Washington State Institute for Public Policy
Electronic monitoring (probation)
Adult Criminal Justice
Benefit-cost estimates updated December 2016.  Literature review updated December 2014.
A computer-based tracking device electronically monitors the location of an offender. Electronic monitoring devices are either radio frequency or Global Positioning System (GPS) units. Offenders are generally required to remain at home except for approved activities such as work, school, or treatment. Electronic monitoring is used for probationers, parolees, or pre-trial defendants and can be used in lieu of, or in addition to, confinement. The use of electronic monitoring varies from lower to higher risk offenders. Parole and probation populations have been placed into two separate categories in order to reflect the statistically significant difference in effectiveness.
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 $7,160 Benefits minus costs $26,863
Participants $0 Benefit to cost ratio n/a
Others $14,424 Chance the program will produce
Indirect $4,155 benefits greater than the costs 94 %
Total benefits $25,739
Net program cost $1,124
Benefits minus cost $26,863
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 $7,160 $0 $14,424 $3,589 $25,172
Adjustment for deadweight cost of program $0 $0 $1 $566 $567
Totals $7,160 $0 $14,424 $4,155 $25,739
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $377 2009 Present value of net program costs (in 2015 dollars) $1,124
Comparison costs $1,405 2009 Cost range (+ or -) 10 %
Electronic monitoring costs per day were provided by the Department of Corrections. The Washington State Institute for Public Policy calculated the total cost per participant assuming 30 days on electronic monitoring in lieu of 30 days in confinement (average daily cost for jail and prison).
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 10 7036 -0.317 0.221 30 -0.317 0.221 40 -0.351 0.130
Citations Used in the Meta-Analysis

Baird, C., Wagner, D., Decomo, B., & Aleman, T. (1994). Evaluation of the effectiveness of supervision and community rehabilitation programs in Oregon. San Francisco: National Council on Crime and Delinquency.

Bonta, J., Wallace-Capretta, S., & Rooney, J. (2000). A quasi-experimental evaluation of an intensive rehabilitation supervision program. Criminal Justice and Behavior, 27(3), 312-329.

Bonta, J., Wallace-Capretta, S., & Rooney, J. (2000). Can electronic monitoring make a difference? An evaluation of three Canadian programs. Crime and Delinquency, 46(1), 61-75.

Di Tella, R., & Schargrodsky, E. (2009). Criminal recidivism after prison and electronic monitoring (Working Paper No. 15602). Cambridge: National Bureau of Economic Research.

Jolin, A., & Stipak, B. (1992). Drug treatment and electronically monitored home confinement: An evaluation of a community-based sentencing option. Crime & Delinquency, 38(2), 158-170.

Jones, M., & Ross, D.L. (1997). Electronic house arrest and boot camp in North Carolina: Comparing recidivism. Criminal Justice Policy Review, 8 (4), 383-404.

Padgett, K.G., Bales, W.D., & Blomberg, T.G. (2006). Under surveillance: An empirical test of the effectiveness and consequences of electronic monitoring. Criminology & Public Policy, 5(1), 61-91.

Petersilia, J., & Turner, S. (1990). Intensive supervision for high-risk probationers: Findings from three California experiments. Santa Monica, CA: RAND.

Sugg, D., Moore, L., & Howard, P. (2001). Electronic monitoring and offending behaviour - reconviction results for the second year of trials of curfew orders (Findings 141). London: Home Office; Research, Development and Statistics Directorate.

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