employer-based cognitive training course, Makin’ It Work, to understand both the behaviors and expectations of employers. Incarcerated individuals may earn Certificates of Proficiency once they complete Makin’ It Work, achieve 1,500+ hours of on-the-job training, and demonstrate satisfactory job performance per criteria established by the U.S. Bureau of Labor Statistics Standard Occupational Classifications. Additionally, CI uses Community Employment Services which connects CI participants with post-release employment with community partners (e.g., FareStart—a 16-week culinary training program with housing and career assistance).

The length of attendance in CI programs varies and typically depends on the length of an individual’s sentence in prison. On average, individuals in the studies in our analysis participated in CI programs for 12 months. Per the studies in our analysis, CI participation is available regardless of sex, age, and risk level.
 
ALL
BENEFIT-COST
META-ANALYSIS
CITATIONS
For an overview of WSIPP's Benefit-Cost Model, please see this guide. The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2023).  The chance the benefits exceed the costs are derived from a Monte Carlo risk analysis. The details on this, as well as the economic discount rates and other relevant parameters are described in our Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $1,461 Benefits minus costs $2,158
Participants $0 Benefit to cost ratio $2.15
Others $2,784 Chance the program will produce
Indirect ($208) benefits greater than the costs 77%
Total benefits $4,036
Net program cost ($1,878)
Benefits minus cost $2,158

^WSIPP’s benefit-cost model does not monetize this outcome.

^^WSIPP does not include this outcome when conducting benefit-cost analysis for this program.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the program impacts measured in the research literature (for example, impacts on crime or educational attainment). Treatment N represents the total number of individuals or units in the treatment group across the included studies.

An effect size (ES) is a standard metric that summarizes the degree to which a program or policy affects a measured outcome. If the effect size is positive, the outcome increases. If the effect size is negative, the outcome decreases. See Estimating Program Effects Using Effect Sizes for additional information on how we estimate effect sizes.

The effect size may be adjusted from the unadjusted effect size estimated in the meta-analysis. Historically, WSIPP adjusted effect sizes to some programs based on the methodological characteristics of the study. For programs reviewed in 2024 or later, we do not make additional adjustments, and we use the unadjusted effect size whenever we run a benefit-cost analysis.

Research shows the magnitude of effects may change over time. For those effect sizes, we estimate outcome-based adjustments, which we apply between the first time ES is estimated and the second time ES is estimated. More details about these adjustments can be found in our Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured Treatment age No. of effect sizes Treatment N Effect sizes (ES) and standard errors (SE) used in the benefit-cost analysis Unadjusted effect size (random effects model)
First time ES is estimated Second time ES is estimated
ES SE Age ES SE Age ES p-value
Crime
Involvement in the criminal justice system (e.g., arrests, charges, convictions, incarceration) measured through administrative records (e.g. court records, arrests) or self-report.
 35 8 7362 -0.052 0.030 36 -0.052 0.030 44 -0.052 0.080
Employment^^
Any employment, including part-time work.
35 5 4988 0.165 0.051 40 n/a n/a 42 0.165 0.001
Technical violations^^
Violations of the conditions of an individual’s terms of probation, parole, or supervision.
 35 2 3775 0.062 0.048 40 n/a n/a n/a 0.062 0.196
Prison misconduct^
Criminal or deviant behavior during incarceration. Misconduct is often associated with violating policy within a prison or secure facility.
35 3 4199 0.132 0.088 40 n/a n/a n/a 0.132 0.132
1In addition to the outcomes measured in the meta-analysis table, WSIPP measures benefits and costs estimated from other outcomes associated with those reported in the evaluation literature. For example, empirical research demonstrates that high school graduation leads to reduced crime. These associated measures provide a more complete picture of the detailed costs and benefits of the program.

2“Others” includes benefits to people other than taxpayers and participants. Depending on the program, it could include reductions in crime victimization, the economic benefits from a more educated workforce, and the benefits from employer-paid health insurance.

3“Indirect benefits” includes estimates of the net changes in the value of a statistical life and net changes in the deadweight costs of taxation.
Detailed Monetary Benefit Estimates Per Participant
Affected outcome: Resulting benefits:1 Benefits accrue to:
Taxpayers Participants Others2 Indirect3 Total
Crime Criminal justice system $1,461 $0 $2,784 $731 $4,975
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($939) ($939)
Totals $1,461 $0 $2,784 ($208) $4,036
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $1,878 2023 Present value of net program costs (in 2023 dollars) ($1,878)
Comparison costs $0 2023 Cost range (+ or -) 10%
The per-participant cost estimate was provided by the Washington State Department of Corrections (DOC). The cost estimate includes incarcerated worker wages plus the costs of training, staff supervision of incarcerated individuals, raw materials, and other operating expenses.
The figures shown are estimates of the costs to implement programs in Washington. The comparison group costs reflect either no treatment or treatment as usual, depending on how effect sizes were calculated in the meta-analysis. The cost range reported above reflects potential variation or uncertainty in the cost estimate; more detail can be found in our Technical Documentation.
Benefits Minus Costs
Benefits by Perspective
Taxpayer Benefits by Source of Value
Benefits Minus Costs Over Time (Cumulative Discounted Dollars)
The graph above illustrates the estimated cumulative net benefits per-participant for the first fifty years beyond the initial investment in the program. We present these cash flows in discounted dollars. If the dollars are negative (bars below $0 line), the cumulative benefits do not outweigh the cost of the program up to that point in time. The program breaks even when the dollars reach $0. At this point, the total benefits to participants, taxpayers, and others, are equal to the cost of the program. If the dollars are above $0, the benefits of the program exceed the initial investment.

Citations Used in the Meta-Analysis

Berk, J.A. (2009). Essays on work and education: Behind bars and in the free world. Dissertation Abstracts International, 69(11), A.

Bohmert, M.N., & Duwe, G. (2012). Minnesota's Affordable Homes Program: Evaluating the effects of a prison work program on recidivism, employment and cost avoidance. Criminal Justice Policy Review, 23(3), 327-351.

Drake, E.K. (2003). Class I impacts: Work during incarceration and its effects on post-prison employment patterns and recidivism. Olympia, WA: Washington State Department of Corrections, Planning and Research Section.

Duwe, G., & McNeeley, S. (2020). The effects of prison labor on institutional misconduct, postprison employment, and recidivism. Corrections, 5(2), 89-108.

Hopper, J.D. (2008). The effects of private prison labor program participation on inmate recidivism. Dissertation Abstracts International, 69(7). Middle Tennessee State University.

Lutze, F.E., Drapela, L.A., & Schaefer, R.L. (2015). Washington State Correctional Industries: An outcome evaluation of its effect on institutional behavior, employment, and recidivism. Pullman: Washington State University.

Maguire, K.E., Flanagan, T.J., & Thornberry, T.P. (1988). Prison labor and recidivism. Journal of Quantitative Criminology, 4(1), 3-18.