Skip to main content

Advertisement

SpringerLink
Log in

The effect of children on male earnings and inequality

  • Published:
Review of Economics of the Household Aims and scope Submit manuscript

Abstract

This study investigates the effect of children on male earnings and how earnings inequality among men arises over the life cycle. We use panel register data on earnings and fertility for sibling brothers and twins, and present estimates from flexible earnings regressions. We find that OLS estimates are confounded by selection effects through family fixed factors. The comparison of twin brothers shows that overall earnings growth does not vary between those who ever become fathers and those remaining childless, and there is no significant effect of children on earnings. We also show that controls for marriage explain only a relatively small part of the effect of children. Men who remain childless and unmarried are on relatively low earnings profiles and therefore contribute significantly to the earnings inequality among men.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. Ludwig and Brüderl (2018) have found positive selection into marriage as a driver of the marriage premium.

  2. In addition, siblings and twins are genetically more similar which may make them also in terms of ability more similar.

  3. For a detailed discussion, see Field et al. (2016).

  4. Studies on the marriage premium such as Antonovics and Town (2004) and Krashinsky (2004) have relied on much smaller samples.

  5. One my hypothesize that in a country with high income equality, free education and low gender differences in the labor market, the expected raw fatherhood premium is small but also that there is relatively little role for family background as determinants of labor market outcomes. For example, the literature on intergenerational income mobility suggest high mobility coefficients in the Scandinavian countries compared to the United States (Bratberg et al. 2017).

  6. Angelov et al. (2016) show the earnings profile of Swedish men with children, before and after first childbirth. However, they do not estimate the effect of children per se, nor do they take account of non-random selection.

  7. Studies tend to find a relatively high fatherhood premium for co-residing and biological fathers (Killewald 2012), which is the main group we focus on in the empirical analysis.

  8. The remaining women were not eligible. Workers are eligible if they have been working for 6 out of 10 months before the date of birth.

  9. Other contributing factors may include free higher education.

  10. Time use data on hours of household work and market work for couples suggest that couples in Norway distribute time equally if they do not have children. These data are only available for 2010, somewhat outside our observation window and not earlier (Vaage 2012).

  11. This results in dropping ~50% of men and the main groups we exclude are sons from one-child families and families with fewer than two boys.

  12. Statistically, ~30% of all twins are monozygotic. Only monozygotic twins are genetically 100% identical at birth. Siblings are genetically more similar than two randomly selected men.

  13. The earnings variable measures all taxable earnings, including unemployment insurance, disability benefits, parental leave, and sick pay, but not means-tested social assistance and interest on financial assets.

  14. We keep information on birth order within the family, counting both girls and boys.

  15. One birth cohort is around 60,000 in Norway. The birth registry is complete. So we can study the effect of children on earnings when considering all fathers who could be directly affected by having children. Note that fathers are always reported when they are cohabiting with, or married to, the mother around the time of birth of the child. A small group that we cannot observe are those fathers not reported, for example, because the mother does not want to name him and the father has no contact with the mother and child. During the observation period, only 400–500 children were adopted per year and we have no information on those.

  16. National statistics show that the fraction of childless men declines only by 2 percentage points between the age of 40 and 45, and by 0.6 percentage points between 45 and 50.

  17. We do not have access to information on cohabitation for men without children. Hence, we also exclude those cohabiting without children.

  18. The basic framework builds on Heckman and Hotz (1989) who investigated the return to training where training is not assigned randomly but self-selected. The selection problem in their study is that those who enter training (the treated) are different—in terms of labor market characteristics—before treatment, compared to the non-treated (those who do not enter training).

  19. In a robustness test, we test whether there is some variation across time using the Norwegian paternity reform; that is we test the assumption \({\gamma }_{t}=\gamma\).

  20. Since men typically work continuously we can neglect non-random selection into work. To incorporate women with more disrupted careers would demand further assumptions.

  21. The direction of selection bias can go either way.

  22. We use that \(E(\epsilon | a,X,Z)=E(\epsilon | X,Z)\). In this case controlling for the observed selection variables (Z) solves the (observed) selection bias problem.

  23. Hence, we do not rely on the assumption that trends are the same before treatment, or childbirth.

  24. Since we cannot distinguish identical twins from fraternal twins we cannot use their comparison to disentangle nature and nurture effects. Another reason why we want to control for family fixed factors is that they are potentially correlated with fertility outcomes if, for example, families pass on fixed values to their offspring that are important traits for having a family later in life (Fernandez and Fogli 2006).

  25. We follow the common assumption in the literature, but acknowledge that it might be restrictive to assume no reverse causality. Identification depends on this assumption for both the family fixed estimator and the individual fixed effect estimator. This assumption can be relaxed only in case of a valid instrumental variable.

  26. Since we cannot make use of data on monozygotic twins, we cannot sweep out \(\mu\) completely and, therefore, have to make assumptions. We also tested whether \({\mu }_{1{f}{^{\prime} }}={\mu }_{2{f}{^{\prime} }}=0\). We tested for second and third order serial correlation of the error term from the model in between-sibling differences, observing that serial autocorrelation remains, yet is small. The results are available on request.

  27. At the individual level, \(i\), all combinations of \({Z}_{it}\) and \({a}_{it}\) are observed, except for the combination \({Z}_{it}=0\) and \({a}_{it}=1\) (i.e. childless man after becoming a father).

  28. This has been used in the literature exploiting sibling data, as in Griliches (1979).

  29. Identification applying the CV estimator depends on sibling pairs where one brother has children and the other does not. In our sample of brothers, 27.94% of all siblings have the combination ‘no children’ and ‘children’. For twins, the corresponding value is 25.73. Hence, the data contain sufficient variation. We also tested for the possibility that sibling pairs that identify the effect of having children in the family fixed effects model are different from the random sibling pairs in our total sample. This could bias the results. The estimation results from a restricted sample of brother siblings with unequal fertility outcomes show that compositional effects do not explain our main findings.

  30. We acknowledge that still we have to make this assumption. We cannot tell whether the genetic component drives our results since we cannot distinguish between fraternal and monozygotic twins in our data.

  31. The twin sample would become too small for estimation if we further restricted the group of childless men, at only 1515 observations or ~700 sets of twins. Summary statistics are reported in Table 1, column 3.

  32. In this calculation, we ignore the curvature parameters, since they are essentially zero.

  33. These results are unchanged when we use only ever married fathers-at-some-point.

  34. Since we will drop annual earnings that are potentially affected by the reform, this rule will minimize measurement problems. Usually fathers take leave at the end of the parental leave period, which is then in 1994 for births in April 1993.

  35. Note, that we present OLS estimation results that condition on the work history in a flexible way, but do not control for family fixed effects. The reason is that we would not expect more insights from the covariance estimation results since the differential effects are already not significant.

  36. The female employment rate was 1990 (2009), 62.5 (68.8)% for women in Norway, compared to 57 (58)% in the U.S. Source: OECD. For more background see NOU (2008): 6 and NOU (2012): 15.

  37. However, our results suggest that studies controlling for family background but not conditioning on pre-birth histories are likely to suffer from upward bias.

References

  • Anderson, D., Binder, M., & Krause, K. (2002). The motherhood earnings penalty: which mothers pay it and why? American Economic Review, 92(2), 354–358.

    Google Scholar 

  • Adda, J., Dustmann, C., & Stevens, K. (2017). The career costs of children. Journal of Political Economy, 125(2), 293–337.

    Google Scholar 

  • Angelov, N., Johansson, P., & Lindahl, E. (2016). Parenthood and the gender gap in pay. Journal of Labor Economics, 34(3), 2016.

    Google Scholar 

  • Angrist, J. D., & Evans, W. N. (1998). Children and their parents’ labor supply: evidence from exogenous variation in family size. American Economic Review, 88(3), 450–477.

    Google Scholar 

  • Antonovics, K., & Town, R. (2004). Are all the good men married? Uncovering the sources of the marital earnings premium. American Economic Review, 94(2), 317–321.

    Google Scholar 

  • Autor, D., & Wasserman, M. (2013). Wayward Sons: The Emerging Gender Gap in Education and Labor Markets, Third Way, Washington, DC.

  • Boschini, A., Håkanson, C., Sjögren, A., & Rosen, Å. (2011). Trading off or having it all? Completed fertility and mid-career earnings of Swedish men and women. IFAU Working paper 2011:15.

  • Becker, G. S. (1985). Human capital, effort, and the sexual division of labor. Journal of Labor Economics, 3(1), S33–58.

    Google Scholar 

  • Bertrand, M., Goldin, C., & Katz, L. (2010). Dynamics of the gender gap for young professionals in the financial and corporate sectors. American Economic Journal, 2(3), 228–255.

    Google Scholar 

  • Blau, F. D., & Kahn, L. M. (1996). International differences in male wage inequality: institutions versus market forces. Journal of Political Economy, 104(4), 791–837.

    Google Scholar 

  • Blomquist, N., & Hansson-Brusewitz, U. (1990). The effect of taxes on male and female labor supply in Sweden. Journal of Human Resources, 25, 317–357.

    Google Scholar 

  • Bound, J., & Solon, G. (1999). Double trouble: on the value of twins-based estimation of the return to schooling. Economics of Education Review, 18, 169–182.

    Google Scholar 

  • Bratberg, E., et al. (2017). A comparison of intergenerational mobility curves in Germany, Norway, Sweden, and the US. The Scandinavian Journal of Economics, 119(1), 72–101.

    Google Scholar 

  • Böckmann, I., & Budig, M. (2013). Fatherhood, Intra-Household Employment Dynamics, and Men’s Earnings in a Cross-National Perspective, LIS Working papers 592, LIS Cross-National Data Center in Luxembourg.

  • Cools, S., Fiva, J. H., & Kirkebøen, L. J. (2015). Causal effects of paternity leave on children and parents. The Scandinavian Journal of Economics, 99(1), 119–127.

    Google Scholar 

  • Correll, S., Bernard, S., & Paik, I. (2007). Getting a job: is there a motherhood penalty? American Journal of Sociology, 112, 1297–1338.

    Google Scholar 

  • Dahl, G., Løken, K. V., & Mogstad, M. (2014). Peer effects in program participation. American Economic Review, 104, 2049–2074.

    Google Scholar 

  • Datta Gupta, N., & Smith, N. (2002). Children and career interruptions: the family gap in Denmark. Economica, 69(276), 609–629.

    Google Scholar 

  • Datta Gupta, N., Smith, N., & Stratton, L. S. (2007). Is marriage poisonous? Are relationships taxing? An analysis of the male marital earnings differential in Denmark. Southern Economic Journal, 74(2), 412–433.

    Google Scholar 

  • Dribe, M., & Stanfors, M. (2009). Does parenthood Strengthen a traditional household division of labour? Evidence from Sweden. Journal of Marriage and Family, 71(February), 33–45.

    Google Scholar 

  • Ejrnæs, M., & Kunze, A. (2013). Work and wage dynamics around childbirth. Scandinavian Journal of Economics, 115(3), 856–877.

    Google Scholar 

  • Fernandez, R., & Fogli, A. (2006). Fertility: the role of culture and family experience. Journal of the European Economic Association, 482(3), 552–561.

    Google Scholar 

  • Field, E., Molitor, V., Schoonbroodt, A., & Tertilt, M. (2016). Gender gaps in completed fertility. Journal of Demographic Economics, 82(2), 167–206.

    Google Scholar 

  • Fortin, N. (2005). Gender role attitudes and the labour-market outcomes of women across OECD countries. Oxford Review of Economic Policy, 21, 416–438.

    Google Scholar 

  • Ginther, D. K., & Zavodny, M. (2001). Is the male marriage premium due to selection? The effect of shotgun weddings on the return to marriage. Journal of Population Economics, 14(2), 3131–328.

    Google Scholar 

  • Glauber, R. (2008). Race and gender in families and at work: the fatherhood premium. Gender and Society, 22, 8–30.

    Google Scholar 

  • Goldin, C. (2006). The quiet revolution that transformed women’s employment, education, and family. American Economic Review, 96(2), 1–21.

    Google Scholar 

  • Gould, E. (2008). Marriage and career: the dynamic decisions of young men. Journal of Human Capital, 2(4), 337–378.

    Google Scholar 

  • Goux, D., Maurin, E., & Petrongolo, B. (2014). Worktime regulations and spousal labor supply. American Economic Review, 104(1), 252–276.

    Google Scholar 

  • Gray, J. S. (1997). The fall in men’s return to marriage. Declining productivity effects or changing selection. Journal of Human Resources, 32(3), 481–504.

    Google Scholar 

  • Griliches, Z. (1979). Sibling Models and Data in Economics: Beginnings of a Survey. Journal of Political Economy, 87(5), S37–S64.

    Google Scholar 

  • Heckman, J. J., & Hotz, V. J. (1989). Choosing among alternative nonexperimental methods for estimating the impact of social programs: The case of manpower training. Journal of the American statistical Association, 84(408), 862–874.

    Google Scholar 

  • Hersch, J., & Stratton, L. S. (2000). Household specialization and the male marriage wage premium. Industrial and Labor Relations Review, 54(1), 78–94.

    Google Scholar 

  • Hodges, M. J., & Budig, M. J. (2010). Who gets the daddy bonus? Organizational hegemonic masculinity and the impact of fatherhood on earnings. Gender and Society, 24, 717–745.

    Google Scholar 

  • Hundley, G. (2000). Male/Female earnings differences in self-employment: the effects of marriage, children, and the household division of labor. Industrial and Labor Relations Review, 54(1), 95–114.

    Google Scholar 

  • 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, 60(3), 683–715.

    Google Scholar 

  • Joshi, H., Paci, P., & Waldfogel, J. (1999). The earnings of motherhood: better or worse? Cambridge Journal of Economics, 23(5), 543–564.

    Google Scholar 

  • Killewald, A. (2012). A reconsideration of the fatherhood premium: marriage, coresidence, biology, and fathers’ wages. American Sociological Review, 78(1), 96–116.

    Google Scholar 

  • Killewald, A., & Lundberg, I. (2017). New evidence against a causal marriage wage premium. Demography, 54(3), 1007–1028.

    Google Scholar 

  • Kleven, H., Landais, C., & Søgaard, J. E. (2018). Children and gender inequality: evidence from Denmark. American Economic Journal, 11(4), 181–209.

    Google Scholar 

  • Korenman, S., & Neumark, D. (1991). Does marriage really make men more productive? Journal of Human Resources, 26(2), 282–307.

    Google Scholar 

  • Krashinsky, H. A. (2004). Do marital status and computer usage really change the earnings structure? Journal of Human Resources, 39, 774–791.

    Google Scholar 

  • Loh, E. S. (1996). Productivity differences and the marriage wage premium for white males. Journal of Human Resources, 31(3), 566–589.

    Google Scholar 

  • Loughran, D. S., & Zissimopoulos, J. M. (2009). Why wait? The effect of marriage and childbearing on the earnings of men and women. Journal of Human Resources, 44(2), 326–349.

    Google Scholar 

  • Ludwig, V., & Brüderl, J. (2018). Is there a male marital wage premium? New evidence from the United States. American Sociological Review, 83(4), 744–770.

    Google Scholar 

  • Lundberg, S., & Rose, E. (2000). Parenthood and the earnings of married men and women. Labour Economics, 7, 689–710.

    Google Scholar 

  • Lundberg, S., & Rose, E. (2002). The effects of sons and daughters on men’s labor supply and earnings. Review of Economics and Statistics, 84(2), 251–268.

    Google Scholar 

  • Miller, A. R. (2011). The effects of motherhood timing on career path. Journal of Population Economics, 24(3), 1071–1100.

    Google Scholar 

  • Mincer, J. (1974). Schooling, Experience and Earnings. New York: Columbia University.

  • Norges offentlige utredninger (NOU). (2008). Kjønn og Lønn – Fakta, analyser og virkemidler for likelønn. Norges offentlige utredninger, 2008, 6.

  • Norges offentlige utredninger (NOU). (2012). Politikk for likestilling, vol 15. Norges offentlige utredninger.

  • OECD. (2017). The Pursuit of Gender Equality. An Uphill Battle. Paris: OECD Publishing.

    Google Scholar 

  • Peters, M., & Siow, A. (2002). Competing premarital investments. Journal of Political Economy, 110(3), 592–608.

    Google Scholar 

  • Petersen, T., & Penner, A. M. (2011). The male marital wage premium: sorting vs. differential pay. Industrial and Labor Relations Review, 64(2), 282–304.

    Google Scholar 

  • Petersen, T., Penner, A. M., & Høgsnes, G. (2014). From motherhood penalties to husband premia: the new challenge for gender equality and family policy, lessons from Norway, American Journal of Sociology, 119(5), 1434–1472.

  • Pencavel, J. (1986). Labor supply of men: a survey. In Orley Ashenfelter & Richard Layard (Eds), Handbook of labor economics, vol. 1 (pp. 3–101), NY: Elsevier Science Pub., 1986.

  • Simonsen, M., & Skipper, L. (2010). The family gap revisited: what wombmates reveal. Labour Economics, 19, 102–112.

    Google Scholar 

  • van Soest, A., & Woittiez ad, A. K. (1990). Labor supply, income taxes, and hours retrictions in the Netherlands. Journal of Human Resources, 25, 517–558.

    Google Scholar 

  • Vaage, O. F. (2012). Tidene skifter: Tidsbruk 1971–2010. Statistics Norway, Oslo Kongsvinger.

  • Waldfogel, J. (1998). Understanding the family gap in pay for women with children. Journal of Economic Perspectives, 12(1), 137–156

    Google Scholar 

Download references

Acknowledgements

The author is grateful for many discussions with Shelly Lundberg, Oddbjørn Raaum, Bernt Bratsberg, Simen Markussen, Kjell Salvanes, Frank Windmeijer, Mette Ejrnæs, Michael Burda, Ken Troske, Øivind A. Nilsen, John Ermisch and various seminar and conference participants.

Author information

Authors and Affiliations

  1. Norwegian School of Economics, Bergen, Norway

    Astrid Kunze

Authors
  1. Astrid Kunze
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Astrid Kunze.

Ethics declarations

Conflict of interest

The author declares that she has no conflict of interest.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kunze, A. The effect of children on male earnings and inequality. Rev Econ Household 18, 683–710 (2020). https://doi.org/10.1007/s11150-019-09469-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11150-019-09469-8

Keywords

Search

Navigation