1

David LamDepartment of Economics

and Population Studies CenterUniversity of Michigan

World Bank Workshop on "Tackling Adolescent Reproductive Health: Impacts and

Interventions to Address Them"December 1, 2009

Impacts of teen fertility on outcomes of teen mothers and their children in South Africa: Evidence from the Cape Area Panel Study

Support for this research was provided by the U.S. National Institute of Child Health and Human Development and the William and Flora Hewlett

Foundation.

2

Cally ArdingtonUniversity of Cape Town

Nicola BransonUniversity of Cape Town

David LamUniversity of Michigan

Murray LeibbrandtUniversity of Cape Town

Letícia MarteletoUniversity of Michigan and University of Texas

Vimal RanchhodUniversity of Michigan and University of Cape Town

This presentation draws on a number of papers produced by various combinations of the following project team:

This work was produced as part of the “Global Teams of Research Excellence in Population, Reproductive Health, and Economic Development” sponsored by the William

and Flora Hewlett Foundation and the Population Reference Bureau

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Background of the Cape Area Panel Study• Study began in 2002 with 4,752 14-22 year-olds

– Collaboration of University of Cape Town and University of Michigan– All areas and all population groups in Cape Town are represented– Integrated survey of education, employment, sexual behavior, health

• Wave 2, 2003 and 2004• Wave 3, 2005

– Successfully reinterviewed about 85% of original young adult sample

• Wave 4, 2006- UCT, Michigan, Princeton collaboration– Tracked all young adults, plus all members of original CAPS

households who were age 50+ in 2006, plus all children of female CAPS young adults

• Wave 5, 2009 (young adult sample, includes HIV testing)• Public access data

– Integrated Wave 1-2-3-4 data available at www.caps.uct.ac.za

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Teen childbearing in South Africa

• Total Fertility Rate of 2.9 is lowest in Sub-Saharan Africa

• Relatively high rates of teen childbearing– 24% had a birth by age 18; 50% by 20

• Significant fractions of teenage mothers return to school after having their child – Over 50% of 15-17 year-olds with a child were in

school

• Most teen childbearing is non-marital– Only 18% of 20 year old mothers had ever been

married

Source: 2001 South African Census Data

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Using CAPS to study the impact of teen fertility – three approaches

1. Compare CAPS young adult respondents who were born to teen mothers with those born to non-teen mothers

2. Look at the outcomes of the children of CAPS YA respondents, comparing those with teen versus non-teen mothers

3. Look at the educational outcomes of YA respondents with and without teen births

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Mother was teen when YA was born

CAPS young adults

Treatment

CAPS young adults

(age 14-22 in 2002)

Mothers of CAPS

young adults

Children of

female CAPS young adults

Analysis 1

Mother was 20+ when YA was born

CAPS young adults

Control

Child of female

CAPS YA

Treatment

Child of female

CAPS YA

Control

CAPS YA had birth as teen

CAPS YA had birth at 20+

Analysis 2

CAPS YA had

teen birth

Treatment

CAPS YA did

not have teen birth

Control

Analysis 3Generation

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1. Using CAPS young adults (YAs) as children of teen mothers

• CAPS has the mother’s age at YA’s birth for both resident and non-resident mothers

• Information on schooling and other characteristics at each age from birth based on retrospective histories

• Information on household characteristics such as income, parent’s education, and employment status of household members

• Information on up to three YAs in same household – allows sibling fixed effects

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Sample and Methods• CAPS 2002-2006, young adult sample

• Young Adults as children of teen mothers

• OLS, with and without controls, plus sibling/cousin fixed effects

Total # of Young Adults   3,662  

  % born to teen mother     14.58%

# of groups (pairs/triplets)   1,045  

 % (#) with variation on teen mother   21% (221)

Includes all African and Coloured YA’s with mother’s age at their birth

Siblings and cousins in the same household

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Estimated impact of being born to a teen mother

Outcome Mean OLS

OLS with

controls

Sibling fixed

effects Mean OLS

OLS with

controls

Sibling fixed

effects(1) (2) (3) (4) (5) (6) (7) (8)

[0.372] -0.202*** -0.14** 0.00 [-0.267] 0.003 -0.018* 0.0170.003 0.064 0.107 0.795 0.01 0.018

[0.737] -0.040*** -0.036*** -0.015 [0.756] -0.095 -0.237*** -0.0980.005 0.013 0.021 0.114 0.061 0.08

[0.5] -0.122** -0.097** -0.025 [0.318] 0.019 -0.063 -0.052

0.011 0.043 0.095 0.656 0.043 0.084[0.266] 0.103*** 0.097*** 0.068 [0.105] -0.031* 0 0.008

0.003 0.032 0.058 0.093 0.017 0.035[0.214] 0.062* 0.056* 0.113** [0.192] -0.041 -0.026 -0.064

0.063 0.033 0.047 0.133 0.029 0.058[0.059] 0.034* 0.033* 0.092*** [0.024] -0.036 -0.017 -0.086**

0.058 0.018 0.034 0.182 0.028 0.036

Note: Robust standard errors in italics; significance levels: *=.10, **=.05, ***=.01

Indicator: completed high school by age 20

Dropped out of school by age 16Lived with an alcoholic when growing up

Fear of physical abuse when growing up

Coloured Sample African Sample

Age standardized mathematics score

Rate of grade progression

For coloured sample, those with teen mother have 0.2 standard deviations lower math score than those with non-teen mother.

Controlling for parents’ education, childhood poverty status, and mother’s fertility reduces coefficient by 30%

Comparing siblings with and without teen mothers reduces coefficent to zero.

For African sample there is no unadjusted difference in test scores.

With controls for parents’ education, childhood poverty status, and mother’s fertility there is a difference of -.02 standard deviations.

Comparing siblings with and without teen mothers the coefficient is similar but has larger standard error.

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CAPS respondents born to teen mothers have younger mothers – as a result their mothers have higher education. Mean education of teen mothers is 1.4 grades higher than for non-teen mothers. This creates a bias in the opposite direction of most studies of teen childbearing.

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Estimated impact of being born to a teen mother

Outcome Mean OLS

OLS with

controls

Sibling fixed

effects Mean OLS

OLS with

controls

Sibling fixed

effects(1) (2) (3) (4) (5) (6) (7) (8)

[0.372] -0.202*** -0.14** 0.00 [-0.267] 0.003 -0.018* 0.0170.003 0.064 0.107 0.795 0.01 0.018

[0.737] -0.040*** -0.036*** -0.015 [0.756] -0.095 -0.237*** -0.0980.005 0.013 0.021 0.114 0.061 0.08

[0.500] -0.122** -0.097** -0.025 [0.318] 0.019 -0.063 -0.052

0.011 0.043 0.095 0.656 0.043 0.084[0.266] 0.103*** 0.097*** 0.068 [0.105] -0.031* 0.000 0.008

0.003 0.032 0.058 0.093 0.017 0.035

Note: Robust standard errors in italics; significance levels: *=.10, **=.05, ***=.01

Coloured Sample African Sample

Age standardized mathematics score

Rate of grade progressionIndicator: completed high school by age 20

Dropped out of school by age 16

Adjusted point estimates are larger in magnitude than unadjusted estimates for three outcomes for Africans

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Sensitivity Checks

• Birth order effect versus teen mother effect

• Does teen childbearing affect all the teen mother’s children or only the one born to her as a teen?

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Teen mother versus birth order• High correlation between being born to teen

mother and being the older sibling/cousin• Older siblings may fare better on certain

outcomes due to birth order effects• We restrict sample to YAs not born to teen

mothers and look for birth order effects• In African sample, older siblings/cousins progress

through school faster and are less likely to drop out by age 16

• Older sibling advantage might be masking a negative effect of being born to teen mother

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Are all children born to teens equally affected by the initial teen birth?

• This would explain the small estimated impacts in the Fixed Effects analysis

• To test this we restrict sample to YAs born to older mothers

• We compare YAs who have older siblings/cousins born to a teen mother to YAs who do not– Mostly negative but insignificant results found for the African

sample

– Evidence of lower math scores in coloured sample

• Some support for “systematic difference” hypothesis, implying that FE estimates may not be informative

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Conclusions from Analysis 1• Negative effects of having a teen mother

found for Coloured young adults• Effects decline when we include controls and

disappear when we compare siblings/cousins– Suggests that unadjusted differences result from

adverse pre-birth factors• Effects for Africans become larger when we

include controls– Teen mothers have more education because they

are younger• Effects disappear comparing siblings/cousins

– Might be a result of the fact that first-born children do better on certain outcomes

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2. Health outcomes of children of CAPS respondents

• We compare children born to teen mothers with children born to mothers age 20+

• Using propensity score matching, we estimate weighted regressions with “born to teen mother” as key variable:– Step 1: Estimate the probability of being a teen mother given

pre-childbirth characteristics

– Step 2: Predict the propensity scores

– Step 3: Calculate a set of weights based on these scores to construct a counterfactual from the children born to older mothers group

– Step 4: Estimate the effect of being born to a teen mother using regressions weighted by the constructed weight

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CAPS data – Timeline & Sample

Wave 1 (2002)4752 young adults (age 14-22)

Wave 2A (2003)1360 young adults (age 15-23) Wave 2B (2004)

2489 young adults (age 16-24)

Wave 3 (2005)all young adults (age 17-25)

Wave 4 (2006-07)All young adults (age 18-26)

pluschildren of female young adults

607 children – African and coloured first born children only

Sample selective of women who begin childbearing early

Majority of teen mothers in their late teens - average age = 17.6

Majority of older mothers in their early 20s - average age = 21.6

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Proportion teen mother

VariableTeen

motherOlder

mother Diff.Teen

motherOlder

mother Diff.

Childhood household poor or very poor 0.08 0.03 0.05* 0.24 0.31 -0.07 Neighborhood household income (log mean) 10.79 10.83 -0.04 9.94 9.91 0.03 Wave 1 household owns 5 or more books 0.78 0.94 -0.16*** 0.66 0.56 0.10* Wave 1 household per capita income 670.0 747.6 -77.6 332.7 356.7 -24.0

Mother's education 7.54 7.80 -0.26 7.39 7.34 0.05 Father's education 8.11 8.51 -0.40 6.53 6.77 -0.24 Proportion of life lived with mother 0.87 0.87 0.00 0.78 0.77 0.01 Proportion of life lived with father 0.58 0.59 -0.01 0.48 0.50 -0.02 Prop. of life lived with maternal grandparent 0.17 0.18 -0.01 0.22 0.23 -0.01

Drug addict in childhood household 0.19 0.1 0.09* 0.03 0.05 -0.02 Alcoholic in childhood household 0.26 0.18 0.08 0.23 0.19 0.04

Highest grade at age 12 5.62 5.63 -0.01 4.79 4.60 0.19 Failed a grade by age 12 0.30 0.29 0.01 0.26 0.21 0.05 Standardized numeracy and literacy score 0.02 0.00 0.02 -0.14 0.09 -0.23** Number of students in class 39.02 35.4 3.62*** 45.18 43.69 1.49 Age at menarche 13.06 12.92 0.14 13.99 14.58 -0.59***

Sample size 169 119 140 179

Table 3. Mean characteristics of teen mothers and older mothers

0.44African

0.57Coloured

Teen mothers are generally worse off in coloured sample, but teen mothers are better off in African sample on a number of characteristics (marked in red).

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Sample

sizeLimited controls

Full controls

Propensity score

weightedBirthweight (Z-score) 422 -0.109 -0.141 -0.255* [0.13] [0.15] [0.15]Underweight at birth 412 0.072** 0.071** 0.098*** [0.03] [0.03] [0.03]Current height for age 481 -0.272 -0.561* -1.093** [0.26] [0.32] [0.55]Stunted 481 0.01 0.022 0.157** [0.06] [0.08] [0.07]

Note: Marginal effects based on regressions. Bootstrapped standard errors in brackets; significance levels: *=.10, **=.05, ***=.01

Effect of being born to a teen mother on child health outcomes

Unlike most analyses of teen mothers, we estimate larger effects when we control for characteristics than when we don’t. For some characteristics teen mothers are better off than older mothers.

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Conclusions of Analysis 2

• We find some evidence that children born to teen mothers are at risk of worse health – More likely to be born underweight– Have lower height for age z-scores and more likely to be stunted

• Unlike previous studies, our results do not suggest that teen mothers are inherently socioeconomically disadvantaged– P-score weighted differences are often larger than unadjusted

differences

• Differences between Africans and coloureds are large– Children born to coloured teen mothers have double the health

disadvantage seen for Africans

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3. Analyzing the impact of teen fertility on educational outcomes of teen mothers

• This analysis uses only the CAPS young adults, comparing teen mothers to other women

• As in analysis 2, we estimate propensity score weighted regressions.– Step 1: Estimate probits using covariates, with

`treatment’ variable, predict the propensity scores. – Step 2: Match untreated observations to treated

observations, based on the pscores. – Step 3: This generates a set of weights for the

untreated group. (treated obs have weight= 1.)– Step 4: Estimate regressions by OLS weighted by the

(sampling weights x propensity score weights).

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Table 4: Regression results, coefficients on “teen birth” variableDependent Variable

Matric by age 20

Matric by age 22

Grades by age 18

Grades by age 20

Grades by age 22 Dropout

Specification 1: -0.303*** -0.302*** -0.931*** -1.331*** -1.130*** 0.190***No sample restriction, sampling [0.026] [0.035] [0.10] [0.12] [0.14] [0.020]weights only, no covariates N 1735 1129 2224 1735 1129 2295

R2 0.07 0.07 0.05 0.09 0.07 0.03

Specification 2: -0.208*** -0.227*** -0.620*** -0.921*** -0.801*** 0.147***No sample restriction, sampling [0.025] [0.033] [0.081] [0.11] [0.12] [0.019]weights only, with limited N 1718 1118 2193 1718 1118 2258covariates R2 0.31 0.28 0.45 0.39 0.37 0.16

Specification 3: -0.125*** -0.112*** -0.382*** -0.568*** -0.358*** 0.102***Had sex by age 19, sampling [0.029] [0.037] [0.096] [0.12] [0.13] [0.024]weights only, with all N 1221 810 1467 1221 810 1486covariates R2 0.27 0.26 0.37 0.37 0.4 0.14

Specification 4: -0.100*** -0.0754* -0.348*** -0.510*** -0.274* 0.0825***Had sex by age 19, sampling [0.032] [0.039] [0.11] [0.14] [0.16] [0.026]and propensity score matching N 1218 807 1464 1218 807 1483weights, with covariates and R2 0.24 0.27 0.36 0.34 0.37 0.14common support restriction

Standard errors in brackets *** p<0.01, ** p<0.05, * p<0.1

“Naïve estimate” – no covariates or sample restrictions. Teen mothers are 30 percentage points less likely to have completed grade 12 (matric) by age 20.

Coefficient falls by 31% with controls for household and socio-economic characteristics

Coefficient falls by 58% when we look at sample that had sex by age 19 and add controls for measures of sexual behavior

Coefficient falls by 67%, but is still negative and statistically signifcicant, when we use propensity score matching weights based on the full set of covariates including measures of sexual behavior

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Table 4: Regression results, coefficients on “teen birth” variableDependent Variable

Matric by age 20

Matric by age 22

Grades by age 18

Grades by age 20

Grades by age 22 Dropout

Specification 1: -0.303*** -0.302*** -0.931*** -1.331*** -1.130*** 0.190***No sample restriction, sampling [0.026] [0.035] [0.10] [0.12] [0.14] [0.020]weights only, no covariates N 1735 1129 2224 1735 1129 2295

R2 0.07 0.07 0.05 0.09 0.07 0.03

Specification 2: -0.208*** -0.227*** -0.620*** -0.921*** -0.801*** 0.147***No sample restriction, sampling [0.025] [0.033] [0.081] [0.11] [0.12] [0.019]weights only, with limited N 1718 1118 2193 1718 1118 2258

covariates R2 0.31 0.28 0.45 0.39 0.37 0.16

Specification 3: -0.125*** -0.112*** -0.382*** -0.568*** -0.358*** 0.102***Had sex by age 19, sampling [0.029] [0.037] [0.096] [0.12] [0.13] [0.024]weights only, with all N 1221 810 1467 1221 810 1486covariates R2 0.27 0.26 0.37 0.37 0.4 0.14

Specification 4: -0.100*** -0.0754* -0.348*** -0.510*** -0.274* 0.0825***Had sex by age 19, sampling [0.032] [0.039] [0.11] [0.14] [0.16] [0.026]and propensity score matching N 1218 807 1464 1218 807 1483weights, with covariates and R2 0.24 0.27 0.36 0.34 0.37 0.14common support restriction

Standard errors in brackets *** p<0.01, ** p<0.05, * p<0.1

Similar declines in coefficients using other outcome measures

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Enrollment by age, women with different ages at first birth

African females

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

12 13 14 15 16 17 18 19 20

Age

Pro

po

rtio

n e

nro

lled

First pregnancy age 23+First pregnancy at age 18First pregnancy at age 17

First pregnancy at age 16First pregnancy at age 15

50% of those with a birth at age 15 are enrolled in school 1 and 2 years later

Those with teen births already had lower enrollment rates at age 14

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Enrollment by age, women with different ages at first pregnancy

African females

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

12 13 14 15 16 17 18 19 20

Age

Pro

po

rtio

n e

nro

lled

First pregnancy age 23+First pregnancy at age 18First pregnancy at age 17

First pregnancy at age 16First pregnancy at age 15

Dropout rate after pregnancy is much higher for coloured teens than for African teens

This may partly reflect the high rates of grade repetition in African schools, which reduce stigma of going back to school

Coloured females

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

12 13 14 15 16 17 18 19 20

Age

Pro

po

rtio

n e

nro

lled

First pregnancy age 23+First pregnancy at age 18First pregnancy at age 17First pregnancy at age 16First pregnancy at age 15

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Grades completed by age, women with different ages at first birth

African females

4

5

6

7

8

9

10

11

12

12 13 14 15 16 17 18 19 20

Age

Gra

des

co

mp

lete

d

First pregnancy age 23+

First pregnancy at age 18

First pregnancy at age 17

First pregnancy at age 16

First pregnancy at age 15

Similar schooling at age 20 for those with birth at age 15, 16, or 17

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Grades completed by age, women with different ages at first pregnancy

Coloured teens gain very little schooling after pregnancy, while Africans continue to pass grades after pregnancy.

Coloured females

4

5

6

7

8

9

10

11

12

12 13 14 15 16 17 18 19 20

Age

Gra

des

co

mp

lete

d

First pregnancy age 23+First pregnancy at age 18First pregnancy at age 17First pregnancy at age 16First pregnancy at age 15

African females

4

5

6

7

8

9

10

11

12

12 13 14 15 16 17 18 19 20

Age

Gra

des

co

mp

lete

d

First pregnancy age 23+

First pregnancy at age 18

First pregnancy at age 17

First pregnancy at age 16

First pregnancy at age 15

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Conclusions from Analysis 3• A large proportion of the mean difference in

schooling disadvantage of teen mothers is accounted for by pre-existing covariates.

• There remain negative and statistically significant effects of teen births on educational attainment after controlling for observeable characteristics.

• Some evidence that there may be heterogeneity depending on actual age at first birth. Schooling often does continue after teen birth.