ED 203 061

AUTHOR

TITLE

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SPONS AGENCY

PUB DATE

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AVAILABLE FROM

DOCUMENT RESUME

CE 029 111

Mallar, Charles: And Others

The Lasting Impacts of Job Corps Participation.

Program Evaluations. Youth Knowledge Development

Report 3.4.

Mathematica Policy Research, Princeton, N.J.

Employment and Training Administration (DOL),

Washington, D.C. Office of Youth Programs.

May 80

253p.: For related documents see CE 029 106.

Superintendent of Documents, U.S. Government Printing

Office, Washington, DC 20402 (Stock No.

029-014-00143-1, S6.501.

ED RS PRICE MF01/PC11 Plus Postage.

DESCRIPTORS Adolescents: Cost Effectiveness: Demonstration

Programs: *Disadvantaged Youth: Economically

Disadvantaged: *Employment Programs: *Federal

Programs: Females: Job Placement: Outcomes of

Education: Participant Characteristics: *Program

Effectiveness: Program Evaluation: Research: Research

Methodology: Research Utilization: Surveys: Training

Methods: Vocational Education: Youth: *Youth

Employment

'IDENTIFIERS *Job Corps: *Youth Employment and Demonstration

Projects Act

ABSTRACT

This study is one of the "knowledge')development"

activities mounted in conjunction with research, evaluation, and

development activities funded under the Youth Employment and

Demonstration Projects Act of 1977 (YEDPAI. It focuses on the impacts

of Job Corps participation on a large croup of participants after 18

months to two years. Significant benefits are documented, benefits

which exceed the costs to society of the investment in Job Corps.

Material covered in the study includes an overview of the Job Corps

and the evaluation: overall impacts on employment and related

activities: changes in family composition and employment-related

impacts for females with children: comparison of benefits and cost:

analysis of differential factors among participants and centers:

analysis of program expenditures: and generalizability of the

findings. (KC1

***********************************************************************

Reproductions supplied by EDR5 are the best that can be made

from the original document. ***********************************************************************

I L.

U S ME NT 0

EDUCATION 4 WC FAT

PIATtOPIA INS IYE OF El ION THIS DOCUMENT H..S SEEN REPRO.

OUCEO EXACTLY AS RECEIVED FROM

TrIE PERSON OR ORGANIZATION ORIGINATING IT POINTS OF VIEW OR OPINIONS

STATE() DO NO NECESSARILY REPRESENT OFF ICIAI - NATIONAL INSTITUTE OF

EOUCAT ION A sITION OR POLICY
U.S. Department of Labor

Ray Marshall, Secretary

Employment ai id Training Administration

Ernest G. Green, Assistant Secretary for

Employment and Training Administration

Office of Youth Programs

Material contained in this publication is

in the public domain and may be

reproduced, fully or partially, without

permission of the Federal Government.

Source credit is requested but not

required. Permission is required only

to reproduce any copyrighted material

contained herein.

3
YOUTH KNOWLEDGE DEVELOPMENT REPORT 3.4

THE LASTING IMPACTS OF JOB CORPS PARTICIPATION

A

Charles Mallar

Stuart Kerachsky

Craig Thornton

Michael Donihue

Carol Jones

David Long

Emmanuel Noggoh

Jennifer Schore,

Mathematica Policy Research, Inc.

May 1980

4
.0:

C

For sale by the Superintendent of Documents. U.S. Government Printing Office

Washington, D.C. 20402

5
OVERVIEW

Job Corps is the cornerstone of youth employment and training programs. Throughout its fifteen years of operation, the program has focused

on the most disadvantaged youth, offering comprehensive services including

vocational training, basic and advanced education, shelter, food, health

care, recreation, counseling and allowandes. The pricetai of this comprehensive approach is substantial--in excess of $12,000 per corpsmember

year in fiscal 1980--making Job Corps the most expensive manpower program

for youth.

Job Corps has been analyzed more than any other social welfare program

over the years because of its cost but also because it is the most

intensive investment in human resources, providing the best test of whether

comprehensive services can alter the lives of severely disadvantaged youth.

Studies have ranged in technical sophistication as well as in their

'conclusions.. There is general agreement that Job Corps has positive

impacts on participants, but disagreement whether the magnitude of benefits.

is sufficient to offset the high costs. Because Job Corps is so intensive,

the benefits should be large enough to be measureable despite the lack of

exactitude in assessment instruments. However, previous evaluations have

not been reliable enough to reach definitive conclusions, either lacking

adequate sample sizes or technical vigor.

In contrast, the following - evaluation represents one of the most

rigorous assessments ever mounted for a major employment and trainir9

program. Initiated by the Office of Policy, Evaluation and Research in. the

Employment and Training Administration, the evaluation trAcks a large

sample of 1977 corpsmembers and a carefully selected comparison group for

two years after the entry point, or an-average of 18 months after the

corpsmembers have left the prol-ram.

Significant benefits are cocumented:

Impacts of Job Corps during 12-18 month period after termination

o Percent time employed

Job Corps Control

Net

Difference

(civilian) .549 .471 + .078

o

o Earnings per week (civilian)

Probability of being

$82.17 $72.48 +$9.69

o in militaryProbability of having high

.091 .051 + .039

school diploma or GED .359 .109 + .250

o

o Probability in college

Number moves excluding

.026 .001 + .025

o Job CorpsPercentage receiving any

.409 .194 + .215

financial assistance .067 .120 - .053

o

o Probability of arrest

?robability of having

illegitimate child (total

.070 .078 - .008

post program period) .F1 .216 - .025

.
Further confirming the impact of the comprehensive treatment, there

are very significant differences in tha outcomes for program completers,

partial completers and early dropouts.

Job Corps Net Impacts for Males During the 12-18 month

Period After Termination

Percent of time

Program

Completers

Partial

Completers -\

Early

Dropouts

employed +.155 +.044 +.047

Probability of

military service +.087 +.058 +.032

Probability of having

a high school

diploma or GED +.399 + .143 + .049

Some previous studies have suggested a decay in Job Corps impacts over

time. The follow-up results indicate the opposite--most differentials

actually increase with time except for impacts on criminality.

Net Impacts of Job Corps by Months After Termination

0-6 6-12 12-18 18-24

Percent employed 0 + .012 + .051 + .078 + .090

Earnings +$2.02 +$6.00 +$9.69 +$9.03

Percent in military + .019 NA + .039 NA

Percent in college + .014 + 0.22 + .025 + .030

Percent receiving

financial assistance - .054 - .055 - .053 - .056

Number civilian

arrests in last

six months - .030 - .028 - .008 - .004-

These and other benefits--when valued, projected and discounted under

the most reasonable assumption--exceed the'costs to society of the substantial investment in Job Corps. ,While the study presents a variety of

alternative assumptions and resulting benefit-cost estimates, the "benchmark" assumptions yield a benefit-cost ratio of 1.38. Put another way, the

returns to society for each corpsmember have a present value which is

$1,927 above the costs of participation. While there are always uncertainties, the size of .this increment provides reasonable certainty that

the Job Corps investment in human resources is profitable.

Job Corps compares favorably with all other youth programs. The most

rigorous comparable assessment to date has been an analysis of the

supported work demonstration which provided structured and supervised work

experience to a youth population very similar to that in Job Corps. In

contrast to the positive post-program impacts for corpsmembers, participants in suppo..ted work realized very minimal gains relative to

controls. The social benefits did not exceed the costs under the same

assumptions as in this evaluation. In other words, work experience does

not have the same long-range impacts as iotensive education and training.
This. study is one of "knowledge development" activities' mounted in

conjunction with research, evaluation and development activities funded

under the Youth Employment and Demonstration Projects Act of 1977. The

knowledge development effort will result in literally thousands of written

products. Each octivity has been structured from the outset so that it is

self-standing but' also interrelated with a host of other activities. The

framework is presented in A Knowledge Development Plan for the Youth Employment and Demonstration Projects Act of 1977, A Knowledge Development

Plan for the Youth Initiatives Fiscal 1979 and Completing the Youth Agenda:

A Plan for Knowledge Development, Dissemination and Application for Fiscal

1980, 4 Information is available or will be coming available from these

various knowledge development efforts to help resolve an almost limitless

array of issues. However, policy and practical application will usually

require integration and synthesis from a wide range of products, which, in

turn, depend on knowledge and availability, of these products. A major

shortcominj of past research, evaluation and demonstration activities has

been the failure to organize and disseminate the products adequately to

assure the full exploitation of the findings. The magnitude and structure

of the youth knowledge development effort puts a premium on structured

analysis and wide dissemination.

As part of its knowledge development' mandate, therefore, the Office of

Youth Programs of the Department of Labor will organize, publish and

disseminate the written products of all major research, evaluation and

demonstration activities supported directly by or mounted in conjunction

with OYP knowledge development efforts. Some of the same products may alsb

be published and disseminated through other channels, but they will be

included in the structured series of Youth Knowledge Development Reports in

order to facilitate access and integration.

The Youth Knowledge Development Reports, of which this is one, are

divided into twelve broad categories:

1. Knowledge Development Framework: The products in this category

are concerned with the structure of knowledge development activities, the

assessment methodologies which are employed, the measurement instruments

and their validation, the translation of knowledge into policy, and the

strategy for dissemination of findings.

2. Research on Youth Employment and Employability Development: The

products in this category represent analyses of existing data, presentation

of findings from new data sourc,s, special studies of dimensions of youth

labor market problems, and policy issi.e assessments.

3. Program Evaluations: The products in this category include

impact, process and benefit-cost evaluations of youth programs including

the Summer Youth Employment Program, Job Corps, the Young Adult Conservation Corps, Youth Employment and Training Programs, Youth Community

Conservation and Improvement Projects, and the Targeted Jobs Tax Credit.

iii
k.' Service and Participant Mix: The evaluations and demonstrations

summarized in this category concern the matching of different types of

youth with different service combinations. This involves experiments with

work vs. work plus remediation vs. straight remediation as treatment

options. It also includes attempts to mix disadvantaged and more affluent

participants, as well as youth with older workers.

5. Education and Training Approaches: The products in this category

present the findings of structured experiments to test the impact and

effectiveness of various education and vocational training approaches

including specific education methodologies for the disadvantaged, alternative education approaches and advanced career training.

6. Pre-Employment and Transition Seriices: The products in this

category present the findings of structured experiments to test the impact

and effectiveness of school-to-work' transition activities, vocational

exploration, job-search assistance and other efforts to better prepare

youth for labor market success.

7. Youth Work Experience: The products in this category address the

organization of work activities, their output, productive roles for youth,

and the impacts of various employment approaches.

8. Implementation Issues: This category includes cross-cutting

analyses of the practical lessons concerning "how-to-do-it." Issues such

as learning curves, replication processes and programmatic "batting

averages" will be addressed under this category,as well as the comparative

advantages of alternative delivery agents.

9. Design and Organizational Alternatives: The products in this

category represent assessments of demonstrations of alternative program and

delivery arrangements such as consolidation, year-round preparation.fer

summer programs, the use of incentives, and multi -year, tracking of

individuals.

:O. Special Needs Groups: The products in this category present

findings on the Special problems of and the programmatic adaptations needed

for significant segments including minorities, young mothers; troubled

youth, Indochinese refugees, and the handicapped.

11. Innovative Approaches: The products in this category present the

findings of those activities designed to explore new approaches. The

subjects covered include the Youth Incentive Entitlement Pilot Projects,

private sector initiatives, the national youth service experiment, and

energy initiatives in weatherization, low-head hydroelectric dam restoration, windpower, and the like.

12. Institutional Linkages: The products in this category include

studies of institutional arrangements and linkages as well as assessments

of demonstration activities to encourage such linkages with education,

volunteer groups, drug abuse, and other youth serving agencies.

In each of these knowledge development categories, there will be a

range of discrete demonstration, research and evaluation activities focused

on different policy, program and analytical issues. In turn, each discrete

iv
knowledge development project may have a series of written products

addressed to different dimensions of the- issue. For instance, all

experimental demonstration projects have both process and impact evaluations, frequently undertaken by different- evaluftion agents. Findings

will be published as they become available so that there will usually be a

series of reports as evidence accumulates. To organize these products,

each publication is classified in one of the twelve broad .knowledge

development categories, described in terms ,of the more specific issue,

activity or cluster of activities to which it is addressed, with in

identifier of the product and what it represents relative to other products

in the, demonstrations. Hence, the multiple products under a knowledge

development activity are closely interrelated and the activites in each

broad cluster have significant interconnections.

This volume should be read in conjunction with ocher evaluqtions of

-Job Corps in Assessments of Job Crops PerforMance and Impactt; In

addition, Enhanced Work Projects- -The Sukoported'Work Approach for Youth includes anFIFE:Lion structured quite similar to this which indicates the

comparable benefits of a work experience approach.

Robert Tacioart

Administrator

Office of Youth Programs

o
CONTENTS

OVERVIEW

EXECUTIVE SUMMARY xi

I. INTRODUCTION

II. OVERVIEW OF JOB CORPS AND THE EVALUATION 6

A. THE JOB CORPS PROGRAM IN 1977 6

1. Institutional Setting 7

2. Enrollees in Job Corps .11* 9

3. Types of Services Provided at Centers . 10

4.-'Size of Job Corps 13

5. Current Trends 14

B. THE EVALUATION, DESIGN 16

1 Policy and ResearchIssues 17

2 Analysis of Participant4Impacts 18

3. Comparative Evaluation of Benefits and Costs 25

4. Evaluation Design 25

III. . OVERALL IMPACTS ON EMPLOYMENT AND RELATED ACTIVITIES 34

A. ECONOMETRIC PROCEDURES 35

1. RegressiOn Approach to Adjust for Differences

Between ,the Job Corps and Comparison Groups 36

2. Disaggregations of`Impact Estimates 38

B. EMPLOYMENT AND EARNINGS 44

C, INVESTMENTS IN HUMAN CAPITAL 55

1. Education-and Training of Civilians 56

2. Other Investments in Human Capital 62

D. DEPENDENCE ON PUBLICTRANSFERE'. . . 65

E. CRIMINALITY 9 69

F. SUMMARY AND CONCLUSIONS 69

APPENDIX TO CHAPTER III: ESTIMATION PROCEDURES

AND REPRESENTATIVE ESTIMATES 80

PAGE

IV. CHANGES IN FAMILY COMPOSITION AND EMPLOYMENT-RELATED

IMPACTS POR FEMALES WITH MILDREN '06

A. INITIAL FINDINGS FOR ZFFECTS ON FAMILY

COMPOSITION 107

B. ESTIMATES OF EMPL.CfMEmT AND RELATED IMPACTS

FOR FEMALES WIT! LAILDREN 114

C. SUMMARY OF FINDINGS 118

V. COMPARATIVE EVALUATION OF BENEFITS AND COSTS 119

A. BENEFIT COMPONENTS 125

1. Output Produced by Corpsmembers 125

2. Reduced Dependence on Transfer Programs . 132

3. Reduced Criminal Activity 134

4. Reduced Drug'and Alcohol Use 142

5. Use of Alternative Training and Educational

Programs 142

6. Other Benefits 145

7. Benefits After the Observation Period 145

vii

.11
CONTENTS (Continued)

Chapter

B. COSTS

1. Program Operating Expenditures

2. Opportunity Cost of Corpamember Labor

3. Nonbudgeted.Costs Other than for

Corpamember Labor,

C. OVERALL FINDINGS FOR NET PRESENT VALUE

D. SUMMARY AND CONCLUSIONS

Page

148

151

151

152

152'

161

VI. DIFFERENTIAL IMPACTS AMONG CORSPMEMBERS AND CEN1ZRS . 164

A. DIFFERENTIALS BY SEX AND FAMILY REpiONSIBILITI . . 165

B. DIFFERENTIALS.BY COMPLETION CATEGORIES 167

C. DIFFERENTIALS BY CORPSMEMBER CHARACTERISTICS

END PROGRAM TREATMENTS '172

'D. SUMMARY AND CONCLUSIONS 184

VII. ANALYSIS OF PROGRAM EXPENDITURES 186

A. OVERVIEW OF JOB CORPS OPERATING EXPENDITURES 186

1. Total Operating Expenditures 187

2. Average Operating' Expenditures 19Q,

B. DETERMINANTS OF OPERATING EXPENDITURES 192 ) 1. Enrollee Expenses 192

2. Operations Expenses 194

3. Staff Expenses 195

4. Work Project Expenses 196

C. SUMMARY AND CONCLUSIONS 197

VIII. GENERALIZABILITY OF, THE FINDINGS 201

A. REPRESENTATIVENESS OF THE SAMPLE AID CHANGES

IN THE CHARACTERISTICS OF CORPSMEMBERS SINCE

1977 202

B. THE VALIDITY OF THE COMPARISON SAMPLE STRATEGY 205

C.' DATA QUALITY 206

D. SUMMARY AND CONCLUSIONS 208

IX. SUMMARY AND CONCLUSIONS 209.

REFERENCES' . . 215

viii

12

1
REPORTS FROM AN EVALUATION OF THE ECONOMIC IMPACT

OF THE JOB CORPS PROGRAM

I. INTERIM REPORT

II. AN EXAMINATION OF JOB CORP.1 PARTICIPATION

III. FIRST FOLLOW-UP REPORT

IV. SECOND FOLLOW-UP REPORT

II. V. TECHNICAL REPORTS:

A. SAMPLE DESIGN AND IMPLEMENTATION FOR AN EVALUATION OF THE

ECONOMIC IMPACT OF THE JOB CORPS PROGRAM

B. SURVEY METHODS AND RESULTS FOR THE BASELINE AND FIRST

FOLLOW-UP INTERVIEWS

C. ECONOMETRIC MODELS AND METHODS FOR THE IMPACT ANALYSIS

D. A COMPARATIVE EVALUATION OF THE BENEFITS AND COSTS OF JOB

CORPS AFTER SEVEN MONTHS OF POSTPROGRAM FOLLOW-UP (superceded

by Technical Report K)

E. VALUE OF OUTPUT IN WORK ACTIVITIES

F. SPECIAL STUDIES OF RESOURCE USE AT JOB CORPS CENTERS

G. THE EXPERIMENT WITH PAYMENTS TO SURVEY RESPONDENTS (Superceded

by Technical Report I)

H. SURVEY METHODS AND RESULTS FOR THE SECOND FOLLOW-UP INTERVIEWS

i. MONETARY INCENTIVES FOR RESPONDING TO INTERVIEWS: EXPERIMENTAL

EVIDENCE FROM A LONGITUDINAL STUDY OF DISADVANTAGED YOUTHS

J. AN ANALYSIS OF PROGRAM OPERATING COSTS

K. A COMPARATIVE EVALUATION OF THE BENEFITS AND COSTS OF JOB

CORPS AFTER EIGHTEEN MONTHS OF POSTPROGRAM OBSERVATION

L. AN ANALYSIS OF NONRESPONSE TO JOB CORPS EVALUATION

INTERVIEWERS

M. COMPARISONS OF JOB CORPS WITH OTHER YOUTH PROGRAMS

N. RELATIONSHIPS BETWEEN DATA FROM THE JOB CORPS MIS AND

INDEPENDENT INTERVIEWS OF CORPSMEMBERS

NOTE All reports are available from the Office of Publications at

NPR for the cost of reproduction.

ix
EXECUTIVE SUMMARY

SECOND FOLLOW-UP REPORT OF THE EVALUMWON OF THE ECONOMIC

IMPACT OF THE JOB CORPSVIKOGRAM

This is the second follow-up report of the main findings from a

study designed to provide the Department of Labor with comprehensive

evaluations of both the short-term economic impact of the Job Corps program on participants and the benefits and costs of the program. The

information provided herein is based on the most comprehensive data yet

available to conduct a study of Corpsmembers. Comprehensive interviews

were first conducted in the spring of 1977 with a sample of Corpsmembers

then participating in the program and with a comparable group of disadvantaged youths who had not attempted to enroll'in Job Corps. At

periods 9 and 24 months after the baseline survey, reinterviews were

conducted with all of the youths in the comparison group and with Corpsmembers who had been out of the program for a long enough time to provide

useful postprogram information.

The hasedine survey obtained detailed information, on the demographic characteristics of the youths, their social-economic backgrounds,

and their work histories and related activities beginning six months

before the Corpsmembers enrolled in the program and continuing up to the

date of the interview, which represented approximately six months of program

experience. The two follow-up surveys continued to collect detailed

information on work histories and related activities during the postprogram period when Corpsmembers had been out of the program from one to

two years (an average of slightly over 18 months): Altogether, the data base

for this eNuation has both baseline and follow-up data on approximately

5,100 youths.

xi
The most important findings covered in this report can be highlighted as follows:

1. The findings on Corpsmembers' postprogram behavior are

generally consistent with the hypothesized economic impacts

and the important program goal of improving participants'

economic prospects. During the first two postprogram years,

we find that Job Corps is at least moderately successful

overall in achieving its desired effect of (1) increasing

employment and earnings, (2) improving future labor-market

opportunities, work experience, education, training, health,

geographic mobility, and military service, (3) reducing

dependence on welfare assistance and other public transfers,

and (4) reducing criminality.

'41

2. Some of the most noteworthy_ effects of Job Corps on the

behavior of former participants during their second post -

program year are (on a per Corpsmember basis): (1) an

increase in employment of over four weeks per year, (2) an

increase in earnings of approximately $500 per year, (3) a

4 percentage-point increase in military service, up from 5

percent to 9 percent, (4) an increase in the probability of

having a high school diploma or equivalent degree, from 11

percent to 36 percent, (5) higher college attendance

equivalent to an increase of nearly 5 full-time college

students for every 100 youths enrolled in Job Corps,

(6) a reduction in the receipt of financial welfare

assistance, amounting to nearly three weeks per year,

and (7) a reduction in the receipt of Unemployment

Insurance of over one week per year.

3. The positive, overall impacts generally persist

through the second year of postprogram observation.

The trend over the two-year postprogram observation

period appears to be an increase in program benefits

during the first few months (especially for,

employability during the transition from center

life to re-entering the regular labor market), and

then relatively stable effects through the rest

of the two-year period. The one exception is for

criminality, which shows relatively large reductions

in the very early post-program period that fade out

rapidly after Corpsmembers are out of the program

for a year. For employment and earnings we find very

stable estimates of gains among civilians, especially

program completers, for months 6 to 20 in the postprogram period--with no evidence of deterioration in

impacts over this period but, in fact, substantial

growth in program effects on employment and earnings

when the increasing military gains are incorporated.

xii
4. Differential impacts among Corpsmembers are found to be

associated with sex, family responsibility, and programcompletion categories. Relatively larger impacts for

males are found for the receipt of Unemployment Insurance

and the probability of being in military service, while

relatively larger impacts for females without children

are found for civilian employment and earnir. I, the

receipt of welfare, and edacation. The estimated Job

Corps impacts for females with children are generally

much smaller than for either males or females without

children. A substantial, positive correlation is

found between the estimated Job Corps impacts and the

proportion of the Job Corps program completed. Program completers consistently benefit the most, particularly

in terms of employment, earnings, and dependence on

welfare. Partial completers are found to benefit little

or not at all. Furthermore, these differential impacts

by completion category seem to be at least partially

attributable to the effect of staying in the program

longer and completing the program, which indicates the

potential for additional benefits to the program from

increased lengths of stay and completions.

5. We find additional differential impacts associated with

program and center-related variables, although the

causality of these differences cannot be attributed with

any degree of accuracy. Completing, a GED program is

posjtively associated with the beneficial impacts, and,

most importantly, the magnitude of this observed relatinnship is approximately the earns as that for receiving a

regular high school diploma. Differential impacts are

also found to be associated with the industrial type of

vocational training'received and the characteristics of

the centers that Corpamembers attended (e.g., the

sexual composition, which suggests that a more equal

sexual composition would increase program completion^_

and subsequent employment and earnings).

6. In an exploratory analysis we find significant Job

Corps effects in terms of reducing extra-marital children

and delaying family formation for females. Furthermore,.

our estimates of overall Job Corps impacts are probably

biased downward by not incorporating either the. Job Corps

effects on family composition or the employment and related

effects for females with children.

7. The, findings from a comprehensive evaluation of the social

benefits and costs of Job Corps suggest that public,invest-.

ment in Job Corps is economically efficient.. Our benchmark

estimate is that the value of benefits in fiscal year 1977

exceeded costs by almost $2,000 per Corpsmember, or by

approximately 39 percent of costs. Furthermore, the program is found to be economically efficient under a wide

range of alternative assumptions and estimates. Because
over 40,000 youths enrolled in Job Corps during fiscal

year 1977, our benchmark estimate of the net social

benefit for the entire program is approximately $80

million for that year.

8. We estimate that over 60 percent of the social benefits

come from increases in the value of output that Corpsmi-Abers produced. Another 30 percent of the social

benefits are attributable to reductions in criminal

activity among Corpsmembers, particularly burglary and

larceny.

9. In r-sessing the distribution of benefits and costs we

'Ind a net transfer from non-Corpsmembers as a group

(everyone in society other than Corpsmembers) to Corps -

members. The main economic benefits to Corpsmembers are

derived from increased earnings (approximately 70 percent

of the benefits) and transfers received while they are in

Job Corps. "'he main economic benefits to non-Corpsmembers

are derived from reductions in Corpsmembers' criminal

activities andin their use of transfer programs.

10. Sensitivity tests were undertaken for a wide variety

of the assumptions and estimates that are used in the

benefit-cost analysis, and these sensitivity tests

generally confirm that Job Corps is an economically

efficient program. 'With respect to the critical

parameter of future growth or fadeout of effects, we

find that Job Corps is an economically efficient use

of resources as long as the earnings effects do not

decay'more rapidly than 37 percent per year after our

observation period.

11. We find that center operating expenses per orpsmember

are determined largely by center size, the industrial mix

of vocational training offered; and institutional factors

associated with center administration (i.e., CCCs versus

'contract centers). Other factors such' as the geographic

location .and coeducational status of centers appear to

be somewhat important but are more difficult to isolate.

The largest differences in operating expenses are associated

with scale economies of larger center size up to approximately 600 Corpsmember positions at a center.

While the estimates are not exact and single numbers do not

generalize very well, after a careful analysis we are relatively confident

about the broad implications of our findings for disadvantaged youths in

general and for Job Corps in particular. In the report, we present detailed

discussions of all of the findings summarized above.

xiv

17
Chapter I introduces the report and briefly indicates the availability of other reports from our evaluation of the Job Corps program.

Chapter II provides an overview of the Job Corps program and our

evaluation. Chapter III presents overall findings on whether Job Corps

is achieving its hypothesized effects--especially with respectAo its

0 goal of improving Corpsmembers' economic prospects. Chapter IV

summarizes brief exploratory analyses of (1) the effects of Job Corps

on family composition and (2) the evidence to date on employment and

related impacts for females with children. The comparative evaluation

of Job Corps benefits and costs is sumilmArized in Chapter V. Chapters

VI and VII disJuss differential program :mpacts for, respectively,

benefits and costs. Chapter VIII examines 1.:!"1°F. with respect to

drawing general inferences about Job Corps from our data base. Finally,

Chapter IX offers some concluding remarks. In addition, 14 other

reports that document specific topics in more detail are available

from this evaluation.

xv
I. INTRODUCTION

This is the second follow-up report of a study designed to provide

the Employment and Training Administration ofthe U.S. Department of Labor

(DOL) with a comprehensive evaluation of the short-term economic impact of

the Job, Corps program. The two major issues addressed in this report are (1) the short-term economic impact of Job Corps on program participants,

and (2) whether the beneficial impacts of Job Corps as a whole outweigh the,

costs of the program. In addition, a number of related issues are also

addressed, including how long the program effects last, what differential

impacts exist among Corpsmembers and centers, and how expenditures and

resource use vary among centers.

1 The information on which this study is based is drawn primarily

from three surveys that collected relevant data both from Corpsmembers and

from a comparison sample composed of youths who did not participate in the

program but who were similar to Corpsmembers along other characteristics.

The first survey (the baseline interview) was administered during April-June

.1977 to a cross-section of Corpsmembers residing at centers and to the

comparison sample. The second survey (the first follow-up interview) was

administered approximately 9 months later to the comparison sample and co youths in the Job Corps sample who had been out of the program'for at least

5 months. The third survey (the second'follow-up interview) was administered

approximately 15 months after the first follow-up survey, again to the same comparison sample, but this time to youths in the Job Corps sample who had

been out of the program for.at least 12 months. Over 4,300 youths were

interviewed for the Second Follow-Up Survey, and, altogether, the data base

for this evaluation has both baseline and some follow-up data on approximately 5,100 youths.

1
The questions in the three surveys were designed to oi.tain

detailed longitudinal information on the following topics:

General demographic characteristics

Socioeconomic background

Employment and earnings

Military service

Education and training

Geographic mobility

Health status

R,ceipt of public assistance

Receipt of Unemployment Insurance and Worker's Compensation

Antisocial behavior

In addition, information was obtained on Corpsmembers' ratings of the

program (see Haller et al., 1978) and on where respondents could be

reached for future interviews.

The next chapter, Chapter II, provides an overview of the Job Corps . program and our evaluation. The first part of'Chapter II describes the

prograM setting in which the evaluation takes place, inclUding descriptions

of the goals of the program, the main Job Corps institutions, the types of

individuals who are served-by the program, the types of services provided

at centers, the size of the program at the time of our study, changes in

the program since our study *wan, and the current direction of changes in

Job Corps. In particular, this discusdion focuses on the program's goal

of increasing the employability of youths who begin the program with

severe employment problems, and on what approaches are used in Job Corps

to achieve tt-at goal. The second part of Chapter II summarizes our

2

20
evaluation design in the context of the two main analytical components:

the impact on participants and the benefit-cost comparison. This discussion

focuses on (1) the policy and research issues underlying the evaluation,

(2) our theoretical approach, and (3) the sample design and survey

implementation.

Chapter III presents overall findings on whether the Job Corps

program is achieving its hypothesized effects--especially with respect

to its goal of improving Corpsmembers' economic prospects during the first

two years after Corpsmembers leave the program. Specifically, empirical

findings are presented on whether Job Corps is successful in (1) increasing

employment and earnings, (2) improving future labor-market opportunities;

(3) reducing dependence on public assistance and other public transfers,

and (4) reducing criminality. Furthermore, this chapter presents the first

statistically reliable information on the duration of Job Corps impacts,

(that is, of course, under the limitations impOsed by an average of only

18 months of postprogram follow-up information).

Chapter IV summarizes (1) a brief, exploratory analysis of the

effects of Job:Corps on family composition'and (2) the evidence to date

on the employment and related impacts for females with children. Job

Corps effects on family composition have never before been analyzed,

and this chapter presents some of the first empirical evidence on the

relevance of this issue to youth traiiiing programs. In addition, as our

sample ages, more of the youths begin to take on family responsibilities--

hence, the impact on employment and related activities for females with

children takes on greater importance.

The comparative evaluation of Job'Corps benefits and costs is

summarized in Chapter V. This chapter develops estimates of the value of

3
Job Corps effects by combining the estimates of postprogram impacts from

Chapter III with secondary data on the values, or prices, of these effects.

Program costs are then estimated with financial data from the Job Corps

financial reporting system, from data we collected at individual centers,

and from the U.S. office of Management and Budget. Finally, estimates of

1 the program's net present value are made under a benchmark set of assumptions

about the rate of discount for future benefits and what happens to impacts

beyond the observation period, the sensitivity of which is then tested by

varying the most speculative of these underlying assumptions.

Chapters VI and VII discuss differential program impacts. In

Chapter VI, we examine differences in program effects among subgroups

of Corpsmembers and centers. In Chapter VII, we investigate differences

in expenditures and resource use among centers. In Chapter VIII we

examine issues with respect to drawing general inferences about Job Corps

from existing data. This chapter discusses the generalizability of the

findings presented in previous chapters. Specifically, we address issues

with respect to an interpretation'of our findings in the context of a

changing program, and the sensitivity of our findings to the econometric

procedures, imerview nonresponse, etc. Finally, Chapter IX offers some

concluding remArks. dr.

Currently availlble are several other reports that were generated

from this evaluation of the economic impact of the Job Corps program, and

the interested reader should consult all appropriate volumes.1/ These

additional reports are listed by title after the table of contents, and

many are referred to in the text of this report. There are three other

primary reports and fourteen supplemental technical reports.

The three additional primary reports include (1) the Interim Report

(which covers baseline data and assesses the adequacy of the comparison

22
sample), (2) An Examination of Job Corps Participation (which describes

Corpsmembers and examines their ratings of, the program), and (3) the First

Follow-Up Report (which covers the first postprogram findings based on the

First Follow-Up Survey). The fourteen technical reports cover a wide

range of topics that can be grouped intothree broad areas, as follows:

(1) supplemental reports on sampling'and survey procedures (four reports:

Technical Reports A, B, H, and L); (2) supplemental reports providing

details and derivations of evaluation findings and econometric procedures

from the main follow-up reports (six reports: Technical Reports C, D, E,

F, J, and K); and (3) supplemental reports on secondary topics, that are outside the main focus of the evaluation, but which are of important policy

interest and can be addressed with the data collected as part of our

evaluation of Job Corps (four reports: Technical Reports G, I, M, and N).

The four sampling and survey reports inude one on sample design and

impLimentation, two on survey methods and results, and one on nonresponse

to the interviews. The six technical reports providing additional detail

include one on econometric methodology, two on a comparison of benefits

and costs, one on the value of output in work projects, one on resource

usage at centers, and one on program operating costs. The four secondary

reports include two on an experiment with incentive payments to survey

respondents, one on comparisons between Job Corps and other youth programs,

and one on Job Corps MIS data.

1 " All these reports are available from the Office of Publications at

MPR for the cost of reproduction.

5 03
'II. OVERVIEW OF JOB CORPS AND THE EVALUATION

Job Corps is a major public program that attempts to alleviate the

severe employment problems faced by disadvantaged youths in the United

States--especially those who live in poverty areas.1/ Youth employment

problems, while always a serious concern, have recently become moresevere

because of increases in the teenage population and the persistent downturn

in our economy. During the time period covered by our analysis (1977 to

1979), an average of four out of every ten black youths between the ages of

16 and 21 who were in the labor market were unemployed. Moreover, recent

surveys have shown that in the poverty areas of central cities, among all

black youths fewer than two out of every ten have jobs.

A. THE JOB CORPS PROGRAM IN 1977

2/

. The Job Corps approach is to provide a comprehensive set of services

that include "vocational skills training, basic education, health care, and

residential support for young people who are poor, out of school and out of

work. Its aim is to break the cycle of poverty permanently by improving

1/The term disadvantaged is used throughout this report to refer

to the set of youths who have employability problems caused by their

socioeconomic background. Thus, it embodies several factors related to

age, educational level, income status, race-ethnicity, employment history,

previous social behavior, etc., that limit the ability of young men and

women to obtain and hold jobs.

?This This chapter,draws very heavily from three documents prepared

by the national Job Corps staff: (1) "Job Corps in. Brief, FY-77,"

1978; (2) "A Planning Charter for the Job Corps," 1978; and (3) "The

Expansion and Enrichment of the Job Corps," 1978. The interested reader

should refer to these papers, as well as to Kerachsky and Mallar (1978) and

Mallar et al. (1978), for further details. Also, Levitan and Johnston (1975)

have summarized the first ten years (1964-74) of Job Corps operations.

6
h1/ lifetime earnings prospects. Job Corps is designed to serve youths who

currently live in such debilitating environments that they must be

relocated tc residential centers to benefit from basic'educatiorr, vocational

training, and ancillary services.-2/ Education and training conducted in a

supportive environment are the key elements in the program's effort.to

improve the employability of disadvantaged youths, which, in turn, will

help them become more productive and responsible citizens,

1. Institutional Setting

The Job Corps program was originally established by the Economic

Opportunity Act of 1964. Control of the program was later transferred (in

1969) from the Office of Economic Opportunity to the Department of Labor

(DOL), and Job Corps was eventually incorporated without changes as Title IV

in the Comprehensive Employment and Training Act (CETA) enacted in 1973. While

there has been a general decentralization and decategorization of the other

employment and training pr' grams under CETA, Job Corps is still administered'

urimarily at the federal lrveq. Its incorporation into CETA, however, has

resulted in the transfer of direct responsibility for program operations and

center conLvacting to DOL's regional employment and training offices.

There are two basiz types of Job Corps centers: those operated

by private contractors selected in a "competitive bidding process which is

conducted by the regional offices, and those locited on public lands

1/Quoted from "The Expansion and Enrichment of the Job CorPs," U.S.

Departiment of Labor, Employment and Training'Administration, 1978, p.1.

?Some Some of the Job Corps centers in urbin:locitions have added a few

nonresidential tlots (i.e., positions) in the 1970s. However, the nonresidential components of Job Corps were not included in our evaluation

and, hence, will not be considered in this report. The nonresidential

components were excluded because the limited funds available for this

project would be more productively allocated to the residential slots, and

residential Corpsmembers include approximately 95 percent of all Corpsmembers.

7

A.
(predominantly in national parks and forests) and operated by the Department

of Agriculture or the Department of the Interior. The former centers are

usually referred to as )'contract centers," and the latter as "civilian

conservation centers" (CCCs). In fiscal year 1977, dr re were sixty-one

centers in operation, located in thirty-two states and Puerto Rico:

twenty-seven CCCs; two CCC-type centers operated by the Commonwealth of

Puerto Rico; thirty centers operated under contracts with priimte bnsineds

firms, nonprofit organizations, And state and local government agencies;

and two extension centers for advanced vocational training operated by

unions.11 Two contract centers had just opened during the yea(a new

center in Mississippi and a relocated center in New York).?-/.

, . Recruitment and placement activities are carried mit under, . contracts with employment service offices, various unions, local -Schodls,,

volunteer agencies such as Womep in Community Service, Inc. (WICS)'and-,

. . Joint Action. in Community Service, Inc; (JACS), and special private

agencied,3/ ,in addition to the efforts of -individual centers and the

1/- One extension center is operated byhe Brotherhood of Railway

Airline, and Steamship Clerks (BRAC) of the AFL/CIO;'the other is operated

by .Stewards Trainin4 and Recreation, Ina., of the Marine Cooks and Stewards

Union of the AFL/CIO. In addition, several unions (particularly in

construction trades) have contracts to provide training At the other centers

(at all CCCs and some of the contract centers).

2/Other centers have since opened and more centers are scheduled to

open in the near future to enable Job Corps to achieve its expansion goal

of doubling the number of slots compared to fiical year 1976 (see Section

E below). The focus df the MPR evaluation of Job Corps and this kgport is

on all centers operating in the;continerltal United Statcs during fiscal year

.0.977. Chapter III and Technical Reports A and B present more detailed

'discussions of the sample used in this evaluation.

2,/Peivate contracting agencies such as the separate GATE-house

(Graduate Aid to Employment for Ex7Corpsmembers) contractors were operating

in six large metropolitan areas (Atlanta, Baltimore, Los Angeles, New York,

Philadelphia, and Washington, D.C.), where many ex-Corpsmembers reside after_

they, leave the centers.

4

'
regional offices. These groups (especially the volunteer agencies and

special private agencies) often provide other support services to youths

who have recently left Job Corps, to facilitate their transition from

center living to a job and regular living arrangements.

2. Enrollees in lob Corps-1/

Data gathered is part of this evaluation snow mat the youths

served by Job Corps are severely disadvantaged. Prior to enrolling in

the program, the Corpsmembers.have relatively low levels of educational

attainment and employment. In addition, they have relatively high

incidences of welfare dependence and brushes with the law. The combined

effectof these Charac4ristica limits the ability of these young people

to obtain and hold productive jobs.

li review Of the socioeconomic characteristics of youths in Job

Corps dilrimg the spring of 1977 shows that:

4

Approximately one-half of the Corpsmembers were under age 18

at the time they enrolled,.and nearly one-quarter were 16

(the statutory age limits were and continue to be 14 to 21,

but very few youth* under age16 were then or are now

admitted).

Approximatily 70 percent of the Corpsmembers were male

(however, efforts are currently being made to increase

female participation to 50 percent of the.total.

'.enrollment).

Over 75 percent came from minority backgrounds - -59 percent

black, 11 percent Hispania, 5 percent American Indian,

and less than 1 percent Asian or Pacific Islander.

Between 85 and 90 percent of the Corpsmembers had not

completed high school at the time they enrolled.

illror a more detailed description of Job Corps participants, see.

Kerachsky and Haller (1978)

9

7
Almost all CorpSmembers had experienced difficulties in

obtaining and holding jobs; moreover, when they did find

work, the jobs usually did not pay well. Over one-third of

the-enrollees never had a job at which they worked at least

twenty hours per week and which lasted for at least one

month. In the six months before enrolling in Job Corps,

the typical Corpsmember was employed less than one-third of

the time and averaged fewer than 12.5 hours of work per week

at a wage rate ($2.81) that was only slightly above the

federal minimum.

Almost all Corpsmembers, had experienced poverty, welfare

dependence, or both; in the six months before enrolling in

Job Corps, over 90 percent either had incomes that were

below the poverty line or were receiving welfare assistance.

While many (28 percent) had attempted to enlist in the

military service, most of them failed to qualify (85 percent

of those who attempted).

Many Corpsmembers had a brush with the law--at least

38 percent had been arrested'at some time before enrolling,

and 19 percent had been convicted (about one-half of those

Corpsmembers who had been arrested).

3. es of Services Provided at Centers

To help Corpsmembers overcome the problems highlighted above, Job

Corps attempts to provide a comprehensive program that is flexible enough

to meet the individual needs and problems of each disadvantaged yotith.

The components of the Job Corps program include remedial education, high

school equivalency classes, vocational training, health care and edtication,

residential living, and counseling and. other ancillary services, each of

which is incorporated into a unified framework tailored to meet the

individual needs of each youth.

AEducation. The Job Corps education program has evolved with the ., intent of meeting the varied deficiencies in the backgrounds of Corpsmembers

and to enable them to proceed at the maximum pace commensurate with their

abilities. The education program includes remedial education (emphasizing

reading and mathematics), World of Work (including consumer education, driver

education, home and family living, health education, and programs designed

10

28
for individuals whose primary language is not English), and General

Educational Development (GED) for Corpsmembers who are academically

qualified. The GED certificate is recognized by state educational

agencies as the equivalent of a high school diploma. The Job Corps

encourages and emphasizes the GED program "for those who are

academically qualified. In fiscal year 1977, over 4,000 enrollees

were awarded the General Education Development Certificate."1/

Vocational Skills Training. Like the education program, the

training program at Job Corps centers'is designed to meet individual

needs and problems and to enable Corpsmembers to advance at the maximum

pace commensurate with their abilitiis. Therefore, all the training

programs provide for an open entrance and exit capability and are . continually being reviewed and revised in order to keep up with the changing

needs of Corpsmembers, as well as with the changing labor market.

There are some Aotable differences between vocational training

programs at CCCs and those at contract centers. The training programs at

CCCs are often operated by unions and tend to be of a "hands-on"

work-project nature, with actual construction and production taking

place.? In contrast, the training programs at contract centers are more

often operated by the centers themselves or by individual private subcontractors, and the training tends to be of a classroom-instruction,

shop-type, or "mock-up" nature, with some work-experience positions

available upon the successful completion of the training.

1/ Job Corps in Brief, FY-77, p. 3.

?Host Mos of the union instructors use curricula approved for the

first two years of the union's apprenticeship program.

11

29
healthsCare and Education. Comprehensive health services are

provided to all enrollees, including medical examinations (with follow-up

'treatments, if necessary), immunization, dental examinations (for all

CorpsmemberaWho stay at least ninety days) and dental treatment,,

professional help for emotional and other mental-health problems, and

instruction in basic hygiene,preventive medicine, and self-care. Health

education is also given high priority in Job Corps, with the, aim of

preparing ,Corpsmembers "to make responsible decisions regarding health

and health-related matters by providing them with relevant, factual

information."1/

Residential Living. Residential living is a key component of the

Job Corps program and distinguishes it from most other public employment

and training programs. The concept behind residential living is that the

target population comes from such debilitating environments that they need

a new'and more supportive environment to derive the intended benefits

of the vocational training and education courses The residential-living

program (including meals, health services, dormitory life, entertainment,

sports and recreation, center government, center maintenance, and other

related activities) is "planned to help new Corpsmembers adapt to center

life, mot vate and support constructive attitudes and lifestyles, and

prepare them to function effectively in the outside world. . It

.., involves such complex areas as relationships among racial and ethnic groups,

motivation of alienated or discouraged young people, adaptation to

unfamiliar group living situations, adult-youth cooperation in an

1/Job Corps in Brief, FY-77, p. 31

12

30
institutional setting, and the role of peer groups in influencing conduct

and attitudes." 11

Counseling and Other Ancillary Services. The centers provide

counseling services and residential advisors both to help Corpsmembers

plan their educational and vocational curricula and to motivate

Corpsmembers and create a supportive environment. Some of the other

support services provided by Job Corps (for example, during recruitment,

placement, and the transition to regular life and jobs) were discussed

above.

4. Size of Job Corps

At the start of fiscal year 1970 the Job Corps program was cut

back drastically in terms of both financial expenditurel and the number

of youths served. From then until fiscal, year 1977 the budget was held

roughly constant in nominal amounts, and the number of youths served

stabilized at approximately 21,000 to 22,000 slots (i.e., positions) and

45,000 new enrollees annually. However, over the same time period,

inflation greatly eroded the real purchasing power of that budget (held

fixed in nominal amounts); consequently, capital equipment was allowed

to deteriorate in order to serve the same number of youths within the

more restrictive purchasing power.

With the decision in fiscal year 1977 to renovate and expand Job

Corps (see the next section), the budget and number of slots in the

program were increased. In fiscal year 1977 the budget was increased

58 percent in nominal terms, to $274 million, while the applied funding

(i.e., the costs actually incurred rather than budgeted) increased by 23

1/Job Corps in Brief, FY-77, pp. 4 and 5.

13
percent, to $231 million. Some of the additional expenditures began to

be allocated to the planning of expansion, actual expansion, improvements

in services, staffing increases, and the repair and replacement of

capital "equipment that had been allowed to deteriorate during the previous

seven years. Similarly, the number of slots in the'provam rose 7

pereent in fiscal year 1977, to 22,225 slots, with the addition of one

new center and a small amount of expansion at some existing centers.

However, the number of new youths enrolled declined slightly in fiscal

year 1977 because the turnover rate fell; hence, the average length of

stay in Job Corps and the proportion of program completers increased

during that year (conceivably as a result of improvements made possible

by the additional resources).

5. Current Trends

The most recent trends in Job Corps are dominated by plans to

expand the program. Job Corps began increasing its capacity in fiscal

year 1977 in response to a congressional authorization to double the size

of the program as recommended by DOL--from its fiscal year 1977 level

of 22,000 slots to 44,000 slots by the end of fiscal yeal- 1978. The

national Job Corps staff expects to reach the full capacity enrollment

of 44,000 by the middle of fiscal year 1981, and the expansion is 75

percent complete now.

In deciding how best to provide the additional program slots,

the program has taken several factors into account. First, positions

are being allocated across the country according to the relative needs

of the various regions (need is determined from recent data on the

incidence of poverty and unemployment among youths). Second, the new

slots will be allocated among the two current types of centers, as well

14

32
as among other new types. The contract centers will receive the bulk of

the new slots; the CCCs will receive only about 5 pe.cent of the new growth

(thus, the proportion of CCCs is declining).

Another 5 percent of,the new slots will be devoted to industry

work-experience programs, and approximately 15 percent of the new slots

will be in the Advanced Career Training program, which allows qualified

Corpsmembers to attend junior college or technical school. (For the most

part, Corpsmembers in these programs will be,assignad, at least for

administrative purposes, to a regular contract center or CCC,)

In addition to the general expansion of Job Corps, DOL has

recently emphasized nine "improvement" areas for Job Corps, as follows

(quoted from the Employment and Training Report of the President, 1979,

page 170):

Arrangements have been made with prime sponsors and

with the Armed Forces for referrals to Job Corps.

Increased outreach is needed to recruit more young

women. Screening procedures should be simplified

wherever possible while they should also assure

that youth who can most benefit from Job Corps are

identified.

Only a minority of Corpsmembers complete training and

are placed directly into training-related jobs.

Better linkages are needed with the labor market.

The Industry Work Experience Program and a variety of

newly developed advanced career training programs

should assist in this effort.

New reading and GED programs have been developed

and are being introduced, and an experimental

college program has been implemented. An

Educational Improvement Effort will experiment with

alternative education approaches.

The world-of-work program to provide Corpsmembers

with jobseeking and jobholding skills needs to be

strengthened. Alternative systems are now being

tested.

15

33
A formula for living and readjustment allowances

has been derived in response to a congressionally

authorized increase while attempting to balance the

effects on recruiting, retention, performance reward,

readjustment, and equity. This formula is now under

review by Job Corps and the Department.

Comprehensive health services are provided at Job

Corps centers, and for 1 in 7 enrollees a previously

undetected health condition is identified.

Food in Job Corps centers is nutritionally sound but

apparently not as appealing to most Corpsmembers as

could be desired. The elimination of the statutory

ceiling on center operating costs will permit modest

increases in the amounts spent on food.

Needed and long-delayed improvements have been made in

center facilities to enhance the quality of life in

Job Corps.

The placement system must be reexamined in the coming

year with the aim of more closely linking jobs and

training as well as shortening the readjustment period.

B. THE EVALUATION DESIGN r The Job Corps program has survived over a dozen years of changing

attitudes toward social problems and has emerged as an important component

of the current effort to train and employ disadvantaged youths. However,

given the relatively large investment per enrollee, surprisingly little was

known about the magnitude of most of its economic impacts.1/ Of important

concern were the following issues: Does the program provide economic benefits

1/ Aside from program data, only the survey conducted by Louis Harris

and Associates between 1966 and 1969 has provided economic data on a

reasonable-size sample of former Corpsmembers (i.e., with reasonable

statistical precision). For a comparison group, however, both program data

and the Harris (1969) survey are limited to either early dropouts or "no

shows" (i.e., youths who signed up for Job Corps and were admitted, but who

never attended). Furthermore, the Harris data are obviously outdated given

the subsequent changes in both Job Corps and youth labor markets. (For

further details, see Louis Harris and Associates, 1969).

16 34
to participants and society? What are the magnitudes of the benefits? Do

some Corpsmembers benefit more than others? Do some variants of the program

work better than others? Does the total dollar value of benefits outweigh

the costs?

In order to design an evaluation to answer the above questions,

we constructed a detailed list of policy and research issues from the

hypothesized effects of Job Corps. (These issues are described in the

next section of this chapter.) We then used the policy and research

issues as a guide in developing an evaluation design (see further below).

1. Policy and Research Issues

The objective of our evaluation is to provide DOL with a comprehensive assessment of the economic impacts of the Job Corps program,

especially in the short term. To meet this objective, we must focus on

concrete policy and research issues. The issues addressed are as follows:

The extent to which the Job Corps program provides

early economic benefits to its participants in terms

of gains in employment, earnings, and other related

measures of economic well-being.

The extent to which participation in Job Corps

influences subsequent decisions to enter school,

training or work-experience programs, or the

military service.

The extent to which the Job Corps program affects

participants' receipt of transfer payments.

The extent to which participation in Job Corps reduces

various forms of antisocial behavior, particularly

criminal activities and drug abuse:

The existence of differential program impacts by type of

participant (age, race, sex, prior educational level),

by duration of participation in the program, by type

of center (size, location, operator), and by components

of the program (education received, vocational training, etc.),

17

35
The extent to which program benefits (both during and

after program participation) outweigh program costs.

o ' The, satisfaction of Job Corps participants with their

program experience, and their assessment of the

strengths and weaknesses of the program (see Mallar

et al., 1978).

The first five items on this research agenda show the range of

potential benefits to participants based on a human capital approach.

The magnitudes of economic impact will be measured by comparing the

postprogram behavior and economic status'of Corpsmembers with what they

would have been had the youths not participated in Job Corps. Item 6

requires valuing program benefits and comparing them to the costs. This

benefit-cost comparison (or set of comparisons, as we describe in Chapter V)

is achieved by aggregating estimates of'the dollar valuei of postprogram

benefits with similar measures of in-program benefits, and comparing the

total dollar value of program benefits to the total dollar value of program

costs. Thus, the benefit-cost research builds upon the impact analysis by

assigning dollar values to the estimated program-benefits-1/ Item 7 on

the research agenda, which focuses on Corpsmembers' perceptions of the

program impacts and their assessments of program-related experiences, was

completed as part of the First Follow-Up Report (see Mallar et al., 1978).

2. Analysis of Participant Impacts

The theory of economic choice underlies many studies of employment

and training programs. Thi theory suggests that individuals choose

1/A bepe'fit -cost analysis has the advantage o f.providing a summary

measure that din be used to judge the worth of the program. In addition

to providing inputs into the benefit-cost calculations, however, the

impact analysis shows program effects that cannot readily be valued in

dollar amounts, and allows readers to make their own judgments about the

value of various program benefits.

18

36
among competing demands on their time according to the wage rates they

can receive, other prices, and sources of nonemployment income, that are

available. A person's wage rate is hypothesized to depend on his or her

productivity, which increases with education and vocational training.

By providing education and vocational training, Job Corps should increase

participants' productivity, wage rates, employment opportunities, and

economic incentives to work. 1/ However, ins *tutional labor-market factors

such as the minimum wage may cause an excess supply of labor in the markets

for disadvantaged youths, so that another effect of Job Corps might be to

increase the employment of Corpsmembers (because they have increased

productivity) without affecting their short-term wage rates:?

The effects of Job Corps on several important postprogram

activities are studied in Chapter III. These activities can be

categorized into four broad areas. The first includes labor-market

activities, such as labor-force status, employment, hours worked, wage

rates, and earnings. Improvement in this area is considereci the primary

objective of Job Corps. The second area includes additional training

and education. Improvement in this area is an important short-term

objective because it is expected to increase employment and earnings in

the long-run. The third area is dependence on welfare and other public

transfers, and the final area is antisocial behavior. The anticipated

1/The effect of an increase in wage rates on economic incentives

to work is not completely unambiguous, because higher wages may afford.

some individuals the opportunity to spend more time in activities other

than work. However, most studies of youth labor supply have found work

effort to be positively associated with wage rates.

?Under this example, the minimum wage bolsters the average wage

rata received by disadvantaged youths who are employed. Job Corps training

helps former Corpsmembers get to the front of the queue for employment when

there is an excess supply of labor, in which case they, displace other disadvantaged youths in the short run.
, changes in'these last two areas are related to the changes in employment

and earnings (and in training and educational activities). As better

opportunities arise in the labor market (and scholastically), we expect

a decline in welfare dependence and antisocial behavior. The hypothesized

effects of Job Corps in each of the four areas are discussed briefly,

below and are summarized in Table II.1.

Employment and Earnings. The primary hypothesis is that, other

things being equal, young adults who obtain Job Corps training will become

more productive and, hence, will receive more employment and higher

earnings than those who do not.-1/ The increased productivity is expected

to lead to improved employability (as measured by increases in labor-force

participation, employment, hours worked per week, and the proportion of

weeks worked), as well as to higher wage rates and higher earnings This

hypothesis is based on previous research on the effects of training and

education on labor-market activities.

In addition to the short-term impacts after leaving Job Corps,

there may be subsequent reinforcing effects. For example, regular employment

often provides on-the-job training and a record of worker reliability that

l '1 Each Each of the hypotheses developed in this section is based on

the difference between the postprogram behavior of Corpsmembers and what

their behavior would have been in the absence of any Job Corps training.

For ease of presentation, the discussion is sometimes conducted as, if - there were no underlying differences between the Corpsmember'and comparison

groups, so that the impacts of Job Corps can be characterized by.direct

contrasts between the behavior of Corpsmembers and that of comparison7group

members. Of course, the statistical techniques used (see Chapter III)

attempt to compensate for any underlying differences between the Corpsmember

and comparison groups. In addition, all the hypotheses discussed herein are

weakened when allowances are made for.the alternative training and education

programs available to youths. In most of the, empirical sections of this

report we measure Job Corps impacts relative to what Corpsmember activities,

would have been had they not participated in Job Corps. In the absence of

Job Corps, many Corpsmembers would not have obtained zero treatment but,

instead, would have received some amount of alternative training and

education that they forego in favor of participating in Job Corps.

20 38
TABLE II.1

SUMMARY OF HYPOTHESES FOR PROGRAM IMPACTS ON PARTICIPANTS

Relative to if they had not gone into the programi participants will:

A. Employment and Earnings

1. Have more employment

2. Have more stable employment

3. Have higher earnings

4. Have higher wage rates

B. Investments in Human Capital

1. Be more likely

2. Be more likely

education in

of education

3. Be more likely

4.

5.

6.

to have productive work experiences

to return to school or continue their

other ways, especially at higher levels

to participate in training programs

Be hzalthier

Be more geographically mobile

Be more likely to qualify for military service

C. Dependence, on Welfare and Other Public Transfers

1. Have reduced receipt

N

of cash transfer payments

2. Have red4c.-.d receipt of in-kind transfer payments

D. Antisocial Behav:.or

1. Be less likely to engage in criminal activities

2. Be less likely to abuse drugs or alcohol

'/

39
is, in turn, rewarded with even higher lage rates and earnings in the future.

In contrast, the impacts of Job Corps could fad out over time as the

inflUence of the program becomes less significant the farther removed'

`former Corpsmembers are from theprogram in time.

Investments in Human Capital.- Economists define "investments.in

human capital" as current activities that lead to future increases in

productivity and, hence, eatningpotential (indirect program effects on

productivity and earnings). In this evaluation we will consider six-typesof investments in human capital: (1) work experience (see above), -(2)

education, (3) trainino), (4) better health, (5) giographiC mobility, and

(6) military service.

Work-experlhpce, educational, and training programs are important

placement alternatives to regular employment for JobCbrps terminees,

especially for younger Corpsmembers. Many of the younger terminees Could

still profit from additional work experience, schooling, and training

after they leave Job Corps, and, moreover, job placements are often

difficult for them. Therefore, both/the impact and benefit-cost analyses

must take into account any postprogram increases in such investments

in human capital. While increased employment and higher earnings continue

to be the long-run goals of both the program and participant, workexperience, educational, and training programs are important short7term,

intervening factori that may lead to higher employment. and earnings in

the future.

We hypothesize that former Corpsmembers have higher Irobabilities

of participating in work-experience, educational, and training programs

than comparison-group members. However, to the extent that Job Corps

succeeds in ,improving immediate postprogram labor-market opportunities

22 40

,

'4

I, 41
(thereby increasing the opportunity cost of time spent in human capital

programs), this hypothesis is weakened. In any case, it is expected that

former Corpsmembers will participate in higher-level programs than youths'',

in the comparison group and will be more likely to complete any given

level (i.e., more likely to obtain advanced degrees or certificates).

An additional hypothesis that falls into the category of human

capital investments is that participation in Job Corps increases

geographic mobility. This is supported by the fact that the Job Corps

program provides services that help terminees relocate to areas where

employment opportunities exist. We also expect that the additional

income from earnings, as well as the health education and treatments

provided by Job Corps, will lead to the improved health Status of former

Corpsmembers relative to youths in the comparison group.

The expected effect of Job Corps on enrollment in the military is

somewhat ambiguous. It is pot clear whether former Corpsmembers should

be more cr less likely to enlist in the military. They may be more likely

to enlist for the investments in human capital associated with military

service (e.g., for the vocational-training aspects and broadened experiences),

or they may be less likely to enlist because of the increased opportunity

cost of their time (i.e., better job opportunities in the civilian labor

force). However, we hypothesize that Job Corps terminees who take the

.Armed Forces Qualifying Test are more likely than comparison-group

members to pass the test. In addition, military service is an explicit

placement target for some Corpsmembers, and GED training in Job Corps,

should increase the' opportunity and rewards for enlisting.11

1/The new working relationship between Job Corps and the military,

which was initiated by the signing of a memorandum of undemtanding by

the Department of Labor and the Department of Defense on January 13, 1978,

should facilitate the enlistment of Job Corps terminees into the military

service.

23

41
. ,Dependence on Welfare and Other Public Transfers. A set of hypotheses that are closely related to labor-market activities concerns the

effects of Job Corps participation on welfare dependence. Of course, dbrpsmembers have reduced receipts from welfare while they are at the enters.

In addition, because of increased earnings after leaving,Job Corps, former

Corpsmembers are expected to receive fewer transfers-- including AFDC,

General Assistance, Food Stamps, public housing, Unemployment Insurance,

and Workers' Compeniationthan they otherwise would, have received during

the postprogram period.

These transfer-payment effects of Job Corps may be attenuated

(or possibly reversed) if participants become more knowledgeable about

the nuances of transfer programs and, consequently, increase their

participation in them. In addition, those Corpsmembers who seek

additional training or education in the postprogram period may obtain a

temporary increase Ln their transfer payments. Nevertheless, on balance,

the amount of transfer payments received by Corpsmembers is expected to

be lower than that received by the comparison group both during the grogram

and in the postprogram period.

Antisocial Behavior. Corpsmembers are expected to reduce drug

and alcohol abuse and have lower probabilities of engaging in criminal

behavior. While the Corpsmembers are at the centers, both of these

responses should be very large because their activities are restricted,

their behavior is closely monitored, and their material needs are

provided; consequently, they have few opportunities and small incentive

to engage in drug abuse or crimes. After Corpsmembers leave the program,

these reductions in antisocial behavioeare expected to continue, but

probably at a smaller rate. The postprogram reductions in antisocial

behavior stem from the entire Job Corps effort to increase employability

24

42
in order to promote more regular life-styles--from vocational training

and educational services to general counseling and center living.

Training and education are important because, to the extent that Job

Corps is successful in increasing the employability and the educational

abilities of Corpsmembers, legitimate activities become increasingly

more attractive relative to illegitimate activities.

3. Comparative Evaluation of Benefits and Costs,

The purpose of the comparative evaluation of benefits and costs

is to determine whether program benefits outweigh costs. Does society

have more goods and services at its disposal because of the investment

in Job Corps? The benefit-cost analysis, which is presented in Chapter V,

builds upon the results for participant benefits and compares the dollar

values of benefits and costs. Implementing a benefit-cost assessment is

especially difficult for programs such as Job Corps, which has a wide range

of potential effects that could occur over several years. The key elements

of our benefit-cost analysis are summarized in Chapter V and presented in

more detail in Technical Report K.

4. Evaluation Design

The previous sections. summarized the objectives in an evaluation

of the economic impact of Job Corps. It should be clear from the discussion

that in order to address all of the relevant policy and research issues

the study design must be comprehensive. This section summarizes the

evaluation design we developed to meet the objectives of the study.

Comparison-Group Methodology. During the design phase of this

study, much effort was devoted to selecting an appropriate comparison

group. Operational considerations prohibited the random assignment of

potential Job Corps enrollees to nonparticipant status. Therefore,

43
considerable effort had to be devoted to developing a suitable group of

nonparticipants with which to compare Corpsmember behavior, so that the

hypothesized impacts of the program could be tested and the magnitude of

the effects of the program estimated.

Within the constraint against randomization and the budget

limitations for the evaluation, we had to develop a sample design that

would both minimize bias and maximize efficiency in estimating the effects

of Job Corps. We had to take into account two important factors:

(1) that Job Corps was geographically clustered (in terms of the home

areas from which Corpsmembers came and in terms of where the centers

were located), and (2) that the Corpsmembers would already be enrolled.

The most efficient procedure called for sequential matching--first obtaining

appropriate sites and then finding appropriate youths within sites.

Finally, we included in the baseline questionnaire detailed information

concerning the Corpsmembers' socioeconomic backgrounds, so that the

comparability of the Corpsmember and comparison groups could be tested

and any differences controlled for in the statistical techniques.

,The first step was to eliminate program sites in order to reduce

the probability of self-selection biases (e.g., more highly motivated

youths enrolling in Job Corps). These were defined as geographical

areas that are saturated by Job Corps participation (i.e., high proportions

of eligible youths entering the program from a location proximate to a

center). The nonsaturated areas were then assigned selection probabilities

in proportion to their similarities to the home areas of Corpsmembers,

based primarily on the poverty and racial composition of the areas as

determined from Census data.1/

1/Socioeconomic characteristics of the home areas of recent Job

Corps participants were used to select the locations of the comparison-group

sites. The Primary Sampling Units (PSUs) were five-digit zip-code areas

26 44
Once the control sites were chosen, youths living in these areas

were assigned selection probabilities in proportion to their similarity

to Job Corps participants (actual participants and not just Job Corps

eligibles), based on their poverty, age, race, and educational status.

Names of youths were obtained from school dropout lists and from local

employment service offices. Together, these two sources provided an

adequate sampling list from the universe of youths who participate

in Job Corps. School dropout lists identified young recent dropouts who

were similar to approximately 70 percent of the Corpsmembers, and the

active files at local employment services provided older youths who had

been out of school for a longer time and were similar to the other 30 percent

of Corpsmembers. A sample of youths was then chosen to be included in

the comparison group, with females oversampled relative to their proportion in Job Corps to increase the efficiency of estimates computed

separately by sex.1/

in urban locations (Standard Metropolitan Statistical Areas) and threedigit zip-code areas in rural lc-ations. Data from the 1970 Census on

population density, geographic ly.Ation, percent_of poverty families,

mean family income, housing quality, percent of young (16 to 21) adults,

percent of Hispanic youths, percent of black youths, and youth unemployment

rates in the PSUs were used to assign selection probabilities. Regression

analysis was used to determine which of these variables would best predict

the home regions of Corpsmembers. For both three-digit and five-digit

zip-codes, the best predictor was the percent of families in the region

that had incomes below the poverty level and that were headed by someone

younger than 54 years of age. The second best predictor was the percent

of minority youths in the region. The percent of poverty families by

itself explained nearly 30 percent of the variances in the proportion of

Job Corps enrollments by zip-code regions. Probabilities of selection

were then assigned to all of the nonsaturated zip-code areas in the

United States, proportional to their similarity to the home areas of Job

Corps participants, as measured by the percent of poverty families.

Proportional stratifications by race and region of the country were

also maintained (see Technical Reports A and B for more details).

1 / The The target for the male/female ratio was 50/50 in the comparison

group, as opposed to the 70/30 split for the Job Corps sample in order to

obtain increased precision in separate estimates for females.

27

iv
This quasi-experimental design seems appropriate for our evaluation

and should lead to reasonably precise estimates of the economic impact of

the program. The assumptions needed for unbiased and relatively efficient

estimates of the program treatment effects seem plausible provided that

appropriate statistical techniques are used (see Chapter III))! There is

no overlap between the Job Corps and comparison-group samples, and the

Corpsmember sample should differ from the comparison group primarily in

terms of access both to information about Job Corps and to Job Corps

centers.-

2/

Sample Size and Selection. The sample selection procedures were

based on the necessity to balance the evaluation, operational, and cost

considerations.2/ For the Job Corps sample, the strategy we chose was to

select a random sample of participants in the program at a point in time.

For. analytical purposes, an enrollment-based sample would have had more

appeal, but would have been much more expensive, would have yielded many

early dropouts, and would have greatly delayed the research findings.

The sample size was targeted to be large enough to ensure a high

probability of observing statistically significant impacts if the "true"

Job Corps effects are large enough to be policy-relevant. Specifically,

1' "'Unbiased," as used here, means that, on average, the estimator Unbiased,"

should yield a value close to the "true" one. In other words, any biases

are both likely to be small and unlikely to affect the substantive findings

of our evaluation. Of course, all estimates are biased to some extent

because all statistical models are only approximations to reality.

"Efficiency" is defined to mean that the estimator has a smaller variance

than any other with the same (or smaller) amount of bias and using the same

data.

? /The comparison-group methodology is further explained and assessed

in Technical Reports A and C. See also Kerachsky and Kellar (1978).

3/The sample design is chosen to minimize the cost of obtaining the

desired level of statistical precision for estimates of Job Corps effects

(see Technical Report A).

28 6
the sample size was chosen to be large enough to have a 90 percent

chance of obtaining statistically significant Job Corps effects for

employment and related activities if the "true" net present value of Job

Corps training is positive (i.e., if the "true" benefit-cost ratio is

greater than one). If the Job Corps program is economically efficient,

we should (and do--see Chapter III) observe many statistically significant

effects for Job Corps on employment and related activities. The sample

size for Corpsmembers was targeted to be larger than for the comparison

group because of interest in estimating differential program impacts

among subgroups of Corpsmembers.11

To obtain an area probability sample, we used standard procedures

to randomly select approximately one-third of the Corpsmembers in the

program during April 1977. Each Corpsmember then at a center had an

equal probability of being selected (approximately one -third).? For

the baseline survey, 5,297 Corpsmembers were selected, and 5,133 of

those were interviewed (completed interviews) during April and May of

1977. The first follow-up sample included everyone from the original

sample who had ....eft.Job Corps before October 15, 1978 and, hence, who

had been out of Job Corps for at least five months (2,887 youths), and

2,417 Corpsmember interviews were completed. The second follow-up

sample included .'.i those who had left'Job Corps before April 15, 1978

."--

1/ For further details and justification, see Technical Report A.

1/There were only two exclusions from the sampling frame--youths

or centers outside the continental United States, and nonresident Corpsmembers. Justifications for these sample exclusions are presented

below.

29
(4,349 youths),*and 3,042 Corpsmember interviews were completed.1/ The

survey response rates for the Job Corps samples were 97 percent of

Corpsmembers sampled at baseline, 84 percent of baseline completions at

the first follow-up, and 79 percent of first follow-up completions at

the second follow-up (70 percent of the baseline sample, cumulative).?/

For the comparison sample, 1,496 youths were interviewed at baseline,

1,306 at first follow-up, and 1,267 at second follow-up.

Note that Corpsmembers who drop out of the program early are less

likely than program completers to be at a center at any point in time;

hence, they will be underrepresented by point-in-time sampling such as

ours.2/ With our point-in-time sampling, there are proportionally more

1/By the Second Follow-Up Survey, 85 percent of the baseline Job

Corps sample had been included in the follow-up sample. The 15 percent

who had not been included were composed of partial and full completers

with long stays in the program. Their exclusion is cost-efficient for

three reasons: (1) they have short postprogram experience, (2) our

sample sizes are adequate for these groups without them, and (3) leaving

them out approximately offsets any biases from a point-in-time survey

over-representing long-term stayers within the completion categories.

2/ Over time, the base for these completion rates include more and

more cases that cannot be interviewed (e.g., deceased youths), and the

real base shrinks over time. The completion rates are lower for the Job

Corps sample at the second follow-up, because one-half the sample was

contacted solely by telephone (for further details, see below as well as

Technical Reports 8 and H).

2/For our purpose, the fundamental difference between "enrollees"

and "participants" is that Corpsmembers who stay in the program a long

time (i.e., program completers) will be over-represented in participant

samples compared to all enrollees. Among Job Corps enrollees, a high

proportion (approximately 40 percent) leave the program within ninety

days. These early dropouts are replaced continuously by new Corpsmembers,

so that a sample of participants at a point in time has a higher proportion

of completers than found among enrollees. For the HPR evaluation of Job

Corps, a high proportion of program completers is desirable because the

impact of the program on early dropouts is probably negligible and

differential impacts for different programs and Corpsmembers could occur

among program completers. In Chapter III we explain how the observations

are reweighted to obtain unbiased estimates for enrollees.

30

Is
program completers in the sample of Corpsmembers than would generally be

obtained from a sampling ame based on all enrollees. For all enrollees

in fiscal year 1977, approximately 40 percent were classified as early

dropouts (terminated during their first ninety days), 30 percent were

classified as having completed only a portion of the program, and 30

percent were classified as having completed a full program; the corres -,

ponding percentages for our second follow-up sample are 9,.35, and 56,

respectively. To obtain estimates that are applicable to an average

enrollee will necessitate reweighting the data (see Chapter III).

Two exclusions were made from the Job Corps sampling frame- -

Corpsmembers in centers or from regions outside of the continental

United States, and those not residing at centers. This was done for

two reasons: (1) those two groups represent only a small proportion

of Corpsmembers (less than 1 percent and approximately 5 percent,

respectively); and (2) their backgrounds and program treatment seem

systematically different from the main group, which would probably

require separate analyses (which would necessarily be imprecise) and

would reduce the precision of estimates for the main group.

Data Collection. All three research topics require'in-depth data

on each sample member that must be obtained from interviews. Alternative

interviewing. strategies were examined to identify the method that would

best minimize response errors, cost, and analytical difficulties. We

adopted a strategy that consisted of administerinj three sets of interviews.

The first set was administered in person to Corpsmumbers at centers and

to the comparison sample in their homes. The purpfte of the first

interview was to collect baseline data on the pmbarttent period for

the Job Corps sample and similar data on the saw 1 r ;:ho V

31
comparison sample. The timing of these interviews represents a compromise between minimizing the length of the recall period and

maximizing the length of the observation period.

The first follow-up interviews were administered in person

approximately nine months after the baseline. The entire comparison

sample and a subset of the Job Corps sample were reinterviewed. The

subset of the Job Corps group included all members of the original

sample who had terminated from the program at least five months prior to

the first follow-up interview (an effective cut-off date of leaving Job

Corps by October 15, 1977). This criterion ensured an adequate period

of postprogram observation within the constraints of the overall budget

and the time permitted for the First Follow-Up Report (Mallar et al.,

- 1978). The first follow-up sample of Corpsmembers had been out of the

progran. for a time ranging from 5 to 9 months and 7 months on average

t. at the time of the survey.

For the Second Follow-Up Survey the Job Corps sample size (as

increased by extending the Cut -off date of Job Corps termination from

October 15, 1977; to April 15, 1978 (yielding reasonable sample sizes- -

including 1,462 additional Corpsmembers compared to first follow-up,

and excluding only long-term stayers who had been over-represented at

baseline). The second follow-up sample of Corpsmemberi had been out

of the program for up to two years and at least one full year and 18 months

on average at the time of the survey.

The only major changes in survey procedures between the Second

Follow-Up Survey and the two previous surveys were decisions to use a

mixed-mode interviewing strategy and to switch the primary interviewing

32 50
mode from in-person interviewing to telephone interviewing)' However,

in order to reduce the nonresponse problems associated with conducting

a telephone survey of a sample that contains a large proportion of

disadvantaged youths, in-person interviews were also attempted for

sample members who either could not be located by telephone or were not

responsive to the telephone interview. The cost-efficient design resulted

in all of the comparison-group sites and one-half of the Corpsmember sites

being targeted for in-person interviews if telephone attempts were unsuccessful.

The comparative evaluation of benefits and costs required additional

data. Data on program costs were provided by the. national Job Corps

office. These cost data were supplemented with information from Job Corps

centers (on center expenditures that were not included in Job Corps'

financial data) and the U.S. Office of Management and Budget (on federal

administrative costs that were not included in the Job Corps' financial

data). In addition, special studies were made of a random selection

of Job. Corps work projects to value the products and services provided.?

Finally, dollar values for many of the benefits had to be imputed froth

secondary data iources.a/

1/This survey process is described further in Technical Reports B

and H. The desirability of telephone interviewing at the second and

subsequent follow-up survey is documented in Technical Report H and is

supported by the analysis of nonresponse (see Chapter X and Technical

Report L).

?This work is described further in Technical Reports D, E, F,

and K.

3/ See Chapter V and Technical Reports D and K for more details.

33

51
III. OVERALL IMPACTS ON EMPLOYMENT AND RELATED ACTIVITIES

One of the primary goals of Job Corps is to help participants

improve their lifetime economic prospects. The hypothesized economic

impacts of Job Corps outlined in Chapter II are generally consistent

with that goal. In this chapter we present overall findings on whether

Job Corps, is successfully fulfilling the hypothesized effects and achieving its goal of improving Corpsmembers' economic prospects during the

first'two years after Corpsmembers leave the program. More Okecifically,

we provide empirical evidence on whether Job Corps is accomplishing the

desired effects of (1) increasing employment and earnings, (2) improving

future labor-market opportunities through work experience, education,'

training, better health, geographic 'nobility, and military service,

(3) reducing dependence on welfare assistance and other public transfers,

and (4) reducing criminality. Furthermore, in this chapter we concentrate

on the overall impacts of Job Corps and their occurrence and timing during

the first two years after Corpsmembers leave the program (only the breakdowns required for estimation purposes are shown and discussed here--that

is, by sex and program-completion categories)))

4

We begink7this chapter with a brief discussion of the estimation

procedures used. Detailed findings are then presented for each of the

four desired impacts listed above.

1/_in C apter VI we present a much more thorough analysis of the

differential acts of Job Corps among Corpsmembers and Centers, including

the differentia_ effects by sex and program-completion categories.

34. 54?
A. ECONOMETRIC PROCEDURESl/-

/

The data from the Second Follow-Up Survey should enable us to

obtain more accurate estimates of Job Corps effects than was previously

l

possible, both because the, 0Ostprogram observation period was extended

...4

and because additihnal Corpsmembers Were interviewed. At the time of

the First Follow-Up Survey, youths in the Corpsmember sample had been,out,.

of Job Corps, only from 5 to 9 months -- approximately 7 months on average:

4 By the time of the Second'Follow-Up Survey, however, they had been out

of the program from 1 to 2 years, with an average of slightly4over 18

months. Further, in the Second Follow-Up Survey, pOstprdgram interviews,

were attempted for 1,462 youths in the Corpsmember sample who had not been

out of Job Corps long enough to be interviewed productiirely at the time

of the First Follow-Up Survey.

The full padei,gf postprogram observations--incorporating data

from both the First and Second Follow-Up surveys--was organized into

quarterly aggregates for each youth in the sample. For example, the

employment variable was defined as the percentage of the quarter employed,

and was constructed for each indiv1dual youth for each quartirly time

period in which any data were available. The data were arrayed into

quarterly aggregates by calendar quarters according to the seasons--summer

(June, July, and August), fall (September, October, and November), winter

(December, January, 4nd February), and spring (March, April, and May)

) which differ from the usual fiscal quarters but provide better controls

for seasonality. The first quarter for whiCh we obtained postprogram

data for any youth was spring 1977, and the last was spring 1979.

1/

For more details, see the appendix to this-chapter and Chapter X'.

, .

35

53
' Therefore, for each youth we have up to nine quarterly observations in the

postprogram period that can be pooled in the statistical analysis, and the

overage is approximately,seven quarterly observations, including_ partial

quarters.

, d/

1. Regression Approach to Adjust for Differences Between the Job Corps

and Comparison Groups

As discussed previously (see Moller et al., 1978, Chapter IV),

before-after differences for participants are inadequate measures of

program impacts for youths and individuals whose pre-enrollment behavior

reflects a temporarydisequilibrium, where substantial changes in behavior

can be expected to take place in the absence of the program. Similarly,

program/cOmparison-group differences in sample means arc sve,plct, even.

for carefully designed sampling strategies, because unobserved differences

can be present in the absence of random assignments.

Generally, before-after differences would greatly overstate the

beneficial economic impacts of youth programs beCause youths are just

beginning to enter labor markets and their economic prospects would improve

substantially with age even in the absence of Job Corps. In contrast,Amth

the direction and magnitude of bias with simple program/Comparison-group

differences would be completely unknown a priori. Youths with the greatest

likelihood of participating in Job Corps couldbe dominated eithei by those who

perform inordinately well in training programs (i.e., large benefits) or by

those who would do especially poorly outside the program (i.e., low opportunity

cost to reducing their effort in the regular labor..market). Given these

competing factors in self-selection into the program, therefore, youths who

choose to participate in Job Corps could be more or less productive in

unobserved dimensions than Observationally similar participants.

36

54
Given the above considerations, it seems clear that a regression

approach is needed to control for both observed and unobserved differences

between the Job Corps and comparison groups. In our previous research

we relied on a relatively simple regression adjustment that was based

on the change over time in program-comparison differences in sample means

(or, equivalently, the program-comparison differences in'changes in sample

means over time), and which showed. that our basic findings were unchanged

c-r a wide range of more and less complicated techniques based on different

assumptions (see Mallar, 1979). However, the cAange-in-differences methodology assumes that if Corpsmembers had not gone into Job Corps the growth

rates in the behavioral variables of interest would be-the same Ln average

for th. 7orpamember and comparison groups--and such an assumption becomes

less tenable as the length of the postprogram observation is increased.

Also, with added observations (more degrees of freedom) and improvements

in computational procedures, Less restrictive techniques (which are more

complex computationally) become practicable. Therefore, in the analysis

for this report we use regression approaches..that control for both observed

and unobserved differences between the Job Corps and comparison groups, but

which have less restrictive underlying assumptions than the techniques used

previously.

The observed variables that are included in the regressions control

fOr the following differences: age (5 variables); pre-enrollment education

(3 variables); race/ethnicity (4 variables); pre-enrollment health (1

variable); seasonality (3 variables) and time L.ends (2 variables); and

pre-enrollment experiences with employment (1 variable), welfare (1 variable), illegal activities (1 variable), and drug usage (2 variables).1/

1/- In the appendix to this chapter we present examples of coefficient

estimates for the control variables and briefly discuss the influences of

these variables on youth employment and related activities.

37
In addition, we use an econometric methodology that has been developed

to control for unobserved differences between samples--specifically in

this application, to control for unobserved differences between youths

in the Job Corps and the comparison groups (for example, unobserved

differences in employability and work motivation)!.With the technique

used to control for unobserved differences, the basic procedure involves

modeling and estimating program participation and then including in the

regression equations for the behavior of interest a control variable that

is a function of the estimated probability of prgram participation-1/

With the econometric procedures outlined above we should obtain

unbiased estimates of the impact of Job Corps on patLicipant°behavior.-

2/

In principle, therefore, the estimates of :ob Corps effects presented in

this chapter are based on differences between groups of Corpsmembers and

comparison youths that have similar compositions in terms of both unobserved

and observed characteristics. These procedures should also enable us to

obtain unbiased estimates of what Corpsmembers' activities would have been

had they not participated in Job Corps (see Table III.1).

2. Disaggregations of Impact Estimates

While-the focus of t._. .s chapter is on the overall effects of Job

Corps on participant behavior, some disaggregations are needed in order

to obtain accurate overall estimates, especially for cases in which the

1

/For further details on the properties and implementation of these

econometric procedures, see Barnow, Cain, and Goldberger (1978), Heckman

(1979), Maddala and Lee (1976), Mallar (1979), and the appendix to, this

chapter.

2/We are using "unbiased" here to mean asymptotically unbiased,

and under usual assumptions the estimators have the large sample property

of statistical consistency.

38

56
unweighted sample over-represents some segments of Corpsmembers and

under-represents others. Two general types of disaggregations are

undertaken: (1) separate estimates of regression equations for subgroups

of the population that have completely different behavioral relationships

for the activities of interest, and (2) decompositions of the programtreatmsnt specification to capture hypothesized differentials in observed

Job Corps impacts.

Subgroups of the Population. In general, we have pooled observations across individuals and time to take full advantage of the panel

nature of the data (discussed further below). However, separate estimates

are computed for three subgroups of youths, based on their personal

characteristics: (1) males, (2) females who have no children present,

and (3) females who have children living with them. Our previous research

(see Mallar et al., 1978) found that the behavioral relationships of

interest were substantially different for these three subgroups, based

on statistical tests (Chow tests) for differences in parameters. With an

appropriate specification, however, we found that observations on youths

could be pooled together across other demographic classifications, such

as age, race/ethnicity, and marital status. 1/

Females were intentionally over-represented in the comparison

group in order to increase the precision of separate estimates for females.

However, the necessity of disaggregating the female subgroup by presence of

children was not completely anticipated, and, unexpectedly, the comparison

group over-represents females who have children living with them. Overall,

for the postprogram observation period, the Job Corps sample is composed

1/The The primary differences in behavior for these latter subgroups

can be captured with simple specifications (e.g., dummy variables for

age, race/ethnicity, and marital status).

39
of approximately 70 percent males, 23 percent females without children,

and 7 percent females with children present; the corresponding percentages

for the comparison group are 48, 26, and 26 percent, respectively. The

Job Corps proportions (70, 23, and 7 percent) are used for weighting

separate estimates to obtain the overall estimates of Job Corps effects.

As discussed more thoroughly in Chapter IV, the female subgroups

pose additional problems for analysis. First, we are only beginning to

explore the impacts of Job Corps on the fertility of Corpswomen (timing

of births, number of births, and illegitimacy rates), and further observation and research are needed on this topic. Potentially, some of the

largest impacts of Job Corps on females' behavior could come from decreases

in fertility (delayed timing of births, reduced number of births, and

decreased illegitimacy), which would increase employability and reduce

welfare dependence. Separate estimates based on the presence and absence.

of children completely miss the impacts of Job Corps on the family status

under which former Corpswomen are observed.

The second problem in the analysis of impacts on females is the

extremely small sample sizes and the concomitant instability'of estimates

for Corpswomen who have children living with them. For example, during the

postprogram period we observe only fifteen females who were early dropouts

from Job Corps and who had children living with them at the time of either

one of the two follow-up surveys. Not surprisingly, for the subgroup of

females with children the estimates of Job Corps impacts on employment

and earnings fluctuate erratically around zero and are sensitive to changes

in the specifications of the control variables in the regression equations

(see further in Chapter IV). For the purposes of the overall estimates in

the current chapter, we factor in zero impacts for finales with children,

40

58
rather than choose among erratic effects that in general are insignificantly different from zero in the statistical sense. Using zero effects

for females with children causes little harm to the overall estimates in

any case, because this group represents only 7 percent of the postprogram

sample of Corpsmembers and would be dominated by the other 93 percent

(i.e., males and females without children). In terms of the overall

impacts, a zero estimate for females with children undoubtedly causes

less bias than the omission of Job Corps impacts on whichever subgroup

in which Corpswomen are observed (i.e., with or without children).

Program-Treatment Specifications. Two disaggregations of Job Corps

statuses among participants are used to improve the overall accuracy and

to explicate the findings: (1) separate estimates by completion category,

and (2) interactions with the length of time since leaving the program.

The program effects are expected to vary across completion categories

and by length of time out of the program. Also, the postprogram sample

has distributions that are unrepresentative of all Corpsmembers in both

of the above dimensions (hence, which will require some reweighting),

and among Corpsmembers the postprogram observation period is shorter

-. the greater the length of stay is in the program.

As discussed briefly in Chapter II, our sample design overrepresentt program completers because youths who stay in JoblCorps for

a long period of time have a highe: probability of being at centers at

any_point in time and, specifically, when the sample was drawn. The

three program-completion categories used by Job Corps--program completers,

partial completers, and early dropouts--are convenient because data are readily available on their actual proportions among all enrollees. However, there is not a perfect correlation between length of stay in Job

Corps and these completion categories because, given the individualized

and self-paced nature of Job Corps instruction, some youths can complete

41

5
the program faster than others. A partial completer is defined as a Corpsmember who stays in the program for at least ninety days and who completes

a segment of the program, but not the entire program. Early dropouts are

defined as youths who terminate from Job Corps before the end of their first

ninety days at a center and who do not complete any part of the program.

For fiscal year 1977 the proportions of all Job Corps enrollees

who become program completers, partial completers, and early dropouts are

approximately 30, 30, and 40 percent, respectively. In contrast, the proportions of program completers, partial completers, and early dropouts in

our postprogram sample are approximately 56, 35, and 9 percent, respectively.

Therefore, in order to obtain impact estimates that are applicable to the

average for all Job Corps enrollees, we need to use our knowledge of the

"correct" proportions by completion status to reweight the observations.

Estimates are computed separately for program completers, partial completers, and early dropouts, and are then added together with weights

of 0.30, 0.30, and 0.40, respectively.1/

1/To obtain estimates that are representatie of all Corpsmembers,

we reweight the separate estimates by completion statuses as follows:

Estimated effect for All Enrollees =

0.30 (Estimated effect for Program Completers)

+ 0.30 (Estimated effect for Partial Completers)

+ 0.40 (Estimated effect for Early Dropouts).

In addition, note that the relationship between the unweighted estimate

for the sample and the separate estimates by completion categories is as

follows:

Unweighted Estimate for Sample =

0.56 (Estimated effect for Program Completers)

+ 0.35 (Estimated effect for Partial Completers)

+ 0.09 (Estimated effect for Early Dropouts),

which clearly shows how the unweighted estimate-over-represents Corpsmembers

who are completers. Because the estimated impacts of Job Corps are usually

much larger for completers, the effect of the reweighting to obtain estimates

that are representative of all enrollees (and, hence, giving completers

less weight than in the sample) is to lower the overall estimates compared

to the unweighted estimates.

42 60
As discussed further in Chapter VI, .ith the data available thus

far, we have not been able to obtain reliable estimates that control for

unobserved differences among Corpsmembers by completion categories, due

to identification problems in modeling completion simultaneously with

employment or other related behavior. Even though there may be some

biases among completion categories, however, the estimates for overall

impacts should be unbiased. (We know the "true" proportion in each

category.) Furthermore, the evidence (discussed further below) supports

the conclusion that the observed differences by completion category are

at least in part attributable to a program effect with completing.1/

Having quarterly data for up to two years of postprogram observation enables us to learn a great deal about the timing of impacts

after Corpsmembers leave the program. Our examinations of the timing

of effects has already been fruitful in identifying transition problems

as Corpsmembers leave the centers and re-enter the regular labor market.

Furthermore, with the Second Follow-Up data we will be able to begin

testing the alleged quick "fadeout," or "decay," of Job Corps effects

that have been supported previously wit less rigorous techniques and

less accurate data. Estimates of the interactions between completion

categories and length of time out of Job Corps are also important,

because we have fewer observations as the length of the postprogram

period increases, and because the observations that we do have for

the longest period are for youths who had shorter stays in Job Corps

on the average.

1 /

Briefly, we obtain statistically significant and moderatesized effects for the program as a whole; the estimated effects for the

group with near zero treatment (early dropouts) are close to zero;

we control for a wide range of important variables that are observed;

and the potential sources of remaining bias work in opposite directions.

43

61
We pool all of the quarterly observations for each individual

youth and estimate two t4s of specifications by length of time out

of the program--(1) 6-month averages (four variables for each completion

category), and (2) a more flexible continuous time pattern (eleven variables for each completion category).1/ The 6-month averages are presented

in tables, discussed extensively in the text, and form the basis for the

benefit-cost estimates in Chapter V. The more continuous time patterns

are presented in figures, and provide the most comprehensive evidence

both on the general timing of effects and, specifically, on the duration

of Job Corps impacts (how long they are maintained, how quickly they fade

out, or how much further they grow).

B. EMPLOYMENT AND EARNINGS

One of the most important goals of Job Corps is to increase the

employability of participating youths. As shown in Table III.1, the

economic prospects for these youths could be expected to improve somewhat

in the postprogram period as they age, even if they had not participated

-in Job Corps--especially when compared to their disadvantaged statuses in

the pre-enrollment period (see Kerachsky and Haller, 1978).i/ On an

absolute scale, however, the economic prospects for Corpsmembers are

not very good if they do not enter the program. For example, even by

1/ Correlations of individual errors over time are adjusted in a

two-stage error-components (or variance-components) model that should

yield greater efficiency than ordinary least squares (for mar., details,

see Maddala, 1971; . Nerlove, 1971a ands1971b; and Wallace and .ussain,

1969). The computational program used enables.us to include individuals

with varying lengths of time (essential for our application) and allows

individuzls to be missing periods of data (early, late, or intervening

quarters). For documentation of the computer program, see Avery (1975).

As noted above, seasonality and time trends across individuali are

specified explicitly in the regression equations.

?The The trend over the two-year postprogram period in Table III.1

is attenuated for the time period of 18 to 24 months after termination,

because the oldest Corpsmembers who were in Job Corps for a long time had

yet to be observed fer this time period; hence, they could not be included.

44

,62
ESTIMATES OF COILI,SHE'll.`.1:-'

Tev-.....ari.0 ,4771 g i. "71EF37--

Variable Aftw:

MILhs

After Termination

la to z. :'4.2ntbs After Tertu..aation

A. Employment and earnings of'civiliaas

Employed (fraction of time)

Hours worked per week

il .,';4 -112 0.471 0.453

Earnings per week (dollars)

7.. 1: lc D5 13.38 17.73

,7'.:(z a.38 72.48 73.73 Employed, inSchool, or in training

(fraction of time)

Employed or looking for work

0.470 0.519 0.562 0.555

(fraction of time)

Employed in union job (fraction of time)

0.653 0.682 0.701 0.715 0.063 0.070 0.083 0.082 Employed in PSE job (fraction of time) 0.044 0.051 0.052 0.042

B. Probability in military during

interview week . . 0.033 N.A. 0.051 N.A.-

C. Education and training of civilians

Probability of having high school

diploma or GED by time of interview 0.151 N.A. 0..09 N.A. In any school (fraction of time) 0.117 0.104 0.093 0.096 In college (fraction of time) <0.001 <0.001 <0.001 0.002 In high school (fraction of time) 0.093 0.073 0.062 0.056 In vocational or technical school

(fraction of time) 0.002 0.001 0.005 0.005 In other scho4 (fraction of time) 0.038 0.033 0.030 0.034 In any training program (fraction of time) 0.036 0.035 0.036 0.035 In CETA training (fraction of time) 0.027 0.030 0.031 0.030 In WIN training (fraction of time) 0.003 0.003 0.004 0.005 4 In other training (fraction of time) 0.003 0.001 <0.001 <0..001

D. Number

r.. of moves for civilians (mobility)

All moves across cities (cumulative) 0.089 N.A. 0.240 N.A. For job opportunities (cumulative) 0.024 N.A. 0.229 N.A. For education or training (cumulative) 0.012 N.A. 0.067 N.A. All moves across cities excluding Job

Corps relocations (cumulative) 0.081' N.A. 0.194 N.A.

E. Serious health problems for civilians

(fraction of time) 0.036 0.042 0.040 0.045

F.. Receipt of public assistance by civilians

Any financial assistance . f (fraction of time) 0.094 0.112 0.120 0.108 . AFDO (fraction of time) 0.059 0.079 0.084 0.078 General Assistance Or other

(fraction of time) 0.036 0.034 0.034 0.033 Food Stamps (fraction of time) 0.184 0.188 0.186 0.169 Public hauling (fraction of time) 0.079 0.105 0.098 0.094

G. Receipt of other transfers by civilians

Unemployment Insurance (fraction of time) 0.025 0.031 0.035 0.040 Workers' Compensation (fraction of time) 0.035 0.002 0.006 Training allowances'(per

six months in dollars) 24.55 15.59

.0.007

10.99 10.71

,H. Criminality

Total number of civilian

arrests per six months 0.092 0.075 0.078 0.081 Number of civilian theft

arrests per six months 0.056 0.047 0.046 0.051 Probability in jail during

survey week 0.022 N.A. 0.011 M.A. N.A. - Not Applicable

E/The entrieL' in this table are the appropriately weighte sample means observed for Job Corps participants minus the estimated effects shown in subsequent tables (Tables 11:.2 to 111.6). Most of the variables are estimated

for the civilian population only (see the notes for Tabi:s 111.2 to 111.6 for more in the variable definitions and computations).

45

er)
the end of the postprogram observation period their average annual

earnings would be well under $4,000 ($73.73 x 52 = $3,833.96), only

between 10 and 15 percent would have had a high school diploma or its

equivalent, almost none of them would have attended college, and many

would have been receiving public transfers (see Table III.1 for more

details).1/

In general, we find increasingly positive employment and earnings

effects from Job Corps participation over the course of the first year of

postprogram obaervation, as well as positive, stable, and statistically

significant overall impacts for Corpsmembers during the second year of

postprogram observation. As summarized in Table 111.2, the estimated

overall effects during their second year after leaving the program show

statistically significant gains in employment among civilian Corpsmembers

of over 8 percentage points, or over four weeks per year (the estimates

of impacts on weeks worked shown in Table 111.2 are for 6-month periods).-2/

The corresponding earnings gain during the second postprogram year is

approximately $500 on average for civilian Corpsmembers and is marginally

significant for statistical tests against zero.21

1/Variables and impact estimates are often presented in "fraction.

of time" units throughout this chapter.. These can easily be converted into

discrete time units through simply multiplying by the appropriate factor.

For example, to convert the numbers to weeks in a six-month period, simply

multiply by 26; to convert the numbers to months in a six-month period,

simply multiply by 6.

?/To obtain observed sample means for Corpsmembers, the program

effects (as in Table 111.2) would be added to the values had they not

participated in Job Corps (the values are given in Table III.1).

211,arger confidence levels than normal for two-teled statistical

tests and the one-tailed test equivalents are shown in all of our tables,

both to provide additional information in a convenient format and because

it can be argued that one-tailed tests are appropriate since participation

in Job Corps is not expected to have deleterious effects ob behavior.

46

64
MU 111.2

.a/ 8871111788 OP 308 CORPS INPICTS ON DIPLOM IND 11111111106-

Var table

9,

Unsighted Job Corps [Mats Job Corps 1t:ects Job Corps Effects .10 Corps Iffects

Postprograsbi 0 to 6 Months 6 to 12 Months 12 to 18 Months 24 Months le Ifler Termination liter Tenilation _itter Terminatij_i 1. WS

I. CiVilleit employment and earnings

1 Employed (fraction of time) 0.546 0.408 0.054 0,019* 0.114 ** **

Howl worked per week 21.74 1.52 2.51* 3.41i* 1.51"* a kernings per week (dollars) 82.81 -0,33 5,34 8.61 8.36

e Weeks worked per six months 14.20 0.22 1.39 LOP* 237****

Employed, in school, or in

training (fraction of till) 0,594 -COQ 0.011 0.024 0.063* a Employed or looking for work (fraction of time) 14 92 -0117 0.008 0.017 0,034

Employed in union job (fraction of time) 0.075 -0,035 .028 -0.033 -0.038

Employed in HI job (fraction of time) 0.054 -0.021 -0,007 0.001 0.01,0

2. Probability In military during interview weekg 0.101 0,0240 N.I. 0.056*** 11.1.

B. FINALE 11111011f CHILDREN

1, Civilians employment and earnings

['played (fraction of time) 0.392 0.021 0.057 0.090* 0.045

Hours worked per' week 14.05 1.16 0.95 3.23* 1.22

'Iarnings per week (dollars) 45.52 9.19 9.86 15.86** 13.79*

Weeks worked per six months 10.20 0.070 1.48 2.51** 1.18

ia Employed, in school, or in,

training (fraction of time) 0.490 -0.042 0.062 0.010 0.031

Employed or looking for work (Inc ion of inn) 0.620 0.179  0.121** * 0.146 * * ** 0.101**

Employed in union job (fraction of time) 0,042 0.012 0.021 0.032 0.048 **

e Employed in PSI job (fraction of time) 0.040 0.014 0.014 0.040** -0.002

2. Probability in military during interview week!' 0.021 0.018 H.I. 0.0003 N.1.
WU 111.1 (continuedi

Variable

1. Civilians employment and earnings

Employed (hullo of time)

o Hours worked per week

e Rarninge per week (dollars)

o Nooks worked per six months

e Employed, in school, or in

training (fraction of time)

o Employed or looking for work (fraction of time)

e Employed in union job (fraction of time)

Employed in PSI job (fraction of time)

2. Probability in military during interview veekfi 7.....

(benighted Job Corps Effects Job Corps Effects Job Corps Wide Job Corps Effects

Postprograki 0 to 6 Months 6 to II Months 12 to 11 Months 18 to 24 Months 8 le ifte After Termination After Termination After Termination

, C. OVERALL

0.472 0.012 0,05l* 0.078*** 0.090****

18.45 1.33 1.91* 3.17/4" 3.66*** 68.44 2.02 6.00 9.69* 9.03*

12.29 0.315 1.31* p weak 2.35****

0.529 -0.039 0.023 0.033 0.051*

0.691 0.029 0.034 0.045$ 0.048*

0.062 -0.022 -0.015 -0.016 -0.010 , 0.041 -0.014 4.002 0.010 0.007

0.077 0.019W N.A. 0.039***' 11.1.

*Significantly different from zero at the 00% level of statistical confidence (90% for a one -tail test). **Significantly different from 'era at the 90% level of statistical confidence (95%, for a on -tail test).

0) ***Significantly different Ira zero at the 95% level of statistical confidence (97.5% for *.one -tail test). **** Significantly different fro zero at the 99% level of statistical confidence' (99.5% for a one-tell test).

N.A. - Not Applicable

A

1 NOTES; The significepcs levels given here may be aliclitly,biased because the estimates of standird'errors used for the underlying significance tests

were obtained from a regression program which does not account, for the implicit heteroecedeetieity whoa controlling for unobserved differenies

between Corpsmembors and the comparison sample via the Nubian (1979)- approach: In practice,` however, the eignifiCance levels from, the

regreelion.program are usually very' clo:e to those from test stAtistics using unbiased ettirstis of standard errors, especially whin the

coefficients for the adjustment variables are statistically insignificant (which is usually the case here). Therefore, the eittificance levels

given here are Approximately accurate and are indicative of the true significance levels. -

67

- Most of the variables in this table' are estimated for the civilian population only. The one exception it for the probability of being in tilt military during the interview week.

kiThe unweighted postprogran sample means indicate the magnitude of the'veriablei for all

Observations (Job Corps And comparison groupet.

Corpsaenber sample means can be obtained by adding the effects shown is this table to the estivate' of Corpsseibers, activities bed they not

participated in Job Corp, (presented in Table 111.1).

ci- The estimates for Job Corps effect-on the probability of being; in the military are based on probit estimates with data from the interview . week for the two follow-up surveys. The estimates with the data from the First Follow-tip Survey are given in the "0 to 6 Months" column, and tee

from the Second Follow-Up Survey are given in the "12 to 10 Month" column. The unweighted postprogram sample mean given hers is from the Sec

Follow-Up data. ,
For two reasons, the estimates presented in Table 111.2 for employment and earnings gains among civilians understate the overall impacts

of Job Corps on employment and earnings. First, Corpsmembers have some

periods of re-enrollment'in the program during our "postprogram" period,

some of which are included with values of zero for employment, earnings,

and all other activities. Second, we find substantial Jab Corps effects

on the probability of being in the military service (large and statisti-

,cally significant).1/ The incidence of Job Corps re-enrollments being

included with zero values is relatively small (less than 1 percent of our

observations) and does not have a major effect on the size or statistical

significance of the estimated impacts (5 percent reductions in effects

at an extreme maximum). However, the inclusion of Job Corps impacts on

military service substantially increases the size and silaficance of the

estimated gain in participants' employment and earnings'

At the time of the Second Follow-Up Survey (approximately 18 months

after termination from Job Corps on average), we find nearly a 4 percentage

point increase in military service, so that, altogether, approximately 9

percent of former Corpsmembers are in the military service (base of 5.1

percent plus estimated impact of 3.9 percent yields 9.0 percent altogether).

With the estimated military effects added to those for employment during

the second postprogram year, we find a 9.7 percentage point increase in

employment overall (i.e., 0.076 attributable to civilian employment plus

0.021 attributable to youths in the military yields 0.097, or 9.7 percent,

'Our Our description of the econometric procedures used as regression "approaches' and regression "equations" are meant in the general sense

of the terms. In fact, all the probability models with binary dependent

variables (e.g., the prIbabilities of military service, of having a high

school dipAcea or OlD, and of being in jail) were estimated with prbit

maximum likelihood techniques.

49
altogether),1/ and a more than 5-week increase in annual employment

(0.097 x 5i * 5.04). Similarly, assuming that the youths in the military

earn $8,000 per year on average,31 the overall gain in earnings for the

second postprogram year would be approximately $606.66 (i.e., $442.92

attributabl.: to civilian employment plus $163.74 attributable to military

service yields $606.66 altogether,3/ compared to $486.72 for civilians).

Other Job Corps effects presented in Table 111.2 are for civilian

activity rates (employment plus related activities), employment in union

jobs among civilians, special public service employment (P5E) jobs under

CETA for civilians, and disaggregations for males and females without children.

By the end of the postprogram period, there are moderate-sized (approximately

5 percentage points) increases in civilian activity rates of marginal

statistical significance, as evidenced by both the fraction of time

employed, in school, or in a training or work-experience program and the

fraction of time employed or looking for work (an approximation to the

usual definition of labor-force participation). There are virtually no

effects on either union employment or PSE employment. Finally, the Job

Corps impacts on employment and earnings are similar for males and females,

except for slightly larger gains among civilians for Corpswomen and much

larger gains in military service for Corpsmen.

1/(0.910) (0.5) (0.078 + 0.090) = 0.076; (0.039) [1.0 - (0.5) (0.471 +

0.453)] * 0.021; and 0.076 + 0.021 0.097.

1/More careful valuations of military gains and estimates of

fringe-benefit increase's are developed and computed for the benefitcost analysis in Chapter V.

2/(0.910) (0.5) (52) ($9.69 + 59.03) = $442.92; (0.039) ($d,000 -

(0.5) (52) ($72.48 + $73.73)] *1163.74; and $442.92 + $163.74 = $606.66.

5/(0.5) (52) ($9.69 + $9.03) * $486.72.

50 7o
Figures 111.1 through 111.4 provide more details on the timing of

Job Corps impacts on participants' employment and earnings during the

postprogram period. The findings for the early postprogram period are generally consistent, with those reported earlier (see Mallar et al., 1978).

After some initial downfall during the transition from center life to the

regular labor market (and after having been out of the regular labor market

from a few days for early dropouts to up to two years for program completers),

the Job Corps effects on employment and earnings become increasingly positive

over time. The estimates average out to near zero for the first 6 months

of postprogram observation and then become positive (see Table 111.2, also).

.(The sources of Job Corps impacts still appear to stem from those other

than job placement.) Furthermore, the current findings are very similar to

those reported earlier. (Any small differences are primarily attributable

to the greater precision in the current estimates due to added observations

and, a longer observation period to help control for spurious, non-Job Corps

influences.)

The most interesting new finding from the extended postprogram

observation period is the, relatively stable estimates of employment and

earnings gains among civilians, especially program completers, for months

6 to 20 in the postprogram period. There is no evidence of a deterioration in impacts over this period--in fact, if the increasing military gains

were incorporated, we would show substantial growth in program effects on

employment and earnings up to the end of postprogram observation period.

We find no support for the fadeout that was previously inferred (see

1 " The The figures end at month 21 of postprogram observation, because

we have too few observations to provide reliable estimates beyond that

point. The more erratic fluctuations for the early dropout group can

be attributed to the small number of observations.

51
FIGURE III.1

ESTIMATES OF TIME PATHS OF NET INCREASES IN PERMIT OF TD EMPLOYED FOR MALES

1102

IOL

FTWANT 01 TIME MATZO

Mo. .... ..... ......... .

/

got /

1102

*OHM OUT OF Jet

ktIO 1.18"" 1.02 $1.02 ULM $1.1111 MAIO 10.02 10.00

manna coorezros

FORM% CUNFLCTERS

........ LMMLT onorour,

(relative to not participating)

FIGURE 111.2

ESTIMATES OF TIME PATHS OF NET INCREASES IN PERCENT OF TIME EMPLOYED FOR FEMALES WITHOUT CHILDREN

1102

302

202

102

ICACENT Of TIME LPOPLOTCO

102 r

202

302

qui

" "

40" AOMMI OUf or JOU COMP,

X5.0/ 1.00 0.02 V.00 10.00 / 10.00 10.00 MOW 10.00 10.000' 10.00

\ /

\ ,' . \ /

/

.

rmoomm cumftcums

asrtaL comrtruns

COAL, OPOOUTI

(relati..4, to not participating)

52
FIGURE 111.3

ESTIMATES OF TIME PATHS OF NET INCREASES IN EARNINGS FOR MALES

Cluirelmel PLR WUX

/ / site \ / '',. / /. \. . ...... N'''. .- ..... 14 -------- C"..;......-- .., .' >

.... .

* is 1 ,1 e LW LW LW coo moo tam m.o. 10.01 moo os.00 moo , e /

t' ... ROOM OttreW

It .; t .,., - AS CORPS

t e ",....

I**.

MOM MUMS

=rums

DROPOUTS

(relative to not participating)

FIGURE 111.4

A ESTIMATES OF TIME .PATES OF NET INCREASES IN EARNINGS FOR ?MALES WITHOUT CHILDREN

WHIM PER KIX

.. ..

..b Of\ fle 440

...41.ft".

11... 04'

0 0 ft 711104;"". "4"fte .... 04'

lig

1 0""

/ i ,,, \ \ . /' \ /

. ) LW 1.01 0.01 1111.0110 ' 31.011 MOO 111.011 111.00 110.011 MOO i \ / \ glieeJOS CORPS

TR, Out OP

Ito \.

---"ROORolee CONII.STCRS

PORTERI. CORPIATZRS

DROPOUTS

(relative to not participating)

53 73
Goldstein, 1972) from comparisons of Cain's (1968) 6-month findings to

Woltman and Walton's (1968) 18-month findings. This is not particularly

surprising, since the program has undoubtedly changed, and since both

of these earlier studies were based on much less adequate data that

prevented researchers from undertaking the kind of rigorous statistical

analysis which underlies our findings.

The data in Figures III.1 through 111.4 also show the differences

by completion category that will be examined in more detail in Chapter VI.

Underlying our moderate overall effects are very large gains in employment

and earnings for program completers, and modest to zero gains for Corpsmembers who drop out before finishing the program. In general, aside from

program completers, only female Corpsmembers who partially complete the

program show statistically significant increases in employability.

Before leaving our discussion of the impacts of Job Corps on

employment and earnings, some potential anomal es lurking behind the

numbers need to be highlighted. First, fro the estimated effects on

employment and earnings, we can infer that #.4),Jre are little if any gains

in hourly wage rates. However, this could I), wy one of three

factors: (1) the inclusion of otherwise ;ess ah' youths among employed

Corpsmembers, with the increases in employment i military service,

(2) the failure to include the gains in .artirm," ..aong youths in the

military service, and (3) effective cons4,,4,'., in youth labor markets,

such as minimum-wage legislation, that tend to equalize obser)ec; hourly

wage rates at young ages.

Secone, while the data from the week prior to the Secuhl 7ol1ow-Up

Survey are generally consistent with the findings repor and discussed

in this section, there is one notable exception--more negative earnings

effeco. or wnles who did not finish the Job Corps progra.A. This could

54
be a spurious phenomenon (perhaps even causing downward bias in all of

the estimated impacts on earnings through the positive correlation of

current fluctuations and recall errors, sometimes referred to as "telescoping"), or the exception could be indicative uf a quicker and more

substantial fadeout of effects in the postprogrsm period, just beyond

what we have observed so far.

Finally, in Chapter X we address othr issues that affect the

generalizability of the findings, such as cdlcation and training received

by comparison group members (and, hence, w1:, are obtaining program treatments of sorts) and the effects of survey .-nresponse on the accuracy of

estimates. However, as will be discussed in Chapter X, both of these

potential problems in generalizing our findings appear, if anything, to

cause us to underestimate the impacts o. Job Corps (xi the employability

of former participants.

C. INVESTMENTS IN HUMAN CAPITAL

Another goal of Job Corps is to increaL.e participants' future,

as well as short-term, employability (indire%.; program effects on

productivity and earnings). Curre7q activities that lead to future

increases in productivity, employment, and earnings are defined in

economics literature as "investments in human capital." Work experience is one type of activity that normally leads to increased productivity

and employability in the future!. Therefore, the short-term increases in

employment and earnings for former Corpsmembers discussed in the previous

section ire also indicators of posii:ve effects on investments in human

capital. In this section we examine Job Corps impacts on participant

education, training,, and other activities that could also potentially

lead to future gains in employment and earnings among Corpsmembers.

55
I. Education and Training of Civilians

as discussed above in Chapter II, the a priori basis for expecting

increased postprogram investments in human capital for Corpsmembers in

terms of.education and training is more ambiguous than for employability

and other forms of investments in human capital, for at least two reasons.

First, education and training are provided in Job Corps, reducing both

the need for and retumr to poatprogram education and training. Second,

increased employabilP.ly in 441e short-term provides inventives to engage

in work activities which are alternatives to further education and training.

The findings for Job Corps effects on education and training are

presented in Table 111.3. They show (1) a very large and statistically

significant increase in the probability of having a high school diploma

or equivalent degree (especially when all of the General Educational

Development, GED, degrees obtained through Job Corps study are included

in the Second Follow-Up data); (2) moderate-sized and statistically

significant increases in college attendance and decreases in high school

attendance; and (3) small but marginally significant reductions in training.

There are also small and marginally significant increases in enrollments

in vocational and technical schools that are almost exactly matched by

reduced enrollments in other miscellaneous educational programs (mostly

adult education courses).

Overall, by the Second Follow-Up Survey there is a 25 percentage

point increase/in the probability that Corpsmembers have a high school

diploma, GED, or equivalent degree. The large increase in high school,

GED, and equivalent degrees among Corpsmembers more than explains the

approximately 5 percentage-point reduction in high school attendance.

College attendance shows a statistically significant increase of from

2 to 3 percentage points among Corpsmembers, or the equivalent of an

56 7G
TAILS 111.3

ISTINATIS OP J08 CONS IFFICTS ON EDUCATION AND TRAINING Of CIVILIANS

Unsighted

Postprogramal

Variable Sample Mean- 1

Job Corps Effect. Job Corps

0 to 6 Maths 6 to

After Termination After

Effects

12 Nonths Termination

Job Corps Effects

12 to 18 Maths

After Termination

Job Corps Effects

18 to 24 Months

After Termination

=1.1MMMIIIME A. MALES

I. Probability of having high school ki diploma or 018 by time of interviewv 0.173 0.056  N.A. 0.1117** ** N.A.

2. In any school (fraction of time) 0.058 -0.064**** -0.017* -0.049*** -0.048*** In college (fraction of tip) 0.013 0.015 0.021** 0.0250** 0.025*** In his school (fraction of time) 0.021 -0.066  -0.054** 0 -0.66**** -0.055**** In vocational or technical school

(fraction ;flip) 0.012 0.006 0.013 0.004 0.001 In other school (fraction of time) 0.015 -0.020* -0.017A -0.022AA -0.020AA

3. In any training program (fraction of time) 0.026 -0.014 -0.00i -0.017 -0.010 In CITA training (fraction of tine) 0.013 -0.021*** -0.019AA 0.022aa* -0.011 In WIN training (fraction of time) 0.0002 -0.001 -0.001 -0.002* -0.001 In other training (fraction of tin) 0.005 -0.001 0.004 0.003 0.002

. FIRMS WITHOUT CHILDRIN

I. Probability of having high school

diploma or 010 by time of intorvievi

2. In any school (fraction of time)

0.349

0.109

0.057****

-0.039

N.A. 0.040

0.533****

0.021 0.046AA 0 In college (fraction of time) 0.037 0.016 0,031* 0.031 0.0540** In high school (fraction of time) 0.032 .0.054asso -0.031A -0.046*** -0.048AAA

In vocational or ticippical school

(fractip of time) 0.024 0.021 0.045  0.0 42** * 0.059****

In other school (traction of time) 0.020 -0.027AA -0.001 -0.001 -0.0001

3. in any training program (traction of time) 0.031 0.003 0,033 ** 0.010 -0.013 In CITA training (traction of time) 0,017 -0.003 0.009 -0.011 -0.0240 In WIN training (fraction of time) 0.002 -0.008* -0.011*** -0.013*** -0.014*** In other training (fraction of ties) 0.003 0.010* 0.025**** 0.027  0.010A

77
111.E 111.3 (continued)

Variable

Unweigbted

Postprogram

a/ Sample MeanJob Corps Effects

0 to Is Months After Termination

Job Corps Effect. 6 to 12 Months After Terminati'

nib Corps Effects

1 to 18 Maths

er Termination

Job Corps Effects

18 to 24 Months After Termination

C. OVERALL

Probability of having high school

diploma or 0(0 by time of interview-1 0.201 0.02** ** N.A. 0.250 * * ** N.A. In any school (fraction of time) 0.066 -0.054**** -0.017 -0.030*, -0.019

In college (fraction of time) 0.018 '0.014* 0.022*** 0.025*** 0.030 

In high school (fraction of tame) 0.022 -0.059** ** '-0.045  -0.049** ** -0.049 

In vocational or technical school o (fraction of time) 0.014 0.009 0.019** * 0.012* 0.014*

In other school (fraction of time) 0.015 -0.020*** -0.014* -0.017** -0.014**

In any training program (fraction of time) 0.025 -0.010 0.003 -0.010 -0.010

In CETA training ( fraction of time) 0.013 -0.015** -0.011* -0.018*** -0.013*

In WIN training (fraction of tine) 0.001 -0.002* -0.003a** -0.004  -0.004** *

In other training (fraction of tine) , 0.004 0.001 0.008* 0.008* 0.004

*Significantly different from zero at the 80% level of statistical confidence (90% for a'ona-tail test).

**Significantly different from zero at the 90% level of statistical confidence (95% for one-tail test),

***Significantly different from zero at the 95% level of utaListical confidence (97.5% for a one-tail test).

AAAsj ipolfIcantly different from zero at the 99% level of statistical confidence (99.5% for one tail test).

LA. - Not Applicable

107111: The significance levels given here may be slightly biased because the estimates of standard errors used for the underlying significance tests were obtained from a regression program which doss not account for the implicit hateromcedesticity when controlling for

unobserved differences between Corpsmembers and the comparison sample via the MAMMA (1979) approach. In practice, however, the

significance levels from the regression program are usually very close to those from test statistics using unbiased estimates of

standard errors, especially when the coefficients for the adjustment variables are statistically insignificant (which is usually the

case here). Therefore, the significance levels given hare are approximately accurate and are indicative of the true significance levers.

1/The unweighted postprogram sample means indicate the magnitude of the variable for all observations (Job Corps and comparison groups).

:orpasember sample means can be obtained by adding the effects shown in this table to the estimates for Corpamembers' activities had they not

Narticipated in Job Corps (presented in Table 111.1).

12/The estimate for Jub Corps effects on the probability of having & high school diploma or 0E0 are based on probit estimates with data

through the First Follow -Up Survey for estimates given in the "0 to 6 Months" column and with data through the Second Follow-Up Survey and

Including information from Job Corps termination forms for the estimates given in the "12 to 18 Menthe" column. (The estimates for the

second period include all of the OED. obtained In the Job Corps, while those for the first time period include only part of them.) The

onweighted postprograr sample mean given here Is from the data underlying the estimate for the "12 to 18 Months" column.

S
increase of nearly 5 full -time college students for every 100 youths

enrolled in Job Corps. Therefore, the education affects appear to

indicate some clear increases in human capital investments among

Corpsmembers, and provide further evidence that the short-term gains

in employability are not-likely to fade out rapidly.

As shown in Table 111.3 and Figures I/I.5 through 111.8, the

estimates of increased investments in human capital from education are slightly larger for females without children than for males. Furthermore,

Figures III.5 through 111.8 also show that the educational effects are relatively constant over tilde and across Job Corps completion categories,

with only small increases in educational effects over the postprogram

period and slightly higher college attendance among program completers.

The estimates of Job Corps effects on training show a very small

(approximately,) percentage point) reduction that is marginally significant and slightly larger in magnitude for females without children than

for males. However, the effects for high school and training activities

and effects do serve to indicate that our comparisons are consistent with

the normal course of activities for youth--including some training and

education that would have occurred if Corpsmembers had not gone into

Job Corps--and do not constitute a "zero treatment" comparison

(discussed further in Chapter X).

In summary, Job Corps-induced increases in human capital investments

are evidenced by estimated increases in both high school equivalent degrees

and attendance in higher education. Enrollments in lower levels of education and for training programs decline somewhat in the postprogram period.

59

7f)
FIGURE 111.5

ESTIMATES OP TIME PATHS OF NET'INCREASES IN PERCENT OF TIME IN COLLEGE FOR MALES

42. FOC2MT Of TIMC IN =Jet

02

22 .... ... ... %ft IlL108---- Wm. . .

.01. 4..

MTN: OUT OF JOS CORPS

at

MOO 4.00 Las s.as 10.011 MOO MOO

CONFIXTERS

PART I IL C01F4.2TU2

ORLI OROFIUTS

111.0 vs.ce Moe

(relative to not participating)

MORE III.6

ESTIMATES OF TIME PATES OF NET INCREASES IN PERCENT CF TIME

IN COLLEGE FOR FEMALES WITHOUT CHILDREN

FOUNT OF TINS IN COLLO(

I

./ / o#

. 1 .0.'14 .. °

I" ,,, .. ....

O. . %,, .0. . a' 1

I% .... 7." ..; 1..c.- ..., . ... '''

I ... I" el. MONTHS CUT OF JOS CORPS

..... ken 1.00 COO 0.00 10.00 111.00 M.011 .111.00 10.00 10.011 Z8.00

ROMAN CORFUTTRO

PRAT I RI. CORF1.2TtRI

. omereur3 (relative to not participating)

60
MIX NI MIR 7008,S MOJ MIMS moimim N2MCIIR0 

=WHIM 10 MIX SEM 10 IZN =Imam NI J0,==d 

=DIE III B' 

11 SO OD011 

_ 

. .. 

\oe. 

001 SO, X1 ION Witt .11! 00 art aril 

SNOW 1110 A KW SAIL, 11:111.11MMIIMIIM, 

OATZVTOX) ZOU (bUT4VdTOT42Vd 

SIANAVO 

S113171111413 

'moose- Ramon 

.uravad A LNI1 NI MIN VON= 

ILI 

Z1 

ZS 

SELYPECSS3 0 WU SWYd 10 SIN SNOIXDOC28 NI IN3=2d 30 MIS NI RIB ZOOMS UOJ BMW 

. I1 S1" L'III 
2. Other Investments in Human'Capital

The fihdings,on Job Corps effects-for other types of investments

in human capital are s arized in Table 111.4. Corpsmembers had.slightly'

better health, fihawed great mobility, and were more likely to ha/lie-joined

the Military.

There are some overall reductions iif,serious health problems, but

they are very s all,(approximately 1 percentage point) and statistically

1 insignificant. ever, the health gains are much larger (5 to, 7 peregge

points) and statistically significant for females without children. The

overall effect on serious hell 0 problems shows only a slight decrease

c despite the findings for females without children, because there is a

slight increase for males and they constitute the bulk (70 percent) of

Job Corps enrollees.

The increases in mobility for Corpsmembers are evidenced by moves

for job opportunities, for education or training, and otherwise. The overall impact estimates are substantial--altogether, over.20 additional moves

for each 100 Corpsmembers- -and statistically significant, but they occur

primarily during thefirst 6 months after Corpsmembers leave the Centers.

The cumulative impacts for moves do not change much from 6 to 18 months'

of postprogram observation...Furthermore, the Job Corps effects on moves

for job opportunities and for education or training actually decline from

month 6 to mcrsth 18 in the postprogram observation period--in part, no doubt,

because Corpsmembers have increased employment at the end of 6 months that

persists ever the remainder of the postprogram observation period.

Finally, Table 111.4 repeats the estimates of Job Corps impacts

on military service. They can be viewed as investments in human capital,

because increasing the ability 'f disadvantaged youths to pass exams to
83

TALI 111.4

ESTIMATES OF J00 CORPS EFFECTS ON MALIN, MOBILITY, AND MILITARY SIRVICEII

Variable

Onveighted Job Corps Effects Job Corps Effects

tostprogr::k 0 to *6 Months 6 to 12 Months Sample Ne After *Irninstion Aster Termination

Job Corps Effects

12 to II Months After Termination

Job Corps Effects

.10 to 24 Months After Termination

A. ML' ES

......

I Serinus health problems for 'civilians (friction of time) 0.027 0.006 0.010 0.012 0,005

2 Number-Of moves for civilians (mobility)Si

e Ail moves across cities (emulative) 0.429 0.26444" N.A. 0.31044* N.A.

e or job opportunities (cmulitive)

e For education or training

(cumulative) e All mows across cities, sictuding Job

corps relocations (cumulative)

0.359

0.077

0,359

0.1914,44 N.A.

0,06304** N.A.

0.17744** N.A.

0.22004

0.011

0.253**"

N.A.

N.A.

M.A.

Probability inApilitary during

interview wet. 0.101 0.024" N.A. 0.056*** N.A.

B. !MU Mint OULDI101

1 Serious health pretties for civilians

(fraction of time) 0.035% -0,050440 -0.05141* -0.074*** -0.060444

2. amber of moms for civilians (mobility)S1

I All nom Acre's cities (cumulative) 0.523 0.32544" N.A. 0,233 N.A.

e For job opportunities (CWWilkiVI)

o For leticitiom or training

(cumilitivs) a All moves Krell cities, ucludinq Job

0.260

0.090

0 105ea* N.A.

0.0504* N.A.

-0,047

0.090

N.A.

1 N.A.

1

. Corps relocations (emulative)

0,411 0,1094404 N.A. 0.163 , N.A.

1 Probability imAgilitary &imp

N ervier meek7

0,027 0.000 N.A. 0.0003

84
TABLE 111.4 (continued)

Variable

Unweighted

Postprogramb,

Sample MeanJob Corps Effects

0 to 6 Months After Termination

Job Corps Effects

6 to 12 Months After Termination

Job Corps Effects

12 to 18 Months After Termination

Job Corps Effects

18 to 24 Months After Termination C. MULL

1. Serious health problems for civilians

(fraction of time) 0.027 -0.007 -0.005' -0.008 -0.012

2. Number of moves for civilians (mobility)- c/

All moves across cities (cumulative) 0.421 0.273**** N.A. 0.270*"* N.A. For job opportunities (cumulative) 0.311 0.184*"* N.A. 0.149* N.A. For education or training

(cumulative) 0.075 0.059**** N.A. 0.030 N.A. All moves across cities, excluding Job

Corps relocations (cumulative) 0.346 0.174  N.A. 0.215** " N.A.

3. Probability inAililitary during interview week- 0.077 0A19*** N.A. 0.039*** N.A. *Significantly different from zero at the 80% level of statistical confidence (90% for a one-tail teat).

*"Significantly different from zero at the 90% level of statistical confidence (95% for a one-tail test).

"" "Significantly different from zero st the 95% level of statistical confidence (97.5% for On a one-tail test).

"**"Significantly different from zero at the 99% level of statistical confidence (99.5% for a one-tail test).

N.A. - Not Applicable

NOTES: The significance levels given here may be slightly biased because the estimates of standard errors used for the underlying signifi- cance tests were obtained from a regression program which does not account for the implicit heterosvAarticity when controlling

for unobserved differences between Corpsmembers and the comparison sample via the Heckman (1979) approa:h. In practice, however, the signifiCance levels from the regression program are usually very close to those from test statistics using unbiased estimates of standard errors, especially when the coefficients for the adjustment variables are statistially insignificant (which is usually the case here). Therefore, the significance levels given here are approximately accurate and are indiative of the true signifi- cance levels.

a/- Most of the variables in this table are estimated for the civilian population

only--the one exception is for the probability of being in the military during the interview week,

b/ The unweighted postprogram sample means iadicate the magnitude of *e variables for all observations (Jab Corps and comparison groups). corpsmember sample means can be obtained by adding the effects showa in this table to the estimates of Carpet:aims' activities had they not participated in Job Corps (presented in Table II1.1).

c/The estimates of Job Corps effects on the number of moves are based on data through the First Follow-Up Survey in the "0 to 6 Mouths" column and with data through the Second Follow-Up Survey in the "12 to 18 Months" column. The estimates in the "12 to 18" Month column are cumulatim through :he Second Follow-Up Survey. The unweighted postprogram sample mean given here is for the data through the Second Follow-Up.

a'The The estimaps for Job Corps effects on the probability of being in the military are based on probit estimates with data from the interview week for/Ehe two follow-up surveys. The estimates with the data from the First Follow-Up Survey are given in the "0 to 6 Months" column, and those from the second Follow-Up Survey are given in the "12 to 18 Months" column. The unweighted postprogram sample mean ggIl here is from the Becond Follow-Up data.
enter the military and the concomitant increases in military service can

be expected to cause an increase in the long-run earnings potential of

.these youths. While the gain in military service was also reported above

as an employment effect, it does have human-capital implications because

(1) entering the military (i.e.-, passing the Armed Forces Qualifying

Examination) indicates the attaithent of a certain level of human-capital

development, and (2) participation in t:.e military offers additional

human-capital development through training and jab experience. As already

noted above, the increases in civilian employment Ad also produce some

long-run human-capital benefits through job experience.

D. DEPENDENCE ON PUBLIC TRANSFU

.Overall, as shown in Table former Corps;: r ,A.ctr.1 their

participation in all of the public tahs .r programs thaL were masured.

We found estimated Job Corps effects oluctions in receipt AFDC,

General Assistance, Food Stamps, public Ixdusing, Unemployment InnirAnce,

Workers' Compensation, and public training allowances. The largest and

most significant reductions were for the regular cash assistance programs--

AFDC General Ass. stance, and Unemployment Insurance. The reductions in

dependence on public assistance were larger magnitude for females without

children than for males, ans.: thf_ reductions in dependence on other transfer

programs were :.a-ger fo. males thin females. Finally, as shown in FigurPs

III.S and MAO for AFDC and General Assistance, fte reductions in welfare

dependence are relatively constant over the postprogram period and are

only slightly larger in magnitude ftdr vouths whu complete the Irogram than

for those who drop out before finishing.

65

87
id 111.5

ISTIKAUS 3F J08 CUPS EFFECTS OA BtftlIT OF PUBLIC 1111111115 81 CIVILIANS

Variable

Unveighted

lostprogres bolo Ikon

Job Corp' Iffecti

0 to 6 Months After Tersinotion

Job Corp' Effects 6 to 12 Months

After Termination

Job Corps Affects

12 to 11 Noutbs After letoinstion

Job Corp' !fleas

18 to 24 Months After termination

A. MALES

I. Receipt of public assistance

e Any financial oilistars

(fraction of tins) 0.017 -0.0304+4 .0.015**** -0.01014, -0.010i114 $ AFDC (fraction of tire' 0.009 -0.002 -0.010 -0.010 -1.013 I General Assistance or other

(friction of tiro) 0.008 -0,02141** -0.0254144 -0.0204"A -0.018414

e Food Steeps (friction of time) 0.134 -0.004 -0.00S 0.004 0.011 a Public boutinOroctiou of tii) 0.018 0.019 0.021 U.007 -0.009

2. Receipt of other transfer,

,a/ a Uneoploystat Insatiate (fraction of Limy 0.014 -0.027114A -0.310141i 6,025 eie4 -0.021'444

e Workers' Coopoistion (fraction of ties).

6/

tilW training allowloces (per silt soothe

0.004 -0.006 -0.003 -Cote -0.004 at in dollars) 11.64 -13.51 -9.54 -12.12 -11.50 IL MIMS W:1110Uf CHILDREN

1. Receipt of public assistance

e Any financial miliaria (fraction of time) I) 043 -0.14344" -0.1331444 0.138eeet -0.149k11* e UDC (fraction of tine)

, General Assistance or other

r 024 .0.1144" -0.10244i* -0.!:fi4i4e -omalal,

(fraction of time) P.014 -0.0301A4 -0.03044/ 0.02714 -0.0301i

e Food Stamp (fraction of time) 0.156 -0.01:* -0.056 -0.042 -0.043

1 Public houiiog (friction of tile) . 0,070 -0.023 -0.012 -0.042 -0.046'

2. lecelpt of other transfers e Unesplopentinsurancs (fraction :. tiee0. 0.004 -0.01S1*i -OAS*" 6.019eee .0.018e4e

I Workers' Ccrp;taation (fraction of Ow)!' 0.002 -0.001 -6.042 -o.002 -0.0001

. Training ellowinces (per sis months

in dollars) 8.16 I2.4, 24.51**4 8.58 3.08 u

as
TULA 111.S icatinued)

Variable

Unweighted

Poltprogram

Slate Nan

Job Corps Affects

0 to 6 Months

After Terlination

Job Corps Affects 6 to 12 Months

After Termination

Job Carps Affects

12 to 18 Months after Termination

C. OVERALL

1. Receipt of public assistance

1 Any financial Willi/MI (hid', ) of time) 0,022 -0.05044 -0.0554444 -0.0534444 e HOC (fraction of time) s General banana or other

(fraction of time)

0.013

0.009

-0,0284444

-0.027444*

0.031444*

-0.0254444

0.031ase

.0,021taaa

. Food Stamps (fraction of time) 0.130 -0.020 0.016 0,007

s Public' ousing (fraction of time) 0,011 0.008 0.008 -0.005

2. Receipt of other transfers

unemployment insurance (fraction of time).

a/ 0.012 -0.0224444 -0.02544"4 -0.0224404

Workers' Compensation (fraction of time) -

A/ 0,003 .0.004 -0.002 -0.O05

Training allowances (per Millionths

in dotterel

10.02 -6.64. -1.04 -7,00

Job Corps Affects

18 to 24 Months After Termination

.0.0564444 .0.036aaa

..0.0204AA 0.002

-0.017

.0.0204444

.0.003

*Significantly different from pro it the 80% level of statistical confidence

(90% for a one -tall test). "Significantly different from :fro at the 90% level of statistical confidence (95% for a one-tell test).

u4Significantly different from zero at the 95% level of statistical confidence (97.5% fora one-tail teen.

44"Significantly different from zero at the 99% level of statistical confidence (99.5% fora one-tail test).

M.I. Not Applicable

4ROTAS; The signiticance levels given here may be illicitly biased because the estimates of standard errors used for the underlying signifi- cance tests were obtained from a regression program which does not account for the implicit

hateroscedasticity when controlling for

unobserved differences between Corpesabert and the comparison sample via the liecksan 1.979) epproach. In practice, however, the

significance levels from the regression program are

usually very close to those from test statistics using unbiased estimates of

standard errors, especially when the coefficients for the adjustment variables are statistically

insignificant (which is usually the

case here). Therefore, the significancelevels given here are epprosiately accurate and are indicative of the true significance

levels. -The The effects on Unemployment Insurance and Workers' Compensation were

also estimated with aggregate data on the number of weeks received during the postprogras period (weeks are the basic time unit for participating in these progress). The resulting estimates

showed slightly larger and mdre significant reductions, However, with estimates based on data aggregated over the whole poaprogra

period, the time patterns of effects could not be discerned. 4
FIGURE 111.9

ESTIMATES OF TIME PATHS OF NET REDUCTIONS IN PERCENT OF TIME ON WELFARE FOR MALES

oi

ST

toe

PCPCZNT Or TINt ON NCLMIC

----MMTIM. MINATO!

---CMILTOIMPOUTO

(relative to not participating)

8.00 S.00 Lao Lao 10.00 18.00

\ i

\

Noon! OUT Of .1011 CORPS

111.00 16.00 MOO 10.00 1800

...... -

.....

.....

..... . ...'' N .0: N. .... .

. 00 .... .4. .... .... "' .

. ... N. .... ' ... ............

FIGURE 111.10

ESTIMATES OF TIME PATHS OF NET REDUCTIONS IN PERCENT

OF TIME ON WELFARE FOR FEMALES WITHOUT CHILDREN

rtNmENT or TINE ON MIME

mom comelfTelT3

PORTION. COMPLETER!

PIM DROPOUT,

(relative to not participating)

manna OUT or .165 coon

102

TOT

Toz

;021

8.00 0.00 8.00 8.00 /

10.00 18.00 10.03 18.00 18.00 80.00 32.00

"%.

/ .........

\ %./

al

68

9 '1ti
R. CRIMINALITY

The reductions in criminality as measured by arrest estimates are

the only area in which the increased observations, and the more rigorous

statistical techniques that they afford, yield substantially smaller estimates

of impacts during the first 6 postprogram months (about half as large

in Table 111.6, compared to those in Haller et al., 1978). The initial

arrest differences for our updated findings shown in Table 111.6 are still

relatively large and statistically significant. .However, they fade out

quickly during the second year of postprogram observation. This deterioration

appears to be caused by some rather sudden shifts in the estimated effects

for crimes other than thefts, and thus must be investigated further.

The differences by subgroup are also puzzling, and require further

investigation. The reductions in arrests for males are exclusively among

theft crimes, and the reductions for females are exclusively among crimes

other than theft. The detailed compositicn of 'arrest effects and their social

value will be examined further in Chapter V.

The effects of Job Corps on the probability of being in jail are

again negligible and completely insignificant (almost none of the youths

is in jail). The data from the postprogram observation period also support

the earlier findings of small but statistically sig4ficant reductions

in the use of drug-treatment programs among Corpsmembers (see Chapter V

for more detailed breakdowns of drug-treatment effects).

F. SUMMARY AND CONCLUSIONS

The hypothesized economic impacts of Job Corps on participants'

postprogram behavior are generally consistent with the program goal of

improving CorpsmeMbers' economic prospects (see Chapter II). In this

chapter, we have presented findings the estimated_postprogram effects

69
TABLE 111.6

ESTIMATES OF JOB CORPS EFFECTS ON CRIMINALITY 1/1D DRUG usiGei

Vsriable

Iltiveighted

Postprogro

Sample Mean

Job Corps Effects

0 to 6 Months

liter Temination

Job Corps Effects

6 to 12 Months

liter termination

Job Corps Effects

12 toill Months

liter termination

Job Corps Effects

16 to 24 Months

liter Termination

1. MILES

1. Total tuber of civilian arrests

per six months 0419 -0.031 -0.033 0.004 0,0003

2. Number, of civilians theft arrests

per six months 0.021 -0.041k" -0.041k" -0 021"

3. Probabilitybin jail Airing

survey week- 0.044 -0.002 N.1. 0,021 M.1.

4. Proportion of time in drug

LI ailment programs 0.004 N.A. -0,008'" -0.008k" -0.0011"k

B. FEMALES WITHOUT CIIILDID1

1. Total welter of civilian struts

'per six mouths

e. Mother of civilians theft arrests

per six months

0.009

0.003

-0.0111k

0.004

-0,021"

0.002

-0.019k

0.003

0.016

0.0003

3. Probabilityhin jail durLug

survey week-1 0.0 0.005 N.1. 0.0 M.I.

4. ProportiOn of time in drug

treatment programs 0.001 N.A. 0.0003 0.0004 0.002

I
TANI 111.6 (continued)

Pariah:-

Unsighted

Postprograo

Semple Mean

Job Corps If:octs

0 to I Montle

After Tormineilon

Job Corps Effects I to 12 baths

After Tersinetion

Job Corps Effects

12 to 18 Months After Termination

Job Corps Effects

III to 24 Booths After Termination

C. 0811111.1,

1. total.nueber of civilian arrests per six months 0.051 -0.030*** -0.028*** -0.008 0.004

2. Number of civilians theft arrests

,. 0

per six month' 0.020 -0.028*** .028 *** -coal -0.033***

3. Probebilitybin jail during

survey week- 0.031 0.0003 N.A. 0.019 N.A.

4. Proportion of time in drug

treatment progress 0.003

-o.00s** -o.00s**

*Significantly different from two at the 80% level of etatistical confidence (90% for a onetall test).

**Significantly different fro' tiro at the 90% level of statistical confidence (95% for s mteil test).

 erificantly different from 100 at the 95% level of statistical confidence (97.5% for a onttail test).

** **Significantly different from aro at the 99% level of statistical confidence (99.5% for A nqi.teil test).

N.A. Not Available (The (psalm in the first Follow -Up on receipt of drug treatment obtained information only on whether received

anytime during the period and do not allow for sedates of the magnitude of usage as presented here. However, the earlier data

did indicate reductions in receipt of drug treatsente on the order of that shown here (see Nellar et al., 1978).

NOTES: The significance levels given kers may be slightly biased becaues the 'athlete" of standard errors used for the underlying

significancL tests were obtained free a regression program which does not account for the implicit hetiroscedasticity when

controlling for unobserved differences

between Ccrpemembers and the comparison "ample via the Heckert (1979) approech. In practice, however, the slyelficance levels fro the regression program are usually very close to thole from test statistic' using unbiased estimates of standard errors, especially when the coefficients for the adjustment variables are statistically

insignificant (which is usually the case here). Therefore, the significance level' given here are approximately accurate and

are indicative of the true *alliance levels.

Host of the variables in this table are estimated for the civilian population only. The one exception is for the probability

of being in jail during the survey week. More detailed estimates of arrest effects are presented with the benefitost analysis in

Chapter V. The estimates in Chapter V include youths In the military Al well as civilians, and Are disaggregated by major crime

categories.

-TheThe estimates for Job Corps effects on the probability of being in jail are based on probit estimates with data from the

interview week for the two follow -up surveys. The estimates with the data from the First Follow-Up Survey are given in the "0 to 6

Months' column, Ind those from thr Second Follow-Up Survey are given in the "12 to 18 Months" column. The unweighted postprogram

sample mein given here is Iron the Second FollowUp data.

97
of Job Corps and have statistically tested the hypotheses and, hence, have

tested how well the program appears to be meeting its goal of improving

Corpsmembers' economic prospects during the first two years after Corps -

members leave the program. Overall, we find that Job Corps is at least

moderately successful in achieving its desired effects of (1) increasing

employment and earnings, (2) improving future labor-market opportunities

through work experience, education, training, better health, geographic

mobility, and military service, (3) reducing depJndence on welfare assistance and other public transfers, and (4) reducing criminality. The

estimates and their statistical significance are summarized in Table

111.7; they are presented in an annualized basis in Table 111.8; and

finally, they are presented on a percentage basis in rable 111.9.

The effects generally represent benefits and are statistically

significant both overall and separately for males and females without

children (excefacIES are noted in the chapter). Also, the effects tend

to be larger for program completers (see Chapter VI).

Beyond the overall positive results, the most noteworthy finding

is that the impacts generally persist through the second year of postprogram observation. In fact, if there is any trend over-the postprogram

observation period, it appears to be toward increased program benefits

during the first few months (especially for employability during the

transition from center life to the regular labor market), and then stable

effects through the rest of the two-year period. The one exception is for

criminality, which shows its largest reductions during the early postprogram

period and fades out rapidly after Corpsmembers have been out of the program

for a year.

72 9s
TABLE 111,7 SUMMARY OF MAIN FINDNGS FOR OVERALL IMPACTS OF JOB CORPS -"

0 to 6 Months

Variable After Termination

6 to 12 Months

After Termination

12 to 18 Months

After Termination

18 to 24 Mont

After Termination,

A. Employment and ,larnings of civilians

Employed (fraction of time) 0.012 0.051* 0.078*** 0.090****..

Hours worked per week 1.33 1.9f* % 3.17*** 3.66***

Earnings per week (dollars) 2.02 6.00 9.69* 9.03*

Employed, in school, or in training

(fraction of time) -0.039 0.023 0.033 0.051*

Employed or looking for work

(fraction of time) 0.029 0.034 0.046* 0.048*

Employed L. union job

(fraction of time) -0.022 -0.015 -0.016 -0.010

Employed in PSI job

'(fraction of time) -0.014 -0.002 0.010 0.007

B. Probability in military during

interview week 0.019*** N.A. 0.039*** N.A.

C. Education and training of civilians

Probability of having high school

diploma or GED by time of interview 0.052  N.A. 0.250** ** N.A. In any school (fraction of time) -0.054**** -0.017 -0.030* -0.019

In college (fraction of time) 0.014* 0.022*** 0.025*** 0.030 

In high school (fraction of time) -0.059** ** -0.045  -0.049** ** -0.049 

In vocational or technical

school (fraction of time) 0.009 0.019** * 0.012* 0.014*

In other school ;.1 (fraction of time) -0.020*** -0.014* -0.017** -0.014**

In any training program

(fraction of time) -0.00 0.003 -0.010 -0.010

In CETA training

(fraction of time) -0.015** -0.011* -0.018*** -0.013*

In WIN training

(fraction of time) -0.002* -0.003*** -0.004  -0.004** *

In other training

(fraction of time) 0.001 0.008* 0.008* 0.004

D. Number of moves for civilians (mobility)

All moves across cities (cumulative) 0.273**** N.A. 0.270 N.A. For job opportunities (cumulative) 0.184  N.A. 0.AS N.A. For education or training

(cumulative) 0.059** ** N.A. 0.030 N.A. All moves across cities excluding Job

Corps relocations (cumulative) 0.174  N.A. 0.215** * N.A.

73

9
rablt 111.7 (continued)

variable

0 to 6 Nbuths

After Termination

6 to 12 Months

After Termination

12 to 18 Months

After Termination

,18 to 24 Months

After Termination

I. Serious health problems for civilians

"(fraction of time) -0.007 -0.005 -0.008 -0.012

V. Receipt of public assistance by

civilians

Any fisamcial assistance

(fraction of time) -0.0%**** -0.055  -0.0S3** ** -0.056 

UDC (fraction of time) -0.028** ** -0.031  -0.033** ** -0.036 

General Assistance or

other (fraction of time) -0.027** ** 1.025  -0.021** ** -0.020 

Food Stamps (fraction of time) -0.020 -0.0141 -0.007 -0.002

Public housing (fraction of time) 0.008 -0.008 -0.00S -0.017

0. Receipt of other transfers by

civilians

4 0nemploopent Insurance (fraction

of time) -0.022** ** -0.025  .-0.022** ** :0.020 

Workers' Compensation

(fraction of time) -0.004 -0.00; -0.005 -0.003

Training allowances (per

six months in dollars) -4.64 -1.04 -7.00 -7.34

M. Criminality

Total number of civilian

arrests per six months -0.030** * -0...28*** -0.00d 0.004

Number of civilian theft

arrests per six months -0.028*** -0.028*** -0.018* -0.033***

Probability in jail during

survey week -0.0003 N.A. 0.019 _N.A.

*Significantly different from zero at the 80% leveA of statistical confidence (90% for a onn.tail test).

**Significantly different from zero at the 90% level of statistical confidence (95% for a on -tail test).

***Significantly different from zero at the 9S% level of statistical confidence (97.5% for i one-tail test).

****Significantly rnt from zero at the 99% level of statistical confidence (99.S% for a one-tail test).

N.A. - Not Applicable

NOT23: The significance levels given here may be slightly biased because the estimates of staff and errors used for the

underlying significance tests were obtained from a regression program which does not account for the implicit

heCeroscedasticity when controlling for unobserved differences between Corpsmembers and the comparison sample

via the Heckman (1979) approach. In practice, however, the significance levels from the regression program are

usually very close to those from test statistics using unbiased estimates of standard errors, especially when

the coefficients for the adjustment variables are statistically insignificant (which is usually the case here).

therefore, the significance levels given here are approximately accurate and are indicative of the true

significance levels.

,The entries in this table summarise the estimates presented in Tables 111.2 to 111.6. molt of the

variables are estimated.for the civilian population only (for more on the variable definitions and computations,

see the notes for Tablei /11.2 to /II.6).

100

74
TABLE 1114

SUMMARY OF MAIN FINDINGS FOR OVERALL IMPACTS OF JOG CORPS ON AN ANNUALIZED BA810/

d

0 to 6 Months 6 to 12 Months 12 to 18 Months 18 to) 24 Months

Variable After Termination After Termination After Termination After Termination

1. Employment and earnings of civilians

Employed (weeks) 0.6? 2.63

'Inure worked per week 1.33 1.98* Earnings per year (dollars) 105.17 312.16

EXployed, in school, or in training (weeks) -2.04 1.22 Employed or looking for work (weeks) 1.51 1.75

Employed "in -union job (weeks) -1.12 -0.76 e Employed in PSI job (weeks) -0.72 -0.09 Probability in military during interview

week 0.019*** N.A. Education and training of civilians

Probability of having high school diploma

or pap by time of interview 0.052  N.A. In any school (weeks) -2.80** " -0.88

i In college (weeks) 0.7S* 1.11*** In high school (weeks) -1.05  -2.12** ** In vocational or technical school (weeks) 0.48 1.00***

In other scholl.. (weeks) -1.01***. -0.71*

In any training programA....eks) -0.50 0.17 In CETA training (weeks) 4 -0.79** -0.57* In WIN training (weeks) -0.11* -0.17*** In other training (weeks) 0.07 0.41*

1. Number of moves fo4 civilians (mobility)

All moves across cities (cumulative) 0.271**** N.A. For job opportunities (cumulative) 0.180*** N.A. For education or training (cumulative) 0.059  N.A. All moves across cities exculding Job Corps

relocations (cumulative) 0:174** ** N.A.

s. 101

4.05*** 4.70  .17** * 1.66***

501.88* 469.11*

1.70 2.66*

2.19* 2.51* -0.83 -0.56 0.50 0.34

0.019*** N.A.

0.250**** N.A. -1.54* -0.99

1.29*** 1.54  -2.56** ** -2.56****

0.64* 0.75*

-0.90** -3.74**

-0.51 . -0.53

-0.95*** -0.70* -0.21**** -0.21*** 0.43* 0.19

0.270***

0.149* N.A. 0.030 N.A. 0.215*** N.A.
Table 111.8 (continued)

0 to 6 Months

1/eatable After Termination

6 to 12 Months

After Termination

12 to 18 Months

After Termination

18 to 24 Months

After Termination

B. Serious health problems for civilians

(weeks) -0.38 -0.24 -0.44 -0.62

F. Receipt of public assistance by civilians

A14, financial assistance (weeks) -2.82**** .2VAA*1! -2.75**** -2.89AAA*

AFDC (weeks) -1.45**** -1.60AAAA -1.70  -Lajas** 

General Assistance or other (weeks) ..1.3gsasa _1.28**** -1.09*** -1.02 

Food Stamps (weeks) -1.02 -0.84 -0.10 Public housing (weeks) 0.43 0.42 -0.26 -0.88

G. Receipt of ot:.er transfers by civilians

Unemployment Insurance (weeks) _Ilysasa -131,4** * -1.12**** -1.06 

Workers' Compensation (weeks) -0.21 -0.13 -0.23 -0.16 Training allowances per year (dollars) ,-345.23 -54.30 -364.07 -381.67

H. Criminality

Total lumber of civilian arrests per year -0.060** * .-0.055*** -0.015 0.008 . Number of civilian theft arrests ptr year -0.056*** ..0.0566** -0.036* -0.066***

Probability in jail during interview week -0.0003 M.A. 0.019 N.A. *Significantly different from zero at the 80% level of statistical confidence (90% for a one-tail test). A *Significantly differenit from zero at the 90% level of statistical confidence (95% for a one-tail test).

'***Significantly difx4rent from zero at the 95% level of statistical confidence (97.5% for a one -tail test).

****Significantly different from zero at the 99% level of statistical confidence (99.5% for a one-tail Wit).

N .A. -14ot Applicable

MOTES: The significance levels given here may be slightly biased because the estimates of standard errors used for the

underlying significance tests were obtained from a regression.program which does not account for the implicit

hetiroscedasticill when controlling for unobseryed differences between Corpsmembers and the comparison sample

via the Ileckelln (1979) approach. In practise, however, the signi.icance levels from the regression program

are, usually very close to those from test statistics using unbiased estimates of standard errors, especially, when the coefficients for at adjustment variables are statistically insignificant (which is usually the_case_

. here). Therefore, the significance levels given here are approximately accurate and ere indicative of the true

significance levels:-

a' The The estimates given here are the same as in Table I11.7, except for being placed on an annualized basis as

n oted. Most of the variables are estimated for the civilian population only (for more on the variable definitions

and computations, set notes for Tables 111.2 to

%.14
TABLE 11I.9

SUMMARY OF MAIN FINDINGS FOR OVERALL IMPACTS OF JOB CORPS ON A PERCENTAGE mist/.

0 to 6 Months 6 to 12 Months 12 to 18 Months 18 to 24 Months

Variable After Termination After Termination After Termination After Terminal on

A. Employment and earnings of civilians

Employed (weeks) 3 Hours worked per week 10 Earnings per year (dollars) 5 Employed, in school, or in training (weeks) -8 Employed or looking for work (weeks) 4 Employed in union job (weeks) -35 Employed in PSI job (weeks) ¢ -32

S. Probability in military during interview

week

12* 17*** 20****

13* 17*** 21***

10 13* 12*

4 6 9*

5 7* 7*

-21 -19 -12

-4 19 17 N.A. 77*** N.A.

C. Education and training of civiliens

Probability of having-high ecgeol diploma

or GED by time of interview 34  N.A. 230** ** M.A. In any school (weeks) _46**** -16 -32* -20

In college (weeks) 1,400* 2,200*** 2,500*i* 1,797****

In high school (weeks) _71  .61** ** -79  Alp** *

In vocational or technical school (weeks) 350 1,357*** 265* 272*

In other school (weeks) -52**A -42* .57** -41**

In any training program (weeks) -28 9 -28 -28

In CIITA training (weeks) _55** -36* .57*** -43*

, In WIN training (weeks) -91* .516*** _94 _ _ ./15** *

4, in othertraimInglweoks) 30 1,278* 800* 400

D. Number of moves for civilians (mobility)

All moves across cities (cumulative) 307**** N.A. 113*** N.A. For job opportunities (cumulative) 767**** N.A. 65* N.A. For education or training (cumulative) 492**** M.A. 45 ° M.A. All moves across cities exculding Job Corps

relocations (cumulative) 214  N.A. 111** * N.A. 103
Table 111.9 (contiOlted)

Variable

0 to 6 Months

After Termination

6 to 12 Months

After Termination

12 to 18 Months

After Termination

18 to 24 Months

After Termination

Serious hfaith problems for civilians,

(weeks) -19 -12 -20 -27

P. Receipt of public assistance by. civilians

Any financial assistance (weeks) -57**** .49111A** .44  -spree'

AFDC (weeks) -47** ** ..3g**** ..3gAmt" ..46amte General Assistance or other (weeks) ..74",ct* -62**** -61  Food Stamps (weeks) -11 -9 -4 -1 Public housing (weeks) 10 -8 -S -18

G. Receipt of other transfers by civilians

unemployment Insurance (weeks) -87** ** -met** ..sozokez Workers' Compensation (weeks) -8S -83 -67 -49

Training allowances per year (dollars) -27 . -7 -64- -69

H. Criminality

Total number of civilian arrests per year -32*** -37*.tk -10 5 Number of civilian theft arrests per year -SO*** -sgA** -39* ..641%** , Probability in jail during interview week -1 N.A. 167 N.A. *Siiptificantly different from zero

,**Significantly different from zero

AAA Significantly different from zero

** *"Significantly different from zero

N.A. - Not Applicable

at the 80% level of statistic&.. confidence (90% for a one-tail test).

at the 90% level of statistical confidence (95% for one -tail test).

at the 95% level of statistical confidence (97.5% for a one-tail test).

at the 99% level of statistical confidence (99.5% for a one -tail test).

NOTES: The cAgnificance levels Jiven bere_say_bestightly biiied because the estimates of standled errors used for the underlying

___significanCe tests -ware e-eibtained from a regression program which does not account for the implicit heteroscudesticity when

controlling for unobserved differences between Corpamembers and the comparison sample via the Heckman (1979) approach. In practice, however,. the significance levels from the regression program are usually very close to those from test statistics

using unbiased estimates of standard errors, especially when the coefficients for the adjustment variables are statistically

insignificant (which is usually the case here). Therefore, the significance levels given here are approximately accurate

anJ are indicative of the true significance levels.

liThe estimates presented in this table are the same as in Table 111.7, except that they are made on percentage basis,

with the estimates given in Table 211.1 as the bas*. Most of the variables are estimated for the civilian population only (for

more on the variable definitions and computations, see notes for Tables 111.2 to IMO.

:1LI
In Chapter V we will compare the-dollar value of these benefits

to.the dollar value of

, program cost in order to estimate whether the program repreients an efficient use of resources. First, howeVer, we turn

to an exploratory'analysis both of the effectsofcJob Corps on family

composition and of the employability and related impacts,for the small

subgroup of Corpswomen who have children living with them during the

postprogram observation period.
APPENDIX TO CHAPTER III

ESTIMATION PROCEDURES AND REPRESENTATIVE ESTIMATES

This appendix is designed-to document the estimation procedures

underlying the findings presented in the text of Chapter III, and to provide

the detailrof some representative estimatess. By necessity, this appendix

is more technical than the rest of the report, and readers with a nontechnical interest will probably want only to skim this appendix or to

.Pproceed directly to Chapter IV.

Our basic econometric model of behaviok is a single-equation

regression that can be represented as:

Yi 13.1c + TT + et = i -t --it it

where Yit is the economic behavior of interest (e.g., employment and

'related activities) for

.th the i individual during the tth time period;

the P's are coefficients; the X's are exogenous variables and lagged

values of dependent variables from pre-enrollmeht that explain the

behavior of interest; the T's are program effects'on the behavior of

interest; the T's are program variables; and e is ah v-rror term.-

1/

, With a nonrandomized control group (a co.:,piri.mln group) the T!s

are potentially correlated' with e. Any unobserved variable that affects

the economic behavior of interest is also likely to affect individual

(1)

1/ The types of behaviors of interest in this study are.related.

Therefore, some gains in statistical efficiency could be achieved by

using a multiple-equation technique that accounts for correlations in

.error terms across equations, such as a seemingly unrelated regression

procedure. However, the. gains in statistical efficiency with, a seemingly

unrelated regression approach would be.small at best, because the explana-'

tory variables, are nearly identical for all of the types of behavior that

we examine. . 80 11)G
decisions about whether to participate in the program and, hence, the T's.

Therefore, the T's are potentially endogenous with respect to the behavior

of interests' in which case ordinary leait squares (OLS)sestimators will

generally be biased.

As an example, variables such as motivation and innate ability

are not observed directly; undotibtedly,.they affeCt both employment-related

oehavior and the decision whether to participate in Job Corps or in other

similar programs. Thus, these unobserved variables can be important i elements in the error terms for both Y and the T's with a coiparisoh group

(with a randomized control coup unobserved as well as observed, variables

should be orthogonal or uncorrelated with the,T1s). Therefore,. the T's

will generally be correlated with c when a comparison group is used, and

the program variables should be treated As endogenous. Furthermore (as

is well known), OLS estimators, will gener,ally be biased when endogenous

'variables are included in regression equations, unless the correlation

between the endogenous variables and the error term (e) canpe netted out.

Different procedures for selecting comparison groups in the o absence of randomization will result in varying levels of (1) statistical

inefficiency from correlation between the X's and the T's, and,(2) OLS

bias from correlation between the T's and c when the program effects,

T's, are estimated via OLS. Some procedures that have been used'to

obtain comparison samples yield very poor matches and, hence, are very

inaccurate estimates for the T's from either a difference-in-samplemeans or OLS-estimatioh procedure (e.g., evaluations that rely on the

use of before-after comparisons with youths or other re-entrants or new

entrants to the labor force, and on the use of individuals who enrolled

but did not show up for the program or who dropped out of the program

very soon after entering).

81

1 o 7
Our comparison-group, survey, and econometric procedures were

designed to yield as efficient estimates as possible.i/ The basic

comparison-group procedure consisted of randomly selecting eligible nonparticipants who were similar to Corpsmembers in observable characteristics

and who lived in geographic areas similar to the neighborhoods where Corpsmembers lived before entering Job Corps centers. (Sites that were very

./*

,prOximate to centers--neighborhoods within the three-digit zip-oiode areas

where centers were located--were eliminated from being chosen as comparison

sites because knowledge of the Job Corps program was likely to be prevalent

in these sites.)

The comparison-group procedure was designed to yield a sample of

youths who were were similar to Corpsmembers but who did not go into the

program, largely becauie they had little (or no) knowledge about the program.

This comparison strategy was feasible for three reasons: (1) there are

large numbers of eligible youths who are similar to participating Corpsmembers who do not attempt to enter Job Corps, (2) program participation

is geographically eustered because of limited recruitment, and (3) most

Corpsmembers first learn about the program from friends or relatives (see

Kerachsky and Haller, 1978).

Our comparison-group procedure should yield a sample of youths

who are similar to Corpsmembers but who do not participate largely because

they do not know about the program. Therefore, it yields a very efficient

comparison group, and estimates of program effects should not be sensitive

to varyingassumptions about observable and unobservable differences

between the program and comparison groups as compared to other potential

-'For more details, see Haller (1979), as well as Technical Reports

A, 8, C, H, and J.

82
comparison groups (see Haller, 1979). Because comparison-group members

differ from CorpsmeYnbers primarily in terms of random access to information

about the program and random proximity to the program, T and c at best

should be weakly correlated.1/

Despite the use of the rigorous comparison-group procedures outlined

above, however, the interview data should be used to control for observed

and unobserved differences that remain between the comparison and participant groups in order to ensure against bias in the estimates of program

effects. Consistent estimates can be obtained by controlling for observed

differences directly and by controlling for unobserved differences indirectly

by modeling the participation decision.?

If a normal distribution is assumed for the error term in equation

(1), this error term can then be decomposed into an unobserved, explanatory

variable plus a new error term that is uncorrelated with the T's, as follows:

where

Y = pox + TT + + w it . .it ..it i it

= Pi gni)

F(ni)

g!'Ei)

1 - F(a'Zi)

P

i is a binary program participation variable that equals one for Corpsmembers (zero otherwise); f(') denotes the standard normal density function

1/ Some of the discussion is phrased as if there were only One

(binary) program variable, which may or may not be the case. However,

the results generalize to multiple T's, as is the case for our application

(see further below).

? /For more details, see Heckman (1979), Barnow, Cain, and Goldberger

(1978), and Haller (1979).

83

1 uo
for program participation; F() denotes the standard normal distribution

function for program participation; the Z's are explanatory variables that

affect program participation; and 6 and the a's are coefficients.

The sign of 6 is determined by the correlation of the errors (e.g.,

from omitted variables) in the underlying equations for Y and P. Therefore,

if the estimated value for 6 is positive, it indicates that individuals who

are likely to participate for unobserved reasons will have higher values of

Y, on average, for unobserved reasons, in which case the failure to adjust

for sample selection bias will make program effects biased in'a positive

direction. Similarly, if the estimated value for 6 is negative, it indicates

that individuals who are likely to participate for unobserved reasons will

have lower values of Y, on average, for unobserved reasons, in which case

the failure to adjust for sample selection bias will make program effects

biased in a negative direction.

As noted in the'text, when estimating Job Corps effects on employment

and related activities, the bias stemming from the failure to adjust for sample

selection could be in either direction. A positive 6 and positive bias will

result if there is a predominance of youths with higher innate abilities

and stronger motivation who are more likely to participate in Job Corps

because they benefit more; a negative 6 and negative bias will result if

there is a predominance of youths with lower innate abilities who are more

likely to participate in Job Corps because it costs them less (fewer

oppOrtunities outside of Job Corps).

If a consistent estimate of F(') is obtained through probit

procedures, then consistent estimates for equation (2) can be obtained

by substituting the resulting predicted values of Xi into equation (2).

One issue that arises with these procedures for controlling for unobserved

differences between program and comparison groups is how to identify

84

110
equations (1.) and (2) when predicted values of X are used. Conceptually,

as suggested by Barnow, Cain, and Goldberger (1978), equations (1) ane

(2) are identified by the inherent nonlinearities in X, even if the X's

and Z's are identical. In practice, however, these nonlinearities often

tun out to be ineffective for identifying behavioral models, as in equations

(1) and (2), and parameter restrictions are needed for identification.

The parameter restrictions amount to observing variables that can be

reasonably modeled as affecting the decision to participate in the program

but not directly affecting the behavior of interest.

In our case, we have variables that relate to participation in

Job Corps from the pre-enrollment neighborhoods of sample members (both

Job Corps and comparison) for years prior to the survey (specifically,

fiscal year 1975). These variables affect the knowledge of the program

and, hence, the decision to participate. However, they can reasonably

be assumed not to affect the behavior of interest, which is supported by

comparing the pre-enrollment neighborhoods where our Corpsmembers and

comparison sample lived. The Job Corps and comparison neighborhoods were

very similar in terms of employment, income, racial/ethnic, and age

distributions that are relevant for the labor-market behavior of youths

(see Kerachsky and Mallar, 1978).

Once the predicted X variable was added, the correlation of error

terms for the same individual over time was accounted for in an errorcomponents (or variance-components) model. This model should yield greater

efficiency for coefficient estimates and more accurate estimates of standard

errors than OLS (for more details, see Maddala, 1971; Nerlove, 1971a and

85
1971b; and Wallace and Hussain, 1969).1/ A two-stage proceduie was used

with the variance component for individual youths, estimated from a

first-stage OLS regression (including the predicted A variable) and then

substituted into a second-stage generalized least squares framework..?

/

The computational program enabled us to include individuals with varying

lengths of time, and allcwed individuals to be missing periods of data

(early, late, or intervening quarters), which is essential for our appl:.-

cation because Corpsmembers' pos4proaram data start at varying points in

3/ time. Seasonality and time trends across individuals are specified

explicitly in the regression equations (there is only an individual component, and no time component, included in the error term for our

econometric model).

The explanatoiy and predetermined variables used as controls in

our regressions are documented in Table IZI.10. These variables control

for age (5 variables); pre-enrollment education (3 variables); race/

ethnicity (4 variables); pre-enrollment healt1 (1 variable); ceasonality

1 /The point-in-time probability models with binary dependent

variables (e.g., the probabilities of military service during the survey

week, of havinga high school diploma or GED by the survey week, and of

being in jail during the survey week) were estimated with probit maximum

likelihood techniques, with one observation vr individual youth.

2 /The lagged values of dependent variables from pre-enrollment

cannot reasonably be assumed to be strictly predetermined when we pool

observations for individual youths over time. These lagged dependent

variables are endogenous in general if we assume (as we must) that equation

error terms are correlated over time for individuals. However, the use

of estimators of error variances and covariances from ordinary least

squares residuals will still yield consistent estimators of coefficients

in a second-stage generalized least squares technique when the errorcomponents model is appropriate, as we assume in our estimation procedure

(for more details and proofs, see Wallace and Hussain, 1969, and Nerlove,

1971a and 1971b).

2

/ For documentation of the computer program, see Avery (1975).

Fir) 1.12
(3 variables) and time trends (2 variables); and pre-enrollment experiences

with employment (1 variable), welfare (1 variable), illegal activities

(3 variable), and drug use (2 variables). The variables used in the Job

Corps participation, employment, and related equations are similar except

for the two variables on youths from pre-enrollment neighborhoods who

enrolled in Job Corps during fiscal year 1975, which are included in

the Job Corps participation equation but not in the equations for

employment and related behavior.

The probit estimates for the probability of being in Job Corps are shown in Tables III.11 and 111.12 for males and females without children,

respectively. The two most important points to note are that (1) the

identifying variables (#JCMEN-75 and VC:MEN-75) are highly significant and,

hence, will provide good identification, and (2) these equations are exceptionally good predictors of who is in the Job Corps versus comparison

groups, as evidenced by the exceptionally high chi-square statistic fdr the

equation.

Tables 111.13 and 111.14 show our regression estimates for employr

ment, Tables 111.15 and 111.16 show our regression estimates for college

attendance, and Tables 111.17 and 111.18 show our regression estimates for

number of arrests.-1/

The coefficients on,,the Job Corps variables in these

1 "The The,standard errors and t-statistics given in Tables 111.13 through

111.18 may be slightly biased because the estimates of the standard errors

were obtained from a regression program which does not account for the implicit

heteroscedasticity when controlling for unobserved differences between Corpsmembers and the comparison sample via the Heckman (1979) approach. In practice,

however, the standard errors and t-statistics from the regression program are

usually very close to their unbiased counterparts, especially when the coefficients fot the adjustment variables are statistically insignificant (which is

usually the case with our estimates). Therefofe, the standard errors and

t-statistics shown are approximately accurate and are indicative of the true

values of these statistics. Maximum likelihood estimates could yield some

gains in terms of the' statistical efficiency or coefficient estimates and

of unbiasedness for estimates of the standarTerrors. With our large sample,

si.es, however, maximum likelihood estimation would be prohibitively expensive.

87,

113
representative regression equations are the ones used to construct the

tables in the text. For employment and college'attendance, the coefficient

estimates for the lambda variables (i.e., 6) are small, negative, and

statistically insignificant. This indicates that Corpstembers would

tend to have slightly lower employability and college attendance than the

comparison sample in the absence of,Job Corps, and that slightly smaller

estimates of the positive'Job Corps effects would be obtained if we did

not control for unobserved differences between the CIrpsmember and the

comparison groups. The coefficient estimates for the lambda variables

(i.e., 6) in the arrest equationi are'small, positive, and statistically

insignificant( This indicates that Corpsmembers would tend to be slightly

more criminally inclined than the comparison sample in the absence of

Job Corps, and that slightly smaller estimates of reductions in crime

for Corpsmembers would be obtained if we did not adjust for unobserved

differences between the Job Corps and comparison groups.

There are also interesting aspects t, the other control variables,

which will not be fully developed here because they are not of primary

.nterest. Some of these other effects can be highlighted briefly as

follows: (1) youths generally do better in the labor market as they

become older; (2) youths with higher pre-enrollment educations generally

do better both in the labor market and at college attendance; (3) minority

youths generally do worse than whites in the labor market; (4) employment

is highest in the summer and fall, and college attendance is lowest

in the summer for youths; (5) the employability of youths was improving

over' the short posiprogram time period but at a slower rate as time passed;

and (6) youths who had better pre-enrollment work and related histories

generally did much better than other youths in those activities during

subsequent time periods.

88
1

CHAPTER III

APPENDED TABLES
TABLE III.10

mossm or EXPLANATORY VARIABLES!'

b/

. Variable Label Definitiog,

AGE the youth's age in years.

AGE18 1 if the youth is at least eighteen years old;

0 otherwise (allows for an intercept change at eighteen).'

OVER18 AGE minus 18 if AGE if greater than eighteen; 0 otherwise

(allows for a slow change at eighteen).

AGE21 1 if the youth is at least twenty-one years old;

0 othirwise (allows for an intercept change at

twenty-one) .

OVER21 AGE minus 21 if AGE is greater than twenty-one;

0 otherwise (allows for a slope change

at twenty-one).

EDUCATION-PRE the youth's highest grade of formal education

in years completed before the Job Corps

enrollment date (preenrollment--defined

as six months before the baseline interview

for the comparison sample).

DIPLOMA-PRE m 1 if the youth had a high school diploma

or equivalency (allows for an intercept.

change with high school diploma orquivalency).

EDUCATION127PRE 1 if the'youth had completed atleast twelve

years of formal education at preenrollment

(allows for-an additional intercept change at

high school diploma).

EDOVER12-PRE EDUCATION-PRE minus 12 if EDUCATION-PRE is

greater than 12; 0 otherwise (allow! for an

intercept change at twelve).'

COLLEGE-PRE 1 if the youth ever attended college

before enrollment; 0 otherwise.

BLACK 1 if the youth is black and not of Hispanic

origin; 0 otherwise:

HISPANIC 1 if the youth is a person of Mexican,

Puerto Rican, Cuban, Central or South

American, or other Spanish culture or,

origin, regardless of race; 0 otherwise.

AMERICAN INDIAN 1 if the youth is an American Indian or

Alaskan native; 0 otherwise. : OTHER'RACE/ETH

HEALTH PROS-BASE

1 if the youth is from a race/ethnicity

other than WHITE, BLACK, HISPANIC, or

AMERICAN INDIAN (mostly Alien or Pacific

Islander); 0 otherwise.

1 if the youth reported a serious health

problem in the baseline.interview that

both limited the kind or amount of work

that (s)he could do and had lasted for

at least one year (misses health problems

present at preenrollment that were cured

before the baseline interview); 0 otherwise

FALL 1 if the quarter is during the fall season

(September, October, and November); 0 otherwise.

90
Table 111.10 (continued)

Variable-b/

DefinitionE/

CAT1 12 to 18

CAT1 18 to 24

CAT2 0 to 6

CAT2 6 to 12

CAT2 12 to 18

CAT2 18 to 24

CAT3 0 to 6'=

CAT3 6 to,. 12

CAT3 12 to .18

CAT3 18 to 24

1 if the youth is a program completer

and the quarter is twelve to eighteen

months after (s)he terminated from Job

Corps; 0 otherwise.

1 if the youth is a program completer

and the quarter is eighteen to twenty-four

months after (s)he terminated trap Job

Corps; 0 otherwise.

1 if the youth is a partial completer

and the quarter is zero to six months

after (s)he terminated from Job Corps;

0 otherwise.

1 if the youth is a partial completer

and the quarter is six to twelve months

after (s)he terminated from Job Corps;

0 otherwise.

1 if the youth is a partial completer

and the quarter is twelve to eighteen

months after (s)he terminated from Job

Corps; 0 otherwise.

1 if the youth is a partial completer

and the quarter is eighteen to twenty-four

months after (s)he terminated from Job corps;

0 otherwise.

1 if the youth is an early dropout and the

quarter is zero to six months after (a)he

terminated from Job Corps; 0 otherwise.

1 if.thw youth is an early dropout and

the quarts! is six to twelve months after . (s)he terminated from Job Corps; 0.otherwise:

1 if the youth is an early dropout and the

quarter is twelve to eighteen months after

(s)he tirminated from Job Corps; 0 otherwise.

1 if the youth is an early dropout and the

quarter is eighteen to twenty -four months

after (s)he terminated from Job carpet0

otherwise.

1 /The lagged values of dependent variables from preenrollment cannot reasonably be assumed

WIN strictly predetermined when we pool observations for individual youths over time. These

lagged dependent variable are endogenous in general if we assume (as we must) that equation error terms are correlated over time for individuals. However, the use of estimators of error variances

and covariances from ordinary least squares residuals will still yield consistent estimators of

coefficients in a second-stage generalised least squares technique when the error-components model

is appropriate, as we assume in our estimation procedure (for more details and proofs, see Wallace

and Hussain, 1969, and Marlowe, 1971a and 1971b).

12/The explanstory'variables are stringed in.this table approximately in the, order that

findings are presented in subsequent tables.

g/The preenrollment period is defined as six months before the baseline interview for the'

comparison sample, because Corpsmembers had been in' the program approximately sik months on average

when the comparison youths were interviewed. The data are arrayed into quarterly, aggregatei by

calendar quarters according to the seasons--summer (June, July, end August), fall (September, October,

and November), winter (December, January, and February), and spring (March, April, and Hay)--which

differ from the usual fiscal quarters but provide better controls'for seasonality. Time-dependent

variables- -such as those related to age, calendar time, and length of time out of Job Corp.-lire defined

for the midpoint of each quarter.
TABLE III.II

PROBIT ESTIMATES FOR Thi PrOBABI TY

OF BEING IN THE JOB CORPS SAMPLE:

Explanatscr

Variable-1

Coefficient

:stimate

Standard

Error

c/ T- Statistic- T-Statistic

Ta1311.

Derivative

at Point

d/ of Means-, CONSTANT -2.297 1.047 -2.193 -0.375 AGE 0.214 0.064 3.329 0.035 'IGE18 -0.006 0.083 -0.070 -0.001

OVER18 -0.521 0.117 -4.464 -0.085

AGE21 -0.681 0.281 -2.425 -0.111

ovEr -0.344 0.171 20.201 -0.056'

EDI :ON -Plar -0.138 0.025 -5.420 -0.022 DIPLOMA-PRE -0.278 0.144 -1.932 -0.045

EDUCATION12-PRE 2.588 4.623 0.560 0.423 EDOVER12 PRE 1.021 0.172 5.945 0.167 BLACK -0.014 0.061

. -0.225 -0.002 HISPANIC -u.067 0.097 -0.689 -0.011 AMERICAN INDIAN 0.342 0.147 2.319 ,0.056 HEALTHPROB-BASI 0.133 0.130 1.020 0.022 ANYEMPLOY-PRE 0.137 0.055 .2.507 0.022 ANYSELF-PRE 0.060 0.104 0.575 0.1.10 ANYARRESTPPRE 0.180 0.069 2.593 0.029

HJ /ALCOHOL -PRE 0.055 0.064 0.872 0.009 COKE/HEROIN-PRE 0.516 0.100 '5.149 0.084

.., IMMEM-75 0.002 0.0004 3.989 0.0003

90CMIM-75 0.006 0.0004. 13.663 0.001

Number of.observations 4,155

Kean of dependent variable 0.829

Chi-Square dtatistic for equation 1 698.134

Degrees of freedom 20 Significance level > 99% statistical confidence

/Maximum likelihood estimates are computed by an iterative Newton-Rapheson procedure.

11/For definitions of explanatory variables, see Table III.10.

o- / The t-statistic equals the coefficient estimate divided by its standard error. However, the

numbers in this column are more accurate than can be obtained from the preceding. two column, because

of less rounding error.

d / The The change in probability associated with a marginal change in the relevant explanatory variable

equals the coefficient estimate times the value of the density function which is obtained here with the

mean values for all explanatory variables (i.e., the point of means). For binary explanatory variables it

is more appropriate to use the difference between the distribution function values with and without the

relevant coefficient with all other explanatory variables at their mean values This latter approach is

used in this report to obtain impact estimates for probability variables.

92

11 8
TABLE 111.12 PROBIT ESTIMATES FOR THE PROBABILITY OF

BEING IN THE JOB CORPS SAMPLE: FEMALES WITHOUT CHILDREN-/

Variable

Coefficient Standard

Ermr T-Statistic

Partial

Derivative

at Point

of means

COMSTANT 1.31t -2.687 -0.624

AGE .0.191 0.080 2.386 0.034

AGE18 -0.204 0.111 -1.838 a -0.036

OVIR18 -0.153 0.156 -0.983 -0.027

A021 1.641 6.995 0.235 0.291

OVER11 0.302 0.280 1.079 0.054

EDUCATION -rga -0.085 0.043

ti -1.969 -0.015

DIPLOMA -PRE -0.065 -0.285 -0.012

INCATION12-PRE 0.021 0.353 0.060 0.004

EDOVER12-PRE 1.064 0.253 4.207 0.188

SLACK 0.592 0.092 6.410 0.105 HISPANIC 0.719 0.148 4.857 0.127 AMERICAN INDIAN 1.151 0.243 4.738 0.204

HEAMPROB-BASE 0.060 0.193 .0.313 0.011 ANYEMPLOY-PRE 0.235 0.084 2.809 0.042

ANYWELF-PRE -0.223 0.149 -1.494 -0.040 ANYARRESTS-PRE ,-0.085 0.198 -0.430 -0.015

MJ/ALCOHOL-PRE 0.218 0.087 2.512. 0.039

COKE/HEROIN-PRE 0.381 0.156 2.442 0.067

JCHIM-75 0.003 0.001 4.498 0.001

WCMEIM-75 0.007 0.001 8.886 0.001

y. NUmber of observations 1,710

Mean of dependent variable 0.760

Chi-Square statistic for equation 555.672

4, Degrees of freedom 20 o Significance level > 99% statistical confidence

1/Maximum likelihood estimates are computed by an iterative Newton-Rapheson procedure.

OfFor definitions of explanatory variables, see Table III.10.

LiThe t-statistic equals the coefficient estimate divided by its standard error. However, the

numbers in this column ere more accurate than can be obtained from the preceding two columns because of

less rounding error.

d / The The change in probability associated with a marginal change in the relevant explantory

variable equals the coefficient sadists times the value of the density function which is obtained.

here with the mean values for all explanatory variables (i.e., the point of means). For binary

explanatory variables it is more appropriate to use the difference between the distribution fundtion

values with and without the relevant coefficient with all other explanatory variables at their mean

values. This latter proach is used in this report to obtain imi.act estimates for probability variables.

93

113
ABLE 111.13

REGRESSION ESTIMATES FOR FRACTION OF TINS EMPLOYED:

a/ MALESImp toyy

VariableCo. .c t Estimate

St

Error' T-StatisticCONSTANT 0.061 0.393 0.154 AGE 0.008 0.023 0.327

1GE18 0.055 0.027 , 2.025

OITER18 -0.006 0.024 -0.270

A0121. -0.007 0.014 -0.498

OVE121 0.018 0.012 1.466 EDUCATION-PRE 0.006 0.006 0.963 DIPLOMA-PRE 0.088 0.036 2.418

IDDCATION1Z-PRE -0.054 0.043 -1.262

&LACK -0.124 0.015 -8.201 HISPANIC 7o.ti 0.022 -2.619 AMERICAN INDIAN -0.168 0.035 -4.858

OTHER RACl/ETH -0.098 0.057 .-1.711 HIALTHPROB-BASE -0.0005 0.029 -0.016 ratz 0.003 0.)08 0.341

-0.041 0.008 -4.877

SPRING, a 0.03 0.009' -4.062

. MOTHS 0.028 0.003 10.474,

&JCL'S SQUARED -0.001 0.0001 -7.876

%EMPLOY-PR 0.158 0.017 9.147

94WELF-PRE. -0.061 0.032 -1.889 ANTARRESTS-PRE -0.02b 0.016 -1.235

NJ /ALCOHOL -PRE 0.028 0.01: 1.873 COM/HEROIN-PRE -0.009 0.022 -0.410 LAMBDA -0.039 0.027 -1.472

CAT1 0 To 6 0.057 0.044 1.303

0 CAT1 6 To 12 '0.131 0.044 2.964

CAT1 12 To 18 0.155 0.044 3.490 CAT1 18 To 24 0.194 0.047 4.162

CAT2 0 To 6 -0.028 0.045 -0.614

CAT2 6 To 12 0.049 0:045 1.079 CAT2 12 To 0.044 0.046 0.960

CAT2 .18 To 24 0.076 '0.048 1.598 CATS 0 To 6 0.052 -0.024

20
Tana tory Coe cient

Variablew Estimate

tan era

Error T-Sta-istic- . 'CA73 6 To 12 -0.001 0.053 -0.015

, CAT3 12 To 18 0.047 0.054, 0.881

CAT3 18 To 24 0.083 0.054 1.538

Numbei of observations = 14,506 k Number of individuals = 2,336

Average number of time periods = 6.209

Indiclass correlation coefficient.(proportion of.error variance attributable to individual

component)=0.372

Mean of dependent Variable = 0.546

F-Statistic for equation = 35.902

Degrees of freedom = 36; 14,469

Signifilance level = > 99% statistical confidence

1./Consistent generalized least squares estimates for civilians aril obtained withAl two-stage

procedure under the assumptions of an error-components regfession model (see Avery, 1975). 4 consistent

animate of LAMBDA is used based on the separate probability model of being, in the Job Corps sample

discussed previously. Using a consistent estimate of LAMBDA Will not affect the consistency of coils efficient estimates but may bias the standard errors and t-statistics(see footnote c below).

12/For definitions of explanatory variables, see Table III.10:

EiThe standard errors and t-statistics given iu this table may be,- slightly biased because the

estimates of the standard errors were obtained from a regreision program which does not account for.the

implicit heteroscedasticity when controlling for unobserved differences between Corpsmembers end tell

compasison sample via the Heckman (1979) approach. In practice, however, the standard orrorsanid,,

t-statistics from the regression program are usually very close to their unbiased counterparts, especially

when the coefficients for the adjustment variables are statistically insignificant (which is usually the

case with our estimates). Therefore, the standard errors and t-statistics presented here are approxiaitely

accurate andare indicative of the true values of these statistics.

g/The t-statistic equals the coefficient estimate divided dy its standard error. However, the

numbers in this column are more accurate than can be obtained from the preceding two columns because

of less rounding error.

ti

95
TULE 122.14

REOMESSION ESTIMATES mit FRACTION OE 72!! EXPLaTED:

EXHALES WITHOUT CHILDPIP

EXplanaticy

Verishlrf

Coefficient

Estimate

Panders'

Error -/ 2-Statistical

*

. CONSTANT' -0.148 0.546 -0.271

AC!. 0 0.009 0.032 0.287

acids -oalli 0.040 -0.271

OVER18 0.003 0.034 0.077

. £0121 0.005 0.021 .0.244

OVER21 u 0.027 0.019 1.423

EDUCATION-Pp 0.022 0.010 2.201

DIPLCIli-M 0.019 0.056 0.337

. EDUCATION12-M '0.016 0.063 0;252

BLACK -0.151 0.026 -5.590

AISPANIC -0.027 0.039 -0.694

ANERICAN_INDIAN 4 -0.151 0.068 -2.218

0211101 RAC!/Em

de 0.021 0.099 0.209 HEALISPROI-RASE -0.056 0.048 -1.178 FALL 0.054 0.012 4.504 WINTER 0.005 0.012 0.389

SPRING -1.0.030 0.013 -2.322

41N= 0.008 . 0.004 2.096

MONTHS SQUARED - 0.0001 0.0001 -0.596

%EMPLOY-PRE 0:171 0.029 5.832 HALE -PRI -0.095 % 0.040 -2.356

,. ANTAINLITS -PP -0.111 0.048 -2.322

NJ/ALCONOL-ERE 0.026 9.021 1.245

COSE/HIROIN-ERE 0.012 ' 0.038 0.324 LAMBDA , -0.006 0.033 -0.190 - CAT1 0 To 6 0.070 0.052 1.348

CAT1 6 16 12 0.172 0.052 3.289

CAT1 11 To 18 0.176 0.053 3.310

CAT1 18 To 24 0.220 'Loss 3.826

CAT2 0 To 6 -0.004 '0.055 -0.080

CAT2 6 To 12 0.059 0.055 1.058

CAT2 12 to 18 0.081 CA 0:057 1.413 CAT2 18 To 24 0.058 0.063 0.913
Table 111.14 (continued)

Explanatiyy Coefficient

Variable- Estimate

Standard

Error

d/ T-StatisticCAT3 0 To 6 0.018 0.072 0.245

CAT3 6 To-24 - 0.030' -0.403

CAT3 12 To 18 0.054 0.079 0.690

CAT3 18 To 24 -0.095 0.083 -1.144

Number of observations le 5,887

Number of individuals 1,042

Average number of time periods 5.649

Intraclatt'correlation coefficient (proportion of error variance attributable to individual

component)=0.423

Mean of dependent variable * 0.392

F-Statistic for equation = 14.903

a Degrees of freedom 36; 5,850

_e.Significance level * > 99% statistical confidence

!"Consistent Consistent generalized least squares estimates for civilians are obtained with a two-stage

procedure under the assumptions of an error-components regression model (see Avery, 1975). A

consistent estimate of LAMBDA is used based on the separate probability model of being in the

Job Corps sample discussed previously. Using a consistent estimate of LAMBDA will not affect

the consistency of coefficient estimates but may bias the standard errors and t-statistics (see

footnote c below).

sk/For definitions of explanatory variables, see Table III.10.

-The The standard errors and t-statistics given in this table may be slightly biased because the

estimates of the standard errots were obtained from a regression program which does not.,account

for the implicit heterescedastpity when. controlling for unobserved differences between Corpsmembers

and the comparison sample via the Heckman (1979) approach. In practice, however, the standard

errors and t-statistics from the regression program are usually very close to their unbiased

counterparts, especially when the coefficients for the adjustment variables are statistically

insignificant (which is usually the case with our estimates). Therefore, the standard errors

And t-statistics presented here are approximately accurate and are indicative of the true

valuee8f these statistics.

1/TheNt-statistic equals the coefficient estimate divided by its standard error. However,

the numbers iethis'column are more accurate than can be obtained from the Oreceding two columns

because of less rounding error.

97
TABLE III.1S

REGRESSION ESTIMATES FOR FRACi;ON OF TIME

IN COLLEGE: MALES -' -

Emplanatecy

Variable-/-

Coefficient

Estimate

Standard/ Error- d/ T-StatisticCONSTANT -0.015 0.092 -0.168 AGE -0.001 0.005 -0.215

AGE18 0.003 0.006 0.493

OVERI8 0.002 0.006 0.369

AGE21 -0.005 d.003 -1.391

OVER21 -0.003 0.003 -1.186 EDUCATION-PRE 0.002 0.002 1.325 DIPLONA-PRE -0.006 0.010 -0.592

EDUCATIONI2-PRE 0.022 0.012 1.902 BLACK - 0.0001 0.004 -0.026 HISPANIC 0.011 0.006 1.738 AMERICAN INDIAN 0.003 0.010 0.322

.0THER.RACE/ETH -0.0001. 0.016 -0.007

HEALTHPROB -BASE -0.009 0.008 -1.091

FALL 0.008 0.002 4.512

G WINTER 0.011 0.002 5.569 SPRING 0.009 0.002 4.253

MONTHS 0.0002 0.001 0.296

MONTHS SQUARED - 0.00002 0.00002 -0.863

%EMPLOY-PRE 0.002 0.005 0.510

WILF-PRE -0.005 0.009 -0.609 ANTARRESTS-PRE 0.003 0.004 0.622

NJ/ALCOHOL-PRE -0.003 0.004 -0.642

COKE/HEROIN-PRE 0.009 0.006 1513

COLLEGE-PRE 0.917 0.026 0.652 LAMBDA -0.010 0.007 -1.405

CAT1 0 To 6 0.019 0.012 1.538 CAT1 6 To 12 0.029 0.012 2.405

CAT1 12 To 18 0.035 0.012 2.876

CAT1 18 To 24 0.030 0.013 2.405

CAT2 0 To 6 0.014 0.012 1.113

CAT2 6 To 12 0.020 0.012 1.571

CAT2 12 To 18 0.023 0.013 1.873

h 98 194
Table III.15 (continued)

txplanaticy

Variable=

Coefficient

Estimate

Standard

Error

d/ T-Statistic

C122 18 To 24 0.023 0.013 1.816

CATS 0 TO 6 0.014 0.014 0.999

CAT3 6 To 12 0.015 0.014 1.076

CAT3 12 To 18 0.019 0.015 1.335

CAT3 18 To 24 0.021 0.015 1.434

Number of observations a 14,506

Number of individuals in 2,336

vie Average number of time periods 6.209

Intraclass correlation coefficient (proportion of error variance attributable to individual

componene)=0.492

Nein of dependent variable 0.013

F-Stitistic for equation a 3.222

Degrees of freedom a 37; 14,468

.Significance level w.> 99% statistical confidence

Consistent generalized least squares estimates forcivilians are obtained with a two-stage,

procedure under the assumptions of an error-components regression model (see Avery, 1975). A consistent

estimate of LAMBDA is used based on the separate probability Model of being in the Job Corps sample

discussed previously. Using a consistent estimate of LAMBDA will not affect the consistency of

coefficient estimates but may bias the standard errors and t-statistics (see footnote c below):

12/For definitions of explanatory variables, Ise Table I11.10..

c/ The standard errors and t-statistics given in this table may be slightly biased because the

estimates of the standard errors were obtained from a regression program which (ces not account for the

implicit heteroscedasticity when controlling for unobserved differences between Corpsmembers and the

comparison sample via the Heckman (1979) approach. In practice, however, the standard errors and

t-statistics from the regression program are usually 'very close to their unbiased counterpirts, especially

when the coefficients for the adjustment variables are statistically insignificant (which is usually

the case with our estimates). Therefore, the standard errors and t-statistics presented here are

approximately accurate and are indicative of the true values of these statistics.

4/The t-statistic equals the coefficient estimate divided by its standard error. However. numbers in this column are more accurate than can be obtained from the preCeding two columns

because of less rounding error.

99

1
TABLE 111.16 REGRESSION ESTIMATES FOR FRACTION OF TOE IN COLLEGE:

FEMALES WITHOUT CHILDREN:1' Explanatpy

Variabler'

Coefficient

Estimate

Standard,

Cf Errordi T-StatisticCONSTANT -0.115 0.220 -0.522 AGE 0.001 0.013 0.097

AGE18 0.022 0.016 1.387

OVER18 -0.016 0.014 -1.173

AGE21 0.001 0.008 0.169

OVER21 0.004 0.008 0.552 EDUCATION-PRE 0.006 0.004 1.430 DIPLOMA-PRE 0.049 0.025 2.005

EDUCATION12-PRE -0.004 0.028 -0.143 BLACK -0.012 0.012 -1.062 HISPANIC -0.001 0.017 -0.058 AMERICAN INDIAN -0.034 0.030 -1.151

OTHER RACE/ETH 0.009 0.043 0.217 HEALTHPROB-BASE 0.021 0.021 0.984

.... FALL 0.028 0.005 5.813 WINTER 0.024 0.005 5.038 SPRING 0.017 0.005 3.248 MONTHS -0.0003 0.002 -0.228

MONTHS SQUARED 0.0001 0.0001 0.966

%EMPLOY-PRE 0.031 0.013 2.429

WELF-PRE 0.052 0.018 2.926

ANYARRESTS -PRE 0.002 0.021 0.100

MJ/ALCOHOL-PRE 0.003 0.009 0.361

COKE/HEROIN-PRE -0.013 0.017 -0.808

CQLLEGE -PRE 0.052 0.039 1.330 LAMBDA -0.015 0.014 -1.050

CAT1 0 To 6 0.029 0.023 1.282

qAT1 6 To 12 0.047 0.023 2.054

CAT1 12 To 18 0.043 0.023 1.858

CAT1 18 To 24 0.060 0.025 2.424

CAT2 0 To 6 0.015 0.024 0.636

CAT2 6 To 12 s 0.024 0.024 1.010

CAT2 12 To 18 0.023 0.025 0.928

100
Table 111.16 (continued)

Explantoky

VariableCoefficient

Estimate

Standard

c/ Error- di T-StatisticCAT2 18 To 24 0.025. 0.027 0.928

CAT3 0 To 6 0.007 0.031 0.217

CAT3 6 To 12 0.02S 0.033 0.768

CAT3 12 To 8 0.027 0.03 0.793

CAT3 18 To 24 0.071 0.035 2.015

Humber of observations 5,887

Humber of individuals 1,042

Average number of time periods s 5.649

Lntraclass correlation coefficient. (proportion of error variance attributable to individual component)m0.490

Haan of dependent variable 0.037

1-Statistic for equation 4.712

Degrees of freedom 37; 5,849

Significance level > 99% statistical cdnfidence

Consistent generalised least squares estimates for civilians are obtained with a -two-stage

procedure under the assumptions of an error-components regression model (see Avery, 1975). A consistent

estimate of LAMBDA is used based on the separate probability model of being in the Job Corps sample

discussed previously. Using a consistent estimate of LAMBDA will not affect the consistency of

coefficient estimate* but may bias the standard errors and t-statistics (see footnote c below).

I/Tor definitions of elplanatory variables, see Table 1II.10.

I/The standard errors and t-statistics given in this table may be slightly biased because the

estimates of the standard errors were obtained ham a regression program which does not account for

the implicit beteroscedasticity when controlling for unobserved differences between Corpsmembers and the

comparison sample via the Heckman (1979) approach. In practice, however, the standard errors and ttatistics from.the regression program are usually very close to their unbiased counterparts, especially

when the coefficients for the adjustment variables are statibtically insignificant (which is usually the

case with our estimates). Therefore, the standard errors and t-statistics presented here are

approximately accurate and are indicative of the true values of these statistics.

g/The t-statistic equals the coefficient estimate divided by its standard error. However,

the numbers in this column are more accurate than can be obtained from the preceding two columns

because of less rounding error.
TABLE VIII.17 REGRESSION ESTIMATES FOR MUNBEI,OF ARRESTS

PER QUARTER: MALES -' Explanatsyy

variable-

, Coefficient

Estimate

Standard Error- T-Statistic di CONSTANT 0.100 0.247 '' 0.407

AGE -0.001 0.015 -0.042

AGE18 -0.008 0.018 -0.435

OVER18 -0.006 0.015 ' k' -0.424 AGE21 -0.002 0.009 -0.207

OVER21 0.010 0.006 1.519 EDUCATION-PRE -0.002 0.002 -1.168

DIPLOMA -PRE 0.016 0.013 1.239

. . EDOCAT/0N12 -PRE -0.011 0.015 -0.714 BLACK -0.012 0.005 -2.285 HISPANIC -0.008 0.008 -1.013 AMERICAN INDIAN 0.015 .0.012 1.196

OTHER RACE /ETH -0.004 0.020 -0.203 HEALTHPROB-BASE -0.012 0.010 -1.167 =FALL 0.001 0.006 0.212

WINTER 0.003 0.006 0.551

SPRING ',0.005 .

.Z. 0.007 -0.721

MONTHS -0c003 .0.002 -1.726

MONTHS SQUARED 0.0001 0.0001 1.822

VEHPLOT -PRE 0.007 0.006 1.219

WILY-PRE -0.002 0.012 -0.133

ANTI/MISTS-PRE 0.034 0.006 0,096

NJ/ALCOHOL-PRE 0.016 0.005 2.933

COKE/HEROIN-PRE 0.011 0.008 1.462 LAMBDA 0.010 0.009 1.073

Cal 0 To 6 -0.026 0.016 -1.624

Cal 6 To 12. -0.015 0,016 -0.914

1 CAT1 12 To 18 -0.001 0.017 -0.036/

r4

Cal 18 To 24 -0.009 0.019 -0.485

CAT2 0 To 6 -0.004 0.017 -0.236

CAT2 6 To 12 -0.003 0.017 -0.189

CAT2 12 To 18 0.007 0.017 0.410

CAT2 18 To 24 0.032 0.020 1.612

CAT3 0 To 6 -0.023 0.021 -1.075

102
Table 111.17 (continued)

Ixplanatgry Coefficient Standard

Variable- Estimate Error T- Statistic'

CAT3 .6 To 12 -0.027 0.022 -1.241

CAT3 11 To*18 -0.010 0.023' -0.455

CAT3 18 To 24 -0.016 0.023 -0.700

Number of observations * 14.406

0 Number of individuals is 2;336

Average number of time periods a 6.209

Intraclass correlation coefficient (proportion of error variance attributable to individual

component) =.0,013,

Mean of dependent variable * 0.040

F-Statistic for equation =-4.070

Degrees of freedom a 36; 14,469

Significance level a > 99%-statistical confide:ice

a/Consistent generalized least squares estimates for civilians are obtained with a two-stage

procedure under the assumptions of an'error-components regression model (see Avery, 1975). A consistent

estimate of LAMBDA is used-based on the separate probability model of being in the Job Corps sample

discussed previously. Using a,consistent estimate of LAMBDA will not affect the consistency of

coefficient estimates but may bias the standard errors and t-statistics (see footnote c below). The

impact estimates in Tables 111.6 and 111.7 are twiceas large as shown here because the numbers are

presented on a six-month rather than quarterly basis in those tables.

14/For definitions of explanatory variables, see Table I/1.10.

EiThe standard errors and t-statistics given in this table may be slightly biased because the

estimates of the standard errors were obtained from a regression program which does not account for the

implicit heteroscedasticity when controlling for unobserved differences between Corpsmembers an4 the

comparison sample via the Heckman (1979) approach., In practice, however, the standard errors and

t-statistics from the regression program are usually very close to their unbiased counterparts,

-- especially when the coeff4cients for the adjustment variables are statistically insignificant (which

is usually the case with our estimates). Therefore, the standard errors add t- statistics presented

here are approximately accurate and are,indicative of the true vapie of these statistics.

a'The t-statistic equals the coefficient estimate divided by its standard error. However,

the numbers in this column are more accurate than can be obtained from the preceding two columns

because of less rounding error.
TABLE 111.18

REGRESSION ESTIMATES FOR NUMBER OF ARRE1TS PER QUARTER:

FEMALES WITHOUT CHILDREN -1

Uplanatry.

Variable-'

Colifficient

Estimate

Standard

c/ Error- T-Statistic-r, CONSTANT

AGE

AGE18

OVER18

0.063

-0.002. 0.008

0.004

0.094

0.006

0.007

.o.pos

0.673

-0.438

1:027 0.694

1021 - -0.007 0.004 -1.921

OVER21 -0.002 0.003 -0.776 EDUCATION-PRK -0.002 0.001 -2.091. DIPLOMA-PRE -0.004 0.005' -0.753

EDUCATION12-PRE 0.008 0.006. 1.318 BLACK -0.001 0.003 -0.474 HISPANIC -0.003 0.004 -0.738

AMERICAN 0.004 0.007 0.580

OTHER RACE/ETH -0.006 0.009 -0.639

HEA4THPROB-BASE 0.004 0.004 0.905 FALL 0,10% 0.003 1.312

WINTER* -0.001 0.003 -0.197 SPRING -0.003 0.003 -0.989 MONTHS 0.0005 0.001 0.618

MONTHS SQUARED' -0.00002 0.00003 -0.607.

%EH:PLOY-PRE 0.001 0.003, 0.348

%WELF -PRE ' -0.004 0.004 -0.973 ANYARRESTS-PRE -0.002 0.005 -0.494

11.1/ALCOHOL-PRE 0.004 0.002 1.920 COKE/HEROIN-PRE -0.001 0.004 -0.278 LAMBDA 0.005 0.003 1.634

CATI C To 6 -0.007 0.005 -1.362

CAT1 6 To 12 -0.010 0.006 -1.850

CAT1 12 To 18 -0.011 0.006 -1.939

CAT1 18 To 24' -0.008 0.007 -1.094

CAT2 0 To 6 -0.006 0.006 -1.099

CAT2 6 To 12 -0.010 0.006 -1.543

CAT2 12 To 18 -0.002 0.007 -0.283

CAT2 18 To 24 0.008 0.008 0.946

104 130
Table 111.18 (continued)

_Explanatsyy

variable

Coefficient

Estimate

Standard

Error T-Statisticd/

CAT3 O'To 6 -0.011 0.009 '-1.320

- ,CAT3 6 To 12 -0.011 0.010 714

CAT3 12 To 18 -0.014 0.011 -1.319

CAT3 18 To.24 0.019 0.012 1.644 Number of,observatioMs 5,887

Number of individuals 1,042

Average number.of time periods a 5.649

Intraclass correlation coefficient (proportion of error variance attributable to indiVidual

component) a 0.0 . Mean of dependent variable a 0.005

F-Statiitic for'equation211.374

Degreei of-freedom 36; 5,850

O Significance level > 90% statistical confidence

al'Consistent Consistent generalized least squares estimates foi civilians are obtained with a two-stage

procedure under the assumptions of an error-components regression model (see Avery, 1975). 'A consistent

estimate of LAMBDA is used based on the separate probability model of being in the Job Corps sample

discussed previously. Using a consistent estimate of LAMBDA will not affect the consistency of

coefficient estimates but may bias the standard errors and t-statistics (see fbotnote c below).; The

impact eitimateslin Tables 111.6 and 111.7 are twice as large as shown here because the numbers'are.

presentedon.4 six-month rather than quarterly basis in those tables.

0-/For definitions for explanatory variables, see Table III.10.

c/The standard errors and t-statistics given in this table may be slightly biased because the

estimates of the standard errors were obtained from a regression program which does not account

for the implicit heteroscedasticity when controlling for unobserved differences betweeniCorpamembers

and the comparison sample via the Heckman (1979) approach. In practice, however, the standard errors

and t-statistics from the regression program-are usually very close to their unbiased counterparts,

especially when the coefficients for the adjustment variables are statistically insignificant (which

isysually the case with our estimates). Therefore, the standard errors and t-statistics presented

here are approximately accurate and are indicative of the true values of these statistics.

-TheThe t-statistic equals the coefficient estimate divided by its standard error. ,However, the

numbers in this column are more accurate than can be obtained from the preceding two columns because

of less rounding error.

105

1I
IV. CHANGES IN FAMILY COMPOSITION AND EMPLOYMENT-RELATED IMPACTS

FOR FEMALES WITH CHILDREN

As our sample ages, two issues will become increasingly important:

the effect of Job Corps on family composition, and its effect on the

employment and related activities of females with children. In this

chapter, the data from our interviews are used to investigate the empirical

evidence on these issues, not with the intention of providing definitive

findings, but in order to explore the relevance of future, research in

this area.

Program effects on family composition are interesting not only

in their own right, but also because there is substantial evidence that

family composition affects the employment and related behavior of females.11

Estimates based on our comparison-group data show significant behavioral

differences in the labor-supply behavior of female youths on the basis

of whether, or not they'have children living with them. (Such behavioral

differences were small in ma etude and not statistically significant

for male youths ip the comparison group.)

The previous theoretical and' 'empirical research in this area finds

that the presence of children in general, and early child-bearing in

particular, reduces the labor supply and earnings of women. Therefore,

Job Corps effects on family composition can have important indirect

effects on the employment and related activities of females, and We do

not want to completely ignore these substantial impacts by focusing only

1/For example, see Bowen and Finegan (1969), Preston (1972), and

Trussell and Abowd (1979).

4

106
on females without children. However, these effects are difficult to

estimate given the apparent underlying differences between our sample. of

Corpswomen and females in the comparison group in terms of family-composition

behavior.1/ For example, prior to enrolling in Job Corps, females in

our Corpsmember sample were much less likely to be married or to have.

children, compared to the women in the comparison sample (see Kerachsky

and Haller, 1977)..

By the second follow-up interview, our sample of female Corpsmembers

with children was still relatively small, comprising only approximately 7

percent of the Corpswomgh on average during the follow-up period. In

particular, we have only 215 postprogram observations for females with

children, and the,small number of observations this implies for some subgroups (e.g., early dropouts) adds greatly to the variability of estimates

of Job Corps effects for this group. However, even though this group is

too small to affect the overall short -term findings and although the

estimates will be very imprecise, the long-4un implications make. it

necessary to examine the findings on the employment and related activities

of females with children.

A. INITIAL FINDINGS FOR EFFECTS ON'FAMILY COMPOSITION

Little previous research has been conducted on the effects of

employment and training prdgrams on family composition.. However, to

the extent that these programs have an impact on employability, they

can consequently be expected to have an affect on the incentives for

family formation, family dissolution, and fertility. in addition,

1/For further evidence on these sample differences, see the

discussion below and Kerachsky and Mallar (1977).
thi resAentia140etting, counseling, and ancillary services provided.

by Job Corps are alsoiiiely to affect the.family-composition decisions

of participating youths,

Tables IV.1 and IV.2 summarize ouT, empirical evidehce on-the

impact of Job Corps on familyicomposition. Tie estimates in these. tables

are based on probit probability models that control for the same,independent 'variables as in Chapter III, with the addition of two variables

that' control for family status at pre- enrollment -'- whether living with

parents at pre-enrollment, and whether achead.pf household at pre-enrollment. ,For females, we find reductions in family formation and fertility

- that are relatively large and generally sicUificant. There are also

reductions in family formation and fertility for male Jcb Corps participants; however:the effects for males are quite small in magnitude and

are not statistically significant. Unfortunately, the female effects

are somewhat clouded by the observed underlying differences in family

composition between the Job Corps and cu4..privison sample: at pre-enrollment

and baseline, which are substantial on observab34: criteria (see Kerachsky.

and Mallar, 1977) and are difficult to model adequately in a simple regression

framework. More definitive findings would require a. much more thorough

modeling and research effort.

The implications of reductions in family formation and fertility

for employment and related activities can be seen by comparing the bottom_

panel of. Table IV.3 to the other two panels. Females without children

generally have higher levels of employment and earnings, more education

and training, less receipt of public assistance, and less Criminal activity

than do females with children. 'Thus, the empirical evidence that Job Corps

participation leads to reductions in family formation and fertility suggests

1Q8 1. j 1
TABLE IV.1

ESTIMATES OF JOB CORPS IMPACTS OM FAMILY COMPOSITION, BY SEX

7! ftweighted

Postprograma,

Variable Sample Mean -.

Probability' . married ai 0.116

second follow-up

married at second

follow-up, given

never married at

pre-enrollment 4.101

head of household

at second

follow-up 0.241

have children e

at second follow -

up (includial

those living

apart)

have childreb

living with them

it second follow- 0.080

up

0:194

io have an extramarital child by 0.163

second follow-up

Probability . . . married at

second follow-up 0.201

married at second

follow-up given

never married.,

at pre-enrollment 0.156

head of household at second 0.233

follow-up ' have children at

'second follow-up

(including those

living apart) 0.453

have children,

living with them

at 'second fbllow-up 0.422

have an extramarital child by

second followup

ar, 0.339

Average

Job Corps . Effect for

Program Completers

Average

Job Corps

Effect-for

Partial Completer'

Average . Job Corpd

Effect for

Earlv DrOpouts

. Average

Job Corps

Effect for

All Enrollees _

A. MALES . 0.007 -0.016 -0.036 -0.017

r

-0.019 -0.042 -0.652 . -0.039

. .. 0.051 -0.016 -0.063 4r015

-0.019 170.031 -0.026 -0.027

0.014 -0.008 -0.021 -0.007

. 4 -0.029 -0.030 -0.003 -0.019

B. FEMALES

-0.079 -0.096* -0.087 -0.087**

-0.0i1 -0.073 -0.062 -0.06?

-0.132*** -0.158*** -0.065 -0.113**

-0.227**** -0.116* -0.095 -0.142*

-0.303**** -0.210*** -0:148* -0.213****

-0.111* 0.005 -0:021 -0.040

109

1 4) - LiA)
lig' tv.z (ismtinued)

MOUS: The significance torile given here may be slightly biased because the estimates of standaf4 errors used

for the underlying significance tests were obtained frail a regression program which does not account

for.Che implicit beteroscedasticity when tootrolling for unobserved differences between Corpsmembers

and the comparison sample via the Whom (1979) approach. In practice, however, the significance levels

from the regression program are usually very close to those from test statistics using unbiased estimates

of standard errors, especially when the coefficients for the adjustment variables are statistically

insignif t (which is usually the cise hers). Therefore, the significance levels given hers are

.approsU i accurate and are indicative of the true significance levels.

g/The unweighted postprogram sample means indicate the magnitude of ths variables for all observations

(Job Corps and comparison groups). Corpsmember sample means can be obtainedy adding the effects shown in

this table to ca. estimates of Corpsmembers, activities had they not participated in Job Corps (presented in

Tabl% III.1).

*Significantly different from zero at the SO% level of statistical confidence (90% for a one-tailed test).

**Significantly different from zero at the 90% level of statistical confidence (95% for a one-tailed test).

*P*Significently different from zero at the 9S% level of statistical confidence (97.5% for a one-tailed test).

****Significantly different from zero at the 99% level of statistical confidence (99.5% for a one-tailed test).

110 1 3G
TABLE IV.2

ESTIMATES OF OVERALL IMPACTS OF JOB CORPS ON FAMILY COMPOSITION . (1)

Estimated

Postprogram

Sample Mean

Variable For All Enrollees

(2)

Estimated

Sample Mean

For All Enrollees

Had They Not

Entered Job Corgi

3

Average

Job Corps Effect

For All Enrollees

(1) - (2)

(4)

Estimated

Percentage

Impact for

All Enrollees

(3) + (2) x 100

Probability . . . married at second 0.106 0.144 -0.038 -26%

follow-up

married 'at second

follow-up given

never married at

pre-enrollment 0.103 0.149 -0.046 -31%

head of household

at second followup 0.224 0.268 -0.044 -16%

have children at

second follow-up

(including those $ living apart) 0.225 0.286 -0.062 -21%

have children

living with them 0.137 0.206 -0.069*** .33%***

have an extramarital

child by second

follow-up

0.191 0.216 -0.025 -12%

NOTES! The significance levels given here may be slightly biased because the estimatei,of

standard errors used for the underlying significance tests were obtained from a

regression program which does not account for the implicit heteroscedasticity when

controlling for unobserved differences between Corpsmeibers and the comparison

sample via the Heckman (1979) approach. In practice, however, the significance

levels from the regression program are usually very close to those from test

statistics using unbiased estimates of standard errors, especially when the

coefficients for the adjustment variables are statistically insignificant (which

is usually the case here). 'Therefore, the significance levels given here are

approximately accurate and are indicdtive of the true significance levels.

111

) k)
TABLE IV.3

ESTIMATES OF CORPSWONEN'S ACTIVITIES HAD THEY NOT PARTICIPATED IN JOB CORPSa-

/

' Variables

0 to 6 Months

After Termination

6 to 12 Months

After Termination

12 to 18 Months

After Termination

18 to 24 Months

After Termination

A. FEMALES WITH CHILDREN, NETTING OUT JOB CORPS EFFECTS WITH STANDARD EQUATIONS

A. Employment and Earnings

Employed (fraction of

time) 0.223 0.213 0.308 0,284

Hours worked per week 7.94 7.35 10.65 9.92

Earnings per week (dollars) 23.55 23.22 31.57 30.12

8. Education and Training

In high school (fraction of time) 0.019 0.011 0.010 0.005

In college (fraction of time) <0.001 <0.001 0.027 0.006

In training program

(fraction of time) 0.036 0.024 <0.001 <0.001

C. Receipt of Public Assistance

Any financial assistance

d/e..o. (fraction of time)

AFDC (fraction of time)

0.458

0.461

0.547

0.550

0.628

0.606 0.544

0.517

General Assistance or

other (fraction of time) 0.296 0.462 0.473 0.451

D. Criminality

Total number of arrests

per six months 0.079 0.014 0.016 0.048

Number of theft arrests

pea six months 0.084 0.017 0.017 0.047

B. Ti IALES WITH CHILDREN, NETTING OUT JOB CORPS EFFECTS WITH EQUATIONS CONTROLLING FOR FERTILITY CHARACTERISTICS

A. Employment and Earnings

Employed (fraction of time) 0.183 0.173 0.267 0.243

Hours worked per week

Earnings per week (dollars)

6.31

17.58

5.73 17.258.98

25.42 . 8.22

23.84

B. Education and Training

In high school (fraction of time) 0.015 0.007 0.006 0.002

In college (fraction of time) , In training program

0.004 <0.001 0.035 0.014

(fraction of time) 0.025 . 0.013 <0.001 <0.001

C. Receipt of Public Assistance

e Any financial assistance

(fraction of time) 0.472 0.561 0.642 0.558

e AFDC (fraction of time) 0.467 0.557 0.613 0.523

General Assistance or

other (fraction of time) 0.302 0.469 0.479 0.457

D. Criminality

Total number of arrests

per six months 0.080 0.015 0.017 0.049

Number of theft arrests

per six months 0.083 0.016 0.016 0.045

112
TABLE IV.3 (continued)

0 to 6 Months

_ Variables After Termination

6 to 12 Months

After Termination

12 to 18 Months

After Termination

18 to 24 Months

After Termination

C. S WITHOUT CHILDREN NETTING OUT JOB CORPS ETTECTS WITH STANDARD I UATIONS

A. Employment and Earnings

Employed (fraction of time) 0.322 0.292 0.355 0.370

Hours worked per week 10.80 11.01 13.41 13.95

Earnings per week (dollars) 22.55 29.27 38.60 41.31

11.Sducation and Training

In high school (fraction of time) 0.073 0.068 0.055 0.048

In college (fraction of time) 0.007 0.010 0.012 0.024

In training program (fraction of time) 0.018 0.023 0.033 0.033

C. Receipt of Public Assistance

Any financial assistance

(fraction of time) 0.176 0.200 0.185 0.163

AFDC (fraction of time) 0.134 0.157 0.147 0.130

General Assistance or

other (fraction of time) 0.043 0.042 0.037 0.032

D. Criminality

a Total number of arrests per six months 0.036 0.024 0.026 0.019

Number of theft arrests per six months 0.031 0.031 0.015 <0.001

NOTES: The sigdificance levels given here may be slightly biased because the.estimates of standard errors used for

the underlying significance tests were obtained from a regression program which does not account for the

implicit heteroscdasticity when controlling for unobserved differences between Corpsmmbers and the comparison

sample via the Heckman (1979) approach. In practice, however, the significance levels from the regression

program are usually very close to those from test statistics using unbiased estimates of standard errors,

especially when the coefficient adjustment variables are statistically insignificant (which is usually the.

case here). Therefore, the significance levels given here are approximately accurate and are indicative

of the true significance levels.

/ All of the dependent variables in this table are estimated for the civilian population only.

*Significantly different from zero at the 80% level of statistical confidence (90% for a one-tailed test).

**Significantly different from zero at the Marvel of statistical confidence (95% for a one-tailed test).

***Significantly different from zero at the 95%vIevel of statistical confidence (97.5% for a one-tailed test).

 Significantly different from zero at the 99% level of statistical confidence (99.5% for a one-tailed test).
additional, indirect Job Corps impacts on employment and related activities

for females. Since the estimates of Job Corps impacts presented in Chapter

III do not take account of this change in family composition, they are likely

to underestimate Job Corps impacts on employment and related activities.

If additional follow-up interviews are undertaken, the effects of Job

Corps on family formation and fertility would need to be modeled and

studied more carefully as the sample ages.

B. ESTIMATES OF EMPLOYMENT AND RELATED IMPACTS FOR FEMALES WITH CHILDREN

In general, for females with children we find significant increases

in participation in training programs, significant reductions in the

receipt of AFDC, and significant reductions in criminality (see Table IV.4

and Figures IV.l to rv.3). The estimated effects on employment and earnings

are small in magnitude and are not statistically significant. As can be

seen from Table IV.4, the employment and earnings impacts also vary quite

substantially on the basis of whether or not we control for fertility

characteristics (i.e., the number of children, presence of extramarital

children, and age at the birth of the first child). However, the significant effects on training, AFDC, and criminality are more robust between

the two models. With our simple empirical approach it is unclear which

underlying model is best; thus, a more structured modeling approach is

needed in order to be more definitive. Adding the fertility variables

increases the precision of estimates but is also likely to impart some bias

(i.e., part of the Job Corps effects will be picked up by these fertility

variables, as discussed above). With both sets of estimates, the effects

for early dropouts are set equal to zero because, as mentioned previously,

we have too few observations to make estimates for this group. When early

dropouts are included, the overall effects are not changed substantially,

114 140
TABLE IV.4

ESTIMATES OF JOB CORPS pekers ON EMPLOIMEN4 AND RELATED ACTIVITIES OF

FEMALES WITH CHILDREN

(ALL CIVILIANS)

Unsighted

Postprogram.,

Variables Sample Mean&

Job Corps Effects

0 to 6 Months

After Termination

Job Corps Effects

6 to 12 Months

After Termination

Job Corps Eszects

12 to 18 Months

After Termination

Job Corps !sleets

18 to 24 Months

After Termination

A. JOB CORPS EFFECTS FROM STANDARD EQUATIONS

A. Employment and Earnings

Employed (fraction of

time) 0.249 -0.063** * -0.047** 40.009 -0.029

Hours worked per week 8.99 -2.04** -1.27 0.17 -0.61 Earnings per week

(dollar) 27.04 -5.64* -4.43 -0.82 -3.11

Weeks worked per six

months 6.48 -1.6S*** -1.23** -0.23 -0.77

B. Education and Training

In high school

(fraction of time) 0.019 -0.011 0.001 -0.003 -0.005

In college (fraction

of tim) 0.019 0.006 0.007 0.013* 0.016*

In training program

(fraction of time) 0.033 0.004 0.023*** 0.028**** 0.018*

C. Receipt of Public Assistance

Any financial assistance

(fraction of time) 0.381 -0.139**** -0.066*** -0.046* -0.0002

AFDC (fraction of time) 0.358 -0.160**** -0.091  -0.062** * -0.018

General Assistance or

other (fraction of

time) 0.023 0.020** 0.024*** 0.016* 0.019**

D. Criminality

Total number of arrests

per six months 0.009 -0.013* -0.007 -0.016* -0.019*

Number of theft arrests

per six months 0.006 -o.ulaw** -0.013* -0.017*** -0.017**

B. ,011501MrrricsSOrrAULTIONS CONTROLLING FOR FERTILITY CHARACTERISTICS

A. Employment and Earnings

Employed (friction of

time) 0.249 -0.024 -0.008 0.032 0.012

Hours worked per week .99 -0.42 0.35 1.84* 1.09

Earnings per week

(dollars) 27.04 0.32 1.55 5.32* 3.16

Weeks worked per six

months 6.48 -0.63 -0.21 0.82 0.30

B. Education and Training

In high school

(fraction of time) 0.019

e In college (fraction

-0.008 0.005 0.001 -0.001

of time) 0.019 -0.002 -0.002 0.006 0.008

In training program

(fraction of time) 0.033 0.015 0.034**** 0.040  0.029** *

C. Receipt of Public Assistance

Any financial assistance

(fraction of time) 0.381 -0.153**** -0.081*** -0.061** -0.014

AFDC (fraction of time) 0.358 -0.166  -0.098** ** -0.069*** -0.024

General Assistance or

other (fraction of

time) 0.023 0.013 0.017* 0.009 0.012

115

1.4
TAMS IV.4 (continued)

.1101=1. Variables

D. Criminality

Unweighted Job Corps Effects Job Corps Effects Job Corps Effects Job Corps Effects

Postprograme 0 to 6 Months 6 to 12 Months 12 to 18 Months 18 to 24 Months

Sari& Ifeaftw After Termination After Termination After Termination After Termination

Total number of arrests

per six months 0.009 -0.014* -0.008 -0.017* -0.019*

Number of theft arrests

per six months 0.006 -0.018*** -0.013* -0.016** -0.016*

NOTES: The significance levels given here may be slightly biased because the estimates of standard errors used for

the underlying significance tests were obtained from a regression program which does not account for the

implicit heteroscedasticity when controlling for unobserved differences between Corpsmembers and the comparison

sample via the Heckman (1979) approach. In practice, however, the significance levels from the regression

program are usually very close to those from test statistics using unbiased estimates of standard errors,

especially when the coefficient adjustment variables are statistically insignificant (which is usually the

case here). Therefore, the significance levels given here are approximately accurate and are indicative

of the true significance levels.

1/The unweighted postprogram sample means indicate the magnitude of the variables for all observations

(Job Corps and comparison groups). Corpsmember sample means can be obtained by adding the effects shown in

this table to the estimates of Corpsmembers' activities had they not participated in Job Corps (presented in

Table III.1).

*Significantly different from zero at the 80% level of statistical confidence (90% for a one-tailed test).

**Significantly different from zero at the 90% level of statistical confidence (95% for a one-tailed test).

***Significantly different from zero at the 95% level of statistical confidence (97.5% for a one-tailed test).

.****Significantly different from zero at the 99% level of statistical confidence (99.S% for a one-tailed test).

116 1 .1 2,
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117

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but the estimates of the timing of effects (i.e., the postprogram time

patterns) become extremely erratic.

As can be seen in Table IV.4, setting the effects equal to zero

for females with children, as was done in Chapter III, will not substantially

bias the estimates of.overall Job Corps impacts, especially because this

group accounts for only 7 percent of Corpmembers during the first two years

of postprogram observation. If findings in Table IV.4 were added to those

presented in Chapter III with a weight of 0.07, the only substantive

influences would be a slightly larger increase in training-program participation and slightly larger reductions in AFDC and criminality. However, it

is expected that the influence of the subgroup of females with children

will become more substantial if additional follow-up interviews are undertaken,

because this subgroup will continue to grow in both size and relative

importance as the sample ages.

C. SUMMARY OF FINDINGS

The findings in this chapter reinforce our estimates of the overall

impacts and suggest, if anything, that our overall estimates of Job Corps

impacts presented in Chapter III are biased downward by ignoring (1) the

Job Corps effects on family composition, and (2) the employment and related

effects for females with children. Furthermore, finding delays Itt family

formation for females indicates that this would be a fruitful am, for

further research, both for the Job Corps program and for other employment

in i training programs. Finally, if additional 2ollow -up surveys art

undertaken, the areas of analysis explored in this chapter will Lnke

increasing importance and will need to be studied more carefully.
V. COMPARATIMEVALUATION OF BENEFITS AND COSTS1/\

An issue that should be addressed in program evaluations is whether

the beneficial effects of the programs outweigh the costs. Answering this

question is rarely a simply matter, however--especially in an evaluation of

a program such as Job Corps, which has such a wide range of impacts occurring

over a long period of time. The effects of Job Corps, for example, include

the increased employability of Corpsmembers and its impact on national output,

dependence on welfare and other public transfers, criminal activity, drug and

alcohol abuse, and the use of alternative training and educational services.

Some aspects of these impacts are difficult to value, and many could potentially

occur over a long period of time for both Corpsmembers and the rest of society.

Comparing these effects of Job Corns-to the corresponding costs requires not

only that the various benefit and cost components be identified and measured,

but that a suitable method be developed for placing relative values on these

components.

Benefit-coht analysis attempts to provide an appropriate framework for

comparing these effects and their costs. The usual approach entails assigning

a current dollar value to each benefit and cost, and aggregating these values

by using standard accounting procedures. By measuring the benefits and costs

of a program in common units (current dollars), the economic desirability of

the program can readily be assessed.

An appropriate procedure in comparing benefits and costs is to calculate

the program's "net present value." This term refers to the difference between

11This - chapter is a summary of the benefit-cost analysis of Job Corps

presented in "Comparative Evaluation of the Benefits and Costs of Job Corps

After Eighteen Months of Postprogram Observation" (Technical Report K). The

interested reader should refer to that report for a more detailed presentation

of the methodology and the findings.

119

1 if
benefits and costs for which all dollar values have been adjlOted to present

value units.1/ To control partially for program size, we divide all dollar

values by the number of Corpsmembers, so that all figures reflect benefits or

costs per Corpsmember. Thus, the resulting criterion used to judge the program

is whether the program's net present value per Corpsmember is greater than

zero. If it is, the program is "desirable" on economic grounds. If the net

present value is less than zero, the progiam is judged to.have been unsuccessful as an economic investment, because the estimatedkurrent value of benefits

is less than the current value of costs

While the net present value criterion is easy to state, the degree

of uncertainty surrounding its estimation is often high, making it

difficult to apply. Sometimes, in fact, equally plausible estimates of a

program's net present value may lie on opposite sides of zero, making it

impossible either to directly apply the net present value rule or to judge

the economic efficiency of a program.

This uncertainty stems from three sources: the estimates of program

outcomes, the estimates of the "shadow price" used to value the outcomes,

and the assumptions underlying the evaluation procedures..-2/ Of these

three areas, the uncertainty surrounding the outcome estimates is best

understood because the estimates are derived using statistical methods

which yield reliable estimates of error variance. Less is known about

the accuracy of the shadow prices. These prices are estimated on the basis

of published data for which standard measures of error or uncertainty

1/In discounting to present value units, we adjust the value of

estimated benefits or cats that accrue in the future to reflect their

worth in the current time period.

1/The term shadow price is used to refer to estimates of the value

per unit of the effects. These prices are then multiplied by the changes in

the outcomes to arrive at their value. This technique is discussed in the

next section.

120
(e.g., stanOard deviations or ranges) are often not available. Finally,

many of the assumptions used'in the analysis .clearly approximate reality--

the.magnitude of the approximation error often being impossible to determine

precisely. 1/

Because of the error associated with any single estimate of net

present value, much of the usefulness of benefit-cost analysis comes from

the comprehensiveness of the analysis. The process of drawing-together

measures of the various'inputs and outcomes and the general patterns that

emerge from the attempts to assign relative values are often more useful

than any specific estimate of net present value. For-this reason, the

. analysis does not focus on a single net present value estimate but, instead,

on a set of estimates. This set includes (1) a benchmark estimate, incorporating the assumptions and estimates with which we feel most comfortable,

and (2) several estimates based on sensitivity tests, each illustrating

the effect of changing one or more of the assumptions used in the benchmark calculations while holding the others constant.

The conclusions of the benefit-cost analysis'are based on all

these estimates. Thus, they do not rely on a single set of, uncertain

assumptions and estimates, but, instead on a range of plausible

assumptions and estimates. By examining the different assumptions,

4.1%the underlying outcome estimates, and thm techniques used to value outcomes, reasonable judgments can be made about the relative value of program.

benefits and costs.

1/

- The relative importance of these types of errors is not well known.

However, it seems likely that uncertainty surrounding the validity of

assumptions, such as the appropriate rate of discount, causes the greatest

uncertainty regarding the true net present value.

121

1 4 "
For Job Corps, the benchmark estimate Of social net present value is

' almost $2,000 per Corpsmember, measured in 1977 dollars. This, along with

the generally positive results of the sensitivity 'tests, suggests thst.Job

Corps is a good investment for society.'

While the evaluation of the program from the pertpective of society

'las a whole is positive, ell groups in society do not share the benefits ' and costs equally. It is therefore important to consider= the effect of

the program on the distribution of resources, as well as its effect on

the total amount of resources. In economics, these two concerns of the

analysis are referred to as "equity" and "efficiency" islues. Efficiehcy

concerns a program's effect on the total.value of the goods and service

available to society (Is the value of those goods and services greater

because of the program under study, or would it have been greater if the

resources used for the program had been de9oted to alternative. uses ?).

Equity concerns the distribution of goods and services among groupS in

society and how the distribution is affected by the program.

To address these two policy questions, the benefit-cost analysis

estimateethe net present value for three key perspectives: society as

a whole, Corpsmembers, and non-Corpsmembers.1/ The'benefit' -cost analysis

will be limited to estimating the magnitude of any distributional changes

without drawing conclusions about their desirability. As might be

expected, given the nature of Job Corps, we find an overall transfer from

non-Corpsmembers to Corpsmembers.V

1/

The torsi non-Corpsmember is-Used, consistently throughout thii

benefit-cost discussion to refer to all members of society'other than those'

who enroll in Job Corps. It should be pointed out that this term is not

meant to refer specifically to that group of non-Corpsmembers interviewed

in our study as a comparison.group, although these individuals are of course,

included as a small fraction of the total non-Corpsmember group.

Since the net present value to society is positive, however, presumably

everyone could be made better off than they would be without the program.

122

1 4
: One analytically useful feature of evaluating Job Corps from these.

three perspectives (society, Corpsmembers, and non-Corpsmembers) is that

the sum of the net present values calculated from the Corpsthember and non

Corpsmember perspectives equals the ic:ial net present value--that is,

Corpsmembers and non-Corpsmembers together include all members of society.

.Therefore, transfers between these two groups (e.g., reduced welfare transfers

or Job Corps stipends) cancel each other out when the net present values

are summed, and thus do not appear in the social net present value)) Benefits

ocosts that accrue to one group and are not offset by corresponding costs

or benefits to the other group (e.g., increased work output) will not

out, and thus will enter into the social net present value calculation.

The components of our benefit-cost ,afielysis of Job Corps and the

relationships among the Corpsmember, non-orpsmember, and social perspectives

are illustrated in Table V.I. This table lists the principal components

of the benefit-cost analysis, suggests whether acomponent'is, on average, a

benefit, a cost, or, neither from each of the three perspectives, and indicates

the data sources used to measure and value each component.? The individual

benefit-cost components listed in Tabla V..1 are the subject of the following

section.

Finally, before proceeding, it is important to note the general

approaCh adopted in our evaluation. In general, impacts and costs are

valued using an accounting framework based on the during-program period

of 1977, and by estimating the market value of the resources saved or used

1/

This assumes that a dollar Of benefit or cost to one'person is

equal to a dollar of benefit or cost to anyone else.

& /Whether Whetherthe effect of Job Corps on a component is +a net benefit

or cost is sometimes problematic. Table V.1 reflects prior judgments

concerning the social value of components. The treatment of all domponents

in the final net present value calculations is, of course, determined by

the measures of the actual outcomes.

123

149
TAILS V.1

CONPONINTS OF BENEFIT -COST ANALYSIS

a Perspective-/ Data Component Social Non- Corpsmember Corpsmember Source(s)

MIMS

A. Output Produced by Corpemembers

e In-program output

Increased ptprogram output

Increased tax payments on postprogram

income

Increased .11ity due to-preferences

for u- over welfare

+

+

0+

+

0++

+

+

5,P

I,P

I,P N

B. Reduced Dependence on Transfer Programs

Reduced transfer payments 0 I,P

Reduced administrative costs + + 0 I,P

C. Reduced Criminal Activity

Reduced criminal justice system colts- + I,P

Reduced personal injury and property

damage + + 0 I,P

Reduced value of stoliq ?Taperty + + I,P

Reduced psychological costa + + + N

D. Reduced Drug/Alcohol Use

Reduced drug-treatment costs + 0 I,P

e Reduced alcoholism-treatment costs + + 0 I,P

Increased utility from reduced drug/

alcohol dependence ' + + + N

E. Reduced Utilization of Alternative Services

Reduced costs of training and educational

programs other than Job Corps + 0 I,P

Reduced net costs of Public Service

. Employment + + 0 I,P

Reduced training allowances 0 + I,P

F. Other Benefits . Increased utility from redistribution + + + N

Increased utility from improved wellbeing of Corpsmembers + + + N

COSTS Program Operating. Expenditures

Center operating expenditures, excluding

transfers to Corpsmembers 0 A Transfers to Corpsmembers A

Central administrative costs 0 A,S

B. Opportunity Cost of Corpsmember Labor

During the Program

Foregone output 0 I,P

Foregone tax payments 0 I,P

C. Unbudgeted Expenditures Other than

Corpsmember Labor

Resource costs 0 S,P

Transfers to Corpsmembers 0 S,P

=The The columns indicate whether the net impact of a particular item is a net benefit (+), a net

cost (:), or neither (0). This is done from the social, non-Corpsmember, and Corpsmember perspectives

in order to indicate redistributive effects. In doing.this, Corpsmembers are treated as nontaxpayers

(except in benefit component A!5 and cost component 8.2) to simplify the exposition, and non- Corpsmembers

encompass everyone in society other than Corpsmembers.

b/ The codes for data sources are: S special study; I 2 interview; Ps published data source; A Job Corps financial accounting system,: N not measured.

124 ()
because of the program. When market values are not observed directly, the

implicit shldow prices will be estimated whenever possible. However, in

some cases, reliable shadow prices cannot be estimated. For example, we

will not value the increase in social mtility due to individuals' preferences

for work over welfare.-1/ When equally plausible estimates exist, we will

adopt the conservative convention of using the value which lowers the

estimate of net present value.

A. BENEFIT.COHPONENTS

Five major benefit components are measured and valued. of

them are expected to derive, at least in part, from an increase in the

long-run employability of Corpsniembers. Improved job 4portunities

should lead to benefits from increases in the product...on of goods and

'services and from reductions in (1) criminal activities, (2) drug and

alcohol abuse, (3) welfare dependence, and (4) the use of alternative

training and educational services. Our estimates for each of the five

components of benefits plus unmeasured benefits are discussed briefly

below; they are then aggregated together with the costs, in Section C.

1. Output Produced by Corpsmembers

The increase 'A goods and services produced by.Corpsmembers constitutes a major benefit of the program. For analytical purposes, it is

useful to distinguish between goods and services that Corpsmembers

produce while they are enrolled in Job Corps and those that they produce

after they leave the program. This distinction is convenient because

11One way to interpret quantitative benefit -cost findings when some

benefits and costs are not measured is that if measured costs exceed ' measured benefits, society (or another perspective) must value the /

difference between unmeasured benefits and costs by at least the amount of

the measured shortfall in the net present value in order for the program

to be considered a worthwhile economic investment.
different techniques are needed for valuing changes in postprogram

versus in-program output. The output produced by Corpsmembers after they

leave the program is produced in the regular labor market, and we estimate

the value of this output on the basis of their wages. In contrast, the output

produced by Corpsmembers while enrolled in Job Corps is produced under

nonmarket circumstances, and their Job Corps stipends (pay allowances) do not

provide an accurate index of the value of that output. (For similar reasons,

the different types of ,utput are treated differently in the accounting

frameworks for the three benefit-cost perspectives.)

In-Program Output. The in-program output produced by Corpsmembers

in connection with their vocational training provides benefits to Corpsmembers, to non-Corpsmembers, and to society as a whole.-1/ These outputsinclude goods produced in work. projects (for instance, the addition built

onto a hospital in rural Colorado by Corpsmembers who were receiving on-

. the-jobtraining in various construction trades)-and services provided

in work-experience programs (for instance, the nursing assistance provided

by Corpsmembers at a county hospital in Guthrie, Oklahoma, as they were

gaining job experience). The value of these goods and services was

estimated on the basis of twenty-two special studies of randomly chosen

work projects and work-experience programs at eleven Job Corps centers.,

The recipients of this Corpsmember-produced output. may be either

the non-Corpspember community or the Job Corps centers themselves. In

the first case (community-serving output), the entire value of the output

1/- For more details regarding the estimated value of in-program

output and the techniques used to obtain those estimates, see Technical

Reports D and E.

126 1 3 2,
produced is considered a benefit to non-Corpsmembers.1/ In the second

case (center-serving output), the output will benefit both Corpsmembers

and non-Corspmembers. Corpsmembers benefit from center-serving output

because they consume some of the output *they produce (e.g., housing

services provided in dormitories built or rehabilitated with Corpsmember

labor, part of which is included as a capitalized cost in the Job Corps

financial data); non-Corpsmembers benefit when the capital stock availeJle

to society is increased by Corpsmember labor in these activities.

The value of the goods and se .1;1 es produced by Corpsmembers in

community- and center-serving_ projects is estimated by the price that

alternative suppliers would have charged to provide those goods and

services.-2/ After adjustments are made to center-serving output (to

account for the value of output used up by Job Corps and transferred

to Corpsmembers), the net benefits per Corpsmember year of service of

in-program output are estimated to be $1,364 for non-Corpsmembers, $175

for Corpsmembers, and therefore $1,539 for society as a whole. Because

the average Corpsmemer stays in the program approximately half a year

(5.9 months in fiscal year 1977), the average social benefit per

Corpsmember is $757.3 On average, Corpsmembers receive $86 of this

benefit, while the remaining $671 accrues to non-Corpsmembers.

1/ Corpsmembers also benefit from the community-serving output as

general members of society. However, for the most part, we will use the

approximate (and computationally convenient) assumption that only nonCorpsmembers benefit from such output.

value of all materials and labor inputs provided by Job

Corps are .4btracted from the, alternative supplier's price. In many

cases, the net value of the Job Corps output was quite close to the

alternative supplier's labor cost.

'That is, 5.9 12 x $1,538.83 = $756.59.

127

1 5 3
These values are based on the price charged by an alternative

supplier and indicate the value of the resources that would be required

to produce the in-program output of Corpsmembers. However, these prices

do not directly measure the value that society places on the output.

While only imprecise estimates of this demand value can be made, tests

presented in Technical Report E suggest that under reasonable assumptions

the demand value will be between 103 and 62 percent of the supply-price

estimate. Thus, using supply price as a measure of the value of in-program

output can provide a reasonably accurate estimate of the demand value (but

probably high by a small amount).

Increased Postprogram Output. The increase in the amount of output

produced by Corpsmembers after they leave the program is estimated by the

increase in earnings.-1/ The use of earnings as a measure of output produced

is based on the assumption that labor markets function in a competitive manner

(earnings is the correct measure from the Corpsmember perspective in any

case). This assumes that employers set the total compensation of a worker

at a value that reflects the output produced by the worker. The increase in

output produced by Corpsmembers is then estimated by the difference between

the gross compensation of the Corpsmember and the amount they would have

been paid had they not entered the program.-2/

The interview data on earnings have two shortcomings with respect to

the estimation of total compensation. First, they deal only with the wage

component of total compensation and ignore the nonwage components, such as

/ This assumes that Corpsmembers do not displace other workers who

subsequently become unemployed (see Technical Report K for more discussion

on this topic).

1/See the discussion in Chapter III for details regarding the

econometric procedures used and the resulting impact estimates obtained

for the Job Corps effects that are being valued in this chapter.

128

4

'
retirement, health, and insurance benefits, the employer's share of payroll

taxes for Social Security, and payments made into Unemployment Insurance

and Workers' Compensation funds. Second, the earnings data per se do not

include increases in output due to Corpsmember increases in military

service.

Estimates of nonwage benefits were made on the basis of secondary

data (e.g., Social Security statutes and Department of Labor estimates of

fringe-benefit rates). For workers like the Corpsmembers, we estimate

the value of the nonwage items to be 15 percent of wages. Thus, the social

benefit derived from the increase in output is estimated at 1.15 times the

estimated increase in Corpsmembers' earnings.

The values of increases in military earnings and output were

estimated on the basis of the estimates of increased military service among

Corpsmembers and of the average compensation paid by the military.

Estimated military compensation was based on the fiscal year 1977 regular

military compensation rates for grades E-1 ($6,861 per year) and E-2

($7,470 per year).1/

Estimates of the total increase in output and its three components --

civilian earnings, military earnings, and fringe benefits--are shown in

Table V.2 (along with the related estimate of the value of increased tax

payments). As discussed in Chapter III, the pattern,of results over time

suggests that Corpsmembers experience some adjustment problems as they

re-enter the labor market after Job Corps. As Corpsmembers overcome the

readjustment problems, earnings rise until the semi-annual increase in

output is worth $325 per Corpsmember. Increases in military output

account for almost half of the output gain during the first 6 months,

1'For further details and justification, see Technical Renort K.

129
TABLE V.2

ESTIMATED VALUE OF INCREASED POSTPROGRAN OUTPUT PER CORPSMEMBER

(1977 DOLLARS)

Source of Income

Months

1 to 6

Months

7 to 12

Months

13 to 18

Months

19 to 24

Total

Discount's'

Value-'

Increased civilian earnings $ 49.79 $147.89 $229.27 $213.65 $595.80

Increased military earnings 43.53 36.34 72.17 70.90 208.31

Total earnings, increase $ 93.32 $184.23 $301.44 $284.55 $804.10

Increased fringe benefits- 14.00 27.63 45.22 42.68 120.61

Value of increased

postprogram output $107.32 $211.86 $346.66 $327.23 $924.72

Increased tax payments2l $ 5.14 $ 27.19 $ 55.05 p 50.12 $127.41

1/Discounted to the in-program period at a 5 percent annual rate (for justification

see the text).

12/Fringe benefits are estimated to be 15 percent of earnings (for justification,

text).

1/Tax payments are estimated to be 23 percent of income, earnings plus transfers

(for justification, see the text).

see the

130
but thin proportion falls as Corpsmembers adjt,t tl ttoc civilian labor market. During the last obserratim per.J.Q.1. ts- iosn'aul

after leaving Job Corps, military output accou:x::4, roc ww.i.

25 percent of the total increase in output. The total - estimated present

valve of increased postprogram output is approximately $925 during the

24-month observation period.

Increased Tax Payments on Postprogram Income. As Corpsmembers'

incomes rise they pay more taxes. Such an increase in tax payments is

a cost to Corpsmembers, but an offsetting benefit to non-Corpsmembers

(i.e., all other taxpayers) and, hence, does not enter the social

perspective.1/

To estimate taxes paid, we used an estimate of the tax rate

applicable to low-income households. This rate was estimated by Pechman

and Okner (1974) to be approximately 23 percent of total income (i.a.,

earnings plus transfers).?/ The major components of this rate are

payroll, sales, and excise taxes. These taxes, especially those on

consumption, are difficult to avoid. Thus, even though Corpsmembers may

face low income-tax rates on wages, and may in fact avoid paying payroll

and income taxes, their total tax burden (as a percentage of income) is

-.As is the case-with all transfers, changes in the resource costs

of making the transfer should be included in the social perspective. In

the case of tax payments, the change in administrative costs is probably

very small and is treated as zero.

?This This discussion draws on the results of Pechman and Okner (1974).

Their data show that the combined effect of all taxes is equivalent to a

proportional tax of approximately 23 percent of income. These data are

rather old--1966--and have some inaccuracies when applied 'co populations

of low-income youths. However, they are the best estimates currently

available--particularly because of their comprehensiveness and because

they are able to incorporate the effects of tax avoidance in their

estimates. ,
not significantly different than the tax burden of most taxpayers

(although the composition of taxes does vary considerably by income

(11

level).

The pattern of changes in tax payments (shown in Table V.2)

-irrors that of increased earnings.-1/ During the first 6 months after

:caving Job Corps, Corpsmembers pay, on average, only about $5 more in

taxes than they would have paid in the absence of the program. This

..ncrease in taxes rises as earnings rise, and during the last observation

ptriod (months 19 to 24) they pay approximately $50 more than they would

have in the absence of the program.

Unmeasured Benefits. In addition to the increases in output and

tax payments, there are also gains for both Corpsmembers and non-Corpsmembers

to the extent that individuals prefer work over welfare. Corpsmembers may

gain from increases in self-esteem due to working in regular, unsubsidized

jobs. Non-Corpsmembers may benefit to the extent that they would prefer

the resources to be used to give Corpsmembers the opportunity to intrease

their human capital and earnings from Job Corps participation, rather than

be used to provide direct transfer payments to Corpsmembers. These'changes

in well-being are intangible and could not be measured accurately for this

analysis.

2. Reduced Dependence on Transfer Programs

Increases in employability attributed to Job Corps should make

participants less reliant on transfer programs. This will cause a

1 1/Because there were reductions in the amount of transfer payments

to Corpsmembers, the change in taxes (figured on the basis of changes in

earnings and transfers) is legs than it would have been if figured only

on the basis of earnings increases shown in Table V.2. These reductions

in transfers are discussed in the next section of this chapter.

132

153
decline in both transfer payments to Corpsmembers and the level of resources

needed to administer those programs. The reductions in transfer payments

represent a cost to Corpsmembers and a corresponding benefit for non-Corpsmembers, who otherwise would have had to pay for them. Therefore, these

transfer payments net out from the social perspective. In contrast, the

administrative savings are a benefit to non-Corpsmembers an do rot

represent a corresponding cost to Corpsmembers; hence, the administrative

savings are a benefit to society.

Reduced Transfer Payments. Six transfer programs were examined

as part of the analysis: Aid to Families with Dependent Children (AFDC),

General Assistance, Food Stamps, Medicaid, Unemployment Insurance, and

Worker's Compensation.1/ Transfers were estimated on the basis of

differences, in months during which the transfers were received and the

average benefit levels of the,.prorams. These benefit levels were

estimated on the basis of published data, except in the cases of

Unemployment Insurance and Workers' Compensation, for which'the average

benefit received by persons in our sample was used (a smaller amount

than the average benefit-levels of the programs).

Corpsmembers reduced their participation in all six programs

both while they were in Job Corps and during the first 24 months after

they had left the program. The largest reductions were in the cash

1/- In addition to these six programs we also examined the use of

_public housing. The principal reason why changes in the use of this program

are not included in the analysis is that almost all of the persons who

reported living in public housing said that they lived with parents or

other relatives. Thus, the fact that they moved out of public housing

would not necessarily imply any change'in public housing subsidies or

administrative-costs, because the parents and relatives ,could continue

to live in the housing unit. In any event, changes in the use of public

housing were quite small, and the estimated error introduced by not

including this program is at most $15 per Corpsmember.

133

6:j
welfare programs, AFDC, and General Assistance (for valuation purposes,

Medicaid benefits were estimated on the basis of AFDC participation).

The as also a sizable reduction in the receipt of Unemployment

Insurance, Estimates of the changes in transfer payments by program

are shown in Table V.3 and total approximately $527 in present value

terms during the observation period.

RedudW Administrative Costs. With the decline in transfers,

the amount of resources needed to administer the programs also declines.

This resource saving is a benefit to non-Corpsmembers and to society as

a whole,- The savings are estimated on the basis of the estimated

changes in months ofprogram use and the average costs per month of

processing a case in each of the programs. The estimated benefits are

presented in Table V.4 and total approximately $63 in present value

terms during the observation period.

1

3. Reduced Criminal Activity-/

Four benefits from the decline in criminal activity among Corpsmembers are the reductions in (1) the resources used in the criminal

justice system; (2) the personal injury and property damage that

accompany victimizations; (3) the value of stolen property; and (4) the

fear and anxiety associated with crime. The resource savings associated

with the first two items are benefits to society and to non-Corpsmembers.

The reduced value of stolen property will be a benefit to non-Corpsmembert,

but part of its value should be viewed as a cost to Corpsmembers, who no

longer receive that theft income. The social benefit of a reduction. in

1 /This section is, by necessity, a brief summary of the crime

evaluation procedures used. Technical Report K contains a more complete

discussion of the proce-, res and their justifications.

134 160
TABLE V.3

ESTIMATED VALUE OF BENEFITS PER CORPS ki I: ER FROM REDUCED TRANSFER PAYMENTS

(1977, DOLLARS)

Months of Reduction in Use

'd

Program

In-PrOgram

Period

PostErogram Period'

Months

1 to 6

Months Months

7 to 12 13 to 18

Months

19 to 24

kid to Families

with Dependent 0.572 0.166 0.185 0.200 0.215

Children

General 0.059 0.158 0.146 0.123 0.117

Assistance

1-4 Medicaid 0.572 1.166 0.185 0.200 0.215

U'

Food Stamps 0.482 0.135 0.122 0.082 0.050

Unemployment 0.128 0.146 0.128 0.119

Insurance

'Workers' 0.023 0.012 0.629 0.018

Compensation

Unemploymenir insurance

and Workers'

b/

Compensation $29.30

Total benefit

. Value Per

Month

$76.41.

$116.05

$76.61

$73.65

$63.43

4109.43

Total

Discounted.

Value-

$99

66

99

'63

'11 . 135

37'

29

,

a/

Discounted to the in-program period

b'For the in-program period, Workers'

combined because of data limitations with the

11.(3nterview self-reports of the totillamount of

4,\

at a 5 percent annual rate (for justification, see the text).

Compensation (WC) and Unemployment Insurance (UI) had to be

Baseline Questionnaire. The estimated value is taken from

WC and UI combined.
TABLE V.4

ESTIMATED VALUE OF BENEFITS PER CORPSMENBER FROM REDUCED ADMINISTRATIVE COSTS OF TRANSFER PAYMENTS

(1977 DOLLARS)

Months of Reduction in Use

Postproorim Period Total

In-Program Months Months Months Months Value Per Discounild

Pro am Period 1 to 6 7 to 12 13 to 18 19 to 24 Month Vilue-1

Aid to Families ri

with Dependent 0.572 0.166 0.185 0.200 0.215 $8.83 $11,

Children

General 0.059 0.158 0.146 d0,123 0.117 13,35 8

Assistance

Medicaid 0.572 0.16 0.185 0.200 0.215 9.49 12 , Food Stamps 0,482 0.135 0.122 0.082 0.050 9.48 8

Unemploymenil 0.144 0.128 0.146 0.128 0.119 30.16 19

InsuranceWorkers'

b/

0.023 0.012 0.029 0.018 '' 53.73 4

CompensationTotal benefit

!'Discounted Discounted to the in-program period at a 5 percent annual rate (for justification, see the text).

b/

For the inprogram period, Workers' Compensation and Unemployment Insurance are combined. The

Unemployment Insurance costs are used because participation in that program is much greater than partici

pation in Workers' C. ,.enration.
stolen property (the difference between the non-Corpsmember benefit and

the Corpsmember cost) is the decrease in the costs of fencing, in

damage to the stolen property, and in the loss of legal titles.

The method used to value the crime-reduction benefits focuses

on the effect of chaiges in arrests among nine crime categories. The

estimates of Job Corps-induced reductions in arrests are adjusted upward

by 70 percent to correct for underreporting in the interview selfreports.1/ These estimated reductions in arrests were then valued by

multiplying them by shadow prices equal to the cost savings per arrest.

The disaggregation of arrests was made by most serious charge, which will

enable changes in both the mix of arrest charges and the overall level

of arrests to be valued. The shadow prices applicable to the social

perspective are presented in Table V.S.

Reduced Criminal Justice'System Costs. Processing persons

through the criminal justice system (police, prosecution, courts,

corrections) is expensive. Court time alone is estimated to cost $15

per minute, so that even the simple process of entering a plea costs

close to $450.31 The prices in the table reflect the probability and

cost of an arrested person parsing through each stage of the system- -

police custody, arraignment, detention, trial, and incarceration.

Reduced Personal Injury and :Toperty Damage. Another major

benefit associated with reduced criminal activity is the decrease in

victimizAtions. The victimization benefits included in this analysis

1/8chore, Maynard, and Piliavin (1979) found that arrests were

underreported by between 41 and 48 percent when interview questions

(essentially the same as those used in this analysis) were compared to

official court records. Thus, the self-reports must be multiplied by

1.7 to obtain an estimate of the actual number of arrests. For further

details, Aee Technical Report K.

/Greenwood et al.'s (1973) estimate adjusted for price inflation.

137
MLR V.5

ESTIMATES OF AVERAGE SOCIII COST OF CRIME PER ARREST, BY ARREST CHARGE

(1977 DOLLARS)

Arrest Charge

Criminal Justice

System Costs

Personal Injury and .1

Property Damage Costs'

Stolen Propertgi

Resource Costs

Total Measured

Cost Per Arrest

Murder $24,767 $100,538 $ 0 $125,305

Felonious assault 2,732 489 0 3,221

Robbery 12,087 569 497 13,135

Burglary 5,895 537 2,317 8,479

Larceny and motor vehicle

theft

2,618 408 1,268 4,294

Drug law violation 2,590 0 0 2,590

Other personal crimes 756 94 0 850

Other miscellaneous crimes 919 0 0 919

Unspecified crimes!' 2,048 171 348 2,567

!'The The drug-law violations and other-miscellaneous-crimes categories contain primarily "victimless"

crimes; hence, a value of zero is assumed.

121Stolen property resource costs, estimated only for property crimes, are estimated as a fraction (65

percent) of the average value of property stolen per arrest (see the text and Technical Report K for details).

'The unspecified-crimes category contains arrests for which the arrest charge was either not

recorded or undecipherable. Costs for this category are estimated as the weighted average of the costs

of the other crime categories.

Jr
are the resource savings from reductions in the amount of personal

injury and property damage. Using data collected as part of the

National Crime Panel Survey program, we estimated (1) the average value

of property damage from criminal acts, (2) the average value of the

medical care needed by victims of personal crimes, (3) the average output

lost when victims lose time from work while they are recovering from

personal crimes, and (4) the average costs of administering insurance

with which to compensate victims.1/ The average cost per victimization

figures were multiplied by the ratio of victimizations to arrests in

order to represent the average cost per arrest.

Reduced Value of Stolen Property. Estimates for the value

associated with the reduction in stolen property were obtained from

vicitimization data in a manner similar to that used to estimate the

cost of reductions in property damage and personal injury. The major

difference is that part of the value of stolen property represents a

transfer from victim to thief. The remaining part of the val,e rnE

stolen property is the social cost associated with fencing the gvpla,

with a decline in the value of the goods because they mut.. 4. be sr'd

with a legal title, or with a decline in value because of . image 'he

relative magnitudes of these components are estimated on toe hp:,

of a study which found that thieves were able to realize or 35 percent

of the value to victims when they converted stolen goods into cash.-

2/

1/We would like to thank Wesley G. Skogan for his help in nbtaining

the ner,..sary estimates from the victimization-incident data that were

gatherti as part of the National Crime Panel program. Technical Report

presents a detailed breakdown and analysis of the average costs of

victimizations by category of crime.

3-/U.S. Drug Enforvement Administration, Heroin-Related Crimes

(1977). The 35 pernent estimate takes account of the fact that stol-n

cash and' other liquid abists do not *seed to be fenced.

139

11.0 r)

116.;
Thus, non-Corpsmembers are assumed to view the full reduction in stolen

property as a benefit, while Corpsmembers view 35 percent of the value

of that reduction as a cost. The remaining 65 percent of the raduced

value of stolen property constitutes a social benefit.

Reduced Psychological Costs. The values presenter! d:ove capture

only part of the costs of criminal victimizations. In pa:Licular, they

fail to capture completely the emotional benefits indivi'uals derive from

reductions in crime. These benefits are undoubtedly important; however,

because there is no accurate way to estimate their ma;paitwle, they have

not been included in the numerical estimates. Their exclusion will hist.,

our benefit-cost estimates downward, and they must be in mind when

interpreting the results.

The Value of Social Benefits from Job Corps ReNct:.Ing i.. Crime.

Table V.6 presents the estimates of the Job Corps-induced chi,,qep

in arrests for the nine arrest types. These figures have bet n adjusted cd7. for underreporting. The social shadow prices (i.e., the wmtrage social

coats from Table V.2) of the different arrest types ha/et been entered in

the next to last column. The final column gives U.e total discounted value

of the crime benefits for the in-program period al.d the first 24 months

after leaving Job Corps. The largest benefits are for reductions in

property crimes, robbery, burglary, and lar,tny. The reductions are

concentrated in the in-program period and appear to fade out quickly

over time. Altogether, the social net value of tY0. reduction in

arrests is estimated to be worth almost $2,000 per Corpsmember over this

period. When the redistributional aspects rf stolen property are taken

into account, we estimate a $2,115 per Corpsmember benefit for nonCorpsmembers, and an average cost to Corpsmembers of $153.

140
TABLE V.6

ESTIMATED VALUE OF SOCIAL BENEFITS PER CORPSHEMBER FROM REDUCED CRIMINAL ACTIVITY

(1977 DOLLARS)

a/

Arrest ChargeReductions in Arrests per Corpsmember

Social

Value Per

Arrest

In-Program

Period

Postprogram Period

Months

1 to 6

Months

7 to, 12

Months

13 to 18

Months

19 to 24

Murder , 0.002 0.001 0.001 0.001 0.001 $125,305

Robbery 0.002 0.006 0.002 0.004 0.004 13,135

Felonious assault 0.005 -0.001 -0.004 0.000 -0.011 3,221

Burglary 0.052 0.001 0.001 0.001 0.005 8,479

I-, H

A

Larceny/motor vehicle

theft

0.059 0.012 0.011 0.009 0.016 4,294

Drug law violation 0.026 0.003 0.002 -0.001 -0.005 2,590

Other personal crimes 0.019 0.001 0.003 0.001 0.000 850

Other miscellaneous

crimes

0.050 -0.001 -0.003 -0.004 -0.013 919

Unspecified crimes" -0.003 0.007 0.009 0.010 0.002 2,567

Total benefit

Total

Discouni d

Value-

$636

223

-31

517

448

63

20

29,

59

I1 22 01.11

NOTE: Details do not sum to totals because of rounding.

1/In those cases where there was more than one arrest charge, only the most serious charge was used.

Discounted to the in-program period at a 5 percent annual rate (for justification, see the text).

L'The The unspecified-crimes category contains arrests for which no charge was recorded. Costs for

this category are estimated as the weighted average of the costs for the other crime categories.

171
4. Reduced Drug and Alcohol Use

The principal measured benefit of the reduction in drug and

alconol use is the decrease in treatment costs. The types of drugalcohol treatments included in the estimates are residential and

nonresidential drug (principally heroin) detoxification, residential

and nonresidential "drug-free" treatment, alcohol detoxification,

and education and counseling services. The, resource savings associated

with the reduction in the use of drug-alcohol treatments will benefit

both non-Corpsmembers and society as a whole. The emotional benefits

from reduced drug and alcohol use, while unmeasured in this report,

will accrue to both Corpsmembers and non-Corpsmembers.

In general, there was veryjittle use of drug or alcohol treatment programs by Corpsmembers. The largest effect was observed while

they were in the Job Corps. During the postprogram period the decreases

in treatment use were all very small (a difference of less than one day

in treatment per 6-month period). The present value of the resources saved

because of these reductions is estimated to be approximately $31 per

Corpsmember for both the in-program period and the first two years of the

postprogram period (approximately $22 of this benefit accrues during the

in-program period).

5. Use of Alternative Training and Educational Programs

Decisions by Corpsmembers to obtain more or less training and

schooling generate benefits and costs to both Corpsmembers and nonCorpsmembers. For example, Corpsmembers enroll in high school programs

much less frequently than individuals in the comparison group. This is

due, in part, to the fact that many Corpsmembers obtained GED degrees

while they were in the program (see Chapter III). In this case, the

142 \

1-1'1p,"
resource savings associated with less frequent high school enrollment

are benefits to non-Corpsmembers and to society. Of course, there are

other benefits associated with additional training and education--most

importantly, increased lifetime earnings.. Ideally, our estimates of

increased'earnings and other effeCts should include these benefits for

both the Corpsmembers and the individuals in our comparison group.

However, the absence of a sufficiently long observation period forces

us to measure the changes in the operational costs of education and training

programs without observing much of the subsequent benefit. Thus, our

estimates of the net present value will be biased downward tq the extent

that Job Corps induces Corpsmembers to obtain higher levels of ed cation

(compared to what they would have obtained in the absence of Job Corps).11

Table V.7 presents the estimated value of changes in Corpsmembers' use of education and training programs; these include the

traditional school programs--high school, vocational school, college

or university education, and other schoolin, (mostly adult education

programs)--and three employment and training programs--CETA training

programs, the Work Incentive Program (WIN), anJ public service

employment programs _(primarily CETA). The largest reduction is in the

use of high school. Also, there are small reductions in the use of the

employment and training programs, especially during the in-program and

early postprogram periods. The increase in the use of college and

vocational education programs results in a small offsetting cost. The

net result is a resource savings of $85 per Corpsmember during the

observation period.

11 Further Further discussion regarding the treatment of long-run

education and traininc. t-ilefits is ?resented in Technical Report K.

143

173
TABLE V.7

ESTIMATED VALUE OF BENEFITS PER CORPSMEMBER FROM REDUCED UTILIZATION OF

ALTERNATIVE TRAINING AND EDUCATIONAL PROGRAMS

(1977 DOLLARS)

Reduction in Weeks 'of Program Use

Postprogram Period Total

In-Program Months Months Months Months Value Per Discounted

Program ' Period 1 to 6 7,to 12 13 to 18 19 to 24 Week Value'

111

I. Employment, Training,

and Work Experience

Programs

CETA and related

training

0.123 01083 0.021 0.062 0.056 $38 $13

P

4

A

WIN 0.000 0.012 0.017 0.023 0.023 74 5 i

Public Service

Employment (PSE) 0.208 0.085 0.017 -0.042 -0.028 14 3

II. School

High school 0.548 0.345 0.263 0.282 0.281 46 76

Vocational

education

0.092 -0.051 -0.108 -0.064 -0.075 23 -4

College/

university

0.065 -0.080 -0,125 -05136 -0.163 85 -34

Other school 0.163 0.118 0.083 0.100 0.084 51 27

Total benefit

P1/11.11110 eiffilINIINIIM101..111111111111.11.111111MINI e/Discounted Discounted to the in-program period at an annual rate of ,5 peicent (for justification, see the text),

174 . 1 hi
In addition to the changes in resource'use in the various education

and training programs, there will also be al.ransfer resulting from changes

LJ

in training allowances paid to Corpsmembers. ,On the basil of interview

data, we estimate that Corpsmembers received an "average of,$49 less in

training allowances (other than`those from Job Ems) because of their

enrollment in Job Corps. lmost half of this reduction is'estimabed to

have taken place while they were in-Job Corps._

6. Other Benefits

In addition to the benefit components discussed above, there are

two benefits that cannot be directly measured and valtiedi however, evidence

On them does exist. One im4rtant benefit that cannot be directly measured

is the utility that participants ,Itnd nonparticipants derive from the income

redistribution per se that is implicit in the Job Corps program. The

other benefit is the improved personal well-beingof participants beyond

what is caused by both increased earnings and the value of Job Corps

expenditures on er(ollees (for room, board, medical services, etc.). In

particular, it is very likely that the value of observed improvements in

health status and basic education are not fully captured in this analysis.

7. Benefits After the Observation Period

To this point, the discussion of benefits has focused on the time

period over which the Corpsmembers were observed--the 6-month in-program . period plus the two years after their exit from Job Corps. However,,

there is a strong reason to believe that at least some of the benefits

discussed will continue to persist after this period. This is particularly true of the earnings gains and of those benefits closely related

to increased earnings: increased taxes and reduced transfer payments.

1 70

145
The existence of these tuLlre benefits creates a difficult problem

for the benefit-cost analysis: 11 order Ito provide an accurate assessment,

it is necessary to estimate the value of all benefits and costs, and,not

just those generated during the period covered by the interviews.

While the extrapolations required by a full assessment are

important; they are subject to much more uncertainty than the estimates

of Observed' benefits and costs.Aorthese future benefits, not only

are there questions about the appropriateness of the valuation methods,

bat, in addition, the lack of direct observations uponihbich to base

those valuations creates further uncertainty. Future benefits and costs

must be estimated on the basis of,trends observed to occur during the

observation period or on the basis of long-run studies of other groups- -

both of whick are subject to considerable error and serious controversy.

;The central hypothesis of the extrapolation procedure is that

all benefits observed during a base time period will persist into the

future, and that their magnitude will decline continuously over time.1/

Thus, for example, an observed increase in earnings per year during

the base period would be assumed to continue for future periods, with

the size of the benefit becoming atelier in each succeeding year.

The base period we have adopted is the last 6 months of the

observation period. The time horizon over which benefits are assumed

to persist is assumed to be, at most, the expected worklife of the

average Corpsmember (43 years after enrolling in Job Corps). The

rate at which earnings, taxes, and transfer-program benefits are assumed

to decay was taken from a study of the long-run effect of Manpower

Development and Training Act (MDTA) training programs on participant

'Technical Technical Report K presents a more detailed explanation and

justification of the extrapolation procedures and issues covered in this

section.

146
earnings. This study found that earnings differentials had declined by

one-half after five years)) While the use of this figure is probably

somewhat conservative for Job Corps, it is the most sound estimate available

at this date and is roughly consistent with the data available toward the

end of the observation period. For all other benefits a much higher rate

was used because participation in these activities declines rapidly with'

age.-

2

In addition to the extrapolation of effects into the future, two

other issues regarding benefits and costs over time had to be addressed.

The first was to correct for the effect of inflation on the dollar-denominated benefits and costs. This was done by measuring all items in terms

of fiscal year 1977 dollars. This time period corresponds approximately

to the period when our sample of Corpsmembers entered Job Corps. As

discussed in the next section, cost data were taken from fiscal year 197",

records and require no special adjustment. For the benefits, we used

shadow prices measured in fiscal 1977 dollars or adjusted to account for

inflation.

1/A study by AshenF#.ter (1978) provides the best evidence

available on the future magnitude of the effect. He found that the

earnings gains for adult men who had participated in MDTA employment

and training programs had declined by approximately 50 percent after

five years, while the gains for adult women did not fade out. If we

assume a decline for Job Corps similar to the larger Magnitude that

Ashenfelter found for males, on a continuous basis it would imply a

rate of decline of just under 14 percent per year. In the absence of

better information, Ashenfelter's decay rate for adult males has been

adopted for both males and females. This probably overstates the decay

rates for Corpsme:mbers, both because Corpsmembers are Young and because

AshenfelteVs estimated decay rate for males is larger than that for

females.

2/Specifically, it was assumed that these effects decay at a

continuous rate that approaches zero by the time Corpsmembers reach an

average age of 25 (approximately 5 years after leaving Job Corps). This

assumption (a decay'rate of 140 percent per year) is consistent with the

observation that decreases in arrest rates and drug-treatment use decay

very rapidly over the observation period, but is overly conservative

regarding the utilization of alternative services.

147

1`x;3
The second adjustment was to account for the fact that benefits

or costs generated in the future will not be worth as much as the same

benefits or costs generated at present. This adjustment process (discounting to present values) converts the observed extrapolated streams

of benefits and costs into an equivalent dollar amount. Wt use a real

(i.e., net of inflation) discount rate of 5 percent per year. With an

inflation rate of 10 percent per year, this would correspond to an annual

interest rate of 15 percent.

Table V.8 presents the extrapolated values for the various

benefits and costs from the social perspective. The largest effect of

extrapolation is for earnings, for which the value of the benefit is

increased four times by the addition of extrapolated benefits. The

smaller numbers for crime-reduction benefits, drug use, and use of

alternative education and training programs reflect (1) the smaller Job

Corps effects observed during months 19 to 24 for these benefits and

(2) the higher fade-out rate assumed for them. Me estimated value of

all the measured benefits is approximately $7,000 per Corpsmember (in

1977 dollars).

B. COSTS

The breakdown of program costs by category and analytical

perspective is shown in Table V.9. There are three basic cost

categories: program operating expenditures; the opportunity cost of

Ccmmember labor; and the nonbudgeted costs other than for Corpsmember

la,lor. The total soci 1 cost (i.e., excluding all transfers) of Job

C-,.ps is estimated to be $5,070 per Corpsmember, while the cost to nonCorpsmembers is $5,736 per Corpsmember enrolled. The difference is the

net value of the transfers provided to Corpsmembers ($665 per Corpsmember).

148
TABLE V.8

ESTIMATED TOTAL VALUE OF SOCIAL BENEFITS PER CORPSMEMBERa/

(1977 DOLLARS)

Discounted Present Value

Observation

Period

,Extrapolation ytal

Period Benefits

A. Output produced by Corpsmembers 1

In-program output

Increased postprogram output

Increased ,ax payments on postprogram

inc lee

Increased utility due tojreferences

for work over welfare

B. Reduced Dependence on Transfp Programs

Reduced transfer payments-1

Reduced administrative costs

C. Reduced Criminal Activity

Total reduction- in observed resource

costs

d/ Reduced psychological costs

D. Reduced Drug/Alcohol Use

Total reductions in treatment Costs

Increased utility fur, reduced drug/

alcohol depenCence="

E. Utilization of Alternative Services

Total reductions in .c.sts of training,

educational, and PSE prngpmz.

Reduced training allowances

F. Other Benefits

d/ Increased utility from zedistribution

Increased utility from improved wellbeing of Corpsmembets

Thtal Measured Benefits

$757

925

0+

0

63

1,9'2

31

85

0

$ 0

2,971

0

+

0

96

150

-1

4

0

$ 757

3,896

0

+

0

158

2,112

30

90

0

$3,823 $3,220 $7,043

NOTE: Details may not sum exactly to t'..tells because of rounding.

a/

See Technical Report K fo: a detailed treatment from the other perspectives.

b/ Discounted to the in-program period at a 5 percent annual rate (fnr

justification, see the text).

£ / Item Item does not enter the social perspective (i.e., transfers between Corpsmembers and non-Corpsmembers).

/

Item is not measured in the analysis.

r49

10 0
TABLE V.9

SUMMARY OF ESTIMATED VALUE OF COSTS PEI/CORPSMEMBER,

BY ANALYTICAL PERSPECTIVE-1

(FISCAL YEAR 1977)

Present Value of Costs by Perspective

Cost Component Social Non- Corpsmember commember

A. Program Operating Expenditures

Center operating expenditures,

excluding transfers to

Corpsmembers $2,796 $2,796

Transfers to Corpsmembers 0 208

Central administrative costs 1,347 317

B. Opportunity Cost of Corpsmember

Labor During the PrograM

0

Foregone output 881 0 881b/

Foregone tax payments 0 -15?-

C. Unbudgeted Expenditures Other

Than Corpsmember Labor

Resource costs 46

Transfers to Corpsmembers 0

Total Costs $5070

46

185

$5,736

!1'The The cost per Corpsmember is estimated by aC.,tiplying the cost per

Corpsmember year (as estimated in Ter!Acal Povort K) by the average length

of stay in years for Job Corps duri; fiscal year 1977-5.9 months.

b '1 Because Because Corpsmembers berl'it from t:lnsfers, they are presented

here as negative costs.

150
1. Program Operating Exrenditures

The breed-!lwn of program operating expenditures into the three

components--center operating expenditures (exclucLng Corpsmember transfers),

Corpsmember transfers, and the central administrative costs--r Elects the

different nature and sources of Job Corps expenditures. Center operating

expenditures are costs to non7Corpsmembers and to society. These

expenditures and figures were obtained from the Job Corps. Financial Reporting

System. The Corpsmember transfers were also obtained from the Job Corps

Financial Reporting System, but they are not social costs; instead, they

represent a transfer of resources from non-Corpsmembert to Corpsmembers.1/

Finally, data on the central administrative expenditures were provided by

the Office of Management and Budget. These expenditures represent costs

to both non-Corpsmembers and society as a whole.

2. Opportunity Cost of Corpsmember Labor

Youths who participate in Job Corps forego employment opportunties

they otherwise would have taken. The wages they would live e,-ned are a

cost to them ofparticipating in Job Corps. This "opportunity cost" of

Corpsmember labOr is not balanced by corresponding benefits non-Ccrpsmembers and thus enters into the social benefit-cost cal, lati'a as a

cost.-

2/

1'Thesee transfers are expenditures for items that many Curpsmembers

would have consumed in the absence of Job Corps (e.g., food, ,AChing, and

housing) and, hence, can be assumed to value near the supply price.

2/- However, if the labor markets are in disequilibrium (i.e , if

disadvantaged youths are unemployed in the labor ma et), non-Corp ,members

receive benefits from replacing Corpsmembers on jo ; thus, social costs

are reduced. While replacement is obviously an im rtant factor given the

labor markets that Corpsmembers leave when they ent the program, we ha%e no

basis currently to estimate either the magnitude or lue of replacement

activities. Furthermore, we have no means to measure displacement during the

postprogram period or to compare its value to that for replacement.

151

i u :2
Another way to view this cost is that, from society's point of view,

the decision to enroll a person in Job Corps implies that the output that

person would have produced in the absence of the program must now be

foregone. The loss of this output is a net cost to society; the value

of this foregone output is measured by the foregone earnings. As was the

case in estimating the increase in output produced, the estimate of

foregcne earnings includes the amount of fringe benefits in order to

measure the total value of the lost output.

N nbudgeted Costs Other than for Corpsmember Labor c The opportunity cost of Corpsmember labor described above is of

course an unbudgeted item. In addition, there are other types of

expenditures whose costs do not appear in the Job Corps financial

accounts. These expenditures includ' the following items: governmental

surplus goods, for which the centers pay only transportation charges;

O

meal costs reimbursed by the National School Lunch program; medial

supplies and services provided by state and local agencies; and other

resources acquired at below-market prices., The Ilse of these resources

is a cost to non-Corpsmembers and ft society. However, the use of many

of these items represents a transfer to Corpsmembers and, hence, does

not enter into the social perspective. The opportunity cost of these

resources was estimated on the basis of special studies conducted at

thirteen Job Corps centers (see Technical Report F for more details).

C. OVERALL FINDINGS FOR NET PRESENT VALUE

Once the various effects of Job Corps have been valued,

calculating the net present value is straightforward. Table V.10

presents the values of the various benefit and cost components with

their associated net present values from the three perspectives. As

152
TABLE V.10

a ESTIMATED NET PRESENT VALUES PER CORPSNEMBER UNDER THE BENCHMAPIC ASSUMPTION/ S

(1977 DOLLARS)

Social Non-Corpsiseebet. Corpsmember BENEFITS

A. Output Produced by Corpsmembers

In-program output $ 757 67.i $ 83 Increased postprogram output 3,896 3,896

Increased tax payments on

postprogram iAt01111 0 582 -582 Increased utility due to

preferences for work over welfare +. B. Reduced Dependence on Transfer Programs

Reduced transfer payments 0 1,357 -1,357

Reduced administrative coats 158 158 0 C. Reduced Criminal Activity

Reduced criminal justice system costs 1,152 1,152 0 Reduced personal injury and

property damage 645 645 0 Reduced stolen property 316 484 -169

Reduced psychological costs

D. Reduced Drug/Alcohol Use

Reduced treatment costs 30 30 0 Increased utility from reduced

drug/alcohol dependence

E. Utilization of Alternative. Services

Reduced costs of training, educational, and PSI programs 90 90 Niduced training allowances 0 49 -49

F Other Benefits

Increased utility from redistribution

Increased utility from improved

well-being of Corpsmembers

Total Benefits $7,043 $5,220 51,823 COSTSA. Program Operating Expenditures

Center operating expenditures,

excluding transfers to

Corpsmambers $2,796 52,796 $ 0 Transfers to Corpsmembers 0 1,208 -1,228

Central administrative costs 1.347 1.347 8. Opportunity Cost of Corpsmember Labor

Foregone output 881 881 Foregone tax payments 0 153 -153 C. Unbudgeted Expenditures other than

Corpsmember Labor

Resource costs 46 46 0 Transfers to Corpsmembers 0 185 -185 Total Costs TI7313 $5,736 ' --7,i65

Net Present Value (3enefits less Costs) $1,971 -$514 ' 32,485

Benefit-Cost Ratio 1.39 0.91 1.82 NOTE: Details may not sum exactly to totals because of rounding.

1/See the text for a review of the assuptions, estimation procedures, and their

implicationi fur the values presented in this table.

b/ Thd numerators for the benefit-cost ratios include all of the benefits listed

in this table as either positive benefits cr negative costs, and the denominator includes

all of the costs listed in this table as either positive costs or negative benefits.

15.3
can be seen, the program yields net benefits to society and to Corps.'

members with our benchmark assumptions. From the social perspective,

the increase in output and the criminal-justice-system cost savings

constitute the bulk of the benefits. The largest social costs are

for the resources necessary to operate the program.

Corpsmembers benefit principally from the increase in their

postprogram earnings and from the program's transfer (shown as negative

costs) in the form of room and board. Their major costs are the foregone

earnings while they are in the program, as well as the reductions in

the transfer payments that accompany their increases in earnings. NonCorpsmembers, who bear both the costs of program operation and the costs

of the transfers to Corpsmembers, have an estimated net cost for measured

Job Corps effects.-

1/ They do receive substantial benefits from reductions

in CorpXmember criminal activity, but thes:are not sufficient to outweigh

their share di program cost. Thus, Job Corps is estimated to be a socially'

efficient use of resources and to lead to a redistribution of resources

from non-Corpsmembers to Corpsmembers.

These benchmark numbers differ from the benchmark reported in the,

earlier benefit-cost analysis of Job Corps.?" The major differences are

a higher estimate of the increase in postprogram earnings and taxes, and

1/ Of course, because there are many more non-Corpsmembers thin

Corpsmembers, the net cost to non-Corpsmembers will, on average, be

quite small (much smaller than the $514 pel Corpsmember). However,

some non-Corpsmembers (e.g., recipients.of the value of output and

additional victims of crimes in the absence of Job Corps) may benefit

substantially.

/Kellar et al. (1978) and Technical Report D.

154
a lower value for the benefits associated with reductions in t ansferprogram use', criminal activity, drug treatment, and use of al ernative

. education and training programs. These differences are due primarily

to the lengthier follow-up data used in this report--data which indicated

(1) that earnings gains persisted longer than tentatively assumed in the

initial analysis, and (2) that the other effects tended to be smaller

and decayed more rapidly than initially estimated.1/

Despite these differences, the major policy conclusion of the

two reports isthe same: Job Corps is an efficient use of resources. In

both cases the social net present value was positive, although the more

recent (and more accurate) estimate is.substantially larger ($1,971 per

Corpsmember compared to the eariler estimate of $251). Thus, this report

confirms the overall earlier finding, but with a substantially different

benefit composition.

The same is true for the conclusions regarding Coipsmember benefits.

The estimate of net present value from this perspective is positive in both

studies, with the more recent number being much larger ($2,485 per Corpsmember

compared to $212 in the previcus study). The reason for this difference is

the large upward revision of the increased earnings estimate &a to the

longer-term observation.

The only major qualitative difference in the reports concerns,the

effect of Job Corps on non-Corpsmembers. The early evaluation estimated

a small positive net present value ($39 per Corpsmember), while this

report estimates a negative value (-$514). Thus, the evaluation's earkier

conclusion that Job Corps generated positive net benefits from all three

1 " Technical Technical Report K provides a detailed examination of the

differences between the studies.

, 155 . 1st`
perspectives cannot be supported. The findings presented here suggest that

the program results in a net transfer of income from non-Corpsmembers to

Corpsmembers. , As mentioned earlier in this chapter there is uncertainty

surrounding any single estimate of net present value. Table V.11

/'

presents estimates of the net present value per Corpsmember made under

1/ our benchmark and seven alternative sets of assumptions and estimates.-

In each case, one specific assumW-ion or estimate is changed (with the

remaining benchmark assumptions and estimates being maintained).

The first four sets of alternative assumptions in Table V:11

concern the rate at which the Job Corps effects fads out over time.

The first alternative presented assumes that there are no effects

other than those already observed by the end of the observation

period (two years after leaving Job Corps). These estimates indicate

that future social benefits (after the first 24 postprogram months)

will have to be worth at least $1,249 per Corpsmember if Job Corps is

to be considered an economically efficient use of resources.-2/ The

second alternative assumption is that the earnings and corresponding

tax and transfer effects do not fade, out, while the other effects

(reduced criminal activity, drug- and alcohol-treatment use, and

1 " Only brief summaries are given here of some of the sensitivity

tests made on the various assumptions. More details arecresented in

Technical Report K.

2/ Notc that because the transfers received by Corpsmembers

ghile they are in the program are worth more than their foregone

earniLgs, Corpsmembers will have a positive net present valueveven if

ttiere are no future effects.

156
TABLE V.11

ALTERNATIVE ESTIMATES OF NET PRESENT VALUE PER CORPSMEMBER1/

(1977 DOLLARS)

Alternative

Analytical Perspective

Social Non-Corpsmember Corpsmember

b/ Benchmark assumptions $1,971 $ -514 $2,485

(1.39) (0.9,1) (1.82)

Effects are zero after the first

24 postprogram months -1,249 -2,070 821

(0.75) (0.64) (1.52)

Earnings and transfer effects do

not fade out but other effects

do fade out at the benchmark

rate 9,384 2,823 6,561

(2.85) (1.49) (1.74)

Crime, drug, and 'alternative

program effects fade out at

the same rate as earnings

effects (14 percent a year) 3,424 1,148 2,276

(1.68) (1.20) (2.10)

Crime, drug, and alternative

program effects are zero after

the fist 24 postprograMjneinths 1,817 -690 2,507

(1.36) (0.89) (1.88)

3 percent discount rate 2,546 -234 2,780

(1.50) (0.96) (f.89)

10 percent discount rate 940 -1,028 1,968

(1.19) (0.82) (1.80)

No underreporting of arrests 1,101 -1,453 2,555

(1.22) (0.75) (1.93)

/ The numbers in parentheses. below the estimates of the net present value are

benefit-cost ratios computed as described in Table V.10.

b " Benchmark Benchmark assumptions are as follows: earnings, tax, and transfer effects

fade out at a rate equal to 50.percent every fkle years; all other effects fade out

completely five years after leaving. Job Corps; the discount rate is 5 percent; the

expected worklife of a Corpsmember is forty-three years after leaving Job Corps.

(For a more'complete discussion of,these and other assumptions, see Chapter V of

Technical Report D.)

15?

183
ed4cation- and training-program use) fade out at the benchmark rate.:/

In this instance, the social, Corpsmember, and non-Corpsmember net present

values are all positive, with the total social benefits outweighing social

costs by almost $9,400 per Corpsmember.

The third and fourth alternatives illustrate the eff.ct of

changing the rate at which the reduced crime, drug treatment, and

alternative education- and training-program use effects fade out. If

these effects fade out at the lower rate (14 percent per year) assumed

1\.

for earnings and transfers, estimated net presept value would be great r . than with the benchmark assumptions, and would be positive from all thre

perspectives. The social net present value would be almost doubled- -

to $3,424 per Corpsmember. On the other hand, if these effects do not

persist after the.two-year postprogram observation period, then net

present value will be lowered. This decline ($154 per Corpsmember) is not

large, however, because the future value of the estimated effects is

small under the benchmark assumptions of an extremely rapid fade-out

rate (140 percent a year) and short-time horizon (5 years after the

observation period ends).1"

The approprate discount rate to use when evaluating government

training and educational programs is always a controversial issue because,'

1 /Thiss test was adopted because there is evidence that Parnings

apd transfer effects are not-fading out, but that criminal activity,

drug use, and participation in training and educational programs decline

a5! people grow older. As a result, the magnitudes of reductions in these

latter activities' would probably fade out even if the percentage reduction

e to Job Corps participation did not..

2/ For example, one year -fter the end of the observation period the

value of theSe effects would bk, reduced 77 percent under the benchmark

iade-out assumptions. After two years, the value would be reduced by 95

plercent.

158

V 4f) 4

/ g
while the-choice of a discount rate is very 'important for the evaluation

and is well established theoretically, there has never been a completely

satisfactory way to estimate discount rates. Imperfections in the markets

for capital, the existence of risk and uncertainty, inflation, and the

fact that many tax-incidence questions are still unresolved have made it

impossible to determine a single discount rate appropriate for evaluating

goyrment investments. As a result, we have adopted a 5 percent real

1/ rate (i.e.., net of inflation) as our benchmark.- Because of the somewhat

arbitrary nature of this assumption, we test the sensitivity of the findings

to variations in thii assumption.

To test the sensitivity of the findings to assumptions about the

discount rate, net present value estimates were made by using 3 and 10

percent real discount rates. (T)ese alternative estimates are presented

in Table V.11). As can be seen, the social net present value changes in

the opposite direction from the discount rate. Lower discount rates

increase Lhe present value of social benefits, but leave social costs

unchanged because all of them are incurred during the,initial time period.

ThUs, using a 3 percent discount rate. increases the social net present

value by approximately $575 per Corismember compared to the benchmark

.11 estimate. In a similar man increasing the discount rate from the. 5

percent benchmark rate to 10 percent decreases the social net present

value by over $1,000 per Corpsmember, although it is positive.

The last sensitivity test presented in Table V.11 concerns the

estimation of tt.; crime-reduction benefits. The benchmark procedure

adjusts the arrest data to account for the underreporting.o arrests

1/

For further documentation, see Technical Report K.

159

1L
in the interviews. However, the estimate of underreporting is subject

to some uncertainty and may not be entirely appropriate for the sample

of youths enrolled in Job Corps.-1/ To see the effect of this adjustment;

we have estimated net present value using the unadjusted self-report data

on arrests. This has the effect of dividing the benchmark estimates of the

crime reduction benefits by 1.7. The resulting net present values display

the same pattern as the benchmark values, but are almost 50 percent smaller

from the social perspective (net present value from the eorpsmember

perspective rises because the estimate of foregone theft income is

reduced).?

The general conclusion of these sensitivity tests is that as long

as the earnings gains do not decay extremely rapidly (e.g., greater than

37 percent per year) after the two-year postprogram observation period

(and there is no evidence that they will), Job Corps is an economically

efficient use of resources. 2/ In addition, Corpsmembers receive large

positive net benefits, while non-Corpsmembers as a group will bear some

costs of a redistribution of income. ,Under diverse assumptions, the

1/The underreporting estimate was made by examining official records

and interview data that: used questions and survey techniques similar to those

used in the Job Corps interviews. However, the interview data used in the

validation study were for a sample of slightly older ex-offenders and exaddicts. Thus, while the results are the best available for our purposes,

they have a large potential for error.

?Other Other assumptions are examined in more detail in Technical Report

K and are found not to substantially alter the results.

2/If only earnings and transfe: effect persist into the future,

then at a 5 percent discount rate social net p. sent value will be positive

as long as these effect do not fade out more rapidly than 37 percent per

year. If all effects persist and decay at the same rate, social net

present value will be positive if the rate is less than 57 percent per year.

Alternatively, if all effects persist unchanged for a year and a half

past the end of the observation period, social net present value will

be positive.

160
sensitivity tests indicate that Corpsmembers will receive a substantial

net benefit, probably worth approximately $2,500 on average. Finally,

if the various benefits that arz left unmeasured (preferences for having

Corpsmembers lead "more acceptable" life-styles; reduced psychological

costs of crime; and satisfaction from the redistribution of income and

improved well-being to Corpsmembers) could be added to the measured

benefits, the results would undoubtedly be even more favorable toward

Job Corps, especially as far as non-Corpsmembers are concerned.

D. SUMMARY AND CONCLUSIONS

The principal issue analyzed in this chapter is whether the

investment in Job Corps is economically efficient--specifically, does

society have more goods and services at its disposal because of the

investment in Job Corps? The findiles of this analysis suggest that

public investment in Job Corps is efficient. Our benchmark estimate is

that the social value of benefits in fiscal year 1977 exceed:: costs by

almost $2,000 per Corpsmember, or by approximately 39 percent of ,osts,

and the program is found to be efficient under a wide range of altecaative

assumptions and estimates. Because over 40, Si9 youths enrolled in Job

Corps during fiscal year 1977, our benchmark estimate of the net social

benefit is approximately $79 million for that year.

We estimate that over 60 percent of the social benefits are

generated '-y increases in the value of output that Corpsmembers produce.

Another 30 percent of the social benefits are attributable to reductions in

criminal activity among Corpsmembers--particularly burglary and larceny.

These benefits from reductions in crime include reductions in personal

injury, property damage, stolen property, and criminal justice systeir

costs. The bulk of the social cists are incurred from operating the

program.

161

1;)2
The analysis of social benefits and costs abstracts from the

fact that members of society share disproportionately in the benefits

and costs. The equity effects of the program are important for a

complete analysis of the program. As a result, we also analyzed the

'benefits and costs of investments in Job Corps from the perspectives of

both Corpsmembers and all other members of society (non-Corpsmembers).

Our benchmark distributional estimates indicate that the average

Corpsmember receives a net benefit of $2,485 from participating in Job

Corps. We estimate that non-Corpsmembers as a group incur a net cost

of $514 per Corpsmember.

Approximately 70 percent of the benefits to Corpsmember are

accounted for by their increased earnings. The other major benefits

are the transfers they receive while they are in Job Corps. The largest

cost borne by Corpsmembers is the reduction in their transfer income,

although the opportunity cost of-the time they spend in Job, Corps and.the

increase in tax payments are also significant costs for them.

Non-Corpsmembers receive over $5,200 per Corpsmember in benefits,

mostly from the reductions in Corpsmembers' criminal activity and the

use of transfer programs. However, they incur almost all of the costs

for the operation and administration of the program. As a result,

measured costs exccul measured benefits from the non-Corpsmember perspective

of the Job Corps expenditures, including a large transfer to Corpsmembers.

Estimating the present value of benefits and costs required

numerous assumptions and approximations. In particular, because this

analysis is based on interview data that covered, on average, only two

years of postprogram activity, we have had to make some speculative

assumptions about the magnitude of Job Corps effects after this observation period. We assume that the Job Corps effects on earnings, tax

1.62
payments, and transferrprogram use fade out at approximately 14 percent

per year. The other effects--reductions in crime, in drug and alcohol.

treatment, and in the use of alternative education and training .. programs

were assumed to fade out entirely 5 years after leaving Job Corps (an

extremely fast fade-out rate). Sensitivity tests of this and other

assumptions suggest that as long as earnings effects do not deday more

rapidly than 37 (32) percent per year, assuming a real discount rate of

5 \10) percent a year, we estimate that Job Corps is an efficient

1/ use of resources.- Alternatively, all observed program effects would have

to be' maintained for approximately one more year in order for the social

net present value to be positive.

1/

- Note that our benchmark assumptions include an even higher decay

rate for other effects, so that to the extent that the observed beneficial

effect are maintained or grow, the implicit internal rate of return is

very large.

163
VI. DIFFERENTIAL IMPACTS AMONG CORSPMEMBERS AND CENTERS

The discussion of the estimates of ..overall Job Corps impacts on

employment and related activities in Chapter III and its companion discussion

in Chapter IV provide only a limited indication of differential impacts among

Corpsmembers and centers. One set of differentials noted in these earlier

chapters is the differential between males and females, and, for females;

between those without and those with children. As explained in Chapter III,

4 our previous research (see Mallar et al., 1978) found that the behavioral

relationships of interest were substantially different foi these three,

subgroups, based on statistical tests for differences in parameters (Chow

tests). With an appropriate specification, however, we foynd that

observations of youths could be pooled together across other demographic

classifications.

We begin this chapter-with a review of the pattern of differences

in impacts between the sexes, including differences by presence of

dependent children for females. We then discuss differential impacts by

Job Corps completion category, which were introduced but not fully

explored in Chapter III. We conclude this chapter by examining

differential impacts by program treatments among Corpsmembers a.id centers,

which is clearly a most important dimension for considering improvements

to program operations. However, for our exploratory analysis of the

differential impacts by program treatments, it, is not possible to separate

the causality of differences in program treatments from underlying

differences in the subgroups receiving those program treatments (see

further lAlow).

164
A. DIFFERENTIALS BY SEX AND FAMILY RESPONSIBILITY

The Jab Corps impacts are quite different in magnitude for males

and females, and among females they are different for those without and

those with children. These impacts are detailed in Tables 111.2 through

111.6 and in Table IV.4 of their respective chapters. Representative

impacts for the 12- to 18-month period after termination are_summarized

in Table VI.1.

An inspection of the estimated effects presented in Table VI.1

finds that 'Job Corps impacts for males are larger relative to females

without children for the receipt of Unemployment Insurance and for the

'probability of being in military service. While the impacts on

Unemployment Insurance are also important for females without children,

the larger impacts for them relative to males are for employment and

earnings, receipt of welfare, and education. However, these comparisons

require some qualification because the base levelslof activity are different for the two groupsthit is, males and females without children

behave differently in the absence of Job Corps participation. For example,

females have aslower probability of employment and earnings in the absence

of Job Corps participation. Therefore, the estimated differenles in

.impacts by sex are even larger in percentage 'terms for employment and

earnings. The opposite-appears to be the case for the receipt of welfare

and education measures, for which larger base levels of activity for

females in both cases suggests smaller percentages compared to absolute

differentials between males and females.

The impacts estimated for females with children are generally

quite different from those estimated foi the other two groups. Employment and earnings impacts, for example, are small in magnitude and are

not significantly different from zero. However, they are sensitive

165

g

1 Jo
TABLE VI.1

RiiRESENTATIV1 ESTIMATES OF DIFiERENTIAL IMPACTS BY iEX AND FAMILY RESPONSIBILITIES,

12 TO 18 MONTHS AFTER TERMINATION!

/

Job Corps Effects for Job Corp Effects for Females

Variable 1%14, Without Children With ChildrenEmployed (fraction of time) 0.079\ 0.099** . -0.009

Earnings per Week (dollars) 8.63 9.69* -0.82

Receipt of AFDC or General

Assistance (fraction of time) -0.030*** -0.138**** -0.046*

Receipt of Unemployment

Insurance (fraction of time) -0.02500 -0.019*** not estimated

Probability in Military

during Survey Week 0.056*** 0.0003 0.000

Probability of having a High,

School Diploma or GED by

Time of Interview 0:187**** 0.53300 not estimated

*Significantly different from zero at the 80% level o! statistical confidence (90% for a one-tail test).

**Significantly different from zero at the 90% level of statistical confidence (95% for a one-tail test).

***Significantly different from zero at the 95% level of statistical confidence (97.5% for a one-tail test).

 Significantly different from zero at the 99% level of statistical confidence (99,5% for aone-tail test).

NOTES: The significance levels given here may be slightly bia!ed because the estimates of standard errors

used for the underlying significance tests were obtained from a regression program which does not

account for the implicit heteroscedasticity when controlling for unobserved differences between

Corpsmembers and the comparista sample via the Heckman (1979) approach. In practice, however, the

significance levels from the regression program are usually very close to those from test statistics

using unbiased estimates of standard errors, especially when the coefficients for the adjustment

variables are statistically insignificant (which is usually the case here). Therefore, the significance levels given here are approximately accurate and are indicative of the true significance levels.

a/

Most of the variables in this table are estimated for the civilian population only. The one

exception is for theprobability of being in the military during the interview week.

/2/Estimates are obtained from models which exclude fertility variables (see Chapter IV); including the

fertility variable makes the estimates much more favorable for Job Corps.. Also, the estimated impacts for

`.early dropouts must be assumed to equal zero because of the extremely small sample sizes.

193
to the'inclusionvof fertility characteristics in the estimating model--that

is, they are much more positive when fertilit characteristics are included

(see Chapter IV). The other major trends are r ductions in the use of

public assistance (primarily AFDC) and, perhaps urprisingly, increases in'

the fraction of time spent in training programs ( of shown in Table

see Chapter IV). The impact on public assistance females with children

is much larger than that for males and childless f les in absolute

magnitude, but smaller in percentage terms.

B. DIFFERENTIALS BY COMPLETION CATEGORIES

Differences in impacts by completion categories re Amportant in

this evaluation for two reasons. First, they are inheren ly interesting

for program operations as measures of the effects of vary g the length of

stay in Job Corps or the degree of program completion.11 ond, we need

to estimate the impacts for each completion category so that we can

reweight them in order to obtain overall impact estimates tha

indicative of the average for all Job Corps enralees-(- see-Chaler III

for more details on this procedure).

An important issue in drawing inferences for program opetions

is whether we have obtained generally unbiased estimates of effect by

completion category (this does not affect the unbiasedness of the o erall.

estimates). As we described in Chapter III, we have not been able t

obtain reliable estimates that control for unobserved differences amo g

Corpsmembers by completion category. We argued that the effects are

plausibly unbiased, however, for a number of reasons. First, the patte

1/- As explained in Chapter III, completion category is not perfectly

correlated with length of stay because of the individualized and selfpaced nature of Job Corps instruction.

167 1JD

\t,
of effects by completion category is reasonable; in particular, the effects

estimated for the group with near zero treiment (early di-opouts),are

close to zero: Second, we control for a wide range of observable

variables, some of 'which may also be7proxy controlsyfor the effects of

un9bservable characteristics. Third, any remaining causes of bias are l%kely to be in opposite direCtions and at least partially offsetting;

for example, the Job Corps completion category includes both youths

who are highly motivated and able (i.e., high benefits to- staying in

the program) and youths who have little initiative and poor labor-imarket - opportunities '(i.e., low opportunity costs to staying in. the program).

The rest of this section will provide additpnal evidence on the first

of these points--the pattern Of effeCts by completion categories.

Patterns of effects over time for each completion category are

shown in Figures III.1 through III.10 in Chapter III. The differentials

among the three categories are exactly what we might expect--there is a

strong correlation between the amount of the program completed and Job

Corps impacts. Program completers fairly consistently benefit the most

from their Job Corps experience; partial completers benefit-somewhat

less; and early dropouts benefit littleor not at all. (The sample sizes

for early dropouts are relatively small, and the estimated impacts

fluctuate a good deal over time. However, they tend to fluctuate' around

zero.) Among'program completers, there are large and relatively uniform

effects (as evidenced by relatively large estimated effects and relatively

small standard errors).

Job Corps impacts by completion categories for a specific time

period (12 to 18 months after termination) are presented in Table VI.2.

The differential impacts by category generally follow the pattern

described above, with only a few exceptions. The most notable exception

168
TABLE VI.2

REPRESENTATIVE ESTIMATES OF DIFFERENTIAL IMPACTS BY COMPLETION CATEGORIES

12 TO 18 MONTHS 'AFTER TERMINATION!

0

Males . Females Without Children

Program Partial Early Program Partial Early

Variable .Completers Completers Dropouts _Clipleters Coppleters Dropouts

Employed (fraction

of time)

Earnings per Week

(dollars)

Receipt of AFDC or General Assistance

(fraction of time)

0.155** ** 0.044* , 0.047 0.176****

24.79 * * ** -1.25 3.92 36.36 

..--,. -0.044** ** -0.033*** -0.018 -0.170 

Receipt of Unemiloyment Insurance

(fraction of time) 1016** 

Probability in Military

during Survey Week 0.087****

Probability of having

a' High School Diploma

or GED by Time of

Interview 0.399****

Iv .*

a

-0.030**** -0.027**** =0.012*

0.058*** 0.032 0.011

0.143**** 0.049* 0 683****

0.081* 0.054

14.63** 5.92

:0.145  -0.108** **

,

-41.022**4 -0.022**

4.003 -0.005

. 0.392  0.525** **.

i

,*Significantly differ t from zero at the' 80% level of statistical confidence (94 for a one-tail test).

**Significantly differ t fail zero at the 90% level of statistical confidence (95%,for a one-tail test).

***Significantly differe t from zero at the 95% level of statistical confidence (97:% for a one-tail test).

****aignificantly different from zero at the 99%.1evel of statistical confidence (99.5% for a one-tail test).

NOTES: The significance levels given, here may be slightly biased because the estimates of standard errors'

used for the underlying significance tests were obtained from a regression program which does not

account for the implicit heteroscedasticity when controlling for unobserved differences between

Corpsmembers and the comparison sample via the Heckman (1979) approach:, In practice, however, the

significance levels from the regression program are usually very close to those from test statistics

using unbiased estimates of standard errore, especially when the coefficients for the, adjustment

variables are statistically insignifiont *ich is usually the casehere). Therefore, the significance levels given here are approximay 4ccurate and are indicative of the true significance levels.

a/

- Most of the.variables in this table are estimated for the civilian population only. The one

exception is for the probability of being in the military during the interview week.

201 4 0 .
is the pattern for the receipt of Unemployment Insurance. However, the

lower reductions in the level of receipt for program completers may be

due to the higher level of employment and, hence, qualification for

Unemployment Insurance benefits for this group. The pattern is also

somewhat unclear for education and the re. -,.pt of welfare among.females.

Overall, these results lend support to the conclusion that the observed

differences, by completion category are at least partially attributable

to a program effect.

Additional evidence for differentials by completion categories

comes from Corpsmembers' self4eraluation of the impact of Job Corps

participation on future employment. Specifically, for each job

Corpsmembers had they were asked whether the training, work experience,

or education they received in Job Corps helped them obtain that job)]

These responses were tabulated to show the proportion who reported their

Job Corps program helped them obtain a job, as well as the proportion of

jobs in the postprogram period that were obtained with help from the Job

Corps program. As summarized in Table VI.3, there, is a strong correlation

between program completion and the amount of help from their program

treatment. Almost two-thirds of the program completer. reported that

their Job Corps program helped them obtain at least one job. The proportions

for partial completer. and early dropouts are one-third and one-quarter,

respectively. The differentials are even greater when all jobs in the

postprogram period are considered: program completer. reported that their

Job Corps program helped them obtain 45 percent of all jobs held in

the period; the figure is only 20 percent for partial completers and less

than 10 percent for early dropouts.

1/- Education was not specifically included in the wording for the

First Follow-Up Questionnaire, which undoubtedly leadb to some unknown

amount of downward bias.

1;a
TABLE VI.3

CORPSMENBERS' SELF-EVALUATION OF JOB CORPS IMPACTS ON EMPLOYMENT

All

Corpsmembers

Program.

Completers

Partial

Completers

Early

Dropouts

Proportion Who reported

that Job Corps

training, work experience, or education

was helpful in

obtainigg at least

one job .502 .626 .347 ,.261

Proportion of all

jobs in the postprogram period for

which Corpsmembers'

program was of help

in obtaining .346 .450 .240 .095

a/

Education was not specifically included in the wording for the First

Follow-Up Questionnaire, which undoubtedly leads to some unknown amount of

downward bias.

171

20,1
The larger beneficial impacts observed for program completers does

seem at least partially attributable to the effect of staying in the

program longer and completing. Therefore, the overall performance of

Corpsmembers would likely be improved if thdy could be induced to stay in

the program longer so that more of them could complete their Job Corps

education and training.

C. DIFFERENTIALS BY CORPSMEMBER CHARACTERISTICS AND PROGRAM TREATMENTS

We have previously reported (Mallar et N1., 1978) the results of

our first attempt at analyzing differences in impacts among Corpqmembers

and centers other than those associated with sex and completion category.

Corpsmember characteristics were measured by interview data, while general

center characteristics were taken from published sources no MIS data on

Corpsmembers had been linked to our sample members' interview, records at

that time). The analysis focused on labor-market impacts (as measured by

employment and earnings) and Job Corps completion and length of stay.

No large or statistically significant differences in the employment

and earnings impacts of Job Corps participation were correlated with the center

characteristics, which included administration, operator, size, location, or

co-educational status. However, characteristics of Corpsmembers did seem to

affect the subsequent labor-market performance of participants. For females

without children, those who,had a high School diploma at preenrollment had

higher levels of employment and earnings in the,postprogram period. In

addition, Corpswomen who were at least 18 years of age when they left Job

Corps tended to have higher earnings. While race/ethnicity differences

appear, they are not significantly different from the overall means for both

employment and earnings. Among Corpsmen, both race/ethnicity and age at

termination influenced their postprogram labor-market experiences. Hispanics

and whites tended to have much higher levels of employment and earnings than

did either blacks or American Indians. In addition, thore who were at least

172
18 years of age when they terminated from the program tended to have better

postprogram labor-force experiences by both measures.

With the availability of the MIS data base and its detailed

Corpsmember and center-related information on program treatments, we sought

to explore further the differential impacts among Corpsmembers and centers

with the last full quarter (approximately 12 to 15 months, on average, after

leaving Job Corps)--eighth-quarter measures of employment and earnings. We

included in the analysis the same Corpsmember characteristics which showed

differentials in the earlier analysis, with one change: the specification

of age wns changed from age at termination to a more policy-relevant measure,

age at enrollment. In place of the general center characteristics which

showed no differential impacts, we included in the analysis (1) the

occupational cluster associated with Job Corps training that each Corpsmember received, (2) whether or rut each Corpsmember completed the Job

Corps GED program, and (3) some more refined center, variables (see,further

belOW).

The,estimates of differential impacts associated with program

treatments that'are presented in,the remainder of this chapter should

be.regaided as only exploratory because of selection and unobserved

variable problems which preclude drawing inferences about the Causality

of observed correlations.. Corpsmimbers are not randomly assigned to

program treatment; rather, Job Corps explicitly attempts to adapt its

program tolit the specifiC needs Of each individual youth. Therefore,

the differential impacts that we observe for program treatments may be

caused by underlying, differences, in ability, motivation, or other

socioeconomic' background factors that affect program assignmOts but that

are not observed in our evaluation data. For example, new Corpsmembers

who cannot read at all are often initially assigned to a vocational
training program that does not require any reading and thus appears to be

relatively ineffective (even if it is in fact very effective), because the

Corpsmembers who are assigned to it have lower ability and less preparation

than average, and we do not control for nonrandom assignments'based on

reading level at entry.

As shown in Tables VI.4 and VI.S, subsequent employment and earnings

performance is associated with race/ethnicity and high school completion

prior to entering Job Corps (All of the effects in this chapter are

estimated with regression models that control for all other characteristics

noted; as well as for pre-enrollment work histories.) Differences for

race/ethnicity are consistently significant for males, and significant in

the case of employment for females. During the postprogram observation

period, whites and hispanics seem to have higher levels of employment and

earnings than blacks and American Indians. Except, perhaps, for employment

among males, receiving a high school diploma prior to entering Job Corps

is associated with higher levels of employment and earnings. Age at

enrollment appears to make little difference for subsequent labor-market

outcomes.

Of the two center-related variables, it is reasonable to expect

that the differential effect of completirg a GED program in Job Corps is

approximately the same as the differential effect of receiving a high

school diploma prior to entering Job Corps. That expectation is generally

confirmed, partiilarly for earnings. For males, the type of occupati6nal

training received affects the Job Corps impacts. Ninety percent of the

Corpsmen were in one of five clusters--Service Occupations, Food Service,

Automotive and Machinery-Repair, Construction Trades, and Industrial

Production. Corpsmen who were in the Service and Food Service training

programs are subsequently employed a lower than average percent of the

time, while those in Automotive and Machinery Repair and Industrial

1.74
TABLE VI .4 Dirratunn IMPACTS AMONG CORPSMEMBERS AND PROGRAM TREATUBMTS FOR MALES

DURING THE LAST FULL QUARTER OF OBSERVATION

Employment Earnings Lentith of Stay Program Completion

Overall Mean: 0.64 (Overall Mean: 106.36 Overall Mean, 295.54) (Overall Mean: ual

Corosmembers

Race/ethnicity

Black (n 577) 0.63 94.90 320.97 0.56

White (n 197) 0.69 141.63 228.56 0.48

Hispanic (n 0 89) , 0.68 112.25. 309.29 0.64

American Indian (n 31) 0.46 74.14 225.41 0.34

Other Race/Ethnicity

(n 10) 0.61 109.96 235.22

(F-value) (2.611)*** .908)  (14.279)** **

0.40

0 (3.60

Age at enrollment

(3.608) ****

15 (n 2) 0.48 118.52 161.61 0.03

16 (n 216) 0.64 98.80 299.42 0.51

17 (n 239) 0.63 106.15 295.17 0.50 18 (n 168) 0.66 113.62 307.38 0.61 19 (n 140) 0.63 106.36 267.04 0.53

20 (n Is 80) 0.67 112.48

315.19

0.58

22 (n 2)

(F-value) (0.292)

0.42

11(i.804)

275.26

(1.241) (1.569)*

0.63 0.59 21 (n 57) 0.61

High school diploma

prior to entering Job

Corps

No (n 792) 0.63 102.91 0.51

r0::7264 Yes (n 112) 0.68 128.12 0.76

(5.307) * ** (23.090)**** (F-value) (1.093) (0.716) Center CoMpletion of GED program

in Job Corps

. a No (n 751) 0.63 103.73

Yes (n 153) 0.68 118.40

(F- value) (1.172) (2.508)*

Occupational Training Cluster

Sub professional (n 11) 0.55 98.63

Clerical and sales

(n 20) 0.63 129.51

Service OCCUp3tione

(n 93) 0.58 99.78

Forestry, farming and

gardening (n 15) 0.67 72.41 Food service (n 84) 0.58 88.81

Automotive and machinery

(n 140) 0.70 108.27

Construction trades

(n 359) 0.62 105.49

Electrical/appliance

repair (n 18) 0.68 94.90

Industrial production

(n 140) 0.69 121.05

Transportation (n 7) 0.98 202.89

Health occupation (n 7) 0.80 83.43

unassigned (n 10) 0.57 84.33

(F-value) (1.351)* (1.702)**

279.57

373.82

(44.199) 

316.21

229.02

282.55

278.30

272.79

333.62

294.91

292.35

307.48

200.70

374.93

134.13 (3.024)** **

0.47 0.88

(85.691) 

0.49

0.29

0.55 0.68

0.63

0.55

0.53

0.52

0.59

0.11 0.46

0.13 (2.291)** **

*Significantly different from zero at the 80% level of statistical confidence (90% for a one-tail test).

**Significantly different from zero at the 90% level of statistical confidence (95% for Lone-tail test).

***Significantly different from zero at the 95% level of statistical confidence (97.5% fdrone-tail test).

 Significantly different from zero at the 99% level of statistical confidence (99,5% for one-tail test).

175

208.
FOOTNOTE FOR TABLE VI.4

/ The findings presented in this table are based on multiple regressions; therefore, the estimates

for each subgroup are net of the independent influences of all other subgroups in the table (i.e., we control for all of the variables in the table simultaneously). The estimates for all relevant subgroups would have to be averaged in order to obtain the estimate. for a particular set of Corpsmember and center characteristics.

The 7-statistics shown in parentheses at the bottom of each factor (subset) are for null hypotheses that all of the regression coefficients underlying the results shown for each factor are simultaneously equal to zero.

176
TABLE VI.5

DIFFERENTIAL IMPACTS AMONG CORPSMEMBERS AND PROGRAM TREATMENTS F2 FEMALES WITHOUT CHILDREN DURING THE LAST FULL QUARTER OF OBSERVATION=

Employment

Subgroup (Overall Mean: 0.53)

Earnings

(Overall Mean: 69.68)

Length of Stay

(Overall Mean: 298.34)

Program Completion

(Overall Mean: 0.67)

Corpsmembers

Race/ethnicity

Black (n 2 153) 0.48 64.71 309.19 0.72

White (n 65) 0.54 74.10 220.09 0.49

Hispanic (n = 40) 0.70 80.55 405.57 0.80

American Indian (n 2 7) 0.52 57.13 210.55 0.61

Other Race /Ethnicity

(n 3) 0.98 112.88 188.88 0.39

(F-value) (2.287)**  (0.791) (9.267)**** (4.101) 

Age at enrollment

16 (n 39) 0.47 65.87 308.54 0.74

17 (n = 57) 0.43 60.21 289.48 0.70

18 (n 22 62) 0.63 85.58 296.37 0.69

19 (n = 48) 0.53 55.50 302.80 . 0.56

20 (n = 40) 0.53 71.99 Z41.65 0.62

21 (n = 21) 0.57 80.29 324.35 0.74

22 (n = 1) 0.93 120.90 27.16 0.81 (F-value) (1.275) (1.155) (0.685) (0.720)

High school diploma

prior to entering Job

Corps

No (n 180 0.47 58.64 291.94 '0.56 Yes (n = 88) 0.66 91.05 311.58 0.90

(F-value) (6.708)** ** (6.635)*** (0.002) (22.174)****

Center Completion of GED program

in Job Corps

No (n 215) 0.51 66.23 274.87 0.60

Yes (n 53) 0.60 85.29 393.09 0.96

(F-value) (1.174) (1.667)* (17.043)**** (20.503)****

Occupational Training Cluster

Sub professional (n 2) 0.51 -0.58 274.16 0.54

Clenical and sales

(n 130) 0.61 , 80.53 306.97 0.61 Service occupals

(n 0 4). 53.66: 424.02 1.05 Forestry, farming and

gardening (n 1) 0.56 66.29 530.77 1.08 Food service (n 20) 0.54 56.15 304.65 0.87

Automotive and machinery

(r 0 1) 0.79 85.78 330.30 0.79

Construction trades

(n 14) 0.50 85.85 274.85 0.47 Electrical/appliance

repair (n 2) -OAS -- 376.54 0.72

Industrial production

(n 13) 0.30 49.28 342.56 0.86

Transportation (n 5) 0.50 49.96 374.61 1.00

e Health occupation (n so74) O.- 60.67 2(5.86 0.68

Unassigned (n 2) -0.1i -11.54 128.34 0.58

(F-value)' (1.449)* (1.158) (1.287) (1.692)**

*Significantly different from zero at the 80% level of statistical confidence (90% for a one -tail test).

**Significantly different from zero at the 9U% level of statistical confidence (95% for a one-tail test).

***Significantly different from zero at the 95% level of statistical confidence (97.5% for one-tail test).

 Significantly different from zero at the. 99% level of statistical confidence (99.5% for one-tail test).

177

210
FOOTNOTE FOR TABLE

!IThe findings presented in this table are based on multiple regressions; therefore, the estimates for each subgroup are net of the independent influences of all other subgroups in the table (i.e., we control for all of the variables in the table simultaneously). The estimates for all relevant subgroups would have to be averaged-in order to obtain theestimate for a particular set of Corpsmember and center characteristics. The F statistics shown in parentheses at the bottom of each factor (subset) are for null. hypotheses that all of the regression coefficients underlying the results shown for each factor are simultaneously equal to zero.

178

2.1
production have the opposite experience. This

-impactsagenerally carries over to earnings.

ttern of differential

\

For females, the type of occupational training received affects

only the Job Corps impacts on employment. Of the clusters with the

Le

largest enrollment, Corpswomen who were enrolled in Clerical and Sales

are employed a greater than average proportion of the time, while those

who were enrolled in Construction Trades, Health Occupations, and

particularly Industrial Production are employed a lower than average

proportion of the time. While most of this pattern for females carries

over to earnings, the differential cluster effects are not statistically

significant.

Since completion of the Job Corps program and length of stay seem

to positively affect the various measures of economic performance, the

differential impacts on these two factors are also important.1/ Blacks

and Hispanics clearly are ore likely than whites and American Indians

to stay longer in Job Corps'and also to complete a program., Receiving

a high school diploma prior to entering Job Corps increases the likelihood

of completing a program, but does not significantly affect length of stay.

Once again, age at enrollment has no effect.

Completing a GED program in Job Corps would seem to require a

Corpsmember to stay in the program longer, and that pattern is quite

evident. A strong positive correlation also exists between completing

a GED program and being classified as a Job Corps completer.

1/Regressions with months in Job Corps as the treatment measure;

instead of the three program completion categories, show poditive and

statistically significant effects on postprogram employment and earnings

associated with an additional month in the program.

179

212
For females, the type of training affects only completion, and

in a pattern that does not closely follow the differential .utpacts on employment. Corpswomen who were enrolled in Clerical and.Sales and

Construction Trades training programs are less likely than average to

be completers, while those who were enrolled in Food Service and

Industrial Production training progrii/are more likely. The pattern that

emerges from this analysis and our earlier analysis of center-related

variables is that, while distinctions in general center characteristics

J not show differential impacts, distinctions in the actual training and

education treatments Corpsmembers receive at centers do, suggest differential

impacts.

Another view concerning differential impacts that is often put

forth by researchers and program personnel is that environment it an important determinant of how much an individual Corpsmember gets out of

the program. In this view, important determinants of Job Corps impacts

are (1) how center characteristics relate to a Corpsmember's home

environment and (2) how his or her activities in Job Corps relate to what

others are doing at the center.

As a test of this view, we analyzed the relationship between the

outcome measures used in the previous two tables and several new measures

of center characteristics that were constructed partially with MIS data.

The first set of variables indicates the similarity between Tarpsmembers

and the centers they 'attended for sex,, race/ethnicity, and location (i.e.,

rural-urban). This is measured As a mean absolute deviation' between a

Corpsmember's characteristics and his or her center's characteristics.-1/ n

1- / The mean absolute deviation is formally defined as X - Xdi

.

. wl n ill ai re n is the number of cells, X '4 is the actual value of X

r the ith observation, andXd4 la some designated level of X for that

bservation. .If, for example, Oe are measuring sex and the tz) ervation is

180

213
\ Thus, a smaller valeffor this variable i.e.,approaching zero) indicates

less deviation and greater similarity; a larger value (i.e., approaching one)

indicates more deviation and less similarity. The second set of variables

indicates the similarity between the characteristics og the center attended

and a uniform distribution of characteristics (i.e., 0 percent'male and

50 percent female for sex; 25 percent each of black, hits, klispanic, and

AMericen Indian for race/ethnicity; and 50 percent ban and 50 percent

rural for location). Once again, the similarity is measured as mean

absolute deviations, so that lower calcu ated values indicate 'less r.

deviation and greater similarity to a uniform distribution. 17 ally,

we include a variable which measurebdi ly the percentage of Corpsmembers

in the center attended who are enrolled in a GED program, and a et of

variables which measure the percentage who are enrolled in each occupational

training cluster. All of the effects were estimated with regression models

which also control for race/ethnicity, education, age, and baseline work

histories.

The results for males and females are shown in Tables VI.6 and VI.7,

respectively. The variables indicating similarity between Corpsmembers and

their centers do not strongly support the importance of such similarity.

The only cases in which effects, are statistically significant are, the sex

and location effects on length of stay for males and the sex effect on

length of stay for females. As was expected, all of these effects are

negative--that is, greater similarity in sex or location is associated

with increased length of stay at centers.

J. female; but the center is only 40 percent female (X = .4), the mean absolute

deviation equals .60. If, on the other hand, the enter is 80 percent female

(Xd = .8), the mean absolute deviation equals .20. Finally, if the center

is all female (Xd = 1.0), the mean absolute deviatiOn equals zero.

181

21.1

I
TABLE VI.6

DIFFERENTIAL IMPACTS BY.CENTER CHAUCTERISTICS FOR NUS

mama THE LAST FULL QUARTER OF OBSERVATIONw

Variable Employment Earnings

Mean absolute deoiatiOn between Corpsmembers

and Center characteristicsw.

Length of Stay Program Completion

.6 Sex Race/ethnicity

Location

Mean absolute' deviation between Center

and uniform distribution of characteristics

tex

Race/ethnicity

Location

Percent of Corpseembors in centers

enrolled,in GED program

Percent of SorpsmeibligAn_centers

enrolled

/ In Occupat caul Training c Cluster-

,Sub professional

Clerical and sales

Service occupations

w 'Forestry, farming and gardening

Food service

Automotive and machinery repair

W.ac.-4'.1.1117oliance repair

Indua'rte, ,74,741Uction

a Trahcforcocl.4 . Health, occupations

Unassigned

(F-volug for All training variables)

-0.431

0.007

0.088

-0.595** *

-0.195

-0.225

.045

0.800

0.510*. 0.080

-0 1'5

-0 316

0 031

J %

-0.038

0.661

0.1E9 . 0.040

(.593)

-26.728

-33.652

14.618

-78.744*

-110.58**

15.081

38.632*

-349.67*

51.374

-65.577*

-151.02*

- 92.168. 0.212

.127.49 26.872

181.69

3I.111

207.64

(1.760)**

-11.839 

0.143

-2.091** *

-11.199****

3.474

0.724

-0.020

r

-16.976

3.864

-2.010

-0.934

-6.065

3.203* +I

-8.474

-0.044

2.995

19.308****

6.279

(1.918)***

-0.286

-0.144

0.047

-0.809 

-0.085,

-0.250 . -0.058

1.280 -0.0e7

0.005

0.316

0.762** 

-0.085

-2.866**

0.184

-1.899**

-0.458

0,939 "- (1.429)*

( Significantly different from zero at the 80% level of statistical confidence (90% for a one -tail test).

**Significantly different from zero at the 90% level of statistical confidence (95% for a one-tail test).

.***Significantly different from zero at the 95% levelwf statistical confidence (97.5% for a one-tail test).

* ** *Significantly different from zero at the 99% level of statistical confidence (99.5% for a one-tail test).

a/ - The fincabgs presented in this table are based oirmultiplw.regressions; therefore, the estimates for each subgroup are net of the independent influendes of all other subgroups in the table (i.e., ye control

for all of. the variables in the table .simultaneously). The estimates for all relevant subgroups would have

to be averaged in order to obtain the estimate for a particular set of Corpsmember and center characteristics.,

The F-statistics shown in parentheses at the bottom of each factor (pubset) ate for null hypotheses that all

of the regression coefficients underlying the results shown for each factor are simultaneously equal to sem

b/ n - The mean absolute deviation is formally defined as I E X." 4 - X , where n is' the number of cells,

n iol

X

ai is the actual value of X for the ith observation, and X

di is some designated level of X for that

observation.

S/The Construction Trades occupational cluster is the omitted category. The differential

impacts estimated for all other clusters are deviations Er= the impact for the Construction Trades

cluster.

182
Variable i.

TABLE VI.7

/ 'DIFFERENT IA& IMPACTS BY CENTEE-CHARACTERISTICS FOP FEMALES..b/

WITHOUT CHI WRDI DURING THE LAST FULL QUARTER OF OBSERVATION/

w

EMplOYUNIA 4;r-tangs Length of Stay Provam Completion

Percent of Corpshembera in centers

enrolled in GED program

Percent of Corpsmombersin canters

enrolled in Occupational Training

ClusterSu6 professional

Clerical and sales

Serviceroccupations

'Forestry, farming and gardening

Food service

Automotive and machinery repair

Electrical /appliance repair

Industrial production

Transportation

Health.. occupations

.Unassigned

(F -value for all training variables)

-Mean absolute deviation befwaan Corpsmembers

and Center characteristics -i

Sex

Race/itbnicity

Location

Mean absolute deviation between Center

and uniform distribution of characteristics

Sam

Race/ethnicity

Location

-0.015 . -0.093

-0.025

0

60.569

-340186

74.999

-0.609 -189.10*** -0.708

-113.31 7.418

0.165 33.150 -0.644

2 =84.807**

-224283****

4.045

'0.070

1.589

-2.175* =56.943****

C320 A -11.066*

°.:14 . 61.332 1.29Q

138.49 1.489

-0.495: -43.784 28.179***. 0.661 29.438 -3.022

2.171 183.93, . .29.913 0.183 -29.014 6.259

0.595 118.48 -24.195**

-0.268 21.770 -16,640 

1.528 209.80 -42.747** 

(1.394)* 4(1.612)** (2.732) 

7

-0.060

-0.014

0,014

,-1.093** 

0.945*

-0.718***

-0.387

. -0.263

0.609

1.894 

3.156** *

1:1:17

-2.213

0.555

2.548***

.-::

0.504

(3.312)****

*Significantly different from zero the 80% leverof statistical confidence (90% for a one -tail test).

**Significantly different from zero at the 90% level of statistical confidence (99% fora one-tail:test).

***Significantly different from zero at the 9S% level of statistical confident` (97.5% for a one -tail test).

****Significantly different from zero at the 99% level of statistical confidence (99.5% for a one -tail test).

I/The findings presented in this table are based on multipl4 regressions; therefore tis sstimates

for each subgroup are net of the independent influences of all other subgroups in tho table (i.e., we

coptrol for all of the variables, in the table simultaneously). The estimates for all telev 1. subgroups

would have to be averaged in order to obtain the estimate for.a particular set of Corpsmamb r and center

characteristics. 21104-statis*ics shown in parentheses at the beat= of each factor (subs ) are for . null hypotheses that all. of the regression coefficients underlying the result! ihown for sac factor a's

simultaneously equal to zero.

12/The mean absolute deviation is formally defined as 1 1 X.4 X , where n is the number of cells,

n ill

Xai is the actual value Cf,X for the ith obstrvation, and X is "sooddloignated level of X for that di

4[4 SiThe Construction Trades occupational clutter ii the omitted category. The di:ferential

Impacts estimated for all other clusters are deviations from the impact for the Construction Trades

cluster. .

observation.

1 183

2iG

<el
The variables indicating the similarity between the characteristics

of the center attended and a uniform distribution of those same characteristics

more consistently affect postprogram labor-force activities and the

length of stay in Job Corps. Sex deviation from a uniform distribution

affects all of the outcome measures for males, and earnings and program

4 completion for females. All of the effects are negative, which suggests

that as centers move toward a uniform sex distribution of 50 percent

males and 50 percent females, Corpsmember performance rises. Racial/ethnic'

deviations affect the subsequent earnings of males and program completion

of females, but in opposite directions. Location deviations also sometimes

appear to affect the program completion of females, but the pattern is

unclear. 4 The distribution of Corpsmembers across occupational training

clusters also tends to affect the various outcome measures. The estimated

effects presented in the tables are actuallyZdeviationsuIrOm Construction

.Trlides training. Few if,-any generalizations can be drawn from these

_ effects at this time besanie ofthesevere selectivity problems for

interpretation.

D. $UNKARY AND CONCLUSIONS

Differential impacts among Corpsmembers and centers have been

found along several important dimensions. The most basic differentials

are associatea-with sex,,family, responsibility, and program completion

categories. Relatively larger impacts for males are fopnd forreceipt.

Unemployment Idlcurince and probability of being -in military service,

.while relatively larger impacts for females without children are associated

with employment and- earnings, receipt of welfare, an education. The

,

184
estimated Job Corps impacts for females with children are generally much

smaller than for the other two groups.

A strong positive correlation exists between our estimates of

Job Corps'impacts and the amount of the Job Corps program completed.

Program completers consistently benefit the most from the program,

partitularly in terms of employment, earnings, and dependence on welfare.

Partial completers benefit less, and early dropouts little or not at all.

Furthermore, these differential effects by completion categories seem to

be at least partially attributable to the effect of staying in the program

longer and completing, which indicates the potential for additional benefits

to the program from increasing the length of stay and completions of Corps-,

members.

In an analysis of other differential impacts on employment and

earnings, as well as on length of stay in Job Corps and program completion,

we reconfirmed our earlier findings of differential outcomes associated

with race/ethnicity and previous educational attainment. With the Job Corps'

HIS data, we'were also able to evaluate the differential impacts of several

previously untested center-related variables. Completing a GED program is

-positively associated with the' beneficial impacts, and, most importantly,

the magnitude of this observed relationship is approximately tbe same as

that for receiving a regular high school diploma. The occupational training

received was also associated-with differential impacts. Finally, more

general center charActeristics also seem to be associated with differential

impaCts. Examples include deviations of the center population from a uniform

sexual composition and the Corpsmember distribution across occupational

training clusters. The former is particularly interesting because the

patterns of effects suggests that the attainment of the Job Corps' goal

. of sp percent female participation might increase program completions and

L subsequent employment and earnings.
VII. ANALYSIS OF PROGRAM EXPENDITURES

This chapter examines the expenditures Job Corps used to operate

the program during fiscal year 1977.1/ We first present an overview of

program expenditures, and then provide an assessment of the determinants

of these expenditures. In addition, we present cost estimates and other

information on program operating expenditures that; because they constitute

the program component most directly controlled by DOL ofacials, are especially important'for policy purposes.

It should be emphasized, however, that an analysis of program

operating expenditures presents only half the picture. Expenditures can be

changed by altering program operations (e.g., the mix of services or the

types of training provided), but such changes may lead to corresponding, changes

in outcomes. Thus, while there are conclusions to be drawn from this

_wipenditures analysii, overall evaluative assessments are better made in the

context of impact and benefit-cost estimates and should not be based solely on

the findings of this.chapter.

A. OVERVIEW OF JOB CORPS OPERATING EXPENDITURES

Most data needed for the analysis were obtained from the Job Corps

Financial Reporting System and pertain to fiscal year 1977. DOL defines

the accounts and procedures for the system, and requires that they be used

by all centers that file a Center Financial Report on a periodic basis:

This report summarizes all expenditures incurred by the centers, as well

1/TThis chapter summarizes a more complete analysis of expenditures his

presented in Technical Report J. For an analysis of those costs of Job

Corps that are not included in the Job Corps budget, see Technical Reports

F and K.

186

210
et, as the number of Corpsmembers served. Expenditures are reported on an

accrual basis so that expenditure and enrollment data are comparable.1/

The enrollment data used in this chapter to compute average or unit costs

are "Corpsmember years," computed from alierage participant levels for the

entire fiscal year.

Two other sources of data were also used. Data on central operating

costs were obtained from the U.S. Office of Management and Budget, and

coveeboth centrally budgeted program functions (such as recruitment. and

placement) and central administration by DOL. Data on the average length

of time that-participants stayed in Job Corps were obtained from the

national Job Corps office. The estimated average length of Corpqmember

participation (in years) is used to convert expenditures per Corpsmember

year to a per-participant basis.

1. Total Operating Expenditures

Total expenditures for fiscal year 177 are summarized in Table

VII.1. These expenditures fall into three categories: center budgeted

expenses, cash allowances toliorpsmembers, and central operating costs.

Center budgeted expenses include all costs of program functions

budgeted at the center level. As shown in Table-VII.1, this was by far the

largest budgeted category of program expenditures duringsfiscal year 1977.

A total of approximately $149 million, or 66 percent of the total program

operating cost, was spent at the centers. Of the total center budgeted

1/- There may be a problem in estimating depreciation, because center

facilities and equipment are retired at the center's acquisition cost, a

procedure that does not account for depreciation over the life of the

facilities. The effort introduced by this procedure is probably fairly

small for fiscal year 1977, since capital use in that year did not appear

to involve an unusual amount of acquisition or retirement.

187

220
TABLE VIII

TOTAL PROGRAM OPERATING EXPENDITURES FOR JOB CORPS

IN FISCAL YEAR 1977, BY CATEGORY

Category

Total Expenditure, '

Fiscal Year 1977

,Expenditures Pere

Corpsmember Year

Center Center Budgeted Expenses

Enrollee Expenses $32,500,335 $1,567

Staff Expenses, 79,034,227 4"44% 3,811

Center Operating Expenses 27,128,221 1,308

Work Project Expenses 5,165,278 249

Capital Expenditure 10,499,624 506

Income (5,569,349) Iiiii

Total $148,758,336 $7,730

1-+ Cash Al

Tota $`0,126,115 $970

Central Operating Costs

Federal Administration $19,200,000

Recruitment and Placement 13,200,000

Engineering Support 13,600,000

Enrollee Transportation 3,600,000

Union Training Contracts . 5,200,000

Other Miscellaneous 2 000 000

Total $56,800,000

Total Program Operating Expenditures $225,684,451

$926

637

656

174

251

96

$2,739

$10 88312/

.1.===1,

SOURCES: Job Corps Financial Reporting Systems and the U.S. office of Management and Budget.

a/

- Expenditures per Corpsmember year are calculated by dividing the overall expenditure figures by 20,738.2--the total Corpsmember years among all centers in fiscal year 1977.

b/

Detail may not sulk to total due to rounding.

2'" 222
expenses, staff expenses accounted"for over 50 percent of the cost, or

$3,811 per CorpsmeMber year. Enrollee expenses accounted for an additional.

22 percent-of the total, which amounted to $32,500,335, or $1,567 per

Corpsmember year. These enrollee expenses were generally for the

residential and support services provided to Corpsmembers. The remaining

categories include expenditures for center maintenance, work project

materials and supplies, and capital improvements. Center income is dsved

from providing food, lodging, and products to staff and visitors,-as well

as from canteen and theatre revenues; this income partially offsets the other

center expenditures.

Cash allowances paid to Corpsmembers both during the enrollment

period and at termination are separately budgeted and issued by the Army

Finance Center. After enrolling in the Job Corps program, Corpsmembers

,received a monthly living cash allowance of $30 to be used to cover

personal expenses. This allowance was, increased in $5 increments to a

maximum of $50 per month in six months. Corpsmembers also received an

alloWance at the time of their termination to help ease their transition

to the outside world. This allowance was $50 for each month of participation in Job Corps if the participant had remained in the program long

enough. (All of the allowances and their computation formulas have

recently been made more generous, but these increases occurred well after

fiscal year 1977.)

For fiscal year 1977, a total of $20,126,115 (approximately 9 percent

of overall program expenditures) was paid to Corpsmembers. Cash allowances

per Corpsmember year amounted to $970, or $477 per participant.

Central operating costs--expenditures for the federal administration

of Job Corps and for centrally provided program services--were estimated

by the U.S. Office of Management and Budget. The' major centrally budgeted

expenditure. are for recruitment and placement services provided by regional

189

223
DOL offices and private agencies, as well as for engineering support (for

work projects and center construction). The total. cost of central

operations was $56.8 million during fiscal year 1977, which was approximately

25 percent of total prograi expenditures. This amount represents $2,739

per Corpsmember year.

. 2. Average Operating Expenditures . The Job Corps operating costs reviewed above are best analyzed in

terms of the units of service supplied (suea as Corpsmember years). Aggregate

expenditures are largely a function of both program size (that is, number of

Corpsmember years) and the makeup of specific program service components.

Analyzing average costs (expenditures per Corpsmember year) will shed light

on what determines program operating costs other than the years of service

provided to Corpsmembers. It will then be possible to assess these other

factors in the context of program size.

Although 61 centers were operating during fiscal year 1977, only

54 were included in the sampling frame used for the benefit-cost evaluation

of Job Corps. In order to be consistent with that evaluation, our analysis

of average center operating costs will be limited to these 54 centers.-1/

This also eliminates certain analytical problems, since some of the omitted

centers were still in their start-up phase in 1977 or were providing substantially different training services than most Job Corps centers. The average

l'The The 54 centers comprise the bulk of the Job Corps program.

Approximately 96 percent of total Corpsmember years of service were

recorded at these centers, along with approximately 96 percent of the

center budgeted costs.

190 2')
center expenditure per Corpsmember year for the 54 centers was approximately

47,700 during fiscal year 1977.1/

Before turning our attention to the program features that determine

this average cost; it will be useful to consider the types of variation

in average cost. Variation in cost across the 54,cehters is substantial:

four centers recorded 4h avc.rage expenditure of under $6,500 in fiscal

year 1977, while six'centers had an average . xpenditure of over $9,000.

This variation is caused by differences in the type of services provided,

in the type of training, and in the size of centers, and can conveniently

be viewed by comparing the differences between CCCs and contract centers.

CCCs are generally smaller, are more rurally situated, are predominantly

all male and residential, tend to provide more training in construction,

and undertake more construction work projects than contract centers.

The larger, more urban contract centers are more likely to have co-educational

facilities and a nonresidential participation option than CCCs, and

provide more training in service skills such as health occupations,

clerical work, repairs, and food services. The average CCC package of

services involves center operating expenditures of $8,455 per Corpsmember

year. The average contract center package costs $1,130 per Corpsmember

year.

The distinction between CCCs and contract centers is useful but

masks the underlying` causes of average cost variation. As discussed in

the next section (and in Technical Report J), the packages of services

1"Central Central operating costs and the Corpsmember cash allowances are

not included in this analysis because appropriate data are not available.

Cash allowances are governed by uniform regulations and vary primarily

because of differences in length of stay. The central operating costs are

largely independent of cross-center differences.

191
offered by the two types of centers have evolved over time and could'

possibly be shifted if conditions warrant.

The two major causes of differences in average coseare center

size and the relative emphasis a center places on Corpsmember training

in the construction trades (see Technical Report J for more details), A

comparison of different-sized centers shows that average expenditures

per Corpsmember fall quickly as size increases (although such economies

of scale seem to taper off once the scale exceeds 600 Corpsmember years

of service per year). Center-costs also decrease as the percentage of

Corpsmembers who receive training in construction trades decreases.

Centers with over half of their training programs in construction recorded

costs per Corpsmember year that were over $1,200 higher than centers

with less than 25 percent of training in tile construction trades.

B. DETERMINANTS OF OPERATING EXPENDITURES

To determine how aspects of center operations influence costs,

jt is necessary to disaggregate costs along functional lines. These

fuhctional costs fall into four major expense groups: enrollee expenses,

center operations expenses, staff expenses, and work-project expenses.

The four types of expenses are shown in Table VII.2 and will be considered

separately below.

1. Enrollee Expenses

As shown in Table VII.2, average enrollee expenses are more than

$900 higher at CCCs than at contract centers, and CCC costs are higher.

for almost all enrollee expense categories. The differences appeat to

be caused by three main factors. First, average enrollee expenses are

inversely related to center size (significant at the 99% level), which

192

.2:3G
TABLE VII.2

CENTER OPERATING EXPENDITURES PER CORPSMEMBER YEAR

IN FISCAL YEAR 1977, BY CENTER TYPE

Type of Expense

Center Type

CCCs Contract Centers All Centers.

Enrollee Expenses

Residential $1,199 $943 $1,071

Educational/Vocational 964 302 662

Recreation 105 73 92

Transportation 8 4.5. 27

Total Enrollee Expenses $2,276 $1,368 $1,822

Operations Expenses

Maintenance $264 $158 $212

Utilities, Fuel, Supplies 628 632 630

Other 0 748 374

Total Operations Expenses $892 $1,538 $1,216

Staff Expenses

Management and Support Staff $1,396 $1,615 8,506

Educational/Vocational Staff 661 853 759

Other Staff 1,835 1,320 1,578

Other Staff-related Expenses 84 38 61

Total Staff Expenses $3,976 $3,826 $3,904

Work Project Expenses

Supplies and EquipmentOperating Expenses $903 $50 $477

Construction 465 380 423

Equipment 216 206 212

Total Work Project Expenses $1,584 $636 $1,111

Total Center Operating Expenses $8,728 $7,368 $8,053

SOURCE: Job Corps Financial Reporting System. The data on expenditures and

Corpsmember years used to compute these figures are from the 54 centers

in the evaluation sample.

4

193

22 7
suggests-that there are economies of scale in delivering residential and

educational/vocational services to enrollees.

Second, approximately half of the contract centers (but no CCCs)

had nonresidential programs for Corpsmembers during 1977. This accounts

forepart of the over $250 difference between CCCs and contract centers

for` residential expenses, as well as for part of the difference for

recreational expenses.

Third, there is a very substantial difference--almost $700 per

Corpsmember ye ,r4-in the amount of money that CCCs and contract centers

spend on vocationaq services and supplies. Moreover, vocational service

and supply costs vary markedly between centers within the CCC and

contract-center groups; this variation far exceeds that associated with

either residential or recreational expenses. The variation is closely

related to the industry mix of vocational training provided by centers.

In particular, the level of the expense is highly correlated with the

ratio of construction training to all training programs offered by a center.

2. Operations Expenses

Table VII.2 shows that center operations expenses per Corpsmember

year at contract centers were over $600 more than at CCCs. However,

this aggregate difference is quite misleading because of accounting

differences between CCCs and contract centers (see further below).

Average maintenance costs were over $100 higher at CCCs than at

contract centers during fiscal year 1977. This expense is inversely

related to center size (significant at the 95% level), again indicating

economies of scale in this aspect of program operations. Utility, fuel,

and supply expenses per Corpsmember year are very similar for CCCs and

194

293
contract centers, and vary relatively among centers within those

two groups. However, other operations expenses (for'legal and accounting

services, insurance, and center security) were dramatically different at

CCCs and contract centers: zero at the former, and almost $750 at the

latter. The reason for this discrepancvis that CCCs,.which are operated

by the federal government; do not include these services as direct costs

in their own budgets (they are an overhead expense in the central agency

budget). This substantial difference more than accounts for the aggregate

difference between the center operations expenses of the two types of

centers.%

3. Staff Expenses

Job Corps center staffs comprise management and support, educational

and vocational, and other center personnel ,assigned to safety and recreation,

guidance and counseling, medical and dental care, and the supervision of

work projects. Table VII.2 shows a breakdown of staff compensation and

related expenditures by staff category aad center type. Staff expenses

are greater than expenditures in the other three major expense categories.

Total staff compensation per Corpsmember year at CCCs exceeds

contract center compensation by approximately 4 percent. Total staff

cost is inversely related to center size (significant at the 99% level),

which suggests potential economies of scale. However, several categories

of staff compensation appear to be more closely related to factors .other

than center size. Most of these factors stem from institutional differences

among 'Job Corps centers. For example, contract centers recorded compensation

. costs for vocational and educational personnel that were almost $200 higher

per Corpsmember year than those of CCCs, due entirely to the contract

centers' practice of utilizing more vocational personnel and less work

195

22;9
project staff in providing training to Corpsmembers. The CCCs actually

spent more on educational staff: $567 compared to 449. The contract II, centers do not rely heavily on work projects (nor, thus, on work project

.staff) ,in the training proqess, The CCCs spent $446 per Corpsmember

year on work-project personnel, while contract centers spent only $37.

This also reflects industrial differences in the`types of training

offered by centers.

Similarly, Table VII.2 indicates that contract centers had higher

compensation costs for safety and recreatio staff. This reflects both

differences in center recreation and safety ograms and in the'Way

,,c.NAters pay for them. Notably, CCCs spent more per Corpsmember,year-W

contracted recreation services, which is part of the recreational cost ' reported in Table VII.2.

4. Work Project Expenses

Work projects are,,a central part of vocational skills. training

in the construction trades. The costs incurred by centers inthese

work projects fall into three categories: work - project supplies ana-,

equipment operation, center construction and rehabilitation, and capital

equipment expenses. As indicated in 17ble VII.2, all three expenses

are higher at CCCs than at contract centers, and the difference in

total work-project costs is almost $1,000 per Corpsmember year.

contract centers undertake few work projects that do not

. constitute capital improvements in center facilities. Thus, the

expenditures recorded by contract centers for work-project supplies and

equipment operation is very small--only $50 per Corpsmember year. Most

contract centers have no expenses of this type, while a few do have work

projects in the surrounding community. In coltrast, CCCs devote over

196

2

'1)
$900 per Corpsmember year for supplies and equipment operation in communityserving work projects. This difference accounts for most of the overall

CCC/contract-center disparity in work-project expenses. It reflects not

o) institutional differences between the two types of centers in the

use of work projects to provide on- the -job training, but also the greater

emphasis that CCCs place op training in the construction trades.

'Both contract centers and CCCs have construction projects designed

as center capital improvements, such as dormitory construction and facilities

rehabilitation: The difference between what the two types of centers spend

on these projects is less than $100. Irfaddition, the &Mounts spent by CCCs

4

and contract centers on capital equipment acquisitions (equipment used in

work projects and for other purposes) is very similar.

C. SUMMARY AND CONCLUSIONS

The determinants of Job Corps operating costs have been assessed

for each of the three major categories of costs: center operating

expenses, cash allowances, And central operating expenses.11 We concluded

that center operating expenses are date pained largely by center size, the

industrial mix of vocational training offered; and institutional factors

associated with center administration (i.e., CCCs versus contract centers).

The importance of other factors, such as the geographic location and

co-educational status of centers, is more difficult to identify. Cash

allowance expenses are primarily a function of the uniform allowance rules

and the average length of Corpsmember stay in. the program. Central

operating costs primarily reflect federally budgeted administrative

functions and contracts for recruitment and placement,. which, for the

1/- See Technical Report J for a more detailed discussion of the

latter two categories.

197

231
most part, are dlermined independently from center operations and from

support of contruction training and work projects.

Three observations should be made about these general findings.

First, the results of the analysis are hardly surprising. Job Corps

is an established social program. Consequently, what had been budgeted

for individual centers in fiscal year 1977, as well as for various

program components, had been worked out over a period of years. CCCs

have always been the rural, smaller centers providing more of the program's

training in the construction trades. Contract.centers have long been

the larger, urban, service-training centers. Moreover, major structural

changes in Job Corps have'not occurred since the late sixties)" and,

as noted at the outset of this report, the recent expansion of the program

began after fiscal year 1977. Therefore, as is clear in Table VII.3,

average center costs (in constant dollars) were relatively stable over

the 1970-77 period, as were the relative expenditures for both CCCs and

contract centers. This stability also applies to most of the categories

of operating costs discussed in previous vhapters.of this report.

Clearlk, the patterns in Job Corps expenditures that have emerged in this

analysis represent, to a great extent, budgetary formulas that were

developed over several years of program operations.

Second, this cost analysis has been limited by the realities of

Job Corps operations. The determinants of program operating costs

(center size, location, industrial types of training, use of work projects,

co-educational status, nonresidential enrollment, and so on) are interrelated, which makes ,it difficult to estimate the unique importance of

1'During the late sixties, responsibility for the program was

shifted from OSO to the Department of Labor, enrollment of women was

increased after a legislative mandate, and 59 centers were closed.

198

2 'Joow
TABLE VII.3

JOB CORPS OPERATING COSTS PER

CORPSHBMBER YEAR, FISCAL YEARS 1970.77

1970

Total Expenditures!'

(millions of dollars) $ 267

Corpsmember Years 20,840

1971 1972 1973 1974 1975 1976 1977

$ 264 $ 278 $ 242 $ 214 $ 191 $ 199 $ 231

22,394 23,808 23,126 21,287 20,707 21,119 21,615

Total Expenditure per

Corpsmember Year 12,800 11,800 11,670 10,480 10,040 9,200 9,430 10,687

Center Expenses and Cash

'1,1 Allowances per Corpsmember Year:

CCCI

Contract Centers

9,437 9,434

8,980 8,109

SOURCES: Job Corps in Brief (Fiscal Year 1977),

and the Job Corps Financial Reporting

a/

- This is the total applied funding for

dollars.

233

U.S. Department of Labor,

System.

loyment and Training Administration;

Job Corps adjusted by the GNP price deflator to reflect 1977

234
any one variable. Also, given the stability mentioned above, particularly

with respect to the fact that center size and expenditures vary little over

time, it is difficult to estimate the magnitude of shale economies and the

marginal costs of serving Corpsmembers. There is certainly, evidence that

large centers have lower average costs than small centers, but it is difficult

to isolate precisely the role of center size in determining costs based on

1977 data. Program expenditure data for fiscal years 1978-80 could provide a basis for analyzing the marginal costs of Job Corps.

Third, it should be emphasized that.any conclusions regarding Job Corps

operating costs shoul&ideally be interpreted in a broad program context. Job

Corps expenditures reflect most, but not all, resources used by the program;

other resources are paid for by other agency budgets and by some nongovernmental

organizations. In addition, many of the direct and indirect benefits of Job

Corps constitute "offsets" to other agency budgets. For example, reduced income

maintenance payments, welfare agency administrative costs, and criminal justice

system costs associated with participation Jo Job Corps--as well as output from

work projects and work-experience programs that benefits government agencies-- all could be viewed as offsets in estimating, a "net cost" of the program

to all government budgets.

Finally, program costs should not be viewed independently of the program

services that are provided and the benefits that result. This is especially

important insofar as cost comparisons are concerned. This applies to comparisons

between Job Corps centers that may not provide identical services, notably in

terms of industrial types of training or residential services supplied. It also

applies to comparisons of Job Corps costs to those of other employment and

training programs, many of which are not residential programs, pay wages instead

of small allowances, or differ in other important ways from Job Corps.

200 2
VIII. GENERALIZABILITY OF THE FINDINGS

One goal of this evaluation was to provide a general statement

about the overall effectiveness of JOb Corps as an employment and training

program for disadvantaged youths. The was to made on the

basis of differences found between a random sample of Corpsmembers and a

carefully selected comparison group. However, a number of questions

arise which could possibly inhibit our ability to generalize the findings

from the evaluation sample to the Job Corps populatAnn as it was in 1977

when the sample was drawn, as well as to potential Job Corps populations

of the future:

Is our sample of Corpsmembers similar to the Job Corps

population ,in 1977, to later Job Corps populations and

to more general populations of disadvantaged youths

that may be of interest (at least similar enough to

facilitate correct statistical inferences)?

Has the Job Corps program changed in any major substantive ways since 1977?

Has the social and economic background against which

the Job Corps evaluation sample was observed changed

in any ways that are likely to influence our

estimates of the effectiveness of Job Corps?

To what degree are our estimates biased by our

having used a comparison sample rather than

a "true" control group, or by other' peculiarities

of the analytical approach?

And, finally, what is the overall quality of the

data used in the evaluation?

Each of these questions will be discussed in turn in the remainder of this

chapter.

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23G
L. REPRESENTATIVENESS OF THE SAMPLE AND CHANGES IN THE CHARACTERISTICS OF

CORPSMEMBERS SINCE 1977,

In Table VIII.1 we compare the percentage distributions for several

demographic characteristics of our Job Corps evaluation sample to those

for the Job Corps populations of 1977 and 1979. We found that the

evaluation sample is, on average, similar to both populations, in terms

of sex, age, race/ethnicity, and educational background.

It is reasonable to question further whether future generations

of Corpsmembers will be affected by Job Corps participation in ways

bimilar to our evaluation sample--that is, can we expect future enrollees

to exhibit increased employability and earnings, and to derive the other

benefits that were found for the evaluation sample? Because our sample

showed no evidence of contradicting the underlying theory of the traditional economic models of behavior tested in our analysis, we have no reason to believe that the behavior of future Job Corps participants

will contradict this theory and thus be affected by the program differently than our evaluation sample. (Of course, it is unlikely that the

temicact estimates of Job Corps' ^ffectiveness would be replicated.)

Since 1977 the Job Corps program has begun to double in size- -

from 22,000 program slots to 44,000. This has been done by expanding

the program in high-poverty, Y IL-unemployment areas and particularly

by encouraging the enrollme, of women (especially those with children),

Hispanics and American Indiana, handicapped individuals, and other, targeted

groups. As shown in Table VIII.1, however, the overall demographic composition of Job Corps changed very little between fiscal years 1977 and 1979.

The education and training component of the program has been enhanced with

the expansion of Job Corps to include more positions in junior colleges

202

p
TABLE VIII.1

COMPARISONS OF EVALUATION SAMPLE TO JOB CORPS POPULATIONS IN 1977 AND 1979.

Evaluation

Sample,

1977-/

Job Corps

Population

1977

Job Corps

Population

1979

Sex

Percentage male 73 69 70

Percentage female 27 31 30

Age

Percentage under age 18 49 49 48

Average age in years 18 18 18

Race

Percentage white (nonSpanish-speaking,including

Asians and Pacific

Islanders 25 31 33

Percentage Black 58 54 53

Pertentage Spanish.;speaking 11 11 10

Percentage American Indian 6 4 4

Education

Percentage with fewer than

12 years 88 85 86

Average number of years 10 10 10 4111

a/ Reweighted by Job Corps completion categories to be representative of

all Job Corps enrollees.

203

232
and specialized preparation for military service for individuals who had

previously failed to met military admissions requirements. In addition,

greater ties have been sought between Job Corps and other employment

programs such as Cr'%. and WIN. It would be difficult to imagine any of

these changes having a negative effect on the ability of Job Corps to

improve employment opportunities for disadvantaged youths. In sum, the

essence of the Job Corps program has not changed since 1977.

As to the social and economic context against which the program

was set, the employment rate for youths in the regular sector (i.e.,

aside from special government programs) has not improved since the

sample period, may have gotten worse, and does not look promising for

the near future. Economic fluctuations no doubt affect Job Corps

impacts. However, to some extent, this is a separate issue and one over

which Job Corps exercises no control. Fiscal year 1977 was relatively

typical of the recent labor experiences for disadvantaged youths.

Furthermore, there are now many more alternative employment

programs for disadvantaged young people than there were in 1977.

However, our analysis has shown that Job Corp S had a larger impact on

earnings than other training programs available to our sample and

was an efficient social investment. (See Chapter VIII for a comparison

of Job Corps with other programs, and Chapter V for results ca° the benefitcost analysis.) We conclude that,, although the Job Corps proq4am has

continued to grow and change and the economy and general pli6lt of

disadvantaged youths may have worsened, our estimates of the 's

Jab Corps participation can be generalized at least in broad

to potential future generations of Corpsmembers aneMoy, in fact, be

somewhat understated for them due to program improvements.

dr

- 204
B. THE VALIDITY OF THE COMPARISON SAMPLE STRATEGY

Ina perfectly controlled experiment, individuals are randomly

assigned either to a group that receives a treatment or to a control

group that receives no treatment. This randomization ensures that

differences between die two groups measured after treatment can be

attributed only to the treatment and not to unobserved differences

between the groups. However, randomization was not possible for the

evaluation of an ongoing program in the Job Corps context. Therefore,

instead of having a true control group, we seleCted a comparison sail ie

that matched our participant sample as closely as possible.

Comparison-group iembers were selected with a two-stage process

in which fifteen areas of the country were chosen in the first stage

because they were similar to the areas from which Corpsmembers came,

but in'which Job Corps did not recruit extensively. One hundred youths

A at each site were then selected in the second stage from school dropout

and employment service lists, so that 70 percent were young, recent

dropouts, and 30 perCent were older dropouts who had been out of school

longer (the assigned selection probabilities ensured comparability in

terms of education levels, agerace/ethnicity,..etc.).

Regression analysis was used to control for differences between

the participant and comparison samples with respect to various demographic

and socioeconomic characteristics, such as age, sex, race/ethnicity,

education, prior health, prior drug use, criminal history, and prior

employment. Other econometric techniques were used to control for

unmeasured preprogram traits, such as motivation and innate employability. (See Chapter III for a more detailed discussion of the econometric methodology employed in the evaluation.)

205

240
Even though we were able to control for inherent differences

between participants and comparisons with respect to both measured and

unmeasured preprogram characteristics, we had to make a second departure

from the controlled experimental design. While participants were

receiving the Job Corps "treatment," comparison-group members were not

treatment-free--there were many other employment and training programs

potentially available to them. However, as mentioned earlier, we found

that participAtion in other training programs was low, and that Job Corps

had a significantly larger impact on earnings than other training programs

available to our sample. Therefore, we conclude that the comparison sample

provided an adequate standard against which the effectiveness of Job Corps

could be measured.

C. DATA QUALITY

When analysis data are pulled from survey interviews, data

quality is always a twofold question. First, are the results biased

by our inability to interview certain individuals either because they

could not be located or refused to be interviewed? Second, given that

we areable to interview an individual, how accurate are the responses we

record for him or her?

An investigation in..o the problems associated with nonresponse

to Job Corps evaluation interviews showed that overall response rates

were relatively high. On average, approximately 85 percent of the sample

responded to at least one follow-up interview and were thus available

for the analysis of postprogram behavior. Even though the response

rate for Corpsmembers was approximately 15 percentage points lower than

it was for comparisons, we did not find that nonresponse had biased estimates

of the impact of Job Corps on employment, earnings, or frequency of arrest.

206

2i
. (See Technical Report. L, "An Analysis of Nonresponse to Jab"Corps . .Evaluation Interviews," for the details o &this investigation.) If

anything, nonresponse'adjustMents tend to show slightly larger impacts

than we have presented.

It should also be noted that the second follow-up interview was

administered to some individuals in person and to some by telephone:

while all previous interviews were-administered in person. Due to budget

restrictions, part of the sample eligible for a second follow-up

interview was contacted by telephone only, while the, remainder were

subject to an in-person search if telephone contact could not be made..

le Previous studies which compared the quality of data from telephone

interviews with those from in-person interviews hive found that differences in the willingness of individuals to submit to each type of

, interview are minimal, and that the different interview modes do not

appear to affect data quality to any great. extent (see Groves, 1977;

Rogers, 1976; Colombotos, 1969).

Not surprisingly, we found that individuals who were eligible

for an in-person contact were, on average, approximately 9 percentage

points more likely to respond than those who were eligible for a

telephone contact only (see Technical Report L). However, as

mentioned above, noniespons\does not seem to hive biased estimates

of program impacts. Furthermore. item nonrespensewas very low

(almost nonexistent, except for some recall problems at baseline):

With the second follow-up interviews, for example, despite both the

large number of questions and the existence of several data items

serving only as interviewer checks, less than one data item per

interview on average was not complete.

242
. D. SUNARF AND CONCLUSIONS k

While the exact estigates and single numbers do not generalize

4: very well, we.sre relatively confident in the broid implications of our

findings for disadvintagedrymiths and for Job Corps in particular. The

evaluation has been largely successful in its narrow range of objectives

4 (including development.of innovative procedures for comparison-gioup

metholodogies). furthermore,.usefulidata have been provided for additional

research on the difficult employment problems faced by disadvantaged youths.

g.

208

4
IX. SUMMARY AND CONCLUSIONS

This second follow -up report has presented the main findings from

a study designed to provide the Departient of Labor with comprehensive

evaluations of both the short-tem economic impact of the Job Corps program

for participants and the benefits and costs of the program.- The information provided herein is based on the most comprehensive data'yet available

to conduct a study of Corpsmembers. Comprehensive interviews were f:.st

conducted in the spring of 1977 with a sample of Corpsmembers who were then

participating in the program and with a comparable group of disadvantaged

youths who had not attempted to enroll in Job Corps. At periods 9 and 24

months after the baseline survey, reinterviews were conducted with all

of the youths in the comparison group and with Corpsmembers who had been

out of the program for a long enough time to provide useful postprogram

information.

The baseline survey obtained detailed information on the demographic characteristics of the youths, their social-economic backgrounds,

and their work histories and related activities beginning six months before

the Corpsmembers enrolled in the program and continuing up to the date

of the interview, which represented approximately six months of program

experience. The two follow-up surveys continued to collect detailed

information on work histories and related activities during the post -

program period when Corpsmembers had been out of the program from one to

1/Also available from this evaluation are f94rteen other reports

that document specific topics in more detail (for more details, see the

Centents.page and Chapter I).

209

2.14

7,
two years, with an average of slightly over 18 months. Altogether, the

data base for this evaluation,has both baselire and follow-up data on

approximately 5,100 youths.

The findings on Corpsmembers' postprogram behavior are generally

consistent with the hypothesized economic impacts and the important pro-

- gram goal of improving participants' economic prospects. During the first

two post' -ogram years we find that Job Corps is at least moderately

successful overall in achieving its desired effect of (1) increasing

employment and earnings, (2) improving future labor-market opportunities,

work experience, education, training, health, geographic mobility, and

military service, (3) reducing dependence on welfare assistance and othet

public transfers, and (4) reducing criminality.

Some of the most noteworthy findings of Job Corps effect3 on the

behavior of former partiCipants during their second postprogram year can

be summarized as follows (on a per Corpsmember basis): (1) an increase in

employment of over. 4 weeks pei year, (2) an increase in earnings of

approximately $500 per year, (3) a 4 percentage -point increase in military

service; up from 5. percent to 9 percent, (4) an increase in the probability

of having a high school diploma or equivalent degree, frOm 11 percent to.36

\ percent, (5). higher college attendance, equivalent to an increase of nearly

5 full=timi college students for every 100 youths enrolled.in Job Corps;

- (6) a 'reduction in the receipt of financial welfare assistance, amounting to

nearly 3 weeks per year, and (7) a reduction in the receipt of Unemployment

Insurance of over one week per year.

The positive, overall impacts geneially persist through the second

year of postprogram observation. The trend over the two-year postprogram

Observation period appears to be an increase in program benefits during

210
the first few months (especially for employability during the transition

from center life to re-entering the regular labor market), and then

relatively stable effects through the rest of the two-year period.

The one exception is for criminality, which shows relatively large

reductions in the very early postprogram period that fade out rapidly

after Corprmeabers are out of the program for a year. For employment

aid earnings vc find very stable estimates of gains among civilians,

especially program completers, for months 6 to 20 in the postprogram

period but, in fact, substantial growth in program effects on employment

and earnings whet the increasing military gains are incorporated.

Differential impacts among Corpsmembers are found to be associated

with sex, family responsibility; and program-comp7etion categories. Relatively larger impacts for males are found-fOr the receipt of Unemployment

Insurance and for the probability of being in military service, while

relatively larger impacts for females without children are found for

civilian'employment and earnings, the receipt of welfare, and education.

The estimated -Job Corps impacts for females with children are generally

much smaller than for either males or females without children. A substantial, positiVe correlation is found between the estimated Job Corps

impacts and the pr.Jportion of the Job Corps program completed. Program

completers consistently benefit the most,' particularly in terms of

employment, earnings, and dependence on welfare. Partial completers

are found to benefit less, and early dropouts are found to benefit

little or not at all. Furthermore, these differential impacts by

completion category seem to be at least partially attributable to the

effect of staying in the program longer and completing the program,

which indicates the potential for additional benefits to the program

from increasing the length of stay and completions of Corpsmembers.

211

246
We find additional'differential impacts associated with program

and center-related variables, although the causality of these differences

cannot be attributed with any degree of accuracy. Completing a ORD program

is positively associated with the beneficial impacts, and, most importantly,

the magnitude of this observed relationship is approximately the same as

that for receiving a regular high school diploma. Differential impacts

4

are also found to be associated with the industrial type of vocational

training received end the characteristics of the centers that Corpsmembers

attended (such as the sexual composition, which suggests that a more equal

sexual composition-would increase program completions and subsequent

employment and earnings).

In an exploratory analysis we find significant Job Corps effects

in terms of reducing extramarital children and delaying family formation

for females.. Furthermore, our estimates of overall Job Corps impacts are

probably bilsed downward by not incorporating either the. Job Corps effects

on family composition or the employment and related effects for females

with children.

The findings from a comprehensive evaluation of the social benefits

and costs of Job'Corps suggest that public investment in Job Corps is

economically efficient. Our benchmark estimate is that the value of

benefits in fiscal year 1977 exceeded costs by almost 82,000 per Corpsmember, or by approximately 39 percent of costs. Furthermore, the

program is found to be economically efficient under a wide range of

alternative assumptions and estimates. Because over 40,000 youths

enrolled in Job Corps during fiscal year 1977, our benchmark estimate

of the net social benefit for the entire program is approximately $80

million for that year.

212

2.4
We estimate that over 60 percent of the social benefits come from

increases in the value of output that Corpsmembers produced. Another 30

percent of the social benefits are attributable to reductions in criminal

activity among Corpsmembers, particularly burglary and larceny.

In assessing the distribution of benefits and costs we find a net

transfer from non-Corpsmembers as a group (everyone in society other than

Corpsmembers) to Corpsmembers. The main economic benefits to Corpsmembers

are derived from increased earnings (approximately 70 percent of the

benefits) and transfers received while they are in Job Corps. The main

economic benefits to non-Corpsmembers are derived from reductions in

Corpsmembers' criminal activities and in their use of transfer programs.

Sensitivity tests were undertaken for a wide variety of the

assumptions and estimates that are used in the benefit-dost analysis, and

'these sensitivity tests generally confirm that Job Corps is an economically

efficient program. With respect to the critical parameter of future

growth or fadeout of effects, we find that Job Corps is an economically

efficient use of resources as long as the earnings effects do not decay

more rapidly than 37 percent per year after our observation period.

We find that center operating expenses per Corpimember'are

determinid largely by center size, the industrial mix of vocational

training offered, and institutional factors associated with center

administration (i.e., CCCs versus contract centers). Other factors

such as the geographic location and coeducational status-of centers

appear to be somewhat important but are more difficult to isolate. The

largelt differences in operating expenses are associated with scale

economies of larger center size up to approximately 600 Corpsmember

positions at a. center.

213

2.48

ti
While the estimates are not exact and single numbers do not

generalize very well, after a careful analysis we are relatively confident

about the broad implications of our findings for disadvantaged youths in

general and for Job Corps in particular. The most tentative finding

concerns whether the effects observed in the second postprogram period will

fade out, grow, or remain stable in the future. Only further postprogram

observation can adequately answer that issue.

In the report we presented detailed discussions of all of the

findings summarized above. In addition, useful data are available from

this evaluation for further research both on the effects of Job Corps

and on the difficult problems faced by disadvantaged youths in general.

214
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