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Demography

, Volume 55, Issue 2, pp 643–668 | Cite as

Early Childbearing, School Attainment, and Cognitive Skills: Evidence From Madagascar

  • Catalina Herrera Almanza
  • David E. Sahn
Article

Abstract

Female secondary school attendance has recently increased in sub-Saharan Africa, and so has the risk of becoming pregnant while attending school. We analyze the impact of teenage pregnancy on young women’s human capital using longitudinal data in Madagascar that capture the transition from adolescence to adulthood for a cohort aged 21–24 in 2012, first interviewed in 2004. We find that early childbearing increases the likelihood of dropping out of school and decreases the chances of completing secondary school. This pregnancy-related school dropout also has a detrimental impact on standardized test scores in math and French. We instrument early pregnancy with the young woman’s community-level access and her exposure to condoms since age 15 after controlling for pre-fertility socioeconomic conditions. Our results are robust to different specifications that address potential endogeneity of program placement and instrument validity.

Keywords

Early childbearing Female education Cognitive skills Family planning Madagascar 

Notes

Acknowledgments

The authors thank Günther Fink, George Jakubson, Ravi Kanbur, David Lam, Paul Schultz, anonymous reviewers and seminar participants at the 2013 Cornell Economics Seminar, the 2013 Population Association of America Conference, the 2013 Northeast Universities Development Consortium Conference-NEUDC, the 2014 Population and Reproductive Health Conference, and the 2015 Harvard Population Center seminar series for helpful comments and discussions. This study was funded by the IZA/DFID GLM | LIC Program under Grant Agreement GA-C1-RA4-067. This document is an output from a project funded by the UK Department for International Development (DFID) and the Institute for the Study of Labor (IZA) for the benefit of developing countries. The views expressed are not necessarily those of DFID or IZA. Herrera is very grateful for the support from the Hewlett Foundation/(IIE) Doctoral Dissertation Fellowship. The authors declare that they have no conflict of interest. Any errors are solely the responsibility of the authors.

Supplementary material

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References

  1. Angeles, G., Guilkey, D. K., & Mroz, T. A. (1998). Purposive program placement and the estimation of family planning program effects in Tanzania. Journal of the American Statistical Association, 93, 884–899.CrossRefGoogle Scholar
  2. Angeles, G., Guilkey, D. K., & Mroz, T. A. (2005). The determinants of fertility in rural Peru: Program effects in the early years of the National Family Planning Program. Journal of Population Economics, 18, 367–389.CrossRefGoogle Scholar
  3. Angrist, J. D., & Pischke, J. S. (2009). Mostly harmless econometrics: An empiricist’s companion. Princeton, NJ: Princeton University Press.Google Scholar
  4. Arceo-Gomez, E. O., & Campos-Vazquez, R. M. (2014). Teenage pregnancy in Mexico: Evolution and consequences. Latin American Journal of Economics, 51, 109–146.CrossRefGoogle Scholar
  5. Ardington, C., Menendez, A., & Mutevedzi, T. (2015). Early childbearing, human capital attainment and mortality risk: Evidence from a longitudinal demographic surveillance area in rural KwaZulu-Natal, South Africa. Economic Development and Cultural Change, 63, 281–317.CrossRefGoogle Scholar
  6. Ashcraft, A., Fernández-Val, I., & Lang, K. (2013). The consequences of teenage childbearing: Consistent estimates when abortion makes miscarriage non-random. Economic Journal, 123, 875–905.CrossRefGoogle Scholar
  7. Ashcraft, A., & Lang, K. (2006). The consequences of teenage childbearing (NBER Working Paper No. 12485). Cambridge, MA: National Bureau of Economic Research.CrossRefGoogle Scholar
  8. Azevedo, J. P., Lopez-Calva, L. F., & Perova, E. (2012). Is the baby to blame? An inquiry into the consequences of early childbearing (World Bank Policy Research Working Paper No. 6074). Washington, DC: World Bank Group.Google Scholar
  9. Baird, S., McIntosh, C., & Özler, B. (2011). Cash or condition? Evidence from a cash transfer experiment. Quarterly Journal of Economics, 126, 1709–1753.CrossRefGoogle Scholar
  10. Bandiera, O., Buehren, N., Burgess, R., Goldstein, M., Gulesci, S., Rasul, I., & Sulaiman, M. (2015). Women’s empowerment in action: Evidence from a randomized control trial in Africa. Retrieved from https://www.povertyactionlab.org/sites/default/files/publications/111%20Womens%20Empowerment%20June%202015.pdf
  11. Behrman, J. R., Murphy, A., Quisumbing, A. R., & Yount, K. M. (2009). Are returns to mothers’ human capital realized in the next generation? The impact of mothers’ intellectual human capital and long-run nutritional status on children’s human capital in Guatemala (IFPRI Discussion Paper No. 850). Washington, DC: International Food Policy Research Institute.Google Scholar
  12. Bongaarts, J. (1994). The impact of population policies: Comment. Population and Development Review, 20, 616–620.CrossRefGoogle Scholar
  13. Branson, N., & Byker, T. (2018). Causes and consequences of teen childbearing: Evidence from a reproductive health intervention in South Africa. Journal of Health Economics, 57, 221–235.CrossRefGoogle Scholar
  14. Breierova, L., & Duflo, E. (2004). The impact of education on fertility and child mortality: Do fathers really matter less than mothers? (NBER Working Paper No. 10513). Cambridge, MA: National Bureau of Economic Research.CrossRefGoogle Scholar
  15. Buckles, K. S., & Hungerman, D. M. (2016). The incidental fertility effects of school condom distribution programs (NBER Working Paper No. w22322). Cambridge, MA: National Bureau of Economic Research.Google Scholar
  16. Canning, D., & Schultz, T. P. (2012). The economic consequences of reproductive health and family planning. Lancet, 380, 165–171.CrossRefGoogle Scholar
  17. Chandra-Mouli, V., McCarraher, D. R., Phillips, S. J., Williamson, N. E., & Hainsworth, G. (2014). Contraception for adolescents in low and middle income countries: Needs, barriers, and access. Reproductive Health, 11.  https://doi.org/10.1186/1742-4755-11-1
  18. Chong, A., Gonzalez-Navarro, M., Karlan, D., & Valdivia, M. (2013). Effectiveness and spillovers of online sex education: Evidence from a randomized evaluation in Colombian public schools (NBER Working Paper No. w18776). Cambridge, MA: National Bureau of Economic Research.Google Scholar
  19. Conley, T. G., Hansen, C. B., & Rossi, P. E. (2012). Plausibly exogenous. Review of Economics and Statistics, 94, 260–272.CrossRefGoogle Scholar
  20. Diaz, C. J., & Fiel, J. E. (2016). The effect(s) of teen pregnancy: Reconciling theory, methods, and findings. Demography, 53, 85–116.CrossRefGoogle Scholar
  21. Duflo, E., Dupas, P., & Kremer, M. (2015). Education, HIV, and early fertility: Experimental evidence from Kenya. American Economic Review, 105, 2757–2797.CrossRefGoogle Scholar
  22. Dupas, P. (2011). Do teenagers respond to HIV risk information? Evidence from a field experiment in Kenya. American Economic Journal: Applied Economics, 3(1), 1–34.Google Scholar
  23. Field, E., & Ambrus, A. (2008). Early marriage, age of menarche, and female schooling attainment in Bangladesh. Journal of Political Economy, 116, 881–930.CrossRefGoogle Scholar
  24. Fletcher, J. M., & Wolfe, B. L. (2009). Education and labor market consequences of teenage childbearing evidence using the timing of pregnancy outcomes and community fixed effects. Journal of Human Resources, 44, 303–325.CrossRefGoogle Scholar
  25. Free, C., Roberts, I. G., Abramsky, T., Fitzgerald, M., & Wensley, F. (2011). A systematic review of randomised controlled trials of interventions promoting effective condom use. Journal of Epidemiology & Community Health, 65, 100–110.CrossRefGoogle Scholar
  26. Friedman, W. (2015, May). Antiretroviral drug access and behavior change. Paper presented at the 7th Annual Meeting on the Economics of Risky Behaviors, Balçova, İzmir, Turkey.Google Scholar
  27. Geronimus, A. T., & Korenman, S. (1992). The socioeconomic consequences of teen childbearing reconsidered. Quarterly Journal of Economics, 107, 1187–1214.CrossRefGoogle Scholar
  28. Glick, P., Randriamamonjy, J., & Sahn, D. E. (2009). Determinants of HIV knowledge and condom use among women in Madagascar: An analysis using matched household and community data. African Development Review, 21, 147–179.CrossRefGoogle Scholar
  29. Glick, P., Randrianarisoa, J. C., & Sahn, D. E. (2011). Family background, school characteristics, and children’s cognitive achievement in Madagascar. Education Economics, 19, 363–396.CrossRefGoogle Scholar
  30. Glick, P. J., Sahn, D. E., & Walker, T. F. (2016). Household shocks and education investments in Madagascar. Oxford Bulletin of Economics and Statistics, 78, 792–813.CrossRefGoogle Scholar
  31. Grant, M. J., & Hallman, K. K. (2008). Pregnancy-related school dropout and prior school performance in KwaZulu-Natal, South Africa. Studies in Family Planning, 39, 369–382.CrossRefGoogle Scholar
  32. Güneş, P. M. (2015). The role of maternal education in child health: Evidence from a compulsory schooling law. Economics of Education Review, 47, 1–16.CrossRefGoogle Scholar
  33. Hotz, V. J., McElroy, S. W., & Sanders, S. G. (2005). Teenage childbearing and its life cycle consequences exploiting a natural experiment. Journal of Human Resources, 40, 683–715.CrossRefGoogle Scholar
  34. Imbens, G. W., & Angrist, J. D. (1994). Identification and estimation of local average treatment effects. Econometrica, 62, 467–475.CrossRefGoogle Scholar
  35. Institut National de la Statistique (INSTAT), & ICF Macro. (2010). Demographic and Health Surveys of Madagascar: 2008–2009. Antananarivo, Madagascar: INSTAT and ICF Macro. Retrieved from http://dhsprogram.com/pubs/pdf/FR236/FR236.pdf Google Scholar
  36. Joshi, S., & Schultz, T. P. (2013). Family planning and women’s and children’s health: Long-term consequences of an outreach program in Matlab, Bangladesh. Demography, 50, 149–180.CrossRefGoogle Scholar
  37. Kane, J. B., Morgan, S. P., Harris, K. M., & Guilkey, D. K. (2013). The educational consequences of teen childbearing. Demography, 50, 2129–2150.CrossRefGoogle Scholar
  38. Klepinger, D., Lundberg, S., & Plotnick, R. (1999). How does adolescent fertility affect the human capital and wages of young women? Journal of Human Resources, 34, 421–448.CrossRefGoogle Scholar
  39. Lee, D. (2010). The early socioeconomic effects of teenage childbearing: A propensity score matching approach. Demographic Research, 23(article 25), 697–736.  https://doi.org/10.4054/DemRes.2010.23.25 CrossRefGoogle Scholar
  40. Levine, D. I., & Painter, G. (2003). The schooling costs of teenage out-of-wedlock childbearing: Analysis with a within-school propensity-score-matching estimator. Review of Economics and Statistics, 85, 884–900.CrossRefGoogle Scholar
  41. Lloyd, C. B., & Mensch, B. S. (2008). Marriage and childbirth as factors in dropping out from school: An analysis of DHS data from sub-Saharan Africa. Population Studies, 62, 1–13.CrossRefGoogle Scholar
  42. Marteleto, L., Lam, D., & Ranchhod, V. (2008). Sexual behavior, pregnancy, and schooling among young people in urban South Africa. Studies in Family Planning, 39, 351–368.CrossRefGoogle Scholar
  43. McQueston, K., Silverman, R., & Glassman, A. (2013). The efficacy of interventions to reduce adolescent childbearing in low- and middle-income countries: A systematic review. Studies in Family Planning, 44, 369–388.CrossRefGoogle Scholar
  44. Meekers, D., Agha, S., & Klein, M. (2005). The impact on condom use of the “100% Jeune” social marketing program in Cameroon. Journal of Adolescent Health, 36, 529–530.Google Scholar
  45. Meekers, D., Silva, M., & Klein, M. (2006). Determinants of condom use among youth in Madagascar. Journal of Biosocial Science, 38, 365–380.Google Scholar
  46. Miller, G. (2010). Contraception as development? New evidence from family planning in Colombia. Economic Journal, 120, 709–736.CrossRefGoogle Scholar
  47. Miller, G., & Babiarz, K. S. (2016). Family planning program effects: Evidence from Microdata. Population and Development Review, 42, 7–26.CrossRefGoogle Scholar
  48. Mmari, K., & Sabherwal, S. (2013). A review of risk and protective factors for adolescent sexual and reproductive health in developing countries: An update. Journal of Adolescent Health, 53, 562–572.CrossRefGoogle Scholar
  49. Molyneaux, J. W., & Gertler, P. J. (2000). The impact of targeted family planning programs in Indonesia. Population and Development Review, 26(Suppl.), 61–85.Google Scholar
  50. Ozier, O. (2018). The impact of secondary schooling in Kenya: A regression discontinuity analysis. Journal of Human Resources, 53, 157–188.CrossRefGoogle Scholar
  51. Paton, D. (2002). The economics of family planning and underage conceptions. Journal of Health Economics, 21, 207–225.CrossRefGoogle Scholar
  52. Pinchoff, J., Boyer, C. B., Mutombo, N., Chowdhuri, R. N., & Ngo, T. D. (2017). Why don’t urban youth in Zambia use condoms? The influence of gender and marriage on non-use of male condoms among young adults. PLoS One, 12(3).  https://doi.org/10.1371/journal.pone.0172062
  53. Pitt, M. M., Rosenzweig, M. R., & Gibbons, D. M. (1993). The determinants and consequences of the placement of government programs in Indonesia. World Bank Economic Review, 7, 319–348.CrossRefGoogle Scholar
  54. Pörtner, C. C., Beegle, K., & Christiaensen, L. (2011). Family planning and fertility: Estimating program effects using cross-sectional data (World Bank Policy Research Working Paper No. WPS5812). Washington, DC: World Bank Group.Google Scholar
  55. Pritchett, L. H. (1994). Desired fertility and the impact of population policies. Population and Development Review, 20, 1–55.CrossRefGoogle Scholar
  56. Raharinjatovo, J. A. (2014). Madagascar (2008): Family planning TRaC study evaluating the condom use and pill use as contraceptive methods among young females 15–24 years—Round three (PSI TRAC Summary report). Washington, DC: Population Services International.  https://doi.org/10.7910/DVN/27620
  57. Ranchhod, V., Lam, D., Leibbrandt, M., & Marteleto, L. (2011, January). Estimating the effect of adolescent fertility on educational attainment in Cape Town using a propensity score weighted regression. Paper presented at the fifth annual PopPov Conference on Population, Reproductive Health, and Economic Development, Marseille, France.Google Scholar
  58. Ribar, D. C. (1994). Teenage fertility and high school completion. Review of Economics and Statistics, 76, 413–424.CrossRefGoogle Scholar
  59. Rindfuss, R. R., Bumpass, L., & St. John, C. (1980). Education and fertility: Implications for the roles women occupy. American Sociological Review, 45, 431–447.CrossRefGoogle Scholar
  60. Schultz, T. P. (2007). Population policies, fertility, women’s human capital, and child quality. Handbook of Development Economics, 4, 3249–3303.CrossRefGoogle Scholar
  61. Sharp, M., & Kruse, I. (2011). Health, nutrition, and population in Madagascar, 2000–09 (World Bank Working Paper No. 216). Washington, DC: World Bank Publications.Google Scholar
  62. Staiger, D., & Stock, J. (1997). Instrumental variables regression with weak instruments. Econometrica, 65, 557–586.CrossRefGoogle Scholar
  63. Stock, J. H., & Watson, M. W. (2007). Introduction to econometrics (2nd ed.). London, UK: Pearson.Google Scholar
  64. Strauss, J., & Thomas, D. (1995). Human resources: Empirical modeling of household and family decisions. Handbook of Development Economics, 3, 1883–2023.CrossRefGoogle Scholar
  65. Strauss, J., & Thomas, D. (2007). Health over the life course. In T. P. Schultz & J. Strauss (Eds.), Handbook of development economics (pp. 3375–3474). Amsterdam, the Netherlands: Elsevier.Google Scholar
  66. Sweat, M. D., Denison, J., Kennedy, C., Tedrow, V., & O’Reilly, K. (2012). Effects of condom social marketing on condom use in developing countries: A systematic review and meta-analysis, 1990–2010. Bulletin of the World Health Organization, 90, 613–622A. CrossRefGoogle Scholar
  67. Thomas, D. (1999). Fertility, education and resources in South Africa. In C. H. Bledsoe, J. B. Casterline, J. A. Johnson-Kuhn, & J. G. Haaga (Eds.), Critical perspectives on schooling and fertility in the developing world (pp. 138–180). Washington, DC: National Academy Press.Google Scholar
  68. Todd, P. E., & Wolpin, K. I. (2003). On the specification and estimation of the production function for cognitive achievement. Economic Journal, 113(485), F3–F33.Google Scholar
  69. United Nations Economic Commission for Africa. (2009). African women’s report: Measuring gender inequality in Africa: Experiences and lessons from the African Gender and Development Index. Addis Ababa, Ethiopia: United Nations Economic Commission for Africa. Retrieved from https://www.uneca.org/sites/default/files/PublicationFiles/awr09_fin.pdf Google Scholar
  70. Urdinola, B. P., & Ospino, C. G. (2015). Long-term consequences of adolescent fertility: The Colombian case. Demographic Research, 32(article 55), 487–1518.  https://doi.org/10.4054/DemRes.2015.32.55 Google Scholar
  71. Williamson, N. E. (2013). Motherhood in childhood: Facing the challenge of adolescent pregnancy. New York, NY: Information and External Relations Division of the United Nations Population Fund.Google Scholar
  72. World Bank. (2013). World Development Indicators. Retrieved from http://data.worldbank.org/data-catalog/world-development-indicators
  73. World Health Organization (WHO). (2011). WHO guidelines on preventing early pregnancy and poor reproductive outcomes among adolescents in developing countries. Geneva, Switzerland: WHO. Retrieved from http://apps.who.int/iris/bitstream/10665/44691/1/9789241502214_eng.pdf Google Scholar

Copyright information

© Population Association of America 2018

Authors and Affiliations

  1. 1.Department of Economics and International Affairs ProgramNortheastern UniversityBostonUSA
  2. 2.Department of Economics and Division of Nutritional SciencesCornell UniversityIthacaUSA
  3. 3.Institute for the Study of Labor (IZA)BonnGermany

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