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Washington State Institute for Public Policy
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Job search and placement

Workforce Development
Benefit-cost methods last updated December 2019.  Literature review updated November 2015.
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Unemployed individuals conduct a supervised job search, attend job search workshops or participate in job clubs, similar to peer support groups for the unemployed. This intervention is very brief, lasting anywhere from a few hours in one day to two months. State Unemployment Insurance (UI) programs, employment departments, and welfare agencies usually provide these program services. UI claimants and TANF/AFDC recipients are the most common participants.
 
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 (2018). 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 $1,419 Benefits minus costs $1,859
Participants $796 Benefit to cost ratio $4.39
Others $0 Chance the program will produce
Indirect $193 benefits greater than the costs 68 %
Total benefits $2,408
Net program cost ($549)
Benefits minus cost $1,859

*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
36 8 13539 0.038 0.024 38 0.000 0.017 40 0.038 0.103
36 9 14070 0.079 0.038 38 0.000 0.017 40 0.079 0.040
36 5 6841 -0.070 0.017 38 0.000 0.017 40 -0.070 0.001
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
Public assistance Public assistance $935 ($341) $0 $467 $1,061
Earnings Labor market earnings $484 $1,137 $0 $0 $1,622
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($275) ($275)
Totals $1,419 $796 $0 $193 $2,408
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $515 2014 Present value of net program costs (in 2018 dollars) ($549)
Comparison costs $0 2014 Cost range (+ or -) 56 %
Job search and placement services are typically provided for a brief period; between one day and two months. We estimated the average annual cost of treatment per participant using data from studies in our meta-analysis that report cost estimates (Corson et al., 1985; Corson & Haimson, 1996; Friedlander et al., 1987; Goldman et al., 1986; Goldman et al., 1981; Vinokur et al., 1991; Wolfhagen & Goldman, 1983). Costs vary by study but may include administrative costs, operating costs, transportation payments, lunches, child care and work-related expenses, staff salaries, and sometimes small stipends for clients.
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

Corson, W., & Haimson, J. (1996). The New Jersey Unemployment Insurance Reemployment Demonstration Project: Six-year followup and summary report. Washington, DC: U.S. Department of Labor, Employment and Training Administration, Unemployment Insurance Service.

Friedlander, D., Freedman, S., Hamilton, G., & Quint, J. (1987). Final report on job search and work experience in Cook County. New York, NY: Manpower Demonstration Research Corporation.

Goldman, B., Friedlander, D., & Long, D. (1986). The San Diego Job Search and Work Experience Demonstration: Final report. New York, NY: Manpower Demonstration Research Corporation.

Goldman, B.S. (1981). Impacts of the Immediate Job Search Assistance Experiment: Louisville WIN Research Laboratory Project. New York, NY: Manpower Demonstration Research Corporation.

Klepinger, D.H., Johnson, T.R., Joesch, J.M., & Benus, J.M. (1997). Evaluation of the Maryland Unemployment Insurance Work Search Demonstration: Final report. Washington, DC: U.S. Department of Labor, Employment and Training Administration, Unemployment Insurance Service.

Vinokur, A.D., van Ryn, M., Gramlich, E.M., & Price, R.H. (1991). Long-term follow-up and benefit-cost analysis of the Jobs Program: A preventive intervention for the unemployed. The Journal of Applied Psychology, 76(2), 213-219.

Vinokur, A.D., Price, R.H., & Schul, Y. (1995). Impact of the JOBS intervention on unemployed workers varying in risk for depression. American Journal of Community Psychology, 23(1), 39-74.

Wolfhagen, C.F., & Goldman, B.S. (1983). Job search strategies: Lessons from the Louisville WIN laboratory. New York, NY: Manpower Demonstration Research Corporation.