Monthly Labor Review February 2005 59

Children of the NLSY79

Children of the NLSY79:

a unique data resource

Lawrence L. Wu

and

Jui-Chung Allen Li

Lawrence L. Wu is

professor and chair,

and Jui-Chung Allen Li

is a Ph.D. candidate, in

the Department of

Sociology at New York

University.

E-mail:

lawrence.wu@nyu.edu

A

remarkable design aspect of the National Longitudinal Survey of Youth

1979 (NLSY79) is the availability of longitudinal data on all children born to women in

the original NLSY79 sample. The resulting data

from the Children of the NLSY79 provide a resource that is unique in many respects. Perhaps not surprisingly, these data have been

used by researchers across a wide range of disciplines, including child development, demography, economics, epidemiology, family studies, social policy, and sociology. Much of the

usefulness of these data stem from two key factors: they can be linked to the rich longitudinal data for the NLSY79 mothers, and the child

and young adult surveys are themselves longitudinal, covering a wide range of ages from

early childhood and adolescence through the

young adult years.

Sample design

As noted in other articles in this issue of the

Monthly Labor Review, the main respondents

in the NLSY79 are a nationally representative

sample of individuals aged 14–22 in 1979, with

surveys conducted annually through 1994 and

biennially since 1996. The child sample—consisting of offspring aged 14 or younger—was

begun in 1986, while the young adult sample—

consisting of offspring aged 15 or older—was

begun in 1994, with both the child and young

adult samples fielded biennially since initial

data collection.1 The survey instruments differ

substantially in the child and young adult surveys, as reviewed below. Because of the longitudinal design of the child and young adult

samples, offspring are interviewed initially in

the child sample, and then in the young adult

sample as they reach adolescence. Thus by design, sample sizes in the two samples will vary

from wave to wave, but as of the 2002 wave,

the child sample contained 11,340 children, and

the young adult sample contained 4,648 young

adults.

These data do not provide a nationally representative sample of children or young adults,

although they are appropriately regarded as

representative of the population of offspring

born to U.S. women who were aged 14–22 in

1979. Sample coverage of this latter population is excellent. However, the child and young

adult samples do not cover children of NLSY79

women who were concealed from the survey

(for example, children born to a NLSY79

woman but given up for adoption), children

who died before the initial 1986 children survey, or children in NLSY79 households who were

lost to the survey because they were not interviewed. The numbers of children in the latter

The survey provides a wealth of information on the education,

socioeconomic background, and cognitive, social, and emotional

development of children aged 14 and younger; and on the workforce

participation, education, marital, and fertility behaviors of young

adults aged 15 or older; the data have been heavily used by

researchers across a wide range of disciplines
60

Children of the NLSY79

Monthly Labor Review February 2005

category far outweigh the numbers in the other two categories, but, by current survey standards, sample attrition is

modest. In the 2002 wave, for example, roughly 84 percent

of NLSY79 women who had one or more births were successfully interviewed, compared with only 74 percent of women

who had no children.

Child assessment battery

A major interview component of the Children of the NLSY79

is the child assessment battery, which gauges the child’s

socio-emotional and cognitive development from birth to age

14 and provides measures of the home environment that are

thought to be important for child development. The validity

and reliability for these child assessments are high, with these

measures available for roughly 90 percent of surveyed children. (An exception is the Home Observation of the Environment-Short Form (HOME–SF) (see below) for infants under

age 3.) While these child assessment instruments were designed to be administered in a face-to-face interview, they

are nevertheless close in quality to similar diagnostic instruments used in the clinical settings of child assessments. The

battery covers multiple domains of a child’s developmental

trajectories, as well as the home environment for the child.

Home observation of the environment. The quality of a

child’s home environment is measured by the HOME–SF.

2

 This

instrument assesses the cognitive stimulation and emotional

support for children under the age of 15. Examples of questions include, “How many children’s books does your child

have?” and “If your child got so angry that he/she hit you,

what would you do?” with the specific questions administered varying according to age suitability. These data have

been widely analyzed, with the instrument adopted by other

surveys (for example, the child assessment module in the New

Immigrant Survey3).

Socio-emotional development. Data on child temperament

are obtained from mothers for children under age 3 and from

interviewers for children between ages 3 and 6. This temperament scale is intended to measure the child’s activity

level, affective attributes, attachment styles, compliance, sociability, and more generally, how a child usually acts. It was

adapted from Rothbart’s Infant Behavior Questionnaire and

Kagan’s compliance scale.4 The Behavior Problem Index

(BPI), completed by mothers with children from age 4 to age

14, has been widely used to gauge problem behaviors in children.5

 Researchers have typically distinguished between two

major BPI subscales: “externalizing behaviors” measuring

behaviors such as aggression, over-activity, and conflictual

relations with peers; and “internalizing behaviors” measuring frustration and negative affect toward oneself. Although

many other studies (usually small-scale studies) have collected BPI data, a unique aspect of the data from the Children

of the NLSY79 survey is its longitudinal nature, with BPI measures repeated every 2 years since 1986. Thus, for some children, BPI is measured at as many as six longitudinal data

points.

Cognitive development. The major instruments evaluating

the cognitive development for the NLSY79 children are three

subscales of the Peabody Individual Achievement Tests

(PIAT)—Mathematics, Reading Recognition, and Reading

Comprehension—for children between ages 5 to 14 and the

Peabody Picture Vocabulary Test – Revised (PPVT–R) for children. The Memory for Digit Span subscale of the widely

known Wechsler Intelligence Scale for Children – Revised

(WISC–R) is also included. These assessments of cognitive

ability are administered in all waves since 1986. Thus, as in

the case of BPI, repeated measures of cognitive ability are

available for individual children, which have proven of great

value to the research community. Less widely used measures of cognitive ability in these data include “body parts

recognition” (for children between ages 1 to 3 years; in the

1986 and 1988 waves), “memory for locations” (for children

between 8 months and 4 years of age; in the 1986 and 1988

waves), and the short-term memory of auditory stimuli

subscale from the McCarthy Scales of Children’s Abilities

(for children between ages 3 and 7 years; in the 1986 to 1994

waves). Taken together, these multiple-repeated measures

provide a comprehensive developmental portrait of early

cognitive ability.

Education, health, neighborhoods

Educational experiences are also assessed longitudinally, including the child’s participation in the Head Start program,

grade retention, number of the child’s friends that the parent

knows (a classic measure of “social capital” 6), attendance in

advanced classes, school activities, and basic school information. Researchers may request permission to view data on

school characteristics, which were gathered in a 1995/1996

school survey, and on neighborhood characteristics, which

are available from geocode information. These items, taken

collectively, provide an unusually comprehensive portrait of

the child’s early formal schooling experiences in ways that

exceed the educational data available for the original NLSY79

respondents.7

Various health-related questions include detailed perinatal conditions (for example, mother’s smoking and drug use

during pregnancy, her access to prenatal care, and child’s

birth weight), hospitalization history, general health conditions, specific illnesses, height, and weight. Many of these

variables are available longitudinally.
Monthly Labor Review February 2005 61

Young adult data

Yet another extremely important design decision in the offspring data is that the young adult survey instrument—administered when offspring are aged 15 or older—in many

ways mirrors the survey instrument given to their NLSY79

mothers. The young adult ages are similar to NLSY79 mothers

when they were first surveyed, and the period marks when

adolescents and young adults begin transitioning from school

to work. Thus, behavioral domains cover the continuing educational experiences of offspring, but also their employment

histories, income, and program participation. Health-related

behavioral items include detailed batteries on substance use

(cigarette, alcohol, marijuana, and other drugs/substance), but

also items related to both general and specific mental and

physical health conditions. Demographic data include information on exposure to sex education, pregnancy, and detailed

fertility and marital histories. Since 1994, a series of questions on computer use has been available, reflecting the

survey’s continuing sensitivity to various sources of social

change.8

Advantages of the Children of the NLSY79

Several design elements of the Children of the NLSY79 make

these data unique. For example, offspring data are available

in the Panel Study of Income Dynamics (PSID), which is also

a nationally representative longitudinal survey of respondents

in the United States. However, the PSID child supplement

consists of only two waves of data to-date; hence, the PSID

parent/child data consists of a long panel of data for parents

but only a short panel for children. By contrast, the National

Survey of Families and Households (NSFH), another national

probability survey, contains longitudinal data on both parents and offspring, but limits data on offspring to a single

focal child within a specific age range. In addition, the NSFH

contains only three waves of data, with interviews occurring

5 or more years apart. By contrast, the NLSY child and young

adult surveys are administered biennially, contain all children

born to a given mother, and provide a long panel of closelyspaced longitudinal data for both mothers and offspring.

As noted earlier, the major limitation of the NLSY79 data

has to do with how the sample is generated. The sample cannot be regarded as a nationally representative sample of any

cross-sectional population of children in the United States,

but is representative of the population of children whose

mothers were born between 1958 and 1965. Because children are added as they are born, the initial data in the child

sample overrepresented children born to the youngest mothers, who tended to be from disadvantaged socioeconomic

backgrounds. Children in the initial rounds of data were observed to do worse than other children of similar ages on a

variety of indicators for cognitive, physical, and socio-emotional developments. These disadvantages are likely due to

their disadvantaged social and economic circumstances.

However, with time, more children have been added to the

child sample as the NLSY79 women have completed their

childbearing; hence, what was problematic in the early history of the child sample has become much less so as the joint

mother-child age distribution has “normalized.” Similar issues hold for the young adult data. The research community

has been sensitive to these issues, and a variety of modeling

strategies can be employed to deal with them. 9

Retrospect and prospect

Although the majority of published refereed research papers

have been in journals specializing in the areas of the family

and child development, studies using these data have also

appeared in fields such as demography, economics, epidemiology, and sociology. (See table 1.) The use of these data by

researchers in child psychology, pediatrics, and psychiatry is

particularly noteworthy because, traditionally, these fields

have not relied on analyses of national probability samples,

but have rather focused heavily on smaller experimental and

clinical samples.

The topics examined with these data are very diverse.

Published studies to-date have examined the consequences

on children’s well-being and cognitive and socio-emotional

development of factors such as maternal employment, povJournal of Marriage and the Family ................ 1 31

Child Development ...................................... 2 13

Journal of Human Resources ........................ 3 12

Demography ............................................... 4 10

Pediatrics ................................................... 5 9

Social Forces .............................................. 5 9

Developmental Psychology ........................... 7 8

Journal of Family Issues ............................... 7 8

Perspectives on Sexual & Reproductive Health

 (previously, Family Planning Perspectives) .... 9 7

American Sociological Review ....................... 10 6

American Journal of Public Health ................. 11 4

Intelligence ................................................. 11 4

Journal of Health and Social Behavior ............ 11 4

Archives of Pediatric & Adolescent Medicine ... 14 3

Journal of Economic Literature ...................... 14 3

Journal of Family and Economic Issues .......... 14 3

Journal of Health Economics ......................... 14 3

NOTE: Journals that have only published less than three papers are not

included, but they include such flagship journals as American Journal of

Sociology, Journal of Political Economy, American Economic Review,

American Educational Research Journal, and Population and Development

Review.

 Number

of

articles

Table 1. Articles using data from the Children of the NLSY79

published in academic journals

Journal name Rank
62

Children of the NLSY79

Monthly Labor Review February 2005

erty and program participation (for example, the Temporary

Assistance for Needy Families (TANF) program and the Special Supplemental Nutrition Program for Women, Infants,

and Children (WIC)), parenting practices, and parental marital history. Similarly, pediatric researchers have used these

data to estimate the association of child obesity and television viewing and how parents deal with children during

mealtimes.1 0

Use of the young adult sample has increased over time as

offspring have aged into this sample. A bibliography maintained by the NLS lists 45 journal articles, book chapters, theses and dissertations, conference papers, and working papers

that have used the young adult data.11 As noted above, early

waves of the young adult data heavily overrepresented offspring born to very young mothers, but selection of offspring

on mother’s age has become far less problematic as offspring

born to older mothers have aged into the young adult sample.

As a consequence, research uses of the young adult data

should continue to gain momentum as more waves of data

become available and as parent/offspring characteristics become less skewed.

Notes

1

 Members of the Center for Human Resource Research (CHRR) and, in

particular, Frank Mott played a crucial role in developing and designing the

child and young adult surveys. Because plans to collect data on offspring

were not part of the original NLSY79 data design, external funding sources

were required to collect these data. As a consequence, the availability of

offspring data were dependent on the foresight of Frank Mott, who in the

early 1980s spearheaded efforts by staff at CHRR and NLS to secure external

support for collecting data on the Children of the NLSY79. It is also important

to recognize that at the time of initial data collection, many of the substantive issues, as well as statistical and methodological techniques appropriate

for these data, were in their infancy. In these and others ways, those who

envisioned these data in the early 1980s were well ahead of their time.

2

HOME–SF is a modification of the HOME inventory, see Bettye M.

Caldwell and Robert H. Bradley, Home Observation for Measurement of

the Environment (Little Rock, AR, University of Arkansas, Center for Child

Development and Education, 1984).

3

 For further information about the New Immigrant Survey, see http://

nis.princeton.edu.

4

 At the time of the first child survey in 1986, there was no existing

temperament scale appropriate for use in a survey setting. As a result, the

temperament scale developed and fielded by NLS investigators lacked a

national norm. Subsequent work has established the psychometric and

measurement properties of this scale. See Frank L. Mott, Paula C. Baker,

David E. Ball, Canada K. Keck, and Steven M. Lenhart, The NLSY Children

1992: Description and Evaluation (Columbus, OH, Ohio State University, Center for Human Resource Research, 1995).

5

 The BPI was developed by Nicholas Zill and James L. Peterson, Behavior Problems Index (Washington, DC, Child Trends Inc., 1986) by

adapting primarily the Achenbach Behavior Problems Checklist. See ThoResearchers can employ advanced statistical techniques

exploiting unique design elements in these data. For example,

researchers have often noted that siblings are more likely to

resemble one another on a variety of behavioral outcomes

than are two otherwise similar but unrelated individuals chosen randomly from the same population. Such resemblance,

it is argued, may reflect characteristics of siblings—how they

were raised, characteristics of their parents and home environment, and genetic influences—that are not captured by the

rich array of variables available in data such as the NLSY79.

To deal with this issue, researchers have increasingly used a

variety of statistical modeling techniques (for example, fixed

effect models) that rely on the availability of sibling data to

purge out the influence of hypothesized unobserved factors.

An innovative elaboration of this idea involves comparisons

of siblings, cousins, and unrelated individuals, a research design that is possible with the offspring data because both siblings and cousins can be identified. A similar idea relies on

the identification of half-siblings, both among the original

NLSY79 respondents and in the offspring data, which has been

used to examine certain models of genetic similarity.

mas M. Achenbach and C. S. Edelbrock, Manual for the Child Behavior

Checklist and Revised Child Behavior Profile (Burlington, VT, University of Vermont, Department of Psychology, 1983).

6

 See James S. Coleman, “Social Capital in the Creation of Human

Capital,” American Journal of Sociology 94, (The University of Chicago

Press, 1988), pp.S95–S120.

7

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

research tool,” Monthly Labor Review, February 2005, 15–20.

8

 Data on substance use, health conditions, sex education, and computer use are also available in the child sample. The fact that similar items

are present in both the child and young adult surveys permits investigators

to compare and combine data from the two samples to assess, for example,

issues of reliability and stability/change in these variables.

9

 See Mark R. Rosenzweig and Kenneth I. Wolpin, “Are There Increasing Returns to the Intergenerational Production of Human Capital? Maternal Schooling and Child Intellectual Achievement,” Journal of Human

Resources 29 (The University of Wisconsin Press, 1994), pp. 670–93.

10 See Laura K. Certain and Robert S. Kahn, “Prevalence, Correlates,

and Trajectories of Television Viewing Among Infants and Toddlers,” Pediatrics 109 (American Academy of Pediatrics, 2002), pp.634–42; Myles

S. Faith, Stanley Heshka, Kathleen L. Keller, Bettylou Sherry, Patty E.

Matz, Angelo Pietrobelli, and David B. Allison, “Maternal-Child Feeding

Patterns and Child Body Weight: Findings from a Population-Based

Sample,” Archives of Pediatric and Adolescent Medicine 157 (American

Medical Association, 2003), pp.926–32.

11 A searchable online bibliography of all sources that have used the NLS

data is on the Internet at http://www.nlsbibliography.org.