Washington State Institute for Public Policy

Functional Family Parole (with quality assurance)
Juvenile Justice
Benefit-cost estimates updated May 2017. Literature review updated January 2013.

Functional Family Parole (FFP) is a case management model for youth who are supervised in the community. FFP is based on Functional Family Therapy (FFT), a structured family-based intervention that uses a multi-step approach to enhance protective factors and reduce risk factors in the family.

In our analysis, we only include effect sizes from programs that were delivered competently and with fidelity to the program model.

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 (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	$3,078	Benefits minus costs	$7,297
	Participants	$431	Benefit to cost ratio	$2.58
	Others	$9,283	Chance the program will produce
	Indirect	($876)	benefits greater than the costs	71 %
	Total benefits	$11,916
	Net program cost	($4,618)
	Benefits minus cost	$7,297

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	$2,832	$0	$9,129	$1,405	$13,365
Labor market earnings associated with high school graduation	$219	$482	$222	$0	$923
Health care associated with educational attainment	$52	($14)	($57)	$26	$7
Costs of higher education	($25)	($37)	($11)	($12)	($85)
Adjustment for deadweight cost of program	$0	$0	$0	($2,294)	($2,294)

Totals	$3,078	$431	$9,283	($876)	$11,916

Detailed Annual Cost Estimates Per Participant
Annual cost		Year dollars	Summary
Program costs	$4,426	2012	Present value of net program costs (in 2016 dollars)	($4,618)
Comparison costs	$0	2012	Cost range (+ or -)	10 %

WSIPP estimates based on implementation costs of FFT and additional supervision costs.

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
Crime	Primary	4	465	-0.087	0.077	19	-0.087	0.077	29	-0.108	0.194

Citations Used in the Meta-Analysis

B. A. Lucenko, L. He, D. Mancuso, and B. Felver (2011). Effects of Functional Family Parole on Re-Arrest and Employment for Youth in Washington State. Research Data Analysis Division: Olympia, Washington.

Sexton, T., Rowland, M., & McEnery, A., (2009). Interim Outcome Evaluation of the Washington State Functional Family Parole Project. Center for Adolescent and Family Studies. Bloomington, Indiana.