Investing in children’s education: are Muslim immigrants different?


Using a unique data set on immigrants living in France in 2003, we investigate whether Muslims invest differently in their children’s education compared to non-Muslims. In particular, we want to assess whether educational inequalities between the children of Muslim and non-Muslim immigrants stem from differences between or within families. After controlling for a broad set of individual and household characteristics, we find no difference in education between children of different religions. However, we do find more within-family inequality in children’s educational achievements among Muslims relative to non-Muslims. The within-family variance is 15 % higher among Muslims relative to Catholics and 45 % higher relative to immigrants with other religions, but the intra-family inequality remains difficult to explain. Overall, our results suggest that Muslim parents tend to redistribute their resources more unequally among their children.

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  1. 1.

    Different sources cited in (Garcia-Munoz and Neuman 2013) indicate that the share of Muslim religious group in the European population is expected to grow from a current 6 to 8 % of the population over the next 20 years. The demographic trend of a growing share of the Muslim populations in Europe is expected to result in a further increase in anti-Moslim taste-based discrimination (Adida et al. 2011).

  2. 2.

    These results are subject to controversy (see Arai et al. 2011; Bisin et al. 2011).

  3. 3.

    One study that investigates the relationship between religion and education is that of Hajj and Panizza (2009). Looking into the gender gap in education between Muslims and Christians households (not immigrants) in Lebanon, these authors find no support that Muslims discriminate against female education.

  4. 4.

    A recent stream of literature, the so-called epidemiological approach summarized by Fernandez (2011), is trying to isolate the cultural traits from the countries of origin that affect the behavior of immigrants in the host countries. The main idea is that culture measured through the persistence of religious traits has an effect on women’s fertility and labor supply (Fernandez and Fogli 2006a, 2006b) as well as on the living arrangements of 18–30-year-olds (Giuliano 2007).

  5. 5.

    For example, differences within family allocations may result in lower outcomes for girls than for boys (when, for instance, the capital markets are incomplete), for higher relative to lower birth-order children (if prices for schooling depend on family size), or for larger than smaller sibship size.

  6. 6.

    The PRI survey was conducted by the Caisse Nationale d’Assurance Vieillesse (CNAV) and the Institut National de la Statistique et des Etudes Economiques (INSEE) from November 2002 to February 2003. The main purpose of the PRI survey was to provide a detailed description of the behavior of older migrants (nearing retirement or already retired) living in France.

  7. 7.

    (Ejrnaes and Portner 2004) also select their sample on the basis of the child’s age. By definition, very young children will not attend school and young children below 16 will be in the secondary school, so they will not have had the opportunity to have obtained a diploma. At the same time, we implicitly account for these young children because they are considered when calculating the number of siblings and other characteristics of the sibship.

  8. 8.

    For the children, the corresponding figures are 44.9 % (Muslims), 37.8 % (Catholics), and 17.4 % (other religions). Other religion category includes the following: Protestant (including Evangelists and Anglicans) (2.8 %), other Christian (Orthodox, Gregorian, Maronite, and other Christian Armenian) (3.1 %), other religion (5.1 %), and also no religion (6.3 %).

  9. 9.

    There is mixed evidence on whether the time since migration is correlated to immigrants’ religiosity. We will return to this issue later.

  10. 10.

    By construction, the rank among siblings is correlated with the size of the sibship: children with many siblings will have higher rank on average. Following (Booth and Kee 2009), we construct an adjusted rank R α among siblings such that \(R_{a} =2\ast \frac {R}{N+1}\), with R as the standard rank and N as the size of the sibship. Whatever the number of siblings, the average adjusted rank is always equal to one at the family level.

  11. 11.

    Results do not change if we do not account for current region of residence. However, one worry here is that some unobservable characteristics that affect the immigrants’ residence choice may also affect the level of parental investment in their children education. Ideally, one would need questions about the families’ location and neighborhood when the children were in school, but such information is not available in our cross-sectional data. In some further specifications, we also account for information about the safety of the neighborhood where the respondents currently live (whether the respondents live in a dangerous place or not). Our main findings are robust to these controls.

  12. 12.

    Our results are not affected by excluding respondents with no religion. These results are available upon request.

  13. 13.

    To further understand these effects, we make use of another variable in our survey—date of entry in France for each child (we already control for the duration since migration, but it is not always the case that all family migrate at one point in time). Unfortunately, there is a large proportion of missing values that prevents us from using it in our main regressions. However, we have looked into our results on a restricted sample of observations for which we have the information, and we find indeed lower education for those children that entered France the latest, while the dummy born abroad, living in France is not significant anymore. All other results, including the religion indicator, are very similar to those in column 3. These results are available upon request.

  14. 14.

    The number of children of the Muslim sample is lower than that of the Catholic sample because we only consider children aged at least 24 years old and not enrolled at the date of the survey (recall that Muslim children are younger on average and have a higher probability to attend school).

  15. 15.

    Additionally, we have also looked into our results excluding all children born abroad and living abroad, as this group may be very different than those living in France. Our results, available upon request, are largely in line with those in Table 2.

  16. 16.

    We believe that it is difficult to assess the importance of this variable for other religion immigrants, because this is a highly heterogeneous group.

  17. 17.

    All these additional estimates are available upon request.

  18. 18.

    As shown in Table 1, Muslim children are, for instance, younger on average and more often enrolled.

  19. 19.

    Here, we suppose that censoring is exogenous in the sense that it is not affected by family characteristics.

  20. 20.

    Even though it remains difficult to explain, we also attempted to put a number on the how much of the within inequality is due to some of our explanatory variables. For each Muslim household, we regress the explained within variance by the standard deviation of the following characteristics: gender, age, raised by both head and spouse until age of 12, born abroad and living in France, and born abroad and living abroad. To assess the contribution of each variable to the within inequality, we perform a Fields’ decomposition of factor contribution. We find that around 18 % of within inequality is explained by the gap in age at the sibship level, 23.5 % by change in raised by both parents, and around 37 % by place of birth. The variation in gender at the sibship level explains less than 0.001 % of the variation.

  21. 21.

    We also only consider families with at most four children satisfying the previous criteria, as at most four transfers to children are recorded in the PRI survey.

  22. 22.

    Both in the education and transfer regressions, we include a set of dummies for the region of origin (instead of countries of origin) with the following categories: Northern Europe, Eastern Europe, Southern Europe, Northern Africa, Southern Africa, America, Middle East, and Asia. We choose to group countries by regions as there were very few children for some countries. For private transfers, we have also estimated a regression pooling all religions. We find that children with Muslim parents are significantly less likely to receive money, while there is no difference between Christian and other religions (see alsoWolff et al. 2007).

  23. 23.

    Note that this variable does not vary a lot at the family level for our sample.

  24. 24.

    According to our data, the proportion of transfers related to family events (like marriage or birth) is extremely low among Muslims (3.2 %). The lower probability of transfers for girls relative to boys in Muslim vs. non-Muslim households may also be a compensation mechanism if the family would have invested more in terms of education for girls than for boys or if girls perform better at school.

  25. 25.

    In 2003, the year of the survey, public spending on education in France was 5.9 % of GDP, while private education expenditures represented 0.5 of GDP.


  1. Algan Y, Dustmann C, Glitz A, Manning A (2010) The economic situation of first and second-generation immigrants in france, Germany and the United Kingdom. Econ J 120:F4–F30

    Article  Google Scholar 

  2. Altonji J G, Dunn T J (1996) The effects of family characteristics on the return to education. Rev Econ Stat 77:692–704

    Article  Google Scholar 

  3. Adida CL, Laitin DD, Valfort MA (2011) One muslim is enough! Evidence from a field experiment in France. IZA Discussion Paper 6122

  4. Arai M, Karlsson J, Lundholm M (2011) On fragile grounds: a replication of are muslim immigrants different in terms of cultural integrationJ Eur Econ Assoc 9:1002–1011

    Article  Google Scholar 

  5. Attias-Donfut C, Davaut P, Gallou R, Rozenkier A, Wolff F C (2006) L’enracinement.Enquête sur le vieillissement des immigrés en France. Armand Colin, Paris

    Google Scholar 

  6. Baetschmann G, Staub K, Winkelmann R (2013) Reconsidering panel data methods for ordered response variables, with an application to the effect of unemployment on life satisfaction. Mimeo, University of Zurich

    Google Scholar 

  7. Bhalotra S, Valente C, Van Soest A (2010) The puzzle of muslim advantage in child survival in India. J Health Econ 29:191–204

    Article  Google Scholar 

  8. Behrman J (1997) Intrahousehold distribution and the family. In: Rosenzweig M R, Stark O (eds) Handbook of population and family economics. Elsevier, North-Holland, pp 125–187

    Google Scholar 

  9. Bhat PN, Francis Zavier AJ (2005) Fertility decline and gender bias in Northern India. Demogr 40:637–657

    Article  Google Scholar 

  10. Bisin A, Patacchini E, Verdier T, Zenou Y (2008) Are Muslim immigrants different in terms of cultural integrationJ Eur Econ Assoc 6:445–456

    Article  Google Scholar 

  11. Bisin A, Patacchini E, Verdier T, Zenou Y (2011) Errata Corrige: are Muslim immigrants different in terms of cultural integrationJ Eur Econ Assoc 9:1012–1019

    Article  Google Scholar 

  12. Bisin A, Verdier T (2011) The economics of cultural transmission and socialization. In: Benhabib J, Bisin A, Jackson M (eds) Handbook of social economics, vol 1A. Elsevier, North-Holland, pp 339–416

    Google Scholar 

  13. Bohlmark A (2008) Age at immigration and school performance: a siblings analysis using Swedish register data. Labour Econ 15:1366–1387

    Article  Google Scholar 

  14. Booth A, Kee H (2009) Birth order matters: The effect of family size and birth order on educational attainment. J Popul Econ 22:367–397

    Article  Google Scholar 

  15. Butler J S, Moffitt R (1982) A computationally efficient quadrature procedure for the one-factor multinomial Probit model. Econometrica 50:761–764

    Article  Google Scholar 

  16. Card D (1999). In: Ashenfelter OC, Card D (eds) The causal effect of education on earnings, vol 3A. Elsevier, Amsterdam, pp 1801–1863

  17. Chamberlain G (1980) Analysis of covariance with qualitative data. Rev Econ Stud 47:225–238

    Article  Google Scholar 

  18. Chiswick B (1988) Differences in education and earnings across racial and ethnic groups: tastes, discrimination, and investment in child quality. Q J Econ 103:571–597

    Article  Google Scholar 

  19. Constant A, Zimmermann K (2013) International handbook on the economics of migration. Edward Elgar, Cheltenham

    Book  Google Scholar 

  20. Constant A, Gataullina L, Zimmermann K, Zimmermann L (2006) Clash of cultures: Muslims and Christians in the ethnosizing process. IZA Discussion Paper 2350

  21. Constant A, Nottmeyer O, Zimmermann K (2012) Cultural integration in Germany. In: Algan Y, Bisin A, Manning A, Verdier T (eds) Cultural integration of immigrants in europe. Oxford University Press, Oxford, pp 69–124

    Google Scholar 

  22. Das M, Van Soest A (1999) A panel data model for subjective information on household income growth. J Econ Behav Organ 40:409–426

    Article  Google Scholar 

  23. Domingues Dos Santos M, Wolff F C (2011) Human capital background and the educational attainment of the second-generation immigrants in france. Econ Educ Rev 30:1085–1096

    Article  Google Scholar 

  24. Dustmann C, Frattini T (2011) Immigration: The European experience. IZA Discussion Paper 6261

  25. Dustmann C, Frattini T, Gianandrea L (2012) Educational achievement of second generation immigrants: an international comparison. Econ Policy 27:143–185

    Article  Google Scholar 

  26. Dustmann C, Glitz A (2011) Migration and education. In: Hanushek E, Machin S, Woessmann L (eds) Handbook of the economics of education, vol 4. Elsevier, Amsterdam, pp 327–441

    Google Scholar 

  27. Ejrnaes M, Portner C (2004) Birth order and the intrahousehold allocation of time and education. Rev Econ Stat 86:1008–1019

    Article  Google Scholar 

  28. Fernandez R (2011) Does culture matter?. In: Benhabib J, Bisin A, Jackson M (eds) Handbook of social economics, vol 1A. Elsevier, Amsterdam, pp 481–510

    Google Scholar 

  29. Fernandez R, Fogli A (2006a) Fertility: the role of culture and family experience. J Eur Econ Assoc 4:552–561

    Article  Google Scholar 

  30. Fernandez R, Fogli A (2006b) Culture: an empirical investigation of beliefs, work, and fertility. Am Econ J Macroecon 1:146–177

    Article  Google Scholar 

  31. Frechette G R (2001) Random effects ordered Probit. Stata Tech Bull 159:23–27

    Google Scholar 

  32. Gang I, Zimmermann K (2000) Is child like parent? Educational attainment and ethnic origin. J Hum Resour 35:550–569

    Article  Google Scholar 

  33. Garcia-Munoz T, Neuman S (2013) Is religiosity of immigrants a bridge or a buffer in the process of integration? A comparative study of Europe and the United States. In: Zimmermann K (ed) Constant A. International handbook on the economics of migration. Edward Elgar, Cheltenham

    Google Scholar 

  34. Garg A, Morduch J (1998) Sibling rivalry and the gender gap: evidence from child health outcomes in Ghana. J Popul Econ 11:471–493

    Article  Google Scholar 

  35. Giuliano P (2007) Living arrangements in Western Europe: does cultural origin matterJ Eur Econ Assoc 5:927–952

    Article  Google Scholar 

  36. Hajj M, Panizza U (2009) Religion and education gender gap: are Muslims differentEcon Educ. Rev 28:337–344

    Article  Google Scholar 

  37. Heckman J, Stixrud J, Urzua S (2006) The effects of cognitive and noncognitive abilities on labor market outcomes and social behavior. J. Labor Econ. 24:411–482

    Article  Google Scholar 

  38. Magnac T, Thesmar D (2002) Analyse économique des politiques éducatives: l’augmentation de la scolarisation en France de 1982 à 1993. Annales d’Economie et Statistiques 65:1–34

    Google Scholar 

  39. Ozyurt S (2009) Living Islam in a non-Muslim society: how religiosity affects acculturation and civic integration of muslim immigrant women in Western host societies. CCIS, Mimeo

    Google Scholar 

  40. Picard N, Wolff F C (2010) Measuring educational inequalities: evidence from Albania. J Popul Econ 23:989–1023

    Article  Google Scholar 

  41. Schaafsma J, Sweetman A (2001) Immigrants earnings: age at migration matters. Canadian J Econ 34:1066–1099

    Article  Google Scholar 

  42. Van Ours J, Veenman J (2006) Age at immigration and educational attainment of young immigrants. Econ Lett 90:310–316

    Article  Google Scholar 

  43. Van Tubergen F, Sindradottir J (2011) The religiosity of immigrants in Europe: a cross-national study. J Sci Stud Relig 50:272–288

    Article  Google Scholar 

  44. Wolff F C, Spilerman S, Attias-Donfut C (2007) Transfers from migrants to their children: evidence that altruism and cultural factors matter. Rev Income Wealth 53:619–644

    Article  Google Scholar 

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We would like to thank our editor Klaus F. Zimmermann, two anonymous referees, Christian Dustmann, and seminar participants at the Conference in Economics of the Family in the honor of G. Becker, Paris, for their very helpful comments and suggestions. Andreea Mitrut gratefully acknowledges support from Jan Wallanders and Tom Hedelius Fond and from the Scientific Council of Sweden and the European Research Council (through Mikael Lindahl’s) ERC 2009 starting grant 24116. Any remaining errors are ours.

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Correspondence to Andreea Mitrut.

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Mitrut, A., Wolff, FC. Investing in children’s education: are Muslim immigrants different?. J Popul Econ 27, 999–1022 (2014).

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  • Immigrants
  • Religion
  • Education
  • Intra-household inequality
  • France

JEL Classification

  • J15
  • D13
  • Z12