Manajemen | Fakultas Ekonomi Universitas Maritim Raja Ali Haji 536.full

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The Impact of Attrition on the

Children of the NLSY79

Alison Aughinbaugh

a b s t r a c t

This paper examines the impact of attrition among the women of the Na-tional Longitudinal Survey of Youth 1979 (NLSY79) and children in the NLSY79 Mother-Child Supplement (NLSY79-C). Attrition among the chil-dren is nonrandom with respect to mother’s marital status, grandfather’ s completed schooling, and family income. These differences that are re-lated to the probability of attrition do not appear to impact estimates of the effects of family income or maternal employment early in the child’s life on either PPVT or BPI standard scores. However, the women who are not interviewed in any child-supplement year and the children for whom supplemental information is never collected appear to be the most disadvantaged. The omission of these children from the NLSY79-C may impact estimates of family characteristics on child outcomes, but because there are relatively few such children, the effects of their omission are likely to be small.

I. Introduction

The National Longitudinal Survey of Youth 1979 (NLSY79) and its corresponding Mother-Child Supplement (NLSY79-C) are widely used to study the outcomes of children and the impact that children have on women’s economic and demographic decisions. As the children of the NLSY79-C age, these data can be used to study important intergenerational relationships regarding human capital

Alison Aughinbaugh is a research economist at the U.S. Bureau of Labor Statistics. The views ex-pressed are those of the author and do not reect the policies of the Bureau of Labor Statistics or the views other BLS staff members. The author thanks Tom Mroz, Mike Horrigan, Frank Mott, Chuck Pierret, Donna Rothstein, and anonymous referees for useful comments. The author takes responsibility for all errors. The data used in this article can be obtained beginning October 2004 through Septem-ber 2007] from Alison Aughinbaugh, 2 Massachusetts Ave. NE, Room 4945, Washington, DC 20212, aughinbaugh.alison@bls.gov.

[Submitted July 1999; accepted July 2003]

ISSN 022-166X; E-ISSN 1548-8004Ó2004 by the Board of Regents of the University of Wisconsin System

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investment and the impact of family background on child outcomes. However, non-random attrition may impact the data set’s ability to examine such questions.

The NLSY79 began in 1979 as a nationally representative sample of young men and women between the ages of 14 and 21 on December 31, 1978. Detailed annual information on fertility, marital transitions, employment, and income is available in this data set. Biennially, beginning in 1986, the mothers among the NLSY79 partici-pants were asked detailed questions about their children, and the children were given a battery of cognitive and behavioral assessments. It is this information that makes up the NLSY79-C. Because the NLSY79-C is made up of the children of the female respondents in the NLSY79, it is designed to be representative of the NLSY79 wom-en’s fertility up to the year of the last survey. By design, the NLSY79-C is not repre-sentative of a cross-section of children. Moreover, it is not reprerepre-sentative of all chil-dren born to women in the NLSY79 cohort because their fertility is not yet complete.1 In this study, I examine the effects of attrition on the NLSY79-C using methods employed by MaCurdy, Mroz, and Gritz (1998) and Fitzgerald, Gottschalk, and Mof-tt (1998) to study the effects of attrition on the NLSY79 and the Panel Study of Income Dynamics (PSID), respectively. The results in this paper show that over the years that the NLSY79-C is collected attrition among the women and children has a relatively small effect on the family background measures, such as women’s marital status, fertility, and family income, and on estimates of two important intergenera-tional relationships: (1) the effect of family income on child development and (2) the effect of maternal employment in the child’s rst year on child development.

Although only about 2 percent of the women in the NLSY79 attrite prior to 1986 and never return to the survey, the women who are not interviewed in 1986 or any later year are unlike those who are interviewed in at least one of the NLSY79-C years. The women who are not interviewed in any of the NLSY79-C years are more likely to have had an early birth or marriage. Additionally, the children for whom the supple-mental information was never collected tend to have mothers who experienced an early birth or marriage. Although attrition over the course of the NLSY79-C has little effect, attrition prior to the supplement’s beginning may have a larger impact.

In most respects, for the measures of family background considered here, the picture drawn when all child observations are considered is no different than the picture drawn when only the nonattritors are examined. Future attrition from the NLSY79-C, however, is more likely for children whose families had higher incomes during their rst three years and less likely for those children whose mothers had never married by the interview in which the child was rst assessed and whose grandfathers had completed more schooling. Despite these systematic differences in the probability of attrition, relationships between either family income and early child assessment scores or maternal employment and assessment scores are largely unaffected by the omission of the attritors.

This paper is organized as follows. In Section II, I present descriptive statistics to assess the patterns of attrition among women in the NLSY79 and the children in the NLSY79-C and to assess how the characteristics of the attritors impact family background, as measured by mother’s highest grade completed and family income,

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538 The Journal of Human Resources

and the children’s scores on developmental assessments. This is done by comparing the full sample with the sample of respondents who have never missed an interview. Section III examines how attrition affects estimates of the relationship between fam-ily characteristics and the children’s assessment scores. Lastly, Section IV summa-rizes and discusses the ndings.

II. Attrition Patterns

The analysis of the NLSY79 and NLSY79-C in this study is based on 4,926 women and their 9,460 children whose births are recorded through the 2000 interview.2 _{Analysis is done separately for the full sample, that is, all 4926} women and their children, and for the cross-sectional sample which omits the women in the Black and Hispanic oversamples and their children. The data are unweighted.3 Table 1 describes the attrition patterns for the women of the NLSY79 by present-ing the rates of attrition and rst-attrition for the full sample and the cross-section. Attrition has been relatively low among the women of the NLSY79, although it has increased over time. The attrition rates range from 3 percent to 4 percent in the early years of the survey and from 12 percent to 17 percent in the recent biennial survey-years with the patterns being quite similar for the full-sample of women and the cross-section. Until the most recent interview, initial attrition was greatest in the second year of the survey when nearly 4 percent of the full-sample and cross-sec-tional women attrited. In the subsequent years, rst attrition is generally between 1 percent and 2 percent until the 1996 interview. The patterns displayed in this table show the extent to which attrition has affected the sample of women in the NLSY79, but do not provide information on whether attrition has caused the sample to be nonrepresentative.

Table 2 compares all person-year observations of the women in the NLSY79 with the annual observations from only those women who have never missed an interview (continuous subsample) to assess whether attrition is nonrepresentative along se-lected characteristics that describe the women’s fertility decisions, marital status and economic status. Fitzgerald, Gottschalk, and Moftt (1998) point out that the appro-priate comparison is between the full sample and the nonattritors, not between the attritors and nonattritors where attrition may lead to bias in both samples.

Table 2 is organized into two panels. Panel A presents the statistics for the full sample, and Panel B the statistics for the cross-section. In each of the panels, umns 1-4 present the descriptive statistics for all person-year observations and Col-umns 5-8 for the person-year observations of women in the continuous subsample.

2. Because they have been dropped from the NLSY79, the samples used in this paper exclude women from the armed forces supplement and the supplement of economically disadvantaged whites and their children.

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Table 1

Attrition Rates for the NLSY79 Women

Attrition First Attrition

Full Cross- Full

Cross-Year Sample Section Sample Section

1980 0.038 0.039 0.038 0.039

1981 0.033 0.033 0.015 0.016

1982 0.039 0.037 0.014 0.011

1983 0.032 0.031 0.010 0.008

1984 0.041 0.043 0.015 0.016

1985 0.052 0.053 0.020 0.018

1986 0.070 0.068 0.024 0.022

1987 0.081 0.080 0.024 0.023

1988 0.090 0.091 0.028 0.029

1989 0.073 0.076 0.011 0.010

1990 0.089 0.088 0.019 0.018

1991 0.080 0.079 0.011 0.010

1992 0.082 0.081 0.014 0.015

1993 0.080 0.082 0.010 0.010

1994 0.093 0.096 0.015 0.013

1996 0.118 0.120 0.027 0.024

1998 0.130 0.131 0.030 0.028

2000 0.167 0.166 0.047 0.044

Number of observations 4,926 3,108

Notes: Attrition rates are dened as the number of noninterviews out of the women in the sample. Rates of rst attrition are dened as the number of women not interviewed in a given year out of the women who have continuously remained in the sample throughout that year.

The descriptive statistics are grouped based on the year of observation. In the rst and fth columns the observations across all years (1986, 1988, 1990, 1992, 1994, 1996, 1998, and 2000) are pooled, in the second and sixth columns the observations from 1986, 1988, and 1990 are pooled, in the third and seventh columns those obser-vations from 1992, 1994, and 1996 are pooled, and in the fourth and eight columns observations from 1998 and 2000 are pooled.

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Table 2a

Descriptive Statistics for Person-Year Observations, Women NLSY79: Full Sample

All Annual Observations Annual observations, Continuous Subsample

All 1986, 1992, 1998 All 1986, 1992, 1998

Child 1988, and 1994, and and Child 1988, and 1994, and and

Years 1990 1996 2000 Years 1990 1996 2000

Age

Mean 32 27 33 38 32 27 33 38

Median 32 27 33 38 32 27 33 38

10 percent 25 23 29 35 25 23 29 35

90 percent 39 31 37 41 39 31 37 41

Any children 0.70 0.60 0.75 0.78 0.70 0.60 0.75 0.79

Number of children

Mean 1.44 1.14 1.60 1.69 1.47 1.15 1.63 1.71

Median 1 1 2 2 1 1 2 2

10 percent 0 0 0 0 0 0 0 0

90 percent 3 3 3 3 3 3 3 3

Marital status*

Never married 0.26 0.36 0.23 0.17 0.26 0.36 0.23 0.18

Married 0.54 0.50 0.56 0.58 0.55 0.50 0.57 0.59

Separated 0.06 0.05 0.07 0.07 0.06 0.05 0.07 0.06

Divorced 0.12 0.09 0.13 0.16 0.12 0.08 0.13 0.16

Widowed 0.02 0.00 0.01 0.03 0.01 0.01 0.00 0.01

Family income*

Mean 29,790 23,277 34,607 32,970 30,153 23,697 34,475 33,599

Median 22,007 19,355 22,310 26,224 22,678 19,756 22,966 27,011

10 percent 5,437 5,139 5,577 6,002 5,790 5,323 6,063 6,603

90 percent 52,399 45,806 51,969 62,617 53,072 46,524 52,148 62,928

Poverty status* 0.19 0.21 0.18 0.15 0.18 0.21 0.17 0.14

Highest grade completed*

Mean 13 13 13 13 13 13 13 13

Median 12 12 12 12 12 12 12 12

10 percent 11 10 11 11 11 11 11 12

90 percent 16 16 16 16 16 16 16 16

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Table 2b

Descriptive Statistics for Person-Year Observations, Women NLSY79: Cross-Section

All Annual Observations Annual observations, Continuous Subsample

All 1986, 1992, 1998 All 1986, 1992, 1998

Years 1990 1996 2000 Years 1990 1996 2000

Age

Mean 32 27 33 38 32 27 33 38

Median 32 27 33 38 32 27 33 38

10 percent 25 23 29 35 25 23 29 35

90 percent 39 31 37 41 39 31 37 41

Any children 0.67 0.55 0.73 0.77 0.68 0.56 0.74 0.78

Number of children

Mean 1.33 1.01 1.49 1.60 1.37 1.03 1.52 1.63

Median 1 1 2 2 1 1 2 2

10 percent 0 0 0 0 0 0 0 0

90 percent 3 3 3 3 3 3 3 3

Marital status*

Never married 0.22 0.31 0.17 0.13 0.21 0.31 0.17 0.12

Married 0.61 0.55 0.64 0.66 0.62 0.55 0.65 0.67

Separated 0.05 0.04 0.05 0.05 0.04 0.04 0.05 0.04

Divorced 0.12 0.09 0.13 0.16 0.12 0.09 0.13 0.15

Widowed 0.00 0.00 0.01 0.00 0.01 0.01 0.00 0.01

Family income*

Mean 33,416 25,582 39,963 36,155 33,689 25,990 39,534 36,854

Median 24,913 21,774 25,744 29,841 25,543 22,305 26,247 30,612

10 percent 6,530 5,916 6,920 7,477 6,996 6,162 7,489 8,163

90 percent 55,701 48,387 55,363 65,541 56,055 49,257 55,433 65,660

Poverty status* 0.14 0.16 0.13 0.11 0.13 0.15 0.11 0.11

Highest grade completed*

Mean 13 13 13 13 13 13 13 14

Median 12 12 12 12 12 12 12 13

10 percent 11 11 12 12 12 11 12 12

90 percent 16 16 16 17 16 16 16 17

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Next, I describe the attrition patterns for the children of the NLSY79 women. The samples of children examined in this paper are limited to children born in 1994 or earlier so that the children will be old enough to have been assessed and to have had at least one chance to attrite after assessment. Because the children are no longer eligible for assessment upon turning 15, they are dropped from the samples at age 15.4

There are two difculties in examining the attrition patterns for the children. First, because children are being born into the sample as the survey continues causing the sample to change over time, the patterns must be described separately for groups of children based on their year of birth. Second, some of the children who are, by deni-tion, part of the sample have never been identied, much less assessed. For instance, there would be no information collected about a child born in 1991 whose mother attrited in 1989 and never returned to the survey. Using information on fertility through the 2000 interview for those women who are interviewed in that round, the expected number of missed births is approximately 150, with an upper bound of 330.5 Table 3 shows the fraction of children about whom supplemental information was collected (1) out of the children known to have been born by the start of the interview period and (2) out of the children whose mothers were interviewed. Because inter-viewers are instructed that interviewing the main youth is the highest priority, assess-ing a child generally accompanies the collection of his mother’s interview. Conse-quently, having a mother who is interviewed substantially increases the odds that information on the child is collected. There are few cases where the child assessment occurs, but the mother is not interviewed. Excluding the 2000 interview —at each interview, supplemental information is not collected for 10 to 20 percent of all known children, and is missing for between 5 and 10 percent of the children whose mothers are interviewed.6

Table 4 attempts to assess the effects of attrition in the child supplement since its beginning in 1986. This table compares the descriptive statistics for the sample of all child-year observations and the subsample of child-year observations for the chil-dren for whom supplemental information is collected in all eligible years (the conti-nuous subsample). This table is organized in the same way as Table 2. The statistics focus on the items that describe the child’s family background and the resources avail-able to the child, such as, mother’s marital status, mother’s highest grade completed, average family income during the child’s rst three years, and maternal employment during the child’s rst year, as well as, the child’s standard scores on the Peabody Pictorial Vocabulary Test (PPVT) and the Behavior Problems Index (BPI).

For the full sample (Table 4a) and the cross-section (Table 4b), the sample of all observation years and the continuous subsample are similar along the dimensions presented. Although children in the continuous samples score higher on the PPVT,

4. Beginning in 1994, a young adult interview was conducted for those children 15 and older. The adminis-tration of the young adult interview is not linked to the interview of the mother.

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Table 3

Fraction of Children Interviewed by Year, Out of all Known Children and Out of Children whose Mothers Were Interviewed. Children Born in 1994 or Earlier

1986 1988 1990 1992 1994 1996 1998 2000

Number of Mother Mother Mother Mother Mother Mother Mother Mother

observations All Interview All Interview All Interview All Interview All Interview All Interview All Interview All Interview

Born Prior to 1986 Interview Period

Full sample 4,533 0.90 0.95 0.88 0.95 0.83 0.89 0.83 0.88 0.83 0.89 0.77 0.85 0.80 0.89 — —

Cross-section 2,462 0.90 0.95 0.89 0.95 0.83 0.89 0.83 0.88 0.83 0.89 0.78 0.84 0.79 0.88 — —

Born After Start of 1986 Interview Period and Prior to Start of 1988 Interview Period

Full sample 1,199 — — 0.90 0.96 0.88 0.95 0.89 0.94 0.87 0.94 0.83 0.91 0.83 0.92 0.62 0.72

Cross-section 730 — — 0.90 0.97 0.89 0.95 0.89 0.95 0.88 0.95 0.83 0.92 0.82 0.91 0.72 0.85

Full sample 1,010 — — — — 0.90 0.95 0.91 0.95 0.89 0.95 0.84 0.92 0.84 0.91 0.65 0.74

Cross-section 638 — — — — 0.91 0.96 0.91 0.95 0.90 0.96 0.82 0.92 0.83 0.91 0.75 0.85

Full sample 806 — — — — — — 0.92 0.95 0.92 0.96 0.87 0.93 0.85 0.92 0.66 0.74

Cross-section 520 — — — — — — 0.92 0.95 0.92 0.96 0.88 0.93 0.84 0.90 0.75 0.86

Full sample 779 — — — — — — — — 0.93 0.96 0.89 0.94 0.87 0.93 0.68 0.75

Cross-section 477 — — — — — — — — 0.94 0.97 0.90 0.95 0.87 0.94 0.80 0.87

Full sample 481 — — — — — — — — — — 0.88 0.92 0.90 0.95 0.67 0.74

Cross-section 310 — — — — — — — — — — 0.89 0.93 0.92 0.97 0.76 0.84

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Table 4a

Descriptive Statistics for Person-Year Observations of Children, Children Born in 1994 or Earlier: Full Sample

All Annual Observations Annual observations, Continuous sample

All 1986, 1992, 1998 All 1986, 1992, 1998

Years 1990 1996 2000 Years 1990 1996 2000

Child’s age (in months)*

Mean 88 69 94 117 92 73 98 118

Median 87 63 94 120 92 68 101 120

10 percent 22 13 26 68 24 14 28 69

90 percent 155 131 159 163 158 137 162 164

Number of children in family*

Mean 2.52 2.36 2.60 2.66 2.54 2.39 2.62 2.66

Median 2 2 2 2 2 2 2 2

10 percent 1 1 1 1 1 1 1 1

90 percent 4 4 4 4 4 4 4 4

Mother’s marital status*

Never married 0.16 0.21 0.14 0.10 0.16 0.21 0.14 0.10 Married 0.63 0.61 0.64 0.67 0.64 0.61 0.65 0.69 Separated 0.08 0.08 0.08 0.07 0.08 0.08 0.08 0.07 Divorced 0.12 0.10 0.12 0.14 0.11 0.10 0.12 0.14 Widowed 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 Mother’s highest grade*

Mean 12 12 13 13 13 12 13 13

Median 12 12 12 12 12 12 12 13

10 percent 10 9 10 11 10 9 10 12

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Family income*

Mean 28,492 20,482 32,509 36,178 28,554 20,520 32,286 36,540 Median 20,945 16,729 21,453 29,283 21,371 16,945 22,026 30,012 10 percent 5,459 4,919 5,706 7,297 5,692 5,076 6,035 7,868 90 percent 49,827 40,323 50,519 66,791 49,844 40,363 49,869 66,044 Hours worked in rst year*

Mean 688 565 720 840 691 567 710 857

Median 62 0 132 463 105 0 144 520

10 percent 0 0 0 0 0 0 0 0

90 percent 2,080 1,880 2,080 2,080 2,080 1,894 2,80 2,080 Worked in rst year* 0.51 0.46 0.53 0.58 0.52 0.47 0.53 0.59 Child’s PPVT score*

Mean 89 85 90 94 90 86 91 95

Median 90 87 91 95 91 88 92 97

10 percent 64 60 67 68 65 61 68 70

90 percent 113 109 113 118 114 109 114 120

Child’s BPI score*

Mean 106 108 106 104 106 108 107 103

Median 105 107 105 103 106 107 106 103

10 percent 88 90 88 84 88 90 89 84

90 percent 126 126 126 123 125 126 126 122

Number of observations 39,607 15,125 17,673 6,809 28,902 10,941 12,653 5,308

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Table 4b

Descriptive Statistics for Person-Year Observations of Children, Children Born in 1994 or Earlier: Cross-section

All Annual Observations Annual observations, Continuous sample

All 1986, 1992, 1998 All 1986, 1992, 1998

Years 1990 1996 2000 Years 1990 1996 2000

Child’s age (in months)*

Mean 86 65 90 116 88 67 92 116

Median 85 59 89 118 87 62 91 118

10 percent 21 11 24 68 22 12 24 67

90 percent 153 127 156 162 155 131 158 163

Number of children in family*

Mean 2.41 2.26 2.47 2.54 2.43 2.29 2.48 2.54

Median 2 2 2 2 2 2 2 2

10 percent 1 1 1 1 1 1 1 1

90 percent 4 4 4 4 4 4 4 4

Mother’s marital status*

Never married 0.09 0.13 0.08 0.06 0.08 0.13 0.08 0.06

Married 0.73 0.70 0.74 0.75 0.74 0.71 0.75 0.76

Separated 0.06 0.06 0.06 0.06 0.05 0.06 0.05 0.05

Divorced 0.12 0.10 0.12 0.13 0.11 0.10 0.11 0.13

Widowed 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01

Mother’s highest grade*

Mean 12 12 13 14 13 12 13 14

Median 12 12 12 12 12 12 12 13

10 percent 10 10 11 12 11 10 11 12

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Family income*

Mean 32,631 23,274 37,799 38,648 32,181 23,240 36,216 38,784

Median 24,930 20,446 25,949 33,013 25,234 20,968 26,057 33,206

10 percent 6,308 5,576 6,780 8,403 6,605 10,595 7,242 8,972

90 percent 53,772 43,306 54,740 67,098 53,084 42,831 53,287 66,231

Hours worked in rst year*

Mean 715 589 743 859 735 603 753 885

Median 221 0 282 560 285 15 332 626

10 percent 0 0 0 0 0 0 0 0

90 percent 2,080 1,920 2,080 2,080 2,080 1,950 2,080 2,080

Worked in rst year* 0.54 0.49 0.56 0.60 0.56 0.50 0.57 0.62

Child’s PPVT score

Mean 95 91 95 98 95 92 96 99

Median 96 93 96 99 96 94 96 99

10 percent 71 67 74 76 72 68 73 77

90 percent 116 112 116 122 117 113 117 123

Child’s BPI score*

Mean 106 108 106 103 106 108 106 103

Median 105 107 105 102 105 108 105 102

10 percent 86 90 87 84 88 91 88 84

90 percent 124 126 124 121 124 126 124 121

Number of observations 23,585 8,489 10,575 4,521 18,419 6,359 8,232 3,828

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Table 5

Means for Children’s Mothers 1979: All Known Children, and Children who were Continuously, Sometimes, and Never in the Child Supplement

Continuously Sometimes in Never in in NLSY79-C NLSY79-C NLSY79-C

All Sample Sample Sample

Full Sample

Age 17.87 17.93 17.73 18.10

Any children 0.23 0.24 0.20 0.31

Number of children 0.33 0.35 0.27 0.49

Married 0.18 0.19 0.16 0.28

Divorced 0.01 0.01 0.01 0.01

Separated 0.02 0.02 0.02 0.04

Widowed 0.00 0 0.00 0

Never married 0.79 0.78 0.81 0.68

Highest grade completed* 10.32 10.40 10.21 10.03

AFQT score* 33.21 35.60 28.83 30.53

Number of observations 8,457 5,256 2,846 355

Cross-Section

Age 17.89 17.91 17.81 18.01

Any children 0.19 0.19 0.19 0.25

Number of children 0.27 0.27 0.26 0.37

Married 0.19 0.19 0.18 0.30

Divorced 0.01 0.01 0.01 0.00

Separated 0.02 0.02 0.03 0.02

Widowed 0 0 0 0

Never married 0.78 0.78 0.78 0.67

Highest grade completed* 10.54 10.61 10.41 10.23

AFQT score* 41.79 44.11 36.36 39.36

Number of observations 4,950 3,322 1,424 204

Notes: Sample is composed mothers of children born in 1994 or earlier. * indicates that some observations are missing values for these variables.

most characteristics of the children and their families are affected little by whether attritors are included or excluded. In general, the comparisons in Table 4 imply that small differences exist between attritors and nonattritors. However, the comparisons neglect the group of children for whom supplemental information is never collected; they are potentially different from those for whom supplemental information is col-lected at least once.

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is presented for all known children and three subsamples: (1) children continuously in the sample, (2) children for whom supplemental information is sometimes col-lected, and (3) children for whom supplemental information is never collected. The comparisons are done separately for the full and cross-sectional samples. Although the mothers of children in the continuous sample score higher on the AFQT than the mothers of children who are either sometimes or never in the NLSY-C, along most other dimensions they look similar to the mothers of the children for whom supple-mental information is sometimes collected. The mothers of the children for whom supplemental information is never collected look different in that they are the most likely to have had a child and the least likely to have never been married at the 1979 interview.

Overall, children who are surveyed in some of the child supplement years in which they are eligible are similar to those who are surveyed in all eligible years. The mothers of these two groups of children also appear similar. However, the children who are not interviewed in any of the mother-child supplement years and their moth-ers are different. These mothmoth-ers more often experienced an early marriage or birth. Attrition from the NLSY79 prior to the start of the child supplement appears nonran-dom with respect to women’s fertility through 1979 and marital status at that time. Evaluating the effects that this attrition has on the sample of children is made difcult because there is no information on children whose mothers attrite before their births, but the fact that there are not many of these children minimizes the chance that their absence will have large consequences.

III. Nature of Attrition

This section further examines how attritors are different from nonat-tritors by estimating two types of equations. The samples for these equations are restricted to children who have been born in 1994 or earlier and have not attrited prior to having been assessed for the rst time on the PPVT (eligible at age three) or the BPI (eligible at age four) depending on the assessment of interest. The rst of these equations is a probit that estimates the probability that an individual is an attritor at a future NLSY79-C interview.

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the assessment. By including individual characteristics, one can test whether children who attrite come from particular backgrounds.7

Table 6 presents coefcient estimates and marginal effects for Equation 1. The full sample results indicate that Black and Hispanic children are more likely than other children to attrite. The children whose mothers have never married are less likely to attrite compared to those whose mothers are married, separated, or divorced. The probability of attrition increases in average family income during the child’s rst three years. In the specications that include family income, the probability of future attrition is decreasing in the educational attainment of one’s maternal grand-father by 0.6 of a percentage point for each additional grade completed by one’s grandfather. Moreover, in the specication that includes early maternal employment and BPI scores, attrition appears nonrandom with respect to BPI scores.

As was the case in the full sample, in the cross-section a child from higher-income family or whose mother is divorced or separated or married is more likely to attrite, and the effects remain small. However, attrition appears less connected to character-istics of the children when the cross-section is examined separately, implying that the process of attrition for the cross-section may be different than that in the Black and Hispanic supplements.

Although attrition is related to some of the characteristics included in the probit equations on attrition, the psuedo-R2_{for these equations is quite low, ranging from} 0.012 to 0.034 which indicates that much of the attrition is not associated with the variables controlled for in these specications. Attrition appears random with respect to maternal employment in the child’s rst year of life, but is related to family income early in the child’s life.

The second type of equation examines the effect of attrition on the estimates of the effect of family characteristics measured early in the child’s life on his BPI and PPVT standard scores.

(2) ASit 5a1rFCiE1b1Zi1b2Zit1eit

whereASit is childi’s assessment standard score on either the PPVT or BPI andt

is the rst interview at which the child is age-eligible for that assessment, FCiEis

a characteristic of the child’s parent or family measured early in the child’s life (at time E), Zare the additional covariates controlled for,eitis a random error, and r

is the coefcient on the family characteristics of interest. These equations are esti-mated using the same samples that are used in the attrition probits above, as well as, the subsample of nonattritors. The differences in the estimates ofrfor the sample with and without the attritors are then compared to see how attrition impacts the estimated relationship. Four models are estimated for each sample and subsample: (1) Model 1 contains no additional covariates, (2) Model 2 includes a dummy vari-able for race, a dummy varivari-able for ethnicity, child’s gender, child’s age in months, and highest grade completed by each of the child’s maternal grandparents in the VectorZ, (3) Model 3 adds a set of dummy variables indicating child’s year of birth

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Table 6a

Attrition Probit, Child Ever Out: Full Sample

Coefcient Marginal Coefcient Marginal Coefcient Marginal Coefcient Marginal Estimate Effect Estimate Effect Estimate Effect Estimate Effect

Black 0.348** 0.119 0.379** 0.132 0.312** 0.107 0.338** 0.118

(0.061) (0.062) (0.071) (0.073)

Hispanic 0.497** 0.175 0.520** 0.186 0.468** 0.167 0.520** 0.188

(0.072) (0.074) (0.080) (0.082)

Mother’s age 1979 20.013 20.004 20.012 20.004 20.023 20.008 20.015 20.005

(0.018) (0.019) (0.021) (0.021)

Mother’s highest grade 1979 0.001 0.000 0.006 0.002 0.013 0.004 0.010 0.003

(0.019) (0.020) (0.022) (0.023)

Number of children 1979 ₂0.093 ₂0.030 ₂0.106 ₂0.035 ₂0.053 ₂0.018 ₂0.038 ₂0.013

(0.060) (0.062) (0.066) (0.066)

Mother’s marital status

Married 0.177* 0.061 0.213* 0.074 0.194* 0.067 0.192* 0.068

(0.081) (0.083) (0.089) (0.093)

Divorced/separated 0.417* 0.151 0.493* 0.183 0.404** 0.148 0.432* 0.160

(0.194) (0.210) (0.213) (0.218)

Male child 0.083* 0.027 0.070 0.023 0.079 0.026 0.056 0.019

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Table 6a

(continued)

Grandmother’s highest grade 0.005 0.002 0.004 0.001 0.002 0.001 0.005 0.002

(0.011) (0.011) (0.012) (0.012)

Grandfather’s highest grade ₂0.018* ₂0.006 ₂0.017 ₂0.006 ₂0.019* ₂0.006 ₂0.018 ₂0.006

(0.009) (0.009) (0.009) (0.010)

PPVT score ₂0.000 ₂0.000 0.000 0.000

(0.001) (0.001)

BPI score ₂0.003 ₂0.001 ₂0.003* ₂0.001

(0.002) (0.002)

Average income in rst three years 0.012* 0.004 0.016* 0.005

($10,000) (0.006) (0.006)

Maternal hours worked 0.053 0.018 0.069 0.023

In rst year (1,000 hours) (0.042) (0.045)

Work rst year ₂0.084 ₂0.028 ₂0.044 ₂0.015

(0.073) (0.080)

Number of observations 5,080 4,582 3,872 3,493

PsuedoR-squared 0.030 0.034 0.031 0.034

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Table 6b

Attrition Probit, Child Ever Out: Cross-Section

Black 0.008 0.002 0.068 0.020 0.018 0.005 0.036 0.011

(0.103) (0.104) (0.116) (0.119)

Hispanic 20.002 20.001 0.059 0.017 0.073 0.022 0.145 0.045

(0.129) (0.134) (0.136) (0.139)

Mother’s age 1979 0.007 0.002 0.005 0.001 0.009 0.003 0.014 0.004

(0.027) (0.028) (0.029) (0.030)

Mother’s highest grade 1979 ₂0.029 ₂0.008 ₂0.016 ₂0.005 ₂0.032 ₂0.009 ₂0.023 ₂0.007

(0.030) (0.031) (0.032) (0.034)

Number of children 1979 ₂0.074 ₂0.021 ₂0.086** ₂0.025 ₂0.081 ₂0.024 ₂0.037 ₂0.011

(0.086) (0.091) (0.092) (0.092)

Mother’s marital status

Married 0.157 0.046 0.213* 0.065 0.209 0.065 0.207 0.065

(0.104) (0.107) (0.113) (0.117)

Divorced/separated 0.635** 0.218 0.642** 0.222 0.685** 0.243 0.667** 0.237

(0.224) (0.244) (0.243) (0.249)

Male child 0.059 0.017 0.069 0.020 0.014 0.004 ₂0.000 ₂0.000

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Table 6b

(continued)

Grandmother’s highest grade 20.010 20.003 20.010 20.003 20.022 20.007 20.017 20.005

(0.017) (0.017) (0.018) (0.019)

Grandfather’s highest grade 20.008 20.002 20.005 20.001 20.003 20.001 20.004 20.001

(0.012) (0.013) (0.013) (0.013)

PPVT ₂0.002 ₂0.001 ₂0.001 ₂0.000

(0.002) (0.002)

BPI 20.001 20.000 20.002 20.001

(0.002) (0.002)

Average income in rst three years 0.014* 0.004 0.018* 0.005

($10,000) (0.007) (0.008)

Maternal hours worked ₂0.004 ₂0.001 ₂0.024 ₂0.007

In rst year (1,000 hours) (0.055) (0.061)

Work rst year 20.067 20.019 20.015 20.005

(0.095) (0.103)

Number of observations 3,139 2,820 2,417 2,155

Pseudo R-squared 0.012 0.014 0.019 0.020

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Aughinbaugh 555

to the variables included in Model 2, and (4) Model 4 adds mother’s AFQT score to those variables in Model 3.

As Fitzgerald, Gottschalk, and Moftt (1998) note, some attrition will have oc-curred before the child reaches age tand consequently the estimates may already be biased. To test whether further attrition is biasing, Fitzgerald, Gottschalk, and Moftt assume that attrition pre- and post- agetbiases the coefcient estimates in the same direction. This assumption is sufcient to permit inference that there is attrition bias in the sample if attrition bias is found in the post-period. I also make this assumption.

Table 7 examines how attrition impacts estimation of the effect of average income during the child’s rst three years (measured in units of 10,000 1984$) on PPVT and BPI standard scores. The top half presents coefcient estimates for the full sam-ple while the bottom half present the estimates for the cross-section.

As in past literature that has examined the effect of family income on child devel-opment (Blau 1999, Mayer 1997), income tends to improve test scores by a small, but statistically signicant amount. In general, the magnitude of the family income effect is slightly larger among the nonattritors; however, in no case is the difference between the coefcient estimates using all observations and using the nonattritors signicantly different from zero.8

Table 8 examines the impact of attrition on estimates of the effect of maternal employment on children’s PPVT and BPI scores. Hours of work (in units of 1,000 hours) during the child’s rst year and a dummy variable indicating whether the mother worked during the child’s rst year are used to measure maternal employ-ment.9_{In Panel A, the coefcient estimates for the maternal employment variables} are presented for the full sample for both all children and for the nonattritors. Panel B presents this same information for the cross-sectional sample. The estimates pre-sented here are in accord with a large number of studies that use the NLSY79-C and nd small effects of maternal employment on early PPVT and BPI scores (for example, James-Burdumy 1999 and Harvey 1999).10

Although in the full sample hours worked in the child’s rst year do not have a signicant impact on PPVT scores, the dummy variable indicating that the mother worked implies that it is benecial for the child to have a mother who works during his rst year of life. These benets decline as controls are added, which seems to imply positive selection of women into the labor force during their children’s rst year. In Models 1 and 2, additional hours of work by the mother appear to reduce behavioral problems and the dummy variable for working in the child’s rst year has

8. The standard errors are calculated using the fact that the variance of the difference in the coefcients for the total sample and the nonattriting subsample is equal to the difference in the variances. See Fitzgerald, Gottschalk, and Moftt (1998) and reference therein for more detail.

9. In much of the literature on the impact of maternal employment on child development, maternal employ-ment is measured by hours worked in the child’s rst three years measured with three variables, one for each year. Owing to the high correlation between hours worked in these years, changes in either the sample used for estimation or the specication can have large effects on all three of the coefcients estimates on hours worked that may balance each other out. Consequently, to study the impact of attrition, I measure early maternal employment using only employment in the child’s rst year.

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Table 7

Estimates of Effect of Average Family Income in First 3 Years on Child Assessments

PPVT BPI

Full Sample

Nonattritors All Nonattritors

All (n53,872) (n52,782) Difference (n55,080) (n53,695) Difference

Model 1 0.957** 1.012** 0.055 20.440** 20.487** 0.047

(0.160) (0.218) (0.148) (0.064) (0.075) (0.039)

[0.030] [0.030] [0.014] [0.015]

Model 2 0.247** 0.236* 0.011 20.320** 20.345** 0.025

(0.095) (0.120) (0.073) (0.058) (0.067) (0.034)

[0.321] [0.342] [0.033] [0.037]

Model 3 0.228* 0.235* 0.007 20.221** 20.237** 0.016

(0.097) (0.124) (0.077) (0.054) (0.062) (0.030)

[0.325] [0.345] [0.060] [0.068]

Model 4 0.061 0.027 0.034 ₂0.175** ₂0.182** 0.007

(0.089) (0.114) (0.071) (0.052) (0.062) (0.034)

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Cross-Section

All (n₅2,417) (n₅1,883) Difference (n₅3139) (n₅2,496) Difference

Model 1 0.663** 0.762** 0.099 20.400** 20.440** 0.040

(0.152) (0.203) (0.135) (0.073) (0.084) (0.042)

[0.020] [0.021] [0.014] [0.014]

Model 2 0.144 0.202 0.058 ₂0.274** ₂0.302** 0.028

(0.093) (0.114) (0.066) (0.064) (0.074) (0.037)

[0.291] [0.295] [0.041] [0.038]

Model 3 0.135 0.193 0.058 ₂0.194** ₂0.203** 0.009

(0.097) (0.121) (0.072) (0.061) (0.069) (0.032)

[0.296] [0.301] [0.071] [0.074]

Model 4 0.007 0.022 0.015 20.165* 20.165** 0.000

(0.091) (0.114) (0.069) (0.060) (0.070) (0.036)

[0.327] [0.333] [0.074] [0.077]

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Table 8a

Estimates of Effect of Maternal Employment in First Year on Child Assessments: Full Sample

PPVT BPI

All (n₅3,493) (n₅2,478) Difference (n₅4,582) (n₅3,289) Difference

Model 1

Hours ₂1.055 ₂1.270 0.215 ₂1.009* ₂1.402** 0.393

(0.649) (0.764) (0.403) (0.416) (0.471) (0.221)

Any work 8.909** 9.007** 0.098 ₂0.651 ₂0.179 0.472

(1.195) (1.359) (0.647) (0.725) (0.828) (0.400)

[0.029] [0.028] [0.006] [0.008]

Model 2

Hours 0.128 20.497 0.625* 21.139** 21.489** 0.350

(0.543) (0.622) (0.303) (0.411) (0.466) (0.220)

Any work 3.540** 3.632** 0.092 0.441 0.933 0.492

(0.976) (1.086) (0.476) (0.726) (0.830) (0.402)

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All (n₅3,493) (n₅2,478) Difference (n₅4,582) (n₅3,289) Difference

Model 3

Hours 0.130 20.401 0.531 20.467 20.785 0.318

(0.577) (0.641) (0.279) (0.412) (0.469) (0.224)

Any work 3.536** 3.702** 0.166 0.151 0.591 0.440

(0.986) (1.098) (0.483) (0.718) (0.825) (0.406)

[0.335] [0.352] [0.061] [0.069]

Model 4

Hours 20.169 20.630 0.461 20.384 20.725 0.341

(0.543) (0.620) (0.299) (0.413) (0.471) (0.226)

Any work 2.294* 2.225* 0.069 0.458 0.959 0.501

(0.986) (1.078) (0.436) (0.717) (0.827) (0.412)

[0.363] [0.383] [0.066] [0.075]

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Table 8b

Estimates of Effect of Maternal Employment in First Year on Child Assessments: Cross-Section

PPVT BPI

All Nonattritors All Nonattritors

(n₅2,155) (n₅1,670) Difference (n₅2,820) (n₅2,225) Difference

Model 1

Hours 20.773 20.965 0.192 20.483 20.991 0.508**

(0.762) (0.849) (0.374) (0.521) (0.554) (0.188)

Any work 6.407** 6.110** 0.297 ₂0.850 ₂0.227 0.623

(1.366) (1.538) (0.707) (0.890) (0.967) (0.378)

[0.018] [0.015] [0.003] [0.004]

Model 2

Hours 0.002 0.041 0.039 20.551 21.057* 0.506*

(0.648) (0.712) (0.295) (0.511) (0.548) (0.198)

Any work 2.332* 1.913 0.419 0.033 0.540 0.507

(1.126) (1.240) (0.519) (0.892) (0.972) (0.386)

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All Nonattritors All Nonattritors

(n₅2,155) (n₅1,670) Difference (n₅2,820) (n₅2,225) Difference

Model 3

Hours 0.135 0.200 0.065 0.166 20.313 0.479*

(0.666) (0.739) (0.320) (0.516) (0.554) (0.202)

Any work 2.198 1.859 0.339 ₂0.226 0.266 0.492

(1.130) (1.246) (0.525) (0.884) (0.967) (0.392)

[0.294] [0.291] [0.071] [0.072]

Model 4

Hours 20.156 20.024 0.132 0.221 20.267 0.488*

(0.647) (0.716) (0.307) (0.516) (0.555) (0.204)

Any work 1.170 0.766 0.404 20.008 0.509 0.517

(1.106) (1.227) (0.531) (0.882) (0.967) (0.396)

[0.322] [0.322] [0.075] [0.076]

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no effect. In both the PPVT and BPI equations, the differences between the coefcient estimates on the maternal employment variables when the attritors are included in the estimation and when they are not included are small and never signicant.

When these equations are estimated using the cross-sectional sample, the coef-cient estimates on the maternal employment variables are rarely signicant. For all four specications of BPI standard scores, the differences in the coefcient estimates on hours worked in the child’s rst year are signicant. Though the coefcient esti-mates themselves are not signicantly different from zero in three of the four speci-cations, exclusion of the attritors makes it appear that hours worked by the mother in the child’s rst year are more effective in decreasing behavioral problems com-pared to those estimates that include the attritors. This may imply that the intensity of work during a child’s rst year varies systematically by future attrition with char-acteristics that are not controlled for here.

I also estimate Equations 1 and 2 using an older sample that employs the assess-ment scores from two years later and requires children not to have attrited up to that point. The sample sizes are much smaller and hence it is not surprising that almost none of the regressors in the attrition probits are signicant. However, family income remains signicantly negative in the probit that includes PPVT. In the estimates of Equation 2 that use the older children, the differences in the estimates ofrbetween samples that include and exclude the attritors are never signicant. Compared with the results presented in Tables 7 and 8, the computed differences and their standard errors are approximately an order of magnitude larger.

IV. Conclusion

For less than 5 percent of the children that are known to have been born to the NLSY79 women supplemental information is never collected—in most cases because their mothers were not interviewed. Conditional on the child’s mother being interviewed, supplemental information is collected for 90 percent to 95 percent of the children.

Children for whom supplemental information is collected at all NLSY79-C inter-views and those for whom supplemental information is sometimes collected appear similar with respect to descriptive statistics on family background. However, the children for whom supplemental information is never collected are different. When the 1979 characteristics of the children’s mothers in these groups are compared, mothers in the last group are more likely to have had a child by 1979, and were more likely to have never been married than the mothers of the other two groups. The probability of attriting is related to a number of characteristics, including family income. However, the differential likelihoods of attriting do not impact the estimated effects of family income or maternal employment on either the children’s PPVT or BPI scores. Taken together, the results imply that attrition behavior may be nonrandom over the years that the NLSY79-C is collected. However, the effects of this attrition on the picture of family background portrayed by the NLSY79-C appear to be minimal.

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relation-Aughinbaugh 563

ships considered in this study. It is important to remember that there are a group of children who are never assessed and a group of children whose births are never recorded in the NLSY79-C. The impact of their absence cannot be gauged and may affect estimates of family background on child outcomes.

References

Baker, Paula C., Canada K. Keck, Frank L. Mott, and Stephan V. Quinlan. 2001.NLSY Child and Young Adult Handbook. Center for Human Resource Research, Ohio State University.

Blau, David M. 1999. “The Effect of Income on Child Development.”Review of Econom-ics and StatistEconom-ics 81(2):261– 76.

Fitzgerald, John, Peter Gottschalk, and Robert Moftt. 1998. “An Analysis of the Impact of Sample Attrition on the Second Generation of Respondents in the Michigan Panel Study of Income Dynamics.” Journal of Human Resources33(2):300– 44.

James-Burdumy, Susanne. 1999. “The Effect of Maternal Labor Force Participation.” Work-ing paper, Mathematica Policy Research.

Han, Wen-Jui, and Jane Waldfogel. 2001. “The Effect of Early Maternal Employment on Later Cognitive and Behavioral Outcomes.” Journal of Marriage and Family63(1): 336– 54.

Harvey, Elizabeth. 1999. “Short-Term and Long-Term Effects of Early Parental Employ-ment on Children of the National Longitudinal Survey of Youth.”Developmental Psy-chology35(2):445– 59.

MaCurdy, Thomas, Thomas Mroz, and R. Mark Gritz. 1998. “An Evaluation of the Na-tional Longitudinal Survey of Youth.Journal of Human Resources33(2):345– 436. Mayer, Susan. (1997. )What Money Can’t Buy: Family Income and Children’s Life

Chances. Cambridge: Harvard University Press, Cambridge.

Mott, Frank L. 1998. “Patterning of Child Assessment Completion Rates in the NLSY: 1986-1996.” Working paper, Center for Human Resource Research, Ohio State Univer-sity.