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Demography

, Volume 54, Issue 1, pp 71–91 | Cite as

Is the Association Between Education and Fertility Postponement Causal? The Role of Family Background Factors

  • Felix C. Tropf
  • Jornt J. Mandemakers
Article

Abstract

A large body of literature has demonstrated a positive relationship between education and age at first birth. However, this relationship may be partly spurious because of family background factors that cannot be controlled for in most research designs. We investigate the extent to which education is causally related to later age at first birth in a large sample of female twins from the United Kingdom (N = 2,752). We present novel estimates using within–identical twin and biometric models. Our findings show that one year of additional schooling is associated with about one-half year later age at first birth in ordinary least squares (OLS) models. This estimate reduced to only a 1.5-month later age at first birth for the within–identical twin model controlling for all shared family background factors (genetic and family environmental). Biometric analyses reveal that it is mainly influences of the family environment—not genetic factors—that cause spurious associations between education and age at first birth. Last, using data from the Office for National Statistics, we demonstrate that only 1.9 months of the 2.74 years of fertility postponement for birth cohorts 1944–1967 could be attributed to educational expansion based on these estimates. We conclude that the rise in educational attainment alone cannot explain differences in fertility timing between cohorts.

Keywords

Fertility postponement Education Fixed effects Twins United Kingdom 

Notes

Acknowledgments

The research leading to these results was funded by the Dutch Science Foundation (VIDI Innovation Grant 452-10-012 to M. Mills), the European Research Council (ERC) Consolidator Grant SOCIOGENOME (615603, www.sociogenome.com), and Economic & Social Research Council (ESRC) UK, National Centre for Research Methods (NCRM) SOCGEN grant (www.ncrm.ac.uk/research/SoCGEN/). The TwinsUK study was funded by the Wellcome Trust, European Community’s Seventh Framework Programme (FP7/2007-2013). The study also received support from the National Institute for Health Research (NIHR)–funded BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy’s and St. Thomas’ NHS Foundation Trust in partnership with King’s College London. The authors wish to express their gratitude to Hans-Peter Kohler and colleagues who generously provided their R-scripts to estimate the ACE-beta model. The authors gratefully acknowledge Tomas Sobotka for information and advice about data on age at first birth for the UK. We wish to thank Melinda Mills, Patrick Praeg, Tomas Sobotka, Renske Verweij, Nicola Barban, Cecilia Potente, Mariana Bonnouvrier, and Noah Carl for useful comments on earlier versions of the article. We wish to thank reviewers and editors, as well as all participants from the TwinsUK.

Supplementary material

13524_2016_531_MOESM1_ESM.pdf (201 kb)
ESM 1 (PDF 201 kb)

References

  1. Allison, P. D., & Christakis, N. (2006). Fixed-effects methods for the analysis of nonrepeated events. Sociological Methodology, 36, 155–172.CrossRefGoogle Scholar
  2. Amin, V., & Behrman, J. R. (2014). Do more-schooled women have fewer children and delay childbearing? Evidence from a sample of US twins. Journal of Population Economics, 27, 1–31.CrossRefGoogle Scholar
  3. Amin, V., Behrman, J. R., Kohler, H.-P., Xiong, Y., & Zhang, J. (2015). Causal inferences: Identical twins help and clarity about necessary assumptions is critical. Social Science & Medicine, 127, 201–202.CrossRefGoogle Scholar
  4. Amin, V., Behrman, J. R., & Spector, T. D. (2013). Does more schooling improve health outcomes and health related behaviors? Evidence from UK twins. Economics of Education Review, 35, 134–148.CrossRefGoogle Scholar
  5. Andersson, G. (2000). The impact of labour-force participation on childbearing behaviour: Pro-cyclical fertility in Sweden during the 1980s and the 1990s. European Journal of Population, 16, 293–333.CrossRefGoogle Scholar
  6. Andrew, T., Hart, D. J., Snieder, H., de Lange, M., Spector, T. D., & MacGregor, A. J. (2001). Are twins and singletons comparable? A study of disease-related and lifestyle characteristics in adult women. Twin Research: The Official Journal of the International Society for Twin Studies, 4, 464–477.CrossRefGoogle Scholar
  7. Balbo, N., & Barban, N. (2014). Does fertility behavior spread among friends? American Sociological Review, 79, 412–431.CrossRefGoogle Scholar
  8. Balbo, N., Billari, F. C., & Mills, M. C. (2013). Fertility in advanced societies: A review of research. European Journal of Population/Revue Européenne de Démographie, 29, 1–38.CrossRefGoogle Scholar
  9. Barban, N., Jansen, R., Vlaming, R., Vaez, A., Mandemakers, J. J., Tropf, F. C., & Mills, M. C. (2016). Genome-wide analysis identifies 12 loci influencing human reproductive behavior. Nature Genetics. doi: 10.1038/ng.3698 Google Scholar
  10. Billari, F. (2015). Integrating macro-and micro-level approaches in the explanation of population change. Population Studies, 69, S11–S20.CrossRefGoogle Scholar
  11. Boardman, J. D., & Fletcher, J. M. (2015). To cause or not to cause? That is the question, but identical twins might not have all of the answers. Social Science & Medicine, 127, 198–200.CrossRefGoogle Scholar
  12. Branigan, A. R., McCallum, K. J., & Freese, J. (2013). Variation in the heritability of educational attainment: An international meta-analysis. Social Forces, 92, 109–140.CrossRefGoogle Scholar
  13. Byars, S. G., Ewbank, D., Govindaraju, D. R., & Stearns, S. C. (2010). Natural selection in a contemporary human population. Proceedings of the National Academy of Sciences, 107, 1787–1792.CrossRefGoogle Scholar
  14. Conley, D., Rauscher, E., Dawes, C., Magnusson, P. K. E., & Siegal, M. L. (2013). Heritability and the equal environments assumption: Evidence from multiple samples and misclassified twins. Behavior Genetics, 43, 415–426.CrossRefGoogle Scholar
  15. Courtiol, A., Tropf, F. C., & Mills, M. C. (2016). When genes and environment disagree: Making sense of trends in recent human evolution. Proceedings of the National Academy of Sciences, 113, 7693–7695.CrossRefGoogle Scholar
  16. Domingue, B. W., Fletcher, J., Conley, D., & Boardman, J. D. (2014). Genetic and educational assortative mating among US adults. Proceedings of the National Academy of Sciences, 111, 7996–8000.CrossRefGoogle Scholar
  17. D’Onofrio, B. M., Lahey, B. B., Turkheimer, E., & Lichtenstein, P. (2013). Critical need for family-based, quasi-experimental designs in integrating genetic and social science research. American Journal of Public Health, 103, S46–S55.CrossRefGoogle Scholar
  18. Felson, J. (2014). What can we learn from twin studies? A comprehensive evaluation of the equal environments assumption. Social Science Research, 43, 184–199.CrossRefGoogle Scholar
  19. Freese, J. (2008). Genetics and the social science explanation of individual outcomes. American Journal of Sociology, 114, S1–S35.CrossRefGoogle Scholar
  20. Gustafsson, S., Kenjoh, E., & Wetzels, C. (2002). The role of education on postponement of maternity in Britain, Germany, the Netherlands and Sweden. In E. Ruspini & A. Dale (Eds.), The gender dimension of social change: The contribution of dynamic research to the study of women’s life courses (pp. 55–79). Bristol, UK: Policy Press.CrossRefGoogle Scholar
  21. Hobcraft, J. (1996). Fertility in England and Wales: A fifty-year perspective. Population Studies, 50, 485–524.CrossRefGoogle Scholar
  22. Hoem, B. (2000). Entry into motherhood in Sweden: The influence of economic factors on the rise and fall in fertility. Demographic Research, 2(article 4), 1986–1997. doi: 10.4054/DemRes.2000.2.4 Google Scholar
  23. Horwitz, A. V., Videon, T. M., Schmitz, M. F., & Davis, D. (2003). Rethinking twins and environments: Possible social sources for assumed genetic influences in twin research. Journal of Health and Social Behavior, 44, 111–129.CrossRefGoogle Scholar
  24. Jenkins, A., & Sabates, R. (2007). The classification of qualifications in social surveys (CLS Cohort Studies Working Paper No. 2007/2). London, UK: Centre for Longitudinal Studies.Google Scholar
  25. Joshi, H. (2002). Production, reproduction, and education: Women, children, and work in a British perspective. Population and Development Review, 28, 445–474.CrossRefGoogle Scholar
  26. Kirk, K. M., Blomberg, S. P., Duffy, D. L., Heath, A. C., Owens, I. P. F., & Martin, N. G. (2001). Natural selection and quantitative genetics of life-history traits in Western women: A twin study. Evolution, 55, 423–435.CrossRefGoogle Scholar
  27. Kohler, H.-P., Behrman, J. R., & Schnittker, J. (2011). Social science methods for twins data: Integrating causality, endowments, and heritability. Biodemography and Social Biology, 57, 88–141.CrossRefGoogle Scholar
  28. Kohler, H.-P., & Rodgers, J. L. (2003). Education, fertility and heritability: Explaining a paradox. In R. A. Bulatao & K. W. Wachter (Eds.), Offspring: Human fertility behavior in biodemographic perspective (pp. 46–90). Washington, DC: National Academies Press.Google Scholar
  29. Kohler, H.-P., Rodgers, J. L., & Christensen, K. (1999). Is fertility behavior in our genes? Findings from a Danish twin study. Population and Development Review, 25, 253–288.CrossRefGoogle Scholar
  30. Kohler, H.-P., Rodgers, J. L., Miller, W. B., Skytthe, A., & Christensen, K. (2006). Bio-social determinants of fertility. International Journal of Andrology, 29, 46–53.CrossRefGoogle Scholar
  31. Lappegård, T., & Rønsen, M. (2005). The multifaceted impact of education on entry into motherhood. European Journal of Population/Revue Européenne de Démographie, 21, 31–49.CrossRefGoogle Scholar
  32. Lesthaeghe, R. (1995). The second demographic transition in Western countries: An interpretation. In K. O. Mason & A.-M. Jensen (Eds.), Gender and family change in industrialized countries (pp. 17–62). Oxford, UK: Clarendon Press.Google Scholar
  33. Liefbroer, A., & Corijn, M. (1999). Who, what, where, and when? Specifying the impact of educational attainment and labour force participation on family formation. European Journal of Population/Revue Européenne de Démographie, 15, 45–75.CrossRefGoogle Scholar
  34. Loehlin, J. C. (1996). The Cholesky approach: A cautionary note. Behavior Genetics, 26, 65–69.CrossRefGoogle Scholar
  35. Lutz, W., Butz, W., & KC, S. (2014). World population and human capital in the twenty-first century. Oxford, UK: Oxford University Press.CrossRefGoogle Scholar
  36. Lyngstad, T. H., & Prskawetz, A. (2010). Do siblings’ fertility decisions influence each other? Demography, 47, 923–934.CrossRefGoogle Scholar
  37. Marini, M. M. (1985). Determinants of the timing of adult role entry. Social Science Research, 14, 309–350.CrossRefGoogle Scholar
  38. Martin, S. P. (2000). Diverging fertility among U.S. women who delay childbearing past age 30. Demography, 37, 523–533.CrossRefGoogle Scholar
  39. McCrary, J., & Royer, H. (2011). The effect of female education on fertility and infant health: Evidence from school entry policies using exact date of birth. American Economic Review, 101, 158–195.CrossRefGoogle Scholar
  40. Miller, W. B., Bard, D. E., Pasta, D. J., & Rodgers, J. L. (2010). Biodemographic modeling of the links between fertility motivation and fertility outcomes in the NLSY79. Demography, 47, 393–414.CrossRefGoogle Scholar
  41. Mills, M. C., Rindfuss, R. R., McDonald, P., & te Velde, E. (2011). Why do people postpone parenthood? Reasons and social policy incentives. Human Reproduction Update, 17, 848–860.CrossRefGoogle Scholar
  42. Mills, M. C., & Tropf, F. C. (2015). The biodemography of fertility: A review and future research frontiers. Kölner Zeitschrift für Soziologie und Sozialpsychologie, 67, 397–424.CrossRefGoogle Scholar
  43. Moayyeri, A., Hammond, C., & Spector, T. D. (2013). Cohort profile: TwinsUK and healthy ageing twin study. International Journal of Epidemiology, 42, 76–85.CrossRefGoogle Scholar
  44. Murphy, M. (1993). The contraceptive pill and women’s employment as factors in fertility change in Britain 1963–1980: A challenge to the conventional view. Population Studies, 47, 221–243.CrossRefGoogle Scholar
  45. Murphy, M. (1999). Is the relationship between fertility of parents and children really weak? Biodemography and Social Biology, 46, 122–145.CrossRefGoogle Scholar
  46. Neale, M. C., & Cardon, L. R. (1992). Methodology for genetic studies of twins and families. Dordrecht, The Netherlands: Kluwer Academic Publishers.Google Scholar
  47. Neiss, M., Rowe, D. C., & Rodgers, J. L. (2002). Does education mediate the relationship between IQ and age of first birth? A behavioural genetic analysis. Journal of Biosocial Science, 34, 259–276.CrossRefGoogle Scholar
  48. Ní Bhrolcháin, M., & Beaujouan, É. (2012). Fertility postponement is largely due to rising educational enrolment. Population Studies, 66, 311–327.CrossRefGoogle Scholar
  49. Nisén, J., Martikainen, P., Kaprio, J., & Silventoinen, K. (2013). Educational differences in completed fertility: A behavioral genetic study of Finnish male and female twins. Demography, 50, 1–22.CrossRefGoogle Scholar
  50. Nisén, J., & Myrskylä, M. (2014). Effect of family background on the educational gradient in lifetime fertility of Finnish women born 1940–50. Population Studies, 68, 321–337.CrossRefGoogle Scholar
  51. Office National Statistics. (2013). Cohort fertility, Table 2 [Data set]. Retrieved from http://www.ons.gov.uk/ons/publications/re-reference-tables.html?edition=tcm:77-263133
  52. Oreopoulos, P. (2006). Estimating average and local average treatment effects of education when compulsory schooling laws really matter. American Economic Review, 96, 152–175.CrossRefGoogle Scholar
  53. Rendall, M. S., Couet, C., Lappegard, T., Robert-Bobée, I., Rønsen, M., & Smallwood, S. (2005). First births by age and education in Britain, France and Norway. Population Trends, 121, 27–34.Google Scholar
  54. Rietveld, C. A., Medland, S. E., Derringer, J., Yang, J., Esko, T., Martin, N. W., & Koellinger, P. D. (2013). GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science, 340, 1467–1471.CrossRefGoogle Scholar
  55. Rijken, A. J., & Liefbroer, A. C. (2009). Influences of the family of origin on the timing and quantum of fertility in the Netherlands. Population Studies, 63, 71–85.CrossRefGoogle Scholar
  56. Rindfuss, R. R., Guilkey, D., Morgan, S. P., Kravdal, O., & Guzzo, K. B. (2007). Child care availability and first-birth timing in Norway. Demography, 44, 345–372.CrossRefGoogle Scholar
  57. Rodgers, J. L., Bard, D. E., & Miller, W. B. (2007). Multivariate Cholesky models of human female fertility patterns in the NLSY. Behavior Genetics, 37, 345–361.CrossRefGoogle Scholar
  58. Rodgers, J. L., Kohler, H.-P., Kyvik, K. O., & Christensen, K. (2001). Behavior genetic modeling of human fertility: Findings from a contemporary Danish twin study. Demography, 38, 29–42.CrossRefGoogle Scholar
  59. Rodgers, J. L., Kohler, H.-P., McGue, M., Behrman, J. R., Petersen, I., Bingley, P., & Christensen, K. (2008). Education and cognitive ability as direct, mediating, or spurious influences on female age at first birth: Behavior genetic models fit to Danish twin data. American Journal of Sociology, 114, S202–S232.CrossRefGoogle Scholar
  60. Rosenzweig, M. R., & Wolpin, K. I. (1980). Testing the quantity-quality fertility model: The use of twins as a natural experiment. Econometrica, 48, 227–240.CrossRefGoogle Scholar
  61. Scott, J. (2004). Family, gender, and educational attainment in Britain: A longitudinal study. Journal of Comparative Family Studies, 35, 565–589.Google Scholar
  62. Skirbekk, V., Kohler, H. P., & Prskawetz, A. (2006). The marginal effect of school leaving age on demographic events. A contribution to the discussion on causality. In S. Gustafsson & A. Kalwij (Eds.), Education and postponement of maternity: Economic analyses for industrialized countries (pp. 65–85). Dordrecht, The Netherlands: Kluwer Academic Publishers.CrossRefGoogle Scholar
  63. Thornton, A. (1980). The influence of first generation fertility and economic status on second generation fertility. Population and Environment, 3, 51–72.CrossRefGoogle Scholar
  64. Tropf, F. C., Barban, N., Mills, M. C., Snieder, H., & Mandemakers, J. J. (2015a). Genetic influence on age at first birth of female twins born in the UK, 1919–68. Population Studies, 69, 129–145.CrossRefGoogle Scholar
  65. Tropf, F. C., Stulp, G., Barban, N., Visscher, P., Yang, J., Snieder, H., & Mills, M. C. (2015b). Human fertility, molecular genetics, and natural selection in modern societies. PloS One, 10(6), e0126821. doi: 10.1371/journal.pone.0126821 CrossRefGoogle Scholar
  66. Tropf, F. C., Verweij, R. M., van der Most, P. J., Stulp, G., Bakshi, A., Briley, D. A., . . . Mills, M. C. (2016). Mega-analysis of 31,396 individuals from 6 countries uncovers strong gene-environment interaction for human fertility. Unpublished manuscript. doi: 10.1101/049163
  67. van de Kaa, D. J. (1987). Europe’s second demographic transition. Population Bulletin, 42, 1–59.Google Scholar
  68. van Doorn, M., Pop, I., & Wolbers, M. H. J. (2011). Intergenerational transmission of education across European countries and cohorts. European Societies, 13, 93–117.CrossRefGoogle Scholar

Copyright information

© Population Association of America 2016

Authors and Affiliations

  1. 1.Department of Sociology/Nuffield CollegeUniversity of OxfordOxfordUK
  2. 2.University of Groningen/ICSGroningenThe Netherlands
  3. 3.Department of Social SciencesWageningen UniversityWageningenThe Netherlands

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