ED 203 059

AUTHOR

TITLE

INSTITUTION

SPONS AGENCY

PUB DATE

NOTE

AVAILABLE FROM

DOCUMENT RESUME

CE 029 109

Kim, Choonaso: Fnd Others

The All-Volunteer Force: A 1979 Profile and Some

Issues. Research on Youth Employment and

Employability Development. Youth Knowledge

Development Report 2.8.

Ohio State Univ., Columbus. Center for Human Resource

Research.

Employment and Training Administration (DOL).

Washington, D.C. Office of Youth Programs.

May 80

169p.: For related documents see CE 029 106.

Superintendent of Documents, U.S. Government Printing

Office, Washington DC 20402 (Stock No.

029-014-00131-7, S6.001.

EnRS PRICE MF01/PC07 Plus Postage.

DESCRIPTORS Adolescents: Armed Forces: Demonstration Programs:

Disadvantaged Youth: Economically Disadvantaged:

Education Work Relationship: Employment Practices:

Evaluation Methods: Federal Programs: Military

Personnel: *Military Service: Military Training:

*National Surveys: Outcomes of Education: *Program

Effectiveness: Public Policy: Research Design:

Research Methodology: Research Utilization: Youth:

*Youth Employment

IDENTIFIERS *All Volunteer Armed Forces: *Youth Employment and

Demonstration Protects Act

ABSTRACT

This report is one of the products of the knowledge

development effort implemented under the mandate of the Youth

Employment and Demonstration Projects Act of 1977. The report

describes the methodology and preliminary findings of the National

Longitudinal Survey (NLS) of youth, which seeks the effects of

military service on the education and employability of youths. The

NLS is a continued survey of 12,693 youth age 14-21 as of July 1,

1979. Of these, 1,281 are persons in the military. This preliminary

study of the first interview in February-May, 1979, reports the

following findings: (1) employment opportunities offered by the Armed

Forces are dramatically affected by public policy decisions: (2) the

limped Forces are more egalitarian than the private sector as a labor

market, perhaps too much so in the sense that almost all entrants are

paid the same and the wage structure is too compressed to attract or

retain enough highly skilled workers: (3) as a result of public

policy, the Armed Forces are less egalitarian in hiring women and

blacks than the private sector: (4) those who went into the service

would be better off there, while those the service wants are less

well ,-,ff in the service than they would be in the private sector: (51

high turnover is the res It of these practices, so the armed forces

must invest heavily in t ining: and (61 the evidence is not yet in

to determine the impacts of the Armed Forces on individual

development. (KC)
YOUTH KNOWLED

REP

RESEARCH ON YO

D EMPLOYABIL

The All-Volunteer Force: A

May

- Socioeconomic Background: Armed Forc
A_

1

a

II

-

r

In

1

'/S DEPARTMENT OF HEALTH

EDUCATION & WELFARE NATIONAL INSTITUTE OF

EDUCATION

THIS DOCUMENT HAS BEEN REPRO- DUCED EXACTLY AS RECEIVED FROM

THE PERSON OR ORGANIZATION ORIGIN

ATING IT POINTS OF VIEW OR OPINIONS STATED 00 NOT NECESSARILY REPRE- SENT OFFICIAL NATIONAL INSTITUTE OF

EDUCATION POSITION OR POLICY

personnel are very similar to
U.S. Department of Labor

Ray Marshall, Secretary

Employment and Training Administration

Ernest G. Green, Assistant Secretary for

Employment and Training Administration

Office of Youth Programs

Material contained in t pis 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 2.8

THE ALL VOLUNTEER FORCE:A 1979

PROFILE AND SOME ISSUES

Choongso Kim

Gilbert Nestel

Robert Phillips

Michael E. Borus

Center for Huma- .:source Research

The Ohic -te University

April 1980

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

Washington, D.C. 20402

4
OVERVIEW

The Armed Forces are the largest single employer of youth with a major residual impact on the civilian labor market.

The military has traditionally operated as a human

resource development mechanism, conscripting or

hiring relatively unskilled recruits, training and educating these for specific functions, promoting from within but

retaining most recruits for only a limited period. In this regard, the military has functioned as a developmental option

to the education and employment and training systems. Finally, the military is an employer which must compete in

the labor market to meet its entry manpower needs and to retain skilled workers even when there is initial conscription of recruits.

Too frequently, the Armed Forces are ignored in discussions

of youth employment problems and solutions, while military

manpower decisions are sometimes made for strategic reasons

without regard for the civilian spillovers. The National

Longitudinal Survey (NLS) of youth provides an opportunity to

bridge the gap and to assess the residual impacts of the Armed

Forces on youth labor market problems, the effectiveness of the

Armed Forces in human resource development, and the factors

determining the success of the military in meeting its needs

as an employer. The NLS is a longitudinal survey of 12,693 youth

age 14-21 as of July 1, 1979. Of these 1,281 are persons in

the military, including a sample of overseas personnel. All

youth in the sample are asked the same basic questions with

the military personnel receiving supplementary queries.

This is a preliminary report on the first interviews in

February - May 1979. The analysis is straightforward and

of course, no longitudinal experience has yet been tracked.

Nevertheless there are some important findings:

First, despite the fact that the Armed Forces are a "volunteer"

force, presumably competing in the labor market and paying

competitive wages and salaries, it is very clear that the

employment opportunities offered by the services are

dramatically affected by public policy decisions.

Second, the Armed Forces, as an internal labo_ market, are

more egalitarian than the civilian sector. As a generalization, minorities and females have a better relative chance

in the military than outside as judged by preferences for

enlistment and the patterns of retention of these withim

the services. Military pay, established by public policy,

is also "egalitarian," perhaps too much so in the sense that

almost all entrants are paid the same and the wage and salary

structure is too compressed to attract or retain enough

highly skilled workers.

J
Third, the Armed Forces are less egalitarian in hiring

than the civilian sector, again as a result of public

policy decisions. There is public concern about the racial

composition of the military. If market forces were allowed

to prevail, there is no doubt that the percentage of Blacks

in the military would increase. The Black share is reduced

by "rationing" so that relatively more qualified Blacks are

hired. A large employer like the automobile industry responds

by rapidly changing composition of its labor force in

response to supply and demand. Likewise, a private sector

employer such as the automobile industry would not be permitted to hire a large portion of White applicants but a substantially lesser portion of Black applicants with the same

qualifications. In the military, this has been accepted

because, in the end, it is the unspoken public policy.

Similarly, opportunities within the military are arbitraribly

restricted so that women have to meet higher standards to

enter than do men. Again, there is a rationing of

opportunity.

Fourth, the egalitarian internal labor market puts more

pressure on the rationing mechanisms since the same groups

that are excluded tend to be relatively better off if they

can get into the Services. Likewise, those who are "desired"

by public policy are least well off in the Services relative

to the civilian sector.

Fifth, high turnover is the result, so that the Armed

Forces must invest heavily in training a constant influx

of recruits. Since the more able within the ervices and

outside are most likely to be attracted and retained by education and training opportunities, these should probably be

stressed to a greater extent by the military since abilityrelated earnings differentials adequate to meet manpower

needs are denied by public policy.

Finally, the evidence is not yet in to determine the impacts

of the Armed Forces on individual development. Initial

evidence is that even for short-term enlistees, the military

experience is positive or at least not negative.

These interpretations are, of course, both tentative and

judgemental. The knowledge development payoff of the NLS

will come when subsequent surveys provide longitudinal

information to resolve the many questions raised by the

initial findings.

6

ii
This volume is one of the products of the "knowledge development" effort implemented under the mandate of the Youth Employment and Demonstration Projects Act of 1977. The National

Longitudinal Survey is primarily funded under the Youth

Employment and Demonstration Projects Act although the military

components of the survey were funded by the Department of Defense.

The observations in this overview are those of the Office of

Youth Programs, while the conclusions in the test represent

the views of the Center for Human Resource Research at Ohio

State University. A range of more sophisticated analyses are

intended by the Center and the Department of Defense.

The knowledge development effort consists of hundreds of

separate research, evaluation and demonstration activities

which will result in literally thousands of written products.

The activities have been structured from the outset so that

each 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 Youth

Initiatives Fiscal 1979 and Completing the Youth Agenda: A

Plan for Knowledge Development, Dissemination and Application

for Fiscal 1980.

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 array of products, which, in turn,

depends on knowledge and availability of these products. A major shortcoming of past research, evaluation and demonstration activities has been the failure to organiie 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 ai.alysis 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 aevelopment efforts. Some of the same products

may also 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:

iii
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

sources, special studies of dimensions of youth labor market

problems, and policy issue 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 arsd Training Programs, Youth Commrnity Conservation and

Improvement Projects and the Targeted Jobs Tax Credit.

4. 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 incudes 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 Services: 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, jobsearch 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.

iv
8. Implementation Issues: This category includes crosscutting analyses of the 15ig3acal __ssons concerning "howto-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 Oraanizational Alternatives: The products in this category represent assessments of demonstrations of

alternative program and delivery arrangements such as consolidation, year-round preparation for summer programs, the

use of incentives and multi-year tracking of individuals.

10. 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 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 agencies and the like.

In each of these knowledge development categories, there

will be a range of discrete demonstratior, research and

evaluation activities focused on different policy, program

and analytical issues. In turn, each discrete 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

evaluation 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 an identifier of the product

v
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 activities in each broad cluster have significant

interconnections.

This volume should be assessed in conjunction with Findings

of the National Longitudinal Survey of Young Americans in the

"research on youth employment and employability development"

category. There are also several papers on the impact of

the military on the youth labor market in Youth Unemployment - It Measurement and Meaning, also in this category.

ROBERT TAGGART

Administrator

Office of Youth Programs

10

vi
PREFACE

The following monograph presents preliminary cross-tabular analyses

of the 1979 National Longitudinal Survey of Youth Labor Market Experience.

These analyses represent only a "first cut" at the data. They should not

be considered definitive in any way: further refinements of the data,

reweighting, and more sophisticated multivariate analyses may yield other

results. Due, however, to the need of the Department of Defense and the

services for early indications of where the 1979 NLS Youth Survey may

lead, we present below a series of descriptive chapters.

This is the first report on a cohort of youth ages 14-21 on January 1,

1979. The cohort will be interviewed annually fur the next five years;

subsequent reports will refine the analyses presented here and trace the

experiences of the youth over the period. The purpose of these surveys

is to better understand the factors affecting success in the labor market

and in life generally.

This cohort of youth is part of the National Longitudinal Surveys of

Labor Force Experience (NLS), which were begun in 1966. Funding for the NLS

comes from the Office of Research and Development and Office of Youth Programs,

Employment and Trai ing ;dinistration, U. S. Department of Labor and the

Office of the Secret .4 of Defense and the three armed services.

Overall responsibility for the NLS rests with the Center for Human

Resource Research, The Ohio State University who design the questionnaires,

analyse the data and provide it to the public. Sample design and

data collection for the youth cohort were conducted by the National Opinion

Research Center (NORC). The Survey Director at NORC for this project is

Celia Humans; sampling design was the responsibility of Martin Frankel.
Other NORC senior staff who made sutstantial contribuvions were Mary

Catherine Burich, Wendi Kreitman, and Karin Steinbrenner.

All of the authors were involved in writing this report. Primary

responsibility by chapter was divided as follows: Chapter 1 - Borus, Kim,

and Nestel; Chapter 2 - Kim and Nestel; Chapter 3 - Phillips; Chapter 4 - Kim and Nestel; Chapter 5 - Borus, Kim and Nestel; and Chapter 6 - Nestel, and Phillips.

Many of the individuals at the Center for Human Resource Research

have been engaged in this study in addition to the authors 3f this report.

While it is not possible to acknowledge all of them, we would particularly

like to thank Susan Carpenter, Joan Crowley, Stephanie Campbell, Dean

Croushore, Dennis Grey, John Jackson, Herbert Parnes, and David Shapiro.

viii

12
Table of Contents

Page

Executive Summary

CHAPTER 1 Introductiwi 1 CHAPTER 2 Partici:. ts in the All Volunteer Force and Their

Quality 6

Appendix A 23

CHAPTER 3 Quality of Employment and Job Satisfaction of Youth

in the Armed Forces 52

Appendix B 76

CHAPTER 4 Intention to Reenlist 80

CHAPTER 5 Post-Service Status of Persons Who Have Left the

Armed Forces 88

CHAPTER 6 Intentions to Serve 93

Appendix C 1.16

CHAPTER 7 Sample Design and Weighting 122

ix

13
EXECUTIVE SUMMARY

A summary of key issues addressed in the report is presented by topic

area. PARTICIPATION RATES (Chapter 2)

Of the 8,239,000 18-21 year old males in the United States, 6.7 percent

were serving in the Armed Forces. Approximately 0.6 percent of the 8,285,000

18-21 year old females were serving. The analysis of participation rates

by group shows:

- The proportion of married men who serve in the Armed Forces is almost

twice that of men who have never married.

- The black youth participation rate is about 1.5 times that of whites

and comes disproportionately from blacks with relatively higher socioeconomic status and with better employment qualifications.

- For whites, high school graduates and high school dropouts participate

at about the same rate. However, the participation rate for black male

high school graduates is five times higher than for black dropouts and

twice the percentage of Hispanic high school graduates participate in the

Armed Forces compared to Hispanic dropouts.

EFFICACY OF THE LABOR MARKET MECHANISM (Chapter 2)

The relative quality of youth in the volunteer force compared to the

labor market was examined. The issue was whether or not the reliance upon

the labor market mechanism for sorting the nation's youth between the

military and private sector resulted in a reasonably representative Armed

Forces, or were those enlisting for service mostly from poor families and

less capable of competing in the private sector?
To the efficacy question, youth (aged 18 through 21) serving

in the Ac,ed i=orces were compared to non-veteran youth employed full time

in the prkate sector. Eight dimensions formed the basis of the comparison.

- Education: The Armed Forces males are on a par with the full time

employed and compare favorably to the total 18-21 year old population

average in the proportion who are high school graduates. Armed Forces

females compare favorably to both groups. However, the proportion who

have some college training is lower for military youth than the full time

employed.

- Educational Experiences: More than twice the percentage in the Armed

Forces have expectations to be college graduates (both male and female)

compared to the full time employed.

- Knowledge of the World of Work (KOWW): The KOWW scale was used as a

proxy for mental ability. The test asks respondents about what is involved

in different jobs, ranging from fork lift operator to an economist. Armed

Forces males and females are about the same and compare favorably to their

respective counterparts in the labor market and in the population as a whole.

- Rotter Score: The Rotter scale was used to measure a respondent's feeling

toward being able to affect his or her destiny. It was hypothesized that if

those with few alternatives were enlisting, then the mean for Armed Forces

would be higher. This was not the case. Armed forces males and

females were essentially the same as the full time employed.

- Marital Status: Both sexes in the Armed Forces are married at about

the same rate as the full time employed. The rate is considerably higher

than the 18-21 year old population average.

xi
- Socioeconomic Background: Armed Forces personnel are very similar to

the full time employed and the overall population on two measures used to

proxy for socio-economic background: parents' education and fathers'

occupation.

- Minority Distribution: The Armed Forc, had more than proportionate

participation by minorities, both males and females. The Armed Forces

minorities were better educated and had higher mental ability than their

full time employed minority counterparts.

- Health: There were no significant differences between the Armed Forces

and the labor market on the proportion of respondents who reported that

health problems were affecting work performance.

Thus, it is clear that the Armed Forces, as an aggregate, is receiving

its share of the capable youth of the Nation.

QUALITY OF EMPLOYMENT AND JOB SATISFACTION (Chapter 3)

An analysis of eighteen measures of different job aspects indicate the

following:

- Military youth perceive greater job disamenities, less motivating job

aspects, and fewer job rewards than their counterparts employed full time

in the civilian sector.

- The three items with the greatest difference between the Armed Forces

and the civilians were the same for males and females--pay, job comfort,

and job challenge. Armed Forces youth saw greater job security than those

in the labor market.

- Armed Forces females generally see more favorable job aspects and have

greater job satisfaction than Armed Forces males.

xii

IC
- The ground combat arms (p y Marine Corps) are generally lower on

measures of job quality than the bchnical services (Navy and Air Force).

- The differences in job quality and level of disamenities between the

Armed Forces and the civilian labor market, as well as differences among

the services themselves, most likely affect attrition, retention, and in

part, account for differing recruiting success among the services.

- The item with the greatest difference between the Armed Forces and the

full time employed civilian males was satisfaction with pay. (It was the

item with the second greatest difference for females.)

- The 'average monthly. pay (Regular Military Compensation) of Armed Forces

males is as much as 12 percent less than the average monthly pay of the

full time employmed males who work the entire year. For male high school

graduates, the Armed Forces` average pay is up to 18 percent less.

- High School graduate, Armed Forces females earn an average of about 16

percent more pay than their civilian counterparts. Nevertheless, military females were still less satisfied with pay thah females in the civilian labor market.

- Perceived pay by Armed Forces personnel is most likely les, than the pay

calculated by use of the Regular Military Compensation formula. In particular,

the value of what the Government imputes to individuals who live in barracks

may not equal the value the individual assigns to such accommodations with

their attendent disamenities. If so, then pay perceptions may well be a

major contribution to relative pay dissatisfaction for military personnel.

THE CORRELATES OF THE INTENTION TO REENLIST FOR FIRST TERM PERSONNEL

(Chapter 4)

- About 25 percent of males and 38 percent of females in the sample

expressed positive reenlistment intentions.
- Surprisingly, reenlistment intention rates are negatively correlated

with length of service. The longer one serves (within the first term of

service) the less likely the expression of positive reenlistment intentions.

- Marital status had a differential effect on reenlistment intention,

by sex. Married males were more likely to expres7, such intentions and

married females, less likely.

- Military personnel from families with lower socioeconomic status had

a higher reenlistment intention rate.

- Length of formal or school training did not play an important role

in reenlistment intention:. The trained service personnel, while more

valuable to the services, also may be better able to find civilian employment

due to their training.

POST SERVICE STATUS OF PERSONS WHO LEFT THE ARMED FORCES (Chapter 5)

The youth of the sample at the time of the first interview meant there

were few in the sample who had separated from the services. The only

analysis possible was a comparison of men leaving before the completion

of their contract and persons who never served. The conclusions are

highly tentative.

- There were no substantial differences in employment to populatior ratios

between those who have served in the Armed Forces and those who had not.

- Employment conditions for the veterans were similar in pay and job

satisfaction. Veterans were more likely to be in service jobs and less

likely to be in professional and managerial jobs.

- Those who attrite from the Armed Forces are much less likely than nonveterans to bcelenrolled in college.

INTENTIONS TO SERVE (Chapter 6)

The interview schedule provided for two items relating to military

service. First, the respondent was asked about whether or not service in

the military would be a good thing for a young person. Second, the respondent

xiv

18
was asked about his/her future plans--whether (Jr not he or she would

definitely enlist, probably enlist or probably or definitely not enlist.

The second question focused on the respondent's expected behavior as opposed

to a generalized feeling about service.

- Approximately three-fourths of all young people (aged 14 through 21)

believed service in .the armed forces is a good thing. There was little

variation by race; however, proportions with positive attitudes generally

increased with age, and females were slightly more positive than males.

Those who expressed positive enlistment intentions are distributed as

follows:

Males Females

Number Percent Number Percent

Age 18-21 1,200,000 16 590,000 7

Age 14-17 2,710,000 35 1,010,000 13

High School Seniors 330,000 21 150,000 10

- The intention to enlist was higher among minorities, youth with lower

socioeconomic backgrounds, youth who do not expect to go to college, the

unemployed, married youth, and youth who have not attended college.

REASONS FOR NOT SERVING (Chapter 6)

Respondents 18-21 who had talked to a recruiter and did not enlist

supplied a reason for nonenlistment.

- The reasons cited most often were to go to school, to do something else

and because the youth thought that he or she would dislike the military.

- When the nonenlistees' activities at the time of the survey were examined,

almost 40 percent were enrolled in school and about two-thirds were

employed.

xv
- The frequent listing of school attendance as a reason for not joining

and the high enrollment rates suggest that increl:n educational incentives

may be more effective means of increasing enlistments than direct pay

increases.

THE ROLE OF SIGNIFICANT OTHERS ON THE ENLISTMENT DECISION (Chapter 6)

Respondents aged 14-17 were asked who influenced them the most on major

life decisions.

- Parents were named by 70 percent of the respondents, peers by 12 percent,

and all other possibilities by a few percent each. The 14-17 year olds

were then asked how their important other would view seven hypothetical

decisions, among which were "join the Armed Forces" and "not go to college."

- Parents were seen to be mildly in favir of sons joining the armed forces,

and mildly opposed for daughters. Of the seven item array, parents were most negative on "not go to college."

- As in the data on reasons for not joining, the significant other data

suggest that educational incentives may be very important in eliciting parental

support for a decision to join the Armed Forces.

20

xvi
CHAPTER 1

INTRODUCTION

Ever since the termination of the draft in 1972, discussions about

the success of the All-Volunteer Force (AVF) have revolved around the

quality and number.of enlistees and the racial composition of the armed

forces. In recent years, the high separation rates of first-term

enlistees also have evoked concern. These problems are interrelated.

More stringent recruitment policies and additional occupational training will improve the quality of those who serve and lower attrition

rates, since separation rates of higher-quality enlistees are known

to be lower than the rates for lower-quality personnel. At the same

time, however, the number of persons in the age groups from which

recruits are drawn is declining, thus requiring a lowering of

standards and/or an increase in the proportion of youth who apply to

the services, if the size of the Armed Forces is to be maintained.

The latter alternative is obviously preferable but must occur within

budget constraints. It is obvious that while the difficulties are

substantial, a successful resolution of the recruitment, racial

composition, and retention problems is a necessary condition for sustaining the AVF system.

In this report we investigate some of these issues as well as

others using the 1979 data of the National Longitudinal Surveys.

Chapter 2 provides the basic overview for subsequent discussions. In

this chapter we distribute the total population of youth 18 to 21

years of age by their survey week activity and study the extent to

which the characteristics of those serving in the armed forces differ

from those in the civilian sector. The intent here is to document
the participation rates of youth in the military and to quantify the

degree to which specific demographic and socioeconomic groups are

represented in the Armed Forces.

In Chapter 2 we also compare the characteristics of the youth who

serve with those who are employed full time in the civilian sector.

Our purpose is to determine whether the Armed Forces are drawing

youth who are above or below the average for the noncollege bound.

We control for the race and sex of the respondent in this chapter as

well as in all other chapters where sufficient sample sizes permit.

Chapter 3 focuses on the perceptions of the quality of employment and job satisfaction of members of the Armed Forces and those in

the civilian labor market working full time. A discussion of the large

differential in pay satisfaction between these two groups is related

to actual and perceived pay of servicemen and women. Some of the

implications of differences in job satisfaction between branches of

the service are also discussed.

Chapter 4 addresses yet another issue that is of considerable

imivirtance to specialists interested in the size and stability of the

Amed Forces, namely the reenlistment rate. Our sample of reenlistees

is not large enough,at this time to conduct a separate analysis. How-

/

ever, reenlistment intentions were asked and we identify a number

of factors expectedto influence the reenlistment decision. Among the

factors studied are the enlistees' job satisfaction, tenure, extent

and type of armed forces training, health status, sex and race.

The issue of separation from the Armed Forces is the focus of the

analysis and discussion in Chapter 5. The universe consists of male

youth who had left military service prior to completing their tour of

duty. Our primary interest is to compare the work and school experiences

22
3

ofthese individuals with those of men who never served. We also

investigate, for those who find employment, selected characteristics

of their jobs, such as the kind of work, average hourly earnings, and

extent of job satisfaction. We are interested in how, this supposedly

inferior group of servicemen (i.e. they were unable to "make it" in

the military) fares in the civilian sector. In future years, as our

sample of persons separating from the service increases, we will assess the success of all those who separate.

In Chapter 6 our focus shifts from those who are currently serving

to those who have never served in the Armed Forces. We try to identify

potential entrants into the Armed Forces by their expression of a positive attitude toward the services and an intention to enlist. We

profile these attitudes by a number of demographic, familial, labor

market and schooling characteristics. The chapter closes with a

discussion of the reasons why eligible individuals with a high propensity

to serve choose not to enlist.

The Sample

The data are based on interviews with 12,693 youth who were born

in the calendar years 1957 through 1964, i.e., persons who were fourteen

to twenty-one as of January 1, 1979. A majority of these young people,

11,412, were selected from over 70,000 households which were screened

for eligible youth. The respondents came from 160 different Standard

Metropolitan Statistical Areas and counties and were selected to provide a nationally representative sample. In addition, the sample was

stratified by sex in order to yield approximately equal numbers of

men and women, and there was oversampling of Hispanic; non-Hispanic

black; and non-Hispanic, non-black, poor youth. As a result, the sample
4

is'composed of the following: 1,872 Hispanic youth (923 males, 949

females), 2,921 non-Hispanic black youth (1,443 males, 1,478 females),

1 1,671 non-Hispanic, non-black youth who met the poverty criteria , (756

males, 915 females), and a cross section of 4,949 non-Hispanic, non2

black youth (2,456 males, 2,493 females).

An additional sample of 1,281 persons within the age group who

were serving in the Armed Forces on September 30, 1978 were interviewed.

These individuals were selected from a list provided by the Armed Forces.

Unlike the sample of nonmilitary youth, the military sample included

persons serving overseas as well as those serving in the United States.

Further, this sample was selected to yield approximately two-thirds males

and one-third females, a heavy over-representation of females. Fuller

details of the sampling and weighting may be found in Chapter 7.

In the analyses which follow, persons are klentified by their

3

characteristics when interviewed --between the end of January, 1979

and August, 1979. The vast majority of interviews were completed during

the months of February, March, April, and May. In some cases, where the

variables being examined are likely to be affected by seasonality,

individuals who were interviewed after May, 1979 are assumed to be

distributed proportionately to those interviewed earlier. In addition,

1 The poverty lines were taken from the Office of Management and

Budget Guidelines and adjusted by the change in the Consumer Price

Index between January and October, 1978.

2

The cross section included youth from poverty households as well

as non-poor households.

3

Exceptions are racial-ethnic designation and sex., which were

gathered in the household screeners conducted between September, 1978

and March, 1979 or from military records.
5

information un civilian or military status is as of the date of interview. Consequently, individuals who were selected from the military

list but had become civilians are included in the civilian totals.

Likewise, persons who were civilians when originally selected for the

sample who had entered the military between the time of screening and

interview are included as serving in the military. All individuals

were assigned a weight indicating their probability of being selected

and interviewed. These weights were used in generating the data presented here. They will be adjusted somewhat in future reports.

Future Reports

Because of its preliminary nature, this report does not include

all of the questions of interest asked in the Youth Survey, nor does

it provide detail ty some independent variables like branch of service.

These shortcomings are due to limitations on time and the necessity

,o revise some of the original information. Subsequent reports will

add to the areas studied, complete and refine the analyses presented

here, and offer further suggestions for military personnel policy.
CHAPTER 2

PARTICIPANTS IN THE ALL VOLUNTEER FORCE

AND THEIR QUALITY

The foundation of an all volunteer force is its ability to recruit

and retain sufficient numbers of high quality enlistees. Further, it

is generally held that the composition of the Armed Forces should

reflect participation from all segments of the overall population. This

chapter is devoted to examining two sets of questions: (1) What proportion of different groups in society are serving in the Armed Forces?

and (2) What are the characteristics of youth serving in the Armed

Forces compared with youth who are employed full time in the civilian

sector?

Some facts concerning participation in the Amed Forces are widely

known: (1) the participation rate of blacks exceeds that of other

racial groups and (2) the proportion of females in the service is small

1 even though in recent years it has been increasing rapidly. However,

many other questions remain. When the military manpower system shifted

from the draft to the all volunteer force, it was hypothesized that

the Armed Forces would become heavily populated with volunteers from

2

the lower socioeconomic segments of the population. These individuals

were thought to have fewer opportunities for schooling and work in

the civilian sector. Likewise, it was thought that the educational

attainment and intellectual ability of the enlistees would be low

because these groups could not find "better" opportunities in the

1 Women comprised 14 percent of all enlistee accessions in the

first quarter of 1979.

2

See The Report of the President's Commission on All Volunteer

Armed Force, U.S.G.P.O., 1910

6

26
civilian sector. On the othu availability of post-service

educational benefits has been cited as an inducement to enlist in the

3

Armed Forces. This would argue that persons seeking higher education

would be more likely to enlist. One would also expect the Armed

Forces to attract persons in better than average health.

4

Participation Rates

Table 2.1 presents the approximately 600,000 persons serving in

the Armed Forces as a percentage of the total population of 16,475,000

5

18-21 year olds, and who have not previously served. These participation

rates appear by sex and race. As expected, the participation rate of

males (6.7 percent) is more than ten times that of females (0.6 percent)

and the black youth participation rate is about 1.5 times that of whites.

Further, participation rates for men are almost two times higher for

20-21 year olds than they are for 18-19 year olds. This is not true

for women, however, who have similar participation rates for both age groups.

One would expect that fewer married individuals would choose to.

serve in the Armed Forces. This is not the case, however, among males.

The proportion of married men who serve in the Armed Forces is approximately

6

double that of men who have never married. The participation rate

of married men is particularly high among blacks where it is more than

three times that of the never marrieds. While we cannot say at this

time whether these young men were married when they enlisted, the high

3

David Gottlieb, Babes in Arms, University of Houston, 1979.

4

Data on the characteristics of the population are measured at

the time of the interview unless another date is mentioned specifically.

5

Persons serving in the National Guard or Reserves are included

in the civilian population, but not among the armed forces which includes

only the active forces.

6

The 2.5 percent of the population who were widowed, separated,

or divorced were excluded from this comparison.
Table 2.1 Participation Rates in the Armed Forces Among Youth 18-21 Years

of Age, by Sex, Race and Other Selected Characteristics: 1979

and sex Males Females

Characteristic Total Black Hispanic White Total Black Hispanic White

Total respondents 6.7 9.7 7.6 6.1 0.6 0.8 0.5 0.6

Education of parenta

Less than 12 years 6.8 7.2 5.2 7.1 0.7 0.5 0.3 0.8 12 years 6.8 11.3 8.1 6.2 0.6 1.2 0.9 0.5 13 years or more 6.0 11.8 10.8 5.4 0.6 0.7 0.5 0.5

Occupation of parent b

Professional or

managerial 5.0 11.0 9.1 4.5 0.5 0.8 0.8 0.4 Sales, clerical 5.9 8.6 9.8 5.5 0.5 1.1 0.2 0.4 Blue collar 7.5 10.7 8.2 7.0 0.7 0.5 0.6 0.8 Service 9.2 10.0 8.0 9.0 0.8 1.6 0.0 0.5

Education of respondent

Less than 12 years 5.2 3.1 4.8 5.8 0.2 0.0 0.0 0.3 12 years or more 7.4 15.7 10.4 6.2 0.7 1.3 0.9 0.7

Educational expectation

Less than 12 years 1.6 0.7 0.0 2.0 0.3 0.0 0.0 0.4 12 years 5.1 5.1 5.8 5.1 0.3 0.2 0.2 0.3 13-15 years 9.6 16.4 17.5 8.0 0.6 1.0 0.8 0.5 16 years or more 7.6 12.8 8.0 6.8 0.9 1.2 0.7 0.9

Knowledge of the world

of work score

0-5 6.1 7.1 6.1 5.5 0.2 0.4 0.2 0.1 6 6.5 6.4 11.0 6.1 0.8 0.6 0.3 0.8

7 7.1 11.9 10.8 6.3 0.6 0.9 0.6 0.6 8-9 6.8 20.2 5.7 6.2 0.8 1.9 1.6 0.7

Marital status

Married 11.7 31.0 6.3 10.7 0.6 1.0 0.4 0.6 Never married 5.8 8.3 7.4 5.3 0.6 0.7 0.5 0.5

Internality (Rotter)

score

4-8 6.3 8.6 7.7 5.9 0.7 0.7 0.6 0.7

9-16 7.3 11.3 7.8 6.5 0.5 0.9 0.3 0.4
Table 2.1 continued

Race and sex

Characteristic

9

Males Females

Total Black Hispanic

7.6

6.5

6.3

8.9

White

6.0

7.1

4.2

8.0

Total

0.6

0.7

0.5

0.6

Black

0.7

2.2

0.8

0.8

Hispanic

0.5

0.0

0.2

0.7

White-,

Health status

6.6

7.0

4.6

8.8

9.9

6.8

6.1

13.9

0.6

0.5

0.5

0.6

Does not affect work

Affects work

Age

18-19 years

20-21 years

aYears of school completed by the parent in the household with the highest educational

attainment.

b

One-digit occupation group of father's job. If father is absent from household and

mother present, then occupation group of mother's job.
10

participation rates of this group do imply high costs for the services

since marriage is usually associated with a greater number of dependents

who will require additional benefits such as quarters, allowances and

medical care.

Two variables have been selected to measure the socioeconomic background of youth--occupation and educational attainment of the youth's

7

parents. Examination of these two variables show conflicting trends,

particularly among the males. Contrary to the expectation that mainly

youth from lower socioeconomic backgrounds would participate in the

Armed Forces, among black and Hispanic young men we find higher

participation rates as parents education increases. This expectation is

supported somewhat, however, among white males, where the inverse

relationship is observed. There does not appear to be any pattern among

blacks and Hispanics when parents' occupation is examined, while among

whites the participation rates of those with professional and managerial

parents are lower. These reversals of participation rates are one of

several pieces of evidence that indicate that minorities, particularly

blacks, from better backgrounds and with better credentials are disproportionately attracted to the armed forces; for whites, this is not

the case.

Another indication of higher than average participation rates

among better qualified minority youth is the proportion of high school

7

Parents' education was defined as the highest number of years'of

schooling completed by either parent. Parents' occupation was defined as that of the father except in cases where intonation on the father

was unavailable, the mothers' occupation was used. If the information

was missing for both parents or the parents' occupation was in farming,

the individual was excluded form the analysis.

30
11

graduates who participate in the military. For whites, the proportions

of male graduates and dropouts are nearly identical. On the other hand,

among Hispanic youth, twice the percentage of graduates participate,

and the participation rate for black males who have completed high

school is five times higher than for those who are high school dropouts.

Similar patterns exist among the women, although very few have not

completed high school.

If we examine scores on a knowledge of the world of work scale

(KOWW), we find the same patterns. Although this scale was constn.cted

to measure young people's knowledge of various occupations, it has in

the past been shown to correlate significantly with mental ability. Since

we do not yet have a direct measure, we have decided to use KOWW as

8

a proxy indicator of mental ability. There is somewhat lower

than average participation in the Armed Forces among persons scoring

from 0-5, as would be expected, given the mental ability standards

applied by the services. Among whites the proportion who partiCipate in

the military is approximately the same for all with scores above 5. For

blacks, though, there is a marked increase in the participation rate

as KOWW score increases; those scoring 8 or 9 are more than three times

as likely to participate in the military as are those scoring 6.

Finally, one sees the same pattern when examining the participation

rate associated with the number of years of schooling which the young

people expect to complete. There are very few in the military who do

not expect to complete high school. This arises in part from the relatively

high percentage of persons serving who have already completed the twelfth

8

The scores run from 0-9 and indicate how many occupations could

be correctly identified. For entire population of youth, the mean

score was between six and seven; the scores increased with age, and

minority youth scored markedly lower.

1

LI 4.
12

grade. However, the participation rates of persons who expect to

complete some college are higher than those of youth whi expect to

complete only twelve years of school. This is particularly true

among the minorities. It appears that many of those serving in the

military view it as a means to gain higher education or at least do

9

not view service and college attendance as mutually exclusive.

It is interesting to note that most of these relationships hold

when the universe is restricted to high school graduates. This is

seen in Table 2.2. Again, we find high participation rates among

the older youth; the married males; minority males whose parents had

more education; white males whose parents had less schooling; blacks

who have higher scores on the knowledge of the world of work test and

among all groups who expect to complete some college. The only noticeable differences between the high school graduates and all youth are

somewhat lower participation rates among black males whose parents are

professionals or managers (a small group) and stronger evidence that

minority males who participate are drawn from persons who feel they

10

have less control over events around them.

The most striking finding on the participation of youth in the

military is the higher participation rate among minorities from higher

socioeconomic backgrounds and with better qualifications. The reason

for this is not clear. One possible explanation is the relative lack

of discrimination in the armed forces when compared with civilian

9

No substantial differences are found in the health status and

the internality of the respondents.

10

This last finding is highly tenative, however, since the higher

degree of externality among the armed forces personnel may reflect

their experiences while in the military service rather than the attitudes

of the young men at the time they entered.

32
13

Table 2.2 Participation Rate in the Armed Forces Among Youth 18-21 Years

of Age with 12-15 Years of School Completed, by Sex, Race and

Other Selected Characteristics: 1979

Race and sex Males Females

Characteristic Total Black Hispanic White Total Black Hispanic White

Total respondents 7.4 15.7 10.4 6.2 0.7 1.3 0.9 0.7

Education of parenta

Less than 12 years 9.8 11.9 9.4 9.1 1.3 1.1 0.8 1.4

12 years 7.7 17.3 9.8 6.6 0.7 1.8 1.3 0.6

13 years or more 5.9 15.7 11.9 5.1 0.5 0.9 0.6 0.5

Occupation of parent

Professional,

managerial 4.8 10.3 10.8 4.4 0.5 1.0 0.9 0.4

Sales, clerical 6.5 16.0 6.3 5.9 0.5 1.4 0.3 0.5

Blue collar 8.9 17.3 13.2 7.6 1.0 0.7 1.2 1.0

Service 10.1 16.0 6.6 8.5 1.3 2.6 0.0 0.8

Educational expectations

12 years 5.0 10.1 6.2 4.5 0.4 0.7 0.6 0.4

13-15 years 9.7 21.0 17.9 7.7 0.7 1.3 1.0 0.5

16 years or more 7.8 15.7 8.7 6.7 1.0 1.5 0.9 0.9

Knowledge of the world

of work score

0-5 9.5 14.0 11.7 7.3 0.4 0.8 0.4 0.2

6 6.4 10.9 12.7 5.1 1.0 1.0 0.5 1.1

7 7.7 14.8 16.5 6.5 0.6 1.2 0.8 0.6

8-9 6.9 22.4 4.5 6.1 0.9 2.2 1.9 0.8

Marital status

Married 14.8 43.5 c 12.8 0.9 1.6 1.1 0.8

Never married 6.4 13.7 9.6 5.3 0.7 1.2 0.8 0.6

Internality (Rotter)

score 4-8 6.7 12.5 8.3 6.1 0.8 1.1 1.0 0.8

9-16 8.6 19.6 13.3 6.6 0.6 1.5 0.8 0.5
14

Table 2.2 continued

Race and sex

Characteristic

Males Females

Total Black Hispanic White Total Black Hispanic

Health status

Affects work

Does not affect work 7.3 15.6 10.8 6.2 0.7 1.0 0.9 0.7 8.3 18.3 0.0 7.6 1.0 3.8 0.0 0.7

.6.9.t

18-19 years

20-21 years

5.4 11.6 10.1 4.5 0.7 1.6 0.4 0.6 8.7 18.5 10.5 7.5 0.8 1.0 1.2 0.7

aYears of school ccmpleted by the parent in the household with the highest attainments. educational

b

One-digit occupation group of father's job. If father is absent from mother is present, then household and

occupation group of mother's job.

cLess than 25 sample cases.
15

pursuits. For more capable minority males, participation in the

military may offer more opportunities for advancement and success than

do civilian pursuits, while this may not be true for whites. This

explanation is unsupported by the finding that higher quality minority

persons are more likely to apply for enlistment (See Chapter Six, below).

Another hypothesis is that the standards the services use to accept

recruits exclude a larger proportion of minorities than whites who

come from lower socioeconomic backgrounds or have not completed high

school. We are unable to test this hypothesis directly because at this

time our sample does not contain a sufficient number of persons who

have been rejected by the military.

Quality of Armed Forces Personnel

The preceding section on participation rates speaks to the

representativeness of the Armed Forces. Of equal or greater importance

is the relative quality of individuals who serve in the military when

compared to persons in other pursuits. Earlier, we stated the hypothesis

that the all volunteer force would be more attractive to persons whose

opportunities in the civilian labor market were limited--persons with

less education, lower ability and from lower socioeconomic backgrounds.

In this section we compare youth in the services with the highest

quality out of school youth to determine whether Armed Forces personnel

are markedly superior or inferior. We have selected as a comparison

11

group youth whose primary status is full-time civilian employment.

We focus on this group because these are the individuals who have

chosen full-time employment in the civilian sector as opposed to full11 Excluded from this group are persons who are full-time employees

but who attend high school or are full-time college students.
16

time employment in the Armed Forces. These individuals have the jobs

which may be thought of as competing with service in the Armed Forces.

Tables 2.3 and 2.4 indicate the differences between the charac1Pristics

of active Armed Forces personnel and the full-time employed youth, 18-21

12

years of age, who have not completed college. Among white males the

Armed Forces personnel and youth employed full time in the civilian

labor market are highly similar. They are alike in the proportion with

health conditions that affect their work, the proportion who are married,

the level of mental ability as measured by the score on the knowledge of

the world of work test, their degree of internality, the proportion who

completed high school, the distribution of their parents' occupation

and their parents' education.

The Armed Forces group appears to be greatly superior to their

civilian counterparts among male minorities, however. More of the

servicemen come from families where a parent had graduated from high

school. The educational attainment of the young men serving in the

Armed Forces was higher than among the full-time employed; 85 percent

of the black and 68 percent of the Hispanic servicemen had completed

high school while the corresponding figures for those employed in fulltime civilian jobs were 57 and 48 percent, respectively. In addition,

the percentage of minority men who were below the mean score on the

13

KOWW test was substantially lower for the men in the Armed Forces.

Finally, many more o the servicemen in the three racial-ethnic

groups expected to complete college than was true of the civilian full12

Again, persons who previously served are excluded from the

civilian group.

13

The other factors were about the same for minorities in the

service and employed full time in civilian jobs.

36
17

Table 2.3 Comparison of Selected Characteristics of Male Youth 18-21 Years

of Age in Armed Forces and At Work Full-Time In Civilian Job, by

Characteristic, Survey Week Activity and Race: 1979

(Percentage distribution)

Race, survey week

activity

'Armed

Characteristic

Total Black Hispanic White

Forces

Employed

full-time

Armed

Forces

Employed

full-time

Armed

Forces

Employed

full-time

Armed

Forces

Employed

full-time

Total number (000) 549 3264 106 321 37 195 405 2748

Education of parenta 100 100 100 100 100 100 100 100

Less than 12 years 23 26 30 48 47 69 20 21

12 years 45 50 45 37 31 24 46 53

13 years or more 32 24 25 15 22 8 34 26

Occupation of

parentbc 100 100 100 100 100 100 100 100

Professional or

managerial 23 22 14 13 18 11 26 23.

Sales, clerical 11 12 8 7 11 5 12 13

Blue collar 52 53 54 52 54 49 51 53

Service 12 8 23 21 18 13 10 7 Education of

respondent 100 100 100 100 100 100 100 100

Less than 12 years 25 26 15 43 32 52 27 22

12 years or more 75 74 85 57 68 48 73 78

Educational expectations 100 100 100 100 100 100 100 100

Less than 12 years 2 11 1 13 0 23 2 10

12 years 27 49 18 41 24 43 29 50

13-15 years 26 25 29 26 39 15 24 25

16 years or more 46 16 52 21 37 20 45 15

Knowledge of world

of work score 100 100 100 100 100 100 100 100

0-5 21 23 39 55 37 49 15 18

6 14 16 10 16 26 15 13 15

7 21 22 20 17 21 14 22 23

8-9 44 39 31 12 16 21 50 44

Marital status 100 100 100 100 100 100 100 100

Married 18 17 15 9 11 20 19 18

Never married 82 83 85 91 89 80 81 82
18

Table 2.3 continued

Race, survey week

activity

:haracteristic

Total Black Hispanic ' White

Armed

Forces

Employed

full-time

Armed

Forces

Employed

full-time

Armed {Employed

Forceslfull-time

Armed

Forces

Employed

full -tine

Internality (Rotter:

score 100 100 100 100 100 100 100 100

4-8 53 54 42 49 49 45 57 55

9-16 47 46 58 51 51 55 43 45

Health status 100 100 100 100 100 100 100 100

Does not affect

work 95 96 96 98 95 96 95 96

Affects work 5 4 4 2 5 4 5 4

aYears of school completed by parent in the household with the highest educational

attainment.

b

One-digit occupation group of father's job. If father is absent from household and

mother is present, then occupation group of mothe's job.

cExcludes employment in farming
19

Table 2.4 Comparison of Selected Characteristics of Female Youth 18-21 Years

of Age In Armed Forces and At Work Full-Time In Civilian Job, by

Characteristic, Survey Week Activity and Race: 1979

(Percentage distribution)

ace, survey week

activity

Total Black Hispanic White

Characteristic

Armed

Forces

Employed

full-time

Armed

Forces

Employed

full-time

Armed ,Employed

Forceslfull-time

Armed

Forces

Employed

full-time

Total number (000) 49 2623 9 231 2 143 37 2249

Education of parenta 100 100 100 100 100 100 100 100

Less than 12 years 29 26 30 44 50 65 27 22

12 years 41 49 50 39 50 24 38 52

13 years or more 31 25 20 18 0 11 35 27

Occu.ation of parentb

100 100 100 100 100 100 100 100

Professional or

managerial 20 22 14 15 0 18 23 23

Sales, clerical 11 14 14 11 0 4 11 15

Blue collar 53 50 29 53 100 57 57 50

Service 13 9 43 20 0 11 9 8

Education of

respondent ,o0 100 100 100 100 100 100 100

Less than 12 years 8 15 0 10 0 34 11 15

12 years or more 92 84 100 90 100 66 89 85

Educational

expectations I 10C 100 100 100 100 100 100 100

Less than 12 years 4 7 0 2 0 14 5 7 12 years 18 45 10 31 0 33 19 47

13-15 years 22 30 30 34 50 32 22 29

16 years or more 55 19 60 33 50 22 54 17

Knowledge of world of

work score 100 100 100 100 100 100 100 100

0-5 10 25 22 46 0 38 5 22

6 18 14 11 12 0 24 18 13

7 22 25 22 20 50 21 24 26

8-9 50 36 44 21 50 17 53 39

Marital status 100 100 100 100 100 100 100 100

Married 25 25 16 18 26 31 27 26

Never married 75 75 84 82 74 69 73 74

33
20

Table 2.4 continued

ace, survey week

activity

Characteristic

Total Black Hispanic White

Employed

full-time

Armed

Forces

Employed

full-time

Armed 'Employed

Forces full-time

Armed

Forces

Employed

full-time

Armed

Forces

Internality (Rotter)

score 100 100 100 100 100 100 100 100

4-8 63 54 44 46 50 46 68 55

9-16 37 46 56 54 50 54 32 45

Health status 100 100 100 100 100 100 100 100

Does not affect

work 88 93 78 96 100 99 92 92

Affects work 12 7 22 4 0 1 8 8

a Years of school completed by parent in the household with the highest educational

attainment.

b

One-digit occupation group of father's job. If father is absent from household and

mother is present, then occupation group of mother's job.

cExcludes employment in farming
21

time employed. Overall, 46 percent of the young servicemen expected to

complete college as opposed to 16 percent of the full-time employed.

Among the young women similar patterns appear. About the same

proportions of both groups of all races are married and have parents

in the various occupational categories. Again, the educational expectations

of the servicewomen are markedly higher: over half expect to complete

college as compared with less than one in five among the full-time

employed. We also find that the minority women in the service are

superior to their civilian counterparts in several respects: more of

them and their parents have completed high school, and their scores on

the knowledge of the world of work test are considerably higher.

Differences between the two groups of women which were not evident

for the men are health conditions and degree of internality. Black

servicewomen appear to have much higher proportions than employed

civilians who say they have a health condition which affects or limits the amount of work they can do.14 With regard to degree of internality, white servicewomen appear to believe that they have less

control over their environment than do their civilian counterparts. 15

In conclusion, there can be little doubt that the quality of the

young people serving in the military forces is at least equal to and

for minorities, superior to the comparable group in the civilian sector.

14

The number of persons involved here is so small that the finding

could very well be due to chance.

15

The same differences between military personnel and the persons

employed full time in civilian jobs were observed for both men and women

who were high school graduates. See Appendix A, Tables A.24 and A.25.

16

Although the minority service personnel are superior to their

civilian counterparts while white service men and women are not, this

does not mean that the minorities serving in the Armed Forces are more

qualified than whites in the military. Comparison of the fourth, sixth

and eighth columns in Tables 2.3 and 2.4 shows this not to be the case.

41

16
22

Our data indicate that the aggregate Armed Forces are drawing recruits

of hish quality, relative to the pool of out-of-school youth employed

17

full-time.

17

It should be noted, however, that on average, the highest "quality"

groups are those youth who are enrolled in college. On the other hand,

the civilians employed full time should be better qualified than those

who are employed only part time, are unemployed, pr4re out of the labor

force.
23

APPENDIX A

The universe for this chapter consists of individuals 18 to 21

years of age with less than 16 years of school completed. It excludes

those who have served previously in the Armed Forces.

Respondents are assigned to one of the following mutually exclusive

survey week activity categories. The assignment is hierarchical in

the sense that an individual who is engaged in more than one activity

is assigned to that with the highest priority. The definition of each

of these activities and its priority status is as follows:

Armed Forces

Civilian Sector

Enrolled

High school

College

Individuals currently serving in the Armed

Forces are classified in this activity re- gardless of civilian sector enrollment and

employment status.

Individuals who are not serving but who are currently enrolled in high school are as- signed to this category.

Individuals who are not serving, but are

enrolled in college, except for those enrolled part time who work full time, are assigned to this activity. The part-time

student working full time is assigned to

the full time employed category.

Not Enrolled

Employed, full

time Out of school youth (except the part time

college student at work full time) who are not serving and who are working or usually

work at least 35 hours per week are assigned

to this category.

Employed, part

time Out of school youth who are not serving and

are at work, or usually work, less than 35

hours per week comprise this category.
24

Unemployed This category includes out of school youth

who are not working and who are actively

seeking work.

Not in labor

force Any individual who is not classified into

any of the previous categories is assigned

to this activity.

Even though we mainly focus on the characteristics of those who

serve, and then compare their attributes with those employed full time,

we also distribute our sample cases across the survey week activities

by characteristic. This appendix indicates the participation rates

for all seven groups.

The lower attrition rates and higher productivity of enlistees

with at least 12 years of school completed make this group particularly

attractive to the Armed Forces. We, therefore, present a comparable

set of tables targeted at this group.
25

Table A.1 .Distribution of Male Population 18-21 Years of Age, by Age, Race, and

Survey Week Activity: 1979

(Percentage distribution)

urvey week Total popu ation

Civilian sectora activity

Age, race

Total

number

( 000 )

Total

percent

Armed

Forces High

school College

Em lo ed

Unemployed

Not in

labor

force

Fulltime

arttime

Total

Ages, 18-21 8239 100.0 6.7 12.8 25.9 39.6 5.3 6.3 3.5

18-19 4205 100.0 4.6 23.5 23.0 33.3 5.3 6.5 3.9

20-21 4038 100.0 8.8 1.7 28.9 46.2 5.2 6.1 3.1

Black

Ages, 18-21 1088 100.0 9.7 18.1 17.0 29.5 7.3 11.4 7.0

18-19 581 100.0 6.1 32.1 15.5 20.6 6.6 10.2 8.9

20-21 507 100.0 13.9 2.0 18.6 39.7 8.1 12.7 4.8

Hispanic

Ages, 18-21 495 100.0 7.6 15.7 17.5 39.3 4.6 7.5 7.8

18-19 254 100.0 6.3 29.6 13.4 33.4 4.2 6.4 6.7

20-21 241 100.0 8.9 1.0 21.8 45.6 4.9 8.7 9.1

White

Ages, 18-21 6658 100.0 6.1 11.7 28.0 41.3 5.0 5.3 2.6

18-19 3370 100.0 4.2 21.5 25.0 35.4 5.2 5.8 2.9

20-21 3291 100.0 8.0 1.7 31.0 47.2 4.7 4.9 2.4

aExcludes individuals with prior service in the Armed Forces.

ry
26

Table A.2 Distribution of Female Population 18-21 Years of Age, by Age, Race and

Survey Week Activity: 1979

(Population distribution)

urvey week Total population

activity

Age, race

Total

number

( 000)

Total

percent

Armed

Forces

Civilian sectora

High

school College

Employed

Unemployed

Not in

labor

force

Fulltime

Parttime

Total

Ages, 18-21 8258 100.0 0.6 8.8 26.2 31.7 8.5 9.3 15.0

18-19 4243 100.0 0.5 16.3 29.2 24.5 8.0 9.5 11.9

20-21 4046 100.0 0.6 0.8 23.1 39.1 8.9 9.1 18.3

Black

Ages, 18-21 1184 100.0 0.8 14.6 22.7 19.5 5.8 17.0 19.6

18-19 602 100.0 0.8 26.7 20.0 12.9 5.5 17.2 16.9

20-21 582 100.0 0.8 2.2 25.5 26.3 6.1 16.7 22.4

Hispanic

Ages, 18-21 523 100.0 0.5 10.2 18.6 27.3 6.2 9.1 28.0

18-19 263 100.0 0.2 18.3 18.5 25.0 3.6 9.6 24.8

20-21 260 100.0 0.7 2.1 18.7 29.6 8.9 8.6 31.3

White

Ages, 18-21 6580 100.0 0.6 7.6 27.5 34.2 9.1 8.0 13.2

18-19 3378 100.0 0.5 14.3 31.7 26.6 8.8 8.2 10.0

20-21 3204 100.0 0.6 0.5 23.0 42.2 9.5 7.8 16.5

aExcludes individuals with prior service in the Armed Forces.
27

Table A.3 Percent of Total Population With 12-15 Years of School Completed, by Age, Sex and Race: 1979

ace, sex Males Females

Age Total White Black Hispanic Total White Black iHispanic

Ages, 18-21 67.8 71.6 52.5 49.1 /2.4 76.1 61.3 51.1

18-19 55.4 59.4 40.4 37.8 63.9 68.5 48.5 40.3

20-21 80.6 84.2 66.3 61.0 81.3 84.1 74.6 62.3
28

Table A.4 Distribution of Male Population 18-21 Years of Age With 12-15 Years of

School Completed, by Age, Race and Survey Week Activity: 1979

(Percentage distribution)

urvey week Total population

activity

Age, race

Total

number

( 000)

Total

percent

Armed 1 Civilian sectora

Forces College Emplo ed

Unemployed

Not in

labor

force

Fulltime

Parttime

Total

Ages, 18-21 5582 100.0 7.4 38.2 43.4 4.3 4.1 2.6

18-19 2331 100.0 5.4 41.4 40.7 5.4 3.9 3.1

20-21 3253 100.0 8.7 35.9 45.3 3.6 4.3 2.2

Black

Ages, 18-21 571 100.0 15.7 32.4 31.8 6.2 10.0 4.0

18-19 235 100.0 11.6 38.4 28.1 5.5 9.8 6.5

20-21 336 100.0 18.5 28.1 34.5 6.6 10.1 2.2

Hispanic

Ages, 18-21 243 100.0 10.4 35.6 38.8 3.7 4.9 6.6

18-19 96 100.0 10.1 35.6 38.7 3.2 4.0 8.4

20-21 147 100.0 10.5 35.6 38.9 4.0 5.5 5.5

White

Ages, 18-21 4770 100.0 6.2 39.0 45.0 4.1 3.4 2.2

18-19 2001 100.0 4.5 42.0 42.3 5.5 3.3 2.4

20-21 2770 100.0 7.5 36.9 46.9 3.2 3.5 2.0

a Excludes individuals with prior service in the Armed Forces.
29

Table A.5 Distribution of Female Population 18-21 Years of Age With 12-15 Years

of School Completed, by Age, Race and Survey Week Activity: 1979

(Percentage distribution)

Survey week Total

Armed ( Forces

population

Civilian sectora activity Total

number

Total

percent College Employed Not in

Age, race ( 000) Fu1Ttime

)arr=""

time

Unemployed labor

force

Total

Ages, 18-21 6000 100.0 0.7 36.2 36.7 9.3 6.8 10.2

18-19 2711 100.0 0.7 45.8 30.8 9.1 6.7 6.9

20-21 3291 100.0 0.8 28.4 41.6 9.5 6.9 12.9

Black

Ages, 18-21 726 100.0 1.3 37.1 28.6 7.1 15.0 11.0

18-19 292 100.0 1.6 41.4 22.7 7.6 16.5 10.2

20-21 434 100.0 1.0 34.2 32.6 6.8 13.9 11.5

Hispanic

Ages, 18-21 267 100.0 0.9 36.5 35.1 9.9 3.7 14.0

18.19 106 100.0 0.4 46.1 32.5 5.7 1.8 13.4

20-21 162 100.0 1.2 30.2 36.7 12.6 5.0 14.3

White

Ages, 18-21 5008 100.0 0.7 36.1 38.0 9.6 5.8 9.9

18-19 2314 100.0 0.6 46.3 31 7 9.5 5.7 6.2

20-21 2695 100.0 0.7 27.3 4. ,7 5.9 13.0

a Excludes individuals with prior service in th. Armed Forces.
30

Table A.6 Distribution of Male Population 18-21 Years of Age, by Education of

Parent, Race and Survey Week Activity: 1979

(Percentage distribution)

urvey week

activity

Parental

education, race

Total population

-Total

number

( 000)

Total

percent

Armed Civilian sectora

Forces High

school

Emplmod

Parttime

Unemployed Not in

labor

force

College Fulltime

Total

Total 8239 100.0 6.7 12.8 25.9 39.6 5.3 6.3 3.5

Less than 12

years 1797 100.0 6.8 15.0 9.5 46.0 5.4 11.2 6.1

.12 years 3428 1)0.0 6.8 13.8 18.9 46.0 5.9 5.6 3.1

13 years or more 2780 100.0 6.0 10.7 47.1 27.0 4.0 3.1 2.0

Black_

Total 1088 100.0 9.7 18.1 17.0 29.5 7.3 11.4 7.0

Less than 12

year_ 404 100.0 7.2 19.7 11.8 34.8 5.8 13.3 7.4

12 years 392 100.0 11.3 20.8 15.1 28.1 8.4 10.5 5.9

13 years or more 202 100.0 11.8 11.2 37.2 21.4 7.9 5.5 5.0

Hispanic

Total 495 100.0 7.6 15.7 17.5 39.3 4.6 7.5 7.8

Less than 12

years 280 100.0 5.2 17.7 8.4 44.7 3.9 11.0 9.1

12 years 120 100.0 8.1 9.0 29.4 36.3 7.4 3.5 6.3

13 years or more 69 100.0 10.8 23.7 37.5 20.8 2.5 3.3 1.5

White

Total 6658 100.0 6.1 11.7 28.0 41.3 5.0 5.3 2.6

Less than 12

years 1113 100.0 7.1 12.G 8.9 50.3 5.7 10.5 4.9

12 years 2916 100.0 6.2 13.0 19.0 48.8 5.5 5.0 2.6

13 years or more 2509 100.0 5.4 10.3 48.2 27.7 3.7 2.9 1.8

a Excludes individuals with prior service in the Armed Forces.

50
31

Table A.7 Distribution of Female Population 18-21 Years of Age, by Education of

Parent, Race, and Survey Week Activity: 1979

(Percentage distribution)

Survey week Total population

ctivity

Parental

education, rac

Total

number

(000)

Total

percent

Armed Civilian sectors

Forces High

school College Unemployed

Not in

labor

force

__Employed

Fulltime

Parttime

Total

Total 8285 100.0 0.6 8.8 26.2 31.7 8.5 9.3 15.0

Less than 12

years 2047 100.0 0.7 11.4 9.5 32.5 7.2 13.5 25.2

12 years 3375 100.0 0.6 7.9 20.5 37.7 10.1 9.8 13.4

13 years or more 2643 100.0 0.6 8.0 47.9 2%3 7.3 4.7 7.2

Black

Total 1184 100.0 0.8 14.6 22.7 19.5 5.8 17.0 19.6

Less than 12

years 489 100.0 0.5 17.3 15.9 19.5 5.0 16.9 25.0

12 years 399 100.0 1.2 13.4 21.9 21.1 7.4 18.9 16.1

13 years or more 216 100.0 0.7 11.4 44.2 17.7 4.3 14.2 7.4

Hispanic

Total 523 100.0 0.5 10.2 18.6 27.3 6.2 9.1 28.0

Less than 12

years 312 100.0 0.3 11.5 13.8 28.1 4.4 10.2 31.7

12 years 114 100.0 0.9 10.3 20.4 29.3 12.3 9.4 '7.4

13 years or more 76 100.0 0.5 7.8 40.1 19.3 6.3 6.9 19.2

White

Total 6580 100.0 0.6 7.6 27.5 34.2 9.1 8.0 13.2

Less than 12

years 1246 100.0 0.8 9.1 5.9 38.7 8.8 13.0 23.7

12 years 2863 100.0 0.5 7.1 20.3 40.3 10.4 8.6 12.9

13 years or more 2350 100.0 0.5 7.7 48.5 25.1 7.6 3.8 6.8

a Excludes individuals with prior service in the Armed Forces.
32

Table A.8 Distribution of Male Population 18-21 Years of Age With 12-15 Years of School Completed, by Education of Parent, Race and Survey Week

Activity: 1979

(Percentage distribution)

urvey week Total population activity

Parental

education, rac

Total

number

(000)

Total

percent

Armed

Forces

Civilian sect ra

' College

Employed

Unemployed

Not in

labor

force

Fulltime

Parttime

Total

Total 5582 100.0 7.4 38.2 43.4 4.3 4.1 2.6

Less than 12

years 792 100.0 9.8 21.5 51.8 4.3 8.5 4.1

12 years 2426 100.0 7.7 26.7 54.3 4.3 4.4 2.7

13 years or more 2308 100.0 5.9 56.8 29.0 4.1 2.3 2.0

Black

Total 571 100.0 15.7 32.4 31.8 6.2 10.0 4.0

Less than 12

years 183 100.0 11.9 26.1 40.9 3.9 12.0 5.2

12 years 216 100.0 17.3 27.5 33.9 6.9 9.8 4.6

13 years or more 144 100.0 15.7 52.1 18.0 6.5 6.4 1.2

Hispanic

Total 243 100.0 10.4 35.6 38.8 3.7 4.9 6.6

Less than 12

Years 106 100.0 9.4 22.3 49.3 1.4 8.4 9.2

12 years 84 100.0 9.8 41.8 32.1 7.9 2.0 6.4

13 years or more 48 100.0 11.9 53.8 21.6 1.7 2.8 2.1

White

1 Total 4770 100.0 6.2 39.0 45.0 4.1 3.4 2.2

Less than 12

years 503 100.0 9.1 19.7 56.2 5.1 7.3 2.6

12 years 2126 100.0 6.6 26.0 57.2 3.9 3.9 2.3

13 years or more 2116 100.0 5.1 57.2 29.7 4.0 2.0 2.0

a Excludes individuals with prior service in the Armed Forces.

52
33

Table A.9 Distribution of Total Female Population 18-21 Years of Age With 12-15

Years of School Completed by Education of Parent, Race, and Survey

Week Activity: 1979

(Percentage distribution)

urvey week Total population

activity

Parental

education, rac

Total

number

( 000)

Total

percent

Armed Civilian sectora

Forces

College

Employed

Unemployed

Not in

labor

force

Fulltime

Parttime

Total

Total 6000 100.0 0.7 36.2 36.7 9.3 6.8 10.2

Less than 12

years 1041 100.0 1.3 18.7 43.6 7.8 11.7 17.0

12 years 2608 100.0 0.7 26.5 42.7 11.4 7.1 11.5

13 years or more 2267 100.0 0.5 55.9 26.5 7.7 3.9 5.5

Black

Total 726 100.0 1.3 37.1 28.6 7.1 15.0 11.0

Less than 12

years 249 100.0 1.1 31.1 31.4 5.8 16.4 14.2

12 years 267 100.0 1.8 32.7 31.0 9.9 14.5 10.2

13 years or more 176 100.0 0.9 54.3 20.9 5.3 13.4 5.3

Hispanic

Total 267 100.0 0.9 36.5 35.1 9.9 3.7 14.0

Less than 12

years 122 100.0 0.8 35.3 40.5 7.7 4.0 11.7

12 years 77 100.0 1.3 30.1 33.7 15.9 2.1 16.9

13 years or more 63 100.0 0.6 48.5 21.6 7.6 5.7 16.0

White

Total 5008 100.0 0.7 36.1 38.0 9.6 5.8 9.9

Less than 12

years 670 100.0 1.4 11.0 48.7 8.5 11.3 19.0

12 years 2265 100.0 0.6 25.7 44.4 11.4 6.4 11.5

13 years or more 2028 100.0 0.5 56.3 27.1 7.9 3.0 5.2

aExciudes individuals with prior service in the Armed Forces.

53
34

Table A.10 Distribution of Male Population 18-21 Years of Age, by 1-Digit

Occupation Group of Parent, Race and Survey Week Activity: 1979

(Percentage distribution)

urvey week----- Totai55pulation activity

Occupatio

of parent, rac

Total

number

(000 )

Total

percent

Armed Civilian sectora

Emp loyed 'Not

Unemployed

in

labor

force

Forces High

school College Fulltime

Parttime

Total

Total 8239 100.0 6.7 12.8 25.9 39.6 5.3 6.3 3.5

Professional,

managerial 2217 100.0 5.0 10.5 49.7 28.6 3.0 2.7 1.2

Sales, clerks 878 100.0 5.9 14.7 30.0 39.1 3.8 4.1 2.4

Blue collar 3278 100.0 7.5 13.5 14.7 'i.9 6.3 7.4 3.7

Service 648 100.0 9.2 8.6 19.7 136.4 8.9 9.'2 7.3

Black

Total 1088 100.0 9.7 18.1 17.0 29.5 7.3 11.4 7.0

Professional,

managerial 109 100.0 11.0 8.5 41.9 28.9 3.3 5.7 0.7

Sales, clerks 80 100.0 8.6 32.7 22.7 20.4 4.4 5.3 6.0

Blue collar 420 100.0 10.7 19.1 14.7 29.4 7.5 12.0 6.6

Service 194 100.0 10.0 14.3 17.1 25.9 11.0 12.4 9.4

Hispanic,

Total 495 100.0 7.6 15.7 17.5 39.3 4.6 7.5 7.8

Professional,

managerial 60 100.0 9.1 17.9 35.7 26.8 3.6 1.4 5.6

Sales, clerks 31 100.0 9.8 14.4 44.1 26.3 0.0 1.8 3.6

Blue collar 181 100.0 8.2 18.6 16.6 39.7 4.0 6.1 6.7

Service 61 100.0 8.0 7.5 15.1 31.8

1 10.7 12.6 14.2

White

Total 6658 100.0 6.1 11.7 28.0 41.3 5.0 5.3 2.6

Professional,

managerial 2048 100.0 4.5 10.3 50.5 28.6 3.0 1.9 1.1

Sales, clerks 766 100.0 5.5 12.9 30.2 41.5 3.9 4.0 2.0

glue collar 2676 100.0 7.0 12.3 14.6 50.2 6.2 6.8 3.0

Service 393 100,0 9.0 6.0 21.6 42.3 7.6 8.3 5.2

aExcludes individuals with prior service in the Armed Forces.

54
3S

Tahle A,11 Distribution of Female Population 18-21 Years of Age, by 1-Digit

Occupation Group of Parent, Race and Survey Week Activity; 1979

(Percentage distribution)

urvey week Total popu ation

activity

Occupation

of parent, race

otal

number

(000 )

Total

percent

Armed

Forces

Civilian sectora

Hig

school

Emp cye

Parttime

Unemployed

Not in

labor

force

College Fulltime

Total

Total 8285 100.0 0.6 8.8 26.2 31.7 8.5 9.3 15.0

Professional,

managerial 2042 100.0 0.5 7.7 48.1 25.2 6.6 4.6 7.3

Sales, clerks 1040 100.0 0.5 6.3 31.3 32.4 11.4 8.3 9.9

Blue collar 3179 100.0 0.7 9.4 16.2 37.6 9.8 10.0 16.2

Service 759 100.0 0.8 10.8 17.3 29.6 8.1 13.4 20.1

Black

Total 1184 1 100.0 0.8 14.6 22.7 19.5 5.8 17.0 19.6

Professional,

managerial 125 100.0 0.8 5.2 46.9 23.3 2.3 12.2 9.3

Sales, clerks 75 100.0 1.1 18.7 19.3 28.0 11.4 7.6 13.9

Blue collar 450 100.0 0.5 14.7 21.3 22.7 7.2 16.1 17.5

Service 221 100.0 1.6 16.2 22.9 17.4 3.8 I 21.4 16.7

Hispanic

Total 523 100.0 0.5 10.2 18.6 27.3 6.2 9.1 28.0

Professional,

managerial 58 100.0 0.8 5.4 27.6 34.1 7.2 4.9 20.1

Sales, clerks 36 100.0 0.2 7.3 38.5 11.0 2.7 12.8 27.5

Blue collar 183 100.0 0.6 8.2 16.0 35.4 5.4 9.1 25.3

Service 61 100.0 0.0 20.6 16.0 21.2 5.8 12.0 24.4

White

Total 6580 100.0 0.6 7.6 27.5 34.2 9.1 8.0 13.2

Professional,

managerial 1859 100.0 0.4 7.9 48.8 25.2 6.8 4.1 6.8

Sales, clerks 929 100.0 0.4 5.3 31.9 33.6 11.7 8.2 8.8

Blue collar 2547 100.0 0.8 8.6 15.4 40.4 10.6 9.0 15.3

Service 477 100.0 0.5 7.0 14.8 36.3 10.4 9.9 21.1

t a Excludes individuals with prior service in the Armed Forces.
36

Table A.12 Distribution of Male Population 18-21 years of Age with 12-15 years

of School Completed by 1-Digit Occupation Group of Parent, Race and

Survey Week Activity: 1979

(Percentage distribution)

Survey week Total population

activity

Occupation of

parent, race

Total

number

( 000 )

Total

percent

Armed

Forces

Civilian sectora

Employed

Parttime

Unemployed

Not in

labor

force

College Fulltime

Total

Total

Professional,

5582 100.0 7.4 38.2 43.4 4.3 4.1 2.6

Sales, clerks

managerial 1859 100.0 4.8 59.3 30.3 3.1 1.4 1.1

Blue collar

654 100.0 6.5 40.2 43.9 3.7 3.2 2.5

Service

2003 100.0 8.9 24.1 54.6 4.9 4.8 2.7 405 100.0 10.1 31.5 38.6 6.2 7.7 5.9

Black

--I Total 571 100.0 15.) 32.4 31.8 6.2 10.0 4.0 Professional,

managerial 87 100.0 10.3 52.3 29.1 3.2 5.1 0.0 Sales, clerks

Blue collar

35 100.0 16.0 52.5 10.6 5.5 12.3 3.1

Service

225 100.0 17.3 27.4 34.3 5.7 9.8 5.6 95 1W.0 16.0 34.9 27.4 8.2 10.9 2.6

Hispanic

Total 243 100.0 10.4 35.6 38.8 3.7 4.9 6.6 Professional,

managerial 42 100.0 10.8 51.5 29.5 0.0 0.0 8.1 Sales, clerks 21 100.0 6.3 66.0 27.7 0.0 0.0 0.0 Blue collar 84 100.0 13.2 36.0 40.5 3.1 1.7 5.5 Service 37 100.0 6.6 25.0 32.3 15.0 10.0 11.0

White

Total 4770 100.0 6.2 39.0 45.0 4.1 3.4 2.2 Professional,

managerial 1730 100.0 4.4 59.8 30.4 3.1 1.2 1.0

Sales, clerks 599 100.0 5.9 38.6 46.4 3.8 2.8 2.5 Blue collar 1694 100.0 7.6 23.0 58.0 4.9 4.3 2.2 Service 273 100.0 8.5 31.2 43.4 4.3 6.3 6.4

aExcludes individuals with prior service in the Armed Forces.
37

Table A.13 Distribution of the Female Population 18-21 years of Age with

12-15 years of School Completed by 1-Digit Occupation Group

of Parent, Race and Survey Week Activity: 1979

(Percentage distribution)

Survey week Total population

activity

Occupation of

parent, race

Total

number

(000)

Total

percent

Armed Civilian sectora

Forces

College

Employed

Unemployed

Not in

labor

force

Fulltime

Parttime

Total

Total 6000 100.0 0.7 36.2 36.7 9.3 6.8 10.2

Professional,

managerial 1712 100.0 0.5 57.4 26.7 6.7 3.7 5.0

Sales, clerks 863 100.0 0.5 37.7 37.3 11.6 4.5 8.4

Blue collar 2199 100.0 1.0 23.5 44.0 11.2 8.0 12.4

Service 481 100.0 1.3 27.2 38.5 9.4 10.5 13.1

Black

Total 726 100.0 1.3 37.1 28.6 7.1 15.0 11.0

Professional,

managerial 103 100.0 1.0 56.8 28.2 2.8 5.7 5.5

Sales, clerks 58 100.0 1.4 25.2 33.7 14.9 9.9 14.9

Blue collar 289 100.0 0.7 33.1 31.4 9.1 15.3 10.3

Service 136 100.0 2.6 37.1 26.1 5.0 19.1 10.1

Hispanic

Total 267 100.0 0.9 36.5 35.1 9.9 3.7 14.0

Professional,

managerial 48 100.0 0.9 33.2 38.8 8.6 3.9 14.5

Sales, clerks 27 100.0 0.3 51.3 14.7 3.5 3.9 26.3

Blue collar 95 100.0 1.2 30.8 46.6 9.2 1.5 10.8

Service 27 100.0 0.0 36.7 25.2 9.7 9.3 19.0

White

Total 5008 100.0 0.7 36.1 38.0 9.6 5.8 9.9

Professional,

managerial 1561 100.0 0.4 58.2 26.3 6.9 3.6 4.7

Sales, clerks 779 100.0 0.5 38.1 38.3 11.7 4.2 7.3

Blue collar 1815 100.0 1.0 21.6 45.8 11.6 7.2 12.8

Service 318 100.0 0.8 22.2 44.9 11.3 6.9 13.9

aExcludes individuals with prior service in the Armed Forces.
38

Table A.14 Distribution of Male Population 18-21 years of Age, by Educational Expectation, Race and Survey Week Activity: 1979

(Percentage distribution)

Survey week Tota popu ation activity

Educational

expectation, rac

Total

number

(000 )

Total

percent

Armed Civilian sectors

Forces High

school

Employed

Parttime

Unemployed

Not in

labor

force

College Fulltime

Total

Total

Less than 12

8239 100.0 6.7 12.8 25.9 39.6 5.3 6.3 3.5

12

years 616 100.0 1.6 3.2 0.2 55.9 11.1 18.6 9.4

13-15

2821 100.0 5.1 17.9 0.0 56.0 6.9 8.8 5.3

16 years or more

1462 100.0 9.6 10.8 12.0 54.1 5.3 5.7 2.5 3259 100.0 7.6 11.4 60.0 15.4 2.7 1.5 1.3

Black

Total

Less than 12

1088 100.0 9.7 18.1 17.0 29.5 7.3 11.4 7.0

12

years 86 100.0 0.7 7.5 0.0 47.4 13.6 15.8 14.0

13-15

375 100.0 5.1 27.4 0.0 34.7 7.4 15.3 10.2

16 years or more

186 100.0 16.4 10.9 7.3 43.6 5.2 12.9 3.7 420 100.0 12.8 16.1 40.8 15.5 5.8 5.6 3.4

Hispanic

Total

Less than 12

495 100.0 7.6 15.7 17.5 39.3 4.6 7.5 7.8

12

years 63 100.0 0.0 2.4 0.0 65.6 6.4 10.8 14.7

13-15

159 100.0 5.8 21.6 0.0 47.9 5.2 12.5 7.1

16 years or more

84 100.0 17.5 10.6 13.3 31.5 9.2 8.3 9.6 171 100.0 8.0 18.3 44.2 20.3 1.5 1.7 6.0

White

Total 6658 100.0 6.1 11.7 28.0 41.3 5.0 5.3 2.6 Less than 12

12

years 467 100.0 2.0 2.4 0.3 56.2 11.3 20.0 7.8 2286 100.0 5.1 16.1 0.0 60.0 7.0 7.5 4.3 13-15

16 years or more

1193 100.0 8.0 10.8 12.6 57.3 5.0 4.4 1.9 2669 100.0 6.8 10.2 64.1 15.1 2.2 0.9 0.7

aExcludes individuals with prior service in the Armed Forces.
39

Table A.15 Distribution of Female Population 18-21 Years of Age, by

Educational Expectation, Race and SurveyWeek Activity: 1979

(Percentage distribution)

Survey week Total population activity

Educational

expectation, racTotal

number

( 000)

Total

percent

Armed Civilian sectora

forces High

school College

Employed

Unemployed

Not 5-

labor

force

Full-I

time

Parttime

Total

Total

Less than 12

8285 100.0 0.6 8.8 26.2 31.7 8.5 9.3 15.0

12 years

years 532 100.0 0.3 0.3 0.0 32.2 7.3 15.6 44.3

13-15 years

2931 100.0 0.3 11.2 0.0 39.7 12.1 13.1 23.6

16 years or more

1857 100.0 0.6 8.0 19.0 42.0 9.7 10.4 10.3 2886 100.0 0.9 8.5 62.7 16.7 4.4 3.6 3.1

Black

Total

Less than 12

1184 100.0 0.8 14.6 22.7 19.5 5.8 17.0 19.6

12 years

years 45 100.0 0.0 0.0 0.0 12.0 2.3 22.6 63.1

13-15 years

398 100.0 0.2 18.2 0.0 17.6 6.9 24.6 32.5

16 years or more

255 100.0 1.0 12.3 16.9 30.6 6.6 16.6 15.9 473 100.0 1.2 14.3 47.8 15.7 4.9 10.5 5.7

Hispanic

Less than 12

Total 523 100.0 0.5 10.2 18.6 27.3 6.2 9.1 28.0

12 years

years 79 100.0 0.0 0.9 0.0 24.1 4.1 9.9 60.9

13-15 years

161 100.0 0.2 15.9 0.0 27.7 5.9 17.1 33.3

16 years or more

126 100.0 0.8 9.0 20.0 35.1 11.1 4.1 19.8 142 100.0 0.7 11.3 51.0 21.0 4.2 3.6 8.2

White

Total

Less than 12

6580 100.0 0.6 7.6 27.5 34.2 9.1 8.0 13.2

12 years

years 409 100.0 0.4 0.2 0.0 36.0 8.5 15.9 39.0

13-15 years

2371 100.0 0.3 9.7 0.0 44.2 13.4 11.0 21.5

16 years or more

1476 100.0 0.5 7.2 19.3 44.5 10.1 9.8 8.6 2271 100.0 0.9 7.2 66.5 16.7 4.3 2.2 2.3

aExcludes individuals with prior service in the Armed Forces.
40

Table A,16 Distribution of Male Population 18-21 Years of Age With 12-15 Years

of School Completed, by Educational Expectation, Race and Survey

Week Activity: 1979

(Percentage distribution)

urvey week Total population

activity

Educational

expectation, rac

Total

number

(000 )

Total "Armed

percent

Civilian sectora

Forces

College

Em.loyed

Unemployed

Not in

labor

force

Ful - Part-'

time time

Total

Total 5582 100.0 7.4 38.2 43.4 4.3 4.1 2.6

12 years 1626 100.0 5.0 0.0 75.9 6.5 7.3 5.1

13-15 years 1132 100.0 9.7 15.5 62.4 5.2 4.6 2.6

16 years or more 2781 100.0 7.8 70.3 16.5 2.7 1.5 1.1

Black

Total 571 100.0 15.7 32.4 31.8 6.2 10.0 4.0

12 years 129 100.0 10.1 0.0 59.5 7.0 13.6 9.8

13-15 years 126 100.0 21.0 10.8 46.5 4.2 14.1 3.5

16 years or more 309 100.0 15.7 55.5 14.4 6.2 6.4 1.9

Hisparic

Total 243 100.0 10.4 35.6 38.8 3.7 4.9 6.6

12 years 56 100.0 6.2 0.0 76.1 2.5 8.4 6.8

13-15 years 59 100.0 17.9 18.9 36.1 10.0 10.3 6.8

16 years or more 128 100.0 8.7 59.2 23.5 1.3 0.8 6.5

White

Total 4770 100.0 6.2 39.0 45.0 4.1 3.4 2.2

12 years 1441 100.0 4.5 0.0 77.4 6.7 6.7 4.7

13-15 years 947 100.0 7.7 15.9 66.2 5.0 3.0 2.2

16 years or more 2345 100.0 6.7 72.9 16.4 2.3 0.9 0.7

aExcludes individuals with prior service in the Armed Forces.
41 Table A.17 Distribution of Female Population 18-21 Years of Age With 12-15

Years of School Completed, by Educational Expectation, Race and

Survey Week Activity: 1979

(Percentage distribution)

urvey week Total population

ctivity

Educational

expectation, rac

Total

number

( 000 )

Total

percent

Armed Civilian sect ?ra

Employed

Unemployed

Not in

labor

force

Forces

College Fulltime

Parttime

Total

Total 6000 100.0 0.7 36.2 36.7 9.3 6.8 10.2

12 years 1862 100.0 0.4 0.1 53.4 15.4 9.6 21.0

13-15 years 1574 100.0 0.7 22.4 47.0 10.1 10.1 9.7

16 years or more 2537 100.0 1.0 71.3 17.9 4.4 2.8 2.5

Black

Total 726 100.0 1.3 37.1 28.6 7.1 15.0 11.0

12 years 139 100.0 0.7 0.0 42.2 10.9 24.4 21.8

13-15 years 201 100.0 1.3 21.4 37.2 7.4 17.6 15.2

16 years or more 381 100.0 1.5 59.3 18.6 5.7 10.0 4.9

Hispanic

Total 267 100.0 0.9 36.5 35.1 9.9 3.7 14.0

12 years 51 100.0 0.6 0.0 53.9 16.4 6.2 22.9

13-15 years 102 100.0 1.0 24.8 38.2 11.8 5.1 19.2

16 years or more 113 100.0 1 0.9 63.8 24.1 5.3 1.5 4.5

White

Total 5008 100.0 0.7 36.1 38.0 9.6 5.8 9.9

12 years 1672 100.0 0.4 0.1 54.4 15.8 8.4 20.9

13-15 years 1270 100.0 0.5 22.4 49.3 10.4 9.3- 8.1

16 years or more 2042 100.0 0.9 73.9 17.4 4.2 1.6 2.0

a Excludes individuals with prior service in the Armed Forces.
42

Table A.18 Distribution of Male Population 18-21 Years of Age, by Health

Status, Race and Survey Week Activity: 1979

(Percentage distribution)

urvey week

activity

Health,

race

Tota population 1 Total -Total

number

( 000)

percent

firmed

Forces

Civilian sectora

High

school College Unemployed

Not in

labor

force

Full- Parttime time

Total

Total 8239 100.0 6.7 12.8 25.9 39.6 5.3 6.3 3.5

Does not affect

work 7843 100.0 6.6 12.6 26.2 40.0 5.3 6.2 3.2

Affects work 396 100.0 7.0 17.9 20.0 32.5 5.0 8.0 9.7

Black

. Total 1088 100.0 9.7 18.1 17.0 29.5 7.3 11.4 7.0

Does not affect

work 1029 100.0 9.9 17.3 17.1 30.4 7.0 11.2 6.9

Affects work 59 100.0 6.8 31.4 14.0 14.0 11.4 13.9 8.5

Hispanic

t . Total 495 100.0 7.6 15.7 17.5 39.3 4.6 7.5 7.8

Does not affect

work 471 100.0 7.6 16.0 17.5 39.6 4.5 7.5 7.3

Affects work 24 100.0 6.5 9.7 16.8 34.3 5.2 8.8 18.8

White

t Total 6658 100.0 6.1 11.7 28.0 41.3 5.0 5.3 2.6

Does not affect

work 6345 100.0 6.0 11.5 28.3 41.5 5.0 5.3 2.3

Affects work 313 100.0 7.1 16.0 21.4 a,.8 3.7 6.8 9.3

a Excludes individuals with prior service in the Armed Forces.
Table A.19 Dist.-lklutii4n Fema.:e ;.:Irs of Age, by Hea

Status, W.1,.:e :rd A.; 1W9

urvey week------

activity

Health,

race

TOt5I-TI:.,Tir--4-ii,,,,...T

numbe,te..ent

( 00G

i-arces

Tut 1 population

Civilian sectors

Higb

school College

Employed

Unemployed

Not in

labor

force

Fulltime

Parttime

Total

Total 8285 100.0 0.6 8.8 26.2 31.7 8.5 9.3 15.0

Does not affect

work 7488 100.0 0.6 9.2 27.6 32.6 8.1 9.3 12.7

Affects work 798 100.0 0.7 4.9 13.8 22.6 11.4 9.8 36.8

Black

Total 1184 100.0 0.8 14.6 22.7 19.5 5.8 17.0 19.6

Does not affect

work 1085 100.0 0.7 14.9 23.9 20.5 5.4 16.8 17,8

Affects work 99 100.0 2.2 11.5 10.5 8.7 9.9 18.6 38.7

Hispanic

Total 523 J 100.0 0.5 10.2 18.6 27.3 6.2 9.1 28.0

Does not affect

work 492 100.0 0.5 9.7 19.4 28.5 6.5 9.3 26.1

Affects work 31 100.0 0.0 17.9 6.2 8.0 2.8 6.8 58.3

White

Total 6580 100.0 0.6 7.6 27.5 34.2 9.1 8.0 13.2

Does not affect

work 5912 100.0 0.6 8.1 28.9 35.2 8.8 7.9 10.6

Affects work 668 100.0 0.5 3.3 14.7 25.4 12.0 8.7 35.5

aExcludes individuals with prior service in the Armed Forces.
44

Table A.20 Distribution of Male Population 18-21 Years of Age With 12-15

Years of School, by Health Status, Race and Survey Activity: 1979

(Percentage distribution)

'urvey week Total oulation

activity

Health,

race

Tota

number

( 000 )

Tota

percent

Armed ivi Ian sector

Forces Emil() ed

Unemployed

Not in

labor

force

College Fu - time

Parttime

Total

Total 5582 100.0 7.4 38.2 43.4 4.3 4.1 2.6

Does not affect,

work 5355 100.0 7.3 33.4 43.5 4.4 4.1 2.4

Affects work 227 100.0 8.3 34.9 41.9 2.8 4.8 7.3

Black

Total 571 100.0 15.7 32.4 31.8 6.2 10.0 4.0

Does not affect

work 549 100.0 15.6 32.1 32.3 6.1 10.2 3.7 I Affects work 22 100.0 18.3 37.9 21.0 8.4 3.2 11.3

Hispanic

Total 243 100.0 10.4 35.6 38.8 3.7 4.9 6.6

Does not affect

work 233 100.0 10.8 35.4 38.4 3.8 5.1 6.5

Affects work 10 100.0 0.0 42.3 48.5 0.0 0.0 9.2

White

Total 4770 100.0 6.2 39.0 45.0 4.1 3.4 2.2

Does not affect

work 4574 100.0 6.2 39.3 45.1 4.2 3.3 2.0

Affects work 196 100.0 7.6 34.2 43.9 2.4 5.2 6.8

aExcludes individuals with prior service in the Armed irorces.
45

Table A.. 21 Distribution of Female Population 18-21 Years of Age With 12-15

Years of School, by Health Status, Race Survey Week Activi )979

(Percentage distribution)

urvey week Total population

activity

Health,

race

Total

number

( 000 )

Total

percent

Armed Civilian sectora

Farces

College

Employed

Unemployed

Not in

labor

force

Fulltime 1 Parttime

Total

Total 6000 100.0 0.7 36.2 36.7 9.3 6.8 10.2

Does not affect

work 5465 100.0 0.7 37.8 37.3 8.8 6.7 8.8

Affects work 535 100.0 1.0 20.6 30.5 14.7 8.4 24.8

Black

Total 726 100.0 1.3 37.1 28.6 7.1 15.0 11.0

Does not affect

work 668 100.0 1.0 38.8 29.8 6.3 14.7 9.5

Affects work 58 100.0 3.8 18.1 14.9 17.0 18.0 28.2

Hispanic

Total 267 100.0 0.9 36.5 35.1 9.9 3.7 14.0

Does not affect

work 259 100.0 0.9 36.9 35.2 10.2 3.9 13.0

Affects work 8 100.0 0.0 23.9 30.8 0.0 0.0 45.2

I--

White

Total 5008 100.0 0.7 36.1 38.0 9.6 5.8 9.9

Does net affect

work 4539 100.0 0.7 37.7 38.6 9.1 5.6 8.4

Affects work 469 100.0 0.7 20.9 32.4 14.6 7.4 24.0

a Excludes individuals with prior service in the Armed Forces.

C5
46

Table A.22 Proportion Married Among Youth 18-21 Years of Age, by Type Universe,

Race, Sex and Survey Week Activity: 1979

(In percent)

Survey week Total population ' ctivity

Sex, race an.

universe

Total Armed

Forces

Civilian sectora

High

school

Emo Qved

Unemployed

Not in

labor

force

College Fulltime

Parttime ,,type

Total

Total

Males 10 18 a 1 17 8 9 7 Females 23 25 4 2 25 37 33 53

12 -15 ears of

schoolMales Ma 8 17 0 1 14 6 7 4

Females 21 26 0 2 L 23 39 29 55

Black

Total

--Pales 5 15 1 0 9 0 2 4

Females 12 16 1 a 18 26 16 19

12-15 years of

school

Riles 5 13 0 0 8 0 2 0

Females 12 16 0 a 16 28 22 19

Hispanic

Total

--Riles 12 11 1 1 20 9 20 19

Females 29 26 2 2 31 32 40 52

12 -15 ears of

school

--Mires 7 13 0 1 11 20 7 0

Females 21 26 0 2 24 28 42 52

White

Total

Males 10 19 0 2 18 10 11 6

Females 25 27 5 2 26 39 39 63

12 -15 ears of

school

Males 9 19 0 2 14 6 9 5 Females 22 28 0 2 24 40 31 61 aExcludes individuals with prior service in the Armed Forces.
47

Table A.23 Mean Rotter and Knowledge of World of Work (KOWW) Scores Among Youth

18-21 Years of Age, by Sex, Race and ''.urvey Week Activity: 1979

Survey week

activity

Sex, race

Rotter, KOWW

Total population

Total Armed Civi Ian sector.

Forces High

school College(

1' Employed

Unemployed

Not in

labor

force

Full-I PartI time time

Total

Males

Rotter 8.13 8.31 8.30 7.41 8.30 8.54 8.70 9.00

KOWW 6.82 6.87 5.95 7.72 6.77 6.56 5.85 5.79

Females

Rotter 8.27 7.88 8.46 7.42 8.28 8.49 9.16 9.00

KOWW 6.55 7.29 5.87 7.21 6.64 6.83 6.00 5.71

Black

Males

Rotter 8.53 8.60 8.17 7.86 8.65 8.41 9.35 9.33

KOWW 5.31 6.02 4.48 6.63 5.25 4.53 5.02 4.68

Females

Rotter 8.82 9.51 8.51 8.03 8.98 9.19 9.15 9.33 KOWW 5.40 3.63 4.86 6.31 5.74 5.45 5.02 4.67

Hispanic

Males

Rotter 8.72 8.74 8.81 7.93 8.99 8.68 8.74 8.94

KOWW 5.63 5.85 4.90 6.99 5.54 4.51 4.82 5.72

Females

Rotter 8.86 8.31 9.24 7.67 8.78 8.07 9.84 9.48

KOWW 5.36 7.05 4.41 6.45 5.82 6.08 4.86 4.49

White

Males

Rotter 8.03 8.20 8.28 7.34 8.21 8.56 8.47 8.87

KOWW 7.15 7.19 6.43 7.87 7.03 7.19 6.24 6.27

Females

Rotter 8.13 7.45 8.33 7.32 8.17 8.43 9.10 8.82

KOWW 6.85 7.48 6.38 7.39 6.79 7.03 6.47 6.19

a Excludes individuals with prior service in the Armed Forces.

C7'
48

Table A.24 Comparison of Selected Characteristics of Male Youth 18-21 Years

of Age with 12-15 Years of School Completed in Armed Forces and

At Work Full-Time in Civilian Job, by Characteristic, Survey Week

Activity and Race: 1979

(Percentage distribution)

ace, survey week Total Black Hispanic White

activity

Characteristic

Armed

Forces

Employed

full-time

Armed

Forces

Employed

full-time

Armed

Forces

Employed

full-time

Armed

Forces

Employed

full-time

Total number (000) 411 2423 90 182 25 94 296 2147

Education of parent 100 100 100 100 100 100 100 100

Less than 12 years 19 17 '7 43 42 57 1F, 13

12 years 47 55 45 42 33 29 48 57

13 years or more 34 28 28 1 15 25 14 37 30

Occusation of pammfbc 100 100 100 100 100 100 100 100

Professional or

managerial 25 26 13 19 26 16 29 26

Sales, clerical 12 13 9 3 5 8 13 14

Blue collar 50 50 56 57 58 47 48 49

Service 11 7 21 19 11 16 9 6

Educational expectations 100 100 100 100 100 100 100 100

12 years 20 51 15 43 15 46 22 52

13-15 years 27 29, 30 33 42 22 25 29

16 years or more 53 19 55 24 42 32 53 18

Knowledge of world of

work score 100 100 100 100 100 100 100 100

0-5 18 17 33 43 28 33 12 14

6 11 15 12 18 24 14 9 14

7 22 24 20 22 32 19 22 24

8-9 49 45 34 16 16 35 56 48

Marital status 100 100 100 100 100 100 100 100

Married 17 14 13 8 13 11 19 14

Never married 83 86 R7 92 87 89 81 86
49

Table A.24 (males) continued

ace, survey wee

activity

Characteristic

Total B ack Hispanic White

Armed

orces Employed

full-time

Armed

orces Employed

full-time

Armed

orces Employedfull-time

Armed

orces Employedfull-time

Internality (Rotter)

score 100 106 100 100 100 100 100 100

4-8 55 57 41 50 44 55 60 58

9-16 45 43 59 50 56 45 40 42

Health status 100 100 100 100 100 100 100 100

Does not affect

work 95 96 96 97 100 95 95 96

Affects work 5 4 4 3 0 5 5 4

aYears of school completed by parent in the household with the highest educational

attainment.

bOne-digit occupation group of father's job. If father is absent from household and

mother is present, then occupation group of mother's job.

c Excludes employment in farming
50

Table A.25 Comparison of Selected Characteristics of Female Youth 18-21 Years

of Age with 12-15 Years of School Completed In Armed Forces and At

Work Full Time In Civilian Job, by Characteristic, Survey Week

Activity and Race: 1979

(Percentage distribution)

ace, survey week Total Black Hispanic White

activity

Characteristic

Armed Employed

Forces full-time

Armed

Forces

Employed

full-time

Armed

Forces

Employed

full-time

Armed

Forces

Employed

full-time

Total number (000) 45 2203 9 207 2 94 33 1902

Education of parenta 100 100 100 f 100 100 100 100 100

Less than 12 years 30 21 30 39 50 55 27 17

12 years 43 51 50 42 50 29 39 53

13 years or more 27 28 20 19 0 16 33 29

Occupation of paren 100 100 100 100 100 100 100 100

Professional or

managerial 20 23 14 16 0 24 22 23

Sales, clerical 10 16 14 11 0 5 13 17

Blue collar 53 48 29 52 100 56 56 47

Service 15 9 43 20 0 9 9 8

Educational expectations 100 100 100 100 100 100 100 100

Less than 12 years

12 years

--18--45

--

10

--28

--0--30

--

21 --48

13-15 years 24 34 30 37 50 41 21 33

16 years or more 58 21 60 35 50 29 58 19

Knowledge of world of

work score 100 100 100 100 100 100 100 100

0-5 9 20 22 44 0 31 6 17

6 18 14 11 12 0 22 21 14

7 20 26 22 22 50 26 21 27

8-9 52 39 44 22 50 21 53 42

Marital status 100 100 100 100 100 100 100 100

Married 26 23 16 16 26 24 28 24

Never married 74 77 84 84 74 76 72 76
51 Table A.25 (females) continued

rRace, survey week

activity

Characteristic

Total Black Hispanic White

Armed

orces Employedfull-time

Armed

Forces

Employed

full-time

Armed

Forces

Employed

full-time

Armed

Forces

Employed

full-time

Internality (Rotter)

score 100 100 100 100 100 100 100 100

4-8 64 57 44 47 50 51 73 58

9-16 36 43 56 53 50 49 27 42

Health status 100 100 100 100 100 100 100 100

Does not affect

work 89 93 78 96 100 98 91 92

Affects work 11 7 22 4 0 2 9 8

aYears of school completed by parent in the household with the highest educational

attainment.

b One-digit occupation group of father's job. If father is absent from household and

mother is present, then occupation group of mother's job.

c Excludes employment in farming
CHAPTER 3

QUALITY OF EMPLOYMENT AND JOB SATISFACTION OF YOUTH IN THE ARMED

FORCES

A comparison of the non-monatary characteristics of jobs in the

military and the civilian sector may indicate the factors affecting

the decision to choose employment in one of the services versus the

civilian job market, and may help to explain post enlistment behavior

in the form of attrition and reenlistment.

Studies conducted in support of the President's Commission on the

All Volunteer Armed Force (Gates Commission) focused on the monetary

differential between the military and civilian sector, in an effort to

forecast enlistment supply.

A common theme of the several studies was the ,.asic notion expressed

by Fechter as follows.

"Our model first assumes that the individual chooses

the set of activities that provides him with the

highest net pecuniary and non-pecuniary benefits.

We further assume that, in principle, the individual

can evaluate non-pecuniary cost and benefits in

pecuniary terms. This implies, for example, that

the individual is able to stipulate the number of

collars of additional pay, or pecuniary benefits,

that he would require to offset the non-pecuniary

cost associated with what he thinks are distasteful

conditions of service life, i.e., that there is

some finite rate of exchange between pecuniary and

non-pecuniary factors."1

Fechter went on to define non-pecuniary costs and benefits as "the

satisfactions or dissatisfactions derived from the work environment."2

1.

Alan Fechter, "Impact of Pay and Draft Policy on Army Enlistment

Behavior" in Studies Prepared for The President's Commission on an All-Volunteer Armed Force, U.S.G.P.O. 1970, p. II-3-2-.

2

'Ibid. p.

52
53

The early predictions by the Gates Commission based mostly on

econometric models whose basic approach was similar to that described

by Fechter must be judged as reasonable, in view of the history of the

volunteer force. The military participation rates of qualified youth

discussed in Chapter 2 are relatively favorable testimonials to the

efficacy of the "comparable military wage " espoused by the Commission.

However, there are some disturbing aspects of the volunteer force

that were not predicted, and which an examination of perception of

job quality may help illuminate. The first is the high attrition rate

(approximately one-third of accessions fail to complete the initial

term of service3). Second, the services are experiencing difficulty in

recruiting a combined strength of two million even though the Gates

Commission had forecast high feasibility of recruiting 2.5 - 3 million.

Third, the Commission did not appear to anticipate the degree of

recruiting difficulty faced by the Army and Marine Corps, especially

in the combat arms. That is, differing degrees of recruiting difficulty

occur even though all services pay the same wages for individuals of a

given rank and years of service. Also, within a given service, such as

the Army, some jobs are more easily filled (technical and medical

positions) than others (combat arms), despite equal pay and opportunity

for advancement, at least during the span of the first term of service.

One possible explanation for the failure to expect higher attrition

rates and much greater recruiting difficulties for the ground combat

arms is the nature of the econometric models used for prediction. For

3

Office of the Assistant Secretary of Defense for Manpower,

Reserve Affairs, and Logistics, America's Volunteers, A Report on the

All-Volunteer Armed Force, p. 65.
54

example, in Fechter's model the wage that would induce an individual

to join the Service, is based upon his or her estimation of both the

pecuniary and nonpecuniary aspects of the military job compared to his

civilian life alternatives. Inherent in such an assumption is the

notion that an individual's estimate of the nonpecuniary job aspects

is reasonably stable. If so, then the reservation wage is a good

proxy of such estimates and provides a reasonably good basis for

predicting not only those who join, but also those who will remain.

If, on the other hand, post enlistment reality turnout to be much worse than

expected, serious organizational dysfunctions such 's high attrition

rates might be predicted. Further, greater dissatisfaction among

service personnel relative to their civilian counterparts in the Tabor

market can be expected to reduce the propensity for military service

in the upcoming cohort, given an assumption of at least a degree of

inter-cohort communication. "Satisfactions and dissatisfactions derived

from the work environment" may greatly assist in accounting for ,high

attrition rates, lower than expected pl,c-.0;"fies for military service,

and highly differentiated recruiting shcc.n,os among the four services,

as well as differences in recruiti i for colain jobs within a service.

The primary purpose of this ch;pter wily be to compare measures of

the nonmonetary aspects of military ead cid ilan jobs held by youth, as

reported by the job incumbents themL.0,.,, and to examine tt.,e nonmonetary

differentials in light of differences in reported pay of ime two groups.

A secondary purpose will be 'o compare the reported pay and all,;,ances

of the firmed Forces sample to their respective entitlements. -le reason

for such a comparison is to determine if it is the ".e:ual pay" or

"perceived pay" which most affects pay satisfaction, ,once the military
55

pay and allowance system is much more complex than the hourly wage

rate of the majority of the civilian sample, and may not be fully

understood by the service member.

Method

For reasons similar to those outlined in Chapter 2, the main

population subgroup selected for comG:rison to service were the nonveteran, noncollege graduate, 18-21 year old, employed full time

(thirty-five hours or more per week 1)

The interview schedule drew mt.,ure;of the job and work environment from two separate and well established lines of research. The

first grew out of the effort to diccuver how various job aspects

affect productivity, absenteei:x, and turnover. The second was

designed to measure the quality of clrloyment in American life. There

were seventeen items in all and a glop,' job satisfaction measure.

Both lines of research provided for a cvibination of several items into

summated scales, designed to report combined job aspects.

Before the differences Intwelti the two groups were examined, the

impact of several variable; on the global job satisfaction measure

was analyzed to ensure that Pny differences could not be attirbuted to

differences in demographic composition rather than to differences in

the work environment of the two populations. The demographic comparison

in Chapter 2 pointed out extreme differences in composition by gender,

differences with respect to race, and minor differences with respect

to education. Table 3.1 presents the mean job satisfaction measure

4

Also, as in Chapter 2, those enrolled in college on a full

time basis were not included in full time employed aggregate in order

to focus on those whose full time employment is, most likely, their

primary endeavor.
56

Table 3.1 Means of the Global Job Satisfaction Measure of Youth

Ages 18-21, By Education, Race and Sex: 1979

Male Female

Black' Hispanic Total Total White Black Hispanic Total White

High scJool

graduatesa

Mean score 3.14 3.10 3.12 3.02 3.02 3.19 3.20 3.05 3.21

Number 2588 1467 1042 273 152 1521 1082 288 151

Standard

deviation .79 .78 .79 .74 .78 .80 .80 .73 .71

High school

dropcats

Mean score 3.09 3.08 3.11 2.86 3.10 3.12 3.15 2.98 3.02

Number 1151 783 449 177 157 368 229 70 69

Standard

deviation .78 .78 .77 .88 .73 .77 .77 .80 .78

Total

Mean score 3.13 3.09 3.11 2.96 3.06 3.17 3.19 3.03 3.15

Number 4139 2250 1491 450 309 1889 1311 358 220

Standard

deviation .79 .78 .78 .80 .75 .79 .80 .75 .73

aOnly graduates who received diplomas are included in this category.
57

by category of the race-sex-education array. Education did not display

a great deal of impact, but sex and, to a much lesser extent race,

appeared to be important factors. Thus, subsequent comparisons will

control for race and sex. 5

Comparison of Job Aspects for Males

Table 3.2 presents the mean satisfaction with specific characteristics of jobs. It should be noted that the first seven items involved

a five point scale, and the last eleven items used a four point scale.

Table 3.3 presents the t values for the differences between the means

of the military and civilian groups. As can be seen from Table 3.2,

servicemen are lower on every measure of job satisfaction except job

security. The fact that those in civilian employment can change jobs

if they are dissatisfied and have an alternative would lead to the

expectation that they might be somewhat higher on measures of job

aspects. Nevertheless, the highly consistent lower evaluations given

their jobs by military males is surprisjng in view of the all volunteer

force policy. If the Armed Forces is to compete in the market place,

one would expect a more even comparison with the civilian labor market,

at least on highly advertised characteristics of military employment

such as a "chance to learn a valuable skill."

Difference patterns for minority males are somewhat more favorable

than for white, but minority servicemen are still below their civilian

counterparts in viewing many aspects of their jobs. Black

5 Education could be an important factor, especially in interaction with race; however, time constraints did not permit a more

extensive analysis. Future effort will consider education as well

as race, sex, and labor market status.
58

Table 3.2 Mean Satisfaction Score In Various Aspects Job Among Military

Personnel and Civilians Employed Full -Time. les 18-21 Years of

Age, by Survey Week Activity, Sex, Race an' qct of Job: 1979

Sex, race and

survey week

Aspect

Armed Forces Civilian sector

activity

in job

Total White Black Hispanic Total White Black Hispanic

Skill variety 2.85 2.95 2.47 2.83 3.20 3.29 2.67 2.93

Task identity 3.92 3.77 3.57 3.58 3.82 3.87 3.63 3.46

Task significance 3.38 3.41 3.22 3.46 3.42 3.49 3.06 3.12

Autonomy 2.87 2.95 2.60 2.68 3.32 3.39 2.88 2.93

Feedback 3.64 3.74 3.27 3,59 3.85 3.90 3.61 3.60

Dealing with others 3.53 3.58 3.36 3.52 3.54 3.60 3.25 3.11

Friendship opportunities 3.51 3.56 3.35 3.38 3.52 3.56 3.39 3.17

Job challenge 2.60 2.68 2.34 2.37 30.1 3.02 2.86 3.01

Comfort 2.43 2.38 2.60 2.45 2.92 2.91 2.98 2.97

Learn valuable skill 2.82 2.87 2.58 2.88 3.08 3.09 2.98 3.08

Safety 2.30 2.30 2.40 2.07 2.52 2.49 2.61 2.56

Healthful condition 2.80 2.80 2.82 2.79 2.90 2.90 2.87 3.05

Pay 2.04 2.05 2.00 2.10 .297 3.00 2.86 2.77

Job security 3.37 3.42 3.18 3.28 3.25 3.29 2.92 3.13

Relation with co-workers 3.39 3.46 3.25 3.11 3.66 3.67 3.61 3.60

Competent supervisors 3.27 3.28 3.20 3.42 3.46 3.47 3.41 3.49

Promotion chances 2.87 2.88 2.81 2.97 2.94 2.96 2.84 2.83

Global job satisfaction 2.77 2.79 2.68 2.82 3.18 3.20 1.03 3.11
59

Table 3.3 T-Values for Differences Between Means of Youth Serving in the

Armed Forces and Employed Full-Time in the Civilian Sector

Males Females

Variety -5.77 -1.46

Task identity -1.67 +0.94

Task significance -0.63 -2.72

Autonomy -7.58 -3.52

Feedback -3.77 0.00

Dealing with others -0.17 +3.34

Friendship opportunities -0.18 -4.19

Job challenge -8.39 -5.94

Comfort -10.02 -11.10

Valuable skill -4.76 -0.62

Safety -4.00 -4.82

Health -1.85 -2.32

Pay -20.49 -6.17

Job security +3.03 +5.94

Relations with co-workers 7.84 -2.46

Competent supervisor -4.42 -1.66

Promotion chances -1.41 +5.99

Global job satisfaction -9.53 -4.74
60

males in the service are higher on "Job Security", "Task Significance",

and "Dealing with Others";and are close on "Task Identity", "Friendship Opportunities", and "Promotion Chances." Hispanic males display

a similar but slightly more favorable difference pattern.6

Lower perceptions of Job Challenge and Autonomy may simply be a function of the necessarily authoritarian nature of military organizations. Certainly, the Armed Forces Population, which of course, includes Army and Marine Corps combat units, cannot be expected to com- pare favorably with civilian employers on items such as Job Comfort

6In order to discern which items had the closest relationship to the global job satisfaction measure, interitem correlations were calculated (Appendix Table B.1). Also, to ensure the aggregate correlation

matrix did not mask differences due to sector or sex, intercorrelations

for five separate sub-populations were run--total, males only, females

only, civilian group only, and military group only (Table B.2).

There are some differences in one or two items between subgroups.

However, the job satisfaction-single item correlation structure is

reasonably stable for both sexes and both labor market sectors. As

can be seen from Table B.1, the single items having the highest correlations with the global job satisfaction measure for the male population

are Job Challenge* (r = .50), Job Significance (r = .43), Job Comfort*

(r = .39), Learn Valuable Skill (r = .38), Skill Variety* (r = .36), Promotion Opportunity (r = .35), Pay* (r = .32), and Autonomy * (r = .30).

Items with an asterisk represent the five items where the differences

between the servicemen and civilians are the greatest. In other words, five of the eight item most related to the global jot satisfaction

measure are the items with the greatest difference between the two groups.
61

which was measured by the perceptions of the pleasantness of physical

surroundings. However, the rather large perceived pay differential is

surprising. 7 The differences in pay satisfaction between the military

and civilian groups ,,fas not only the greatest difference for males,

but was almost twice the difference as any other item. It also was

the second greatest difference for females; Job Comfort was first.

Further discussion of pay perceptions will be included in the monetary

comparison section later in this chapter.

Comparison of Job Aspects for Females

Females in the Armed Forces are generally less satisfied with

their jobs than their civilian counterparts. However, these women

see more favorable job characteristics than male military personnel.

As Table 3.4 indicates, service women saw a significantly greater

degree of presence of three items compared to the civilian females-- "Dealing with Others," "Job Security," and "Promotion Chances."8

Whereas men serving in the Armed Forces saw their opportunity

for dealing with others and for friendships in almost equal terms

with the civilians employed full time females in the services had a

fundamentally different perspective. Perhaps, reflecting the highly

interactive nature of the Armed Forces and the high male percentage

7 The actual pay item was simply, "The pay is good." Respondents

were asked to answer on a four point scale. In further discussion, the

pay item will be referred to frequently as pay satisfaction.

8

Again, the items with the highest correlation with the jou satisfaction measure, and with the greatest difference for the women, were

selected for closer examination. The three items, also included in the

listing for males, (soe Tables B.1 and B.2), were Job Challenge, Job

Comfort, and Pay.. As pointed out in the discussion on males, a lower

rating by military females compared to civilians on Job Challenge and

Job Comfort is not surprising. But a major difference in pay perceptions

is surprising and will be further discussed in the monetary section.
62

Table 3.4 Mean Satisfaction Score In Various Aspects of Job Among Military

Personnel and Civilians Employed Full-Time, Females 18-21 Years of

Age, by Survey Week Activity, Sex, Race and Aspect of Job: 1979

Sex, race and

survey week

Aspect

Armed Forces Civilian sector

activity

in job

Total White Black Hispanic Total White Black Hispanic

Skill variety 3.01 3.12 2.48 3.44 3.12 3.17 2.76 2.83

Task identity 3.88 4.00 3.29 4.24 3.81 3.86 3.61 3.35

Task significance 3.19 3,19 3.0? 3.86 3.42 3.45 3.34 3.15

Autonomy 2.87 2.89 2.73 3.11 3.14 3.19 2.84 2.84

Feedback 3.84 3.80 3.99 3.74 3.84 3.88 3.60 3.56

Dealing with others 3.93 3.89 4.15 3.62 3.69 3.74 3.31 3.38

Friendship opportunities 3.17 3.23 2.80 3.61 3.48 3.52 3.24 3.32

Job challenge 2.76 2.77 2.65 3.02 3.07 3.09 2.82 2.96

Comfort 2.59 2.68 2.18 2.72 3.25 3.28 3.19 3.11

Learn valuable skill 3.09 3.10 3.06 3.05 3.13 3.15 2.98 3.07

Safety 3.04 3.06 2.97 2.94 3.36 3.35 3.47 3.32

Healthful condition 3.25 3.33 3.00 2.91 3.40 3.40 3.36 3.40

Pay 2.49 2.57 2.14 2.62 2.84 2.87 2.64 2.74

Job security 3.55 3.58 3.47 3.40 3.25 3.28 3.08 3.07

Relation with co-workers 3.54 3.61 3.27 3.54 3.64 3.65 3.49 3.63

Competent supervisors 3.39 3.39 3.47 3.19 3.48 3.48 3.48 3.50

Promotion chances 3.08 3.07 3.06 3.19 2.71 2.71 2.76 2.59

Global job satisfaction 2.98 3.09 2.53 3.15 3.25 3.28 3.10 3.12

Cr)

C ti
63

composition. military women saw significantly greater job requirements

for dealing with others than either Armed Forces males or civilian

females, but saw significantly fewer opportunities for friendships.

It may well be that the small percentage of females in the Armed

Forces basically feel, at least at times, somewhat isolated within

the highly male dominated organization. The perceptions of black

servicewomen were even more pronounced in that they saw greater

requirements for dealing with others on the job than white enlisted

women, but saw even less friendship opportunities. Curiously, Hispanic

females in the Armed Forces had higher perceptions of both interpersonal

dealings and opportunities for friendship than did their civilian

counterparts.

Another interesting aspect of Table 3.3 is the rather large

positive difference in perceived promotion opportunity for enlisted

females compared to women employed full time in the civilian sector

and servicemen. The Armed Forces may, indeed, be in the forefront

of offering equal opportunity for women.

Hackman and Oldham9 developed a method of combining the intrinsic

aspects of jobs into an equation that taps the motivating potential

of the job itself. The equation combines the first five job instrinsic

items. As can be seen from Table 3.5, the means for Armed Forces

personnel (both male and female) are significantly lower than the

respective means for civlians employed full time. Differences are

much less for females, however, with Hispanic females in the military

9 R. J. Hackman and G. R. Oldham. "The Job Diagnostic Survey:

An Instrument for the Diagnosis of Jobs and the E\Aluation of Job

Redesign Projects' Technical Report No. 4, Contract No. N00014-67A0097-0026, NR 170-744. USG.P.O. 1974.
64

Table 3.5 Mean Aggregate Dimensions of Jlb Satisfaction Among Youth 18-21

Years of Age In t.,e Armed Forces and Employed Full-Time,in

Civilian Jobs, by Type of Measure, Race and Sex: 1979

Sector and sex

Type Male. Female

,of measure,

race Armed Forces Civilian Armed Forces 1 Civilian

Total

Motivating potential 34.64 44.48 37.01 41.60

Quality of employment

job facet 3.03 3.31 3.15 3.29

Environment 2.55 2.71 3.15 3.38

Black . Motivating potential 26.24 32.44 31.92 33.09

Quality of employment

job facet 2.89 3.18 2.97 3.14

Environment 2.61 2.74 2.99 3.42

Hispanic

Motivating potential 31.65 33.44 44.86 31.54

Quality of employment

job facet 2.94 3.20 3.23 3.20

Environment 2.43 2.96 2.93 3.36

White

Motivating potential 37.25 46.93 37.74 43.24

Qua'ily of employment

job facet 3.08 3.34 3.19 3.32

Environment 2.55 2.70 3.20 3.38
65

higher than their civilian counterparts. For civilian females employed

part time the mean was 31.88, lower than for women in the services.10 Thus,

to the extent that the Hackman and Oldham equation taps the intrinsically

motivating aspects of jobs, and to the extent that the items measured

in the NLS instrument accurately represent Hackman and Oldham's factors,

it must be concluded that Armed Forces jobs are inherently less motivating

than jobs found in the civilian labor market, especially for males.

The summated scale from the second line of research involved the

Quality of Employment job facet scale of Quinn and Staines.11 Whereas

the Motivating Potential scale involved only job intrinsic items, the

quality of employment scale has a mixture of intrinsic factors with

other factors such as comfort, job security, and competency of supervisor. However, as can be seen in Table 3.5, the results are about

the same as for the Motivating Potential scale. The military population is significantly lower.

The final scale was simply the combination of two items having

to do with the work environment. The environmental factor combined

10 The significantly lower measures on motivating potential for

military personnel led to the comparison to those who are employed

only part time, with the expectation that the part time employed,

on the average, would have fewer motivating items contained

in the Hackman and Oldham equation than either their full time

employed or service counter parts. Indeed, the part time employed

males (males not enrolled in college and working less than 35 hours

per week) scored lower on the motivating potential (37.7) compared

to the full time employed; but, surprisingly, were higher than

servicemen. The same was not true for females.

11 R. P. Quinn and G. L. Staines. The 1977 Quality of Employment Survey. (Ann Arbor: Inst. of Social Research, 1979.)
66

perceptions of danger and degree of unhealthful conditions on the job.

Not surprisingly, service personnel came out lower for all sex race

groups. They saw greater danger and more unhealthful conditions associated with their jobs than did those in the civilian sector.

Comparison Across Services

The previous measures clearly indicate that Armed For-..es jobs are

less desirable on nonpecuniary measures than are jobs held by civilians

employed full time. It is quite plausible that the degree of difference

between the nonpecuniary aspects of military and civilian jobs was not

anticipated by m?ny enlistees, and may be a major factor in the high

attrition rates for military personnel.

The fact the military jobs are less desirable, on the average, does

not mean there are not highly desirable jobs available in the Armed

Forces. Indeed, the question arises as to tie role of nonpecuniary

job aspects in recruiting and retention differences among the Services.

The expectation is that controlling for all other factors, if a group

of jobs pay the same rate, the jobs with greater nonpecuniary satisfactions will be more attractive. It was hypothesized that services

known for a greater number of "tough" jobs, that is, jobs requiring

little or no applicable to civilian life, and with a great number

of associated disamenities (Army and Marine Corps) would be significantly

lower in job satisfaction than the two, more technical services (Navy and

Air Force). 12

Further; it was suggested that differences would be

12

It should be emphasized that all services have jobs varying

in associate.; disamenities and degree of skill applicability to

civilian life. (The Air Force has remote radar sites and the Navy,

of course, has a fairly large number at sea at any given time.)

However, it is suggested that the Marine Corps have a higher proportion of such jobs.
67

significant for men, but not necessarily for women due to the policy

of excluding women from combat units where disamenities are expected

to be greater.

The services were compared using the global job satisfaction

measure as a summary of all job aspects. In order to control for

possible differences in service conpositiwi, the data are presented

by education and sex. As can be seen from the data in Table 3.5

the results were basically as expected.

Further, since pay is reasonably equal acros. s ices, then the

branches with a higher perrntige of tough jobs shrit :It only manifest

lower overall job satisfacticn (4hich, according to tw.1 in Table

3.6, they do), but should attra fewer highly qua.i:!E youth. To

perform a rather quick check of chls hypothesis, the four S?vices

were compared on four dimensions in Chapter 2 to examine differences

between military personnel and those civilians employed full time. The

results in Table 3.7 are not only in the hypothesized direction, but

suggest the danger in examining the Armed Forces only as an aggregate.

A Comparison of Monetary Factors

As indicated Perli.A., the fact that the differential in pay satisfaction between the military and civilian was the largest difference

for male, and second largest for females was surprising. Further

analyst.: 1,..s conducJd in an effort to investigate four questions.

1. 'Could the differences be attributed to real differences in

pay?

Might the differences be a result of underestina ed on the part of the military personnel, since the military pry

and allowance system is complex?
68

Table 3.6 Mean Global Job Satisfaction Score Among You 18-21 Years

of Age, by Branch of Service, Sector of Empl..ment, Hours

Worked Per Week, Educational Attainment and 1,cx: 1979

Education and

Sector, sex branch and

hours per

week

Total ti school diploma graduate

Male Female Male Female

Armed Forces

Army 2.5 2.75 2.68 2.78

Marine Corps 2.V2 2.75 2.76 2.74

Navy 2.82 3.37 2.88 3.:2

Air Force 2.92 3.J1 2.90 2.88

Civilian

Employed full-time 3.18 3.&) 3.19 3.27
69

Table 3.7 Selected Characteristics of Youth 18-21 Years of Age in the

Armed Forces, by Branch of Service and Characteristic: 1979

Branch

Characteristic

Army Navy Air Force Marine Corps

Educational attainment

Percent high school

diploma graduate 69 79 95 74

Knowledge of world

of work score

0-3 30 13 9 23

7-9 32 56 54 45

Education of parent

Less than 12 vears 28 21 16 22

12 years or more 25 36 37 26

Educational expectations

Percent

college gradua*e 37 49 63 42
70

3. Could pay differences, either real or perceived, largely

account for expressed differences in job satisfaction?

4. Conversely, might job satisfaction largely account for

differences in pay perceptions?

To determine average monthly pay for those employ-d full time

in the civilian sector, the prodwt of each respondent's reported

hourly wage and usual number of hours worked per week was multiplied by

4.33 weeks per month. This calculated average will be approximate since

overtime pay rates were not considered and some respondents worked over- time on a regular basis. At the same time the estimated monthly pay

of the civilian labor market jobs does not include reductions for spells

of unemployment, strikes, layoffs, etc. Thus, the civilian estimate

represents a view of the monthly pay of those employed full time for

the entire year exclusive of overtime premiums. Also excluded are

certain fringe benefits provided both sets of personnel. Overall, it

appears the expected annual earnings of military personnel should be

greater for a given wage rate.

For those in the military sample, the average monthly pay was

based upon the military pay schedule in effect at the time of interview.

Also, in order to exclude any :wersea allowances, only those military

respondents stationed in the contic.ental United States were included.

The monthly pay was the yearly Regular Military Compensation (RMC)

rate divided by 12.12 The RMC calculatioo will also be somewhat

understateo since additional allowances for children were not considered.

12

RMC = Base Pay + Allowance for Quarters + Allowance for Food

and Tax Advantage Calculation, since the allowances (quarters and food)

are tax free.

DO
71 In order to gain some insight on how service members view their

pay, two additional measures of military pay were examined. First,

the military respondents were asked how much they received per month

in pay and allowances (reported pay).13 Second, pay was figured for

each service member, based only upon what he or she would most likely see

in his or her pay voucher, and labeled Monthly Apparent Pay (MAP). It was

assumed that single service members would not "see" the imputed value

for the barracks and mess hall, but that married service members would

since the vast majority of them are provided quarters allowance.14

Table 3.8 presents a comparison of the three measures of military pay and

the estimated earnings of the fully employed civilians.

As can be seen from Table 3.8, Armed Forces males receive 12

percent less monthly pay than their civilian counterparts. However,

females receive 18 percent more pay. In order to make the military RMC

equivalent to wages for high school graduates employed full time,

lrmed Forces males would require an 18 percent increase.15 On the

other hand, the Armed Forces appear to be in the forefront of offering

equal opportunity for women as evidenced by greater perceived promotion

opportunities reported in the earlier section and higher pay, compared

to their civilian counterparts.

As Table 3.8 illustrates, actual pay differences may indeed be a

major factor in explai ling pay satisfaction differences for males, but

not for females. Also, it is doubtful that al2 percent pay difference can

explain all of the variance in the pay satisfaction differential for

13

A single service member living in barracks may or may not have

included allowances for food and housing.

14

It was not expected that any service member would see the tax

advantage pay increment.

15

It should be emphasized again that unemployment and layoffs

were not factored in the calculations; however, it is not at all clear

that individuals consider such contingencies when making pay comparisons.
72

Table 3.8 Estimated Monthly Earnings of Full-Time Employed Youth 18-21

Years of Age, by Sector of Employment, Education, Race and

Sex: 1979

(in dollars)

Sex and

race Male Female

Sector

and education Total Black Hispanic White Total Black Hispanic White

Armed Forces

Regular militvy

compensation 752 745 751 755 737 725 776 737

Reported pay 585 541 547 602 563 519 575 573

Apparent pay 557 547 549 561 555 529 605 558

Civilianb

857 753 761 876 626 617 605 628

High school diploma

graduate

Armed Forces

Regular milit ry

compensation 754 744 745 758 737 726 776 737

Reported pay 595 537 544 618 564 518 575 574

Apparent pay 557 540 536 564 555 531 605 558

Civilian b

890 820 792 900 635 627 640 635

Hi h school dro.out

Armed Forces

Regular military

compensation ° 746 748 765 743 c c c c Reported pay 553 558 555 551 c c c c Apparent pay 559 552 575 576 c c c c Civilianb

767 658 736 7S',6 577 534 554 585

a Consists of base pay, quarter allowances, subsistence allowances and tax

advantages.

b

Computed as the product of average hourly earnings, usual hours worked and

4.33 weeks per month.

cLess than 25 sample cases.

02
73

males. Thus, perceptio,: .f pay becomes an important consideration.

Military pay struct,11?-; are complex and may result in large differences between what a service member believes he is paid and what the

Government indicates he is paid. For example, the average rank for

males in the Youth Survey was E-3, with slightly over two years of

service. His base pay was $512 oer month. If he is single and

lives in the barracks, his RMC monthly pay is ($752 per month.

Thus, the Government imputes to his salary $239 per month for the

priv;lege of eating in the mess hall and sleeping in the barracks. It

is highly questionable that the service member himself would value

mess hall and barracks at such a rate, bearing in mind that most service

members living in barracks share rooms and are constantly subject to

inspection. Thus, it was anticipated that the MAP would most likely

be the figure that most service memers would use to compare their pay

to their "relevant others" in the labor market.

As can be seen in Table 3.8, the reported pay and apparent pay

(MAP) of armed forces personnel are fairly close. The degree of con- vergence does not necessarily indicate service members value their

pay more according to what is visible since there was no item asking

them to estimate their RMC pay. However, the evidence on pay satisfaction, especially for the women, suggests that military pay is seen

more according to what is in the pay voucher rather than imputed pay

based upon RMC calculations. Thus, perceived pay, most probably

contributes significantly to the pay satisfaction differentia1.16

16 It should be emphasized at this point that pay perceptions

on the part of service members maw ..ot entirely be due to a lack of

understanding of the pay system. Even if it were fully understood,

it might lead to other dissatisfactions since, as stated earlier, it

is doubtful that service personnel would value the barracks and mess

hall as worth $239 per month.

9
74

There were no significant differences in the three mean pays

among the four services. Yet, as indicated in Table 3.6, there were significant differences in global job satisfaction, the summary measure

of both the pecuniary and nonpecuniary job aspects. When the ranking

among the Services were compared, the Army personnel, who had the lowest

overall satisfaction had the highest satisfaction with pay. Thus, job

satisfaction appears to be a function of three factors--job characteristics

and their associate disamenities, pay, and the reference group against

which the individual compares his job and pay.17 Thus, a uniform pay

policy is likely to sort individuals such that those with the better

qualifications go into the jobs with the fewer disamenities,18 If

this is not the case, job satisfaction is likely to vary across the

services and recruiting and retention will be more difficult for

some jobs.

Implications

Although it appears that the Armed Forces jobs are well below the civilian

labor market in both pecuniary and nonpecuniary aspects, simply raising

pay may not be the answer. Further, with the unique requirements for

combat resources and necessary deployment in sometimes remote and overseas locations, it is doubtful that the services can bring about large

scale improvements in job aspects. Most likely, the bulk of the job

associated disamenities for the Armed Forces are inevitable.

Pay itself is an important consideration and cannot fall too

far behind without affecting both enlistment and retention. However,

17

Presumably the more qualified the individual the higher

reference group he or she will use.

18

This does not guarantee high job satisfaction, only a uniform level of satisfaction or dissatisfaction across branches of

the service. D4
75

many Armed Forces jo:s have reasonably pleasant job aspects and other

extensive training in valuable skills. Apparently the "good" jobs

are not difficult to sell, and they attract high quality volunteers, even at

the present pay level. But the jobs with high disamenities, such as

combat arms, offer a special challenge. Two basic approaches are

possible: more direct pay could be offered either in tl'a form of

salary or bonus, or special incentives such as greatly improved post

service educational benefits might be provided.

Which approach would be more effective cannot be determined with

the data discussed in this chapter. However, based upn the findings

in Chapter 2, where the Armed Forces were seen to be attracting a

disproportionate number who aspire to be college graduates, and based

upon subsequent findings in Chapter 6 concerning parental influence

and concerning reasons for not joining a military service, the

educational incentive may be more effective, especially in drawing

high quality youth. In other words, for "good jobs" the services

should continue to advertise skill training and growth opportunity

in a vocation. But for "tough jobs," an instrumental approach could

be taken; challenge, toughness, and post service educational incentives

should be emphasized in advertisements.
76

APPENDIX B Items Used to Measure Job Characteristics

HAND CARD H. We would like to know what kinds of opportunities this job

offers you. (First/Next), how much opportunity does this job give you

(READ CATEGORY)--a minimum amount, not too much, a moderate amount, quite

a lot, or a maximum amount? (READ CATEGORIES 1-5 AND CODE FOR EACH.)

A Not A Quite A

Minimum Too Moderate A Maximum

Amount Much Amount Lot Amount

Skill To do a number of different

Variety things 1 2 3 4 5 Task To do a job from beginning

Identity to end--(PROBE IF NECESSARY:

that is, the chance tc; do the

whole job) 1 2 3 4 5 Task How much does your job give you

Signifi- the feeling that the job itself

cance is very significant or important

in the broader scheme of tidings 1 2 3 4 5 Autonomy For independent thought or action 1 2 3 4 5 Feedback How much does your job give you

the feeling that you know whether

or not you are performing your

job well or poorly? 1 2 3 4 5 Dealing To deal with other people 1 2 3 4 5

with

others

Friendship To develop close friendships in

Opportune your job... 1 2 3 4 5

ties
77

We would like to know how well or poorly each of the following statements describes your job. (First/Next), (READ CATEGORY). Thinking of your present job, would you say this is very true, somewhat true, not too true, or not at all true?

EACH.

HAND CARD I. THEN READ CATEGORIES 1-10 AND CODE FOR

Job You are given a chance to do

Very

True

Somewhat

True

Not Too

True

Not At All

True

Challenge the things you do best... 4 3 2 1 Comfort The physical surroundings are

pleasant... 4 3 2 1 Valuable The skills you are learning

Skills would be valuable in getting

a better job 4 3 2 1 Safety *The job is dangerous... 4 3 2 1 Health *You are exposed to unhealthy

conditions 4 3 2 1 Pay The pay is good... 4 3 2 1 Security The job security is good 4 3 2 1 Co-Workers Your co-workers are friendly... 4 3 2 1 Competent Your supervisor is competent

Superivsor in doing the job... 4 3 2 1 Promotion The chances for promotion are Chances good... 4 3 2 1 Job *How do you feel about the job Satisfaction you have now? Do you like it

very much, like it fairly well,

dislike it somewhat, or dislike

it very much? CODE ONE ONLY. 4 3 2 1 Like it very much 1 Like it fairly well 2

Dislike it somewhat 3

Dislike it very much. 4

*Reversed scored
Table 81 Matrix 0 Zero-Order urrelatiol

Loefficients Among liarious Aspects of Juu or Youth Ages 18-21 in Armed Forces and Employed Full-Time in Civilian Jobs: 1979

Global Aspects of

job

job

satisfaction Variety

1,00 0.36 0.18

0,30

0.21 0.19 0.43

0.e6

0.50

0.39

0.38

0.05

0.13

0,32 0.26

0.26

0.26

0.35

Others

1.00 0,30

0.36 0.22

0.22

0.31

0.21 0,30 0.20

0,35

0.04

0.02 0.17 0.18

0,10

0.08

0.26

1.00

0,2S

0.24

0.24 0.19

0.20

0,16 0.15

0.18

0.09

0.06 0,03 0.08

0.01

0.03

0,14

Autonomy Friends

1.00

0.22

0.31

0,31 0.26 0,28 0.16

0.26

0.01

0.06

0.12 0.17 0.08

0.13

0.22

1.00 0,23

0.18

0.20

0.18

0.15

0.15 0.00

0.02

0,11 0.18

0.29

0.10

0.19

Identity

1.00 0.20

0.24

0.16 0.15

0,18

0.06

0.06 0.09 0.10

0.14

0,10

0.13

Significance

1.00

0.31 0.34 0.23

0,33 0.03

0.05 0.23

0.25

0.14

0,20

0.30

Feed- back Challenge

1.00 0.20

0.11

0.19

0.04

0,04

0.11 0.19

0.16

0,14

0.16

Comfort

1.00 0.39

0,43

0.00

0.12 0.23

0.18

0.19

0.22

0.32

1.00

0.31 0.22

0.36

0,21 0.19

0.28

0.27 0.23

Skills Safety

1.00 0.00

0,07 0.18

0.20

0,17

0.14

0.33

Condi

1,00

0.46

0.01 0.00

1,07

0.07

0.01

tions

1.00 0.05

0.09

0.13

0,15

0.09

Pay Security

1.00

0.31 0.13

0.19

0.30

Coworkers

1.00 0.18

0.21 0.32

Supervisor

1.00

0.30

0.11

Pro- motion

1.00

0.26 1.00

Global job

satisfaction

Variety Deal with others

Autonomy Close friends Task identity

Task significance

Feedback Challenge

Comfort learn valuable

skills

Safety Unhealthy conditions

Pay Job security

Friendly coworkers

Competent supervisor

Promotion chances

99
79

:able Zero-Order Correlation Coefficients Between Global Job Satisfaction and Various Aspects of Jobs Among Youth Age 18-21, by Sex and Survey

Work Activity: 1979

Activity and

sex Aspects of Job

Total Sex Activity

Female Male

Full time

Civilian Armed Forces

Variety 0.36 0.36 0.37 0.36 0.29 Deal with others 0.18 0..18 0.15 0.18 0.16 Autonomy 0.30 0.27 0.32 0.29 0.34 Close friends 0.21 0.20 0.22 0.22 0.18 Task identit; 0.19 0.15 0.21 0.19 0.20 Task significance

Feedback

0.43 0.44 0.42 0.44 0.41

Challenge

0.26 0.26 0.26 0.25 0.34

Comfort

0.50 0.45 0.51 0.49 0.44 0.39 0.30 0.42 0.38 0.32 Learn valuable

Safety

skills 0.38 0.23 0.41 0.37 0.36 0.05 0.10 0.03 0.03 0.11 Unhealthy condiPay

tions 0.13 0.06 0.12 0.11 0.15 0.32 0.33 0.32 0.30 0.25 Job security 0.26 0.28 0.25 0.28 0.15 Friendly coworkers 0.26 0.29 0.23 0.24 0.22 Competent supervisors 0.26 0.26 0.25 0.26 0.24 Promotion chances 0.35 0.30 0.40 0.37 0.22
CHAPTER 4

INTENTION TO REENLIST

One of the ways the armed forces achieve their personnel goals

is to pursue a very active and attractive reenlistment program. The

retention of an experienced work-force has the obvious advantage of

saving recruitment and training costs associated with enlistments.

Moreover, enlistees should be more productive on the job than a force

dominated by more recent accessions. On the other hand, the retention

of a disproportionate number of experienced workers means that the

average age of the military force increases and the costs of salaries

and future retirement benefits also rises.

Due to the young age of our sample - 14 to 21 on January 1, 1979 -

the numbers were too small to conduct an analysis of the factors affecting reenlistments. However, all persons serving at the time of the

interview were asked whether they intended to reenlist at the end of

their current tour of service. Based on their response we identified

a sample of potential reenlistees, namely respondents who reported

they would definitely or probably try to reenlist.

In this chapter we investigate the interrelationship between re- enlistment intention and a number of factors expected to impact on the

reenlistment decision. Among the factors studied are: job satisfaction,

tenure, educational attainment, educational expectation, health, marital

status, socioeconomic background, and incidence and duration of Armed

Forces training, by type.

1 Although there were approximately 680,000 youth who were serving

in the active forces approximately 50,000 enlistees in their second tour

of duty are excluded from this analysis.

80

101
81

Overall, 1 in 4 males and about 4 in 10 females intend to reenlist

(Table 4.1). Black males are more likely than white males to have positive

intentions. In contrast, white females are significantly more likely

than their black counterparts to intend to reenlist.

As expected, there is a strong asv)ciation between reenlistment

intentions and job satisfaction, with the satisfied male youth having a probability of reenlistment four times greater than the dissatisfied

group. The same general pattern is found among females, but the relation2

ship is not nearly as strong.

The reenlistment intention rate among male youth is inversely

related to the number of years served in the armed forces; first-year

enlistees are about twice as likely as those with at least two years

of service to express positive intentions to reenlist. This relationship generally prevails regardless of racial group. A similar association

is found among females and is particularly pronounced among the whites.

The inverse relationship between reenlistment intentions and tenure

is somewhat unexpected since in the civilian sector, one usually finds

that the longer the period on the job the greater the attachment to the

employer. An explanation for the declining job satisfaction and intention

to reenlist with increased tenure is the difference in employee mobility

in the civilian and military sectors. To the extent that an employee

is not satisfied with his civilian job he :an change employers. However,

an enlistee is generally precluded from such a change until his tour of

duty is completed. Thus, employees in the civilian sector who become

2

It will be interesting to trace and compare the career paths of

enlistees who express satisfaction in their jobs but do not intend to

reenlist and those who are dissatisfied with their work but intend to

serve a second tour. The latter group may regard the Armed Forces as their only viable employment option while the former group may feel that

they will encounter no difficulty in finding satisfactory work in the

civilian economy.

11)2
82

Table'4.1 Reenlistment Intention Rate Among First-Term Youth in Armed

Forces, by Sex, Race and Other Selected Characteristics: 1979

Race and sex Males ensiles

Characteristic Total Black L Hispanic White Total Black Hispanic White

Total number (000) 579 115 39 426 49 10 2 37

Reenlistment intention

rate 25 39 32 21 38 32 28 41

Job satisfaction

Satisfied 37 53 41 32 48 45 b 49

Dissatisfied 9 18 21 6 17 18 b 18

Tenure

Less than 13 months 36 54 b 30 48 18 b 60

13-24 25 34 b 21 35 58 b 29

25 months or more 19 30 b 16 29 b b 31

Educational attainment

less than 12 years 24 48 b 18 b b b b

12 years or more 25 37 34 21 38 32 28 41

Educational expectations

12 years 24 43 b 20 24 b b 25

13-15 23 28 26 21 43 51 b 42

16 years or more 27 42 b 21 40 26 b 45

Health status

Does not affect work 24 38 28 20 38 30 50 39

Affects work 25

a b b 23 18 b b 25

Education of parent

Less than 12 years 35 49 33 30 55 39 b 63

12 25 40 b 21 32 28 b 34

13 years or more 16 17 b 15 32 b b 31 Marital status

Married 28 54 b 22 23 b 25 24

Never married 24 35 34 20 45 35 37 48

Formal school training

Less than 8 weeks 26 41 32 19 49 25 24 60

8 weeks or more 25 39 29 22 31 43 34 29

a Years of school completed by the parent in the household with the highes,

educational attainment.

b

Less than 25 sample cases

ua
83

dissatisfied in their jobs change employers lowering their tenure while

their counterparts in the Armed Forces build up their tenure.

The number of years of school completed at time of entry into

the armed forces has no overall effect on the reenlistment intention

rate of male youth. However, black males with less than 12 years of

school completed are about 1.3 times more likely than their high school

graduate counterparts to have positive attitudes about reenlistment.

The limited number of women in the Armed Forces with less than 12

years of school completed prevents us from studying this relationship

for female enlistees.

We previously showed that the participation rate in the Armed

Forces is positively associated with the number of years of school the

respondent expects to complete (Table 2.2). Reenlistment intention rates

also are positively correlated with educational expectations. The

relationship is very modesc for males but fairly strong for females.

The reenlistment intention rate for male enlistees is generally

unrelated to health status. In the case of women enlistees, however,

those who report their health affects the kind or amount of work they

can do are about one-half as likely as their healthy counterparts to

have positive attitudes about reenlistment.

We earlier found that the participation rate in the Armed Forces

among white youth is negatively related to their socioeconomic background

but that the association among nonwhite youth is positive (Table 2.1). In

contrast, the reenlistment intention rate declines with increases in

parental education for all race and sex groups. The below-average

participation and reenlistment intention rates of white youth from

above average family backgrounds suggest that this subgroup will become
84

3

an increasingly smaller part of the Armed Forces.

We also observed earlier that the participation rate of married

4

youth is higher than for those never married. The reenlistment

intention rate of male enlistees follows the same pattern, particularly

among blacks where those who are married are about 1.5 times more

likely than their never married counterparts to want to reenlist.

This association is reversed for women, however, with the never married

twice as likely as those married to have positive attitudes. These

differences by sex may reflect a greater concern among married men

about the availability of adequate job opportunities i the civilian

economy while married females may find the Armed Forces less desirable

because of their greater family responsibilities.

There are two obvious competing hypotheses about the relationship

between the type and duration of training received and reenlistment

intentions. On the one hand, those who receive some training may find

that they can transfer their acquired skills to jobs in the civilian

sector, suggesting below-average reenlistment intention rates for

this group. On the other hand, the trained enlistee is a more valuable

resource to the Armed Forces and may be induced to stay by being promoted

more quickly and/or assigned to jobs with more favorable career paths.

In this case we expect a positive association between training and re- enlistment intention rates. Which of these two factors dominates is

an empirical question.

3

Needless to say this implication only holds under the assumption

that demand conditions do not change. If the Armed Forces decide to accept

disproportionately more whites than nonwhites who want to reenlist, the

racial imbalance by socioeconomic status will be less affected.

4

The proportion of the Armed Forces sample, however, who are

married is no larger than for the full time employed in the civilian

sector.

11)5
85

There is almost no difference between the duration of formal

school training in the Armed Forces and reenlistment intention rates

among males, while among females there is a negative association with

5

higher rates reported among women with shortest duration of training.

To study possible interactions between length and type of training,

enlistee characteristics and reenlistment intentions, we restricted the

sample to enlistees who received at least 8 weeks of formal school

training after completing basic training. This stratification by

duration of training eliminated from the sampte all enlistees with no

MOS/RATING/AFSC. We also restricted the analysis to white youth because

of the limited number of black and Hispanic enlistees who had received

training.

These restrictions do not generally alter our earlier findings

(Table 4.2). One exception concerns the interrelationship between years

of school completed and reenlistment intention rates for male enlistees.

In the larger universe we found no relation between these measures; now

we find male high school graduates with at least 8 weeks of formal

schooling in the service are about 1.5 times more likely than their high

school dropout counterparts to intend to reenlist. We also find in this

more restricted universe a stronger relationship between educational

expectations and reenlistment intentions among men. This finding does

not generalize to women, however.

5

There is a very discernible association between the extent of the

on-the-job training (OJT) and reenlistment intentions. Males who receive

8 or more weeks of training are about 1.3 times mqre likelyto have

positive intention.. about reenlistment than those with no training or

shorter periods of training. Among women the relationship is even stronger with those who receive longer priods of OJT about 1.5 times

more likely to want to reenlist than women with less training. The

definition of OJT used by the respondents is not clear, however. Therefore, we are uncertain of the meaning of this finding at this time.

6

Eight weeks of training was selected as the dividing point because

it was the modal frequency for those who received some training.
86

Table 4.2 Reenlistment Intention Rate Among First-Term Youth In Armed Forces

With At Least 8 Weeks of Post Basic School Training, by Sex, Race,

and Other Selected Characteristics: 1979

Race, sex

Males Females

Characteristic Total White Total White

Total number (000) 291 229 23 19

Reenlistment, intention rate 25 22 31 29

Job satisfaction

Satisfied 36 32 36 35 Dissatisfied 8 6 17 13

Tenure

40 34 21 22

tin than 13 months

13-24 24 22 36 32 25 months or more 20 17 32 31

Educational attainment

Less than 12 years 19 13 a a 12 years or more 27 24 30 28

Educational expectation

21 19 24 23 12 years

13-15 28 22 36 30 16 years or more 27 24 29 29

Health status

Does not affect work 24 21 26 26 Affects work

b

a a 25 26

Education of parent

Less than 12 years 30 28 36 41

12 28 23 33 31 13 years or more 19 20 2i 20

Marital Status

Married 29 23 24 23 Never married 24 22 35 32

abLess than 25 sample cases.

Years of school completed by the parent in the household with the highest

educational attainment.
87

The restriction of the universe does not substantially alter

the inverse relationship between tenure and reenlistment intention

rates for men, but it weakens the association for women, particularly

for those with at least 8 weeks of formal school training. In the

of job satisfaction there is again no change for men, but a

weaker relationship for women.

In summary, we find that reenlistment intention rates are positively

associated with job satisfaction and inversely related to the number

of months served in the armed forces. Reenlistment intention rates

are also positively related to educational expectations, but there is

no evidence of an association among male enlistees between propensity

to reenlist and years of school completed. In contrast, we find a

negative association between the education of the parent and the reenlistment intention of the enlistee. Married male enlistees report a

higher propensity to reenlist than never married enlistees, but the

relationship is reversed among females.

Even though some of the associations are weakened by the restriction

of the universe to enlistees who received at least 8 weeks of formal

school training, the most significant change has to do with the education

measure. Whereas for the entire universe there was no association

between schooling completed and reenlistment intention rates for male

enlistees, among those who received at least 8 weeks of training , higher the educational attainment the more likely the'reenlistment

intention.
CHAPTER FIVE

POST-SERVICE STATUS OF

PERSONS WHO HAVE LEFT THE ARMED FORCES

One of the most basic questions which the National Longitudinal

Surveys will answer is what are the effects of military service on the

subsequent labor market experience of young men and Because of

the young age of the sample at the present time, there are relatively

few respondents who have served in the military and reentered the

civilian sector. In addition, those who have separated from the service

are overwhelmingly (75 percent) persons who left before completing

their initial tour of duty. Thus, we must wait until subsequent interview waves have been conducted to compare the experience of those who

served in the military with those who choose not to volunteer.

We can, however, examine the nearly 200,000 mala "attriters,"

persons leaving the military before completion of the tour of duty

for which they originally contracted, to determine if these individivals

suffer in the labor market subsequent to their service. Several hypotheses may be offered which argue for poor performance by these individuals. First, they may not have the qualities which make them attractive

to civilian employers in the same manner that they did not have the

abilities to complete their terms of military service. The same factors

which cause them to leave the armed forces may affect their ability to

get and keep decent employment in the civilian sector. Second, employers

may discriminate against these individuals by using the completion of

a tour of duty as a screening device for hiring. A third factor weighing

against success in the labor market is the fact that the attriters were

out of the labor market and unable to build as much seniority as

did those who never served.

88

1 u
89

All three of these reasons would 'Ie.( .:rie to believe that the attriters

would have greater unemployment and lower quality jobs than would those

who never served. We will test below whether this is in fact the case.

We should note, however, that the small number of attelters in our sample

at this time (83 men) makes this test highly tentative.

Table 5.1 compares the men who left the service with those non- veterans in the civilian population who are 18-22 years of age. In

examining this table one immediately notices the much higher proportion

of the civilian group who are enrolled in high school (13 percent) than

is true of those who left the service before completing their tour of

duty (3 percent). It would appear that the non-veteran group is younger

than are the veterans. 1 Even so, however, the non-veteran group has a

much higher percentage than the attriters enrolled iu college (30 percent

as opposed to 8 percent).2

When we turn to employment status we find little difference in the

employment to population ratios of the attriters and the nonveterans.

The unemployment rate, however, was higher for the attriters, 18 percent as compared with 12 percent.

3

This differential in unemployment

rate is not large enough to be statistically significant due to our sample

size.

1 An examination of the knowledge of world work scores, educational

attainment and educational' expectations for the attriters and the group

who never served indicated very little difference between the two groups.

Those who had completed their tour of duty, however, were substantially

superior on all three aspects to the attriters and those who had never

served.

2 Among the very small number of veterans who had completed their

tour of duty the enrollment rate in college was higher--21 percent.

3

As one would expect the unemployment rate was much higher and the

employment to population ratio much lower among those persons who had attrited

from the armed forces during the preceding twelve months.
90

Table 5.1 Survey Week Activity of Veteran and Civilian Males Ages 18-22

Years Old, by Reason for Separation for Veterans: 1979

(Percentage distribution)

Separations

Activity

and

characteristics

Total

separations Attrites

Never served,

Civilian

population

Total sample (000) 260 195 8208

Activities

Enrolled in high

school 2 3 13

Enrolled in college 12 8 30

Employed 74 70 71 Unemployed 15 16 10

Not in labor force 11 14 19
91

Another dimension of post service success of the attriters, is shown

by the types of jobs they hold and their satisfaction with them. Table

5.2 shows a slightly higher concentration of the attriters among service

occupations and fewer professionals and managers and farmers. The hourly

rate of pay of the attriters was slightly higher than that of the youth

who had never served.

4

This difference, however, may reflect the greater

number of students among the civilian group who are working part time.

Finally, an examination of satisfaction with their jobs indicates that

fewer of the attriters liked their work very much, but more of them viewed

their jobs favorably than was true of the civilian nonveteran population.

Based on these data it appears that the servicemen who leave before

completing their tour of duty are not subsequently disadvantaged in the

labor market, particularly if some time has passed and they have had the

opportunity to find employment. On the other hand, it is also clear that

these individuals are not as highly qualified or as successful in the

labor market as are those persons who have completed their service obligations. We conclude with the impression, although it is tentative

because of the small number in our sample, that the persons leaving the

armed forces prior to fulfilling their commitments are similar to the

average person who never served and early termination does not harm

them in the civilian sector. 5

4

Those persons who had completed their tour of duty had substantially

higher rates of pay than either the attriters or the non-veteran group.

5

Their lower college enrollment rates, however, may indicate greater

problems in the long run.
92

Table 5.2 Job Satisfaction, Occupational Status, Wage Rates of Employed

Males 18-22 Years of Age by Type: 1979

(Percentage distribution)

Separations

Activity

and

characteristics

Total

separations Attrites

Never served,

civilian

population

Total sample (000) 192 136 5820

Job satisfaction: 100 100 100

Like very much 22 20 34 Somewhat like 69 69 50 Somewhat dislike 4 5 13 Dislike very'much 5 6 4

One-digit occupation:

Professional,

managers 7 6 9 Sales, clerks 11 13 13 Blue collar 62 58 60 Service 19 23 16

Farmers 0 0 4

Hourly rates of pay:

(dollars)

$ 0-2.99 14 11 19 3-3.99 30 34 30 4-5.99 29 31 26 6-9.99 18 14 15

10.00 or more 0 0 1
CHAPTER 6

INTENTIONS TO SERVE

In the next five years, the pool of young men and women in the 18 to 21

year old age group will decline. Thus to maintain personnel strength

the Armed Forces will have to increase the proportion of young people who

enlist.1 This will necessitate greater attention to the factors associated

with enlistment rates and the reasons why young people choose not to enlist.

In this chapter, we examine the attitudes of young people toward enlistment

and their present intentions to enlist. We also focus on the responses

of persons who chose not to enter the Armed Forces after first indicating

an intention to do so.

Attitudes Toward the Military

Youth who had not served in the military were asked the following

question, "Do you think for a young person to serve ir the military is:

definitely a good thing, probably a good thing, probably not a good thing,

or definitely not a good thing?" We would expect that on average those

persons who have a positive attitude (i.e., they believe the service is

definitely or probably a g od thing) are more likely to enlist than those

with negative attitudes. In addition, this reaction indicates how the

Armed Forces are generally viewed by young people. As can be seen in

lAnother, short run, solution would be to improve retention markedly.

93
94

Table 6.1, almost three-fourths of all young people were favorably disposed

to service in the Armed Forces.2 Further, we find little variation by

race. Positive attitudes generally increased with age and females were

slightly more favorably disposed than were men.

In Table 6.2, we present the proportion with positive attitudes for

groups of youth displaying many characteristics. In this table we divide

the young people into three groups: those age 14 to 17, who are as yet

ineligible to enter the service3; persons 18 to 21 who are of prime

enlistment age; and high school seniors, the group which is probably the

most direct target for military recruiting.

The figures in Table 6.2 indicate a lack of systematic association

between attitude toward the military and family income, but stronger approval

of the military service is associated with lower socioeconomic backgrounds

as shown by parents' educational level. Males not expecting to complete

high school, men who do not have health problems which affect the amc'nt

or kind of work they can do, married men, and men and women who have not

attended college all had about average proportions believing service was

a good thin. None of these groups, however, was very far above average

in po5itive attitude toward military service. Consequently, we

conclude that there are generally favorable attitudes toward service in the

Armed Forces among all segments of youth.

2Actually, a larger proportion of all youth would be favorably disposed

to the Armed Farces since those currently serving in the military were not

asked this queAlon.

3While 17 year olds may enlist, the number who serves is extremely

small.

11 5
95

Table 6.1 Proportion With Positive Attitudes Toward Armed Forces Among Youth

14-21 Years of Age Who Have Not Served by Year of Age, Race and

Sex: 1979

ace o a to : ac 'ispanic

Sex

Total T number

(thousand) Percent

Total

number

(thousand) Percent

Total

number

(thousand) Percent

Totai

number

(thousand) Percent

Males

14 1,581 68 1,255 I 70 214 61 112 57 15 2,198 67 1,719 68 325 58 155 68 16 2,044 67 1,639 67 276 65 129 72

17 2,063 77 1,631 77 291 78 142 76

18 2,033 77 1,599 78 300 74 133 74

19 1,985 77 1,633 77 246 77 106 78

20 1,947 75 1,607 76 220 69 118 74

21 1,770 76 1,448 76 217 77 105 88

Total 15,621 70 12,533 70 2,089 67 1,000 70

Females

14 1,461 66 1,159 68 194 59 108 62

15 2,068 69 1,625 69 309 67 134 72

16 2,032 70 1,627 69 283 75 123 73

17 2,034 79 1,641 79 274 79 120 77

18 2,067 81 1,620 81 312 83 135 86

19 2,154 85 1,741 85 285 84 127 89

20 1,985 82 1,578 82 281 85 126 78

21 2,119 84 1,683 84 301 84 135 82

Total 15,920 75 12,674 75 2,239 75 1,008 75

116
96

Table 6.2 Proportion With Positive Attitudes Toward Armed Forces Among Youth

14 to 21 Years of Age Who Never Served by Age, Race, Sex, and Selected

Characteristics: 1979

Race, Sex Mares Fema es

Characteristic Total White BlackHis anic Total White Black His anic

Education of Parent

A'e 14-17 70 70 66 69 71 71 71 71 Less than 12 years 71 74 63 67 73 73 74 70

12 70 70 66 70 73 74 70 77

13 years or more 69 69 71 69 68 68 66 67

Ane 18-21 76 77 74 78 83 83 84 84

Less than 12 years 80 82 74 82 85 85 84 82

12 77 78 73 72 83 83 86 87

13 years or more 74 73 79 67 83 83 79 86

High School Seniors 76 76 77 76 81 81 82 75

Less than 12 years 78 80 77 70 81 81 84 75

12 79 80 76 a 84 84 83 a 13 years or more 72 71 85 a 79 80 79 a Family Income

Age 14-17 70 70 66 69 71 71 71 71 Less than $10,000 70 73 65 74 70 72 68 67

$10,000 or more 69 70 66 64 72 71 72 73

A.e 18-21 76 77 74 78 83 83 84 84

Less than $10,000 7o 75 75 84 85 84 86 84

$10,000 or more 77 77 73 75 83 83 81 88

High School Seniors 76 76 77 76 81 81 82 75

Less than $10,000 79 80 76 a 83 81 88 a $10,000 or more 77 76 83 73 82 82 80 78
Table 6.2 (continued) 97

Race, Sex

C .Jacteristic Total 114i,ite Black Hispanic Total White Black Hispanic

EAucational expectatiui5

Age 14-17 70 70 66 69 71 71 71 71 Less than 12 years 77 80 69 69 69 72 53 82

12 68 68 66 57 72 72 72 68

13-15 75 77 69 63 73 74 67 73

16 years or more 69 70 64 71 70 70 72 72

Aye 18-21 76 77 74 78 83 83 84 84

Less than 12 years 81 82 76 85 76 79 65 70

'2 79 80 76 81 85 85 84 85

13-15 78 79 71 73 85 84 89 91 16 years or more 72 72 74 73 82 82 83 83

High School Seniors 76 76 77 76 81 81 82 75

Less than 12 years a a a a a a a a 12 79 81 72 79 80 79 84 a 13-15 82 85 a a 84 85 84 a 16 years or more 71 68 85 78 79 79 80 70

Health Status

70 70 66 69 71 71 71 71 Age 14-17

Does not affect work 70 71 66 69 71 71 71 72

Affects work 63 64 65 a 72 73 67 60

Age 18-21 76 77 74 78 83 83 84 84

Does not affect work 77 77 75 79 84 84 84 85

Affects work 74 76 70 a 78 78 80 71 High School Seniors 76 76 77 76 81 81 82 75

Does not affect work 76 76 79 76 81 82 82 77

Affects '1iork a a a a a a a a
98

Table 6.2 (continued)

Race, sex

Characteristic Total

Knowledge of The

World of Work Score

Age 14-17 70

0-5 68

6-7 67

8-9 71

Age 18-21 76

0-5 71

6-7 71

8-9 72

High School Seniors 76

0-5 7"J 6-7 80

8-9 68

Internality (Rotter) Score

Age 14-17 70

4-8 70

9-16 66

Age 18-21 76

4-8 69

9-16 73

High School Seniors 76

4-8 74

9-16 74

Males Females

White Black Hispanic Total White Black Hispanic

70 66 69 71 71 71 71

68 66 68 68 69 67 69

68 62 59 72 73 71 69

71 59 77 67 67 74 72

77 74 78 83 83 84 84

71 69 73 79 79 81 79

71 72 71 80 80 79 83

73 67 76 81 82 76 79

76 77 76 81 81 82 75

72 78 67 80 79 83 70

80 86 66 79 80 74 80

68 63 a 75 74 87 a

70 66 69 71 71 71 71

72 64 65 69 69 67 71

66 65 68 70 70 71 68

77 74 78 83 83 84 84

69 69 71 79 79 78 81

74 70 74 81 81 81 80

76 77 76 81 81 82 75

75 74 62 75 73 79 80

72 80 80 83 84 83 65

11 a
Table 6.2 (continued) 99

Race, Sex

CharacteristiEr '- - -..4

tia es Females

Total ,White Black Hispanic Total White Black Hispanic

Employment Status

A'e 14-17 70 70 66 69 71 71 71 71

Employed 71 72 65 66 71 70 82 72

Unemployed 68 67 69 69 71 72 66 76

Age 18-21 76 77 74 78 83 83 84 84

Employed 70 70 68 75 82 81 82 85

Unemployed 76 79 68 75 80 79 82 82

High School Seniors 76 76 77 76 81 81 82 75

Employed 75 74 77 75 79 79 86 69

Unemployed 70 69 74 a 75 72 83 a Age 18-21 76 77 74 78 33 83 84 84

Marital Status

Married, spouse

present 81 81 a 85 86 86 82 78

Never married 76 76 75 78 83 82 85 87

Grade Attending

Attending high

school 77 78 75 75 79 77 84 85

Attending college 73 73 74 72 82 81 85 81

Educational

Attainment

9-11 years 78 79 76 77 81 79 84 82

12 78 79 74 71 86 86 84 87

13 years or more 70 70 I 69 77 81 81 86 82

aLess than 25 single cases.
100

Intuition to Enlist

A second question asked of all nonveteran youth who were not serving

in the military was, "Do you think, in the future, that you will: definitely

try to enlist; probably try to enlist; probably not try to enlist; or definitely

not try to enlist in the military." This question provides a more direct

test of individual enlistment intentions than the generalized question

about young people serving in the military. Defining a positive enlistment

intention as a statement that the respondent will "definitely" or "probably"

try to enlist, we find approximately 3.9 million young men (25 percent) and

1.6 million young women (10 percent) have a positive propensity to enlist.

This includes 35 percent of 14-17 year old young men, 16 percent of 18-21

year old males and 21 percent of male high school seniors. The rates are

13, 7 and 10 percent for the respective groups of yumIg women.

As can be ser.ci 1,kle 6.3, intention to en i t (ie.:lines sharply with

age for. both men and women. The decline, however, is more precipitous for

whites than it c for minority youth. 4 Further, a higher proportion of males

than female:: axpress an intention to enlist in the military, although the

difference between the intentions of young men and women is not nearly as

great as present participation rates would indicate. It would appear based

on these numbers that the pool of potential applicants among females will

4Part of the decline with age of persons who intend to enlist is

explained by omission from the group being examined of the youth who

have already enlisted. However, using the participation rates of

Chapter 2, we still see a substantial decline in the proportion who

intend to or have enlisted as the youth get older although the decline

for minority males would not be nearly as sharp as it appears in Table 6.3.

In addition, it would appear that the 18-21 year old group who wish to

enlist is of a lower quality than persons serving in the Armed Forces, i.e.,

the services may have already skimmed much of the cream from this age group. The group saying they intend to enlist are lower than service personnel on

educational attainment and expectations, KOWW, and parents' education and

are more external.

1 '"
101

Table 6.3 Preportion Intending To Enlist Among Youth 14 to 21 Years of Age Who Never Served, by Year of Age, Race and Sex: 1979

Race

Age,

Sex

Total White Black Hispanic Total

number

(thousand)

Total

number

Percent,(thousand) Percent

Total

number

(thousand) Percent

Total

number

(thousand) Percent

Males

14

15

1,581

2,198

40 1,255 38 214 47 112 48

16

39 1,719 38 325 42 155 51

17

2,044

2,063

32 1,639 28 276 48 129 49

18 2,033

29 1,631 25 291 43 142 45

19 1,985

25 1,599 21 300 41 133 40

20 1,947

17 1,633 14 246 35 106 24

21 1,770

13 1,609 10 220 27 118 17 9 1,448 5 217 27 105 23

Total 15,621 25 12,533 22 2,089 38 1,000 37

Females

14

15

1,461

2,068

14 1,159 10 194 30 108 16

16 2,032

16 1,625 12 309 35 134 30

17 2,034

14 1,627 11 283 28 123 24

18 2,067

10 1,641 6 274 25 120 24

19 2,154

11 1,620 8 312 24 135 19

20 1,985

7 1,741 4 285 25 127 18

21 2,119

6 1,548 4 281 18 126 9

4 1,683 2 301 13 135 8

Total 15,920 10 12,674 7 2,239 24 1,008 18

14.4
102

increase in the next several years.

With the exception of 14 and 15 year old males, the intention to enlist

in the Armed Forces is much higher among minorities than among white youth.

Since blacks and Hispanics will make up an increasing proportion of young

people in the next decade, their high enlistment propensities that minorities

will constitute an increasing proportion of applicants to the services.

The enlistment intentions of different groups of youth are shown in

Table 6.4. Many of the characteristics which were found to be related to a positive attitude toward the military are also evidently associated with

intention to enlist.5 Enlistment intentions are higher among youth for

whom neither parent had attended college, for youth with families having

incomes of less than $10,000, for youth who do not expect to go on to

college, among those who are not currently employed, single youth, and youth

who have not attended college. Thus, when we look at the characteristics

of youth with high propensities to enlist, we find many of the factors which

were hypothesized to occur with the changeover to an all volunteer force.

Youth from lower socioeconomic backgrounds with less education and lower

educational expectations are those who express the greatest interest in

enlisting in the Armed Forces.

The findings in this chapter appear to contradict those of Chapter 2.

5It should be noted that not all of the persons indicating an intention

to enlist in the Armed Forces answered that service is a good thing for a

young person. Approximately 530,000 young men and 140,000 young women ages

14-21 said service is probably or definitely not a good thing for &young

person but at the same time indicated that they would probably or definitely

try to enlist. The proportion of civilian youth who made these seemingly

contradictory statements is inversely related to age, is higher among males

than females, and is more prevalent among minorities than among whites. See

Table C.1 and C.2 in Appendix C.

This group may see unemployment as their alternative to service and

view enlistment as the lesser of evils. It will be interesting to follow

these youth to see how many enlist and whether their earlier attitudes

affect their performance in the service.

123
103

Table 6.4 Proportion Intending to Enlist Among Youth 14 to 21 Years of Age

Who Never Served, by Age, Race, Sex, and Selected Characteristics

(In Percent)

Race, sex

. Males Females

Characteristics Total White Black Hispanic Total White Black Hispanic

Education of Parent

Age 14-17 35 32 45 48 13 10 30 24 less than 12 years 46 43 49 55 21 15 36 26 12 35 33 45 43 12 9 27 24

13 years or more 25 25 31 32 8 7 21 17

Age 18-21 16 13 33 27 7 5 20 14

Less than 12 years 25 18 41 31 12 6 24 18 12 15 13 31 19 7 5 17 10 13 years or more 11 10 20 20 4 3 16 3

High School Seniors 21 18 37 35 10 7 25 24

Less than 12 years 38 35 49 33 21 12 38 34

12 25 23 32 a 7 4 22 a 13 years or more 11 9 27 a 6 6 0 a Family Income

Age 14-17 35 32 45 48 13 10 30 24 Less than

$10,000 45 40 49 59 24 16 33 34 $10,000

or more 31 30' 39 39 11 9 25 17

Age 18-21 16 13 33 27 7 5 20 14

Less than

$10,000 20 13 40 a 10 6 21 a $10,000 or more 14 13 24 22 6 4 10 17

High School Seniors 21 18 37 35 10 7 25 24

Less than

$10,000 32 23 47 41 25 14 36 36 $10,000

or more 20 18 31 31 6 4 19 18
104

Table 6.4 (continued)

ace, sex

Males Females

Characteristics Total White Black Hispanic Total White Black Hispanic

Educational Expectations

Age 14-17 35 32 45 48 13 10 30 24

Less than 12 years 51 47 67 59 18 11 49 40 12 41 38 53 54 18 13 38 24

13-15 30 28 38 36 10 7 25 22

16 years or more 27 25 32 41 10 8 20 21

Age 18-21 16 13 33 27 7 5 20 14

Less than 12 years 28 23 52 29 6 3 29 9

12 22 17 45 34 8 4 25 18

13-15 15 14 23 16 9 6 16 17

16 years or more 10 7 22 25 6 4 18 10

High School Seniors 21 18 37 35 10 7 25 24

Less than 12 years a a a a a a a a 12 32 28 55 46 13 7 41 a 13-15 22 22 a a 9 8 21 a 16 years or more 12 8 25 33 7 5 14 18

Knowledge of The World of Work

Age 14-17 35 32 45 48 13 10 30 24

0.75------ 38 34 45 48 16 9 33 25

6-7 34 31 47 43 12 10 24 19 8-9 30 29 35 54 11 10 22 23

A.e 18-21 16 13 33 27 7 5 20 14

0-5 19 10 34 25 9 4 23 15

6-7 15 13 27 27 5 4 18 9

8-9 11 10 27 22 7 6 11 16

High School Seniors 21 18 37 35 10 7 25 24

0-5 27 22 38 41 11 3 35 20

6-7 16 14 29 24 8 6 8 36

8-9 18 16 34 a 11 10 23 a
105

Table 6.4 (continued)

Race, sex

Males Females

Characteristics Total White Black Hispanic Total White Black Hispanic

Health Status

Age 14-17 35 32 45 47 13 10 30 24

Does not affect

work 35 32 45 49 13 10 30 24

Affects Work 29 27 41 a 17 14 27 29

Age 18-21 16 13 33 27 7 5 20 14

Does not affect

work 16 13 33 27 7 4 21 13

Affects work 20 16 42 a 8 6 14 17

High School Seniors 21 18 37 35 10 7 25 24

Does not affect

work 22 19 37 36 10 7 25 24

Affects Work a a a a 12 a a a

Employment Status

Agg_142. 35

31

32

29

45

47

48

46

13

10

10

8

30

38

24

WITIVid 24

Unemployed 42 38 50 48 15 10 27 30

Age 18-21 16 13 33 27 7 5 20 14

Employed 14 11 32 23 6 4 18 15

Unemployed 29 25 36 40 11 6 22 21

High School Seniors 21 18 37 35 10 7 25 13

Employed 20 16 43 41 7 5 21 34

Unemployed 36 36 39 a 16 10 33 a

126
106

Table 6.4 (continued)

Race, sex

Males Females

Characteristics Total White Black Hispanic Total White Black Hispanic

A.e 18-21

Marital Status 16 13 33 27 7 5 20 14

Married, spouse

present 10 8 a 27 2 1 10 6

Never married 17 13 34 27 9 6 22 18

Grades Attending

Attending high

school 29 23 44 46 16 10 31 29

Attending college 8 6 17 13 5 3 17 7 Educational Attainment

9- T1 years 28 21 47 38 14 8 29 20

12 12 10 26 14 6 5 18 12

13 years or more 7 6 11 17 3 2 8 6

Internality (Rotter)

score A.e 14-17 35 32 45 48 13 10 30 24

4-8 33 32 39 49 13 10 28 21

9-16 35 32 48 46 14 9 32 25

Age 18-21 . 16 13 33 27 . 7 5 20 14

4-8 16 13 31 25 6 4 14 12

9-16 15 12 33 26 8 4 25 15

High school seniors 21 18 37 35 10 7 25 13

4-8 19 15 41 31 8 5 24 23

9-16 23 20 34 35 21 8 26 24

a Less than 25 sample cases
107

Here, while we find higher intentions to enlist among minority youth, we do not find them among minorities from better backgrounds and with above

average qualifications, although these youth had higher participation rates. It

would also appear that those who wish to enlist are not of as high a quality

as are the persons who do not have this intention; in contrast in Chapter 2

military personnel compared favorably with out of school youth employed

full time in the civilian labor force. These apparent inconsistencies can

be explained, however.

First, the military services select from those who intend to enlist to

eliminate the poorly qualified. The recruitment standards mean that the

persons who are selected for military service are likely to come from the

more qualified segments of the pool of individuals who intend to enlist.

Thus, we would have a larger proportion of the small group of highly qualified

individuals who apply to the military actually accepted, while only a few

of the large number of less qualified persons enter the service. Second,

the selection criteria may eliminate proportionately more minority than

white applicants. For instance, among male high school seniors, twice as

many blacks and Hispanics indicate an intention to enlist than is the case for whites; the participation rate for minorities, however, is only 1.5

times that of whites. Thus, it would appear that more minorities who

indicate an intention to join the military do not do so.6

One should also note that the group who indicate that they do not intend

to enlist includes persons who go directly from high school to college. We

know from a variety of data that this group comes from higher socioeconomic

backgrounds, is very able, and by definition, has high educational expectations.

6

While the emphasis has been placed in the selection criteria eliminating

more minority than white youth, it is also possible that more of these youth

change their minds and do not apply.
108

In Chapter 2 we compared the persons in the military with those employed full

time and found the service men and women to be of equal or superior caliber.

In this chapter we are considering not only these individuals, but also the

over 40 percent of young people who move from high school directly to college.

While the military may be competitive with the civilian labor market, it is

not competitive for the majority of youth who seek college educations at

the time they graduate from high school.

Why Youth Choose Not to Serve in the Armed Forces

In the preceding section, we found that intention to enlist in the Armed

Forces is inversely related to family background, educational expectations,

and to some extent, capability. While many young people never intend to

volunteer, there is a substantial group who do make an effort to enlist, but

who do not subsequently serve. Based on our sample, over six million young

people 18-21 had talked to a military recruiter to get information about a

branch of the military. Almost one million of these entered the service.

We asked the remaining individuals what was their primary reason for not

enlisting.? The results appear in Table 6.5.8

Overall, 23 percent of the men said they decided to go to school instead

of entering the service, 21 percent indicated that they did not think they

would like the military, 17 percent decided to do something else, 6 percent

7Others who did not meet the physical examinations or were in the

delayed entry program were not asked these questions.

8Persons who had not completed nine years of schooling or who had

completed college are not considered.
109

Table 6.5 Primary Reasons Never Served in Armed Forces Among Youth

18-21, by Race, Sex and Degree of Enlistment Effort: 1979

(Percentage distribution)

Race and

sex Males Females

Reason Total White Black Hispanic Total White Black Hispanic

All respondents

who talked to a

recruiter (000) 2908 2325 456 127 1775 1352 333 91

Total percent 100 100 100 100 100 100 100 100

Else 17 17 19 20 23 24 17 31

Dislike 21 24 11 13 22 24 16 12

School 23 23 21 26 18 18 17 24

Civilian job 6 7 6 5 2 2 1 1 Other 33 29 43 36 35 32 49 32

Talked to a

710 469 198 43 276 150 99 28

recruiter and plan

to enlist (000)

Total percent 100 100 100 100 100 100 100 100

Else 18 21 13 9 18 18 15 34

Dislike 9 10 7 13 7 6 10 7

School 24 24 22 28 22 27 16 14

Civilian job 5 5 6 2 1 0 2 0

Other 44 40 52 48 52 49 57 45

Talked to a

recruiter and took

ASVAB (000) 829 635 161 34 501 371 99 31 Total percent 100 100 100 100 100 100 100 100

Else 17 17 22 8 27 30 12 43

Dislike 19 22 9 8 16 17 17 6

School 18 17 15 35 14 14 12 22

Civilian job 7 8 3 10 2 2 3 0

Other 39 36 51 39 41 37 56 30

Passed all

entrance exams

000 183 137 39 7 50 41 7 2

Total percent 100 100 100 100 100 100 100 100

Else 10 9 a a a a a a Dislike 9 10 a a a a a a School 23 27 a a a a a a Civilian job 9 9 a a a a a a Other 49 45 a a a a a a

aLess than 25 sample
110

got a better civilian job, and the remaining 33 percent gave a variety of

other reasons. Among females the figures were 18, 23, 22, 2, and 35 percent,

respectively. Among the persons listing other reasons, some of them

indicate that they have not yet made a decision not to join. Nearly one

million of the young who have spoken to a recruiter, but not served in the

military, answered affirmatively the question indicating a positive intention

to enlist in the military in the future.9

The categories of answers are not totally specific. We do not know

whether the "something else" the youth decided to do was work or school,

and we have a large proportion who gave various reasons which were not on

our precoded list. We, therefore, thought it appropriate to examine the

status of the persons who spoke to a recruiter but did not enlist (See

Table 6.6) at the time of the interview. Approximately two-thirds of both

the men and women were employed while about four-tenths were enrolled in

school (these are not mutually exclusive categories). Thus, while a relatively small proportion of the youth said that they did not enter the military

because they got a better job, a large majority ended up in civilian

employment. Likewise, about two times more people ended up in school than

listed this as their reason for not enlisting.10 The employment and enrollment

statuses of other (although overlapping) groups who talked to a recruiter--

9We also examined the reasons given by two other subgroups of persons

who contacted a recruiter; those who had taken the Armed Services Vocational

Aptitude Battery (approximately 830,000 men and 500,000 women) and those

who had passed the entrance examinations but then not enlisted (180,000

men and 50,000 women). Their reasons for not enlisting are similar to those

for the entire population. See Table 6.5.

100f course, the individual may have made the decision not to enter the

military prior to deciding to go on to school or before accepting civilian

employment. Thus, there could be a mismatch between the reason given for

nonenlistment and activity at the time of the survey because of the different

dating of the responses.
111

Table 6.6 Enrollment and Employment Status At Time of Interview Among Youth 18 to

21 Years Old, by Race, Sex and Degree of Enlistment Effort: 1979

Race, sex

Characteristics

Males Females

Total White Black Hispanic Total White Black Hispanic

All respondents who

2,908 2,325 456 127 1,775 1,352 333 91

talked to a

recruiter 000)

Percent enrolled 40 39 42 44 35 32 46 37

Percent employed 72 75 57 66 60 63 48 57

Talked to a recruiter

469 198 43 276 150 99 28

andilan to Enlist

(000) 710

Percent enrolled 42 43 37 46 38 29 51 36

Percent employed 63 66 56 63 57 61 47 68

Talked to a recruiter

and took ASVAB Test

(000) 829 635 161 34 501 371 99 31

Percent enrolled 30 28 35 45 31 28 44 29

Percent employed 78 81 68 61 57 60 44 52

Passed all entrance

2.12xaminations

(000) 183 137 39 7 50 41 7 2

Percent enrolled 40 44 a d a a a a Percent employed 74 79 a a a a a a

aLess than 25 sample cases.

132
112

those who plan to enlist, those who too the Armed Services Vocational

Aptitude Battery (ASVAB) and those who passed the entrance examinations

--are not much different.

Based on these data it is not clear exactly how important civilian

employment is as an alternative to young men and women considering the

service. The substantial number attending school and the finding that this

was the most often cited single reason for nonenlistment implies that

additional educational incentives may be a more effective recruiting (and

retention) device than an increase in military pay. Obviously to the extent

that the services can identify the factors that shape the attitudes of young

people to believe they will dislike military service and alter these factors

or compensate for the disliked conditions, recruiting might also increase.

This may not be an option, however, since there are some disamenities

associated with military service which are unalterable (e.g., discipline).

Attitudes Toward Military Service of Significant Others

A major factor affecting a young person's enlistment propensity is the

attitude toward service by his "significant other"-- that is, the person whose

advice is considered most in important decisions. See Table 6.7.

In order to examine the attitudes of significant others toward various

life and career decisions, all youth aged 14 through 17 were asked, "Who

has influenced you the most on how you feel about things like school,

marriage, jobs, and having children?" The respondents were then given a

list of possible influencers ranging from parents through peers, sibling,

other relatives, to "another type of person." About 70 percent selected

one or both of their parents. Even though males were somewhat more likely

than females to name parents, and were less likely to select peers, there

are no major differences by either race or sex.
113

Table 6.7 Proportion Intendiny to Enlist Among Youth 14 to 17 Years of

Age Who Never Served by Race, Sex and Attitude of Significant

Other: 1979

(in percent)

Race and Sex t Males Females

Attitude

toward

enlistment by

significant others

Total White Black Hispanic Total White Black Hispanic

Strongly Approve

Somewhat approve

Somewhat disagree

Strongly disagree

35

57

2116

23

54

19

14

45

67

32

20

48

69

29

30

13

35

7

6

10

26

5

5

30

6120

14

24

43

18

9
114

Respondents were then asked how their respective princiral influencer

would feel toward various life and career decisions. The hypothetical

decisions involved both positive and negative events and included the

following:

Become a carpenter

Join the Armed Forces

Become an accountant

Become an electrical engineer

Not go to college

Move far away at age 21

Never have children

Response categories were based upon a scale from one to four, with one being

equal to "Strongly Disapprove." Thus the higher the number, the more

supportive the significant other is perceived to be for that particular

decision. The neutral point would be 2.50.

Table 6.8 presents the perceived support from significAnt others for

the seven hypothetical decisions, by sex. Parents are seen to be mildly

positive toward joining the Armed Forces by males, and mildly negative

by females. The least supportive group for joining Llw Armed For:es, for

both males and females, is peers. Of the seven possibil:tles, the most

negative thing, either males or females, could do in the eyes of parents

is not go to college. Apparently college attendance by sons and daughters

continues to be viewed as very important in the value system of parents as

seen by their children. Thus, if parents continue to be the major group of

significant others as the youth reach enlistment age and parents are viewed

as valuing college attendance highly, then post service educational incentives

may well be more effective than improved military wages in attracting recruits.
115

Table 6.8 Mean Support for Life Decisions of Youth 14 to 17 Years cf Age, by Types of Significant Others and Sex of Respondent: 1979

Life decision

Unrelated

adult

Parents Unrelated

peers

Sibling

or

Spouse

Other Total

Percent choosing this group 6 70 12 6 6 100

You decided to become

a carpenter.

Female 2.46 2.64 2.47 2.53 2.38 2.60 Male 3.07 3.23 3.28 3.27 3.36 3.24

You decided to k,come:

an accountant.

Female 3.19 3.49 3.29 3.34 3.43 3.43 Male 3.10 3.34 3.01 3.23 3.31 3.28

You decided to 1)2come

an electrical engineer.

Female 2.76 2.90 2.57 2.66 2.68 2.81 Male 3.37 3.50 3.46 3.45 3.51 3.49

Yeti decided to join the

armed forces.

Female 2.17 2.31 1.95 2.13 2.04 2.23 Male 2.73 2.81 2.40 2.53 3.04 2.75

You decided not to go

to college.

Female 1.74 2.01 2.05 2.14 1.82 2.00 Male 1.99 2.01 2.43 2.23 2.03 2.07

You decided to move far

away from where your parents

live when you are 21.

Female 2.60 2.27 2.57 2.49 2.11 2.34 Male 2.51 2.37 2.68 2.68 2.50 2.43

You decided never to

have children.

Female 2.11 2.31 2.18 2.31 2.29 2.27 Male 2.34 2.22 2.20 2.31 2.22 2.23
Table Cl

116

Appendix C

Proportion With Positive Attitude To Armed Forces and Intending

To Enlist Among Youth 14 to 21 Years of Age Who Never Served,

by Year of Age, Race and Sex: 1979.

(In Percent)

Race

.-- Total White Black Hispanic

Sex

11 rumber

thousand) Percent

Total

number

(thousand)

Males

Percent

Total

number

(thousand) Percent

Total

number

(thousand) Percent

14 1,581 34 1,255 33 214 36 112 34 15 2,198 33 1,719 32 325 31 155 44 16 2,044 28 1,639 24 276 41 129 43 17 2,063 25 1,631 21 291 38 142 41 18 2,033 22 1,599 18 300 34 133 34 19 1,985 16 1,633 13 246 32 106 21 20 1,947 10 1,609 8 220 21 118 15

21 1,770 7 1,448 4 217 22 105 19

Total 15,621 22 12,533 19 2,089 33 1,000 33

females

14 1,461 12 1,159 9 194 24 108 11 15 2,068 14 1,625 10 309 28 134 28

16 2,032 14 1,627 11 283 24 123 21

17 2,034 9 1,641 5 274 23 120 23

18 2,067 11 1,620 8 312 22 135 18 19 2,154 7 1,741 4 285 22 127 18 20 1,985 6 1,578 4 281 15 126 8

21 2,119 4 1,683 2 301 12 135 8

Total 15,920 9 12,674 6 2,239 21 1,008 17
117

Table C.2 proportion With Positive Attitude to Armed Forces and Intending to Enlist

Among Youth 14 to 21 Years of Age Who Never Served, by Age, Race, Sex,

and Selected Characteristics: 1979

Race, Sex Ma es _ Fema es

Characterist c Total Whfte Black Hispanic Total White Black Hispanic

Education of Parent

/tie 14-17 29 27. 37 41 12 9 2.5 21

Less than 12 years 38 35 40 43 19 14 32 23

12 30 29 35 39 11 8 22 21

13 years or more 22 21 28 31 7 6 15 15

A.e 18-21 14 11 28 23 7 4 18 13

Less than 12 years 22 17 34 27 11 6 21 17

12 12 10 26 17 6 5 15 10

13 years or more 9 8 18 14 4 3 14 3

High School Seniors 18 14 35 32 9 6 22 23

Less than 12 years 34 30 47 30 20 12 34 33

12 20 18 29 a 6 4 19 a 13 years or more 9 7 27 a 5 5 0 a Family Income

A.e 14-17 29 27 37 41 12 9 25 21 Less than $10,000 38 34 40 48 21 14 28 30

$10,000 or more 27 26 31 33 10 8 20 15

A'e 18-21 14 11 28 23 7 4 18 13

Less than $10,000 16 9 34 26 9 6 19 11 $10,000 or more 13 12 21 19 6 4 18 16

High School Seniors 18 14 35 32 9 6 22 23

Less than $10,000 27 17 45 a 23 13 33 a $10,000 or more 18 16 31 29 5 4 15 18
118

Table C.2 (continued)

"---

Race, Sex Ma es Fema es Characteristic Total White Black hispanic Total White Black Hispanic

Educational Expectations

A.e 14-17 29 27 37 41 12 9 25 21 Less than 12 years 46 45 49 49 13 9 27 39

12 34 31 43 43 16 12 33 20

13-15 27 25 32 35 9 7 19 20

16 years or more 23 21 27 37 9 7 18 20

A.e 18-21 14 11 28 23 7 4 18 13

'Less than 12 years 25 22 40 26 5 2 24 8

12 18 14 38 29 7 4 20 17

13-15 14 13 21 15 8 6 16 17

16 years or more 8 5 18 21 6 4 17 10

High School Seniors 18 14 35 32 9 6 22 23

Less than 12 years a a a a a a a a 12 25 20 51 39 13 7 37 a 13-15 21 22 a a 9 8 18 a 16 years or more 11 7 25 32 5 3 12 17
119

Table C.2 (continued)

Race, Sex Ma es Fema es Characteristi Total White Black Hissanic Total White Blac Hispanic

Health Status

A.e 14-17 29 27 37 41 12 9 25 21 Does not affect work 30 28 37 42 12 9 25 21 Affects work 23 22 37 a 14 11 22 24

Ae 18-21 14 11 28 23 7 4 18 13

Does not affect work 14 11 28 23 7 4 18 13

Affects work 19 16 33 a 7 5 14 17

High School Seniors 18 14 35 32 9 6 22 23

Does not affect work 18 15 35 33 9 6 22 23

Affects work a a a a 6 a a a
120

Table C.2 (continued)

Race, Sex Ma es Fema es

Characteristic Total White Black Hisonlc Total White Black Hisonic

Knowledge of the World

of Work Score

Ase 14-17 29 27 37 41 12 9 25 21 0-5 32 29 38 40 14 8 27 22

6-7 29 27 36 39 12 10 22 19

8-9 27 26 29 44 10 9 19 23

A.e 18-21 14 11 28 23 7 4 18 13

0-5 17 12 30 23 8 3 21 14

6-7 14 12 25 24 5 3 17 9

8-9 9 8 25 21 7 6 9 16

High School Seniors 18 14 35 32 9 6 22 23

0-5 22 16 37 38 10 3 30 20

6-7 15 12 29 24 7 5 8 36

8-9 16 14 28 a 10 9 23 a Internality (Ratter)

Score

A.e 14-17 29 27 37 41 12 9 25 21 4-8 29 28 32 41 11 9 23 21 9-16 30 26 40 40 12 8 27 22

A.e 18-21 14 11 28 23 7 4 18 13

4-8 14 11 28 21 6 4 13 12

9-16 14 11 28 24 8 4 23 15

High School Seniors 18 14 35 32 9 6 22 23

4-8 17 13 40 29 7 4 23 23

9-16 19 16 31 35 11 7 22 24

aLess than 25 sample cases.
121

Table C.2 (continued)

Sex Males Females

Characteristic Total White Black Hispanic Total White Black Hispanic

Employment Status

A'e 14-17 29 27 37 41 12 9 25 21 Employed 27 26 39 39 9 7 32 23

Unemployed' 33 29 41 41 14 10 23 28

Age 18-21 14 11 28 23 7 4 18 13

Employed 12 9 29 21 6 4 18 15

Unemployed 27 24 30 40 10 5 20 21 High School Seniors 18 14 35 32 9 6 22 23

Employed 17 13 42 41 7 4 20 34

Unemployed 29 25 37 a 15 10 29 a Age 18-21 14 11 28 23 7 4 18 13

Marital Status 14 11 28 23 7 4 18 13

Married, spouse

present 10 8 a 25 2 1 9 5 Never married 14 11 29 23 8 5 20 17

Grade Attending

Attending high

school 24 19 38 38 15 9 28 27

Attending college 6 5 14 12 5 3 17 7 Educational attainment

9-11 years 23 18 39 33 12 8 25 19

12 11 9 23 11 6 4 17 12

13 years or more 5 4 10 16 3 2 8 6
Chapter 7 SAMPLE DESIGN AND WEIGHTING

INTRODUCTION

The 1979 National Longitudinal Survey of Youth made use of three independent probability samples. Two of these samples were designed to cover the

non-institutionalized, civilian population in the age range 14-21 (as of

January 1, 1979). A third sample was designed specifically to cover the

military portion of the '14-21 age cohort.

The two samples which cover the civilian portion of the age cohort will

be referred to by the terms "cross-sectional" and "supplemental." The study

design for the 1979 National Longitudinal Survey of Youth required exteAsive

disproportionate oversampling among Hispanic, Black, and Economically Disadvantaged non-Hispanic non-Black youth. The cross-sectional sample was designed

to yield approximately 3,000 males and 3,000 females, with various racial,

ethnic, and income groups represented in their proper population proportions.

The supplemental sample was designed to produce, in the most statistically

efficient way, the required oversamplvi of Hispanics, Blacks and Economically

Disadvantaged non-Hispanic non-Blacks. The distribution of year one sample

cases across these two samples is shown in Table 1.

122
123

TABLE 1

DISTRIBUTION OF COMPLETED CASES ACROSS

CROSS- SECTIONAL AND SUPPLEMENTAL SAMPLES

Sample Size

Population Group Cross-Sectional Supplemental Total

Male

Hispanic 207 716 923

Non-Hispanic Black 342 1,101 1,443

Economically- Disadvantaged 166 756 922

Other 2,290 2,290

Female

Hispanic 215 734 949

Non-Hispanic Black 399 1,078 1,477

Non-Hispanic Non-Black

Economically Disadvantaged 163 915 1,078

Other 2,330 2,330
124

CROSS-SECTIONAL SAMPLE

The cross-sectional sample used f,r the non-institutionalized civilian portion of the 14-21 youth cohort based upon the 102 PSU NORC National Probability Sample. This sample was developed and initially used in 1973. The

sample has been continuously updated since that time. The sampling frame

covers the continental United States.

Stare I. The Primary Sampling Units are composed of: Standard Metropolitan Statistical Areas (SMSAs), counties, 1 parts of counties, 2 and

independent cities. Stratification criteria used in the first stage of

selections include: Census Division, SMSA-nonSMSA, county size, and percentage black. The selection of primary units was carried out with probabilities proportional to 1970 Census population (PPS), using replicated

"zone" selection. A total of 204 PSUs was selected. In this survey, we

made use of two of the four replicates comprising 102 PSUs.

Stage II. The secondary units of seleCtion are block groups (BGs) in

areas for which Census blocks hive been designated, and enumeration districts

(EDs) in unblocked areas. Prior to selection, the secondstage (within-PSU)

frame of EDs and BGs was stratified on the basis of median family income and

percentage black. 3 For each primary sampling unit, eighteen secondary

selections were made with probability proportional to size from eighteen

equal-size zones. A subsample of nine secondary units was used for the 1979

1

Where necessary, counties were combined so that th'ir aggregarcd

1970 population exceeded 12,000.

2 In New England, we defined the portion of a county outside an SSA

as a PSU.

3 In areas that were not tracted, median household income and pPrcentage black were estimated using a regression routine based on M('D c:

tract information.
125

National Longitudinal Survey of Youth.

Stage III. Whenever possible, secondary selections were subdivided4

into third stage listing units (segments).5 One listing unit was then

selected for each secondary selection with probability proportional to

estimated housing. If it was impotsible to subdivide a secondary selection

into well-defined subunits, this stage of sampling was bypassed (i.e., subsampling at Stage III was accomplished with probability one).

NOR interviewers have carried out dwelling unit listing within all

third-stage segments. Prior to initial use, those listings were subjected

to a number of checks.6 In order to maintain an accurate record of dwelling units, master sample listings are periodically updated. This updating

procedure occurs at the end of the field period for each research study.

During the updating period, and in conjunction with NORC "missed dwelling

unit" procedure, information is gathered regarding changes in the entire

segment (e.g., demolition of DUs, new construction). This information is

then integrated into our computer-based Master Listing of NORC PSUs.

Stage IV. Approximately 20,500 listed DUs and IQs 7 were screened

(household rosters were obtained) from the cross-sectional sample. Stage

III segments were subsampled in order to produce an equal probability sample

of households and individual quarters distributed among the 909 segments

(102 PSUs x 9 segments per PSU). Selection of these listings was accomplished

through the use of ANSPAK (NORC's computerized sampling program package).

There were an average of twenty-two selected dwelling units and IQ's per

sample cluster resulting in an average of 6.8 inscope youths. All inscope

youths found in this screening stage were designated for subsequent interview.

4 For BCs we employed Block Statistics, for EDs we made field counts.

S The minimum size for listing units was 100 DUs.

6 A comparison was made with Census estimates and/or field counts. Also, a number of internal consistency checks for sequential listing and procedures were initiated.

7 INDIVIDUAL QUARTERS (IQ) is a term used to describe non dwelling

unit non-institutional living quarters'

140
126

SUPPLEMENTAL SAMPLE

As aoted previously, this sample was designed specifically to yield a

highly efficient sample of the three youth cohorts designated for over-sampling

(i.e., Hispanics, non-Hispanic Blacks, and non-Hispanic non-Black economically

disadvantaged). Thus for this sample, stratification specifically relevant for

these groups was used. In addition, Probability Proportional to Size (PPS) procedures were based on size measures for these cohorts rather than the general population. In multi-stage samples, PPS procedures are used in order to achieve

control over the distribution of sample cases among the primary sampling units and

within the ultimate clusters that form the primary sampling units. By using

size measures basea on the three over-sampled cohorts, it was possible to

more nearly equalize the distribution of these groups among the various sampling

units than would have been possible in a cross-sectional design which used PPS

procedures based on total population.

STAGE I

Primary sampling units consisted of counties and independent cities.

First-stage selection of these units was carried out with probabilities

proportional to measures of size that reflected the black, Hispanic and

economically disadvantaged population within the PSU. These measures of size

were constructed from the 1970 Census Fifth Count (File C), which provided

required estimates at the enumeration district-block group level within each

county and independent city. Prior to use, 1970 size estimates were updated

to 1977 Census estimates on a county basis.

For each primary sampling unit a measure of size was constructed as MOST H + .5 x B i+ ED

i

where H

i

and ED

i denote the estimated population sizes for Hispanics,

blacks and economically disadvantaged non-Hispanics non-Blacks respectively.

Given that the measures of size need only reflect relative population

size, and given the relatively uniform ratio of estimated 14-21 cohort to

total population, no attempt was made to reapportion size measures to the youth

cohort. The factor of .5 applied to the Black population in the construction of

PSU measures reflected the fact that among the three population groups of

interest the oversampling rate for Blacks was approximately one half the rate
127

to be used for Hispanics and economically disadvantaged non-Hispanic nonBlacks. Prior to sample selection, PSUs were stratified on the basis of

the 9 standard Census Divisions. Within each of these divisions, further

stratification was based upon Urban-Rural location (within or outside

and SMSA). Finally, within each of the 18 major strata (9 divisions x 2

urban/rural classes) PSUs were ordered by proportion of PSU population containing target group members. A systematic "zone" selection procedure was

used to select 100 Primary Sampling Units with probabilities porportional to

the previously discussed target group measures of size.

STAGE II

Within selected primary units, the units of second stage selection were

either Census block groups or enumeration districts. These second stage sampling units were assigned measures of size by the same procedure that had been

used in constructing measures at the first stage of sampling. Since the first

stage measures had been created by aggregating information at the block group

and enumeration district level, from the Fifth Count File C Census tape, the

process of assigning second stage measures was simply a disaggregation procedure.

Prior to selection, second stage units were sort ordered by estimated

proportion of population containing members of the target population. Adjoining units were then linked, when necessary, in order to have a minimum

size measure of 25.

Within each selected primary sampling unit, nine secondary units were

selected using a systematic zone procedure with probabilities proportional

to to..Eat group measures of size.

STAGE III

Whenever possible, selected secondary selections were subdivided into

third stage listing units (segments). One listing unit was then selected

for each secondary selection with probability proportional to estimated

housing. If it was impossible to subdivide a secondary selection into well

defined subunits, this stage of sampling was bypassed (i.e. subsampling at

stage III was accomplished with probability one). It should be noted that

because measures of size used at stages one and two were based upon target

population rather than total population, the number of housing units con-
128

tained within any two third-stage segments with the same measure of size

might be quite different. In general, we tried to make use of third stage

segments containing measures of size in the range 25-50 with between 50 to

500 housing units.

NORC interviewers carried out dwelling unit listings within all 900

third stage segments. Prior to use, these listings were subjected to a

number of internal and external checks. Listers were 'required to seek out

reasons for differences between number of housing units found at the time

of listing and the number of housing units reported by the 1970 Census.

Within each block, checks were made, where possible, for consistent ordering of street numbering of listed units.

STAGE IV

The fourth stage of selection involved selecting a sample of dwelling

unit and individual quarters listings within the 900 selected third-stage

segments. Screening, which involved enumeration of all persons within

selected dwelling units (cm a family unit basis) was conducted in two Waves.

In general, selection of third stage listings was carried out with probabilities designed to equalize the overall probability of selection through the

four stages of sampling. However, there was some degree of oversampling

(increased probability of selection) among third stage units which were

estimated to contain a higher proportion of individuals in the three population groups designated for overrepresentation (i.e. Hispanics, non-Hispanic

Blacks, and economically disadvantaged non-Hispanic and non-Blacks).

The fourth stage of sampling resulted in the selection of approximately

65,000 listed lines (dwelling units and indidividual quarters) over the 900

third stage segments.

STAGE V

Family unit screening of selected dwelling units and individual quarters

selected at stage IV produced somewhat more individuals in the Hispanic and

non-Hispanic Black cohorts than were required. As a result, it was necessary

to select a subsample of these individuals for base year interviewing. Table

II shows the number of individuals in each of the six oversampled cohorts

that were located in the screening phase and the number selected for base

year interviewing.

149
129

TABLE II

NO. OF INDIVIDUALS LOCATED IN SCREENING AND DESIGNATED

FOR BASE YEAR INTERVIEW-SUPPLEMENTARY SAMPLE

DESIGN COHORT

MALES

LOCATED IN SCREENING SELECTED FOR BASE YEAR

INTERVIEW

HISPANIC 1,015 854

NON-HISPANIC 1,318 1,268

BLACK

ECONOMICALLY 887 886

DISADVAIIAGED

(non-hispanic

non-black)

FEMALES

HISPANIC 1,060 855

NON-HISPANIC 1,502 1,204

BLACK

ECONOMICALLY 1,073 1,073 DISADVANTAGED

(non-hispanic

non-black)
130

Procedures used for the selection of individuals. for base year interview

were designed to equalize, as much as possible, final overall probabilities

of selection for individuals within the same design cohort. Specifically,

since some degree of differential oversampling was applied in the fourth

stage selection of dwelling units for screening, individuals located in the

screening process had not been selected with the same probabilities. Within

the constraints of probability sampling, probabilities associated with the

stage five subsampling process were set inversely proportional to the probabil

ities of selection for prior stages (i.e. product of stages one through

four). As a result, the variation in probability of selection among individuals

(within a design_ -t) retained in the sample after stage five was decreased

from the variation 4.t, probabilities among all screened individuals within the

same design cohort.
131

SPECIAL PROCEDURES USED IN BOTH THT. CROSS-SECTIONAL AND SUPPLEMENTAL SAMPLES

There were several special procedures used in both the cross-sectional

and supplemental samples to accomplish the following goals:

1. Inclusion of Dwelling Units in the sample which were either missed

in the listing process or were constructed after the listing process

took place.

2. Inclusion in the bample of non-college individuals living in non- institutionalized, nor-duelling unit living arrangements.

3. Inclusion in the sample of college students living in non-dwelling

unit quarters.

PROCEDURES FOR TNCLUSION OF 'MISTED (MISSED) DWELLING UNITS

As part of its standard field methods, NORC makes use of a procedure to

give a proper probability of selection to dwelling units that did not exist

or were missed at the time of original listing or during segment updating.

The method we employ is an app7ication of the half-open interval technique.

This procedure explicitly links every nonlisted DU in a segment wit). exactly

one listed DU is that segment.

It should be noted that through the implementation of the ha:I-open

interval procedure each listed dwelling unit represents a cluster of dwelling

units. This cluster is composed of the listed DU (line) and any other missed

D'Js associated with that line.

Conceptually, the procedure is simple. The set of DU listings (lines)

for a segment is made up of one or more subsets of lines (blocks). Each

block consists of an ordered set of lines. Each of the lines represents

either a complete structure (i.e., a single-family dwelling unit) or a subunit

within a structure (i.e., an apartment in an apartment building or complex).e

Whenever a line is selected that is a complete structure, all dwelling units

within that structure are included in our sample, as are any dwelling units

berween9 the selected structure and the next structure listed in the same

block."

8 Even if a listing contains a within-structure description (e.g., 304

Main, 2nd floor) it is considered a structure listing if there is no other

listing that refers to that structure.

9 If structures have numbered street addresses, "between" is defined in

terms of these address numbers. In areas where numbers are not used, "between"

is defined in terms of location.

10 The listings within each block are considered circular (i.e., the last

listing within a block is followed by the first).
132

If a selected line is a complete structure, our insturctions to the interviewer are as follows:

(selected line description)

Message 1: Check for missed DUs at the addtess above.

Check for missed DUs between street address

above and street address below.

(next listed line description)

For each listing that identifies a subunit within a structure, there

must be at least one other listing within the same structure." Our listings

are so ordered that for each structure in which subunits are listed there

must be a unique first-subunit and a unique last-subunit listing.

When we select the first subunit in a multiple structure, we include in

our sample all dwelling units that exist within the selected subunit, as well

as any dwelling units within the structure that are not already listed. When

the first subunit of a multiple structure is selected, the following instruction is given to the interviewer:

(selected line description)

Message 2: Check for missed DUs at this apt.

number.'

Check for DUs at this street address

not listed on the (attached) segment

printout.

When the selected line is the last subunit listing of a multiple structure,

we include in our sample all dwelling units within the selected subunit and

all dwelling units between the structure in which the subunit is contained

and the next listed structure in the block. Here the instruction to the

interviewer is:

(selected line description)

Message 4: Check for missed DUs at this apt.

number.

Check for missed DUs between this

street address and the street address

below.

(next listed line description)

If the selected line is a non-first/non-last subunit listing, we include

in'the sample only dwellings within the selected subunit. In this case, the

following instruction is used:

(selected line description)

Message 3: Check for.missed DUs at this apt. only.

11 This follows from the definition of a listing as either a complete

structure listing or a subunit within structure.
133

PROCEDURES.TO INSURE COVERAGE OF THE NON-DU POPULATION (COLLEGE DORMS AND

OTHER GROUP QUARTERS)

Since the initial cohort definitions include civilian youth aged 14 to

21 living in all noninstitutional settings, special procedures were used to

insure appropriate sample coverage in living units not classified as dwellings.

These nonDU living units include college dormitories and other group quarters.

In past surveys of the noninstituticnal adult population, NORC has used

a single procedure to obtain sample coverage of the nonDU, noninstitutional

civilian population. Because of the restricted age distribution in the

proposed survey, NORC made use of two procedures. One of these procedures

was used to cover the noncollege portion of this nonDU population: another

procedure was used for college students.

PROCEDURES FOR THE INCLUSION ON NONCOLLEGE "GROUP QUARTERS"

The inclusion of the noncollege, noninstitutional, nonDU population aged

14 to 21 was accomplished by the folloWing two-stage procedure. The first

stage was carried out prior to the beginning of field interviewing. Each

segment in use for the survey was field enumerated for all group quarters

structures, except college dormitories. Within these group quarters structures,.

a complete listing of individual quarters (IQs: beds and/or rooms with beds)

was undertaken. The listing of IQs was then subsampled using the same finalstage selection procedure applied to dwelling units within the segment.

The second stage in the NORC group quarters sampling procedure was

carried out at the time of screening in conjunction with the standard NORC

missed dwelling unit procedure. All group quarters except college dorms that

were not explicitly listed in the first step of the individual quarters

procedure were eligible for selection at this stage. These non-first-stage

group quarters are implicitly linked to listed dwelling units by the same

linking rules applicable to nonlisted dwelling units. For each selected

dwelling unit, a check was made for implicitly linked but unlisted dwelling

units as well as for implicitly linked but unlisted individual quarters

units. As is the case with our missed dwelling unit procedure, the instructions

for the missed individual quarters procedure were computer-generated for each

selected dwelling unit. The interviewer was provided with specific instructions

indicating the appropriate DU/IQ checks that must be carried out at each

selected dwelling unit.

154
134

SPECIAL PROCEDURES FOR COLLEGE STUDENTS

As of October 1976, approximately one-third of the civilian population

between the ages of 18 and 21 was enrolled in college.12 In many household

surveys the coverage of the college population is haphazard and ill-defined.

Given the nature of the proposed research, special procedures were used to

insure complete coverage of this portion of the youth cohort.

Through a set of explicit rules, every full- or part-time college

student was "linked" to a unique living unit that had a known probability of

entering the sample. These rules "link" college students who live in a non-DU

setting (Dorms) away from their parents' homes for parts of the year to their

parents' home. This alternative was chosen for both sampling and operational

reasons. From a sampling standpoint, linkage of college students living in

non-DU settings to parents' DUs will tend to minimize the occurrence of small

area "pockets" of inscope population and the resulting large variability in

cluster size. From the standpoint of field operations, the parents' home

represents a contact location of relative stability. This will be most crucial

in the yearly follow-up efforts.

The specific linkage rules are as follows:

College students who live in a specified dwelling unit on a yearround basis are linked to that dwelling unit.

. College students whn do not live in dwelling units on a year-round

basis are linked to their parents' or guardians' DUs.

. In situations where the application of this condition results in

multiple linkages (e.g., divorced or separated parents living in

two separate DUs), a unique linkage is established on the basis

of maximum financial support.

Should this condition not provide a unique linkage, the following priority

scheme is used:

Living natural or adoptive mother

Living natural or adoptive father

Living female guardian

Living male guardian

12 Source: U.S. Bureau of the Census School Enrollment-Social and

Economic Characteristics of Students P20N309
135

Should these rules provide no linked DUs, a student was linked to his

or her non-year-round place of residence.

In order to implement this procedure, we collected potential linkage

information at all sample.DUs and CQs (i.e., we asked parents about children

that are away at school). In most situations, unmarried college students

in the 14 through 21 cohort were linked to their parents' DU; married couples

or cohabiting couples living in DUs on a year-round basis were linked to

their own DUs, married couples or cohabiting couples not living in a DU on a year-round basis were linked to their respective parents' DUs.

156
136

SAMPLE OF YOUTH COHORT IN ACTIVE MILITARY SERVICE

As of September 30, 1978, there were 657,549 members of the Active Armed

Forces who would be between the ages of 17 and 21 as of January 1, 1979.

Individuals in this group were sampled by a stratified, two stage selection

procedure. The sample design for this portion of the youth cohort was

developed in cooperation with DOD, Defense Manpower Data Center, the Rand

Corporation DOD Survey Group, the NLS staff and NORC. Actual selection of

sample individuals was carried out jointly by DOD, Defense Manpower Data

Center and NORC.

The basic sample design called for the selection of a sample of approximately 1300 members of the active armed forces. In order to provide samples

of sufficient size for separate estimates with respect to sex, it was decided

to sample females at a rate approximately six times that used for males.

This would produce approximately. 850 males and approximately 450 females.

Within each group, all individuals were to be sampled with equal probability.

Within each sex, the sample was stratified on the basis of branch of service

and geographic location. Proportionate allocation was used with respect to

these stratification cells. Sample selection was carried out in two stages.

STAGE 7:

Each of the four armed services (Army, Air Force, Navy and Marine Corps)

maintains up to date lists of all personnel. Included in these lists is information about age, sex and assignment UIC (unit identification code). It would

have been possible to sample individuals from these lists directly in a single

stage of sampling (i.e. simple random element sampling), however. because

of the face-to-face nature of the base Year interview, it was decided to

make use of cluster sampling.
137

The primary units of sample selection were composed of individuals within

the same unit identification code. This unit code typically defines a group

of individuals residing at the same physical location. Over all services there

Were a total of 12,488 UIC's containing one or more persons in the 17 21

youth cohort. Because of the differential sampling rates to be applied to

males and females, these UIC's were first separated into two groups: Group 1

consisted of UIC's with no females in the 17 21 cohort; Group 2 consisted

of UIC's with at least one female in the 17 21 cohort.

Each of the two groups of UIC's was divided into 20 basic strata, defined

on the basis of armed service branch and geographic location as follows:

I. ARMED SERVICE BRANCH: (4 branches)

A. ARMY

B. NAVY

C. AIR FORCE

D. MARINE CORPS

II. GEOGRAPHIC LOCATION (5 categories)

A. EASTERN UNITED STATES

B. WESTERN UNITED STATES

C. EUROPE

D. FAR EAST

E. OTHER

Within each of these 20 bhsic strata UIC's were linked together in order

to form primary sampling units (PSU's) as follows:

1. UIC's in group 1 (males only) were linled in order to form PSU's

with a minimum of 20 males.

2. UIC's in group 2 (at least one female) were linked in order to

form PSU's with a minimum of 20 males and 10 females.

1
138

In the .linkage process, attempts were made to

distance among UIC's within the same PSU. This linka ; r0e6;*.t 1:(!1.1f.

the formation of 3,711 group 1 and 2,256 group 2 PSU's across the 20 basic

strata.

First stage selection of PSU's was carried out within each of the 20

basic design strata separately for males and females. Within each sex the

probability of selection for a PSU was proportional to the number of 17 21

youth (of that sex) within the PSU.

Let MOSmi = the number of 17 21 males within the ith

PSU

MOS

fi = the number of 17 21 females within the ith

PSU

For the male sample, the probability of selection for the ith

PSU was

150 MOSmi f = mi 579,508

For the female sample, the probability of selection for the ith PSU was

110 MOS

fi

f =

fi 47,305

For both the male and female samples the probability of selection for

the ith

PSU was constrained to an upper limit of unity. Thus, any PSU whose

measure of size for males (MOS ) exceeded 579,508/150 . 3863.38 was selected mi

with certainty. Any PSU whose measure of size for females (MOS

fi) exceeded

47,305/110 = 430.05 was selected with certainty.

It should be noted that although separate samples were selected for males

and females, a form of the Keyfitz procedure was used in order co maximize

the 'overlap between PSU's selected for the male sample and PSU's selected

for the female sample.

In total, 146 PSU's were selected for the male sample and 103 PSU's were

selected for the female sample. The overlap among these units was 58.
139

STAGE IIa

Within PSU selection was carried out by DMDC. On the basis of specifi

cations provided by NORC. selected PSU's were subsampled at the rates 13.35/MOSmi

for the mai:, sample and 9.35/MOSfi for the female sample. In those instances

where stage sne PSU selection had been made with certainty (probability a 1)

within PSU selection was carried out with sampling rates 1/289.3922 for male

sample PSU's and 1/45.7495 for female sample PSU's. This sampling produced

a list of 3,073 persons.

STAVE TIb

The sample produced at Stage IIa was systematically subsampled at a rate

of one in two in order to provide 1,537 names. Prior to subsampling the Stage

lla list produced by DMDC was ordered by PSU in order to assure that all PSU's

would be included in the subsample. Subsequently, an additional subsample of

256 names were selected by systematic selection from the remaining unselected

names on the DMDC Stage IIa sample list.

In combination these sub3amples produced a uniform stage IIb subsample

rate of 1792.5/3073.

OVERALL SAMPLING RATES

The stages of sampling described above produced the following over all

sampling rates:

150 MOSmi 13.35 1792.5 f(males) = = 1/496.124 579,508 MOSmi 3073

110 MOS

fi 9.35 1792.5 ffemales) = = 1/78.851 47,305 x x MOS

fi

1E0
140

DESCRIPTION OF WEIGHTING: NON-MILITARY

OBJECTIVES

Data weighting for the initial year cohort involved five basic steps.

These steps were designed to accomplish the following objectives:

1. Correction for differential probability of selection

at the initial stage of household selection.

2. Correction for differential completion rates at the

initial "screening phase" of data collection.

3. Correction for differential subsampling rates for

Hispanic and Black cohort members prior to initial

interview. Correction of differential completion

rates among all cohort members at the first year

interview stage of data collection.

4. Proper combination of cases obtained in the crosssectional and supplemental samples; across these

samples.

5. Adjustment of weighted cohort sizes to conform with outside,

independent Census estimates projected to January 1, 1979.

PROCEDURES AND STEPS

1. In the initial step, weights were assigned to each completed case

on the basis of the selection probability for the dwelling unit

which contained the family unit where the respondent was initially

located (i.e. listed).. For the ith respondent, this weighting

factor was

Wii = l /fi, where fi is the probability of selection

for the dwelling unit containing the family unit where the respondent

was initially listed in the screening process.

2. In this step, a cluster specific adjustment was introduced in order

to compensate for differential completion rates in the family unit

within dwelling unit screening process. There were 1,81S selection

clusters in the entire sample (91S in the cross-sectional sample

and 900 in the supplemental sample).

For the ith respondent, this adjustment factor was

142i=

Number of family units selected in the cluster

containing the ith respondent

Number of family units in the ith respondent's

. cluster where screening information was obtained
141

In thcle instrmnes where refusals were encountered at the dwelling

unit level (i.e. it was impossible to determine whether or not there

was more than one family unit within the dwelling unit), the ratio

of family units to dwelling units for the remainder of the cluster

was used to estimate the number of family units contained within the

dwelling unit. W2i was constrained to an upper limit of 1.5.

In this step adjustments were made for the additional stage of subsampling applied to Blacks and Hispanics screened in the supplemental

sample prior to initial interview. In addition, adjustment factors

were applied to all selected respondents to compensate for differential response rates in the first interview. These non-response

adjustment factors were applied at the PSU level (102 cross-sectional

PSU's and 100 supplemental PSU's) for each of the eight basic design

cohorts listed below:

1. Hispanic Males

2. Hispanic Females

3. non-Hispanic, Black Males

4. non-Hispanic, Black Females

5. Economically Disadvantaged, non-Hispanic, non-Black Males

6. Economically Disadvantaged, non-Hispanic, non-Black females

7. Other Males

8. Other Females

NOTE: All basic design cohorts, except 7 and 8, were sampled in

both the cross-sectional and supplemental samples.

Thus, the step 3 weight factor for the ith respondent was

W3i = A3i/Si

where,

and

Number of assigned cases with respondent i's

PSU and design cohort A

3i ." Number of completed cases within respondent i's

PSU and design cohort

si = probability of retention in sample if ith

respondent was in Black or Hispanic design cohort

of supplemental sample,

1, otherwise

An upper limit of 1.5 was applied to the factor A3i.

1 U2
142

4. The purpose of this step was to rescale the weights developed in

steps one, two and three for cases in design cohorts 1-6 in order

to properly combine respondents from the cross-sectional and

supplemental samples. Prior to this step, the supplemental and

cross-sectional samples were treated as independent units.

This rescaling was carried out separately for each of the 6 design

cohorts present in both the cross-sectional and supplemental samples.

Within each of the cohorts a preliminary weight was computed for

each respondent within the cohort. For the ith respondent within the

cohort, this preliminary weight was the product of weights developed

at steps 1, 2 and 3. Specifically,

W4i = Wli X W2i x W

3i

Within each of the cohorts separate means and standard deviations

were calculated for these preliminary weights from the cross-sectional

and supplemental portions of the cohort. Thus within a specified

cohort

Mc = Mean of weights WIti from the cross-sectional portion of the

cohort.

Ms = Mean of weights Witi from the supplemental portion of the

cohort.

Sc = Standard deviation of weights 1424i from the cross-sectional

portion of the cohort.

Ss = Standard deviation of weights W4i from the supplemental

portion of the cohort.

These means and standard deviations were used to determine the weighting efficiency factor for the cross-sectional and supplemental portions

of the sample for the cohort as follows:

WEFc = 1

= weighting efficiency factor crosssectional portion

WEF5 -

(1 + (ms/sc)2)

1

(1 + (Ms/Ss)2)

These efficiency factors were used in conjunction with the actual

number of cases within the cross-sectional and supplemental portions

of the cohort to determine the effective sample bases for these

portions of the cohort.

1

= weighting efficiency factor supplemental portion
143

Thus,

ESBc = nc x WEPc

ESBs ns x WEFs

where,

ne and ns are defined as the number of sample cases

cross-sectional and supplemental

tively. And,

ESBc and ESBs are defined as the

cross-sectional and supplemental

pectively.

in the

portions of the cohort respeceffective sample bases for the.

portions of the cohort resUsing these effective sample bases, adjustment factors were developed

for the cross-sectional and supplemental portions of the specified

cohort so that the proportion of weighted cases from the crosssectional aad supplemental parts of the cohort would be in the same

relationship as the effective sample bases from these two parts of

the total.cohort.

Using the preliminary weights W4i, the total sum of weights from

both portions of the cohort is

TSW = (nc x Mc) + (ns x Ms)

The adjustment factor for the cross-sectional portion of the cohort

was

Pc x TSW

A4c

nc x Mc

, where Pc = ESBc

ESBc + ESBs

The adjustment factor for the supplemental portion of the cchort

was

A4s

a.

Ps x TSW

ns x Ms

, where Ps = ESBs ESBc + ESBs

These adjustment factors were applied to the preliminary step 4

weights W4i to produce final step 4 weights W4i.

W4i u A4c W41.

W4i s A4s x W4i

, for i within cross-sectional portion,

, for i within supplemental portion.

14
144

5. In the final step of weighting, the sum of weights from each of 64

post- strata (8 basic design cohorts x8 age groups) was aeinsted to

estimates of population size derived from US Census estimates. This

was accomplished by application of the adjustment factor A5, within

each of the 64 post-strata as follows:

Within each of the 64 post-strata,

NSP = total population estimate developed as above.

NSS = total sum of weights W41 for the cohort

A5 = NSP/NSS.

This factor was applied to each of the final step 4 weights to

produce a final respondent weight for year me.

Wi = A5 x W

4i (W = final weight for ith respondent)

As noted above the 64-post-strata were defined on the basis of the

8 basic design cohorts Ly 8 age groups, as follows:

8 DESIGN COHORTS

Males - Hispanic

Males - Black Non-Hispanic

Tiles - Economically Disadvantaged Non-Hispanic, Non-Black

Males - Others

Females - Hispanic

Females - Black, Non-Hispanic

Females - Economically Disadvantaged, Non-Hispanic, Non-Black

Females - All others

2 AGE GROUPS

Single Birth Years 1957, 1958, ..., 1964

Estimates of Post-stratum size were derived as follows:

1. Estimates of the Civilian Population of the U.S. were obtained

by sex,.single year of age and race (black, other) as of July 1,

1978 from Table 3, of Current Population Reports Series P-25, No.800.

2. By using the 13 and 21 year cohorts, these population estimates

were carried forward 6 months to produce estimates of the

14 - 17 and 18 - 21 population by sex as of January 1, 1979.
145

3. Current Population Reports Series P-20, No.339: Persons of

Spanish Origin in the United States: March, 1978 was used

to estimate the number of non-Black Hispanics in each of

the single year age cohorts. Current Population Reports

Series P-60, No.120: Money Income and Poverty Status of

Families and Persons in the United States: 1978 was used

in order to estimate the number of economically disadvantaged non-Hispanics, non-Blacks in each of the single year

age cohorts.
146

DESCRIPTION OF WEIGHTING: MILITARY

OBJECTIVES

Data weighting for the initial year in military cohort involved three basic

steps designed to accomplish the following objectives.

1. Correction for differential probability of selecion for males

and females.

2. Correction for differential interview completion rates.

3. Adjustment of weighted sample. size to conform to known population

size by service and sex.

PROCEDURES AND STEPS

1. In the initial step, weights were assigned to each case on the basis of

selection probability. For eke ith respondent, this weighting factor was

W 1/f

i'

where f

i is the probability of selection for

the ith respondent. For all males, this probability fi =2 1/496.124.

For females f 1/78.851.

2. In the second step a completion rate adjustment factor was calculated on a PSU by sex basis as follows:

Selected individuals of same sex

within ith respondents PSU

W2i Number of completed cases of same sex within ith respondents PSU

The factor W

2i was constrained to an upper limit of 1.5.

3. For each respondent, a preliminary step three weight was calcWated by

multip7ication of the weights from steps one and two

W3i Wli x W

2i

These preliminary weights were then summed within 8 (4 service by 2 sex)

post strata. The third step, final adjustment factors were then determined

as the ratio of the actual population within the post-stratum to the sum

of step three preliminary weights within the post-stratum.

11.10v

,1
147

An = Population size within ith respondent's post-stratum

Sum of step three preliminary weights within ith

respondent's post stratum

'The final weight assigned to the ith respondent was Wi Wii x W2i x A3i

It should be noted that population sizes within the 8 post strata

[(ARMY, NAVY, MARINE CORPS, AND AIRFORCE) by (MALE-FEMALE)) were

obtained from the list sampling frame of all persons in the armed

forces as of September 30, 197.8 who would be between 14 and 21 as of January 1, 1979. Although information was available which would

have allowed the use of a finer level of post-stratification based

upon age and race/ethnicity, this finer post-stratification was not

implemented. On the basis of the sample composition, it was felt

that the use of this finer post-stratification would greatly

increase the amount of sampling variation without an equal decrease

in total survey error (i.e., mean squared error).1

1 If required, population distributions can be provided which

will allow for this finer post-stratification weighting.
AFTERWARD

This report is based on data from a special

survey--the 1979 National Longitudinal Survey (NLS) of youth-- funded by the

Departments of labor and Defense and conducted by the Cente for Human

Resource Research at Ohio State University. The young people in the survey

will be interviewed annually for the next 5 years, enabling researchers to

trace their labor market experiences and problems over time.

Many facets of youth labor market activity are covered in this volume,

including current labor force status, hours and weeks worked, job search

activities, and youth attitudes and aspirations towards school and their

future labor market prospects.

Even though a wealth of useful information is covered here, it is

important to note, as the authors emphasize, that the data are preliminary,

not definitive. Thus, further refinements, reweighting, and more sophisticated analyses may change some of the results.

The NLS estimates of employment and unemployment differ somewhat from

those obtained from the official figures published by the Labor Department

In particular, the NLS estimates of unemployment, especially among youth

ages 16 to 17 whose major activity is attending school, are higher than

the official published figures. There is much less variation between the

two surveys' estimates of employment, though the NLS employment estimates

are somewhat higher. Standard errors of the NLS data are not yet available

to allow testing for the statistical significance of the differences.

Previous surveys of youth--the National Longitudinal Study of the

High School Class of 1972, and the old National Longitudinal Survey begun

in 1966--have also yielded different estimates of labor force status than

the official figures. However, unlike the data presented in this monograph,

the differences in unemployment rate estimates tended to be lower, marginal

or nonexistent.

There are a number of possible reasons for the survey differences:

these range from survey procedures, design and methodology, interviewer

experience, questionnaire content and design, and whether the youth respond

to the labor force questions themselves or the information is provided by

another member of the family.

The fact that unlike labor force estimates have been found in different

surveys raises, once again, the problem of obtaining precise measures of the

labor force status of persons with very marginal and fluctuating attachment

to the labor market. It is in this context that the Bureau of Labor Statistics is continuing its in-depth analysis of each youth survey and their

differences from the official government survey to answer questions concerning the significance of any differences that exist, and to probe for the

explanation(s) for such differences.

* U,S. GOVERNMENT PRINTING orrice 1 IVRO 0 - 326-8.6 1:J9