Monthly Labor Review February 2005 3

The NLSY79 at 25

The National Longitudinal Survey

of Youth: 1979 cohort at 25

The 1979 cohort of the National Longitudinal Survey of Youth

has been a font of information for researchers of all stripes;

the Monthly Labor Review brings together the results of research

on topics ranging from employment, to attrition in the survey,

to data on education, to the children of survey respondents

Charles Pierret

Charles Pierret is

Director of National

Longitudinal Surveys,

Office of Employment

and Unemployment

Statistics, Bureau of

Labor Statistics.

E-mail:

pierret.charles@bls.gov

T

his issue of the Monthly Labor Review

celebrates the 25th anniversary of the

National Longitudinal Survey of Youth,

1979 Cohort (NLSY79). The National Longitudinal

Surveys (NLS) program, of which the NLSY79 is

the flagship survey, is a bit of an anomaly among

the Bureau of Labor Statistics many data collection efforts. None of the Bureau’s key economic

indicators relies on NLS data. Only a couple of

the more than one hundred press releases the

Bureau publishes each year involve data collected by the NLS program. It is doubtful that

financial markets ever will react strongly to the

release of NLS data. And unlike the current

employment statistics, the inflation statistics, or

the unemployment rate, measures from the

NLSY79 are not likely to be discussed in everyday

conversation or even in the business news.

Yet, the NLSY79 has been extremely influential.

Over the last 25 years, it has provided the data

for thousands of Ph.D. dissertations, working

papers, journal articles, and books that have

shaped theory and knowledge in disciplines such

as economics, sociology, education, psychology,

and health sciences. The survey’s primary constituency includes hundreds of researchers

within universities, think tanks, and government

agencies both in the United States and abroad.

Because of its quality, breadth, and thoroughness, the NLSY79 has become probably the most

analyzed longitudinal data set in the social

sciences. Almost every issue of leading labor

economics and demography journals contain at

least one article that uses NLSY79 data.

The main product of the NLS program, unlike

that of most other BLS programs, is the actual

microdata generated by the surveys. For each

respondent, researchers can access a record that

details his or her responses to every question in

the survey, along with summary and supporting

information. Of course, this record is stripped of

all information that could identify the individual

respondent.1 With 20 rounds of data currently

available, the NLSY79 has become an enormous

data set, comprising more than 75,000 variables

for each respondent and requiring about 500

megabytes for its storage. The NLSY79 provides

researchers with data from a nationally representative sample of 12,686 individuals who have

participated in up to 21 hour-long interviews over

the last 25 years.2 These individuals were 14 to

22 years old when they were first surveyed in

1979; they are now in their forties. By observing

their lives over the 25-year period, researchers

can study the life course of a large sample of

American men and women born at the end of the

baby boom (1957 to 1964) as they navigate the

years between adolescence or young adulthood

and middle age.

Although the primary focus of the survey is

labor force behavior, the content of the survey is

considerably broader. The NLSY79 contains an

expansive set of questions ranging from childcare

costs to welfare receipt. For example, the survey
4 Monthly Labor Review February 2005

The NLSY79 at 25

includes detailed questions on educational attainment,

investment in training, income and assets, health conditions,

workplace injuries, insurance coverage, alcohol and substance

abuse, sexual activity, and marital and fertility histories.

This wide array of subject matter is certainly one key to the

survey’s broad utilization for academic research. Recognizing

that decisions made in one realm of life often affect and are

affected by events in other realms, the NLSY79 questionnaire

tries to get a comprehensive view of the lives of survey respondents. For example, health, childcare, and family constraints are important inputs to any labor market choices. By

collecting information in many domains, the NLSY79 gives

researchers the ability to simultaneously examine and control

for multiple correlates of complex phenomena.

The NLSY79 also benefits from the inclusion of information

collected outside of the main survey. For example, scores on

the Armed Services Vocational Aptitude Battery, a series of

10 tests measuring knowledge and skill in areas from

paragraph comprehension to electronics, are available for 94

percent of sample respondents. The Armed Forces Qualifying

Test score, a composite of the scores on four of these tests, is

one of the most popular variables in the survey, in that it can

be used to control for differences in cognitive development

prior to the start of the survey. Other ancillary data include a

survey of the secondary schools attended by NLSY79 respondents and detailed information from the respondents’

high school transcripts.

The breadth of the content in the survey is complemented

by the longitudinal design, a second key to the success of

the NLSY79. Not only can researchers correlate behavior in

multiple domains, but they can do so over long periods; for

example, they can investigate how family structure or educational experiences as a teenager affect employment decisions

in a person’s twenties and thirties. To facilitate this type of

analysis, much of the information in the NLSY79 is gathered

in event history format, in which dates are collected for the

beginning and ending of important life events. Data on

respondents’ labor market status, marital status, fertility, and

participation in government assistance programs such as

unemployment insurance and Aid to Families with Dependent

Children are all collected in this manner. The event history

format allows researchers to sequence key events so that a

first attempt at establishing causality can be made: only if A

precedes B can we postulate that A caused B.

But the real advantage of longitudinal data in terms of

studying causality is the existence of multiple observations

of the same person. A classic econometric problem is the

existence of unobserved personal characteristics that may be

correlated with both the dependent variable of interest and

an independent variable that is hypothesized to cause the

dependent variable. For example, consider the wage premium

 With cross-sectional data, one might compare the wages

of married men with those of unmarried men to calculate the

wage premium. Even after controlling for all observable

characteristics, though, one might suspect that there are

some differences that are not easily measurable (for example,

interpersonal skills or ambitiousness), but that might make

one both more likely to be married and more likely to earn

higher-than-average wages. With longitudinal data, the

standard technique is to analyze changes either directly, by

regressing the change in wages on the change in marital

status, or indirectly, by using a fixed-effects framework. In

this way, longitudinal data give us the ability to control for

individual effects by using multiple observations of the same

individual.

A final key to the NLSY79’s success is the high quality of

its data. The fundamental measure of quality in longitudinal

data is the retention rate—the percentage of initial respondents who respond in later rounds. Among social science

surveys, the NLSY79 is the undisputed leader in this regard.

In 1994, after 15 rounds of interviewing, more than 90 percent

of the survey’s eligible initial respondents were still being

interviewed.4 While attrition has picked up since that time,

more than 80 percent of living initial respondents were

interviewed in the 2002 survey.

Other dimensions of data quality are also high in the

NLSY79. Nonresponse to individual questions (either refusals

or “don’t know” responses) is quite low; only a handful of

questions have nonresponse rates above 1 percent. Because

of the longitudinal design of the survey, missing data can

often be recaptured in subsequent interviews. As Randall J.

Olsen explains, this approach can lead to effective sample

sizes larger than the response rate would imply.5

Given the size of the NLSY79 data set, using the data is

relatively easy.6 Researchers can download the entire data

set, along with extraction software to pull off particular

variables on their own computer, or they can use the

extraction software at the Web site and download smaller

data sets. Typically, researchers then use statistical software

such as SAS, SPSS, or STATA to process the data and perform

their analyses. This accessibility can be combined with the

richness of the data to study many topics across myriad

disciplines. The remaining articles in this issue of the Review

highlight the contributions of the NLSY79 to research, with

special emphasis on issues in the area of labor economics.

James A. Walker points out that the introduction of

nationally representative longitudinal microdata sets,

combined with ever-increasing computing power, has created

a revolution in social science research over the last few

decades.7 Previously, researchers had to rely on aggregate

statistics to grasp the workings of large complex systems.

Now they can study individual actors to build an under-

 associated with marriage among men. standing of social structure based upon those micro- 3
Monthly Labor Review February 2005 5

foundations. Before, analysts were forced to use small,

potentially unrepresentative samples to infer “normal”

behavior. Now, large surveys give them access to thousands

of individuals to study at very low cost. The combination of

massive amounts of data and growing computing power led

to the development of new statistical methods to exploit this

new source of information.

The first of these data sets, including the original NLS,

failed to fully exploit their longitudinal design. Instead, they

tended to ask questions as if the survey were cross sectional,

concentrating on the situation at the time of the interview.

The genius of the NLSY79 was that it attempted to capture

information about what was happening between interviews.

Now events of short duration—jobs, marriages, spells of

unemployment or public assistance, and the like—were

captured, and events across different domains could be

sequenced. Analysts now knew, for example, whether the job

change happened before or after the marriage, so issues of

causality could be addressed.

A second major improvement in the NLSY79 over previous

surveys using longitudinal data sets was the NLSY79’s strong

emphasis on reducing attrition and the effects of attrition on

the data. Even seemingly modest attrition can lead to sharp

declines in sample size. If participants who do not respond in

a particular round are never recontacted, and if 3 percent of

the remaining sample declines to participate in every round,

only slightly more than one-half of the initial sample will be

left after 20 rounds. The NLSY79’s retention rate has required

interviewing an average of 99 percent of the number of the

previous round’s respondents every round. As Olsen’s article

shows, this task involved increased efforts in terms of both

survey design and field operations. All respondents were

recontacted every round, regardless of how long it had been

since they were last interviewed. A surprising number were

reinterviewed after missing one or several rounds. In addition,

questions were written to recapture data that had not been

retrieved in interviews that had been missed. Respondents

were asked about events that had occurred since the last

interview, not those which were ongoing or had happened in

the past year.

Of course, even the highest-quality data are worthless if

they are unrelated to any valuable or interesting content.

The other six articles in this edition focus on particular

content areas. Kenneth I. Wolpin’s article on education data

in the NLSY79 details a large number of correlates of educational attainment that can be found in the survey’s database.8

 Not only do more educated individuals earn more

money, on average, but they work more hours, are less likely

to be unemployed or receive welfare payments, have better

health and less obesity, drink less, wait longer to have children

and have fewer of them, and, among women in the survey,

bear children who weigh more at birth and score higher on

cognitive tests. These findings hint at the richness of the

NLSY79 data, among which associations like these can be

explored in great depth.

In her article on early career job churning, Julie A. Yates

also touches on the richness of the education data in the

NLSY79.

9

 She shows that the concept of educational attainment is not at all static: people leave school and return,

sometimes getting new educational credentials, sometimes

not. This ever-present activity adds significantly to the level

of education in the United States. Indeed, only 11 percent of

those born between 1961 and 1964 had a college degree when

they first left school, but more than 25 percent had a degree

by their 35th birthday.

The main focus of Yates’s article, though, is the length of

time required after leaving school to acquire a job that will

last 1, 3, or 5 years. She finds that, by age 35, about 60 percent

of those who left school with a high school degree or greater

have worked at a job for at least 5 years. For high school

dropouts, however, the figure is only 36 percent. Interestingly, the route high school graduates take to acquire a job of

this duration is different from that taken by college graduates:

the median high school graduate takes 10.1 years and 5

shorter jobs before finding the job that will last 5 years,

whereas a college graduate requires only 3.5 years and 2 jobs.

Audrey Light also uses the work history data of the NLSY79

to study employment dynamics—specifically job mobility

and wage growth.10 She asks whether wage growth is greater

for those who stay in one job or those who change employers

frequently. The answer she arrives at depends at least partially on the reasons for mobility. Those who change jobs

voluntarily have wage growth of the same magnitude as those

who stay in jobs; those who change jobs involuntarily have

lower wage growth. Light admits that her analysis is “cursory.” Given the complexities underlying her question—

including the role of spells out of the labor force and their

interactions with education and gender—it is not surprising

that there is no simple answer to the question of how job

mobility affects wage growth. But by providing longitudinal

employment data along with comprehensive contextual data,

the NLSY79 will continue to play a key role in our growing

understanding of employment dynamics.

The NLSY79, states Robert W. Fairlie, has many features

that make it attractive for the study of self-employment:11 a

large, nationally representative sample; detailed financial

information; dara on family and educational background; and

measures of cognitive and psychological suitability. But the

survey’s strongest asset is its comprehensive work history,

which tracks transitions into and out of self-employment as

well as wage and salary employment. A great deal of selfemployment, at least among the young, is episodic, with

workers moving often between employment states. But as

workers age, their participation in self-employment grows and

becomes more stable. Only 5 percent of 22-year-old men are

self-employed; by age 42, 12 percent of men are self-employed.
6 Monthly Labor Review February 2005

The NLSY79 at 25

The NLSY79, because of its longitudinal design, is ideal for

investigating the dynamics of self-employment.

Since the 1950’s, the reigning paradigm of labor economics

has been human capital theory, in which workers invest in

productive skills in order to earn higher wages. The study of

human capital has divided skills acquisition into two components: education—in which general knowledge is acquired

largely prior to the start of one’s working career; and training—in which more specific, job-related skills are acquired,

often during one’s career. As Harley J. Frazis and James R.

Spletzer assert, empirical labor economics research on training has lagged behind research on education because research on training placed much greater demands on the

data.12 Again, the NLSY79 has been a key data set in this

literature, not only because it captures details about training,

but because it contains a complete history of employment

and thousands of other contextual variables.

The final article in this volume introduces an additional

dimension of the NLSY79. In a unique collaboration between

Federal Government agencies with complementary interests,

the NLS program, with the financial support of the National

Institute of Child Health and Human Development, has been

surveying the children of all women respondents to the

NLSY79 every 2 years since 1986. In their article, Lawrence L.

Wu and Jui-Chung Allen Li describe this survey, called the

Children of the NLSY79 .

13 Mothers are asked about pregnancy, prenatal care, and childcare, as well as the early

development of their children. Young children are given

cognitive and developmental assessments from the age of 4

to the age of 14. Children between ages 10 and 14 are

interviewed briefly about school and family life. Those older

than 15 years are given an interview that is similar to the

NLSY79 interview. What emerges is a unique data set with a

complete developmental history from birth and a comprehensive background of the mother, starting many years before

birth. Over time, the sample size has grown to rival that of the

NLSY79 itself. At its inception in 1986, the Children of the

NLSY79 survey comprised 4,971 children. In 2002, 7,467

children were assessed or interviewed, ranging in age from 2

to 30 years.

These articles only scratch the surface of what is available

in the NLSY79. Space limitations and the customary focus of

the Monthly Labor Review dictate a concentration on

employment, education, and training. But there is much more.

The NLS program tracks research using NLS data in the NLS

bibliography.14 Among other topics that have been the

subject of at least 100 papers using NLSY79 data are income

and earnings, marriage, maternal employment, adolescent

fertility, alcohol and substance use, childcare, family

structure, and government assistance programs. Smaller

numbers of papers have used NLSY79 data to examine topics

as diverse as job satisfaction, depression, migration, breastfeeding, parental leave, savings, and the involvement of

fathers in raising children. There truly are few topics in social

science that have not seen a contribution from NLSY79 data.

The success of the NLSY79 also led the Bureau of Labor

Statistics to introduce a new cohort to its own longitudinal

survey program. The NLSY97 is a survey of 8,984 youths who

were born between 1980 and 1984 and who were 12 to 17

years of age when first interviewed in 1997. While the basic

design of this survey is quite similar to that of the NLSY79,

several changes were introduced because of the NLS

program’s experience with earlier surveys. The most

important change was that NLSY 9 7 respondents were

younger when first interviewed than were those in the

NLSY79. It was felt that respondents should be observed

while still in school and still in the parental home, so that all

transitions to the world of work and to independent living

could be recorded. Also, starting with a younger sample

allowed the survey to collect more background on the

respondents’ introduction to the labor market. Information

on informal jobs such as babysitting and yard work was

collected for those as young as 12 years.15 In another attempt

to understand initial conditions, the NLSY97 interviewed a

parent for each respondent. These interviews focused on the

child’s family, health, and schooling background, as well as

the resources available to the child in the parental home. The

eighth annual interview of the NLSY97 is currently in the field,

and the respondents are now in their twenties. Already, a

number of articles using these data have been published on

a wide array of topics. It appears that the NLSY97 is poised to

emulate the success of the NLSY79.

Many people have contributed to the success of the

NLSY79 program, which is managed and funded by the Bureau

of Labor Statistics. Since the survey’s inception, the Center

for Human Resource Research at the Ohio State University

has directed survey operations under contract to the

Department of Labor. The Center is responsible for survey

development, data processing, and user support. In turn, the

actual interviewing has been performed under subcontract

by the National Opinion Research Center at the University of

Chicago. Designing, preparing, fielding, processing, and

disseminating a survey of the complexity of the NLSY7 9

requires many dedicated professionals. The success of the

survey is a tribute to their hard work and dedication.

The contributions of two groups are especially noteworthy.

Over the last 25 years, the field-interviewing staff at the

National Opinion Research Center has consistently exceeded

response rate targets by locating elusive respondents, convincing reluctant respondents to participate, and maintaining

high levels of data quality. Still, the most important group in

the success of the NLSY79 is the respondents. For 25 years,

the members of this group have endured thousands of

sometimes difficult and intrusive questions for little more than
Monthly Labor Review February 2005 7

the knowledge that they are involved in an important research

project. Their assistance has added immensely to academic

and policy research across a wide array of disciplines, helping

Notes

1 Under special arrangement, researchers can access certain

geographic information about respondents in order to link

environmental variables to the records of those respondents.

Personally identifying information, however, is never available to

those involved to increase their knowledge,elaborate new

theory, and develop new ways of understanding critical

issues in the social sciences.

researchers; it is protected by law through the Confidential

Information Protection and Statistical Efficiency Act.

2

 Much of the summary information that follows can be found on

the NLSY79 Web site at http://www.bls.gov/nls/nlsy79.htm or in the

NLSY79 User’s Guide (Bureau of Labor Statistics, 2001).

3 For a more thorough discussion of this issue, see Harry A. Krashinsky,

“Do Marital Status and Computer Usage Really Change the Wage

Structure?” Journal of Human Resources, summer 2004, pp. 774–91.

4 Two subsamples comprising roughly 3,000 respondents were

dropped from the sample in 1985 and 1991 to reduce costs. The

current sample size is 9,964 initial respondents, of which 346 were

deceased at the time of the 2002 survey.

5 Randall J. Olsen, “The problem of respondent attrition: survey

methodology is key,” this issue, pp. 63–70.

 

 7 James A. Walker, “Antecedents and predecessors of the NLSY79:

paving the course,” this issue, pp. 8–14.

8

 Kenneth I. Wolpin, “Education data in the NLSY79: a premiere

research tool,” this issue, pp. 15–20.

 9 Julie A. Yates, “The transition from school to work: education

and work experiences,” this issue, pp. 21–32.

10 Audrey Light, “Job mobility and wage growth: evidence from the

NLSY79,” this issue, pp. 33–39.

 11 Robert W. Fairlie, “Self-employment, entrepreneurship, and the

NLSY79,” this issue, pp. 40–47.

12 Harley J. Frazis and James R. Spletzer, “Worker training: what

we've learned from the NLSY79,” this issue, pp. 48–58.

13 Lawrence L. Wu and Jui-Chung Allen Li, “Children of the NLSY79:

a unique data resource,” this issue, pp. 59–62.

14 On the Internet at http://www.chrr.ohio-state.edu/nls-bib/.

15 See, for example, “Employment of Teenagers during the School

Year and Summer,” news release 04–217, on the Internet at http://

www.bls.gov/news.release/pdf/nlsyth.pdf.

 

6

 The data are available at no cost on the Internet at http://

www.bls.gov/nls/nlsy79.htm.