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Youth Villages LifeSet (YV LifeSet) for former foster youth

Child Welfare
Benefit-cost methods last updated December 2024.  Literature review updated July 2019.
Youth Villages LifeSet (YV LifeSet) is a transitional living program for youth aging out of state custody. This analysis is on YV LifeSet for youth aging out of the foster system. Each youth is assigned to a YV LifeSet Specialist. YV LifeSet Specialists have a caseload of eight to ten youth. The YVLS Specialist meets with individuals weekly to help youth establish goals in the areas of education, employment, housing, and life skills. YV LifeSet Specialists may also refer youth to program-provided practices for mental health or substance abuse treatment. The program duration can range from a few months to over a year. More information can be found on the Youth Villages website: https://www.youthvillages.org/yvlifeset/.

In the included study, youth participated in YV LifeSet for an average of 215 days. Program and comparison group youth had access to usual services upon aging out of the foster system.

We report a separate analysis on YV LifeSet for youth released from juvenile custody.
 
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 $381 Benefits minus costs ($16,921)
Participants $1,569 Benefit to cost ratio ($0.41)
Others ($762) Chance the program will produce
Indirect ($6,121) benefits greater than the costs 6%
Total benefits ($4,933)
Net program cost ($11,989)
Benefits minus cost ($16,921)

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

*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 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.
 19 1 372 0.034 0.151 20 0.034 0.151 28 0.034 0.821
Earnings*
Percent change in labor market earnings, typically weekly or monthly wages.
19 1 372 0.073 0.146 20 0.000 0.014 21 0.073 0.616
Problem alcohol use
Alcohol use reflecting problem behaviors (e.g., high frequency drinking, binge drinking, or drinking that has a high impact on daily life) for individuals who do not have an alcohol use disorder.
 19 1 319 -0.149 0.088 19 -0.020 0.132 21 -0.149 0.091
Homelessness^
A lack of stable housing, often measured through self-report of conditions like living on streets or in shelters in a given time period.
 19 1 319 -0.196 0.088 19 n/a n/a n/a -0.196 0.026
Enroll in any college^
Enroll in either a 2-year or 4-year higher education institution.
 19 1 372 -0.094 0.107 20 n/a n/a n/a -0.094 0.378
Illicit drug use^
Adult use of illicit drugs that does not rise to the level of “disordered.” When possible, we exclude cannabis/marijuana use from this outcome.
 19 1 330 -0.037 0.116 19 n/a n/a n/a -0.037 0.753
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 ($299) $0 ($783) ($150) ($1,232)
Problem alcohol use Property loss associated with problem alcohol use $0 $2 $3 $0 $5
Health care associated with problem alcohol use $16 $3 $18 $8 $46
Mortality associated with problem alcohol $0 $1 $0 $15 $16
Earnings Labor market earnings $664 $1,563 $0 $0 $2,227
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($5,994) ($5,994)
Totals $381 $1,569 ($762) ($6,121) ($4,933)
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $9,690 2015 Present value of net program costs (in 2023 dollars) ($11,989)
Comparison costs $0 2015 Cost range (+ or -) 20%
The per-participant cost is based on information provided by Youth Villages (June 2016). The cost per day enrolled in the program ranges from $40 to $50. In the included study, the average youth was enrolled for 215 days. We multiply the mid-range daily rate of $45 by the average number of days enrolled.
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

Skemer, M. & Valentine, E.J. (2016). Striving for Independence: Two-Year Impact Findings from the Youth Villages Transitional Living Evaluation. New York, NY: MDRC.

Valentine, E.J., Skemer, M., & Courtney, M.E. (2015). Becoming Adults: One-Year Impact Findings from the Youth Villages Transitional Living Evaluation. New York, NY: MDRC.