NATIONAL CENTER FOR EDUCATION STATISTICS

Statistical Analysis Report April 1998

Postsecondary Education Descriptive Analysis Reports

Gender Differences in

Earnings Among Young

Adults Entering the

Labor Market

Suzanne B. Clery

John B. Lee, Ed.D.

Laura G. Knapp

JBL Associates, Inc.

C. Dennis Carroll, Project Officer

National Center for Education Statistics

U.S. Department of Education

Office of Education Research and Improvement NCES 98-086
For sale by the U.S. Government Printing Office

Superintendent of Documents, Mail Stop: SSOP, Washington, DC 20402-9328

U.S. Department of Education

Richard W. Riley

Secretary

Office of Educational Research and Improvement

Ramon C. Cortines

Acting Assistant Secretary

National Center for Education Statistics

Pascal D. Forgione, Jr.

Commissioner

The National Center for Education Statistics (NCES) is the primary federal entity for collecting, analyzing, and

reporting data related to education in the United States and other nations. It fulfills a congressional mandate

to collect, collate, analyze and report full and complete statistics on the condition of education in the United

States; conduct and publish reports and specialized analyses of the meaning and significance of such statistics;

assist state and local education agencies in improving their statistical systems; and review and report on

education activities in foreign countries.

NCES activities are designed to address high priority education data needs; provide consistent, reliable,

complete and accurate indicators of education status and trends; and report timely, useful and high quality data

to the U.S. Department of Education, the Congress, the states, other education policymakers, practitioners, data

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like to hear from you. Please direct your comments to:

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April 1998

The NCES Work Wide Web Home Page address is

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Suggested Citation

U.S. Department of Education, National Center for Education Statistics. Gender Differences in Earnings Among

Young Adults Entering the Labor Market, NCES 98-086, by Suzanne B. Clery, John B. Lee and Laura G.

Knapp. Project Officer: C. Dennis Carroll. Washington, DC: 1998.

Contact:

Aurora D’Amico

(202) 219-1365
iii

FOREWORD

The National Education Longitudinal Studies (NELS) program of the National Center for

Education Statistics (NCES) was established to study the educational, vocational, and personal

development of young people beginning with their elementary or high school years, and following

them over time as they begin to take on adult roles and responsibilities. Thus far, the NELS program

consists of three major studies: the National Longitudinal Study of the High School Class of 1972

(NLS-72), High School and Beyond (HS&B), and the National Education Longitudinal Study of

1988 (NELS:88).

The HS&B survey included two cohorts: the 1980 senior class, and the 1980 sophomore

class. Both cohorts were surveyed every two years through 1986, and the 1980 sophomore class was

surveyed again in 1992. 

This descriptive report uses HS&B to discuss the educational attainment, employment

consistency, gender dominance of major field of study for those who attained a postsecondary

certificate or degree, and annual earnings of the 1980 sophomore class in 1992, ten years after most

of the students in that cohort graduated from high school. The report explores in some detail the

relationships between characteristics of the 1980 sophomores, their work consistency, educational

attainment and gender dominance of their major field of study, family formation characteristics and

earnings.

Martin Orland

Associate Commissioner

Data Development and Longitudinal Studies Group
iv

ACKNOWLEDGMENTS

Writing these reports is very much a team effort. Our thanks go to all those who helped

produce this report. Robert Harmon, Barry Christopher, and Mary Lee of JBL Associates, Inc.

formatted tables, checked statistical statements and edited text. Dennis Carroll of NCES provided

the guidance and recommendations that come from long years of experience. Laura Horn of MPR

Associates, as always, had good ideas that helped shape the issues and tables. Vicky Dingler of MPR

Associates provided technical expertise in developing variables for the Data Analysis System. Special

thanks to Ellen Bradburn of Education Statistics Services Institute for her diligent edit and review

efforts that greatly improved this report.

The reviews provided by Robert Burton, Kristin Perry, and Chris Chapman of NCES and

David Goodwin of Planning and Evaluation Services improved the final product.
v

HIGHLIGHTS

In 1993, more women than men continued their education after high school: 55 percent of all

postsecondary degrees and certificates were awarded to women (table 2). Women have also become

more likely to work outside of the home. In 1981, 51 percent of married women participated in the

labor force. By 1995, 61 percent of married women participated in the labor force.1 However, at

every level of education, from high school dropout to postgraduate degree earner, women earned less

than men.

2

This analysis considers two factors that might have contributed to the earnings gap between

men and women. Women were more likely than men to interrupt their careers for an extended period

of time to take care of young children,3 and women were also more likely than men to prepare for

jobs that historically have lower income potential.4

This report examines earnings of men and women who worked consistently by their education

level and the gender dominance of major field of study. A consistent worker was defined as one who

worked at least 91.67 percent of the total months in the labor force after attaining his or her highest

level of education.5 Further, respondents who earned postsecondary certificates or higher were

assigned to categories based on the dominant gender of graduates in their major fields of study.

Gender dominance was based on the proportion of women or men in a major field of study. A major

field of study was declared gender dominant if 65 percent or more of the program’s graduates were

male or female.

Χ Women were less likely to work consistently than men after they left school. One-third of the

women worked consistently after they left school compared to 46 percent of the men (table

5). 

 

1 U. S. Department of Commerce. Statistical Abstract of the United States, 1996. (Washington, D.C.: Bureau of the

Census, 1996), p. 399.

2

Ibid, p. 471.

3

 U. S. Department of Labor, Women’s Bureau. 1993 Handbook on Women Workers: Trends and Issues. 

(Washington, D.C.: author, 1993), p. 74.

4

Jerry Jacobs. Revolving Doors: Sex Segregation and Women’s Careers. (Stanford, CA: Stanford University Press,

1989).

5 Care should be taken in using these results as the data did not allow identification of part- and full-time workers.
HIGHLIGHTS

vi

Χ Having children had different effects on the probability of working consistently for males and

females. Seventeen percent of the women with two children worked consistently compared

to 45 percent of those with no children (table 6). Men, on the other hand, were more likely

to work if they had two children instead of none. One-half of the men with two children

worked consistently compared to 44 percent of those with no children.

Χ Nine percent of the women who dropped-out of high school worked consistently compared

to one-half of the women with a bachelor’s degree (table 7). One-half of the men with a

bachelor’s degree worked consistently compared to 37 percent of those who dropped out of

high school.

Χ Men with no more than a high school diploma or GED earned $25,601 while women earned

$19,333 (in constant 1992 dollars) in the last full year after highest degree attainment (table

8). However, first year annual earnings of men and women who started work immediately

after high school did not differ significantly.

Χ Men who earned certificates or associate’s degrees earned $22,410 in the first year of work

while women earned $19,446, a difference of $2,964. In the last year of work, these men

earned $26,969 while women earned $21,868, a difference of $5,101. 

Χ Female workers with bachelor’s degrees earned $22,602 the year after they graduated

compared to $26,778 earned by men. By the last year of work, men were earning $34,104

compared to $27,259 for women. 

Χ The percentile ranking of income change indicates that men’s average income increased more

than women’s from the first year to the last year of work (table 12). This was true at all levels

of education.

Χ The gender dominance of the major field of study for students who earned any postsecondary

degree or certificate was related to their earnings. Workers who graduated in female

dominated fields started work earning an average of $20,855 while those in male dominated

fields earned $26,170 (table 9). By their last full year of employment studied, workers in

female dominated fields earned $24,307 compared to those in male dominated fields who

earned $31,292.

Χ Men who earned certificates or associate’s degrees in female dominated majors were

compared to women who also graduated in female dominated majors. These men earned

more than the comparable women in the beginning of their careers as well as the last year of
HIGHLIGHTS

vii

employment studied (table 10). Too few women in this sample graduated with male

dominated majors to provide a comparison. 

Χ Men who graduated with bachelor’s degrees in gender-neutral fields earned more than women

in the same fields in their first year out of college and in the last year of the study (table 11).

 Significant differences did not exist between the earnings for men and women for the first

year after graduation for those who majored in male or female dominated majors. By the last

full year of employment, however, men earned more than women in male and female

dominated majors.
viii

TABLE OF CONTENTS

Foreword ..................................................................................................................................iii

Acknowledgments ....................................................................................................................iv

Highlights..................................................................................................................................v

List of Tables.............................................................................................................................x

List of Figures ........................................................................................................................ xiii

Introduction ..............................................................................................................................1

Background.....................................................................................................................1

Women increased their enrollment in postsecondary education and their numbers in

the workforce ...........................................................................................1

Higher proportions of educated women entered the labor force ............................3

The Earnings Gap............................................................................................................4

Possible reasons for the earnings gap....................................................................5

Women pursued different educational and career interests than men..........5

Family formation ......................................................................................6

Data and Methodology ....................................................................................................7

Data source..........................................................................................................7

Analytic approach ................................................................................................7

Data constraints .................................................................................................10

Work Consistency of Men and Women .................................................................................13

Demographics................................................................................................................13

Family Formation...........................................................................................................14

Level of Education.........................................................................................................15

Earnings of Consistent Workers.............................................................................................17

Workers with High School Diplomas or GEDs ..............................................................17

Workers with Certificates or Associate’s Degrees..........................................................19

Workers with Bachelor’s Degrees..................................................................................20

Consistent Workers' Earnings by Gender Dominance of Major Field of Study ..................21

Gender Dominance of Major Field of Study ...................................................................21

Workers with certificates or associate’s degrees.................................................21

Workers with bachelor’s degrees........................................................................23

Earnings Growth Experienced by Men and Women Working Consistently........................25
TABLE OF CONTENTS

ix

Factors Associated with Earnings in the Top and Bottom Categories of Men and Women

Working Consistently..................................................................................................27

Workers with High School Diplomas or GEDs ..............................................................27

Male workers.....................................................................................................27

Female workers..................................................................................................29

Workers with Bachelor's Degrees ..................................................................................29

Male workers.....................................................................................................29

Female workers..................................................................................................32

Factors Associated with Earnings in the Top Category After Controlling for Background

Variation......................................................................................................................35

Workers with High School Diplomas or GEDs ..............................................................35

Male workers.....................................................................................................35

Female workers..................................................................................................37

Workers with Bachelor’s Degrees..................................................................................38

Male workers.....................................................................................................39

Female workers..................................................................................................39

Summary and Implications.....................................................................................................44

Appendix A: Glossary.............................................................................................................47

Appendix B: Technical Notes.................................................................................................56

Bibliography............................................................................................................................70
x

LIST OF TABLES

Table Page

1 Average earnings of year-round, full-time workers age 25 and older according

to gender, and female to male earnings ratio, by level of education: 1995 ............. 4

2 Percentage of postsecondary degrees and certificates awarded to women, by

degree level: 1993-94........................................................................................... 5

3 Percentage of married women with a husband in the household who worked,

by age of youngest child: 1981-1995.................................................................... 7

4 Percentage of 1980 high school sophomores working consistently who earned

less than $8,000 in the last full year of employment after attainment according

to highest level of education, by gender.............................................................. 11

5 Percentage of 1980 high school sophomores working consistently according

to gender, by race/ethnicity and family socioeconomic status, 1980 .................... 13

6 Percentage of 1980 high school sophomores working consistently according

to gender, by marital status and number of children, June 1992........................... 14

7 Percentage of 1980 high school sophomores working consistently according

to gender, by highest level of education completed and gender dominance of

major field of study ............................................................................................ 15

8 Mean annual earnings in the first and last full year of employment after

attainment, number of years in the labor force and number of months

employed among 1980 high school sophomores working consistently, by

highest level of education and gender................................................................. 19

9 Mean annual earnings in the first and last full year of employment after

attainment among 1980 high school sophomores working consistently, by

gender dominance of major field of study ........................................................... 21

10 Mean annual earnings in the first and last full year of employment after

attainment, number of years in the labor force and number of months

employed among 1980 high school sophomores working consistently with

certificates or associate's degrees as highest degree, by gender and gender

dominance of major field of study....................................................................... 22
LIST OF TABLES

xi

11 Mean annual earnings in the first and last full year of employment after

attainment, number of years in the labor force and number of months

employed among 1980 high school sophomores working consistently with

bachelor’s degrees as highest degree, by gender and gender dominance of

major field of study ............................................................................................ 23

12 Mean percentile ranking of change in annual earnings among 1980 high school

sophomores working consistently from first full year to last full year of

employment after attainment of highest degree according to highest degree

attained by 1992, by gender................................................................................ 25

13 Percentage distribution of 1980 male high school sophomores working

consistently with high school diplomas or GEDs as highest degree, according

to annual earnings in constant 1992 dollars for the last full year of employment

after attainment, by selected characteristics ........................................................ 28

14 Percentage distribution of 1980 female high school sophomores working

consistently with high school diplomas or GEDs as highest degree, according

to annual earnings in constant 1992 dollars for the last full year of employment

after attainment, by selected characteristics ........................................................ 30

15 Percentage distribution of 1980 male high school sophomores working

consistently with bachelor’s degrees as highest degree, according to annual

earnings in constant 1992 dollars for the last full year of employment after

attainment, by selected characteristics ................................................................ 31

16 Percentage distribution of 1980 female high school sophomores working

consistently with bachelor’s degrees as highest degree, according to annual

earnings in constant 1992 dollars for the last full year of employment after

attainment, by selected characteristics ................................................................ 33

17 Percentage of 1980 male high school sophomores working consistently with

high school diplomas or GEDs as highest degree who were in the highest

earnings quartile during the last full year of employment after attainment, and

the adjusted percentage after taking into account the covariation of the

variables listed .................................................................................................. 36

18 Percentage of 1980 female high school sophomores working consistently with

high school diplomas or GEDs as highest degree who were in the highest

earnings quartile during the last full year of employment after attainment, and

the adjusted percentage after taking into account the covariation of the

variables listed .................................................................................................. 38
LIST OF TABLES

xii

19 Percentage of 1980 male high school sophomores working consistently with

bachelor’s degrees as highest degree who were in the highest earnings quartile

during the last full year of employment after attainment, and the adjusted

percentage after taking into account the covariation of the variables listed ......... 40

20 Percentage of 1980 female high school sophomores working consistently with

bachelor’s degrees as highest degree who were in the highest earnings quartile

during the last full year of employment after attainment, and the adjusted

percentage after taking into account the covariation of the variables listed ......... 42

B1 Percentage distribution of 1980 high school sophomore women and men

according to work consistency, by selected characteristics.................................. 59

B2 Standard errors for Table B1: Percentage distribution of 1980 high school

sophomore women and men according to work consistency, by selected

characteristics.................................................................................................... 62
xiii

LIST OF FIGURES

Figure Page

1 Percentage of population participating in the labor force by gender: 1960-

2000.......................................................................................................................... 2

2 Percentage of women working by education level: 1970-90 ....................................... 3

1

INTRODUCTION

The cultural roles of women have altered over the last several decades. An increasing number

of women have selected careers outside of the home, and more women have attended college and

other postsecondary institutions than ever before. Nevertheless, as recently as 1992, after a

generation of social evolution, women’s economic rewards in the workplace continued to lag behind

those of men. This report documents the status of young women as they entered the labor market

in the late 1980s and early 1990s. Women’s earnings are compared to those of men with equal

education and experience in the workplace. Factors are also presented that were associated with the

differences between incomes of women and men.

The report investigates two possible contributing factors for the income differences between

men and women. First, women may have been more likely than men to leave their jobs for extended

periods while they raised their children. Second, women may have prepared themselves for jobs that

are traditionally held by women. These jobs have typically paid less than those held by men. The

income differences between men and women at three levels of education are examined: those who

entered the job market with no more than a high school diploma or general equivalency diploma

(GED), those with a certificate or associate’s degree, and those who completed a bachelor’s degree.

BACKGROUND

Women increased their enrollment in postsecondary education and their numbers in

the workforce

In the last few decades, a larger percentage of women enrolled in postsecondary education

and earned certificates and degrees than in the past. In 1960, 38 percent of the female high school

graduates enrolled in college compared to 54 percent of the males. By 1995 the rates were nearly

equal, with 61 percent of the female and 63 percent of the male high school graduates entering

college.6 In 1994, women comprised 55 percent of the undergraduate enrollment in postsecondary

institutions.7

 

6

U. S. Department of Education. Digest of Education Statistics, 1996. (Washington, D.C.: author, 1996), p. 187.

7

Ibid., p. 182.
INTRODUCTION

2

The number of women working outside the home also increased over the past several

decades. According to the U.S. Department of Labor, the most important labor market development

between 1965 and 1992 was the dramatic increase in the number and proportion of working women.

In 1970, women comprised 38 percent of the civilian labor force.8 By 1994, the share had increased

to 45 percent.9 The U.S. Department of Labor projects the female share of the labor force will

increase to 47 percent by 2005.10 Females will comprise nearly two-thirds of the new entrants into

the labor force over the next few years.11

Figure 1--Percentage of population participating in the labor force by gender: 1960-2000*

*Data for 2000 are projected.

SOURCE: U.S. Department of Commerce. Statistical Abstract of the United States, 1996. (Washington, D.C.: Bureau

of the Census, 1996), p. 394-395.

 

8

Hudson Institute. Workforce 2000, Work and Workers for the 21st Century. (Indianapolis: author, 1987), p. 85.

9

U. S. Department of Labor. Civilian Labor Force, 1982, 1993, and 1994 and Projected 2005, and Entrants and

Leavers 1982 and Projected 1994-2005. (Washington, D.C.: Bureau of Labor Statistics, 1997),

www.stats.bls.gov/emptab03.htm.

10U. S. Department of Labor, Women’s Bureau. 1993 Handbook on Women Workers: Trends and Issues. 

(Washington, D.C.: author, 1993), p. 231.

11Hudson Institute. Workforce 2000, Work and Workers for the 21st Century. (Indianapolis: author, 1987), p. 85.

Men Women

Year

1960 1970 1980 1990 2000*

0

20

40

60

80

100
INTRODUCTION

3

The labor force participation rate of women rose rapidly between 1960 and 1995. In 1960,

38 percent of adult women and 83 percent of adult men were in the labor force. By 1995, the share

of men in the labor force had declined to 75 percent and the share of women increased to 59 percent

(see figure 1).12

Higher proportions of educated women entered the labor force

Attaining higher levels of education is related to increases in the likelihood that women will

work. Figure 2 displays the percentage of women who worked by their educational level for the past

twenty years. This chart illustrates two points. First, women without a high school education were

less likely to work than those who earned a high school diploma or higher. Second, among women

who did not earn a high school diploma, the percentage who worked changed by 3 percentage points

over time, increasing from 43 percent in 1970 to 46 percent in 1990. However, among women who

earned a high school diploma or higher, the percentage working increased more over the same twenty

years: 18 percentage points for women with a high school diploma (51 to 69 percent), 25 percentage

points for women with some college (51 to 76 percent), and 20 percentage points for women with

four years of college (61 to 81 percent).

Figure 2--Percentage of women working by education level: 1970-90

SOURCE: U.S. Department of Commerce. Statistical Abstract of the United States, 1996. (Washington, D.C.: Bureau

of the Census, 1996), p. 395.

 

12U. S. Department of Commerce. Statistical Abstract of the United States, 1996. (Washington, D.C.: Bureau of the

Census, 1996), p. 394.

1970 1980 1990

43

51 51

61

44

61

66

73

46

69

76

81

Education Level

Less than high school High school Some College 4 years of college

0

20

40

60

80

100
INTRODUCTION

4

THE EARNINGS GAP

A gap between men’s and women’s earnings existed in 1970. Although women made

educational and employment advances, the gap persisted in 1995. Adelman studied young women

entering the labor market in the 1970s. He found that compared to men, women:

Χ experienced more unemployment,

Χ worked in lower paying and traditionally female occupations, and

Χ had lower incomes when all relevant educational and experience variables were

considered.13

Table 1 shows that the historical inequalities between women’s and men’s earnings still

existed in 1995. On average, women earned two-thirds of men’s earnings in 1995. Thus, although

more women persisted to higher levels of education, they still earned less than men with the same

level of education. Women’s earnings as a share of men’s earnings varied between 70 percent for

those with some college but no degree to a low of 64 percent for those with a bachelor’s degree. 

Further, a woman with a bachelor’s degree could expect to make $327 more annually than a male

who achieved an associate’s degree ($39,271 compared to $38,944, respectively), but $21,737 less

than a man with a bachelor’s degree in 1995 ($39,271 compared to $61,008, respectively). 

Table 1--Average earnings of year-round, full-time workers age 25 and older according to gender, and

female to male earnings ratio, by level of education: 1995

Female earnings/

Males Females male earnings x 100

Total $41,118 $27,162 66.1

Level of education

 Less than 9th grade 20,461 13,349 65.2

 9th to 12th grade, no diploma 24,377 16,188 66.4

 High school graduate, includes equivalency 31,081 21,383 68.8

 Some college, no degree 35,639 24,787 70.0

 Associate’s degree 38,944 26,903 69.1

 Bachelor’s degree or higher 61,008 39,271 64.4

SOURCE: U. S. Department of Commerce. Statistical Abstract of the United States: 1996. (Washington, D.C.:

Bureau of the Census, 1996), p. 471.

 

13Clifford Adelman. Lessons of a Generation: Education and Work in the Lives of the High School Class of 1972. 

(San Francisco: Jossey-Bass, 1994), p. 57.
INTRODUCTION

5

Possible reasons for the earnings gap

Several factors may have caused this earnings gap. First, although more women have

achieved higher levels of education, they have been more likely than men to enter fields of study and

occupations traditionally dominated by females.

14 These pay less than those traditionally held by

males.15 Second, married women and women with children may have been more likely than men to

take time off from a career for family. Women who leave the labor market for family reasons often

return to wages lower than those of women who did not leave. Further, women who leave the labor

market lose seniority and are less likely to receive on-the-job-training, their job skills may depreciate,

and their employers may believe they will take another leave.16

Women pursued different educational and career interests than men

In 1994, females received more degrees than males at nearly all education levels. Table 2

shows that in 1994 women were more likely than men to receive a postsecondary degree or certificate

at all educational levels, except doctoral and first professional.

Table 2--Percentage of postsecondary degrees and certificates awarded to women, by degree level: 1993-94

Percent of degrees

awarded to women

Total 55.4

Degree level

 Certificate of less than one year programs 51.6

 Certificate of one, but less than two year programs 58.2

 Associate’s degree 59.2

 Bachelor’s degree 54.5

 Master’s degree 54.5

 Doctorate 38.5

 First professional 40.7

SOURCE: U. S. Department of Education. Digest of Education Statistics, 1996. (Washington, D.C.: National Center

for Education Statistics, 1996).

Often, men and women graduated in different majors. Women continued to earn the highest

proportion of degrees in fields traditionally dominated by females, such as education and nursing,

 

14 Jerry Jacobs. “Long Term Trends in Occupational Segregation by Sex,” American Journal of Sociology. vol. 95, 

(1989), p. 160-173.

15 Donald J. Treiman and Heidi I. Hartmann. Women, Work and Wages. (Washington, D.C.: National Academy Press,

1981).

16 Joyce P. Jacobson & Laurence M. Levin. “Effects of Intermittent Labor Force Attachment on Women’s Earnings,”

Monthly Labor Review. vol. 118, n. 9, (Sept. 1995), p. 4-19.
INTRODUCTION

6

while males dominated technology and engineering fields.17 These areas of educational interest lead

to jobs with different income potentials. As will be seen later, the choice of a male- or femaledominated major was associated with income.

Men’s and women’s chosen occupations influenced their earnings level. In 1991, the

frequently occupations traditionally held by women included secretary, cashier, bookkeeper, nurse

and nursing aide, elementary school teacher and child care worker. Historically, careers traditionally

held by women paid less than those held by men. In 1991, 11 of the 20 frequently held occupations

for women were in the traditionally female held list. Further, 14 of the 20 frequently held occupations

for women paid less than the average weekly pay for all women employed. This translates to 69

percent of women in the 20 frequently held occupations earning less than the average weekly pay for

all women.18

Family formation

Women’s participation in the work force varies by age and number of children in the family.

Women age 35 to 44 display the highest labor force participation, 77 percent. The share drops to 73

percent for women between 45 and 54 years of age and declines to 47 percent for women between

55 and 64.19 In 1991, the labor force participation rate for married women with no children was 53

percent. However, for their single counterparts the labor force participation rate was 70 percent.20

Several contributing factors exist that may explain this phenomenon. Among these contributing

factors are: older married women with grown children may not have been as likely to work as

younger single women, or married women with no children may have interrupted their careers to

move when a husband was transferred.

The most dramatic increase in the labor force participation between 1981 and 1995 was for

married women with children (table 3). The labor force participation rate for married women with

a child less than 18 increased by 14 percentage points, from 56 to 70 percent, over the 14 year period.

The labor force participation rate for married women with no children less than 18 increased 7

percentage points during the same period, from 46 to 53 percent.

 

17 Jerry Jacobs. Revolving Doors: Sex Segregation and Women’s Careers. (Stanford, CA: Stanford University Press,

1989).

18U. S. Department of Labor. 1993 Handbook on Women Workers: Trends and Issues. (Washington, D.C.: Women’s

Bureau, 1993), p. 17.

19U. S. Department of Labor. Facts on Working Women. Number 93-2. (Washington, D.C.: Women’s Bureau, 1993),

p. 2.

20U. S. Department of Labor. 1993 Handbook on Women Workers: Trends and Issues. (Washington, D.C.: Women’s

Bureau, 1993), p. 75.
INTRODUCTION

7

Although more women with children worked in 1995 than 1981, they still interrupted their

careers for the care of the very young and returned to the labor force as their children grew older. In

1995, the labor force participation rate for women with children under the age of 6 was 64 percent,

while 75 percent of the women with children age 6 to 13 were in the labor force, and 80 percent of

women with children age 14 or older worked.21

Table 3--Percentage of married women with a husband in the household who worked, by age of youngest child:

1981-95

1981 1991 1995

Total 51.0 58.5 61.1

Presence and age of youngest child in household

No child less than 18 46.3 51.2 53.2

With a child less than 18 55.7 66.8 70.2

Child less than 6 47.8 59.7 63.5

Child 6-13 62.1 72.8 74.9

Child 14-17 63.3 75.7 79.6

SOURCE: U. S. Department of Commerce. Statistical Abstract of the United States: 1996. (Washington, D.C.: 

Bureau of the Census 1996), p. 400.

DATA AND METHODOLOGY

Data source

The source of data for this analysis was the High School and Beyond (HS&B) study. HS&B

collected data from sophomores in 1980--the high school class of 1982--twelve years, with the

final data collection in 1992. HS&B tracked sophomores in 1980 from high school to

postsecondary education and the labor market. The data collected allowed for identification of the

amount and type of education received by individuals, calculation of their annual earnings, and

identification of their work consistency after school.

Analytic approach

This analysis considered men’s and women’s education levels, the gender dominance of their

major field of study, time spent in the labor force and their consistency of work. The report begins

by describing the characteristics of men and women who worked consistently and inconsistently. It

then examines the earnings of consistent male and female workers. The highest level of education

and gender dominance of their major field of study were considered in the earnings analysis. The

difference between men’s and women’s earnings is included in the analysis. Finally, a discussion of

 

21Ibid.
INTRODUCTION

8

the factors associated with the probability of achieving earnings in the highest income quartile within

gender groups is included.

The first step was to sort individuals into one of three groups for each year: respondents

whose predominant activity was work, those whose primary activity was postsecondary education,

and those who did not fit in either group. For example, respondents who did not fit in a work or

education group may have stayed home to raise a family or been unemployed for several months.

Family formation was also considered in this analysis. Marriage and birth of children may

have been associated with women leaving their jobs or working less than full-time. These factors

could have depressed women’s earnings. It was expected that family formation would have less

relationship to men’s participation in the labor market than women’s because men’s rate of labor

force participation has historically not varied across the period of family formation.22

The postsecondary degree level or certificate an individual received was determined. 

Postsecondary levels included certificate programs of less than 2 years (certificate), degrees of 2 but

less than 4 years (associate’s degree), and baccalaureate degrees (bachelor’s degree).23 Individuals

with no more than a high school diploma or general equivalency diploma (GED) were sorted into two

groups: those who enrolled in a postsecondary institution but did not receive a degree, and those who

never enrolled in a postsecondary institution. 

Respondents who earned certificates, associate's degrees and bachelor's degrees were

assigned to a category based on the gender dominance of their major field of study. Gender

dominance was based on the proportion of women or men in a major field of study. A major field

of study was declared gender dominant if 65 percent or more of the program’s graduates were male

or female.24 This provided a basis to analyze the relationship between the gender dominance of the

major fields and earnings. Only respondents who earned a postsecondary certificate or higher were

assigned to a dominant gender category. High school graduates were not assigned a gender

 

22 David C. Bloom and Adi Brender. “Labor and the Emerging World Economy,” Population Bulletin. (1993).

23 For purposes of this analysis, the 3.1 percent of respondents who earned post-baccalaureate degrees by 1992 were

excluded. These respondents were not in the labor force long enough to produce reliable employment and earnings

patterns. The average number of months employed for this group was 23, and average number of months in the labor

force was 30. Thus, this group was employed, on average, 76.7 percent of the time. Since this group was so small and

had such relatively low work consistency, it was not included in the balance of the analysis. The low work consistency

of graduate students may be the result of a relatively short amount of time elapsed since degree completion.

24 The major field of study categories were derived using the U.S. Department of Education, National Center for

Education Statistics, Integrated Postsecondary Education Data System, 1990-91 Completions Survey. By defining a

major field of study gender dominant if 65 percent or more of the program’s graduates were male or female, degree

recipients were divided into thirds for the program gender dominance variable (one-third in female dominated programs,

one-third in male dominated programs and one-third in gender-neutral programs). Also, using this definition, resulting

groups in the HS&B data were large enough to analyze. 
INTRODUCTION

9

dominance for a major field of study. These individuals were usually in general programs not specific

to one gender. Appendix A includes a complete listing of the major fields of study and their

respective dominant gender.

Nearly two-thirds of the HS&B students who received a postsecondary degree or certificate

completed a program defined as gender dominant. A degree is defined as gender dominant if 65

percent of the graduates were female or male. This definition divided the population evenly: one-third

of 1994 graduates were in a male dominated program, one-third in a female dominated program, and

the remaining one-third in a gender-neutral program. In sub-baccalaureate programs, women

dominated fields such as business (70 percent) and health professions (86 percent) while men tended

to complete engineering technology (89 percent) and auto technician (93 percent) programs. At the

baccalaureate level, women dominated education (79 percent) and health fields (84 percent) while

men comprised most of the engineering (86 percent) and computer science (71 percent) graduates.

 Appendix A includes a complete list of major fields of study organized by gender dominance. 

Once an individual received his or her highest degree, he or she was assigned to one of two

categories: employed consistently or employed inconsistently. Consistent employment was defined

as working at least 91.67 percent of the total months in the labor force after attaining the highest level

of education, or 11 out of 12 months for each year in the labor force.25 The months an individual was

not in the labor market before graduating were not considered in the definition of work consistency.

Individuals’ time unemployed may have been distributed across the years, or occurred all at

once. For example, someone who was in the labor force for ten years could have been unemployed

for nine months at one time and be defined as a working consistently. Or, an individual who missed

one month of work each year for ten years would also be defined as working consistently. On the

other hand, an individual with five years in the labor market and nine months of unemployment would

be working inconsistently. 26

An individual could have been out of work for many reasons. He or she could have been laidoff and seeking work, or have voluntarily left employment. Non-graduating students who worked

while enrolled were considered working consistently. If they received the degree, the employment

 

25 Employment data was collected on a monthly basis on the HS&B survey. Thus, to derive the consistent employment

variable, 11 months of work in a year was determined to be the mark of consistent work; 10 out of 12 months would

have resulted in an extremely lenient definition of consistent work, while 12 out of 12 months would have been too strict.

26 To take into account differences in the length of time working due to education, only the earnings of those respondents

with degrees or diplomas of the same level were compared.
INTRODUCTION

10

status determination started three months after graduating. This provided enough time for most

graduates to find a job.27

Annual earnings were measured twice. First, earnings were measured during the first full year

of employment after attainment of highest degree. If one individual took four years to achieve a

bachelor’s degree and another took six years, their incomes were compared for their first full year

after earning the degree. Second, earnings were measured in the last full year reported. All earnings

were adjusted for inflation using the consumer price index (CPI) and reported in 1992 dollars. The

annual earnings of consistent male and female workers who achieved the same level of education in

fields of the same gender dominance were compared in their first and last years. If someone did not

qualify as working consistently, he or she was not included in the earnings comparisons. 

Several tables display percentage distributions across earnings categories. The earnings

categories in these tables were calculated to approximate earnings quartiles and were rounded to the

closest $50. Earnings categories were developed separately for men and women at each educational

level.

Change in income between the first and last earning periods was calculated as a percentile

ranking of the dollar amount of change. First, earnings for each worker in the first full year of

employment were subtracted from the earnings in the last full year reported. The result is a dollar

value of change in earnings. Next, the changes in earnings values were ranked from smallest to

largest within each educational attainment group. A percentile ranking of the change values in

each educational level was calculated. This ranking provides a relative measure of respondents’

change in earnings.

Data constraints

There were several constraints on the HS&B data. Throughout the 1980s, approximately

two-thirds of all part-time workers were women. 28 Further, women with children, especially those

with children under the age of 6, were more likely to be part-time workers than other women.29

However, because of the way the HS&B information was collected and reported, it was not possible

to determine directly whether a respondent was working full- or part-time. It could only be

determined whether he or she worked regularly. In an attempt to estimate the percentage of

 

27 In 1990, the average unemployment duration was 12 weeks. (U.S. Department of Commerce. Statistical Abstract of

the United States, 1996. (Washington, D.C.: Bureau of the Census, 1996), p. 413.

28 U. S. Department of Labor. 1993 Handbook on Women Workers: Trends and Issues. (Washington, D.C.: Women’s

Bureau, 1993), p. 8.

29 Ibid.
INTRODUCTION

11

respondents who worked part-time, the percentage of those working consistently and earning less

than $8,000 in the last full year reported was calculated. Based on a 40 hour week at minimum wage,

it would not be possible to work full-time and earn less than $8,000. Table 4 shows, overall, 3

percent of males and 4 percent of females earned less than $8,000 in the last year they worked.

Although women were generally more likely than men to earn less than $8,000, within each of the

educational levels, the difference between the percent of consistent male and female workers who

earned less than $8,000 was not significant.30

Table 4--Percentage of 1980 high school sophomores working consistently1 who earned less than $8,000 in the

last full year of employment after attainment according to highest level of education, by gender

High school Certificate or Bachelor’s

All degree or GED2associate’s degree degree3

Total 3.3 4.2 3.2 1.6

Gender

Male 2.6 3.4 1.9 1.1

Female 4.3 5.5 4.4 2.0

1Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

2

Includes high school degree or GED recipients who had some postsecondary experience and no certificate or degree, as

well as those who had no postsecondary experience.

3

Includes respondents who obtained a bachelor’s degree as highest degree by 1992.

SOURCE: U. S. Department of Education, National Center for Education Statistics, 1992 High School and Beyond:

Sophomore Cohort 1980-1992 (HS&B:92), Data Analysis System.

The second data constraint was the lack of ability to determine the type of job a respondent

obtained. Although respondents were categorized by gender dominance of their major field of study,

the type of job obtained was not determined. Therefore, a man and a woman, both in male dominated

majors, could have taken jobs with different income potentials. For example, a man and a woman

 

30 This analysis was used to indirectly estimate the portion of consistent workers who worked part-time in the sample. 

According to the Bureau of Labor Statistics (FTP address: stats.bls.gov/pub/special.requests/lf/aa8.txt), in 1996, 12

percent of working men worked part-time, while 37 percent of working women worked part-time. These statistics

include consistent and inconsistent workers. Also, HS&B does not allow identification of higher paid part-time workers,

or those who, for example, work only four days, or five short days per week. These two factors explain the higher

percentage of part-time workers BLS reported than was found in the HS&B sample. 
INTRODUCTION

12

could have both attained a bachelor’s degree in engineering; however, they may have obtained

different types of engineering jobs, or never obtain an engineering job. Although the magnitude is

unknown, job type differences account for some of the pay differentials between men and women.31

 

31 For an analysis of job types held by men and women see Barbara H. Wootton, “Gender Differences in Occupational

Monthly Labor Review. vol. 120. N. 4, (April 1997), p. 15-34.
13

WORK CONSISTENCY OF MEN AND WOMEN

Women were less likely than men to work consistently after they left school. One-third of

women worked consistently after they left school, compared to 46 percent of men (table 5). This

means that two-thirds of women and 54 percent of men were not working, on average, for more than

one month per year after they attained their highest degrees.

DEMOGRAPHICS

Race/ethnicity was associated with work consistency for both men and women. White, nonHispanic and Asian/Pacific Islander women were more likely to be employed consistently than black,

non-Hispanic and Hispanic women. Thirty-five percent of the white, non-Hispanic women and 40

percent of the Asian/Pacific Islander women were employed consistently compared to 22 percent of

the black, non-Hispanic women and 26 percent of the Hispanic women. 

Table 5--Percentage of 1980 high school sophomores working consistently* according to gender, by

race/ethnicity and family socioeconomic status, 1980

Women Men

Total 32.8 45.7

Race/ethnicity

 American Indian/Alaskan Native 26.8 32.9

 Asian/Pacific Islander 40.0 36.7

 Black, non-Hispanic 21.5 33.0

 White, non-Hispanic 35.4 48.4

 Hispanic 26.1 44.0

Family socioeconomic status, 1980

 Lowest third 25.5 41.6

 Middle third 37.4 50.5

 Highest third 38.6 45.4

*Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest

degree attainment to the end of the data collection period.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: 

Sophomore Cohort 1980-1992 (HS&B:92), Data Analysis System.
WORK CONSISTENCY OF MEN AND WOMEN

14

White, non-Hispanic men were more likely to be employed consistently than black, nonHispanic men. Forty-eight percent of the white, non-Hispanic men worked consistently compared

to 33 percent of the black, non-Hispanic men. 

For women, family background was also related to the probability of working consistently

after leaving school. Females from families with high or middle socioeconomic status (SES) were

more likely to work consistently than those from families with low SES. Twenty-six percent of the

lowest SES women compared to 37 percent of the middle SES and 39 percent of the highest SES

women were employed consistently.

FAMILY FORMATION

Marital status was related to work consistency for both males and females. Men who had

never been married by June 1992 were less likely to work consistently than men who were either

married or were no longer married, 39 percent compared to 54 and 49 percent, respectively (table

6). Women who were either married or had never been married by June 1992 were more likely to

work consistently than women who were no longer married by June 1992 (33 and 36 percent

compared to 26 percent, respectively). 

Table 6--Percentage of 1980 high school sophomores working consistently* according to gender, by marital

status and number of children, June 1992

Women Men

Total 32.8 45.7

Marital status, June 1992

 Married 33.3 54.1

 Never married 36.0 38.6

 No longer married 26.3 48.9

Number of children, June 1992

 None 45.1 43.6

 One 35.3 48.7

 Two or more 17.1 49.7 

*Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: 

Sophomore Cohort 1980-1992 (HS&B:92), Data Analysis System.

Having children was a predictor of work consistency for both men and women. Women with

multiple children were less likely to work consistently than those who did not have children. In June
WORK CONSISTENCY OF MEN AND WOMEN

15

1992, 17 percent of women with two or more children worked consistently, while 35 percent of those

with one child, and 45 percent of those with no children worked consistently. On the other hand,

having more than one child was associated with increased probabilities that men worked consistently.

 In June 1992, 44 percent of men with no children worked consistently, while 50 percent of those

with two or more children worked consistently.32

LEVEL OF EDUCATION

For both men and women, education was positively associated with work consistency after

leaving school. Women who earned a high school diploma, certificate, associate’s or bachelor’s

degree were more likely to be employed consistently than those who earned either a general

equivalency diploma (GED) or no diploma or degree (table 7). Nine percent of the women who

dropped out of high school worked consistently. Further, comparing women with a GED or

equivalent to those without a high school diploma or equivalency, achievement of a GED or

equivalent was not associated with the chance that a woman would work consistently.

Table 7--Percentage of 1980 high school sophomores working consistently* according to gender, by highest

level of education completed and gender dominance of major field of study

Women Men

Total 32.8 45.7

Highest degree the respondent received

 No diploma/degree 8.5 36.5

 GED/Certificate 10.2 36.4

 High school diploma 30.0 47.7

 Certificate 38.1 46.8

 Associate’s degree 40.9 50.9

 Bachelor’s degree 49.6 49.9

*Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: 

Sophomore Cohort 1980-1992 (HS&B:92), Data Analysis System.

Men who did not earn a high school diploma or degree were less likely to be employed

consistently than those who earned a bachelor’s degree. Thirty-seven percent of men who did not

earn a diploma or degree were employed consistently, compared to 50 percent of those who earned

a bachelor’s degree. When compared to men who did not achieve a high school diploma or GED,

 

32 Work consistency was not significantly different between men having one child compared to having no children.
WORK CONSISTENCY OF MEN AND WOMEN

16

achieving a GED did not improve the chances of working for men, but achieving a high school

diploma was significantly related to work consistency.
17

EARNINGS OF CONSISTENT WORKERS

Annual earnings represent a measure of the value assigned by employers to a job. As noted

earlier, consistent workers’ earnings were measured three ways: in the first full year of employment

after graduating, in the last year of work reported, and as a change from the first to the last year. All

income is reported in 1992 dollars, and income is reported exclusively for respondents who worked

consistently after they left school. 

At all levels of education, men either enjoyed an earnings advantage over women in both the

first and last full years reported, or no significant difference existed. Women never experienced an

earnings advantage over men, nor did their increase in annual earnings out-rank that of men from the

first to last year.

Attaining a bachelor’s degree was compensated with higher earnings for both men and

women. Women with a high school diploma and no postsecondary education earned $13,452 in their

first year of work. Women who attained an associate’s degree or certificate33 earned $19,446, which

was not significantly different from the earnings of high school graduates with no postsecondary

education (table 8). Women who went to work with a bachelor’s degree started work at $22,602 per

year, which was more than those with less education. Male high school graduates also earned less

than those with a bachelor’s degree. Male high school graduates with no postsecondary education

earned $14,106 in their first year of work, those with some postsecondary education earned $11,357,

while men who attained a bachelor’s degree started at $26,778.

WORKERS WITH HIGH SCHOOL DIPLOMAS OR GEDS

In the last full year of employment reported, male workers who had worked consistently

earned $6,268 more than female workers, $25,601 compared to $19,333, respectively. Time on the

job did not account for the income difference in 1991. Both men and women had been in the work

force for nearly 10 years (117 months). However, earnings in the first year of employment for male

and female workers who earned a high school diploma or GED did not differ significantly. Men

earned $14,106 and women earned $13,452 immediately after graduating from high school.

 

33Associate’s degree recipients were combined with certificate attainers because neither group by itself was large

enough to report meaningful data. 
EARNINGS OF CONSISTENT WORKERS

18

Earnings in the last full year reported differed by $6,693 for men and women with a high

school diploma or GED and some postsecondary education who worked consistently; women earned

$20,106 and men, $26,799. However, earnings for the groups did not differ significantly in the first

full year.

Table 8 shows that the first full year of earnings for both male and female workers with a high

school diploma or GED and no postsecondary experience were higher than their counterparts with

some postsecondary experience. Women who did not pursue any postsecondary education earned

$13,452 in their first year versus $10,711 earned by women who enrolled, but did not complete a

postsecondary degree or certificate. Men who did not continue their education earned $14,106 in

the first full year compared to $11,357 for those who did continue, but did not complete any

postsecondary certification. 

By their last full year reported, the earnings of men and women with a high school diploma

and some postsecondary education caught up with that of men and women with no postsecondary

education. No significant difference existed in the last year earnings of men who graduated from high

school and those who continued and did not receive a degree. Annual earnings for men with a high

school diploma or GED and no postsecondary experience were $25,601, while earnings of those with

some postsecondary experience were $26,799. Women who continued their education after high

school, but did not graduate, did not have an income advantage over those who did not proceed with

education beyond a high school diploma by the last year reported. Last year earnings for women with

a high school diploma or GED and no postsecondary experience was $19,333, compared to $20,106

for women with some postsecondary experience.

These results suggest that attempting postsecondary education, but dropping out, may not

improve earnings significantly compared to not enrolling in postsecondary education. Most of the

respondents were in their late twenties in the final year earnings were reported. Thus, income

differences attributable to education might possibly appear later in their career. Or, it may be the case

that those attempting some postsecondary education and not completing were not enrolled long

enough to make an earnings difference in their careers.
EARNINGS OF CONSISTENT WORKERS

19

Table 8--Mean annual earnings in the first and last full year of employment after attainment, number of years

in the labor force and number of months employed among 1980 high school sophomores working

consistently,

1

 by highest level of education and gender

Annual earnings

First Last Years in Months

full year full year labor force employed

High school diploma or GED,

no postsecondary experience

Total $13,886 $23,523 10.0 117.0

Gender

 Male 14,106 25,601 10.0 117.0

 Female 13,452 19,333 10.0 116.9

High school diploma or GED,

some postsecondary experience

Total 11,075 23,873 10.0 117.0

Gender

 Male 11,357 26,799 10.0 117.0

 Female 10,711 20,106 10.0 116.9

Certificate or associate’s degree

Total 20,854 24,270 6.7 78.2

Gender

 Male 22,410 26,969 6.5 76.0

 Female 19,446 21,868 6.9 80.1

Bachelor’s degree2

Total 24,733 30,749 5.5 63.1

Gender

 Male 26,778 34,104 5.4 62.0

 Female 22,602 27,259 5.6 64.2

1Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

2

Includes respondents who obtained a bachelor’s degree as highest degree by 1992.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: 

Sophomore Cohort 1980-1992 (HS&B:92), Data Analysis System.

WORKERS WITH CERTIFICATES OR ASSOCIATE’S DEGREES

Men with an associate’s degree or certificate possessed an earnings advantage over women

in their first and last full year reported. Consistent female workers with a certificate or associate’s

degree earned $19,446, while their male counterparts earned $22,410 in their first full year, a $2,964
EARNINGS OF CONSISTENT WORKERS

20

difference. Consistent male workers with a certificate or associate’s degree earned $5,101 more than

their female counterparts, $26,969 compared to $21,868, respectively, in the last year reported.

Women worked more months after graduating than men; therefore, difference in length of

employment does not explain the earnings advantage of men over women. Women with an

associate’s degree or certificate were in the workplace for 80 months compared to 76 months for

men.

WORKERS WITH BACHELOR’S DEGREES

Male workers who received a bachelor’s degree earned more, on average, than females in

both the first and last full year reported. Consistent female workers with a bachelor’s degree earned

$4,176 less in the first full year than their male counterparts. Female workers with a bachelor’s

degree earned $22,602, while their male counterparts earned $26,778. The earnings differential for

men and women in the same groups during the last full year was $6,845; men earned $34,104

compared to $27,259 earned by women. 

The difference between the earnings of men and women with a bachelor’s degree cannot be

attributed to women spending less actual time on the job. On average, consistent female workers

who obtained a bachelor’s degree spent more time in the labor force after earning their degree than

their male counterparts. Consistent female workers spent 5.6 years working after college while their

male counterparts spent 5.4 years.

These results suggest that education did not eliminate the earnings differential between men

and women. On average, employers paid men more than women with the same level of education.

Time spent in the labor market also did not eliminate these differences. In these comparisons, women

either worked the same, or more time than men.
21

CONSISTENT WORKERS’ EARNINGS BY GENDER

DOMINANCE OF MAJOR FIELD OF STUDY

GENDER DOMINANCE OF MAJOR FIELD OF STUDY

The gender dominance of major field studied by students earning a postsecondary degree or

certificate was related to earnings. On average, graduates in male dominated majors earned more

than graduates in female dominated majors. Table 9 displays the annual earnings of all students,

regardless of gender or degree level. During their first full year of employment, workers in female

dominated majors earned an average of $20,855 while those in male dominated majors earned

$26,170, a $5,315 difference. Workers who graduated in female dominated fields earned an average

of $24,307 in the last year reported while those in male dominated fields earned $31,292. The

difference between the last year earnings of men and women was $6,985.

Table 9--Mean annual earnings in the first and last full year of employment after attainment among 1980 high

school sophomores working consistently,

1

by gender dominance of major field of study2

First full year Last full year

Total $23,373 $27,917

Gender dominance of major field of study, highest degree/certificate2

Male 26,170 31,292

Female 20,855 24,307

Gender neutral 24,486 30,125

1Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

2A program is gender dominant if 65 percent or more of the graduates were of the same sex.

SOURCE: U. S. Department of Education, National Center for Education Statistics, 1992 High School and Beyond:

Sophomore Cohort 1980-1992 (HS&B:92), Data Analysis System.

Workers with certificates or associate’s degrees

Male workers who received postsecondary certificates or associate’s degrees in female

dominated majors had an earnings advantage over women who graduated with degrees in female

dominated major programs. Male graduates with certificates or associate’s degrees in female

dominated programs earned $20,357 in the first full year of employment compared to $18,635 for
CONSISTENT WORKERS’ EARNINGS BY GENDER DOMINANCE OF MAJOR FIELD OF STUDY

22

women. This was an advantage of $1,722 for men (table 10). The earnings difference persisted in

the last full year reported. Male workers with certificates or associate’s degrees in female dominated

fields earned $26,065 compared to $21,197 earned by women, a $4,868 difference.

Table 10--Mean annual earnings in the first and last full year of employment after attainment, number of years

in the labor force and number of months employed among 1980 high school sophomores working

consistently1 with certificates or associate's degrees as highest degree, by gender and gender

dominance of major field of study2

Annual earnings

First Last Years in Months

full year full year labor force employed

Women

 Total $19,446 $21,868 6.9 80.1

Gender dominance of major field of study, highest degree/certificate2

 Male -- -- -- --

 Female 18,635 21,197 7.0 82.3

 Gender neutral 21,570 25,489 6.6 75.9

Men

 Total 22,410 26,969 6.5 76.0

Gender dominance of major field of study, highest degree/certificate2

 Male 23,892 27,374 6.7 78.2

 Female 20,357 26,065 6.1 71.3

 Gender neutral 21,020 23,815 7.3 85.1

--Sample size is too small for a reliable estimate.

1Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

2A program is gender dominant if 65 percent or more of the graduates were of the same sex.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: 

Sophomore Cohort 1980-1992 (HS&B:92), Data Analysis System.

Male and female workers with certificates or associate’s degrees in gender-neutral majors did

not have incomes that were significantly different in either the first or last full year reported. It was

not possible to determine whether female or male workers earned more if they graduated in male

dominated majors at the certificate or associate’s degree level, as too few women in the sample

graduated in male dominated majors to report the results. 
CONSISTENT WORKERS’ EARNINGS BY GENDER DOMINANCE OF MAJOR FIELD OF STUDY

23

Workers with bachelor’s degrees

Women who graduated with bachelor’s degrees earned $22,602 when they started their

careers, compared to men who earned $26,778, a $4,176 difference (table 11). After being on the

job for more than five years, women with bachelor’s degrees earned $27,259, while their male

counterparts earned $34,104, a $6,845 difference.

Table 11--Mean annual earnings in the first and last full year of employment after attainment, number of years

in the labor force and number of months employed among 1980 high school sophomores working

consistently1 with bachelor’s degrees as highest degree, by gender and gender dominance of major

field of study2

Annual earnings

First Last Years in Months

full year full year labor force employed3

Women

Total $22,602 $27,259 5.6 64.2

Gender dominance of major field of study, highest degree/certificate2

Male 23,968 31,363 5.5 64.6

Female 22,152 25,424 5.6 64.4

Gender neutral 22,905 28,558 5.6 64.5

Men

Total 26,778 34,104 5.4 62.0

Gender dominance of major field of study, highest degree/certificate2

Male 30,888 38,007 5.4 62.5

Female 23,036 30,982 5.4 62.5

Gender neutral 26,073 33,401 5.4 62.7

1Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

2A program is gender dominant if 65 percent or more of the graduates were of the same sex.

3

Total is not within the range of some of the subgroup estimates due to the number of observations with missing values

within the subgroup.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: 

Sophomore Cohort 1980-1992 (HS&B:92), Data Analysis System.

After controlling for the gender dominance of the major, the earnings difference still existed

between men and women. Men who received bachelor’s degrees in gender-neutral majors earned

more than women in both the first and last full year of work. During the first full year, men working

consistently with bachelor’s degrees in gender-neutral programs earned $3,168 more than their female

counterparts, women earned $22,905 while men earned $26,073. During the last full year reported,
CONSISTENT WORKERS’ EARNINGS BY GENDER DOMINANCE OF MAJOR FIELD OF STUDY

24

the difference in earnings for consistent male and female workers with bachelor’s degrees in genderneutral programs was $4,843. Female workers with bachelor’s degrees in gender-neutral programs

earned $28,558, while their male counterparts earned $33,401 in that last year.

Earning differences appeared in the last full year reported between male and female workers

with bachelor’s degrees in both male and female dominated majors. Female workers with bachelor’s

degrees in female dominated majors earned $25,424 in the last year, while men earned $30,982, for

a difference of $5,558. Female workers who graduated with bachelor’s degrees in male dominated

majors earned $31,363 in the last year while their male counterparts earned $38,007. The earnings

difference between male and female workers who graduated in male dominated fields was $6,644 in

the last year. However, significant differences did not exist between men’s and women’s earnings

for the first year after graduation for those who received bachelor’s degrees in either male or female

dominated majors.

Again, the earnings differential between male and female workers who received bachelor’s

degrees cannot be attributed to time in the labor force. No significant difference existed between

male and female workers in the number of years working or the number of months employed for

graduates in male, female or gender-neutral majors.
25

EARNINGS GROWTH EXPERIENCED BY MEN AND WOMEN

WORKING CONSISTENTLY

At all degree levels, men’s annual earnings increased more than women’s from the first year

of work to the last year reported. The measure of change in earnings reported in table 12 illustrates

the relative increase in men’s and women’s earnings in constant 1992 dollars. The percentile ranking

of change in earnings provided a measure of the difference in men’s and women’s earnings growth.34

Table 12--Mean percentile ranking of change in annual earnings among 1980 high school sophomores working

consistently1 from first full year to last full year of employment after attainment of highest degree

according to highest degree attained by 1992, by gender

High school High school

diploma diploma

or GED, no or GED, some Certificate

postsecondary postsecondary or associate's Bachelor's

experience experience degree degree2

Total 48.5 48.2 48.6 50.0

Gender

Male 51.6 53.1 51.3 54.1

Female 42.4 41.8 46.0 45.8

1Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

2

Includes respondents who obtained a bachelor’s degree as highest degree by 1992.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: 

Sophomore Cohort 1980-1992 (HS&B:92), Data Analysis System.

At all degree levels, the average percentile ranking of change in earnings for males exceeded

that of their female counterparts. This suggests that the earnings of male workers increased more

during the study period than those of women. Male workers with a high school diploma or GED and

no postsecondary education had an average percentile ranking of change in earnings of 52, while

female workers ranked 42. The mean percentile ranking of change in earnings for male workers who

had some postsecondary education, but no degree, was higher than females by 11 percentile points.

 

34The design of this measure was necessary for technical reasons when developing the HS&B Data Analysis System.
EARNINGS GROWTH EXPERIENCED BY MEN AND WOMEN WORKING CONSISTENTLY

26

As reported earlier, the earnings of males and females were not significantly different in the first year

for either of these earnings levels, but men earned more than women in the last year reported.

The mean percentile ranking of change in earnings for male workers with a certificate or

associate’s degree was also higher than that of women with the same level of education. Men were

ranked at 51 percent compared to 46 percent for women. Finally, the mean percentile ranking of

change in earnings for male workers with a bachelor’s degree was 8 percentile points higher than their

female counterparts, 54 compared to 46, respectively. Thus, males with postsecondary degrees or

certificates made more money than females when they started working and their income increased

faster than females.
27

FACTORS ASSOCIATED WITH EARNINGS IN THE TOP AND

BOTTOM CATEGORIES OF MEN AND WOMEN WORKING

CONSISTENTLY

Given the earnings differential between men and women after controlling for education level,

gender dominance of major field of study and work consistency, the characteristics of those men and

women who achieved either high or low earnings was of interest. The following sections identify the

characteristics of men and women, separately, that were associated with achievement of high or low

earnings. Earnings categories were developed to approximate quartiles in their respective gender

groups and were rounded to the closest $50. The information is presented for high school graduates

and bachelor’s degree recipients.

WORKERS WITH HIGH SCHOOL DIPLOMAS OR GEDS

Male workers

A male high school graduate had to earn a minimum of $31,000 to qualify for the top earnings

quartile in table 13. Race/ethnicity and family formation factors for male high school graduates were

related to the probability that earnings would be in the highest or lowest quartile in the last year of

the study.

Family formation factors were related to the likelihood of earning in the highest or lowest

category for male workers with no more than a high school diploma or GED. Consistent male

workers with a high school diploma or GED who were married or never married by 1992 were more

likely to have earnings of $31,000 or more than men who were no longer married by 1992. Twentyeight and 27 percent of married and never married men, respectively, had final year incomes in the

highest earnings category, compared to 9 percent of those no longer married. Being married

compared to never married was not associated with a significantly different probability of achieving

earnings in the top quartile.
FACTORS ASSOCIATED WITH EARNINGS IN THE TOP AND BOTTOM CATEGORIES OF MEN AND WOMEN

WORKING CONSISTENTLY

28

Table 13--Percentage distribution of 1980 male high school sophomores working consistently1 with high school

diplomas or GEDs as highest degree, according to annual earnings in constant 1992 dollars for the

last full year of employment after attainment, by selected characteristics

Annual earnings in constant 1992 dollars for last

full year of employment after highest degree attainment

Less than $17,500- $23,500- $31,000

$17,500 $23,499 $30,999 or more

Total 24.1 23.8 26.4 25.7

Family socioeconomic status, 1980

 Lowest third 28.1 24.1 26.5 21.3

 Middle third 21.9 26.3 25.8 26.0

 Highest third 23.5 17.9 27.0 31.5

Race/ethnicity

 American Indian/Alaskan Native -- -- -- --

 Asian/Pacific Islander -- -- -- --

 Black, non-Hispanic 30.6 32.4 14.3 22.7

 White, non-Hispanic 22.8 22.6 27.2 27.4

 Hispanic 30.0 23.5 32.2 14.3

Grades in high school2

 90-100 -- -- -- --

 80-89 21.7 24.5 27.8 26.1

 Less than 80 24.7 23.7 26.1 25.5

Number of children, June 1992

 None 28.3 21.2 25.2 25.3

 One or more 20.1 26.3 27.5 26.2

Marital status, June 1992

 Married 20.8 25.2 26.5 27.5

 No longer married 16.1 29.2 45.6 9.0

 Never married 31.5 19.9 21.8 26.9

Postsecondary education experience, non-attainers

 No postsecondary education 23.5 25.7 26.0 24.8

 Some postsecondary education 25.4 19.9 27.1 27.6

--Sample size is too small for a reliable estimate.

1Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

2On a 100 point scale.

NOTE: Percentages may not sum to 100 percent due to rounding.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: 

Sophomore Cohort 1980-1992 (HS&B:92), Data Analysis System.
FACTORS ASSOCIATED WITH EARNINGS IN THE TOP AND BOTTOM CATEGORIES OF MEN AND WOMEN

WORKING CONSISTENTLY

29

Race/ethnicity of males was also related to achieving earnings in the highest quartile. White,

non-Hispanic male workers with no more than a high school diploma or GED were more likely than

Hispanic males to have earned $31,000 or more in the last year. Twenty-seven percent of white, nonHispanic males achieved highest quartile earnings compared to 14 percent of Hispanic males.

Female workers

The minimum earnings for women to qualify for the top earnings quartile in table 14 were

$24,000. For women with a high school diploma or GED, attaining some postsecondary education

experience was associated with attaining earnings in the highest earnings quartile. Thirty percent of

women who attempted postsecondary education earned in the highest quartile compared to 21

percent of those who never enrolled.

WORKERS WITH BACHELOR'S DEGREES

Male workers

For men with a bachelor’s degree, the minimum earnings to qualify for the top earnings

quartile in table 15 were $41,000. High school grades and gender dominance of major field were

related to achieving earnings in the top or bottom quartiles during the last year reported for men with

a bachelor’s degree.

High school grades were related to the eventual earnings of college graduates. Male workers

who received a bachelor’s degree and had average high school grades of 90 or above (on a 100-point

scale) were more likely to earn $41,000 or more during their last reported year than those with grades

less than 80. Further, male workers with high school grades below 80 points were more likely to earn

less than $25,000 during their last employment year than those with high school grades of 90 or

above.

Men who majored in a female dominated major were more likely to have earnings in the

lowest quartile than men who majored in male dominated or gender-neutral majors. Forty-two

percent of men in female dominated majors had earnings under $25,000, compared to 23 percent of

men in gender-neutral majors, and 14 percent in male dominated ones. The gender dominance of

men’s major field of study was not significantly related to earning $41,000 or more in the last full year

reported.
FACTORS ASSOCIATED WITH EARNINGS IN THE TOP AND BOTTOM CATEGORIES OF MEN AND WOMEN

WORKING CONSISTENTLY

30

Table 14--Percentage distribution of 1980 female high school sophomores working consistently1 with high

school diplomas or GEDs as highest degree, according to annual earnings in constant 1992

dollars for the last full year of employment after attainment, by selected characteristics

Annual earnings in constant 1992 dollars for last

full year of employment after highest degree attainment

Less than $14,500- $19,500- $24,000

$14,500 $19,499 $23,999 or more

Total 25.5 25.2 24.6 24.7

Family socioeconomic status, 1980

 Lowest third 32.5 26.0 21.9 19.7

 Middle third 18.9 29.7 26.7 24.7

 Highest third 26.8 15.8 25.2 32.2

Race/ethnicity

 American Indian/Alaskan Native -- -- -- --

 Asian/Pacific Islander -- -- -- --

 Black, non-Hispanic 23.3 22.7 31.6 22.5

 White, non-Hispanic 25.0 25.7 24.0 25.3

 Hispanic 31.6 24.1 15.6 28.7

Grades in high school2

 90-100 -- -- -- --

 80-89 22.0 22.1 28.2 27.7

 Less than 80 27.8 27.3 22.8 22.1

Number of children, June 1992

 None 25.0 22.1 24.3 28.6

 One or more 26.0 28.1 24.8 21.2

Marital status, June 1992

 Married 29.3 24.0 24.4 22.4

 No longer married 25.0 26.2 26.8 22.1

 Never married 17.9 27.0 23.5 31.7

Postsecondary education experience, non-attainers

 No postsecondary education 26.2 30.0 22.7 21.1

 Some postsecondary education 24.7 18.9 27.0 29.5

--Sample size is too small for a reliable estimate.

1Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

2On a 100 point scale.

NOTE: Percentages may not sum to 100 percent due to rounding.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: 

Sophomore Cohort 1980-1992 (HS&B:92), Data Analysis System.
FACTORS ASSOCIATED WITH EARNINGS IN THE TOP AND BOTTOM CATEGORIES OF MEN AND WOMEN

WORKING CONSISTENTLY

31

Table 15--Percentage distribution of 1980 male high school sophomores working consistently1 with bachelor's

degrees as highest degree, according to annual earnings in constant 1992 dollars for the last full year

of employment after attainment, by selected characteristics

Annual earnings in constant 1992 dollars for last

full year of employment after highest degree attainment

Less than $25,000- $32,750- $41,000

$25,000 $32,749 $40,9992or more

2

 Total 25.3 23.2 26.0 25.5

Family socioeconomic status, 1980

 Lowest third 32.8 27.2 22.4 17.6

 Middle third 25.1 25.1 23.3 26.6

 Highest third 22.6 21.8 27.1 28.5

Race/ethnicity

 American Indian/Alaskan Native -- -- -- --

 Asian/Pacific Islander -- -- -- --

 Black, non-Hispanic 48.5 16.0 14.4 21.2

 White, non-Hispanic 23.0 24.6 26.7 25.8

 Hispanic 20.1 10.8 20.8 48.3

Grades in high school3

 90-100 9.8 7.9 31.6 50.6

 80-89 23.9 22.5 23.5 30.2

 Less than 80 30.4 29.0 27.2 13.4

Number of children, June 1992

 None 24.5 24.0 24.9 26.6

 One or more 25.3 21.5 26.8 26.5

Marital status June 1992

 Married 24.0 21.3 25.0 29.7

 No longer married -- -- -- --

 Never married 26.9 25.9 23.9 23.3

Age received highest degree

 Less than 24 23.0 23.9 24.9 28.3

 24 or older 31.5 14.2 35.7 18.5

Gender dominance of major field of study, highest degree/certificate4

 Male 14.0 14.3 38.1 33.6

 Female 41.5 21.9 15.4 21.2

 Gender neutral 22.9 31.0 23.6 22.5
FACTORS ASSOCIATED WITH EARNINGS IN THE TOP AND BOTTOM CATEGORIES OF MEN AND WOMEN

WORKING CONSISTENTLY

32

Table 15--Percentage distribution of 1980 male high school sophomores working consistently1 with bachelor's

degrees as highest degree, according to annual earnings in constant 1992 dollars for the last full year

of employment after attainment, by selected characteristics--Continued

Annual earnings in constant 1992 dollars for last

full year of employment after highest degree attainment

Less than $25,000- $32,750- $41,000

$25,000 $32,749 $40,9992or more

2

Undergraduate grade point average

 Less than 2.50 28.3 23.4 24.3 24.0

 2.50-3.50 22.6 26.1 25.6 25.7

 Higher than 3.50 21.6 10.9 18.9 48.6

--Sample size is too small for a reliable estimate.

1Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

2

Total is not within the range of some of the subgroup estimates due to the number of observations with missing values

within the subgroups.

3On a 100 point scale.

4A program is gender dominant if 65 percent or more of the graduates were of the same sex.

NOTE: Percentages may not sum to 100 percent due to rounding.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: 

Sophomore Cohort 1980-1992 (HS&B:92), Data Analysis System.

Female workers

The top earnings quartile starts at $32,000 for female workers with a bachelor’s degree. 

Table 16 shows that high school grades and gender dominance of major field of study were associated

with the likelihood that a female worker had earnings in the top or bottom quartile.

High school grades of female college graduates were related to the earnings in their last full

year. Thirty-nine percent of the female workers with a bachelor’s degree who had high school grades

of 90 or above (on a 100-point scale) earned $32,000 or more during their last year reported

compared to 15 percent of those with grades below 80. Female workers who received bachelor’s

degrees and had high school grades of less than 80 were more likely to have earnings in the bottom

quartile (below $20,250) during their last year reported than women with scores between 80 and 89.

Gender dominance of major field of study was related to earning in the bottom quartile in the

last full year reported for women. Thirty percent of the women workers who received bachelor’s

degrees in female dominated majors had last year earnings in the lowest quartile compared to 6

percent of those in male dominated majors. Women with bachelor’s degrees in male dominated
FACTORS ASSOCIATED WITH EARNINGS IN THE TOP AND BOTTOM CATEGORIES OF MEN AND WOMEN

WORKING CONSISTENTLY

33

majors who worked consistently were no more likely than those in female dominated majors to

achieve earnings in the high income category. 

Table 16--Percentage distribution of 1980 female high school sophomores working consistently1 with bachelor's

degrees as highest degree, according to annual earnings in constant 1992 dollars for the last full year

of employment after attainment, by selected characteristics

Annual earnings in constant 1992 dollars for last

full year of employment after highest degree attainment

Less than $20,250- $26,000- $32,000

$20,2502$25,999 $31,999 or more

2

Total 23.3 24.3 26.9 25.5

Family socioeconomic status, 1980

 Lowest third 28.2 28.5 24.8 18.5

 Middle third 27.5 28.8 19.9 23.8

 Highest third 18.9 21.0 31.9 28.2

Race/ethnicity

 American Indian/Alaskan Native -- -- -- --

 Asian/Pacific Islander -- -- -- --

 Black, non-Hispanic 23.1 36.8 21.8 18.3

 White, non-Hispanic 23.0 23.3 28.0 25.7

 Hispanic 18.6 24.8 23.7 32.9

Grades in high school3

 90-100 21.3 16.1 23.4 39.2

 80-89 19.2 26.0 28.8 26.1

 Less than 80 34.5 24.8 25.7 15.0

Number of children, June 1992

 None 20.8 23.2 29.5 26.4

 One or more 28.9 28.1 19.6 23.4

Marital status, June 1992

 Married 24.9 24.4 24.9 25.9

 No longer married -- -- -- --

 Never married 20.2 23.5 30.6 25.8

Age received highest degree

 Less than 24 22.7 23.8 27.7 25.7

 24 or more 9.7 43.1 21.0 26.1

Gender dominance of major field of study, highest degree/certificate4

 Male 5.5 20.7 32.7 41.2

 Female 29.7 26.7 24.9 18.8

 Gender neutral 19.2 23.3 27.5 30.0
FACTORS ASSOCIATED WITH EARNINGS IN THE TOP AND BOTTOM CATEGORIES OF MEN AND WOMEN

WORKING CONSISTENTLY

34

Table 16--Percentage distribution of 1980 female high school sophomores working consistently1 with bachelor's

degrees as highest degree, according to annual earnings in constant 1992 dollars for the last full year

of employment after attainment, by selected characteristics--Continued

Annual earnings in constant 1992 dollars for last

full year of employment after highest degree attainment

Less than $20,250- $26,000- $32,000

$20,2501$25,999 $31,999 or more

2

Undergraduate grade point average

 Less than 2.50 25.9 31.0 25.5 17.7

 2.50-3.50 21.0 24.4 29.2 25.4

 Greater than 3.50 24.9 13.1 22.5 39.5

--Sample size is too small for a reliable estimate.

1Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

2

Total is not within the range of some of the subgroup estimates due to the number of observations with missing values

within the subgroups.

3On a 100 point scale.

4A program is gender dominant if 65 percent or more of the graduates were of the same sex.

NOTE: Percentages may not sum to 100 percent due to rounding.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: 

Sophomore Cohort 1980-1992 (HS&B:92), Data Analysis System.
35

FACTORS ASSOCIATED WITH EARNINGS IN THE TOP

CATEGORY AFTER CONTROLLING FOR BACKGROUND

VARIATION

Crosstabulations have limitations when used with survey data. Sample size restricts the

number of cells into which the data can be usefully subdivided. In many instances, complex

interrelationships exist among variables that cannot be disentangled in tabular analysis. To overcome

the limitations of crosstabulations, a linear regression model was used to take into account the effects

of all variables in the model simultaneously and control for interrelationships among variables that

could influence findings in the crosstabulations, yielding adjusted means.35 By estimating the joint

effect of all variables taken together, the regression model was used to test individual parameters

while holding the influence of other variables constant. Because of the interrelationships between

variables, it was of interest to learn if differences were still found with the use of a linear model.

WORKERS WITH HIGH SCHOOL DIPLOMAS OR GEDS

Male workers

Table 17 shows the adjusted percentages of male consistent workers with high school

diplomas or GEDs by 1992 who achieved the top earnings category, taking into account other

characteristics. The unadjusted means are included for comparison.

After the other variables in the model were taken into consideration, some findings remained

consistent with the tabular analysis. Male workers who were married by 1992 were still more likely

to have earnings of $31,000 or more than males who were no longer married by 1992. The

regression also confirmed that Hispanic men were less likely to achieve earnings in the highest

earnings category in the last year reported compared to white, non-Hispanic male workers with no

more than a high school diploma or GED.

 

35Appendix B contains a description of the means adjustment method.
FACTORS ASSOCIATED WITH EARNINGS IN THE TOP CATEGORY AFTER CONTROLLING FOR BACKGROUND

VARIATION

36

Table 17--Percentage of 1980 male high school sophomores working consistently1 with high school diplomas or

GEDs as highest degree who were in the highest earnings quartile during the last full year of

employment after attainment, and the adjusted percentage after taking into account the covariation

of the variables listed2

Unadjusted Adjusted WLS Standard

Percentage3percentage4coefficient5error

6

Total 25.7 25.7 53.1 2.7

Family socioeconomic status, 1980

Lowest third 21.3 20.7 + +

Middle third 26.0 25.9 5.2 3.8

Highest third 31.5 29.5 * 8.8 4.0

Race/ethnicity

White, non-Hispanic 27.4 26.7 + +

Black, non-Hispanic 22.7 22.3 -4.4 6.0

Hispanic 14.3 * 15.0 * -11.7 4.8

Grades in high school7

90-100 -- -- + +

80-89 26.1 25.3 -31.7 21.2

Less than 80 25.5 25.0 -32.0 20.9

Number of children, June 1992

None 25.3 23.4 + +

One or more 26.2 27.1 3.7 3.9

Marital status, June 1992

Married 27.5 26.6 + +

No longer married 9.0 * 8.8 * -17.8 5.0

Never married 26.9 27.6 1.0 4.1

Postsecondary education experience, non-attainers

No postsecondary education 24.8 25.0 + +

Some postsecondary education 27.6 25.7 0.7 3.4

--Sample size is too small for a reliable estimate.

* p<=.05 comparing to the reference group, indicated by +.

+ Not available for reference group.

1Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

2

The group in italics is the reference group for comparison.

3

Estimates from HS&B:92 Data Analysis System.

4

Percentages adjusted for differences associated with other variables in the table (see appendix B for details).

5Weighted least squares (WLS) coefficient (see appendix B for details) multiplied by 100 for conversion to a percentage.

6

Standard error of WLS coefficient, adjusted for design effect (see appendix B for details) multiplied by 100 for

conversion to a percentage.

7On a 100 point scale.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: Sophomore

Cohort 1980-1992 (HS&B:92), Data Analysis System.
FACTORS ASSOCIATED WITH EARNINGS IN THE TOP CATEGORY AFTER CONTROLLING FOR BACKGROUND

VARIATION

37

One result did change. After the means were adjusted, males whose 1980 family

socioeconomic status was in the highest third were more likely to have an income in the top earnings

quartile when compared to those whose family was in the lowest socioeconomic group. In the

crosstabulation, the respondent’s family SES was not associated with earnings differences.

Female workers

Table 18 shows the adjusted percentages of consistent female workers with high school

diplomas or GEDs by 1992 who had earnings in the top quartile. The linear regression yields

different results from those reported in the crosstabulation. First, the adjusted results indicate that

pursuing a postsecondary education without obtaining a degree or certificate did not change the

probability that female workers would be in the top earnings quartile compared to those with no

postsecondary experience. In the crosstabulation, these women were more likely to have incomes

in the highest quartile. 

Second, the linear regression revealed a relationship between grades in high school and the

probability that female high school graduates would have incomes in the top quartile. The adjusted

results suggest that workers with high school grades below 80 were less likely to achieve earnings

in the top quartile than workers with high school grades of 90 to 100. Again, a significant

relationship between grades and earnings was not found in the crosstabulation. 

Third, the crosstabular analysis did not show any difference in the probability of earning in the

highest quartile by family SES. However, after adjusting the means, the linear regression revealed

that women in the lowest third of family SES were less likely to achieve earnings in the top category

than those in the top third.
FACTORS ASSOCIATED WITH EARNINGS IN THE TOP CATEGORY AFTER CONTROLLING FOR BACKGROUND

VARIATION

38

Table 18--Percentage of 1980 female high school sophomores working consistently1 with high school diplomas

or GEDs as highest degree who were in the highest earnings quartile during the last full year of

employment after attainment, and the adjusted percentage after taking into account the covariation

of the variables listed2

Unadjusted Adjusted WLS Standard

percentage3percentage4coefficient5error

6

Total 24.7 24.7 40.5 3.6

Family socioeconomic status, 1980

Lowest third 19.7 20.2 + +

Middle third 24.7 24.4 4.2 4.1

Highest third 32.2 31.0 * 10.8 5.4

Race/ethnicity

White, non-Hispanic 25.3 24.7 + +

Black, non-Hispanic 22.5 21.6 -3.1 6.9

Hispanic 28.7 32.4 7.7 8.2

Grades in high school7

90-100 -- -- + +

80-89 27.7 27.3 -18.3 12.1

Less than 80 22.1 22.0 * -23.7 12.1

Number of children, June 1992

None 28.6 27.1 + +

One or more 21.2 22.2 -4.8 4.2

Marital status, June 1992

Married 22.4 23.1 + +

No longer married 22.1 21.6 -1.5 6.5

Never married 31.7 28.8 5.7 4.9

Postsecondary education experience, non-attainers

No postsecondary education 21.1 22.7 + +

Some postsecondary education 29.5 * 27.0 4.4 4.0

--Sample size is too small for a reliable estimate.

* p<=.05 comparing to the reference group, indicated by +.

+ Not available for reference group.

1Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

2

The group in italics is the reference group for comparison.

3

Estimates from HS&B:92 Data Analysis System.

4

Percentages adjusted for differences associated with other variables in the table (see appendix B for details).

5Weighted least squares (WLS) coefficient (see appendix B for details) multiplied by 100 for conversion to a percentage.

6

Standard error of WLS coefficient, adjusted for design effect (see appendix B for details) multiplied by 100 for

conversion to a percentage.

7On a 100 point scale.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: Sophomore

Cohort 1980-1992 (HS&B:92), Data Analysis System.

WORKERS WITH BACHELOR’S DEGREES
FACTORS ASSOCIATED WITH EARNINGS IN THE TOP CATEGORY AFTER CONTROLLING FOR BACKGROUND

VARIATION

39

Male workers

Table 19 displays the adjusted percentages of male consistent workers with bachelor’s

degrees by 1992 who achieved the top earnings category, taking into account other characteristics.

After adjusting the means, high school grades were still related to earnings. Male workers who had

high school grades of 90 to 100 had a higher probability of having earnings in the top quartile

compared to those with lower high school grades. Also, the linear regression revealed that male

workers who received a bachelor’s degree and were never married were less likely to achieve earnings

in the top category than those who were married. This finding was not significant in the tabular

analysis.

Female workers

Table 20 shows the adjusted percentages of female workers with bachelor’s degrees by 1992

who achieved the top earnings category, taking into account other characteristics. The linear

regression for these individuals confirmed the finding from the crosstabulation analysis that high

school grades were a predictor of high earnings for female workers who received bachelor’s degrees.

Also, the linear regression revealed that obtaining a bachelor’s degree in a male dominated major

rather than a female dominated or gender-neutral major was a predictor of earning a high income.
FACTORS ASSOCIATED WITH EARNINGS IN THE TOP CATEGORY AFTER CONTROLLING FOR BACKGROUND

VARIATION

40

Table 19--Percentage of 1980 male high school sophomores working consistently1 with bachelor’s degrees as

highest degree who were in the highest earnings quartile during the last full year of employment

after attainment, and the adjusted percentage after taking into account the covariation of the

variables listed2

Unadjusted Adjusted WLS Standard

percentage3,8 percentage4coefficient5error

6

Total 25.5 25.5 57.0 2.3

Family socioeconomic status, 1980

Lowest third 17.6 19.3 + +

Middle third 26.6 26.2 6.9 7.6

Highest third 28.5 26.2 6.9 7.1

Race/ethnicity

White, non-Hispanic 25.8 23.9 + +

Black, non-Hispanic 21.2 26.8 2.9 8.3

Hispanic 48.3 46.9 23.0 12.5

Grades in high school7

90-100 50.6 47.5 + +

80-89 30.2 28.8 * -18.7 8.2

Less than 80 13.4 * 14.1 * -33.4 9.2

Number of children, June 1992

None 26.6 26.4 + +

One or more 26.5 22.5 -3.9 5.8

Marital status, June 1992

Married 29.7 29.3 + +

Never married 23.3 20.8 * -8.5 4.3

Age received highest degree

Less than 24 28.3 26.4 + +

24 or older 18.5 9.8 * -16.6 7.6

Gender dominance of major field of study, highest degree/certificate9

Male 33.6 32.0 + +

Female 21.2 23.3 -8.8 6.5

Gender neutral 22.5 22.4 -9.6 5.0
FACTORS ASSOCIATED WITH EARNINGS IN THE TOP CATEGORY AFTER CONTROLLING FOR BACKGROUND

VARIATION

41

Table 19--Percentage of 1980 male high school sophomores working consistently1 with bachelor’s degrees as

highest degree who were in the highest earnings quartile during the last full year of employment

after attainment, and the adjusted percentage after taking into account the covariation of the

variables listed2--Continued

Unadjusted Adjusted WLS Standard

percentage3,8 percentage4coefficient5error

6

Undergraduate grade point average

Less than 2.50 24.0 29.4 + +

2.50-3.50 25.7 22.1 -7.3 4.6

Greater than 3.50 48.6 42.1 12.7 8.3

--Sample size is too small for a reliable estimate.

* p<=.05 comparing to the reference group, indicated by +.

+ Not available for reference group.

1Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

2

The group in italics is the reference group for comparison.

3

Estimates from HS&B:92 Data Analysis System.

4

Percentages adjusted for differences associated with other variables in the table (see appendix B for details).

5Weighted least squares (WLS) coefficient (see appendix B for details) multiplied by 100 for conversion to a percentage.

6

Standard error of WLS coefficient, adjusted for design effect (see appendix B for details) multiplied by 100 for

conversion to a percentage.

7On a 100 point scale.

8

Total is not within the range of some of the subgroup estimates due to the number of observations with missing values

within the subgroups.

9A program is gender dominant if 65 percent or more of the graduates were of the same sex.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: Sophomore

Cohort 1980-1992 (HS&B:92), Data Analysis System.
FACTORS ASSOCIATED WITH EARNINGS IN THE TOP CATEGORY AFTER CONTROLLING FOR BACKGROUND

VARIATION

42

Table 20--Percentage of 1980 female high school sophomores working consistently1 with bachelor’s degrees as

highest degree who were in the highest earnings quartile during the last full year of employment

after attainment, and the adjusted percentage after taking into account the covariation of the

variables listed2

Unadjusted Adjusted WLS Standard

percentage3,8 percentage4coefficient5error

6

Total 25.5 25.5 50.1 2.0

Family socioeconomic status, 1980

Lowest third 18.5 21.6 + +

Middle third 23.8 24.3 2.7 6.7

Highest third 28.2 26.8 5.2 6.8

Race/ethnicity

White, non-Hispanic 25.7 25.1 + +

Black, non-Hispanic 25.7 24.9 -0.3 7.5

Hispanic 32.9 31.7 6.6 6.6

Grades in high school7

90-100 39.2 38.8 + +

80-89 26.1 25.6 * -13.2 5.5

Less than 80 15.0 * 16.3 * -22.5 6.9

Number of children, June 1992

None 26.4 26.3 + +

One or more 23.4 22.7 -3.5 5.0

Marital status, June 1992

Married 25.9 26.7 + +

Never married 25.8 24.6 -2.1 4.2

Age received highest degree

Less than 24 25.7 25.4 + +

24 or older 26.1 31.4 6.1 11.6

Gender dominance of major field of study, highest degree/certificate9

Male 41.2 42.7 + +

Female 18.8 20.3 * -22.4 7.0

Gender neutral 30.0 26.6 * -16.1 6.6
FACTORS ASSOCIATED WITH EARNINGS IN THE TOP CATEGORY AFTER CONTROLLING FOR BACKGROUND

VARIATION

43

Table 20--Percentage of 1980 female high school sophomores working consistently1 with bachelor’s degrees as

highest degree who were in the highest earnings quartile during the last full year of employment

after attainment, and the adjusted percentage after taking into account the covariation of the

variables listed2--Continued

Unadjusted Adjusted WLS Standard

percentage3,8 percentage4coefficient5error

6

Undergraduate grade point average

Less than 2.50 17.7 22.1 + +

2.50-3.50 25.4 25.3 3.1 4.8

Greater than 3.50 39.5 31.7 9.6 6.8

--Sample size is too small for a reliable estimate.

* p<=.05 comparing to the reference group, indicated by +.

+ Not available for reference group.

1Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

2

The group in italics is the reference group for comparison.

3

Estimates from HS&B:92 Data Analysis System.

4

Percentages adjusted for differences associated with other variables in the table (see appendix B for details).

5Weighted least squares (WLS) coefficient (see appendix B for details) multiplied by 100 for conversion to a percentage.

6

Standard error of WLS coefficient, adjusted for design effect (see appendix B for details) multiplied by 100 for

conversion to a percentage.

7On a 100 point scale.

8

Total is not within the range of some of the subgroup estimates due to the number of observations with missing values

within the subgroups.

9A program is gender dominant if 65 percent or more of the graduates were of the same sex.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: Sophomore

Cohort 1980-1992 (HS&B), Data Analysis System.
44

SUMMARY AND IMPLICATIONS

Over the past several decades, an increasing number of women have pursued postsecondary

education. Women now exceed men in the rate of completion at most levels of postsecondary

education. At the same time, women are increasingly likely to work out of the home, while they

continue to earn less than men. Several theories have been put forth to explain this income

discrepancy. This report considered two of these possibilities. First, the disparity between the

incomes of men and women may have been due to the interruption of women’s careers for family

reasons such as caring for children or following a transferred husband. Second, women may have

obtained training and education to prepare for occupations traditionally held by females that paid less

than occupations pursued by men.

Women were less likely than men to work consistently after leaving school. Further, both

men and women with less education were less likely to work consistently than those with higher levels

of education. Nine percent of the female and 37 percent of the male high school dropouts worked

consistently compared to 50 percent of both males and females who earned bachelor’s degrees.

Family formation was another factor that was associated with work consistency. Compared

to having no children, the effect of having two or more children was that women were less likely to

work consistently and men were more likely. Several possible explanations exist as to why women

with two or more children were less likely to be work consistently than their childless counterparts.

First, women with children may have found it more difficult to hold down a job consistently than

those without children. Second, the costs associated with daycare may have reduced the value of

work, especially for women with lower income potential. In 1986, poor women had to utilize 25

percent of their earnings for childcare, while women in households that were not poor utilized 6

percent.36 Thus, work may not have made economic sense for low-income women who had to pay

for childcare.

Earnings information was limited to respondents who worked consistently after they left

school; therefore, earnings differences reported were not due to women working fewer years after

leaving school or leaving the labor market for extended lengths of time. The prevailing finding was

 

36 U. S. Department of Labor, Women’s Bureau. 1993 Handbook on Women Workers: Trends and Issues. 

(Washington, D.C.: author, 1993), p. 13.
SUMMARY AND IMPLICATIONS

45

that men either earned more or did not have significantly different incomes when compared to

women. In no case did women enjoy an earnings advantage over men. Although education improved

earnings for both men and women, it did not eliminate the income gap. Differences in earnings were

apparent between men and women even when education level was controlled. Further, controlling

for gender dominance of major field of study did not explain the difference in earnings between men

and women completely.

Although more women earned bachelor’s degrees than men, and consistent female workers

spent more time in the labor market after graduation than their male counterparts, in each category

of gender dominance of field of study, incomes of men with a bachelor’s degree were higher than

women’s in the last year. Thus, the increased success of women in higher education and the

commitment to their jobs after graduation has not been rewarded with the same income as men.

Several data limitations may have affected the results. First, the inability to determine if a

person was working part- or full-time may have influenced the results. As reported, among consistent

workers, women were slightly more likely than men to have had annual earnings below $8,000 in the

last year of work (this was used as an indicator of working part-time). However, the difference was

not large enough to explain the income differences noted between men and women. Also, type of job

was not classified in the data. Men and women with the same majors may have taken different types

of jobs. This job type difference could have contributed to the earnings discrepancies between men

and women.

Other factors beyond those considered in this report may also have helped cause the earnings

discrepancies between males and females. Among factors that might explain the differential between

men’s and women’s earnings are employment choices made by women and socialized differences

between men and women. First, women may be more likely than men to accept a less demanding,

lower paying position early in their career. A woman may make early career choices because she

expects to require time to be the primary caretaker for children. Second, from birth, girls and boys

are socialized differently. Girls are expected to be passive and less aggressive than boys. Socialized

differences are carried through life into the work place. Aggressiveness in business is usually seen

as an asset, and these socialized characteristics may help men achieve higher positions and incomes

than women.37

 

37 B. Deckard. The Women’s Movement: Political, Socioeconomic and Psychological Issues. (New York: Harper &

Row, 1983), p. 87.
SUMMARY AND IMPLICATIONS

46
47

APPENDIX A: GLOSSARY

This glossary describes the variables used in this report. The variables were taken directly

from the NCES HS&B:92 Data Analysis System (DAS). This is an NCES software application that

generates tables from the HS&B data. A description of the DAS software can be found in appendix

B. The labels in parentheses correspond to the names of the variables in the DAS.

Age at degree attainment AGE

Respondent’s age upon completion of highest degree.

Annual earnings during the first full calendar year reported STRT_PAY

For consistent workers, annual earnings during the first full calendar year of employment after

completion of highest degree. Years included were 1983 to 1991. The earnings were corrected

to 1992 constant dollars. Consistent employment was defined as working at least 91.67 percent

of the total months in the labor force after attaining the highest level of education, or 11 out of 12

months for each year in the labor force.

Annual earnings during the last full calendar year reported END_PAY

For consistent workers, annual earnings during the last full calendar year the respondent was

working, up to and including 1991. The earnings were corrected to 1992 constant dollars.

Consistent employment was defined as working at least 91.67 percent of the total months in the

labor force after attaining the highest level of education, or 11 out of 12 months for each year in

the labor force.

Continuously enrolled in postsecondary education,

degree/certificate attainers BREAK_ED

For respondents completing a postsecondary certificate or degree, whether there was a break in

their postsecondary education of greater than six months.

Break in postsecondary education

No break in postsecondary education
APPENDIX A: GLOSSARY

48

Employment consistency CONS_EMP

Consistent employment, or whether the respondent was employed 91.67 percent of the time, from

completion of highest degree until June 1992.

Consistently employed

Not consistently employed

Family income, 1991 Y4601C

Total household income, before income taxes, in 1991 (in 1991 dollars).

Family socioeconomic status, 1980 PBYSES

Percentile ranking of respondent's base year socioeconomic status. Socioeconomic status was

based on father's occupation, father's education, mother's education, family income, and material

possessions of the household.

Gender SEX

Male

Female

Gender dominance of major field of study, highest degree or certificate PGM_GNDR

Dominant gender associated with a student's major field of study for the highest degree or

certificate received. A program was male or female dominated if 65 percent or more of the

awards were made to males or females, respectively. A program was gender-neutral if neither

men nor women comprised 65 percent of the award recipients.

Male Sixty-five percent or more of the graduates in a major field of study were male.

Female Sixty-five percent or more of the graduates in a major field of study were

female.

Gender-neutral Neither males nor females comprise 65 percent of the graduates in a major field

of study.

The following were determined to be male dominated certificate and associate's degree programs:

Agribusiness, production

Agriculture, animal, plant science

Air transportation

Automobile, air mechanics
APPENDIX A: GLOSSARY

49

Chemical engineering

Civil, ocean engineering

Communication technology

Construction, industrial art

Drama, speech

Electrical, communication engineer

Electronic mechanics and repairs

Engineering, science technologies

Environmental science

Film arts

Fine art, art history

Forestry, forest production

Integrated, general science

Mechanical engineering

Music

Natural resource conservation

Other engineering

Other mechanics

Other transportation

Precision production

Protective service

The following were determined to be female dominated certificate and associate's degree

programs:

Accounting

Allied health, general

Architect, environmental design

Area studies

Business administration, management

Childcare, guidance

Clinical health sciences

Community, mental health

Cosmetology

Data processing

Dental, medical technician

Dentistry

Early childhood education

Elementary education

English, American literature

Finance

Health, hospital administration

Home economics, other

Law

Letters

Liberal studies

Library, archival science

Marketing, distribution

Medicine

Nursing

Nutrition, food science

Other business support

Other consumer services

Other education

Other ethnic studies

Other health sciences

Paralegal, pre-law

Physical, health education

Practical nursing

Psychology

Public health

Secondary, junior high education

Secretarial, clerical

Special education

Speech pathology, audiology

Textiles, fashion

Veterinary medicine

Vocational home economics

Writing, creative and technical

The following were determined to be gender-neutral certificate and associate's degree programs:

American, civil studies

Anthropology, archaeology

Basic, personal skills

Biochemistry, biophysics

Biopsychology

Botany

Chemistry

Communications

Computer programming, information science

Economics

Foreign languages
APPENDIX A: GLOSSARY

50

Geography

Geology, earth science

Graphic design, printing

History

Interdisciplinary studies

International relations

Journalism, broadcasting

Mathematics

Operations research

Other biology sciences

Other physical sciences

Philosophy

Physics

Political science

Public administration

Recreation, sports

Religious studies

Social work

Sociology, demography, criminology

Statistics, biostatistics

Theology

Zoology

The following were determined to be male dominated bachelor’s and post baccalaureate

programs:

Agribusiness, production

Agriculture, animal, plant science

Air transportation

Automobile, air mechanics

Chemical engineering

Civil, ocean engineering

Construction, industrial art

Economics

Electrical, communications engineer

Electronic mechanics and repair

Engineering, science technologies

Environmental science

Forestry, forest production

Geography

Geology, earth science

Law

Mechanical engineering

Natural resource conservation

Operations research

Other consumer services

Other engineering

Other mechanics

Other physical sciences

Other transportation

Philosophy

Physics

Theology

The following were determined to be female dominated bachelor’s and post baccalaureate

programs:

Allied health, general

Childcare, guidance

Clinical health sciences

Communications

Community, mental health

Dental, medical technician

Dentistry

Early childhood education

Elementary education

Fine art, art history

Foreign languages

Health, hospital administration

Home economics

Letters

Library, archival science

Nursing

Nutrition, food science

Other business support

Other education

Other health sciences

Physical, health education

Political science
APPENDIX A: GLOSSARY

51

Practical nursing

Psychology

Secondary, junior high education

Secretarial, clerical

Social work

Sociology, demography, criminology

Special education

Speech pathology, audiology

Textiles, fashion

Vocational home economics

The following were determined to be gender-neutral bachelor’s and post baccalaureate programs:

Accounting

American, civil studies

Anthropology, archaeology

Architect, environmental design

Area studies

Basic, personal skills

Biochemistry, biophysics

Biopsychology

Botany

Business administration, management

Chemistry

Communications technology

Computer programming

Computer, information science

Cosmetology

Data processing

Drama, speech

English, American literature

Film arts

Finance

Graphic design

Graphics, printing

History

Integrated, general science

Interdisciplinary studies

International relations

Journalism, broadcasting

Liberal studies

Marketing, distribution

Mathematics

Medicine

Music

Other biology sciences

Other ethnic studies

Paralegal, pre-law

Precision production

Protective services

Public administration

Public health

Recreation, sports

Religious studies

Statistics, biostatistics

Veterinary medicine

Writing, creative and technical

Zoology

Grade point average GPA

Respondent's grade point average in postsecondary education.

Highest degree the respondent received by June 1992 HIGH_DEG

No diploma/degree

GED/certificate

High school graduate

Certificate

Associate’s degree
APPENDIX A: GLOSSARY

52

Bachelor’s degree

Master’s degree

Professional degree

Doctoral degree

High school grades HSGRADES

High school grades on a 100 point scale, combined from 1980 survey, 1982 follow-up survey and

high school transcripts.

Mostly A’s Numerical average of 90-100.

About half A’s and half B’s Numerical average of 85-89.

Mostly B’s Numerical average of 80-84.

About half B’s and half C’s Numerical average of 75-79.

Mostly C’s Numerical average of 70-74.

About half C’s and half B’s Numerical average of 65-69.

Mostly D’s Numerical average of 60-64.

Mostly below D Numerical average below 60.

Marital status, June 1992 MARST92

Married Respondent was married or in a marriage-like relationship as of

June 1992.

No longer married Respondent was separated, divorced or widowed as of June 1992.

Never married Respondent was never married as of June 1992.

No degree, attending some postsecondary education, what degree attempted PSE_ATMT

Postsecondary degree attempted, but no degree obtained

No degree

Certificate

Associate’s degree

Bachelor’s degree

Master’s degree

Professional degree

Doctoral degree

Number of children, June 1992 Y4402

Number of children respondent has, living in or out of the household.
APPENDIX A: GLOSSARY

53

Number of months employed NUMMNTHS

Number of months the respondent was employed out of the number of months he or she was in

the labor force.

Number of months the respondent was enrolled in postsecondary education SCH_MNTH

The number of months a respondent was enrolled in postsecondary education between July 1982

and June 1992, degree or certificate completers.

Number of years in the labor force LABOR_YR

Number of years a respondent was eligible to be included in the labor force.

Percentile ranking of the change in starting and ending pay RANK_CHG

Percentile ranking of the respondent's change in annual earnings from the first full year of

employment after completion of highest level of education to the last full year reported. A

ranking was completed for each highest degree earned category. This variable was created for

consistent workers. 

Personal income, 1991 Y4301B9

Respondent’s annual earnings in 1991 (in 1991 dollars).

Postsecondary education experience, non-attainers SOME_PSE

For respondents with a high school diploma or GED as highest degree attained, whether they

were enrolled in any postsecondary education between July 1982 and June 1992.

Enrolled in postsecondary education

Did not enroll in postsecondary education

Race/ethnicity RACE4
APPENDIX A: GLOSSARY

54

American Indian/Alaskan Native A person having origins in any of the original peoples of North

America and who maintains cultural identification through

tribal affiliation or community recognition.

Asian/Pacific Islander A person having origins in any of the Asian or Pacific Islander

original peoples of the Far East, Southeast Asia, the Indian

Subcontinent, or Pacific Islands. This included people from

China, Japan, Korea, the Philippine Islands, Samoa, India and

Vietnam.

Black, non-Hispanic A person having origins in any of the black racial groups of

Africa, and not of Hispanic origin.

Hispanic A person of Mexican, Puerto Rican, Cuban, Central or South

American, or other Spanish culture or origin, regardless of

race.

White, non-Hispanic A person having origins in any of the original peoples of

Europe, North Africa, or the Middle East (except those of

Hispanic origin).
APPENDIX A: GLOSSARY

55

Worked while attending school SCH_WRK

The percent of months a respondent was enrolled in postsecondary education and worked.

0-33 percent The respondent worked between zero and 33 percent of the time attended

postsecondary education.

34-66 percent The respondent worked between 34 and 66 percent of the time attended

postsecondary education.

67-100 percent The respondent worked between 67 and 100 percent of the time attended

postsecondary education.
56

APPENDIX B: TECHNICAL NOTES

The High School and Beyond Fourth Follow-up

The High School and Beyond (HS&B) survey began in the spring of 1980 with the collection

of base year questionnaire and test data on over 58,000 high school seniors and sophomores. The

first follow-up survey was conducted in the spring of 1982, the second follow-up in the spring of

1984, the third follow-up in the spring of 1986, and the fourth follow-up in the spring of 1992.

The HS&B Fourth Follow-up Survey was the fifth wave of the longitudinal study, but unlike

previous rounds, the fourth follow-up focused exclusively on the sophomore class. The Fourth

Follow-up included two components: a respondent survey which sampled 14,825 members of the

1980 sophomore cohort, and a transcript study based on the 9,064 sophomore cohort members who

reported postsecondary attendance. The goals of the fourth follow-up were to obtain information

on issues of access to and choice of undergraduate and graduate educational institutions, persistence

in fulfilling educational goals and progress through the curriculum, rates of graduation and of other

educational outcomes, and labor market outcomes in relation to level of education obtained and labor

market experiences.

Sample design

In 1980, the base year, students were selected using a two-stage, stratified probability sample

design with schools as the first-stage units and students within schools as the second-stage units.38

The total number of schools selected for the sample was 1,122, from a frame of 24,725 schools with

grades 10 or 12 or both. Within each stratum, schools were selected with probabilities proportional

to the estimated enrollment in their 10th and 12th grades. Within each school, 36 seniors and 36

sophomores were randomly selected. In those schools with fewer than 36 seniors or 36 sophomores,

all eligible students were drawn in the sample.

The first follow-up sophomore and senior cohort samples were based on the HS&B base year

samples, retaining the essential features of a stratified multi-stage design (for further details see

 

38For further details on the base year sample design see M. Frankel, L. Kohnke, D. Buonanno, & R. Tourangeau. High

School and Beyond Sample Design Report (Chicago: National Opinion Research Center, 1981).
APPENDIX B: TECHNICAL NOTES

57

Tourangeau et al., 1983).39 Subsequent to the first follow-up survey, high school transcripts were

sought for a probability subsample of nearly 18,500 members of the 1980 sophomore cohort. The

subsampling plan for the Transcript Study emphasized the retention of members of subgroups of

special relevance for education policy analysis. Compared to the base year and first follow-up

surveys, the Transcript Study sample design further increased the over-representation of racial and

ethnic minorities (especially those with above average HS&B achievement test scores), students who

attended private high schools, school dropouts, transfers and early graduates, and students whose

parents participated in the base year Parent's Survey on financing postsecondary education.

The samples of the 1980 sophomore cohort for the second and third follow-up surveys were

based upon the transcript study design. A total of 14,825 cases were selected from among the 18,500

retained for the transcript study. As was the case for the transcript sample, the sophomore cohort

second and third follow-up samples included disproportionate numbers of sample members from

policy-relevant subpopulations (e.g., racial and ethnic minorities, students from private high schools,

high school dropouts, students who planned to pursue some type of postsecondary schooling, and

so on).40 The members of the senior cohort selected into the second follow-up sample consisted

exactly of those selected into the first follow-up sample. The third follow-up was the last one

conducted for the senior cohort.

The fourth follow-up was composed solely of members from the sophomore cohort. The

members of the sophomore cohort selected into the fourth follow-up sample consisted exactly of

those selected into the second and third follow-up sample. For any student who ever enrolled in

postsecondary education, complete transcript information was requested from the institutions

indicated by the student.

Sample weights

The general purpose of weighting was to compensate for the unequal probability of selection

into the sample, and to adjust for respondent nonresponse to the survey. The weights were based on

the inverse of the selection probabilities at each stage of the sample selection process and on

nonresponse adjustment factors computed within weighting cells. The fourth follow-up had two

major components, the collection of survey data and the collection of postsecondary transcript data.

Nonresponse occurred during both of these data collection phases. Weights were computed to

 

39R. Tourangeau, H. McWilliams, C. Jones, M. Frankel, & F. O'Brien. High School and Beyond First Follow-Up

(1982) Sample Design Report (Chicago: National Opinion Research Center, 1983).

40C. Jones & B. D. Spencer. High School and Beyond Second Follow-Up (1984) Sample Design Report (Chicago:

National Opinion Research Center 1985), tables 2.4-1 through 2.4-4.
APPENDIX B: TECHNICAL NOTES

58

account for nonresponse during either phase. For the survey data, two weights were computed. The

first weight (FU4WT) was computed for all fourth follow-up respondents. The second weight

(PANEL5WT) was computed for all fourth follow-up respondents who also participated in the base

year and first, second and third follow-up surveys. For more information about the design and

implementation of the survey weights, see the High School and Beyond Fourth Follow-up

Methodology Report.41

Accuracy of Estimates

The estimates in this report were derived from samples and were subject to two broad classes

of error--sampling and nonsampling error. Sampling errors occurred because the data were collected

from a sample of a population rather than from the entire population. Estimates based on a sample

differ somewhat from the values that would have been obtained from a universe survey using the

same instruments, instructions, and procedures. Nonsampling errors come from a variety of sources

and affect universe surveys as well as sample surveys. Examples of sources of nonsampling error

include design, reporting, and processing errors and errors due to nonresponse. The effects of

nonsampling errors are more difficult to evaluate than those resulting from sampling variability. As

much as possible, procedures were built into surveys in order to minimize nonsampling errors.

The standard error is a measure of the variability due to sampling when estimating a

parameter. It indicates how much variance there is in the population of possible estimates of a

parameter for a given sample size. Standard errors can be used as a measure of the precision

expected from a particular sample. The probability that a complete census parameter would differ

from the sample estimate by less than the standard error is about 68 out of 100. The chances that the

difference would be less than 1.65 times the standard error are about 90 out of 100; that the

difference would be less than 1.96 times the standard error, about 95 out of 100. Table B2 displays

standard errors for table B1.

 

41D. Zahs, S. Pedlow, M. Morrissey, P. Marnell, & B. Nichols. The High School and Beyond Fourth Follow-Up

Methodology Report (Washington, D.C.: U.S. Department of Education, National Center for Education Statistics,

1994), section 3.
APPENDIX B: TECHNICAL NOTES

59

Table B1--Percentage distribution of 1980 high school sophomore women and men according to work

consistency1, by selected characteristics

Men Women

Inconsistent Consistent Inconsistent Consistent

workers workers workers workers

 Total 67.2 32.8 54.3 45.7

Family socioeconomic status, 1980

 Lowest third 74.5 25.5 58.4 41.6

 Middle third 62.6 37.4 49.5 50.5

 Highest third 61.4 38.6 54.6 45.4

Race/ethnicity

 American Indian/Alaskan Native 73.2 26.8 67.1 32.9

 Asian/Pacific Islander 60.0 40.0 63.3 36.7

 Black, non-Hispanic 78.5 21.5 67.0 33.0

 White, non-Hispanic 64.6 35.4 51.6 48.4

 Hispanic 73.9 26.1 56.0 44.0

Total household income before taxes, 1991

 Less than $10,000 82.7 17.3 77.1 22.9

 $10,000-19,999 80.8 19.2 69.0 31.1

 $20,000-29,999 67.2 32.8 53.4 46.6

 $30,000-39,999 66.4 33.6 45.5 54.5

 $40,000-49,999 54.4 45.6 43.3 56.7

 $50,000 or more 53.6 46.4 42.7 57.3

Personal annual earnings, 1991

 Less than $10,000 88.2 11.8 82.2 17.8

 $10,000-19,999 61.6 38.4 58.2 41.8

 $20,000-29,999 46.0 54.0 47.9 52.1

 $30,000-39,999 48.8 51.2 41.6 58.4

 $40,000-49,999 39.0 61.0 37.5 62.5

 $50,000 or more 58.9 41.1 40.8 59.2

Grades in high school2

 90-100 63.3 36.7 60.8 39.2

 80-89 60.7 39.3 49.1 50.9

 Less than 80 72.1 27.9 56.1 43.9

Marital status, June 1992

 Married 66.7 33.3 45.9 54.1

 Never married 64.0 36.0 61.4 38.6

 No longer married 73.7 26.3 51.1 48.9

Number of children, June 1992

 None 54.9 45.1 56.4 43.6

 One 64.7 35.3 51.3 48.7

 Two or more 82.9 17.1 50.3 49.7
APPENDIX B: TECHNICAL NOTES

60

Table B1--Percentage distribution of 1980 high school sophomore women and men according to work

consistency1, by selected characteristics--Continued

Men Women

Inconsistent Consistent Inconsistent Consistent

workers workers workers workers

Highest degree the respondent received

 No diploma/degree 91.5 8.5 63.5 36.5

 GED/Certificate 89.8 10.2 63.6 36.4

 High school diploma 70.0 30.0 52.3 47.7

 Certificate 61.9 38.1 53.2 46.8

 Associate’s degree 59.1 40.9 49.1 50.9

 Bachelor’s degree 50.4 49.6 50.1 49.9

 Graduate degree 88.2 11.8 84.7 15.3

Enrolled in any postsecondary education, non-attainers

 No postsecondary education 76.6 23.4 53.6 46.4

 Some postsecondary education 69.6 30.4 57.8 42.2

Degree/certificate attempted, non-attainers

 None 56.8 43.2 68.4 31.6

 Certificate 73.2 26.8 53.7 46.3

 Associate’s degree 64.4 35.6 51.2 48.8

 Bachelor’s degree 75.3 24.7 61.0 39.1

 Graduate degree -- -- -- --

Age received highest degree, degree/certificate attainers

 Less than 24 50.5 49.5 45.1 54.9

 24 or older 94.8 5.2 90.4 9.6

Gender dominance of major field of study, highest degree/certificate3

 Male 42.4 57.6 48.8 51.2

 Female 54.7 45.3 47.9 52.1

 Gender neutral 52.7 47.3 49.7 50.3

Continuously enrolled in postsecondary education, degree/certificate attainers

 Continuously enrolled 58.2 41.9 53.7 46.4

 Not continuously enrolled 39.9 60.1 -- --

Undergraduate grade point average, postsecondary degree/certificate attainers

 Less than 2.50 67.4 32.6 55.5 44.5

 2.50-3.50 58.0 42.0 55.4 44.6

 Greater than 3.50 62.0 38.0 51.4 48.6

Number of months enrolled in postsecondary education, degree/certificate attainers

 Less than 24 70.4 29.6 54.9 45.1

 24 or more 67.1 32.9 61.3 38.7
APPENDIX B: TECHNICAL NOTES

61

Table B1--Percentage distribution of 1980 high school sophomore women and men according to work

consistency1, by selected characteristics--Continued

Men Women

Inconsistent Consistent Inconsistent Consistent

workers workers workers workers

Percent of months working while enrolled, degree/certificate attainers

 None 82.2 17.8 79.4 20.6

 1-33% 69.2 30.8 68.7 31.3

 34-66% 71.6 28.4 67.8 32.2

 67-100% 50.9 49.1 43.8 56.2

--Sample size is too small for a reliable estimate.

1Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

2On a 100 point scale.

3A program is gender dominant if 65 percent or more of the graduates were of the same sex.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: Sophomore

Cohort 1980-1992 (HS&B:92), Data Analysis System.
APPENDIX B: TECHNICAL NOTES

62

Table B2--Standard errors for Table B1: Percentage distribution of 1980 high school sophomore women and

men according to work consistency1, by selected characteristics

Men Women

Inconsistent Consistent Inconsistent Consistent

workers workers workers workers

 Total 0.83 0.83 0.93 0.93

Family socioeconomic status, 1980

 Lowest third 1.33 1.33 1.81 1.81

 Middle third 1.33 1.33 1.65 1.65

 Highest third 1.51 1.51 1.53 1.53

Race/ethnicity

 American Indian/Alaskan Native 6.40 6.40 5.72 5.72

 Asian/Pacific Islander 4.09 4.09 4.95 4.95

 Black, non-Hispanic 1.98 1.98 2.74 2.74

 White, non-Hispanic 0.98 0.98 1.08 1.08

 Hispanic 2.52 2.52 3.29 3.29

Total household income before taxes, 1991

 Less than $10,000 1.73 1.73 2.77 2.77

 $10,000-19,999 1.86 1.86 2.39 2.39

 $20,000-29,999 2.02 2.02 1.97 1.97

 $30,000-39,999 2.00 2.00 2.26 2.26

 $40,000-49,999 2.38 2.38 2.69 2.69

 $50,000 or more 1.97 1.97 2.22 2.22

Personal annual earnings in 1991

 Less than $10,000 1.59 1.59 2.57 2.57

 $10,000-19,999 1.60 1.60 1.91 1.91

 $20,000-29,999 1.74 1.74 1.63 1.63

 $30,000-39,999 2.87 2.87 2.19 2.19

 $40,000-49,999 4.95 4.95 3.74 3.74

 $50,000 or more 7.79 7.79 4.41 4.41

Grades in high school2

 90-100 3.31 3.31 4.78 4.78

 80-89 1.40 1.40 1.62 1.62

 Less than 80 1.07 1.07 1.17 1.17

Marital status, June 1992

 Married 1.08 1.08 1.36 1.36

 No longer married 2.34 2.34 3.45 3.45

 Never married 1.55 1.55 1.36 1.36

Number of children, June 1992

 None 1.35 1.35 1.28 1.28

 One 1.72 1.72 2.21 2.21

 Two or more 1.14 1.14 1.96 1.96
APPENDIX B: TECHNICAL NOTES

63

Table B2--Standard errors for Table B1: Percentage distribution of 1980 high school sophomore women and

men according to work consistency1, by selected characteristics--Continued

Men Women

Inconsistent Consistent Inconsistent Consistent

workers workers workers workers

Highest degree the respondent received

 No diploma/degree 1.80 1.80 3.36 3.36

 GED/Certificate 3.07 3.07 4.65 4.65

 High school diploma 1.25 1.25 1.35 1.35

 Certificate 2.47 2.47 3.13 3.13

 Associate’s degree 2.75 2.75 3.59 3.59

 Bachelor’s degree 1.91 1.91 1.86 1.86

 Graduate degree 2.88 2.88 3.53 3.53

Enrolled in any postsecondary education, non-attainers

 No postsecondary education 1.24 1.24 1.50 1.50

 Some postsecondary education 1.95 1.95 2.07 2.07

Degree/certificate attempted, non-attainers

 None 6.66 6.66 4.91 4.91

 Certificate 5.63 5.63 6.96 6.96

 Associate’s degree 3.42 3.42 3.84 3.84

 Bachelor’s degree 2.66 2.66 3.13 3.13

 Graduate degree -- -- -- --

Age received highest degree, degree/certificate attainers

 Less than 24 1.41 1.41 1.66 1.66

 24 or older 1.39 1.39 2.13 2.13

Gender dominance of major field of study, highest degree/certificate3

 Male 5.64 5.64 2.73 2.73

 Female 1.76 1.76 3.50 3.50

 Gender neutral 2.68 2.68 2.61 2.61

Continuously enrolled in postsecondary education, degree/certificate attainers

 Continuously enrolled 1.25 1.25 1.44 1.44

 Not continuously enrolled 9.07 9.07 -- --

Undergraduate grade point average, postsecondary degree/certificate attainers

 Less than 2.50 1.63 1.63 1.91 1.91

 2.50-3.50 1.50 1.50 1.64 1.64

 Greater than 3.50 3.44 3.44 4.30 4.30
APPENDIX B: TECHNICAL NOTES

64

Table B2--Standard errors for Table B1: Percentage distribution of 1980 high school sophomore women and

men according to work consistency1, by selected characteristics—Continued

Men Women

Inconsistent Consistent Inconsistent Consistent

workers workers workers workers

Number of months enrolled in postsecondary education, degree/certificate attainers

 Less than 24 2.61 2.61 3.04 3.04

 24 or more 2.82 2.82 3.07 3.07

Percent of months working while enrolled, degree/certificate attainers

 None 2.01 2.01 2.74 2.74

 1-33% 2.52 2.52 2.73 2.73

 34-66% 2.92 2.92 3.38 3.38

 67-100% 1.46 1.46 1.55 1.55

--Sample size is too small for a reliable estimate.

1Consistent employment was defined as working 91.67 percent of the total months in the labor force after highest degree

attainment to the end of the data collection period.

2On a 100 point scale.

3A program is gender dominant if 65 percent or more of the graduates were of the same sex.

SOURCE: U.S. Department of Education, National Center for Education Statistics, High School & Beyond: Sophomore

Cohort 1980-1992 (HS&B:92), Data Analysis System.

Data Analysis System

The estimates presented in this report were produced using the National Center for Education

Statistics (NCES) Data Analysis System (DAS) for the HS&B Fourth Follow-up. The DAS software

makes it possible for users to specify and generate their own tables from the HS&B data. With the

DAS, users can recreate or expand upon the tables presented in this report. In addition to the table

estimates, the DAS calculates appropriate standard errors and weighted sample sizes for the

estimates.42 For example, table B2 presents the standard errors that correspond to table B1. If the

number of valid cases is too small to produce an estimate, the DAS prints the message "low-N"

instead of the estimate (converted to a"--" in the tables).

In addition to the tables, the DAS will also produce a correlation matrix of selected variables

that can be used in linear regression models, and the design effects (DEFT) for all the parameter

 

42The HS&B sample was not a simple random sample, and techniques for estimating standard errors that are

appropriate for simple random samples do not produce accurate standard errors for these data. The DAS takes into

account the complex sampling procedures and calculates standard errors that are appropriate for the variable. The

method for computing sampling errors used by the DAS involves approximating the estimator by the linear terms of a

Taylor series expansion. The procedure is typically referred to as the Taylor series method.
APPENDIX B: TECHNICAL NOTES

65

estimates in the correlation matrix. Since statistical procedures generally compute regression

coefficients based on simple random sample assumptions, the standard errors must be adjusted with

the design effects to take into account the complex sampling procedures used in the HS&B surveys.

For more information about the 1992 HS&B Fourth Follow-up DAS, visit the Web Site at

www.pedar-das.org, or contact:

Aurora D’Amico

Postsecondary and Education Outcomes Longitudinal Studies Program

555 New Jersey Ave., NW

Washington, D.C. 20208-5652

(202) 219-1365

Internet address: aurora_d’amico@ed.gov

Statistical Procedures

Two types of statistical procedures were employed in this report: testing differences between

means, and adjustment of means after controlling for covariation among a group of variables. Each

procedure is described below.

Differences between the means

The descriptive comparisons were tested in this report using Student's t statistics. Differences

between estimates are tested against the probability of a Type I error, or significance level. The

significance levels were determined by calculating Student's t values for the differences between each

pair of means or proportions and comparing these with published tables of significance levels for twotailed hypothesis testing.

Student’s t values may be computed, for comparisons using these tables’ estimates, with the

following formula:

P1 – P2

t = (1)

se1

2

 + se2

2

where P1 and P2 are the estimates to be compared, and se1 and se2 are their corresponding standard

errors. Note that this formula is only valid for independent estimates. When estimates were not

independent (for example, when comparing a total percentage with that for a subgroup that is

included in the total), a covariance term was added to the denominator of the t-test formula.
APPENDIX B: TECHNICAL NOTES

66

There are hazards in reporting statistical tests for each comparison. First, comparisons based

on large t statistics may appear to merit special attention. This can be misleading since the magnitude

of the t statistic is related not only to the observed differences in means or percentages, but also to

the number of students in the categories used for comparison. Hence, a small difference compared

across a large number of students will produce a large t statistic.

A second hazard in reporting statistical tests for each comparison is making multiple

comparisons among categories of an independent variable. For example, when making paired

comparisons among different levels of income, the probability of a Type I error for these

comparisons, when taken as a group, is larger than the probability for a singe comparison. When

more than one difference between groups of related characteristics or “families” is tested for statistical

significance, one must apply a standard that assures a level of significance for all of those comparisons

taken together.

Comparisons were made in this report only when p<=.05/k for a particular pairwise

comparison where that comparison was one of k tests within a family. This guarantees both that the

individual comparison would have p<=.05 and that when k comparisons were made within a family

of possible tests, the significance level of the comparison would sum to p<=.05.43

For example, in a comparison between males and females of average earnings, only one

comparison is possible (males versus females). In this family, k = 1, and the comparison can be

evaluated with Student’s t test. When students are divided into five race/ethnicity groups and all

possible comparisons are made, then k = 10 and the significance level of each test must be p<=.05/10,

or .005. The formula for calculating family size (k) is as follows:

k = [ j * ( j – 1 ) ] / 2 (2)

where j is the number of categories for the variable being tested. In the case of race/ethnicity, there

are five race/ethnicity groups (American Indian, Asian/Pacific Islander, black non-Hispanic, Hispanic,

and white non-Hispanic), so substituting 5 for j in equation 2 yields:

k = [ ( 5 ) ( 5 – 1 ) ] / 2 = 10 (3) 

Adjustment of means to control for background variation

 

43The standard that p<=.05/k for each comparison is more stringent than the criterion that the significance level of the

comparisons should sum to p<=.05. For tables showing the t statistic required to ensure that p<=.05/k for a particular

family size and degrees of freedom, see Olive Jean Dunn, “Multiple Comparison Among Means,” Journal of the

American Statistical Association. vol. 56, p. 52-64.
APPENDIX B: TECHNICAL NOTES

67

Tabular results are limited by sample size when attempting to control for additional factors

that may account for the variation observed between two variables. For example, when examining

the percentages of those who completed a degree, it is impossible to know to what extent the

observed variation is due to low-income status differences and to what extent it is due to differences

in other factors related to income, such as type of institution attended, parents’ education, and so on.

However, if a nested table were produced showing income within type of institution and within

parent’s education, the cell sizes would be too small to identify the patterns. When the sample size

becomes too small to support controls for another level of variation, one must use other methods to

take such variation into account.

To overcome this difficulty, multiple linear regression was used to obtain means that were

adjusted for covariation among a list of control variables.44 The dependent variable, earnings in the

highest category, was regressed on a set of descriptive variables such as gender, race-ethnicity, etc.

Substituting ones or zeros for the subgroup characteristic(s) of interest and the mean proportions for

the other variables results in an estimate of the adjusted proportion for the specified subgroup,

holding all other variables constant. For example, consider a hypothetical case in which two

variables, age and gender, are used to describe an outcome, Y (such as completing a degree). The

variables age and gender are recoded into a dummy variable representing age and a dummy variable

representing gender:

Age A

24 years or older 1

Under 24 years old 0

Gender G

Female 1

Male 0

The following regression equation is then estimated from the correlation matrix output from the DAS:

Y = a + ß1A + ß2G (4)

To estimate the adjusted mean for any subgroup evaluated at the mean of all other variables,

one substitutes the appropriate values for that subgroup’s dummy variables (1 or 0) and the mean for

 

44For more information about regression, including the weighted least squared (WLS) regression used here, see M. S.

Lewis-Beck, Applied Regression, vol. 22 (Beverly Hills, CA: Sage Publications, Inc., 1980) and W. D. Berry and S.

Feldman, Multiple Regression in Practice, vol. 50 (Beverly Hills, CA: Sage Publications, Inc. 1987).
APPENDIX B: TECHNICAL NOTES

68

the dummy variables representing all other subgroups. For example, suppose Y represents earning

a degree, and is being described by age (A) and gender (G), coded as shown above, with means as

follows:

Variable Mean

A 0.355

G 0.521

Next, suppose the regression equation results in:

Y = 0.15 + (0.17)A + (0.01)G (5)

To estimate the adjusted value for older students, one substitutes the appropriate parameter

estimates and variable values into equation 5.

Variable Parameter Value

a 0.15 --

A 0.17 1.000

G 0.01 0.521

This results in:

Y = 0.15 + (01.7)(1) + (0.01)(0.521) = 0.325 (6)

In this case, the adjusted mean for older students is 0.325 and represents the expected

outcome for older students who look like the average student across the other variables (in this

example, gender). In other words, the adjusted percentage of older students who attained a degree

is 32.5 percent (0.325 x 100 for conversion to a percentage).

It is relatively straightforward to produce a multivariate model using the DAS, since one of

the output options of the DAS is a correlation matrix, computed using pairwise missing values.45 This

matrix can be used by most statistical software packages as the input data to produce least-squares

regression estimates of the parameters. That was the general approach used for this report, with an

additional adjustment to incorporate the complex sample design into the statistical significance tests

 

45Although the DAS simplifies the process of making regression models, it also limits the range of models. Analysts

who wish to use other than pairwise treatment of missing values to estimate probit/logit models (which are the most

appropriate for models with categorical dependent variables) can apply for a restricted data license from NCES. For

more information on these alternative model specifications see John. H. Aldrich and Forrest D. Nelson “Linear

 Quantitative Applications in the Social Sciences, vol. 45. (Beverly Hills, CA:
APPENDIX B: TECHNICAL NOTES

69

of the parameter estimates (described below). For tabular presentation, parameter estimates and

standard errors were multiplied by 100 to match the scale used for reporting unadjusted and adjusted

percentages.

Most statistical software packages assume simple random sampling when computing standard

errors of parameter estimates. Because of the complex sampling design used for HS&B, this

assumption is incorrect. A better approximation of their standard errors is to multiply each standard

error by the average design effect associated with the independent variable (DEFT),46 where the

DEFT is the ratio of the true standard error to the standard error computed under the assumption of

simple random sampling. It is calculated by the DAS and produced with the correlation matrix.

 

Sage University Press, 1984).

46The adjustment procedure and its limitations are described in C. J. Skinner and T. M. F. Smith (eds.). Analysis of

Complex Surveys. (New York: John Wiley & Sons, 1989).
70

BIBLIOGRAPHY

Adelman, Clifford. Lessons of a Generation: Education and Work in the Lives of the High

School Class of 1972. (San Francisco: Jossey-Bass, 1994).

Aldrich, John. H. and Nelson, Forrest. D. Linear Probability, Logit and Probit Models, vol. 45

(Beverly Hills, CA: Sage Publications, Inc., 1984).

Berry, W. D. and Feldman, S. Multiple Regression in Practice, vol. 50 (Beverly Hills, CA: Sage

Publications, Inc., 1987).

Bloom, David C. and Brender, Adi. “Labor and the Emerging World Economy,” Population

Bulletin. (1993).

Deckard, B. The Women’s Movement: Political, Socioeconomic and Psychological Issues. 

(New York: Harper & Row, 1983).

Dunn, Olive Jean. “Multiple Comparison Among Means,” Journal of the American Statistical

Association. vol. 56, pp. 52-64.

Frankel, M., Kohnke, L., Buonanno, D. and Tourangeau, R. High School and Beyond Sample

Design Report (Chicago: National Opinion Research Center, 1981).

Hudson Institute. Workforce 2000, Work and Workers for the 21st Century. (Indianapolis:

author, 1987).

Jacobs, Jerry. “Long Term Trends in Occupational Segregation by Sex,” American Journal of

Sociology. vol. 95, (1989), pp. 160-173.

Jacobs, Jerry. Revolving Doors: Sex Segregation and Women’s Careers. (Stanford, CT:

Stanford University Press, 1989).

Jacobson, Joyce P. and Levin, Laurence M. “Effects of Intermittent Labor Force Attachment on

Monthly Labor Review. vol. 118, n. 9, (Sept. 1995), pp. 4-19.

Jones, C. and Spencer, B. D. High School and Beyond Second Follow-Up (1984) Sample Design

Report (Chicago: National Opinion Research Center, 1985): tables 2.4-1 through 2.4-4.

Lewis-Beck, M. S. Applied Regression, vol. 22 (Beverly Hills, CA: Sage Publications, Inc.,

1980).
BIBLIOGRAPHY

71

Skinner, C. J. and Smith, T. M. F. (eds.). Analysis of Complex Surveys. (New York: John Wiley

& Sons, 1989).

Tourangeau, R., McWilliams, H., Jones, C., Frankel, M. and O'Brien, F. High School and

Beyond First Follow-Up (1982) Sample Design Report (Chicago: National Opinion

Research Center, 1983).

Treiman, D. J. and Hartmann, H. I. Women, Work and Wages. (Washington, D.C.: National

Academy Press, 1981).

U. S. Department of Education. Digest of Education Statistics, 1996. (Washington, D.C.:

National Center for Education Statistics, 1996).

U. S. Department of Commerce. Statistical Abstract of the United States, 1996. (Washington,

D.C.: Bureau of the Census, 1996).

U. S. Department of Labor. 1993 Handbook on Women Workers: Trends and Issues. 

(Washington, D.C.: Women’s Bureau, 1993).

U. S. Department of Labor. Civilian Labor Force, 1982, 1993, and 1994 and Projected 2005,

and Entrants and Leavers 1982 and Projected 1994-2005. (Washington, D.C.: Bureau of

Labor Statistics, 1997), www.stats.bls.gov/emptab03.htm.

U. S. Department of Labor. Employment Perspective: Women in the Labor Force. Report 860. 

(Washington, D.C.: Bureau of Labor Statistics, 1993).

U. S. Department of Labor. Facts on Working Women. Number 93-2. (Washington, D.C.:

Women’s Bureau, 1993).

Wootton, Barbara H. “Gender Differences in Occupational Employment,” Monthly Labor

Review. vol. 120. N. 4, (April 1997), p. 15-34

Zahs, D., Pedlow, S., Morrissey, M., Marnell, P., and Nichols, B. The High School and Beyond

Fourth Follow-Up Methodology Report. (Washington, D.C.: U.S. Department of

Education, National Center for Education Statistics, 1994).