Although teenage mothers have lower educational attainment and earnings than women who delay fertility, causal interpretations of this relationship remain controversial. Scholars argue that there are reasons to predict negative, trivial, or even positive effects, and different methodological approaches provide some support for each perspective. We reconcile this ongoing debate by drawing on two heuristics: (1) each methodological strategy emphasizes different women in estimation procedures, and (2) the effects of teenage fertility likely vary in the population. Analyses of the Child and Young Adult Cohorts of the National Longitudinal Survey of Youth (N = 3,661) confirm that teen pregnancy has negative effects on most women’s attainment and earnings. More striking, however, is that effects on college completion and early earnings vary considerably and are most pronounced among those least likely to experience an early pregnancy. Further analyses suggest that teen pregnancy is particularly harmful for those with the brightest socioeconomic prospects and who are least prepared for the transition to motherhood.
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The predicted probability for teen pregnancy in the population in our data is slightly higher than reported national rates. One reason is that our sample is not nationally representative of young women: it is representative of the children born to the 1979 cohort of women. In other words, our respondents represent offspring born to younger women (and who may be more disadvantaged) than the average female.
In all analyses presented here, we employ an Epanechnikov kernel with asymptotically optimal constant bandwidths, the default in Stata using the lpoly function.
All but 1 of the 1,969 cases excluded from our analytic sample were too young (not yet 18) to have reported teen pregnancy data as of 2010. Depending on the outcome, 10 % to 20 % of cases were dropped because of missing outcome data, with the remainder being too young to have met the age cutoff. See our discussion of attrition and missing data.
When items are categorical, factor analyses are performed on polychoric correlation matrices, and those tapping multiple factors use promax rotation to allow constructs to be correlated. Further details are available on request.
We tested alternative specifications that included mothers’ desired number of children and expected number of children when surveyed in 1979. Because these measures do not predict whether daughters go on to experience a teen pregnancy, we dropped these indicators from our prediction model to improve efficiency.
We create 25 imputed data sets separately by whether the respondent reported being pregnant before 18.
Attrition weights are multiplied by the IPW weights in reweighting analyses.
We tested all two-way interactions and quadratic terms and retained those that approached statistical significance. We then added a squared term for the predicted logit as a covariate to capture residual nonlinearities. (See Table S1, Online Resource 1.)
Measures characterized with standardized differences exceeding .10 include self-worth, intellectual skills, risk aversion, delinquency, educational expectations, negative peer pressure, private school attendance, mother’s age at birth, mother’s expected age at marriage, family income, and maternal education.
See Tables S8–S10 in Online Resource 1 for additional sensitivity tests for both teen pregnancy and teen childbearing. Results are substantively similar across different treatment cutoff points.
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The authors would like to acknowledge the Ford Foundation (Diaz, Pre-doctoral Fellowship #CHK-7020411); the Institute of Education Sciences, U.S. Department of Education (Fiel, Award #R305B090009); and the National Science Foundation Graduate Research Fellowship (Fiel, Award #DGE-0718123). This research was partially supported by the Center of Demography and Ecology at the University of Wisconsin–Madison. We thank participants of the Inequality & Methods Workshop at the Minnesota Population Center for providing valuable feedback, as well as Jenna Nobles for comments on earlier drafts. The authors are solely responsible for all content.
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Diaz, C.J., Fiel, J.E. The Effect(s) of Teen Pregnancy: Reconciling Theory, Methods, and Findings. Demography 53, 85–116 (2016). https://doi.org/10.1007/s13524-015-0446-6
- Teenage childbearing
- Teenage pregnancy
- Effect heterogeneity
- Socioeconomic attainment