Washington State Institute for Public Policy
Training, no work experience
Workforce Development
Benefit-cost estimates updated May 2017.  Literature review updated November 2015.
Participants receive job search and placement assistance, adult basic education, ESL and GED preparation, vocational training, or support services such as child care and housing support. Training targets occupations as diverse as electromechanics, nursing, and construction, among many others. Some of these programs take place at community colleges, targeting adults who failed to graduate high school, while others occur at proprietary trade schools and colleges. Community-based organizations and welfare agencies may also provide these program services. They typically target TANF/AFDC recipients, dislocated workers, or low-income* individuals, lasting anywhere from one month to two years.
*The low-income population may be defined in a variety of ways, including all workers in the 25th percentile of hourly wages, individuals at or below 130% of the federal poverty line, individuals at or below 200% of the federal poverty line, or an income that meets eligibility requirements for welfare or food stamps.
The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2016). 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 $2,404 Benefits minus costs ($4,470)
Participants $5,813 Benefit to cost ratio $0.47
Others $0 Chance the program will produce
Indirect ($4,294) benefits greater than the costs 39 %
Total benefits $3,923
Net program cost ($8,394)
Benefits minus cost ($4,470)
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
Benefits from changes to:1 Benefits to:
Taxpayers Participants Others2 Indirect3 Total
Labor market earnings associated with employment $2,585 $5,692 $0 $0 $8,277
Public assistance ($90) $38 $0 ($45) ($96)
Food assistance ($91) $82 $0 ($46) ($54)
Adjustment for deadweight cost of program $0 $0 $0 ($4,203) ($4,203)
Totals $2,404 $5,813 $0 ($4,294) $3,923
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $8,284 2014 Present value of net program costs (in 2016 dollars) ($8,394)
Comparison costs $0 2014 Cost range (+ or -) 31 %
These programs typically last anywhere from one month to two years. We estimated the average annual cost of treatment per participant using data from studies in our meta-analysis that report cost estimates (Bloom et al., 2002; Burghardt et al., 1992; Cave et al., 1993; Hollenbeck & Huang, 2014; Hollenbeck & Huang, 2006; Hollenbeck & Huang, 2003). Costs vary by study but may include foregone earnings, foregone tax receipts, tuition payments if any, support services such as transportation and child care, medical/dental services, and safety net services.
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.
Estimated Cumulative Net Benefits Over Time (Non-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 non-discounted dollars to simplify the “break-even” point from a budgeting perspective. 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.

*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.

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 Primary or secondary participant 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
Earnings* 41 289201 0.062 0.013 37 0.000 0.032 38 0.062 0.001
Employment 41 289201 0.085 0.024 37 0.000 0.032 38 0.085 0.001
Food assistance 25 171188 0.011 0.008 37 0.000 0.032 38 0.011 0.163
Public assistance 25 169101 0.006 0.008 37 0.000 0.032 38 0.006 0.446
Citations Used in the Meta-Analysis

Black, D.A., Smith, J.A., Berger, M.C., & Noel, B.J. (2003). Is the threat of reemployment services more effective than the services themselves? Evidence from random assignment in the UI System. American Economic Review, 93(4), 1313-1327.

Bloom, D., Scrivener, S., Michalopoulos, C., Morris, P., Hendra, R., Adams-Ciardullo, D., . . . Vargas, W. (2002). Jobs First: Final report on Connecticut's welfare reform initiative. New York, NY: Manpower Demonstration Research Corporation.

Bloom, H.S., Riccio, J.A., & Verma, N. (2005). Promoting work in public housing: The effectiveness of Jobs-Plus: Final report. New York, NY: Manpower Demonstration Research Corporation.

Burghardt, J.A., Rangarajan, A., Gordon, A., & Kisker, E. (1992). Evaluation of the Minority Female Single Parent Demonstration: Volume I. New York, NY: Rockefeller Foundation.

Cave, G., Bos, H., Doolittle, F., & Toussaint, C. (1993). JOBSTART: Final report on a program for school dropouts. New York, NY: Manpower Demonstration Research Corporation.

Fein, D., & Beecroft, E. (2006). College as a job advancement strategy: Final report on the New Visions Self-Sufficiency and Lifelong Learning Project. Bethesda, MD: Abt Associates.

Hollenbeck, K., & Huang, W.-J.(2014). Net impact and benefit-cost estimates of the workforce development system in Washington State (Upjohn Institute Technical Report No. 13-029). Kalamazoo, MI: W.E. Upjohn Institute for Employment Research.

Hollenbeck, K., & Huang, W.-J. (2006). Net impact and benefit-cost estimates of the workforce development system in Washington State. Kalamazoo, MI: W.E. Upjohn Institute for Employment Research.

Hollenbeck, K., & Huang, W.-J. (2003). Net impact and benefit-cost estimates of the workforce development system in Washington State. Kalamazoo, MI: W.E. Upjohn Institute for Employment Research.

Jacobs, E., & Bloom, D. (2011). Alternative employment strategies for hard-to-employ TANF recipients: Final results from a test of transitional jobs and preemployment services in Philadelphia (OPRE Report 2011-19). Washington, DC: Office of Planning, Research and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services.

Maguire, S., Freely, J., Clymer, C., Conway, M., & Schwartz, D. (2010). Tuning in to local labor markets: Findings from the Sectoral Employment Impact Study. Philadelphia, PA: Public/Private Ventures.

Milkman, R.H. (1985). Employment services for ex-offenders field test: Detailed research results (Document No. NCJ 099807). McLean, VA: The Lazar Institute.

Miller, C., Bos, J. M., Porter, K.E., Tseng, F.M., & Abe, Y. (2005). The challenge of repeating success in a changing world: Final report on the Center for Employment Training replication sites. New York, NY: Manpower Demonstration Research Corporation.

Molina, F., Cheng, W.-L., & Hendra, R. (2008). Results from the Valuing Individual Success and Increasing Opportunities Now (VISION) program in Salem, Oregon. New York, NY: Manpower Demonstration Research Corporation.

Navarro, D., van Dok, M., & Hendra, R. (2007). Results from the Post-Assistance Self-Sufficiency (PASS) program in Riverside, California. New York, NY: Manpower Demonstration Research Corporation.

Smith, T., Christensen, K., & Cumpton, G. (2015). An evaluation of local investments in workforce development. Austin, TX: Ray Marshall Center for the Study of Human Resources.

For more information on the methods
used please see our Technical Documentation.