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Employment counseling and job training with paid work experience in the community

Adult Criminal Justice
Benefit-cost methods last updated December 2023.  Literature review updated August 2016.
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Employment counseling programs with job training teach skills necessary for seeking employment. These include both hard skills (e.g., job preparedness and skills training) and soft skills, (e.g., effective job searches, applications, and resumes). Some programs may also specifically address barriers to employment for convicted persons. The studies in this category differ from those in the “Employment counseling and job training in the community," as each program in this category also includes subsidized or transitional jobs to help participants transition to regular employment. For this broad grouping of studies, programs were delivered in the community after release from incarceration for a period of three to nine months.
 
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 (2022). 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 $4,164 Benefits minus costs $4,776
Participants $4,475 Benefit to cost ratio $1.76
Others $4,494 Chance the program will produce
Indirect ($2,031) benefits greater than the costs 59%
Total benefits $11,102
Net program cost ($6,326)
Benefits minus cost $4,776

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

*The effect size for this outcome indicates percentage change, not a standardized mean difference effect size.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic in order to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the types of program impacts that were measured in the research literature (for example, 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.

Adjusted effect sizes are used to calculate the benefits from our benefit cost model. WSIPP may adjust effect sizes based on methodological characteristics of the study. For example, we may adjust effect sizes when a study has a weak research design or when the program developer is involved in the research. The magnitude of these adjustments varies depending on the topic area.

WSIPP may also adjust the second ES measurement. Research shows the magnitude of some effect sizes decrease 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. We also report the unadjusted effect size to show the effect sizes before any adjustments have been made. 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 Adjusted 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
31 3 1673 0.041 0.068 33 n/a n/a n/a 0.061 0.371
31 2 1457 0.121 0.090 32 0.000 0.018 33 0.121 0.180
31 10 5777 -0.076 0.036 33 -0.076 0.036 43 -0.087 0.035
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 $2,264 $0 $4,494 $1,132 $7,890
Earnings Labor market earnings $1,900 $4,475 $0 $0 $6,375
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($3,163) ($3,163)
Totals $4,164 $4,475 $4,494 ($2,031) $11,102
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $4,717 2007 Present value of net program costs (in 2022 dollars) ($6,326)
Comparison costs $0 2007 Cost range (+ or -) 10%
Per-participant cost estimate, based on 6-month program duration, are from Cook, P. J., Kang, S., Braga, A. A., Ludwig, J., & O’Brien, M. E. (2015). An Experimental Evaluation of a Comprehensive Employment-Oriented Prisoner Re-entry Program. Journal of Quantitative Criminology, 31, 3, 355-382.
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, R.A., Lenihan, K.J., & Rossi, PH. (1980). Crime and poverty: Some experimental evidence from ex-offenders. American Sociological Review, 45(5), 766-786.

Jacobs, E. (2012). Returning to work after prison: Final results from the Transitional Jobs Reentry Demonstration. New York, NY: Manpower Demonstration Research Corporation.

Mallar, C.D., & Thornton, C.V.D. (1978). Transitional aid for released prisoners: Evidence from the life experiment. The Journal of Human Resources, 13(2), 208-236.

Redcross, C., Bloom, D., Jacobs, E., Manno, M., Muller-Ravett, S., Seefeldt, K., . . . Zweig, J. (2010). Work after prison: One-year findings from the Transitional Jobs Reentry Demonstration. New York: Manpower Demonstration Research Corporation.

Redcross, C., Millenky, M., Rudd, T., & Levshin, V. (2012). More than a job: Final results from the Evaluation of the Center for Employment Opportunities (CEO) Transitional Jobs Program. OPRE Report 2011-18. Washington, DC: Office of Planning, Research and Evaluation, Administration for Children and Families, U. S. Department of Health and Human Services.

Uggen, C. (2000). Work as a turning point in the life course of criminals: A duration model of age, employment, and recidivism. American Sociological Review, 65(4), 529–546.