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Gender, educational attainment, and the impact of parental migration on children left behind

Abstract

Estimation of the causal effect of parental migration on children’s educational attainment is complicated by the fact that migrants and nonmigrants are likely to differ in unobservable ways that also affect children’s educational outcomes. This paper suggests a novel way of addressing this selection problem by looking within the family to exploit variation in siblings’ ages at the time of parental migration. The basic assumption underlying the analysis is that parental migration will have no effect on the educational outcomes of children who are at least 20 years old because they have already completed their education. Their younger siblings, in contrast, may still be in school, and thus will be affected by the parental migration experience. The results point to a statistically significant positive effect of paternal US migration on education for girls, suggesting that pushing a father’s US migration earlier in his daughter’s life can lead to an increase in her educational attainment of up to 1 year relative to delaying migration until after she has turned 20 years old. In contrast, paternal domestic migration has no statistically significant effect on educational attainment for girls or boys, suggesting that father absence does not play a major role in determining children’s educational outcomes. Instead, these results suggest that the marginal dollars from US migrant remittances appear to enable families to further educate their daughters. Thus, policymakers should view international migration as a potential pathway by which families raise educational attainments of girls in particular.

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Fig. 1

Notes

  1. Author’s own calculation from the Mexican Migration Project 118 (MMP118). http://mmp.opr.princeton.edu/.

  2. See Antman (2012) for a review of the literature on the impact of parental migration on children left behind.

  3. Consistent with this notion, Yang (2008) finds that Philippine households experiencing favorable exchange rate shocks tied to the migration of family members increase educational investments in their children.

  4. This observation is not so different from that employed by Bleakley and Chin (2004, 2010) who identify the effects of language skills on earnings and assimilation by arguing that older immigrant children are more likely to have difficulty acquiring a new language than their younger peers. Nobles (2007) also uses a similar strategy to estimate the effect of parental migration on child health, arguing that parental migration after a certain age should have no effect on child height.

  5. I later relax that assumption to consider a 15-year-old cutoff.

  6. Barcellos et al. (2010) investigate gender discrimination across families in India and argue that son-biased stopping rules will make comparisons between girls and boys difficult because unobserved family characteristics may be correlated with family size and gender composition. Family fixed effects will only correct for these sources of endogeneity if they are fixed over time. Evidence from Mexican fertility patterns presented in Dahl and Moretti (2004), however, suggest that parents are biased in favor of sons. Thus, if this type of endogeneity biases any of the estimates here, I would expect it to act as a bias against finding evidence of gender discrimination in favor of girls.

  7. Kroeger and Anderson (2011) also include both domestic and international migration measures to estimate the impact on schooling of children in Kyrgyzstan. Since they do not observe actual migration of household members, however, they focus on receipt of domestic versus international remittances.

  8. This is in line with Acosta (2011) who finds that remittances result in increased schooling for girls, but not boys in El Salvador. In contrast, other studies have found negative effects of migration on schooling outcomes for girls, a result that is thought to be linked with an increase in housework for girls in particular (Meyerhoefer and Chen 2011; McKenzie and Rapoport 2011).

  9. A study by Booth (1995) is one of a handful of papers that considers the effects of father absence on children outside of the USA. While the study is relevant because it considers the effects of father’s migration, it does not address the endogeneity of paternal migration.

  10. The wider literature on child outcomes also suggests that girls and boys respond differently to environments outside the home. Kling et al. (2007) review omnibus results from the Moving to Opportunity housing lottery experiment indicating that moving to a better neighborhood improves educational and health outcomes for girls, while having adverse consequences for boys. Similarly, Kling et al. (2005) show that the housing experiment was linked with lower crime rates for female youth but more problem behavior for teenage boys, suggesting that boys and girls adapt differently to new environments.

  11. The MMP is publicaly avaiable at http://mmp.opr.princeton.edu/. In principle, all survey years are eligible to be included in the sample here, provided that respondents are interviewed in Mexico. This restriction eliminates the 1983 sample. All remaining survey years are included.

  12. According to the interviewer’s manual (Durand et al. 2005), in the case of a couple, the head is the husband unless he is migrating and his wife does not know enough about her partner to answer questions about his migration experience. In the latter cases, the wife is labeled as the head.

  13. Unfortunately, I have no additional information on household composition at the time of migration, thus ruling out an examination into the effects of migration on other children that may have resided in the household at the time of the head’s migration.

  14. Note that this does not mean that the child will necessarily be living in the head’s household at the time of the survey since nonresident children are included in the sample. This also does not restrict the nature of the household in which the child was living at the time of migration, since the migration data are constructed from retrospective histories. Unfortunately, I have no additional information on the household circumstances in which the child was living at the time of migration.

  15. I selected this window of time because it is the 10-year period following the change in currency to Mexican “new pesos” and thus avoids any confusion in record-keeping.

  16. One alternative would be to use explicit data on the duration of parental migration and thus examine the effect of an additional month of migration on children’s educational attainments. Given that the migration episodes are all based on retrospective data, however, the explicit duration data are likely to be subject to greater recall bias. In contrast, using the dummy variable approach also has the added value of not making as strict an assumption about the functional dependence of educational attainment on the duration of parental absence.

  17. As seen above, the number of children per family in the sample is relatively large, and thus, I opt for a linear birth order variable and variables indicating the oldest and youngest. This specification will also make for ease of comparison when the sample is split into girls and boys.

  18. It may also be that the father that migrates domestically may be able to return home more frequently, or in case of emergency, than the father who migrates internationally. Unfortunately, I have no data to investigate the extent to which this occurs in practice.

  19. A previous version of this paper attempted to distinguish between the effect of the parent’s first migration trip and parental migration episodes overall as well as the effects of maternal versus paternal migration. The results suggested that the main effects operated through the father’s first migration trip and thus led to similar conclusions as those made here.

  20. Interested readers may be curious about the results when the sample includes children who have migrated before the age of 20. The point estimates for paternal migration are not statistically significant for boys; and for girls, the magnitude of the point estimate on paternal US migration drops to 0.4, but remains statistically significant at the 10% level. Intuitively, this makes sense since one might expect the effect of a child’s own migration experience to hamper educational attainment and thus work against any positive effect of paternal migration.

  21. Using data from Bangladesh, Pitt et al. (2010) suggest that this type of differential investment pattern across gender might make sense if the labor market returns to schooling and nutrition also vary by gender.

  22. See Ashraf et al. (2009) for a discussion of the problem faced by international migrants in exerting control over the channeling of remittances.

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Acknowledgements

I would like to thank Doug Bernheim, Luigi Pistaferri, Aprajit Mahajan, Terra McKinnish, Julie Berry Cullen, Silvia Giorguli Saucedo, Marie Mora, three anonymous referees, and the editor, Klaus F. Zimmermann, for helpful comments. Additionally, participants at the 2008 PAA meeting, seminar participants at Colorado State University, and participants of the public economics group, as well as the labor and development reading groups at Stanford University provided useful feedback. An earlier version of this paper was entitled “Parental Migration and Child Education: Evidence from Variation in Child Age During Parental Absence.” My thanks go to an anonymous referee for inspiring a reframing of this paper. Any errors are my own. This research was supported by the Leonard W. Ely and Shirley R. Ely Graduate Student Fund through a grant to the Stanford Institute for Economic Policy Research.

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Correspondence to Francisca M. Antman.

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Responsible editor: Klaus F. Zimmermann

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Antman, F.M. Gender, educational attainment, and the impact of parental migration on children left behind. J Popul Econ 25, 1187–1214 (2012). https://doi.org/10.1007/s00148-012-0423-y

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Keywords

  • Migration
  • Father absence
  • Education
  • Gender

JEL Classification

  • O15
  • J12
  • J13
  • J16
  • J24
  • F22