Educational inequalities between the French overseas territories and metropolitan France: The determinant role of parents’ transmission of human capital

Emmanuel Valat; Paul Reeve

Educational inequalities between the French overseas territories and metropolitan France: The determinant role of parents’ transmission of human capital
Suivre cet auteur Emmanuel Valat, translated by Suivre cet auteur Paul Reeve
In Population Volume 76, Issue 1, January 2021, pages 107 to 147

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France is marked by strong territorial inequalities. Compared to metropolitan France, the overseas territories have long had higher unemployment rates and lower levels of educational attainment. Understanding the mechanisms of educational disadvantage for young people born there is key for public policy. To reduce inequalities, is it necessary to take action regarding the school system, the living conditions of the population, or the labour market to make it more attractive? Based on two comparable surveys, one conducted in metropolitan France and the other in the overseas territories, the author investigates the individual and family factors that put young adults in the overseas territories at an educational disadvantage. The article’s econometric analysis highlights the decisive weight of the cultural and economic capital of parents and the living conditions of families.

1People born in France’s overseas departments and regions (départements et régions d’outre-mer [DROMs]) [1] have lower levels of education than those born in metropolitan France. In the late 2000s, 18- to 34-year-olds born in the DROMs were on average twice as likely to hold no educational qualifications (or only a lower secondary certificate) compared to individuals in the same age range from metropolitan France. This finding applies to both women and men (Appendix Table A.1). Likewise, around half of 18- to 34-year-olds born in Guadeloupe, Martinique, French Guiana, and Réunion have not completed upper secondary (baccalauréat), versus only a third of those born in metropolitan France (Table 1). These lower levels of initial education among young people born in the French overseas territories raise questions both in social justice (equal access to education) and economic terms. First, the effective application in the DROMs of the right to education is a problem, as recalled in a recent report by the National Consultative Commission on Human Rights (CNCDH, 2017). According to this report, the quality of the education offered in the French overseas territories is lower (less qualified staff than in metropolitan France, more degraded infrastructure, less access to schools by transport, less developed extracurricular activities, etc.) and is also poorly adapted to their realities (first languages insufficiently taken into account, Eurocentric programmes, etc.). Beyond the issue of equal access to schooling, educational inequalities are also concerning insofar as they are linked to the problem of mass unemployment in the overseas territories. [2] According to some studies, this problem is partly due to lower levels of education (L’Horty, 2014). Besides these high unemployment rates, employers face significant difficulties with recruitment, which also reflect problems with the training of jobseekers.

Table 1: Levels of education attained by 18- to 34-year-olds regardless of whether they had completed their studies when interviewed, by place of birth

Metropolitan France Guadeloupe Martinique French Guiana Réunion Overall No qualifications, lower secondary certificate (BEPC) 13.4 17.9 20.9 34.5 29.4 13.8 Intermediate vocational certificate (CAP, BEP) 20.7 27.4 23.2 21.7 26.1 20.9 Upper secondary (vocational or general) 29.2 25.2 26.3 22.8 23.6 29.1 ≥ Upper secondary + 2 years higher education 36.6 29.5 29.6 21.0 20.9 36.2 Number of observations 7,223 578 620 595 976 9,992

Table 1: Levels of education attained by 18- to 34-year-olds regardless of whether they had completed their studies when interviewed, by place of birth

Note: As some MFV survey respondents were born in metropolitan France and living in a DROM, while inversely, some TeO survey respondents were born in a DROM and living in metropolitan France, each of the five groups includes some individuals interviewed in both surveys. Weighted data.
Coverage: Individuals aged 18–34 born in metropolitan France, Guadeloupe, Martinique, French Guiana, and Réunion.

2If we wish to define public policies capable of increasing levels of education among people born in the DROMs, the causes of the phenomenon must be properly identified. Several explanations could be given. One is that lower-quality educational resources in the overseas territories (poor-quality infrastructure, difficulties recruiting permanent and experienced teachers, etc.) may play a role (DEPP, 2017). The facts that (a) the DROMs feature a higher concentration of individuals from families with significant socioeconomic difficulties (DEPP, 2017; Caro, 2018) and (b) families in the DROMs are less likely to use the French language than those in metropolitan France may also affect some parents’ ability to invest in their children’s human capital. [3] Parents may thus be less able to help their children in various ways (time to devote to children, material and financial support, etc.) [4] to acquire skills and qualifications enabling greater academic success and, possibly, better adaptation to the job market. The relative lack of career opportunities in the DROMs may also not necessarily encourage young people to invest in education to acquire job skills. Finally, as major cultural specificities exist in the DROMs, it could also be that academic success is not valued in the same way as in metropolitan France. But what is the actual role of each of these explanations?

3Taking an econometric approach that allows us to look both at young people having completed their studies and at those still in school, we assess the extent to which educational inequalities between individuals born in the DROMs and metropolitan France are linked to the quality of human capital transmitted by their parents. This question is particularly important insofar as the proportion of the DROM population from modest backgrounds is high, and in France social backgrounds have traditionally had a major impact on academic achievement (Goux and Maurin, 1995). In France, more than in most other OECD countries, social origins, which partly reflect family levels of cultural resources or possibly ‘intellectual stimulation’ at home, affect young people’s educational performance (Meuret and Morlaix, 2006; OECD, 2015). [5] Our analysis is based on two surveys conducted by INED and INSEE: the Migration, Family, and Aging survey (MFV), carried out in Guadeloupe, Martinique, French Guiana, and Réunion in 2009–2010, and the Trajectories and Origins survey (TeO), carried out in 2008–2009 in metropolitan France (excluding Corsica). These surveys include a large number of identical questions on several dimensions with a potential influence on the quality of the human capital parents transmit to their children. More specifically, these questions concern family living standards, parents’ social origins and cultural characteristics, and other aspects of family life during childhood.

4Section I of this article presents the potential sources of educational inequalities between the natives of DROMs and of metropolitan France, as well as the arguments for studying factors relating to the quality of the human capital transmitted by parents more specifically. Section II presents the data and some descriptive statistics. The third section is devoted to describing the econometric method and discussing the results.

I – Potential causes of educational inequalities between natives of the DROMs and metropolitan France

5Individuals born in metropolitan France have higher levels of education than individuals born in the DROMs (Table 1). They are more likely to have completed some higher education (almost 37% in metropolitan France vs. 21%–30% depending on the DROM) and are less likely to hold no educational qualifications or only a lower secondary certificate (BEPC) (13% in metropolitan France vs. 18%–35% depending on the DROM). [6] These observations apply to both women and men, except graduates from higher education among young people from Martinique, who are as likely to have graduated with some higher education as those from metropolitan France (Appendix Table A.1). These findings are consistent with the conclusions of numerous reports analysing the educational difficulties of young people in the overseas territories (Senate, 2009; Boudesseul et al., 2016; DEPP, 2017). The social science literature on educational inequalities suggests four principal reasons as likely to explain lower levels of education among young people born in the DROMs compared to those born in metropolitan France.

1 – Educational infrastructure in the DROMs and metropolitan France

6A first possible explanation relates to the disadvantage in educational resources and infrastructure quality in the overseas territories compared to metropolitan France (DEPP, 2017). Educational institutions in the DROMs are geographically less well distributed than in metropolitan France, with students more concentrated in large institutions. This concentration can make access difficult for some, potentially increasing early school departures and thus decrease the school enrolment rate. As some areas of French Guiana are isolated (many young people live in areas with very limited access to the outside), this département is the most affected by the problem of concentration. The territory’s strong demographic growth, the lack of a policy of large-scale construction, and school transport networks either inadequate or too expensive for many families, tend to reinforce the problem. The ratio of the number of lower and upper secondary schools (collèges and lycées) to numbers of young people of equivalent school age in French Guiana is much lower than in the other DROMs (CNCDH, 2017). The risks of non-attendance and early school leaving, especially beginning in lower secondary school, are higher in French Guiana than in the other DROMs (CNCDH, 2017).

7School occupancy rates [7] are also higher in the DROMs than in metropolitan France, and the average surface area per pupil is smaller, which can affect the quality of teaching, particularly at the primary and secondary levels (DEPP, 2017). Overseas institutions are also less well supplied with IT equipment [8] than metropolitan institutions (DEPP, 2017). The lack of resources also applies to teaching. Compared to metropolitan France, the number of teachers with agrégé [9] status is much lower in the DROMs, and the number of contractual instructors is higher: 19.9% of lower secondary teachers in the DROMs do not hold permanent positions versus 5.5% in metropolitan France (DEPP, 2017). Similarly, in the DROMs, 16.0% of upper secondary school teachers have obtained the agrégation versus 28.3% in metropolitan France (DEPP, 2017). This phenomenon once again affects French Guiana more than the other DROMs, no doubt due to the territory’s lack of attractiveness, linked to sometimes difficult living conditions and a climate of insecurity (CNCDH, 2017). Options for higher education in the DROMs are also more limited than in metropolitan France.

8Nevertheless, the strength of the effect of these inequalities in endowments should be questioned for at least two reasons. First, apart from French Guiana, while differences exist between the DROMs and metropolitan France, they are not very large, and the education systems remain fairly similar (DEPP, 2018). Some heterogeneity exists within metropolitan France, so that the situation in some areas of the DROMs is similar to, or even better than, the situation in some metropolitan areas. For example, the number of students per teacher is relatively similar between the DROMs and metropolitan France, or even slightly lower in the DROMs, in both primary and secondary schools. Furthermore, many natives of the overseas territories come to study in metropolitan France, particularly in higher education (Temporal et al., 2011). Public funding for such educational mobility has been facilitating these movements for many years (Haddad, 2018).

2 – Differences in returns on education between territories?

9A second factor that could explain educational inequalities are limited career opportunities in the DROMs. According to the literature, a lack of opportunities is likely to discourage individuals from investing in education, i.e. from devoting time and effort to attaining a higher level of education to improve their chances of obtaining a well-paid job (Chiswick, 1988). Levels of unemployment are particularly high in the DROMs compared to metropolitan France (Lasserre, 2018), and have been for many years (Treyens and Catherine, 2015). But the role of this phenomenon in educational inequalities between overseas and metropolitan areas is questionable. Educational qualifications increase the probability of accessing employment significantly in all parts of France, but this effect is even stronger in the DROMs than in metropolitan France (L’Horty, 2014). Immigration to the metropolis, where unemployment is lower, is a possibility individuals can use for expanding their career opportunities. Many graduates from the DROMs do choose to migrate to metropolitan France. A large proportion settle and pursue a career there once they have completed their higher education (Temporal et al., 2011).

3 – Cultural differences in the valuing of academic success in the DROMs and metropolitan France?

10The third reason is a cultural one. Differences in educational ‘tastes’ between certain population groups could also produce educational inequalities (Chiswick, 1988). As each overseas territory has its own cultural specificities, linked notably to Creole culture (Prudent, 2005), it is conceivable that academic success is not valued identically in metropolitan France and in the DROMs. However, residents of the DROMs are French and have shared the same school system with metropolitan France for many generations. It is thus not at all certain that the relationship to academic success will differ significantly between these territories, at least to the point of explaining the observed inequalities.

4 – Differences in parents’ transmission of human capital?

11The fourth and final potential source of inequality is that many pupils in the DROMs are from modest backgrounds and from families whose main spoken language at home is not French (DEPP, 2017). This may affect the quality of human capital transmitted by parents, at least as a factor favouring academic achievement at all levels (Chiswick, 1988; Domingues Dos Santos and Wolff, 2011). Numerous analyses of educational inequalities between different groups in France, particularly those of foreign origin (Brinbaum and Kieffer, 2009; Domingues Dos Santos and Wolff, 2011; Ichou, 2013), but also others relating to educational inequalities in general in France (Picard and Wolff, 2014), have highlighted the determining role of this factor.

12The present study focuses on this source of educational inequalities between young people from the DROMs and from metropolitan France. The surveys used provide detailed information on many items relating to individuals’ social origins, their families’ cultural characteristics, and their living conditions during childhood. These elements could influence the quality of human capital transmitted by parents.

II – Population data and characteristics

1 – The MFV and TeO surveys: two detailed and complementary sources

13The Migration, Family, and Ageing (MFV) and Trajectories and Origins (TeO) surveys are, to our knowledge, the only sources that allow a detailed study of the impact of social origin and family background during childhood on the academic achievement of young people in the DROMs and metropolitan France. They have the advantage of having been conducted at almost the same time in the DROMs (excluding Mayotte) and in metropolitan France (excluding Corsica): 15,770 individuals aged 18–79 from different households were interviewed in Guadeloupe, Martinique, French Guiana, and Réunion between the third quarter of 2009 and the first quarter of 2010; and 21,761 individuals aged 17–60 years in metropolitan France between the second quarter of 2008 and the third quarter of 2009. [10] Most importantly, the two surveys feature a large number of similar questions, so that each enables a precise description of the respondents’ social origin and living conditions during childhood.

14This study focuses on individuals aged 18–34 for two reasons. First, it seems wise to look at cohorts close enough together in age that they can be considered to have experienced relatively similar contexts. The type and effectiveness of education systems and teaching methods, as well as families’ average wealth, influence the context in which young people grow up and are likely to change over successive cohorts. Moreover, in the MFV survey, several of the questions relating to family living conditions during childhood were only asked to respondents aged 18–34. Focusing only on these individuals thus allows more questions to be used.

15Immigrants to France are also excluded from the sample, as most were enrolled in other school systems for at least a few years, and many may have obtained an educational qualification abroad. The objective here is to investigate the probability of reaching a certain level of education having mainly attended school within the French educational system. Descendants of immigrants, however, are included. Like immigrants, they are mainly present in metropolitan France and French Guiana (Table 2).

16Once the two databases had been compiled, the sample included 9,992 people aged 18–34 interviewed in metropolitan France or one of the DROMs. Individuals are divided into five groups according to their place of birth: Guadeloupe, Martinique, French Guiana, Réunion, and metropolitan France. The choice to group individuals according to their place of birth and not their place of residence is made for two reasons. First, most individuals who migrated had first completed their primary and secondary education in their territory of birth. [11] Secondly, because the present study examines the link between the level of education attained by children and the human capital transmitted by their parents (who for the most part grew up and lived in the territory where their children were born), it makes more sense to analyse educational inequalities according to young people’s place of birth than their place of residence at the time of the survey. More than two-thirds of people born in a DROM lived in the DROM of their birth throughout their entire schooling, having generally moved after their studies or, among those with the highest levels of education, towards the end of their studies (Temporal et al., 2011). [12]

Table 2: Characteristics of respondents aged 18–34 by place of birth

Metropolitan France Guadeloupe Martinique French Guiana Réunion Overall Still studying 19.6 22.4 23.9 21.2 15.9 19.6 Female 49.9 48.3 51.1 52.2 50.9 49.9 Mean age 26.0 26.0 25.6 24.4 25.8 25.9 Serious family financial problems (a) 19.4 33.9 28.3 20.7 34.2 19.8 Father’s SPC Unknown 0.7 3.0 5.0 7.8 4.3 0.8 Inactive or unemployed (never held paid employment) 0.0 0.9 0.8 3.7 2.5 0.1 Manual worker, farmer 46.7 45.0 44.1 44.3 57.7 46.8 Clerical or sales worker 11.9 13.7 13.8 11.8 12.4 12.0 Artisan 12.5 16.7 15.9 16.7 9.2 12.5 Intermediate occupation 16.1 16.1 12.0 11.7 9.3 15.9 Manager/professional 12.1 4.5 8.5 4.1 4.5 11.9 Mother’s SPC Unknown 0.5 0.9 0.4 4.2 3.1 0.5 Inactive or unemployed (never held paid employment) 11.2 14.7 13.8 24.5 30.5 11.5 Manual worker, farmer 17.6 11.7 14.8 14.7 12.3 17.4 Clerical or sales worker 45.0 47.9 47.9 36.6 43.6 45.0 Artisan 4.3 5.9 1.6 5.8 1.9 4.3 Intermediate occupation 17.0 13.0 17.1 12.6 6.2 16.8 Manager/professional 4.5 5.8 4.4 1.8 2.4 4.4 Language spoken most often by mother during childhood French 93.0 77.2 86.4 53.8 25.8 91.7 Creole 1.2 18.3 9.2 10.6 68.4 2.4 Other language or had no (or little) exchange with mother 5.8 4.5 4.5 35.6 5.8 5.9 Language spoken most often by father during childhood French 92.5 57.0 60.1 42.3 22.5 90.9 Creole 1.2 14.9 8.7 5.2 54.6 2.2 Another language or had no (or little) exchange with father 6.3 28.1 31.2 52.4 22.9 7.0 French spoken in family (a) 98.3 89.4 95.6 71.1 33.5 97.2 Descendant of at least one immigrant parent 17.8 4.0 2.2 31.6 2.3 17.4 At least one parent born in the DROMs 1.7 94.9 94.8 57.7 96.4 4.6 Number of siblings 0 7.5 6.5 5.7 4.6 3.5 7.4 1 37.9 19.5 31.0 12.0 20.6 37.4 2 30.8 27.9 23.4 23.1 24.5 30.7 3 12.4 15.4 17.8 17.0 17.0 12.5 4 or more 11.3 30.7 22.1 43.3 34.4 12.0

Table 2: Characteristics of respondents aged 18–34 by place of birth

Metropolitan France Guadeloupe Martinique French Guiana Réunion Overall Sibling rank 1st 43.1 31.7 36.1 25.6 32.9 42.8 2nd 32.5 27.1 33.1 29.7 23.0 32.3 3rd 14.1 15.2 10.9 15.1 20.2 14.1 4th or higher 10.3 26.0 20.0 29.6 23.9 10.8 Grew up mainly… with both parents 86.5 72.6 79.1 73.1 83.4 86.2 with mother only 8.0 22.3 16.5 16.5 10.5 8.2 with father only 0.9 0.5 0.8 2.4 1.2 0.9 in a reconstituted/blended family 3.5 1.3 1.1 1.4 1.7 3.4 with grandparents 0.8 3.2 1.4 5.7 2.6 0.8 Other (hostel, collective housing, etc.) 0.4 0.2 1.0 0.9 0.7 0.4 Suffered personal violence in the family (a) 3.7 6.9 5.2 4.6 8.2 3.8 Parent’s alcoholism (a) 9.7 11.3 7.7 13.9 23.5 9.9 Parent’s illness, disabilities, etc. (a) 17.1 16.6 12.2 16.4 20.3 17.1 Serious arguments or conflicts between parents (a) 21.1 32.3 29.1 23.4 30.2 21.4 Had a room to do homework in alone 85.8 75.2 75.5 72.2 77.1 85.5 Help with homework from parents Often 33.1 31.7 31.2 23.5 19.5 32.9 Sometimes 41.6 39.6 42.2 24.9 36.8 41.5 Never/not applicable 25.3 28.7 26.6 51.7 43.7 25.7 Help with homework from siblings Often 8.1 17.9 14.5 13.6 12.9 8.3 Sometimes 22.6 29.6 29.6 32.1 26.2 22.8 Never/not applicable 69.4 52.5 55.9 54.3 60.9 69.0 Number of observations 7,223 578 620 595 976 9,992

(a) Before age 18.
Coverage: Individuals aged 18–34 years born in metropolitan France, Guadeloupe, Martinique, French Guiana, and Réunion. Weighted data.

17The sample includes 7,223 young people born in metropolitan France, 578 in Guadeloupe, 620 in Martinique, 595 in French Guiana, and 976 in Réunion. It includes both individuals having completed their studies at the time of the survey and those still in school. The latter situation implies a censoring problem, since the final level of studies was not observed for this portion of the sample (19.6%). All individuals meeting the other criteria were nonetheless included (this point is justified in Section III.1).

2 – More advantageous family financial situations and social backgrounds in metropolitan France

18Let us first look at the material and financial situation of the respondents’ families during childhood and the level of difficulties to which they were exposed. According to some studies using French data, financial difficulties can in themselves [13] have a negative impact on academic achievement (Maurin, 2002; Duée, 2005). Having limited financial resources makes parents less able to provide living conditions (material, health, etc.) conducive to children’s academic achievement. Respondents from a DROM were far more likely than those from metropolitan France to come from families that went through major financial difficulties during their childhood. Among those born in Réunion and Guadeloupe, more than a third reported this situation versus less than 20% of those from metropolitan France. [14]

19The data can also be used to look at effects of individuals’ social origin by considering their parents’ social position, which, through the transmission of human capital, strongly influences individuals’ level of education (Chiswick, 1988). While no information is available on parents’ level of education, [15] the data collected does provide information on both parents’ last occupation or highest socioprofessional category (SPC). Six categories concerning the parents’ SPC are used (Table 2). Here there are few differences between those born in metropolitan France and the Antilles (Guadeloupe and Martinique). Differences are mainly found for those from Réunion and, to a lesser extent, French Guiana. In particular, while more than a quarter of those born in metropolitan France had a father in an intermediate or managerial/professional occupation, this proportion was smaller among those from a DROM (around 20% of Antilleans and 15% of those from French Guiana and Réunion). Regarding the highest SPCs, differences are also found between the mothers of young people born in metropolitan France and the DROMs, particularly those from Réunion. [16] Also, respondents from the overseas territories, including the Antilles, were more likely than those from metropolitan France to report not knowing their parents’ SPC. Less than 1% of respondents from metropolitan France reported this of either their father or mother, while, depending on the territory, between 3% and 8% of those born in a DROM reported not knowing their father’s SPC (the differences with metropolitan respondents were smaller for mothers). DROM respondents were also more likely to have parents who had never held paid employment. The differences between those born in metropolitan France and in the DROMs were particularly marked for mothers: around 11% of the mothers of those born in metropolitan France had never held paid employment versus as many as 30% for respondents born in Réunion.

3 – Relationship to the French language and cultural origins vary widely depending on place of birth

20Cultural origins could also influence parents’ transmission of human capital to children (Chiswick, 1988) through language use within the family. As Dustmann et al. (2012) indicated, compared to other countries, in France the use of the national language within the family has a particularly large effect on school performance. Three variables reflect the use of French in the family [17] (Table 2). Here we look at the language spoken most often during childhood with both the respondent’s mother and father. For DROM respondents, French competes with the local Creole and possibly with languages from surrounding territories, notably among those from French Guiana (Portuguese or other regional Creole languages, particularly from Haiti and Suriname). Moreover, some individuals communicated little or not at all with at least one of their parents during childhood, especially with the father in certain DROMs. The situations in the DROMs and metropolitan France differ considerably on this point. Having spoken little or no French with a parent is likely to influence pupils’ school outcomes insofar as teaching takes place predominantly in French. As expected, French was less used by families in the overseas territories, particularly in French Guiana and Réunion, than by families in metropolitan France. A variable indicating whether French was used at all in the family during childhood, regardless of whether it was the language the respondent used most frequently with their parents, is also analysed. The disparity with metropolitan France is smaller for Antillean respondents, a little larger for those from French Guiana, and very large for those from Réunion.

21The analysis also looks at whether respondents are descendants of immigrants, a common situation in metropolitan France and French Guiana. If parents did not grow up or receive (part or all of) their education in France, this is likely to affect their ability to help their children with schoolwork, as various studies using French data have shown (Brinbaum and Kieffer, 2009; Domingues Dos Santos and Wolff, 2011; Ichou, 2013).

22The observation that at least one of a respondent’s parents was born in the DROMs also enables the analysis to consider that some respondents from a DROM have parents not born there but who migrated either from abroad or from metropolitan France.

4 – Living situations during childhood differ considerably between places of birth

23A series of indicators is needed to reflect living environments during childhood. First, the MFV and TeO surveys provide information on sibship size for each individual. A higher number of siblings generally has a negative effect on individuals’ level of education. This is mainly because the more children parents have, the less time they can devote to each child, an effect that increases with sibling rank (Booth and Kee, 2009). This result has generally been verified using French data (Domingues Dos Santos and Wolff, 2011). It is important to examine these factors, as they differ significantly between the DROMs and metropolitan France. Indeed, those born in a DROM are more often from sibships of three or more.

24A second variable indicates whether the individual grew up mainly with both parents or in another family type (single-parent family, etc.). Some research has found that growing up with both parents creates an environment more conducive to academic achievement (Brown, 2004). Those born in a DROM were slightly less likely to have grown up with both of their parents (86% of respondents born in metropolitan France; for the DROMs, 73% for Guadeloupe and 83% for Réunion).

25In addition, more of the respondents from the overseas territories had suffered personal violence in childhood and had at least one alcoholic parent. They were also more likely to have grown up in families where arguments and conflicts between parents were common. [18] Each of these elements may affect young people’s ultimate level of education (Harold et al., 2007; Mangiavacchi and Picolli, 2018). They may affect the time parents spend raising their children, but also the children’s self-esteem, a factor that strongly influences academic achievement (Wang et al., 1999; Coleman and De Leire, 2003; Araujo and Lagos, 2013). Another characteristic that can affect parents’ investment in their children’s education is their own state of health (Bratti and Mendola, 2014). The variable used here is whether at least one parent experienced health problems, which was more common among respondents from Réunion than others (20% for respondents born in Réunion, 12% for Martinique, and around 17% for the other groups). [19]

26The data also provide information about the family’s involvement in their children’s school life, which may be linked to academic achievement (Avvisati et al., 2010, 2014). Three variables related to this issue are included: whether the respondents had access to a room to do their homework in alone, how often they were helped with homework by their parents, and how often they were helped by their siblings. The data reveal significant differences in whether children had a room to do their homework in alone. Children from metropolitan France were more likely to have such a space than those from the DROMs. Regarding parents’ help with homework, children born in French Guiana and Réunion tended to receive less than those from other territories. Around 44% of the respondents from Réunion and 52% of those from French Guiana never had help with homework from their parents versus only about a quarter of individuals from the other territories. On the other hand, respondents from the DROMs were more likely to receive help from siblings than those from metropolitan France. Around 70% of those from metropolitan France never received help from their siblings versus a little over half of individuals from a DROM and 60% from Réunion. This may be linked to differences in sibship size.

27Given that there is some educational mobility between the DROMs and metropolitan France and that educational infrastructure differs between territories, it would have been interesting to refine the analysis by neutralizing the effect of the location of studies (individuals who studied only in the DROMs, in the DROMs then in metropolitan France, etc.). Incorporating this information would be problematic, however. Migration is an endogenous decision for those born in a DROM. It depends in part on unobservable individual characteristics that can also influence academic achievement (motivation, school results, etc.). Temporal et al. (2011) noted that migrants reach higher levels of education than individuals with similar observable characteristics who stayed in their DROM. Consequently, including the location of studies would risk disrupting the analysis, whose objective is to understand the impact of exogenous elements influencing the quality of human capital transmitted by an individual’s parents on their subsequent level of education.

III – Analysis of the determinants of educational inequalities between individuals born in overseas territories and in metropolitan France

1 – Econometric strategy

28To measure the impact of the abovementioned characteristics on inequalities in levels of education between individuals born in a DROM versus in metropolitan France, we use an ordered probit model on the data for all individuals, regardless of whether they had completed their studies at the time of the survey; that is, taking into account that some of the data are censored. [20] As 19.6% of the individuals in our sample may have ultimately reached a higher level of education than that reported at the time of the survey, they must be considered separately from the others. Not including them would create a sample selection problem that could bias the analysis. To take this censoring problem into account, we estimate a modified ordered probit model, which allows all individuals to be included while considering them separately depending on whether they had completed their studies at the time of observation. More precisely, we estimate, for each individual i, in a different manner de pending on whether they had completed their studies [21], the probability educ_i of attaining each of the four levels of education presented in Table 1. The ordered probit model includes all individuals and is written as follows:

29

30where X_i is a vector of all control variables, b is the coefficient associated with X_i, and u_i ~ N(0,1) is the error term, educ_i = 0 if educ_i^* ≤ a₁, educ_i = 1 if a₁ < educ_i^* ≤ a₂, educ_i = 2 if a₂ < educ_i^* ≤ a₃, educ_i = 3 if educ_i^* > a₃.

31Within this model, individuals who have completed their studies are distinguished from others. For those who have completed their studies, the probability P[educ_i = j] of individual i reaching level of education j is estimated:

32

33where φ is the standard normal distribution function. For respondents still in school, a censored probability is estimated, which differs from the first and is such that they can at minimum reach the level of education declared at the time of the survey, or exceed it. This probability is as follows:

34

35The dichotomous variable α = 1 if individual i has finished their studies, and α = 0 if still a student, then the probability P[educ_i = j] of reaching level of education j, regardless of α, is written:

36

37The model parameters are estimated by maximum likelihood. [22] The values and signs of the coefficients can be used to compare the educational levels of individuals with respect to each control variable, including place of birth. [23]

38The results are presented below, including all the elements whose potential influence was discussed in Section II, step by step. The five regressions are presented in Table 3. [24] The first column, including only place of birth, assesses whether the differences between the DROMs and metropolitan France are significant. The second column adds individuals’ sex and age. The third adds the family’s perceived material and financial situation during childhood, as well as the parents’ social origin (via the SPC of the two parents). In the fourth, several indicators of the respondents’ cultural origin are included: language spoken in the family during childhood and parents’ foreign or DROM origin. Finally, the fifth column contains an additional set of variables concerning the childhood living environment: sibship size and sibling rank, family type, problems in the family (violence, alcoholism, etc.), and having a room for homework as well as help from parents and/or siblings.

2 – At a given age and sex, individuals born in metropolitan France have completed more education than those born in a DROM

39The level of education attained by individuals born in any one of the DROMs is significantly lower than that attained by those born in metropolitan France (Table 3, Column 1). Sex and age have significant effects (Column 2), but their inclusion makes little difference to the effect of place of birth. In particular, while the coefficient associated with age is low, [25] being a woman has a greater effect. However, taking gender into account does little to change the differences between departments. Women from all territories in the studied cohorts are more educated on average than men (Appendix Table A.1), including with matched characteristics (cf. the regressions by DROM in Appendix Table A.2). Thus, for a given age and sex, individuals born in metropolitan France have significantly higher levels of education than individuals born in the Antilles, who themselves have much higher levels than those born in French Guiana and especially Réunion.

Table 3: Effects of individual and family characteristics on educational level attained (ordered probit model)

(1) (2) (3) (4) (5) Place of birth Metropolitan France Ref. Ref. Ref. Ref. Ref. Guadeloupe – 0.23*** (0.05) – 0.23*** (0.05) – 0.24*** (0.05) – 0.12* (0.07) – 0.00 (0.07) Martinique – 0.22*** (0.05) – 0.24*** (0.05) – 0.26*** (0.05) – 0.16** (0.07) – 0.07 (0.07) French Guiana – 0.46*** (0.05) – 0.48*** (0.05) – 0.44*** (0.05) – 0.32*** (0.06) – 0.20*** (0.06) Réunion – 0.54*** (0.04) – 0.55*** (0.04) – 0.46*** (0.04) – 0.15** (0.07) – 0.07 (0.08) Female 0.24*** (0.02) 0.28*** (0.02) 0.27*** (0.02) 0.31*** (0.02) Age – 0.01*** (0.00) – 0.00 (0.00) – 0.00 (0.00) 0.00 (0.00) Serious family financial problems(a) – 0.21*** (0.03) – 0.20*** (0.03) – 0.07** (0.03) Father’s SPC Unknown – 1.16*** (0.10) – 1.09*** (0.10) – 0.95*** (0.10) Inactive or unemployed (never held paid employment) – 1.41*** (0.14) – 1.36*** (0.14) – 1.27*** (0.14) Manual worker, farmer – 0.94*** (0.06) – 0.90*** (0.06) – 0.85*** (0.06) Clerical or sales worker – 0.72*** (0.07) – 0.69*** (0.07) – 0.66*** (0.07) Artisan – 0.68*** (0.07) – 0.65*** (0.07) – 0.64*** (0.07) Intermediate occupation – 0.29*** (0.07) – 0.28*** (0.07) – 0.28*** (0.07) Manager/ professional Ref. Ref. Ref. Mother’s SPC Unknown – 1.41*** (0.14) – 1.40*** (0.14) – 1.18*** (0.14) Inactive or unemployed (never held paid employment) – 0.92*** (0.09) – 0.87*** (0.09) – 0.77*** (0.09) Manual worker, farmer – 0.82*** (0.09) – 0.78*** (0.09) – 0.74*** (0.09) Clerical or sales worker – 0.68*** (0.09) – 0.65*** (0.09) – 0.62*** (0.09) Artisan – 0.66*** (0.11) – 0.64*** (0.11) – 0.64*** (0.11) Intermediate occupation – 0.31*** (0.09) – 0.30*** (0.09) – 0.29*** (0.09) Manager/ professional Ref Ref. Ref. Language spoken most often by mother during childhood French Ref. Ref. Creole – 0.12 (0.07) – 0.06 (0.07) Another language or had no (or little) exchange with mother 0.09** (0.04) 0.08* (0.05) Language spoken most often by father during childhood French Ref. Ref. Creole – 0.15** (0.07) – 0.20*** (0.07) Another language or had no (or little) exchange with father – 0.17*** (0.04) – 0.08* (0.04)

Table 3: Effects of individual and family characteristics on educational level attained (ordered probit model)

(1) (2) (3) (4) (5) French spoken in family (a) 0.14*** (0.04) 0.11** (0.05) Descendant of at least one immigrant parent 0.01 (0.03) 0.04 (0.03) At least one parent born in the DROMs – 0.05 (0.05) – 0.02 (0.05) Number of siblings 0 Ref. 1 0.02 (0.06) 2 – 0.14** (0.06) 3 – 0.20*** (0.06) 4 or more – 0.35*** (0.06) Sibling rank 1st Ref. 2nd – 0.06* (0.03) 3rd – 0.07* (0.04) 4th or higher – 0.08* (0.04) Grew up mainly… with both parents Ref. with mother only – 0.34*** (0.04) with father only – 0.19 (0.13) in a reconstituted/ blended family – 0.23*** (0.08) with grandparents – 0.47*** (0.10) Other (hostel, collective housing. etc.) – 0.11** (0.05) Experienced personal violence in the family(a) – 0.25*** (0.06) Parent’s alcoholism(a) – 0.16*** (0.04) Parent’s illness, disabilities, etc. (a) – 0.03 (0.03) Serious arguments or conflicts between parents (a) – 0.02 (0.03) Had a room to do homework in alone 0.18*** (0.03) Help with homework from parents Often Ref. Sometimes 0.13*** (0.03) Never/not applicable 0.11*** (0.03) Help with homework from siblings Often Ref. Sometimes 0.06 (0.04) Never/not applicable 0.06* (0.04) Number of observations 9,992 9,992 9,992 9,992 9,992 Log likelihood – 11,560.5 – 11,500.8 – 10,822.8 – 10,789.0 – 10,606.5

(a) Before age 18.
* p < .10. ** p < .05. *** p < .01. Standard deviations in parentheses.
Coverage: Individuals aged 18–34 born in metropolitan France, Guadeloupe, Martinique, French Guiana, and Réunion.

3 – Level of education differs by parents’ social origin mainly among individuals from Réunion and French Guiana

40Taking into account the family’s financial situation during childhood and the parents’ social origin (Table 3, Column 3) decreases the gap between individuals from metropolitan France and Réunion, and to a lesser extent French Guiana, largely because individuals from Réunion and French Guiana are more likely not to have parents who work in an intermediate or managerial/professional occupation (Table 2). Parents in a high SPC have a positive effect on their children’s educational attainment in all territories (Appendix Table A.2). The level of family financial insecurity during childhood reported by individuals from French Guiana differs little from that reported by individuals from metropolitan France. [26] However, in Réunion more than for the other DROMs, disadvantaged social origins are a source of inequality in levels of education with respect to metropolitan France (Appendix Table A.3, Interaction B).

4 – Family cultural characteristics play an important role in all groups, but more so among those from Réunion

41Including cultural characteristics (language spoken in the family, parents’ foreign or DROM origin) as additional control variables (Table 3, Column 4) has a significant impact on differences in level of education between those born in a DROM and in metropolitan France. The differences remain significant, but they decrease markedly. In particular, the difference between individuals born in Réunion and in metropolitan France decreases by more than two-thirds between Columns 3 and 4. Family cultural characteristics also explain a non-negligible portion of the difference between metropolitan France and the other three DROMs: a drop of 30%–50% is observed between Columns 3 and 4 in the coefficients associated with the level of education of those born in these territories. These results reflect the differences between groups observed in Table 2, but also the effect of these variables depending on individuals’ place of birth (Appendix Tables A.2 and A.3). For those from Réunion, the effect is mainly due to the large number of people not to have spoken French with their parents during childhood (Table 2). Indeed, this variable is an important marker of low levels of education in Réunion (Appendix Table A.2) compared to metropolitan France (Appendix Table A.3, Interaction E), as most of those in the latter group spoke French with their families during childhood, unlike those from Réunion (Table 2). Individuals from French Guiana are also slightly more likely than those in other groups not to have spoken French during childhood, and this variable plays a major role in the difference between this group and the group born in metropolitan France (Appendix Table A.3, Interaction E). French Guiana is a significant destination for immigration, and many of those born in this territory are also descendants of at least one immigrant parent (Table 2). This status weighs negatively on levels of education in French Guiana (Appendix Table A.2), also compared to individuals from other overseas territories, whether or not they are descendants of immigrants (Appendix Table A.3, Interaction F).

5 – Taking family living conditions into account explains almost all remaining differences

42Taking into account living conditions during childhood explains all remaining gaps between those born in metropolitan France or in a DROM, aside from French Guiana (Table 3, Column 5). In the final model, for natives of Guadeloupe, Martinique, and Réunion, the differences with the metropolitan France group are either zero or non-significant. For respondents from French Guiana, although the difference remains significant and substantial, it drops significantly between Columns 4 and 5.

43A first explanatory factor is that more of those from the DROMs are from a large group of siblings (3 or more siblings) (Table 2), a situation that is also a little more of a hindrance to academic achievement for those born in a DROM versus in metropolitan France (Appendix Table A.3, Interaction H). Moreover, due to larger sibships, individuals from the DROMs are less often the eldest child. Being the eldest favours academic achievement, although this applies more among those born in metropolitan France and less among those born overseas (Appendix Table A.3, Interaction I). Among individuals born in French Guiana, not being the eldest child has a negative effect on level of education. The sizes of the effects of sibship size and sibling rank on level of education differ between individuals born in a DROM and in metropolitan France, doubtless because the circumstances of life within households tend to differ between the DROMs and the metropolis. Notably, in some DROMs, the household is more often likely to extend beyond siblings and parents, which can modify the effect of sibship size and sibling rank on level of education (Marie and Breton, 2015, mention the existence of many complex households in the DROMs). [27] Another difference between overseas and metropolitan households that likely influences the effect of birth order and number of siblings on level of education is the greater frequency of single-parent families in the DROMs.

44The second explanatory factor—having grown up with both parents—is more common among individuals from metropolitan France and has a slightly greater positive effect on level of education in this group than among individuals from a DROM (Appendix Table A.3, Interaction J). For French Guiana, it even has no effect. One of the possible explanations once again relates to the reality of family life in this territory. Due to the size of the department, its low population density, and the existence of a large number of isolated residential areas, many young people in French Guiana attend school far from the parental home and are housed with host families during the school term (CNDH, 2017). Even when they report having grown up in a two-parent family, this does not necessarily correspond to the same reality in French Guiana as in other territories. Similarly, since complex families are more common in French Guiana (Marie and Breton, 2015) and sibships larger, the effect of living with both parents may be reduced.

45Certain markers of family living conditions during childhood, such as having experienced personal violence and parental alcoholism, also play an important role in the educational attainment gap between young people from a DROM compared to metropolitan France. For individuals from all territories, these two phenomena are negatively linked to level of education in comparison to the reference situation (having been born in metropolitan France and not having experienced parental alcoholism), although the coefficients are not always significant (Appendix Table A.3, Interactions K and L). These situations are more common in the DROMs (Table 2). With a few exceptions, these phenomena have a greater impact overall on inequalities between territories (Appendix Table A.3) than within the same territory (Appendix Table A.2). This may be linked, first, to the existence of significant differences between territories, and second, to competition with other sources of inequality within each territory.

46The availability of a room to do homework in alone also plays a role in the educational inequalities between individuals from a DROM and those from metropolitan France. This situation is not only more common in metropolitan France than the DROMs (Table 2), but it has a greater positive impact on the level of education attained in the former than in the latter, except in Guadeloupe (Appendix Table A.3, Interaction O).

47Frequent help from parents with homework, which is less common among individuals from French Guiana and Réunion than others (Table 2), on the other hand, has little effect on differences in educational attainment between individuals from the different territories. Specifically, young people from metropolitan France and Guadeloupe who sometimes or never had parental help had higher levels of education than those who often received such help, while no effect was detected for the other territories (Appendix Table A.2; Appendix Table A.3, Interaction P). There are several possible explanations for this initially surprising result. It may be linked to a reverse causal effect that weakens the potentially positive effect of the help: a portion of those who receive the most help are those who experience the most difficulties. It may also be due to the variable referring to parental help without specifying a precise period. [28] Help may be more common in the earlier school years, as almost all parents have the skills to help their children at these levels, which may become less the case at increasing grade levels. The proportion of individuals reporting help from their parents may thus be expected to be higher among those who ended their education at a young age. Frequent help from siblings, on the other hand, is more common among individuals from a DROM (Table 2) than from metropolitan France, which is at least partly due to larger sibships in the DROMs. It is not straightforward to explain why some young people who were sometimes or never helped by their siblings did better than those often helped by their siblings (Appendix Table A.2; Appendix Table A.3, Interaction Q). As we control for sibship size, it cannot be related to individuals born in a DROM having more siblings. Another explanation, as with parental help, is that as the level of education increases, the frequency of help may decrease, so that those who reported often receiving help are more likely to be individuals who ended their studies earlier.

48Finally, the only difference with respect to metropolitan France that remains unexplained by our models concerns individuals born in French Guiana. Unlike the other DROMs, the difference in educational attainment between this group and individuals from metropolitan France seems not to be entirely explained by factors influencing the quality of human capital transmitted by parents.

49Because average levels of education in France differ between women and men (Picard and Wolff, 2014; Chabanon and Steinmetz, 2018), the assessments are produced separately for the two sexes. Table 4 confirms that the control variables almost entirely explain the differences in educational attainment between individuals born in a DROM and in metropolitan France, for both women and men. Some variables have a greater effect in one sex than in the other, however. Financial problems during childhood weigh more heavily on men’s educational attainment. Women are at more of a disadvantage than men when they are from a family with more siblings, and if they had an alcoholic parent. It could be that, in these cases, they take on more tasks within the family neglected by parents (such as taking care of siblings). However, women also benefit more than men from factors with a positive impact on level of education, such as the use of French in the family and having grown up with both parents.

Table 4: Effects of individual and family characteristics of women and men on educational level attained (ordered probit model)

Women Men (1) (2) (3) (4) Place of birth Metropolitan France Ref. Ref. Guadeloupe – 0.19*** (0.07) 0.01 (0.10) – 0.29*** (0.07) – 0.08 (0.10) Martinique – 0.21*** (0.06) – 0.09 (0.10) – 0.30*** (0.08) – 0.14 (0.11) French Guiana – 0.50*** (0.06) – 0.21** (0.08) – 0.44*** (0.07) – 0.25*** (0.09) Réunion – 0.56*** (0.05) – 0.06 (0.11) – 0.55*** (0.06) – 0.11 (0.11) Age – 0.00 (0.00) 0.01** (0.00) Serious family financial problems(a) – 0.02 (0.04) – 0.13*** (0.04) Father’s SPC Unknown – 0.93*** (0.14) – 1.01*** (0.15) Inactive or unemployed Never held paid – 1.26*** (0.18) – 1.29*** (0.23) employment Manual worker, farmer – 0.81*** (0.08) – 0.90*** (0.09) Clerical or sales worker – 0.61*** (0.09) – 0.71*** (0.10) Artisan – 0.61*** (0.09) – 0.67*** (0.10) Intermediate occupation – 0.23** (0.10) – 0.32*** (0.09) Manager/professional Ref. Ref. Mother’s SPC Unknown – 1.00*** (0.20) – 1.34*** (0.22) Inactive or unemployed Never held paid – 0.62*** (0.13) – 0.92*** (0.13) employment Manual worker, farmer – 0.58*** (0.13) – 0.90*** (0.13) Clerical or sales worker – 0.46*** (0.12) – 0.76*** (0.13) Artisan – 0.52*** (0.15) – 0.74*** (0.16) Intermediate occupation – 0.14 (0.13) – 0.42*** (0.13) Manager/professional Ref. Ref. Language spoken most often by mother during childhood French Ref. Ref. Creole 0.02 (0.11) – 0.15 (0.11) Other language or had no (or little) exchange with mother 0.10 (0.06) 0.10 (0.07) Language spoken most often by father during childhood French Ref. Ref. Creole – 0.20** (0.10) – 0.23** (0.11) Another language or had no (or little) exchange with father – 0.07 (0.05) – 0.12** (0.06) French spoken in family (a) 0.23*** (0.06) – 0.04 (0.07) Descendant of at least one immigrant parent (0.05) 0.00 (0.05) At least one parent born in the DROMs 0.050.07 (0.07) – 0.08 (0.07)

Table 4: Effects of individual and family characteristics of women and men on educational level attained (ordered probit model)

Women Men (1) (2) (3) (4) Number of siblings 0 Ref. Ref. 1 – 0.05 (0.08) 0.11 (0.08) 2 – 0.25*** (0.08) – 0.00 (0.08) 3 – 0.29*** (0.09) – 0.08 (0.09) 4 or more – 0.48*** (0.09) – 0.18* (0.09) Sibling rank 1st Ref. Ref. 2nd – 0.05 (0.05) – 0.07 (0.05) 3rd – 0.06 (0.06) – 0.09 (0.06) 4th or higher – 0.09 (0.06) – 0.08 (0.07) Grew up mainly… with both parents Ref. Ref. with mother only – 0.45*** (0.05) – 0.13** (0.06) with father only – 0.32* (0.18) – 0.04 (0.19) in a reconstituted/ blended family – 0.35*** (0.11) – 0.11 (0.11) with grandparents – 0.59*** (0.15) – 0.36** (0.15) Other (hostel, collective housing, etc.) – 0.61*** (0.23) – 0.23 (0.26) Suffered personal violence in the family(a) – 0.21*** (0.08) – 0.26*** (0.09) Parent’s alcoholism(a) – 0.25*** (0.06) – 0.05 (0.06) Parent’s illness, disabilities, etc. (a) – 0.07 (0.04) 0.01 (0.05) Serious arguments or conflicts between parents (a) – 0.02 (0.04) – 0.01 (0.05) Had a room to do homework in alone 0.16*** (0.04) 0.20*** (0.04) Help with homework from parents Often Ref. Ref. Sometimes 0.09* (0.05) 0.17*** (0.05) Never/not applicable 0.06 (0.05) 0.16*** (0.05) Help with homework from siblings Often Ref. Ref. Sometimes 0.01 (0.05) 0.12** (0.06) Never/not applicable 0.03 (0.05) 0.11** (0.06) Number of observations 5,298 5,298 4,694 4,694 Log likelihood – 5,951.2 – 5,428.6 – 5,534.0 – 5,118.4

(a) Before age 18.
* p < .10. ** p < .05. *** p < .01. Standard deviations in parentheses.
Coverage: Individuals aged 18–34 born in metropolitan France, Guadeloupe, Martinique, French Guiana, and Réunion.

Conclusion

50There are significant economic inequalities between the DROMs and metropolitan France. They are found in both income (Michel et al., 2010) and employment (Lasserre, 2018). The economic development of the DROMs, as well as the improvement of the labour market integration of individuals from the DROMs both in the overseas territories and in metropolitan France, depend largely on improvement in the initial levels of education attained by young people from the DROMs (L’Horty, 2014), which are much lower than those of young people from metropolitan France. But to improve their levels of education, the sources of their lower academic performance must be identified.

51Based on detailed data on the social origins of young people born in a DROM and in metropolitan France, this article provides new results that shed light on the origins of educational inequalities between the French overseas territories and metropolitan France. These inequalities are partly explained by the higher likelihood of individuals from a DROM to come from a disadvantaged social background. In particular, they are likely to be from families that have experienced serious financial difficulties, with parents very often from lower socio-occupational categories, who are thus less able to help their children succeed in school. In addition, young people from the DROMs are less likely to speak French with their families during childhood, increasing the educational difficulties facing many children in these departments, where education takes place primarily in French. The people of Réunion are the most affected by this phenomenon. Individuals from a DROM are also more likely to come from large families and difficult contexts (violence, alcoholism, etc.). We thus found that given identical family, social, and cultural characteristics, only natives of French Guiana have significantly lower levels of education than natives of metropolitan France. According to some studies, the latter may be explained by the lower quality of education and the particular geographical context in French Guiana (CNCDH, 2017; DEPP, 2017). In particular, the risk of early school leaving is greater than in the other DROMs, beginning in lower secondary school. This phenomenon results from the poor geographical distribution of educational institutions, with much lower numbers of middle and upper secondary schools per school-age person than in other departments. Many residential areas in French Guiana are located far from schools, and the territory lacks school transport networks. In addition, it lacks teachers and struggles to attract them.

52To improve the level of education of young people in the French overseas territories compared to metropolitan France, policies are needed to compensate for the lesser ability of some parents to help their children succeed in school. This could be achieved by providing more resources to teachers in schools (for example, by reducing class sizes significantly from an early age; cf. Bouguen et al., 2017) and by developing social policies that help to prevent phenomena such as domestic violence (more common in Guadeloupe and Réunion), alcoholism (more common in Réunion), etc. These policies must consider the heterogeneity of the different territories. While most of these phenomena play a role everywhere, their intensity varies between places. Having a parent who had problems with alcohol and not having spoken French with family during childhood, for example, largely explains the lower level of education of individuals from Réunion, while individuals from French Guiana are more affected by large sibships and not having the space to do their homework individually. This study’s results are thus consistent with previous research suggesting that the transmission of human capital within the family lies at the centre of the educational inequalities that mark French society (Goux and Maurin, 1995; Meuret and Morlaix, 2006; OECD, 2015). They indicate that this phenomenon is particularly significant when young people born in a DROM and in metropolitan France are distinguished.

Appendix

Table A.1: Level of education attained by women and men aged 18–34 who either had or had not completed their studies at the time of the survey, by place of birth

Metropolitan France Guadeloupe Martinique French Guiana Réunion Overall Women No qualifications, lower secondary certificate (BEPC) 12.0 14.2 15.1 28.6 27.6 12.3 Intermediate vocational certificate (CAP, BEP) 19.2 18.7 15.8 11.6 17.1 19.2 Baccalauréat (vocational or general) 29.3 33.0 28.7 30.4 28.1 29.3 ≥ Baccalauréat + 2 years higher education 39.5 34.2 40.4 29.3 27.2 39.2 Number of observations 3,704 302 391 339 562 5,298 Men No qualifications, lower secondary certificate (BEPC) 14.9 21.5 26.8 41.0 31.3 15.3 Intermediate vocational certificate (CAP, BEP) 22.2 35.6 31.0 32.6 35.4 22.6 Baccalauréat (vocational or general) 29.1 17.8 23.8 14.6 18.9 28.8 ≥ Baccalauréat + 2 years higher education 33.8 25.1 18.3 11.8 14.4 33.3 Number of observations 3,519 276 229 256 414 4,694

Table A.1: Level of education attained by women and men aged 18–34 who either had or had not completed their studies at the time of the survey, by place of birth

Coverage: Individuals aged 18–34 years born in metropolitan France, Guadeloupe, Martinique, French Guiana, and Réunion.

Table A.2: Effects of individual and family characteristics on educational level attained, for each DROM and metropolitan France (ordered probit model)

Metropolitan France Guadeloupe Martinique French Guiana Réunion Female 0.30*** (0.03) 0.38*** (0.10) 0.41*** (0.10) 0.29*** (0.10) 0.35*** (0.08) Age – 0.00 (0.00) – 0.00 (0.01) 0.01 (0.01) 0.01 (0.01) 0.02* (0.01) Serious family financial problems(a) – 0.06* (0.04) – 0.29** (0.12) 0.07 (0.12) – 0.22* (0.12) 0.06 (0.09) Father’s SPC Unknown – 1.01*** (0.15) – 0.74* (0.39) – 0.65* (0.35) – 0.64** (0.32) – 0.72** (0.33) Inactive or unemployed (never held paid employment) – 2.65*** (0.52) – 0.52 (0.52) – 0.08 (0.53) – 0.68** (0.35) – 1.41*** (0.33) Manual worker, farmer – 0.90*** (0.07) – 0.25 (0.29) – 0.72*** (0.25) – 0.41 (0.27) – 0.90*** (0.26) Clerical or sales worker – 0.69*** (0.08) – 0.04 (0.32) – 0.52* (0.28) – 0.31 (0.28) – 0.74*** (0.27) Artisan – 0.68*** (0.08) – 0.12 (0.30) – 0.53** (0.27) – 0.31 (0.28) – 0.57** (0.28) Intermediate occupation – 0.33*** (0.08) 0.39 (0.31) – 0.14 (0.29) 0.27 (0.30) – 0.48* (0.27) Manager/ professional Ref. Ref. Ref. Ref. Ref. Mother’s SPC Unknown – 0.96*** (0.22) – 1.93*** (0.49) – 1.46** (0.65) – 1.31*** (0.39) – 1.12*** (0.35) Inactive or unemployed, never held paid employment – 0.78*** (0.12) – 1.08*** (0.33) – 0.80** (0.34) – 0.97*** (0.29) – 0.48* (0.28) Manual worker, farmer – 0.75*** (0.12) – 0.86*** (0.33) – 0.79** (0.34) – 0.95*** (0.29) – 0.52* (0.29) Clerical or sales worker – 0.59*** (0.12) – 0.91*** (0.31) – 0.62* (0.32) – 0.79*** (0.27) – 0.54** (0.27) Artisan – 0.68*** (0.14). – 1.19*** (0.37) – 0.70* (0.42) – 0.39 (0.36) – 0.07 (0.37) Intermediate occupation – 0.23* (0.12) – 0.73** (0.33) – 0.48 (0.34) – 0.52* (0.30) – 0.10 (0.31) Manager/ professional Ref Ref. Ref. Ref. Ref. Language spoken most often by mother during childhood French Ref. Ref. Ref. Ref. Ref. Creole 0.31* (0.19) 0.37 (0.25) – 0.21 (0.28) – 0.03 (0.25) – 0.02 (0.20) Other language or had no (or little) exchange with mother 0.04 (0.05) 0.04 (0.33) 0.22 (0.30) – 0.22 (0.20) – 0.11 (0.31) Language spoken most often by father during childhood French Ref. Ref. Ref. Ref. Ref. Creole – 0.37** (0.17) – 0.44* (0.23) – 0.15 (0.23) – 0.27 (0.30) – 0.35** (0.17) Another language or had no (or little) exchange with father – 0.02 (0.05) – 0.35** (0.14) – 0.23* (0.13) – 0.22 (0.15) – 0.50*** (0.18) French spoken in family 0.00 (0.06) 0.17 (0.24) 0.15 (0.31) – 0.11 (0.22) 0.44** (0.18) Descendant of at least one immigrant parent 0.07* (0.04) – 0.13 (0.25) – 0.42 (0.29) – 0.27** (0.13) 0.00 (0.30) At least one parent born in the DROMs – 0.06 (0.06) – 0.44 (0.32) – 0.10 (0.39) – 0.07 (0.14) – 0.43 (0.35)

Table A.2: Effects of individual and family characteristics on educational level attained, for each DROM and metropolitan France (ordered probit model)

Metropolitan France Guadeloupe Martinique French Guiana Réunion Number of siblings 0 Ref. Ref. Ref. Ref. Ref. 1 0.02 (0.07) 0.28 (0.26) 0.18 (0.21) – 0.33 (0.27) 0.01 (0.23) 2 – 0.11 (0.07) 0.32 (0.26) 0.03 (0.22) – 0.63** (0.27) – 0.46** (0.23) 3 – 0.17** (0.08) – 0.03 (0.27) – 0.02 (0.23) – 0.63** (0.27) – 0.38 (0.24) 4 or more – 0.29*** (0.08) – 0.19 (0.28) – 0.25 (0.24) – 0.89*** (0.26) – 0.65*** (0.24) Sibling rank 1st Ref. Ref. Ref. Ref. Ref. 2nd – 0.06 (0.04) 0.04 (0.14) – 0.19 (0.13) 0.07 (0.15) – 0.10 (0.11) 3rd – 0.12** (0.05) – 0.17 (0.17) – 0.21 (0.17) 0.14 (0.18) 0.13 (0.12) 4th or higher – 0.17*** (0.06) 0.19 (0.20) – 0.09 (0.18) 0.18 (0.16) 0.04 (0.13) Grew up mainly… with both parents Ref. Ref. Ref. Ref. Ref. with mother only – 0.37*** (0.05) 0.19 (0.16) – 0.36** (0.15) – 0.17 (0.15) – 0.13 (0.15) with father only – 0.19 (0.17) 0.12 (0.58) – 0.17 (0.58) – 0.22 (0.37) 0.12 (0.46) in a reconstituted/ blended family – 0.18* (0.09) – 0.39 (0.41) – 0.22 (0.32) 0.02 (0.29) – 0.09 (0.29) with grandparents – 0.67*** (0.19) 0.01 (0.34) – 0.30 (0.42) – 0.03 (0.26) – 0.26 (0.33) Other (hostel, collective housing, – 0.06 (0.28) – 0.24 (0.67) – 0.66 (0.52) – 0.24 (0.44) – 0.27 (0.47) etc.) Suffered personal violence in the family (a) – 0.30*** (0.08) – 0.15 (0.21) – 0.25 (0.21) – 0.17 (0.21) – 0.13 (0.15) Parent’s alcoholism(a) – 0.16*** (0.06) – 0.39** (0.17) – 0.18 (0.19) – 0.10 (0.16) – 0.03 (0.10) Parent’s illness, etc. (a) – 0.05 (0.04) – 0.08 (0.14) – 0.01 (0.14) 0.31** (0.15) – 0.06 (0.10) Serious arguments or conflicts between parents (a) 0.00 (0.04) 0.19 (0.12) – 0.02 (0.12) – 0.03 (0.13) – 0.13 (0.09) Had a room to do homework in alone 0.13*** (0.04) 0.34*** (0.12) 0.43*** (0.11) 0.40*** (0.12) 0.14 (0.09) Help with homework from parents Often Ref. Ref. Ref. Ref. Ref. Sometimes 0.15*** (0.04) 0.29** (0.13) – 0.04 (0.13) 0.06 (0.15) – 0.10 (0.11) Never/not applicable 0.12*** (0.04) 0.24* (0.14) 0.09 (0.14) 0.09 (0.15) – 0.17 (0.11) Help with homework from siblings Often Ref. Ref. Ref. Ref. Ref. Sometimes 0.07 (0.05) 0.10 (0.16) 0.05 (0.17) 0.09 (0.17) 0.00 (0.13) Never/not applicable 0.05 (0.05) 0.29* (0.16) – 0.02 (0.17) 0.28* (0.16) 0.01 (0.12) Number of observations 7,223 578 620 595 976 Log likelihood – 7,456.9 – 620.5 – 673.9 – 629.9 – 1,092.7

(a) Before age 18.
* p < .10. ** p < .05. *** p < .01. Standard deviations in parentheses.
Coverage: Individuals aged 18–34 years born in metropolitan France, Guadeloupe, Martinique, French Guiana, and Réunion.

Table A.3: Educational level attained (ordered probit model): Introduction of interaction variables: Place of birth × …

A. Place of birth × Sex B. Place of birth × Serious family financial problems during childhood(c) Metropolitan France × Male Ref. Metropolitan France × No problems Ref. Metropolitan France × Female 0.30*** (0.03) Metropolitan France × Problems – 0.06* (0.03) Guadeloupe × Male – 0.04 (0.09) Guadeloupe × No problems 0.04 (0.08) Guadeloupe × Female 0.34*** (0.09) Guadeloupe × Problems – 0.13 (0.10) Martinique × Male – 0.12 (0.10) Martinique × No problems – 0.09 (0.08) Martinique × Female 0.26*** (0.08) Martinique × Problems – 0.08 (0.10) French Guiana × Male – 0.17** (0.09) French Guiana × No problems – 0.15** (0.07) French Guiana × Female 0.08 (0.08) French Guiana × Problems – 0.38*** (0.10) Réunion × Male – 0.05 (0.09) Réunion × No problems – 0.08 (0.08) Réunion × Female 0.22*** (0.08) Réunion × Problems – 0.09 (0.10) Other control variables (a) Yes Other control variables (b) Yes Number of observations 9,992 Number of observations 9,992

(a) Variables in Table 3, excluding place of birth and sex.
(b) Variables in Table 3, excluding place of birth and serious family financial problems during childhood.
(c) Before age 18.
* p < .10. ** p < .05. *** p < .01. Standard deviations in parentheses.
Coverage: Individuals aged 18–34 years born in metropolitan France, Guadeloupe, Martinique, French Guiana, and Réunion.

C. Place of birth × Father’s SPC D. Place of birth × Mother’s SPC Metropolitan France × Neither manager/ professional nor intermediate occupation Ref. Metropolitan France × Neither manager/ professional nor intermediate occupation Ref. Metropolitan France × Manager/professional or intermediate occupation 0.61*** (0.04) Metropolitan France × Manager/professional or intermediate occupation 0.44*** (0.05) Guadeloupe × Neither manager/professional nor intermediate occupation 0.01 (0.08) Guadeloupe × Neither manager/professional nor intermediate occupation 0.02 (0.08) Guadeloupe × Manager/ professional or intermediate occupation 0.48*** (0.13) Guadeloupe × Manager/ professional or intermediate occupation 0.32** (0.14) Martinique × Neither manager/professional nor intermediate occupation – 0.07 (0.08) Martinique × Neither manager/professional nor intermediate occupation – 0.04 (0.08) Martinique × Manager/ professional or intermediate occupation 0.43*** (0.14) Martinique × Manager/ professional or intermediate occupation 0.22* (0.13) French Guiana × Neither manager/professional nor intermediate occupation – 0.21*** (0.07) French Guiana × Neither manager/professional nor intermediate occupation – 0.19*** (0.07) French Guiana × Manager/ professional or intermediate occupation 0.38*** (0.14) French Guiana × Manager/ professional or intermediate occupation 0.25* (0.14) Réunion × Neither manager/ professional nor intermediate occupation – 0.09 (0.08) Réunion × Neither manager/ professional nor intermediate occupation – 0.08 (0.08) Réunion × Manager/ professional or intermediate occupation 0.49*** (0.12) Réunion × Manager/ professional or intermediate occupation 0.44*** (0.14) Other control variables (a) Yes Other control variables b) Yes Number of observations 9,992 Number of observations 9,992

(a) Variables in Table 3, excluding place of birth and father’s SPC.
(b) Variables in Table 3, excluding place of birth and mother’s SPC.
* p < .10. ** p < .05. *** p < .01. Standard deviations in parentheses.
Coverage: Individuals aged 18–34 years born in metropolitan France, Guadeloupe, Martinique, French Guiana, ans Réunion.

E. Place of birth × French spoken in family during childhood F. Place of birth × Descendant of at least one immigrant parent Metropolitan France × Not spoken Metropolitan France × Spoken Ref. – 0.02 (0.05) Metropolitan France × Not a descendant Metropolitan France × Descendant Ref. 0.09** (0.04) Guadeloupe × Not spoken – 0.19 (0.14) Guadeloupe × Not a descendant 0.08 (0.08) Guadeloupe × Spoken – 0.02 (0.09) Guadeloupe × Descendant 0.05 (0.21) Martinique × Not spoken – 0.28 (0.19) Martinique × Not a descendant 0.03 (0.08) Martinique × Spoken – 0.07 (0.09) Martinique × Descendant – 0.39 (0.28) French Guiana × Not spoken – 0.40*** (0.10) French Guiana × Not a descendant – 0.01 (0.09) French Guiana × Spoken – 0.18** (0.09) French Guiana × Descendant – 0.28*** (0.09) Réunion × Not spoken – 0.44*** (0.10) Réunion × Not a descendant 0.01 (0.08) Réunion × Spoken 0.13 (0.10) Réunion × Descendant 0.10 (0.28) Other control variables (a) Yes Other control variables (b) Yes Number of observations 9,992 Number of observations 9,992

(a) Variables in Table 3, excluding place of birth and French spoken in family during childhood.
(b) Variables in Table 3, excluding place of birth and having at least one immigrant parent.
* p < .10. ** p < .05. *** p < .01. Standard deviations in parentheses.
Coverage: Individuals aged 18–34 years born in metropolitan France, Guadeloupe, Martinique, French Guiana, and Réunion.

G. Place of birth × At least one parent born in a DROM Metropolitan France × Not born in a DROM Ref. Metropolitan France × Born in a DROM – 0.04 (0.06) Guadeloupe × Not born in a DROM 0.16 (0.26) Guadeloupe × Born in a DROM – 0.02 (0.06) Martinique × Not born in a DROM – 0.06 (0.36) Martinique × Born in a DROM – 0.09 (0.06) French Guiana × Not born in a DROM – 0.30*** (0.09) French Guiana × Born in a DROM – 0.17** (0.07) Réunion × Not born in a DROM 0.36 (0.30) Réunion × Born in a DROM – 0.10 (0.07) Other control variables (a) Yes Number of observations 9,992

(a) Variables in Table 3, excluding place of birth and at least one parent born in a DROM.
* p < .10. ** p < .05. *** p < .01. Standard deviations in parentheses.
Coverage: Individuals aged 18–34 years born in metropolitan France, Guadeloupe, Martinique, French Guiana, and Réunion.

H. Place of birth × At least 3 siblings I. Place of birth × Eldest sibling Metropolitan France × < 3 siblings Ref. Metropolitan France × Sibling rank ≥ 2 Ref. Metropolitan France × ≥ 3 siblings – 0.18*** (0.04) Metropolitan France × Eldest sibling 0.07* (0.04) Guadeloupe × < 3 siblings 0.02 (0.09) Guadeloupe × Sibling rank ≥ 2 0.02 (0.08) Guadeloupe × ≥ 3 siblings – 0.25*** (0.09) Guadeloupe × Eldest sibling 0.03 (0.10) Martinique × < 3 siblings – 0.08 (0.09) Martinique × Sibling rank ≥ 2 – 0.09 (0.08) Martinique × ≥ 3 siblings – 0.27*** (0.09) Martinique × Eldest sibling 0.02 (0.10) French Guiana × < 3 siblings – 0.17* (0.09) French Guiana × Sibling rank ≥ 2 – 0.19*** (0.07) French Guiana × ≥ 3 siblings – 0.43*** (0.07) French Guiana × Eldest sibling – 0.15 (0.10) Réunion × < 3 siblings – 0.08 (0.08) Réunion × Sibling rank ≥ 2 – 0.06 (0.08) Réunion × ≥ 3 siblings – 0.28*** (0.09) Réunion × ≥ Eldest sibling 0.00 (0.09) Other control variables (a) Yes Other control variables (b) Yes Number of observations 9,992 Number of observations 9,992 (a) Variables from Table 3, excluding place of birth and sibship size. (b) Variables from Table 3, excluding place of birth and sibling rank. * p < .10. ** p < .05. *** p < .01. Standard deviations in parentheses. Coverage: Individuals aged 18–34 years born in metropolitan France, Guadeloupe, Martinique, French Guiana, and Réunion. Sources: MFV survey (2009–2010) for DROM residents and TeO (2008–2009) for residents of metropolitan France.

(a) Variables from Table 3, excluding place of birth and sibship size.
(b) Variables from Table 3, excluding place of birth and sibling rank.
* p < .10. ** p < .05. *** p < .01. Standard deviations in parentheses.
Coverage: Individuals aged 18–34 years born in metropolitan France, Guadeloupe, Martinique, French Guiana, and Réunion.

J. Place of birth × Grew up mainly with both parents K. Place of birth × Experienced personal violence in the family during childhood(c) Metropolitan France × Not with both parents Ref. Metropolitan France × No violence Ref. Metropolitan France × With both parents 0.33*** (0.04) Metropolitan France × Vio-lence – 0.29*** (0.08) Guadeloupe × Not with both parents 0.15 (0.09) Guadeloupe × No violence – 0.01 (0.07) Guadeloupe × With both parents 0.30*** (0.10) Guadeloupe × Violence – 0.23 (0.19) Martinique × Not with both parents 0.08 (0.09) Martinique × No violence – 0.07 (0.07) Martinique × With both parents 0.25** (0.10) Martinique × Violence – 0.34* (0.19) French Guiana × Not with both parents – 0.01 (0.08) French Guiana × No violence – 0.21*** (0.06) French Guiana × With both parents 0.04 (0.09) Guyane × Violence – 0.38** (0.18) Réunion × Not with both parents 0.03 (0.09) Réunion × No violence – 0.08 (0.08) Réunion × With both parents 0.30*** (0.09) Réunion × Violence – 0.25* (0.14) Other control variables (a) Yes Other control variables (b) Yes Number of observations 9,992 Number of observations 9,992

(a) Variables from Table 3, excluding place of birth and having grown up mainly with both parents.
(b) Variables in Table 3, excluding place of birth and having suffered personal violence in the family during childhood.
(c) Before age 18.
* p < .10. ** p < .05. *** p < .01. Standard deviations in parentheses.
Coverage: Individuals aged 18–34 years born in metropolitan France, Guadeloupe, Martinique, French Guiana, and Réunion.

L. Place of birth × Alcoholic parent during childhood(c) M - Place of birth × Parents illness, disabilities, etc. during childhood(c) Metropolitan France × No alcoholism Ref. Metropolitan France × No illness Ref. Metropolitan France × Alcoholism – 0.17*** (0.05) Metropolitan France × Illness, etc. – 0.05 (0.04) Guadeloupe × No alcoholism 0.00 (0.08) Guadeloupe × No illness, etc. 0.00 (0.08) Guadeloupe × Alcoholism – 0.21 (0.15) Guadeloupe × Illness, etc. – 0.11 (0.13) Martinique × No alcoholism – 0.07 (0.07) Martinique × No illness, etc. – 0.09 (0.08) Martinique × Alcoholism – 0.24 (0.17) Martinique × Illness, etc. – 0.07 (0.14) French Guiana × No alcoholism – 0.21*** (0.07) French Guiana × No illness, etc. – 0.24*** (0.07) French Guiana × Alcoholism – 0.32** (0.14) French Guiana × Illness, etc. – 0.01 (0.14) Réunion × No alcoholism – 0.08 (0.08) Réunion × No illness, etc. – 0.08 (0.08) Réunion × Alcoholism – 0.20* (0.10) Réunion × Illness, etc. – 0.10 (0.11) Other control variables (a) Yes Other control variables (b) Yes Number of observations 9,992 Number of observations 9,992

(a) Variables in Table 3, excluding place of birth and an alcoholic parent during childhood.
(b) Variables in Table 3, excluding place of birth and a parent with illness, disabilities, etc. during childhood.
(c) Before age 18.
* p < .10. ** p < .05. *** p < .01. Standard deviations in parentheses.
Coverage: Individuals aged 18–34 years born in metropolitan France, Guadeloupe, Martinique, French Guiana, and Réunion.

N. Place of birth × Serious arguments or conflicts between parents during childhood(c) O. Place of birth × Had a room to do homework in alone Metropolitan France × No conflict Ref. Metropolitan France × No room Ref. Metropolitan France × No conflict – 0.01 (0.04) Metropolitan France × Room 0.13*** (0.04) Guadeloupe × No conflict – 0.03 (0.08) Guadeloupe × No room – 0.14 (0.11) Guadeloupe × Conflict 0.06 (0.10) Guadeloupe × Room 0.17** (0.08) Martinique × No conflict – 0.07 (0.08) Martinique × No room – 0.22** (0.10) Martinique × Conflict – 0.09 (0.10) Martinique × Room 0.12 (0.09) French Guiana × No conflict – 0.19*** (0.07) French Guiana × No room – 0.37*** (0.11) French Guiana × Conflict – 0.24** (0.10) French Guiana × Room – 0.01 (0.07) Réunion × No conflict – 0.03 (0.08) Réunion × No room – 0.11 (0.11) Réunion × Conflict – 0.14 (0.09) Réunion × Room 0.07 (0.08) Other control variables (a) Yes Other control variables (b) Yes Number of observations 9,992 Number of observations 9,992

(a) Variables in Table 3, excluding place of birth and serious arguments or conflicts between parents during childhood.
(b) Variables from Table 3, excluding place of birth and access to a room to do homework in alone.
(c) Before age 18.
* p < .10. ** p < .05. *** p < .01. Standard deviations in parentheses.
Coverage: Individuals aged 18–34 years born in metropolitan France, Guadeloupe, Martinique, French Guiana, and Réunion.

P. Place of birth × Often helped by parents with homework Q. Place of birth × Often helped by siblings with homework Metropolitan France × Not often Ref. Metropolitan France × Not often Ref. Metropolitan France × Often – 0.14*** (0.03) Metropolitan France × Of-ten – 0.07* (0.04) Guadeloupe × Not often 0.06 (0.08) Guadeloupe × Not often 0.03 (0.08) Guadeloupe × Often – 0.29*** (0.10) Guadeloupe × Often – 0.21 (0.13) Martinique × Not often – 0.11 (0.08) Martinique × Not often – 0.08 (0.08) Martinique × Often – 0.13 (0.11) Martinique × Often – 0.09 (0.14) French Guiana × Not often – 0.21*** (0.07) French Guiana × Not often – 0.19*** (0.07) French Guiana × Often – 0.32*** (0.11) French Guiana × Often – 0.30** (0.13) Réunion × Not often – 0.13 (0.08) Réunion × Not often – 0.08 (0.08) Réunion × Often 0.01 (0.11) Réunion × Often – 0.01 (0.12) Other control variables (a) Yes Other control variables (b) Yes Number of observations 9,992 Number of observations 9,992

(a) Variables in Table 3, excluding place of birth and help from parents with homework.
(b) Variables in Table 3, excluding place of birth and help from siblings with homework.
* p < .10. ** p < .05. *** p < .01. Standard deviations in parentheses.
Coverage: Individuals aged 18–34 years born in metropolitan France, Guadeloupe, Martinique, French Guiana, and Réunion.

Table A.3: Educational level attained (ordered probit model): Introduction of interaction variables: Place of birth × …

Notes

[1]
This study includes Guadeloupe, Martinique, French Guiana, and Réunion, but not Mayotte (which has been a DROM since 2011).
[2]
Their unemployment rate is on average twice that of metropolitan France (Lasserre, 2018).
[3]
‘Human capital’ is widely used in economics. The term refers to know-how and knowledge accumulated by individuals (Becker, 1964). In the sociological literature, the notion of cultural capital is sometimes used to refer to the ability more specifically to succeed in school and to parents’ ability to help their children succeed in school (Bourdieu, 1979).
[4]
Regarding the notion of investment in children’s human capital, see also Arrondel and Wolff (1998) and Chiswick (1988). Difficulties can arise in the transmission of human capital from parents to children, either because parents lack sufficient knowledge to help their children, or because their personal difficulties are too great for them to help effectively.
[5]
According to Meuret and Morlaix (2006), the performance advantage of pupils from advantaged backgrounds, which is particularly large in France, can be explained in part by the fact that French schools have traditionally emphasized what is sometimes referred to as ‘high culture’ (grande culture) or ‘classical culture’, and pupils from privileged backgrounds are better prepared for such education. In particular, they have a better understanding of the value of the materials taught.
[6]
In this article, ‘level of education’ refers to the highest qualification obtained.
[7]
The number of pupils per institution divided by the number of places available as declared by the heads of institutions at the start of the school year.
[8]
Number of computers per student.
[9]
The highest competitive exam for becoming a teacher in French public secondary schools.
[10]
A weighting coefficient assigned to each individual, provided with the data from the two surveys, was used for the descriptive statistics. The regressions, however, were carried out on the unweighted data.
[11]
More than 80% of the respondents born in metropolitan France and living in a DROM at the time of the survey had arrived there after age 15; nearly 70% of those in the opposite situation arrived in metropolitan France after age 15 (weighted averages calculated by the author).
[12]
The proportion of those born in a DROM who had never studied outside their DROM of birth is 62% for Guadeloupe, 66% for Martinique, 60% for French Guiana, and 79% for Réunion. More than 95% of those born in metropolitan France completed their entire education in metropolitan France (weighted averages calculated by the author).
[13]
That is, beyond this factor’s correlation with family social origin, which also has an effect on academic achievement.
[14]
In both surveys, the following question was asked: ‘When you were young, before age 18, did you experience the following situations…?’ Several scenarios were included among the answers, including ‘serious money problems in the family’. Respondents could answer yes or no.
[15]
This variable is not available for all individuals, and in particular for large numbers of respondents from the DROMs.
[16]
There are no differences between mothers in metropolitan France and Martinique, however.
[17]
Here, three response categories were used: speaking French, speaking the Creole of the DROM of birth, and an ‘other’ category for other languages, along with the situation of not having exchanged (or exchanged little) with the parent during childhood (this last was particularly prevalent for the Antilles and, to a lesser extent, French Guiana).
[18]
The possible experiences mentioned with the question ‘When you were young, before age 18, did you experience the following situations…?’ in both surveys included ‘serious violence against yourself’, ‘serious arguments or conflict between your parents’, and ‘alcoholism of one of your parents’.
[19]
The possible experiences mentioned with the question ‘When you were young, before age 18, did you experience the following situations…?’ in both surveys included ‘serious illness, disability, or accident for one of your parents’.
[20]
This type of estimation was also used by Domingues Dos Santos and Wolff (2011).
[21]
This division into four levels was chosen to provide balanced subsample sizes for each level of education and each place of birth.
[22]
The programme was written by the author, and not drawn from an existing procedure in a software package.
[23]
Mean probabilities of progressing from one level of education to another are estimated.
[24]
Separate regressions for each DROM are added in Appendix Table A.2, and regressions including interaction terms in Appendix Tables A.3.
[25]
It is no longer significant when parents’ social origin and the family situation during childhood are taken into account (Columns 4 and 5). It is also low in the regressions for the individual DROMs (Appendix Table A.2), although the effect is positive and significant for Réunion.
[26]
This similarity between French Guiana and metropolitan France, which is surprising given the differences in wealth between them, may be partly because the variable represents the situation as perceived by the respondent and is thus relative to the other inhabitants of the same territory.
[27]
For example, it is more common in the DROMs than in metropolitan France for multiple generations or members of an extended family to live under the same roof.
[28]
The question asked in the two surveys is the same: ‘During your schooling, were you helped with your homework by…?’

English

Individuals born in the French overseas departments and regions (DROMs) have lower levels of education than those born in metropolitan France. Improving young people’s levels of education is an important issue for the DROMs, as education is closely linked to the economic development of these territories. To define effective public policies, however, the precise reasons for these lower levels of education must be understood. This study is based on data from the Migration, Family, and Ageing and Trajectories and Origins surveys, conducted respectively in the DROMs and in metropolitan France, and including many identical questions. The results indicate that almost all the educational inequalities between young people from French overseas territories and metropolitan France are explained by differences in families’ material and financial situations, parents’ social and cultural origins, and the family living environment during childhood. These elements can influence parents’ transmission of human capital to children. When these characteristics are similar, levels of education among young people from the DROMs (excluding French Guiana) and metropolitan France are also similar. These results suggest directions for sharpening the focus of public policies in order to reduce educational inequalities between the overseas territories and metropolitan France.

inequalities
education
French overseas territories DROM
France
human capital
Migration, Family, and Ageing survey
Trajectories and Origins survey

Français

Les inégalités d’éducation entre les natifs des Drom et de métropole : le rôle déterminant du capital humain transmis par les parents

Les natifs des départements et régions d’outremer (Drom) sont moins diplômés que les métropolitains. Améliorer le niveau d’études des jeunes ultramarins est un enjeu important pour les Drom, la question de l’éducation étant intimement liée à celle du développement économique de ces territoires. Pour définir des politiques publiques efficaces, il est toutefois nécessaire de connaître précisément les raisons du moindre niveau d’études des ultramarins. Ce travail s’appuie sur les données des enquêtes Migration-famille-vieillissement (MFV) et Trajectoires et origines (TeO), menées respectivement dans les Drom et en métropole, et comportant un grand nombre de questions similaires. Les résultats indiquent que la quasi-totalité des inégalités d’éducation entre les ultramarins et les métropolitains s’explique par des différences liées à la situation matérielle et financière des familles, à l’origine sociale et culturelle des parents et au cadre de vie en famille pendant l’enfance. Tous ces éléments influencent le capital humain potentiellement transmis par les parents. Lorsque les caractéristiques précédentes sont similaires, les ultramarins (hors natifs de Guyane) et métropolitains atteignent des niveaux d’études comparables. Ces résultats offrent des pistes de réflexion pour améliorer le ciblage des politiques publiques afin de réduire les inégalités d’éducation entre ultramarins et métropolitains.

Español

Las desigualdades de educación entre los nativos de los territorios franceses de ultramar y los nacidos en Francia metropolitana: el papel decisivo del capital humano transmitido por los padres

Los nativos de los departamentos y regiones de ultramar (Drom) son menos diplomados que los metropolitanos. Mejorar el nivel de estudios de los jóvenes de ultramar es un desafío importante para los Drom, pues la cuestión educativa está estrechamente asociada a la del desarrollo económico de estos territorios. Pero para definir políticas públicas eficaces es necesario conocer con precisión las razones del menor nivel de estudios de los nativos de los Drom. Nuestro trabajo se apoya en los datos de las encuestas Migración-familia-envejecimiento (MFV) y Trayectorias y origines (TeO), llevadas a cabo respectivamente en los Drom y en Francia metropolitana, y que contienen un gran número de preguntas similares. Los resultados indican que la desigualdad de educación entre los nativos de Drom y los metropolitanos se debe casi totalmente a las diferencias vinculadas a la situación material y financiera de las familias, al origen social y cultural de los padres y al cuadro de vida familiar durante la infancia. Todos estos elementos influyen en el capital humano potencialmente transmitido por los padres. Cuando las características precedentes son similares, los nativos de los Drom (excepto los nativos de Guyana) alcanzan un nivel de estudios comparable al de los metropolitanos. Estos resultados ofrecen pistas de reflexión para mejorar la orientación de las políticas públicas y reducir las desigualdades de educación entre los nativos de Drom y los nativos de Francia metropolitana.

Português

Les inégalités d’éducation entre les natifs des Drom et de métropole : le rôle déterminant du capital humain transmis par les parents

I - Potential causes of educational inequalities between natives of the DROMs and metropolitan France
II - Population data and characteristics
III - Analysis of the determinants of educational inequalities between individuals born in overseas territories and in metropolitan France
Conclusion

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Emmanuel Valat

ERUDITE, Université Gustave Eiffel.
Laboratoire ERUDITE, 5 boulevard Descartes, 77420 Champs-sur-Marne, France.

emmanuel.valat@hotmail.com

Translated by

Paul Reeve

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ISO 690		Copy VALAT Emmanuel, « Les inégalités d’éducation entre les natifs des Drom et de métropole : le rôle déterminant du capital humain transmis par les parents », Population, 2021/1 (Vol. 76), p. 115-153. DOI : 10.3917/popu.2101.0115. URL : https://preprod.cairn.info/revue-population-2021-1-page-115.htm
ISO 690		Copy VALAT Emmanuel, "Educational inequalities between the French overseas territories and metropolitan France: The determinant role of parents’ transmission of human capital", Population, 2021/1 (Vol. 76), p. 107-147. DOI: 10.3917/popu.2101.0115. URL: https://preprod.cairn-int.info/journal-population-2021-1-page-107.htm
MLA		Copy Valat, Emmanuel. « Les inégalités d’éducation entre les natifs des Drom et de métropole : le rôle déterminant du capital humain transmis par les parents », Population, vol. 76, no. 1, 2021, pp. 115-153.
MLA		Copy Valat, Emmanuel. "Educational inequalities between the French overseas territories and metropolitan France: The determinant role of parents’ transmission of human capital", Population, vol. 76, no. 1, 2021, pp. 107-147.
APA		Copy Valat, E. (2021). Les inégalités d’éducation entre les natifs des Drom et de métropole : le rôle déterminant du capital humain transmis par les parents. Population, 76, 115-153. https://doi.org/10.3917/popu.2101.0115
APA		Copy Valat, E. (2021). Educational inequalities between the French overseas territories and metropolitan France: The determinant role of parents’ transmission of human capital. Population, 76, 107-147. https://doi.org/10.3917/popu.2101.0115
DOI		Copy https://doi.org/10.3917/popu.2101.0115

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Table 1: Levels of education attained by 18- to 34-year-olds regardless of whether they had completed their studies when interviewed, by place of birth

Table 1: Levels of education attained by 18- to 34-year-olds regardless of whether they had completed their studies when interviewed, by place of birth

I – Potential causes of educational inequalities between natives of the DROMs and metropolitan France

1 – Educational infrastructure in the DROMs and metropolitan France

2 – Differences in returns on education between territories?

3 – Cultural differences in the valuing of academic success in the DROMs and metropolitan France?

4 – Differences in parents’ transmission of human capital?

II – Population data and characteristics

1 – The MFV and TeO surveys: two detailed and complementary sources

Table 2: Characteristics of respondents aged 18–34 by place of birth

Table 2: Characteristics of respondents aged 18–34 by place of birth

2 – More advantageous family financial situations and social backgrounds in metropolitan France

3 – Relationship to the French language and cultural origins vary widely depending on place of birth

4 – Living situations during childhood differ considerably between places of birth

III – Analysis of the determinants of educational inequalities between individuals born in overseas territories and in metropolitan France

1 – Econometric strategy

2 – At a given age and sex, individuals born in metropolitan France have completed more education than those born in a DROM

Table 3: Effects of individual and family characteristics on educational level attained (ordered probit model)

Table 3: Effects of individual and family characteristics on educational level attained (ordered probit model)

3 – Level of education differs by parents’ social origin mainly among individuals from Réunion and French Guiana

4 – Family cultural characteristics play an important role in all groups, but more so among those from Réunion

5 – Taking family living conditions into account explains almost all remaining differences

Table 4: Effects of individual and family characteristics of women and men on educational level attained (ordered probit model)

Table 4: Effects of individual and family characteristics of women and men on educational level attained (ordered probit model)

Conclusion

Appendix

Table A.1: Level of education attained by women and men aged 18–34 who either had or had not completed their studies at the time of the survey, by place of birth

Table A.1: Level of education attained by women and men aged 18–34 who either had or had not completed their studies at the time of the survey, by place of birth

Table A.2: Effects of individual and family characteristics on educational level attained, for each DROM and metropolitan France (ordered probit model)

Table A.2: Effects of individual and family characteristics on educational level attained, for each DROM and metropolitan France (ordered probit model)

Table A.3: Educational level attained (ordered probit model): Introduction of interaction variables: Place of birth × …

Table A.3: Educational level attained (ordered probit model): Introduction of interaction variables: Place of birth × …

Notes

Abstract

Les inégalités d’éducation entre les natifs des Drom et de métropole : le rôle déterminant du capital humain transmis par les parents

Las desigualdades de educación entre los nativos de los territorios franceses de ultramar y los nacidos en Francia metropolitana: el papel decisivo del capital humano transmitido por los padres

Outline

References

References

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