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Can migration reduce educational attainment? Evidence from Mexico


This paper examines the impact of migration on educational attainment in rural Mexico. Using historical migration rates to instrument for current migration, we find evidence of a significant negative effect of migration on schooling attendance and attainment. IV-censored ordered probits show that living in a migrant household lowers the chances of boys completing junior high school and of boys and girls completing high school. We find that the observed decrease in schooling of 16- to 18-year-olds is accounted for by current migration of boys and increased housework for girls.

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  1. For example, the World Bank’s 2006 Global Economic Prospects report was fully dedicated to exploring the “Economic implications of remittances and migration” (World Bank 2005).

  2. See Cox Edwards and Ureta (2003) for Nicaragua, López-Córdoba (2005) for Mexico, Yang (2008) for the Philippines, and Rapoport and Docquier (2006) for a survey of the remittances literature.

  3. See Doquier and Rapoport (2009) for a review of the various channels through which a beneficial brain drain can be obtained and Beine et al. (2008) for macro evidence.

  4. See the Appendix in McKenzie (2005) for a methodological discussion of this point. Examples of papers that just look at the impact of remittances on education are Acosta (2006) and López-Córdoba (2005).

  5. Theoretically, one could separate the effect of remittances from other effects of migration through the use of a valid instrument that predicts whether or not one migrant will send more remittances than another. Such instruments are uncommon in practice, with the exchange rate shocks used by Yang (2008) coming closest in this regard among the existing literature (although as he acknowledges, these shocks also affect migrant wealth holdings).

  6. Source: own calculations from ENADID data (see Table 1).

  7. Two recent papers written in parallel to this one also find a negative overall impact of migration on schooling. de Brauw and Giles (2006) look at the impact of migration on school enrolment in China, and Antman (2005) looks at the impact of migration on school attendance and hours of schooling, in Mexico, using data from the Mexican Migration Project. Neither study controls for the censoring of educational outcomes or is able to consider the years of schooling attained.

  8. In related work, Hanson and Woodruff (2003) also estimate the overall impact of migration on education in Mexico. They use the 2000 Mexican census and look at the impact on number of school grades completed of 10- to 15-year-olds. Their main finding is that migration to the USA is associated with more years of completed education for 13- to 15-year-old girls but only for those whose mothers have three years or less of education. We consider a broader measure of household migration experience and obtain an insignificant effect of migration on education for 12- to 15-year-old girls with poorly educated mothers and cannot reject positive effects of similar magnitudes to those they find. However, our work builds on their findings in three important respects. Most fundamentally, we consider 16- to 18-year-olds, who are at the age when migration for work starts to become a possibility, especially for males, and who are also at the age when they may be entrusted with household responsibilities that take the place of schooling. That is, this is precisely the age range at which many of the other channels through which migration affects education start to manifest themselves. Secondly, Hanson and Woodruff (2003) note that school attendance is high among their sample, with 82.5% of 10- to 15-year-olds attending school. Nevertheless, they use two-stage least squares for estimation, which does not account for this high rate of right-censoring. Once we account for censoring, insignificant 2SLS results for 12- to 15-year-old males become significant. Finally, the survey we use enables examination of what children are doing when they are not in school, enabling investigation of the channels through which migration is affecting schooling.

  9. Survey methodology, summary tables, and questionnaires are contained in INEGI (1999).

  10. See also Rivera-Batiz (1999). We do not try and separate the impacts of legal and illegal migration on child schooling given the small sample of legal first-time migrants and the lack of an identification strategy for explaining why some migrants go legally and otherwise identical migrants go illegally.

  11. We carry out analysis separately for 12- to 15-year-olds, who were all below the school-leaving age in 1993 at the time of education reform, and 16- to 18-year-olds, who had already reached the existing school-leaving age at the time of reform.

  12. Hanson and Woodruff (2003), McKenzie and Rapoport (2007, 2010), López-Córdoba (2005), and Hildebrandt and McKenzie (2005) all employ historical migration rates as instruments for current migration.

  13. Thanks to Chris Woodruff for supplying these historical rates.

  14. Mexico has 31 states and a federal district. Cameron et al. (2008) have shown that cluster-robust standard errors are downward biased when the number of clusters is small. They find the size of the tests is not too far off with 30 clusters (a 0.069 rejection rate for a nominal size of 0.05) suggesting that our results would not be that affected by this concern. Nevertheless, we experimented with a cluster bootstrap to get standard errors and found little changes in the standard errors of our estimates here. Given the slow time for convergence for the censored ordered probits and difficulty incorporating sample weights in Stata’s bootstrap command, we present asymptotic standard errors that are cluster robust.

  15. Land ownership data were kindly provided by Ernesto López-Córdoba.

  16. As a check on this assumption, we split states into those above and below the median migration rate in 1924 and, then, regress years of schooling on a dummy variable for being in a high migration state for children in nonmigrant households. The effect of the community network is insignificant for three out of the four groups and has a small positive effect on school attainment of 12- to 15-year-old females. This provides us with further confidence in our instrument and suggests that a finding of migration lowering education rates is not a result of the community network directly lowering education rates.

  17. Estimation was carried out using the IV-probit command in Stata version 9.

  18. See Appendix A of Glick and Sahn (2000) for specification of the likelihood function. Estimation was carried by programming the likelihood in Stata version 9.

  19. Such an approach is also carried out by Maitra (2003).

  20. For example, in a survey of students in Zacatecas, Kandel and Kao (2001) find that living in a migrant household is negatively associated with directly elicited university aspirations.

  21. We obtain similar results qualitatively using the census definition of a migrant household and less negative correlations for having a current migrant. When we look by gender of the migrant, the negative association is much stronger for having a male migrant. However, as we have discussed, we do not have a credible identification strategy for explaining how a household chooses to engage in migration, only for whether it does, and so cannot separately identify the effects of these different types of migration.

  22. The ENADID asks whether or not you have worked in the past week, regardless of whether or not you are also attending school, which we define as “working.” Another possible activity in the last week for individuals who were not students and who were not working was doing “housework.” Among the individuals who are working, we also look more closely to see whether or not they are working as unpaid workers in a family enterprise, defined as “unpaid family workers.”

  23. It is unlikely that many of these youth are migrating to continue their education in the USA. The ENADID specifically asks whether individuals have migrated to the USA to work or seek work. Eighty-one percent of 16- to 18-year-old males going to the USA went for these reasons. It is also likely that some of the remainder were also not in school even if they did not go specifically for work.


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We thank an anonymous referee, Thomas Bauer, Gordon Hanson, Frédéric Jouneau, Omar Licandro, Ernesto Lopez-Cordoba, François-Charles Wolff, and various seminar and conference audiences for useful comments on earlier drafts.

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Correspondence to David McKenzie.

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Responsible editor: Klaus F. Zimmermann



Table 8 First-stage regressions

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McKenzie, D., Rapoport, H. Can migration reduce educational attainment? Evidence from Mexico. J Popul Econ 24, 1331–1358 (2011).

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  • Migration
  • Educational attainments
  • Mexico

JEL Classification

  • O15
  • J61
  • D31