Washington State Institute for Public Policy
Intensive supervision (parole)
Juvenile Justice
Benefit-cost estimates updated May 2017.  Literature review updated September 2015.
In this broad grouping of programs, intensive supervision emphasizes a higher degree of surveillance than traditional supervision in the community. This meta-analysis includes only studies of offenders who were on parole (not probation). The average number of monthly contacts of any kind for studies included in our meta-analysis was 37. Conditions of supervision vary across the studies, but some characteristics include urinalysis testing, increased face-to-face or collateral contacts, or required participation in treatment.

We used multiple regression to test for the possibility of an “interaction,” (a simultaneous effect of two variables) between monthly contacts and treatment. The interaction indicates that more contacts, coupled with treatment, result in a bigger reduction in crime. We only found this effect for parole populations. For probation populations, we found a statistically significant increase in recidivism when there was a combination of more contacts and more treatment.
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 $1,660 Benefits minus costs $4,611
Participants $269 Benefit to cost ratio $3.14
Others $5,154 Chance the program will produce
Indirect ($316) benefits greater than the costs 68 %
Total benefits $6,768
Net program cost ($2,156)
Benefits minus cost $4,611
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 $1,506 $0 $5,058 $746 $7,311
Labor market earnings associated with high school graduation $136 $300 $138 $0 $575
Health care associated with educational attainment $32 ($9) ($35) $16 $4
Costs of higher education ($15) ($22) ($7) ($7) ($51)
Adjustment for deadweight cost of program $0 $0 $0 ($1,071) ($1,071)
Totals $1,660 $269 $5,154 ($316) $6,768
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $1,947 2009 Present value of net program costs (in 2016 dollars) ($2,156)
Comparison costs $0 2009 Cost range (+ or -) 10 %
We used WSIPP’s annual marginal cost estimate for juvenile supervision (as reported in Washington State Institute for Public Policy (July 2015). Benefit-cost technical documentation. Olympia, WA: Author) to compute a daily cost estimate. The daily cost estimate for parole was multiplied by the weighted average months on supervision, 5.95, as reported by the studies included in the meta-analysis.
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 9 1101 -0.049 0.060 18 -0.049 0.060 28 -0.059 0.328
Citations Used in the Meta-Analysis

Barnoski, R. (2002). Evaluating how Juvenile Rehabilitation Administration's Intensive Parole Program affects recidivism. Olympia: Washington State Institute for Public Policy.

Cillo, G.C. (2001). Evaluation of a theory-based transitional aftercare program for court-adjudicated adolescents (Unpublished doctoral dissertation). Fordham Unversity, New York, NY.

Greenwood, P.W., Deschenes, E.P., & Adams, J. (1993.) Chronic juvenile offenders: Final results from The Skillman Aftercare Experiment. RAND: Santa Monica.

Sontheimer, H., & Goodstein, L. (1993). Evaluation of juvenile intensive aftercare probation: aftercare versus system response effects. Justice Quarterly 10, 197-227.

Weibush, R.G. (1993). Juvenile intensive supervision: the impact on felony offenders diverted from institutional placement. Crime and Delinquency, 39(1), 68-89.

Weibush, R.G., Wagner, D., McNultly, B., Wang, Y., & Le, T. (2005). Implementation and outcome evaluation of the intensive aftercare program, final report. Office of Juvenile Justice and Delinquency Prevention. Washington DC: U.S. Department of Justice.

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