EFFECTS OF DRUG ABUSE TREATMENT ON LEGAL AND ILLEGAL EARNINGS

MICHAEL T. FRENCH AND GARY A. ZARKIN*

Although recent research has shown that drug abuse treatment reduces drug use and criminal activity in some clients, the impact of treatment on clients'post-treatment labor market behavior is relatively unknown. This study uses datafrom a longitudinal survey to analyze annual legal and illegal earnings for 2,420 drug abusers. The analysis focuses on two different time intemals-one year before entering a drug abuse treat- ment program and one year after leaving the same program. It describes client char- acteristics, labor market variables, and treatment histo y, and estimates the eflects of length of time in treatment on post-treatment earnings. The regression analysis shows that length of time in treatment had a positive (negative) and statistically sign9cant impact on real legal (illegal) earnings following treatment for methadone and residen- tial clients, but the magnitude was small; accounting for possible selection bias had little effect on the results. Although residential clients experienced the largest relative changes in earnings outcomes, simply comparing the direct cost of residential treatment with the benefits from improved legal earnings and lower illegal earnings suggests that additional residential treatment is not cost-beneficial.

1. INTRODUCTION

The renewed national attack on drug abuse has forced a closer scrutiny of the costs and outcomes of anti-drug-abuse policies. Among these policies is the pro-

*French is Senior Economist, Center for Economics Research, Research Triangle Institute, Research Trian- gle Park, NC 27709, and Assistant Professor, North Carolina State University, Raleigh, NC; Zarkin is Se- nior Economist, Center for Economics Research, Re- search Triangle Institute, and Reseamh Associate Pro- fessor, Duke University, Durham, NC. The National Institute on Drug Abuse, Public Health Service, US. Department of Health and Human Services supported this work by Grant R01 DA05599-01. The views ex- pressed in this paper are those of the authors and do not represent an official position of the National Insti- tute on Drug Abuse or the U.S. Department of Health and Human Services. The authors gratefully acknowl- edge the programming support of Anne Theisen and also are indebted to Maria Bachteal, Judy King, and Judy Parsons for their assistance in preparing tables and editing the manuscript. This paper is a revision of an earlier version presented at the Western Eco- nomic Association International 65th Annual Confer- ence, San Diego, Calif., July 2, 1990, in a session or- ganized by Robert Michaels, California State Univer- sity, Fullerton.

Contemporary Policy Issues Vol. X, April 1992

vision of drug abuse treatment in private and federally funded clinics. Recent re- search has found that drug abuse treat- ment is effective in reducing the use of illicit drugs for some clients (Hubbard et al., 1989; Institute of Medicine, 1990). Ball et al. (1988) studied methadone treatment programs in three cities and found that 71 percent of the patients who remained in treatment one year or more ceased intra- venous (IV) drug use during the follow-up period, while 82 percent of those who remained in treatment less than one year quickly resumed IV drug use. McLellan et al. (1983) demonstrated that effective matching of clients to treatment modali- ties can improve outcomes. McAuliffe et al. (1985) showed that successfully treated opiate addicts who received aftercare had better outcomes than clients who were not offered aftercare.

Studies have also shown that drug abuse treatment helps to lower criminal activity and improve mental health. Har- wood et al. (1988) found a benefit-cost

98

@Western Economic Association International

FRENCH & ZARKN EFFECTS OF DRUG ABUSE TREATMENT 99

ratio of about 3:l by comparing the costs of drug abuse treatment with the benefits derived from reduced criminal activity. Exploring the costs and benefits of signif- icantly expanding treatment programs for incarcerated drug abusers, Anglin and Hser (1990) concluded that clients enter- ing treatment under legal coercion did as well by most outcome criteria as did vol- unteer clients.

Despite the upsurge in treatment out- come analysis, few studies have analyzed the effects of treatment on drug abusers’ follow-up earnings-both legal and ille- gal. On average, drug abusers entering treatment derive 49 percent of their total income from a legitimate job and 28 per- cent from illegal sources (French, forth- coming).

This study examines the impact of length of time in drug abuse treatment on post-treatment legal and illegal earnings. The analysis occurs in three stages. To determine the effects of time in treatment on clients’ legal earnings 12 months fol- lowing discharge, the first stage estimates several specifications of the legal earnings equation and corrects for potential selec- tion bias created by client’s decision to work. The second stage estimates the ef- fects of time in treatment on 12-month follow-up illegal earnings. The third stage estimates the relationship between time in treatment and the ratio of legal earnings to total earnings (legal and illegal).

II. DATA

Drug abuse treatment is a complex psy- chosocial process administered by thou- sands of programs in several different settings to a mixture of drug abusers. Under these conditions, trying to charac- terize a typical treatment process or pro- gram is unadvisable. Most experts agree, however, that treatment is delivered in three major modalities: outpatient metha- done maintenance, residential, and outpa- tient drug-free. Outpatient methadone in-

volves weekly counseling, various ancil- lary services (e.g., vocational training), and daily dosing of the synthetic narcotic, methadone, to block the craving for her- oin. Outpatient drug-free is essentially the same as outpatient methadone, but with- out the aid of methadone. Residential treatment can vary from intensive services in a 28 day program to long-term care in a therapeutic community. Because each modality possesses a unique treatment philosophy, regimen, and type of client, this study analyzes data by modality.

Using data from TOPS, a long-term, large-scale study of 11,000 drug abusers who entered treatment in 1979, 1980, and 1981 at 41 selected drug abuse treatment programs, this investigation provides ex- tensive information about the nature of drug abuse treatment and describes char- acteristics and behavior of drug abusers prior to treatment, at admission, and at several follow-up intervals (Hubbard et al., 1984). Although the TOPS data are over a decade old, newer, comparable data will not be available for several years.

TOPS was not a statistically representa- tive sample of treatment programs, but its scope and depth has enabled researchers to examine a wide range of clinical and policy questions. The study presented here analyzes clients’ legal and illegal earnings during the year after leaving a TOPS treatment program. The sample for the study here includes all 2,420 clients who participated in the 12-month follow- up interview-the largest follow-up co- hort in TOPS.

A. Admission Characteristics Drug abusers who entered TOPS treat-

ment programs often had long histories of drug use, emotional problems, and crimi- nal activity. Seventy-five percent of meth- adone clients, approximately 50 percent of residential clients, and nearly 33 percent of outpatient drug-free clients had experi- enced at least one treatment episode be-

100 CONTEMPORARY POLICY ISSUES

fore entering TOPS programs. In addition to drug abuse treatment, 20 percent of all clients had received treatment for alcohol- related problems, and 25 percent had re- ceived treatment for other mental health or emotional problems not related to sub- stance abuse (Marsden, Hubbard, and Bai- ley, 1988).

As an alternative to incarceration, the criminal justice system referred a substan- tial proportion of residential (38 percent) and outpatient drug-free clients (40 per- cent) to a TOPS program. In addition, criminal justice clients may have entered a program based solely on the informal recommendation of criminal justice sys- tem personnel. Even when admission was not the result of a formal referral, many clients had a criminal justice status at admission (e.g., probation, parole, or in- carceration). To examine the differences between criminal justice referrals and non- criminal justice referrals, the study seg- mented samples by criminal justice status. Sample means and regression coefficients vary little by type of referral. Thus, the discussion here does not deal with these differences. (The authors will provide on request the statistical analyses by type of referral.)

Most individuals with severe drug abuse problems cannot pay for treatment or afford private health insurance. Only 18 percent of methadone clients and 15 per- cent of residential clients had private in- surance coverage for their treatment. A much higher proportion of outpatient drug-free clients-28 percent-had insur- ance coverage. Less than half of all clients had any health insurance, public or pri- vate. Furthermore, 22 percent of metha- done clients, 9 percent of residential cli- ents, and 12 percent of outpatient drug- free clients reported that their primary source of income was public assistance (French, forthcoming). The lack of private insurance and client resources to pay for treatment implies that offering drug abuse

treatment on demand would require a substantial public investment.

B. Client Characteristics Table 1 presents clients’ demographics,

employment and earnings, and treatment history at the time of admission to a TOPS treatment program. It also reports employ- ment and earnings one year after leaving a TOPS program. The table shows variable means and standard deviations for each modality and for the full sample of clients. Variable means highlight some of the cli- ent differences across modalities. For ex- ample, methadone clients were predomi- nantly nonwhite, and outpatient drug-free clients were mostly white. Residential cli- ents were less likely to be married, and outpatient drug-free clients were less likely to be the head of a househoId. Methadone clients were about 5 years older than outpatient drug-free clients. All three modalities shared similar distribu- tions of male clients, educational level, and classification as seriously depressed.

The clients in the sample for this study entered a TOPS treatment program in 1979 or 1980. Depending on the clients’ length of stay, 12-month follow-up interviews were administered as late as 1983. As a result, clients’ annual legal and illegal earnings could correspond to any 12- month period between 1978 and 1983. Monthly consumer price indexes from 1978 to 1983 provided the basis for con- verting each clients’ nominal earnings to a base year (1983).

Average real legal earnings during the year prior to admission were slightly higher for outpatient drug-free clients ($6,302) compared with methadone clients ($5,702), while residential clients earned much less ($4,377). Prior to TOPS admis- sion, both methadone ($9,324) and resi- dential clients ($8,179) had substantial il- legal earnings-almost twice their legal earnings. Illegal earnings for outpatient

FRENCH & ZARKIN: EFFECTS OF DRUG ABUSE TREATMENT 101

drug-free clients were about 40 percent of their legal earnings.

Methadone and residential clients held full- or part-time legitimate jobs for almost the same number of weeks during the year prior to admission. But the number of weeks employed for outpatient drug-free clients surpassed both of the other two modalities. Outpatient drug-free clients also were more likely than clients in the other modalities to be working in the legal economy during the one-year period prior to admission. More than 80 percent of the former worked one or more weeks.

Treatment histories also show some marked differences between the modali- ties. On average, methadone clients had more treatment admissions (3.4) and longer average stays in treatment (18.8 weeks) than the other clients had. Outpa- tient drug-free clients had the lowest num- ber of treatment admissions (1.1) and the shortest average stay (6.5 weeks). Their younger average age as compared with clients in other modalities may partially explain their relatively fewer prior treat- ment admissions.

Sample means at the one-year follow- up, as well as at admission to a TOPS program, differ considerably across mo- dalities. For example, methadone clients stayed longer in a TOPS treatment pro- gram, were more likely to seek further treatment within the subsequent year, and had longer average stays in treatment after TOPS. Outpatient drug-free clients had the shortest total and average length of stay in a TOPS program and afterward.

A greater percentage of clients were married and heads of households at the one-year follow-up than at admission. Sig- nificantly fewer clients in all modalities reported serious depression at the follow- up. Clients also experienced labor market changes that varied considerably across modalities. On average, methadone clients recorded an 18 percent decline in real legal earnings from the year prior to admission. Residential clients also experienced a drop

in real legal earnings, albeit less severe (5 percent). In contrast, real legal earnings increased approximately 13 percent for out- patient drug-free clients. On average, real illegal earnings declined by 64 percent for methadone clients, 54 percent for residen- tial clients, and 23 percent for outpatient drug-free clients.

At first glance, treatment appears to have done little to improve real legal earn- ings for clients in methadone and residen- tial programs. However, from 1978 to 1983, real median earnings for full-time U.S. wage and salary workers declined by more than 11 percent (U.S. Department of Commerce, 1988). Thus, the drop in real legal earnings for methadone and residen- tial clients is not atypical of the U.S. pop- ulation. Even more impressive is the 13 percent real earnings improvement for outpatient drug-free clients during this time.

Legal and illegal earnings are only two labor market outcomes of drug abuse treatment. Maintaining a legitimate job or business is also important. Table 1 shows little change in total weeks worked for clients in all three modalities. Weeks worked by residential and outpatient cli- ents slightly increased between admission and follow-up, and slightly decreased for methadone clients. Similarly, a greater proportion of residential clients worked during the year after leaving a TOPS pro- gram than during the year prior to admis- sion. A slightly lower proportion of meth- adone and outpatient drug-free clients were working after TOPS treatment rela- tive to before TOPS treatment.

111. METHODS

Sample means measure central tenden- cies, but they do not control for the influ- ence of other variables on earnings, such as demographics, prior earnings, and treatment history. Regression analysis can estimate the impact of length of stay in treatment on post-treatment legal and ille- gal earnings, while controlling for other

102 CONTEMPORARY POLICY ISSUES

TABLE 1 Average Client Characteristics at Admission and at One-Year Follow-Up

to a TOPS Treatment Program Modality

Outpatient Outpatient All Methadone Residential Drug-Free Modalities

Variable (N = 835) (N = 731) (N = 854) (N - 2,420)

Demographics (at admission) Males

Caucasian/white

Highest grade attended

Age (months)

Married

Head of household

Number of dependents

Serious depression

0.673 (0.469)

0.434 (0.496) 11.311 (2.171)

370.072 (84.173)

0.384 (0.487)

0.611 (0.488)

1.069 (1.319)

0.540 (0.499)

Employment and Earnings (at admission) Real legal earnings past year

(1983 dollars) 5,701.69 (9,699.15)

(1983 dollars) 9,324.32 (18,794.84)

legal job past year 18.429 (21.224)

job past year 0.543 (0.498)

Real illegal earnings past year

Weeks employed at full- or part-time

Worked at full- or part-time legal

Employment and Earnings (at follow-up) Real legal earnings past year

(1983 dollars) 4,680.88 (8,174.16)

(1983 dollars) 3,382.82 (1 0,565.41)

legal job past year 15.783 (20.494)

job past year 0.478

Real illegal earnings past year

Weeks employed at full- or part-time

Worked at full- or part-time legal

0.788 (0.409)

0.577 (0.494) 11.092 (2.236)

321.907 (86.994)

0.141 (0.349)

0.620 (0.486)

0.534 (1.078)

0.610 (0.488)

0.676 (0.468)

0.776 (0.417) 11.578 (2.249)

312.131 (86.031)

0.266 (0.442)

0.469 (0.499)

0.657 (1.181)

0.604 (0.489)

0.709 (0.454)

0.598 (0.490)

11.339 (2.226)

335.081 (89.429)

0.269 (0.444)

0.563 (0.496)

0.762 (1.223)

0.584 (0.493)

4,377.00 6,302.15 5,499.85 (7,227.90) (7,720.20) (8,364.31)

8,178.78 2,561.81 6,474.06 (16,468.33) (8,197.35) (15,204.44)

17.162 26.156 20.769 (17.482) (19.858) (20.066)

0.670 0.803 0.673 (0.471) (0.398) (0.469)

4,166.33 7,101.40 5,376.57 (5,500.65) (8,904.76) (7,857.17)

3,792.06 1,962.98 2,997.51 (11,528.08) (8,517.15) (10,266.35)

19.942 27.921 21.312 (19.100) (20.622) (20.769)

0.696 0.791 0.654 . - ~

(0.500) (0.460) (0.407) (0.476)

FRENCH & ZARKIN: EFFECTS OF DRUG ABUSE TREATMENT 103

TABLE 1 continued Average Client Characteristics at Admission and at One-Year Follow-Up

to a TOPS Treatment Program Modality

Outpatient Outpatient All Methadone Residential Drug-Free Modalities

Variable (N = 835) (N = 731) (N = 854) (N = 2,420)

Treatment History Total treatment admissions before

entering a TOPS program 3.395 2.173 1.068 2.212 (4.263) (3.697) (2.310) (3.641)

entering a TOPS program 56.414 28.936 15.779 33.891 (79.151) (52.454) (39.607) (62.087)

treatment before entering a 18.785 10.884 6.539 12.113 TOPS program (32.215) (22.477) (18.264) (25.625)

Weeks in a TOPS program 40.375 23.099 15.846 26.503 (35.431) (27.001) (20.724) (30.240)

Total weeks in treatment before

Average length of stay (weeks) in

Note: Standard deviation in parentheses.

variables that also influence these out- comes.

Consider a simple regression model that describes a labor market outcome as a function of several explanatory vari- ables:

(1) Y = xp + E,

where Y is a labor market outcome (e.g., real legal or illegal earnings), X is a vector of explanatory variables, p is a coefficient vector, and E is a stochastic error term. Re- searchers have used this model exten- sively to estimate the effects of demo- graphic variables (e.g., education, age, sex, experience, health status) on earnings (Luft, 1975; Mincer, 1975).

The analysis here expanded this general framework to incorporate the effect of length of stay in treatment on labor market outcomes. Because the impact of all treat- ment-not just treatment in a TOPS pro- gram-on labor market variables may be

important, the framework includes treat- ment episodes before and after the TOPS episode in each model specification. Fifty- six percent of the TOPS sample received treatment prior and/or subsequent to the TOPS episode. Considering clients’ full treatment histories revealed whether bet- ter outcomes resulted from time in a TOPS program or from accumulated treatment. This specification also revealed whether time in treatment positively or negatively affected earnings after leaving a TOPS program. The following regression model specifies the relationship between treat- ment duration and labor market out- comes:

Y, = X, p + yPRETOPS

+ bTOPS + (pPOSTTOPS + E ,

where Yfis a labor market outcome vari- able at the one-year follow-up, Xf is a vec- tor of explanatory variables at the one-

104 CONTEMPORARY POLICY ISSUES

year follow-up, and PRETOPS, TOPS, and POSTTOPS are treatment duration vari- ables. PRETOPS is a measure of total time in treatment prior to entering a TOPS pro- gram, TOPS is total time in a TOPS pro- gram, and POSTTOPS is total time in treat- ment during the year after leaving a TOPS program. Thus, equation (2) estimates the effect of TOPS treatment on earnings, while controlling for demographic charac- teristics and for prior and ensuing treat- ment episodes.

One should consider three sources of potential sample selection bias when inter- preting these results. First, since not all drug users seek and/or receive treatment, the TOPS sample is not representative of the entire drug-using population. Unfor- tunately, because the sample consists only of drug users who received treatment- some at the mandate of the criminal justice system-potential censoring may have af- fected the data. Thus, only statements about the impact of drug treatment for the non-random subpopulation of drug users that sought and/or received treatment can be made.

A second source of selection bias may arise if those individuals with greater amounts of treatment have systematically different earnings prospects than those with shorter treatment durations. How- ever, the direction of the bias this potential problem might cause remains unclear. Cli- ents with short treatment duration may be earnest individuals who require less treat- ment and, consequently, enjoy higher sub- sequent earnings, or they may be unmoti- vated individuals who leave treatment prematurely and, consequently, experi- ence lower subsequent earnings. A similar possibility for bias exists when interpre- ting data for those individuals with long treatment durations. Given that the esti- mates presented in this study have no obvious bias, a full investigation of these issues has been deferred to future work. French et al. (forthcoming) have estimated first-difference models similar to the spec-

ifications presented here to eliminate the impact of unobserved individual charac- teristics that might be corre,lated with treatment duration and subsequent earn- ings. These first-difference results are es- sentially the same as the cross section results.

The third source of selection bias may arise if one estimates earnings regressions only on individuals with positive amounts of legal and illegal earnings. Earnings re- gressions estimated in this way do not necessarily identify population earnings functions. Following Heckman (1979) and Maddala (1983), the analysis here esti- mated two-stage earnings regressions to generate consistent parameter estimates.

IV. RESULTS

Because of the numerous client and treatment differences across modalities, this study estimated separate regression models for methadone maintenance, resi- dential, and outpatient drug-free samples. Following the model described by equa- tion (2), the analysis regressed real legal and illegal earnings at the one-year fol- low-up on demographic variables, lagged earnings, and three treatment duration variables. Table 2 reports selected regres- sion estimates for both the real legal earn- ings and the real illegal earnings specifi- cations. (The authors will provide on re- quest the full set of regression results.)

The dependent variable in the legal earnings specification is total real legal earnings from all full- or part-time jobs during the 12 months after the client left a TOPS program. Total real illegal earn- ings include all income derived from crim- inal activities during these 12 months. As discussed earlier, clients’ actual legal and illegal earnings were converted to infla- tion-adjusted 1983 dollars. All client and demographic variables in the earnings specifications were the same as those re- ported in table 1. The time in treatment variables were total weeks in treatment

FRENCH & ZARKIN: EFFECTS OF DRUG ABUSE TREATMENT 105

prior to a TOPS admission (PRETOPS), weeks in a TOPS treatment program (TOPS), and weeks in treatment during the 12 months after the client left a TOPS program (POSTTOPS).

Regarding the legal earnings results, coefficient estimates for each modality- specific equation had the expected signs and usually were statistically different from zero at the 90 percent confidence level or higher. The coefficient estimates for the time in TOPS treatment variable were positive for each modality and sta- tistically significant for methadone and residential clients. On average, one addi- tional week in treatment increased annual real earnings for methadone clients by $18 and for residential clients by $43 during the year following TOPS treatment. Calcu- lated in relative terms at the sample means, a 10 percent increase in treatment duration led to a 1.5 percent increase in annual real earnings for methadone clients and a 2.4 percent increase in annual real earnings for residential clients. Time in treatment prior to and following TOPS had a negative and usually insignificant effect on real earnings for each modality.

Illegal earnings prior to TOPS treat- ment consistently showed a positive and statistically significant impact on illegal earnings post-TOPS. Length of time in a TOPS treatment program had a statisti- cally significant negative impact on post- treatment illegal earnings for methadone and residential clients. The coefficient es- timate for outpatient drug-free clients was small, negative, and insignificant. On av- erage, one additional week in treatment decreased annual real illegal earnings for methadone clients by $27 and for residen- tial clients by $68 during the year follow- ing TOPS treatment. Calculated in relative terms at the sample means, a 10 percent increase in treatment duration led to a 3.2 percent decrease in annual real illegal earnings for methadone clients and a 4.1 percent decrease in annual real illegal earnings for residential clients. Time in

treatment prior to and following TOPS had mixed and insignificant effects on real illegal earnings across modalities.

Segmenting the sample into positive legal earners facilitated determining the earnings effects of time in treatment on working clients. Ordinary least squares with a two-step procedure to account for the possibility of sample selection bias estimated linear and log-linear legal earn- ings specifications. The same procedure estimated a log-linear illegal earnings specification for positive illegal earners. Table 3 reports the coefficient estimates for time in TOPS treatment for each specifica- tion by modality.

Residential clients showed a positive and statistically significant time-in-treat- ment effect for all specifications of the legal earnings equations. Time in TOPS treatment also had a consistently negative and statistically significant impact on post-treatment illegal earnings for resi- dential clients. For methadone clients, the estimated impact of time in treatment on legal and illegal earnings was statistically significant for each linear specification, including the selectivity-corrected model. None of the log-linear specifications had statistically significant coefficient esti- mates. For both methadone and residen- tial samples, the magnitude of the elastic- ity estimates was similar across specifica- tions. Furthermore, selectivity bias does not appear to be a problem with these samples. In comparison, coefficient esti- mates from the outpatient drug-free sam- ple were not statistically significant.

An estimate of the effect of time in TOPS treatment on the ratio of legal earn- ings to total earnings (legal plus illegal) provided a final test of the treatment/ earnings relationship. If treatment im- proves legitimate employment and re- duces criminal activity, clients with more treatment should derive a greater share of their total earnings from a legitimate job or business. The time in treatment coeffi- cient estimates are positive and statisti-

TABL

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TABL

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0.53d

O.lld

O.lld

0.12d

to e

nter

ing

a TO

PS tr

eatm

ent

(0.03)

(0.03)

(0.04)

(0.02)

(0.03)

(0.03)

prog

ram

Tot

al w

eeks

in tr

eatm

ent p

rior

-1

.00

-0.1

5 -5.03

-5.92

3.86

6.89

to e

nter

ing

a TO

PS tr

eatm

ent

(3.48)

(4.30)

(6.75)

(4.90)

(10.82)

(7.56)

prog

ram

prog

ram

(9.25)

(8.3

5)

(1 2.73)

(12.74)

(19.92)

(14.19)

afte

r le

avin

g a

TOPS

trea

tmen

t (1

3.03)

(14.88)

(19.76)

(18.02)

(35.53)

(22.82)

prog

ram

R-s

quar

e 0.30

0.16

0.41

0.11

0.09

0.07

2 % s $ 5 To

tal w

eeks

in tr

eatm

ent 12

mon

ths

-21.6F

-17.58

-24.22

10.44

9.25

-5.60

4 2

Tota

l wee

ks in

a T

OPS

trea

tmen

t 18.36d

43.19d

19.76

-27.05d

-67.99d

-4.87

m E

Not

e: S

tand

ard

erro

r in

pare

nthe

ses.

aDep

ende

nt va

riab

le is

tota

l rea

l leg

al e

arni

ngs (

1983

dol

lars

) fro

m f

ull- or p

art-t

ime j

obs

one

year

afte

r le

avin

g a

TOPS

pro

gram

. be

pend

ent

vari

able

is t

otal

rea

l ille

gal e

arni

ngs

(198

3 do

llars

) one

yea

r af

ter

leav

ing

a TO

PS p

rogr

am.

'Sig

nific

antly

diff

eren

t fro

m z

ero

at t

he 90% c

onfid

ence

leve

l (t

wet

aile

d te

st).

dSig

nific

antly

diff

eren

t fro

m z

ero

at t

he 9

5% co

nfid

ence

leve

l (tw

o-ta

iled

test

).

1

108 CONTEMPORARY POLICY ISSUES

TABLE 3 Time in TOPS Treatment Coefficient Estimates by Treatment Modality

Modalitv Outpatient Outpatient

Dependent Variable Methadone Residential Drug-Free

Legal Earnings (Full Sample)

Legal Earnings (Positive Earners)

Legal Earnings (Selectivity Correction)

Log Legal Earnings (Positive Earners)

Log Legal Earnings (Selectivity Correction)

Illegal Earnings (Full Sample)

Log Illegal Earnings (Positive Earners)

Legal Earnings/Total Earnings

Legal Earnings/Total Earnings

(Full Sample)

(Positive Earners)

18.36b (9.25)

29.93b (15.17)

29.Ma (15.00)

0.0025 (0.0023)

0.0015 (0.0027)

-27.05b (1 2.74)

-0.0046 (0.0039)

0.0010 (0.0007)

(0.0005) 0,001 2b

43.1gb (8.35)

36.91b (9.88)

44.91b (20.77)

0.0093b

0.009Gb (0.0047)

(0.0022)

-67.9gb (19.92)

-0.0135b (0.0067)

0.0041b (0.0006)

0.0027b (0.0005)

19.76 (12.73)

7.07 (14.17)

3.05 (16.48)

0.0029 (0.0023)

(0.0032) -0.0013

-4.87 (14.19)

0.0059 (0.0107)

0.0016b (0.0006)

0.0007a (0.0004)

Note: Standard error in parentheses. 'LSignificantly different from zero at the 90% confidence level (two-tailed test). bSignificantly different from zero at the 95% confidence level (two-tailed test).

cally significant for the full sample of clients and for positive legal earners for each modality (see table 3). Residential clients who spent additional time in a TOPS treatment program experienced the largest absolute effect on the share of legal earnings in total earnings.

V. CONCLUSION

This is one of the first econometric studies of the impact of length of stay in drug abuse treatment on clients' legal and illegal earnings following treatment (see also French et al., forthcoming). Even after accounting for potential selection bias, the

regression analyses indicate that length of stay in treatment had a statistically signif- icant positive, albeit small, impact on the follow-up real legal earnings of clients in the major treatment modalities. Time in treatment had a somewhat larger (in abso- lute value) negative impact on real illegal earnings following discharge. The follow- ing points summarize these findings:

(i) On average, clients in the three major treatment modalities experienced rela- tively small changes (i.e., less than 18 per- cent) in real legal earnings and relatively large changes (i.e., as high as 64 percent) in real illegal earnings from the year prior

FRENCH & ZARKIN: EFFECTS OF DRUG ABUSE TREATMENT 109

to entering a TOPS treatment program to the year after leaving the same program.

(ii) The length of time in a TOPS treat- ment program had a small, positive (neg- ative), and statistically significant impact on real legal (illegal) earnings for metha- done and residential clients.

(iii) The length of time in a TOPS treat- ment program had a positive and statisti- cally sigruficant impact on the ratio of legal earnings to total earnings for clients in all three modalities.

Overall, residential clients experienced the largest earnings impact from length of time in treatment: the longer their time in treatment, the greater their chances of earning higher salaries from a legitimate job and of curtailing their income-generat- ing criminal activities. Their legal earnings results are quantitatively similar and sta- tistically significant after differencing the data between the 12-month follow-up and the values at admission (French et al., forthcoming). Unfortunately, residential treatment is the most costly. The average annual cost per bed for residential treat- ment in TOPS programs was $7,416 (1983 dollars). The average annual per-client costs of providing outpatient methadone

and outpatient drug-free treatment during this period were considerably lower at $2,351 and $2,418, respectively (Hubbard et al., 1989).

A simple comparison of the costs and benefits can determine whether residential treatment was a worthwhile investment based on earnings outcomes alone. The regression results show that residential clients would have earned approximately $43 more from a legal job and $68 less from illegal activities for a total social benefit of $111 if they stayed an additional week in treatment. However, the average weekly cost of residential treatment for each TOPS client was approximately $143 ($7,416/52). Considering only the earn- ings outcomes of length of time in treat- ment, the investment in additional resi- dential treatment would not be cost-bene- ficial. But the calculation excludes several elements of cost (e.g., foregone salary while in residential treatment) and bene- fits (e.g., lower drug use, reduced preda- tory crime, improved health status), thereby minimizing the significance of this comparison. Further analyses of these costs and benefits are necessary to help design contemporary drug abuse treat- ment strategies.

110 CONTEMPORARY POLICY ISSUES

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Ball, J. C., W. R. Lang, C. P. M ers, and S. R. Friedman, "Reducing the Risk of A& Through Methadone Maintenance Treatment," Journal of Health and So- cial Behavior, September 1988, 214-226.

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