, Volume 50, Issue 6, pp 2129–2150 | Cite as

The Educational Consequences of Teen Childbearing

  • Jennifer B. KaneEmail author
  • S. Philip Morgan
  • Kathleen Mullan Harris
  • David K. Guilkey


A huge literature shows that teen mothers face a variety of detriments across the life course, including truncated educational attainment. To what extent is this association causal? The estimated effects of teen motherhood on schooling vary widely, ranging from no discernible difference to 2.6 fewer years among teen mothers. The magnitude of educational consequences is therefore uncertain, despite voluminous policy and prevention efforts that rest on the assumption of a negative and presumably causal effect. This study adjudicates between two potential sources of inconsistency in the literature—methodological differences or cohort differences—by using a single, high-quality data source: namely, The National Longitudinal Study of Adolescent Health. We replicate analyses across four different statistical strategies: ordinary least squares regression; propensity score matching; and parametric and semiparametric maximum likelihood estimation. Results demonstrate educational consequences of teen childbearing, with estimated effects between 0.7 and 1.9 fewer years of schooling among teen mothers. We select our preferred estimate (0.7), derived from semiparametric maximum likelihood estimation, on the basis of weighing the strengths and limitations of each approach. Based on the range of estimated effects observed in our study, we speculate that variable statistical methods are the likely source of inconsistency in the past. We conclude by discussing implications for future research and policy, and recommend that future studies employ a similar multimethod approach to evaluate findings.


Teen childbearing Educational attainment Semiparametric maximum likelihood Propensity score matching Add Health 



Kane is the corresponding author; she carried out most of the statistical analysis and wrote the first draft of this article. She was also responsible for coordinating input from coauthors on subsequent drafts. This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website ( This research received support from the Population Research Training grant (T32 HD007168) and the Population Research Infrastructure Program (R24 HD050924) awarded to the Carolina Population Center at The University of North Carolina at Chapel Hill by the Eunice Kennedy Shriver National Institute of Child Health and Human Development. Opinions reflect those of the authors and not necessarily those of the granting agencies. An earlier version of this article was presented at the 2012 meeting of the American Sociological Association in Denver, CO. The authors wish to thank Jason Fletcher, Ron Rindfuss, Duncan Thomas, and participants of the 2012 Duke-UNC Demography Daze Symposium for providing helpful comments.

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Copyright information

© Population Association of America 2013

Authors and Affiliations

  • Jennifer B. Kane
    • 1
    Email author
  • S. Philip Morgan
    • 2
  • Kathleen Mullan Harris
    • 2
  • David K. Guilkey
    • 3
  1. 1.Carolina Population CenterUniversity of North Carolina at Chapel HillChapel HillUSA
  2. 2.Department of Sociology and Carolina Population CenterUniversity of North Carolina at Chapel HillChapel HillUSA
  3. 3.Department of Economics and Carolina Population CenterUniversity of North Carolina at Chapel HillChapel HillUSA

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