Washington State Institute for Public Policy
Flexible funding (Title IV-E waivers)
Child Welfare
Benefit-cost estimates updated December 2016.  Literature review updated April 2012.
The flexible funding allowed by states obtaining Title IV-E waivers is designed to allow states to reallocate federal dollars normally used for foster care to other types of child welfare services, such as prevention or treatment.

Federal funds for foster care are "categorical." That is, as foster care caseloads rise or fall, the federal funds change in proportion. Thus, if states reduce the number of children in foster care, the federal support is reduced. With Title IV-E waivers, if states reduce foster care caseloads they may reallocate saved foster care dollars to other types of child welfare services, such as prevention or treatment services.
BENEFIT-COST
META-ANALYSIS
CITATIONS
The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2015). 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 $385 Benefits minus costs $1,192
Participants $685 Benefit to cost ratio n/a
Others $57 Chance the program will produce
Indirect $66 benefits greater than the costs 91 %
Total benefits $1,192
Net program cost $0
Benefits minus cost $1,192
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
Crime $18 $0 $40 $9 $67
Child abuse and neglect $6 $138 $0 $3 $147
Out-of-home placement $80 $0 $0 $40 $120
K-12 grade repetition $3 $0 $0 $1 $4
K-12 special education $17 $0 $0 $8 $25
Property loss associated with alcohol abuse or dependence $0 $0 $0 $0 $0
Health care associated with PTSD $18 $6 $23 $9 $56
Labor market earnings associated with child abuse & neglect $254 $558 $0 $1 $812
Costs of higher education ($12) ($18) ($5) ($6) ($41)
Adjustment for deadweight cost of program $0 $0 $0 $0 $0
Totals $385 $685 $57 $66 $1,192
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $0 2011 Present value of net program costs (in 2015 dollars) $0
Comparison costs $0 2011 Cost range (+ or -) 10 %
This waiver strategy allows states to reallocate funds from foster care to other kinds of services. One state evaluation reported that children on the waiver cost more than comparison children, one evaluation reported waiver children cost less than comparison children. In nearly all evaluations, the waiver was reported as "cost-neutral", which was the aim of the waiver: to be able to re-allocate dollars normally spent on foster care to other services. Therefore, we have taken a cautious approach and estimated that the cost of this program is zero relative to business-as-usual.
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.

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
Child abuse and neglect 3 29252 -0.040 0.032 8 -0.040 0.032 17 -0.040 0.221
Out-of-home placement 5 99344 -0.090 0.045 8 -0.090 0.045 17 -0.090 0.045
Citations Used in the Meta-Analysis

Lehman, C.M., Liang, S., & O Dell, K. (2005). Impact of flexible funds on placement and permanency outcomes for children in child welfare. Research on Social Work Practice 1(5), 381-388.

Loman, L.A., Filonow, C.S., & Siegel, G.L. (2011). Indiana IV-E child welfare waiver demonstration extensions: final evaluation report. St. Lous, MO: Institute of Applied Research.

Human Services Research Institute (2010). Comprehensive final evaluation report: Ohio's Title IV-E eaiver demonstration project "ProtectOhio." Tualatin, OR: Author.

Institute of Applied Research. (2003). Indiana Title IV-E child welfare waiver demonstration project: final evaluation report. St. Louis: Institute of Applied Research.

Usher, C.L., Wildfire, J.B., Duncan, D.F., Meier, A., Brown, E.L., Salmon, M.A. (2002). Evaluation of North Carolina's Title IV-E waiver demonstration. Chapel Hill: University of North Carolina, School of Social Work, Jordan Institute for Families.

For more information on the methods
used please see our Technical Documentation.
360.664.9800
institute@wsipp.wa.gov