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Intergenerational transmission of education among female immigrants

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Abstract

This paper uses high-quality register data to perform one of the first descriptions of the patterns of intergenerational transmission of education among immigrant mothers and their daughters. The paper also raises several methodological points related to functional form and measurement error in immigrants’ education. The results show that the degree of intergenerational persistence is lower among immigrants compared to natives, and that the relationship is weaker among those who start out disadvantaged. I find large variations across different immigrant groups, which are partly explained by the first generation’s position in the educational distribution.

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Notes

  1. A related strand of the literature examines the intergenerational transmission in self-employment (e.g. Fairlie 1999; Andersson and Hammarstedt 2011).

  2. Closely related studies are also Nielsen et al. (2003) and Bauer and Riphahn (2006, 2007). Nielsen et al. (2003) analyze the relationship between parental education and probability of completing a qualifying education for sons and daughters with an immigrant and a native background in Denmark. They find a weaker relationship among immigrants compared to natives. Bauer and Riphahn (2006, 2007) instead analyse the probability of reaching a low, middle or high education for 17 years old immigrant youths depending on whether the mother/father has a low or high education. They find a weaker relationship among immigrant youths compared to native youths.

  3. This section builds on Lundh and Ohlsson (1999).

  4. Except in 1972–1973 due to a large return migration to Finland.

  5. The standard model is based on works by Becker and Tomes (1979, 1986).

  6. Measurement error may occur in both administrative data and in survey data. However, it is likely more frequent in survey data. There are several sources of measurement error in administrative data. An individual may not apply for a formal degree after finishing higher education. Furthermore, individuals that attain their highest education abroad may not validate it in Sweden, meaning that their educational level will be downward biased. This type of measurement error probably only affects daughters’ schooling, since a larger proportion of individuals in the younger generation attends higher education. However, the errors are not likely to differ much across daughters with different origins and will therefore not affect the findings in this study.

  7. Information on daughters’ educational attainment is drawn only from administrative data.

  8. In order to simplify the expressions, probability limits are not used in the equations.

  9. Schooling is not censored among daughters and native born mothers since Sweden has a 9-year compulsory schooling system (at least 7 years before 1962). For more information, see Meghir and Palme (2005).

  10. For more detailed information about Stativ, see SCB (2009).

  11. Their mothers and fathers immigrated to Sweden prior to 1981.

  12. I exclude daughters with a native father as I am mainly interested in understanding the intergenerational relationship among second generation immigrant daughters (i.e. daughters of foreign born parents). It is well known that children with only one foreign born parent, on average, perform better than children with both parents foreign born. By excluding daughters with native fathers the intergenerational association in education may therefore get stronger. As will be shown, the association is however weaker among immigrant daughters than among native daughters.

  13. Information on maternal schooling is available in my data from 1998 (the information also covers education received by mothers prior to 1998) and onwards.

  14. The Census has not been repeated since then.

  15. Mothers who have more than one daughter in the sample are overrepresented since each daughter is treated as a unit in the analysis.

  16. I have aggregated countries with fewer than 50 observations, resulting in 38 groups of origins among foreign born mothers. They are defined in Table 11.

  17. That is schooling levels above 11 years and below 16 years.

  18. The specified model is:

    \(Edu_{ij}^{d} = \alpha + \beta Edu_{ij}^{m} + \tau^{d} + \tau^{m} + \rho_{j} + \varepsilon_{ij}\)

    where the unit of observation i denotes the daughter-mother pair and the superscripts d and m refer to daughter and mother characteristics, respectively. The dependent variable \(Edu_{ij}^{d}\) denotes the years of schooling of daughter i belonging to the country of origin group j. Similarly, \(Edu_{ij}^{m}\) denotes the years of schooling of the mother. The model includes birth cohort fixed effects for daughters \(\tau^{d}\) and mothers \(\tau^{m}\) as well as country of origin fixed effects \(\rho_{j}\).

  19. This result is probably not driven by measurement errors in maternal schooling as measurement errors caused by censoring and miss-reports are likely to have offsetting effects.

  20. The specified model is: \(Edu_{ijc}^{d} = \alpha + \beta Edu_{ijc}^{m} + \gamma \left[ {Size_{jc} \times Edu_{j}^{m} } \right] + \theta Size_{jc} + \tau^{d} + \tau^{m} + \rho_{j} + \varepsilon_{ijc}\).

  21. The size of the network is measured at the county level c.

  22. Note also that the amount of variation in schooling is limited since I control for birth year fixed effects of both daughters and mothers.

  23. For instance; heritability of traits, environmental factors and cultural factors.

  24. However, caution should be warranted when interpreting the transmission estimates from this exercise since the estimates are likely to be biased by measurement errors in both mothers’ and fathers’ years of schooling.

  25. Mandatory education was lower in Portugal than in many other countries. In Turkey, for instance, education was mandatory for 5 years at the same period (OECD 2007b???).

  26. I have also experimented with using the share of highly educated mothers instead of the average educational level and the findings remain stable. Results are available upon request.

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Acknowledgments

I thank Anders Stenberg and Eskil Wadensjö for encouragement and support. I am grateful to Hans Grönqvist for many helpful discussions and comments. I have also benefitted from valuable comments and suggestions by Anders Björklund, Miles Corak, Markus Jäntti, Mårten Palme, Inga Persson and seminar participants at RC28 2008 (Palo Alto), CED, ESPE 2009 (Seville), EALE 2009 (Tallinn) and SOFI.

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  1. SOFI, Stockholm University, 106 91, Stockholm, Sweden

    Susan Niknami

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Correspondence to Susan Niknami.

Appendix

Appendix

See Figs. 2, 3, 4 and Tables 10, 11.

Fig. 2
figure 2

The Swedish Census 1990 questionnaire

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Fig. 3
figure 3

Scatter Plot of Grouped Data of Mean Education Immigrant Mothers and their daughters. Note: The intersection point of the dotted lines represents the point observation of natives

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Fig. 4
figure 4

Scatter Plot of Grouped Data of Mean Education Immigrant Mothers and the Intergenerational Transmission Estimate adjusted for Assortative Mating. Note: The intersection point of the dotted lines represents the point observation of natives. Transmission estimates that are statistically insignificant appear as yellow dots in the figure (Color figure online)

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Table 10 Description of how years of schooling is constructed
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Table 11 Groups of countries
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Niknami, S. Intergenerational transmission of education among female immigrants. Rev Econ Household 14, 715–744 (2016). https://doi.org/10.1007/s11150-015-9294-9

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