This chapter analyses the intergenerational aspects of the labour market integration of youth with an immigrant background in Europe. It begins with a look at labour market outcomes by parental background for three main groups of natives in their adulthood: those with native-born parents, EU-born parents, and parents born outside the EU. The focus is on parental education levels, but individual-level characteristics are also taken into account. A second section investigates occupational mobility by analysing the extent to which adults are employed in work that requires higher skills than their parents needed in their work. As in the previous section, the analysis aims to shed light on whether natives with immigrant parents are more or less mobile in terms of occupations. Finally the chapter looks at the intergenerational transmission of economic vulnerability, concentrating on those at the bottom of the strata and how their disadvantaged positions are inherited from one generation to another.
Catching Up? Intergenerational Mobility and Children of Immigrants
Chapter 4. Intergenerational mobility in the labour market
Abstract
Main findings
Parental education matters for the labour market outcomes of their adult children generally – but at the aggregate level it tends to be somewhat less determining for children with immigrant parents than for their peers with native-born parents. In Europe, natives with low-educated parents of non-EU origin have roughly the same employment probability as their peers with low-educated native-born parents. However, having parents educated at a medium (as opposed to low) level increases the employment rate for natives with native-born parents by 10 percentage points, while the rate increases only by 5 percentage points for peers with non-EU parents. The picture is broadly the same for those with highly educated parents (as opposed to medium educated). This mirrors findings of earlier OECD work showing that foreign degrees from non-EU countries are much more strongly discounted in the labour market than those from EU countries (Damas de Matos and Liebig, 2014). The chapter’s findings suggest that this reduction may have intergenerational consequences.
Across all levels of parental education, adult children with EU parents have higher employment rates than the two other groups observed in this chapter, i.e. adult children of native parents and of parents born outside the EU. The difference is largest with parents who have the lowest level of education, suggesting that an immigrant background has a larger impact on the less educated than on the higher educated.
However, for those adult children who are themselves low educated, having medium-educated as compared to low-educated parents gives a larger boost to the employment chances of adult children of non-EU immigrants than for their peers with native parents.
Differences in educational attainment partly explain employment gaps among the different groups of natives. Generally, the employment gap decreases with the level of educational attainment, suggesting that education is a stronger driver for labour market integration among children of non-EU immigrants than among children of natives. Low-educated natives with low-educated parents born outside the EU have an almost 8 percentage points lower employment rate than their peers with native parents, while the gap is only about half that for higher levels of education.
Employment gaps by parental origin vary by country. In Austria, Switzerland, Spain, France, Norway and the United Kingdom, the employment gap between natives with low-educated non-EU-born parents and natives with equally low educated native-born parents ranges between -5 percentage points and -10 percentage points, even after controlling for the person’s own highest educational attainment, age and gender. Differences are largest in Belgium, where natives with low-educated parents born outside the EU have an 18 percentage points lower probability of being in employment compared to natives with native-born parents.
For persons with low-educated parents, an employment gap by parental origin arises in the age group 25-29 and continues to widen in older cohorts. At age 45‑49, the employment gap is 8 percentage points larger for natives with parents born outside of the EU than for natives with native-born parents. This may suggest that young persons with parents born outside the EU take up jobs that prove less stable over the long term than the jobs taken up by natives with native-born parents.
The correlation between parental educational level and the share of those not in employment, education or training (NEET) is somewhat weaker for natives with parents born outside the EU than for the other groups. At first sight, these findings could be interpreted as higher social mobility for the former. However, this finding could also be driven by a discount of immigrants’ foreign education that is observed in immigrant labour market outcomes more generally, as has been shown in previous OECD work.
A full 15% of natives with non-EU parents have a mother with no completed formal education at all, which is five times the share in the other groups. The overrepresentation of mothers with no education among natives with non-EU origins indicates that they have a more challenging “starting point” which could partly explain their weaker performance on the labour market.
Immigrant mothers’ labour market participation seems to have an important impact on the outcomes of their children, more than for their peers with native-born parents. While this is observed for both genders, the association is particularly strong for women: having had a working mother at age 14 (as opposed to a mother staying at home) increases the employment probability for natives with non-EU parents by 9 percentage points, more than twice the number for their peers with native parents at 4 percentage points.
Natives with parents born outside the EU experience less occupational upward mobility than their peers with EU origins or with native-born parents. About a third of natives in the latter two categories manage to move upward on the occupational ladder. For natives with parents born outside the EU, only 1 in 5 manages to find work in an occupation requiring a higher skill level than his/her father needed in his occupation.
Intergenerational mobility patterns in the transmission of financial vulnerability (based on a subjective evaluation of the household's financial situation when the native is 14 years old and in their adulthood) do not differ across groups of natives. The financial situation in childhood is a significant predictor of poverty and deprivation, but this association disappears once educational attainment is accounted for. That suggests that the financial situation of the household during childhood mainly impacts future life chances through its impact on the child’s chances of receiving higher educational attainment.
Introduction
Ensuring equal opportunities for all and promoting upward social mobility have become crucial policy objectives for inclusive societies. At the same time, natives with immigrant parents – despite being born in a given country – are often at a disadvantage in terms of education and labour market outcomes (OECD/EU, 2015). Over the past decade the share of natives with immigrant parents has considerably increased in European Union and OECD countries. In the EU, there are now more than 10 million children with immigrant parents below the age of 15, accounting for almost 20% of the population in that age group. Facilitating a successful labour market performance of natives with immigrant parents is thus an increasingly urgent policy challenge in EU and OECD countries.
Parental background matters for labour market outcomes. Living conditions in childhood can significantly affect later achievements and the whole life of individuals, as has been shown in the literature (e.g. Luo and Waite, 2005). In other words, parents with higher living standards tend to transmit better education, ability and non-cognitive skills to their children, providing them also with greater labour market success and, consequently, higher incomes (Blanden, Paul and Lindsey, 2006).
The aim of this chapter is to investigate the extent to which differences in labour market outcomes between native-born children of immigrants and their peers with native-born parents may be explained by differences in the socio-economic characteristics of their parents. More precisely, this discussion aims to shed light on whether the intergenerational transmission of social and economic disadvantage is more pronounced among natives with immigrant parents. Although a great deal of quantitative research has gone into mapping the labour market outcomes of children of immigrants, very little effort has gone into analysing these outcomes from an intergenerational perspective, i.e. comparing the outcomes of children of immigrants to those of their parents. Exploring differences in social mobility patterns by comparing natives with native-born parents to natives with immigrant parents across countries is one of the main objectives of the chapter.
The analysis will cover intergenerational links in labour market participation for three main groups: natives with native-born parents, natives with EU-born parents and natives with parents born outside the EU. The degree of association between the parental educational background and labour market outcomes of their children in adulthood provides insights into the importance of family background for the different groups of natives, and thus presents some evidence on social mobility patterns. Considering that immigrants have on average lower education levels than natives, a native with immigrant parents may not be expected to do as well as a child of native-born parents. To analyse the intergenerational transmission of disadvantage, it is therefore important to compare children of natives and immigrants with similar family characteristics. That comparison can help to ascertain whether a gap in outcomes may be linked to family background. Intergenerational transmission from the perspective of female labour market participation is also investigated, by analysing the intergenerational employment link between a mother and daughter.
Beyond labour market participation, which is the focus of the first part of this chapter, the correlation between an adult child and his/her parent’s occupation is one of the most important components in understanding intergenerational mobility in many countries. Thus the second part of the chapter investigates whether natives with immigrant parents are at disadvantage in terms of occupational upward mobility compared to natives with native-born parents. Finally, the economic environment in which a child grows up may determine his/her financial stability in adulthood. The chapter’s last section analyses the intergenerational transmission of economic vulnerability, conditional on a given parental educational level.
By analysing intergenerational mobility in labour market participation, occupations and financial vulnerability, the chapter aims at providing a comprehensive picture of social mobility patterns among natives with native-born and immigrant parents. That knowledge can help provide a better understanding of the policies needed to improve social mobility across countries.
Intergenerational links in labour market participation
This section analyses labour market outcomes by parental background for three main groups of natives in their adulthood: those with native-born parents, EU-born parents, and parents born outside the EU. Parental background is mainly measured by the parents’ highest educational attainment.1 Information on the parental educational level is available for EU countries as well as Norway and Switzerland, in the 2014 EU Labour Force Survey’s ad-hoc module on migrants and their children.2 By comparing the association between parental educational level and labour market outcomes of the offspring in adulthood, this section attempts to shed some light on intergenerational mobility patterns across groups. More precisely, the analysis seeks to help build a better understanding of whether natives with differing parental origins are more or less mobile – or in other words, whether the intergenerational transmission of economic and social (dis-)advantage is more or less pronounced in a given group.
Considering that low-educated parents are overrepresented among immigrant groups, a native with immigrant parents may on average not be expected to do as well as a child of native-born parents. Thus to analyse the intergenerational transmission of disadvantage, it is important to compare adult children of natives and of immigrants with similar family characteristics. This can help clarify whether and to what extent the gap in labour market outcomes may be linked to family background.
Employment rates by parental educational level
How does the educational level of parents affect the employment rate of their children in adulthood? Figure 4.1 displays the employment rate by parental educational level for each group of natives. As expected, the employment rate increases with the parental educational level across all groups. Natives with EU-born parents experience overall higher employment rates than the other two groups. With low-educated parents, the employment rate for both natives with native-born parents and those with parents born outside the EU is slightly above 70%, lagging behind the employment rate of natives with low-educated EU-born parents by about 8 percentage points.
The gain of having medium-educated parents as opposed to low-educated parents is largest for natives with native-born parents. With medium-educated parents, natives with native-born parents experience an increase in the employment rate of about 10 percentage points and thus reach the employment rate of natives with similarly educated EU-born parents (of about 80%). Natives with medium-educated parents born outside the EU have a 6 percentage points higher employment rate than the same group with low-educated parents. Thus, having medium-educated parents as opposed to low-educated parents does not translate into an increased employment rate of the same magnitude for all groups of natives. This suggests that the transmission of advantage seems somewhat hampered for natives with parents born outside the EU.
Natives with highly educated parents experience employment rates between 80% and 85%, with the lowest rate observed in the group of natives with parents born outside the EU, and the highest rate in the group of natives with EU-born parents. However, an important finding is that natives with highly educated parents born outside the EU experience a somewhat lower employment rate than natives with medium-educated native-born or EU-born parents.
Figure 4.1. Employment rates by parental origin and parental education level, 2014, percentages
Note: Population aged 25-54.
Source: Eurostat, EU-LFS 2014 ad-hoc module (AHM).
Interestingly, Figure 4.1 mirrors the findings of earlier OECD work that showed that foreign qualifications have a much lower value in the labour market than domestic ones, and their returns are lower than those for domestic qualifications in terms of both employment and job quality. Foreign degrees from non-EU countries are much more strongly discounted in the labour market than those from EU countries, which results in a flatter curve of employment rates by educational attainment for natives with parents from non-EU countries (Damas de Matos and Liebig, 2014). Figure 4.1 suggests that this discounting has intergenerational consequences.
What is the employment rate by parental educational level, when considering the educational level of the respective groups of natives? Figure 4.2 shows employment rates by educational level, parental origin and parental educational level. As expected, low-educated individuals have overall the lowest employment rates independent of their parental origin and parental educational background. However, low-educated natives with low-educated parents born outside the EU have an almost 8 percentage points lower employment rate than other low-educated natives with equally low-educated EU-born parents. This suggests somewhat lower intergenerational mobility for natives with low-educated parents born outside the EU.
Figure 4.2. Employment rates by parental origin and parents’ and natives’ educational attainment, 2014, percentages
Note: Population aged 25-54.
Source: Eurostat, EU-LFS 2014 AHM.
The return to medium-level education is large, even for the most vulnerable group: completing an educational level of ISCED level 3-4 (as opposed to completing low-level education) increases the employment rate by about 16 percentage points for natives with low-educated parents born outside the EU. The return to medium-level education is even larger for natives with low-educated EU-born parents (+21 percentage points). Medium-educated natives with low-educated EU-born parents have the same employment rate, of about 80%, as the other two highly educated groups of natives with equally low-educated parents.
The most resilient individuals are those who have completed higher education despite their low parental educational background. Highly educated natives with low-educated parents born outside the EU, experience an employment rate similar to their peers with native-born parents, of well above 80%.
With highly educated parents, highly educated natives with native-born and EU-born parents experience very high employment rates of almost 90%. Highly educated natives with equally highly educated parents born outside the EU, however, have a 5 percentage points lower employment rate than the other groups of highly educated natives, suggesting that socio-economic advantage is less easily transmitted in the group of natives with parents born outside the EU.
The 2008 economic and financial crisis may have contributed to an increased gap between those with low and high educational attainment across the groups of natives. Between 2008 and 2014, all groups of natives experienced decreases in employment rates (see Annex Figure 4.A.1). Overall, the impact of the economic crisis was strongest on the immigrants with non-EU origins and lowest on those with EU origins. Those with parents born outside the EU and a low level of education saw sharp decreases of 7.3 percentage points in their already low employment rates of about 57%. The decreases were more moderate for those with a higher level of education, ranging from 4.2 percentage points in the case of natives with parents born outside the EU to 0.5 percentage points for natives with EU-born parents.
Taking a closer look at employment rates by gender, a lower rate can be observed for women across all groups of natives and across all parental educational levels (see Figure 4.3). Comparing women by parental origin, the largest employment gap of 11 percentage points can be observed for women with low-educated parents born outside the EU. At the same time, when parents are highly educated, the employment gap is the most narrow (-2.5 percentage points) for women with parents born outside the EU.
Figure 4.3. Employment rates by parental origin, parental education level and gender, 2014, percentages
Note: Population aged 25-54.
Source: Eurostat, EU-LFS 2014 AHM.
Accounting for individual-level characteristics
The differences in employment rates among natives may well be explained by an individual’s particular socio-economic characteristics, such as highest educational attainment, age, gender and parental educational level. To produce more meaningful results, this section estimates the employment probability for natives of EU and non-EU origin, taking those with native-born parents as a baseline and accounting for individual-level characteristics.
Table 4.1 displays the employment probability by gender for natives with immigrant parents (EU-born and non-EU-born) as compared to natives with native-born parents. The results show that even after controlling for individual-level characteristics, natives with parents born outside the EU have a 10 percentage points lower employment rate than natives with native-born parents (column 2). Columns 3-6 show that the employment gap is higher for women (-11 percentage points) than for men (-7.4 percentage points). Native men with EU-born parents show a slightly higher probability to be employed than natives with native born parents (columns 3 and 4).
Table 4.2 shows that the gap in employment rates decreases with the level of educational attainment. Natives with non-EU origins that complete higher education have a much lower employment gap (compared to natives with native-born parents) than those with lower educational attainment. As shown in the first column of Table 4.2, low-educated natives with parents born outside the EU have a 12 percentage points lower probability of being in employment, compared to natives with native-born parents. This employment gap reduces to 10 percentage points when they reach medium education and to 6 percentage points when they complete higher education.
Table 4.1. Employment probability by parental origin and gender, 2014
Percentage point difference with the reference group natives with native-born parents
Note: *** p<0.01, ** p<0.05, * p<0.1. OLS regression. Controls include age, educational attainment and parental educational attainment. With country dummies. Population aged 25-54.
Source: Eurostat, EU-LFS 2014 AHM.
Table 4.2. Employment probability by parental origin and educational attainment, 2014
Percentage point difference with the reference group natives with native-born parents
Note: *** p<0.01, ** p<0.05, * p<0.1. OLS regression. Controls include age, gender and parental educational attainment. Educational attainment categories: Low indicates ISCED 0‑2; Medium indicates 3‑4; High indicates 5‑6. Population aged 25-54.
Source: Eurostat, EU-LFS 2014 AHM.
The influence of low-educated parents
As shown in the previous section, individuals with low-educated parents have more difficulties in succeeding in the labour market. This section therefore focuses on natives with low-educated parents and analyses their association with labour market performance for the three groups of natives, given a similarly disadvantaged socio-economic background and thus starting point.
Figure 4.4 displays regression outcomes by country,3 analysing the effects of low-educated parents on the employment probability of natives with immigrant parents compared to natives with equally low educated native-born parents. Natives with low-educated parents born outside the EU have a lower probability of being in employment in all observed countries. The magnitude, however, varies. In Austria, Switzerland, Spain, France, Norway and the United Kingdom their employment gap ranges between -5 percentage points and -10 percentage points. In Belgium, natives with low-educated parents born outside the EU have an 18 percentage points lower probability of being in employment compared to natives with native-born parents – even after controlling for their highest educational attainment, age and gender.
As for natives with low-educated EU-born parents living in Austria, France, Norway, Sweden, and the United Kingdom, their probability does not significantly differ from the employment probability of natives with native-born parents. In Belgium, Switzerland and Spain, natives with low-educated EU-born parents have a 5 percentage points lower probability of being in employment compared to natives with low-educated native-born parents.
It is equally interesting to analyse how socio-economic advantage, measured by a high parental educational level, affects the employment probability of natives with immigrant parents as compared to natives with native-born parents. When looking at individuals with highly educated parents, the sample size becomes smaller and statistically significant results are only obtained for Belgium (-4 percentage points for EU-born parents; -9 percentage points for parents born outside the EU); the United Kingdom (no effect for EU-born; -8 percentage points for parents born outside the EU); Sweden (-7 percentage points for parents born outside the EU). This indicates that in some countries the transmission of advantage is equally challenging.
Figure 4.4. Employment probability if both parents are low educated, by parental origin, 2014
Note: Population aged 25-54. Controlling for educational attainment, age and gender.
Source: Eurostat, EU-LFS 2014 AHM.
Low is not equal to low – the influence of a mother with no education
A drawback of most available data sets is the fact that the parental education level is only available on a very aggregate level (low, medium and high). A low education level implies having completed education up to ISCED level 2. This means that among low-educated parents there could be parents with several years of education alongside parents with no education at all. For the question on the highest educational attainment of the parent, the 2011 EU Statistics on Income and Living Conditions data (EU-SILC) includes a category of “no education” (i.e. the parent is not able to read or write in any language) in addition to the more common low, medium and high education levels. This allows for a more detailed analysis of the influence of parents’ education level on their adult children’s labour market outcomes. Considering that parents with “no education” may be overrepresented in the group of natives with immigrant parents, analysing this issue is particularly relevant in the context of intergenerational mobility.
Figure 4.5 shows the distribution of parental education by parental origin. The most important result in this figure is that 15% of natives of non-EU origin have a mother with no education at all (and 9% of fathers) compared to about 3% in the other groups. In fact, about 65% of both natives with native-born parents and natives with parents born outside the EU have a mother with either no education or low education. Yet a significant share of mothers of non-EU origin have no education at all – without it being evident unless a specific category indicating no education is included.4
Figure 4.5. Distribution of parental education level by origin, 2011, percentages
Note: Population aged 25-54.
Source: EU-SILC data, 2011.
To analyse the influence of a mother with no education, a regression of two groups is performed: firstly, the influence of having a low-educated mother (ISCED 1-2); secondly, the influence of having a low-educated mother or a mother with no education at all. The overrepresentation of mothers with no education for natives with parents born outside the EU (as shown in Figure 4.5) could have a stronger negative effect on employment rates in this group.
Figure 4.6 displays the regression outcome of having either a low-educated mother (ISCED 1-2, in columns 1, 3 and 5) or having a mother with low education and no education combined (columns 2, 4 and 6) across the different groups of natives, controlling for some individual-level characteristics.
Before controlling for education, having a very low-educated mother (i.e. comprising a low education level and no education at all) can have a negative effect on the employment rate of up to 10 percentage points. Once educational attainment is controlled for, the effect decreases for all groups. The main result of Figure 4.6 is that for natives with parents born outside the EU, including mothers who have no education, the analysis doubles the negative effect on the employment rate. For the other groups, the difference between the two educational groups of the mother remains marginal.
Figure 4.6. Employment probability in percentage points by mother’s education level, 2011
Note: Population aged 25-54. Controlling for highest educational attainment, age and gender.
Source: EU-SILC data, 2011.
Employment gaps by age groups
The transition from school to work can have long-term consequences for labour market integration (OECD/EU, 2015). This is therefore the critical stage in life in which potentially long-lasting employment gaps arise between those with and without immigrant parents. Young natives with immigrant parents who start out struggling to make the transition are at a considerable risk of experiencing further difficulty in finding a suitable and stable job.
As can be observed from Figure 4.7, low-educated natives with low-educated parents in the cohort aged 20-24 have an employment rate at slightly above 45%, independent of their parents’ origin. The employment gap arises in the age group 25-29 and continues to widen in older cohorts. At age 45-49, the employment gap between low-educated individuals and equally low-educated parents is about 8 percentage points, in favour of natives with native-born parents. This may suggest that 20-24 year-olds and 25-29 year-olds with parents born outside the EU take up jobs that may prove less stable than the jobs taken up by natives with native-born parents.
Medium-educated natives aged 20-24 with low-educated parents born outside the EU have an 8 percentage points lower employment rate than their peers with native-born parents. The transmission of disadvantage as measured by the low education level of the parental generation is thus more pronounced among natives with non-EU origins. The employment gap by parental origin at age 40-44 and 45-49 is even wider than at the beginning of the career.
Figure 4.7. Employment rate by age group, educational level and parental origin, 2014, percentages
Note: Population aged 20-49.
Source: Eurostat, EU-LFS 2014 AHM.
The risk of labour market exclusion: NEET5 rate by parental education
To what extent does the parents’ educational level determine the probability of not being in employment, education or training at a young age? Overall, NEET6 rates are higher for natives with parents born outside the EU than for natives with native-born or EU-born parents. When analysing the NEET rate by parental educational level (see Figure 4.8), it can be observed that the young with low-educated parents across all parental origins are more likely to fall into the NEET category as compared to the young with medium- or highly educated parents. Figure 4.8 shows that almost one in four native-born youth with low-educated parents born outside the EU falls into the NEET category; having highly educated parents significantly “protects” the young from doing so. For natives with highly educated and native-born parents, only 6.6% fall into the NEET category, compared to 9.5% of the natives with parents born outside the EU.
About 40% of the NEETs are low educated (ISCED 1-2), about 50% have completed medium-level education (ISCED 3-4), and less than 10% have completed higher education (ISCED 5+). Across different population groups, it is the low-educated young that are at risk of falling into the NEET category. The overrepresentation of natives with immigrant parents – particularly those with parents born outside the EU – among the low educated explains in part why those natives show overall higher NEET rates than other groups of natives (EU/OECD, 2015).
Thus it is no surprise that young individuals with low-educated parents across all parental origins are overrepresented in the NEET category. The question that arises when analysing intergenerational mobility, however, is whether one group is more affected by the parental educational level than another. The question to be analysed therefore is whether the influence of the parental background is more or less pronounced among one group of natives.
Figure 4.8. NEET rate by parents’ origin and education level, for age group 15-29, 2014, percentages
Note: Countries included are Austria, Belgium, Switzerland, France, the Netherlands, Norway, Sweden, and the United Kingdom.
Source: Eurostat, EU-LFS 2014 AHM.
Figure 4.9 displays regression outcomes analysing the influence of the parents’ educational attainment on the probability of falling into the NEET category for each group of natives. Natives with native-born parents see their NEET rate increased by 11 percentage points when they have low-educated parents (as opposed to having medium- or highly educated parents) – even after controlling for individual-level characteristics such as age, gender, highest educational attainment and area of residence (rural/urban). Natives with parents born outside the EU experience a slightly smaller increase of 8.5 percentage points in the NEET rate when they have low-educated parents. This indicates that there is a somewhat weaker association between (low) parental education and the NEET rate for natives with parents born outside the EU.
Figure 4.9. Influence of the parents’ educational attainment on the probability of being NEET (in percentage points) for population aged 15-29 by parental origin, 2014
Note: Controlling for highest educational attainment, area of residence (rural/urban), age and gender.
Source: Eurostat, EU-LFS 2014 AHM.
Highly educated parents yield an 8 percentage point lower probability for natives with native-born parents to be NEET. Again, the influence is somewhat weaker for natives with non-EU-born parents: having highly educated parents implies a 7 percentage point lower probability of being a NEET. Overall, the correlation between the parental educational level and falling into the NEET category is somewhat weaker for natives with parents born outside the EU, indicating higher social mobility for this group.
Intergenerational employment link between mother and daughter
The intergenerational link between a mother’s labour force participation and that of her daughter is an important component for understanding the causes of the rise in female labour force participation. A large number of studies have only looked at father-son pairs, thereby factoring out the intergenerational mobility of women. This focus is partially due to data limitations, lower labour market participation among women, and the assumption that the fathers’ socio-economic profile adequately represents family resources (Korupp, Ganzeboom and van der Lippe, 2002). The socio-economic status of mothers, however, can significantly influence their children’s mobility. For the United States, the mobility of sons and daughters is found to be overestimated when excluding the socio-economic status of mothers, both those working and stay-at-home (Beller, 2009).
Recent research also shows that working mothers increase the labour market participation of their daughters in particular. Relying on survey data from 24 countries, McGinn, Lingo and Castro (2015) show that adult daughters of employed mothers are more likely to be employed, are more likely to hold supervisory responsibility if employed, work more hours, and earn marginally higher wages than women whose mothers stayed at home full time. One channel that could explain these findings involves preferences and culture (on e.g. gender role attitudes) that are transmitted between generations and shape labour market outcomes. Daughters of employed mothers and mothers with more education tend to be less traditional in their attitudes toward gender roles when compared to daughters of nonemployed and less educated mothers. Farré and Vella (2013) investigate the presence of intergenerational transmission of gender role attitudes and find a statistically significant relationship between a mother’s and her children’s inherited views regarding the role of females in the family and the labour market.
Figure 4.10 shows employment rates by maternal employment status7 at age 14 of the respondent (i.e. the mother was either fulfilling domestic tasks or care responsibilities, or was employed) and parental origin. Generally, about 60% of native-born mothers work, compared to 45% of mothers of non-EU origin. It can be observed in Figure 4.10 that there is only a minor difference between natives with native-born parents and natives with EU-born parents. The female (male) employment rate in those groups is above 80% (90%) independent of the mother’s employment status. For natives with parents born outside the EU, however, having a working mother increases the female employment rate by 16 percentage points. The employment rate for men on the other hand increases by only 4 percentage points.
Figure 4.10. Employment rate by maternal employment status and parental origin, 2011, percentages
Note: Population aged 25-54; from financially non-vulnerable households at age 14.
Source: EU-SILC data, 2011.
Table 4.3 shows the correlation between an employed mother with the respondent at age 14 and the employment rate of the adult child. The main result of the table is that having had an employed mother increases the employment rate of women with parents born outside the EU by 14 percentage points. Even after controlling for a set of variables – such as age, educational attainment, the mother’s educational attainment, financial situation at age 14 and at present – the employment gain of having had an employed mother at age 14 is higher by 9 percentage points. The correlation is also positive for the other groups of natives, although much weaker. For men with parents born outside the EU, the employment gain of 5 percentage points almost disappears when controlling for individual-level characteristics. Women with native-born parents have a 4 percentage point’s higher probability if their mother was in employment when they were 14, even after controlling for individual-level characteristics.
Table 4.3. Correlation between males and females having an employed mother at age 14 and their employment rate as adults, by parental origin, 2011, percentage points
Note: *** p<0.01, ** p<0.05, * p<0.1. Controls include age, educational attainment, mother's educational attainment, financial situation at present, and financial situation when child was 14.
Source: EU-SILC data, 2011.
Analysis by the mother’s educational level reveals that the results in Table 4.3 are mainly driven by women with a low-educated mother. It seems that having had a low-educated working mother at age 14 increases the women’s employment probability in adulthood (even after controlling for the financial situation of the household at age 14 and in adulthood). The results for medium- and highly educated working mothers remain positive but are somewhat weaker. Due to the small sample size, however, the regressions by educational level of the mother do not produce any statistically significant results, and thus somewhat impair the interpretation of this finding.
These findings suggest that measures to reach out to and improve labour market outcomes of mothers of non-EU origin are likely to have an additional intergenerational payoff. This is particularly important since the available data suggest that almost two-thirds of the mothers of non-EU origin have arrived as family migrants, and often lack access to integration measures.
Occupational mobility
This section investigates occupational mobility by analysing the extent to which adults are employed in work that requires higher skills than their parent needed in their work. As in the previous section, the analysis aims to shed light on whether natives with immigrant parents are more or less mobile in terms of occupations.
It has been argued that a correlation between an adult child and their father’s occupation is one of the most important components in understanding intergenerational mobility in many countries. An individual’s occupation can reveal information not only about economic resources but also about (for example) their social status, cultural capital and social network. Further, it has been shown that status is strongly associated with individuals’ income, but also with other aspects of peoples’ economic lives: their income security and unemployment risks, short-term income stability and longer-term income prospects in terms of wage progression over the life course (Lucchini and Schizzerotto, 2010; Watson, Whelan and Maître, 2010). From a methodological point of view, occupation-based measures are more stable and more accurately describe lifetime earnings profiles, making age-related biases less problematic.
Several factors lie behind the fact that the occupation of parents influences the occupation of their children, even many years later. For instance, some types of occupations are more often transmitted than others, as they require job-specific human capital that can be transmitted from parents to children. Intergenerational occupational persistence is also linked to entry barriers limiting access to certain professions. Furthermore, in other cases it is the natural result of educational stratification. Finally, another channel through which persistence in occupations work are family ties, as many jobs are filled through networks and referrals by friends of family.
Occupational mobility across countries varies. Checchi and Dardadoni (2002) provide international evidence on the intergenerational correlation and show that the United States and the Netherlands rank among the most mobile countries, while in Austria and Germany mobility across generations in terms of occupation is low. Li and Heath (2016) show that for visible UK-born minorities, there is some occupational convergence across generations. Meurs et al. (2015) show that children born in France to immigrant parents are still strongly disadvantaged compared to their peers with native-born parents, with regard to employment, occupational status and access to jobs in the civil service, even when controlling for parental and individual background characteristics. Intergenerational mobility is particularly low for French of North African, sub-Saharan African and Turkish descent.
Distribution of occupations
What is the share of individuals working in occupations requiring a higher skill level than that required of their parents? Figure 4.11 shows the distribution of occupations8 by parental origin. Occupational mobility is measured by comparing the father’s occupation (i.e. skill level) when the respondent was 14 years old to his/her occupational skill level in the current job (or previous job in case of unemployment or inactivity9). Upward mobility means that the respondent works in an occupation requiring a higher skill level compared to that of their father and downward mobility implies the opposite. Immobility implies that the respondent is working in an occupation requiring the same skill level as that required in their father’s work.
Figure 4.11. Distribution of natives’ occupations by parental origin, 2011, percentages
Note: Population aged 30-49. Following the literature on intergenerational inequality (Haider and Solon, 2006), only prime-age workers are considered in order to reduce life cycle bias. In particular, the figure considers workers aged 30-49, for whom the process of intergenerational transmission is likely to have fully displayed its effects.
Source: EU-SILC data, 2011.
Generally, adult children seem to work in occupations requiring a skill level similar to that required of their father with some differences by parental origin and skill level. Figure 4.11 shows that 60% of natives whose native-born or EU-born parents are working in high-skill-level occupations are also working in occupations where a high skill level is required. On the other hand, 50% of the natives with parents born outside the EU whose father used to work in a high-skill occupation are also working in occupations requiring high skills. Overall, with high-skilled parents, downward mobility is most pronounced for natives with parents born outside the EU.
For parents working in occupations where a medium skill level is required, the distribution of “immobility” is the same across the groups of natives. As for upward and downward mobility, a disadvantage can be seen for natives with parents born outside the EU. For example, over 20% of natives with medium-skilled parents born outside the EU end up in occupations where only a low skill level is required (compared to less than 10% of natives with native-born or EU-born parents). At the same time, about 20% of natives with parents born outside the EU manage to move up the occupational ladder, compared to 30% of the other two groups of natives.
For individuals with low-skilled parents, upward mobility can be observed for all (i.e. across all parental origins). The upward occupational mobility across all skill levels is particularly pronounced for natives with EU-born parents. However, about 30% of natives with low-skilled parents born outside the EU end up working in occupations where a low skill level is required, compared to about 22% for natives with native-born parents and 10% for natives with EU-born parents. This result indicates more immobility at the low skill level for this group. Sixteen percent of natives with parents born outside the EU are high achievers: they manage to work in an occupation requiring high skills despite having a father who was working in a low-skilled job. Thirty percent of the natives with EU-born parents are high achievers, compared to 22% of natives with native-born parents.
Figure 4.12 shows occupational upward mobility,10 downward mobility and immobility by parental origin. Generally, about half of the natives across all parental backgrounds remain immobile (i.e. they work in an occupation requiring the same skill level as their father needed in his work when they were 14 years old). However, when looking at upward and downward mobility, it can be observed that about a third of natives with native-born parents and of natives with EU-born parents manage to move upward in occupational level. For natives with parents born outside the EU, about 20% move upward. The share of downward mobility reflects this picture. Fifteen percent of natives with EU-born parents and seventeen percent of natives with native-born parents have a job requiring a lower skill level than his/her father needed in his work. At the same time, about a third of the natives with parents born outside the EU experience downward occupational mobility. Again, it can be observed that natives with parents born outside the EU experience more difficulties in moving upward in their occupational level.
Figure 4.12. Upward and downward occupation mobility and immobility, by parental origin, 2011, percentages
Note: Population aged 30-49.
Source: EU-SILC data, 2011.
Analysing occupational mobility
To what extent does a parent’s occupation matter for an adult child’s occupation in relative terms? Table 4.4 shows the likelihood of occupational upward mobility (i.e. working in an occupation requiring a higher skill level than the father needed in his occupation) for natives with immigrant parents relative to natives with native-born parents. The main result of this table is that even after controlling for individual-level characteristics, natives of non-EU origin have a 12 percentage points lower probability of upward occupational mobility relative to natives with native-born parents, the reference group. For natives of EU origin there is no significant difference for upward mobility compared to natives with native-born parents.
Table 4.4. Probability of upward occupational mobility, 2011
Reference group: Natives with native-born parents
Note: *** p<0.01, ** p<0.05, * p<0.1. Controls include age, educational attainment and gender. With country dummies
Source: EU-SILC data, 2011.
Figure 4.13 displays regression outcomes by country (for which data are available and where the sample size is large enough to provide meaningful results). Even after controlling for individual-level characteristics such as age and gender, for natives with parents born outside the EU the probability of moving upward in occupations is significantly lower in Austria, Norway, Spain and Belgium (between 20 percentage points lower in Austria and 13 percentage points in Belgium). In France, Switzerland and the United Kingdom, the probability of moving upward in occupations is also negative, but much less pronounced. Natives with EU-born parents have a higher probability of moving upward in occupations than their peers with native-born parents. In Belgium, they have a 10 percentage points higher probability of moving upward and less than 5 percentage points in Austria, Switzerland and Spain.
If immigrant parents are overqualified for the job they are doing in the settlement country, their occupation neither reflects their skills nor their previous social standing in the country of origin. An average of 35% of highly educated immigrants, even when they are long-term residents, are overqualified in OECD countries, compared to about 25% of the native-born in 2012-13 (OECD/EU, 2015). A number of papers have addressed this issue by also taking into account parents’ socio-economic status before migrating (Feliciano, 2005; Ichou, 2014; Feliciano and Lanuza, 2017). Overqualification of the foreign-born (i.e. the parental generation) complicates the interpretation of the outcomes. If, for instance, children with university-educated parents who work in low-skilled jobs attain a medium-skilled profession, it is debatable whether they experienced upward or downward mobility.
Figure 4.13. Likelihood of occupational upward mobility, by parental origin and country, 2011, percentages
Note: OLS regression outcomes controlling for age, gender and highest educational attainment.
Source: EU-SILC data, 2011.
Transmission of economic vulnerability
This section analyses the intergenerational transmission of economic vulnerability, concentrating on those at the bottom of the strata and how their disadvantaged positions are inherited from one generation to another. The assessment of transmission of economic vulnerability in this analysis is mainly based on a retrospective subjective evaluation of financial stress in the household when the respondent was 14 years old, and a similar evaluation at present.11 Taking into account the subjective nature of the phenomenon, international comparisons should reflect the cultural differences and changes in socio-economic conditions in the countries analysed.
The empirical literature offers various evidence suggesting that economic living conditions in the past (in childhood) can significantly affect living conditions in the future (in adulthood). Thus there is an obvious relationship between deprivation of a person in childhood resulting from parents’ poverty and experiencing poverty in one’s own youth, which can further predict poverty in the later phases of life, and a consecutive transmission of poverty to descendants. However, the phenomenon cannot be generalised, as other factors such as family/household structure, environment and social isolation may independently affect an individual’s living conditions throughout their life cycle (Bird, 2007). In the literature, the transmission of economic vulnerability has been analysed mostly by investigating income mobility i.e. the probability of being part of an income quintile in the income distribution, given that the parents fell into the same category.
Poverty in childhood can reappear in adulthood in various ways. Literature has shown that growing up in a low-income household increases children’s probability of experiencing unemployment later in life (O’Neill and Sweetman, 1998). There is also evidence demonstrating that the poorer the family, the higher will be the likelihood of a child dropping out of school (Bukodi and Goldthorpe, 2013; Wiborg and Hansen, 2009). In addition, parents’ low income increases their children’s probability of receiving social assistance in adulthood (Kauppinen et al., 2014). Some evidence in fact indicates that, compared with a wide range of parental factors, (long-term) poverty and receipt of social assistance have the most severe consequences in adulthood (Bäckman and Nilsson, 2011). In summary, as measured by multiple factors, a strong association exists between parental poverty and adulthood disadvantages of the children. However, the role of poverty and the significance of other factors related to poverty are unclear (Vauhkonen et al., 2017).
Figure 4.14 shows the distribution of the subjective perception of the financial situation at age 14 (i.e. the parental household) and in adulthood. Overall, the largest share of individuals consider their financial situation to be moderate, although natives with parents born outside the EU are overrepresented in reporting a difficult financial situation, both in adulthood and in childhood. Generally, the financial situation in adulthood seems to be perceived as more vulnerable than in childhood. In childhood, 32% of natives with parents born outside the EU consider their financial situation as good or very good, while 23% assess their adult household positively. Nineteen percent of natives with native-born parents and twenty‑one percent of natives with EU-born parents consider their financial situation as good or very good, compared to about 30% in childhood.
Figure 4.14. Distribution of the financial situation at age 14 and in adulthood, by parental origin, 2011, percentages
Source: EU-SILC data, 2011.
One out of five adults with native-born parents and with EU-born parents consider their financial situation to be bad or very bad, while only 12% consider that their financial situation at age 14 was bad or very bad. As for natives with parents born outside the EU, 27% of the adults consider their financial situation to be bad or very bad and about 20% relate their childhood environment with financial difficulties.
Upward social mobility is associated with positive change in perception of the household’s financial situation. Very few adults overall perceive their financial situation in adulthood as better than in childhood. About 8% of natives with native-born parents and EU-born parents assess the adult financial situation more positively than their childhood household. This share is somewhat higher for natives with parents born outside the EU, at 10%.
How does the financial situation at age 14 affect the financial situation in adulthood? Table 4.4 shows a regression output analysing the effect of a household with financial difficulties when the respondent was 14 on their financial situation today. The main result of the table is that growing up in a difficult financial environment in childhood does not affect natives with parents born outside the EU more than natives with native-born parents (the reference group). In fact, it seems that the financial situation of natives with parents born outside the EU is less affected by their difficult childhood environment. However, the results need to be interpreted with caution, as the regressions do not produce statistically significant coefficients due to a very small number of observations.
Table 4.5. Correlation between difficult financial situation in childhood and financial situation in adulthood, in 2011
Reference group: Natives with native-born parents
Note: *** p<0.01, ** p<0.05, * p<0.1. Controls include age, educational attainment, gender, and the father's educational level. With country dummies.
Source: EU-SILC, 2011 data.
Conclusion
Intergenerational mobility has important economic, political and social consequences. Therefore, promoting an environment that allows everyone to fulfil their potential – regardless of the parental socio-economic background – is crucial for the future of EU and OECD countries. This chapter has explored intergenerational mobility in labour market outcomes, occupations and economic vulnerability for natives with native-born parents, with EU-born parents and with parents born outside the EU. The aim of the chapter was to shed light on the transmission of disadvantage in these groups, and thus help provide a better understanding of intergenerational mobility patterns across countries.
Parents’ socio-economic background matters for the labour market outcomes of their children in adulthood. It is unquestionable that an advantaged background will to a considerable extent facilitate success in later life. The parental generation of immigrants are in many countries overrepresented at the bottom of the educational strata: they are employed in lower occupational levels and are thus economically more vulnerable than the native-born parental generation. Given the importance of parental background for success, it is to some extent no surprise that children with immigrant parents perform on average less well on the labour market than native-born children with native-born parents.
However, even when individuals have similar educational attainments and (equally disadvantaged) family backgrounds, it is the natives with parents born outside the EU who experience weaker labour market outcomes and more difficulties in obtaining good jobs requiring high levels of skills. This indicates that there are potentially other factors that particularly natives with non-EU origins need to overcome, which in turn could partly explain their (weaker) performance on the labour market. While there is some convergence in terms of educational mobility among natives with and without an immigrant background, more policy efforts are needed after education is completed to ensure a successful performance on the labour market for all.
School-to-work transition, or the first entry into the labour market, is a crucial moment for individuals, as it determines to a large extent labour market success later in life. While the employment gap between natives with parents born outside the EU compared to other groups of natives is relatively small at the beginning of the career, the gap increases for older age cohorts. This suggests that the disadvantage associated with an immigrant background may not only work during the school-to-work transition but also extend beyond. One reason for this may be that the first jobs of children of immigrants are less stable and of poorer quality – an issue that merits further scrutiny. Fostering equality of opportunity for immigrant families, and especially those with a low level of education, is key to ensuring that immigrants and their children can integrate successfully.
An important policy conclusion also arises from the finding that having a working mother seems to convey strong benefits to the outcomes of her children – especially the daughters. This suggests that measures to reach out to and improve the labour market outcomes of immigrant mothers have an additional intergenerational payoff. This is particularly important since the available data suggest that almost two-thirds of the immigrant mothers concerned have arrived as family migrants, who often lack access to integration measures.
Intergenerational mobility is linked to the institutional setting of the country. The evidence in this chapter suggests that there are differences between OECD countries in the extent to which parents’ and adult children’s outcomes are correlated. A better understanding of cross-country differences in intergenerational mobility of natives with and without immigrant parents – and how these relate to country-specific labour market institutions and settings – would be a crucial next step toward better understanding differences in mobility patterns.
References
Bäckman, O. and A. Nilsson (2011), “Pathways to social exclusion: A life-course study”, European Sociological Review, Vol. 27, No. 1, pp. 107-23.
Beller, E. (2009), “Bringing intergenerational social mobility research into the twenty-first century: Why mothers matter”, American Sociological Review, Vol. 74, Issue 4, pp. 507-28.
Bird, K. (2007), “The intergenerational transmission of poverty: An overview”, CPRC Working Paper 99, Chronic Poverty Research Centre, Manchester, United Kingdom.
Blanden, J., G. Paul and M. Lindsey (2006), Accounting for Intergenerational Income Persistence: Non-Cognitive Skills, Ability and Education, Centre for the Economics of Education, London School of Economics and Political Science, London.
Bukodi, E. and J.H. Goldthorpe (2013), “Decomposing social origins: The effect of parents’ class, status, and education on the educational attainment of their children”, European Sociological Review, Vol. 29, Issue 5, pp. 1024-1039.
Bukodi, E., M. Paskov and B. Nolan (2017), “Intergenerational class mobility in Europe: A new account and an old story”, INET Oxford Working Paper, No. 2017-03, Institute for New Economic Thinking at the Oxford Martin School.
Cingano, F. (2014), “Trends in income inequality and its impact on economic growth”, OECD Social, Employment and Migration Working Papers, No. 163, OECD Publishing, Paris, http://dx.doi.org/10.1787/5jxrjncwxv6j-en.
Corak, M. (2006), “Do poor children become poor adults? Lessons for public policy from a cross country comparison of generational earnings mobility”, in Research on Economic Inequality, Volume 13: Dynamics of Inequality and Poverty, Elsevier Press, the Netherlands, pp. 143-88. Available in unabridged form as IZA Discussion Paper No. 1993, http://ftp.iza.org/dp1993.pdf.
d’Addio, A. (2007), “Intergenerational transmission of disadvantage: Mobility or immobility across generations?”, OECD Social, Employment and Migration Working Papers, No. 52, OECD Publishing, Paris, http://dx.doi.org/10.1787/217730505550.
Damas de Matos, A. and T. Liebig (2014), “The qualifications of immigrants and their value in the labour market: A comparison of Europe and the United States”, Chapter 6 in OECD/EU, Matching Economic Migration with Labour Market Needs, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264216501-en.
European Union Labour Force Survey (EU-LFS) and its Ah-Hoc Module (AHM) 2014.
European Union Statistics on Income and Living Conditions (EU-SILC) 2011.
Farré, L. and F. Vella (2013), “The intergenerational transmission of gender role attitudes and its implications for female labour force participation”, Economica, Vol. 80, Issue 318, pp. 219-247.
Feliciano, C. and Y. Lanuza (2017), “An immigrant paradox? Contextual attainment and intergenerational educational mobility”, American Sociological Review, Vol. 82, Issue 1, pp. 211-41.
Feliciano, C. (2005), “Does selective migration matter? Explaining ethnic disparities in educational attainment among immigrants’ children”, International Migration Review, Volume 39, No. 4, pp. 841-71.
Ferguson, H., S. Bovaird and M. Mueller (2007), “The impact of poverty on educational outcomes for children“, Paediatrics and Child Health, Vol. 12, No. 8, pp. 701-06.
Ichou, M. (2014), “Who they were there: Immigrants’ educational selectivity and their children’s educational attainment,” European Sociological Review, Vol. 30, Issue 6, pp. 750-65.
Haider, S. and G. Solon (2006), “Life-cycle variation in the association between current and lifetime earnings”, NBER Working Papers, No. 11943, National Bureau of Economic Research.
Heath, A., C. Rothon and E. Kilpi (2008), “The second generation in Western Europe: Education, unemployment, and occupational attainment”, Annual Review of Sociology, Vol. 34.
Hellerstein, J.K. and M. Morill (2011), “Dads and daughters: The changing impact of fathers on women’s occupational choices”, Journal of Human Resources, Vol. 46, Issue 2, pp. 333-72.
Kauppinen, M., A. Angelin, T. Lorentzen, O. Bäckman, T. Salonen and P. Moisio (2014), “Social background and life-course risks as determinants of social assistance receipt among young adults in Sweden, Norway and Finland”, Journal of European Social Policy, Vol. 24, Issue 3, pp. 273-88.
Korupp, S.E., H.B.G. Ganzeboom and T. van der Lippe (2002), “Do mothers matter? A comparison of models of the influence of mothers’ and fathers’ educational and occupational status on children’s educational attainment”, Quality & Quantity, Vol. 36, Issue 1, pp. 17-42.
Li, Y. and A. Heath (2016), “Class matters: A study of minority and majority social mobility in Britain, 1982-2011”, American Journal of Sociology, Vol. 122, No. 1, pp. 162-200.
Long, J. and J. Ferrie (2013), “Intergenerational occupational mobility in Great Britain and the United States since 1850”, American Economic Review, Vol. 103, No. 4, pp. 1109-37.
Luo, Y. and L.J. Waite (2005), “The impact of childhood and adult SES on physical, mental, and cognitive well-being in later life”, Journals of Gerontology: Series B, Vol. 60, Issue 2, pp. S93‑S101.
Lucchini, M. and A. Schizzerotto (2010), “Unemployment risk in four European countries: A validation study of the ESeC”, in D. Rose and E. Harrison (eds.), Social Class in Europe: An Introduction to the European Socio-economic Classification, Routledge, pp. 235-44.
McGinn, K.L., E.L. Lingo and M.R. Castro (2015), “Mums the word! Cross-national effects of maternal employment on gender inequalities at work and at home”, Harvard Business School Working Paper, No. 15-094.
Meurs, D., P.A. Puhani and F. von Haaren (2015), “Number of siblings and educational choices of immigrant children: Evidence from first- and second-generation immigrants”, CREAM Centre for Research and Analysis of Migration, University College London Discussion Paper Series, No. 08/15.
OECD (2010), Equal Opportunities? The Labour Market Integration of the Children of Immigrants, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264086395-en.
OECD/EU (2015), Indicators of Immigrant Integration 2015: Settling In, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264234024-en.
O’Neill, D. and O. Sweetman (1998), “Intergenerational mobility in Britain: Evidence from unemployment patterns”, Oxford Bulletin of Economics and Statistics, Vol. 60, No. 4, pp. 431‑47.
Solon, G. (2004) “A model of intergenerational mobility variation over time and place,” Chapter 2 in M. Corak (ed.), Generational Income Mobility in North America and Europe, Cambridge University Press, pp. 38-47.
Vauhkonen, T., J. Kallio, T. Kauppinen and J. Erola (2017), “Intergenerational accumulation of social disadvantages in young adulthood”, Research in Social Stratification and Mobility, Vol. 48, pp. 42-52.
Watson, D., C.T. Whelan and B. Maître (2010), “Class and poverty: Cross-sectional and dynamic analysis of income poverty and lifestyle deprivation”, in D. Rose and E. Harrison (eds.), Social Class in Europe: An Introduction to the European Socio-economic Classification, Routledge, pp. 191-215.
Wiborg, O. and M. Hansen (2009), “Change over time in the intergenerational transmission of social disadvantage”, European Sociological Review, Vol. 25, Issue 3, pp. 379-94.
Annex 4.A.
Annex Figure 4.A.1. Employment rates of population, by parental origin and by educational attainment, in 2008 and 2014
Note: Population aged 25-54.
Source: Eurostat, EU-LFS AHM 2014.
Notes
← 1. The parental highest educational attainment is disaggregated into low, medium and high levels, corresponding to ISCED level 1-2, 3-4 and 5-6, respectively.
← 2. The Labour Force Survey (LFS) is the largest household sample survey carried out in the EU-28. It provides detailed quarterly and annual data on the employment, unemployment and economic inactivity of persons aged 15 and over. The 2014 ad hoc module (AHM) contains information on the parental educational level. The module was not collected by Denmark, Ireland, the Netherlands or Germany; these countries are therefore excluded from the analysis. Countries with very low numbers of observations in one of the categories of natives (<200) were dropped. These countries are Bulgaria, the Czech Republic, Hungary, Malta, Romania, and the Slovak Republic.
← 3. Only countries for which data are available and where the sample size is sufficiently large to produce meaningful results are kept in the analysis.
← 4. From a methodological point of view, not including a category with “no education” leads to an overestimation of the parental educational level of natives with parents born outside the EU, which in turn has implications for the interpretation of this type of analysis.
← 5. The rate of people not in employment, education and training (NEET) complements the unemployment rate. It provides a better picture of the labour market situation and exclusion of the young (age group 15-24 and/or 15-29), as it also covers the inactive and those not in education and training.
← 6. The small sample size of the EU-LFS AHM 2014 does not allow for a separate analysis of the parental educational background by education level.
← 7. The maternal employment rate includes self-employment and part-time employment.
← 8. For the respondent, occupation refers to the main job – that is, the current main job for people at work or the last main job for people who do not have a job. Occupational data for respondents and their parents, in each country, are coded to a common occupational classification, ISCO-88. Due to a small sample size, the occupation codes are then merged by skill level (low-, medium- and high-skill-level jobs).
← 9. For the occupational level of the parent, the EU-SILC data counts about 20% missing observations. The missing observations are random across parental origins and skill levels. The missing variables are not necessarily linked to unemployment of the parent, as there is a separate question investigating labour market participation. The missing observations are rather related to absence of the father, death, inadequate age group, or non-response to the question.
← 10. Mobility is independent of the baseline skill level, i.e. the individual could have moved up from a low-skilled father to a medium-level occupation or from a medium-skilled father to a high-level occupation.
← 11. The evaluation of the financial situation is available at six levels: very bad; bad; moderately bad; moderately good; good; and very good. Based on EUSILC 2011 data.