Correctional Treatment as an Economically Sound Approach to Reducing the High Costs of Recidivism: A Review of the Research

Steven N. Zane; Jhon A. Pupo; Brandon C. Welsh

doi:doi:10.21428/cb6ab371.74454b4f

Abstract

Background: Prior research indicates that correctional treatment programmes can be highly effective in reducing reoffending. Less studied, however, is whether such programmes are economically efficient. Aims: To review the research literature on the economic efficiency of correctional treatment programmes. Methods: A review of cost-benefit analyses of correctional treatment programmes from 2004 to the present was carried out. To be included in the review, studies must have attempted to measure monetary costs and benefits of correctional treatment programmes and be based on experimental or high-quality quasi-experimental evaluations. Results: A total of 22 cost-benefit studies of correctional treatment programmes met the criteria for inclusion in our review, 19 of which estimated (or allowed estimation of) benefit-to-cost ratios. All 19 studies yielded a favourable benefit-to-cost ratio. Conclusions: Correctional treatment programmes appear to be economically efficient, with the monetary benefits produced by such programmes substantially exceeding their monetary costs. This finding appears to hold across a variety of different intervention types, and offers policy-makers and practitioners ample evidence in favour of providing additional resources for correctional treatment programmes.

Keywords: correctional treatment; cost-benefit analysis; recidivism; offender re-entry; rehabilitation

1 INTRODUCTION

It has become common wisdom that mass incarceration in the Unites States is a failed social experiment, at least as a measure of sustainable and effective crime prevention (see Clear & Frost, 2014; National Research Council, 2014). In an emerging era of de-carceration and criminal justice reform, there remains, however, the question of how best to respond to criminal offenders, both in institutional and community settings. Public support for reducing prison populations requires that recidivism rates do not increase (see Cullen et al., 2017), and this requires effective correctional treatment (among other things, such as crime prevention; see Welsh & Farrington, 2012; Welsh & Pfeffer, 2013). Correctional treatment programmes attempt to modify offender behaviour through some combination of treatment and external controls. While much has been written on the effectiveness of correctional treatment programmes (see Weisburd et al., 2017), less work has focussed on the economic efficiency of correctional treatment (but see Farrington et al., 2001; Welsh, 2004; Welsh & Farrington, 2000). When evaluating correctional treatment programmes as a social investment, however, it is not enough to ask whether they “work” in the sense of effectiveness. Importantly, such programmes must represent an economically efficient approach to reducing reoffending.

The main aim of this article is to review what is known about the economic efficiency of correctional treatment programmes.[1] It focuses on prior assessments of the monetary costs and benefits of correctional interventions. In doing so, it updates Welsh (2004), the last comprehensive review of cost-benefit analyses of correctional treatment programmes.

2 BACKGROUND

The potential for reducing reoffending through the use of correctional treatment programmes has long been a topic of interest for policy-makers, practitioners, researchers, and the general public. At their core, correctional treatment programmes aim to increase the odds of successful offender re-entry and, thus, reduce recidivism. Importantly, empirical research has shown that correctional treatment programmes can be effective in reducing recidivism (see, Weisburd et al., 2017). Also important is whether correctional programmes are economically efficient—that is, do they yield monetary benefits that exceed their costs?

Welsh and Farrington (2000) conducted the first detailed review of cost-benefit studies of correctional intervention programmes as part of their larger review of crime prevention programmes. Using systematic search strategies, they located seven studies (published between 1974 and 1994) of correctional programmes that conducted a cost-benefit analysis. All seven studies produced desirable benefit-to-cost ratios, ranging from a low of $1.13 to a high of $7.14 in economic return per one-dollar investment (see also Farrington et al., 2001). In a later review, Welsh (2004) identified 14 cost-benefit studies of correctional treatment programmes. Consistent with the prior review, 13 of the 14 studies reported desirable benefit-to-cost ratios. Welsh (2004) also found that for some interventions “benefits from improvements in education, employment, health, social service use, and illicit substance use exceeded the benefits from reduced recidivism” (p. 12).

Despite this evidence that correctional treatment programmes can be economically efficient, it has been nearly two decades since the last comprehensive review of the literature. It is thus important to take stock of more recent cost-benefit studies of correctional treatment.

3 METHODS

Our major criteria for inclusion of studies in the review are as follows. First, we included all studies from 2004 to the present (i.e., subsequent to the prior review) that estimated the monetary costs and benefits of correctional treatment programmes. This includes community as well as institutional programmes, and programmes aimed at adult as well as juvenile offenders. It did not include cost-benefit estimates of state-level policies (e.g., Duwe & McNeeley, 2021; Hamilton et al., 2015) in contrast to specific programmes, and it did not include studies that focussed only on institutional conduct as opposed to recidivism (e.g., Zhang et al., 2009). Additionally, studies that estimated only costs (e.g., using a cost-analysis) were not included.

Second, because a cost-benefit analysis is only as defensible as the evaluation upon which it is based, lower quality evaluations were not included. Weimer and Friedman (1979) recommend that cost-benefit analyses be limited to programmes that have been evaluated with an “experimental or strong quasi-experimental design” (p. 264).[2] Third, we have used the benefit-to-cost ratio to measure the economic efficiency of programmes rather than net value (i.e., benefits minus costs). Doing so provides a single measurement of the value of a programme that is gained from one monetary unit of investment or expenditure. It also controls for different time periods from which net benefits might be calculated. (That is, inflation makes it difficult to compare net programme benefits from different time periods.) The benefit-to-cost ratio thus represents a direct measurement of the value the public receives for its investment, which invariably is made through taxes.[3]

4 RESULTS

A total of 22 cost-benefit studies of correctional treatment programmes met the criteria for inclusion in our review. The studies in Table 1 have been organised in chronological order. All studies but one were conducted in the United States and each is reported in U.S. dollars (but see Jolliffe et al., 2013). Most interventions targeted general recidivism, though several focussed on specific offending behaviours, such as drug/alcohol abuse and sex offences. In 13 of the studies, the treatment took place in an institutional setting, while the setting was the community in six studies; the other three studies included both settings. Fifteen studies involved adult offenders and seven involved juvenile offenders. Sample sizes ranged from a low of 48 persons (Borduin & Dopp, 2015) to a high of 3,570 persons (Duwe, 2015). Main intervention types included substance abuse (n=6), re-entry programmes (n=5), educational or vocational programmes (n=3), multisystemic therapy (n=3), and boot camps (n=2). Post-programme treatment effects were assessed in each of the studies, and the length of follow-up ranged from 12 months (French et al., 2010) to 25 years (Dopp et al., 2014). When studies provided multiple estimates, we used the longest follow-up.

[Table 1 about here]

Seven studies carried out cost-benefit analyses based on programme impact evaluations that used random allocation. The other 15 studies were based on quasi-experimental designs. For 11 of these 15 studies, this involved propensity score matching. Fifteen studies calculated benefit-to-cost ratios and four studies provided the information from which such ratios could be calculated (Cheesman et al., 2012; Duwe, 2015; Roman et al., 2008; Rossman et al., 2011). For the other three studies, calculation of benefit-to-cost ratios was not possible because the treatment programme costs were reported as negative, meaning that there were cost savings relative to the comparison condition (see Rossman et al., 2011).[4] For example, a benefit-to-cost ratio could not be calculated for French et al. (2010) because the average daily cost for the treatment group was $75 per inmate compared to $109 per inmate in the comparison correctional facility. As the authors put it, “treatment-related cost savings are highly unusual for a program that also generates significant economic benefits relative to standard incarceration” (French et al., 2010, p. 38).

While all studies measured benefits in terms of criminal justice system savings (including police services, court administration, and incarceration), 15 studies also included tangible victim costs, with 12 of these studies also including intangible costs to victims or society more generally. Roman et al. (2008) stands out for its multivariate cost-benefit analysis in contrast to the traditional approach of monetising benefits and costs and comparing the two.[5] Additionally, costs were measured differently across studies. Twelve studies measured total average costs per participant, three studies measured marginal costs per participant (i.e., excluding overhead costs), and seven studies measured incremental (i.e., additional) costs over the comparison condition.

All of the studies yielded a favourable benefit-to-cost ratio (or net benefits), meaning that programme benefits outweighed programme costs. The economic return on a one-dollar investment ranged from a low of $1.08 for a drug treatment court (Cheesman et al., 2012) to a high of $48.80 for a multisystemic therapy programme (Borduin & Dopp, 2015). Among major intervention types, substance abuse programmes ranged from $1.08 (Cheesman et al., 2012) to $3.67 (Roman et al., 2008), re-entry programmes ranged from $1.82 (Duwe, 2013) to $5.64 (Duwe, 2014), educational and vocational training programmes ranged from $1.54 (Cochran, 2018) to $34.50 (Miller et al., 2015), and multisystemic therapy programmes ranged from $5.04 (Dopp et al., 2014) to $48.80 (Borduin & Dopp, 2015).

While prior research suggests that higher quality evaluation designs may produce smaller effect sizes (Weisburd et al., 2001; Welsh et al., 2011), such a pattern is not immediately apparent here. It is worth noting, however, that the largest benefit-to-cost ratios based on experimental evaluations involved multisystemic therapy (Borduin & Dopp, 2015; Klietz et al., 2010), which is known to be highly effective—one of four Blueprint “model plus” programmes (Elliott et al., 2020). Additionally, while studies that included intangible victim costs did not always produce larger benefit-to-cost ratios, the four largest ratios (i.e., > 10) did include such costs (Borduin & Dopp, 2015; Cooke et al., 2021; Fumia et al., 2015; Miller et al., 2015).

5 DISCUSSION AND CONCLUSIONS

This article reviewed research on the economic efficiency of correctional treatment programmes. No attempt was made to determine conclusively which of the strategies produced the greatest economic return on investment. This was largely because of the small number of studies identified and variability in intervention modality, in addition to some variability in the measurement of benefits and costs. Despite these differences among the studies the overall picture is clear: correctional treatment programmes have the potential to provide monetary benefits that greatly exceed their costs. As Welsh (2004) put it almost 20 years ago, “if the monetary benefits of correctional treatment programs outweigh their costs, this may be a persuasive argument for increasing treatment resources for offenders” (p. 9). As such, the research literature provides ample support for providing additional resources for correctional treatment programmes.

It is important to note a key limitation of this review, specifically, that “the top-down cost estimation approaches that are so common in this literature tend to over-estimate statistical significance by under-estimating variance” (Rossman et al. 2011, p. 229). Since the traditional approach of monetising benefits and subtracting costs to produce a net benefit (or using a benefit-to-cost ratio) is not performed in a multivariate statistical framework, it is possible that the effect size (drawn from an impact evaluation) is statistically significant while the benefit-to-cost ratio is not (Roman et al., 2008).[6] Relatedly, the traditional approach does not allow for calculating confidence intervals around the benefit-to-cost ratio.

Limitations aside, the results provide evidence, consistent with prior reviews, that correctional treatment programmes are, on average, cost-efficient. This has important implications for those considering adopting treatment programmes in correctional settings. First, various intervention modalities produced costs savings to the criminal justice system, victims, and society at-large. While the range of benefit-to-cost ratios varied, every type of correctional intervention—drug courts, substance abuse treatment, educational and vocational programmes, multisystemic therapy—produced monetary benefits that exceeded their costs. Second, many of the included studies support the notion that return on investment can occur in a relatively short time period—within two years for 10 studies. This short time frame may have political significance as “the potential to produce immediate benefits is far more appealing because of the short time horizons of politicians” (Welsh, 2004, p. 12). Third, the results highlight that correctional treatment programmes are economically efficient for juvenile and adult offenders. For adults, the results offer evidence that correctional treatment programmes may be cost-efficient for facilitating successful offender re-entry, an important policy goal as part of criminal justice reform. For juveniles, this suggests that the juvenile court’s historical mission—to address the best interests of the child through individualised treatment—is not only just, but cost-efficient.

A final observation is that the cost-efficiency of correctional treatment programmes is due, in large measure, to the high cost of crime to society. As Welsh et al. (2015, p. 455) observe:

Since the cost of offending is very high, programs do not need to be very effective to save money. For example, if a program cost $1,000 per participant, and 1,000 persons received the program, $1 million would have been spent. On the basis of Cohen and Piquero’s (2009) estimates, if only one person were saved from a life of crime, between $3.2 million and $5.8 million would be saved. Therefore, the benefits could outweigh the costs even if the program was only effective with one in 1,000 participants.

This point carries further important implications. Many correctional treatment programmes are associated with significant-but-small reductions in recidivism compared to day-to-day correctional practices (see Weisburd et al., 2017). Yet even small benefits, in terms of reducing future crimes, can be substantial monetarily when compared with the relatively low cost of programme operations. This too may justify a continued dedication of public resources to correctional treatment programmes.

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

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Table

Table 1. Summary of correctional treatment programmes

Author, Publication Date, and Location	Targeted Offending Behaviour	Treatment Setting	Duration; Type of Intervention	Sample Size	Evaluation design	Follow-up; Treatment Effects^*	Costs Measured	Benefits Measured	Benefit-to-Cost Ratio^†
Aos (2004), King, Snohomish, Pierce, and Kitsap counties, WA	Juvenile substance abuse and recidivism	Institution (juvenile residential facility); community	6–8 months; family- and community-based re-entry programme	273 youth: T = 104, C = 169	Before-after, with matching	18 months; total re-convictions (0), felony re-convictions (+), violent felony re-convictions (0)	Total programme cost per youth	CJS savings, crime victim expenses (future)	3.15
Piper & Spohn (2004), Douglas County, NE	Adult substance use and recidivism	Institution (adult drug courts)	NA; drug court with judicial monitoring and case management	940 felony drug offenders (mean age = 33)	Before-after, with matching	24 months; felony re-arrest (+), misdemeanor re-arrest (+), total re-arrest (+)	Total programme costs	CJS savings, crime victim expenses (tangible), social costs (intangible)	NA^††
Zarkin et al. (2005), Kings County, NY	Adult substance use and recidivism	Institution (adult drug courts)	15–24 months; drug treatment based on therapeutic community model	279 nonviolent felony drug offenders (mean age = 33): T = 149, C = 130	Before-after, with matching	4 years; re-arrest: 1 year (+), 2 years (+), 3 years (+), 4 years (+)	Total programme cost	CJS savings	2.17
Caldwell et al. (2006), Madison, WI	Severe and violent juvenile delinquency and recidivism	Institution (state juvenile institutions)	NA; intensive mental health treatment	202 incarcerated youth (mean age = 17): T = 101, C = 101	Before-after, with propensity score matching	4.5 years (average); new offences (+), new violent offenses (+)	Incremental programme cost per youth (i.e., cost difference)	CJS savings	7.18
Roman et al. (2007), Baltimore, MD	Any criminal recidivism	Community, institution	NA; pre- and post-release services (including housing assistance, substance abuse treatment, mental health counseling, education, vocational training)	599 African American males (mean age = 37): T = 229, C = 370	Before-after, with propensity score matching	38 months (average); re-arrest (0), number of re-arrests (+), re-conviction (0), number of re-convictions (0)	Total programme cost per participant	CJS savings, crime victim benefits (tangible), crime victim benefits (intangible)	3.09
Roman et al. (2008), Anchorage, AK	Alcohol/drug-related offending	Institution (therapeutic drug court)	18 months (average); substance abuse treatment, moral recognition therapy, recovery meetings, case-management	277 arrestees (mean age = 39): T = 136, C = 141	Before-after, with propensity score matching	24, 30, 36, 48 months; re-arrest: 24 (+), 30 (+), 36 (+),48 months (+); number of re-arrests: 24 (0), 30 (0), 36 (0), 48 months (0); re-conviction: 24 (0), 30 (0), 36 (0), 48 months (0); number of re-convictions: 24 (0), 30 (0), 36 (0), and 48 months (0)	Marginal programme cost per participant	Multivariate analysis of CJS savings and crime victim savings	3.67 (opt-in group, 48 months)
Bierie (2009), Baltimore City and Jessup, MD	Any criminal recidivism	Institution (adult boot camp)	6 months; correctional boot camp programme	226 men (mean age = 23): T = 105, C = 121	Randomised experiment	NA; re-arrest (NA)	Total programme cost	CJS savings, crime victim expenses (tangible), crime victim benefits (intangible)	NA^††
French et al. (2010), NJ	Adult substance use and recidivism	Institution (substance abuse facility)	NA; pre-release substance abuse treatment for repeat male offenders	571 male offenders (mean age = 34): T = 176, C = 395	Before-after, with propensity score matching	12 months; days without re-arrest (+), odds of re-arrest (+), odds of re-conviction (+), odds of re-incarceration (+)	Total programme cost per participant	CJS savings, victim costs, offender wage loss	NA^††
Klietz et al. (2010), St. Louis and Columbia, MO	Serious and violent juvenile recidivism	Community (home, school, recreation centre)	4–6 months; multisystemic therapy	176 youth (mean age = 14.5): T = 92, C = 84	Randomised experiment	13.7 years (average); NA	Incremental programme cost (i.e., cost difference)	CJS savings, crime victim expenses (tangible), crime victim benefits (intangible)	6.6
Rossman et al. (2011), multiple courts across eight states	Adult substance use and recidivism	Institution (adult drug courts)	NA; drug treatment, drug-testing, supervision requirements, support services	1,533 adult drug offenders: T = 1,009, C = 524	Before-after, with propensity score matching	6, 18, 24 months; self-reported offending (+), number of re-arrests (0), number of days in prison/jail (+)	Incremental programme cost (i.e., cost difference)	CJS savings, crime victim expenses (tangible), social costs (intangible)	1.75
Cheesman et al. (2012), 12 counties in VA	Adult drug addiction/dependency and recidivism	Institution (adult drug courts)	12 months (minimum); court-ordered supervision, drug testing, treatment services	1,555 offenders (mean age = 34.7): T = 748, C = 807	Before-after with propensity score matching	2 years; re-conviction (+), number of re-convictions (+)	Total programme cost per drug court participant	CJS savings, victim expenses (tangible), victim and social costs (intangible)	1.08
Duwe (2013), 5 counties in MN	Adult sexual recidivism	Community	12 months; re-entry services/support	62 sex offenders (mean age = 37.5): T = 31, C = 31	Randomised experiment	2 years (average); re-arrest (+), re-conviction (0), re-sentence (0), revocation (+), re-incarceration (+)	Total programme cost per participant	CJS savings	1.82
Jolliffe et al. (2013), Thorn Cross, England	Any recidivism	Institution	25 weeks; boot camp programme for young offenders (ages 18–21)	250 young men (mean age = 19.4): T = 125, C = 125	Before-after, with matching	10 years; prevalence of re-conviction (0), frequency of re-conviction (+)	Incremental programme cost (i.e., cost difference)	CJS savings, crime victim expenses (tangible), crime victim benefits (intangible)	3.93
Duwe (2014), 3 counties (MN)	Any criminal recidivism	Community, institution	NA; re-entry services/support	689 prisoners (mean age = 35): T = 415, C = 274	Randomised experiment	35 months (average); re-arrest (+), re-conviction (+), re-incarceration (0), revocation (+), recidivism (+)	Marginal programme cost per participant	CJS savings	5.64
Dopp et al. (2014), St. Louis and Columbia, MO	Violent, serious, and chronic juvenile recidivism	Community (home, school, and/or neighborhood settings)	4–6 months; multisystemic therapy	176 serious juvenile offenders (mean age = 14.5): T = 92, C = 84	Randomised experiment	25 years (average); re-arrest for any offense (+), re-arrest for felony offense (+)	Incremental programme cost (i.e., cost difference)	CJS savings, crime victim expenses (tangible), crime victim costs (intangible)	5.04
Duwe (2015), MN	Any criminal recidivism	Institution (prison work programme)	4 months (average); work release programme (paid employment and services)	3,570 prisoners T = 1,785, C = 1,785	Before-after, with propensity score matching	24–72 months; re-arrest (+), re-conviction (+), re-incarceration (+), revocation (-)	Total revocation cost of early release	CJS savings, tax revenue from post-release employment	1.36
Borduin & Dopp (2015), St. Louis and Columbia, MO	Juvenile sexual offending and recidivism	Community (home, school, and/or neighbourhood settings)	31 weeks (average); multisystemic therapy	48 youth (mean age = 14): T = 24, C = 24	Randomised experiment	8.9 years (average); re-arrest for any crime (+), re-arrest for felony crime (+)	Incremental programme cost (i.e., cost difference)	CJS savings, tangible victim expenses, intangible victim benefits	48.80
Fumia et al. (2015), Snohomish County, WA	Any juvenile recidivism	Institution (juvenile court)	12 hours over 2–3 days; educational early intervention programme	1,398 youth (mean age = 16): T = 699, C = 699	Before-after, with propensity score matching	18 months; total re-conviction (0), felony re-conviction (0), misdemeanor re-conviction (0)	Total programme cost per youth	CJS savings, crime victim expenses, social and health care-related benefits	23.34
Miller et al. (2015), King County, WA	Any juvenile recidivism	Community	6 months (average); educational and employment training	532 youth (mean age = 17): T = 266, C = 266	Before-after, with propensity score matching	18 months; any re-conviction (+), felony re-conviction (0), violent felony re-conviction (0), misdemeanor re-conviction (+)	Incremental programme cost (i.e., cost difference)	CJS savings, crime victim expenses, social and health care-related benefits	34.50
Cochran (2018), Windham, TX	Any criminal recidivism	Institution (vocational programme in prison)	NA; vocational education and industry certification	3,000 prison inmates (mean age = 35.4): T = 1,500, C = 1,500	Before-after with propensity score matching	1–2.5 years; re-incarceration (0), post-release employment (+)	Total programme cost per youth	CJS savings	1.54
Duwe (2018), 5 counties in MN	Adult general and sexual recidivism	Community	6–12 months; re-entry services/support	100 prisoners (mean age = 38): T = 50, C = 50)	Randomised experiment	73 months (average); re-arrest (+), sex offence re-arrest (+), re-conviction (+), sex offence re-conviction (0), re-sentence (+), revocation (+).	Marginal programme cost per participant	CJS savings	3.73
Cooke et al. (2021), 12 correctional facilities in FL	Any criminal recidivism	Institution (prison dog-training programme)	> 31 days; in-prison dog-training programme	822 men (mean age = 36): T = 363, C = 459	Before-after, with propensity score matching	1 year; re-arrest for any reason (+), re-arrest for crime (+)	Total programme cost per participant	CJS savings, victim expenses (tangible), victim and social costs (intangible)	22

Notes. CJS = criminal justice system; T = treatment group; C = control group; NA = not available.

^* 0 = null effects; + = significant desirable effects; - = significant undesirable effects

^† Expressed as a ratio of benefits to costs in monetary units (national currencies)

^††Benefit-to-cost ratio not possible because treatment costs were lower than comparison (i.e., negative cost)

[1] A brief note on terminology is warranted. Scholars across disciplines have argued that economic efficiency “does not have one widely accepted definition, although it appears in speeches about program costs about as often as, and sometimes interchangeably with, 'cost-benefit' and 'cost-effectiveness’” (Yates, 2015, p. 56). Two traditional conceptualizations of economic efficiency are technical and allocative efficiency (Farrell, 1957). Technical efficiency refers to the degree to which a given intervention produces the desired outcome at the lowest possible cost. Allocative efficiency refers to the extent to which a given intervention maximizes benefits––here, the main concern is achieving the optimal allocation of resources to interventions that produce the highest net economic benefit (Turner et al., 2021). In cost-benefit analyses, intervention costs and outcomes are both monetised, allowing the calculation of net benefits—and of benefit-to-cost ratios as a measure of (allocative) efficiency.

[2] While there are many potential reasons for exclusion based on poor implementation (e.g., high attrition rates), we did not state a priori criteria based on subjective assessment of study quality. Instead, we limited our methodological inclusion criteria to whether a study compared treatment and control groups using quasi-experimental (e.g., matching) or experimental techniques. In large part, this reflects the dearth of high-quality cost-benefit studies of correctional treatment programmes.

[3] There are some criticisms of the benefit-to-cost ratio. Most notably, strategic decision-making must account for the overall allocation of resources toward correctional programmes, even where a benefit-to-cost ratio is high. As Rossman and colleagues (2011, p. 229) observe, benefit-to-cost ratios “do not account for scale (a program that saves $200 on a $100 investment receives the same score as a programme that saves $20,000 on a $10,000 investment).” Additionally, sometimes benefit-to-cost ratios cannot be calculated because program costs are negative (i.e., treatment costs less than the control condition): “if the costs and the benefits have different signs, the results are difficult to interpret. Suppose a program saves $200 and has benefits of $100 the cost-benefit ratio is -$2 to 1, which is nonsensical” (Rossman et al., 2011, p. 229). This latter problem precludes the calculation of benefit-to-cost ratios for three studies included in the present review.

[4] These studies report total cost savings instead of benefit-to-cost ratios. Bierie (2009) reports $94,700 in total cost savings per boot camp participant, French et al. (2010) report a treatment effect of $4,497 to $6,209 per person, and Piper and Spohn (2004) report $11,336 in total cost savings per drug court participant.

[5] In their quasi-experimental evaluation of wellness courts in Alaska, Roman et al. (2008) first used propensity scores used to balance the treatment and comparison samples. For the cost-benefit analysis, they computed a dependent variable that represented the sum of costs to society per offender (non-recidivists had a value of zero) and conducted multivariate analysis controlling for other baseline differences. The treatment coefficient (i.e., average treatment effect) was “interpreted as the net change in social welfare,” such that negative values represented cost savings due to treatment (p. 40).

[6] Additionally, the effect size estimate from impact analysis is likely from a multivariate model that controls for other covariates that “may have an independent effect on benefits to society”—which is not taken into account in the simple benefit-to-cost ratio (Roman et al., 2008, p. 40).