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Indicators of Immigrant Integration 2015

Settling In

Please cite this publication as:
European Union/OECD (2015), Indicators of Immigrant Integration 2015: Settling In, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264234024-en.

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ISBN: 978-92-64-23871-8 (epub) - 978-92-64-23230-3 (print) - 978-92-64-23402-4 (pdf)

DOI: http://dx.doi.org/10.1787/9789264234024-en

This work is published under the responsibility of the Secretary-General of the OECD. The opinions expressed and arguments employed herein do not necessarily reflect the official views of the OECD member countries or the European Union.

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Foreword

This publication presents the first broad international comparison across all EU and OECD countries of the outcomes for immigrants and their children. It is the fruit of a joint co-operation between the European Commission (DG Migration and Home Affairs) and the OECD’s International Migration Division, in the perspective of a regular monitoring of comparable indicators of integration across EU and OECD countries. This report has been produced with the financial assistance of the European Union.

This publication builds on a first set of indicators presented for OECD countries in the 2012 OECD Publication “Settling In” and draws on the data and information gathered through its work on integration issues carried out by the OECD’s International Migration Division. It also benefited from data provided by Eurostat and specific data requests to EU and OECD countries. This publication would not have been possible without the support of the Delegates to the OECD Working Party on Migration who provided valuable support in the data collection for this report.

Chapter 1 provides an overview of the issues involved and the main findings. Chapters 2 to 4 present contextual information on immigrant populations. Chapter 2 makes basic socio-demographic comparisons with the native-born, while Chapter 3 focuses on factors specific to the immigrant population, such as reasons for migrating, countries of origin, and length of residence. Chapter 4 supplies background on the composition of immigrant households and how they compare with their native-born peers.

Against the background set out in the Chapters 2- 4, the remainder of the publication goes on to consider actual indicators of integration: Chapter 5 looks at key indicators of immigrants’ participation in the labour market, an important component of their integration in the work force. Chapter 6 examines another aspect of labour market integration – indicators that assess the quality aspects of immigrants’ jobs. Chapter 7 addresses education and training in immigrant integration. Chapters 8- 10 consider several aspects of social inclusion: household income in Chapter 8, housing in Chapter 9, and health status and access to healthcare in Chapter 10. Chapter 11 addresses civic engagement. Chapter 12 deals with some measurable aspects of social cohesion, namely discrimination and host society opinions of immigration.

This publication also includes two large special chapters. Chapter 13 looks at young people with a migrant background. Chapter 14 discusses third-country nationals – i.e. non-EU nationals living in an EU country – and examines outcomes measured against the EU “Zaragoza indicators” of integration.

This publication has been drafted by Yves Breem and Cécile Thoreau under the supervision of Thomas Liebig. Rachele Poggi provided statistical assistance. The publication also benefited from contributions by Jeffrey Mo, Jan Saver and Anne-Mareike Vanselow. Ken Kincaid provided the editing, and Marlène Mohier and Sylviane Yvron publication support.

Many useful comments were received from Jean-Christophe Dumont, Mark Pearson and Stefano Scarpetta (all OECD) as well as from Simona Ardovino, Laurent Aujean, Jan Saver, and Eva Schulz (all DG Migration and Home Affairs) as well as from several officials from other DG Home Units, DG Employment and Eurostat.

Editorial

The issue of immigration and the integration of immigrants and their children are high on the policy agenda of EU and OECD countries, both from an economic and a social standpoint. The active participation of immigrants and their children in the labour market and, more generally, in public life is vital for ensuring social cohesion in the host country and the ability of migrants to function as autonomous, productive and successful, self-realised citizens. This is also critical for facilitating their acceptance by the host-country population.

Immigration and the integration of immigrants are also repeatedly mentioned as one of the main issues of concern in public opinion surveys in many countries. At the same time, there are many preconceptions about the actual integration outcomes of immigrants and their children. Against this backdrop, having reliable facts is a prerequisite for a better-informed public debate and for better targeted policy making.

To contribute to this aim, this publication presents the first broad international comparison across all EU and OECD countries of the outcomes for immigrants and their children. It covers all main areas of integration and includes a special focus on two concrete groups. The first group is that of young people with an immigrant background, whose outcomes are often seen as the benchmark for the success or failure of integration. Indeed, with growing numbers of young people with immigrant parents in virtually all countries, it is essential to better understand their economic and social integration, including the degree to which their outcomes may be attributable to the foreign origin of their parents.

The second group are third-country nationals in the European Union, who are the target of EU integration policy. The EU has identified key indicators that monitor the results of integration policies in the areas of employment, education, social inclusion and active citizenship. Introduced at a ministerial conference under the Spanish presidency of the EU, in 2010, these indicators are now known as the “Zaragoza indicators” and are analysed in this publication for the first time for all EU countries – along with further indicators of integration.

The international comparisons of integration outcomes provide policy-makers with benchmarks so that they can compare results in their own country with those of other countries. They also reveal aspects of integration which national data often do not capture and allow comparing trends across countries which also helps to focus on the most relevant issues. These international comparisons are not intended to be used to rank countries, but rather to put into perspective the differences between them.

This publication identifies peer groups of countries with similar challenges so as to promote the exchange of experiences and practices. This should help countries to design better policies for the better integration of immigrants and their children – to the benefit of both host-country societies and immigrants themselves.

Indeed, successful integration means equal opportunities for immigrants, ensuring they become an integral part of society. In most countries, there is still some way to go to achieve this goal. We hope that the facts and figures in this report will help our countries to advance in the pursuit of this objective.

Angel Gurría

Secretary-General of the OECD

Dimitris Avramopoulos

European Commissioner for Migration, Home Affairs and Citizenship

Executive summary

In 2012, one in ten people living in the EU and OECD areas was born abroad, totalling around 115 million immigrants in the OECD and 52 million in the EU, of which 33.5 million were from non-EU countries. In both the EU and the OECD, the immigrant population has grown by more than 30% since 2000. This report presents a detailed international comparison of the outcomes of immigrants and their children in all EU and OECD countries, in the areas of labour market, education, income, housing, health, civic engagement, and social cohesion, accompanied by comprehensive background information.

In most areas, immigrants tend to have lower outcomes than the native-born, though not always by much. Outcomes tend to be less favourable in European countries, partly because immigrants in these countries have less favourable socio-demographic characteristics than the native-born. At the same time, whereas immigrants with higher levels of qualifications have better outcomes than those with lower levels, higher education protects them less well against disadvantage than it does for the native-born. Nevertheless, gaps between immigrant and native-born populations tend to reduce over time, as immigrants become more familiar with the host-country.

Key findings for immigrants in the OECD and EU

Integration challenges do not increase with the share of immigrants in the population. There is no obvious link between the proportion of immigrants in the total population and immigrant integration outcomes. If anything, countries that are home to high proportions of immigrants tend to have better integration outcomes.

In virtually all countries, income inequality is higher among immigrants than among the native-born. This reflects the wide diversity of the immigrant populations.

In 2012-13, two in three immigrants in OECD countries were employed – a proportion that was one percentage point higher than among the native-born. In the EU, the figures are slightly less favourable and the employment rate of immigrants (62%) is three percentage points lower than that of the native-born.

One in three immigrants of working age in the OECD and one in four in the EU holds a tertiary education degree. A high level of education makes it easier to join the labour market. Yet immigrants with higher-education degrees struggle more to enter the workplace than their native-born peers.

Around two-thirds of all immigrants obtained their highest qualifications abroad. Forty-two percent of highly-educated, foreign-educated immigrants working in the EU have jobs that would only require lower levels of education. This is twice the number of their foreign-born peers who hold qualifications from the host country.

Having a job affords protection against poverty, but less so among immigrants. Immigrants in employment are twice as likely as their native-born peers to live in a household whose income is below the country’s relative poverty threshold.

Partly as a result of their lower income, immigrants are more than twice as likely to live in overcrowded accommodation as their native-born peers (19% versus 8%), OECD-wide.

Immigrants are more likely to experience involuntary inactivity, that is, willing to work but not actively seeking work. Across the EU, a higher proportion of inactive immigrants (21%) than inactive native-born (16%) declare that they are willing to work. Shares are slightly lower in the OECD (17% versus 14%).

Almost two-thirds of settled immigrants have adopted the nationality of their host country.

Key findings for third-country nationals in the EU

This publication offers a special focus on “third-country”, or non-EU, nationals in the European Union, who are a target group for EU integration policy. A full set of indicators of integration for third-country nationals is presented here for the first time.

Differences in outcomes between third-country nationals and host country nationals tend to be greater than those between foreign-born (whatever their nationality) and native-born. This is partly because foreigners are more likely to be recent arrivals, as citizenship take-up increases with time spent in the host country.

The employment rate of third-country nationals is below that of EU nationals in virtually all EU countries. For both groups, similar proportions are employed among the low-educated. In contrast, third-country nationals with higher education degrees have greater trouble finding a job than their EU peers.

The poverty rate of third-country national households is twice as high as among host-country national households.

Key findings for youth with an immigrant background

The publication also includes a special focus on youth aged 15-34 who are either foreign-born or native-born with immigrant parents, a group whose outcomes are often seen as the benchmark for the success or failure of integration. In 2013, in the 22 EU and OECD countries for which data are available, nearly 20% of 15-34 year-olds was native-born with at least one immigrant parent or immigrated as a child. A further 9% arrived in the host country as adults. In European countries, the outcomes of such youth tend to be lower than those of other youth, in contrast to what is observed in the non-European OECD countries. This reflects the often less favourable characteristics of their parents. Nevertheless, the outcomes of native-born youth with immigrant parents tend to be better than those of their peers who have themselves immigrated.

School performance at age 15 improves the longer pupils have resided in the host country, and the native offspring of foreign-born parentage outperform immigrants who arrived during their childhood.

A high concentration of children of immigrants in schools is only an issue if their parents are low-educated, as is often the case in EU countries.

In the OECD in 2012, an average of only 6% of immigrant students from disadvantaged socio-economic backgrounds are among the top performers despite their background, compared with 12% among their peers of native-born parentage.

Education is a strong driver of the labour market integration of youth from migrant backgrounds; among men, the increase in employment rates for high- compared to low-educated is even slightly larger than among their peers without a migration background.

In the EU, the youth unemployment rate among native-born immigrant offspring is almost 50% higher than among the young with native-born parents. In non-EU OECD countries, the rates of the two groups are similar.

Since 2007-08, youth employment rates among those of migrant background have deteriorated in most countries, more than among the offspring of the native-born, especially among men.

Native-born immigrant offspring in the EU are more likely to report being discriminated against than their peers who are foreign-born and immigrated to the EU. This stands in marked contrast to the non-European OECD countries.

Chapter 1.

Introduction and overview

1.1. Information on the integration of immigrants and their children is key for a proper policy debate

The integration of immigrants and their children is high on the policy agenda of EU and OECD countries for a number of reasons. Flows of immigrants into many countries have increased over the past two decades and the labour markets have seen an increasing number of immigrant offspring. Integrating immigrants and their children into the labour market and society as a whole is vital for promoting social cohesion and economic growth of host countries and the ability of migrants to become self-reliant, productive citizens. It is also a frequent prerequisite for the host population’s acceptance of further immigration.

However, many preconceptions shape public perceptions of immigrants. It is therefore crucial to provide policy makers and the public with solid facts and figures. They make it possible to assess integration outcomes of immigrants and their children over time and to address the right questions and challenges. Although integration indicators are not necessarily, in themselves, gauges of integration policies, they do point to successes and failures and so shed light on possible policy responses. This first chapter discusses the benefits of developing monitoring tools of integration at the international level, based on harmonised concepts and definitions, and presents cross-cutting issues.

The discussion of the various concepts of “integration” as it applies to immigrants is beyond the scope of this publication. Its focus is on indicators used in statistical measures of the economic and social convergence between immigrants and the native-born. That approach poses two sets of issues:

how the immigrant population should be defined and to which subset of the population their outcomes should be compared

how to use indicators to measure integration.

Who are the immigrants?

Countries tend to have different groups in mind when they refer to their “immigrant population”. While settlement countries (Australia, Canada, New Zealand and the United States) and Central and South America deem anyone born abroad an immigrant, Europe has a range of concepts that include factors like current citizenship, birth-right citizenship, and self-reported ethnicity. In Japan and Korea, statistics predominantly use the notion of nationality.

However, unlike their places of birth, peoples’ citizenship can change over time. In addition, conditions for obtaining host-country citizenship vary widely, hampering international comparisons. In countries that are more liberal in this respect –e.g. OECD countries that have been settled by migration – most foreign nationals may naturalise after five years’ residence. Some European countries, such as Sweden, have similar requirements. In others, like Switzerland and Luxembourg, even many native-born immigrant offspring are not citizens of the host country.

This report defines immigrants as the foreign-born population. There are many reasons why the outcomes of immigrants – particularly those who arrived as adults – tend to differ from those of the native-born population. They have been raised and educated in an environment – and often in a language – that may be different from that of their host country. And some elements of their foreign origin will always be part of them. Although some of these may affect their full integration, they generally become less of a hindrance the longer migrants reside in the host country.

Issues are very different when it comes to the native-born offspring of immigrants. As they have been raised and educated in the host country, they should not be facing the same obstacles as their immigrant parents and outcomes similar to those of their peers of native-born parentage may be expected. In many respects, the outcomes of the native-born offspring of immigrants are thus key benchmarks of integration (Card, 2004). The situation of people who are foreign-born, but arrived as children when they were still of mandatory schooling age, is also different from those who came as adults.

The report presents, for the first time, a comprehensive overview of the population with a migrant background – the native-born offspring of immigrants with one or two foreign-born parents, the foreign-born who arrived as children, and the foreign-born who arrived as adults. The report examines the first two groups with particular focus on their youth.¹

In 2013, one in ten people residing in the OECD and the EU was born abroad – over 115 and 50 million respectively (Figure 1.1). Over a quarter of these people arrived before the age of 15. Native-born offspring with at least one foreign-born parent account for a further 8% of the population in the OECD and 6% in the EU. More than half of the native-born population with a migrant background have two foreign-born parents (and are often referred to as the “second generation”). The exceptions are France, Israel as well as some Central and Eastern European countries that were affected by border changes and/or where the immigrant population is predominantly old (the Czech and Slovak Republics, Poland, and Romania).

In the OECD, among the countries for which data are available, 18% of the population have some migrant background, either because they are themselves foreign-born or because they have at least one immigrant parent. The figure is 16% in the European Union. In Israel and Luxembourg, more than 60% of the population have a migration background, while proportions in other countries – Australia, Canada, New Zealand and Switzerland –exceed 40%. Only a handful of countries – Korea, Japan, Hungary, the Slovak Republic, and Poland – have less than 5% of migrant background.

Figure 1.1. Immigrants and native-born offspring of immigrants, 2013 or most recent year

Percentage of the total population

Notes and sources are to be found at the end of the chapter.

StatLink  http://dx.doi.org/10.1787/888933212017

How is integration measured?

Measuring integration calls for a benchmark against which outcomes can be assessed. This report compares the outcomes of immigrants with those of the native-born, and the outcomes of the native-born offspring of both groups with each other. The most common ways of measuring the outcomes of a target group against those of a reference group are: as differences in outcomes expressed in percentage points and as a ratio between the two outcomes.

Focussing on unemployment, the two measurements yield different country rankings, as shown in Figure 1.2. Norway and Switzerland, for example, are among the top of the ranking when it comes to the ratio of immigrant to native-born unemployment rates, while differences in unemployment rates between the foreign- and native-born populations put them much further down, with Spain and Greece showing the widest gaps. Although both measurements assess differences in average foreign- and native-born rates, ratios disregard magnitude. Whereas the immigrant unemployment rate in Norway catches the eye for being over three times higher, it actually stands at just 7.7% – one of the lowest in the OECD. This report consequently presents indicators both as absolute values and as differences in percentage points, but rarely as a ratio.

Figure 1.2. Unemployment rates of foreign-born compared with native-born aged 15 to 64, 2012-13

Notes and sources are to be found at the end of the chapter.

StatLink  http://dx.doi.org/10.1787/888933212025

1.2. Compiling indicators at the international level is challenging but fruitful

In many respects, international comparisons of integration outcomes are challenging. First, because the characteristics of immigrant (that is, foreign-born) populations vary widely across countries and change over time within each of them. Second, comparing immigrant outcomes from country to country can be used to assess the success of “integration”, only if it takes into account country-specific economic and social contexts, which contribute to shaping these outcomes. Third, international comparisons often suffer from a lack of reliable and harmonised data across countries. National data must therefore be adapted to comply with common categories and definitions, losing some of their specificity and links with country-specific characteristics.

The added value of international comparisons

Nevertheless, international comparisons bring much added value to indicators at the national level. They can, in particular, act as benchmarks for assessing national performance and help interpret the magnitude of differences; for example, whether or not a 5 percentage points lower employment rates for immigrants is little or a lot. International comparisons can also help to focus on the right issues and identify challenges that are not necessarily visible from evidence from individual countries. It is commonly claimed, for example, especially in Europe, that concentrations of immigrants in the same schools risks impairing the overall educational performance.

What does emerge is that, in all countries, immigrant children’s academic performance is systematically lower in schools where there are high proportions of children with poorly educated parents. On average, they lag more than two years behind their peers in schools with few such students. And in many countries there is a close correlation between the two groups – in other words, schools with large numbers of immigrant children are also those where many pupils have parents with low levels of education. In this instance, international comparisons help focus on the right issue: the educational background of parents, not where they come from.

Integration is a multidimensional process, and some aspects are more difficult to measure than others

The effective integration of migrants is not an economic and labour-market process alone. It also has social, educational – even spatial – facets. None, though, are mutually exclusive: disadvantage and the failure to integrate in one dimension are likely to have multiple repercussions. Concentrations of migrants in geographically disadvantaged areas, for example, may affect effective integration in the education system and, later, the labour market.

However, harmonised indicators relating to migrant integration are easier to identify in some areas than in others. While the extent of labour market integration can be approximated using outcomes from large standardised cross-country surveys, it is harder to capture social integration where measures often rely on surveys of attitudes, feelings, and perceptions. Although such subjective indicators go some way towards measuring how at home migrants feel in their host society, they are prone to a number of problems. Cross-country comparisons may draw on non-harmonised data sources, for example, or different national contexts may shape subjective measures.

Integration is, and must be, a multidimensional process. Failure in any one field is likely to severely jeopardise progress in others. Capturing integration’s multiple domains in easily comparable indicators inevitably involves some degree of simplification and approximation. Taken together, however, they paint a more subtle picture of the success of migrant integration across OECD countries.

To fully interpret immigrants’ integration outcomes, the composition of the immigrant population must be considered as well. Context-related facts and figures are crucial to the proper interpretation of immigrants’ actual outcomes and observed differences with native-born populations. The use of indicators to depict migrant integration outcomes in all spheres entails a degree of simplification that must be factored into cross-country comparisons. From one OECD country to another, the migrant population may be made up of quite different groups – depending on geographical, linguistic, and policy factors. In Sweden, for example, which takes in a large number of humanitarian migrants, the migrant population differs quite substantially from that of the United Kingdom, where many immigrants come to work. Furthermore, even within each country, immigrants are not a homogenous group.

Table 1.1 presents an overview of this contextual information and the areas of integration and the indicators included in this publication. The key indicators are also presented separately for two key focus groups of this publication, that is youth with a migrant background (Chapter 13) and third-country (non-EU) nationals in the EU, the so-called “Zaragoza Indicators” (Chapter 14).

Table 1.1. Contextual information and areas of immigrant integration considered in the publication
| Description | Measured by
Contextual information
Socio-demographic characteristics (Chapter 2) | Integration outcomes are shaped by socio-demographic factors, such as age and gender. Understanding differences in immigrants’ socio-demographic characteristics across countries and with their native-born counterparts is a prerequisite for the interpretation of integration outcomes. | Distribution by age and gender Endogamous partnership and fertility

Defining characteristics of immigrant populations (Chapter 3)

Discrepancies in outcomes between immigrants and the native-born sometimes spring directly from the migration process itself. The very fact of being born abroad may constitute an obstacle in that, for example, the immigrant may lack the native-born in-depth knowledge of the host society (how the labour market functions, networks, familiarity with public services, skills in the host-country language etc.). Difficulties are supposed to vanish as the experience of the host country increases.

Immigration flows by category of entry

Distribution of the immigrant populations by:

Duration of stay

Regions of origin

Citizenship

Language of origin

Language spoken at home

Household characteristics (Chapter 4)

Household and family structures are determinants of a number of integration outcomes. For example, the home environment (whether parents are present and the size of the family) has an impact on children’s school performance, which in turn affects their economic integration later on. Family structure also determines such living conditions as income and housing, as well as the ability of adults to both work and support their children.

Average size of households

Composition of households

Area of Integration

Labour Market Outcomes (Chapter 5)

The participation of immigrants in the labour market is fundamental since work is their chief source of income. It is key for them to become part of the host country’s economic fabric and also confers social standing vis-à-vis the host-country population.

Employment rate

Activity rate

Unemployment rate

Long-term unemployment rate

Share of inactive who wish to work

Job quality (Chapter 6)

The kind of job obtained by immigrants yields a more comprehensive picture of the nature of their place in the labour market than mere access to employment.

Jobs distribution by:

Types of contracts

Working hours

Involuntary part-time

Job skills

Overqualification rate

Share of self-employment

Share of employment in the “public services” sector

Adult’s cognitive skills and training (Chapter 7)

Cognitive skills have a strong bearing on immigrants’ career paths and are decisive determinants in their economic and social integration. Access to training in the host country helps immigrants to meet the requirements of the labour market more closely and free up their skills potential.

Distribution by:

Educational attainment

Literacy skills

Participation in education and training

Share with unmet training needs

Participation in job-related training

Usefulness of job-related training

Household income (Chapter 8)

Income is a decisive factor in determining many socio-economic outcomes. Low income affects the well-being of immigrants and can lead to marginalization and damage social cohesion.

Poverty rate

In-work poverty rate

Share of households with a bank account

Share of households with an overdrawn bank account

Housing (Chapter 9)

Access to adequate housing is an important factor to improve living conditions and well-being of immigrants and their family.

Home ownership rate

Share of renters at a reduced rate

Share of overcrowding dwellings

Share of substandard dwellings

Housing cost overburden rate

Health status and health care (Chapter 10) | Health is integral to wellbeing and affects the degree and manner of engagement with society as a whole. | Share of people reporting good health status or better Share of people who report unmet medical needs Share of people who report not to have seen a doctor
Civic engagement (Chapter 11) | Becoming actively involved in the host country’s society shows that immigrants are an integral part of their new country. | Naturalisation rate Voter participation rate
Social cohesion (Chapter 12) | Being an integral part of the society and actively involved in the host country is a key element of immigrant integration. Since integration is a two-way process, mutual acceptance and trust are key conditions to social cohesion. | Share of immigrants who feel to have been discriminated against Share of people who think that their area is a good place for migrants to live Perceived economic impact of immigration

1.3. Key cross-cutting findings on the integration of immigrants and their children

Immigrants tend to have lower outcomes than the native-born, though not always by much

Measured against most indicators, immigrants enjoy worse socio-economic outcomes than the native-born on average. Some exceptions are noticeable with regard to employment rate, labour force participation rate, share of self-employed and perceived health status, for which the differences between foreign- and native-born are not significantly different from zero (Table 1.2). With regard to access to the labour market, immigrants tend to make greater efforts to compensate for any disadvantage in the labour market. Some studies have shown, for instance, that immigrants tend to apply for more jobs than the native-born (see Liebig and Huddleston, 2014) to eventually find a job. Furthermore, they are generally less fussy about jobs, accepting ones that may not always match their skills. Indeed, indicators point to wide and significant immigrant-native differences in overqualification. Differences between immigrants and native-born remain large also, OECD and EU-wide, especially in job skills, relative poverty and households overcrowding.

Integration improves when migrants stay longer

Integration is a process that occurs over time. The longer immigrants reside in a host country, the more familiar they become with the way it functions, the more friends and acquaintances they make and – where it is an issue – the better they master the host-country language. In European OECD countries, for example, an additional year of residence is associated with significant increases in immigrant employment rates and with lower rates of over-qualification (Liebig and Huddleston, 2014). However, the impact of the duration of stay varies across groups of migrants. Improvements that come with experience in the host country are particularly pronounced among refugees.

Table 1.2. Average differences between immigrants/children of immigrants and the native-born/children of native-born against key indicators, 2013 or most recent year
Indicator | OECD difference | EU difference
Immigrants |  |
Employment rate (5.1) | -1.7 | -1.9
Unemployment rate (5.2) | 3.4 | 4.2
Labour force participation rate (5.1) | 1.0 | 1.2
Share of workers hired under a temporary contract (6.1) | 3.4 | 4.7
Share of workers in low-skilled jobs (6.3) | 7.7 | 9.4
Share of self-employed (6.5) | 0.6 | 0.7
Overqualification rate among highly-educated employed (6.4) | 10.0 | 11.0
Share of highly educated (7.1) | 3.7 | 4.0
Share with only basic literacy skills among the 16-64 years old (7.2) | 18.9 | 18.3
Poverty rate (8.2) | 12.7 | 12.3
Share reporting being in good health or better (10.1) | -1.1 | -0.3
Share of persons living in an overcrowded dwelling (9.2) | 9.2 | 8.4
Share of persons living in an overcrowded or deprived dwelling (9.3) | 10.9 | 8.1
Voter participation (11.2) | -5.9 | -5.5
Native-born immigrant offspring |  |
Share of low achievers in reading at the age of 15 (13.6) | 8.7 | 11.1
Share of persons aged 15-34 neither in employment, education or training (13.11) | 5.3 | 8.4

Note: The numbers in brackets refer to the indicator in the publication. Differences between the outcomes of native-born with two foreign-born parents and native-born with two native-born parents for the share of low achievers in reading at the age of 15 and the share of 15-34 neither in employment, education or training. For all other indicators, the foreign-born outcomes are compared with those of the native-born aged 15 to 64 (unless otherwise stated).

The OECD/EU differences show the difference between the foreign- and the native-born unweighted averages (between the native-born immigrant offspring and the offspring of natives). The unweighted average considers each country as a single entity with equal weight. This average is thus the arithmetical average derived from the statistics of the countries whose data are available. Figures in bold are statistically different from zero.

Sources are to be found at the end of the chapter.

StatLink  http://dx.doi.org/10.1787/888933213976

Figure 1.3 shows the dispersion of outcomes among recent and settled immigrants relative to those of the native-born across countries (“recent” migrants are defined as those with less than ten years in the host country while the “settled” have resided in the host country for over ten year). Immigrant-native differences tend to narrow as the duration of residence lengthens. Furthermore, outcomes are generally less dispersed among settled immigrants who have lived in the host country for at least ten years than among more recent arrivals. However, the dispersion of outcomes and how much differences narrow vary from indicator to indicator.

Figure 1.3. Dispersion of recent and settled foreign-born migrants measured against key indicators relative to the native-born, 2012-13

Native-born = 100

Notes and sources are to be found at the end of the chapter.

StatLink  http://dx.doi.org/10.1787/888933212032

Integration shows some signs of improvement with regard to educational attainment, although important gaps remain…

Over the last ten years, many EU and OECD countries have put significant efforts into integration. In addition, new arrivals are, on average, better educated than longer-settled immigrants. The result has been better outcomes in many countries, precisely for the most recent arrivals. This also translated into better performances at school among immigrant offspring. Indeed, in most countries, there has been an improvement in the educational outcomes of the children of immigrants although they still often perform worse at school than their peers with native-born parents.

That being said, in most countries, there is still a significant gap to be closed and immigrant offspring also face more difficulties than their peers with native parents in overcoming social disadvantage. An average of only 6% of immigrant students from disadvantaged socio-economic backgrounds are resilient – i.e. top performers despite their background – compared with 9% among native-born students with immigrant parents and 12% among their peers of native-born parentage.

… and the economic crisis has put a halt to progress made in labour market integration

In many countries, the 2007-08 global financial and economic crisis has hindered the progress being made by immigrants, notably in labour market and economic integration. Job losses have been greater among immigrants than the native-born. Foreign-born men, who widely work in sectors more exposed to cyclical fluctuations, have been worse affected than women. However, immigrant women have seen greater deterioration in the quality of their jobs.

For immigrant offspring, education is a key driver of integration

Among both immigrants and their native-born offspring of both genders, labour market outcomes tend to improve with higher levels of educational attainment. However, improvement varies greatly in degree. It is weakest among immigrants – irrespective of gender – who arrived as adults, since they have educational credentials from abroad which host-country employers have trouble assessing and labour markets substantially downgrade (Damas de Matos and Liebig, 2014). Training, which includes language courses, can help immigrants secure recognition of their foreign qualifications and eventually enter the labour market. Indeed, immigrants report that training was useful more often than their native-born counterparts do. Yet they tend to participate less in such courses, including on-the-job programmes, even though studies have shown them to be particularly beneficial for labour market integration (Liebig and Huddleston, 2014).

Among children of immigrants, improvements in employment rates associated with high levels of education are large for both gender. Among young men of immigrant parents in the EU, education is even a slightly stronger driver of better employment prospects than it is for their peers of native-born parents. However, in most countries under review, highly-educated men born in the country to migrant parents still perform less well than their peers with no such background on the labour market. The gaps are even larger for women.

There is progress “across generations”…

Since immigrant offspring are raised and educated in the host country, their outcomes are more often similar to those of children with native parents than to those of young immigrants. The pattern holds true in many areas of integration, especially education, the labour market, and economic well-being.

Among women in the 15-34 age group in almost every EU and OECD country for which data were available, the native-born offspring of immigrants were less than half as likely as young immigrants to be economically inactive in 2012-13 (Figure 1.4).

The same pattern is even more pronounced in comparisons within the broader 15-64 year-old age group of foreign-born women. Indeed, it emerges that in most countries the inactivity rates among young native-born women of immigrant parentage are close to those of their peers born to two native parents in most countries. In Israel, Luxembourg, North America and Australia, they are even lower.

Figure 1.4. Inactivity rate among women by own and parents’ place of birth, not in education, 2012-13

As a percentage of the population, persons aged 15-34

Notes and sources are to be found at the end of the chapter.

StatLink  http://dx.doi.org/10.1787/888933212046

… but the high perceived discrimination among immigrant offspring is worrisome, in particular in Europe

An interesting contrast emerges with respect to perceptions of discrimination in countries for which data are available. There is improvement across the generations in all non-EU OECD countries, whereas the reverse is the case in most of the EU countries for which data are presented in Figure 1.5. In these latter countries, the native-born children of immigrants are in fact more likely to feel discriminated against than their peers who have actually immigrated. Their sentiment could have grave implications for social cohesion.

A possible explanation for this pattern is that persons who have themselves immigrated may have frames of reference more oriented to the origin country, while the native-born offspring of immigrants have been socialised into host-country norms and standards of equal treatment and are thus more aware of and sensitive to infractions of these standards. The fact the pattern is the reverse in the settlement countries, Luxembourg and Switzerland – where native-born offspring of immigrants claim less frequently to be discriminated against than their peers who are born abroad – seems to reflect the more positive outcomes of the native-born children of immigrants in these latter countries (Heath, Liebig and Simon, 2014).

Figure 1.5. Persons who consider themselves members of a group that is or has been discriminated against on the grounds of ethnicity, nationality or race, 2002-12

Percentages

Notes and sources are to be found at the end of the chapter.

StatLink  http://dx.doi.org/10.1787/888933212057

In the EU, it is generally more challenging to integrate immigrants from outside the Union

In EU countries, differences in outcomes between third-country (non-EU) nationals and host country nationals are generally greater than between foreign-born and native-born (Figure 1.6 illustrates that trend in the relative poverty rate). There are a number of reasons. First, third-country nationals are more likely to be recent arrivals, as citizenship take-up increases with time spend in the host country. They may also face legal barriers – to employment in the public sector in some countries, for example. Similarly, third-country citizens may have limited access to social services (e.g. low-rent housing or benefits), which can also impact on their outcomes. Furthermore, most third-country nationals come from lower-income countries where educational systems do not always perform as well as those in EU countries and deliver qualifications whose worth host country employers may struggle to recognise.

Figure 1.6. Differences in relative poverty rate by citizenship and by country of birth, 2012

Notes and sources are to be found at the end of the chapter.

StatLink  http://dx.doi.org/10.1787/888933212066

Integration challenges do not increase with the share of immigrants in the population

Few indicators point to a link between the proportion of immigrants in the total population and immigrant integration outcomes, as Figure 1.7 illustrates with respect to employment and relative poverty rates.

Figure 1.7. Link between two indicators – employment rate and relative poverty rate – and the proportion of immigrants in the total population, 2012-13

Percentages

Notes and sources are to be found at the end of the chapter.

StatLink  http://dx.doi.org/10.1787/888933212077

Where there is a clear link, though, is in the employment rate: countries that are home to high proportions of immigrants also tend to have the highest immigrant employment rates. One reason is that such countries tend to have greater shares of employment-driven migrants, the only truly discretionary category of migration.² In other words, labour migrants come on top of family and humanitarian migrants, who generally have lower labour market outcomes.

1.4. Classifying immigrant destination countries

The key findings outlined in Section 1.3 hold true for most OECD and EU countries. At the same time, immigrant populations differ largely in their size, length of residence, age, education level, language, predominant entry categories, and share coming from high-income countries. On the basis of these background characteristics, eight groups of OECD and EU countries can be identified (Figure 1.8).

These peer groups of countries often face similar, group-specific integration challenges (see Table 1.3 below), which differ from those encountered by other groups of countries. While countries can always learn from the exchange of experiences, such an exchange will be particularly fruitful with those countries that have immigrants with similar characteristics and integration challenges.

Group 1: Settlement countries (Australia, Canada, Israel, New Zealand)

In this group of countries, settlement has been a constituent element of nation-building, and immigration is considered part of the national heritage. On average, one person out of four is foreign-born, while the native-born who have at least one immigrant parent account, on average, for another 23%.

There is a high proportion of immigrants who have been educated to tertiary level: an average of 50% have a tertiary degree, a level well above those in other countries and higher than among the native-born (36%). Such educational attainment is linked partly to immigration policies that have, for many years, accepted large numbers of highly skilled labour migrants. As a result, current per capita inflows are also well above average.

More than one-third of migrants in settlement countries are native speakers. Israel is an exception and proportions of native speakers and recent migrants are relatively small.

Integration outcomes in settlement countries are generally regarded as successful. Due to the high share of highly-educated people, many of whom came as labour migrants, immigrants generally boast good labour market outcomes, access to training, and social inclusion. The vast majority of immigrants with more than ten years of residence have host-country citizenship. Linked with the high education levels of their immigrant parents, immigrant offspring tend to have better outcomes both at school and in the labour market than their peers with no migration background.

Figure 1.8. Classification of OECD and EU countries as immigrant destinations according to key foreign-born population characteristics, around 2013

Percentages

Notes and sources are to be found at the end of this chapter.

StatLink  http://dx.doi.org/10.1787/888933212087

Group 2: Long-standing destinations with many recent and highly educated migrants (Luxembourg, Switzerland, the United Kingdom, the United States)

These countries host significant numbers of both recent and long-settled migrants. Immigrants account for shares of the total population that range from about 12% in the United Kingdom and the United States to 28% in Switzerland and 43% in Luxembourg. Although immigration is longstanding, there have been many arrivals in the last ten years, particularly in the three European countries where they make up 40%-50% of the foreign-born population of working age. For these countries, the high share of recent immigrants stems largely from free movement within the EU-EFTA area, driven chiefly by migration for employment. Immigrants – particularly recent arrivals – tend to be highly educated, and at least 35% of those of working age have a tertiary degree. The United States is an exception, however, both because recent migration has been more limited and because the vast majority of immigrants came from lower-income countries, mainly in Latin America.

As in the settlement countries, immigrant labour market outcomes are positive and broadly similar to those of the native-born. The same trend holds for the native-born children of immigrants in comparison with their peers who have no migration background. However, immigrants have lower home ownership rates than the native-born and live in poorer-quality housing.

Group 3: Long-standing destinations with many settled low-educated migrants (Austria, Belgium, France, Germany, the Netherlands)

Immigration to these countries was largely shaped by flows of low-educated so-called “guest workers” during the economic boom period in the wake of World War II. They were later followed by large inflows of family migrants, also with low levels of education.

Much of that migration went into urban areas and, indeed, although the immigrant population is more heavily concentrated in densely populated areas than the native-born throughout the OECD and EU, nowhere are they more so than in the countries in this group. Here, immigrants are, on average, almost twice as likely to live in densely-populated areas as the native-born. All the countries in this group also host significant numbers of humanitarian migrants and their families.

Although all five countries still experience significant migration inflows, recent arrivals account for a small share of the total immigrant population. Between 12% and 16% of the total population is foreign-born. Due to the long-standing nature of immigration, the share of the native-born with at least one foreign-born parent is also relatively high, ranging from 7% in Germany to 15% in France.

Partly because of their lower levels of educational attainment and partly because a significant share arrived for non-employment reasons, immigrants have worse labour market outcomes than their native-born peers. Immigrants’ employment rate is, on average, 10 percentage points lower than that of the native-born, their unemployment rate is 6.5 points higher, and immigrant women tend to be largely over-represented among the economically inactive.

Immigrants also face other integration issues linked to their relatively low levels of employment and education. These include higher relative poverty rates and poorer-quality housing than among the native-born. Moreover, due to the high share of older migrants – mainly early “guest worker” cohorts now reaching retirement age – health issues are more frequent among the foreign- than the native-born.

Disadvantages related to the poor educational background of many immigrant parents have been passed on to their native-born children, whose educational outcomes lag well behind those of their peers with no migration background. At the age of 15, the difference is between 1 and 1.5 years of schooling. As a result, the school-to-work transition is also more difficult for immigrant offspring, who have a much higher chance of find themselves neither in employment, education, or training (NEET).

Group 4: Destination countries with significant recent and humanitarian migration (Denmark, Finland, Norway, Sweden)

Humanitarian immigrants and their families have accounted for much of the immigration into these Scandinavian countries. They are overrepresented at both ends of the education spectrum. Almost half of the resident foreign-born population of working age has arrived over the past ten years, a significant share of whom are EU-EFTA free mobility migrants. The share of the foreign-born and their offspring remains smaller than in the long-standing destination countries, but has increased sharply over the last decade. The overwhelming majority of immigrants are non-native speakers.

Humanitarian migrants and their families tend to struggle to integrate. Indeed, they show rather poor labour market outcomes and experience much higher levels of relative poverty and lower-standard housing than the native-born. Immigrant offspring also have lower education outcomes and more difficult school-to-work transitions than their peers with no migration background – although the differences tend to be less pronounced than in Group 3.

A high share of immigrants has taken up host-country citizenship, and more than two-thirds of those with more than ten years of residence are nationals. Integration policies are strong and long-standing, partly reflected in the fact that immigrants are well integrated in the public service sector and enjoy almost the same level of access to training as the native-born.

Group 5: New destination countries with many recent, low educated migrants (Greece, Italy, Portugal, Spain)

This group encompasses most of the southern European countries, which were destinations for large numbers of labour migrants who came to fill low-skilled jobs in the first half of the 2000s up to the onset of the global financial and economic crisis. That migration is mirrored by the large share of low educated immigrants and the fact that the migrants account for higher proportions of the less populated areas than elsewhere in the European Union and OECD. Three-quarters of the working-age foreign-born population is from lower-income countries and, because most immigration is somewhat recent, few immigrants have naturalised.

The 2007-08 downturn hit all four countries hard, disproportionally affecting the foreign-born and in particular the many third-country nationals. The reason is partly that they were concentrated in sectors sorely affected by job losses and partly because many migrants arrived just before or during the crisis. Before then, immigrants had a higher employment rate than the native-born and, even now, it is still roughly the same as that of the native-born. Since 2006-07, the unemployment rate of the foreign-born has increased by 17 percentage points, compared with 11 points among the native-born. For the many poorly educated migrants, employability has become a critical issue. And, while the children of immigrants are still a rather small group, the number entering the labour market is growing rapidly and they already show worrying outcomes.

Over-qualification is a further concern. Among highly-educated immigrants it is much more pronounced than elsewhere – both in absolute terms and relatively to the native-born. In 2012-13, the over-qualification rate was twice as high among the foreign- as the native-born.

With the exception of Portugal, the relative poverty rate among immigrants is twice as high as among the native-born, and their standards of housing are also much worse.

Table 1.3. Selected integration indicators for OECD and EU countries classified by the immigrant-destination group to which they belong
|  | Differences between foreign-born and the native-born (percentage points) +: Higher than native-born ; -: Lower than native-born |  | % among foreign-born living in the country for 10 years or more | Gap between native-born with foreign-born parents and native-born with native-born parents
|  |  | Employment rate (15-64) | Overqualifi-cation rate (15-64) | Relative poverty rate (15+) | Overcrowding rate (15+) | Share of persons in overall good health (15+) | Share of nationals (15+) | Mean PISA reading scores (points), 15 years | NEET rate (percentage points), 15-34
Settlement countries |  | Australia | -4 | +8 | +8 | .. | .. | 83 | +30 | 0
New Zealand | -1 | 0 | +7 | +8 | .. | .. | -17 | -4
Israel* | +11 | 0 | -2 | -7 | .. | .. | +22 | -5
Canada | -4 | +7 | +8 | +4 | +1 | 92 | +4 | -3
Longstanding destinations | Many recent and high-educated immigrants | Luxembourg | +11 | +4 | +18 | +9 | +1 | 22 | -53 | +1
Switzerland | -5 | -2 | +9 | +8 | +1 | 45 | -53 | +2
United States | +2 | +1 | +14 | +18 | +4 | 60 | 0 | -1
United Kingdom | -5 | +8 | +10 | +9 | +7 | 66 | -6 | +4
Longstanding lower-educated immigrants | Austria | -7 | +9 | +14 | +23 | -3 | 53 | -49 | +15
Belgium | -11 | +11 | +26 | +4 | -1 | 62 | -60 | +18
Germany | -8 | +15 | +5 | +7 | -1 | 61 | -43 | +3
France | -8 | +7 | +18 | +9 | -4 | 62 | -56 | +9
Netherlands | -14 | +8 | +15 | 0 | +1 | 78 | -56 | +8
Destinations with significant recent and humanitarian migration |  | Sweden | -14 | +19 | +11 | +9 | +1 | 84 | -40 | +3
Norway | -7 | +22 | +14 | +15 | +7 | 72 | -31 | +4
Denmark | -12 | +14 | +18 | +12 | +1 | 50 | -49 | +6
Finland | -6 | +11 | +23 | +6 | +20 | 66 | -65 | +17
New destinations with many recent labour immigrants | Low-educated | Spain | -5 | +21 | +21 | +6 | +14 | 34 | -47 | +8
Italy | +3 | +39 | +17 | +28 | +17 | 37 | -40 | ..
Portugal | +4 | +8 | +5 | +11 | +18 | 81 | -31 | ..
Greece | -1 | +32 | +25 | +30 | +16 | 29 | -33 | ..
High-educated | Cyprus1, 2 | +6 | +25 | +18 | +5 | +20 | 45 | .. | ..
Ireland | 0 | +11 | +5 | +2 | +9 | 56 | -3 | ..
Iceland | -1 | +26 | +14 | +17 | +10 | 83 | -16 | ..
Malta | +2 | 0 | - | +8 | +11 | 57 | .. | ..
Countries with immigrant population shaped by border changes |  | Estonia | 0 | +23 | +11 | +1 | -28 | 38 | -36 | ..
| Slovenia | -2 | 0 | +14 | +21 | -2 | 91 | -36 | ..
| Latvia | -3 | +5 | +3 | -3 | -25 | 27 | - | ..
| Croatia | -5 | +3 | +6 | +4 | -5 | 99 | -12 | ..
| Czech Republic | +1 | +7 | +14 | +21 | -3 | 75 | -21 | ..
| Lithuania | +4 | +10 | +6 | -1 | -15 | 92 | -25 | ..
| Hungary | +10 | +3 | -3 | -4 | +8 | 85 | - | ..
| Slovak Republic | +5 | -5 | - | +2 | -18 | 89 | - | ..
| Poland | +1 | -4 | +10 | -11 | -39 | 92 | - | ..
Emerging destinations with small immigrant population |  | Chile | +11 | .. | .. | .. | .. | .. | - | ..
Korea | +10 | .. | .. | .. | .. | .. | - | ..
Japan | -5 | .. | .. | .. | .. | .. | - | ..
Bulgaria | -3 | - | -9 | +19 | -13 | 68 | - | ..
Turkey | -3 | -5 | .. | .. | .. | .. | - | ..
Romania | +4 | - | - | - | - | - | - | ..
Mexico | -7 | .. | .. | .. | .. | .. | -52 | ..
|  | EU total | -3 | +13 | +13 | +5 | +5 | 59 | -32 | +4
OECD total | +1 | +7 | +14 | +11 | +7 | 62 | -3 | +1
Notes and sources are to be found at the end of this chapter.
StatLink  http://dx.doi.org/10.1787/888933213984

Group 6: New destination countries with many recent highly-educated immigrants (Cyprus,1, 2 Iceland, Ireland, Malta)

Like Group 5, the countries in this group have seen large numbers of labour migrants arrive in the last 10-15 years, and half of the foreign-born population have lived in their host countries for less than ten years. However, in contrast to Group 5, many recent migrants are highly educated and, with the exception of those going to Cyprus1, 2, more than three-quarters come from a high income country.

Although the situation of immigrants in this group is heterogeneous, overall integration outcomes tend to be better than in Group 5. They reflect the immigrant population’s more advantaged socio-economic background and its higher education level in particular. However, with the exception of Malta, the highly educated experience high incidences of over-qualification in the labour market.

Group 7: Countries with an immigrant population shaped by border changes and/or by national minorities (Croatia, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, the Slovak Republic, Slovenia)

The group includes most new EU member countries from Central and Eastern Europe. None have experienced much recent migration. The bulk of the foreign-born population found themselves to be foreign-born as a result of border changes or nation-building in the late 20th century, mainly related to the fall of the Iron Curtain. Consequently, the foreign-born are an aging group and the share of nationals among the foreign-born tends to be high. The overall size of the foreign-born population differs widely, ranging from 3% in the Slovak Republic and Poland to 15% and above in Estonia, Slovenia, and Latvia.

For most indicators, the foreign-born population has outcomes that are similar to, if not better than, those of the native-born, particularly in the labour market. However, the fact that many immigrants are relatively old means that they tend to be less healthy than the native-born.³

Group 8: Emerging destination countries with small immigrant populations (Bulgaria, Chile, Japan, Korea, Mexico, Romania, Turkey)

The last group of immigrant destinations takes in OECD countries from the Americas, Asia, and Europe. In all of them, less than 2% of the population is foreign-born. As the result, reliable information on many integration outcomes is not available and where it is – as for employment – there are relatively wide variations. For example, immigrants have better labour market outcomes than the native-born in Chile, Korea, and Romania, whereas the reverse is the case in the other countries. However, the immigration situation is changing rapidly. The proportion of foreign-born residents has more than doubled since 2000-1 in all countries, driven either by the offspring of former emigrants “returning to the land of their parents” or by labour immigrants. In Japan and Korea, marriages between nationals and foreigners have also accounted for a non-negligible share of immigration.

In summary, whereas many integration challenges are shared across virtually all OECD and EU countries, others mainly concern only certain groups of countries whose immigrant populations share similar characteristics. These characteristics notably include composition by category of entry, duration of residence and educational attainment. But even within these peer groups of countries, there is wide divergence, with some countries showing much better integration results in spite of similar circumstances. This suggests that policies have a role to play. Although an analysis of such policies is beyond the scope of this report, looking at their peers should help countries identify areas where they could do better.

Notes, sources, and further reading

Note to Israel

* Information on data concerning Israel: http://dx.doi.org/10.1787/888932315602.

Notes to Cyprus1, 2

1. Note by Turkey:

The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Turkey recognises the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of the United Nations, Turkey shall preserve its position concerning the “Cyprus issue”.

2. Note by all the European Union Member States of the OECD and the European Union:

The Republic of Cyprus is recognised by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus.

Notes to figures and tables

.. : not available.

– : not significant.

Figure 1.1

Data are not available for Malta, Croatia, Iceland, Mexico, Chile and Turkey. The EU average includes data for Romania and Bulgaria although data cannot be shown individually for sample size issues. The distinction between immigrant offspring and the offspring of the native-born rests on people’s self defined ethnicity in the United Kingdom’s labour force surveys. The offspring of native-born parents are termed “White” and from “England and Wales”, “Northern Ireland” or “Scotland”. People born in the United Kingdom with one immigrant and one native-born parent come under the heading “Mixed/multiple ethnic group”. The children whose parents are both immigrants are included in the various classifications of people born in the United Kingdom who report to belong to any other ethnic group categorised as follows: “White”, “Irish”, “Gipsy or Irish Traveller”, “Any other White”; “Asian/Asian British”, “Indian”, “Pakistani”, “Bangladeshi”, “Chinese”, “Any other Asian”; “Black/African/Caribbean/Black British”; and “Other ethnic group”. Compared with other countries, the number of persons with a migration background in the United Kingdom could thus be under-estimated, especially among the native-born with mixed background. In New Zealand’s General Social Survey it is only possible to estimate the native-born immigrant offspring raised by people born abroad (or a mixed couple) without specifying if one or both people were actually the biological parents. The estimate is also constrained by sample size limitations. Korea and Japan determine who is an immigrant on the basis of nationality, not on the basis of country of birth. The estimates for immigrant offspring is based on its share observed from the 2012 PISA.

Data differ slightly from those presented in Figure 1.8 since data sources are different.

Figure 1.4

Data are sorted by the difference between native-born with two native-born parents and native-born with two foreign-born parents.

Figure 1.5

Data on European countries refer to the sense of belonging to a group that is discriminated against on the grounds of race, ethnicity, or nationality. Canadian data refer to immigrants who have experienced discrimination or have been treated unfairly in the past five years because of their ethnicity, culture, race, or colour. Data for the United States refer to respondents in employment who feel, in one way or another, discriminated against at work because of their race or ethnicity. Data for New Zealand refer to immigrants who report having been treated unfairly or having had an unpleasant experience within the prior 12 months because of their ethnicity, race, or nationality. The relative sampling error for New Zealand is 30-49% for immigrant men, immigrants born in high-income countries, those with an average level of education, and those who are inactive. It is 50-99% for those aged 15-24 or 55-64, the low-educated, and the unemployed.

Sources

Population by migration background (Figure 1.1)

Labour Force Surveys for Israel (2011), France (2012), the Netherlands (2013), Switzerland (2013) and United Kingdom (2013). Census 2011 for Australia, Luxembourg and Spain. Population registers for Denmark (2013), Finland (2012), Norway (2013) and Sweden (2013). Ad hoc module of European Union Labour Force Survey (EU-LFS) 2008 for Cyprus1, 2, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, the Slovak Republic and Slovenia. Ad hoc module of European Union Labour Force Survey (EU-LFS) 2008 (native-born) + European Labour Force Surveys (EU-LFS) 2013 (foreign-born) for Greece, Ireland, Italy and Portugal. Other sources: Mikrozensus for Austria (2013) and Germany (2012). Canadian National Household Survey (2011). US Current Population Survey (2013). International Migration Outlook 2014 for Japan and Korea. Belgium: Banque Carrefour de la Sécurité Sociale 2012 (native-born) + European Labour Force Survey (EU-LFS) 2013 (foreign-born). New Zealand: General Social Survey 2010 (native-born aged 15+) + Household Labour Force Survey 2014 (foreign-born and native-born aged less than 15).

Employment rate, unemployment rate, labour force participation and inactivity rates, share of self-employed, overqualification rate, share of temporary workers, share of workers in low-skilled jobs, share of highly educated (Figures 1.2,  1.3,  1.4, and 1.7, and Tables 1.2 and 1.3)

European Union Labour Force Surveys (EU-LFS) 2012-13. United States: Current Population Survey (CPS) 2012-13. Australia, Canada and New Zealand: Labour Force Surveys 2012-13. Israel: Labour Force Survey 2011. Chile: Encuesta de Caracterización Socioeconómica Nacional (CASEN) 2011. Mexico: Encuesta Nacional de Ocupación y Empleo (ENOE) 2012. Japanese Population Survey 2010. Korea: Foreign Labour Force Survey 2012-13 and Economically Active Population Survey of Korean nationals (EAPS) 2012-13. For “Overqualification rate”, “Share of low-skilled workers” and “Share of highly educated”, Australian Survey of Work and Education (ASEW) 2013. For “Share of temporary workers”, Australian Forms of Employment 2012.

PISA scores (Table 1.3)

OECD Programme for International Student Assessment (PISA) 2012.

NEET rate (Tables 1.2 and 1.3) and inactivity rate (Figure 1.4)

Labour Force Surveys: Belgium (foreign-born population in 2012), Israel (2011), France (2012), Greece (2012), Ireland (2012), Italy (2012), Portugal (2012), Switzerland (2013), United Kingdom (2013), Netherlands (2013) and New Zealand (2014). Censuses in 2011: Australia, Spain and Luxembourg. Population registers: Denmark (2013), Finland (2012), Norway (2013) and Sweden (2013). National Household Survey (NHS) 2011: Canada. Banque Carrefour de la Sécurité Sociale 2012 on population born in Belgium. Mikrozensus 2012: Germany. Mikrozensus 2013: Austria. Current Population Survey 2013: United States.

Low achievers among adults (Table 1.2)

OECD Programme for the International Assessment of Adult Competences (PIAAC) 2012.

Relative poverty rate and income distribution (Figures 1.3,  1.6,  1.7 and Tables 1.2 and 1.3)

European Union Statistics on Income and Living Conditions (EU-SILC) 2012. United States: Current Population Survey (CPS) 2012. Australian Census on Population and Housing 2011. Canadian National Household Survey (NHS) 2011. New Zealand Household Economic Survey (HES) 2013. Israeli Integrated Household Survey 2011. German Socio-Economic Panel (G-SOEP 2012 95% sample).

Share of persons living in overcrowded dwellings (Figure 1.3 and Tables 1.2 and 1.3)

European Union Statistics on Income and Living Conditions (EU-SILC) 2012. United States: American Community Survey (ACS) 2012. Canadian National Household Survey (NHS) 2011. New Zealand: Household Economic Survey (HES) 2013. Israel: Household Expenditure Survey (HES) 2012.

Share of persons in good health (Table 1.2)

European Union Statistics on Income and Living Conditions (EU-SILC) 2012. Canadian Community Health Survey (CCHS) 2011-12. US National Health Interview Survey (NHIS) 2012.

Turnout in election (Table 1.2)

European Social Survey (ESS) 2002-12. US Current Population Survey (CPS) 2012, supplement on voter participation. Canadian Labour Force Survey 2011, supplement. New Zealand General Social Survey (NZGSS) 2012.

Discrimination (Figure 1.5)

European Social Surveys (pooled 2002 to 2012 data); United States: General Social Surveys (2004-12); Canada: General Social Surveys, cycle 23 (2009); New Zealand: General Social Survey (NZGSS 2012).

Share of foreign-born (Figures 1.7 and 1.8)

OECD Database on International Migration (2010-11). Eurostat Database on International Migration and Asylum for non-OECD EU countries (2012-13). European Union Labour Force Survey (EU-LFS) 2012-13 for Croatia and Turkey.

Share of recent migrants (Figure 1.8)

European Union Labour Force Survey (EU-LFS) 2012-13. American Community Survey (ACS) 2012. Israeli Labour Force Survey 2011. OECD Database on Immigrants in OECD Countries (DIOC) 2010-11 for other non-European countries.

Share of migrants from high-income countries and share of old migrants (Figure 1.8)

OECD Database on Immigrants in OECD Countries (DIOC) 2010-11. European Union Labour Force Survey (EU-LFS) 2012-13 for Croatia.

Share of native speakers (Figure 1.8)

OECD Programme for the International Assessment of Adult Competences (PIAAC) 2012. For countries not included in PIAAC, the estimate is based on the “language exposure before migration” concept from the French research centre in international economics (CEPII): Trade, Production and Bilateral Database.

Share of nationals (Table 1.3)

European Union Labour Force Survey (EU-LFS) 2012-13. American Community Survey (ACS) 2012. Australian Census on Population and Housing 2011. Canadian National Household Survey (NHS) 2011.

Further reading

Card, D. (2004), “Is the New Immigration Really So Bad?”, Economic Journal, Vol. 115, No. 507.

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”, Matching Economic Migration with Labour Market Needs, OECD/EU Publishing, Paris, http://dx.doi.org/10.1787/9789264216501-9-en.

Heath, A., T. Liebig and P. Simon (2013), “Discrimination against Immigrants – Measurement, Incidence and Policy Instruments”, International Migration Outlook 2013, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2013-7-en.

Liebig, T. and T. Huddleston (2014), “Labour Market Integration of Immigrants and their Children: Developing, Activating and Using Skills”, International Migration Outlook 2014, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2014-5-en.

Notes

 1. In European countries, native-born young people with immigrant parents are occasionally referred to as “second-generation immigrants”. The term, however, has connotations that risk perpetuating the immigrant status in minds and suggests that they are not considered – and do not feel – part of the host country’s society. OECD countries that have been settled by migration also occasionally use the term, albeit with a different connotation. Canada, for example, refers to “second-generation Canadians”, to reflect the fact that both immigrants and their offspring are considered an integral part of society.

 2. Countries that have job opportunities for labour migrants tend to attract more of them. That is, labour migration responds to market forces.

 3. In addition, there are often challenges related to the border changes and economic restructuring. For example, in Estonia – as elsewhere in the Baltics – during the Soviet period many Russians came as labour migrants with no perceived need for learning the Estonian language since Russian was official language in the whole Soviet Union. They arrived to work in sectors that were hard hit by the economic restructuring after independence.

Chapter 2.

Socio-demographic characteristics of immigrant populations

The societies of countries in the OECD and European Union have been shaped by successive waves of immigration. Their scale and makeup vary widely and many integration outcomes are shaped by different socio-demographic factors, such as place of residence, age, gender, etc. To interpret those outcomes, understanding differences in immigrants’ socio-demographic characteristics across countries and with their native-born counterparts is a prerequisite.

This chapter looks at the broad socio-demographic characteristics of immigrants and compares them with those of the native-born population. Indicator 2.1 considers the size of the immigrant population and the proportion living in densely populated areas. The chapter then goes on to address gender and age (Indicator 2.2), followed by birth rates and rates of unions with spouses or partners of the same origin (Indicator 2.3).

The rest of the publication will make constant references to this background data as it seeks to explain some of the disparities that affect immigrants. For further discussion of issues raised in each section, see the section entitled “Data limitations” at the end of the chapter.

Key findings

In 2012, there were around 115 million immigrants (foreign-born people) in the OECD area, and 52 million in the European Union – of which 33.5 million from non-EU countries. Altogether, one person in ten was born abroad, though the proportion varies widely from country to country – from more than 25% in Australia, Luxembourg, and Switzerland to less than 2% in Bulgaria, Japan, Korea, Mexico, Poland, Romania, and Turkey.

The immigrant population has grown by one-third in the course of the last ten years. It more than doubled in Chile, Finland, Korea, Ireland, Italy and Spain.

In virtually all countries, immigrants were overrepresented in densely populated areas in 2011-12. The overrepresentation is strongest in such longstanding European destinations as Austria, Belgium, France, and the Netherlands, where immigrants are more than 50% more likely to live in such areas as the native-born.

In 2010-11, 80% of immigrants in the OECD and the European Union were of working age, compared with 66% of the native-born. The share of young immigrants tends to be high in countries of recent immigration where most immigrant youngsters are the offspring of former emigrants, such as Mexico and Romania.

Women are slightly overrepresented among the immigrant population of working age, accounting for about 52%.

60% of immigrants who lived in couples in 2010 lived with a partner or spouse from the same region of origin.

Immigrant women were mothers at an earlier age in 2012 than their native-born counterparts, and they had more children. The differences in birth rates tend to be most pronounced in those European countries where the fertility rates of the native-born are particularly low.

Section 2.1. Size and share living in densely populated areas

Background

Definition

An immigrant is a person born abroad (i.e. foreign-born). A densely populated area is defined as a cluster of contiguous built-up grid cells with a certain minimum population threshold (generally at least 50 000 persons) and a minimum population density (generally at least 1 500 inhabitants per square kilometer). The geographic unit used to define the area varies between countries.

Coverage

Total population for the size of the immigrant population and people aged 15-64 years old for immigrants living in densely-populated areas.

In 2012, the OECD was home to more than 115 million foreign-born people, representing more than 9% of the total population. The number of immigrants has grown by one-third since 2000-01, despite a slowing in migration flows following the onset of the economic crisis in 2008. More than one-third of the foreign-born live in the United States. In the European Union, 52 million, or 10% of the population, are immigrants – of which 33.5 million from non-EU countries. Germany accounts for 20% of the EU immigrant population, and the United Kingdom and France for 14% each.

With 43% of its population born abroad, Luxembourg has the highest proportion of immigrants, while in Switzerland and Australia, one resident in four is an immigrant, and one in five in most other settlement countries. By contrast, immigrants account for low proportions of the population in central Europe and the OECD countries of Latin America and Asia – less than 2% of the population in Mexico, Romania, Turkey, Bulgaria, Japan, Poland and Korea is foreign-born. In countries that have the highest absolute numbers of immigrants (the United States, Germany, the United Kingdom and France), their share of the total population is only slightly above average – around 12 to 13%.

In OECD countries as a whole, the share of the immigrant population rose by two percentage points between 2000-01 and 2011-12 (Figure 2.1). The increase was observed in virtually all countries, with the exception of Israel and the Baltic countries, where the ageing of the foreign-born population has not been offset by new entrants. Over the last ten years, Luxembourg has seen its share of immigrants as a proportion of its total population grow by more than 9 percentage points. In Italy and in Ireland, the immigrant population doubled in ten years, and tripled in Spain. Lastly, while immigrant populations are still relatively small in Finland, Chile and Korea, they, too, have more than doubled over the last decade.

In 2011-12, immigrants were overrepresented in densely populated urban areas. Across the OECD, more than three-quarters of immigrants lived in such areas, compared with 60% of native-born. With the exception of Iceland, immigrants are overrepresented in densely populated areas everywhere (Table 2.1). They are most strongly concentrated in the United States and in the settlement countries (Canada and Israel in particular). Within the European Union, where the population is less likely than outside Europe to live in such areas, immigrants are still overrepresented in them – 57% versus 38%. In the United Kingdom, the Netherlands and France, more than two-thirds of immigrants live in densely populated areas. The fact that immigrants are overrepresented in urban areas is a key element in explaining differences in integration outcomes, as some problems (e.g. unemployment and inadequate housing) are more pronounced in the cities.

Figure 2.1. Foreign-born population, 2000-01 and 2011-12

Percentage of the total population

StatLink  http://dx.doi.org/10.1787/888933212090

Table 2.1. Foreign-born population aged 15-64 living in densely populated areas, 2011-12
Percentage of the foreign-born population and differences with native-born in percentage points
| % of total foreign-born population | Difference (+/-) with native-born +: higher than native-born -: lower than native-born
Australia | 85.0 | +21.0
Austria | 54.6 | +29.8
Belgium | 55.7 | +33.6
Canada | 96.1 | +17.4
Cyprus1, 2 | 59.7 | +6.6
Czech Republic | 46.0 | +17.8
Denmark | 51.5 | +17.5
Estonia | 56.7 | +16.7
Finland | 54.6 | +22.9
France | 65.8 | +23.6
Germany | 49.7 | +15.9
Greece | 54.2 | +12.5
Hungary | 45.4 | +16.3
Iceland | 16.1 | -0.5
Ireland | 37.0 | +2.7
Israel* | 95.5 | +5.2
Italy | 36.2 | +5.0
Latvia | 64.2 | +24.0
Lithuania | 49.0 | +5.7
Luxembourg | 35.3 | +16.8
Netherlands | 68.0 | +25.4
Norway | 42.2 | +15.4
Poland | 62.6 | +27.3
Portugal | 55.9 | +13.8
Slovak Republic | 35.6 | +15.8
Slovenia | 29.2 | +12.2
Spain | 52.4 | +4.6
Sweden | 55.3 | +16.8
Switzerland | 37.2 | +15.4
United Kingdom | 80.2 | +25.1
United States | 95.5 | +12.5
EU total (26) | 56.6 | +17.9
OECD total (26) | 75.6 | +15.1
StatLink  http://dx.doi.org/10.1787/888933213996

Notes and sources are to be found at the end of the chapter.

Section 2.2. Composition by age and gender

Background

Definition

This indicator shows the composition of the immigrant population by gender and age group.

Coverage

Total population.

In 2010-11, an average of 80% of the immigrants living in OECD or EU countries were of working age (15-64 years old), while 13% were over 64 and 6% under 15. Immigrants are overrepresented in the working-age population (80% compared with 66% of the native-born), particularly in the 25-44 age group. The 25-44 year-olds are an especially large age group in the countries of recent immigration, as well as in Scandinavia and the United Kingdom, where they account for more than half of the foreign-born population of working age. Immigrants in Japan are most concentrated in age group below most under 35, but less numerous beyond that age. In contrast, immigrants are underrepresented in the 15-24 age group (Figure 2.2) and among children (i.e. up to the age 15), as immigrants are more likely to have children after they have migrated, which explains why their children are more likely to be native-born (see Indicator 2.3). There are also fewer immigrants among the 55-64 year-olds and the over-64s.

The proportion of over-64s is higher in settlement countries and longstanding immigration destinations, with nearly one in five being over 64 years old in France, Canada, and Australia. Yet, the countries with the oldest immigrant populations are those of central Europe, where history (e.g. World War II and the fall of the Iron Curtain) has shifted borders over the course of time causing the repatriation of population groups or making people who had never crossed a border into foreign-born, as in the former Czechoslovakia or former Yugoslavia. Similarly, in Poland, two-thirds of the foreign-born are over 64 years old.

Countries that have experienced significant recent migration also often have large proportions of young immigrants below the age of 15, as in Ireland, Norway and Chile, where they account for 10% of the foreign-born. In other countries, the size of young immigrant populations reflects the return migration of the offspring of former emigrants to their parents’ country of birth. In the wake of the 2008 economic crisis, many people who had settled abroad returned to their home country, bringing with them – as immigrants – their children born in the country that had hosted their parents. Examples are Poland, Romania and, especially, Mexico, where half of the foreign-born are under 15 years old (Figure 2.3).

Comparing the proportions of younger and older immigrants with those of working age makes it possible to estimate immigrant communities’ dependency ratios – i.e. the ratio of the population not of working age to that which is. In 50% of OECD countries, the proportion of the population not of working age is twice as high among the native- as among the foreign-born. The overrepresentation of immigrants in the working-age population is especially pronounced in southern Europe, notably Greece and Italy, and in northern Europe. In central Europe, where immigrants are older (as a result of border changes) and in Mexico, where most are children born in the United States who have returned with their parents, the dependency ratio of the immigrant community is greater than that of the native-born population.

Across the OECD and the European Union, women represent about 52% of immigrants of working age (Table 2.A1.1) and are overrepresented among the foreign-born in all countries except the Czech Republic, Finland, Luxembourg, Norway, Mexico, Romania, Spain and Slovenia.

Figure 2.2. Age composition of the 15-64 population by place of birth and region of stay, 2010-11

Percentages of foreign- and native-born populations

StatLink  http://dx.doi.org/10.1787/888933212109

Figure 2.3. Population aged 0-14 years old and over 65 by place of birth, 2012

Percentages of foreign- and native-born populations

StatLink  http://dx.doi.org/10.1787/888933212117

Notes and sources are to be found at the end of the chapter.

Section 2.3. Endogamous partnership and fertility

Background

Definition

The endogamous partnership rate is the share of individuals cohabiting with a person of the same origin. The region of origin is based on regional groupings of countries of birth or, in the case of the native-born, the parents’ country of birth. Data are not available in the United States.

The total fertility rate (TFR) is the number of births per woman in a country. It is calculated as the number of children that would be born alive to a woman during her lifetime if she were to spend her childbearing years bearing children in accordance with the age-specific fertility rates of a given year. The TFR is estimated from the number of under-fives declared by respondents in the course of household surveys, then matched with the official TFR drawn from birth registers. The average age of the mother at birth is estimated in the same way. Data for this indicator are not available for Switzerland, the Scandinavian countries, or New Zealand.

Coverage

For endogamous partnerships: all over-15s who report that they are cohabiting. For the fertility rate: all women aged 15-49, the “childbearing years”.

Across the European Union and the OECD, 60% of cohabiting immigrants lived with a partner of the same origin in 2010. The proportion rises to 90% among native-born couples (Figure 2.4). Immigrants are particularly endogamous in recent immigration countries, such as Greece and Spain and in Estonia, too, where there is a large Russian minority. The native-born, by contrast, are more likely to be living in mixed couples in countries of longstanding immigration, where the percentage of mixed couples has grown with the rise in the number of native-born children of immigrants, as in France, Luxembourg and Israel. In the two latter countries, immigrants are more endogamous than the native-born. In all countries, immigrant men are as likely as women to be living in an endogamous partnership.

In OECD countries, immigrant women had 1.98 children on average in 2012, compared with 1.64 among the native-born. Immigrant women’s total fertility rate (TFR) was 0.5 births higher on average in the European Union than that of native-born women (Figure 2.5). Between 2008 and 2012, the highest average TFR among immigrant women was in France, a country where the native-born TFR is already high in itself, followed by Estonia and Belgium. The difference between the TFRs of immigrant and native-born women is particularly wide in some European countries where native-born fertility is low, such as Germany, Greece, Lithuania and Spain. On the other hand, the fertility rates of foreign- and native-born are very similar in most central European countries, as well as in Canada, Ireland, the United Kingdom and the Netherlands. In Israel, like New Zealand and Australia, the fertility of immigrant women is actually lower than that of their native-born peers.

Evidence suggests that women who decide to migrate (often for family reasons) postpone having children until after arriving in the host country. They then have more children in the years after arrival before adapting gradually to the fertility patterns of the host country. Controlling for such factors often limits the differences in fertility patterns.

Immigrant mothers are on average younger than their native-born counterparts when their children are born (Figure 2.6) – one year younger across the European Union, and four months younger in the OECD. That age difference widens to two years in Germany and three years in countries of recent immigration. By contrast, they have their children one year later in the Slovak Republic, the United Kingdom, and in the settlement countries (notably New Zealand). In the United States, in France and in most of the countries of central Europe, they give birth at the same age as native-born women.

Figure 2.4. Endogamous partnership rate in the cohabiting population aged 15 and older, by place of birth, around 2010

StatLink  http://dx.doi.org/10.1787/888933212129

Figure 2.5. Total fertility rate of foreign- and native-born women aged 15-49 years old, births during the five years 2008-12

Number of births per woman

StatLink  http://dx.doi.org/10.1787/888933212135

Figure 2.6. Average age at birth of immigrant mothers aged 15-49, births during the years 2008-12

Difference with native-born women, in years

StatLink  http://dx.doi.org/10.1787/888933212142

Notes and sources are to be found at the end of the chapter.

Data limitations

Estimating the immigrant population

Two principal criteria are used to estimate the size of immigrant population: nationality and country of birth. These are unfortunately not sufficient to deliver precise estimates, as foreign populations may in fact include people born in the host country. In many countries the native-born children of foreign parents are foreigners and may obtain nationality only later – typically at the age of majority. In other countries (e.g. Switzerland, Italy and Greece) the principle of jus sanguinis (“law of blood”) determines nationality – so the host country nationality can be transmitted only by parents of that nationality. Therefore, some adults who have foreign parents – even grandparents – may still be of foreign nationality.

More problematic still from a statistical point of view is that the foreign population may exclude, de facto, immigrants who take host-country nationality. Any international comparison then becomes tenuous and dependent on how liberal or restrictive nationality legislation is in different countries. What complicates matters even further is that the proportion of naturalised persons may also be very different, depending on the origin and duration of residence of the immigrant population. An immigrant’s attachment to his or her nationality of origin varies according to his or her age, duration of residence, qualifications, and country of origin.

A better solution is therefore to use the country of birth as the criterion for estimating the size of immigrant population (as it is done through this publication) as the number of immigrants does not depend on nationality. Nevertheless, that definition, too, has its limitations. The country of birth considered is the country in its current boundaries. In countries that have experienced changes in their borders (the Czech and Slovak Republics, the Baltic countries, Poland, Slovenia and Croatia), a significant proportion of the population may have been born in a region that was once, but is no longer, part of their country. They are now automatically classified as foreign-born even though they have never actually migrated internationally, only internally.

Another limitation is that the foreign-born population may include people who acquire the nationality of the country of current residence because:

They are the children of former expatriates (e.g. the children of French or British colonials, or the children of military personnel posted abroad).

They belong to ethnic groups that have links to the country of residence or were created by changes in borders, sometimes long ago – e.g. ethnic immigrants of Hungarian descent, or German Aussiedler.

They were born abroad by chance in a country in which they never actually lived.

For all those reasons, the notion of “immigrant population” should ideally be confined to people born abroad who have foreign nationality at birth. Such a view is not affected by acquisitions of nationality or boarder changes in the country of birth. Unfortunately, few countries have information on nationality at birth. The country of birth, then, is still the least biased criterion for estimating the size of the immigrant population.

Densely populated areas

Immigrant populations reside for the most part in heavily populated urban areas. Yet, it is a complex matter to accurately measure residential segregation for purposes of international comparisons. Segregation denotes a state of separation between social or ethnic groups. In the context of migration research, segregation is the geographic separation between immigrants and native-born people, with immigrants living in certain areas and the native-born in others. Several indices of residential segregation have been developed:

The segregation index, devised by Duncan and Duncan (1955), measures the proportion of the group that would have to move in order to obtain perfect balanced distribution.

Bell’s isolation index (Bell, 1954) measures the probability of a member of a group living in the same spatial unit with a member of his or her own group.

The concentration index measures the number of members of a group relative to the size of the geographical area it occupies.

The aggregation index, developed by White (1983), compares the average relative proximity of the members of two different groups.

The centralisation index measures the proportions of groups living in city centres (Duncan and Duncan, 1955).

All these indices require local data that need to be precise, consistent and internationally comparable. The best comparable data available relate to densely populated areas, i.e. the share of immigrant communities living in such areas. Even here, however, data are not flawlessly comparable from one country to another, as the degree of density varies according to the size of the area on which it is calculated. The smaller it is, the more accurate the calculation will be. Concentration in European countries is calculated over areas of one square kilometre (the Eurostat definition). In the United States and in Israel, such zones generally correspond to the boundaries of the municipality or the metropolitan area in question, which renders results less precise.

Endogamous partnership and fertility

National statistics on marriage and fertility are generally derived from official marriage and birth records. Administrative data of this kind are rarely available to the public. Moreover, partners’ or mothers’ country of birth are not always recorded. Data from household surveys have therefore been used to estimate the endogamy and fertility indicators.

Endogamy

Calculating the endogamous partnership rate requires knowledge of both partners’ and mothers’ countries of origin, but for reasons of sample size – the sole exceptions being Australia and Canada –countries are grouped into regions of the world.

European countries are grouped into the following regions: own country, EU15, ten new member countries of 2004, two new member countries of 2007, other Europe, North Africa, other Africa, Near and Middle East, East Asia, South and South-East Asia, North America, Central America and Caribbean, South America, Australia and Oceania.

For Israel, regions are: Israel, Iraq, Iran, Egypt, Morocco, other Northern Africa, other Near and Middle East countries, Scandinavian countries, Western Mediterranean countries, other central and western Europe, Russia, former USSR Asian Republics, other former USSR, eastern European countries, other Asian countries, Ethiopia, other African countries, South Africa-Zimbabwe-Australia-New Zealand, United States and Canada, Central America, South America.

The rate by region of origin is higher than the rate by country of origin, as two partners born in two different countries, but from the same region, will be deemed to be endogamous. Australia does not record the countries of origin of the parents of immigrant offspring, so the endogamous union rate is underestimated.

Fertility

Estimating fertility retrospectively from surveys, as this chapter does, is also an imperfect method. The main drawback of surveys is that, by definition, only people present in the country are counted: all those – mothers and children – who died or left between the time of birth and the time of the survey, are unaccounted for. The attendant risk is that fertility is underestimated and the former tends to affect migrants disproportionately. Moreover, most countries do not record information on family ties, so there is no way of knowing whether the child is really living with its mother or, in the presence of several women of childbearing age, who the mother of the child is. In such cases, the woman closest to the maximum childbearing age is considered the mother. The estimated total fertility rate has been matched on the official total fertility rate.

Notes, sources, and further reading

Note to Israel

* Information on data concerning Israel: http://dx.doi.org/10.1787/888932315602.

Notes to Cyprus1, 2

1. Note by Turkey:

The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Turkey recognises the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of the United Nations, Turkey shall preserve its position concerning the “Cyprus issue”.

2. Note by all the European Union Member States of the OECD and the European Union:

The Republic of Cyprus is recognised by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus.

Notes to figures and tables

Figure 2.1: Lithuanian data are from 2002.

Table 2.1: The Eurostat definition of densely populated area (numbers of inhabitants per km2) is used for European countries. The Australian Statistical Geography Standard (ASGS) uses the notion of Significant Urban Areas. Canada uses data from the Census Metropolitan Areas and Census Agglomerations. Israel and the United States use municipalities of more than 50 000 inhabitants as yardsticks of densely populated areas.

Australia and Canada are not included in the OECD average.

Figure 2.2: Weighted average for OECD countries excluding Korea and EU countries excluding Croatia.

Figure 2.4: Data on the native-born include only those with at least one native-born parent in Australia and in Canada. No data is available for Australia on the country of birth of immigrant parents of children born in Australia.

Figures 2.5 and 2.6: As children’s country of birth is not available in Israel, all young children in the family are deemed to be born in the country.

Israel is not included in the OECD average.

Korea and Japan determine who is an immigrant on the basis of nationality, not on the basis of country of birth.

Averages factor in rates that cannot be published individually because sample sizes are too small.

Sources to figures and tables

Figure 2.1: OECD Database on International Migration (2000-01 and 2011-12). Eurostat Database on International Migration and Asylum for non-OECD EU member countries (2012-13). European Labour Force Survey (EU-LFS) 2012-13 for Croatia and Turkey.

Table 2.1: European Union Labour Force Survey (EU-LFS) 2012. US Current Population Survey (CPS) 2012. Annual Social and Economic Supplement, 2011 Australian Census. Canadian Household Survey (NHS) 2011. Israeli Labour Force Survey 2011.

Figure 2.2: OECD Database on Immigrants in OECD Countries (DIOC) 2010-11. European Union Labour Force Survey (EU-LFS) 2010-11 for non-OECD EU countries and Turkey.

Figure 2.3: OECD Database on Immigrants in OECD Countries (DIOC) 2010-11. European Union Labour Force Survey (EU-LFS) 2012-13 for non-OECD EU member countries and Turkey.

Figure 2.3: Ad hoc module of European Union Labour Force Survey (EU-LFS) 2008. Australian Census of Population and Housing 2011. Canadian National Household Survey (NHS) 2011. Israeli Labour Force Survey 2011.

Figures 2.5 and 2.6: European Union Labour Force Survey (EU-LFS) 2012. American Community Survey (ACS) 2012. Australian Census of Population and Housing 2011. Canadian National Household Survey (NHS) 2011. New Zealand Labour Force Survey 2013. Israeli Labour Force Survey 2011.

Further reading

Arslan, C. et al. (2015), “A New Profile of Migrants in the Aftermath of the Recent Economic Crisis”, OECD Social, Employment and Migration Working Papers, No. 160, OECD Publishing, Paris, http://dx.doi.org/10.1787/5jxt2t3nnjr5-en.

Bell, W. (1954), “A Probability Model for the Measurement of Ecological Segregation”, American Sociological Review, No. 32, Washington, DC.

Duncan, O.D. and B. Duncan (1955), “A Methodological Analysis of Segregation Indexes”, American Sociological Review, No. 41, Washington, DC.

Eurostat (2011), “Migrants in Europe: A Statistical Portrait of the First and Second Generation”, Statistical Books, European Commission, Luxembourg.

OECD (2013), International Migration Outlook 2013, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2013-en.

OECD (2012), Settling In: OECD Indicators of Immigrant Integration 2012, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264171534-en.

OECD-UNDESA (2013), World Migration in Figures, OECD and United Nations High-Level Dialogue on Migration and Development, OECD Publishing, Paris and United Nations Publications, New York.

White, M.J. (1983), “The Measurement of Spatial Segregation”, American Journal of Sociology, Vol. 88, No. 5, Washington, DC.

Annex 2.A1.

Additional tables and figures

Table 2.A1.1. Size and composition by age and gender of the foreign-born population, 2011-12
| All foreign-born persons | Foreign-born | Difference (+/-) with the native-born | Percentage of women among the foreign-born
0-14 | 15-64 | 65+ | 0-14 | 15-64 | 65+
Total number of persons (thousands) | Percentage of the total population | Distribution in % | Percentage points
Australia | 6 209 | 27.3 | 6.1 | 75.0 | 19.0 | -18.2 | +11.1 | +7.1 | 51.0
Austria | 1 365 | 16.2 | 5.9 | 86.3 | 7.7 | -12.3 | +14.3 | -2.0 | 52.5
Belgium | 1 690 | 15.2 | 7.9 | 79.3 | 12.8 | -10.6 | +15.7 | -5.0 | 51.1
Bulgaria | 96 | 1.3 | 9.2 | 76.0 | 14.8 | -6.0 | +2.2 | +3.8 | 55.0
Canada | 6 920 | 19.8 | 6.1 | 74.8 | 19.0 | -14.0 | +7.3 | +6.6 | 52.2
Switzerland | 2 218 | 27.7 | 5.4 | 80.3 | 14.3 | -13.3 | +17.6 | -4.3 | 51.4
Chile | 416 | 2.4 | 14.1 | 81.0 | 4.9 | -7.1 | +13.5 | -6.4 | 55.3
Cyprus1, 2 | 201 | 23.2 | 7.3 | 88.6 | 4.2 | -14.7 | +18.5 | -3.8 | 56.1
Czech Republic | 744 | 7.1 | 2.8 | 77.6 | 19.7 | -12.4 | +8.3 | +4.1 | 48.3
Germany | 10 918 | 13.3 | 3.1 | 83.1 | 13.8 | -11.4 | +19.6 | -8.2 | 51.0
Denmark | 456 | 8.2 | 7.6 | 84.5 | 7.9 | -11.3 | +21.1 | -9.8 | 51.4
Spain | 6 618 | 14.3 | 9.7 | 83.9 | 6.4 | -6.3 | +18.4 | -12.1 | 49.3
Estonia | 198 | 14.9 | 1.5 | 59.2 | 39.4 | -16.5 | -9.0 | +25.5 | 60.5
Finland | 285 | 5.3 | 9.3 | 85.7 | 5.0 | -7.5 | +20.6 | -13.1 | 49.5
France | 7 538 | 11.9 | 5.5 | 75.1 | 19.4 | -14.6 | +11.6 | +3.0 | 51.3
United Kingdom | 7 588 | 11.9 | 7.3 | 81.2 | 11.5 | -11.7 | +17.4 | -5.7 | 51.6
Greece | 730 | 6.6 | 5.4 | 87.0 | 7.6 | -10.3 | +23.8 | -13.5 | 51.5
Croatia | 425 | 10.1 | 2.4 | 74.8 | 22.7 | -14.5 | +9.1 | +5.3 | 53.3
Hungary | 424 | 4.3 | 5.6 | 69.1 | 25.4 | -10.5 | +1.7 | +8.8 | 54.7
Ireland | 749 | 16.3 | 12.2 | 83.0 | 4.7 | -11.2 | +19.5 | -8.4 | 50.3
Iceland | 35 | 11.0 | 14.5 | 81.4 | 4.1 | -7.1 | +16.8 | -9.7 | 51.8
Israel* | 1 835 | 23.2 | .. | .. | .. | .. | .. | .. | ..
Italy | 5 696 | 9.4 | 7.3 | 86.6 | 6.1 | -7.3 | +23.3 | -16.0 | 55.5
Japan | 2 034 | 1.6 | 10.1 | 83.0 | 6.9 | -3.5 | +19.8 | -16.2 | 56.0
Korea | 933 | 1.9 | .. | .. | .. | .. | .. | .. | ..
Lithuania | 140 | 4.7 | 1.1 | 79.0 | 19.9 | -15.8 | +4.5 | +11.4 | 56.3
Luxembourg | 226 | 42.6 | 7.4 | 82.7 | 9.9 | -16.5 | +23.3 | -6.8 | 49.8
Latvia | 279 | 13.8 | 1.2 | 60.2 | 38.6 | -14.7 | -11.1 | +25.8 | 59.9
Mexico | 974 | 0.8 | 56.4 | 39.1 | 4.5 | +27.5 | -25.4 | -2.0 | 49.4
Malta | 38 | 9.0 | 6.3 | 84.3 | 9.3 | -10.8 | +9.8 | +0.9 | 52.5
Netherlands | 1 928 | 11.5 | 4.8 | 85.8 | 9.4 | -14.2 | +20.8 | -6.6 | 52.5
Norway | 664 | 13.2 | 10.3 | 84.1 | 5.6 | -9.6 | +20.3 | -10.7 | 48.8
New Zealand | 1 066 | 24.1 | 10.7 | 73.8 | 15.4 | -13.7 | +12.1 | +1.6 | 51.4
Poland | 679 | 1.8 | 15.0 | 21.0 | 64.0 | -0.2 | -51.0 | +51.2 | 58.6
Portugal | 881 | 8.4 | 7.5 | 85.9 | 6.6 | -8.1 | +21.6 | -13.5 | 53.1
Romania | 183 | 0.9 | 15.7 | 77.0 | 7.4 | -0.7 | +1.3 | -0.7 | 37.4
Slovak Republic | 158 | 2.9 | 9.4 | 65.1 | 25.5 | -6.1 | -7.1 | +13.2 | 54.1
Slovenia | 300 | 14.6 | 4.1 | 81.3 | 14.6 | -11.3 | +13.5 | -2.2 | 42.6
Sweden | 1 473 | 15.5 | 7.0 | 78.7 | 14.3 | -11.3 | +16.2 | -4.9 | 51.6
Turkey | 867 | 1.2 | 6.5 | 75.4 | 18.1 | -19.2 | +8.2 | +11.0 | 56.1
United States | 40 738 | 13.0 | 5.6 | 82.4 | 12.0 | -16.6 | +17.7 | -1.1 | 50.8
EU total (28) | 52 008 | 10.3 | 6.2 | 80.8 | 13.0 | -10.5 | +15.0 | -4.5 | 51.7
OECD total (34) | 115 555 | 9.2 | 6.6 | 80.4 | 13.1 | -13.4 | +15.5 | -2.1 | 51.4
Note: Korea and Japan determine who is an immigrant on the basis of nationality, not on the basis of country of birth.
1, 2: See “Notes, sources, and further reading” section.
* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
Sources: OECD Database on International Migration (2011-12). European Union Labour Force Survey (EU-LFS) 2012-13 for Turkey. Eurostat Database on International Migration and Asylum (2013) for Croatia and Switzerland. OECD Database on Immigrants in OECD Countries (DIOC) 2010-11.
StatLink  http://dx.doi.org/10.1787/888933214009

Chapter 3.

Defining characteristics of immigrant populations

Some of the factors that explain the discrepancies in outcomes between immigrants and the native-born spring directly from the migration process itself. The very fact of being born abroad may constitute an obstacle in that, for example, the immigrant may lack the native-born in-depth knowledge of the host society (how the labour market functions, networks, familiarity with public services, etc.). Understanding the constituent elements of the host country takes time, and integration outcomes tend to improve with duration of stay in the country of residence. More generally, structural differences – like the quality of the education system – between the home and host countries can also have an impact on integration. Mastering the language of the host country is especially important for success in the new country of residence.

A person’s reason for migrating to another country can also play an important part in determining outcomes, particularly on the labour market. For example, labour migrants usually have a job waiting for them on arrival or land one shortly afterwards. The situation is very different when it comes to family and humanitarian migrants. Immigrants’ countries of birth, particularly if they are lower-income countries where education systems tend to perform less well, also play a role in integration outcomes.

This chapter considers those immigrant-specific characteristics for which data are available through comparable sources internationally. They are: the composition of new immigration flows by category (Indicator 3.1); duration of stay, regions of origin, and citizenship (Indicator 3.2); immigrants’ language of origin and languages spoken at home (Indicator 3.3).

Throughout the publication, reference will be made to the background information presented in this chapter so as to explain certain disparities with native populations that affect immigrants. For further discussion of issues raised in each section, see the section entitled “Data limitations” at the end of the chapter.

Key findings

Some 4 million immigrants settled permanently in OECD countries in 2013, half of them in an EU country. These flows account for 0.4% of the OECD population and 0.5% of the EU’s. A quarter arrived as labour migrants from outside free mobility areas, while a third came for family reasons (in the European Union, this is the case for a quarter of immigrants). A further quarter of new arrivals were free mobility migrants. EU-wide, 43% of all new permanent migrants are EU citizens who have taken advantage of free mobility.

In 2012-13, two-thirds of immigrants had been living in the host country for more than 10 years, primarily in the settlement countries and in the longstanding immigration destinations.

In 2010-11, some 40% of immigrants living in an OECD or EU country had the nationality of their host country.

One-third of the foreign-born population is from high-income countries. Most migrants come from the same continent or countries that lie close by. Accordingly, half the foreign-born in the European Union are Europeans, and 50% of immigrants to the United States are from Latin America. Likewise, nearly half the immigrants in the OECD countries of Asia and Oceania are Asians, while African immigrants are much more likely to head for Europe than non-European OECD countries.

Two-thirds of immigrants spoke a foreign language in 2012. The share of immigrants who are foreign speakers and do not use the host-country language at home is larger in Canada and the United States than in several European countries with longstanding immigration, such as France and Germany.

Section 3.1. Composition of new immigration flows by category

Background

Indicator

The legal category of immigration is of great importance in explaining immigrants’ outcomes, particularly in the labour market. Since 2003, the OECD has collected data by category of permit from most EU and OECD countries. These administrative data are standardised, allowing cross-country comparison. While they cover only new immigration flows since 2005, they offer insight into reasons why foreign migrants settle in a country.

This section considers data on permanent immigration as a percentage of the total population.

Coverage

Permanent immigrants are foreign nationals of any age whose residence permit, issued on entry into the host country, grants them the right to stay permanently. They include foreigners who obtain a permanent residence permit immediately, those who have an initial temporary residence permit which is routinely renewed, and free mobility migrants (excluding those on short-term stays). To these may be added temporary immigrants who become permanent residents following a change in their status, such as students taking on employment after completing their studies.

In the 22 OECD countries for which standardised data are available, 3.9 million immigrants obtained permanent residence rights in 2013, half of them in an EU country. Those inflows account for 0.4% of the OECD’s total population and 0.5% of the EU’s, with the most new migrants heading for the small European countries with the lowest unemployment rates – Switzerland and Norway (Figure 3.1).

New inflows, as share of the resident population, have risen compared with their average share over the last ten years in Australia, the countries of northern Europe, the Netherlands, Germany and Austria. In contrast, permanent immigration to the countries of Southern Europe and Ireland is much lower than in the pre-crisis period. While flows still account for 0.9% of the population in Ireland, per capita, flows to Spain have declined by as much as half to 0.5%. In Canada and the United States, legal permanent migration flows have been stable, and they remain negligible in Mexico and the Asian destinations of Japan and Korea. Altogether, large countries tend to experience lower per capita flows than small ones.

Between 2005 and 2013, labour migrants from outside free mobility areas and their families accounted for almost a quarter of new permanent immigration. In the OECD, one-third of new flows came in the form of family migration versus a quarter in the European Union, while freedom of movement accounted for a further quarter, compared to 43% in the European Union (Figure 3.2). The high numbers of permanent immigrants arriving in Switzerland and Norway in 2012-13 brought with them particularly large shares of free-mobility flows. In the settlement countries of Oceania, as well as Canada and the United Kingdom, labour migration (which included accompanying family members) accounted for half of permanent inflows. Family immigration is still the driving force behind immigration to the United States (accounting for two-thirds), Korea and, to a lesser extent, France and Sweden. Sweden has also the largest share of humanitarian migrants in its inflows, followed by North America and Finland.

Figure 3.1. Permanent inflows to OECD and EU countries, 2003-11 and 2012-13

Annual averages in percentage of the total population

StatLink  http://dx.doi.org/10.1787/888933212157

Figure 3.2. Permanent inflows to OECD and EU countries by category of immigrant, 2005-13

Total = 100

StatLink  http://dx.doi.org/10.1787/888933212166

Notes and sources are to be found at the end of the chapter.

Section 3.2. Duration of stay, regions of origin, and citizenship

Background

Definition

The duration of stay indicator refers to the time that has elapsed between the year of arrival and the year of the survey. The composition by region of origin is subdivided into the five broad regions of Asia, Africa, Europe, Latin America and the Caribbean, Canada-United States, and Oceania. Nationality relates to current nationality – data on nationality at birth are not available for most countries.

Coverage

Immigrants aged between 15 and 64 years old, excluding those whose country of origin is not reported.

Across the OECD and the EU, around two-thirds of immigrants had resided in the host country for at least ten years in 2012-13. In the Baltic countries, and in other countries where borders have changed (countries once in the former USSR and former Yugoslavia), the long-settled proportions reach 90%. Three-quarters of immigrants are also long-time residents in Israel, the Netherlands, Germany, France, and the United States.

Most countries in southern and northern Europe have experienced significant migration inflows in recent years. In the last ten years, much greater numbers have arrived than in previous periods. The proportion of recent arrivals is highest in Japan, where three-quarters of immigrants have arrived in the last five years. In some Scandinavian countries (Denmark, Norway and Finland), in Cyprus,1, 2 and in Chile, too, one-third of the immigrant population are recent arrivals.

The recent immigration countries of Europe – particularly Ireland, Spain, Italy and Iceland – experienced large-scale immigration before the crisis, in the early years of the century. About one-third of their foreign-born population has thus been living in the country for more than five years, but for less than ten. Last, some countries (Switzerland, the United Kingdom, Luxembourg and Belgium) with long-settled immigrant populations have also recently experienced large migrant inflows.

On average, around 45% of immigrants held the nationality of the host country in 2010-11 (Figure 3.4). It may have been granted at birth or acquired (by naturalisation or through marriage to a national), or when a nation has been (re-)established. For example, in countries that were (re-) established after the fall of the Iron curtain (Croatia, Lithuania, the Slovak Republic), more than three-quarters of immigrants have the nationality of the country of residence. Over half of all immigrants are also nationals in countries that repatriated large numbers of settler nationals from their colonies during decolonisation. France is a case in point. Last, in countries which grant citizenship relatively easily, larger numbers of immigrants have obtained nationality – in settlement countries such as Canada and Australia and, a little longer ago, in the Netherlands.

Conversely, the share of foreigners is the highest in countries hosting many free-mobility migrants who tend to be less likely to naturalise, like in Luxembourg, as well as in countries where immigration is too recent for large-scale naturalisation, like those in southern Europe.

In 2010-11, one-third of immigrants were born in high-income countries (Figure 3.A1.1), a proportion that is even higher in the European Union. In Luxembourg, four out of five come from high-income countries, while shares are also high in Malta, the Slovak Republic and Ireland. By contrast, high-income countries – like Chile, Croatia, and the United States – that border poorer neighbours tend to be hosts to large numbers of immigrants from those lower-income countries as it is the case in most new recent immigration destinations, such as the countries of southern Europe.

Figure 3.3. Distribution of foreign-born population aged 15 to 64, by duration of stay, 2012-13

Percentage of the total foreign-born population

StatLink  http://dx.doi.org/10.1787/888933212174

Figure 3.4. Distribution of foreign-born population aged 15 to 64, by nationality, 2010-11

Total = 100

StatLink  http://dx.doi.org/10.1787/888933212187

Notes and sources are to be found at the end of the chapter.

In the OECD area in 2010-11, one-third of 15-64 year-old immigrants was born in a European country, while Latin America and Asia each accounted for 25% (Figure 3.6). A further 10% were born in Africa, while just 4% came from North America and Oceania. As for countries of origin, Mexico is the one where most immigrants were born with 12% of the total, followed by China and India (4% each), then by Poland and Germany with 3% each (Table 3.A1.1).

The first decade of this century saw a diversification in the countries of origin of the new migrants. This has been exerting a gradual impact on the composition of resident immigrant populations as well. The share of immigrants originating from Europe in particular declined from 36% in 2000-01 to 34% in 2010-11 (Figure 3.A1.2) while, over the same ten years, the proportion of resident born in Asia rose from 22% to 25%. The shares of other regions of origin (Latin America and Africa) have remained stable.

Immigrants from neighbouring countries or from the host-country region nevertheless account for the bulk of immigrants in OECD countries (Figure 3.5). One-half of the immigrant population living in the European union in 2011 came from within Europe: 5.6% from Poland (2.2 million), 5.4% from Romania (2.14 million), 5.3% from Turkey (2.1 million), and 3.8% from Russia (1.5 million). Other main regions of origin are Africa with 18% of foreign-born residents, of whom 5.3%, or 2.1 million, originate from Morocco. Asia accounts for a similar proportion with 17%. Similarly, half of the immigrant population in the OECD countries of the Americas comes from Latin America, chiefly Mexico with 10.5 million, or one-quarter of the total. The rest are predominantly from Asia (29%), primarily India, the Philippines and China, while only 14% are from Europe. Last, 43% of the immigrant population living in the OECD countries of Asia and Oceania originates from Asia (primarily China and Korea), and one-third from Europe.

Intra-European movement accounts for more than two-thirds of the immigrant population in six European countries out of ten, primarily in central Europe together with Luxembourg and Austria. Indeed, Europe is the principal continent of origin of immigrants to Europe. The only exceptions are France, Spain, and Portugal. France and Portugal have sizable African immigrant populations, while Spain is home to a contingent from Latin America with which it has close historical ties. Persons born in Africa account for half of France’s immigrants (three-quarters of whom are from North Africa and include repatriated settlers from Algeria) and 43% of Portugal’s, who come predominantly from African countries where Portuguese is an official language. In Belgium, the United Kingdom, the Netherlands, and in some countries of recent immigration, too, Africa also provides at least 20% of all immigrants (Figure 3.6).

The proportion of immigrants from Asia is largest in Japan, where the continent accounts for 80% of all immigrants, primarily from Korea, China, and the Philippines. Asian immigration is also very significant in Canada (49%) and Australia (42%), with the main origin countries being China, India, the Philippines, and Vietnam. In Europe, immigration from Asia represents one-third of immigrants in the United Kingdom (reflecting post-colonial ties with the Indian subcontinent), as well as in Scandinavia which hosts many refugees from the Middle East and other Asian countries (Iraq in particular).

More than one-half of immigrants in the United States were born in Latin America or the Caribbean. The share of immigrants from that region is also high in Spain (41%), which has many ties with the region, as mentioned above. The same also holds for Portugal and the Netherlands, where one immigrant out of five was born in South America, respectively in Brazil and Surinam, in the main.

Figure 3.5. Distribution of the 15-64 year-old foreign-born population, by region of birth and destination, 2010-11

StatLink  http://dx.doi.org/10.1787/888933212198

Figure 3.6. Composition of the 15-64 year-old foreign-born population, by region of birth and country of destination, 2010-11

StatLink  http://dx.doi.org/10.1787/888933212205

Notes and sources are to be found at the end of the chapter.

Section 3.3. Language of origin and languages usually spoken at home

Background

Indicator

The information in this section is drawn from the OECD Programme for the International Assessment of Adult Competencies (PIAAC). It considers information on: 1) one or two languages that respondents stated they had learned in childhood and still understood; 2) the language usually spoken at home.

Foreign-language immigrants are those who do not state that the host-country language is one of the two main languages that they learned in childhood and still understand. A distinction is made among foreign-language immigrants between those who usually speak the host-country language at home and those who do not. Among immigrant native-speakers – those who report that the host-country language is one of the two main languages they learned in childhood and still know – a distinction is made between those who can speak another language (multilingual native-speakers) and those who cannot (monolingual native-speakers). The language which the foreign-language respondents are asked to describe is the first language they spoke in childhood and still know. It is considered the language of origin, or native tongue.

Coverage

Adults aged between 16 and 65 years old at the time of the survey.

In all 20 countries for which data are available, nearly two out of three immigrants were foreign-language speakers in 2012. That proportion was higher in host countries where the official language is little used beyond their borders – e.g. Italy and the Nordic and German-speaking countries – as well as in the United States (Figure 3.7). By contrast, more than half the immigrants in Spain, Ireland, and Cyprus1, 2 were native-speakers.

In most countries, few foreign-language immigrants speak the host-country language at home. Exceptions, though, are the Czech and Slovak Republics, because most immigrants in both countries are from the other one – a result of the break-up of the former Czechoslovakia. In France, the Netherlands and Germany, nearly 50% of foreign-language immigrants speak the host-country language at home. The proportions may be attributed to many immigrants being long-settled and to the relatively high numbers of mixed cohabiting couples (see Chapter 4). In France and the Netherlands, the large migrant communities from the former colonies are also a factor. By contrast, most foreign-language immigrants in the United States, in Belgium (Flanders), Ireland, and Canada still speak their language of origin at home.

Spanish is the mother tongue of nearly one-third of foreign-speaker immigrants, while other common languages are Chinese and Arabic, which are both the native tongues of around 6% of foreign-language immigrants (Table 3.1). Intra-EU migration has made certain languages – particularly Romanian and Polish – into Europe’s most widely spoken foreign languages. Arabic-speakers (who account for 13% of immigrants in the European countries shown in Table 3.1) are concentrated in a handful of host countries. In France, they account for one-third of foreign-language immigrants and for sizable shares in Spain (21%) and Belgium (Flanders), the Netherlands, and Sweden (about 15% each).

The predominance of immigrants from Latin America in the United States makes Spanish the language of origin of nearly three foreign-language immigrants in five. By contrast, Canada exhibits great linguistic diversity, with 18% of foreign-language immigrants speaking Chinese, 9% Spanish, and 6% each speaking Tagalog, Arabic or Punjabi.

Figure 3.7. Languages learned and spoken by immigrants aged 16 to 64, 2012

Total = 100

StatLink  http://dx.doi.org/10.1787/888933212218

Table 3.1. Foreign-language immigrants aged 16 to 64, by destination and main language learned in childhood, 2012
Europe (18) | United States | Canada | OECD (22)
| Numbers | % of foreign speakers |  | Numbers | % of foreign speakers |  | Numbers | % of foreign speakers |  | Numbers | % of foreign speakers
Arabic | 1 921 900 | 13.4 | Spanish, Castillian | 11 937 100 | 56.8 | Chinese | 728 800 | 18.4 | Spanish, Castillian | 12 847 200 | 32.4
Romanian | 1 208 100 | 8.4 | Chinese | 1 346 800 | 6.4 | Spanish, Castillian | 337 400 | 8.5 | Chinese | 2 470 800 | 6.2
Portuguese | 880 200 | 6.1 | Vietnamese | 502 200 | 2.4 | Tagalog | 246 400 | 6.2 | Arabic | 2 429 900 | 6.1
Polish | 836 200 | 5.8 | Russian | 430 100 | 2.0 | Arabic | 243 000 | 6.1 | Romanian | 1 297 900 | 3.3
Albanian | 606 000 | 4.2 | Tagalog | 359 300 | 1.7 | Panjabi, Punjabi | 236 100 | 6.0 | Polish | 1 217 600 | 3.1
Spanish, Castillian | 573 100 | 4.0 | Persian | 320 500 | 1.5 | Polish | 143 300 | 3.6 | Portuguese | 1 121 100 | 2.8
Turkish | 539 400 | 3.8 | Tamil | 293 000 | 1.4 | Portuguese | 131 400 | 3.3 | Russian | 940 000 | 2.4
English | 498 600 | 3.5 | French | 277 600 | 1.3 | Russian | 121 700 | 3.1 | Albanian | 794 100 | 2.0
French | 397 200 | 2.8 | Arabic | 267 100 | 1.3 | Italian | 114 100 | 2.9 | Vietnamese | 753 100 | 1.9
German | 386 200 | 2.7 | Urdu | 260 500 | 1.2 | Persian | 109 000 | 2.8 | French | 708 500 | 1.8
Total | 14 355 300 |  | Total | 21 024 100 |  | Total | 3 962 200 |  | Total | 39 626 100 |
StatLink  http://dx.doi.org/10.1787/888933214015

Notes and sources are to be found at the end of the chapter.

Data limitations

Categories of immigration

Data on legal immigration categories are available from the OECD International Migration Database but cover only a selected number of OECD countries. The OECD statistics on migration flows distinguish among six broad reasons for permanent immigration. The labour category comprises foreigners who come to work as employees or self-employed. The families accompanying them are recorded separately. The family category includes foreigners who come to join their already resident family (through the family immigration reunification procedure) or to form a family (through marriage), regardless of whether the family member is a foreigner or a host-country national. The humanitarian category covers all foreigners who have obtained some form of internationally protected status (refugees, beneficiaries of subsidiary protection, etc.). The free circulation category applies to foreigners who move within free-mobility zones, generally staying in countries for at least a year, e.g. as part of EU and EFTA agreements or the Trans-Tasman travel arrangement between Australia and New Zealand. All immigrants who do not fit into any of those categories (for country-specific reasons or because they have special residence permits) are classed as “Other”.

Further information on the methodology and limitations can be found in Lemaitre et al. (2007). Surveys can be an alternative source of data that help shed light on reasons for migrating. Such data do not reveal the legal ground for obtaining a residence permit, but self-reported reasons, which may be quite different. An immigrant may report a motive that has nothing to do with the category shown on his or her first residence permit, either because it was easier to get a permit on this ground, or because he or she has forgotten the original reason (something that is more likely to happen when immigrants resided in the host country for a long time).

Survey data on the declared reason for migrating are particularly valuable in helping to understand the motives that drive free mobility immigrants, which cannot be obtained through administrative data, by definition. Very few surveys yield regular insights into the reasons for migrating and they generally question only recent immigrants. For all the above reasons, this chapter confines itself to administrative data on residence permits.

Eurostat also publishes annual administrative data on initial residence permits issued in the 28 member states to non-EU citizens. The data distinguish between family, education, employment, and other reasons (including international protection). For further information, see http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Residence_permits_statistics.

Languages learned and spoken by immigrants

The OECD Programme for the International Assessment of Adult Competencies (PIAAC) examines a number of issues relating to migrants’ language skills and the ways in which they are utilised and rewarded in the labour market. It has, however, some limitations. One important one is that migrants who do not speak the host country language are generally not surveyed. Another limitation is that in all countries – except Canada, the United Kingdom, Estonia, France, Korea and Poland – the PIAAC survey uses samples of around 5 000 people, giving small sample sizes for immigrants in countries where the immigrant population is small. The migrant sample is particularly small in Japan, Korea, Poland, and the Slovak Republic, all of which were therefore excluded from the analysis.

Notes, sources, and further reading

Note to Israel

* Information on data concerning Israel: http://dx.doi.org/10.1787/888932315602.

Notes to Cyprus1, 2

1. Note by Turkey:

The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Turkey recognises the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of the United Nations, Turkey shall preserve its position concerning the “Cyprus issue”.

2. Note by all the European Union Member States of the OECD and the European Union:

The Republic of Cyprus is recognised by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus.

Notes to Japan and Korea

Japan and Korea determine who is an immigrant on the basis of nationality, not on the basis of country of birth.

Notes to figures and tables

Averages factor in rates that cannot be published individually because samples are too small.

Figure 3.1: 2012 for Belgium, Finland, France and Spain. 2005-11 for Belgium. 2007-11 for Spain.

Figure 3.2: 2005-12 for Belgium, France and Ireland. 2006-12 for Finland. 2010-13 for Mexico. 2007-12 for Spain.

Figure 3.3: Population of 15 years and older for Australia, Canada and New Zealand.

Figure 3.5: All OECD countries (except Korea), all EU countries (except Croatia).

Sources to figures and tables

Indicator 3.1: OECD (2014), International Migration Outlook 2014, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2014-en.

Indicator 3.3: European Union Labour Force Survey (EU-LFS) 2012-13. American Community Survey (ACS) 2012. Israeli Labour Force Survey 2011. OECD Database on Immigrants in OECD Countries (DIOC) 2010-11 for the other non-European countries.

Figures 3.4,  3.5,  3.6: OECD Database on Immigrants in OECD Countries (DIOC) 2010-11. European Union Labour Force Survey (EU-LFS) 2012-13 for Croatia.

Figure 3.7 and Table 3.1: OECD Programme for the International Assessment of Adult Competencies (PIAAC) 2012.

Further reading

Eurostat (2011), “Migrants in Europe: A Statistical Portrait of the First and Second Generation”, Statistical Books, European Commission, Luxembourg.

Lemaitre, G., T. Liebig, C. Thoreau and P. Fron (2007), “OECD Standardised Statistics on Immigrant Inflows: Results, Sources and Methods”, OECD Publishing, Paris, www.oecd.org/els/mig/37035672.pdf.

OECD (2014a), Migration Policy Debates: Is Migration Really Increasing, OECD Publishing, Paris, www.oecd.org/els/mig/OECD%20Migration%20Policy%20Debates%20Numero%201.pdf.

OECD (2014b), A New Profile of Migrants in the Aftermath of the Recent Economic Crisis, OECD Publishing, Paris, http://dx.doi.org/10.1787/5jxt2t3nnjr5-en.

OECD (2014c), International Migration Outlook 2014, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2014-en.

OECD (2013a), International Migration Outlook 2013, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2013-en.

OECD (2013b), OECD Skills Outlook 2013. First Results from the Survey of Adult Skills, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264204256-en.

OECD (2012), Settling In: OECD Indicators of Immigrant Integration 2012, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264171534-en.

OECD – UN-DESA (2013), World Migration in Figures. OECD Publishing, Paris, United Nations Publications, New York, www.oecd.org/migration/mig/World-Migration-in-Figures.pdf.

Annex 3.A1.

Additional tables and figures

Table 3.A1.1. Main countries of origin of 15-64 year-old immigrants by region of destination, 2010-11
OECD (33) | Mexico | India | China | Poland | Germany | Total Foreign-born
| 10 628 391 | 3 197 624 | 3 185 410 | 2 818 337 | 2 707 764 | 90 699 872
EU (27) | Poland | Romania | Turkey | Marocco | Russia | Total Foreign-born
| 2 220 070 | 2 135 785 | 2 111 727 | 2 083 198 | 1 512 884 | 39 519 226
OECD America (4) | Mexico | India | Philippines | China | Vietnam | Total Foreign-born
| 10 541 389 | 1 991 766 | 1 948 338 | 1 633 378 | 1 197 677 | 41 606 956
OECD Asia-Oceania (4) | United Kingdom | China | Korea | New Zealand | India | Total Foreign-born
| 912 067 | 791 264 | 396 226 | 394 636 | 333 917 | 7 287 171
Source: OECD Database on Immigrants in OECD Countries (DIOC) 2010-11.
StatLink  http://dx.doi.org/10.1787/888933214021

Table 3.A1.2. Foreign-born 15-64 year-old population, by region of origin, 2010-11
|  | Born in : | Born in:
| All places of birth | Lower-income country | High-income country | Africa | Asia | Latin America and the Caribbean | United States, Canada and Oceania | Europe
| (Thousands) | (% of all foreign-born 15-64) | (% of all foreign-born 15-64)
Australia | 3 969 | 50.4 | 49.6 | 6.6 | 41.9 | 2.3 | 15.7 | 33.5
Austria | 1 057 | 66.6 | 33.4 | 3.3 | 10.1 | 2.2 | 1.0 | 83.5
Belgium | 1 291 | 51.0 | 49.0 | 28.4 | 9.3 | 3.1 | 1.3 | 57.9
Bulgaria | 18 | 55.5 | 44.5 | 0.0 | 20.0 | 0.6 | 1.0 | 77.9
Canada | 5 362 | 65.8 | 34.2 | 7.8 | 49.0 | 12.7 | 4.8 | 25.7
Switzerland | 1 620 | 41.8 | 58.2 | 6.2 | 8.2 | 5.6 | 2.6 | 77.3
Chile | 196 | 88.1 | 11.9 | 0.3 | 2.2 | 87.7 | 4.4 | 5.4
Cyprus1, 2 | 142 | 67.1 | 32.9 | 4.6 | 27.9 | 0.3 | 2.2 | 65.0
Czech Republic | 537 | 45.7 | 54.3 | 1.0 | 15.8 | 0.5 | 1.4 | 81.3
Germany | 8 887 | 49.1 | 50.9 | 2.8 | 19.7 | 1.8 | 1.3 | 74.4
Denmark | 416 | 55.3 | 44.7 | 7.6 | 31.8 | 2.8 | 3.5 | 54.2
Spain | 4 740 | 76.7 | 23.3 | 17.1 | 4.2 | 41.4 | 0.8 | 36.5
Estonia | 117 | 26.0 | 74.0 | 0.1 | 6.1 | 0.1 | 0.3 | 93.3
Finland | 208 | 35.6 | 64.4 | 9.5 | 20.5 | 2.0 | 2.4 | 65.6
France | 5 412 | 71.0 | 29.0 | 50.7 | 9.9 | 4.2 | 1.1 | 34.1
United Kingdom | 6 468 | 60.0 | 40.0 | 18.3 | 35.1 | 4.9 | 5.9 | 35.8
Greece | 1 119 | 73.8 | 26.2 | 3.9 | 12.4 | 0.6 | 4.8 | 78.3
Croatia | 281 | 88.9 | 11.1 | 0.1 | 0.3 | 0.1 | 0.2 | 88.6
Hungary | 265 | 76.6 | 23.4 | 1.3 | 8.2 | 0.7 | 1.5 | 88.2
Ireland | 637 | 24.4 | 75.6 | 7.3 | 10.4 | 2.0 | 4.6 | 75.7
Iceland | 27 | 24.9 | 75.1 | 2.8 | 15.3 | 2.6 | 5.6 | 73.7
Israel* | 1 169 | 66.9 | 33.1 | 15.8 | 16.8 | 4.1 | 5.1 | 58.1
Italy | 4 168 | 78.6 | 21.4 | 17.2 | 13.7 | 11.0 | 1.9 | 56.3
Japan | 1 218 | 68.4 | 31.6 | 0.5 | 80.0 | 13.0 | 3.6 | 2.8
Lithuania | 86 | 48.5 | 51.5 | 0.0 | 8.2 | 0.1 | 0.2 | 91.5
Luxembourg | 168 | 19.7 | 80.3 | 6.6 | 3.7 | 2.1 | 1.1 | 86.4
Latvia | 185 | 40.4 | 59.6 | 0.2 | 7.0 | 0.0 | 0.0 | 92.8
Mexico | 379 | 32.1 | 67.9 | 0.4 | 4.2 | 30.6 | 54.8 | 10.0
Malta | 16 | 14.6 | 85.4 | 4.0 | 4.7 | 0.0 | 32.2 | 48.3
Netherlands | 1 372 | 73.9 | 26.1 | 18.7 | 20.9 | 20.4 | 2.3 | 37.7
Norway | 479 | 49.5 | 50.5 | 10.3 | 28.6 | 4.2 | 3.5 | 53.4
New Zealand | 931 | 45.0 | 55.0 | 6.5 | 30.3 | 1.5 | 20.0 | 23.1
Poland | 141 | 48.7 | 51.3 | 2.6 | 11.2 | 1.1 | 5.6 | 79.5
Portugal | 749 | 76.0 | 24.0 | 43.1 | 3.5 | 20.2 | 1.8 | 31.4
Romania | 15 | 74.1 | 25.9 | 5.7 | 27.4 | 4.0 | 0.9 | 62.0
Slovak Republic | 97 | 20.8 | 79.2 | 0.7 | 3.3 | 0.4 | 0.6 | 95.0
Slovenia | 186 | 73.4 | 26.6 | 0.2 | 0.8 | 0.4 | 0.6 | 98.0
Sweden | 1 023 | 55.8 | 44.2 | 8.3 | 32.9 | 5.7 | 1.6 | 51.6
Turkey | 623 | 64.2 | 35.8 | 0.9 | 15.8 | 0.3 | 0.5 | 82.4
United States | 35 670 | 78.1 | 21.9 | 3.9 | 26.6 | 55.0 | 2.4 | 12.1
EU total (28) | 39 602 | 62.9 | 37.1 | 17.6 | 17.2 | 9.4 | 3.0 | 52.8
OECD total (33) | 90 796 | 55.6 | 44.4 | 9.4 | 18.3 | 10.5 | 5.3 | 55.9
Note: Japan determines who is a foreigner or a national on the basis of nationality, not on the basis of country of birth.
1, 2: See “Notes, sources, and further reading” section.
* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
Sources: OECD Database on Immigrants in OECD Countries (DIOC) 2010-11. European Union Labour Force Survey (EU-LFS) 2012-13 for Croatia.
StatLink  http://dx.doi.org/10.1787/888933214031

Figure 3.A1.1. Immigrant population aged 15 to 64 years old and born in a high-income country, 2010-11

Percentage of the total immigrant population

Note: Japan determines who is a foreigner or a national on the basis of nationality, not on the basis of country of birth.

1, 2: See “Notes, sources, and further reading” section.

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: OECD Database on Immigrants in OECD Countries (DIOC) 2010-11. European Union Labour Force Survey (EU-LFS) 2012-13 for Croatia.

StatLink  http://dx.doi.org/10.1787/888933212226

Figure 3.A1.2. Changes in the distribution of the 15-64 year-old foreign-born population in the OECD area, by region of origin, 2000-01 (inner circle) and 2010-11 (outer circle)

Note: Percentages are slightly different to those in Figure 3.5 because data for 2000-01 are available only for 30 countries.

Source: OECD Database on Immigrants in OECD Countries (DIOC) 2000-01 and 2010-11.

StatLink  http://dx.doi.org/10.1787/888933212239

Chapter 4.

Characteristics of immigrant households

The household and family structures are determinants in a number of integration outcomes. Studies have shown, for example, that the home environment (whether parents are present and the size of the family) has an impact on children’s school performance, which in turn affects their economic integration later on. Family structure also determines such living conditions as income and housing as well as the ability of adults to both work and support their children.

The integration outcomes of households that are solely composed of immigrants differ significantly from those of mixed households (where one mantainer is immigrant and the other native-born) – with the latter broadly resembling those of native households. Beyond socio-demographic characteristics, a prerequisite for understanding the outcomes of the foreign-born is thus to understand the differences between their household structure and that of the native-born.

This chapter volunteers two definitions of “immigrant household” and goes on to analyse the size of such households (Indicator 4.1) and their composition (Indicator 4.2).

Throughout this publication, reference will be made to the background information presented in this chapter so as to explain certain defining immigrant characteristics. For further discussion of issues raised by the indicators considered, see the section entitled “Data limitations” at the end of the chapter.

Key findings

Across the OECD in 2012, 15% of households had at least one immigrant adult among the persons declared as responsible for the household: in 11%, all the reference persons were immigrants and 4% were mixed households. Those percentages were highest in countries of longstanding immigration.

In the European Union, 4% of households have at least one member who is a non-EU national.

Immigrant households are more likely than native-born ones to be families with children (34% versus 24% in the OECD), especially in countries of recent immigration. In the European Union, immigrants living alone are also overrepresented (36% versus 31% in native-born households), particularly in longstanding immigration countries.

On average, immigrant households are larger than native-born ones.

Section 4.1. Definition and size of immigrant households

Background

Definition

Two definitions of “immigrant household” are possible. The looser definition deems a household an immigrant household if at least one of the responsible persons is an immigrant. Under the terms of the more restrictive definition, all those responsible for the household are immigrants. In general up to two people can be responsible for a household. The definition of the person responsible varies from country to country (see “reference person” in “Glossary”).

Any household where at least one responsible person was born in the country of residence is considered to be a native-born household in this publication, unless otherwise stated.

The average size of households takes into account all the occupants identified as living in the dwelling, whatever their age. In order not to overestimate the average size of native-born households, mixed households (which have at least two occupants by definition) are excluded from the latter category for the calculation of the average size.

Coverage

Households with at least one responsible person over the age of 15.

Across the OECD in 2012, an average of 15% of all households had at least one reference person who was an immigrant (Figures 4.1). In three-quarters of those households (or 11% of all households) all the reference persons were immigrants. In the European Union, at least one immigrant was responsible for 11% of all households, and in 8% of all households all the reference persons were immigrants.

Whatever the definition used, less than one household in ten includes an immigrant in most central European countries and Korea. There are also relatively few immigrant households in Scandinavian countries, with the exception of Sweden. In Luxembourg, by contrast, half of households have at least one immigrant member, 43% in Israel, and one-third in Australia and Switzerland.

In the European Union, 4% of households are composed of at least one non-EU national responsible for the household, one-third of which are of mixed origin (one responsible person is a third-country national and the other a host-country national or another EU national). In the Baltic countries, more than one household in six has at least one member who is a third-country national. The highest shares of households with at least one non-EU national in other countries are to be found in Spain, Austria, and Luxembourg.

Immigrants who reside in longstanding destinations are more likely to be living in mixed households. Examples are the Netherlands, France and Germany, where more than two households in five with at least one immigrant inhabitant are mixed. Australia, too, has a high proportion of immigrant households that are mixed (a third), as have immigrant households in the countries of central Europe and Portugal. By contrast, fewer than 25% of households with immigrants in the Baltic countries of Estonia and Latvia and in southern Europe are mixed.

Immigrant households are larger than native-born ones in half of all OECD countries. They have, on average, three members in the United States and Canada, as well as in Spain, Ireland and New Zealand. In those countries, at least 0.4 more people live in immigrant households than in those inhabited solely by the native-born (Figure 4.2). Differences are particularly wide in the United Kingdom, Austria and Luxembourg. In countries where the immigrant population tends to be older than the native-born, native-born households are larger, as in Israel and Poland, for example. Children account for differences in size (see Indicator 4.2).

Figure 4.1. Immigrant households according to two definitions, 2012

Percentage of all households

StatLink  http://dx.doi.org/10.1787/888933212243

Figure 4.2. Average size of solely immigrant and solely native-born households, 2012

StatLink  http://dx.doi.org/10.1787/888933212252

Notes and sources are to be found at the end of the chapter.

Section 4.2. Composition of immigrant households

Background

Definition

This section analyses household composition with respect to two criteria: the number of adult persons and the presence of children under the age of 18. It identifies four types of households: a person living alone, more than one adult (living as a couple or not) without children, a single person with children (single-parent family), and more than one adult (living as a couple or not) with children, referred to as “families” for the sake of simplicity.

Coverage

Households with at least one responsible person over the age of 15.

Immigrant households are more likely to have children than native-born ones. In 2012, they were overrepresented among single-parent families and, even more so, among families – particularly in southern European countries, Ireland, Finland, and the United States.

In the OECD, 29% of immigrant households consisted of a single person, 31% of more than one adult without children, 6% of a single adult with a child or children, and 34% were families. In the European Union, families accounted for a lower share of immigrant households (29%) than the OECD, although even that lower share was larger than among the native-born. The proportion of single-person immigrant households was higher, at 36%, than in the OECD, and also higher than among native-born households. In countries where immigrants are older than the native-born (central Europe, the Baltic countries and, in particular, Israel), at least three-quarters of all immigrant households are childless. In Poland, two-thirds of immigrant households are occupied by a single person (Table 4.1). Individuals living alone also account for over half of immigrant households in the European countries where free mobility under EU and EFTA arrangement is an important factor – Germany, the Netherlands, Denmark and Norway.

Immigrant households with children are overrepresented in the recent immigration countries of southern Europe and Ireland, where they account for over two households in five. They also make up 46% of immigrant households in the United States and half in Canada. Single-parent families are about twice as common in immigrant as in native-born households in Iceland, Portugal, Finland, and the Netherlands.

Table 4.1. Composition of immigrant households, 2012
| Immigrant households | Difference (+/-) with the native-born households +: higher than the native-born -: lower than the native-born
| No child in the household | Child(ren) in the household | No child in the household | Child(ren) in the household
| Single person | More than one adult without children | Single person with one or more children | More than one adult with one or more children | Single person | More than one adult without children | Single person with one or more children | More than one adult with one or more children
| Total = 100 | Difference in percentage points
Australia | 26.6 | 29.1 | 12.9 | 31.4 | +3.0 | -3.6 | +2.1 | -1.5
Austria | 33.2 | 29.1 | 4.0 | 33.7 | -3.8 | -11.1 | +1.7 | +13.2
Belgium | 39.0 | 25.0 | 7.2 | 28.8 | +4.6 | -15.0 | +3.6 | +6.8
Canada | 24.1 | 24.2 | 9.7 | 42.1 | -4.4 | -8.6 | +1.1 | +11.8
Croatia | 24.7 | 45.4 | 0.9 | 29.0 | +0.2 | -0.3 | +0.1 | +0.0
Cyprus1,2 | 29.5 | 36.9 | 4.8 | 28.9 | +10.2 | -10.9 | +3.5 | -2.8
Czech Republic | 44.5 | 30.9 | 2.6 | 22.0 | +17.8 | -14.6 | -0.1 | -3.1
Denmark | 56.2 | 17.6 | 8.3 | 17.9 | +9.5 | -12.0 | +3.4 | -1.0
Estonia | 45.2 | 42.9 | 1.3 | 10.6 | +11.0 | +6.8 | -2.7 | -15.1
Finland | 42.0 | 18.7 | 10.1 | 29.2 | +1.8 | -18.4 | +7.2 | +9.4
France | 43.1 | 29.9 | 6.4 | 20.6 | +9.1 | -8.7 | +2.6 | -3.0
Germany | 51.9 | 29.5 | 4.7 | 13.8 | +12.3 | -10.6 | +1.5 | -3.2
Greece | 19.9 | 38.4 | 1.6 | 40.1 | -0.8 | -13.6 | +1.0 | +13.4
Hungary | 21.3 | 44.6 | 3.4 | 30.7 | -2.4 | -3.8 | +1.5 | +4.7
Iceland | 41.7 | 16.2 | 12.6 | 29.5 | +12.8 | -19.4 | +5.9 | +0.7
Ireland | 14.9 | 26.9 | 8.9 | 49.3 | -8.0 | -12.9 | +2.8 | +18.1
Israel* | 42.0 | 33.0 | 6.0 | 19.0 | +18.0 | +12.0 | -1.0 | -29.0
Italy | 35.5 | 23.1 | 3.8 | 37.6 | +5.1 | -20.9 | +1.6 | +14.2
Latvia | 44.2 | 42.5 | 1.5 | 11.8 | +16.0 | +1.0 | -2.7 | -14.4
Lithuania | 57.4 | 29.5 | 4.4 | 8.8 | +23.5 | -8.1 | +0.8 | -16.2
Luxembourg | 30.8 | 31.4 | 3.7 | 34.1 | -4.2 | -9.6 | +1.8 | +12.1
Malta | 47.4 | 34.8 | 4.1 | 13.7 | +25.4 | -14.5 | +1.6 | -12.4
Netherlands | 50.6 | 20.1 | 8.8 | 20.5 | +15.4 | -19.2 | +6.6 | -2.7
New Zealand | 15.6 | 47.9 | 4.0 | 32.5 | -8.3 | +0.6 | -0.6 | +8.3
Norway | 52.0 | 16.0 | 8.1 | 24.0 | +11.2 | -15.9 | +3.4 | +1.3
Poland | 66.4 | 26.5 | 2.7 | 4.3 | +41.6 | -15.8 | +1.1 | -26.8
Portugal | 21.9 | 28.7 | 10.2 | 39.1 | +2.7 | -20.8 | +7.5 | +10.6
Slovenia | 37.6 | 37.3 | 3.2 | 21.9 | +9.7 | -5.7 | +0.9 | -4.9
Spain | 19.4 | 34.0 | 2.9 | 43.7 | -4.4 | -14.4 | +1.0 | +17.8
Sweden | 32.7 | 29.0 | 7.4 | 30.9 | -6.9 | -5.7 | +3.4 | +9.2
Switzerland | 32.6 | 34.9 | 3.4 | 29.1 | -0.4 | -9.3 | +1.1 | +8.6
United Kingdom | 27.0 | 33.6 | 6.8 | 32.5 | -2.2 | -10.4 | +1.9 | +10.7
United States | 21.5 | 32.7 | 5.7 | 40.1 | -7.3 | -8.2 | +0.2 | +15.3
EU total (28) | 35.9 | 30.0 | 5.3 | 28.9 | +4.7 | -12.5 | +2.3 | +5.5
OECD total (29) | 28.7 | 30.7 | 6.2 | 34.4 | -1.9 | -10.4 | +2.0 | +10.4
StatLink  http://dx.doi.org/10.1787/888933214040

Notes and sources are to be found at the end of the chapter.

Data limitations

The definitions of immigrant households in this section describe households where the two responsible people are immigrants. Although many countries mean something different by “reference person”, most countries define “family structure” in the same manner, so ensuring comparability. As there is no way of always knowing the nature of the relationship between the people living in household, no distinction is made between married couples and two persons cohabiting out of wedlock. As the data are taken chiefly from household surveys, they cover only “ordinary” dwellings (excluding hostels and group homes, retirement homes, military barracks, encampments, hospitals, prisons, etc.).

Notes, sources, and further reading

Note to Israel

* Information on data concerning Israel: http://dx.doi.org/10.1787/888932315602.

Notes to Cyprus1, 2

1. Note by Turkey:

The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Turkey recognises the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of the United Nations, Turkey shall preserve its position concerning the “Cyprus issue”.

2. Note by all the European Union Member States of the OECD and the European Union:

The Republic of Cyprus is recognised by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus.

Notes to figures and tables

Figure 4.2: In order not to overestimate the average size of native-born households, mixed households (which have at least two occupants by definition) are excluded from the latter category for the calculation of the average size in this figure.

Korea determines who is an immigrant on the basis of nationality, not on the basis of country of birth.

In Sweden, there is only one reference person for the household.

Averages factor in rates that cannot be published individually because samples are too small.

Sources to figures and tables

European Union Statistics on Income and Living Conditions (EU-SILC) 2012; American Community Survey (ACS) 2012; Australian Census of Population and Housing 2011; Canadian National Household Survey (NHS) 2011; Israeli CBS Household Expenditure Survey 2012; Korean Population Census 2010; New Zealand Household Economic Survey (HES) 2012.

Further reading

Eurostat (2010), “Household Structure in the EU”, Statistical Books, European Commission, Luxembourg.

OECD (2012), Settling In: OECD Indicators of Immigrant Integration 2012, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264171534-en.

Chapter 5.

Labour market outcomes of immigrants

Jobs are immigrants’ chief source of income. Finding one is therefore fundamental to their becoming part of the host country’s economic fabric. It also helps them – though there is no guarantee – to take their place in society as a whole by, for example, clearing the way into decent accommodation and the host country’s health system. Work also confers social standing in the eyes of the immigrant’s family, particularly children, and with respect to the host-country population.

This chapter examines three indicators: employment and activity rates (Indicator 5.1), the unemployment rate (Indicator 5.2), and a labour market exclusion indicator – long-term unemployment and inactivity (Indicator 5.3). “Data limitations” at the end of this chapter further discusses the indicators and any issues of data availability and definition.

Key findings

In 2012-13, two in three immigrants aged 15 to 64 were in employment across the OECD – a proportion that was one percentage point higher than among the native-born. An average of three-quarters of male immigrants were employed, three percentage points more than among their native-born peers. As for female employment rates, they were the same among foreign- and native-born women at 57%.

EU immigrant employment rates were, on average, lower than in non-EU OECD countries, among both men (70%) and women (54%).

Between 2006-07 and 2012-13, in the OECD, a slight dip in the overall employment rates translated into a 4-point drop in the male employment rate, while among women it was stationary.

In EU countries, the employment gap between immigrants and natives widened slightly in the wake of the 2007-08 economic and financial downturn, while it stayed stable in the non-EU OECD area.

Immigrants with no or low education were more likely to be in work than their native-born peers in half of all OECD and EU countries. Indeed, their employment rates were far higher in some countries, e.g. the United States and Luxembourg.

A high level of education makes it easier to join the labour market. Yet, immigrants with higher-education degrees struggle more to enter the workplace than their native-born peers.

In 2012-13, the immigrant unemployment rate was 11% across the OECD and 16% in the European Union – respectively 3 and 6 percentage points higher than native-born rates.

In OECD countries, the unemployment rate widened by one percentage point on average among both men and women between 2007-08 and 2012-13. In the European Union, it widened by nearly two points among men over the same period. The harder the 2007-08 crisis hit a country (like those in southern Europe), the wider the unemployment gap between the foreign- and native-born has grown.

EU-wide, higher proportions of inactive immigrants (21%) than inactive native-born (16%) are willing to work. In other words, they are more likely to experience involuntary inactivity. Shares and gaps with the native-born are slightly lower in the OECD.

Section 5.1. Employment and activity

Background

Indicator

All the indicators in this section use definitions drawn up by the International Labour Organization (ILO). Employed persons are all those who worked at least one hour in the course of the reference week and those who had a job but were absent from work. The employment rate denotes people in employment as a percentage of the population of working age (15-64 years old). The activity rate is the active population (employed plus unemployed) divided by the working-age population.

Immigrants who arrive in a new host country need time to develop the human capital that will enable them to find their place in the host country’s labour market. The longer they stay, the better their employment outcomes become, gradually converging with those of the native-born. In the absence of longitudinal data, the section entitled “Data limitations” at the end of the chapter explains how pseudo-cohort datasets were used to estimate the effect on labour outcomes of length of residence. In other words, instead of following over time the same immigrants, the approach is to look at findings from 2007 and 2012 surveys of randomly sampled immigrants who reported arriving the same years (from 2003 to 2007).

Coverage

Population of working age (15-64 years old). For the pseudo-cohort analysis, outcomes of the 15-60 years old in 2007 are compared to those of 20-65 years old in 2012.

Across the OECD in 2012-13, the average proportion of immigrants of working age who were in employment was, at 65.5%, comparable to the 64.4% share of their native-born peers. Those rates exceeded 70% in countries where immigration is primarily labour-driven and those where employment is relatively buoyant, like the settlement destinations, Switzerland, and Luxembourg (Figure 5.1). In the European Union, by contrast, immigrants were less likely to be in employment than the native born (62% versus 65%), chiefly because women’s average 54% employment rate was 5 percentage points lower than that of their native peers (Figure 5.1). Far fewer immigrant than non-migrant women are in work in the longstanding immigration destinations of the EU15 countries, where the gap between the two groups exceeds 10 points, particularly in Germany, Sweden, the Netherlands and Belgium. In Israel, Korea, Chile, Luxembourg, Hungary and Italy, immigrant women are more likely to be working than their native counterparts. In those countries, like the United States, foreign-born men also show higher employment rates than native male workers.

High levels of education improve immigrants’ and non-migrants’ prospects of entering the workplace everywhere. Yet, immigrants with higher-education degrees always struggle on the host country’s labour market more than their native peers (Figure 5.2). They show an employment shortfall of over 10 percentage relative to the native-born in southern Europe and in longstanding immigrant countries like Belgium, France, the Netherlands and Sweden. The trouble that foreign-educated immigrants have in getting their credentials recognised in the labour market are a barrier to the workplace in most countries. Across the European Union, tellingly, the employment rate among immigrants with a host-country degree is 10 points higher than among those with a foreign qualification and comparable, on average, to the rate among native-born (Figure 5.A1.3).

Figure 5.1. Employment rates by place of birth and gender, 2012-13

Percentage of the working-age population (15-64 years old)

StatLink  http://dx.doi.org/10.1787/888933212265

Figure 5.2. Employment rates of foreign-born population aged 15-64 not in education by educational level, 2012-13

Difference in percentage points with the native-born

StatLink  http://dx.doi.org/10.1787/888933212298

Notes and sources are to be found at the end of the chapter.

The labour market integration of low-educated immigrants paints a very different picture. They enjoy average employment rates that are similar to those of their native-born peers in the European Union and higher in the OECD. In fact, they are more likely to be in work in half of all OECD and EU countries, in particular in countries which have seen recent inflows of immigrants with no or low qualifications. In the United States, their employment rate is 18 percentage points higher than that of native workers. They have also carved out a very wide gap in Cyprus1, 2 and Luxembourg. However, in the Netherlands, Estonia and northern Europe, migrants struggle more than natives in the labour market, regardless of education level.

The age and education level of the working-age population are two elements that are decisive in determining the average employment rate. Immigrants are widely overrepresented in very economically active age groups and among workers with no or low qualifications. Such structural factors may account in part for differences with the native-born in average employment rates. If, for example, the EU immigrant population was of the same age and educational level as the native-born population in 2012-13, the employment rate would be constant among women and 2.5 percentage points lower among men (Figure 5.A1.1).

Across the European Union, the employment rates of immigrants were lower than those of native workers in 2012-13, with the gap widening very slightly in the wake of 2006-07. The opposite trend prevails in non-EU OECD countries (Figure 5.4) and in European economies that have recovered in recent years, such as Austria, Germany, Switzerland and the United Kingdom, where the employment gap between foreign- and native-born workers has narrowed, even though immigrant employment rates are still lower. In Sweden, however, the gap – already wide in 2006-07 – grew further in 2012-13, while the southern European and the Baltic States worst hit by the crisis (Spain, Latvia and Greece) now register lower rates among immigrants than among native workers, in contrast to the pre-crisis period. In the other southern European and Baltic countries, however, immigrants’ employment rates are still higher, albeit by less, while in Luxembourg and the United States the gap with domestically born workers has actually widened in their favour.

Between 2006-07 and 2012-13, the slight dip in the share of immigrants in work in the OECD was the reflection of a 4-point drop in men’s employment rate and the stationary situation in the female rate. The same trend was observed in the European Union (Figure 5.3). The female immigrant employment rate has thus held its own against the mounting joblessness triggered by the 2007-08 crisis, the only exception being the countries hardest hit by the downturn (Spain, Greece and Ireland, Slovenia), where immigrant women’s employment rate has dropped by 8 to 12 percentage points. In most countries, though, it has gone on climbing, particularly in European economies that have recovered in recent years, in Australia, New Zealand, and in countries where rates were very low prior to the crisis, e.g. Belgium, Poland, Mexico and Malta. Native women’s employment has followed much the same patterns.

As for immigrant men, they were sorely affected by the 2007-08 crisis – even more so than their native-born peers. In southern Europe (except Malta and Portugal) and the Baltic countries, their employment rates fell twice as sharply between 2006-07 and 2012-13. By contrast, in the Oceania and North America – and in European countries that were left relatively unscathed by the crisis – immigrant men employment rates have remained steady, risen since 2006-07 (as in Australia and German-speaking Europe), or experienced falls that have been no worse than for native-born men, as in the United States and the United Kingdom.

Figure 5.3. Employment rates among foreign-born by gender in 2006-07 and 2012-13

Percentages of the working-age population (15-64 years old)

StatLink  http://dx.doi.org/10.1787/888933212309

Figure 5.4. Employment gap between foreign- and native-born aged 15-64 in 2006-07 and 2012-13

Percentage points

StatLink  http://dx.doi.org/10.1787/888933212315

Notes and sources are to be found at the end of the chapter.

In 2012-13, the OECD-wide employment rate of recent immigrants – resident in the host country for less than five years – was some 10 percentage points lower than that of the native-born and as much as 13 points worse in the European Union (Figure 5.A1.4.). Their situation was particularly worrying in such EU15 countries as Sweden, the Netherlands, France, Germany, as well as in Turkey.

The immigrant situation in the labour market tends to improve with the years spent in the host country. Still, the 2007-08 economic and financial crisis has made labour market integration even more fraught for cohorts who immigrated just before the crisis. The employment rates of arrivals between 2003 and 2007 fell between 2007 and 2012 in half of OECD countries. They suffered worse in European countries like Spain, Ireland and Greece that the crisis hit hardest, with their employment rates tumbling by 10 percentage points (Figure 5.5). All foreign-born workers were affected, but the low-skilled have borne the brunt in Spain, Greece, Denmark, and Ireland (Figure 5.A1.5).

Countries relatively spared by the crisis have brought confirmation of the duration-of-stay convergence process. It is more visible among immigrants with low or no education in Germany, Israel, and the Netherlands and, to a lesser degree, Switzerland, while in France it is to be observed among higher-education degree holders. Highly educated immigrants are also converging with the native-born in the United States, Norway, and the United Kingdom, whereas low educated ones have seen their employment rates dwindle over the last five years.

The share of economically active (both employed and unemployed) in the working-age population encompassed an average of nearly three-quarters of immigrants in 2012-13 in the OECD and the European Union, a share comparable with that of people born in the host country. It exceeds 80% in Iceland, Switzerland, and southern Europe (particularly Portugal), while in Turkey, Croatia, and Mexico it is below 60% (Figure 5.6). In Luxembourg, Chile, Korea and southern Europe, male and female immigrants are more likely to be economically active than the native-born, while the opposite applies to the Nordic countries, the Netherlands and Mexico. In longstanding immigration destinations like France, Germany, Belgium and the United States, relatively fewer foreign- than native-born women join the labour force, while relatively more immigrant men do.

Figure 5.5. Change between 2007 and 2012 in employment rates of 15-64 immigrants not in education who arrived between 2003 and 2007

Percentage points

StatLink  http://dx.doi.org/10.1787/888933212327

Figure 5.6. Activity rates by place of birth and gender, 2012-13

Percentage of the working-age population (15-64 years old)

StatLink  http://dx.doi.org/10.1787/888933212330

Notes and sources are to be found at the end of the chapter.

Section 5.2. Unemployment

Background

Indicator

All the indicators in this section use definitions from the International Labour Organization (ILO). Unemployed persons are those without work, available for work and who have been seeking work in the course of the reference week. The unemployment rate is the percentage of unemployed people in the labour force (the total number of people employed and unemployed).

Analyses using pseudo-cohort datasets are presented at the end of this section (see “Background” in Indicator 5.1). They consist in comparing the unemployment rates in 2007 and in 2012 of immigrants who declared they arrived in the host country between 2003 and 2007.

Coverage

The economically active population of working age (15-64 years old). For the pseudo-cohort analysis, outcomes of the 15-60 years old in 2007 are compared to those of 20-65 years old in 2012.

Across the OECD in 2012-13, the immigrant unemployment rate was some 11%, compared to 8% among the native-born. In the European Union, it rose to 16%, against 10% among natives (Figure 5.7). The highest rates are to be found in Greece and Spain, where one foreign-born worker in three was out of work and lowest in Luxembourg. In all non-EU OECD member states, the rate was less than 9%, and as little as 1 in 20 in Korea, Israel, and Australia.

In most countries, though, unemployment rates are higher among the foreign- than the native-born, whether men or women. There are some noteworthy exceptions, such as the settlement countries, the United States, Chile, and a few Central European countries (Figure 5.8), where rates are low in international comparisons. In some longstanding immigration countries in the European Union, such as Belgium and the Netherlands, and in destinations where humanitarian migrants have accounted for much of the inflow (e.g. Denmark and Sweden), immigrant unemployment rates are high and nearly double those that affect natives. The same is true of Austria, Germany, Switzerland and Norway, albeit with lower rates (Figure 5.8).

Although unemployment is generally greater among people with low levels of education, the gap between the foreign- and native-born is wider among those who are tertiary education graduates. Across the OECD and the European Union, degree-holding immigrants are on average twice as likely to be out of work than their native counterparts. In the United States, New Zealand and Israel, too, highly educated migrants show higher unemployment rates than natives, though the gap is narrower than in Europe. And, in all settlement countries and the United States, low educated immigrants of working age are less likely to be looking for work than their native peers with the same level of educational attainment (Figure 5.7).

Figure 5.7. Unemployment rates by place of birth, gender, and level of education, 2012-13

Percentages of the economically active population (15-64 years old)

StatLink  http://dx.doi.org/10.1787/888933212344

Figure 5.8. Unemployment rates by place of birth, 2012-13

Percentage of the economically active population (15-64 years old)

StatLink  http://dx.doi.org/10.1787/888933212358

Notes and sources are to be found at the end of the chapter.

Between 2006-07 and 2012-13, the unemployment rate rose 3.5 percentage points in the OECD area among immigrants and the gap between them and the native-born widened by 1 point. In the European Union, it increased by more than 4 percentage points, especially in Greece and Spain, where immigrant unemployment rates climbed by 25 percentage points, compared to 15 among the native-born. The gap also stretched in Denmark, Sweden and the Netherlands (Figure 5.9). The trend was the opposite in the United Kingdom, Switzerland and New Zealand, where gaps narrowed, while Germany and Israel actually saw unemployment fall between 2006-07 and 2012-13, with the drop sharper among the foreign- than the native-born in Germany. As for the Czech Republic, the unemployment rate fell among immigrants and rose among natives.

The economic and financial downturn has affected certain population groups particularly badly, especially the poorly educated. The fact that there are disproportionate numbers of immigrants in that group explains in part that they should have been worse hit by rising unemployment than native-born. For a given level of education, the growth in unemployment has, on average, been comparable among foreign-born and native-born residents in most other countries, with the exception of immigrants with low or no education in southern Europe, Denmark and Sweden. In North America, Ireland, and the United Kingdom, by contrast, the rise in unemployment has not been as steep among low educated foreign-born workers as it has been among their native counterparts. As for immigrants with tertiary degrees, the climb in unemployment has hit them harder than their native peers in most OECD and EU countries.

Unemployment is a serious problem for recent immigrants, particularly in the EU15 countries. In the OECD and the European Union, immigrants who have been resident for less than five years show unemployment rates that are 5 and 9 percentage points higher than among native-born people, respectively (Figure 5.A1.6). In Sweden, it is as much as 20 percentage points higher, double that observed for all immigrants. Recent immigrants have also been badly affected in France, Turkey and Belgium, though not in the United States, New Zealand, Latvia, or Cyprus.1, 2

Immigrants who arrived in an OECD country before the downturn – between 2003 and 2007 – showed an average unemployment rate in 2012 that was 4 percentage points higher than in 2007. As for the European Union, the steep rise in joblessness in southern Europe, particularly Spain and Greece, has driven up the immigrant unemployment rate (Figure 5.10). In fact, in one out of two counties, it has not fallen since 2007 among those who arrived between 2003 and 2007. However, in the countries where their situation has improved, their unemployment rate has receded more markedly than among incomers who arrived before 2003 (Figure 5.10). In countries that have registered steep climbs in unemployment, the 2003-07 cohort has been less impacted than long-settled immigrants (with the exceptions of Denmark, Ireland, and Portugal).

Figure 5.9. Change in unemployment rates of the 15-64 persons by place of birth and level of education between 2006-07 and 2012-13

Percentage points

StatLink  http://dx.doi.org/10.1787/888933212369

Figure 5.10. Change between 2007 and 2012 in unemployment rates of 15-64 immigrants by arrival period

Percentage points

StatLink  http://dx.doi.org/10.1787/888933212277

Notes and sources are to be found at the end of the chapter.

Section 5.3. Risk of labour market exclusion

Background

Indicator

Unemployment and inactivity can result in social exclusion if they persist over time. This section addresses two indicators of the risk of exclusion from the labour market: i) Long-term unemployment (the number of job seekers who have been without a job for at least 12 months as a percentage of all the unemployed); ii) the discouraged workers (as a percentage of the 15-64 economically inactive population). Discouraged workers are persons who, while willing and able to engage in a job, are not actively seeking work or have ceased to seek work because they believe there are no suitable available jobs. This involuntary inactivity is a key indicator of labour market exclusion.

Coverage

The 15-64 unemployed and the 15-64 economically inactive people.

Over one-third of unemployed immigrants across the OECD had been looking for work for over 12 months in 2012-13 – a proportion similar to that among native-born job seekers (Table 5.1). Much the same situation prevailed in the European Union, although the share of long-term job seekers among the unemployed was greater at 45%.

Long-term unemployment affects over one in two unemployed immigrants in Ireland, Greece and Latvia, but less than one-tenth in the settlement countries like Canada, Australia and New Zealand where it is scarce among people born in the country, too. It is, though, more widespread among the foreign- than the native-born in two-thirds of OECD and EU countries. In the Netherlands, Switzerland and Sweden, it is 10 percentage points higher. By contrast, the immigrant long-term unemployment rate is lower than among the native-born in southern Europe, Ireland, the United Kingdom and Oceania (Table 5.1).

Since 2006-07, the share of the long-term jobless among unemployed immigrants has climbed by over 20 percentage points in Spain, Ireland and Iceland – a rise that is, on average, 10 percentage points higher than among the native-born.

An average of one in six inactive immigrants OECD-wide wished to work in 2012, compared to one in seven native-born (Figure 5.11). In the European Union, over one-fifth inactive immigrants were in the same situation. Nearly 3 million economically inactive immigrants in the OECD wanted to work and over 2 million in the European Union. In countries where the overall unemployment picture is grim (southern and Central Europe), a good many inactive immigrants who want to work have grown discouraged, particularly in Italy, Latvia and the Netherlands. In Switzerland and Austria, by contrast, inactivity can be more widely attributed to family commitments (one in six inactive immigrants in Switzerland) or to ill health. The share of inactive immigrants who would like to work is low in Israel, France, Greece and the United States.

Inactivity is more likely to be involuntary among the foreign- than the native-born, except in Iceland and the United Kingdom. On average, slightly more men than women are inactive against their will, though higher proportions of mothers of children under the age of six have been forced into inactivity. In the United Kingdom, Spain, Italy, Germany, and the United States, more native- than foreign-born mothers with young children experience involuntary inactivity (Figure 5.A1.8).

Table 5.1. Long-term unemployment rates among immigrants aged 15-64 in 2006-07 and 2012-13
| Long-term unemployment of the foreign-born population (% of total unemployment) | Differences with the native-born (% points) +: higher than natives: -: Lower than natives
| 2006-07 | 2012-13 | 2006-07 | 2012-13
Australia | 17.9 | 17.0 | +1.4 | -2.2
Austria | 30.0 | 25.4 | +4.4 | +1.3
Belgium | 57.2 | 51.0 | +8.5 | +8.4
Canada | 10.4 | 15.3 | +3.2 | +3.9
Cyprus1,2 | 19.6 | 30.2 | +0.9 | -6.4
Czech Republic | 69.8 | 52.3 | +17.0 | +9.2
Denmark | 20.3 | 32.8 | +2.0 | +7.6
Finland | 31.9 | 25.1 | +8.3 | +4.5
France | 49.3 | 46.5 | +10.0 | +7.6
Germany | 56.7 | 47.1 | -0.1 | +2.7
Greece | 44.2 | 58.5 | -8.7 | -5.9
Hungary | 43.5 | 46.9 | -2.4 | +0.1
Iceland | 8.1 | 29.8 | -0.1 | +10.6
Ireland | 23.3 | 59.0 | -9.7 | -2.8
Israel* | 28.7 | 23.1 | -1.4 | +0.1
Italy | 41.2 | 48.4 | -8.3 | -8.3
Latvia | 29.4 | 57.2 | -2.6 | +7.6
Luxembourg | 29.8 | 30.7 | +1.7 | +1.1
Netherlands | 50.0 | 46.2 | +11.4 | +14.5
New Zealand | 10.4 | 17.7 | -0.8 | -2.4
Norway | .. | 23.3 | .. | +5.9
Portugal | 42.3 | 51.3 | -7.0 | -1.3
Slovenia | 54.8 | 48.7 | +7.9 | -1.0
Spain | 12.9 | 45.8 | -10.4 | -1.8
Sweden | 20.0 | 26.6 | +7.4 | +11.9
Switzerland | 46.3 | 37.5 | +16.2 | +13.1
Turkey | .. | 29.0 | .. | +7.4
United Kingdom | 22.9 | 30.9 | -0.1 | -5.5
United States | 6.6 | 23.9 | +0.2 | +2.8
EU total (28) | 41.3 | 45.1 | -3.7 | -1.2
OECD total (28) | 29.3 | 36.1 | -2.0 | +0.0
StatLink  http://dx.doi.org/10.1787/888933214055

Figure 5.11. Inactive foreign- and native-born who wish to work, by the reason for their inactivity, 2012

Percentage of the inactive working-age population (15-64 year olds)

StatLink  http://dx.doi.org/10.1787/888933212283

Notes and sources are to be found at the end of the chapter.

Data limitations

Employment and unemployment

Labour market outcomes can be measured in two ways: i) from labour force survey data; ii) from administrative data. Generally speaking, all countries have their own “official” definition of employment and unemployment based on the number of people who register – usually as job seekers – with the public employment service. How people are registered and counted varies from country to country and the employment and unemployment rates produced by national statistics systems are seldom comparable.

National labour force surveys, however, use relatively well harmonised definitions of employment and unemployment in line with the recommendations of the International Labour Organization (ILO). Almost all OECD and EU countries carry out labour force surveys on a regular – monthly or quarterly – basis. They offer clear advantages for international comparisons. However, there are two main caveats that should be borne in mind when comparing countries.

First, some countries – e.g. the United States and, up to 2011, Israel – include in their sample only the civilian population. They automatically exclude the armed forces (whether professional or conscripts), regardless of whether they live in barracks or in ordinary dwellings. Second, although all countries theoretically use the ILO definitions, they may interpret them differently, and have actually done so. Differences of interpretation can ultimately modify rates of employment and unemployment slightly and disrupt time series data. Chile, for example, did not start strictly applying ILO definitions of employment and unemployment until 2010, while until 2011 Belgium’s definition of unemployment required people to be out of work for over four weeks. Other criteria, too, can affect to varying degrees published rates and make international or year-on-year comparison more difficult. Such criteria are, for example, population coverage (from 16 years of age instead of 15 in Iceland), reworked survey systems (switched from quarterly to monthly), or changes made to questionnaires (better coverage of people with insecure, short-term job contracts in Germany).

Proper evaluation of the convergence process to native-born outcomes requires longitudinal data, but very few employment surveys use representative samples of immigrants over long periods of time. For instance, the EU’s six waves of quarterly labour force surveys cover no more than one-and-a-half years in total – hardly enough to measure convergence. To make up for the dearth of longitudinal data, convergence between labour market outcomes of the foreign- and native-born is estimated with a pseudo-cohort method from samples in different years of immigrant respondents who declared they arrived the same year. The method involves supposing that the randomly selected samples are samples of population groups with the same characteristics on the grounds that they arrived the same year, which is not necessarily the case, particularly when emigration is selectively biased. Outcomes should consequently be considered with caution.

Risks of labour market exclusion

Involuntary inactivity is especially tricky to estimate and compare on an international scale as some surveys do not include questions on the will to work. While many surveys do ask respondents whether they are looking for work, they often neglect to ask why not, which leads to underestimates of involuntary inactivity and its reasons (e.g. family commitments). This chapter does not therefore consider data for non-European OECD countries.

Notes, sources, and further reading

Note to Israel

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Notes to Cyprus1, 2

1. Note by Turkey:

The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Turkey recognises the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of the United Nations, Turkey shall preserve its position concerning the “Cyprus issue”.

2. Note by all the European Union Member States of the OECD and the European Union:

The Republic of Cyprus is recognised by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus.

Notes to figures and tables

Figures 5.1 and 5.6: Population in Korea aged from 15 to 59 years old.

Figure 5.2: Canadian data include people still in education. Australian data include people aged over 24 who are still in education. The United States includes people over 55 who are still in education and calculates employment rates for the 16-64 age group.

Figures 5.5 and 5.10: For the United States the situation in 2007 of immigrants who arrived between 2002 and 2007 is compared to the situation in 2012 of immigrants who arrived between 2003 and 2007.

Figures 5.7 and 5.8: Population of 15 years old and over is considered in Korea.

Table 5.1: Norway and Turkey are not included in the OECD average in 2012-13.

Korea and Japan determine who is an immigrant on the basis of nationality, not on the basis of country of birth.

Sources to figures and tables

European Union Labour Force Surveys (EU-LFS) 2006-07 and 2012-13.

Australia, Canada, and New Zealand: Labour Force Surveys 2006-07 and 2012-13.

Australian Survey on Education and Work (ASEW) 2007 and 2013 for data that includes levels of educational attainment.

Chile: Encuesta de Caracterización Socioeconómica Nacional (CASEN) 2007 and 2011.

Israel: Labour Force Surveys 2006-07 and 2011.

Japanese Population Survey 2010.

Korea: Foreign Labour Force Survey 2012-13 and Economically Active Population Survey of Korean nationals (EAPS) 2012-13.

Mexico: Encuesta Nacional de Ocupación y Empleo (ENOE) 2007 and 2012.

United States: Current Population Surveys (CPS) 2006-07 and 2012-13.

Further reading

Eurostat (2011), “Migrants in Europe: A Statistical Portrait of the First and Second Generation”, Statistical Books, European Commission, Luxembourg.

Liebig, T. and T. Huddleston (2014), “Labour Market Integration of Immigrants and their Children: Developing, Activating and Using Skills”, International Migration Outlook 2014, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2014-5-en.

OECD (2014a), International Migration Outlook 2014, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2014-en.

OECD (2014b), Jobs for Immigrants (Vol. 4): Labour Market Integration in Italy, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264214712-en.

OECD (2012a), Jobs for Immigrants (Vol. 3): Labour Market Integration in Austria, Norway and Switzerland, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264167537-en.

OECD (2012b), Settling In: OECD Indicators of Immigrant Integration 2012, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264171534-en.

OECD (2008), Jobs for Immigrants (Vol. 2): Labour Market Integration in Belgium, France, the Netherlands and Portugal, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264055605-en.

OECD (2007), Jobs for Immigrants (Vol. 1): Labour Market Integration in Australia, Denmark, Germany and Sweden, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264033603-en.

Annex 5.A1.

Additional tables and figures

Table 5.A1.1. Employment rates of the foreign-born by gender, 2006-07 and 2012-13
Percentages of the working-age population (15-64 years old)
| Total | Men | Women
| Employment rate | Difference (+/-) with native-born persons | Employment rate | Difference (+/-) with native-born persons | Employment rate | Difference (+/-) with native-born persons
| 2006-07 | 2012-13 | 2006-07 | 2012-13 | 2006-07 | 2012-13 | 2006-07 | 2012-13 | 2006-07 | 2012-13 | 2006-07 | 2012-13
Australia | 68.1 | 70.0 | -6.5 | -3.5 | 77.2 | 78.4 | -3.4 | +0.2 | 59.1 | 61.8 | -9.5 | -6.9
Austria | 64.2 | 66.6 | -7.9 | -7.2 | 73.8 | 74.8 | -4.7 | -3.2 | 55.6 | 59.3 | -10.2 | -10.1
Belgium | 50.5 | 52.3 | -12.6 | -11.4 | 60.8 | 60.3 | -8.5 | -7.6 | 40.8 | 44.9 | -16.0 | -14.6
Canada | 69.8 | 69.6 | -4.3 | -3.7 | 76.8 | 75.3 | -0.1 | -0.0 | 63.1 | 64.1 | -8.2 | -7.0
Chile | 64.9 | 68.1 | +8.2 | +11.4 | 78.9 | 79.3 | +6.7 | +8.6 | 54.4 | 59.7 | +12.2 | +15.6
Croatia | 53.0 | 45.1 | -3.9 | -5.5 | 63.7 | 49.0 | +0.6 | -5.6 | 43.0 | 41.4 | -7.6 | -5.1
Cyprus1, 2 | 71.5 | 67.4 | +1.4 | +5.6 | 76.0 | 70.2 | -4.3 | +2.0 | 68.5 | 65.5 | +9.0 | +10.4
Czech Republic | 63.9 | 68.5 | -1.8 | +1.4 | 73.6 | 80.0 | -0.6 | +5.0 | 54.2 | 56.5 | -2.9 | -2.5
Denmark | 65.1 | 62.4 | -13.4 | -11.8 | 71.0 | 65.2 | -10.9 | -11.1 | 59.9 | 59.9 | -15.1 | -12.1
Estonia | 73.2 | 67.5 | +5.3 | -0.3 | 76.4 | 71.3 | +5.0 | +0.8 | 70.8 | 64.7 | +6.1 | -0.5
Finland | 62.2 | 63.6 | -7.9 | -5.8 | 68.5 | 68.9 | -3.3 | -1.4 | 56.2 | 58.6 | -12.1 | -9.9
France | 57.6 | 57.2 | -7.2 | -7.8 | 67.0 | 66.2 | -2.2 | -2.0 | 48.9 | 49.1 | -11.5 | -12.8
Germany | 59.4 | 68.5 | -10.3 | -8.0 | 67.7 | 77.5 | -6.8 | -2.9 | 51.4 | 59.8 | -13.2 | -12.6
Greece | 66.9 | 49.0 | +6.2 | -1.5 | 84.2 | 57.5 | +10.3 | -2.2 | 50.3 | 40.7 | +2.8 | -0.3
Hungary | 62.6 | 67.2 | +5.3 | +9.6 | 73.0 | 76.5 | +9.3 | +13.3 | 53.8 | 59.0 | +2.8 | +6.7
Iceland | 85.0 | 79.5 | -0.2 | -1.2 | 90.3 | 82.6 | +1.5 | +0.1 | 80.0 | 76.6 | -1.3 | -2.3
Ireland | 71.7 | 59.7 | +3.4 | +0.1 | 80.6 | 65.8 | +3.7 | +2.3 | 62.3 | 54.1 | +2.8 | -1.8
Israel* | 66.1 | 70.3 | +9.3 | +11.1 | 69.6 | 72.7 | +8.7 | +10.4 | 63.1 | 68.2 | +10.4 | +12.4
Italy | 65.5 | 59.0 | +7.6 | +3.2 | 82.2 | 70.4 | +12.5 | +5.3 | 50.5 | 49.3 | +4.4 | +2.9
Japan | .. | 65.5 | .. | -4.7 | .. | 77.1 | .. | -2.7 | .. | 56.9 | .. | -3.7
Korea | .. | 69.2 | .. | +9.8 | .. | 82.0 | .. | +11.2 | .. | 53.3 | .. | +4.7
Latvia | 72.2 | 61.6 | +5.5 | -2.7 | 78.3 | 65.7 | +7.7 | +0.2 | 67.2 | 58.4 | +4.4 | -4.7
Lithuania | 70.0 | 66.6 | +6.0 | +3.9 | 75.6 | 69.8 | +8.7 | +6.5 | 64.7 | 64.0 | +3.4 | +1.8
Luxembourg | 70.0 | 71.5 | +10.4 | +11.0 | 79.3 | 79.3 | +11.6 | +13.4 | 60.8 | 63.5 | +9.2 | +8.6
Malta | 56.0 | 61.6 | +1.9 | +1.9 | 75.6 | 75.4 | +2.5 | +1.7 | 38.6 | 48.6 | +4.3 | +3.4
Mexico | 54.4 | 53.6 | -6.6 | -7.4 | 75.1 | 63.8 | -5.7 | -14.8 | 33.8 | 42.3 | -9.9 | -2.5
Netherlands | 63.5 | 62.9 | -13.5 | -13.7 | 72.4 | 70.2 | -10.6 | -10.4 | 55.3 | 56.6 | -15.5 | -16.0
New Zealand | 70.2 | 72.0 | -6.5 | -0.7 | 78.4 | 77.4 | -4.7 | -0.2 | 62.3 | 66.4 | -8.3 | -1.5
Norway | 67.2 | 70.6 | -10.0 | -7.3 | 72.0 | 74.9 | -8.3 | -4.5 | 62.3 | 65.7 | -11.8 | -10.7
Poland | 36.0 | 60.4 | -19.8 | +0.6 | 44.9 | 70.2 | -17.5 | +3.7 | 28.1 | 49.5 | -21.4 | -3.8
Portugal | 72.5 | 64.7 | +5.0 | +3.5 | 78.2 | 66.4 | +4.7 | +2.1 | 67.1 | 63.0 | +5.6 | +5.0
Slovak Republic | 59.9 | 65.2 | -0.2 | +5.4 | 71.4 | 70.8 | +3.8 | +4.3 | 48.7 | 60.1 | -3.8 | +7.1
Slovenia | 67.4 | 62.2 | +0.2 | -1.7 | 72.8 | 71.3 | +0.9 | +4.5 | 61.7 | 52.0 | -0.5 | -8.7
Spain | 70.6 | 51.6 | +5.3 | -4.9 | 80.4 | 54.4 | +3.6 | -7.3 | 61.1 | 49.0 | +7.4 | -2.2
Sweden | 63.4 | 63.1 | -12.5 | -13.6 | 67.7 | 67.6 | -10.2 | -10.3 | 59.5 | 58.9 | -14.4 | -16.7
Switzerland | 73.2 | 76.1 | -6.9 | -5.0 | 82.4 | 83.7 | -3.7 | -1.7 | 64.2 | 68.5 | -9.7 | -8.1
Turkey | .. | 46.5 | .. | -2.8 | .. | 64.0 | .. | -5.4 | .. | 32.9 | .. | +3.7
United Kingdom | 68.5 | 68.0 | -7.8 | -4.5 | 78.0 | 77.8 | -1.4 | +1.1 | 59.1 | 58.8 | -13.9 | -9.4
United States | 71.9 | 68.0 | +1.5 | +2.4 | 83.8 | 79.0 | +8.8 | +9.7 | 59.2 | 57.2 | -6.7 | -4.9
EU total (28) | 63.5 | 61.7 | -2.0 | -3.3 | 73.3 | 69.8 | +1.1 | -0.3 | 54.3 | 54.3 | -4.5 | -5.5
OECD total (31) | 68.0 | 65.7 | +0.9 | +0.3 | 78.5 | 74.8 | +3.7 | +3.1 | 57.5 | 57.0 | -2.2 | -2.1
Notes: Korea and Japan determine who is an immigrant on the basis of nationality, not on the basis of country of birth. Population in Korea aged 15 to 59 years old. Japan, Korea and Turkey are not included in the OECD average for 2012-13.
1, 2: See “Notes, sources, and further reading” section.
* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: European Union Labour Force Surveys (EU-LFS) 2006-07 and 2012-13. Australia, Canada, and New Zealand: Labour Force Surveys 2006-07 and 2012-13. Israel: Labour Force Surveys 2006 and 2011. United States: Current Population Surveys (CPS) 2006-07 and 2012-13. Chile: Encuesta de Caracterización Socioeconómica Nacional (CASEN) 2007 and 2011. Japanese Population Survey 2010. Mexico: Encuesta Nacional de Ocupación y Empleo (ENOE) 2007 and 2012. Korea: Foreign Labour Force Survey 2012-13 and Economically Active Population Survey of Korean nationals (EAPS) 2012-13.

StatLink  http://dx.doi.org/10.1787/888933214060

Figure 5.A1.1. Differences in employment rates between foreign- and native-born 15-64 populations by gender, 2012-13

Percentage points

Notes: Korea and Japan determine who is an immigrant on the basis of nationality, not on the basis of country of birth. Population in Korea aged 15 to 59 years old. “Adjusted difference” refer to the expected difference if immigrants had the same educational attainment and age structure as the native-born.

1, 2: See “Notes, sources, and further reading” section.

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: European Union Labour Force Surveys (EU-LFS) 2012-13. Australia, Canada, and New Zealand: Labour Force Surveys 2012-13. Israel: Labour Force Surveys 2011. United States Current Population Surveys (CPS) 2012-13. Chile: Encuesta de Caracterización Socioeconómica Nacional (CASEN) 2011. Japanese Population Survey 2010. Mexico: Encuesta Nacional de Ocupación y Empleo (ENOE) 2012. Korea: Foreign Labour Force Survey 2012-13 and Economically Active Population Survey of Korean nationals (EAPS) 2012-13.

StatLink  http://dx.doi.org/10.1787/888933212371

Figure 5.A1.2. Change in 15-64 immigrant unemployment rates and in unemployment gap with the native-born between 2006-07 and 2012-13

Percentage points

1, 2: See “Notes, sources, and further reading” section.

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: European Union Labour Force Surveys (EU-LFS) 2006-07 and 2012-13. Australia, Canada, and New Zealand: Labour Force Surveys 2006-07 and 2012-13. Israel: Labour Force Surveys 2006 and 2011. United States: Current Population Surveys (CPS) 2006-07 and 2012-13. Chile: Encuesta de Caracterización Socioeconómica Nacional (CASEN) 2007 and 2011. Mexico: Encuesta Nacional de Ocupación y Empleo (ENOE) 2007 and 2012.

StatLink  http://dx.doi.org/10.1787/888933212385

Figure 5.A1.3. Employment rates of the highly educated foreign-born aged 15-64 years old, whether highest qualifications were obtained abroad or in the host country, not including those still in education, 2012

Notes: Data for the United States include the population still in education.

1, 2: See “Notes, sources, and further reading” section.

Sources: European Union Labour Force Surveys (EU-LFS) 2012. United States: Current Population Survey (CPS) 2012, March 2012 Supplement.

StatLink  http://dx.doi.org/10.1787/888933212399

Figure 5.A1.4. Employment rates of 15-64 immigrants (recent and total), 2012-13

Differences in percentage points with the native-born population

Notes: Canada includes only recent immigrants who have obtained permanent residence status. In the United States, recent immigrants are those who arrived after 2008 (less than approximately four years of residence). In the other countries, recent immigrants are those with less than five years of residence.

1, 2: See “Notes, sources, and further reading” section.

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: European Union Labour Force Surveys (EU-LFS) 2012-13. Australia, Canada, and New Zealand: Labour Force Surveys 2012-13. Israel: Labour Force Surveys 2011. United States: Current Population Surveys (CPS) 2012-13.

StatLink  http://dx.doi.org/10.1787/888933212402

Figure 5.A1.5. Change in employment rates between 2007 and 2012 of immigrants who arrived between 2003 and 2007, by educational attainment levels, not including those still in education

Percentage points (persons aged 15-64)

Notes: Data for the United States compare the situation in 2007 of immigrants who arrived between 2002 and 2007 to the situation in 2012 of those who arrived between 2003 and 2007. They include the over-24s who are still in education.

1, 2: See “Notes, sources, and further reading” section.

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: European Union Labour Force Surveys (EU-LFS) 2007 and 2012. United States: Current Population Surveys (CPS) 2007 and 2012. Australian Survey of Education and Work (ASEW) 2007 and 2013. Israel: Labour Force Surveys 2007 and 2011.

StatLink  http://dx.doi.org/10.1787/888933212415

Figure 5.A1.6. Unemployment rates of immigrants (recent and total), 2012-13

Difference in percentage points with the native-born population (persons aged 15-64)

Notes: Recent immigrants in Canada are those with a permanent residence status.

In the United States, recent immigrants are those who arrived after 2008 (less than approximately four years residence).

1, 2: See “Notes, sources, and further reading” section.

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: European Union Labour Force Surveys (EU-LFS) 2012-13. Australia, Canada, and New Zealand: Labour Force Surveys 2012-13. Israel: Labour Force Surveys 2011. United States: Current Population Surveys (CPS) 2012-13.

StatLink  http://dx.doi.org/10.1787/888933212423

Figure 5.A1.7. Change in unemployment rates between 2007 and 2012 of immigrants who arrived between 2003 and 2007, by educational attainment levels

Percentage points (persons aged 15-64)

Note: Data for the United States compare the situation in 2007 of immigrants who arrived between 2002 and 2007 to the situation in 2012 of those who arrived between 2003 and 2007. They include the over-24s who are still in education.

1, 2: See “Notes, sources, and further reading” section.

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: European Union Labour Force Surveys (EU-LFS) 2007 and 2012. United States: Current Population Surveys (CPS) 2007 and 2012. Australian Survey of Education and Work (ASEW) 2007 and 2013. Canada: Labour Force Surveys 2007 and 2013). Israel: Labour Force Surveys 2007 and 2011.

StatLink  http://dx.doi.org/10.1787/888933212430

Figure 5.A1.8. Percentages of inactive women with a child under 6 and wishing to work by reason for inactivity, foreign- and native-born populations, 2012

Percentage of the inactive working-age population (15-64 years old)

Notes: Only children living in the household are considered. Data for the United States include only the children of the person of reference living in the household.

1, 2: See “Notes, sources, and further reading” section.

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Source: European Union Labour Force Surveys (EU-LFS) 2012. Israel: Labour Force Surveys 2011. United States: Current Population Surveys (CPS) 2012.

StatLink  http://dx.doi.org/10.1787/888933212443

Table 5.A1.2. Unemployment rates of the foreign-born by gender, 2006-07 and 2012-13
Percentage of the economically active population (15-64 years old)
| Total | Men | Women
| Unemployment rate | Difference (+/-) with native-born persons | Unemployment rate | Difference (+/-) with native-born persons | Unemployment rate | Difference (+/-) with native-born persons
| 2006-07 | 2012-13 | 2006-07 | 2012-13 | 2006-07 | 2012-13 | 2006-07 | 2012-13 | 2006-07 | 2012-13 | 2006-07 | 2012-13
Australia | 5.0 | 5.7 | +0.6 | +0.2 | 4.6 | 5.5 | +0.4 | -0.1 | 5.6 | 6.0 | +0.9 | +0.7
Austria | 9.4 | 8.8 | +5.7 | +5.0 | 9.1 | 9.2 | +5.9 | +5.4 | 9.7 | 8.3 | +5.5 | +4.5
Belgium | 16.8 | 17.1 | +10.1 | +10.7 | 15.8 | 17.9 | +9.9 | +11.5 | 18.3 | 16.0 | +10.5 | +9.6
Canada | 7.1 | 8.4 | +1.1 | +1.5 | 6.6 | 8.2 | +0.2 | +0.7 | 7.6 | 8.6 | +2.2 | +2.4
Chile | 5.4 | 5.9 | -2.3 | -2.2 | 2.5 | 3.9 | -3.7 | -2.8 | 8.4 | 7.7 | -1.5 | -2.2
Croatia | 12.8 | 21.8 | +2.4 | +5.4 | 11.3 | 24.3 | +2.3 | +7.7 | 14.8 | 18.9 | +2.7 | +2.6
Cyprus1, 2 | 5.7 | 14.9 | +1.7 | +1.1 | 6.0 | 17.9 | +2.6 | +4.0 | 5.5 | 12.7 | +0.6 | -0.9
Czech Republic | 10.2 | 8.6 | +4.0 | +1.6 | 8.0 | 7.3 | +3.0 | +1.3 | 13.1 | 10.4 | +5.4 | +2.2
Denmark | 7.7 | 13.4 | +4.1 | +6.8 | 7.8 | 12.8 | +4.7 | +6.1 | 7.6 | 14.0 | +3.5 | +7.5
Estonia | 6.8 | 12.0 | +1.6 | +2.7 | 7.9 | 13.1 | +2.2 | +3.2 | 5.8 | 11.1 | +1.1 | +2.5
Finland | 15.1 | 14.5 | +8.0 | +6.8 | 13.2 | 14.5 | +6.4 | +6.0 | 17.1 | 14.6 | +9.7 | +7.6
France | 14.0 | 15.9 | +6.2 | +6.9 | 12.7 | 15.7 | +5.6 | +6.6 | 15.5 | 16.3 | +7.1 | +7.2
Germany | 15.5 | 8.5 | +7.0 | +3.6 | 15.9 | 8.7 | +7.4 | +3.6 | 15.0 | 8.2 | +6.3 | +3.6
Greece | 9.0 | 35.7 | +0.3 | +10.9 | 5.1 | 35.7 | -0.5 | +14.2 | 14.5 | 35.7 | +1.3 | +6.5
Hungary | 5.7 | 9.5 | -1.8 | -1.2 | 3.4 | 8.5 | -3.9 | -2.3 | 8.2 | 10.5 | +0.4 | +0.1
Iceland | 2.8 | 9.1 | +0.2 | +3.7 | 2.5 | 9.1 | +0.1 | +3.3 | 3.1 | 9.1 | +0.4 | +4.0
Ireland | 6.3 | 16.4 | +2.1 | +2.8 | 6.4 | 17.9 | +1.9 | +1.4 | 6.2 | 14.6 | +2.4 | +4.6
Israel* | 6.6 | 5.1 | -1.9 | -1.0 | 6.1 | 5.5 | -1.6 | -0.3 | 7.0 | 4.6 | -2.2 | -1.6
Italy | 8.2 | 15.3 | +1.8 | +4.3 | 5.5 | 14.2 | +0.2 | +3.8 | 11.9 | 16.7 | +3.8 | +4.8
Japan | .. | 8.3 | .. | +1.9 | .. | 8.9 | .. | +1.5 | .. | 7.8 | .. | +2.6
Korea | .. | 4.1 | .. | +0.9 | .. | 3.2 | .. | -0.1 | .. | 5.7 | .. | +2.8
Latvia | 6.3 | 15.9 | -0.2 | +2.5 | 5.0 | 15.8 | -2.3 | +1.3 | 7.6 | 16.0 | +1.8 | +3.6
Lithuania | 7.1 | 12.3 | +2.1 | -0.5 | 6.3 | 11.5 | +1.2 | -3.0 | 7.9 | 13.1 | +3.1 | +1.9
Luxembourg | 5.5 | 6.9 | +2.1 | +3.0 | 4.5 | 5.9 | +1.7 | +1.9 | 6.9 | 8.2 | +2.6 | +4.3
Malta | 7.8 | 9.6 | +1.2 | +3.2 | 7.0 | 10.3 | +1.0 | +4.3 | 9.2 | 8.4 | +1.2 | +1.6
Mexico | 6.2 | 7.4 | +2.4 | +2.3 | 4.1 | 8.0 | +0.5 | +2.9 | 10.7 | 6.4 | +6.5 | +1.3
Netherlands | 7.8 | 11.6 | +4.8 | +6.3 | 7.4 | 11.8 | +4.8 | +6.3 | 8.3 | 11.4 | +4.9 | +6.4
New Zealand | 4.5 | 7.2 | +0.9 | +0.2 | 3.8 | 6.6 | +0.3 | +0.0 | 5.3 | 7.8 | +1.5 | +0.4
Norway | 7.6 | 7.7 | +5.1 | +5.2 | 8.4 | 7.6 | +5.9 | +4.8 | 6.7 | 7.7 | +4.2 | +5.6
Poland | 8.2 | 9.8 | -3.7 | -0.5 | 8.6 | 4.7 | -2.5 | -5.0 | 7.5 | 16.9 | -5.3 | +5.8
Portugal | 9.7 | 20.6 | +1.5 | +4.3 | 7.7 | 21.3 | +0.8 | +4.9 | 11.7 | 20.0 | +2.1 | +3.7
Slovak Republic | 10.7 | 11.1 | -1.6 | -3.0 | 8.9 | 12.7 | -2.2 | -1.1 | 13.0 | 9.3 | -0.7 | -5.3
Slovenia | 6.4 | 13.2 | +1.0 | +3.9 | 4.8 | 9.7 | +0.3 | +0.7 | 8.4 | 18.1 | +1.8 | +8.5
Spain | 11.5 | 35.3 | +3.6 | +11.6 | 9.4 | 37.0 | +3.5 | +14.0 | 14.1 | 33.6 | +3.4 | +9.0
Sweden | 12.7 | 16.2 | +7.0 | +9.7 | 12.6 | 16.9 | +7.1 | +10.3 | 12.7 | 15.4 | +6.8 | +9.1
Switzerland | 7.5 | 7.4 | +4.8 | +4.3 | 6.3 | 6.8 | +4.1 | +3.6 | 9.0 | 8.1 | +5.8 | +5.0
Turkey | .. | 11.1 | .. | +2.5 | .. | 10.5 | .. | +2.6 | .. | 12.0 | .. | +1.8
United Kingdom | 7.6 | 9.0 | +2.6 | +1.4 | 7.2 | 8.1 | +1.6 | -0.2 | 8.2 | 10.1 | +3.7 | +3.2
United States | 4.2 | 7.5 | -0.7 | -0.5 | 3.9 | 7.0 | -1.1 | -1.4 | 4.7 | 8.3 | +0.0 | +0.7
EU total (28) | 11.5 | 15.9 | +4.2 | +5.8 | 10.6 | 15.7 | +3.8 | +5.6 | 12.7 | 16.0 | +4.6 | +5.9
OECD total (31) | 7.5 | 11.1 | +1.5 | +2.6 | 6.8 | 10.7 | +1.1 | +2.1 | 8.5 | 11.6 | +2.0 | +3.1
Notes: Korea and Japan determine who is an immigrant on the basis of nationality, not on the basis of country of birth. Population in Korea aged 15 to 59 years old. Japan, Korea, and Turkey are not included in the OECD average.
1, 2: See “Notes, sources, and further reading” section.
* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Source: European Union Labour Force Surveys (EU-LFS) 2006-07 and 2012-13. United States: Current Population Surveys (CPS) 2006-07 and 2012-13. Australia, Canada, and New Zealand: Labour Force Surveys 2006-07 and 2012-13. Israel: Labour Force Surveys 2006-07 and 2011. Chile: Encuesta de Caracterización Socioeconómica Nacional (CASEN) 2006 and 2011. Mexico: Encuesta Nacional de Ocupación y Empleo (ENOE) 2007 and 2012. Japanese Population Survey 2010. Korea: Foreign Labour Force Survey 2012-13 and Economically Active Population Survey of Korean nationals (EAPS) 2012-13.

StatLink  http://dx.doi.org/10.1787/888933214073

Chapter 6.

Quality of immigrants’ jobs

While access to employment is a key indicator of integration, the kind of job yields a more comprehensive picture of the nature of an immigrant’s place in the labour market. Indicators include job security, working hours, matches or mismatches between workers’ qualifications and skills and those required by the job. The incidence of self-employment and proportions of immigrants working in the public services sector are also relevant indicators. When it comes to immigrants, job quality indicators should be gauged against their experience (estimated by individuals’ ages), their levels of educational attainment, and the length of time they have resided in the host country.

This chapter looks first at job contracts (temporary versus unlimited duration – Indicator 6.1), working hours (Indicator 6.2), job skills (Indicator 6.1), and the match between the level of qualifications required and those held by the worker (Indicator 6.4). It then considers the shares of self-employment (Indicator 6.5) and the integration of immigrant workers in the public services sector (Indicator 6.6). For further discussion of some of the issues that the indicators raise, see the section entitled “Data limitations” at the end of the chapter.

Key findings

An average of 35% of highly educated immigrants in employment are overqualified OECD-wide, compared to one native-born in four in 2012-13.

The standard of education systems across countries of origin is variable, as is the adequacy of arrangements for recognising foreign credentials. The result is overqualification rates among foreign-educated immigrants to the European Union that are double those of their peers who hold qualifications from the host country. In Switzerland, Germany and the United States, tertiary-educated immigrant workers trained in the host country are not more likely to be overqualified than their native-born peers.

The longer immigrants reside in a country the better the quality of their jobs generally is. For example, on average, across the OECD in 2012-13, immigrants who had lived in the host country for ten years were no more likely to work with temporary contracts than their native counterparts. Such was the trend in the settlement countries, Portugal, Italy, and the United Kingdom.

Nevertheless, even when they are long-term residents, the foreign-born are worse-off than their native-born peers when it comes to overqualification and working hours. Across the OECD, even after ten years in an OECD host country, nearly one-third of immigrants with a tertiary degree are overqualified for their job – by 6 percentage points more than the native-born. The gap is even wider in the European Union, where 30% of such foreign-born are overqualified, against less than 20% of the native-born.

Across OECD countries, the share of immigrants working with a temporary contract evolved little between 2006-07 and 2012-13. In Spain, however, and – to a lesser degree – in Portugal, job losses chiefly affected temporary positions and their share in total immigrant employment fell by over 15 percentage points between 2006-07 and 2012-13.

Conversely, the effect of the crisis on immigrants’ job quality has translated into a fall in the number of working hours, particularly among women. In 2012-13, immigrant women were more likely than their native-born peers to be working part-time, except in the settlement countries, the Netherlands, and Switzerland. In all OECD countries, however, the share of women who work part-time but want to work longer hours is higher among immigrants than women born in the host country. That proportion grew by 6 percentage points among immigrant women in the wake of the economic crisis that unfolded throughout the OECD. In the worst-hit countries – Greece, Ireland, and Spain – the increase was as high as 20 to 30 percentage points.

Bar recent immigration destinations, immigrants are a little more likely than the native-born to be self-employed, especially if they have resided for at least ten years in the host country. However, foreign-born self-employed are more often sole proprietors of small businesses.

The integration of immigrant workers in the public services sector varies widely. The longer immigrants reside in host country, the higher their rates of employment in the sector become, eventually becoming comparable with those of the native-born after ten years’ residence in Scandinavia and the United Kingdom.

Section 6.1. Types of contracts

Background

Indicator

In European countries temporary work denotes any kind of work governed by a fixed-term contract, including apprenticeships, “temp” agency work, and remunerated training courses. It is the opposite of work governed by contracts of unlimited duration. In Australia, temporary work does not incorporate paid leave and everywhere it excludes the self-employed. Because no survey yields comparable information in the United States or New Zealand, this section does not consider those two countries.

In addition to not being as well paid as permanent positions, temporary jobs often do not entitle workers to paid holidays, sick leave, unemployment insurance, other non-wage benefits, and training to the same degree as permanent positions. And employment protection legislation often does not require the same standards from employers. By its very nature temporary work often breeds a sense of insecurity.

Coverage

People aged 15-64 who are in employment, not including the self-employed or those still in education.

Across the OECD in 2012-13, 13% of immigrants who were in work had a temporary contract, against some 11% of native-born workers. In the European Union, too, the percentage was higher among immigrants (16% versus 11%). And in most countries, both male and female immigrants were more likely to be hired under short-term contracts than their native-born peers. In Spain and Cyprus,1, 2 one immigrant in three had a short-term contract – a gap with the native-born of at least 15 percentage points. Temporary work is also widespread among immigrants in southern Europe, Sweden and Finland. However, in half of all countries, temporary work accounts for no more than 10% of immigrant employment, a proportion that shrinks as residence lengthens (Figure 6.1).

It follows, therefore, that recently arrived immigrants are more likely to work temporary jobs, which they see as a way into the labour market. Indeed, in countries like the settlement destinations, Portugal, Italy, and the United Kingdom, the incidence of temporary work is no higher among immigrants with ten years residence to their name than among their peers born in the host country. The gap with the native-born also narrows considerably as the duration of residence lengthens in Cyprus.1, 2

Temporary work is more widespread among women in most countries, with the exception of southern Europe, where the trend is attributable to the fact that many work in personal care services, so generally have contracts of unlimited duration. Temporary work is more frequent among low-educated immigrants than among those who are highly qualified in most countries (Figures 6.2 and 6.3). Exceptions, though, are European countries where temporary work is less common (Austria, Luxembourg, Switzerland), together with Germany where roughly 15% of highly educated immigrants have short-term contracts.

In most countries, temporary work does not account for much more of a share of employment than in 2006-07. Two stand-out exceptions are Spain and, to a lesser degree, Portugal, where half of all employed immigrants (most of whom had arrived by 2005) had fixed-term contracts in 2006-07. That share dropped to 35% in 2012-13, partly because job losses primarily affected short-term positions (Figure 6.A1.1).

Figure 6.1. Workers with a temporary contract, 2012-13

Percentages of total employment, persons aged 15-64 not in education

StatLink  http://dx.doi.org/10.1787/888933212451

Figure 6.2. Low-educated workers with a temporary contract, 2012-13

Percentages of low-educated workers, aged 15-64 not in education

StatLink  http://dx.doi.org/10.1787/888933212501

Figure 6.3. Highly educated workers with a temporary contract, 2012-13

Percentages of highly educated workers, aged 15-64 not in education

StatLink  http://dx.doi.org/10.1787/888933212516

Notes and sources are to be found at the end of the chapter.

Section 6.2. Working hours

Background

Indicator

There is no such thing as a universally agreed definition of part-time work. The International Labour Organisation describes part-time work as “regular employment in which working time is substantially less than normal”. Where the dividing line lies between part-time and “normal” – i.e. full-time – varies from country to country. In this section, part-time work denotes a working week of less than 30 hours. This section also considers data on the incidence of involuntary part-time work – in other words, proportions of part-time employees who would like to work longer hours.

The number of working hours gives an indication of how well the labour market uses human capital. The term “part-time” suggest in itself that only part of labour potential is used. It is also associated with lower wages, fewer training or career prospects, and less job security than full-time work.

Coverage

People aged 15-64 who are in employment, not including the self-employed or those still in education.

Across the OECD, an average of around 19% of immigrants held a part-time job in 2012-13 – 9% of men and 30% of women. In the European Union, the proportion was one in four, with men accounting for 11% and women 40% – respectively 5 and 10 percentage points higher than native-born male and female rates. Outside Europe, the relative numbers of immigrants working part-time were no higher than among the native-born, and sometimes slightly lower. Part-time work is most widespread among immigrant women in the Netherlands, Germany, and Switzerland, where it is also high among native-born. In southern Europe, however, it is less common, as it is in North America (Figure 6.4).

There is generally little difference between foreign- and native-born women when it comes to the incidence of part-time work, save in the settlement countries and European countries where part-time female employment is particularly widespread. Native-born women in the Netherlands and Switzerland, for example, are more likely to work part-time than their immigrant peers, while in Germany it is the other way round. However, immigrant women across the OECD are more likely than their peers born in the host country to state that they would like to work longer hours – one in three versus one in four.

Although part-time work’s share of employment has increased only a little since 2006-07 among foreign- and native-born, the share of immigrant women OECD-wide wishing to work longer hours since the onset of the crisis has grown by 6 percentage points (Figure 6.5) and the share of men by over 10. And even though only 9% of the latter hold part-time positions, over half of them currently wish to work more.

In the countries worst hit by the crisis, there has been a rise in the share of part-time employees among working immigrant women and those wanting to work longer hours. In Greece and Spain, for example, over three-quarters of part-time female immigrant workers fitted that profile in 2012-13 (Figure 6.4), doubtless because many of them wanted to make up for the loss of a salary in the household. In Ireland, involuntary part-time work was something marginal in 2006-07. Six years later it affects over one-third of immigrant women with part-time jobs.

Figure 6.4. Part-time workers by intention to work longer hours, 2012-13

Percentages of total employment, persons aged 15-64 and not in education

StatLink  http://dx.doi.org/10.1787/888933212529

Figure 6.5. Evolution of part-time and involuntary part-time work between 2006-07 and 2012-13, 15-64 year-old women not in education

StatLink  http://dx.doi.org/10.1787/888933212530

Notes and sources are to be found at the end of the chapter.

Section 6.3. Job skills

Background

Indicator

The International Standard Classification of Occupations (ISCO) drawn up by the International Labour Organization (ILO) describes the tasks and duties undertaken in some 400 jobs divided into families of jobs. ISCO enables jobs to be grouped by the levels of skills and qualifications required.

This section divides jobs into three main skill levels: highly skilled – senior managers, professionals, technicians and associate professionals (ISCO 1-3); low-skilled – elementary occupations (ISCO 9); medium-skilled – all other (ISCO 4-8).

The three skills levels draw on respondents’ self-reported ratings of their jobs and may therefore be over- or underestimated. Moreover, the three levels do not indicate whether job incumbents actually have the skills that their occupation requires (see Indicator 6.4, “Overqualification”), whether they have been trained accordingly, or whether they might be qualified for another job.

Coverage

People in employment aged between 15 and 64 years old.

Across the OECD and the European Union, immigrants held an average of one-quarter of low-skilled jobs in 2012-13. However, in some countries the levels were much higher – 75% in Luxembourg, over 60% in Switzerland and Cyprus1, 2 and more than 40% in Greece and Austria. In fact, in most countries, immigrants are largely overrepresented in low-skilled occupations (Figure 6.A1.2).

Over one-third work in low-skilled jobs in the countries of recent immigration in southern Europe (save Malta and Portugal). And in Greece, they are eight times more likely than the native-born to do so. Similarly, in Iceland, Italy, Sweden, and Switzerland, immigrants who work are some four times more likely to be in low-skilled position.

With the exception of settlement countries (Australia, Canada, Israel and New Zealand) and Ireland, far more immigrant women than men have menial jobs. Throughout the OECD area, the rates are around one-quarter of foreign women in work, compared to 14% of men. The native-born gender gap is not so wide (Figure 6.6).

In some settlement countries and others, like Hungary, Poland, Turkey and Malta where they account for a small share of total employment, immigrants are overrepresented in both highly skilled and low-skilled occupations. Otherwise, though, they are widely under-represented in highly skilled jobs (Table 6.A1.1), particularly in southern Europe, where most have no or low qualifications and are generally hired to fill menial positions. Relatively low proportions of immigrants in highly skilled occupations may also be observed in some of the countries – e.g. Austria, Germany, Belgium and France – that used to be destinations for large inflows of low-skilled migrants in the past.

Nevertheless, the share of immigrants in highly skilled jobs has increased since 2006-07 (Figure 6.7), even if it has risen at a faster pace among the native-born in many countries including the United Kingdom, Sweden, and France. Those outcomes are the result of a combination of factors: the general rise in the levels of skills that jobs require, the characteristics of the new immigrants, and how the overqualification rates of the foreign- and native-born have evolved.

Figure 6.6. Low-skilled employment among 15-64 foreign- and native-born workers by gender, 2012-13

Percentages of total employment

StatLink  http://dx.doi.org/10.1787/888933212548

Figure 6.7. Evolution of the share of highly skilled employment by place of birth, 2006-07 and 2012-13

Percentage points

StatLink  http://dx.doi.org/10.1787/888933212558

Notes and sources are to be found at the end of the chapter.

Section 6.4. Overqualification

Background

Indicator

In this section, overqualification denotes situations where workers’ levels of formal education are higher than those required by the jobs they fill. The overqualification rate estimated here is the share of people with tertiary-level qualifications who work in a job that is classified as low- or medium-skilled by the International Standard Classification of Occupations (ISCO, see Indicator 6.3). The level of educational attainment is taken from the international standard Classification of Education (ISCED) whose Levels 5 and 6 describe two standards of tertiary education.

Coverage

People aged 15-64 who are in employment and are highly qualified (ISCED Levels 5 and 6), not including military occupations (ISCO 0), where data on skills levels are not referenced.

Across the OECD and the EU, over one-third of immigrants who hold a tertiary degree are overqualified for their jobs, compared to one in four native-born. Rates are as high as 50% in recent immigration destinations like Greece, Italy and Spain where inflows have come in response to the demand for low- and medium-skilled labour over the decade. In those countries, overqualification is the lot of twice as many foreign- as native-born workers as it is in Germany and the Nordic countries. Yet among the few exceptions are the United States, New Zealand, and Switzerland (Figure 6.8). Immigrant women struggle more than men with overqualification, being 3 percentage points more likely to be overqualified in the OECD area and 6.5 in the EU. The gaps are even wider in southern European countries, though not between native-born men and women. As for the Nordic countries, overqualification is a problem primarily for men and, especially, refugees.

Rates of overqualification among the foreign- and native-born have, on average, risen very little since the crisis. In most recent immigration countries – like Greece, there was even a downward trend among immigrants, while rates climbed among native-born workers. The only exception of note was Italy where immigrant overqualification rose by over 10 percentage points and by 4 among the native-born. In the United Kingdom, Estonia and Iceland, there was a rise in the numbers of immigrants accepting jobs that underemployed their skills, while overqualification remained unchanged in the rest of the population (Figure 6.9).

In practically all countries, the scale of overqualification is lower among immigrants with longer length of residence, though not in Austria, Germany or the United States, or in countries where there is little overqualification anyway. The rate of overqualification among immigrants with ten years of residence is, on average, 4 points lower than among recent arrivals. Duration of stay has a particularly pronounced effect in Portugal and in northern European countries like Sweden and Iceland. Still, even after living in the host country for ten years or more, immigrants with a tertiary education degree are dogged by overqualification rates that are some 6 points greater than among their native peers (Figure 6.A1.3).

Highly educated immigrants who graduated abroad are more likely to have qualifications in excess of job requirements. EU-wide, overqualification affects 42% of such immigrants (Figure 6.A1.4), double the rate of those trained in the host country. In Italy, Portugal and Sweden, where the foreign-educated immigrants predominantly come from low-income countries, differences between the two groups are even higher. While immigrants with a host-country qualification run less risk of being overqualified, they are nevertheless a little more likely to be so than their counterparts born in the host country. That trend is not, however, observed in Switzerland, Germany (where domestic qualifications are highly prized on the labour market) or the United States, where overqualification rates are high among both the foreign- and native-born.

Figure 6.8. Overqualification rates among 15-64 year-olds who are not in education, by place of birth and gender, 2012-13

Percentages of the highly educated employed persons

StatLink  http://dx.doi.org/10.1787/888933212568

Figure 6.9. Evolution of the overqualification rates of 15-64 highly educated workers who are not in education, by place of birth, 2006-07 and 2012-13

Percentage points

StatLink  http://dx.doi.org/10.1787/888933212570

Notes and sources are to be found at the end of the chapter.

Section 6.5. Self-employment

Background

Indicator

The incidence of self-employment in the population that has work makes it possible to gauge its contribution to job creation. When workers create their own jobs by employing themselves they join the labour market and may also create jobs for others. However, self-employment – of which there are different types and survival rates – is not always a byword for successful participation in the labour market, but can also be a way of avoiding being left on its sidelines.

The self-employed are people who work in their own firms or create their own business, sometimes hiring employees. Self-employment includes business people with their own firms, the professions, artisans, traders, and many other freelance activities. Because of the specific nature of self-employment in agriculture, this section does not consider that sector. Any calculation of the share of self-employed workers in the whole employed population excludes the agricultural sector. To estimate the size of the part that self-employment plays in total employment, this indicator also proposes data relating to firms’ sizes. These data are not available for non-European countries.

Coverage

People aged between 15 and 64 who are in employment, excluding the agricultural sector.

Across the OECD and the European Union, an average of 12% of immigrants are self-employed. The proportion is slightly higher than among the native-born in most countries and considerably higher in central Europe, Canada and the United Kingdom. And in Poland and the Czech Republic, more than one immigrant in four is self-employed – a rate that is two to three times higher than among their domestically born peers (Figure 6.10). However, in countries where self-employment is widespread, particularly in southern Europe, immigrants are not more likely than the native-born to be self-employed. In Greece and Italy, they are actually half as likely.

Although self-employment is widespread in many immigrants’ countries of origin (particularly low-income ones), it seldom affords them a way into the host country’s labour market. They may have difficulty adapting to the business community and self-employment standards in the host country. Rules and regulations are many and varied from country to country, foreigners’ right to create their own businesses may be restricted, and the amount of start-up capital required may be too much for recent arrivals. Immigrants need time to adapt.

Taking only those who have resided for at least ten years in the host country, it emerges that 13% of immigrant workers are self-employed on average in the OECD and the European Union – 3 percentage points more than recent arrivals (Figure 6.11). Numbers have grown remarkably in recent immigrant countries like Ireland and Spain as well as in New Zealand, where long-settled immigrants now account for proportionally more self-employed workers than the native-born. In Germany, however, recent immigrants are more likely to set up their own businesses than their settled peers.

With the exception of those living in Hungary, most self-employed immigrants – three out of four across the European Union – have no employees. And only 1 in 25 employ over ten people. In the Czech Republic, the United Kingdom and Italy the foreign-born are particularly unlikely to be employers (Figure 6.12). Altogether, immigrant-owned businesses with employees account for just 3.5% of immigrants in work, slightly less than the share observed for natives (Figure 6.A1.5). Everywhere there are fewer foreign- than native-owned businesses with more than ten employees.

Figure 6.10. Foreign- and native-born self-employed workers aged 15-64 years old, 2012-13

Percentages of total employment (not including the agricultural sector)

StatLink  http://dx.doi.org/10.1787/888933212468

Figure 6.11. Foreign-born self-employed workers aged 15-64 by duration of stay, 2012-13

Percentages of total employment (not including the agricultural sector)

StatLink  http://dx.doi.org/10.1787/888933212474

Figure 6.12. Foreign-born self-employed workers aged 15-64 by size of enterprise, 2012

Total = 100 (not including the agricultural sector)

StatLink  http://dx.doi.org/10.1787/888933212489

Notes and sources are to be found at the end of the chapter.

Section 6.6. Employment in the public services sector

Background

Indicator

The indicator that this section considers is the share of immigrants employed in the public services sector, among all immigrant employment. The public services sector encompasses public administration, healthcare, the social services, and education.

Immigrant recruitment in the public sector is firm evidence of the host country’s commitment to integration. It gives the immigrant community greater visibility, showing the private sector the way and improving the way the host society perceives them in the long term. What’s more, appointments to key jobs – teaching for example – give immigrant adults the chance to be role models for children of immigrants. However, jobs in the public administration are typically not entry jobs into the labour market for newly arrived immigrants. In addition, foreigners tend to be barred from holding some public sector positions. Such restrictions further skew comparisons between the foreign- and native-born. For all those reasons, this section considers only long-settled immigrants, i.e. those who have resided in the country for at least ten years. In most OECD and EU countries, they are eligible for naturalisation and can, in theory, apply for all vacancies in the public services sector.

Coverage

People aged 15-64 years old, not including the self-employed.

Across the OECD and the European Union, one in four long-settled immigrants works in the public service sector, against a native-born share of 30%. Public services sector employees account for widely varying proportions of immigrant workers, both in cross-country comparisons and compared to natives (Figure 6.13).

In southern Europe (save in Malta), the public service sector employs few immigrants but around one in three of the native-born. In Scandinavia and the United Kingdom, on the other hand, it makes a significant contribution to the labour market integration of foreign-born. Between 20% and 30% of recent immigrants in those two countries work in public service, while long-settled immigrants are as likely as their native peers to do so. In most of the other EU15 countries – particularly Luxembourg, Austria and Germany – and in the United States, long-settled immigrants are considerably underrepresented in public services. It is also worth noting that in Portugal and Malta, the share of immigrant public employees is much higher for those with longer duration of residence.

Figure 6.13. People aged 15-64 employed in the public services sector by place of birth and duration of stay, 2012-13

Percentages of total employment

StatLink  http://dx.doi.org/10.1787/888933212496

Notes and sources are to be found at the end of the chapter.

Data limitations

This chapter addresses only some qualitative aspects of immigrants’ jobs – indicators of job security, use of human capital, employment in the public sector, and self-employment. Due to the lack of reliable data available, salary levels are not discussed. Nor, because of the shortage of internationally comparable data, does the chapter look at a number of other facets of the labour market integration of immigrants, e.g. the overall working environment, worker autonomy in carrying out duties, interaction with co-workers and management, and occupational health and safety.

Overqualification

The overqualification indicator considered here does not incorporate average wage levels by type of job (wage downgrades). It considers only matches between levels of educational attainment and job categories. Matches are, however, somewhat arbitrary, as the exact conditions required by a given job are not examined and can vary from one country to another. Moreover, the available data do not allow levels of educational attainment to be measured or factor in qualifications obtained outside educational establishments or through working experience. A last constraint is that part of the differences observed may result from some immigrants’ low proficiency in the host-country language, notably among the foreign-trained immigrants, which seems to prevent them from fully transfer their skills to the host country.

Self-employment

Although self-employment can be a way of not being sidelined by the labour market, it is no byword for successful integration in the world of work. Comparisons with the native-born population can be distorted by the fact that, in certain countries, setting up a company is dependent on the number of years the immigrant entrepreneur has spent in the host country or whether he or she has a long-term residence permit.

Data on self-employed workers would gain from being supplemented by official data on entrepreneurship, which would yield the number of jobs that set-ups create – a useful estimate of self-employment’s overall impact on the labour market. Similarly, government agencies have information on the survival rates of newly created firms after a certain number of years – particularly useful for estimating how many companies eventually take their place in the economy over the longer-term. However, company registers seldom provide data on entrepreneurs’ nationality, and even more rarely on their country of birth. . So no information is available for comparing the creation of new business from country to country.

Immigrant employment in the public services sector

The term “public service” refers to very different things from one country to another. In some, recruitment rules and practices bar part of the immigrant populations from working as civil servants, particularly by demanding that they should have the host country’s nationality. Although that is the case in some parts of the civil service, such as the military, requirements are different in other areas of public service. This chapter considers public service from a broad perspective that includes governmental departments, healthcare, the social services, and education. In many countries some services are managed by the private sector, but nonetheless serve the public interest and are partly state-funded. Given that working in some public services requires host country citizenship, comparisons with the native-born population should be treated with caution.

Notes, sources, and further reading

Note to Israel

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Notes to Cyprus1, 2

1. Note by Turkey:

The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Turkey recognises the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of the United Nations, Turkey shall preserve its position concerning the “Cyprus issue”.

2. Note by all the European Union Member States of the OECD and the European Union:

The Republic of Cyprus is recognised by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus.

Notes to figures and tables

Indicators 6.2,  6.3 and 6.4: The United States includes people over 25 who are still in education.

Figure 6.4: The ranking of the countries is according to the part-time share for foreign-born women.

Figure 6.13: Australia and New Zealand are not included in the OECD average.

Averages factor in rates that cannot be published individually because samples are too small.

Sources to figures and tables

European Union Labour Force Surveys (EU-LFS) 2006-07 and 2012-13.

Australia, Canada, and New Zealand: Labour Force Surveys 2006-07 and 2012-13. Australian Survey on Education and Work (ASEW) 2007 and 2013 for data that includes levels of educational attainment; Australian Forms of Employment 2012 for temporary workers

Israel: Labour Force Surveys 2006-07 and 2011.

United States: Current Population Surveys (CPS) 2006-07 and 2012-13

Further reading

Damas de Matos, Ana (2014), “Immigrant Skills, their Measurement, Use and Return: A Literature Review”, Matching Economic Migration with Labour Market Needs, OECD/European Union, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264216501-8-en.

Dumont, J.C. and O. Monso (2007), “Matching Educational Background and Employment: A Challenge for Immigrants In Host Countries”, International Migration Outlook 2007, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2007-4-en.

Eurostat (2011), “Migrants in Europe: A Statistical Portrait of the First and Second Generation”, Statistical Books, European Commission, Luxembourg.

Liebig, T. and T. Huddleston (2014), “Labour Market Integration of Immigrants and their Children: Developing, Activating and Using Skills”, International Migration Outlook 2014, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2014-5-en.

OECD (2014a), Jobs for Immigrants (Vol.4): Labour Market Integration in Italy, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264214712-en.

OECD (2014b), International Migration Outlook 2014, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2014-en.

OECD (2014c), “How Good is Your Job? Measuring and Assessing Job Quality”, OECD Employment Outlook 2014, OECD Publishing, Paris, http://dx.doi.org/10.1787/empl_outlook-2014-6-en.

OECD (2012), Jobs for Immigrants (Vol. 3): Labour Market Integration in Austria, Norway and Switzerland, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264167537-en.

OECD (2010a), Open for Business: Migrant Entrepreneurship in OECD Countries, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264095830-en.

OECD (2010b), Equal Opportunities? The Labour Market Integration of the Children of Immigrants, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264086395-en.

OECD (2008), Jobs for Immigrants (Vol. 2): Labour Market Integration in Belgium, France, the Netherlands and Portugal, OECD Publishing, Paris, http://dx.doi.org/ 10.1787/9789264055605-en.

OECD (2007), Jobs for Immigrants (Vol. 1): Labour Market Integration in Australia, Denmark, Germany and Sweden, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264033603-en.

Annex 6.A1.

Additional tables and figures

Figure 6.A1.1. Change in the shares of foreign- and native-born workers on temporary contracts between 2006-07 and 2012-13

Percentage points

Note: Not including self-employed workers and people still in education.

1, 2: See “Notes, sources, and further reading” section.

Sources: European Union Labour Force Surveys (EU-LFS) 2006-07 and 2012-13. Canada, and New Zealand: Labour Force Surveys 2006-07 and 2012-13. Australian Forms of Employment 2006 and 2012.

StatLink  http://dx.doi.org/10.1787/888933212583

Table 6.A1.1. Foreign-born workers aged 15-64, by skill level of job and duration of stay, 2012-13
| Distribution in % | Difference with the native-born
| Foreign-born | Foreign-born (10 years of residence or more) | Foreign-born | Foreign-born (10 years of residence or more)
| Low skilled | Medium skilled | High skilled | Low skilled | Medium skilled | High skilled | Low skilled | Medium skilled | High skilled | Low skilled | Medium skilled | High skilled
Australia | 7.7 | 42.4 | 49.9 | 7.0 | 42.3 | 50.6 | 1 | -5 | 4 | 0 | -5 | 5
Austria | 21.3 | 51.4 | 27.3 | 20.9 | 53.9 | 25.2 | 15 | -1 | -14 | 15 | 2 | -16
Belgium | 20.3 | 44.0 | 35.7 | 17.3 | 45.2 | 37.4 | 12 | -1 | -10 | 9 | 0 | -9
Canada | 8.1 | 46.7 | 45.2 | 7.5 | 45.4 | 47.1 | 1 | -3 | 2 | 1 | -4 | 4
Croatia | 12.2 | 54.7 | 33.1 | 12.2 | 54.9 | 32.9 | 5 | -4 | -1 | 5 | -4 | -1
Cyprus1, 2 | 39.1 | 41.4 | 19.5 | 14.7 | 51.6 | 33.7 | 30 | -8 | -22 | 5 | 2 | -7
Czech Republic | 8.2 | 55.7 | 36.1 | 8.2 | 55.6 | 36.2 | 3 | -2 | -1 | 3 | -2 | -1
Denmark | 21.6 | 40.3 | 38.2 | 17.6 | 47.6 | 34.8 | 14 | -2 | -12 | 10 | 5 | -15
Estonia | 14.4 | 53.3 | 32.3 | 15.0 | 54.3 | 30.8 | 7 | 4 | -10 | 7 | 5 | -12
Finland | 14.0 | 48.6 | 37.4 | 8.9 | 48.9 | 42.3 | 9 | -1 | -8 | 3 | -1 | -3
France | 18.4 | 45.2 | 36.4 | 16.9 | 45.9 | 37.2 | 10 | 0 | -10 | 8 | 1 | -9
Germany | 19.8 | 51.4 | 28.7 | 19.6 | 53.1 | 27.3 | 14 | 4 | -18 | 13 | 6 | -19
Greece | 33.4 | 57.4 | 9.2 | 29.6 | 59.6 | 10.9 | 29 | -4 | -25 | 25 | -2 | -24
Hungary | 9.3 | 49.6 | 41.1 | 7.9 | 48.3 | 43.8 | 0 | -6 | 6 | -2 | -7 | 9
Iceland | 20.1 | 49.2 | 30.7 | 15.3 | 41.7 | 43.0 | 16 | 8 | -23 | 11 | 0 | -11
Ireland | 15.4 | 46.2 | 38.4 | 8.1 | 43.1 | 48.8 | 8 | -4 | -4 | 1 | -7 | 6
Israel* | 36.5 | 51.6 | 12.0 | 38.7 | 50.4 | 10.9 | -10 | 3 | 7 | -8 | 2 | 5
Italy | 30.9 | 57.5 | 11.7 | 27.8 | 57.6 | 14.6 | 23 | 4 | -27 | 20 | 4 | -24
Latvia | 17.3 | 48.2 | 34.5 | 17.2 | 48.8 | 34.1 | 5 | 0 | -4 | 4 | 0 | -5
Lithuania | 9.6 | 51.3 | 39.2 | 9.7 | 51.7 | 38.6 | 2 | 2 | -4 | 2 | 2 | -4
Luxembourg | 11.6 | 28.9 | 59.5 | 13.9 | 34.7 | 51.4 | 7 | -9 | 2 | 10 | -3 | -6
Malta | 7.1 | 44.0 | 48.9 | 6.0 | 46.4 | 47.6 | -3 | -7 | 10 | -4 | -4 | 9
Netherlands | 14.1 | 45.2 | 40.7 | 12.9 | 45.7 | 41.4 | 8 | 2 | -10 | 7 | 2 | -9
New Zealand | 9.3 | 40.0 | 50.7 | 9.0 | 39.7 | 51.2 | 0 | -7 | 7 | -1 | -7 | 7
Norway | 9.1 | 54.7 | 36.1 | 5.1 | 49.3 | 45.5 | 7 | 11 | -18 | 3 | 6 | -8
Poland | 4.9 | 37.8 | 57.3 | 5.2 | 38.4 | 56.4 | -2 | -20 | 22 | -2 | -19 | 21
Portugal | 16.2 | 47.9 | 35.9 | 11.6 | 47.7 | 40.6 | 4 | -8 | 4 | 0 | -8 | 8
Slovak Republic | 8.6 | 52.3 | 39.2 | 9.8 | 52.8 | 37.4 | 1 | -8 | 7 | 2 | -7 | 5
Slovenia | 14.8 | 59.4 | 25.8 | 14.6 | 58.4 | 27.0 | 8 | 10 | -18 | 8 | 9 | -17
Spain | 31.9 | 51.6 | 16.6 | 25.5 | 54.3 | 20.2 | 22 | -3 | -19 | 16 | -1 | -15
Sweden | 11.9 | 49.6 | 38.5 | 8.7 | 50.4 | 40.9 | 9 | 4 | -12 | 5 | 4 | -10
Switzerland | 9.0 | 45.5 | 45.5 | 9.6 | 51.8 | 38.6 | 7 | 2 | -9 | 7 | 8 | -15
Turkey | 11.7 | 55.1 | 33.3 | 9.9 | 55.7 | 34.4 | -3 | -11 | 14 | -5 | -10 | 15
United Kingdom | 13.8 | 39.0 | 47.2 | 8.3 | 38.4 | 53.2 | 6 | -4 | -2 | 0 | -5 | 4
EU total (28) | 20.9 | 48.6 | 30.5 | 18.1 | 50.0 | 31.9 | 13 | -2 | -11 | 10 | -1 | -10
OECD total (29) | 17.8 | 47.8 | 34.5 | 16.2 | 48.8 | 35.0 | 9 | -3 | -6 | 8 | -2 | -5
1, 2: See “Sources, notes, and further reading” section.
* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
Sources: European Union Labour Force Surveys (EU-LFS) 2012-13. Canada, and New Zealand: Labour Force Surveys 2012-13. Israel: Labour Force Surveys 2011. Australian Survey on Education and Work (ASEW) 2013.
StatLink  http://dx.doi.org/10.1787/888933214082

Figure 6.A1.2. Foreign-born workers aged 15-64 who have low-skilled jobs, 2012-13

Percentages of employment

1, 2: See “Sources, notes, and further reading” section.

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: European Union Labour Force Surveys (EU-LFS) 2012-13. Canada, and New Zealand: Labour Force Surveys 2012-13. Israel: Labour Force Survey 2011. Australian Survey on Education and Work (ASEW) 2013.

StatLink  http://dx.doi.org/10.1787/888933212597

Figure 6.A1.3. Overqualification rates among the 15-64 year-old native- and foreign-born who are not in education, by duration of stay, 2012-13

Percentages of highly educated employed

Notes: The United States includes people over 25 who are still in education.

1, 2: See “Sources, notes, and further reading” section.

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: European Union Labour Force Surveys (EU-LFS) 2012-13. Canada, and New Zealand: Labour Force Surveys 2012-13. Israel: Labour Force Surveys 2011. United States: Current Population Surveys (CPS) 2012-13. Australian Survey on Education and Work (ASEW) 2013.

StatLink  http://dx.doi.org/10.1787/888933212605

Figure 6.A1.4. Overqualification rates among the native- and foreign-born 15-64 year-olds who are not in education, whether or not they obtained their qualification in the host country, 2011-12

Percentage of highly educated employed

Notes: The country in which a qualification was obtained is derived from information based on the year it was obtained, the immigrant’s arrival in the host country, and the length of the study programme. Data for the United States include the population still in education.

1, 2: See “Sources, notes, and further reading” section.

Sources: European Union Labour Force Surveys (EU-LFS) 2011-12. United States: Current Population Surveys (CPS) 2012, March 2012 Supplement.

StatLink  http://dx.doi.org/10.1787/888933212614

Figure 6.A1.5. Foreign- and native-born self-employed workers aged 15-64, 2012, not including those with no employees

Percentage of total employment (not including the agricultural sector)

1, 2: See “Sources, notes, and further reading” section.

Source: European Union Labour Force Surveys (EU-LFS) 2012.

StatLink  http://dx.doi.org/10.1787/888933212622

Chapter 7.

Cognitive skills and training of immigrant adults

Adults’ cognitive skills have a strong bearing on their career paths. They also shape how immigrants find their place in society and give their offspring a better chance of a high-quality education. Although individuals’ skills are obviously decisive determinants in their economic and social integration, they can in themselves be considered indicators not of how well immigrants actually integrate or fare in the host society but of their ability to do so. Many received their initial training and education and built at least part of their skills as adults in their country of origin before they migrated. Against that background, the host country often plays only a limited role in educating the foreign-trained people.

Host countries can, however, play a telling part in ensuring lifelong training and education. It can round off immigrants’ initial education and training so that their skills and qualifications meet the requirements of the labour market more closely. Immigrants, including those who are highly qualified, may struggle to free up their skills potential if they are hampered by a poor command of the host country’s language or a lack of understanding of how its labour market works.

This chapter begins by considering and comparing the levels of education attained by foreign- and native-born adults (Indicator 7.1). It then goes on to assess literacy in the host country’s language as the OECD’s Programme of International Assessment of Adult Competencies (PIAAC) measures it (Indicator 7.2). Finally, the chapter examines access to adult education and training (Indicator 7.3) with a special focus on work-related training (Indicator 7.4). For further discussion of some of the issues that the indicators raise, see the section entitled “Data limitations” at the end of the chapter.

Key findings

In 2012-13, 1 in 3 immigrants of working age in the OECD area and 1 in 4 in the European Union held a tertiary education degree. In numbers that is respectively 28 and 9.2 million people, although those with no more than a low level of educational attainment are proportionately more numerous in the European Union than in the OECD – one in three versus one in four.

Comparable shares of immigrants – around two-thirds – residing in the OECD and EU areas obtained their highest qualifications abroad.

Immigrants have markedly lower levels of literacy (in the host-country language) than people born in the host country, regardless of level of education. Gaps are widest among the poorly educated, particularly in Scandinavian countries, the Netherlands and Belgium.

Immigrants’ literacy skills in the host-country language are closely related with their familiarity with this language. Across the OECD and the European Union, more than 70% of foreign-language immigrants (who did not learn the host-country language in their childhood) have no more than basic literacy skills (at best equivalent to PIAAC Level 2), among whom more than a half have inadequate literacy skills (at best equivalent to PIAAC Level 1).

Immigrants are less likely than the native-born to attend education and training courses. The gap tends to widen as the level of education rises.

Migrants (whether employed or not) are less likely than host-country-born adults to attend employment-oriented training courses, while economically active immigrants are less likely to take part in on-the-job training.

Immigrants state more often than natives that they need training, but do not take up courses. Reasons given are chiefly that they do not meet the standards required or that they cannot afford it.

Section 7.1. Level of educational attainment

Background

Indicator

This section uses the International Standard Classification of Education (ISCED) to categorise levels of qualification. People falling into ISCED groups 0-2 are described as having no or low education. They have no more than a lower-secondary level of education. Within those groups, a distinction is made between people who have gone no further than primary education (ISCED 0 and 1). People with ISCED 3-4 are described as having a medium level of education. They completed upper secondary school or post-secondary non-tertiary studies. As for those who have tertiary education degrees, they belong to ISCED 5-6 and completed the first stage of tertiary education at least.

Coverage

People not in education who were aged 15-64 years old at the time of the survey.

OECD-wide, immigrants of working age are overrepresented at both ends of the educational attainment scale. In 2012-13, an average of a little over 1 in 4, or 25 million, immigrants of working age (against 24% of the native born) were poorly educated. At the opposite end of the spectrum, about 1 in 3, or 28 million people, compared to 29% of domestically born natives, had a tertiary level degree. As for the European Union, similar proportions – 26% – of the foreign- and native-born had tertiary education qualifications. Only those with low education levels were overrepresented. They numbered 12.7 million – or 36% of immigrants – and outnumbered their highly qualified peers – of whom there were 9.2 million, or 26.1% of immigrants.

The largest shares of highly educated immigrants tend to be found in the settlement countries that practice selective migration policies or, when it comes to the European Union, in countries where inflows have a large European component. In 2012-13, for example, Canada, Ireland, Luxembourg, Israel and Australia were the five OECD countries where the highly educated accounted for largest share of immigrants – over 45% and markedly more than proportions of highly educated native-born (Figure 7.1 and Table 7.A1.1). Conversely, immigrants are considerably overrepresented among those with no or low education in southern Europe and in countries which used to take in high numbers of low-skilled workers during the post-World War II reconstruction of Europe (Belgium, France and Germany). Half of Italy’s and Spain’s immigrants have no or low education qualifications.

In most countries, the numbers of highly educated foreign- and native-born have grown faster than those of people with no or low education since 2006-07 (Figure 7.2 and Table 7.A1.2). There are exceptions, though. They are the countries, like those of southern Europe, where immigration is made up chiefly of low-skilled workers and a few others where immigration accounts for a fraction of the total population (e.g. Mexico, Chile and Finland). Luxembourg, the United Kingdom, Australia, Canada, and Switzerland are among the major immigration destinations which have seen the steepest rises in numbers of highly educated immigrants. The reasons may be effective immigration policies designed to attract more highly educated individuals and the career prospects that some of those countries offer immigrants.

An OECD-wide average of around three immigrants in five obtained their highest degree abroad (Table 7.A1.3). In southern Europe, Austria, and Luxembourg, the proportions exceed 70%, doubtless because of the relatively high proportions of labour migrants who have been trained and educated abroad. Poorly educated immigrants are more likely than their highly educated counterparts to have been schooled in their country of origin.

Figure 7.1. Shares of the low- and highly educated among native- and fi foreign-born 15-64 year-olds who are not in education, 2012-13

Percentages of the native- and foreign-born

StatLink  http://dx.doi.org/10.1787/888933212631

Figure 7.2. Changes in the shares of highly educated 15-64 year-olds who are not in education between 2006-07 and 2012-13, by place of birth and duration of stay

StatLink  http://dx.doi.org/10.1787/888933212689

Notes and sources are to be found at the end of the chapter.

Section 7.2. Adult literacy

Background

Indicator

The adult literacy indicator draws on the tests in the OECD’s 2012 Programme for International Assessment of Adult Competencies (PIAAC). It scores literacy skills on a six-level scale according to respondents’ ability to find information in written material of varying complexity. Those who score less than Level 1 (176 points) are able to read only short passages on familiar topics. The skills required to reach Level 1 (from 176 to 226 points) are knowledge of basic vocabulary to process meaning at sentence level and the ability to read written text. Level 2 requires higher cognitive skills, particularly the ability to connect information at different points in a written text. For information on higher literacy skills levels, see OECD (2013). This section classifies basic skills as Level 1 or less.

The PIAAC survey asks respondents which language or languages (no more than two) they learned as children and still speak. By comparing that information with the language in which the literacy test is conducted, this section separates the results of immigrants who speak a foreign language (i.e. those who did not learn the test language in childhood) and those whose native tongue is the same as the majority language in the host country. It is nevertheless important to stress that this language-related information does not measure proficiency. A foreign-language immigrant might be able speak the host country language very well. Conversely, the proficiency of an immigrant whose native language is also the one spoken in the host country might be limited by poor cognitive skills or a low level of educational attainment.

The OECD and averages are simple averages of the results shown in the different tables or figures.

Coverage

Adults aged between 16 and 64 years old at the time of the survey.

In all the countries covered by the survey, immigrants’ literacy skills lag behind those of people born in the host country. Their average scores are 248 points (Level 2) in 2012, compared to 276 points (Level 3) among the native-born (Figure 7.3). Immigrants’ average score in Italy, France, Spain, and Sweden are only just Level 2. Gaps with the native-born are especially pronounced in the Scandinavian countries and the Netherlands. In all the OECD countries covered, nearly one-third of immigrants have only the most basic literacy skills (equivalent to Level 1 or below) compared to less than 15% of the native-born (Figure 7.4). In Italy, France, Spain, Sweden, and the United States, the proportion is in excess of two in five.

With the exception of the United States, however, immigrants have better average results in English-speaking countries, Cyprus,1, 2 and Estonia. In Ireland and Australia, immigrants’ average scores are comparable to those of native-born nationals (Figure 7.3). In Australia, more than half boast scores that are equivalent to or higher than 3, while the share of those who score Level 4 and above – 16% – is high compared to other countries and similar to the share for the native-born. In Canada and the United Kingdom, immigrants are overrepresented at both ends of the literacy scale, with over one-quarter lacking basic skills (Figure 7.4).

Figure 7.3. Mean literacy scores of 16-64 year-olds by place of birth, 2012

StatLink  http://dx.doi.org/10.1787/888933212699

Figure 7.4. Distribution of foreign- and native-born aged 16-64 year-olds by level of literacy scores, 2012

StatLink  http://dx.doi.org/10.1787/888933212701

Notes and sources are to be found at the end of the chapter.

Literacy skills tend to increase with educational attainment, although competencies among immigrants are more mixed than those of the native-born for a given level of education. The average literacy score in the OECD countries among immigrants who complete upper secondary school (medium education level) is comparable to that of the native-born with no or low education (Figure 7.5). Low educated immigrants have much lower literacy skills than their native-born peers, with the lowest scores coming in North America, Sweden, Finland, France, and Belgium.

Particularly in host countries whose language is little spoken beyond the national borders, a tertiary education degree is no guarantee of proficiency in literacy. In the Scandinavian countries, highly educated immigrants’ literacy scores are at about the same level as those of the poorly educated native-born. The trend can probably be attributed to a command of language that is not proficient enough to allow immigrants to give full expression to their potential.

Familiarity with the host country’s majority language is a decisive element in immigrants’ literacy skills. In most countries in 2012 – save the Netherlands, France, Germany and Estonia – the literacy scores of immigrants whose language of origin (learnt in childhood and still spoken) was the same as the host country’s majority language were close to those of the native-born (Figure 7.6). Positive selection among immigrants is probably behind average results that are better than those of the native-born among English-speaking immigrants in Australia and Ireland and German-speaking immigrants in Austria. OECD-wide, the gap between foreign-language-speaking immigrants and host country natives is 36  points, while just 7 points separate the foreign-born who have learned the host country language in their childhood from the native-born. In Spain, Italy, France, and Belgium, foreign-language immigrants’ average literacy scores are between 218 and 223 points (Level 1). In France and Belgium – and in Sweden, the Netherlands, and Finland, too – their literacy scores lag 50 points behind those of the native-born (Table 7.A1.4).

Controlling for age, gender, and levels of educational attainment narrows the gap with people born in the host country only if their language of origin is that spoken in the host country. For foreign-language immigrants, the disparities may be ascribed to other factors not observed (Figure 7.A1.1). Mastering the host country’s language certainly appears a key determinant. In southern Europe, France, Belgium, and the United States, about a half of foreign-language immigrants have very basic levels of literacy (equivalent at best to Level 1). And even in countries where the average scores of foreign-language immigrants are higher, at least 25% fail to meet the basic literacy requirements (Figure 7.A1.2).

Some foreign-language immigrants need time to master the host country’s language. Indeed, their literacy skills are significantly higher for those with longer duration of stay, as can be observed in the Scandinavian countries (Figure 7.7). The outcomes for Indicator 7.3 (access to adult education and training) may therefore suggest that the relatively weak outcomes of recent immigrants are closely linked to poor command of language, but may subsequently be improved by learning the language as part of an integration programme for example. For a given age structure, gender, and level of educational attainment, the longer the duration of stay, the better the outcomes. That trend is bucked, however, in the English-speaking countries where recent immigrants’ outcomes stand up well in international comparisons.

Figure 7.5. Mean literacy scores of 16-64 year-olds immigrants and native-born people by level of education, 2012

StatLink  http://dx.doi.org/10.1787/888933212712

Figure 7.6. Mean literacy scores of 16-64 year-olds immigrants by native language, 2012

Difference with the native-born scores in points

StatLink  http://dx.doi.org/10.1787/888933212725

Figure 7.7. Foreign-language immigrants’ mean literacy scores by duration of stay, 16-64 years old, 2012

Difference in points between immigrants who arrived within the previous 5 years and those with more than 5 years of residence, controlled for age, sex and educational attainment

StatLink  http://dx.doi.org/10.1787/888933212736

Notes and sources are to be found at the end of the chapter.

Section 7.3. Access to adult education and training

Background

Indicator

Data are drawn from the OECD’s 2012 PIAAC survey (see Indicator 7.2 for further details). They refer to all types of education and training schemes followed in the previous 12 months – education programmes, remote learning platforms, on-the-job training, seminars, working groups, and private lessons. This section also looks at respondents’ reasons for not taking up training opportunities despite expressing a need. Reasons are split into three categories: i) Education or financial: “Don’t meet the standard for following a course” or “The programme is too expensive”; ii) Employment: “Lack of support from employer” or “Too busy at work”; iii) Family: “The course is scheduled at an inconvenient time” or “Don’t have time because of family commitments”. Respondents give other reasons occasionally, e.g. ”Something came up that stopped me from attending”, or do not give an explanation.

The OECD and EU averages are simple averages of the outcomes displayed in the tables and figures.

Coverage

Adults aged 25-64 years old at the time of the survey. People aged 16-24 years old were excluded from the sample in order to limit the number of students in initial education.

In OECD and EU countries in 2012, some 50% of foreign-born adults had attended a training programme in the 12 months prior to the survey. Overall, immigrants are less likely to train than native-born, a trend that is more pronounced among women (Figure 7.8). There are wide disparities from one country to another which vary more, in fact, than the gaps between the foreign- and native-born within a country. Finland, Norway and Australia stand out for high attendance rates among immigrants that are equivalent to, and sometimes higher than, among natives.

Recent immigrants are almost everywhere more likely to participate in training schemes than their peers who have been residents for over five years. Rates among recently arrived women are lower than among men, particularly in Germany, Austria and the United States. This may reveal difficulties for family members to participate in training programmes since more women migrate for purposes of family reunification (Table 7.A1.6).

Across countries, participation rates increase with levels of educational attainment, possibly because the most highly qualified people are more likely to have a job that requires continuous training. The same trend can be observed among immigrants. Apart from the Nordic countries and the United Kingdom, only one in three immigrants with the most basic literacy skills (no higher than Level 1) accesses training programmes, even though they are the very people who would need them the most. There is only limited scope for comparison with native-born peers, because there are very few of them with such low levels of literacy skills. Immigrants with good literacy skills (Level 2 and higher) generally attend less training programmes than their native peers, although rates are comparable in Nordic European countries, North America, Australia, and the United Kingdom (Table 7.A1.7).

In 2012 more than one immigrant in four OECD-wide took part in no training activity in the previous 12 months, even though they expressed they would have needed to. That proportion is only a very slight overrepresentation of immigrants among people who claim to need training but fail to take it up. However, like the native-born, it is likely to grow as their competencies improve (Figure 7.9 and Table 7.A1.8). The main reasons that immigrants give for letting training needs go unmet are, apart from in the United States, more often related to education – ”don’t have the standard to keep up with a learning programme” – or to money – ”can’t afford it” (Figure 7.10). This holds true, regardless of literacy level.

Figure 7.8. Participation in education and training over the last 12 months among 25-64 year-olds, by place of birth and gender, 2012

StatLink  http://dx.doi.org/10.1787/888933212740

Figure 7.9. People aged 25-64 who report unmet training needs, by place of birth, 2012

StatLink  http://dx.doi.org/10.1787/888933212753

Figure 7.10. Main reasons advanced by immigrants for unmet training needs, 2012

Difference in percentage points with native-born 25-64 year-olds

StatLink  http://dx.doi.org/10.1787/888933212642

Notes and sources are to be found at the end of the chapter.

Section 7.4. Work-related training for adults

Background

Indicator

This section considers data drawn from the OECD’s 2012 PIAAC survey (see Indicator 7.2 for further details.) The data relate to the most relevant education or training programme (see Indicator 7.3) followed in the previous 12 months and, primarily, whether it was work-oriented. Training may be work-related because co-workers or superiors organise it during working hours to help employees perform their duties more effectively, or because its content focuses on a specific job and is designed to increase trainees’ chances of finding work or securing a better job. If the purpose is to find work or a better job, anyone may be concerned, regardless of their employment status (in work, unemployed, or inactive) when training begins.

This section also discusses whether the training course was perceived to be of benefit to attendees in their current job or the job they held at the time. That information was gathered only from respondents who reported having worked, even part-time, during the course.

The OECD and EU averages are simple averages of all the outcomes shown in each table and figure.

Coverage

Adults aged 25-64 years old at the time of the survey. All 16-24 year-old were excluded from the sample in order to limit the number of students in initial education.

In OECD and EU countries, immigrants are less likely to participate in work-oriented training than the native-born. In 2012, an average of 85% of training schemes attended by host-country natives in the previous 12 months were work-related, while only 78% of those were taken up by immigrants were. Employment-based programmes accounted for even less of the training that immigrant women followed – 25% of the courses they attended had nothing to do with jobs, compared to 20% among their native-born counterparts. These shares are similar EU-wide. Around one-third of the training courses that immigrant women attended in France, and the Netherlands had no connection with jobs – a far higher share than among native females (Figure 7.11). Nevertheless, in Cyprus,1, 2 North America, Australia, Austria and Sweden, foreign- and native-born women relatively participated in job-related training in the same proportions.

Immigrants who report working, even part-time, during their training programme, or who are still employed, access less on-the-job training (organised by employers or co-workers) than their host-country peers (Figure 7.12). Foreign- and native-born women are more likely to benefit from on-the-job training than their male counterparts, although not in Germany, Ireland, or southern Europe. Less than 10% of female immigrant employees benefitted from on-the-job training in Italy, and less than 25% in Spain. In both countries their rates of access to training were over 15 percentage points lower than those of their native counterparts. The reason might be the high concentrations of women in sectors that offer little prospect of training, such as personal care services.

In countries where male immigrants enjoy equal access to job-related training, they may still come up against difficulties getting into on-the-job schemes once they find employment – which is what happens in Germany, Belgium, Canada and the United Kingdom. In Ireland, by contrast, immigrant men have no more trouble than their native peers in being admitted to employment-related or on-the-job training courses.

A final point is that, unlike their host-country peers, most immigrants who have worked, even discontinuously, in the previous 12 months state that the training course they attended was beneficial for them in the job they held at the time or on completion of the course, or in the job they were working at the time of the survey. In Denmark, the United Kingdom, the United States, and Australia, over 60% of these immigrants state that it was very useful, compared to one native-born in five (Figure 7.13).

Figure 7.11. Share of immigrants who participated in job-related training, by gender, 2012

Difference in percentage points with the 25-64 year-old native-born who participated in education or training over the last 12 months

StatLink  http://dx.doi.org/10.1787/888933212651

Figure 7.12. Immigrants who participated in on-the-job training, by gender, 2012

Difference in percentage points with the 25-64 year-old native-born persons employed (even partially) during the training

StatLink  http://dx.doi.org/10.1787/888933212661

Figure 7.13. Persons who reported that a training course was very useful, by place of birth, 2012

Percentage of 25-64 persons who were employed at any time while participating in job-related training over the last 12 months

StatLink  http://dx.doi.org/10.1787/888933212678

Notes and sources are to be found at the end of the chapter.

Data limitations

Adult levels of educational attainment and competencies

The most widely used measure of competencies is the education level that students attain on completion of their studies, as it indicates the content of the initial education programme. It is extensively used by all OECD and EU countries and enables international comparisons to be made. The International Standard Classification of Education (ISCED, 1997) breaks education systems down into seven distinct levels. Each level, however, covers a wide range of different competencies. One reason is that qualifications, which ISCED considers of equivalent levels, are in fact of varying standard when it comes to content. Another reason is that individuals’ competencies develop differently throughout their lives, shaped particularly by their family and work environments.

The issue of the equivalence between foreign and domestic qualification is an additional obstacle for assessing levels of competency through the education levels that students attain on completion of their studies. Moreover, although immigrants bring with them a certain standard of education, their competencies may not be transferable to the host country if, for example, their command of its language is inadequate or they have not yet developed a network of contacts.

Another measure of adults’ competencies is through the evaluation of their cognitive skills – literacy, numeracy, and problem-solving in technology-rich environments. Their scores yield indications of their ability to perform certain tasks, like extracting information from a written document. It would also be useful to test non-cognitive competencies like the ability to interact and communicate with others or to persevere when performing different tasks.

Levels of literacy among the foreign- and native-born as determined by the OECD’s Programme for International Assessment of Adult Competencies

The OECD’s Programme for International Assessment of Adult Competencies (PIAAC) is a unique source of data on the competencies of adults (aged 16-64 years old) in literacy, numeracy, and problem-solving in technology-rich environment. PIAAC tests were carried out in 22 OECD countries, Cyprus,1, 2 and the Russian Federation. Depending on their computer literacy, respondents either used laptop computers or filled in printed forms.

Those with very low literacy levels did not complete the tests and took an additional “reading component” test to assess their basic competencies. It concerned knowledge of vocabulary, the ability to process meaning at the level of the sentence, and fluency in reading passages of text. Seven per cent could not fill in the basic questionnaire because they had linguistic or learning difficulties. Most of the immigrants among them doubtless struggled because of their poor command of the host country’s written language. However, it was impossible to judge from the survey whether their difficulties sprang from their cognitive skills or command of the language. It follows therefore that all the respondents who were able to take the test had some knowledge, albeit rudimentary, of the test’s written language (the most widely spoken host country language).

Although PIAAC is a unique tool, it has its limitations. The chief drawback is that since the tests are conducted in the host-country language, it is not possible to clearly separate language skills from “general” literacy skills. Further, in all countries (apart from Canada, the United Kingdom, Estonia, France, Korea and Poland), it drew on a sample of around 5 000 people. There are also limitations to the migrant sample base. It did not include those who lived in collective accommodation or those who were undocumented.

The migrant sample was very small in Japan, Korea, Poland and the Slovak Republic, all countries where immigrants account for less than 2.5% of the total population. Therefore, these four countries were excluded from analysis. Furthermore, data from the Czech Republic, Finland, Belgium, Italy and the Netherlands, did not lend themselves to fine-tuned analysis. Because samples were too small and relevant variables in short supply, countries do not all always appear in all the chapter’s tables and figures.

Belgian data relate only to Flanders, and British data to England and Northern Ireland. It is impossible to tell from Australian data in which country migrants obtained their highest qualification. As for Germany, it does not distinguish between EU and third-country migrants.

Data from PIAAC have not been aggregated to produce weighted averages for all countries. The averages shown are therefore only simple averages of all the results shown in the different tables and figures.

Notes, sources, and further reading

Notes to tables and figures

Korea and Japan determine who is an immigrant on the basis of nationality, not on the basis of country of birth.

Figure 7.1: Japan is not included in OECD average. Canadian and New Zealand data include people still in education. The United States includes people over 55 who are still in education and calculates the share of low- and highly educated for the 16-64 age group.

Figure 7.2: Canadian and New Zealand data include people still in education. The United States includes people over 25 who are still in education.

Note to Israel

* Information on data concerning Israel: http://dx.doi.org/10.1787/888932315602.

Notes to Cyprus1, 2

1. Note by Turkey:

The information in this document with reference to “Cyprus” relates to the southern part of the island. There is no single authority representing both Turkish and Greek Cypriot people on the island. Turkey recognises the Turkish Republic of North Cyprus (TRNC). Until a lasting and equitable solution is found within the context of the United Nations, Turkey shall preserve its position on the “Cyprus issue”.

2. Note by all the European Union Member States of the OECD and the European Union:

The Republic of Cyprus is recognised by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus.

Sources to tables and figures

Indicator 7.1: European Union Labour Force Survey (EU-LFS) 2006-07 and 2012-13. Australian Survey of Education and Work (ASEW) 2007 and 2013. Canada, and New Zealand: Labour Force Surveys 2006-07 and 2012-13. Israel: Labour Force Survey 2006 and 2011. Unites States: Current Population Surveys (CPS) 2006-07 and 2012-13. Chile: Encuesta de Caracterización Socioeconómica Nacional (CASEN) 2011. Japan: Population Survey 2010. Mexico: Encuesta Nacional de Ocupación y Empleo (ENOE) 2012. Korea: Foreign Labour Force Survey 2012-13 and the Economically Active Population Survey (EAPS) 2012-13 for nationals.

Indicators 7.2,  7.3 and 7.4: OECD Programme for International Assessment of Adult Competencies (PIAAC) 2012.

Further reading

Bonfanti, S. and T. Xenogiani (2014), “Migrants’ Skills: Use, Mismatch and Labour Market Outcomes – A First Exploration of the International Survey of Adult Skills (PIAAC)”, Matching Economic Migration with Labour Market Needs, OECD/EU Publishing, Paris, http://dx.doi.org/10.1787/9789264216501-11-en.

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”, Matching Economic Migration with Labour Market Needs, OECD/EU Publishing, Paris, http://dx.doi.org/10.1787/9789264216501-9-en.

Eurostat (2011), “Migrants in Europe: A Statistical Portrait of the First and Second Generation”, Statistical Books, European Commission, Luxembourg.

Liebig, T. and T. Huddleston (2014), “Labour Market Integration of Immigrants and their Children: Developing, Activating and Using Skills”, International Migration Outlook 2014, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2014-5-en.

OECD (2013), OECD Skills Outlook 2013: First Results from the Survey of Adult Skills, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264204256-en.

Annex 7.A1.

Additional tables and figures

Table 7.A1.1. Distribution of the immigrant and native-born populations not in education, 15-64 year-olds, by level of education, 2012-13
Total by group = 100
| Foreign-born | Difference with the native-born +: higher than the native-born -: lower than the native-born
| Total | Men | Women | Total | Men | Women
| Low-educated | Medium educated | highly educated | Low-educated | Medium educated | Highly educated | Low-educated | Medium educated | Highly educated | Low-educated | Medium educated | Highly educated | Low-educated | Medium educated | Highly educated | Low-educated | Medium educated | Highly educated
Australia | 19 | 34 | 47 | 18 | 37 | 45 | 20 | 31 | 49 | -11 | -7 | 18 | -13 | -9 | 21 | -10 | -6 | 15
Austria | 31 | 50 | 19 | 28 | 54 | 18 | 35 | 46 | 19 | 17 | -18 | 1 | 17 | -16 | -2 | 16 | -19 | 3
Belgium | 41 | 30 | 29 | 41 | 32 | 28 | 41 | 29 | 30 | 15 | -9 | -6 | 13 | -10 | -4 | 17 | -9 | -8
Canada | 10 | 30 | 60 | 10 | 32 | 58 | 10 | 28 | 62 | -3 | -12 | 14 | -5 | -14 | 19 | -1 | -9 | 9
Chile | 25 | 49 | 26 | 24 | 48 | 28 | 25 | 50 | 25 | -18 | 8 | 10 | -18 | 6 | 11 | -17 | 9 | 8
Croatia | 28 | 55 | 17 | 21 | 61 | 18 | 35 | 49 | 16 | 8 | -7 | -1 | 4 | -6 | 2 | 11 | -8 | -4
Cyprus1, 2 | 23 | 41 | 36 | 21 | 45 | 34 | 24 | 39 | 37 | 0 | 2 | -2 | -2 | 3 | -1 | 2 | 3 | -5
Czech Republic | 17 | 58 | 25 | 14 | 60 | 26 | 21 | 56 | 23 | 9 | -15 | 7 | 7 | -16 | 8 | 10 | -14 | 5
Denmark | 28 | 38 | 34 | 31 | 40 | 30 | 25 | 37 | 38 | 5 | -6 | 1 | 8 | -10 | 2 | 2 | -2 | 0
Estonia | 6 | 53 | 41 | 7 | 57 | 36 | 6 | 50 | 44 | -6 | 0 | 6 | -9 | -2 | 11 | -3 | 2 | 0
Finland | 27 | 45 | 28 | 31 | 46 | 23 | 23 | 44 | 33 | 11 | -2 | -9 | 13 | -5 | -8 | 10 | 1 | -11
France | 43 | 30 | 27 | 42 | 32 | 26 | 45 | 29 | 27 | 19 | -15 | -4 | 18 | -16 | -2 | 20 | -14 | -6
Germany | 35 | 43 | 21 | 32 | 46 | 21 | 38 | 40 | 22 | 25 | -18 | -7 | 24 | -14 | -10 | 26 | -22 | -4
Greece | 45 | 40 | 15 | 52 | 37 | 11 | 38 | 43 | 18 | 12 | 0 | -12 | 18 | -3 | -16 | 7 | 2 | -8
Hungary | 14 | 55 | 31 | 11 | 56 | 32 | 16 | 54 | 30 | -6 | -5 | 11 | -6 | -9 | 15 | -5 | -1 | 7
Iceland | 31 | 39 | 30 | 29 | 44 | 27 | 32 | 35 | 32 | -2 | 4 | -2 | -2 | 2 | 1 | -2 | 8 | -6
Ireland | 20 | 32 | 48 | 21 | 35 | 44 | 19 | 29 | 52 | -7 | -6 | 13 | -9 | -4 | 13 | -4 | -8 | 12
Israel* | 14 | 34 | 51 | 15 | 36 | 49 | 14 | 33 | 53 | -3 | -11 | 14 | -5 | -11 | 16 | -1 | -11 | 12
Italy | 46 | 43 | 11 | 51 | 41 | 8 | 42 | 44 | 14 | 3 | 1 | -4 | 7 | -2 | -6 | 1 | 2 | -3
Japan | 22 | 46 | 32 | .. | .. | .. | .. | .. | .. | 9 | -4 | -5 | .. | .. | .. | .. | .. | ..
Korea | 28 | 46 | 26 | .. | .. | .. | .. | .. | .. | -1 | 8 | -7 | .. | .. | .. | .. | .. | ..
Latvia | 8 | 66 | 27 | 10 | 68 | 22 | 6 | 64 | 30 | -6 | 8 | -2 | -8 | 6 | 2 | -4 | 10 | -6
Lithuania | 3 | 64 | 33 | 2 | 73 | 25 | 4 | 57 | 39 | -6 | 6 | 0 | -8 | 10 | -1 | -3 | 3 | 0
Luxembourg | 23 | 29 | 48 | 23 | 27 | 50 | 24 | 31 | 46 | 1 | -21 | 20 | 3 | -24 | 21 | -1 | -19 | 20
Malta | 45 | 27 | 27 | 48 | 30 | 22 | 43 | 25 | 32 | -15 | 3 | 12 | -11 | 3 | 8 | -19 | 3 | 17
Mexico | 32 | 32 | 35 | 31 | 33 | 36 | 34 | 32 | 34 | -31 | 10 | 21 | -32 | 11 | 20 | -30 | 9 | 21
Netherlands | 33 | 41 | 26 | 33 | 40 | 27 | 33 | 42 | 26 | 7 | -1 | -6 | 8 | -2 | -7 | 6 | -1 | -6
New Zealand | 17 | 36 | 47 | 17 | 40 | 44 | 18 | 33 | 50 | -5 | -11 | 16 | -7 | -11 | 18 | -3 | -11 | 14
Norway | 23 | 40 | 37 | 23 | 45 | 33 | 23 | 35 | 42 | 2 | -5 | 2 | 2 | -5 | 3 | 3 | -6 | 2
Poland | 8 | 47 | 45 | 9 | 42 | 49 | 6 | 53 | 41 | -3 | -19 | 22 | -2 | -28 | 30 | -4 | -9 | 13
Portugal | 42 | 33 | 25 | 45 | 34 | 22 | 40 | 31 | 28 | -20 | 12 | 8 | -23 | 14 | 8 | -18 | 11 | 8
Slovak Republic | 12 | 62 | 26 | 10 | 63 | 27 | 14 | 60 | 26 | 2 | -11 | 8 | 2 | -13 | 11 | 2 | -8 | 6
Slovenia | 29 | 57 | 13 | 23 | 64 | 12 | 36 | 50 | 15 | 15 | -1 | -14 | 10 | -1 | -9 | 21 | -2 | -18
Spain | 46 | 32 | 23 | 48 | 30 | 22 | 43 | 33 | 24 | -2 | 11 | -10 | -1 | 10 | -9 | -2 | 12 | -11
Sweden | 31 | 36 | 34 | 31 | 38 | 31 | 31 | 33 | 36 | 15 | -17 | 2 | 14 | -20 | 5 | 16 | -14 | -3
Switzerland | 27 | 38 | 35 | 25 | 38 | 37 | 30 | 37 | 33 | 20 | -20 | 0 | 20 | -14 | -6 | 20 | -26 | 6
Turkey | 42 | 36 | 22 | 41 | 38 | 21 | 43 | 34 | 23 | -27 | 18 | 10 | -23 | 16 | 7 | -32 | 20 | 12
United Kingdom | 20 | 33 | 47 | 19 | 35 | 46 | 20 | 32 | 48 | -3 | -9 | 12 | -3 | -9 | 12 | -4 | -8 | 12
United States | 27 | 37 | 37 | 28 | 37 | 35 | 25 | 37 | 38 | 18 | -13 | -5 | 19 | -15 | -4 | 17 | -11 | -6
EU total (28) | 36 | 38 | 26 | 36 | 39 | 25 | 36 | 37 | 27 | 1 | -6 | 5 | 2 | -7 | 5 | 0 | -5 | 5
OECD total (33) | 29 | 37 | 34 | 30 | 38 | 33 | 29 | 36 | 36 | 11 | -11 | 0 | 11 | -11 | 0 | 11 | -10 | -1

Notes: Canadian and New Zealand data include people still in education. The United States includes people over 55 who are still in education and calculates the share of low- and highly educated for the 16-64 age group. Korea and Japan determine who is an immigrant on the basis of nationality, not on the basis of country of birth. Japan is not included in OECD average.

1, 2: See the “Notes, sources, and further reading” section.

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: European Union Labour Force Surveys (EU-LFS) 2006-07 and 2012-13. Australian Survey of Education and Work (ASEW) 2013. Canada and New Zealand: Labour Force Surveys 2006-07 and 2012-13. Israel: Labour Force Surveys 2006 and 2011. United States: Current Population Surveys (CPS) 2013. Chile: Encuesta de Caracterización Socioeconómica Nacional (CASEN) 2011. Japan: DIOC 2005-06. Mexico: Encuesta Nacional de Ocupación y Empleo (ENOE) 2012. Korea: Foreign Labour Force Survey 2012-13.

StatLink  http://dx.doi.org/10.1787/888933214095

Table 7.A1.2. Change in the distribution of the immigrant and native-born populations by level of education between 2006-07 and 2012-13, 15-64 not in education
Change in percentage points
| Foreign-born | Native-born
| Total | Men | Women | Total | Men | Women
| Low-educated | Medium educated | Highly educated | Low-educated | Medium educated | Highly educated | Low-educated | Medium educated | Highly educated | Low-educated | Medium educated | Highly educated | Low-educated | Medium educated | Highly educated | Low-educated | Medium educated | Highly educated
Australia | -8 | -1 | 9 | -6 | -2 | 8 | -10 | -1 | 11 | -6 | 3 | 3 | -4 | 2 | 1 | -9 | 4 | 5
Austria | -4 | 2 | 2 | -3 | 3 | 0 | -5 | 2 | 3 | -3 | 1 | 2 | -2 | 0 | 2 | -5 | 2 | 3
Belgium | -4 | 1 | 2 | -3 | 2 | 1 | -5 | 1 | 4 | -5 | 2 | 4 | -4 | 2 | 3 | -6 | 1 | 5
Canada | -4 | -4 | 8 | -3 | -4 | 7 | -5 | -5 | 9 | -3 | -1 | 4 | -3 | 1 | 2 | -4 | -2 | 6
Chile | 2 | 3 | -6 | 6 | 2 | -7 | 0 | 4 | -4 | -5 | 2 | 3 | -5 | 2 | 2 | -5 | 3 | 3
Croatia | -5 | 1 | 4 | -3 | -1 | 4 | -6 | 3 | 3 | -4 | 1 | 3 | -3 | 1 | 2 | -5 | 1 | 3
Cyprus1, 2 | -6 | 4 | 2 | -9 | 7 | 2 | -4 | 2 | 2 | -7 | -1 | 8 | -6 | 0 | 6 | -8 | -3 | 11
Czech Republic | -6 | -1 | 7 | -5 | -2 | 8 | -6 | 0 | 6 | -3 | -3 | 6 | -2 | -3 | 4 | -4 | -4 | 7
Denmark | -2 | 0 | 2 | 1 | 2 | -3 | -5 | -2 | 7 | 0 | -2 | 2 | 1 | -1 | 0 | -2 | -3 | 4
Estonia | -1 | -4 | 6 | -1 | -2 | 3 | -1 | -6 | 7 | -3 | -2 | 4 | -3 | 0 | 3 | -3 | -3 | 6
Finland | -1 | 1 | 0 | 2 | -2 | 0 | -3 | 4 | -1 | -6 | 2 | 4 | -6 | 3 | 3 | -6 | 0 | 6
France | -5 | 1 | 4 | -4 | 1 | 4 | -6 | 2 | 4 | -6 | 1 | 5 | -5 | 1 | 4 | -6 | 1 | 5
Germany | -4 | -1 | 4 | -3 | 0 | 3 | -4 | -2 | 6 | -3 | -1 | 4 | -2 | -1 | 3 | -4 | -2 | 5
Greece | 0 | 0 | 0 | 0 | 1 | -1 | 0 | -1 | 1 | -8 | 2 | 6 | -7 | 3 | 5 | -8 | 2 | 7
Hungary | -2 | 0 | 2 | -2 | 0 | 2 | -2 | 0 | 3 | -4 | 0 | 4 | -3 | 0 | 3 | -5 | -1 | 6
Iceland | -2 | 9 | -6 | -3 | 11 | -8 | -2 | 6 | -4 | -9 | 3 | 6 | -8 | 5 | 3 | -10 | 1 | 9
Ireland | -1 | -5 | 6 | -1 | -5 | 6 | 0 | -5 | 5 | -8 | 0 | 8 | -9 | 2 | 7 | -8 | -1 | 9
Israel* | -2 | -1 | 3 | -3 | 0 | 3 | -2 | -1 | 3 | -3 | -1 | 4 | -4 | -1 | 4 | -3 | -1 | 4
Italy | -2 | 3 | -1 | -1 | 3 | -2 | -3 | 3 | -1 | -7 | 4 | 3 | -6 | 4 | 2 | -8 | 4 | 4
Japan | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | ..
Korea | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | ..
Latvia | -5 | 2 | 3 | -5 | 5 | 0 | -5 | 0 | 5 | -6 | -3 | 9 | -6 | 1 | 6 | -5 | -7 | 12
Lithuania | -4 | -5 | 9 | -7 | 3 | 3 | -1 | -12 | 13 | -5 | -2 | 7 | -6 | 1 | 5 | -5 | -4 | 9
Luxembourg | -14 | -3 | 17 | -14 | -4 | 18 | -13 | -3 | 16 | -11 | 3 | 8 | -8 | 0 | 8 | -14 | 6 | 9
Malta | -8 | 0 | 8 | -4 | -1 | 5 | -12 | 1 | 10 | -7 | 3 | 4 | -5 | 2 | 3 | -9 | 4 | 5
Mexico | 2 | 7 | -9 | 2 | 5 | -7 | 3 | 9 | -11 | -5 | 2 | 2 | -4 | 3 | 2 | -5 | 2 | 3
Netherlands | 1 | -5 | 4 | 2 | -5 | 3 | 0 | -4 | 5 | -3 | 0 | 3 | -1 | 0 | 2 | -4 | 0 | 4
New Zealand | -2 | -2 | 5 | -2 | -2 | 4 | -2 | -4 | 6 | -3 | 2 | 0 | -2 | 2 | 0 | -4 | 3 | 1
Norway | -10 | 7 | 4 | -11 | 9 | 1 | -10 | 4 | 6 | -4 | -1 | 6 | -4 | 0 | 4 | -5 | -2 | 8
Poland | -13 | -6 | 19 | -9 | -12 | 21 | -17 | 0 | 16 | -4 | -3 | 7 | -3 | -2 | 5 | -4 | -4 | 8
Portugal | -11 | 6 | 4 | -12 | 7 | 4 | -10 | 5 | 4 | -12 | 7 | 5 | -11 | 6 | 4 | -13 | 7 | 6
Slovak Republic | -2 | -2 | 4 | 3 | -5 | 1 | -8 | 0 | 8 | -3 | -2 | 5 | -2 | -1 | 3 | -4 | -3 | 7
Slovenia | -3 | 2 | 1 | 1 | 0 | -1 | -7 | 3 | 4 | -4 | -2 | 6 | -3 | -1 | 4 | -5 | -3 | 8
Spain | 1 | -2 | 1 | 1 | -2 | 1 | 1 | -2 | 1 | -6 | 1 | 5 | -5 | 1 | 4 | -7 | 1 | 6
Sweden | -1 | -5 | 5 | 0 | -4 | 4 | -1 | -5 | 7 | -5 | 0 | 5 | -4 | 1 | 3 | -6 | 0 | 6
Switzerland | -5 | -2 | 7 | -4 | -3 | 7 | -6 | -2 | 8 | -2 | -5 | 7 | -1 | -4 | 4 | -3 | -6 | 9
Turkey | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | ..
United Kingdom | -4 | -13 | 17 | -3 | -13 | 16 | -5 | -13 | 18 | -6 | 0 | 6 | -4 | -1 | 5 | -8 | 1 | 6
United States | -4 | 0 | 4 | -5 | 1 | 3 | -3 | 0 | 4 | -1 | -2 | 3 | -1 | -1 | 2 | -1 | -3 | 5
EU total (28) | -3 | -2 | 5 | -2 | -2 | 4 | -3 | -2 | 5 | -5 | 0 | 5 | -4 | 1 | 3 | -6 | 0 | 6
OECD total (31) | -3 | -1 | 4 | -3 | 0 | 4 | -3 | -1 | 5 | -4 | 0 | 4 | -3 | 1 | 3 | -5 | -1 | 5
Notes: Canadian and New Zealand data include people still in education. The United States includes people over 25 who are still in education.
1, 2: See the “Notes, sources, and further reading” section.
* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: European Union Labour Force Surveys (EU-LFS) 2006-07 and 2012-13. Australian Survey of Education and Work (ASEW) 2007 and 2013). Canada and New Zealand: Labour Force Surveys 2006-07 and 2012-13. Israel: Labour Force Surveys 2006 and 2011. United States: Current Population Surveys (CPS) 2006-07 and 2012-13. Chile: Encuesta de Caracterización Socioeconómica Nacional (CASEN) 2011. Mexico: Encuesta Nacional de Ocupación y Empleo (ENOE) 2007 and 2012.

StatLink  http://dx.doi.org/10.1787/888933214100

Table 7.A1.3. Share of migrants with foreign education, by gender and level of education, 2011-12
Percentages
| Total | Highly educated
| Total | Men | Women | Total | Men | Women
Austria | 72 | 69 | 74 | 68 | 68 | 67
Belgium | 70 | 69 | 71 | 65 | 67 | 63
Canada | 55 | .. | .. | 57 | .. | ..
Cyprus1, 2 | 83 | 81 | 85 | 76 | 74 | 78
Czech Republic | 67 | 69 | 65 | 56 | 57 | 55
Denmark | 51 | 51 | 51 | 47 | 49 | 44
Estonia | 34 | 31 | 36 | 29 | 28 | 29
Finland | 57 | 56 | 58 | 47 | 40 | 51
France | 53 | 50 | 54 | 36 | 35 | 38
Germany | 61 | 59 | 63 | 58 | 56 | 60
Greece | 80 | 80 | 80 | 67 | 60 | 71
Hungary | 70 | 69 | 72 | 57 | 59 | 55
Iceland | 64 | 65 | 63 | 50 | 49 | 51
Ireland | 69 | 70 | 67 | 71 | 71 | 70
Italy | 76 | 74 | 77 | 65 | 60 | 67
Latvia | 32 | 35 | 30 | 18 | 24 | 14
Lithuania | 44 | 49 | 40 | 33 | 39 | 30
Luxembourg | 75 | 75 | 74 | 83 | 85 | 81
Netherlands | 42 | 39 | 44 | 41 | 36 | 45
Poland | 54 | 58 | 50 | 55 | 60 | 49
Portugal | 41 | 38 | 44 | 23 | 20 | 25
Slovak Republic | 54 | 56 | 51 | 45 | 52 | 37
Slovenia | 59 | 55 | 63 | 31 | 33 | 29
Spain | 79 | 78 | 79 | 72 | 72 | 72
Sweden | 58 | 57 | 59 | 59 | 63 | 56
Switzerland | 67 | 67 | 68 | 66 | 67 | 64
United Kingdom | 54 | 54 | 53 | 48 | 49 | 48
United States | 62 | 60 | 63 | 54 | 54 | 55
EU total (26) | 63 | 62 | 64 | 54 | 53 | 54
OECD total (24) | 62 | 61 | 64 | 54 | 54 | 55
Notes: The PIAAC sample covers people aged 16-64. In the Australian data, it is not possible to identify the country in which the highest qualification was obtained. The country has therefore been ommitted from the table. Canada is not included in the OECD average.
“..” stands for not available.
1, 2: See the “Notes, sources, and further reading” section.
Sources: Norway and Canada: OECD Programme for the International Assessment of Adult Competencies (PIAAC) 2012. American Community Survey (ACS) 2012. European Union Labour Force Surveys (EU-LFS) 2011-12 for European countries.
StatLink  http://dx.doi.org/10.1787/888933214114

Table 7.A1.4. Literacy mean scores by native language, 16-64 year-olds, 2012
| Foreign-born | Difference with the native-born +: Higher than the native-born -: Lower than the native-born
| Native speakers | Foreign speakers | All | Native speakers | Foreign speakers | All
Australia | 289 | 256 | 272 | 4 | -29 | -12
Austria | 279 | 237 | 248 | 5 | -37 | -26
Belgium (Fl.) | 279 | 221 | 242 | 0 | -58 | -37
Canada | 269 | 250 | 256 | -10 | -30 | -24
Cyprus1, 2 | 269 | 250 | 260 | -1 | -21 | -10
Czech Republic | 267 | 269 | 269 | -8 | -5 | -5
Denmark | 273 | 232 | 238 | -3 | -44 | -38
Estonia | 257 | 256 | 257 | -22 | -24 | -22
Finland | 301 | 240 | 240 | 9 | -51 | -52
France | 243 | 221 | 230 | -24 | -47 | -37
Germany | 257 | 236 | 241 | -18 | -39 | -34
Ireland | 274 | 249 | 263 | 6 | -19 | -5
Italy | 248 | 223 | 228 | -5 | -30 | -25
Netherlands | 267 | 239 | 247 | -23 | -51 | -44
Norway | 283 | 242 | 246 | -1 | -42 | -38
Slovak Republic | 263 | 274 | 269 | -11 | 0 | -5
Spain | 240 | 218 | 232 | -15 | -37 | -23
Sweden | 277 | 230 | 235 | -13 | -60 | -55
UK (Engl./N. Ireland) | 269 | 245 | 255 | -6 | -30 | -21
United States | 266 | 230 | 239 | -9 | -45 | -36
OECD average (19) | 268 | 241 | 248 | -8 | -36 | -28
EU average (16) | 266 | 240 | 247 | -8 | -34 | -27
1, 2: See the “Notes, sources, and further reading” section.
Source: OECD Programme for the International Assessment of Adult Competences (PIAAC) 2012.
StatLink  http://dx.doi.org/10.1787/888933214127

Figure 7.A1.1. Mean literacy scores of 16-64 year-olds immigrants by native language, 2012

Difference in points with the native-born, controlled for age, sex and educational attainment

1, 2: See the “Notes, sources, and further reading” section.

Source: OECD Programme for the International Assessment of Adult Competences (PIAAC) 2012.

StatLink  http://dx.doi.org/10.1787/888933212762

Figure 7.A1.2. Percentage of people with very basic literacy skills by place of birth and native language, 16-64 year-olds, 2012

1, 2: See the “Notes, sources, and further reading” section.

Source: OECD Programme for the International Assessment of Adult Competences (PIAAC) 2012.

StatLink  http://dx.doi.org/10.1787/888933212779

Table 7.A1.5. Distribution of the foreign- and native-born populations by level of literacy, 16-64 years old, 2012
Total by group = 100
| Foreign-born | Native-born
| Below level 1 | Level 1 | Level 2 | Level 3 | Level 4 | Level 5 | Below level 1 | Level 1 | Level 2 | Level 3 | Level 4 | Level 5
Australia | 7 | 11 | 30 | 36 | 15 | 1 | 2 | 9 | 30 | 42 | 17 | 1
Austria | 10 | 23 | 36 | 25 | 6 | .. | 1 | 11 | 38 | 41 | 9 | ..
Belgium | 15 | 22 | 29 | 27 | 6 | .. | 2 | 11 | 31 | 42 | 13 | ..
Canada | 9 | 18 | 34 | 30 | 8 | 1 | 2 | 11 | 31 | 40 | 15 | 1
Cyprus1, 2 | 5 | 17 | 39 | 33 | 6 | .. | 1 | 12 | 40 | 40 | 6 | ..
Denmark | 17 | 21 | 31 | 25 | 5 | .. | 2 | 10 | 34 | 42 | 10 | ..
Estonia | 4 | 19 | 42 | 31 | 4 | .. | 2 | 10 | 33 | 43 | 12 | 1
Finland | 21 | 16 | 26 | 27 | 9 | 1 | 1 | 7 | 26 | 42 | 21 | 2
France | 18 | 25 | 34 | 20 | 3 | .. | 3 | 15 | 36 | 37 | 8 | ..
Germany | 9 | 29 | 38 | 20 | 4 | .. | 2 | 12 | 34 | 40 | 11 | 1
Ireland | 7 | 13 | 38 | 35 | 8 | .. | 4 | 13 | 38 | 37 | 8 | ..
Italy | 15 | 27 | 42 | 14 | 1 | .. | 4 | 22 | 42 | 28 | 4 | ..
Netherlands | 12 | 24 | 29 | 28 | 7 | 1 | 1 | 7 | 26 | 45 | 19 | 1
Norway | 15 | 20 | 30 | 25 | 9 | .. | 1 | 8 | 31 | 46 | 14 | 1
Spain | 15 | 28 | 37 | 18 | 3 | .. | 6 | 19 | 40 | 30 | 5 | ..
Sweden | 18 | 24 | 29 | 23 | 6 | .. | 1 | 6 | 28 | 46 | 17 | 1
UK (Engl./N. Ireland) | 9 | 20 | 31 | 30 | 9 | 1 | 2 | 12 | 34 | 38 | 13 | 1
United States | 15 | 25 | 31 | 22 | 6 | .. | 2 | 12 | 34 | 38 | 12 | 1
OECD average (19) | 12 | 21 | 34 | 27 | 6 | .. | 2 | 11 | 34 | 40 | 12 | 1
EU average (16) | 11 | 21 | 35 | 27 | 6 | .. | 2 | 12 | 35 | 40 | 11 | 1
| Foreign-born
| Native speakers | Foreign speakers
| Below level 1 | Level 1 | Level 2 | Level 3 | Level 4 | Level 5 | Below level 1 | Level 1 | Level 2 | Level 3 | Level 4 | Level 5
Australia | 3 | 7 | 26 | 41 | 21 | 2 | 11 | 16 | 33 | 31 | 9 | 1
Austria | 3 | 11 | 30 | 40 | 16 | .. | 12 | 27 | 38 | 20 | 3 | ..
Belgium | 2 | 11 | 29 | 46 | 11 | 1 | 23 | 29 | 29 | 15 | 3 | ..
Canada | 4 | 15 | 35 | 34 | 11 | 1 | 11 | 20 | 33 | 28 | 7 | ..
Cyprus1, 2 | 2 | 12 | 39 | 39 | 7 | .. | 7 | 22 | 39 | 27 | 4 | ..
Denmark | 4 | 11 | 31 | 44 | 10 | .. | 19 | 23 | 31 | 22 | 5 | ..
Estonia | 3 | 19 | 43 | 31 | 4 | .. | 4 | 23 | 39 | 29 | 5 | ..
Finland | 1 | 2 | 22 | 47 | 24 | 3 | 18 | 18 | 30 | 28 | 6 | ..
France | 12 | 22 | 39 | 24 | 3 | .. | 23 | 27 | 31 | 16 | 2 | ..
Germany | 6 | 18 | 39 | 33 | 4 | .. | 10 | 32 | 38 | 16 | 4 | ..
Ireland | 3 | 9 | 37 | 40 | 10 | 1 | 11 | 17 | 39 | 28 | 5 | ..
Italy | 6 | 16 | 53 | 24 | 1 | .. | 18 | 30 | 39 | 11 | 1 | ..
Netherlands | 7 | 17 | 27 | 34 | 13 | 1 | 14 | 26 | 29 | 25 | 4 | ..
Norway | 1 | 13 | 23 | 45 | 17 | 1 | 17 | 20 | 31 | 24 | 8 | ..
Spain | 10 | 27 | 41 | 20 | 3 | .. | 23 | 29 | 32 | 14 | 2 | ..
Sweden | 1 | 8 | 43 | 36 | 12 | 1 | 21 | 26 | 27 | 22 | 5 | ..
UK (Engl./N. Ireland) | 4 | 18 | 30 | 34 | 13 | 2 | 13 | 22 | 32 | 27 | 6 | 1
United States | 4 | 17 | 35 | 33 | 10 | .. | 19 | 28 | 30 | 18 | 4 | ..
OECD average (19) | 4 | 14 | 34 | 36 | 10 | 1 | 14 | 23 | 34 | 24 | 5 | ..
EU average (16) | 4 | 15 | 36 | 36 | 9 | 1 | 14 | 23 | 35 | 24 | 4 | ..
1, 2: See the “Notes, sources, and further reading” section.
Source: OECD Programme for the International Assessment of Adult Competences (PIAAC) 2012.
StatLink  http://dx.doi.org/10.1787/888933214132

Table 7.A1.6. Participation in education and training of immigrants over the last 12 months by duration of stay and gender, 25-64, 2012
In percentage
| Recent immigrants | More settled immigrants (> 5 years)
| Men | Women | Total | Men | Women | Total
Australia | .. | .. | .. | .. | .. | ..
Austria | 76 | 49 | 61 | 42 | 38 | 40
Belgium | 29 | 56 | 44 | 34 | 48 | 42
Canada | 60 | 56 | 58 | 51 | 53 | 52
Cyprus1, 2 | 35 | 25 | 30 | 41 | 39 | 40
Denmark | 75 | 71 | 73 | 49 | 58 | 54
Estonia | 74 | 65 | 69 | 34 | 43 | 39
Finland | 88 | 72 | 81 | 64 | 64 | 64
France | 38 | 43 | 41 | 24 | 25 | 25
Germany | 59 | 45 | 50 | 39 | 37 | 38
Ireland | 58 | 46 | 51 | 54 | 51 | 52
Italy | 9 | 11 | 10 | 23 | 23 | 23
Netherlands | 78 | 82 | 80 | 59 | 51 | 55
Norway | 77 | 71 | 75 | 58 | 66 | 62
Spain | 51 | 38 | 43 | 43 | 36 | 39
Sweden | 60 | 71 | 66 | 54 | 57 | 55
UK (Engl./N. Ireland) | 58 | 53 | 55 | 53 | 58 | 55
United States | 64 | 44 | 54 | 52 | 48 | 50
OECD average (19) | 62 | 55 | 58 | 16 | 10 | 13
EU average (16) | 59 | 52 | 55 | 15 | 10 | 12
1, 2: See the “Notes, sources, and further reading” section.
Source: OECD Programme for the International Assessment of Adult Competences (PIAAC) 2012.
StatLink  http://dx.doi.org/10.1787/888933214149

Table 7.A1.7. Participation in education and training by place of birth and level of literacy, 25-64 year-olds, 2012
| Foreign-born | Difference with the native-born +: Higher than the native-born -: Lower than the native-born
| Below level 1 | Level 1 | Level 2 | Level 3 | Level 4/5 | Below level 1 | Level 1 | Level 2 | Level 3 | Level 4/5
Australia | 18 | 33 | 47 | 61 | 78 | 3 | 4 | 4 | .. | 1
Austria | 18 | 28 | 43 | 57 | 70 | -5 | .. | 2 | -2 | -4
Belgium | 28 | 27 | 42 | 62 | 53 | 11 | -1 | 2 | 5 | -15
Canada | 21 | 38 | 51 | 68 | 78 | -1 | 2 | 1 | 1 | -2
Cyprus1, 2 | 25 | 32 | 36 | 42 | 48 | -1 | 3 | 2 | .. | -6
Denmark | 41 | 48 | 63 | 72 | 82 | 11 | 6 | 2 | -3 | -3
Estonia | 19 | 31 | 39 | 47 | 61 | -3 | -5 | -8 | -14 | -17
Finland | 54 | 53 | 70 | 78 | 82 | 33 | 16 | 17 | 7 | -1
France | 18 | 19 | 25 | 42 | 60 | 2 | -3 | -6 | -4 | 1
Germany | 18 | 27 | 39 | 60 | 75 | 1 | -6 | -8 | -4 | -4
Ireland | 33 | 40 | 45 | 64 | 69 | 8 | 8 | 1 | 7 | -6
Italy | 23 | 17 | 19 | 35 | 24 | 14 | 3 | -1 | -5 | -34
Netherlands | 46 | 44 | 56 | 68 | 86 | 17 | 4 | 4 | -3 | 6
Norway | 57 | 59 | 65 | 73 | 75 | 28 | 21 | 13 | 3 | -2
Spain | 27 | 37 | 38 | 57 | 75 | 12 | 6 | -7 | -7 | -4
Sweden | 41 | 45 | 58 | 73 | 86 | 5 | 7 | 1 | 1 | 4
UK (Engl./N. Ireland) | 35 | 48 | 55 | 60 | 77 | 14 | 11 | 8 | -3 | 1
United States | 31 | 40 | 50 | 69 | 83 | 2 | 1 | -2 | .. | 3
OECD average (19) | 28 | 34 | 46 | 61 | 70 | 7 | 3 | 1 | -1 | -5
EU average (16) | 27 | 32 | 43 | 58 | 67 | 6 | 1 | .. | -1 | -6
1, 2: See the “Notes, sources, and further reading” section.
Source: OECD Programme for the International Assessment of Adult Competences (PIAAC) 2012.
StatLink  http://dx.doi.org/10.1787/888933214150

Table 7.A1.8. Percentage of people with unmet training needs, by level of literacy, 25-64 year-olds, 2012
| Foreign-born | Difference with the native-born +: Higher than the native-born -: Lower than the native-born
| Below level 1 | Level 1 | Level 2 | Level 3 | Level 4/5 | Below level 1 | Level 1 | Level 2 | Level 3 | Level 4/5
Australia | 6 | 21 | 24 | 31 | 35 | -4 | 5 | 5 | 6 | 3
Austria | 15 | 16 | 22 | 29 | 30 | 5 | 6 | 6 | 5 | -1
Belgium | 8 | 10 | 18 | 29 | 17 | 1 | 2 | 3 | 8 | -9
Canada | 15 | 27 | 36 | 41 | 49 | -4 | 11 | 12 | 7 | 7
Cyprus1, 2 | 45 | 22 | 26 | 29 | 22 | 26 | 2 | 6 | 6 | -11
Denmark | 27 | 32 | 39 | 42 | 39 | 9 | 13 | 11 | 3 | -7
Estonia | 18 | 17 | 26 | 29 | 34 | 0 | -6 | -2 | -7 | -13
Finland | 25 | 42 | 46 | 37 | 54 | 16 | 26 | 23 | 5 | 12
France | 14 | 17 | 20 | 22 | 28 | 3 | 4 | 3 | -1 | 1
Germany | 18 | 24 | 28 | 35 | 52 | 8 | 7 | 4 | 0 | 7
Ireland | 22 | 34 | 39 | 41 | 48 | 3 | 9 | 13 | 10 | 11
Italy | 8 | 15 | 25 | 28 | 15 | 2 | 7 | 11 | 3 | -28
Netherlands | 11 | 10 | 19 | 32 | 41 | 1 | -2 | 3 | 6 | 9
Norway | 28 | 22 | 35 | 39 | 43 | 11 | 10 | 15 | 12 | 9
Spain | 26 | 37 | 37 | 37 | 51 | 7 | 14 | 9 | -2 | 5
Sweden | 31 | 26 | 36 | 42 | 53 | 12 | 2 | 11 | 8 | 10
UK (Engl./N. Ireland) | 11 | 28 | 31 | 37 | 52 | -2 | 12 | 10 | 12 | 19
United States | 19 | 26 | 42 | 49 | 53 | -9 | -1 | 12 | 7 | 3
OECD average (19) | 16 | 22 | 29 | 34 | 38 | 3 | 6 | 8 | 5 | 1
EU average (16) | 18 | 21 | 27 | 32 | 35 | 5 | 6 | 7 | 4 | -1
1, 2: See the “Notes, sources, and further reading” section.
Source: OECD Programme for the International Assessment of Adult Competences (PIAAC) 2012.
StatLink  http://dx.doi.org/10.1787/888933214163

Table 7.A1.9. Employer’s financial contribution to job-related training, by place of birth, 2012
Percentage of persons who participated in a job-related training
| Foreign-born Total = 100 | Difference with the native-born +: Higher than the native-born -: Lower than the native-born
| Fully financed by the employer | Partly financed by the employer | Not financed by the employer | Free training | No employer | Fully financed by the employer | Partly financed by the employer | Not financed by the employer | Free training | No employer
Australia | 55 | 4 | 21 | 13 | 7 | -6 | 2 | 2 | .. | 2
Austria | 53 | 3 | 21 | 8 | 14 | -3 | -2 | .. | -1 | 7
Belgium | 52 | 1 | 24 | 8 | 16 | -14 | -1 | 6 | -1 | 10
Canada | 49 | 4 | 27 | 15 | 5 | -9 | 1 | 6 | .. | 2
Cyprus1, 2 | 46 | 5 | 27 | 17 | 4 | 2 | -1 | -2 | .. | 1
Denmark | 55 | 2 | 18 | 11 | 14 | -20 | .. | 7 | 5 | 7
Estonia | 50 | 5 | 22 | 16 | 7 | -4 | 1 | 2 | -2 | 3
Finland | 48 | 2 | 27 | 9 | 13 | -20 | 1 | 13 | -2 | 8
France | 51 | 2 | 13 | 11 | 23 | -15 | -1 | 1 | 1 | 13
Germany | 53 | 4 | 21 | 6 | 17 | -11 | 1 | 5 | -5 | 11
Ireland | 44 | 4 | 28 | 16 | 9 | -7 | .. | 5 | 2 | ..
Italy | 54 | 9 | 12 | 9 | 17 | 1 | 5 | .. | -5 | ..
Netherlands | 52 | 4 | 19 | 13 | 11 | -16 | 2 | 4 | 4 | 7
Norway | 51 | 7 | 23 | 13 | 6 | -23 | 4 | 10 | 5 | 4
Spain | 47 | 2 | 25 | 10 | 15 | -5 | -2 | .. | -1 | 7
Sweden | 46 | 4 | 22 | 17 | 11 | -12 | 1 | 3 | 1 | 7
UK (Engl./N. Ireland) | 55 | 3 | 18 | 15 | 10 | -8 | 1 | 6 | -3 | 5
United States | 36 | 6 | 31 | 22 | 5 | -10 | 2 | 8 | -2 | 2
OECD average (19) | 51 | 4 | 22 | 12 | 11 | -10 | .. | 4 | .. | 5
EU average (16) | 51 | 4 | 21 | 12 | 12 | -8 | .. | 3 | .. | 5
1, 2: See the “Notes, sources, and further reading” section.
Source: OECD Programme for the International Assessment of Adult Competences (PIAAC) 2012.
StatLink  http://dx.doi.org/10.1787/888933214178

Chapter 8.

Income of immigrant households

Income is a decisive factor in determining many socio-economic outcomes. A variety of studies have shown, for example, that a higher level of income is associated with better health and education, and greater civic participation and social cohesion. In contrast, poverty adversely affects the well-being of immigrants in the host society in many ways, such as poor housing and inhibited skills development. Beyond poverty itself, inequitable distribution of income can lead to marginalisation and damage social cohesion.

People’s levels of income are largely shaped by their employment status. Their labour market outcomes and the nature of the job they hold are important determinants of income, as labour earnings themselves account for the bulk of family incomes in the OECD and in the EU. The degree to which income can provide a decent living is affected by many other socio-demographic factors, such as the number of children and their ages, and the availability of social transfers that help to even out income inequalities.

This chapter considers four indicators. It looks first at household disposable income (Indicator 8.1) and the overall risk of poverty (Indicator 8.2). Because having a job does not necessarily fully protect against poverty, the third indicator focuses on the risk of poverty among workers (Indicator 8.3). Last, the fourth indicator considers the risk of financial exclusion – i.e. not having a bank account or having one that is overdrawn (Indicator 8.4).

For further discussion of issues raised by the indicators considered, see the section entitled “Data limitations” at the end of the chapter.

Key findings

In 2012, income was more unevenly distributed within the immigrant population than in the native-born population, especially in southern Europe.

Immigrants are twice as likely than native-born to live in households which fall within the poorest income decile and below the national poverty threshold, especially in wealthy countries where poverty is widespread, such as the United States.

Having a job affords protection against poverty, but less so among workers living in an immigrant household, who have twice the poverty rate of their native-born peers. The incidence of in-work poverty among immigrants is particularly pronounced in North America and southern Europe, where a large part of the immigrant population works in low-paid occupations.

Disparities between highly educated foreign- and native-born are even greater than among low-educated workers. In the European Union, highly educated immigrants who have jobs are three times more likely than their native-born counterparts to be poor.

In the EU15 countries in 2009, immigrants were more often excluded from banking services and, when they had a bank account, were more likely to have it overdrawn.

Section 8.1. Household income distribution

Background

Indicator

Households’ annual equivalised disposable income is calculated as the income per capita adjusted by the square root of household size.

Income is expressed in euros (EUR) at the purchasing power parity (PPP) rate. It includes earnings from labour and from capital before accounting for income tax, social contributions, in-kind services provided by governments and other entities, consumption taxes, and imputed income flows resulting from home ownership. The median income (fifth decile, D5) divides households into two halves: one half receives less and the other more than the median. One-tenth of the population has an income lower than the first decile (D1) and one-tenth an income higher than the ninth decile (D9). The ratio between those two deciles is an indicator of income inequality.

Coverage

People aged 15 years and above who live in an ordinary housing. The household’s annual equivalised income is attributed to each individual member.

In 2012, the median income of immigrant households averaged around EUR 17 000 per capita in the OECD and EUR 15 000 in the European Union. It is 13% lower than in native-born households in the European Union and 17% lower in the OECD. The sole exception is Bulgaria where immigrant incomes are one-third higher than those of the native-born. The median equivalised income of immigrants ranges from around EUR 7 000 in Latvia and Greece to more than EUR 23 000 in Canada and Luxembourg.

As for inequality within countries between foreign- and native-born incomes, it is particularly pronounced in the United States and many European countries, but less so in Germany, Switzerland, and central and eastern Europe (Figure 8.A1.1). The situation is particularly egregious in Greece, where immigrants’ income is only slightly more than half that of the native-born, itself already well below average. And, although the gap is less glaring, immigrant households’ median incomes are lower than in native-born households even in countries with longstanding skilled labour migration, such as Australia and Canada.

Income inequalities within the immigrant population also tend to be wider than among the native-born population. Immigrants in the EU’s richest decile boast nearly four times the income of their peers in the poorest decile, compared to the factor of 3.5 which separates the richest native-born from the poorest. In countries where there are acute income inequalities across the entire population, they are even wider among immigrants. In the United States, the highest level of income inequality in the OECD, the inter-decile ratio is nearly 7 among immigrants and 6.5 among the native-born (Figure 8.1).

Income disparities among immigrants are also stark in Spain and Denmark, where they are twice as high as among native-born. In fact, Spain is the country where income inequality among immigrants is at its most acute, while the low levels of income inequality in Denmark among the native-born are in sharp contrast to the marked inequality among the foreign-born. On the other hand, in Israel, where inequalities are pronounced, immigrants are, on the whole, better off than the native-born.

In the OECD, 16% of immigrants fall into the lowest income decile, a proportion that is slightly higher within the European Union. The situation is particularly striking in Belgium, Finland and in the Czech Republic, where a quarter of the immigrant population is in the poorest decile (Figure 8.2). France and the Netherlands also come close to that proportion. At the same time, with 6%, immigrants are underrepresented among households in the highest income decile, except in Bulgaria, Hungary and Portugal.

Figure 8.1. Income distribution by household immigration status, 2012

StatLink  http://dx.doi.org/10.1787/888933212786

Figure 8.2. Share of persons aged 16 and older living in an immigrant household in the lowest and highest deciles, 2012

Percentages

StatLink  http://dx.doi.org/10.1787/888933212794

Notes and sources are to be found at the end of the chapter.

Section 8.2. Poverty

Background

Indicator

The relative poverty rate is the proportion of individuals living below the poverty threshold. According to the Eurostat definition used here, the poverty threshold is 60% of the median equivalised disposable income in each country (see definition of “equivalised income” in Indicator 8.1).

Coverage

All persons aged 15 years and over living in ordinary housing. The household annual equivalised income is attributed to each individual.

On average in 2012, one-third of the members of immigrant households live in relative poverty. The relative poverty rate is lowest among foreign-born persons in Hungary and Bulgaria, where less than one immigrant in seven is poor. With the exception of these two countries and Israel, immigrants are more likely than the native-born to be poor. Disparities in poverty levels are relatively low in the countries of Oceania, Poland and Germany. On the other hand, the immigrant relative poverty rate is more than twice that of the native-born in France and the Nordic countries, notably Finland, where 40% of immigrants are poor (Table 8.1). In Belgium and Luxembourg, the foreign-born are three times as likely to be poor as their native-born counterparts.

More than one-third of the foreign-born are poor in the United States, compared with one in four of the native-born. The situation is similar in the southern European countries of recent immigration (Greece, Spain and Italy), where nearly 40% of immigrants are poor, compared with 20% of the native-born. In those countries, a substantial share of the immigrant population is employed in unskilled and low-paid jobs. In central Europe, where the proportion of poor households is also high, but where the median income is much lower, poverty gaps between immigrants and native-born are less visible. A quarter of immigrants in those countries relatively live in poverty, compared with a fifth of the native-born.

The poverty gaps between immigrants and the native-born in the countries of western Europe reflect inequalities between the two groups that are wider in those countries than in the rest of Europe. They do not mean, however, that absolute poverty is worse in western Europe. In fact, as the concept of “relative poverty” is a function of the median income in each country, it can be associated with widely differing levels of material well-being. The poorest 10% of people living in Luxembourg, for example, have an income level that exceeds the overall median income in half the other OECD and EU countries (Figure 8.A1.1).

Table 8.1. Relative poverty rates by household immigration status in the population aged 16 and older, 2012
Percentages
| Individuals living in an immigrant household | Individuals living in a native-born household | Ratio to the native-born households
Australia | 29.2 | 21.5 | 1.4
Austria | 27.6 | 13.9 | 2.0
Belgium | 39.1 | 13.0 | 3.0
Bulgaria | 13.0 | 21.9 | 0.6
Canada | 30.1 | 21.6 | 1.4
Croatia | 27.0 | 20.6 | 1.3
Cyprus1,2 | 34.0 | 15.6 | 2.2
Czech Republic | 24.6 | 10.3 | 2.4
Denmark | 31.6 | 14.1 | 2.2
Estonia | 29.7 | 18.8 | 1.6
Finland | 38.1 | 14.9 | 2.6
France | 30.4 | 12.5 | 2.4
Germany | 20.8 | 15.4 | 1.4
Greece | 44.8 | 20.3 | 2.2
Hungary | 10.2 | 13.4 | 0.8
Iceland | 23.9 | 9.5 | 2.5
Ireland | 21.4 | 15.9 | 1.3
Israel* | 23.1 | 25.0 | 0.9
Italy | 35.2 | 18.7 | 1.9
Latvia | 23.4 | 20.0 | 1.2
Lithuania | 24.4 | 18.9 | 1.3
Luxembourg | 26.1 | 8.1 | 3.2
Netherlands | 25.7 | 10.2 | 2.5
New Zealand | 25.3 | 18.7 | 1.4
Norway | 25.5 | 11.2 | 2.3
Poland | 27.4 | 17.7 | 1.5
Portugal | 22.6 | 17.7 | 1.3
Slovenia | 27.3 | 13.7 | 2.0
Spain | 39.9 | 19.1 | 2.1
Sweden | 26.8 | 15.4 | 1.7
Switzerland | 23.9 | 14.9 | 1.6
United Kingdom | 26.1 | 16.2 | 1.6
United States | 37.3 | 23.4 | 1.6
EU total (28) | 29.6 | 16.3 | 1.8
OECD total (29) | 32.9 | 18.8 | 1.8
StatLink  http://dx.doi.org/10.1787/888933214187

Notes and sources are to be found at the end of the chapter.

Section 8.3. In-work poverty

Background

Indicator

The indicator that this section considers is the relative poverty rate among people in employment (see the definition of the relative poverty rate in Indicator 8.2. Earnings from work are the main source of disposable income for most of the population. Although employment helps to reduce the risk of poverty, it is not always enough to fully protect individuals from poverty, especially if they have dependent children.

Coverage

People aged 16 years and older living in an ordinary housing who have been in employment for at least seven months of the year. The household annual equivalised income is attributed to each individual.

In all countries, having a job offers protection against poverty. Indeed, the relative poverty rate among immigrant workers was 11 percentage points lower, on average, than among all immigrants in 2012. Yet one immigrant worker in five is poor. Proportions are especially high in Canada, the United States, and southern Europe (except Portugal), where immigrants are concentrated in low-skilled, low-paid occupations. In Canada, then, and in Greece and Italy, about one immigrant worker in three is poor (Table 8.2). By contrast, fewer than 10% of workers in most central and eastern European countries and Israel are poor. In Israel, the relative poverty rate among immigrant workers is actually lower by a third than that for the native-born workers.

Having a job tends to afford immigrants less protection than the native-born against poverty. While the relative poverty rate among immigrant workers is 40% lower than that among immigrants as a whole, it is 50% lower among native-born workers.

For the same levels of educational attainment, the share of working poor is consistently higher among the foreign- than the native-born. An invidious example is Cyprus,1, 2 where it is nearly 50% among low-educated immigrant workers, compared with 13% among their native-born counterparts (Figure 8.A1.2). Immigrant in-work relative poverty rates are also especially higher in southern Europe, Slovenia, and Luxembourg, where immigrants with low levels of education tend to be more highly concentrated than the native-born in the lowest-paid jobs. By contrast, in Germany and the Netherlands, many low-educated native- and foreign-born workers are in occupations which are relatively well paid, and both groups can rely on employment to avoid poverty. In Israel the situation is unique in that jobs afford low-educated native-born less protection against poverty – their relative poverty rate is 20 percentage points higher than that of their immigrant peers with low levels of educational attainment.

In all countries, highly educated immigrant workers are better protected against poverty than their low-educated peers. However, they are still more likely to be poor than the highly educated native-born. On average across the OECD, highly educated immigrant workers are twice as likely to be poor as their native-born counterparts (and three times as likely in the European Union). In fact, the disparity is wider than among low- educated workers (Figure 8.3).

Highly educated immigrants often find themselves shunted into jobs that pay less than their qualifications entitle them to expect (see Indicator 6.4). Poverty differentials are greater among highly educated workers in nearly all countries, especially in Italy and Greece. The only exceptions are Ireland, Slovenia and Croatia, where high levels of educational attainment sharply reduce relative poverty rates among immigrant and native-born workers alike. In Israel, the relative poverty rate among highly educated workers is the same, regardless of origin.

Table 8.2. In-work relative poverty rates by household immigration status among 16-64 year-olds, 2012
Percentages
| Individuals living in an immigrant household | Ratio to the native-born households
Australia | 11.9 | 1.3
Austria | 19.8 | 2.5
Belgium | 16.7 | 5.3
Canada | 29.6 | 1.5
Croatia | 9.0 | 1.5
Cyprus1, 2 | 29.2 | 4.5
Czech Republic | 16.3 | 3.3
Denmark | 16.1 | 2.7
Estonia | 14.9 | 1.8
Finland | 15.9 | 4.2
France | 21.8 | 2.8
Germany | 10.6 | 1.3
Greece | 32.4 | 2.4
Hungary | 7.3 | 1.3
Iceland | 16.6 | 2.5
Ireland | 10.3 | 2.1
Israel* | 9.1 | 0.7
Italy | 29.0 | 2.7
Latvia | 9.5 | 1.0
Lithuania | 9.4 | 1.2
Luxembourg | 20.4 | 3.5
Netherlands | 9.7 | 1.9
New Zealand | 12.2 | 2.1
Norway | 17.3 | 3.1
Portugal | 14.1 | 1.4
Slovenia | 21.7 | 3.8
Spain | 25.1 | 2.3
Sweden | 15.9 | 2.2
Switzerland | 14.9 | 2.1
United Kingdom | 14.8 | 1.7
United States | 25.5 | 2.2
EU total (28) | 18.8 | 2.1
OECD total (26) | 22.3 | 2.2
StatLink  http://dx.doi.org/10.1787/888933214199

Figure 8.3. Ratio of foreign-born in-work relative poverty rates to native-born 16-64 year-olds, by educational level, 2012

StatLink  http://dx.doi.org/10.1787/888933212805

Notes and sources are to be found at the end of the chapter.

Section 8.4. Financial exclusion

Background

Indicator

As many financial flows in developed countries are handled through financial institutions and banks, not having a bank account is an obstacle to economic integration. By the same token, financial exclusion is an important indicator of economic integration. It has two dimensions and sheds light on the difficulties encountered by households in their dealings with financial institutions: they may not have a bank account or, when they have one, it may be overdrawn. Data on financial exclusion are available only for EEA countries.

Coverage

All households with at least one responsible person over the age of 15.

In the European Union in 2008, nine households in ten had a bank account in both immigrant and native-born households. Significant shares of households without a bank account are found only in central, eastern and southern Europe and Ireland. It is also in those countries – where the banking system does not cover all native-born – that disparities between the foreign- and native-born are widest. The most glaring example is Greece, the only country where most of the population has no bank account. Whereas 28% of households with at least one person born in the country have a bank account, the figure for immigrants is about half that. Most other countries with low banking coverage are in central and eastern Europe and have few foreign-born residents (Figure 8.4).

However, even when households do have a bank account, they are not necessarily immune to financial exclusion, particularly when their accounts are overdrawn. Across the European Union, 14% of immigrant households with a bank account overdraw, compared with 11% among the native-born (Figure 8.5). In most countries, in fact, immigrant households with a bank account have higher overdraft rates, with Slovenia showing the highest incidence – a third of immigrant households are overdrawn. That rate should be seen in the context of a high overdraft incidence even among native-born households, a quarter of which overdraw on their accounts. In Germany, on the other hand, where the overdraft rate among the native-born is the second highest in Europe, immigrants are much less likely than native-born to be overdrawn.

In most other countries with significant foreign-born populations, however, immigrant households overdraw on their accounts more often than their native-born counterparts. In Portugal, where overdrafts are rare, they do so four times more, while in Austria, Belgium and in the Netherlands, they are twice as likely to overdraw as native-born.

Figure 8.4. Share of households with a bank account, by immigration status, 2008

StatLink  http://dx.doi.org/10.1787/888933212815

Figure 8.5. Share of households with at least one overdrawn bank account, among households with at least one bank account, by immigration status, 2008

StatLink  http://dx.doi.org/10.1787/888933212821

Notes and sources are to be found at the end of the chapter.

Data limitations

Household income

The income data used here come from surveys which rely on self-reporting. Data on households’ assets (be they financial, property, or material assets) are not available.

The level of income is surveyed at the household level. Household expenses – e.g. rents and expenditure on children – do not grow proportionately with the number of members. To assess total disposable income in a household, it should be adjusted for the size of the household by dividing at a rate that is lower than the number of household members. There are two ways to do that. The first divides income by the square root of household size (see “Background” to Indicator 8.1). The second method factors in the size and the makeup of the household. In that case, household income is divided by the “equivalent household size”, which attributes a weight of 1 to the first adult, 0.5 to any other household member aged 14 and older, and 0.3 to each child under the age of 14. The two methods yield similar results, but the first one has been selected here.

The sources used for this indicator are drawn chiefly from panel surveys. Newly arrived immigrants are not included in surveys unless they join a household that has previously been surveyed or when a panel is renewed. Panel surveys consequently underestimate recently arrived migrants. The EU-SILC panel is fully renewed every four years and the United States Current Population Survey panel every two years. The longer the panel renewal process takes, the more distorted the results will be.

Poverty

The relative poverty rate indicator presented here is the proportion of persons living below the poverty threshold, defined as 60% of a country’s median income. The relative poverty rate indicator fails to account for income differences between countries. It does not measure the nonfinancial dimensions of poverty, such as material deprivation.

In-work poverty

This indicator in effect compares a worker’s occupational situation with the income of the household to which he or she belongs. The worker’s equivalised income therefore depends both on his or her individual earnings and those of other household members. A worker whose personal earnings exceed the poverty threshold, but who lives with a spouse and/or children with no income, may then be considered as in in-work poverty, or belonging to the working poor.

Financial exclusion

The actual importance of having an overdrawn bank account depends on the household’s level of indebtedness. However, this information is not available.

Notes, sources, and further reading

Note to Israel

* Information on data concerning Israel: http://dx.doi.org/10.1787/888932315602.

Notes to Cyprus1, 2

1. Note by Turkey:

The information in this document with reference to “Cyprus” relates to the southern part of the island. There is no single authority representing both Turkish and Greek Cypriot people on the island. Turkey recognises the Turkish Republic of North Cyprus (TRNC). Until a lasting and equitable solution is found within the context of the United Nations, Turkey shall preserve its position on the “Cyprus issue”.

2. Note by all the European Union Member States of the OECD and the European Union:

The Republic of Cyprus is recognised by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus.

Notes to tables and figures

Figure 8.2: A decile represents 10% of the total population. If the proportion of the immigrant population in the first decile is greater than 10%, it is overrepresented in low incomes. If, however, that proportion in the last decile is greater than 10%, then it is overrepresented in high incomes.

Figures and tables for Indicator 8.3: For Israel, a worker is a person in employment at the time of the survey. Australia, Canada and New Zealand are not included in the OECD average.

Averages factor in rates that cannot be published individually because samples are too small.

Sources of tables and figures

European Union Statistics on Income and Living Conditions (EU-SILC) 2012.

Australian Census on Population and Housing 2011.

Canada: National Household Survey (NHS) 2011.

United States: Current Population Survey (CPS) 2012.

Israeli Integrated Household Survey 2011.

New Zealand: Household Economic Survey (HES) 2013.

Indicator 8.4: Ad hoc module of European Union Statistics on Income and Living Conditions (EU-SILC) 2008.

Further reading

Eurostat (2013), Household Composition, Poverty and Hardship across Europe, European Commission, Luxembourg.

Eurostat (2011), “Migrants in Europe: A Statistical Portrait of the First and Second Generation”, Statistical Books, European Commission, Luxembourg.

OECD (2014), Society at a Glance 2014: OECD Social Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/soc_glance-2014-en.

OECD (2012), Settling In: OECD Indicators of Immigrant Integration 2012, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264171534-en.

OECD (2011), Divided We Stand: Why Inequality Keeps Rising, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264119536-en.

OECD (2009), “Is Work the Best Antidote to Poverty?”, Chapter 3 of OECD Employment Outlook 2009, OECD Publishing, Paris, http://dx.doi.org/10.1787/empl_outlook-2009-4-en.

Annexe 8.A1.

Additional tables and figures

Figure 8.A1.1. Distribution of annual equivalised disposable income by household immigration status, 2012

EUR in 2011 current prices

1, 2: See “Notes, sources, and further reading” section.

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: European Union Statistics on Income and Living Conditions (EU-SILC) 2012. Australian Census on Population and Housing 2011. Canada: National Household Survey (NHS) 2011. United States: Current Population Survey (CPS) 2012. Israeli Integrated Household Survey 2011. New Zealand: Household Economic Survey (HES) 2013.

StatLink  http://dx.doi.org/10.1787/888933212832

Figure 8.A1.2. Relative poverty rate among low-educated workers aged 16-64 by household immigration status, 2012

Percentages

Note: For Israel, a worker is a person in employment at the time of the survey. Australia, Canada and New Zealand are not included in the OECD average.

1, 2: See “Notes, sources, and further reading” section.

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: European Union Statistics on Income and Living Conditions (EU-SILC) 2012. Australian Census on Population and Housing 2011. Canada: National Household Survey (NHS) 2011. United States: Current Population Survey (CPS) 2012. Israeli Integrated Household Survey 2011. New Zealand: Household Economic Survey (HES) 2013.

StatLink  http://dx.doi.org/10.1787/888933212840

Chapter 9.

Immigrants and housing

Housing conditions depend on such circumstances as financial resources and family size. Immigrants’ housing conditions, too, are very much dictated by circumstances, including the category of entry to which they belong.

Migrants who arrive to join their family benefit, in theory, from already having suitable accommodation on arrival, since the requirements governing family reunification in most countries set minimum thresholds for resources, space, and/or number of rooms. Those who arrive in other circumstances, by contrast, may have neither the money to rent nor the time to find decent accommodation. Market forces – property prices and the standard of housing available at those prices – indeed restrict the choice of accommodation available to immigrants who on average have lower incomes. A further risk to which immigrants are more exposed is that of finding themselves in substandard housing – partly because they are often less informed about the rental market and partly because it is harder for them to borrow money. They may also be discriminated against by landlords. Social housing and housing benefits may be the way into bigger homes of a higher standard, but immigrant households in need may not necessarily be eligible to such assistance and applications can take a long time to process before new arrivals can move in.

This chapter considers four housing indicators: housing tenure (Indicator 9.1), the share of overcrowded housing (Indicator 9.2), and more global housing conditions (Indicator 9.3), as well as housing costs (Indicator 9.4). The section entitled “Data limitations” at the end of the chapter discusses some of the issues raised by these indicators.

Key findings

In 2012, OECD-wide, immigrants were on average less likely to own their homes than the native-born population – 46% versus 67% – even at comparable age and income levels.

In half of all countries, they are not more likely than native-born to live in low-rent housing.

With the exception of central Europe, immigrants are slightly more likely to live in substandard housing. They are twice as likely to be in overcrowded accommodation.

In the European Union in 2009, immigrants were slightly more likely to live in deprived neighbourhoods than the native-born, except in the United Kingdom, Ireland, Spain, Italy and Luxembourg.

In 2012, extreme overcrowding – defined as living in a dwelling needing two extra rooms – affected immigrants almost as much as the native-born in most EU countries, but was a problem largely specific to immigrants in the United States, Austria and Italy.

When renting at market rates, immigrant households live in housing conditions that are poorer than among native-born households.

A quarter of immigrants – compared to a fifth of the native-born population – are under pressure from the cost of housing relative to their income. Housing subsidies do not significantly offset that inequality, except in Norway, Finland, Netherlands and France.

Section 9.1. Housing tenure

Background

Indicator

Tenure is generally disaggregated into three kinds: owner occupancy, tenancy, and free occupancy. In most European countries, tenants rent at market or reduced rates (social housing, employer-subsidised housing, or housing whose rent is set by law). There is no such distinction in Denmark, the Netherlands, the United States, Australia or New Zealand. Low-rent housing does not include accommodation rented at market rates by tenants who receive housing benefit. No information is available on immigrants living in accommodation free of charge in Denmark, Norway and Sweden.

Coverage

Households living in ordinary housing (see “Data limitations”) in which at least one responsible person is aged 16 years of age or over.

Throughout the OECD area, immigrant households are less likely to own their homes than households in which at least one member was born in the host country. In 2012, 46% of immigrant households owned their homes, compared to 67% of the native-born. This figure falls to 39% of immigrants in the European Union. Immigrants have higher rates of home ownership in the Baltic countries, central Europe, and settlement countries, where disparities with the native-born are relatively small. In Estonia, immigrants are actually more likely to own their homes than their native-born counterparts.

In the EU15 countries and in Switzerland, however, immigrants have lower rates of property ownership than natives. The gap in ownership rates is widest in countries where immigration is recent such as Ireland, Italy, Spain and Greece (Figure 9.1). Indeed, in Ireland and Italy, just one quarter of immigrant households own their homes, whereas three-quarters of native-born households do. Adversely, in Germany, although immigrants are slightly less likely to own their home than the native-born, the gap is one of the lowest in the OECD.

Immigrants are less likely to own their homes because they are, on average, younger and earn less. Gaps in ownership rates between the foreign- and native-born narrow after adjusting for the age of the head of household and household income. Nevertheless, age and income account for only 15% of the gap, which remains wide. Unequal access to property ownership would therefore seem attributable to other factors. One is the time spent in the host country – the longer it is, the more likely the immigrant is to want to build or buy a home. Moreover, it takes time to accumulate enough savings to obtain a mortgage, a frequent prerequisite to buying property. Other non-observable factors, such as personal preferences and the choice to live in immigrant communities, may lead to immigrants living in the kind of areas that affords little access to ownership (social housing, for instance), thereby further contributing to the relatively low rate of immigrant property ownership.

With their relatively low rates of property ownership, immigrant households are overrepresented in tenancy. Yet, despite a lower average income, they are less likely to benefit from low-rent housing than native-born households (Figure 9.2). In the countries under review, the proportion of immigrants living in subsidised housing is, on average, 5 percentage points lower than among native-born households. They are underrepresented in reduced-rate accommodation in two-thirds of the countries, with gaps of over 20 percentage points in Ireland, Portugal, and Spain. The reverse is true in Finland and Croatia, where immigrants are overrepresented, as they are in Germany and, to a lesser extent, in Canada. In France, Switzerland, and Belgium, there is no difference between the proportions of immigrants and the native-born living in low-rent housing.

Figure 9.1. Home ownership rate by household migration status, 2012

Percentage of all households

StatLink  http://dx.doi.org/10.1787/888933212856

Figure 9.2. Households renting at a reduced rate among tenant immigrant households, 2012

Difference in percentage points with native-born households

StatLink  http://dx.doi.org/10.1787/888933212861

Notes and sources are to be found at the end of the chapter.

Section 9.2. Overcrowded housing

Background

Indicator

A dwelling is considered to be overcrowded if the number of rooms is less than the sum of one living room for the household, one room for the couple responsible for the dwelling (or two rooms if the two people responsible do not form a couple), one room for every two additional adults (people aged 18 and over), and one room for every two children. Canada and New Zealand use a different definition of overcrowding (see “Data limitations” at the end of chapter).

Housing qualifies as extremely overcrowded if the number of rooms is at least two rooms less than the number required by the household. People living alone and childless couples cannot be affected by extreme overcrowding, since by definition such households need no more than two rooms. The extreme overcrowding indicator therefore excludes the two categories.

Coverage

People aged 16 years of age and over living in ordinary housing. People living alone and childless couples are, by definition, excluded from the calculation of extreme overcrowding.

In 2012, an average of 19% of adults in an immigrant household in an OECD country lived in overcrowded conditions, compared to 8% of the native-born. In the European Union, the share of overcrowded immigrant homes was lower at 16%.

Overcrowding is very rare in the Netherlands, Ireland, Belgium and Canada regardless of migration status. By contrast, it affects over four immigrants out of ten in Bulgaria, Greece and Italy. In most countries, immigrants are at least twice as likely to live in overcrowded homes as the native-born. Slovenia, Austria and the United States also show sharp disparities in the overcrowding rates experienced by immigrants and the native-born. In those countries, over a quarter of immigrants live in overcrowded accommodation, compared to about 7% among the native-born (Figure 9.3). In Israel, on the other hand, immigrant households are only a third as likely to be overcrowded as native-born households.

In all the countries covered, overcrowding is far more frequent if the household is a tenancy, and especially if it rents at the market rate. The issue is even starker among immigrant households, as those immigrant households renting at market rates in the European Union and the United States are respectively 10 and 25 percentage points more likely than native-born households to live in overcrowded conditions (Figure 9.4). Immigrant households are heavily overrepresented in overcrowded housing at market rate in the recent immigration countries of southern Europe (apart from Spain), Austria, Norway and the United States. In contrast, immigrants are equally or less affected by overcrowding in a handful of countries, namely Latvia, Israel, the Netherlands and Ireland, where the problem itself is generally scarce. Indeed, countries where overcrowding is low in the population at large, it is also low among immigrants.

A non-negligible share of overcrowded households consists of people living alone and childless couples in single-room homes who have no living space except their bedrooms. However, the most extreme examples are families with children and households of more than three adults. On average, 8% of such households in the OECD and 5% in the European Union live in extremely overcrowded conditions (Figure 9.3). In most European countries, that type of overcrowding is as almost as common among the native-born as it is among immigrants. However, extreme overcrowding particularly affects four times as many immigrant as native-born households in the United States, Italy and Slovenia. The situation in Austria is also worrying, with one in ten immigrant households versus less than 1 in 200 native ones affected by extreme overcrowding.

Figure 9.3. People aged 16 and over living in overcrowded dwellings, by household migration status and level of overcrowding, 2012

Percentages

StatLink  http://dx.doi.org/10.1787/888933212870

Figure 9.4. People aged 16 and over living in overcrowded dwellings among tenant immigrant households renting at market rate, 2012

Difference in percentage points with native-born households

StatLink  http://dx.doi.org/10.1787/888933212882

Notes and sources are to be found at the end of the chapter.

Section 9.3. Housing conditions

Background

Indicator

Housing conditions are one dimension of well-being. They encompass a range of different criteria which include, in addition to the overcrowding rate (see Indicator 9.2), standards of housing and the deprivation in the neighbourhood.

Housing quality is assessed against various yardsticks. It is described as deprived or substandard if the accommodation is too dark, if it does not have exclusive access to a bathroom (bath- or shower-room and flushing lavatory), or if the roof leaks. No comparable information on housing quality is available for OECD countries outside Europe.

The external environment is also part of residential well-being. Dilapidated surroundings can undermine a neighbourhood’s reputation, which will over time indirectly affect, among other things, education and employment opportunities. Neighbourhoods are classified as dilapidated if waste is commonly seen in the street and if public facilities are damaged. No comparable information on neighbourhood dilapidation is available for OECD countries outside Europe.

Sample

People aged 16 years old or over living in ordinary housing.

Across all countries in 2012, an average of less than one household in ten, regardless of origin, lived in poor-quality housing. Indeed – apart from Ireland, and some central and eastern European countries – the share of the total population living in poor-quality housing was less than 15% (Figure 9.5). Fewer immigrants than native-born live in deprived housings in a number of countries in central Europe, although immigrants are twice as likely to live in deprived conditions as the native-born in Poland. Housing is generally of better quality elsewhere in Europe, but immigrant households are generally more likely to have to contend with housing conditions that are of an inferior standard to those of the native-born. The gap is especially wide in Iceland and Italy. Across the European Union, an average of 30% of immigrants live in accommodation that is overcrowded or of poor quality, compared to 20% of the native-born (Figure 9.A1.1).

Few people live in housing that is both overcrowded and of poor quality, though immigrants do so in slightly higher proportions than the native-born. In Italy, Slovenia and Poland, immigrants are at least 5 percentage points more likely than the native-born to live in such housing. Furthermore, immigrants renting at market rates are overrepresented in housing that falls into both categories in three-quarters of the countries reviewed (Figure 9.6), particularly in the Czech Republic, Slovenia, Austria and Portugal. However, in Denmark immigrants are less likely than the native-born to live in housing that is both overcrowded and substandard.

In the vast majority of countries in 2009, immigrants are overrepresented in run-down neighbourhoods. In Hungary, the Slovak Republic and in Portugal, over one in three immigrants live in that kind of environment (Figure 9.A1.2). Alongside Belgium and France, the Slovak Republic and Portugal are the ones where immigrants are most overrepresented in deprived neighbourhoods. By contrast, in a handful of countries with high immigrant populations (Spain, Luxembourg, Italy, Ireland and the United Kingdom), immigrants are less likely to live in dilapidated neighbourhoods than the native-born.

Figure 9.5. Share of people aged 16 and over living in substandard housing by household migration status, 2012

Percentages

StatLink  http://dx.doi.org/10.1787/888933212899

Figure 9.6. Share of people aged 16 and over living in overcrowded, substandard housing rented at the market rate, by household migration status, 2012

Difference in percentage points between immigrant and native-born households

StatLink  http://dx.doi.org/10.1787/888933212900

Notes and sources are to be found at the end of the chapter.

Section 9.4. Housing cost overburden

Background

Indicator

The housing cost overburden rate is the percentage of households that spend over 40% of their disposable income on rent. After housing subsidies have been taken into account, the result is the net overburden rate. This indicator is calculated only for tenant households that rent their home.

No information on housing subsidies is available for non-European OECD countries.

Sample

Tenant households living in ordinary housing in which at least one responsible person is 16 or over.

In almost all countries in 2012, immigrant households were more likely to be overburdened by housing costs than native-born households. Across all OECD countries, 27% of immigrants were in that situation, compared to 20% of the native-born. The figures were lower in the European Union, where only 25% of immigrants and 15% of the native-born population were overburdened by housing costs (Figure 9.7).

The pressure of rent on income in immigrant households is strongest in southern Europe (especially Spain and Portugal), the United States, the Czech Republic and Norway, where over one-third of immigrant households pay rent that exceeds 40% of their income. On the other hand, in a large number of settlement countries (Australia and Canada), as well as in Latvia and Croatia, just one-tenth of immigrants are overburdened by housing costs. In Germany and Switzerland, immigrants and the native-born are similarly affected by the rent burden, while in Croatia, Latvia, Ireland and Sweden, immigrants are slightly less so. On the other hand, they are noticeably more likely to spend in excess of 40% of their income on rent in the southern European countries of Spain, Italy and, especially, Portugal where there is a 24 percentage point gap with the native-born. In most other countries, the housing cost overburden gap between immigrants and the native-born is close to the OECD average of 6 points.

Housing subsidies can be one way of plugging the gap in the housing cost overburden rate between immigrants and the native-born. Yet, in most countries, such support makes no substantial difference (Figure 9.8), though in Norway and Finland, the gap disappears. Differences between immigrant and native-born households in the Netherlands and France, too, are greatly diminished after factoring in housing subsidies. There are a few countries, by contrast, in which the native-born receive significantly more housing subsidies than immigrants, which further compounds inequality between the two groups. The disparity is most visible in the Czech Republic, where the gap in the overburden rate – already high at 11 points – rises to 14 after factoring in housing subsidies.

In some countries, such as Spain, Belgium and the Netherlands, immigrant households find financial overburdening to be a greater problem than overcrowding, which is a relatively minor issue (Figure 9.9). The opposite is true of Italy, Greece, Slovenia, Latvia and Austria, where immigrants often live in overcrowded accommodation, but where rent is more commensurate with income. In many other countries, though, financial overburdening and overcrowding go together.

Figure 9.7. Gross rates of housing cost overburden among tenants, 2012

StatLink  http://dx.doi.org/10.1787/888933212912

Figure 9.8. Tenant households' housing cost overburden rates, before and after adjustment for housing subsidies, 2012

Difference in percentage points between immigrant and native-born households

StatLink  http://dx.doi.org/10.1787/888933212924

Figure 9.9. Overcrowding and housing overburden rates among immigrant tenant households, 2012

StatLink  http://dx.doi.org/10.1787/888933212939

Notes and sources are to be found at the end of the chapter.

Data limitations

The absence of housing surveys in many countries makes it hard to measure residential integration. Some research, however, provides information on housing conditions, although it gathers information only from people living in so-called “ordinary” housing. The data presented therefore exclude the homeless and people living in collective accommodation, such as hostels, retirement homes, barracks, camps, hospitals, and prisons.

Tenure status

Tenure is partly determined by people’s individual choices. It does, however, yield indications as to the ability and desire to settle in the host country (in the event of access to ownership) and the financial resources available.

Overcrowded housing

There are different grounds for describing accommodation as overcrowded. It can be because occupants perceive their own living space to be small by asking such precise questions as: “Do you think that your home is too small?”. Since that approach depends largely on respondents’ subjective views, it has not been used here. Another method is to calculate the floor area per inhabitant (occupants aged under 12 are often counted as 0.5 people). Although that approach draws on more precise information, it is still difficult to apply because, in many cases, information on the size of the accommodation is unavailable.

The definition of overcrowding used here is based on Eurostat’s. It takes into account the number of rooms, the number of adults cohabiting and not cohabiting, and the age and sex of children. Some sources do not divulge the relationships between adults (apart from those responsible for the household) or the ages of the children. The definition used here has been adjusted accordingly, and all occupants, including the people responsible, are considered able to share a room with one other person, even though – compared to the Eurostat definition – that entails underestimating family overcrowding rates and complex households. Country rankings remain similar, however.

Canada and New Zealand use the Canadian definition of overcrowding, which has not been adapted therefore underestimated overcrowding rates in those countries. However, because it is based on the number of bedrooms and not the total number of living areas, it also lessens the incidence of overcrowding as defined by European data, especially in single-room accommodation. According to Eurostat’s definition, single-room housing is necessarily overcrowded (since there is no living room), whereas in Canada and New Zealand it is not, since its sole constituent room would be considered as a bedroom. Comparisons between these two countries and others should therefore be made with caution.

Housing conditions

Many of the material properties of a dwelling can be used to assess its quality. Ideally, this indicator should be calculated from a set of requirements for comfortable accommodation: construction materials, mains electricity, ventilation, heating, clean running water, drainage, kitchen, lighting, washing facilities, weather-proofing, and so on. In a large number of countries, however, only the last three criteria are considered.

A home’s surroundings are equally important to well-being, although information about neighbourhoods is rarely available from general surveys. The information presented here is based on a handful of criteria relating to neighbourhood dilapidation from the 2009 ad hoc module of the European Union’s Statistics on Income and Living Conditions survey (EU-SILC). There are no comparable data on non-European countries. Here again, a residential neighbourhood’s level of dilapidation can be assessed in different ways, including exposure to noise, pollution levels, feeling unsafe, cleanliness, and damage to facilities. EU-SILC supplies only the last two criteria. Well-being derived from the neighbourhood can also be estimated by measuring access to, for instance, public services, public transport, and shops.

Housing costs

The financial aspects of housing considered here focus on the affordability ratio, i.e. the share of income spent on “paying” for accommodation (see Chapter 8 for a definition of income). Payment may be mortgage repayments for homeowners or rental payments for tenants, possibly including building management fees. Since few surveys propose data on mortgage repayments, this indicator refers to tenants only. If the affordability ratio is over 40% of available income, the household is deemed to be at considerable risk of falling into debt and arrears. People in this situation are said to be “housing cost overburdened”.

The affordability ratio and the resulting overburden rate are considered to be net if housing subsidies are deducted from the cost of the accommodation. The net rate gives a more accurate impression of the real cost of housing for households, but information on housing subsidies is not available for non-European countries.

The affordability ratio and housing cost overburden indicators are tools for assessing the situation of adults living in households. They cover, therefore, only people aged sixteen or over.

Their sources are chiefly panel surveys, which can slightly distort results. The samples used in this kind of survey are representative only of the first wave and recent immigrants can be included in the survey only if they have joined a household that has previously been surveyed. Panel surveys therefore frequently underestimate the number of recent immigrants, and the longer the time between renewals, the greater the bias. The EU-SILC panel is fully renewed every five years and the CPS panel every two.

Notes, sources, and further reading

Note to Israel

* Information on data concerning Israel: http://dx.doi.org/10.1787/888932315602.

Notes to Cyprus1, 2

1. Note by Turkey:

The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Turkey recognises the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of the United Nations, Turkey shall preserve its position concerning the “Cyprus issue”.

2. Note by all the European Union Member States of the OECD and the European Union:

The Republic of Cyprus is recognised by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus.

Notes to figures and tables

Figure 9.1: The adjusted ownership rate is the rate of home ownership among immigrants if the household’s main responsible person were in the same age group as their native-born counterpart and if the income of the immigrant household were the same as that of a native-born household. A grey diamond indicates a non-significant adjustment.

Figures 9.2,  9.4 and 9.6: The grey bars show that the differences are not statistically significant at the 5% level.

Figures 9.3,  9.4 and 9.5: Total population for Canada.

Figures 9.3 and 9.4: Israel is not included in the OECD average.

Figure 9.7: Rates for the United States and Australia are calculated on the basis of total income, not disposable income. They are probably underestimated, therefore. The New Zealand rate is net and calculated on the basis of all people and not all households. New Zealand is not included in the OECD average.

Averages take into account rates that cannot be published separately because of minimal sample sizes.

In New Zealand, the responsible people are those who meet the costs of the household. In Australia, a single responsible person is considered for households which do not include a couple.

Canada and New Zealand use a definition of overcrowding based on Canada’s National Occupancy Standard (NOS). According to this standard, housing is considered overcrowded if the number of bedrooms is lower than the following minimum requirement: one per adult couple, one per single parent, one per additional adult (person aged over 18), one for every two children (people aged under 18) of the same sex, two for two children of opposite sex, and one for every two children aged under five of opposite sex. A single person is not considered to live in overcrowded accommodation if he or she lives in a single room with no bedroom.

Sources

European Union: EU Statistics on Income and Living Conditions (EU-SILC) 2012. Australian Census on Population and Housing 2011. Canadian National Household Survey (NHS) 2011. Israel: Household Expenditure Survey (HES) 2012. New Zealand: Household Economic Survey (HES) 2013. United States: American Community Survey (ACS) 2012.

Further reading

Eurostat (2011a), Housing Conditions in Europe in 2009, European Commission, Luxembourg.

Eurostat (2011b), “Migrants in Europe: A Statistical Portrait of the First and Second Generation”, Statistical Books, European Commission, Luxembourg.

OECD (2012), Settling In: OECD Indicators of Immigrant Integration 2012, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264171534-en.

Annex 9.A1.

Additional tables and figures

Figure 9.A1.1. People aged 16 and over living in overcrowded dwellings or in substandard living among tenant immigrant households renting at market rate, 2012

Difference in percentage points with native-born households

Note: The grey bars indicate that the differences are not statistically significant at 5% level.

1, 2: See “Notes, sources, and further reading” section.

Source: European Union Statistics on Income and Living Condition (EU-SILC) 2012.

StatLink  http://dx.doi.org/10.1787/888933212940

Figure 9.A1.2. Share of people aged 16 and over, living in a neighbourhood where waste is regularly left in the street and/or public facilities are often damaged, by household migration status, 2009

Percentages

1, 2: See “Notes, sources, and further reading” section.

Source: Ad hoc module of European Union Statistics on Income and Living Conditions (EU-SILC) 2009.

StatLink  http://dx.doi.org/10.1787/888933212958

Chapter 10.

Immigrants’ health status and their health care

Health is integral to wellbeing and affects the degree and manner of engagement with society as a whole. Healthier immigrants are able to work and earn more and can build broader social networks. Fuller integration in turn improves health outcomes, as immigrants increasingly have the ability to seek health care when needed.

Socio-demographic characteristics such as gender and age, participation in risky behaviour (e.g. drinking alcohol or smoking), and living and working conditions are among the most important determinants of health. As immigrants generally have to be in good health to be able to migrate, they tend to be healthier than non-migrants – the so-called “healthy migrant effect”, which fades with the length of residence, however.

The quality of life in the country of origin, the migration process itself, and working and living conditions in the host country also affect health outcomes. Some migrant groups, such as refugees, are particularly vulnerable and may be more prone to certain diseases or mental disorders. The migratory experience itself can cause stress, which may affect migrants’ health outcomes in different ways down the line, depending on socio-economic and health conditions in the home country and how well they settle in the host country. Nutritional habits in the country of origin may also affect health outcomes in the medium-to-long term. Age, educational attainment, and income, too, are important determinants of health.

This chapter analyses self-reported health (Indicator 10.1) and the lack of medical treatment (Indicator 10.2) both among immigrants and the native-born. Data-related issues are discussed in “Data limitations” at the end of this chapter.

Key findings

Seven out of ten of the over-15s in the OECD area claimed to be in good health in 2012, whether native- or foreign-born.

The similar reported overall health statuses mask differences between, on one hand, the recent immigration countries of southern Europe, where the health statuses self-reported by immigrants are significantly better than those self-reported by the native-born and, on the other hand, central European countries and longstanding immigration destinations such as France and Germany, where immigrants feel less healthy.

Adjusting for age reduces differences between the figures for immigrants and natives. The social and economic circumstances of some migrant groups – such as poor education, income, working conditions, and social integration – adversely affect their access to and use of health care services.

Approximately 7% of both immigrants and the native-born had unmet medical needs in 2012. Differences between the two groups were observed chiefly in certain central and eastern European countries, as well as in those that host large numbers of refugees, such as Sweden, where immigrants are more likely to report unmet medical needs than the native-born.

Roughly one in five of the foreign- and native-born did not see a doctor in 2009. The greatest differences between immigrants and natives were mainly in countries that had seen significant recent labour inflows, such as Iceland and Ireland, where immigrants were much less likely to have seen a doctor.

Section 10.1. Self-reported health status

Background

Indicator

A person’s self-reported health status is how they perceive their physiological and psychological health. This section looks at: 1) perceptions overall health; 2) the absence of chronic illness or health conditions, such as disabilities; and 3) a compound good health indicator that combines perceived good health and the absence of chronic illnesses or health-related limitations. Different surveys capture all three dimensions of the reported health status indicator in very different ways, which may inhibit international comparisons (see “Data limitations”). This section considers proportions of people who rate their health as “good” or better.

Immigrant outcomes are adjusted to assess what they would be if foreign-born residents had the same age structure as their native peers.

Coverage

People aged over 15 years old.

In 2012, an average of seven immigrants out of ten in OECD countries and six out of ten in the European Union responded positively in all three dimensions of the self-reported health status indicator – perception of overall good health, no chronic illnesses, and no health-related limitations. The levels were very similar to those of the native-born. In the United States, Ireland, and in the recent migration countries of southern Europe (Cyprus1, 2, Greece, Italy and Spain), more than three immigrants in four reported that they suffered in none of the three dimensions. In contrast, less than one immigrant out of four made such claims in the Baltic countries or Poland (Figure 10.1), where the immigrant populations are the oldest (see Indicator 2.2).

In southern Europe, immigrants tend to be generally healthier than their native-born counterparts. In most of those countries, recent migrants – on average younger than the rest of the population – account for a high proportion of foreign-born residents. In France and Germany, both longstanding hosts, and in a number of central and eastern European countries, immigrants are on average less likely than the native-born to report being in good health or better, with gaps of 39 percentage points in Poland and 28 in Estonia (Figure 10.1).

After adjusting for age, differences between the foreign- and native-born in self-reported health status narrow or become statistically insignificant in most countries. Indeed, in Germany and southern Europe, accounting for age makes immigrants healthier than the native-born. In Austria and Belgium, however, the gap with the native-born both widens and remains significant, while in the Baltic countries and Poland, it closes and stays significant (Figure 10.1). The differences in perceived health statuses between the foreign- and native-born populations can be attributed to factors not included in the analysis such as gender, health behaviour, country of origin, and other social and economic circumstances.

Similar patterns are observed in all three dimensions of the self-reported health status (Figures 10.2,  10.3  and 10.A1.1). Immigrants to southern Europe, for example, are significantly less likely than the domestically born to suffer from a chronic condition or health-related limitations. The same goes for Germany, where fewer immigrants report chronic health conditions (Figure 10.3). As for most other countries, differences with the native-born close after adjustment and become statistically insignificant.

Figure 10.1. Foreign- and native-born adults who report good health status or better, no health-related limitations, and no chronic health conditions, 2012

Percentages

StatLink  http://dx.doi.org/10.1787/888933212960

Figure 10.2. Foreign- and native-born adults who report they are in good health or better, 2012

Percentages

StatLink  http://dx.doi.org/10.1787/888933212979

Figure 10.3. Foreign- and native-born adults who report they do not suffer from chronic health conditions, 2012

Percentages

StatLink  http://dx.doi.org/10.1787/888933212980

Notes and sources are at the end of the chapter.

Section 10.2. Health care

Background

Indicator

This indicator measures whether, in the previous 12 months, respondents felt they had needed health care (excluding dental examination or treatment) but did not receive it, and whether they had in fact seen a doctor (either a general practitioner or specialist). Sample sizes were generally too small to permit a detailed account of the reasons for why a medical need went unmet.

Data on visits to doctors are not available in Canada and the United States, although Canada does supply comparable data on immigrants’ unmet health needs. Data from the United States, however, refer only to medical needs that went unmet for reasons of cost. They should therefore be compared to data from other countries with caution.

The indicator is adjusted for the immigrant population to assess what outcomes would be if foreign-born populations had the same age structure as the native-born.

Coverage

People aged over 15 years old.

In the OECD, an average of 7% of immigrants reported an unmet medical need in 2012, the same proportion as in the native-born population (Figure 10.4). In the EU, foreign-born residents reported unmet medical needs slightly less often than their native counterparts (6% versus 7%). Proportions were similar between the two groups (Figure 10.5) when it came to reports of seeing a doctor – 21% of immigrants had not seen one in 2009, compared to 19% of the native-born.

Immigrants in central and eastern Europe, as well as in Scandinavia, were the most likely to report unmet needs – 24% in Poland and 15% in Sweden and in Estonia. The least likely were those in Slovenia, the Netherlands, and Austria, where levels were all below 2%. Differences in the prevalence of unmet needs between the foreign-born and the native-born were widest in central and eastern Europe and in countries that host a large number of refugees. The foreign-born were 5.5 percentage points more likely to have unmet needs than the native-born in Estonia, 4 points more in Sweden, and 2 points in Switzerland (Figure 10.4). As with the native-born, 8% of immigrants in the United States said they had let a medical need go unmet as a result of cost alone. However, immigrants in few other countries – notably Iceland, Canada, and Germany – were less likely than the native-born to report unmet medical needs.

The incidence of immigrants not having seen a doctor in 2009 was highest in recent labour migration destinations, such as Iceland (44%), Ireland and Cyprus1, 2 (36% each), while it was lowest in France (7%), Luxembourg (7%), and Poland (8%) (Figure 10.5). Many countries, particularly in Scandinavia, were plagued by low response rates to the question about seeing a doctor.

After adjusting for age, only Estonia, Sweden, Italy, Belgium, and Switzerland exhibited significant differences in the prevalence of unmet medical needs between the foreign- and native-born in 2012, with the former more likely to have unmet medical needs (Figure 10.4). Once age had been factored in, immigrants were significantly more likely than natives not to have seen a doctor – by 16.5 percentage points in Iceland, and by 3 to 11 points in Cyprus,1, 2 Hungary, Malta, the Czech Republic and Germany (Figure 10.5). In the Netherlands, though, they were significantly less likely (5 percentage points) than the natives.

The higher incidence of failing to see a doctor among the foreign- than the native-born could be attributable to individual socio-economic factors. Some migrants’ less fortunate circumstances –e.g. poorer education, incomes, working conditions, and social integration – tend to adversely affect their access to and use of health care services.

Figure 10.4. Foreign- and native-born adults who report unmet medical needs, 2012

Percentages

StatLink  http://dx.doi.org/10.1787/888933212997

Figure 10.5. Foreign- and native-born adults who report not to have seen a doctor (general practicioners or specialist) in the last 12 months, 2009

Percentages

StatLink  http://dx.doi.org/10.1787/888933213005

Notes and sources are at the end of the chapter.

Data limitations

Perceived health status

An ideal set of immigrant health indicators would objectively describe health status together with the factors that contribute to good health. However, the indicators that are available and easily measurable are static. They tend to measure only current health outcomes, not risk factors that may affect future ones. Commonly used health indicators, such as infant mortality and life expectancy, are either inapplicable or unavailable for immigrant populations. Although health checks and medical examinations (e.g. blood tests and chronic illness reports) would be ideal, they require specific surveys that countries seldom, if ever, carry out.

This chapter analyses different aspects of the self-reporting of health statuses among both the native- and foreign-born populations. Some caution is recommended in interpreting the self-reported responses to the survey questions, since social and cultural differences in self-perception and self-reporting across countries and between native- and foreign-born residents within a country may limit the validity of comparison. A joint indicator, combining perceived health status with chronic illnesses and health-related limitations, gave the most robust results. It should be noted that the indicators are captured in very different ways in different surveys, which may impede international comparisons. Although perceived health status comprises five levels in all surveys, responses in the European Union Statistics on Income and Living Conditions (EU-SILC) questionnaire range from “very bad” to “very good” and are centred on “fair”, while responses in the American and Canadian surveys range from “bad” to “excellent”, centred on “good”, which could bias comparison.

Medical treatment

Visits to the doctor for preventative and curative health care and medical check-ups (e.g. cancer screening, particularly for breast cancer, and the vaccination of children) are key indications of access to professional health care. However, national health survey sample sizes are too small to yield robust results for immigrants. Another method of gauging equity of access to health care services is by assessing reports of unmet medical needs. To that end, individuals are typically asked whether there was a time in the previous 12 months when they felt they needed health care but did not receive it, then why the need went unmet (Indicator 10.2).

Less frequently, respondents are also asked how often they have visited a doctor in the previous 12 months. Caution should be exercised using this indicator, however, because poor access to health care and ill health that calls for multiple visits to the doctor – both negative outcomes – lie at opposite ends of the spectrum.

Notes, sources, and further reading

Notes to Cyprus1, 2

1. Note by Turkey:

The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Turkey recognizes the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of United Nations, Turkey shall preserve its position concerning the “Cyprus issue”.

2. Note by all the European Union Member States of the OECD and the European Union:

The Republic of Cyprus is recognized by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus.”

Notes to tables and figures

White markers in all figures indicate that differences between adjusted immigrant rates and native-born rates are not statistically significant (with a probability of 0.05).

Figure 10.4: Data from the United States refer only to medical needs that go unmet for reasons of cost.

All panel designs tend to underrepresent recent arrivals. EU-SILC surveys update one quarter of the panel every year. Newly-arrived immigrants are included if they appear in this one-quarter or if they join a resident household, e.g. through family reunification and formation, in the other three-quarters.

Sources

European Union Statistics on Income and Living Conditions (EU-SILC) 2012.

Canadian Community Health Survey (CCHS) 2011-12.

US National Health Interview Survey (NHIS) 2012.

Figure 10.5: Ad hoc module of European Union Statistics on Income and Living Conditions (EU-SILC) 2009.

Further reading

OECD (2013), Health at a Glance 2013, OECD Publishing, Paris, http://dx.doi.org/10.1787/health_glance-2013-en.

OECD (2012), Settling In: OECD Indicators of Immigrant Integration 2012, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264171534-en.

Annex 10.A1.

Additional tables and figures

Figure 10.A1.1. Foreign- and native-born adults who do not report to suffer from health-related limitations, 2012

Percentages

Note: White markers indicate that differences between adjusted immigrant rates and native-born rates are not statistically significant (with a probability of 0.05).

1, 2: See “Notes, sources, and further reading” section.

Sources: European Union Statistics on Income and Living Conditions (EU-SILC) 2012. US National Health Interview Survey (NHIS) 2012. Canadian Community Health Survey (CCHS) 2011-12).

StatLink  http://dx.doi.org/10.1787/888933213011

Chapter 11.

Civic engagement of immigrants

Becoming actively involved in the host country’s society is a key element in immigrant integration. By making their voices heard, taking an interest in how society works, and participating in the decisions that shape its future, immigrants show that they are an integral part of their new country – the very objective of integration. There are many forms of civic engagement, be it through associations, voluntary groups, labour unions, or politics. But measuring levels of participation is a very complex matter, as involvement can be highly variable and motivations diverse.

Whether obtaining nationality is the ultimate goal of the integration process is a question of keen, ongoing debate among specialists. Being foreign is not in itself proof of failure to integrate, any more than attachment to the country of origin means rejecting the host country. Moreover, the legislation that governs nationality is more restrictive in some countries than in others. Nevertheless, having host-country nationality is often perceived to be a sign of integration into the host-country society, particularly since many countries require applicants to take a number of tests relating to their language, values, and culture before they grant nationality. From the viewpoint of the host country, conferring nationality on an immigrant is a way of welcoming him or her into the community of citizens.

One fundamental citizen’s right is the right to vote. Participating in elections is therefore viewed as a sign of integration – a desire to influence the life of society by getting involved in selecting those who will govern it.

This chapter examines two key aspects of civic engagement: the acquisition of nationality (Indicator 11.1) and, flowing therefrom, voter participation (Indicator 11.2). For a discussion of those indicators and the issues they raise, see the section entitled “Data limitations” at the end of the chapter.

Key findings

Nearly 2 million foreigners acquired the nationality of an OECD country in 2012 and 850 000 of an EU country.

In the OECD and the European Union in 2012-13, almost two-thirds of immigrants who had lived in the host country for at least 10 years had the nationality of that country.

The acquisition of nationality is more common in countries where naturalisation rules are less stringent and/or citizenship take-up actively encouraged (i.e. the settlement countries and, to a lesser degree, some Scandinavian countries) and where there are historic ties between the host country and the country of origin.

Free mobility is associated with lower levels of naturalisation – among European nationals, for example, who take the nationality of the host country relatively seldom.

Highly educated immigrants born in lower-income countries are more likely to naturalise than those from richer countries, while the trend is the opposite among low-educated immigrants.

Between 2002 and 2012, three-quarters of immigrants with the nationality of their host country took part in its latest national elections. The proportion was 80% of the native-born. Immigrants with host-country nationality who have been longer in the country are more likely to vote, but a small gap persists with the native-born.

On average, immigrants from high-income countries are more likely to vote than those from lower-income countries. There are only two host countries where that trend is not observed – the United Kingdom and Israel.

Section 11.1. Acquisition of nationality

Background

Indicator

Ideally, nationality acquisition rates should be calculated by dividing the stock of national foreign-born by the eligible foreign-born population. However, the definition of “eligible foreign-born population” varies from one country to the next because the legal practicalities of acquisitions differ greatly across countries.

A key criterion for nationality acquisition is a minimum duration of residence. In virtually all countries, this is at most ten years. To focus on those who are eligible in principle, the acquisition rate considered in this section is therefore based on the share of immigrants who have resided in the host country for at least ten years and who hold its nationality. Data are not available for Israel, Japan, Korea and Turkey.

Coverage

Immigrants aged 15 years and older who have resided in the host country for at least ten years. Immigrants with the nationality of the host country at birth (e.g. expatriates) are included as they cannot be separately identified.

In 2012, nearly 2 million foreigners acquired the nationality of an OECD country and 850 000 of an EU member state (Table 11.A1.1). In more than two-thirds of the countries covered in 2012-13, most long-standing immigrants (i.e. who had been settled for at least ten years) had the nationality of the host country. On average, 62% of long-standing immigrants in the OECD held host-country nationality, while the figure for the European Union was slightly lower at 59% (Figure 11.1).

In countries that have become independent or undergone border changes, around 90% of long-standing immigrants are nationals. Long-standing immigrants are also more likely to take nationality in countries which encourage it, like Canada, Australia and Sweden. Conversely, less than one-third of long-standing immigrants hold host-country nationality in Luxembourg, southern European countries or the Baltic countries (except Lithuania).

Acquisition rates among immigrants born in Europe are lower than among those born in other parts of the world. Free mobility in the EU makes naturalisation a less attractive prospect, and less than half the European migrants in the EU have host-country nationality. In Australia, Canada and the United States, by contrast, at least 80% of European migrants have become nationals (Figure 11.2). Geographic proximity, too, is associated with a lower citizenship acquisition rate. In the United States, for example, only 44% of immigrants from Latin America have taken American nationality.

Access to nationality can also depend on historic ties between host and home countries. Immigrants born in former colonies acquire nationality more smoothly, as exemplified by the 87% of immigrants from Africa in Portugal. Some migrant groups, such as refugees, benefit from fast-track naturalisation procedures – one reason why 90% of African and Asian immigrants have taken host-country nationality in Sweden and Norway, where humanitarian immigration has been substantial.

In most countries, highly educated immigrants from high-income countries are less likely to naturalise than their lower-income countries counterparts (70% vs 80%, OECD-wide, Figure 11.A1.1), since their qualifications – obtained in a rich country – earn them sufficient opportunity for occupational (and international) mobility. As for highly educated immigrants from poor countries, having the nationality of a high-income country offers them greater opportunity for mobility. Low-educated immigrants from lower-income countries are, by contrast, less likely to naturalise on average than their counterparts from high-income countries.

Figure 11.1. Share of nationals among the foreign-born population who have resided in the host country for at least ten years, population aged 15 and over, 2012-13

StatLink  http://dx.doi.org/10.1787/888933213020

Figure 11.2. Share of nationals in the foreign-born population who have resided in the host country for at least ten years, by region of origin, population aged 15 and over, 2012-13

StatLink  http://dx.doi.org/10.1787/888933213030

Notes and sources are to be found at the end of the chapter.

Section 11.2. Voter participation

Background

Indicator

This section considers self-reported participation in elections. It is measured through surveys which ask respondents whether they voted in the most recent national parliamentary election in their country of residence. Two versions of the self-reported electoral participation rate are presented here: gross rates (Figure 11.3) and adjusted rates (Figure 11.4). The adjusted rate hypothesises as to what the participation rate would be if immigrants were the same age and the same level of education as their native-born counterparts. These data are not available for Australia, where voting is compulsory.

Coverage

All persons aged 18 and over who are authorised to vote in national elections. As few countries give voting rights to foreigners for elections of this kind, this indicator is confined to those who have acquired the nationality of the host country.

Across the OECD and the EU, three-quarters of immigrants who have the host-country nationality report that they voted in the latest election to take place between 2002 and 2012. At 80%, a slightly higher share of the native-born cast its vote. The only two countries in which immigrants are significantly more likely than natives to vote are Hungary and Israel (Figure 11.3). Generally speaking, foreign- and native-born voter participation rates are most similar in central Europe, where many immigrants are people born in a place outside the host country’s current borders that was inside them at the time of their birth. Immigrant and native electoral participation rates are also very similar in countries, like Israel and France.

The voter participation rate of immigrants is lowest in the United States and in some recent immigration countries, particularly Portugal. In Spain, two-thirds of the foreign-born voted in the last election, compared to four-fifths of native-born. The lower participation rate of immigrants in the countries of southern Europe reflects the fact that many immigrants obtained their citizenship only recently and might, therefore, be less interested or informed about national politics. Indeed, in some of those countries, foreigners can acquire nationality soon after arrival, either through marriage (as in Greece) or through old colonial ties with the host country, as in Portugal and Spain.

On average, men – both foreign- and native-born – are somewhat more likely than women to vote. However, in countries where the immigrant voter turnout is low, it is foreign-born women who vote the most.

In all countries, the longer the length of residence, the more the foreign-born vote (Figure 11.A1.2). In the European Union, voter turnout among those with at least ten years residence behind them is on average 20 percentage points greater than among recently arrived immigrants with host-country nationality. In the United States it is 15 percentage points higher, while in Israel and the United Kingdom foreign-born electoral participation rates are similar or higher than among the native-born after ten years of residence. In all other countries, though, turnout among long-settled naturalised immigrants is still at least 5 percentage points lower than among native-born.

Immigrants’ voting behaviour varies greatly by country of birth. Those born in high-income countries vote more often than all others almost everywhere, as Switzerland and Ireland confirm most visibly. The adjusted election participation rate of immigrants from high-income countries in those countries is 20 percentage points higher than among those from lower-income ones (Figure 11.4). In Poland, France and Slovenia, those foreign-born participation rates actually exceeds native-born turnout among persons of similar age and education level. In the United Kingdom, Israel and Estonia, by contrast, immigrants from lower-income countries are the ones most likely to vote.

Figure 11.3. Self-reported participation in most recent election, immigrants and native-born populations, by gender, 2002-12

Percentage of the 18 years old and over population with the nationality of the country of residence

StatLink  http://dx.doi.org/10.1787/888933213040

Figure 11.4. Self-reported participation in the most recent election by place of birth and income level of their home country, voter participation rates adjusted by age and level of education, 2002-12

Percentage of the 18 years old and over population with the nationality of the country of residence

StatLink  http://dx.doi.org/10.1787/888933213050

Notes and sources are to be found at the end of the chapter.

Data limitations

Civic engagement

There are a number of indicators that could be used to measure civic commitment. Examples include: membership of community associations, sporting or leisure activities, neighbourhood committees, trade unions, political parties, and volunteer activities. Going out with friends is also a good indicator of social integration. However, everyday life surveys gather little data for such indicators. Their questions usually focus on the mere fact of participation, not on the actual scope of engagement. Participation in a given activity does not necessarily mean that a person is engaged in society. Moreover, being actively involved in ethnic or local community subgroups rather than in society as a whole is not civic engagement. Everyday life surveys very seldom ask respondents for details about the types of activities and other participants, like age, gender, or country of origin. For all those reasons, this chapter concentrates exclusively on acquisition of host-country nationality and participation in elections.

Acquisition of nationality

Using the nationality acquisition rate as an indicator of civic engagement is a complicated undertaking. How it interacts with the integration process is difficult to establish. Naturalisation can be seen both as the final step in the integration process and as a tool that can help enhance integration itself in several sectors. Acquisition of nationality, then, at once a social indicator, an indicator of policies, and an indicator of the openness of the host society.

With the current availability of data, it is impossible to estimate the nationality acquisition rate. Two estimates can be attempted using administrative sources. The first involves a comparison between the number of acquisitions registered in a given year and the foreign-born population in that year (Table 11.A1.1). This method, which gives an indication of the flows of nationality acquisition over time (and not the number of persons naturalised at some point in time), has a major drawback in that it uses two different sources: one for acquisitions and the other for the foreign population as a whole. An acquisition rate can also be estimated from records of residence permits issued to foreigners. This source, however, is generally not very reliable. The registry of foreigners is frequently out of date and may not take into account “exits” (deaths, departure from the territory, or acquisitions of nationality), making it an unreliable source for measuring the number of acquisitions and the size of the foreign-born population.

Some surveys provide good estimates of the proportion of immigrants with the nationality of the host country. However, this information is still not enough to show the proportion of immigrants who have acquired nationality. First, most surveys do not allow multiple nationalities to be reported: the immigrant’s decision to declare one nationality rather than another will naturally influence the measurement of the acquisition rate.

Another shortcoming is that an immigrant may have been born abroad with the nationality of the host country (children of expatriates who were born abroad by “happenstance” or foreigners retroactively deemed nationals at birth after independence or a change in borders). Information on nationality at birth is rarely gathered in the surveys. The 2008 ad hoc module of the Labour Force Survey published by Eurostat is one of the rare international sources to address this question, but its data are no longer current and the subsequent 2014 module on the subject is not yet available. Ideally, calculation of the acquisition rate should exclude immigrants born with the nationality of the host country – who in 2008 accounted for up to a third of immigrants in Slovenia, a quarter in Portugal, and a sixth in France – as it would tend to bias the rate upwards.

The final problem is that calculating the proportion of immigrants with nationality should be based only on the eligible immigrant population. The conditions required for obtaining citizenship are many and complex, and they vary greatly depending on the country and on the immigrant’s individual situation, e.g. length of residence, economic conditions, and knowledge of the host country and its language. There exists no survey that can adequately compare all these conditions and thereby identify and define the eligible population. In this chapter, the acquisition rate has been estimated from length of residence. In all OECD and EU countries, access to nationality is subject to length-of-residence conditions – between two and 12 years, depending on the country, but most often five years. In practice, those time horizons are often inadequate for acquiring nationality, as meeting the other conditions can require yet more time. To obtain a realistic number of immigrants eligible for naturalisation, the acquisition rate in the end has been calculated for the population that has been resident for at least ten years.

Participation in elections

The electoral participation indicator is subject to a number of reservations. The official participation rate, derived from lists of checked-off voters, is available only for the eligible population as a whole (and is not broken down by sex or country of birth). The indicator presented here, then, is measured from opinion surveys. The first drawback of the measure of voter participation is that it is declarative, i.e. based on self-reporting. In the great majority of cases, self-reported participation rates obtained from surveys will exceed the overall participation rate measured by electoral authorities. Second, voting is compulsory in some countries, which renders moot the measurement of electoral participation as an indicator of integration. Most importantly, however, voting in elections is open only to nationals in nearly all countries.

To avoid the situation where immigrants declare themselves eligible to vote when in fact they are not, this indicator considers only the population that has the nationality of the country of residence, even in those rare countries (the United Kingdom and Portugal) that extend voting rights to certain foreign nationalities. Confining the indicator to nationals has a real impact on inter-country comparisons, as national rules governing the acquisition of nationality have a strong influence on the voter participation rate. Different acquisition procedures may affect in different ways eligible people’s inclination to vote. For example, a lengthy naturalisation process will leave an immigrant time to develop an interest in the political life of the host country, unlike the situation where naturalisation can be obtained after only a few years of residence – unless, of course, the immigrant was entertaining the idea of permanent settlement from the outset. The authorisation of dual nationality may be another determining factor in voter participation. All those elements tend to complicate inter-country comparisons on this subject.

The indicator presented here considers only national elections and does not, therefore, cover the full range of immigrant participation in other types of elections (e.g. municipal or, within the EU, European), in which they can vote without having host country nationality in certain countries (See the European Parliament’s report in “Further reading”).

Lastly, electoral participation is only one aspect of civic engagement. Political participation is an important dimension. Considered more broadly, certain political activities (signing a petition, joining a political organisation, attending political rallies, belonging to a committee) could usefully be quantified, but few surveys provide information on such subjects.

Notes, sources, and further reading

Note to Israel

* Information on data relating to Israel: http://dx.doi.org/10.1787/888932315602.

Notes to Cyprus1, 2

1. Note by Turkey:

The information in this document with reference to “Cyprus” relates to the southern part of the island. There is no single authority representing both Turkish and Greek Cypriot people on the island. Turkey recognises the Turkish Republic of North Cyprus (TRNC). Until a lasting and equitable solution is found within the context of the United Nations, Turkey shall preserve its position on the “Cyprus issue”.

2. Note by all the European Union Member States of the OECD and the European Union:

The Republic of Cyprus is recognised by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus.

Notes to figures and tables

Figure 11.3: The grey bars indicate that the differences are not statistically significant to a probability level of 5%.

Figure 11.4: The differences are not statistically significant to a probability level of 5% for Israel, Poland, Portugal, and Slovenia. Differences for Canada and New Zealand are not adjusted.

The averages take into account the rates that cannot be published individually for reasons of sample size.

Sources of figures and tables

Figure 11.1: European Union Labour Force Survey (EU-LFS) 2012-13. American Community Survey (ACS) 2012. Australian Census on Population and Housing 2011. Canadian National Household Survey (NHS) 2011.

Figure 11.2: European Social Survey (ESS 2002-12). US Current Population Survey (CPS) November 2012, voter supplement. New Zealand General Social Survey (NZGSS) 2012. Canadian Labour Force Survey 2011, supplement.

Further reading

Arrighi, J.T. and D. Hutcheson (2013), EUDO CITIZENSHIP Database on Electoral Rights, European University Institute, San Domenico di Fiesole, http://eudo-citizenship.eu/electoral-rights/comparing-electoral-rights.

European Parliament – Committee on Constitutional Affairs (2013), Franchise and Electoral Participation of Third Country Citizens Residing in EU and of EU Citizens Residing in Third Countries, Brussels, www.europarl.europa.eu/RegData/etudes/etudes/join/2013/474441/IPOL-AFCO_ET(2013)474441_EN.pdf.

OECD (2012), Settling In: OECD Indicators of Immigrant Integration 2012, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264171534-en.

OECD (2011), Naturalisation: A Passport for the Better Integration of Immigrants?, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264099104-en.

Annex 11.A1.

Additional tables and figures

Table 11.A1.1. Trends in the number of naturalisations, 2002-12
| 2002-06 | 2007-11 | 2012
| Numbers (annual average) | % of the foreign population | Numbers (annual average) | % of the foreign population | Numbers (annual average) | % of the foreign population
Australia | 90 965 | .. | 111 715 | .. | 83 698 | ..
Austria | 36 594 | 4.8 | 9 014 | 1.0 | 7 043 | 0.7
Belgium | 35 650 | 4.1 | 34 192 | 3.3 | 38 612 | 3.3
Bulgaria | 5 103 | 41.5 | 11 114 | 30.6 | .. | ..
Canada | 189 971 | 11.4 | 171 562 | 9.8 | 113 150 | 6.4
Chile | 393 | .. | 749 | .. | 1 225 | ..
Croatia | 10 797 | 29.8 | 6 528 | 17.6 | 1 081 | 3.9
Cyprus1, 2 | 2 913 | 3.2 | 2 887 | 2.0 | 2 314 | 1.4
Czech Republic | 3 587 | 1.5 | 1 753 | 0.4 | 2 036 | 0.5
Denmark | 11 403 | 4.2 | 4 575 | 1.4 | 3 267 | 0.9
Estonia | 5 229 | 2.0 | 2 145 | 1.0 | 1 339 | 0.6
Finland | 4 914 | 4.6 | 4 762 | 3.2 | 9 087 | 4.8
France | 148 851 | 4.2 | 132 578 | 3.5 | 96 088 | 2.4
Germany | 132 848 | 1.9 | 102 418 | 1.5 | 112 348 | 1.6
Greece | .. | .. | 15 992 | 2.3 | 21 737 | 2.9
Hungary | 6 021 | 4.4 | 9 798 | 5.1 | 18 379 | 12.9
Iceland | 612 | 5.9 | 622 | 2.7 | 413 | 1.9
Ireland | 4 087 | 1.3 | 6 547 | 1.1 | 25 039 | 4.6
Italy | 21 431 | 1.0 | 56 128 | 1.4 | 65 383 | 1.4
Japan | 15 533 | 0.8 | 13 223 | 0.6 | 10 622 | 0.5
Korea | 9 196 | 2.3 | 17 602 | 2.0 | 12 528 | 1.3
Latvia | 15 124 | 3.5 | 4 383 | 1.4 | 3 784 | 1.4
Lithuania | 481 | 3.0 | 259 | 0.7 | 183 | 0.7
Luxembourg | 892 | 0.5 | 2 838 | 1.3 | 4 680 | 2.0
Malta | 552 | 4.8 | 807 | 4.5 | 1 138 | 5.3
Mexico | 5 054 | .. | 3 643 | 2.8 | 3 590 | 1.2
Netherlands | 31 574 | 4.5 | 28 702 | 3.9 | 30 955 | 3.9
New Zealand | 22 774 | .. | 21 201 | .. | 27 230 | ..
Norway | 9 934 | 4.8 | 12 634 | 4.0 | 12 384 | 2.9
Poland | 1 722 | 3.3 | 2 067 | 3.8 | 3 792 | 6.8
Portugal | 1 806 | 0.4 | 19 520 | 4.4 | 21 819 | 5.1
Romania | 304 | 0.6 | 5 005 | 8.6 | .. | ..
Slovak Republic | 2 507 | 9.7 | 586 | 1.0 | 255 | 0.4
Slovenia | .. | .. | 1 513 | 3.0 | 768 | 0.7
Spain | 38 374 | 1.1 | 94 779 | 1.7 | 115 557 | 2.1
Sweden | 35 597 | 7.8 | 31 891 | 5.5 | 50 179 | 7.6
Switzerland | 38 554 | 2.6 | 41 553 | 2.5 | 34 121 | 1.9
Turkey | 13 004 | 4.5 | 7 434 | 5.5 | .. | ..
United Kingdom | 142 929 | 5.1 | 174 127 | 4.1 | 194 209 | 4.1
United States | 576 033 | 2.8 | 752 967 | 3.5 | 757 434 | 3.6
EU total (28) | 701 290 | 2.7 | 766 909 | 2.4 | 853 456 | 2.5
OECD total (33) | 1 638 040 | 2.9 | 1 890 831 | 2.9 | 1 888 183 | 2.9
1, 2: See “Notes, source and further reading” section.
Sources: OECD Database on International Migration (2002-12). Eurostat Database on International Migration and Asylum (2002-12) for Cyprus1, 2, Croatia, Malta, Portugal (2012) and Turkey.
StatLink  http://dx.doi.org/10.1787/888933214208

Figure 11.A1.1. Naturalisation rates among immigrants who have resided in the host country for at least ten years, by level of education, population aged 15 and over, 2012-13

StatLink  http://dx.doi.org/10.1787/888933213062

Figure 11.A1.2. Immigrants’ self-reported participation in most recent election, by duration of stay in host country and native-born, 2002-12

Percentage of the 18 years old and over population with the nationality of the country of residence

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: European Social Survey (2002-12). US Current Population Survey (CPS) 2012, supplement on voter participation.

StatLink  http://dx.doi.org/10.1787/888933213076

Chapter 12.

Social cohesion and immigrants

The nature of the relationship between a host society and its immigrant population is a critical factor in integration. If such social cohesion is strong, it will promote integration. If it is weak, immigrants will find it harder to fit in. Social cohesion is hard to measure but can, however, be estimated from certain kinds of information produced by satisfaction surveys.

Discrimination against immigrants is one factor that can have a deeply adverse impact on social cohesion, thought its real extent is hard to quantify. It is essential to measure discrimination on the grounds of ethnicity, race or nationality, however, because it undermines immigrants’ willingness to invest in education and training, which are the best ways to improve the integration process. Opinion polls are a means of assessing the levels of discrimination that immigrant populations perceive (Indicator 12.1).

Social cohesion can also be measured by analysing the host country’s degree of acceptance of immigration. A high level of acceptance will indirectly promote the conditions for successful integration – if the immigrant population is welcomed, it will be better able to contribute to the life of the community. This report assesses acceptance by gauging public opinion of its perceived impact and with respect to the perceived local conditions for immigrant settlement (Indicator 12.2).

The section entitled “Data limitations” at the end of the chapter discusses in detail the social cohesion indicators and the issues they raise.

Key findings

In the OECD and EU areas, between 2002 and 2012, one immigrant in seven felt that they were discriminated against on the grounds of their origin.

Perceived discrimination is more widespread among men and people born in lower-income countries. Foreigners born abroad also perceive more often to be the target of discrimination than their peers who have naturalised.

The groups most exposed to ethnic discrimination (young people, the unemployed, and the elderly) vary widely from one country to another.

In 2012, a quarter of the host-country population in European countries considered the economic impact of immigration to be negative. Views on the economic impact of migration were mostly positive in Switzerland and the Scandinavian countries. Opposite views are observed in most countries of southern and central Europe.

In the settlement countries, most people consider their area a good place for immigrants to live in, whereas the opposite is the case in most countries of southern and central Europe.

Immigrants felt less discriminated against in 2008-12 than in 2002-06 even though the share of people who consider their area to be a good place to live for immigrants slightly declined.

Section 12.1. Perceived discrimination

Background

Indicator

Ethnic discrimination is generally understood as unfairly treating an individual or a certain group of people on the grounds of their ethnicity, race, or citizenship. It can come in various guises and may be inherent in individual behaviour and institutional structures and practices. This indicator measures ethnic discrimination perceived by people born abroad. Depending on the country, it reflects discrimination that is perceived personally in a given situation or by the respondent’s entire ethnic group.

Coverage

Foreign-born people aged between 15 and 64.

In all European countries between 2002 and 2012, 14% of immigrants claimed to belong to a group that had been subjected to discrimination on the grounds of ethnicity, nationality, or race (Figure 12.1). Levels were particularly high in Greece, Latvia and Austria, where a quarter of the foreign-born population felt they were discriminated against. In general, immigrants to southern Europe and the Baltic countries were more likely to feel discriminated against than in Scandinavia, and Luxembourg. In non-European OECD countries about one in seven respondents felt personally discriminated against.

In all countries, higher proportions of immigrants from lower-income countries report discrimination against their community (Figure 12.1). In the European Union, and especially in the EU15 countries (particularly Portugal, France and Belgium), they were 12 percentage points more likely to do so than their peers from high-income countries, while in Greece and Austria, up to 35% felt discriminated against. In North America and Australia, the share of immigrants born in lower-income countries who said they had experienced discrimination was almost 10 percentage points higher than those from high-income countries, with the rate in Australia standing at one in four in 2012-13.

Between 2002 and 2012, having a foreign nationality has been associated with intensified perceptions of ethnic discrimination. It is difficult to ascertain whether obtaining the host-country nationality protects people from further discrimination, or whether meeting the often integration-related criteria to qualify for nationality makes people less likely to be discriminated against. Whatever the case, around 17% of foreigners in the European Union claimed discrimination against themselves or the group to which they belonged (Figure 12.2).

Country rankings by level of perceived discrimination is broadly the same whether on the grounds of country of birth or nationality. In southern Europe, especially in Greece, Portugal, and in Austria, foreigners born abroad are far more likely to report discrimination than naturalised immigrants, with the rate as high as four out of ten in Greece (Figure 12.A1.1). Conversely, foreigners born abroad living in northern Europe, the Netherlands or the United Kingdom often say they are less subject to discrimination than naturalised immigrants, although they are more likely than immigrants with the host-country citizenship to be so in the United States and Australia, as in other European countries.

Figure 12.1. Share of 15-64 year-old immigrants who consider themselves members of a group that is discriminated/has been discriminated against on grounds of ethnicity, nationality or race, by place of origin, 2002-12

StatLink  http://dx.doi.org/10.1787/888933213084

Figure 12.2. Share of 15-64 year-old foreigners who consider themselves members of a group that is discriminated/has been discriminated against on grounds of ethnicity, nationality or race, 2002-12

StatLink  http://dx.doi.org/10.1787/888933213093

Notes and sources are to be found at the end of the chapter.

Although all OECD countries share some patterns of perceived discrimination – e.g. higher levels of perceived discrimination against immigrant men than women, and against those from lower-income countries than from higher-income countries – there are differences that may spring from the country’s migration history and socio-economic factors. Some differences may also be attributable to methods of measuring discrimination from one country to another (see “Data limitations” at the end of the chapter).

Within the European Union, between 2008 and 2012, immigrants born in Africa were most likely to feel their group was discriminated against on the grounds of ethnicity, race, or nationality. One quarter reported discrimination – twice the average for all immigrants (Figure 12.3). Younger people of working age were more likely to report discrimination than those aged 55 and older, who were coming to the end of their careers. It is, however, unclear whether the higher incidence is the effect of age or generation (younger cohorts may be more likely to perceive discrimination than older cohorts).

People with traits that might hamper labour market integration feel most discriminated against – 19% of unemployed immigrants, for example, and 17% with a low level of education. Immigrants whose native language is not that of the host country are also more likely to complain of discrimination. However, immigrants to the European Union have reported less ethnic discrimination in recent years, with a 1 percentage point drop between 2002-06 and 2008-12. Yet, immigrants born in North Africa have become more likely to feel discriminated against as members of an ethnic group than they were in the mid-2000s.

In Canada in 2009, Asian immigrants were the most likely to report discrimination (20%). By contrast, immigrants from Africa do not report higher levels of discrimination than the foreign-born in general. Unlike Europe, immigrants to Canada are most likely to report discrimination when they are well integrated in the labour market: 17.5% of the highly educated report being discriminated against, compared to 9% of their low-educated peers (Figure 12.4). One explanation could be that Canada selects most of its highly qualified immigrants, which may raise their expectations of favourable treatment and help explain why immigrants in work report more discrimination than those who are unemployed. Finally, while the oldest immigrants are the least likely to report unfair treatment on the grounds of ethnic identity, the youngest, in the 15-24 year-old age bracket, are more likely to complain of discrimination (20%), just as they are in Europe.

As in Canada, Asian, young, or highly qualified immigrants in Australia and New Zealand were most likely to report discrimination in 2012-13, while people with jobs felt more discriminated against than those who were not in the labour market.

In the United States, where discrimination figures between 2004 and 2012 are available for only the employed, immigrants born in Asia reported less discrimination than the foreign-born as a whole. As in Europe, immigrants with the fewest qualifications were the most likely to perceive discrimination (20%). However, ethnic discrimination at work was a much greater problem for older immigrants, who reported being singled out twice as often as immigrants aged under 25. Again, more detailed research would be needed to establish whether that more widely perceived sense of discrimination is related to age or to generation.

Figure 12.3. Share of 15-64 year-old immigrants who state that they have been discriminated against, EU countries, 2002-06 and 2008-12

StatLink  http://dx.doi.org/10.1787/888933213106

Figure 12.4. Share of 15-64 year-old immigrants who state that they have been discriminated against, 2008-12

StatLink  http://dx.doi.org/10.1787/888933213111

Notes and sources are to be found at the end of the chapter.

Section 12.2. Host-society attitudes towards immigration

Background

Indicator

Unlike previous indicators, this one seeks to assess the integration of immigrants from the point of view of the host country, as positive attitudes make integration easier. Host country opinions of immigration have been assessed using various questions: is the respondents’ city or area of residence a good place for migrants to live – which can be considered an indicator of welcoming – and what impact does immigration have on the economy and cultural life. The latter question is not asked in surveys of non-European countries.

Coverage

People aged 15 and older, both native-born and immigrant.

In 2012, an average of 73% of the population of the OECD area considered the place where they lived to be a good place for immigrants to settle. At 69%, that opinion was not quite as prevalent in the European Union (Figure 12.5).

Levels differ widely between countries. In most central European countries, the Baltic countries, Greece, and Israel, people generally think their area is not a good place for immigrants to live in. Just one-third of Israelis say that their neighbourhood is a good place for immigrants.

Lower-income countries (such as Mexico and Turkey) generally perceive the welcoming of immigrants in their area more sceptically than richer ones. Settlement countries, particularly Canada, New Zealand, and Australia, have more favourable views, with nine out of ten people agreeing that their place of residence is a good place for migrants. The same is true of Scandinavian countries, especially Iceland and Sweden. In the other OECD countries (the United States and the EU15), most people think that immigrants will have a good place in their area.

Public opinion in OECD and EU countries was, on average, slightly more sceptical on this issue in 2012 than in 2007. In 2007, most people everywhere – with the exception of Israel – considered their neighbourhood to be a good place for immigrants to settle. That balance has reversed in five countries, however. In Greece, for example, the share of the population who agreed that where they lived was a good place for immigrants to settle fell from 67% to 41% (Figure 12.6). Here again, countries with lower living standards and those worst-affected by the financial crisis have become less accepting of immigration. By contrast, public opinion has grown more positive on this issue in the EU15 countries that were the least impacted by the crisis, except in the Benelux countries and France. Germans, Austrians, and particularly Scandinavians viewed their area of residence as a good place for immigrants. In settlement countries, public opinion varies: people in Canada are currently perceiving their area more welcoming than five years ago, whereas positive views in Australia have fallen by 3 percentage points.

Public opinion on the settlement of new immigrants closely reflects public opinion on the impact of immigration. Across all European countries between 2008 and 2012, 26% of the population saw immigration as having an adverse impact on the economy, and 29% a positive effect (Figure 12.7). In Greece, Turkey, Cyprus,1, 2 and Hungary, at least 45% of the population felt the economic impact was negative, while more than 40% of the respondents in Scandinavia and Switzerland viewed it as positive. Immigration’s effect on cultural life is widely seen as more positive than its impact on the economy with 43% expressing their approval in the OECD (Figure 12.A1.2). Country rankings against the culture criterion reflect opinions of immigration’s economic impact.

Figure 12.5. Share of the population who think that their city or area of residence is a good place for migrants from other countries to live, 2012

StatLink  http://dx.doi.org/10.1787/888933213122

Figure 12.6. Changes in the share of the population who think that their city or area of residence is a good place for migrants from other countries to live, 2007-12

StatLink  http://dx.doi.org/10.1787/888933213135

Figure 12.7. Perceived economic impact of immigration, 2008-12

StatLink  http://dx.doi.org/10.1787/888933213140

Notes and sources are to be found at the end of the chapter.

Data limitations

Discrimination

Measurements of perceived discrimination remain highly subjective. People perceive discrimination differently, depending on their attributes, those of their community, and even public discourse on integration in the host country. Victims may not recognise a discriminatory practice when they encounter it or they may, alternatively, attribute to discrimination obstacles or disadvantages that are in fact due to other factors. Self-reported data on discrimination should therefore be treated with caution.

There exist other, more objective measurements of discrimination, but they are difficult to apply in international comparisons. There are, for example, econometric methods of measuring the residual difference between the immigrant and native-born populations for some indicators, adjusted for observable characteristics. After adjustment, the remaining difference is the unexplained part, which includes factors such as discrimination. It is impossible, however, to measure the real extent of discrimination within those non-observable characteristics. First, observable data vary depending on the source. Language proficiency, for example, can be included either in the observable adjustment criteria or in the unexplained part, according to whether it was measured in the survey. Second, even in surveys in which as much data as possible are observed, there always remain factors that cannot be measured objectively, such as personal networks, understanding of the procedures and culture of the host country, and personal motives.

There is also one further objective method for measuring discrimination: testing in real conditions. Such tests compare the results of applications for jobs or housing sent simultaneously by two people with equivalent profiles and whose only distinctive attribute is the migration profile, often indicated by the first and last name. It assesses discrimination as a function of the difference in the number of return calls, interviews, or property viewings received by the candidates. That kind of testing is more rigorous, but difficult to use in international comparisons because the methods used vary so widely between tests.

The evaluation of discrimination in this report is based on questions put to immigrants in various surveys. Every survey words the question differently, and the data are therefore not directly comparable. In Canada, New Zealand and the United States, immigrants are asked about their experience of discrimination based on ethnicity, race or nationality. In Australia, they are also asked about discrimination on the grounds of religion. Further, respondents are not always interviewed in the same conditions. In the United States, only job discrimination is measured, so the level of perceived discrimination and the factors that influence it are not comparable with those that emerge from other studies. In New Zealand, Australia and Canada, the same question is asked, but over different periods: last year prior to 2012 in New Zealand and prior to 2012 or 2013 in Australia but for the last five years prior to 2009 in Canada, which automatically increases the number of immigrants who suffer from discrimination in Canada. Nor are the results of the European Social Survey comparable to non-European OECD countries because the question it asks does not concern personal experience, but whether respondents belong to a group that is discriminated against. This is a slightly ambiguous measurement of perceived discrimination because it blurs the line between personal experience and the general perception of the overall situation of the ethnic group to which the respondent belongs, which tends to bias perceived discrimination upwards.

Opinion in host countries

Opinion in host countries, or public opinion, is measured by surveys, with the most frequent responses seen as “the will of the people”. The results of that kind of survey must be qualified. First, they are influenced by the sampling method, the size of the sample, and the design of the questions. Second, sociological research is now questioning whether public opinion is really the aggregate result of individual answers to opinion surveys. For one thing, surveys are based on the assumption that everybody has an opinion on every subject – tantamount to ignoring non-response, which is information in itself. Moreover, the strength and importance of the views may largely differ from one individual to another. Lastly, public opinion surveys are based on the assumption that there exists a tacit consensus as to which issues people are interested in.

More importantly, the question whether the area of residence is a “good place to live for immigrants” is only a crude measure of welcoming. It can refer to many other things than acceptance and welcoming of immigrants by the society, and can notably be interpreted by the respondents as an indication of local economic conditions or the quality of the amenities available to immigrants.

Notes, sources, and further reading

Notes for figures and tables

Indicator 12.1: Data on European countries refer to the sense of belonging to a group that is discriminated against on the grounds of race, ethnicity, or nationality. Australian data refer to immigrants who report being discriminated against on the grounds of colour, ethnicity, or religion. Canadian data refer to immigrants who have experienced discrimination or have been treated unfairly in the past five years because of their ethnicity, culture, race, or colour. Data for the United States refer to respondents in employment who feel, in one way or another, discriminated against at work because of their race or ethnicity. Data for New Zealand refer to immigrants who report having been treated unfairly or having had an unpleasant experience within the prior 12 months because of their ethnicity, race, or nationality. The relative sampling error for New Zealand is 30-49% for men, people aged 25-54 years old, those born in high-income countries, people with an average or high level of education, people in work, or those who are inactive. It is 50-99% for those aged 15-24 or 55-64, the low-educated, and the unemployed.

Indicator 12.2: Non-responses are not included.

Figures 12.5 and 12.6: 2011 data for Chile, Germany, Japan, Korea, Mexico, and the United Kingdom. 2006 data for Austria, Bulgaria, Cyprus,1, 2 Finland, Ireland, Norway, Portugal, Norway, Slovakia, Slovenia, and Switzerland. 2008 data for Iceland, Luxembourg, and Malta.

Data for Luxembourg, Italy and Austria are not available from 2008 to 2012.

Note to Israel

Information on data concerning Israel: http://dx.doi.org/10.1787/888932315602.

Notes to Cyprus1, 2

1. Note by Turkey:

The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Turkey recognises the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of the United Nations, Turkey shall preserve its position concerning the “Cyprus issue”.

2. Note by all the European Union Member States of the OECD and the European Union:

The Republic of Cyprus is recognised by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus.

Sources

Indicator 12.1: European Social Surveys (ESS) 2002-12. Canada: General Social Survey (CGSS) 2009. New Zealand: General Social Survey (NZGSS) 2012. United States General Social Survey (USGSS) 2004-12. Australia: Scanlon Survey on Social Cohesion (SSCC) 2012-13.

Indicator 12.2: Gallup World Poll 2007 and 2012.

Figure 12.7: European Social Surveys (ESS) 2008-12.

Further reading

Heath, A., T. Liebig and P. Simon (2013), “Discrimination against Immigrants –Measurement, Incidence and Policy Instruments”, in OECD International Migration Outlook 2013, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2013-7-en.

OECD (2012), Settling In: OECD Indicators of Immigrant Integration 2012, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264171534-en.

OECD (2011), Naturalisation: A Passport for the Better Integration of Immigrants?, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264099104-en.

OECD (2008), “The Price of Prejudice: Labour Market Discrimination on the Grounds of Gender and Ethnicity”, OECD Employment Outlook 2008, OECD Publishing, Paris, http://dx.doi.org/10.1787/empl_outlook-2008-5-en.

Spielvogel, G. (2010), “Public Opinions and Immigration: Individual Attitudes, Interest Groups and the Media”, OECD International Migration Outlook 2010, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2010-6-en.

Annex 12.A1.

Additional tables and figures

Figure 12.A1.1. Share of 15-64 year-old immigrants who consider themselves members of a group that is discriminated/has been discriminated against on grounds of ethnicity, nationality or race, by citizenship, 2002-12

Note: Data on European countries refer to the sense of belonging to a group that is discriminated against on the grounds of race, ethnicity, or nationality. Australian data refer to immigrants who report being discriminated against on the grounds of colour, ethnicity, or religion. Data for the United States refer to respondents in employment who feel, in one way or another, discriminated against at work because of their race or ethnicity.

Sources: European Social Surveys (ESS) 2002-12. United States General Social Survey (USGSS) 2004-12. Australia: Scanlon Survey on Social Cohesion (SSCC) 2012-13.

StatLink  http://dx.doi.org/10.1787/888933213159

Figure 12.A1.2. Perceived impact of immigration on cultural life, 2008-12

Source: European Social Surveys (ESS) 2008-12.

StatLink  http://dx.doi.org/10.1787/888933213168

Chapter 13.

Young people with a migrant background

How well they integrate the offspring of immigrants can be considered a yardstick of host countries’ integration policies. In theory, because they were schooled in their parents’ host country, children of immigrants should not encounter the same difficulties as adult immigrants who arrived in a foreign country as workers, spouses, partners, members of the family, or as humanitarian migrants. Ultimately, their outcomes should be much the same as those of young people with no migrant background and the same social and demographic profiles. Yet that is not what happens in many host countries, particularly in Europe.

The chapter begins by considering some basic demographic and immigrant-specific pointers that help situate young people with immigrant parents (Indicators 13.1 to 13.3). It then goes on to analyse how well integrated they are in host country schools (Indicators 13.4 to 13.6). It then assesses the educational level ( 13.7) and literacy skills of young adults of foreign parentage ( 13.8) and examines what share of young people have dropped out of school early ( 13.9). The chapter then looks at the school-to-work transition ( 13.10) and proportions of NEETs ( 13.11) before addressing labour market integration ( 13.12 to 13.5). The last area of focus is social inclusion and civic involvement: child poverty (13.16), voter participation ( 13.17) and, finally, perceived discrimination ( 13.18).

Indicators specific to the immigrant offspring

Some of the issues related to young people of immigrant background that this chapter addresses apply only to them and not to immigrants who arrived as adults. In particular, the levels of educational attainment of immigrants’ children raised and schooled in the host country and how they fare in its education system are important yardsticks of integration because they affect participation in the labour market and society at large.

Furthermore, standard labour market integration indicators are not sufficient to evaluate to what extent new entrants are barred from the workplace. Some new entrants, particularly in times of economic crisis, do not become part of the work force when they complete their schooling and are likely to end up economically inactive. Indicator 13.11 (Neither in employment, education or training – NEET) helps address the issue which, like the school-to-work transition (Indicator 13.10), is specific to the young generation. Because they were born and/or brought up in the host country, they should also be able to seek and find work in the public sector (see Indicator 13.15) just like young people with no migrant background – but unlike their immigrant parents who arrived as adults, for whom the public sector often offers few prospects (see Indicator 6.6).

Active participation in the community is of particular importance for immigrant offspring, as it assesses to what extent they succeed in getting on, becoming interested in the world around them, and speaking out. Finally, that a section of the population with a migrant background is or feels discriminated against on the grounds of origin is in itself a sign that the integration process is not over yet and that the host country and young people of foreign origin do not fully trust each other. The consequences can be very serious in the long term.

Key findings

Immigrant offspring account for a sizeable share of the young in OECD countries

In the 22 OECD countries for which recent data are available, in 2013, nearly one in five 15-34 year-olds (35.4 millions of people) was the child of an immigrant or had immigrated as a child. A further 9% arrived in the host country as adults.

The United States (16.1 million), France and Germany (3.3 million each), Canada (2.3 million) and the United Kingdom (1.9 million) are the host countries that are homes to the largest numbers of youngsters with an immigration background (not counting 6.4 million, 840 000, 1.5 million, 740 000 and 2.1 million of immigrants entered as adults, respectively).

In the European Union in 2008, around half of young native-born people with two immigrant parents who were in a couple had a spouse/partner of different origin (defined here as their parents’ place of birth). This compares with nine in ten young natives of mixed parentage (spouse/partner from a different migrant background as his/her immigrant parent), nearly three out of five immigrants who arrived as children and 30% of adult immigrants (part of whom had already a partner before migrating).

Progress in performance at school is noticeable, both over time and with greater experience of the host country

In non-EU OECD countries, native-born children with two immigrant parents perform on average as well in reading at the age of 15 as children with two native-born parents. In contrast, foreign-born students lag behind. In the European Union, both foreign-born pupils and natives with two immigrant parents show average outcomes that are well below those of children with two native-born parents. Between those of mixed and native parentage there is generaly no difference.

However, since 2003, there has been OECD-wide progress in academic performance at the age of 15 among immigrant and native pupils with two foreign-born parents. However, the improvement is driven primarily by a handful of countries, such as Germany, Belgium and OECD settlement countries.

School performance improves the longer pupils reside in the host country, with the native offspring of foreign-born parentage outperforming immigrants who arrived in childhood.

Despite progress over the decade, a significant share of students with a migrant background lack basic skills

In 2012, an average of 30% of foreign-born pupils across the European Union lacked basic reading skills at 15, compared with around 25% of native students born to immigrant parents and 14% of native children of mixed parentage and of children of native-born parents. By contrast, comparable average shares of around 17% of native-born pupils of native- and foreign-born parents struggled with reading literacy at 15 years old across the OECD.

In the OECD, an average of only 9% of immigrant students from disadvantaged socio-economic backgrounds are resilient – i.e. top performers despite their background – compared with 11% among their peers of native-born parentage from the same background. Australia and Canada stand out for having comparable shares of resilient students from both two groups. Disadvantaged immigrant students in Israel, the United Kingdom and the United States are slightly more likely to be resilient than their peers with native-born parents. By contrast, the share of resilient immigrant students is particularly low in France, Germany, Portugal and Luxembourg – more than four times lower than among the offspring of the native-born.

Education is generally a key driver of the labour market integration of immigrant offspring and of immigrants who arrive as children, although less so among women than men

In the European Union, young immigrant offspring with two immigrant parents are 4 percentage points more likely to be neither in employment, education, or training (NEET) than those with no migrant background. In contrast, in the non-European OECD countries, such youth have similar NEET rates than their peers with native-born parents.

In the European Union, the youth unemployment rate among native-born offspring of immigrant parents is almost 50% higher than among the young with native-born parents. In non-EU OECD countries, rates are similar.

In the OECD, an average of only two-thirds of immigrant youth or native youth born to two immigrant parents are employed. The rate is 75% among the young with native-born parents.

Although the native-born offspring of immigrants boast better education outcomes than foreign-born youth who entered the host country as children, they do not tend to show a higher employment rate.

Higher levels of male education are more closely associated with improved employment rates among native-born immigrant offspring than the children of the native-born, though not for women.

Higher education levels are less closely associated with improved employment rates among foreign-born youth who immigrated as children than among their native-born peers with immigrant parents.

Only one-fifth of young people born in the host country to immigrant parents worked in the public services sector in 2013, compared with one-quarter of the offspring of native-born parents. The gaps were widest in Germany and Austria.

Since 2007-08, youth employment rates among those of migrant background have deteriorated more than among the offspring of the native-born, especially among men, except in the United States and Sweden.

The disadvantages of youth with a migrant background extend beyond education and labour market outcomes

In 2012, nearly one in two children (aged less than 16 years old) living in a migrant household were living below the relative poverty threshold, compared with less than a quarter of those in a native-born household. Shares are the highest in the United States, Greece and Spain.

Between 2002 and 2012, the turnout of young people eligible to vote in national elections was, at 50%, lower among natives born to immigrant parents than among the offspring of native-born parents (70%).

In the European Union, one-fifth of young people born in the host country to foreign-born parents report belonging to a group that is discriminated against on the grounds of ethnicity or nationality. In fact, they are more likely to report being discriminated against than young immigrants. This stands in marked contrast to non-EU OECD countries, where the reverse is true.

Section 13.1. Immigrant and native-born immigrant offspring populations in the 15-34 age group

Background

Definition

The main target groups in this chapter are native-born young people who have at least one foreign-born parent and foreign-born youth at least partly educated in the host country (see the “Target groups” section at the end of this chapter). Unless stated otherwise, the reference group is native-born offspring with two native-born parents.

Coverage

Population aged 15 to 34 years old.

In the OECD (22 countries for which data are available), nearly one in five of 15-34 year-olds were of a migrant background in 2013, either born in the host country to at least one foreign-born parent or immigrated as children. A further 9% immigrated as adults. In the European Union (15 countries), by comparison, 14% of the 15-34 age group originated from a migrant background, while a further 10% arrived as adults. Of the three categories of youth of migrant parents, young natives born to two foreign-born parents account for the largest single share of 15-34 year-olds – 7% in the OECD and 5% in the European Union. For immigrants who arrived as children, the figures are 6% and 5%, respectively. The native-born of mixed parentage make up around 4.5% of both OECD and EU populations (Figure 13.1). Among the 35.4 million 15-34 year-olds of immigration background living in the OECD, 16.1 million reside in the United States, 3.3 million in France and in Germany, 2.3 million in Canada, and 1.9 million in the United Kingdom (Table 13.1). Some longstanding immigration countries, such as Austria and Germany, as well as some Scandinavian countries and Spain host more young child-arrivals than young natives with two foreign-born parents. In all other countries, by contrast, and particularly in France, where recent inflows are relatively low, migrant offspring outnumber the foreign-born who arrived as children.

Again, the United States, Germany and France host the largest numbers of native-born offspring with two foreign-born parents. However, in relative terms, the highest shares of immigrant offspring are to be found in European countries whose total populations have substantial proportions of immigrants (Luxembourg, Israel and Switzerland) and in settlement countries like Canada and Australia. In the recent migration destinations of southern Europe and Finland, by contrast, less than 1% of young people were born in the host country to foreign-born parents.

In the European Union, Australia and New Zealand, immigrants who arrived as adults outnumber by two to one those who were children. By contrast, in the United States and Germany, where flows of family members are significant, 45% and 48% immigrated as children, respectively. Luxembourg boasts the largest share of immigrants, whether they arrived as children (13% of 15-34 year-olds) or later in life (22%). High shares of child-arrival immigrants reside in Switzerland and settlement countries like Israel and New Zealand, where they account for almost one-tenth of 15-34 year-olds.

Unlike other categories of residents from migrant backgrounds, the native-born of mixed parentage are more numerous in the European Union than in the United States. They form a diverse group that also includes children whose parents are foreign- and native-born but of the same origin. In Luxembourg and, to a lesser extent, Germany and the United States, there are fewer native-born children of mixed parentage than those who have two immigrant parents or immigrated as children. By contrast, they account for nearly half of all young people with an immigrant background and outnumber immigrant offspring in Denmark, France and Australia.

Figure 13.1. Categories of immigrants and immigrant offspring among 15-34 year-olds, 2013

Percentage of the total population aged 15 to 34

StatLink  http://dx.doi.org/10.1787/888933213172

Table 13.1. Distribution of the population aged 15 to 34 by migration background, 2013
Numbers in thousands and percentages
| Native-born offspring of foreign-born | % of total population | Native-born with a mixed background | % of total population | Foreign-born who arrived as children | % of total population | Foreign-born who arrived as adults | % of total population
Australia | 547.4 | 10.1 | 753.4 | 13.9 | 450.2 | 8.3 | 869.5 | 16.0
Austria | 132.9 | 6.3 | 110.0 | 5.2 | 134.8 | 6.4 | 241.5 | 11.5
Belgium | 198.3 | 7.4 | 240.7 | 8.9 | 142.5 | 5.3 | 291.3 | 10.8
Canada | 882.0 | 10.2 | 697.2 | 8.1 | 698.8 | 8.1 | 744.5 | 8.6
Denmark | 54.1 | 4.0 | 78.0 | 5.7 | 43.8 | 3.2 | 131.9 | 9.6
Finland | 9.8 | 0.7 | 32.4 | 2.4 | 38.1 | 2.8 | 72.6 | 5.4
France | 1 263.1 | 8.4 | 1 519.0 | 10.1 | 557.5 | 3.7 | 840.9 | 5.6
Germany | 1 366.0 | 7.2 | 475.0 | 2.5 | 1 419.0 | 7.5 | 1 536.0 | 8.1
Greece | 15.1** | 0.6** | 38.2** | 1.5** | 94.1 | 3.7 | 180.0 | 7.0
Ireland | 9.7** | 0.8** | 58.0** | 4.5** | 68.0 | 5.3 | 218.4 | 17.0
Israel* | 334.1 | 14.5 | 342.3 | 14.9 | 220.4 | 9.6 | 117.4 | 5.1
Italy | 30.7** | 0.2** | 277.4** | 2.1** | 577.7 | 4.3 | 1 381.6 | 10.4
Luxembourg | 18.9 | 14.0 | 11.1 | 8.2 | 17.3 | 12.8 | 29.3 | 21.7
Netherlands | 296.0 | 7.3 | 310.0 | 7.6 | 193.0 | 4.7 | 202.0 | 5.0
New Zealand | .. | .. | .. | .. | 124.9 | 9.5 | 270.7 | 20.6
Norway | 33.7 | 2.5 | 69.4 | 5.1 | 78.3 | 5.8 | 195.5 | 14.5
Portugal | 38.7** | 1.5** | 58.6** | 2.3** | 111.2 | 4.3 | 107.5 | 4.2
Spain | 80.3 | 0.7 | 331.7 | 2.8 | 583.6 | 5.0 | 1 506.3 | 12.9
Sweden | 151.2 | 6.2 | 208.1 | 8.5 | 170.2 | 7.0 | 297.5 | 12.2
Switzerland | 231.5 | 11.5 | 224.4 | 11.1 | 176.1 | 8.7 | 387.2 | 19.2
United Kingdom | 990.2 | 6.4 | 224.7 | 1.5 | 642.0 | 4.2 | 2 063.6 | 13.3
United States | 7 277.2 | 8.6 | 3 563.9 | 4.2 | 5 230.4 | 6.2 | 6 430.2 | 7.6
OECD total (22) | 13 960.9 | 7.0 | 9 623.6 | 4.8 | 11 771.9 | 5.9 | 18 115.4 | 9.0
EU total (15) | 4 654.9 | 4.9 | 3 973.0 | 4.2 | 4 792.9 | 5.0 | 9 100.3 | 9.6
StatLink  http://dx.doi.org/10.1787/888933214214

Notes and sources are to be found at the end of the chapter.

Section 13.2. Regions of parental origin

Background

Indicator

This section compares the regions of origin of the three different groups of young people from migrant backgrounds. It considers that an immigrant’s region of origin is his or her region of birth. As for the native-born of mixed parentage it is the immigrant parent’s region of birth. For those with two foreign-born parents, the father’s region of birth is considered. Countries of origin are grouped as follows: EU28, other Europe, Africa, Asia, Latin America and the Caribbean, and United States, Canada and Oceania. High- and lower-income countries are also distinguished using the World Bank country classification (http://data.worldbank.org/about/country-and-lending-groups#High_income).

Coverage

Population aged 15 to 34 years old. For the groupings, see Indicator 13.1.

Across the OECD in 2013, an average of only one in eight native-born immigrant offspring aged 15 to 34 had at least one parent born in a high-income country (Figure 13.2). In the EU, by contrast, the ratio was almost one in four. In the OECD, percentages ranged from 6% in the United States, 8% in the Netherlands and Austria, to 88% in Luxembourg. As for parents’ region of origin in non-European OECD countries, most were born in Latin America and the Caribbean (61%), a proportion chiefly attributable to the high number of offspring from that region living in the United States. The largest group in the EU is made up of native-born people whose fathers migrated from Africa, with more than one-third of fathers born in that region (Figure 13.3). That large share is driven chiefly by countries like France, Belgium, Spain and the Netherlands, which have close links with some African countries. The second largest group in the EU is immigrant offspring from non-EU European countries. They account for particularly high shares in Scandinavia and countries of longstanding labour migration from non-EU Europe, such as Germany and Austria (Figure 13.A1.2).

With regard to native-born children of mixed background, the share of those whose migrant parent was born in a high-income country is substantially higher than among the native-born with two immigrant parents. The percentages are 45% in the OECD and 49% in the EU, driven primarily by the high proportion of EU-born migrant parents in the mixed parentage group – 45% on average in the EU and 28% in non-European OECD countries.

Of immigrants who arrived as children in the OECD, one-quarter were born in a high-income country – a share that is slightly higher in the European Union at one-third. Like the two previous categories, the country with the highest share of young immigrants from high-income countries is Luxembourg (75%). The one with the lowest share is again the United States (15%), followed by Denmark (15%) and the Netherlands (19%). In North America, almost half of all immigrants who arrived as children came from Latin America or the Caribbean.

The average share of young immigrants arriving from high-income countries as adults is 23% in the OECD and 36% in the EU (levels similar to those for child arrivals), with EU immigrants accounting for higher average shares in both non-European OECD countries (9%) and the EU (35%). Not counting intra-European migration, distributions by origin of both immigrants who arrived before the age of 15 and those who arrived later, show few differences and reflect historical migration patterns.

Africa is the most common birthplace of young non-EU migrants to Belgium and France, while in the United Kingdom, Canada and New Zealand most immigrants come from Asian countries. Also from Asian countries are the young humanitarian migrants in Sweden, Norway and Denmark, which take in large flows of refugees. In the United States and Spain, by contrast, most immigrants were born in Latin America or the Caribbean.

Figure 13.2. Regions of origin of immigrants and immigrant offspring aged 15-34, 2013

Percentage of all 15-34 year-olds

StatLink  http://dx.doi.org/10.1787/888933213281

Figure 13.3. Distribution of immigrants and immigrant offspring aged 15-34 by their own or parents’ region of origin, 2013

StatLink  http://dx.doi.org/10.1787/888933213394

Notes and sources are to be found at the end of the chapter.

Section 13.3. Endogamy and mixed couples

Background

Definition

Partnership choice can be analysed by the rate of endogamy, i.e. the share of unions in which both partners or spouses are of the same origin. The terms “regions of origin” denotes either regional groupings of countries of birth or, for the native-born, parents’ countries of birth. For further information, see Indicator 2.3.

Coverage

All 15-34 year-olds who report being in a couple.

Across the European Union in 2008, 52% of native-born young people of immigrant parentage lived together with spouses or partners from the same region of origin – i.e. immigrants or children of immigrants who originated from the same region of origin as their parents (Figure 13.4). Among immigrant offspring, rates of endogamy are as low as one in three in France and less than one in two Israel, but higher in Belgium and Estonia among the offspring of both immigrant and mixed parentage. Ties with regions and countries of origin are, in fact, much looser among offspring of mixed parentage, the vast majority of whom live in a union with someone born in a country other than their immigrant parent’s birthplace. EU-wide, in fact, just 12% live with a partner of the same origin as the immigrant parent. At the other end of the spectrum are young nationals with native-born parents, nine out of ten of whom live in endogamous couples.

Young immigrants in the European Union are generally more likely than immigrant offspring to live with a partner from their region of origin, though that likelihood depends on the age of arrival. Those who immigrate before they are 15 build ties with the native-born during their childhood and are less likely than adult-arrival immigrants to live with a partner from their birth region. In several countries – like the United Kingdom, Germany and Belgium – they are actually less endogamous than immigrant offspring.

The average rates of endogamy in the European Union are 43% among child-arrival immigrants and 52% among immigrant offspring. At 68%, immigrants who arrive after the age of 15 show the highest rate, which may be because they were already in a union with a national from their country of birth even before they migrated. In Ireland, Portugal and Italy, childhood immigrants are three times less likely than other immigrants to live with a partner from their country or region of origin. By contrast, in Germany, Austria and, to a lesser degree, the Netherlands, the endogamy rates of childhood and adult immigrants are similar.

Figure 13.4. Endogamy rates by migration background among 15-34 year-olds living as couples, 2008

StatLink  http://dx.doi.org/10.1787/888933213474

Notes and sources are to be found at the end of the chapter.

Section 13.4. Participation in early childhood education programmes

Background

Indicator

This section examines attendance rates in early childhood education programmes. Early childhood education programmes encompass such pre-primary education provision as preschool, kindergarten, and day care. The way they are organised and the ages of children to whom they cater vary widely from one country to another. A number of countries offer some preschool programmes free of charge. The quality and opening hours of preschool facilities are also highly variable.

The indicator is rounded off by data from the OECD’s 2012 Programme for International Student Assessment (PISA) on how at least one year of preschool attendance affects school performance of 15-year-olds.

Coverage

Children aged three to less than six years old. Figures may include children already attending primary school, depending on the age at which compulsory schooling starts in some countries. For present purposes, immigrants’ offspring are considered as 3-6 year-olds living in households where all household maintainers were born abroad. Children who are considered to be native-born children are those where all household maintainers were born in the host country.

Across the OECD, an average of 69% of 3-6 year-old immigrant children were enrolled in early childhood education programmes in 2012 – an attendance rate that was 7 percentage points lower than among their native-born peers (Figure 13.5). In the European Union, they are only marginally less likely than native-born children to be preschool-goers. There are, however, some exceptions: Italy, Norway and the Czech Republic, for example, show attendance rates that are 10 percentage points lower among immigrant children.

In countries where preschool programmes are free, attendance rates are higher than 90% and gaps between the children of immigrants and the native-born are negligible. Attendance is, by contrast, much lower among families in all countries where parents have to pay, as in the United States (apart from the poorest families). In countries where there is little demand from families or the preschool provision starts at four or five years old (e.g. Greece and Ireland), attendance rates among immigrant offspring are generally well below those of the children of the native-born.

Yet early childhood education in the host country is particularly beneficial for immigrant offspring. Among children of comparable socio-economic backgrounds, those who attend preschool in their current OECD host country obtain better reading literacy results at 15 years old than those who do not. The gap between the two groups is 75 points, roughly equivalent to two years at school, although there is a less of a preschool gap among children with native-born parents (Figure 13.6).

Immigrant pupils derive particular advantage in the United States, France, Israel and Finland. The finding has special resonance in the United States where proportions of immigrant preschool-goers are relatively low.

Figure 13.5. Early childhood education attendance rates , 2013

Percentages, children aged 3 to less than 6-year-old

StatLink  http://dx.doi.org/10.1787/888933213481

Figure 13.6. Mean PISA reading scores of 15-year-old students who did or did not attend preschool in the host country, 2012, differences in points

StatLink  http://dx.doi.org/10.1787/888933213499

Notes and sources are to be found at the end of the chapter.

Section 13.5. Reading literacy at 15 years old

Background

Indicator

Reading literacy results are drawn from the OECD Programmes of International Student Assessment (PISA) tests. A 40-point gap is equivalent to roughly a year of school. Survey results for 2012 are compared to those of 2003.

Coverage

Pupils aged 15 years old at the time of the survey (with three-month margin). For the groupings, see Indicator 13.1.

Across most of the OECD, the average level of reading literacy among children of immigrant background in 2012 was lower than that of the offspring of native-born parents. Foreign-born children lagged 21 points behind and the native-born of immigrant parentage 3 points. The shortfalls were as high as 42 and 32 points in the European Union and even higher in Benelux, Germany, Austria, Denmark, Finland, France and Sweden. The situation was worrying in southern Europe, and Mexico, where the showings of pupils with immigrant backgrounds were weak in comparison to international results and to those of host-country pupils with native-born parents (Figure 13.7). Results were good, however, in the settlement countries, the United Kingdom and Ireland. And throughout the OECD, with a few exceptions such as Belgium and Germany, pupils with only one foreign-born parent were as good as, and sometimes better than, those with both parents born in the host country.

Since 2003, the rise in proportions of pupils of immigrant background has gone hand in glove with a slight overall improvement in their results, the only exceptions being Scandinavian and Southern European countries (Tables 13.A1.1 and 13.A1.2 in Annex 13.A1). The performance gap with the offspring of the native-born has, in contrast, remained stable (Figure 13.8) in most countries, save in southern Europe, part of Scandinavia and France. In Germany, Austria, Belgium and the settlement countries, however, results of pupils with a migration background have improved since 2003.

Families’ socio-economic backgrounds are a decisive element in academic performance. For the same background, gaps between pupils of foreign- and native-born parents have narrowed, albeit unevenly from one country to another and depending on the capacity of school systems to bring out the best in pupils from underprivileged backgrounds (Tables 13.A1.3 and 13.A1.4). Across the OECD, the difference in the average marks between the most privileged and underprivileged pupils in the PISA economic, social, and cultural status index (ESCS) is over 100 points among immigrant students, 87 points among those whose parents are foreign-born (Table 13.A1.5), and 84 points among the children of natives. The inference may be that a deprived background penalises children of immigrant origin even more than others.

Figure 13.7. Mean PISA reading scores of 15-year-old students by migration background, 2012

StatLink  http://dx.doi.org/10.1787/888933213509

Figure 13.8. Mean PISA reading scores of 15 year-old students by migration background, 2003 and 2012

Differences with native-born offspring of native-born, in points

StatLink  http://dx.doi.org/10.1787/888933213510

Notes and sources are to be found at the end of the chapter.

Section 13.6. Proportions of pupils who lack basic reading skills at 15

Background

Indicator

PISA assessment results are broken down into five achievement levels. Pupils who score no higher than Level 1 are considered to be struggling and lacking in basic reading skills. The indicator here denotes the share of pupils who score no better than Level 1 (407 points and below). Also considered in parallel is the share of resilient students – those from a background classified by PISA’s Economic, Social and Cultural Status (ESCS) index as underprivileged, but who perform to a standard that puts them in the top quartile of pupils in their host country.

Coverage

Students aged 15 (more or less three months). For the groupings, see Indicator 13.1.

Across the OECD in 2012, comparable average shares of around 17% of native-born pupils of native- and foreign-born parents struggled with reading literacy at 15 years old. The figure was a lower 14% among children with one foreign-born parent, but over 25% of immigrant children. While proportions are comparable between the offspring of native-born and mixed parents in the European Union, they are higher among native-born children with two immigrant parents (around 25%) and pupils who themselves immigrated (30%).

On average, less than 10% of immigrant children from backgrounds which the ESCS index rates as the most deprived quartile manage to perform in the top quartile of their host country – lightly lower than the 11.3% among the offspring of native parentage from a similar walk of life (Figure 13.10). In the European Union, however, there were only half as many resilient immigrant pupils as ones with native-born parents. The countries where disfavoured foreign-born students are most likely to be among the best are settlement destinations like the United States and Israel and the United Kingdom. Many longstanding immigrant destinations in Europe, however, record resilience rates among immigrant pupils that are as low as under 5% – four or more times lower than among the offspring of native-born parents. Examples of such countries are France, Portugal, Luxembourg and Germany.

Speaking the host country’s language at home is generally good for pupils. The gaps in PISA test results between pupils born to foreign- and native parents narrow by over a half in northern Europe, France and Switzerland among immigrants who speak a PISA test language, i.e. a host-country language, at home. For comparable socio-economic backgrounds, the price of not speaking a PISA test language at home is an average drop of 9 points across the OECD and 20 in the European Union (Figure 13.11).

Arriving in the host country before the age of five contributes to better results among immigrant pupils. Those who arrive between the ages of 11 and 16 obtain marks that are, on average, 30 points lower (Table 13.A1.6), with particularly wide gaps of over 100 points in Israel, Iceland, France and Germany. In Austria, the United Kingdom, the Netherlands and the United States, differences are less marked, however.

Other factors that may influence performance are the kinds of schools that pupils of immigrant background attend. Adverse effects have less to do with high concentrations of such pupils than with the proportions of children from underprivileged homes, regardless of origin. In schools of socio-economically comparable level – and classified accordingly into quartiles – performance gaps between pupils with immigrant parents and the rest narrow in the vast majority of countries. (Table 13.A1.7 in Annex 13.A1).

Figure 13.9. Shares of low school performers in reading among 15-year-old students by migration background, 2012

StatLink  http://dx.doi.org/10.1787/888933213528

Figure 13.10. Shares of resilient 15-year-old students by migration background, 2012

StatLink  http://dx.doi.org/10.1787/888933213184

Figure 13.11. Differences in PISA reading scores between 15-year-old immigrant students who generally speak the test language at home and those who do not, 2012

StatLink  http://dx.doi.org/10.1787/888933213193

Notes and sources are to be found at the end of the chapter.

Section 13.7. Young adults’ educational attainment levels

Background

Indicator

See Indicator 7.1.

Coverage

People aged 25-34 years old who are not in education. For the groupings, see Indicator 13.1

An average of 45% of immigrant offspring in OECD countries were tertiary-educated in 2012-13 –similar to the proportion of children with native-born parents (Figure 13.12). In the European Union, by contrast, they were less likely to hold degrees than offspring of native-born. With the exception of Norway and the United States, there are wide variations between the two groups and from one country to another. Immigrant offspring are more likely to have higher education than the children of native-born parents in Canada, the United Kingdom and Israel, where over half do so. In all other countries, they are underrepresented in higher education, particularly in France, Denmark and Spain, where they often have no or low education. Although the same may be said of Germany and Austria – where relatively few immigrant children go on to tertiary education – most children pursue non-higher post-secondary education pathways, irrespective of their origin.

Young people of mixed parentage find their place in the education system more easily. With the exceptions of Germany and Finland, their levels of attainment are very similar to those of students with two native parents.

Everywhere, apart from Australia and Canada, immigrants are less likely than the offspring of natives to have tertiary degrees. Arriving in the host country before the age of 15 is not associated with a higher chance of having higher education. It merely lessens the likelihood of no or low education, particularly in the European Union, where two in five immigrants who arrive after the age of 15 and one in three who arrive before receive no or low education. In countries with relatively high inflows of skilled immigrants like Australia and New Zealand, or in those (e.g. Denmark, Luxembourg, Norway and Switzerland) where the bulk of foreigners are from another EU member country, higher proportions of latecomers have degrees than immigrants schooled – even partly – in the host country.

Overall, more women than men enter higher education. Apart from a few exceptions, the trend is true of both immigrant and native offspring even if the gender gap is narrower among immigrants (Figure 13.13). Unlike their male peers, women appear to enjoy a higher chance of going on to higher education if they attend school in the host country.

Figure 13.12. Low- and highly educated 25-34 year-olds who are not in education, 2013

Percentages of each group

StatLink  http://dx.doi.org/10.1787/888933213202

Figure 13.13. Gender gap in the rates of highly educated 25-34 year-olds not in education, by migration background, 2013

StatLink  http://dx.doi.org/10.1787/888933213210

Notes and sources are to be found at the end of the chapter.

Section 13.8. Young adults’ literacy skills

Background

Indicator

The literacy skills indicator is drawn from the OECD’S 2012 Programme for the International Assessment of Adult Competencies (PIAAC). For further detail, see Indicator 7.2.

Coverage

People aged between 16 and 34 years old at the time of the survey. Immigrant offspring are people born in the host country to two foreign parents (GEN2). Their results are compared to those of children born in the host country to two native-born parents (NB) and those of immigrants (or the foreign-born [FB]). For reason of sample size, immigrant offspring’s scores by levels of education and literacy apply only to a limited number of countries and no OECD or EU averages are given.

The literacy scores of immigrant offspring lie between those of immigrants and the children of natives. Their average score in 2012 was 271 points (the upper limit of PIAAC Level 2) against 254 points (mid-Level 2) among immigrants and 286 (Level 3) for offspring of parents born in the host country (Figure 13.14). Immigrant offspring’s average scores were weakest in Belgium, Austria, Denmark and Germany, where they were similar to the performance of immigrants. Just as for all working-age immigrants (Indicator 7.2), young immigrants’ scores were at their lowest in southern Europe, Scandinavia and France, ranging from 227 to 242 points. They lag particularly far behind their peers with two native-born parents in the Scandinavian countries and the Netherlands. In all the OECD countries under consideration, 30% of young immigrants show very basic reading skills (Level 1 or less), in contrast to just 10% of their counterparts with native parents (Figure 13.15).

Immigrant offspring score as well as, if not better than, the offspring of native-born parents in North America and Australia, where between 15% and 20% shows standards equivalent to PIAAC Level 4 or more, i.e. are on a par with their peers who have no migrant background. Only small shares of immigrant offspring lack the basic skills (score equivalent to or lower than Level 1) in these countries, even though those shares are considerably higher than among the children of natives.

Literacy increases with the level of education attained, although the disparities between the two ends of the education spectrum are generally wider among immigrants than among the offspring of natives. In the OECD, the average literacy score of immigrants who graduate from secondary school (medium education) is lower than among people with low or no education born in the host country. Among the poorly educated, immigrants’ scores are well short of others’ – particularly in the United Kingdom, Sweden, Belgium and Italy, where those with low or no education obtain the weakest average score.

A further consideration is that a tertiary degree obtained abroad may not be the guarantee of sufficient linguistic proficiency in a host country whose language is little spoken outside its borders. In the Scandinavian countries, for example, immigrant degree holders score worse in literacy than the native-born with low or no education (Figure 13.16) – probably because immigrants’ command of the language prevents them from giving the full measure of their skills.

Figure 13.14. Mean literacy scores by migration background among 16-34 year-olds, 2012

StatLink  http://dx.doi.org/10.1787/888933213225

Figure 13.15. Distribution by migration background and literacy score among 16-34 year-olds, 2012

StatLink  http://dx.doi.org/10.1787/888933213234

Figure 13.16. Mean literacy scores of foreign- and native-born 16-34 year-olds by level of education, 2012

StatLink  http://dx.doi.org/10.1787/888933213241

Notes and sources are to be found at the end of the chapter.

Section 13.9. Early school leaving

Background

Indicator

Proportion of young people aged 15-24 who are neither in school or training and have gone no further than lower-secondary school.

Coverage

People aged 15 to 24 years old. For the groupings, see Indicator 13.1.

Across the OECD in 2013, an average of nearly 10% of pupils with two immigrant parents left the education system prematurely. The proportion was comparable among young people with two native-born parents. However, young immigrants who arrived in the host country after the age of 15 are more likely to drop out early – either before they arrive or on completion of compulsory schooling in the host country. One-quarter of them do so, compared to 14% of their peers who arrived before the age of 15. The school-leaving gap is generally more pronounced in EU countries. Adult-arrivals are more likely to leave school early than the offspring of people born in the host country, in particular in Finland, Austria, Belgium, France and Germany (Figure 13.17).

In Scandinavian countries (except Finland) and the United States, the situation of native-born immigrant offspring is comparable to that of the children of native parents. In non-European settlement countries and the United Kingdom, it is even better. As for pupils of mixed parentage, drop-out rates are relatively similar to those observed among their peers with no migrant background.

Figure 13.17. Early school leavers among 15-24 year-olds, 2013

Differences in percentage points with native-born offspring of native-born

StatLink  http://dx.doi.org/10.1787/888933213253

Notes and sources are to be found at the end of the chapter.

Section 13.10. Transition from school to work

Background

Indicator

This indicator denotes periods of time needed to transit from formal education to a first job that exceed three months. This section also supplies information on percentages of youngsters who have never held a job longer than three months. Data are available for 2009 only and are not available for non-European countries.

Coverage

Population aged 15 to 34 years old. For the groupings, see indicator 13.7.

Across the European Union, an average of over one-third of 15-34 year-old native-born immigrant offspring had never held a job longer than three months in 2009. A similar proportion of young immigrants were in the same situation compared with 29% of offspring of children of native-born parents and 26% of those of mixed parentage. Those trends should be seen against the backdrop of the rise in youth unemployment (Indicator 13.13) triggered by the 2007-08 economic crisis.

It is a known fact that the transition from school to work can have long-term consequences for labour market integration. Youngsters with immigrant parents who struggle to make the transition are at a considerable risk of experiencing further difficulty in finding a suitable job. The highest proportions of the native-born offspring of immigrant parents who have never worked in a job for more than three months are to be found in Germany, Spain and Italy. Although it is common practice in Germany to enter stable employment at a late age, the Italian situation seems due to the lack of pathways bridging the gap between formal education and the labour market. All school-leavers in Italy suffer, whatever their migration background. In contrast, low proportions who have never worked – as in the United Kingdom and Ireland – may spring from the prevalence of short vocational pathways and the attendant risk of finding a non-sustainable job.

As for those who manage to find a job that lasts at least three months in the European Union (which includes those who are not currently employed), the mean duration of the school-to-work transition is much the same among the offspring of the native-born and native-born youngsters from a migrant background (10 to 13 months) (Figure 13.18 and Table 13.A1.8). Southern European countries, Belgium and the Czech Republic stand out as the countries where transition time lasts longest for the native-born offspring of foreign-born parents and, with the exception of Italy, average durations (which range from 20 to 33 months) are significantly longer than for the children of native parents. In contrast, transitions are relatively short (seven to nine months) for immigrant offspring in Sweden, the Netherlands, Luxembourg, Germany, Switzerland, the United Kingdom and Ireland. Nevertheless, they are generally slightly longer than for the offspring of the native-born.

In the European Union, immigrants take longer to make the switch from school to work, even when they have been partly educated in the host country. Durations are 23 months on average for immigrants who arrived before the age of 15 and 21 months among other migrants. The longest transition times for immigrants arriving as children are in the countries hardest hit by the crisis, such as Greece, Italy and Spain, where they range from 31 to 40 months. By contrast, it takes less than eight months to make the move to the workplace in some central eastern European countries, Ireland, the Netherlands and Sweden.

Figure 13.18. Average duration of school-to-work transition periods to get a first job over 3 months, 2009

Durations in months, population aged 15 to 34 year-olds

StatLink  http://dx.doi.org/10.1787/888933213261

Notes and sources are to be found at the end of the chapter.

Section 13.11. Neither in employment, education or training

Background

Indicator

The rate of people not in employment, education or training (NEET) rate complements the unemployment rate. It is a fuller indicator than the unemployment rate of how many and why young people are excluded from the labour market: many may still be in education, which distorts labour market participation and unemployment rates. The NEET rate is disaggregated into three further components: “inactive”, “short-term unemployment”, and “long-term unemployment” to better understand its country-specific patterns.

Coverage

Population aged 15 to 34 years old. For the groupings, see Indicator 13.1.

In most OECD countries, immigrants and the native-born offspring of migrants are more likely to be NEET than the children of the native-born (Table 13.2). Around one in five of the native-born young with immigrant parents (17% in the OECD and 19% in the EU) fell into the NEET category - in other words, 800 000 in the European Union and 2.2 million in the OECD in 2013. At 860 000 and 2.2 million, numbers are similar among young immigrants who arrived as children, but higher for those who arrived as adults, with almost one in three being NEET – 2.2 million in the European Union and 4.3 million in the OECD. NEET rates among both categories of immigrants are particularly high in Belgium, Finland and southern Europe.

In Belgium, Spain and Finland, more than one-third of the native-born offspring of two migrant parents across all levels of education were NEETs, while in Canada, Switzerland and Luxembourg less than one in ten were. The NEET rates among the native-born of mixed background are comparable to those of the children of native-born parents. In some countries, such as Canada, Germany and the United States, their NEET rates are even lower.

In all the population groups under review, the poorly educated are more likely than the highly educated to be NEETs. The over-representation of immigrants and their offspring among the poorly educated explains in part why they show higher overall NEET rates than the offspring of the native-born (Figure 13.19). In southern Europe and some Nordic countries (e.g. Denmark and Finland), which record the highest immigrant population NEET rates, the shares of NEETs who are also poorly educated are significantly greater among the population with a migrant background than without. In nearly all countries, elevated rates affect young immigrant women who arrived as adults, with economic inactivity being the chief cause.

Table 13.2. NEET rates by migration background among 15-34 year-olds, 2013
Percentages of the population
| Native-born offspring of foreign-born | Native-born with a mixed background | Foreign-born who arrived as children | Foreign-born who arrived as adults
| Number of people in NEET (thousands) | Percentage of NEET | Difference (+/-) with native-born offspring of native-born | Number of people in NEET (thousands) | Percentage of NEET | Difference (+/-) with native-born offspring of native-born | Number of people in NEET (thousands) | Percentage of NEET | Difference (+/-) with native-born offspring of native-born | Number of people in NEET (thousands) | Percentage of NEET | Difference (+/-) with native-born offspring of native-born
Australia | 62.3 | 11.5 | -2.0 | 88.1 | 11.8 | -1.8 | 92.2 | 17.9 | +4.3 | 129.5 | 15.4 | +1.8
Austria | 22.1 | 24.2 | +14.9 | 12.4 | 15.9 | +6.7 | 21.7 | 20.7 | +11.4 | 60.6 | 28.1 | +18.9
Belgium | 64.3 | 32.5 | +18.2 | 50.2 | 20.8 | +6.6 | 40.9 | 28.7 | +14.5 | 112.9 | 38.8 | +24.5
Canada | 85.0 | 9.6 | -2.9 | 72.4 | 10.4 | -2.1 | 75.1 | 10.7 | -1.8 | 151.0 | 20.3 | +7.8
Denmark | 10.8 | 20.1 | +6.4 | 12.7 | 16.3 | +2.6 | 11.4 | 26.2 | +12.5 | 55.4 | 42.0 | +28.3
Finland | 3.5 | 35.7 | +16.8 | 8.7 | 26.7 | +7.8 | 11.9 | 31.2 | +12.3 | 29.9 | 41.2 | +22.3
France | 293.5 | 23.2 | +9.1 | 243.3 | 16.0 | +1.8 | 131.2 | 23.6 | +9.4 | 325.0 | 38.7 | +24.5
Germany | 171.0 | 12.5 | +3.3 | 26.0 | 5.5 | -3.8 | 209.0 | 14.7 | +5.5 | 439.0 | 28.6 | +19.3
Greece | .. | .. | .. | .. | .. | .. | 37.7 | 40.1 | .. | 88.7 | 49.3 | ..
Ireland | .. | .. | .. | .. | .. | .. | 17.7 | 26.2 | .. | 52.4 | 26.4 | ..
Israel* | 78.9 | 23.5 | -4.9 | 81.9 | 23.7 | -4.7 | 54.3 | 24.5 | -3.9 | 27.1 | 23.1 | -5.3
Italy | .. | .. | .. | .. | .. | .. | 159.4 | 27.6 | .. | 526.1 | 38.1 | ..
Luxembourg | 1.5 | 8.2 | +1.3 | 0.8 | 7.8 | +1.0 | 1.8 | 10.5 | +3.7 | 5.0 | 18.2 | +11.3
Netherlands | 45.0 | 15.3 | +8.0 | 21.0 | 7.0 | -0.3 | 36.0 | 18.6 | +11.3 | 61.0 | 30.2 | +22.9
New Zealand | .. | .. | .. | .. | .. | .. | 14.8 | 11.8 | .. | 39.5 | 15.1 | ..
Norway | 4.3 | 13.9 | +4.3 | 8.0 | 12.0 | +2.4 | 12.6 | 17.3 | +7.7 | 58.5 | 31.3 | +21.6
Portugal | .. | .. | .. | .. | .. | .. | 22.4 | 20.2 | .. | 29.2 | 27.2 | ..
Spain | 27.9 | 34.8 | +8.1 | 88.2 | 26.6 | -0.1 | 203.6 | 35.0 | +8.3 | 659.9 | 43.8 | +17.1
Sweden | 19.8 | 14.5 | +3.5 | 25.6 | 12.6 | +1.6 | 30.6 | 15.5 | +4.5 | 51.8 | 21.6 | +10.5
Switzerland | 19.4 | 8.4 | +1.7 | 20.7 | 9.2 | +2.6 | 21.4 | 12.1 | +5.5 | 62.5 | 16.1 | +9.5
United Kingdom | 202.3 | 20.4 | +4.1 | 42.8 | 19.0 | +2.7 | 95.3 | 14.8 | -1.4 | 398.6 | 19.3 | +3.0
United States | 1 096.5 | 19.1 | +0.3 | 577.7 | 17.3 | -1.6 | 957.7 | 19.1 | +0.3 | 1 633.9 | 25.4 | +6.5
OECD total (17) | 2 208.1 | 16.6 | -0.1 | 1 380.6 | 15.5 | -1.2 | 2 006.6 | 18.9 | +2.2 | 4 261.4 | 26.9 | +10.3
EU total (11) | 861.7 | 19.1 | +4.2 | 531.7 | 15.2 | +0.3 | 793.5 | 20.2 | +5.2 | 2 198.9 | 30.9 | +15.9
StatLink  http://dx.doi.org/10.1787/888933214231

Figure 13.19. NEET rates by migration background and level of education, population aged 15 to 34, 2013

Percentages of the population

StatLink  http://dx.doi.org/10.1787/888933213278

Notes and sources are to be found at the end of the chapter.

Overall, the native-born children of immigrants are less likely to be NEET than their immigrant peers, including those who arrived as children. That pattern is not, however, observed in Austria, Belgium, Finland and the United Kingdom. In 2013, Finland, Spain and Greece stand out for having the highest NEET rates among young immigrants who arrived as children, while Canada, New Zealand and Luxembourg have the lowest. Those rates for young immigrants who arrived as adults fall below 20% only in countries that have welcomed large inflows of highly skilled labour migrants, e.g. settlement destination like Australia and New Zealand, Luxembourg, the United Kingdom and Switzerland.

The economically inactive are the biggest single group among NEETs (see Figure 13.A1.3). Their share is highest among immigrants who arrived as adults (an average of 73% in the European Union and 78% in the OECD), especially in countries with high shares of migrants arriving for family reunification (Germany, Denmark and the United States). Long-term unemployment, however, accounts for a significant share of NEETs in countries such as Belgium and Switzerland and the recent immigration countries hardest hit by the crisis (Greece and Ireland).

Both male and female immigrants and immigrant offspring are more likely to be NEET than their counterparts without a migrant background (Figure 13.21). While few gender differences may be observed in unemployment, more women generally fall into the NEET category than men, chiefly because they account for a larger share of the inactive (Figure 13.20). The gender difference is widest among immigrants who arrived as adults – an average of 24 percentage points in the OECD and 20 points in the European Union. It is at least five times greater than the gender gap among youth with native-born parents in the OECD and the European Union and some three times wider than among immigrants who arrived as children.

Figure 13.20. Gender gaps in NEET rates by migration background among 15-34 year-olds, 2013

Differences in percentage points

StatLink  http://dx.doi.org/10.1787/888933213293

Figure 13.21. NEET rates by migration background and gender among 15-34 year-olds, 2013

Percentages of the total population

StatLink  http://dx.doi.org/10.1787/888933213308

Notes and sources are to be found at the end of the chapter.

Section 13.12. Employment

Background

Indicator

The employment rate indicator denotes the share of employed people in the total population. For further information, refer to Indicator 5.1.

Coverage

The population aged 15 to 34 years old not in education. For the groupings, see Indicator 13.1.

In all countries for which data are available (except Israel), both immigrant youth and the offspring of immigrants are less likely to be employed than those with native-born parents. As for the native-born offspring of two migrant parents, the gap in employment rates in 2013 was on average 12 percentage points in the European Union – i.e. a rate of 65% among immigrant offspring and 77% for their counterparts with native-born parents in 2013. In the OECD, the average gap was 4 percentage points (Table 13.A1.9).

While in Spain less than two out of five native-born offspring of immigrants are employed, more than 80% have a job in countries such as Australia, Luxembourg and Switzerland. In the instance of Spain, however, the total size of the active population of young people with immigrant parents is small, since half of 15-34 year-olds are still in education.

Immigrants who arrived as children show similar average employment rates to the native-born offspring of two foreign-born parents – 66% in the European Union and 70% in the OECD. Although the latter have generally lived longer in the host country, they are not always more likely to be employed than their peers who immigrated as children – possibly because of cohort effects. The employment rates of both groups vary from less than 50% in those worst hit by the economic crisis (e.g. Spain, Greece and Ireland) to more than 80% in Luxembourg and Switzerland.

Immigrants who arrive as adults show the worst average labour market outcomes. Their employment rate is 15 percentage points less than that of the offspring born to native parents in the European Union, and 8 points across the OECD. The countries with the largest gaps are such EU15 countries as Belgium, Denmark, France and the Netherlands, which have high percentages of immigrants from low-income countries. In contrast, settlement destinations like the United States and Australia, and countries with large proportions of immigrants from high-income countries like Luxembourg, or large proportion of labour migrants (Italy and Ireland) show the narrowest disparities in labour market outcomes. In those countries, together with the United Kingdom, however, foreign-born men who migrated as adults have better labour market outcomes than their native-born counterparts, while female adult migrants have significantly worse ones. One reason might be that a sizeable number migrated for family reunification purposes (Figure 13.22).

Figure 13.22. Employment rates by migration background, people aged 15-34 years old, 2013

StatLink  http://dx.doi.org/10.1787/888933213313

Figure 13.23. Employment rates by migration background and educational level, people aged 15 to 34 not in education, 2013

Differences in percentage points with native-born offspring of native-born

StatLink  http://dx.doi.org/10.1787/888933213321

Higher education helps the young with and without migrant backgrounds into the workplace. However, highly educated young with a migration background (native-born offspring of immigrants and immigrants arrived as children) can hardly close the gap with the offspring of natives in the EU (Figure 13.23), Conversely, in settlement countries as well as in Luxembourg and Switzerland, these groups have a similar likelihood to be employed. Employment rates of immigrants who arrived as adults, since they have educational credentials from abroad which host-country employers have trouble assessing and labour markets substantially downgrade.

Notes and sources are to be found at the end of the chapter.

Among offspring of immigrants, improvements in employment rates associated with high levels of education are large for both gender (Figure 13.24). Among young men of immigrant parents in the EU, education is even a slightly stronger driver of better employment prospects than it is for their peers of native-born parents.

In most countries, the employment rates of the young population with a migration background have deteriorated since 2007-08, though not in Luxembourg and the United States or among those who immigrated as children to Germany, Sweden and the United Kingdom (Figures 13.25 and 13.A1.4). With regard to the employment situation of immigrant offspring, it generally worsened more sharply than that of the offspring of the native-born. The largest drops came in Denmark and the Netherlands, followed by France. In Germany, employment rates declined among immigrant offspring, while they increased among offspring of natives.

As for immigrants who arrived as children, the employment gap with the offspring of native-born parents widened further in most countries except forLuxembourg, Germany, the United States, New Zealand, Sweden and the United Kingdom (Figure 13.25). It worsened most, dropping by 10 points, in Australia, Belgium and Denmark. In mitigation, it should be mentioned that two-thirds of young immigrants were still in work in Australia, though only one in two were in Denmark.

An overall trend to emerge is the sharper drop in the employment rates of male immigrant offspring than among their female counterparts (Figure 13.A1.5). Although the gender gap narrowed as a result in most countries, employment among immigrant women who entered as children still lags behind that of the offspring of the native-born in all countries under review.

In the European countries that were hit less hard by the crisis (e.g. Austria, Switzerland and Germany), and in the settlement countries, too, the situation of poorly educated immigrant offspring improved relatively to their peers with no migration background between 2007-08 and 2013 (Figure 13.A1.6).

The situation of poorly educated immigrants who arrived as children improved significantly more than that of their native-born peers without migration background in Austria, Luxembourg and, markedly so, in Germany, the United Kingdom and New Zealand (Figure 13.A1.6). In the last three countries, poorly educated immigrants were actually more likely to be in employment than their counterparts of native parentage in 2013. There was a contrasting trend in Spain, Australia and Switzerland, where the employment gap between low-educated immigrants and their peers of native parentage widened.

Labour market integration among highly-educated immigrants varies widely across countries. Those which registered the greatest improvement were Germany and Denmark. By contrast, the labour market situation of highly educated foreign-born youth has, over the last five years, worsened or been stationary in most other countries under review, deteriorating sharply in southern European countries, the United Kingdom, Australia and France.

Figure 13.24. Return to education by migration background and gender, people aged 15 to 34 not in education, 2013

Differences in percentage points between highly and low-educated

StatLink  http://dx.doi.org/10.1787/888933213339

Figure 13.25. Changes in employment rates by migration background among 15-34 year-olds between 2007-08 and 2013

Percentage points

StatLink  http://dx.doi.org/10.1787/888933213346

Notes and sources are to be found at the end of the chapter.

Section 13.13. Unemployment

Background

Indicator

The unemployment rate is the share of unemployed people in the total labour force (employed and unemployed). For further information, refer to Indicator 5.2.

Coverage

The labour force (employed or unemployed) aged 15-34 years old. For the groupings, see Indicator 13.1.

The average OECD-wide unemployment rates of the 15-34 year-old offspring of foreign- and native-born parents were very similar at 13% and 12% respectively in 2013. In the European Union, however, the gap between the two groups was greater – 20% versus 14% (Table 13.A1.10). In Austria, Belgium and the Netherlands, the unemployment rate of immigrant offspring was as much as three times higher than that of their peers of native parentage. In contrast, settlement countries – like Australia, Canada, the United States and Israel – registered rates that were almost the same. The highest unemployment level among immigrant offspring was in Spain (48%), while levels were also high in France, Belgium and the United Kingdom, where one in five immigrant offspring in the labour market was unemployed (Table 13.A1.10).

When it comes to immigrants who arrived before the age of 15, their unemployment rates are 1.4 times greater in the European Union than those of the children of native parents and 1.1 in the OECD. The ratios are highest in Australia, Belgium and Switzerland at more than 2.5. The countries with the highest levels of unemployed immigrants who arrived as children are the ones in Europe worst affected by the crisis, such as Spain and Greece, where rates reach 50%. As already mentioned, though, the grim picture in Spain may be tempered by the fact that almost half of the immigrant population aged 15-34 is still in education. The share of unemployed youth in the country’s total population is therefore not as large as the unemployment rate might suggest.

As for immigrants who arrived as adults, the ratio of their unemployment rates to the offspring of the native-born is 1.4 in the European Union and close to 1.1 in the OECD. The worst unemployment is again to be found in southern Europe, while France and Belgium also have unemployment rates higher than 20%. However, in countries such as the United States, Israel and the United Kingdom, immigrants who migrated as adults are actually less likely to be unemployed than their peers of native parentage.

Unemployment rates among immigrant youth aged 15-24 are particularly high in many European countries, both compared with their older peers (25-34 years old) and with the native-born offspring of native parents in the same age group. Those gaps are especially striking in such EU countries as France, the United Kingdom, the Netherlands and Austria (Figure 13.26). Again, however, the situation can be tempered in those countries by the fact that high proportions of young people of migrant background in the 15-24 age group are still in education.

Native women with foreign-born parents and women who arrived as children are, in general, less likely to be unemployed than their male counterparts. The opposite, though, is true of women who arrived after the age of 15 (Figure 13.27).

Figure 13.26. Unemployment rates, 15-34 year-olds, 2013

StatLink  http://dx.doi.org/10.1787/888933213359

Figure 13.27. Gender gap in unemployment rates, 15-34 year-olds, 2013

StatLink  http://dx.doi.org/10.1787/888933213365

Notes and sources are to be found at the end of the chapter.

Section 13.14. Overqualification

Background

Indicator

The over-qualification rate is calculated as the share of highly educated people employed in low- or medium-skilled jobs among all employees. For further information, refer to Indicator 6.4.

Coverage

People aged between 25 and 34 years old who are highly educated – Levels 5 to 6 in the International Standard Classification of Education [ISCED], excluding the armed forces (International Standard Classification of Occupations [ISCO], Level 0). For the youth groupings, see Indicator 13.1.

In most OECD countries in 2013, young immigrants and the native-born offspring of two immigrant parents aged 25-34 were more likely to be formally overqualified for the jobs they held than their peers with native parents (Figure 13.28). Differences in overqualification rates between people with a migrant background and those born to two native-born parents are more pronounced in the European Union than in non-EU OECD countries. In the United States, for example, around 40% of the native-born, irrespective of their migration background, are overqualified, while the proportion is slightly lower among immigrants, regardless of their age at arrival.

In the European Union, the rate of overqualification among the employed native-born offspring of two migrant parents is 28%, compared with 24% for the children of native-born. Rates vary from 12% in Luxembourg to more than 40% in Spain, with gaps between the offspring of the foreign- and native-born particularly high – at 10 percentage points or more – in European countries such as Germany and the Netherlands (Figure 13.29).

Of tertiary-educated immigrants in employment who arrived as children some 30% are overqualified in the European Union and in the OECD. Those levels are higher than among the offspring of the native-born, but less than those of the native-born with immigrant parents. The highest overqualification rates among immigrants who arrived as children are to be found in Spain, Greece and Ireland, with almost one in two high-educated immigrants working in jobs for which they are formally overqualified. By contrast, in countries such as Canada, the United States and France, such immigrants are even less likely to be overqualified than the offspring of native-born parents.

As for adult-arrival immigrants (a large proportion of whom graduated abroad), the highest over-qualification rates come in countries where many migrants entered relatively recently to take up low-skilled jobs, chiefly in Spain, Italy and Greece. In Greece, almost three in four highly-educated young immigrants work in jobs for which they are overqualified. However, when it comes to differences with the native-born offspring of native parents, gaps are also wide in countries with substantial inflows of humanitarian migrants such as Norway (33 percentage points) and Sweden (26 points). The gap is wide in Israel, too, at 26 percentage points. By contrast, migrants who arrived as adults are less likely to be overqualified than their child-migrant counterparts in countries such as Switzerland and Luxembourg.

While native-born women with foreign or native parents are more likely than their male counterparts to be in jobs that match their formal level of education, immigrant women who arrived as adults are 5 percentage points more likely to be overqualified than their male peers in the OECD (Figure 13.28).

Figure 13.28. Overqualification rates among 25-34 year-olds by migration background and gender, 2013

Percentages of the highly educated population

StatLink  http://dx.doi.org/10.1787/888933213375

Figure 13.29. Overqualification rates by migration background among 25-34 year-olds, 2013

Differences in percentage points with native-born offspring of native-born

StatLink  http://dx.doi.org/10.1787/888933213380

Notes and sources are to be found at the end of the chapter.

Section 13.15. Employment in the public services sector

Background

Indicator

Share of the employed population working in the public services sector. This sector encompasses public administration, healthcare, the social services, and education. For further information, refer to Indicator 6.6.

Coverage

Employed population aged 15 to 34 years old. For the groupings, see Indicator 13.1.

Immigrants and the native-born offspring of two immigrant parents aged 15-34 years old are less likely to be employed in the public services sector than the children of native-born parents. One-fifth of immigrant offspring employed in the European Union worked in the public sector in 2013, compared to one-quarter of youth with native-born parents (Figure 13.30). In the OECD, the share was only slightly more to the advantage of young people with migrant parents – 22% compared to 24% of their peers of native parentage.

While the proportion of native-born offspring of immigrants who work in the public services sector in Germany is less than one in ten, it is as high as one-third in countries like France, the Netherlands and Sweden. The widest differences with the offspring of native-born are to be found in Germany, Austria and Finland

Among the immigrant population who arrived as children, the share working in public services is significantly lower at 15% in the European Union and 18% in the OECD. The percentages who work in public services range from 2% in Australia and 6% in Italy to 37% in Sweden. In this latter country which has a longstanding diversity policy, immigrants who arrived as children are more likely to work in the public services sector than the offspring of the native-born.

Adult-arrival immigrants, however, account for an even lower share of public-sector employees both in the European Union (16%) and the OECD (15%). Part of the reason is that most public sector jobs are no typical entry jobs for adult arrivals in the labour market. Moreover, studies show that children who have a parent working in the public services sector are substantially more likely to work there, too. By that token, having two migrant parents may lessen the prospect of entering the public services sector. The lowest percentages of adult-arrivals working in the public sector are to be found in recent migration destinations like Greece, Italy and Portugal – less than 10% – and the highest share again in Sweden with 32%.

In most European countries, lower levels of public sector employment among immigrants and immigrant offspring account in part for their lower overall employment rates. However, in the United States and the United Kingdom, the relatively low share of people of migrant background in public services is offset by the large number of jobs they hold in the private sector (Figure 13.31).

Figure 13.30. 15-34 year-olds working in the public service sector by migration background, 2013

StatLink  http://dx.doi.org/10.1787/888933213404

Figure 13.31. Breakdown of employment rates in the public services and in other sectors, 2013

Percentage of the population aged 15 to 34 years old

StatLink  http://dx.doi.org/10.1787/888933213410

Notes and sources are to be found at the end of the chapter.

Section 13.16. Child poverty

Background

Indicator

The relative child poverty rate, in accordance with the Eurostat definition used here, is the share of children living in a household whose equivalent annual income lies below the poverty threshold – lower than 60% of a country’s median equivalised disposable income. For further information, see Indicator 8.2.

Coverage

Any person aged less than 16 years old living in a household with at least one maintainer who is aged over 15 years old. The household’s annual equivalised income is attributed to each child.

Across the OECD in 2012, a third of adult immigrants lived in relative poverty, as did over 40% of children in immigrant households (Figure 13.32). Such children were twice as likely to be exposed to poverty as their peers in native households. Relative poverty rates are four times higher among the children of immigrants than those of native parents in the Nordic and Benelux countries. In Greece, Spain and France, between 45% and 55% of children of immigrants live in relative poverty – rates that are twice those of children born to native parents. Such gaps are less glaring in North America, Australia and New Zealand. In the United States, over one-third of children, regardless of their migration background, live in relative poverty.

Poverty is more widespread in families where women are economically inactive or there are many children to be looked after. Both situations are more common in immigrant households. There are some exceptions, however, such as Poland, Latvia and Israel, where immigrant women have less children than the international norms. As a result, relative poverty rates there are lower in immigrant than in native-born households.

Figure 13.32. Relative poverty rates among children aged less than 16, 2012

Percentages

StatLink  http://dx.doi.org/10.1787/888933213424

Notes and sources are to be found at the end of the chapter.

Section 13.17. Voter participation

Background

Indicator

Self-reported voter participation is measured here through public polls in which respondents are asked if they voted in the last national parliamentary elections in their country of residence. For further information, see Indicator 11.2.

Coverage

All 18-34 year-olds entitled to vote in national elections. With the exception of the United Kingdom and Portugal which allow certain nationalities to vote, no OECD member country grants voting rights to foreigners in national parliamentary elections. This indicator therefore applies only to people with the nationality of the country in which they live. For the youth grouping, see Indicator 13.1.

In all OECD countries under consideration, over the period 2002-12, half of all 18-34 year-old nationals born to immigrant parents report that they voted in the most recent national elections. The rate is 70% among their peers with two native parents and very similar among the native-born of mixed parentage (Figure 13.33). Compared with their peers who have native parents, higher proportions of immigrant offspring cast their vote only in the United Kingdom and Israel. In Belgium, where it is compulsory to vote, and in the United States, voting trends among young people of foreign- and native-born parents are very similar.

Two countries where immigrant offspring’s electoral turnout is much lower are Germany and Switzerland, where it is nearly 20 percentage points less. The lack of automatic citizenship for people born in those countries to foreign parents appears not to strengthen civic engagement among those who do naturalise. In Germany – though not in Switzerland – children of mixed parentage, most of whom were German at birth, vote in the same proportions as the offspring of native parents.

Immigrants who are eligible to vote in national elections report being less likely to do so than other groups (see Indicator 11.2). The same trend emerges among immigrant youth, despite variations related to the age at which they arrive in the host country. Two-thirds of immigrants who arrived in an EU country before they were 15 took part in that country’s most recent elections – a proportion comparable with their peers born to native parents and in contrast to a rate of less than 45% among other immigrants. The United States and Israel are again exceptions with immigrants voting in much the same proportions as the offspring of foreign- and native-born parentage, regardless of their age of arrival in the country.

Figure 13.33. Self-reported turnout in the most recent elections by migration background, 2002-12

Percentages of national population aged 18-34 years old

StatLink  http://dx.doi.org/10.1787/888933213432

Notes and sources are to be found at the end of the chapter.

Section 13.18. Perceived discrimination

Background

Indicator

This indicator measures ethnic discrimination perceived by youth who are either foreign-born or native-born with immigrant parents. Parents’ countries of birth are not available in social cohesion surveys in Australia. As for other non-EU countries, no data are available for the offspring of mixed parentage or immigrants’ ages on arrival in their host countries. For further information, see Indicator 12.1.

Coverage

Foreign-born 15-34 year-olds and people born in the host country to at least one immigrant parent. For the groupings, see Indicator 13.1.

Across the European Union, one young immigrant offspring in five felt, between 2002 and 2012, that he or she belonged to a group which suffered from discrimination on the grounds of ethnicity, nationality, or race (Figure 13.34). The proportion fell over the period 2008-12. The sense of being discriminated against was especially keen in the Netherlands and Austria (where it is reported by one-third of immigrant offspring), France and the United Kingdom. In countries where many young people were of foreign European parentage – like Luxembourg, Israel and Switzerland – the feeling was much less widespread.

Of people born in host countries to mixed parents, only 6% reported discrimination – three times less than immigrant offspring. In half of EU countries, young immigrants feel less singled out than the native-born of immigrant parents, particularly in the United Kingdom, Belgium and Portugal. Similarly, young adult arrivals have a sharper sense of being discriminated against than those who immigrate before the age of 15. France and Sweden are the only countries where child arrivals report discrimination twice as often as their peers who arrived when they were adults.

Perceptions of discrimination vary with socio-economic background. More men than women feel it, both among actual immigrants and the native-born of foreign parentage. Among young immigrants who arrived in an EU country before they were 15 years old, those who report the most perceived discrimination are those born in a low-income country, while among adult incomers, it is the poorly educated and unemployed (Figure 13.35). By contrast, native-born youth of immigrant parentage feel discrimination more sharply when they hold a higher-education degree or when they have a job. And if they are citizens of the country where they were born, the sense of being singled out is again slightly stronger than among those of foreign nationality (Figure 13.36).

A poor grasp of the host country may sharpen the sense of discrimination. At the same time, good understanding can also raise expectations of fair treatment in the host society. In non-European OECD countries, the native-born offspring of immigrants – in theory more familiar with the host country – feel less discriminated against than immigrants, while the reverse is true in the European Union (Figure 13.35). What is more, immigrants who arrive before they are 15 years old are more likely to report discrimination when their mother tongue is the host country’s language (Figure 13.35).

Less than one immigrant in ten in Canada said they experienced discrimination in 2009 and less than one in twenty in New Zealand in 2008. In both those countries, as many young women as men report discrimination and levels of education have little impact on that perception. In the United States, men suffer more than women.

Figure 13.34. Share of 15-34 year-olds who state that they have been discriminated against, 2002-12

StatLink  http://dx.doi.org/10.1787/888933213440

Figure 13.35. Share of 15-34 year-olds in the EU who state that they belong to a group that is discriminated against, 2008-12

StatLink  http://dx.doi.org/10.1787/888933213456

Figure 13.36. Share of 15-34 year-olds immigrant offspring who state that they belong to a group that is discriminated against, 2008-12

StatLink  http://dx.doi.org/10.1787/888933213466

Notes and sources are to be found at the end of the chapter.

Data limitations

Target groups

The population of migrant origin targeted in this chapter is:

young people born in the host country with one or both parents born in a foreign country;

young foreign-born people schooled, for at least a few years, in the host country – i.e. immigrants who arrived before the age of 15.

European countries sometimes refer to the native-born youth with immigrant parents as “second-generation immigrants”. This, however, risks connotations that the immigrant status is perpetuating. OECD countries that have been settled by migration also occasionally use the term, but with a positive connotation. In Canada, for example, it refers to “first-generation Canadians” (foreign-born persons) and to “second-generation Canadians” (Canadian-born of two foreign-born parents). This reflects the fact that both immigrants and their offspring are considered an integral part of society.

When the country of birth of one parent is unknown, children are considered to originate from the other parent’s. So, if one parent of a child born in the host country is foreign-born and the other parent’s country of birth is unknown, the child is considered to be the offspring of an immigrant (i.e. born in the host country to two foreign-born parents). Attributing foreign origin in that way may skew comparisons between the outcomes of children with two immigrant parents and those with one. But to define that group properly would require knowing the nationalities of both parents.

Indicators 13.1,  13.2,  13.7,  13.9,  13.11,  13.12,  13.13,  13.14,  13.15

Data are available for 22 OECD countries. For five of them – Greece, Ireland, Italy, New Zealand and Portugal – figures were calculated from labour force surveys which provide the countries of birth of foreign-born parents only for respondents living in the same household. Consequently, the five countries supply only data on the foreign-born. To ensure the comparability of outcomes of the different population groups (immigrant or host-country native-born depending on the origin of the parents), OECD averages are based on a homogeneous group of 17 countries that supply data for all target groups. The countries are Australia, Austria, Belgium, Canada, Switzerland, Germany, Denmark, Spain, Finland, France, United Kingdom, Israel, Luxembourg, Netherlands, Norway, Sweden and the United States. Of those countries, the 11 EU member countries are used to calculate EU averages.

The distinction between immigrant offspring and the offspring of the native born in the United Kingdom rests on people’s self-defined ethnicity in labour force surveys and therefore the data are not fully comparable with those for other countries.

“White” and from “England and Wales”, “Northern Ireland” or “Scotland” are presumed to be the offspring of native-born parents.

“Mixed/multiple ethnic groups” are presumed to be the people born in the United Kingdom to one immigrant and one native-born parent.

“White” – “Irish”, “Gypsy or Irish Traveller”, “Any other White”; “Asian/Asian British” – “Indian”, “Pakistani”, “Bangladeshi”, “Chinese”, “Any other Asian”: “Black/African/Caribbean/Black British”; and “Other ethnic group” are presumed to be the children whose parents are both immigrants.

The region of origin of immigrant offspring is the region of birth of the father. In the case of native-born with a mixed background, the region of origin is the region of birth of the immigrant parent.

In a number of OECD countries, the total size of the active population of young people with immigrant parents represents only a small share of the 15-34 years old, since most of them are still in education. This is particularly the case among the native-born immigrant offspring in recent immigration countries (Finland, Denmark, Southern European countries). Furthermore, absolute numbers in each population groups are small in countries where the share of immigrants in the total population is small and this tends to be a bias towards those who are younger. This should be kept in mind when analysing the employment rates for those countries.

It should also be noted that data presented in these indicators come from diverse types of data sources that may not be fully comparable. In particular, population register data are used for Denmark (2013), Finland (2012), Norway (2013) and Sweden (2013). These data are not comparable to survey data, both in terms of population coverage and of definition of employment status (employed, unemployed and inactive). However, this should matter less for differences between groups in the same country.

Indicators 13.5,  13.6 – OECD Programme of International Student Assessment (PISA)

PISA tests assess to what extent pupils nearing the end of compulsory schooling have acquired the skills and knowledge they need to play a full part in modern society. Pupils aged between 15 years and three months and 16 years and two months are tested in reading literacy, mathematics and science. They have completed at least six years of formal education, regardless of the kind of establishment they attended, whether it was public, private, or a foreign school in the host country, whether they attended on a full- or part-time basis, and whether curricula were academic or vocational. The indicator considered in this chapter relates to reading literacy.

For the PISA results to be published, the sample should take in at least 30 pupils from five different schools. For that reason the results of pupils of immigrant background in Bulgaria, Chile, Korea, Hungary, Latvia, Poland, the Slovak Republic, Romania, Japan and Turkey are not commented on here. Their results are, however, factored into calculations of the average scores – weighted or not – for the whole OECD and/or European Union, which may hamper comparability with non-weighted averages.

PISA also contains information on whether the 15-year-olds who take its tests attended preschool (for at least one year). They have to think back and may not remember correctly, which might limit the significance of results. The advantage, nevertheless, is that it is possible to distinguish pupils of immigrant background (who may have attended preschool in the host country and therefore arrived before the age of six), native-born children with two foreign-born parents, and children born in the host country to native-born parents. The use of PISA information on preschool also helps assess how attending preschool affects pupils results, limited here to reading literacy.

Indicators 13.8: Programme for the International Assessment of Adult Competencies (PIAAC)

For a comprehensive look at the OECD’s PIAAC programme, see “Data limitations” at the end of Chapter 7.

Although PIAAC is an unique tool, it has its limits. The chief one is that in almost all countries – with the exceptions of Canada, the United Kingdom, Estonia, France, Korea and Poland – it considers only samples of some 5 000 respondents.

The migrant and migrant offspring sample is particularly small in Japan, Korea, Poland and the Slovak Republic, where migrants account for only 2.5% of the total population. Although that percentage matches those from other data sources, all four countries have been excluded from analysis. With the exception of a handful of countries (Australia, Austria, Germany, Canada, Estonia, the United States, France and the United Kingdom), migrant offspring samples are too scarce for any fine-tuned distribution of results. Consequently, only the eight countries where data are sufficient have been used to examine the immigrant offspring’s scores by level of education and reading literacy.

Belgian data relate only to Flanders and British data to England and Northern Ireland. PIAAC data have not been aggregated so as to produce weighted averages for all OECD and EU countries. Consequently, the graphs and tables show only simple averages of OECD and EU findings.

Indicators 13.9: Early school leaving

Statistics on parents’ place of birth could not be obtained for Greece, Ireland, Italy, New Zealand or Portugal. For those countries data therefore relate to immigrants only, although they do distinguish between those who immigrated before 15 years of age and the rest. To ensure that the results of the different population groups can be properly compared with each other, the outcomes of the immigrants in the five countries were not used to calculate OECD and EU averages.

Indicators 13.18: Perceived discrimination

European country data relate to the sense of belonging to a group that experiences discrimination on the grounds of ethnicity, race, or nationality. Canadian data come from reports by young people who state that, over the last five years, they have been discriminated against or treated unfairly because of their ethnicity, culture, race, or skin colour. Data from New Zealand refer to young people who report unfair treatment or an unpleasant experience in the previous 12 months because of their ethnicity, race, nationality. Data from the United States relate to respondents who feel discriminated against in the workplace on the ground of their race or ethnicity. See also Indicator 12.1 for further issues.

Notes, sources, and further reading

Note to Israel

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Notes to Cyprus1, 2

1. Note by Turkey:

The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Turkey recognizes the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of United Nations, Turkey shall preserve its position concerning the “Cyprus issue”.

2. Note by all the European Union Member States of the OECD and the European Union:

The Republic of Cyprus is recognized by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus.

Note to Austria

Data for Austria in Figures 13.12,  13.13,  13.17,  13.20,  13.21,  13.23,  13.27,  13.28,  13.29,  13.A1.2,  13.A1.3,  13.A1.6 and in Table 13.A1.10 should be flagged since the estimated size of the population groups they concern is between 3 000 and 6 000 persons.

Note to the United States

Immigrants who entered as children (defined as those who arrived before the age of 15) are immigrants who entered before the age of 18 in the United States.

Note to tables and figures

Note for Table 13.1

The symbol “**” points 2008 instead of 2013 data, based on the 2008 EU Labour Force Survey ad hoc module.

Note for Figure 13.6

Grey bars and markers indicate differences which are not statistically significant (with a probability of 0.05).

Note for Figure 13.8

Croatia, Estonia, Israel* and Slovenia are not included in OECD and EU averages in 2012.

Note for Figure 13.19

Belgium is not included in the OECD and EU totals.

Note for Figure 13.25

Austria, Belgium and Sweden are not included in the OECD and EU totals.

Note for Figure 13.26

For non-EU OECD countries in 2007-08 immigrants entered in their childhood are defined as those entered before the age of 18.

Note for Indicator 13.15

Finland, Netherlands, Norway and Sweden are not included in the OECD and EU totals.

Note for Indicator 13.16

For Australia, Canada and New Zealand, data refer to the 0-14 years old.

Note for Indicator 13.18

Data from the European Social Survey (ESS) refer to the perception of generally belonging to a group that is discriminated against on the grounds of race, ethnicity or nationality. Canadian data include foreign-born who, in the past five years, have experienced discrimination or being treated unfairly by others in Canada because of their ethnicity or culture, race or colour. Data for the United States refer to employed respondents who feel “in any way discriminated against” in their job because of their race or ethnic origin. New Zealand data include foreign-born who report to have been treated unfairly or to have had “something nasty” done to them within the prior 12 months because they belong to a certain ethnic/racial group or nationality.

General note for 2013 data presented in Indicators 13.2,  13.7,  13.9,  13.11,  13.12,  13.13,  13.14,  13.15

Data for Greece, Ireland, Italy, New Zealand and Portugal in these indicators cover the foreign-born population only and not the native-born with foreign-born parents. For these five countries, outcomes for foreign-born are compared to those of all native-born (including offspring of immigrants). In order to provide comparable outcomes across target groups for the mentioned indicators, OECD totals do not include data for these five countries but only those for the 17 countries for which data are available for all target groups (Australia, Austria, Belgium, Canada, Switzerland, Germany, Denmark, Spain, Finland, France, United Kingdom, Israel, Luxembourg, Netherlands, Norway, Sweden, United States). EU totals include the 11 EU countries included in the above list.

Sources

Indicator 13.1

Data for native-born offspring of immigrants and native-born with a mixed background in Greece, Ireland, Italy and Portugal are from the ad hoc module of European Labour Force Survey (EU-LFS) 2008. Other data come from the following sources:

Labour Force Surveys: Belgium (foreign-born population in 2012), Israel (2011), France (2012), Greece (2012), Ireland (2012), Italy (2012), Portugal (2012), Switzerland (2013), United Kingdom (2013), the Netherlands (2013), New Zealand (2014). Censuses in 2011: Australia, Spain and Luxembourg. Population registers: Denmark (2013), Finland (2012), Norway (2013) and Sweden (2013). National Household Survey (NHS) 2011: Canada. Banque Carrefour de la Sécurité Sociale 2012 on population born in Belgium. Mikrozensus 2012: Germany. Mikrozensus 2013: Austria. Current Population Survey 2013: United States.

Indicators 13.2,  13.7,  13.9,  13.11,  13.12,  13.13,  13.14,  13.15,  13.16

Labour Force Surveys: Belgium (foreign-born population in 2012), Israel (2011), France (2012), Greece (2012), Ireland (2012), Italy (2012), Portugal (2012), Switzerland (2013), United Kingdom (2013), the Netherlands (2013), New Zealand (2014). Censuses in 2011: Australia, Spain and Luxembourg. Population registers: Denmark (2013), Finland (2012), Norway (2013) and Sweden (2013). National Household Survey (NHS) 2011: Canada; Banque Carrefour de la Sécurité Sociale 2012 on population born in Belgium. Mikrozensus 2012: Germany. Mikrozensus 2013: Austria. Current Population Survey 2013: United States.

Indicator 13.12 (2007/08 data)

2007/2008 data are extracted from the ad hoc module of European Union Labour Force Survey (EU-LFS) 2008 except for Nordic countries (register data); Liebig and Widmaier (2009) for non-EU OECD countries in 2007-08.

Indicator 13.3

Ad hoc module of European Union Labour Force Survey (EU-LFS) 2008; Israeli Labour Force Survey (2011).

Indicator 13.4

European Union Survey on Income and Living Conditions (EU-SILC) 2012. American Community Survey (ACS) 2012. OECD Programme of International Student Assessment (PISA) 2012.

Indicators 13.5 and 13.6

OECD Programme of International Student Assessment (PISA) 2003 and 2012.

Indicator 13.8

OECD Programme for the International Assessment of Adult Competencies (PIAAC) 2012.

Indicator 13.10

Ad hoc module of European Union Labour Force Survey (EU-LFS) 2009.

Indicator 13.16

European Union Survey on Income and Living Conditions (EU-SILC) 2012. Australian Census 2011. Canadian National Household Survey (NHS) 2011. US Current Population Survey (CPS) 2012. Israeli Integrated Household Survey 2011. New Zealand Household Economic Survey (HES) 2013.

Indicator 13.17

European Social Surveys (ESS) 2002-12. US Current Population Survey (CPS) 2012, supplement on voter participation.

Indicator 13.18

European Social Survey (ESS) 2002-12. Canadian General Social Surveys (CGSS) 2009. New Zealand General Social Survey (NZGSS) 2008. United States General Social Surveys (USGSS) 2004-12.

Further reading

Heath, A., T. Liebig and P. Simon (2013), “Discrimination against Immigrants – Measurement, Incidence and Policy Instruments”, OECD International Migration Outlook 2013, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2013-7-en.

Liebig, T. and T. Huddleston (2014), “Labour Market Integration of Immigrants and their Children: Developing, Activating and Using Skills”, OECD International Migration Outlook 2014, OECD Publishing, Paris, http://dx.doi.org/10.1787/migr_outlook-2014-5-en.

Liebig, T. and S. Widmaier (2009), “Children of Immigrants in the Labour Markets of EU and OECD Countries: An Overview”, OECD Social, Employment and Migration Working Papers, No. 97, OECD Publishing, Paris, http://dx.doi.org/10.1787/220823724345.

OECD (2013), PISA 2012 Results: Excellence through Equity (Volume II): Giving Every Student the Chance to Succeed, PISA, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264201132-en.

OECD (2012a), Settling In: OECD Indicators of Immigrant Integration 2012, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264171534-en.

OECD (2012b), Untapped Skills: Realising the Potential of Immigrant Students, PISA, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264172470-en.

OECD (2011), Naturalisation: A Passport for the Better Integration of Immigrants?, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264099104-en.

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 (2008), “Labour Market Discrimination on the Grounds of Gender and Ethnicity”, OECD Employment Outlook 2008, OECD Publishing, Paris, http://dx.doi.org/10.1787/empl_outlook-2008-5-en.

Annex 13.A1.

Additional tables and figures

Figure 13.A1.1. Age distribution by migration background, 2013

Total = 100%

Notes: Data for Greece, Ireland, Italy, New Zealand and Portugal cover the foreign-born population only and not the native-born with foreign-born parents. For these five countries, outcomes for foreign-born are compared to those of all native-born (including offspring of immigrants). In order to provide comparable outcomes across target groups, OECD and EU averages do not include data for these five countries.

Sources: Labour Force Surveys: Belgium (foreign-born population in 2012), France (2012), Greece (2012), Ireland (2012), Italy (2012), Portugal (2012), United Kingdom (2013), New Zealand (2014). Censuses in 2011: Australia, Spain and Luxembourg. Population registers: Denmark (2013), Finland (2012), Norway (2013) and Sweden (2013). National Household Survey (NHS) 2011: Canada. Banque Carrefour de la Sécurité Sociale 2012 on population born in Belgium. Mikrozensus 2012: Germany. Mikrozensus 2013: Austria. Current Population Survey 2013: United States.

StatLink  http://dx.doi.org/10.1787/888933213530

Figure 13.A1.2. Immigrants and immigrant offspring aged 15-34 by own or parents’ place of birth, 2013

Total = 100%

Notes: Data for Greece, Ireland, Italy, New Zealand and Portugal cover the foreign-born population only and not the native-born with foreign-born parents. For these five countries, outcomes for foreign-born are compared to those of all native-born (including offspring of immigrants). In order to provide comparable outcomes across target groups, OECD and EU averages do not include data for these five countries.

Sources: Labour Force Surveys: Belgium (foreign-born population in 2012), France (2012), Greece (2012), Ireland (2012), Italy (2012), Portugal (2012), United Kingdom (2013), the Netherlands (2013), New Zealand (2014). Censuses in 2011: Spain and Luxembourg. Population registers: Denmark (2013), Finland (2012), Norway (2013) and Sweden (2013). National Household Survey (NHS) 2011: Canada. Banque Carrefour de la Sécurité Sociale 2012 on population born in Belgium. Mikrozensus 2012: Germany. Mikrozensus 2013: Austria. Current Population Survey 2013: United States.

StatLink  http://dx.doi.org/10.1787/888933213543

Table 13.A1.1. Percentage of 15-year-old students with a migration background, 2003 and 2012
| Native-born with a mixed background | Native-born offspring of foreign-born | Foreign-born
| 2003 | 2012 | 2003 | 2012 | 2003 | 2012
Australia | 17 | 15 | 12 | 12 | 13 | 12
Austria | 5 | 8 | 4 | 11 | 10 | 7
Belgium | 10 | 12 | 6 | 8 | 8 | 10
Bulgaria | .. | 2 | .. | 0 | .. | 1
Canada | 10 | 10 | 9 | 17 | 12 | 15
Chile | .. | 1 | .. | 0 | .. | 1
Croatia | .. | 16 | .. | 8 | .. | 6
Czech Republic | 6 | 7 | 0 | 1 | 1 | 3
Denmark | 6 | 7 | 3 | 6 | 5 | 6
Estonia | .. | 11 | .. | 7 | .. | 2
Finland | 2 | 5 | 0 | 1 | 3 | 3
France | 11 | 10 | 11 | 10 | 5 | 7
Germany | 5 | 7 | 7 | 11 | 9 | 4
Greece | 5 | 8 | 1 | 4 | 9 | 8
Hungary | 1 | 3 | 0 | 1 | 3 | 1
Iceland | 5 | 7 | 0 | 1 | 6 | 9
Ireland | 10 | 13 | 1 | 2 | 7 | 16
Israel* | .. | 13 | .. | 13 | .. | 8
Italy | 4 | 6 | 0 | 2 | 3 | 7
Japan | 0 | 1 | 0 | 0 | 0 | 1
Korea | 0 | 0 | 0 | 0 | 0 | 0
Latvia | 19 | 7 | 8 | 1 | 3 | 1
Lithuania | .. | 14 | .. | 4 | .. | 1
Luxembourg | 14 | 15 | 16 | 29 | 20 | 20
Mexico | 1 | 2 | 0 | 0 | 2 | 2
Netherlands | 6 | 8 | 7 | 8 | 5 | 5
New Zealand | 14 | 14 | 7 | 10 | 17 | 21
Norway | 6 | 8 | 2 | 5 | 6 | 7
Poland | 0 | 1 | 0 | 0 | 0 | 0
Portugal | 7 | 12 | 2 | 3 | 7 | 7
Romania | .. | 1 | .. | 0 | .. | 1
Slovak Republic | 6 | 4 | 1 | 0 | 1 | 1
Slovenia | .. | 7 | .. | 6 | .. | 4
Spain | 4 | 6 | 1 | 1 | 4 | 10
Sweden | 8 | 11 | 6 | 9 | 8 | 9
Switzerland | 14 | 17 | 9 | 17 | 13 | 10
Turkey | 1 | 2 | 0 | 1 | 1 | 1
United Kingdom | 9 | 9 | 5 | 6 | 5 | 10
United States | 6 | 8 | 8 | 15 | 8 | 8
OECD total (30) | 5 | 6 | 5 | 7 | 5 | 6
EU total (20) | 6 | 7 | 4 | 6 | 5 | 6
Notes: Bulgaria, Chile, Croatia, Estonia, Israel*, Lithuania, Romania and Slovenia are not included in OECD and EU averages in 2012.
* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
Source: OECD Programme for International Student Assessment (PISA) 2003 and 2012.
StatLink  http://dx.doi.org/10.1787/888933214243

Table 13.A1.2. Change in PISA reading scores of 15-year-old students between 2003 and 2012, by migration background
PISA score points
| Native-born offspring of native-born | Native-born with a mixed background | Native-born offspring of foreign-born | Foreign-born
Australia | -19 | -12 | 12 | 0
Austria | 0 | -25 | 23 | 20
Belgium | -1 | -1 | 27 | 32
Bulgaria | .. | .. | .. | ..
Canada | -9 | -2 | -16 | 14
Chile | .. | .. | .. | ..
Croatia | .. | .. | .. | ..
Czech Rebuplic | -3 | 1 | 23 | 4
Denmark | 7 | 13 | 15 | -18
Estonia | .. | .. | .. | ..
Finland | -16 | -28 | -61 | -29
France | 14 | 6 | 6 | 0
Germany | 7 | -11 | 61 | 23
Greece | 7 | 7 | -22 | -5
Hungary | 7 | 3 | 114 | 14
Iceland | -5 | 0 | -46 | -43
Ireland | 6 | 12 | 31 | 18
Israel* | .. | .. | .. | ..
Italy | 19 | 10 | -7 | -9
Japan | 41 | 90 | 29 | 29
Korea | 2 | -4 | -51 | -49
Latvia | -3 | 1 | 10 | -35
Lithuania | .. | .. | .. | ..
Luxembourg | 13 | 6 | 9 | 33
Mexico | 20 | 20 | 23 | 71
Netherlands | -4 | -9 | -10 | -3
New Zealand | -10 | -5 | -10 | -4
Norway | 8 | 10 | 35 | -1
Poland | 21 | 49 | -16 | 39
Portugal | 11 | 18 | -11 | 28
Romania | .. | .. | .. | ..
Slovak Republic | -5 | -7 | 18 | -18
Slovenia | .. | .. | .. | ..
Spain | 12 | 26 | 8 | 1
Sweden | -25 | -29 | -45 | -32
Switzerland | 8 | 14 | 11 | 39
Turkey | 35 | 36 | 37 | -13
United Kingdom | -6 | 5 | -15 | 2
United States | -1 | -8 | 21 | 23
OECD total (30) | 8 | -3 | 19 | 19
EU total (20) | 7 | 2 | 14 | 11
Notes: Bulgaria, Chile, Croatia, Estonia, Israel*, Lithuania, Romania and Slovenia are not included in OECD and EU averages in 2012.
* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
Source: OECD Programme for International Student Assessment (PISA) 2003 and 2012.
StatLink  http://dx.doi.org/10.1787/888933214250

Tableau 13.A1.3. PISA reading scores of 15-year-old students by migration background, 2012
PISA score points and differences in score points
| Native-born offspring of foreign-born | Native-born with a mixed background | Foreign-born
% of all students | Score | Difference with native-born offspring of native-born | Difference adjusted for family socio-economic background | % of all students | Score | Difference with native-born offspring of native-born | Difference adjusted for family socio-economic background | % of all students | Score | Difference with native-born offspring of native-born | Difference adjusted for family socio-economic background
Australia | 12 | 538 | 30 | 34 | 15 | 524 | 16 | 12 | 12 | 519 | 12 | 11
Austria | 11 | 451 | -49 | -22 | 8 | 494 | -6 | -10 | 7 | 451 | -49 | -27
Belgium | 8 | 466 | -60 | -36 | 12 | 498 | -29 | -21 | 10 | 457 | -70 | -53
Canada | 17 | 527 | 4 | 11 | 10 | 538 | 15 | 9 | 15 | 529 | 6 | 4
Croatia | 8 | 474 | -12 | -5 | 16 | 493 | 7 | 6 | 6 | 469 | -18 | -9
Czech Rebuplic | 1 | 474 | -21 | -16 | 7 | 482 | -13 | -10 | 3 | 483 | -12 | -9
Denmark | 6 | 454 | -49 | -21 | 7 | 510 | 6 | 3 | 6 | 456 | -48 | -34
Estonia | 7 | 487 | -36 | -35 | 11 | 504 | -19 | -17 | 2 | 496 | -27 | -36
Finland | 1 | 465 | -65 | -49 | 5 | 517 | -13 | -14 | 3 | 453 | -76 | -65
France | 10 | 464 | -56 | -25 | 10 | 508 | -12 | -10 | 7 | 447 | -73 | -50
Germany | 11 | 481 | -43 | -15 | 7 | 498 | -27 | -13 | 4 | 455 | -70 | -49
Greece | 4 | 450 | -33 | -18 | 8 | 494 | 10 | 5 | 8 | 434 | -49 | -28
Iceland | 1 | 473 | -16 | -8 | 7 | 494 | 6 | 5 | 9 | 452 | -37 | -33
Ireland | 2 | 518 | -3 | -10 | 13 | 534 | 12 | 8 | 16 | 529 | 8 | 4
Israel* | 13 | 502 | 22 | 26 | 13 | 531 | 51 | 42 | 8 | 486 | 6 | 12
Italy | 2 | 457 | -40 | -28 | 6 | 501 | 4 | 1 | 7 | 428 | -69 | -58
Lithuania | 4 | 455 | -25 | -25 | 14 | 466 | -13 | -14 | 1 | 476 | -4 | -10
Luxembourg | 29 | 463 | -53 | -20 | 15 | 499 | -17 | -12 | 20 | 471 | -45 | -22
Mexico | 0 | 375 | -52 | -50 | 2 | 414 | -13 | -23 | 2 | 386 | -41 | -40
Netherlands | 8 | 465 | -56 | -31 | 8 | 508 | -12 | -11 | 5 | 479 | -42 | -35
New Zealand | 10 | 496 | -17 | -5 | 14 | 538 | 25 | 13 | 21 | 510 | -3 | -10
Norway | 5 | 481 | -31 | -17 | 8 | 513 | 0 | -4 | 7 | 459 | -54 | -40
Portugal | 3 | 460 | -31 | -31 | 12 | 510 | 19 | -1 | 7 | 470 | -21 | -19
Slovenia | 6 | 450 | -36 | -14 | 7 | 482 | -5 | -5 | 4 | 433 | -54 | -38
Spain | 1 | 448 | -47 | -40 | 6 | 495 | 0 | -4 | 10 | 451 | -44 | -32
Sweden | 9 | 457 | -40 | -25 | 11 | 494 | -3 | -6 | 9 | 420 | -77 | -58
Switzerland | 17 | 473 | -53 | -30 | 17 | 520 | -5 | -11 | 10 | 472 | -53 | -42
United Kingdom | 6 | 494 | -6 | -4 | 9 | 521 | 21 | 14 | 10 | 500 | -1 | 0
United States | 15 | 502 | 0 | 26 | 8 | 505 | 3 | 7 | 8 | 484 | -17 | 6
OECD total (34) | 7 | 495 | -3 | 3 | 6 | 506 | 8 | -3 | 6 | 477 | -21 | -19
EU total (26) | 5 | 472 | -32 | -17 | 7 | 505 | 1 | -2 | 6 | 463 | -42 | -32
Note: Figures in bold show differences significantly different from zero at a 5% level.
* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
Source: OECD Programme for International Student Assessment (PISA) 2012.
StatLink  http://dx.doi.org/10.1787/888933214261

Table 13.A1.4. PISA reading scores of 15-year-old students by migration background, 2003 and 2012
Differences with native-born offspring of native-born
| Native-born offspring with a mixed background | Native-born offspring of foreign-born | Foreign-born
| Unadjusted difference | Adjusted for family socio-economic background | Unadjusted difference | Adjusted for family socio-economic background | Unadjusted difference | Adjusted for family socio-economic background
| 2003 | 2012 | 2003 | 2012 | 2003 | 2012 | 2003 | 2012 | 2003 | 2012 | 2003 | 2012
Australia | 9 | 16 | 5 | 12 | -1 | 30 | 7 | 34 | -7 | 12 | -9 | 11
Austria | 19 | -6 | 3 | -10 | -72 | -49 | -31 | -22 | -69 | -49 | -44 | -27
Belgium | -28 | -29 | -26 | -21 | -88 | -60 | -44 | -36 | -102 | -70 | -77 | -53
Canada | 8 | 15 | -2 | 9 | 11 | 4 | 11 | 11 | -17 | 6 | -21 | 4
Croatia | .. | 7 | .. | 6 | .. | -12 | .. | -5 | .. | -18 | .. | -9
Czech Rebuplic | -17 | -13 | -13 | -10 | -46 | -21 | -27 | -16 | -19 | -12 | -11 | -9
Denmark | 1 | 6 | -2 | 3 | -57 | -49 | -27 | -21 | -23 | -48 | -13 | -34
Estonia | .. | -19 | .. | -17 | .. | -36 | .. | -35 | .. | -27 | .. | -36
Finland | -2 | -13 | -8 | -14 | -20 | -65 | -20 | -49 | -64 | -76 | -62 | -65
France | -3 | -12 | -3 | -10 | -48 | -56 | -12 | -25 | -59 | -73 | -42 | -50
Germany | -10 | -27 | -7 | -13 | -98 | -43 | -53 | -15 | -86 | -70 | -43 | -49
Greece | 10 | 10 | -3 | 5 | -5 | -33 | -11 | -18 | -37 | -49 | -27 | -28
Iceland | 1 | 6 | -1 | 5 | 26 | -16 | 27 | -8 | 2 | -37 | -6 | -33
Ireland | 6 | 12 | 3 | 8 | -29 | -3 | -35 | -10 | -4 | 8 | -14 | 4
Israel* | .. | 51 | .. | 42 | .. | 22 | .. | 26 | .. | 6 | .. | 12
Italy | 13 | 4 | 3 | 1 | -13 | -40 | -23 | -28 | -40 | -69 | -37 | -58
Lithuania | .. | -13 | .. | -14 | .. | -25 | .. | -25 | .. | -4 | .. | -10
Luxembourg | -10 | -17 | -8 | -12 | -49 | -53 | -28 | -20 | -65 | -45 | -40 | -22
Mexico | -13 | -13 | -20 | -23 | -55 | -52 | -43 | -50 | -92 | -41 | -77 | -40
Netherlands | -8 | -12 | -11 | -11 | -50 | -56 | -23 | -31 | -43 | -42 | -31 | -35
New Zealand | 19 | 25 | 10 | 13 | -17 | -17 | -2 | -5 | -9 | -3 | -16 | -10
Norway | -2 | 0 | -6 | -4 | -59 | -31 | -45 | -17 | -45 | -54 | -32 | -40
Portugal | 12 | 19 | -9 | -1 | -9 | -31 | -17 | -31 | -39 | -21 | -33 | -19
Slovenia | .. | -5 | .. | -5 | .. | -36 | .. | -14 | .. | -54 | .. | -38
Spain | -15 | 0 | -23 | -4 | -43 | -47 | -34 | -40 | -34 | -44 | -27 | -32
Sweden | 1 | -3 | 2 | -6 | -20 | -40 | 0 | -25 | -70 | -77 | -53 | -58
Switzerland | -11 | -5 | -19 | -11 | -56 | -53 | -34 | -30 | -84 | -53 | -62 | -42
United Kingdom | 9 | 21 | -3 | 14 | 2 | -6 | 15 | -4 | -9 | -1 | -16 | 0
United States | 11 | 3 | 5 | 7 | -21 | 0 | 1 | 26 | -41 | -17 | -23 | 6
OECD total (30) | 17 | 6 | 1 | -4 | -16 | -5 | -5 | 2 | -34 | -23 | -28 | -20
EU total (20) | 3 | -2 | -4 | -4 | -43 | -36 | -17 | -20 | -49 | -45 | -34 | -35
Note: Bulgaria, Chile, Croatia, Estonia, Israel*, Lithuania, Romania and Slovenia are not included in the respective OECD and EU averages in 2012. Figures in bold show differences significantly different from zero at a 5% level.
* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
Source: OECD Programme for International Student Assessment (PISA) 2003 and 2012.
StatLink  http://dx.doi.org/10.1787/888933214270

Table 13.A1.5. Mean PISA reading scores of 15-year-old students by migration background, 2012
Mean score for lowest quartile of family socio-economic background and difference with top quartile
| Native-born offspring of native-born | Native-born with a mixed background | Native-born offspring of foreign-born | Foreign-born
| Mean score Lowest quartile | Difference with mean score (top quartile) | Mean score Lowest quartile | Difference with mean score (top quartile) | Mean score Lowest quartile | Difference with mean score (top quartile) | Mean score Lowest quartile | Difference with mean score (top quartile)
Australia | 466 | 84 | 478 | 85 | 507 | 63 | 458 | 109
Austria | 459 | 82 | 451 | 79 | 428 | 92 | 412 | 112
Belgium | 476 | 99 | 454 | 104 | 442 | 81 | 406 | 128
Bulgaria | 374 | 141 | 415 | 120 | 259 | 188 | 348 | 59
Canada | 489 | 70 | 509 | 56 | 509 | 58 | 479 | 89
Chile | 404 | 106 | 413 | 117 | 352 | 175 | 420 | 116
Croatia | 454 | 75 | 453 | 78 | 458 | 69 | 449 | 68
Czech Republic | 453 | 91 | 442 | 119 | 442 | 87 | 445 | 83
Denmark | 460 | 82 | 460 | 74 | 441 | 41 | 417 | 84
Estonia | 502 | 57 | 488 | 46 | 470 | 46 | 501 | 54
Finland | 501 | 60 | 486 | 62 | 454 | 39 | 398 | 123
France | 460 | 116 | 459 | 119 | 454 | 92 | 409 | 158
Germany | 477 | 83 | 460 | 78 | 456 | 74 | 425 | 60
Greece | 441 | 85 | 462 | 74 | 428 | 51 | 423 | 114
Hungary | 440 | 106 | 484 | 66 | 494 | 58 | 472 | 66
Iceland | 465 | 52 | 468 | 40 | 450 | 73 | 392 | 132
Ireland | 483 | 83 | 487 | 91 | 496 | 43 | 481 | 94
Israel* | 426 | 108 | 470 | 91 | 471 | 78 | 447 | 71
Italy | 460 | 72 | 471 | 53 | 428 | 59 | 409 | 59
Japan | 505 | 70 | 518 | 43 | 521 | 132 | 457 | 101
Korea | 507 | 62 | 517 | -6 | .. | .. | .. | ..
Latvia | 453 | 76 | 450 | 83 | 448 | 84 | 390 | 139
Lithuania | 445 | 72 | 436 | 57 | 467 | -1 | 423 | 98
Luxembourg | 459 | 89 | 450 | 86 | 441 | 96 | 414 | 142
Mexico | 396 | 67 | 379 | 71 | 344 | 106 | 358 | 71
Netherlands | 480 | 77 | 467 | 71 | 454 | 21 | 439 | 95
New Zealand | 460 | 111 | 483 | 92 | 449 | 130 | 447 | 122
Norway | 486 | 54 | 480 | 59 | 456 | 55 | 431 | 95
Poland | 482 | 85 | 534 | 38 | .. | .. | .. | ..
Portugal | 448 | 94 | 443 | 100 | 421 | 100 | 411 | 98
Romania | 399 | 95 | 347 | 172 | .. | .. | 371 | 120
Slovak Republic | 400 | 127 | 397 | 124 | 388 | 194 | 321 | 195
Slovenia | 442 | 88 | 442 | 87 | 439 | 52 | 393 | 117
Spain | 457 | 81 | 454 | 81 | 409 | 47 | 428 | 66
Sweden | 459 | 76 | 453 | 65 | 445 | 47 | 395 | 96
Switzerland | 485 | 74 | 483 | 65 | 456 | 71 | 423 | 104
Turkey | 444 | 81 | 463 | 46 | 370 | 204 | 397 | 116
United Kingdom | 461 | 84 | 483 | 80 | 480 | 71 | 455 | 106
United States | 460 | 84 | 445 | 114 | 479 | 94 | 448 | 99
OECD total (34) | 458 | 84 | 459 | 91 | 472 | 87 | 437 | 104
EU total (26) | 460 | 90 | 463 | 87 | 452 | 77 | 424 | 110
* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
Source: OECD Programme for International Student Assessment (PISA) 2012.
StatLink  http://dx.doi.org/10.1787/888933214288

Table 13.A1.6. PISA reading scores of 15-year-old students by immigrants’ age at arrival, 2012
| PISA reading scores | Difference with early arrivers
| Early arrivers | Mid arrivers | Late arrivers | Mid arrivers | Late arrivers
Australia | 537 | 522 | 497 | -15 | -41
Austria | 458 | 444 | 468 | -14 | 10
Belgium | 491 | 443 | 416 | -48 | -75
Canada | 538 | 536 | 510 | -2 | -28
Chile | 483 | 446 | 444 | -37 | -39
Croatia | 471 | 462 | 478 | -9 | 7
Czech Republic | 508 | 480 | 467 | -27 | -40
Denmark | 473 | 439 | 409 | -34 | -63
Estonia | 510 | 478 | 490 | -32 | -20
Finland | 484 | 426 | 411 | -58 | -73
France | 483 | 435 | 375 | -48 | -108
Germany | 485 | 426 | 387 | -59 | -98
Greece | 456 | 428 | 407 | -28 | -49
Hungary | 537 | 506 | 435 | -31 | -102
Iceland | 481 | 414 | 340 | -67 | -141
Ireland | 543 | 525 | 521 | -19 | -23
Israel* | 516 | 463 | 412 | -53 | -104
Italy | 447 | 433 | 385 | -14 | -63
Lithuania | 470 | 520 | 436 | 50 | -34
Luxembourg | 483 | 460 | 462 | -23 | -22
Mexico | 388 | 400 | 418 | 13 | 30
Netherlands | 492 | 479 | 483 | -12 | -9
New Zealand | 534 | 515 | 486 | -19 | -48
Norway | 477 | 465 | 408 | -12 | -69
Portugal | 478 | 477 | 444 | -1 | -34
Slovak Republic | 477 | 444 | 482 | -33 | 5
Slovenia | 462 | 436 | 388 | -26 | -74
Spain | 464 | 449 | 434 | -16 | -30
Sweden | 448 | 413 | 374 | -36 | -75
Switzerland | 482 | 468 | 452 | -14 | -30
Turkey | 501 | 420 | 422 | -81 | -78
United Kingdom | 501 | 502 | 503 | 1 | 2
United States | 498 | 468 | 477 | -29 | -21
OECD total (34) | 491 | 472 | 462 | -19 | -30
EU total (26) | 481 | 458 | 440 | -23 | -41
Note: Early arrivers are children who arrived before the age of 6, mid arrivers those who arrived between the age of 6 and 10, late arrivers those who arrived at 11 or after. Figures in bold show differences significantly different from zero at a 5% level.
* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
Source: OECD Programme for International Student Assessment (PISA) 2012.
StatLink  http://dx.doi.org/10.1787/888933214295

Table 13.A1.7. Mean PISA reading scores of 15-year-old students by school socio-economic background and migration background, 2012
| Native-born offspring of native-born | Native-born with a mixed background | Native-born offspring of foreign-born | Foreign-born
| Score Lowest quartile of schools | Difference with highest quartile of schools | Score Lowest quartile of schools | Difference with highest quartile of schools | Score Lowest quartile of schools | Difference with highest quartile of schools | Score Lowest quartile of schools | Difference with highest quartile of schools
Australia | 461 | 94 | 471 | 89 | 483 | 104 | 455 | 117
Austria | 437 | 123 | 426 | 131 | 396 | 131 | 395 | 158
Belgium | 443 | 149 | 432 | 150 | 412 | 151 | 392 | 156
Canada | 495 | 65 | 517 | 43 | 503 | 55 | 487 | 82
Croatia | 443 | 116 | 445 | 115 | 414 | 134 | 435 | 107
Czech Republic | 446 | 144 | 426 | 178 | 374 | 207 | 405 | 189
Denmark | 464 | 67 | 479 | 57 | 438 | 49 | 421 | 86
Estonia | 504 | 55 | 491 | 58 | 472 | 34 | 453 | 100
Finland | 508 | 38 | 486 | 50 | 445 | 58 | 401 | 115
France | 418 | 166 | 419 | 171 | 394 | 165 | 368 | 225
Germany | 448 | 136 | 434 | 126 | 417 | 146 | 383 | 186
Greece | 410 | 114 | 424 | 102 | 401 | 107 | 390 | 130
Iceland | 466 | 53 | 466 | 52 | 389 | 143 | 407 | 88
Ireland | 477 | 85 | 489 | 77 | 499 | 66 | 493 | 73
Israel* | 407 | 147 | 457 | 120 | 435 | 128 | 388 | 132
Italy | 430 | 129 | 427 | 134 | 394 | 153 | 372 | 148
Lithuania | 435 | 97 | 404 | 120 | 350 | 152 | 397 | 146
Luxembourg | 464 | 109 | 455 | 102 | 431 | 127 | 413 | 163
Mexico | 391 | 82 | 372 | 93 | 327 | 142 | 354 | 90
Netherlands | 437 | 143 | 430 | 132 | 415 | 102 | 397 | 148
New Zealand | 465 | 108 | 488 | 89 | 441 | 114 | 449 | 118
Norway | 486 | 63 | 500 | 34 | 458 | 81 | 431 | 71
Poland | 486 | 83 | 513 | 35 | 373 | 202 | .. | ..
Portugal | 440 | 101 | 455 | 91 | 418 | 89 | 446 | 57
Slovenia | 406 | 152 | 409 | 147 | 410 | 122 | 374 | 142
Spain | 463 | 65 | 466 | 59 | 432 | 69 | 427 | 78
Sweden | 470 | 58 | 475 | 41 | 440 | 51 | 374 | 110
Switzerland | 488 | 80 | 480 | 74 | 437 | 95 | 423 | 117
Turkey | 428 | 123 | 440 | 120 | 385 | 218 | 384 | 158
United Kingdom | 453 | 96 | 486 | 86 | 466 | 105 | 445 | 125
United States | 453 | 91 | 450 | 109 | 470 | 96 | 447 | 95
OECD total (34) | 443 | 110 | 450 | 108 | 458 | 104 | 425 | 125
EU total (26) | 442 | 119 | 444 | 119 | 417 | 135 | 403 | 152
Note: Figures in bold show differences significantly different from zero at a 5% level.
* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.
Source: OECD Programme for International Student Assessment (PISA) 2012.
StatLink  http://dx.doi.org/10.1787/888933214303

Table 13.A1.8. Transition from school to work, 15-34 year-olds, 2009
| Native-born offspring of foreign-born | Native-born with a mixed background | Foreign-born who arrived as children | Foreign-born who arrived as adults | Native-born offspring of native-born
| % who never worked | Time to access the first job (in months) | % who never worked | Time to access the first job (in months) | % who never worked | Time to access the first job (in months) | % who never worked | Time to access the first job (in months) | % who never worked | Time to access the first job (in months)
Austria | 26.2 | 14 | 16.1 | 10 | 16.1 | 11 | 25.5 | 24 | 11.6 | 8
Belgium | 34.4 | 20 | 26.1 | 9 | 33.4 | 12 | 30.8 | 20 | 22.1 | 6
Cyprus1, 2 | - | - | 28.6 | 10 | 10.2 | 18 | 5.9 | 16 | 18.7 | 14
Czech Republic | 33.6 | 24 | 25.3 | 9 | 33.3 | 5 | 28.3 | 9 | 27.1 | 6
Denmark | 26.8 | 16 | 13.0 | 10 | 20.8 | 9 | 32.9 | 15 | 11.7 | 6
Estonia | 10.0 | 11 | 9.0 | 13 | - | - | - | - | 10.8 | 13
Finland |  |  | - | - | - | - | 33.1 | 12 | 26.6 | 11
France | 27.1 | 10 | 26.0 | 7 | 34.0 | 28 | 37.2 | 20 | 22.9 | 9
Germany | 65.3 | 9 | 49.9 | - | 56.9 | 18 | 59.9 | 6 | 55.2 | 5
Greece | 27.1 | - | 39.7 | 27 | 25.9 | 40 | 28.9 | 44 | 27.0 | 33
Hungary | - | - | - | - | 21.0 | 5 | 24.5 | 10 | 23.4 | 10
Iceland | - | - | 39.7 | 7 | 35.6 | 18 | 17.9 | 12 | 23.0 | 12
Ireland | 12.7 | 7 | 18.8 | 5 | 11.8 | 7 | 12.8 | 8 | 12.2 | 6
Italy | 49.9 | 20 | 49.9 | 25 | 37.7 | 32 | 45.1 | 41 | 50.4 | 26
Latvia | 9.1 | 14 | 16.9 | 20 | 18.5 | 12 | 39.8 | 20 | 21.4 | 13
Luxembourg | 11.0 | 8 | 13.8 | 5 | 8.9 | 11 | 11.8 | 9 | 14.4 | 7
Malta | - | - | - | - | - | - | 53.2 | 12 | 50.7 | 10
Netherlands | 29.4 | 9 | 15.4 | 6 | 25.3 | 7 | 30.9 | 10 | 10.4 | 5
Norway | .. | .. | .. | .. | .. | .. | .. | .. | .. | ..
Portugal | 15.6 | 33 | 26.4 | 14 | 17.5 | 16 | 9.8 | 16 | 11.9 | 17
Slovenia | 19.6 | 18 | 11.8 | 21 | - | - | 9.4 | 56 | 9.5 | 19
Spain | 59.6 | 30 | 25.9 | 16 | 43.7 | 31 | 41.2 | 20 | 26.9 | 18
Sweden | 30.9 | 8 | 24.9 | 6 | 36.0 | 6 | 34.7 | 8 | 22.3 | 5
Switzerland | 19.0 | 7 | 12.6 | 6 | 22.2 | 15 | 21.1 | 12 | 13.4 | 6
United Kingdom | 7.7 | 8 | 6.6 | 6 | 10.3 | 17 | 9.0 | 13 | 6.9 | 6
EU total (26) | 35.7 | 12 | 26.2 | 10 | 37.1 | 23 | 37.1 | 21 | 29.2 | 13
1, 2: See “Notes, sources, and further reading” section.
Source: Ad hoc module of European Union Labour Force Survey (EU-LFS) 2009.
StatLink  http://dx.doi.org/10.1787/888933214221

Figure 13.A1.3. NEET rates by migration background and by contributory factors, 2013

Percentages of the population aged 15 to 34

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Notes: Data for Greece, Ireland, Italy, New Zealand and Portugal cover the foreign-born population only and not the native-born with foreign-born parents. For these five countries, outcomes for foreign-born are compared to those of all native-born (including offspring of immigrants). In order to provide comparable outcomes across target groups, OECD and EU averages do not include data for these five countries.

Sources: Labour Force Surveys: Belgium (foreign-born population in 2012), Israel (2011), France (2012), Greece (2012), Ireland (2012), Italy (2012), Portugal (2012), Switzerland (2012); United Kingdom (2013), the Netherlands (2013), New Zealand (2014). Population registers: Denmark (2013) and Sweden (2013). Banque Carrefour de la Sécurité Sociale 2012 on population born in Belgium. Mikrozensus 2012: Germany. Mikrozensus 2013: Austria. Current Population Survey 2013: United States.

StatLink  http://dx.doi.org/10.1787/888933213552

Table 13.A1.9. Employment rates by migration background and gender, 2013
Percentage of population aged 15 to 34 not in education
| Native-born offspring of foreign-born | Native-born with a mixed background | Foreign-born who arrived as children | Foreign-born who arrived as adults | Native-born offspring of native-born
| Total | Men | Women | Total | Men | Women | Total | Men | Women | Total | Men | Women | Total | Men | Women
Australia | 80.7 | 85.0 | 76.2 | 81.2 | 85.9 | 76.4 | 66.8 | 69.1 | 64.5 | 76.9 | 86.3 | 67.9 | 79.2 | 84.8 | 73.3
Austria | 67.6 | 70.7 | 64.4 | 77.2 | 74.8 | 80.1 | 75.3 | 79.0 | 71.1 | 69.1 | 83.4 | 58.7 | 88.4 | 90.3 | 86.3
Belgium | 56.2 | 59.3 | 52.9 | 70.3 | 69.8 | 70.8 | 51.8 | 55.9 | 47.9 | 54.9 | 65.7 | 46.2 | 80.4 | 80.5 | 80.3
Canada | 79.7 | 81.2 | 78.2 | 80.3 | 82.3 | 78.1 | 75.6 | 78.5 | 72.6 | 70.5 | 82.7 | 61.0 | 78.4 | 80.7 | 75.8
Denmark | 53.8 | 53.8 | 53.7 | 66.0 | 65.8 | 66.2 | 52.0 | 53.6 | 50.0 | 48.1 | 55.7 | 41.2 | 74.6 | 75.9 | 73.2
Finland | 35.3 | 33.7 | 37.0 | 48.4 | 47.2 | 49.7 | 52.2 | 53.0 | 51.4 | 46.3 | 54.5 | 37.5 | 68.4 | 67.6 | 69.3
France | 61.3 | 61.8 | 60.9 | 73.0 | 74.6 | 71.2 | 61.5 | 64.1 | 59.0 | 55.1 | 73.3 | 41.2 | 77.4 | 80.6 | 74.1
Germany | 71.8 | 76.0 | 66.3 | 73.7 | 70.5 | 78.9 | 76.7 | 84.2 | 68.3 | 65.0 | 81.8 | 50.7 | 84.7 | 88.0 | 81.3
Greece | .. | .. | .. | .. | .. | .. | 42.9 | 48.0 | 37.3 | 48.7 | 63.3 | 35.3 | 53.6 | 59.2 | 47.6
Ireland | .. | .. | .. | .. | .. | .. | 42.2 | 40.2 | 44.3 | 69.6 | 78.1 | 62.8 | 63.6 | 62.4 | 64.8
Israel* | 66.3 | 63.0 | 69.6 | 63.4 | 57.6 | 69.5 | 65.0 | 62.5 | 67.3 | 73.9 | 75.6 | 72.8 | 54.9 | 58.4 | 51.1
Italy | .. | .. | .. | .. | .. | .. | 49.6 | 58.6 | 37.9 | 59.9 | 78.8 | 45.0 | 61.9 | 67.6 | 55.5
Luxembourg | 84.6 | 84.7 | 84.5 | 85.8 | 87.4 | 84.1 | 80.9 | 82.3 | 79.3 | 80.7 | 89.1 | 73.6 | 88.4 | 90.0 | 86.6
Netherlands | 66.5 | 69.2 | 68.9 | 82.4 | 88.6 | 85.5 | 65.3 | 72.5 | 62.5 | 60.9 | 79.3 | 50.0 | 86.8 | 87.7 | 86.0
New Zealand | .. | .. | .. | .. | .. | .. | 75.7 | 78.5 | 72.8 | 80.5 | 90.5 | 69.8 | 75.0 | 83.0 | 66.8
Norway | 68.1 | 68.8 | 67.4 | 76.1 | 76.4 | 75.8 | 67.4 | 67.8 | 66.8 | 64.4 | 72.3 | 56.1 | 83.2 | 84.4 | 81.9
Portugal | .. | .. | .. | .. | .. | .. | 70.2 | 73.6 | 66.2 | 68.0 | 70.8 | 65.9 | 67.5 | 69.2 | 65.6
Spain | 38.9 | 40.0 | 37.7 | 46.9 | 46.1 | 47.8 | 32.2 | 32.5 | 31.8 | 47.5 | 50.9 | 44.4 | 56.9 | 58.0 | 55.6
Sweden | 71.3 | 73.9 | 71.1 | 79.8 | 80.0 | 83.1 | 73.3 | 73.5 | 75.1 | 66.4 | 75.9 | 56.6 | 83.2 | 83.9 | 82.3
Switzerland | 86.8 | 90.6 | 81.8 | 85.1 | 83.9 | 86.5 | 82.3 | 83.2 | 81.2 | 79.4 | 89.1 | 70.6 | 90.1 | 91.3 | 88.8
United Kingdom | 66.4 | 70.5 | 61.8 | 68.6 | 71.1 | 66.2 | 72.4 | 80.4 | 64.7 | 74.1 | 88.9 | 61.1 | 77.0 | 81.2 | 72.4
United States | 72.5 | 75.3 | 69.3 | 72.8 | 78.3 | 67.0 | 71.8 | 79.8 | 63.6 | 70.3 | 89.3 | 50.5 | 72.9 | 77.0 | 68.8
OECD total (17) | 70.9 | 73.7 | 68.0 | 73.4 | 76.3 | 70.7 | 69.7 | 75.7 | 63.6 | 66.9 | 82.1 | 52.7 | 74.9 | 78.2 | 71.4
EU total (11) | 65.1 | 68.1 | 62.2 | 71.1 | 72.0 | 70.9 | 66.0 | 70.8 | 61.1 | 61.6 | 74.0 | 50.9 | 76.6 | 79.1 | 73.9

Notes: Data for Greece, Ireland, Italy, New Zealand and Portugal cover the foreign-born population only and not the native-born with foreign-born parents. For these five countries, outcomes for foreign-born are compared to those of all native-born (including offspring of immigrants). In order to provide comparable outcomes across target groups, OECD and EU averages do not include data for these five countries.

* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: Labour Force Surveys: Belgium (foreign-born population in 2012), Israel (2011), France (2012), Greece (2012), Ireland (2012), Italy (2012), Portugal (2012), Switzerland (2013), United Kingdom (2013), the Netherlands (2013), New Zealand (2014). Censuses in 2011: Australia, Spain and Luxembourg. Population registers: Denmark (2013), Finland (2012), Norway (2013) and Sweden (2013). National Household Survey (NHS) 2011: Canada. Banque Carrefour de la Sécurité Sociale 2012 on population born in Belgium. Mikrozensus 2012: Germany. Mikrozensus 2013: Austria. Current Population Survey 2013: United States.

StatLink  http://dx.doi.org/10.1787/888933214312

Figure 13.A1.4. Employment rates by migration background, 2007-08 and 2013

Percentage of population aged 15 to 34

Notes: For non-EU OECD countries in 2007-08 immigrants entered in their childhood are defined as those entered before the age of 18. Data for Greece, Ireland, Italy, New Zealand and Portugal cover the foreign-born population only and not the native-born with foreign-born parents. For these five countries, outcomes for foreign-born are compared to those of all native-born (including offspring of immigrants). In order to provide comparable outcomes across target groups, OECD and EU averages do not include data for these five countries.

Sources: Labour Force Surveys: Belgium (foreign-born population in 2012), France (2012), Greece (2012), Ireland (2012), Italy (2012), Portugal (2012), Switzerland (2013), United Kingdom (2013), the Netherlands (2013), New Zealand (2014). Censuses in 2011: Australia, Spain and Luxembourg. Population registers: Denmark (2013) and Sweden (2013). National Household Survey (NHS) 2011: Canada. Banque Carrefour de la Sécurité Sociale 2012 on population born in Belgium. Mikrozensus 2012: Germany. Mikrozensus 2013: Austria. Current Population Survey 2013: United States. Ad hoc module of European Union Labour Force Survey (EU-LFS) 2008; Liebig and Widmaier (2009) for non-EU OECD countries in 2007-08.

StatLink  http://dx.doi.org/10.1787/888933213568

Figure 13.A1.5. Evolution of employment rates among 15-34 year-olds by migration background and gender between 2007-08 and 2013

Notes: For non-EU OECD countries in 2007-08, immigrants entered in their childhood are defined as those entered before the age of 18. Data for Greece, Ireland, Italy, New Zealand and Portugal cover the foreign-born population only and not the native-born with at least one foreign-born parent. For these five countries, outcomes for foreign-born are compared to those of all native-born (including offspring of immigrants). In order to provide comparable outcomes across target groups, OECD and EU averages do not include data for these five countries.

Sources: Labour Force Surveys: Belgium (foreign-born population in 2012), France (2012), Greece (2012), Ireland (2012), Italy (2012), Portugal (2012), Switzerland (2013), United Kingdom (2013), the Netherlands (2013), New Zealand (2014). Censuses in 2011: Australia, Spain and Luxembourg. Population registers: Denmark (2013) and Sweden (2013). National Household Survey (NHS) 2011: Canada. Banque Carrefour de la Sécurité Sociale 2012 on population born in Belgium. Mikrozensus 2012: Germany. Mikrozensus 2013: Austria. Current Population Survey 2013: United States. Ad hoc module of European Union Labour Force Survey (EU-LFS) 2008. Liebig and Widmaier (2009) for non-EU OECD countries in 2007-08.

StatLink  http://dx.doi.org/10.1787/888933213579

Figure 13.A1.6. Differences in employment rates by migration background and educational level in 2007-08 and 2013

Differences in percentage points with offspring of native-born

Notes: Data for Belgium, Greece, Ireland, Italy, New Zealand and Portugal cover the foreign-born population only and not the native-born with foreign-born parents. For these six countries, outcomes for foreign-born are compared to those of all native-born (including offspring of immigrants). In order to provide comparable outcomes across target groups, OECD and EU averages do not include data for these six countries.

Sources: Labour Force Surveys: Belgium (foreign-born population in 2012), France (2012), Greece (2012), Ireland (2012), Italy (2012), Portugal (2012), Switzerland (2013), United Kingdom (2013), the Netherlands (2013), New Zealand (2014). Censuses in 2011: Australia, Spain and Luxembourg. Population registers: Denmark (2013) and Sweden (2013). National Household Survey (NHS) 2011: Canada. Mikrozensus 2012: Germany. Mikrozensus 2013: Austria. Current Population Survey 2013: United State. Ad hoc module of European Union Labour Force Survey (EU-LFS) 2008. Liebig and Widmaier (2009) for non-EU OECD countries in 2007-08.

StatLink  http://dx.doi.org/10.1787/888933213586

Table 13.A1.10. Unemployment rates by migration background among 15-34 year-olds, 2013
| Native-born offspring of foreign-born | Native-born with a mixed background | Foreign-born who arrived as children | Foreign-born who arrived as adults
| Unemployment rate | Difference (+/-) with offspring of native-born | Unemployment rate | Difference (+/-) with offspring of native-born | Unemployment rate | Difference (+/-) with offspring of native-born | Unemployment rate | Difference (+/-) with offspring of native-born
Australia | 6.3 | -0.7 | 6.7 | -0.3 | 18.7 | +11.7 | 7.9 | +0.8
Austria | 18.0 | +12.7 | 12.3 | +7.0 | 13.3 | +8.0 | 10.6 | +5.2
Belgium | 23.4 | +15.7 | 12.9 | +5.1 | 23.2 | +15.5 | 21.3 | +13.6
Canada | 7.6 | -1.0 | 7.7 | -0.9 | 9.0 | +0.4 | 10.3 | +1.7
Denmark | 16.3 | +9.3 | 9.0 | +2.0 | 17.1 | +10.1 | 9.2 | +2.2
Finland | 16.0 | +3.9 | 15.1 | +3.1 | 18.7 | +6.7 | 24.3 | +12.2
France | 23.8 | +10.1 | 16.5 | +2.8 | 22.6 | +8.9 | 21.9 | +8.2
Germany | 15.0 | +8.6 | 14.1 | +7.7 | 9.7 | +3.3 | 9.6 | +3.2
Greece | .. | .. | .. | .. | 46.6 | .. | 35.2 | ..
Ireland | .. | .. | .. | .. | 33.8 | .. | 15.8 | ..
Israel* | 9.0 | +0.7 | 10.1 | +1.8 | 8.9 | +0.6 | 6.2 | -2.1
Italy | .. | .. | .. | .. | 28.4 | .. | 16.4 | ..
Luxembourg | 9.8 | +3.3 | 9.1 | +2.5 | 12.0 | +5.5 | 10.3 | +3.8
Netherlands | 15.5 | +10.1 | 5.7 | +0.3 | 13.0 | +7.5 | 13.1 | +7.6
New Zealand | .. | .. | .. | .. | 9.4 | .. | 6.4 | ..
Norway | 5.4 | +2.9 | 3.2 | +0.8 | 6.1 | +3.6 | 5.6 | +3.2
Portugal | .. | .. | .. | .. | 18.3 | .. | 23.3 | ..
Spain | 48.1 | +12.9 | 42.1 | +6.9 | 55.3 | +20.1 | 43.1 | +7.8
Sweden | 15.6 | +7.3 | 9.8 | +1.6 | 15.4 | +7.2 | 19.2 | +11.0
Switzerland | 7.3 | +3.7 | 7.0 | +3.4 | 10.9 | +7.3 | 9.3 | +5.7
United Kingdom | 20.0 | +9.1 | 18.1 | +7.1 | 13.8 | +2.9 | 8.4 | -2.6
United States | 11.2 | +0.6 | 10.7 | +0.1 | 9.7 | -0.9 | 6.7 | -3.9
OECD total (17) | 13.5 | +1.8 | 12.1 | +0.5 | 13.2 | +1.5 | 12.7 | +1.1
EU total (11) | 20.1 | +6.5 | 16.7 | +3.2 | 18.6 | +5.0 | 19.7 | +6.1
* Information on data for Israel: http://dx.doi.org/10.1787/888932315602.

Sources: Labour Force Surveys: Belgium (foreign-born population in 2012), Israel (2011), France (2012), Greece (2012), Ireland (2012), Italy (2012), Portugal (2012), Switzerland (2012); United Kingdom (2013), the Netherlands (2013), New Zealand (2014). Population registers: Denmark (2013) and Sweden (2013). Banque Carrefour de la Sécurité Sociale 2012 on population born in Belgium. Mikrozensus 2012: Germany. Mikrozensus 2013: Austria. Current Population Survey 2013: United States.

StatLink  http://dx.doi.org/10.1787/888933214323

Chapter 14.

Third-country nationals in the European Union

This chapter considers the full set of “Zaragoza indicators” for third-country nationals in the European Union (for a presentation, see below), comparing their outcomes with those of domestic and EU nationals. Built on existing data for most member states, they are limited in number, comparable in time, productive, cost-effective, simple to understand and communicate, and outcome-focused. They are therefore highly meaningful support tools for monitoring integration policy outcomes at European, national and regional level.

The chapter looks first at the size and composition of third-country national populations (14.1). It then goes on to consider their countries of birth and length of residence (14.2), before analyzing outcomes in employment and activity (14.3), unemployment (14.4), self-employment (14.5), overqualification (14.6), levels of education and literacy (14.7), income distribution (14.8), poverty (14.9), housing tenure status (14.10), perceived health status (14.11), long-term resident status (14.12), participation in voting (14.13), the acquisition of nationality (14.14), and perceived discrimination (14.15). Data limitations will be discussed at the end of the chapter.

The “Zaragoza” indicators: indicators for monitoring integration policy outcomes in the European Union

“Migrants” in the context of the European Union are understood to be non-EU, or third-country, nationals who reside legally in the European Union. Their situations often differ markedly from those of EU citizens moving between or living in EU member states other than their own. Although many enjoy equal rights with host-country nationals, there are greater restrictions on third-country national’s mobility within the European Union. Their reasons for migrating are also likely to be different from those that prompt EU nationals to move, and often include asylum or family reunification.

The Europe 2020 strategy considers better integration of third-country nationals as a factor that will help it meet its first headline target of a 75% employment rate among 20-64 year-olds. Given the share of non-EU nationals in its labour force today, the European Union can meet that employment target only if it improves their labour market outcomes.

Although integration policies are defined and implemented primarily at national or sub-national level, they are closely linked to the EU equality framework and to EU provisions that grant migrants residing in the European Union certain rights (e.g. equal working conditions and equal access to goods and services). The European Union indeed has adopted a number of EU non-discrimination laws which are of relevance for the integration of third-country nationals, in particular the Directive 2000/43/EC on racial equality and the employment equality directive (Directive 2000/78/EC). Moreover, since 2009, the Treaty on the Functioning of the European Union states, in Article 79.4, that the European Union may offer support and incentives to member states who take action to promote the integration of legally resident third-country nationals (though that does not include any legal harmonisation).

The European Union has also developed Common Basic Principles for Immigrant Integration Policy. They were adopted in 2004 and reaffirmed in 2014 as the general framework for EU policy co-operation on integration and for member countries’ assessments of their own efforts. The Common Basic Principles cover the main aspects of integration – employment, education, access to institutions, goods and services, and integration into the society in general. And, most importantly, they define it as a two-way process of mutual accommodation between migrants and EU nationals.

Known as the “Zaragoza indicators”, those Common Basic Principles were introduced at a ministerial conference under the Spanish presidency of the European Union in April 2010. Following the conclusions on integration adopted by the Justice and Home Affairs (JHA) Council in June 2010, the Commission worked with member states to draw up those indicators for monitoring the results of integration policies in the four areas of employment, education, social inclusion and active citizenship. These indicators are in line with Europe 2020. A pilot study on the common indicators published its findings in a report, “Using EU Indicators of Immigrant integration”, which was unveiled in 2013. Eurostat updates the indicators annually, drawing on already harmonised data sources, such as the EU Labour Force Survey and the EU Survey on Income and Living Conditions.

Key findings

Third-country nationals account for a growing share of the total population in the European Union

In 2013, there were 20 million third-country nationals living in the European Union, with high numbers living in the EU15 countries and relatively fewer in new member states. The share of third-country nationals is on the increase, climbing from 3.4% in 2005 to 4.1% in 2013. The countries where rises were steepest were Italy and Slovenia.

Except for low-educated ones, third-country nationals perform worse on the labour market

EU-wide, 54% of third-country nationals are in employment. The employment rate of third-country nationals is less than that of host-country nationals in all countries with the exception of men in the Czech Republic, Slovenia, Hungary, Italy, Luxembourg and women in Cyprus,1, 2 Malta and the Czech Republic.

The same proportions of third-country nationals and host-country citizens with low levels of educational attainment are employed. In contrast, third-country nationals with higher education degrees have greater trouble finding a job than their EU peers.

In 2012-13, 22% of non-EU foreigners were unemployed, a rate double those of host-country and EU nationals. In Sweden, Luxembourg and Belgium, their unemployment rates were four times higher than those of nationals.

The financial and economic crisis of 2007-08 hit third-country foreigners, especially men, harder than EU nationals. The unemployment rate has fallen mostly in Germany, Luxembourg and the Czech Republic.

The average rate of overqualification among third-country workers stands at 44%, compared to 20% among host-country nationals. It is as high as 80% in Italy and Greece.

A significant share of third-country nationals lack basic skills

Three countries have achieved the Europe 2020 education goal of 40% of 30-34 year-olds completing a tertiary education done so for their third-country residents: the United Kingdom, Ireland and Luxembourg.

Across the European Union, 18% of third-country foreigners aged 25-34 have very low levels of education (equivalent to primary schooling at best) in contrast to host-country nationals for whom the figure is 4%.

Although healthier, third-country nationals face poorer living conditions compared to host-country nationals

The annual median revenue of third-country nationals in EU countries were lower than that of host-country nationals. 39% of third-country national households live in poverty – twice as high as among national households.

Third-country nationals in all EU countries were three times less likely than host-country nationals to own their own homes in 2012.

Third-country nationals report being in better health than nationals, particularly in south Europe.

Most immigrants born in a third country have the citizenship of the host country and vote

Seven out of ten third-country immigrants with host-country citizenship voted in the most recent national elections, compared to 8 in 10 native-born nationals.

In 2012-13, nearly two-thirds of immigrants born in a third country had acquired the nationality of the host country after 10 years of residence. Highly qualified third-country immigrants are the most likely to take up this nationality.

Perceived discrimination is larger among third-country nationals than among EU nationals, even for those born in the host country

In 2002-12, nearly a quarter of third-country nationals felt that they were discriminated against because of their origin. Perceived discrimination is lowest in the Scandinavian countries and Luxembourg, and most widespread in Greece and Austria. Third-country citizens born in the host country and those born abroad feel equally discriminated against.

Section 14.1. Size and composition by age and gender

Background

Definition

A third-country national is a foreigner who has the nationality of non-EU country (see Glossary).

Coverage

Total population in EU countries.

In 2013, 20 of the 34 million foreigners residing in a European Union country – or 4.1% of the Union’s total population – were nationals of a third country. Nearly one-quarter lived in Germany, while Italy and Spain accounted for 15%, France 13%, and the United Kingdom 12%.

Third-country residents account for the highest shares of the total population in Latvia and Estonia (Figure 14.1) where, after the breakup of the Soviet Union, many residents originally from Russia kept their Russian nationality. In Austria, Luxembourg and Germany, and in most of southern Europe, particularly Spain, over 5% of the population originates from a third country. Shares are low, however, in the majority of central European countries, particularly in Poland and Romania. Numbers of third-country nationals are higher than those of non-host-country EU nationals in most member states. There are, however, twice as many EU foreigners as third-country foreigners in Ireland and Belgium, and six times more in Luxembourg (Figure 14.A1.1).

The share of foreigners from third countries in the total EU population rose from 3.4% to 4.1% between 2005 and 2013 (Figure 14.1). The increase was observed in all countries, except in the Baltic States and those, like Germany and the Netherlands, that had experienced steep climbs in arrivals of residents from other EU countries. Italy and Slovenia, with 2 percentage points, and Belgium and Portugal, with 1.5, also saw considerable increases over the period.

On average, 78% of third-country nationals in the European Union are of working age (15-64 years old), 7% are over 64, and 15% are less than 15. With the chances of obtaining host-country nationality increasing with length of stay, the younger age brackets account for the bulk of the foreign population (Figure 14.3). The share of 15-24 year-olds among third-country nationals (including those born in the host country) is much the same as among host-country nationals and higher than among EU citizens. One in four third-country nationals in the Baltic states is over 64 years old, while in countries of longstanding immigration like Germany and France the rate is one in ten.

With the exception of Latvia, host countries’ national populations have an older average age than their residents from non-EU countries – particularly in central Europe (Romania being a prime example), some southern European countries (Cyprus1, 2 and Malta), the United Kingdom and the Netherlands. There are proportionally more under-15s in third-country than in national populations in host countries like Italy where the naturalisation of minors born to immigrant parents is more difficult, and in those where most immigration is for family reasons, as in Austria and France (Figure 14.2).

Figure 14.1. Populations of third-country nationals, 2005 and 2013

Percentage of the total population

StatLink  http://dx.doi.org/10.1787/888933213599

Figure 14.2. Population aged under 15 and over 65 years old by citizenship, 2012-13

Percentage of the third-country population and national populations

StatLink  http://dx.doi.org/10.1787/888933213702

Figure 14.3. Age distribution of working-age populations by citizenship, 2012-13

Percentages of the third-country national, EU national and national populations, respectively

StatLink  http://dx.doi.org/10.1787/888933213814

Notes and sources are to be found at the end of the chapter.

Section 14.2. Places of birth and length of residence

Background

Definition

This section looks separately at people born in the host country but who do not have citizenship and at those born abroad, and how long the latter have lived in the host country.

Coverage

Third-country citizens aged between 15 and 64 years old.

Across the European Union in 2012-13, the vast majority of third-country residents were born abroad. Just 7% were born in the host country (Figure 14.4). That percentage is far higher in countries where birthright citizenship is not automatic.

Half of all non-EU foreigners living in Estonia and Latvia, for example, were in fact born there. The proportion is so high because, at independence, neither country automatically granted nationality to the offspring of residents who had immigrated during the Soviet era. Up to the year 2000 Germany required the offspring of foreign parents to choose between their parents’ nationality and German citizenship, which explains why as many as 17% of foreigners of third-country extraction were born in Germany. By contrast, in over half of all EU member states less than 1 in 50 non-EU foreigners was born in the host county. In France and Cyprus,1, 2 the proportion is as low as 1 in 100.

Across member states, 1.1% of 15-34 year-olds born in the country have only foreign nationality. Of that figure, two-thirds are third-country nationals (Figure 14.5). The situation varies widely from one country to another. In those which automatically grant nationality at birth or on majority, like France and the United Kingdom, less than 1 in 500 people are foreign citizens. The reverse trend prevails in countries which still restrict dual nationality. For example, 1 in every 20 people born in the Baltic countries (with the exception of Lithuania) keeps their parents’ nationality, while over 1 in 50 also has third-country nationality in Germany and Austria, and nearly 1% in Denmark and Greece. In Luxembourg, where third-country immigration is low, 17% of the young people born in the country are citizens of another EU member state.

An EU-wide average of 47% of third-country residents have lived in their host countries for at least ten years, a proportion that exceeds 50% in long-standing immigrant destinations like Germany, France and the Netherlands. In Sweden, by contrast, where most immigrants from third countries naturalise relatively quickly, some two-thirds of non-EU nationals are residents of less than five years standing (Figure 14.6).

As for southern Europe, although countries have continued to take in new non-EU migrants over the last ten years, most of those who reside in Italy and Greece are long-settled. In both countries, legislation governing the acquisition of nationality is relatively restrictive. Immigrant communities who arrived more than 10 years ago (Moroccans in Italy and Albanians in Italy and Greece) have kept their original nationality and still account for the bulk of third-country immigrants.

Figure 14.4. Third-country national population by place of birth, 2012-13

StatLink  http://dx.doi.org/10.1787/888933213856

Figure 14.5. Native-born population by foreign citizenship, 2012-13

In percentage of the native-born population

StatLink  http://dx.doi.org/10.1787/888933213867

Figure 14.6. Third-country nationals by duration of stay, 2012-13

Total = 100 (15 to 64 year-olds)

StatLink  http://dx.doi.org/10.1787/888933213876

Notes and sources are to be found at the end of the chapter.

Section 14.3. Employment and activity

Background

Indicator

The employment rate is the percentage of 15-64 year-olds who are in employment. The activity rate denotes the economically active population (whether in employment or not) as a proportion of all 15-64 year-olds. For further information, see Indicator 5.1.

Coverage

Working-age population (15-64 years old).

In 2012-13, the average employment rate of third-country citizens living in an EU country was 54% – 8 percentage points lower than that of the immigrant population as a whole. It exceeded 60% in the new member states where generally young immigrants arriving from third countries have filled unskilled jobs, and over 70% in the Czech Republic and Cyprus.1, 2 They are the only two countries yet to have met the Europe 2020 employment target for third-country residents aged 20-64 years old, even though five countries (Germany, Austria, Denmark, the Netherlands and Sweden) have done so for nationals and eight for EU foreigners. Less than a half of third-country foreigners had a job in crisis-ridden southern Europe, France and Sweden, and even fewer in Belgium (Figure 14.7).

On average, third-country nationals are much more likely to be out of work than all their EU peers. The employment gap that separates them from host-country nationals is 7 percentage points for men and 15 among women. Indeed, women are even less likely to be in work in longstanding immigrant destinations like the EU15, particularly in Sweden, Belgium and France.

However, in some central European countries (particularly the Czech Republic and Slovenia), Italy and Luxembourg, third-country males are slightly more often in employment than host-country nationals. While the employment rate of third-country males is much the same as their host-country peers in Cyprus,1, 2 among non-EU females it is, at 76%, considerably higher than those of women in all other EU countries, irrespective of their nationality.

With the exception of members states where much past migration has been low-skilled labour migration (e.g. Cyprus1, 2 and Greece), high levels of education are generally associated with higher employment rates. However, the employment gap between third- and host-country nationals with higher education qualifications is wider across the EU – 16 percentage points (Figure 14.8). The employment gap between EU and non-EU nationals even exceeds 20 percentage points in such EU15 countries as Belgium and Finland. A main cause is the difficulty that third-country nationals encounter in getting their foreign qualifications valued in the labour market. Even in the United Kingdom and the Czech Republic, where employment gaps are not so stark, it stands at 8 percentage points between host- and third-country nationals with tertiary education degrees.

When third-country immigrants have no or low qualifications, their employment levels are higher than those of host-country nationals educated to the same degree in the recent immigration countries, Luxembourg and central Europe. In fact, their employment rates can be as high as 40 percentage points more than those of host-country peers in the Czech Republic and Cyprus.1, 2 Elsewhere , however, the employment rates of low and unskilled third-country workers are at least 10 percentage points lower than those of their national peers and, in Sweden and the Netherlands, the figure is 20 points.

Figure 14.7. Employment rates by citizenship and gender, 2012-13

Percentage of the working-age population (15-64 years old)

StatLink  http://dx.doi.org/10.1787/888933213888

Figure 14.8. Difference between employment rates of third-country national and national populations aged 15 to 64 by level of education (excluding persons still in education), 2012-13

Percentage points

StatLink  http://dx.doi.org/10.1787/888933213893

Notes and sources are to be found at the end of the chapter.

Between 2006-07 and 2012-13, employment rates among third-country workers fell by 4 percentage points, while those of host-country nationals, other EU national  residents, and immigrants as a whole remained relatively stable. Third-country male workers were hardest hit by the economic and financial crisis, with their employment rates dropping 7 percentage points, against just 2 points among their female peers (Figure 14.9).

Employment rates among third-country female workers had constantly risen since the early 2000s before being brought to a halt by the crisis in 2007-08. In the worst affected countries (e.g. Spain, Ireland, Greece), their employment levels were high until they fell by over 10 percentage points compared to 2006-07. The labour market prospects of third-country women have also dimmed in some central European countries like Hungary, in the Baltic States and in Sweden. In other countries, however, where their employment rates were as low as 40% or less in 2006-07, non-EU women were not unduly affected by the 2007-08 crisis. As for countries like Germany and Luxembourg, where economic conditions have now improved, female employment has increased.

Third-country male workers – who tend to be chiefly employed in sectors most sensitive to the economic climate (e.g. construction and manufacturing) – have suffered much more from the recession in the European Union. In the hardest hit countries, their employment rates tumbled twice as fast as those of women and in others, such as Greece and Italy, three times as fast. In the last six years, however, some countries have seen firm growth in the employment rates of third-country nationals. They include Germany, Luxembourg and Poland.

In 2012-13, 69% of third-country nationals of working age residing in the European Union were economically active, whether they were in work or not. The rate had remained stable for five years, while the overall immigrant employment rate rose. In Cyprus,1, 2 it was as high as 80% and levels were similar in the Baltic states (particularly Lithuania) and southern Europe (e.g. Portugal, Spain). They barely exceeded 60% in France and the Netherlands, however, and were even lower in Belgium (Figure 14.10).

Across the European Union, male citizens from third countries are, on average, more economically active than host-country nationals, with an activity rate that is 3 percentage points higher. Women, on the other hand, are as much as 10 points less active. Although they are more likely to be economically active than their host-country peers in southern Europe, the opposite holds true in such traditional immigration destinations as the EU15, where one third-country female national in two is disconnected from the labour market. Those countries – especially Belgium, France and the Netherlands – host many women who immigrate for reasons of family reunification and hail from countries where employment rates of women are low. In the Nordic countries, where they are often humanitarian migrants, women show a similar picture.

Figure 14.9. Employment rates of third-country nationals by gender, 2006-07 and 2012-13

Percentage of the working-age population (15-64 years old)

StatLink  http://dx.doi.org/10.1787/888933213904

Figure 14.10. Activity rates by citizenship and gender, 2012-13

Percentage of the working-age population (15-64 years old)

StatLink  http://dx.doi.org/10.1787/888933213601

Notes and sources are to be found at the end of the chapter.

Section 14.4. Unemployment

Background

Indicator

The unemployment rate is the percentage of unemployed workers in the economically active population. For further information, see Indicator 5.2.

Coverage

Economically active population of working age (15-64 years old).

In 2012-13, the average unemployment rate among third-country nationals in the European Union was 22%, against 12% among EU foreigners, and 10% for host-country nationals (Figure 14.11). To put those figures into perspective, the number of unemployed third-country nationals, estimated at 3.2 million, was equivalent to 70% of the total number of unemployed immigrants.

Unemployment reaches its highest levels in countries that are recent immigration destinations and have been sorely affected by the crisis. In Spain and Greece, for example, four out of ten third-country nationals in the labour force are unemployed. Yet unemployment for this group is also high in countries where the economic situation is less grim. One in four of the economically active is out of work in France and one in three in Belgium and Sweden. Indeed, unemployment rates are under 10% only in a few new member states like the Czech Republic, where is it is only 6%.

Third-country nationals are affected by higher unemployment rates than host-country nationals and EU foreigners in practically every country in the European Union, with the exception of the Czech Republic, Cyprus1, 2 and Hungary. In southern Europe, where unemployment is also high among EU citizens and host-country nationals, unemployment rates are 1.5 times higher among third-country nationals, twice as high in EU15 countries of longstanding immigration (Austria, the Netherlands, Germany and France), and four times greater in Sweden and Belgium (Figure 14.12).

Generally speaking, unemployment rates are higher among the poorly educated, regardless of their nationality, although the ratio between third- and host-country individuals in that group is less pronounced. In the few countries where most low-qualified migrants arrived as labour migrants (Cyprus,1, 2 the Czech Republic and Greece), low-educated non-EU workers actually slot into the labour market more easily than the highly educated.

On average, highly educated third-country nationals are almost three times more likely to be unemployed than their host-country peers – a gap that is wider than for non-host-country EU citizens. Indeed, in Benelux, Austria and Germany, they are five times more likely to be without a job than their host-country peers (Figure 14.11).

Figure 14.11. Unemployment rates by citizenship and level of education, 2012-13

Percentage of the economically active population (15-64 years old)

StatLink  http://dx.doi.org/10.1787/888933213613

Figure 14.12. Unemployment rates by citizenship, 2012-13

Percentage of the economically active population (15-64 years old)

StatLink  http://dx.doi.org/10.1787/888933213620

Notes and sources are to be found at the end of the chapter.

In 2012-13, male and female unemployment rates were broadly similar. Among third-country nationals, however, women were slightly more likely to be unemployed, a trend that was even more pronounced among their peers from other EU countries (Figure 14.13). In Slovenia, for example, the unemployment rate among third-country women was four times higher than among their male counterparts. In northern Europe, the Netherlands and the United Kingdom, non-EU women in the labour force were also more often unemployed, while among host-country nationals men were worse affected. Spain shows the opposite pattern, with third-country males more likely than females to be unemployed and host-country women worse hit than men.

Since the onset of the crisis, gender differences in unemployment rates have narrowed regardless of national origin because there have generally been greater job losses in sectors where men dominate, i.e. construction, manufacturing, etc. However, in southern European countries like Spain and Portugal, which saw particularly strong construction booms in the 2000s, third-country male unemployment rates –  lower than those of their female counterparts in 2006-07 – are now 5 percentage points higher.

While the economically active population among nationals grew by 1% on average in the European Union between 2006-07 and 2012-13, the number of jobless rose by 38% in the wake of the crisis. That increase was as high as 73% among third-country foreigners whose economically active numbers grew 18% over the same period. Altogether, the number of third-country nationals who were unemployed climbed from 1.9 million in 2006-07 to 3.2 million in 2012-13. Over the same period, unemployment rates among third-country nationals increased by an average of 7 percentage points in the European Union, compared to +3 points among host-country nationals and other EU citizens.

In almost half of all EU countries, third-country workers were actually less affected by job losses than host-country nationals. Their unemployment rates actually fell more sharply than among host-country nationals in Germany, Luxembourg, the Czech Republic and Finland. In some other countries where unemployment rates rose in the six years to 2013, they suffered less than host-country nationals. Examples are the United Kingdom and, in particular, Cyprus.1, 2 Nevertheless, in the countries worst hit by the crisis, like those of southern Europe, unemployment rates climbed even more steeply among third-country workers than among their peers from the host and other EU countries. In Greece and Spain, for example, they rose more than 25 percentage points, compared to 16 among nationals. There were also steep increases in Sweden, while host-country national unemployment rates stayed relatively stable (Figure 14.14).

The financial and economic crisis of 2007-08 was particularly hard on the most vulnerable people on the labour market, such as those with low levels of education. Third-country nationals are overrepresented among unskilled workers, which explains why they have suffered more from the crisis than host-country nationals. However, the increase in the unemployment rates of third- and host-country nationals with the same level of education has been similar. Low-educated third-country workers have even been less affected than their host-country counterparts in the bulk of EU15 countries (e.g. Germany, France, United Kingdom), though not in southern Europe.

Despite their advantages, higher-education degree holders also experienced a wholesale rise in unemployment across the European Union, albeit less so than all immigrants taken as a whole. In Greece, the increase in unemployment rates among the highly educated was almost the same as for their counterparts with low education. More high-educated third- than host-country nationals lost their jobs in most member states, with the exceptions once again of Germany, Luxembourg and the Czech Republic.

Figure 14.13. Unemployment rates by citizenship and gender, 2012-13

Percentage of the economically active population (15-64 years old)

StatLink  http://dx.doi.org/10.1787/888933213634

Figure 14.14. Evolution of unemployment rates between 2006-07 and 2012-13

Percentage points, 15-64 years old

StatLink  http://dx.doi.org/10.1787/888933213647

Notes and sources are to be found at the end of the chapter.

Section 14.5. Self-employment

Background

Indicator

A self-employed worker is a person who works in his or her own enterprise or creates his or her own business for profit. For further information, see Indicator 6.5.

Coverage

Employed population aged 15-64 years old, excluding the agriculture sector.

In 2012-13, 11% of all third-country nationals in employment in the European Union were self-employed. There was a similar proportion among host-country nationals, and a rather higher one among EU foreigners, 15% of whom were self-employed, particularly in the EU15 and Estonia. The percentage of non-EU self-employed workers was much higher than in the rest of the population in only a few central European countries – more than one in four in the Czech Republic, Poland and Hungary, double the level of host-country nationals (Figure 14.15). At the opposite end of the scale came the recent immigration destinations of southern Europe (e.g. Greece and Italy), where many domestic nationals are self-employed – twice as many, in fact, as third-country nationals, who are widely low-skilled wage-earners. In the rest of the EU15 area, the incidence of self-employment is broadly similar among both host- and third-country nationals.

Theoretically self-employment should be of unlimited duration. But business must be viable. Numerous national studies have shown that start-up survival rates are lower when the entrepreneur is a foreigner, particularly from a third country. In addition, on average across the European Union, three-quarters of the self-employed have no employee. Sole proprietor businesses are the norm practically everywhere, particularly in the Czech Republic, the United Kingdom and the countries of southern Europe (Figure 14.16).Only in Latvia and Austria do over half of all third-country entrepreneurs have one or more salaried employees.

Far fewer third-country nationals are self-employed if only businesses with employees are considered. Such entrepreneurship accounts for only 3% of non-EU employment, compared to 4% among host-country nationals, and 3.6% for EU foreigners (Figure 14.17). However, in the Czech Republic third-country nationals are twice as likely as host-country nationals to be employers. They also have a higher likelihood to be employers in the Netherlands.

Only 1.5% of business owners with more than ten employees are third-country nationals. In most member states, in fact, less than 1 in 30 are. Exceptions are Estonia with 8% and Latvia with 15%. Both countries have long-standing Russian communities which have set up small and medium-sized enterprises. With the exception of Latvia again and Cyprus,1, 2 far less third- than host-country national entrepreneurs have firms employing more than ten people. Such under-representation is especially pronounced in economies like Austria, Germany and the Nordic countries.

Figure 14.15. Self-employed workers by citizenship, 2012-13

Percentage of employment (excluding the agricultural sector), persons aged 15-64

StatLink  http://dx.doi.org/10.1787/888933213659

Figure 14.16. Self-employed third-country nationals by firm size, 2012

Total = 100 (excluding the agricultural sector), persons aged 15-64

StatLink  http://dx.doi.org/10.1787/888933213668

Figure 14.17. Self-employed workers, not including those who have no employee, 2012

Percentage of employment (excluding the agricultural sector), persons aged 15-64

StatLink  http://dx.doi.org/10.1787/888933213679

Notes and sources are to be found at the end of the chapter.

Section 14.6. Overqualification

Background

Indicator

Overqualification denotes the proportion of people with tertiary education whose activity requires only lower levels of qualifications. For further information, see Indicator 6.4.

Coverage

Employed 15-64 year-old with tertiary educational attainment (high-educated; Levels 5 to 6 in the International Standard Classification of Education [ISCED]), excluding the armed forces (International Standard Classification of Occupations [ISCO], Level 0), where job skills are not referenced.

In 2012-13, 44% of high-educated third-country nationals were overqualified for the job they occupied, while only one-third of EU foreigners and one-fifth of host-country nationals were. Two-thirds of high-educated non-EU workers were overqualified in southern European member states, with the proportion reaching four-fifths in Italy and Greece. Such countries have seen considerable growth in low-skilled jobs which been partly filled by third-country nationals, who include the most highly qualified. Overqualification is three times more likely among third- than host-country nationals in southern Europe, (particularly Portugal and Italy), northern Europe (especially Denmark) and Luxembourg (Figure 14.18).

The prevalence of overqualification among third-country nationals can be partly attributed to the trouble they have having their credentials valued in the host-country labour market and partly to their inadequate command of the host country’s language and understanding of its labour market. Although EU education systems generally automatically recognise each other’s academic qualifications, systems for third countries are less well developed. As a result, the qualifications of many third country workers are never recognised, which prevents them from finding matching jobs.

Although overqualification affects host-country male and female workers, foreign women are worse off in almost every country. The overqualification rate of third-country women is 11 percentage points higher than among their male peers and 13 points higher than among EU female citizens. Overqualification gender gaps are at their widest in southern European countries, Finland and the Czech Republic. The only countries where men in employment are more likely than women to be overqualified are the Baltic countries and Denmark.

Since the 2007-08 economic and financial downturn, the overqualification rate has risen only slightly in national populations, with the exception of Greece and the Czech Republic. As for third-country nationals, however, trends between 2006-07 and 2012-13 vary widely from country to country. Overqualification rates declined 15 points in Luxembourg and Latvia, and by 25 points in Malta. They also fell in Spain and France, while Greece also saw a drop, even though it had grown in the rest of the population. Since 2006-07, overqualification rates have increased in a number of other southern European countries – such as Cyprus,1, 2 Italy and Portugal – and the United Kingdom, where the non-EU overqualification rate climbed more than 5 percentage points in six years (Figure 14.19). In other EU countries, both third- and host-country overqualification rates have changed little.

Figure 14.18. Overqualification rates by citizenship and gender, 2012-13

Percentages of 15-64 year-old workers with tertiary education who are not in education

StatLink  http://dx.doi.org/10.1787/888933213680

Figure 14.19. Evolution of overqualification rates among 15-64 years old workers with tertiary education who are not in education, by citizenship, 2006-07 and 2012-13

Percentage points

StatLink  http://dx.doi.org/10.1787/888933213694

Notes and sources to be found at the end of the chapter.

Section 14.7. Educational attainment and literacy skills

Background

Indicator

Educational levels are based on ISCED ratings: low (ISCED Levels 0-1-2, with 0-1 denoting a very low level); medium (ISCED Levels 3-4), and high (ISCED 5-6). For further information, see Indicator 3.1. Literacy skills are based on tests in the PIACC 2012 survey of adults in OECD countries. As PIAAC does not specify nationality, literacy data uses country of birth. For further information, see Indicators 7.1 and 7.2.

Coverage

For the level of educational attainment, people between 15 and 64 years old who are not in education. For literacy levels, people between the ages of 16 and 64.

Across the European Union in 2012-13, a large share of third-country nationals was poorly educated – 47%, compared to one in four of their host-country peers and 29% of other EU citizens. Only one in five had a higher education degree, compared to more than one in four host-country nationals and EU citizens. Poorly educated non-EU nationals accounted for 2.8% of the working-age population (15-64 year-olds, excluding students) – i.e. 4.2 million individuals – and the highly educated for 0.5% – i.e. a little over 800 000 individuals.

Greater proportions of third- than host-country nationals hold tertiary degrees in some new EU member states (e.g. Poland and Hungary) and in countries where  there have been large inflows of high-educated labour migrants in the last decade – Ireland, the United Kingdom and Luxembourg (Figure 14.20). All three meet the Europe 2020 education target of 40% of non-EU nationals in the 30-34 year-old age group with higher education degrees, even though no EU state has met the target for its nationals. In southern Europe, whose many of third-country nationals arrived to meet the demand for low-skilled jobs, over half are low-educated. The same is true of longstanding immigrant host countries like France, Belgium and Germany, where many foreigners arrived at a time when education levels in their countries of origin (particularly Turkey and North African countries) were low.

An average of 18% of third-country nationals have completed no more than primary schooling, compared to 4% of host-country nationals (Figure 14.21). Proportions are highest in the longstanding immigrant destinations countries and southern Europe. In Belgium, France, Spain and Germany, the share of third-country citizens who have gone no further than primary school is 20 points higher than among nationals. In the United Kingdom and the new member states, their levels of attainment are higher.

In 2012, third-country immigrants’ average literacy score was 237 points (ISCED Level 2), against 259 among immigrants from other EU states and 275 (Level 3) among native-born (Figure 14.A1.2). They scored no higher than Level 1 (between 176 and 226 points) in Belgium, Italy and Sweden. As a rule, literacy gaps with the native-born were especially wide in northern Europe, Benelux and Austria. Cyprus1, 2 and Ireland, however, registered similar scores for third- and host-country nationals.

The language spoken and/or learnt in childhood goes a long way towards accounting for immigrants’ literacy skills. The further removed it is from that (or those) of the host country, the lower literacy scores tend to be. Generally speaking, literacy gaps between third-country immigrants and the native-born widen significantly when immigrants have not learned host-country languages as children. In Spain and Ireland, the gap is twice as wide among immigrants whose native language is not respectively Spanish or English (Figure 14.A1.3). In Spain, France, Denmark, Austria, Belgium and Italy, third-country immigrants who speak a foreign tongue on average score only Level 1 in literacy skills.

Figure 14.20. Shares of 15-64 year-olds with low and high levels of educational attainment by citizenship, not including those still in education, 2012-13

StatLink  http://dx.doi.org/10.1787/888933213718

Figure 14.21. Shares of 25-54 year-olds with very low and low levels of educational attainment by citizenship, not including those still in education, 2012-13

StatLink  http://dx.doi.org/10.1787/888933213725

Notes and sources are to be found at the end of the chapter.

Section 14.8. Household income distribution

Background

Indicator

Equivalised annual disposable household income is income per capita adjusted according to the square root of the number of household members. Income is expressed in euros (EUR) at the purchasing power parity (PPP) exchange rate. To estimate the effect of social transfers on income differentials between third- and host-country nationals, incomes before and after transfers are compared. Transfers include unemployment, sickness, disability, school-related, family, and housing benefits. (Old-age and war veteran pensions are not included.) For further information, see Indicator 8.1.

Coverage

An individual of over 15 years of age living in an ordinary residence. The equivalised annual income is attributed to each individual.

Across the European Union, the median income of people living in a household of third-country nationals in 2012 was a little less than EUR 13 000, compared with EUR 15 500 for EU nationals, and around EUR 17 000 in a household of host-country nationals. At one end of the scale lies Greece with a non-EU median income of EUR 7 000 and, at the other end, Austria and the United Kingdom at EUR 17 000. The picture is more varied among home-country nationals, with median incomes ranging from EUR 11 000 to EUR 30 500. The incomes of non-EU households are almost always considerably lower than among host-country nationals. They are almost half in northern European countries and in Belgium, France and Luxembourg (Figure 14.22), while the gap is narrower in the Czech Republic, Ireland and the United Kingdom. However, the differences between member countries are greater than between foreigners and nationals in the same country.

The income of the richest 10% of third-country nationals is five times greater than that of the poorest 10% (Figure 14.23). The ratio is 4/1 among host-country nationals and EU foreigners. However, in Italy, Belgium, Portugal, Ireland, Finland and Luxembourg, the gaps between the richest and the poorest are wider among host-country nationals than third-country nationals. Income inequalities are on average less pronounced among EU than non-EU migrants, except in Austria, France, Benelux and Scandinavia. Income distribution among EU foreigners is particularly inequitable in Austria, where the richest 10%, chiefly German nationals, boast an income that is 14 times that of the poorest, who hail mainly from new member states.

Except in Ireland, third-country nationals are always overrepresented in the lowest decile – one in four on average. Around one-half are in the lowest decile in Belgium (Table 14.1), while France, Luxembourg and much of northern Europe also paint a worrying picture. By the same token, third-country nationals are particularly under-represented in the highest income decile, the sole exception being the United Kingdom. In some countries – like Denmark, France and Italy – less than one third-country national in 300 boasts an income that can be classified in the top decile.

A portion of available income comes from social transfers. Although third-country nationals always have lower post-transfer incomes than host-country nationals (except in the Czech Republic), transfers do help ease income inequality between third- and host-country nationals in three-quarters of countries – particularly in Finland, Denmark, Austria and France, where social transfers close the income gap by one-third (Figure 14.A1.4). However, non-EU foreign residents benefit less from social transfers than host-country nationals in Greece, Cyprus1, 2 and the United Kingdom.

Figure 14.22. Equivalised annual disposable incomes by citizenship, 2012

EUR in 2011 prices

StatLink  http://dx.doi.org/10.1787/888933213738

Figure 14.23. Income distribution by citizenship, 2012

StatLink  http://dx.doi.org/10.1787/888933213745

Table 14.1. Adults aged 15 + living in a third-country national household, 2012
Percentages
| % in the lowest decile | % in the highest decile
Austria | 24.6 | 1.5
Belgium | 48.6 | 2.5
Cyprus1, 2 | 37.6 | 5.5
Czech Republic | 17.5 | 9.2
Denmark | 39.5 | 0.0
Finland | 39.1 | 1.3
France | 41.0 | 0.3
Germany | 22.8 | 5.5
Greece | 27.1 | 1.5
Ireland | 7.1 | 1.0
Italy | 17.4 | 0.3
Luxembourg | 38.7 | 0.7
Portugal | 22.3 | 1.6
Spain | 27.0 | 2.1
Sweden | 33.4 | 3.4
United Kingdom | 20.4 | 12.6
EU total (24) | 23.9 | 4.0
Norway | 36.9 | 2.1
Switzerland | 17.2 | 3.0
StatLink  http://dx.doi.org/10.1787/888933214330

Notes and sources to be found at the end of the chapter.

Section 14.9. Poverty

Background

Indicator

The relative poverty rate, in line with the Eurostat definition applied here, is the proportion of individuals living below the poverty line – in other words, with an income that is less than 60% of a country’s equivalised median disposable income. The relative poverty rate indicator thus helps to assess the scale of income inequality between different groups within a country, although it cannot be used to identify situations of absolute poverty. The concept of “poverty” as a function of a country’s median revenue does not denote the same situation across member states. In Greece and Portugal, for example, the highest income decile among third-country nationals is lower than the median income observed in one-third of EU countries. For further information, see Indicator 8.2.

Coverage

All people over 15 years old living in an ordinary residence. Each individual is assigned the household’s equivalised annual income.

Across the European Union in 2012, an average of 39% of people in third-country national households were living in relative poverty. The rate was over twice that among host-country nationals (17%) and was also considerably higher than for EU foreigners (28%). At less than 20%, relative poverty rates among third-country nationals (and EU foreigners) were at their lowest in the Czech Republic and Ireland. Relative poverty is also less pronounced in the United Kingdom, Germany and Austria, even though it affected one-third of non-EU nationals.

Poverty affected both EU and non-EU foreign residents in all countries more widely than host-country nationals. Still, third-country nationals were worst hit. They were more than four times more likely to be living in relative poverty than host-country nationals in northern Europe, France and Belgium (Table 14.2), and as much as six times in Luxembourg.

With the exception of Germany, relative poverty rates among third-country nationals are even higher in countries where their employment rates are low and they work in the worst paid jobs – as in long-standing immigrant destinations (France, Belgium and Luxembourg) and in the Scandinavian countries, homes to large numbers of refugees who face more difficulties in the labour market. Poverty spares relatively more third-country nationals in the United Kingdom, which has recently experienced significant inflows of highly qualified immigrants.

In most countries, the relative poverty rates of EU nationals lie somewhere between host- and third-country nationals. However, in countries like Austria and Italy where a sizeable share of foreign EU residents originates from new member states, the relative poverty rates of foreigners living in an EU household are higher –roughly 40% – than in third-country households.

Table 14.2. Relative poverty rates by citizenship of household members aged 15 years old or more, 2012
Percentages
| Individuals living in a third-country national household | Individuals living in an EU national household | Individuals living in a national household | Ratio third-country national / national household
Austria | 30.4 | 41.6 | 14.5 | 2.1
Belgium | 58.1 | 29.3 | 14.8 | 3.9
Cyprus1, 2 | 48.4 | 34.5 | 15.6 | 3.1
Czech Republic | 17.5 | 11.5 | 10.6 | 1.6
Denmark | 54.3 | 28.0 | 14.3 | 3.8
Finland | 56.7 | 27.2 | 15.1 | 3.8
France | 50.8 | 25.0 | 13.0 | 3.9
Germany | 33.8 | 28.0 | 16.8 | 2.0
Greece | 51.1 | 52.1 | 20.5 | 2.5
Ireland | 20.8 | 18.0 | 16.4 | 1.3
Italy | 34.5 | 37.6 | 19.0 | 1.8
Luxembourg | 52.2 | 23.4 | 8.4 | 6.2
Portugal | 40.1 | - | 17.5 | 2.3
Spain | 46.8 | 33.3 | 19.5 | 2.4
Sweden | 46.6 | 32.4 | 16.0 | 2.9
United Kingdom | 28.8 | 20.0 | 16.9 | 1.7
EU total (24) | 38.8 | 27.8 | 16.8 | 2.3
Norway | 47.1 | 22.5 | 11.6 | 4.1
Switzerland | 29.6 | 19.0 | 15.9 | 1.9
StatLink  http://dx.doi.org/10.1787/888933214344

Notes and sources are to be found at the end of the chapter.

Section 14.10. Housing tenure

Background

Indicator

There are three main types of housing tenure: owner occupancy, tenancy, and free occupancy. In most EU member states, tenants pay rents at market rates or occupy low-rent accommodation (reduced rates due to public social housing, employer social housing, or rents set by the law). For further information, see Indicator 9.1.

Coverage

Households living in an ordinary residence where at least one person who is responsible for the household is aged over 15 years old.

Across the European Union in 2012, third-country national households were three times less likely to be owner-occupiers than their host-country peers. Owner occupancy was the form of tenure in only one in four third-country households, against one in three among foreign EU households, and seven out of ten for host-country nationals. Less than one-fifth of third-country households were owner occupiers in France, Austria and Greece, and less than one-tenth in Belgium. The share is a little higher in the United Kingdom and Luxembourg, but nevertheless lower than 40%.

Third-country nationals are everywhere less likely to be owner occupiers than their home-country peers, with a gap that is consistently wider than 25 percentage points (Figure 14.24). The disparity is even greater in recent immigration destination countries, partly because newcomers have not had the time to decide whether to become home owners and/or request a loan to that end. In Belgium, non-EU home owners are 12 times less likely to own their homes than host-country nationals.

In most of the European Union, foreign EU residents are a little more likely than third-country nationals to own their homes, but much less so than host-country nationals. Exceptions are Sweden and France, where European immigration is longstanding and incomers have been settled for long enough to purchase property. In some countries – e.g. the United Kingdom, Ireland and Italy – new member state nationals who arrived after 2004 make up the bulk of the foreign EU population. As a rule, they have low incomes and exhibit rates of property ownership comparable to or lower than those of third-country nationals.

By adjusting third-country nationals’ outcomes, it is possible to hypothesise what their rates of home ownership would be if their ages and incomes were the same as those of host-country nationals. It emerges that, although they would be higher, they would still be considerably lower. Access to home ownership is in fact a more complex business for foreigners, as they have greater difficulty opening bank accounts or securing loans, particularly if they are newly arrived immigrants who have not yet saved enough. Other non-observable factors also strongly shape home ownership among non-EU citizens. They might, for example, prefer to invest in the home country or live in areas where their compatriot community is concentrated but where there is little property for sale.

Third-country nationals are mostly tenants. However, even though their often low incomes entitle them to apply for low-rent housing, only 16% live in such accommodation, compared to 25% of host-country nationals. Such under-representation is particularly pronounced in some recent immigration destinations like Portugal and Ireland, where the shares of non-EU nationals living in low-rent accommodation are 35 percentage points lower than among host-country nationals (Figure 14.25). Nevertheless, in one-third of countries – e.g. France, Sweden and Greece – third-country nationals enjoy equal access to low-rent tenancies.

Figure 14.24. Rates of home ownership by citizenship of households, 2012

Percentage of all households

StatLink  http://dx.doi.org/10.1787/888933213752

Figure 14.25. Share of third-country households renting at a reduced rate among renters, 2012

Differences in percentage points with national households

StatLink  http://dx.doi.org/10.1787/888933213765

Notes and sources are to be found at the end of the chapter.

Section 14.11. Self-reported health status

Background

Indicator

This section looks at people’s self-reported health status, i.e. how they perceive their state overall of physiological and psychological health. The section also considers a compound indicator that combines perceptions of overall good health and the absence of chronic illness or health-related limitation (usually a disability). For further information, see Indicator 10.1.

Coverage

People aged over 15.

In 2012, an average of seven foreign nationals out of ten (whether from the European Union or a third country) responded positively to all three dimensions of self-reported health status – perception of overall good health, no chronic illnesses, and no health-related limitations. With over six out of ten, proportions among host-country nationals were similar. Almost four third-country nationals out of five in southern European countries, the Czech Republic, Ireland and the United Kingdom reported good health (Figure 14.26). On the other hand, fewer than six in every ten in Lithuania, Austria and France reported likewise.

In all EU countries, domestic nationals were less likely to report good health in all dimensions than either other EU or third-country citizens. Many foreign nationals have recently immigrated, so originate from a healthier subset of the (pre-migration) population – the so called “healthy migrant effect”. An additional factor may be age, with foreign citizens being younger and therefore generally healthier than their national counterparts.

Indeed, adjusting for age shows that non-EU foreigners are less or equally likely to report poor health than domestic nationals in most countries. The only country where fewer report having good health than domestic nationals is Austria. The healthy migrant effect among non-EU nationals again comes into play in southern European countries, where immigration is recent.

Similar results emerge in the self-reporting of good versus poor health (Figure 14.27). Just under four in five foreign residents (whether EU or third-country nationals) reported good health in 2012, compared to just over two out of three host-country citizens. After adjustment, domestic nationals in all EU countries still appear less or equally likely to report being in good health than third-country nationals, except in Austria, France, Luxembourg and Belgium. In the southern European countries, a greater proportion of third-country nationals report good health than nationals.

In the European Union, a greater proportion of third-country nationals report to be of better health than do EU nationals, with the exceptions of Austria and Portugal. A further exception is the United Kingdom, possibly because free labour mobility attracts disproportionally more healthy EU citizens than third-country nationals.

Differences in the self-reported health status of third- and host-country nationals may also be attributable to a number of factors not included in the analysis – e.g. gender, lifestyle, country of citizenship or other social and economic circumstances.

Figure 14.26. Adults who report good health status, no health-related limitations, and no chronic health conditions, by citizenship, 2012

Percentages

StatLink  http://dx.doi.org/10.1787/888933213772

Figure 14.27. Adults who report they are in good health, by citizenship, 2012

Percentages

StatLink  http://dx.doi.org/10.1787/888933213780

Notes and sources are to be found at the end of the chapter.

Section 14.12. Long-term residents

Background

Indicator

A long-term resident is a third-country national who has been granted long-term residence status in accordance with Directive 2003/109/EC of 25 November 2003. The status may be granted to all non-EU citizens if they have resided legally and continuously for five years in an EU member state, have health insurance coverage, and enjoy sufficient financial resources not to have to rely on social assistance. Some countries may also have additional requirements, such as proficiency in the host country language. All long-term residents enjoy equal rights to reside as EU nationals, particularly as regards the right to reside in an EU country other than the one where they were awarded long-term residence. This indicator relates to the share of long-term residents in the population of third-country nationals who live legally in the European Union. All member countries may deliver permanent residence permits that confer more advantageous conditions than the directive mandates but that are not considered to be long-term residence status because they do not allow residents to live in other EU countries.

Coverage

All third-country nationals with a valid residence permit.

In 2013, an average of one-third of legal third-country nationals enjoyed long-term residence status. Although that EU-wide share had quadrupled in five years, it varied greatly from country to country. In Austria, the Czech Republic, Slovenia, Spain, Italy and the Baltic countries , more than half of non-EU foreign nationals had long-term residence status, while less than 1% did in France, Germany, Greece and Sweden (Table 14.3). It depends, in fact, on the date that countries incorporated the directive into their legislation, on further requirement conditions in some countries, and on whether permanent residence permits that are more advantageous than long-term residence status were in place prior to the directive. In countries that grant that kind of residence permit, it is not in third-country nationals’ interest to apply for long-term residence status unless they wish to settle in another member state.

Table 14.3. Proportion of third-country nationals with long-term residence status at the end of the year, 2008-12
Percentage of all valid residence permits
| 2008 | 2009 | 2010 | 2011 | 2012 | 2013
Austria | 36.1 | 37.4 | 40.0 | 67.4 | 66.2 | 61.9
Belgium | 0.2 | 0.5 | 38.8 | 33.2 | 30.0 | 28.2
Bulgaria | 1.6 | 1.0 | 1.0 | 1.2 | 1.3 | 0.8
Cyprus1, 2 | 0.0 | 0.1 | 0.3 | 0.3 | .. | 2.6
Czech Republic | 15.7 | 16.1 | .. | 19.5 | 57.3 | 61.8
Denmark | .. | .. | .. | 0.4 | 1.3 | 2.2
Estonia | 88.4 | 88.0 | 88.1 | 88.7 | 88.3 | 88.4
Finland | 0.0 | 0.0 | 0.0 | 0.1 | 0.1 | 0.4
France | 0.0 | 0.1 | 0.3 | 0.5 | 0.7 | 0.9
Germany | 0.0 | 0.1 | 0.1 | 0.1 | 0.2 | 0.2
Greece | 0.0 | 0.0 | 0.1 | 0.1 | 0.2 | ..
Hungary | 3.3 | 3.8 | 45.8 | 45.5 | 36.8 | 33.0
Ireland | 3.6 | 2.9 | 6.3 | 6.0 | 4.8 | 4.5
Italy | 23.6 | 28.1 | 34.7 | 52.0 | 54.8 | 56.4
Latvia | 0.0 | 0.1 | 0.1 | 97.4 | 96.5 | 95.1
Lithuania | 62.5 | 68.6 | 69.8 | 65.1 | 63.2 | 58.6
Luxembourg | .. | .. | 8.1 | 16.3 | 23.3 | 29.8
Malta | 2.2 | 3.6 | 2.4 | 2.6 | 2.7 | 6.8
Netherlands | 3.2 | 4.5 | 25.4 | 25.6 | 32.7 | 19.7
Poland | 4.0 | 5.2 | 37.0 | 23.4 | 21.5 | 18.3
Portugal | 0.4 | 0.6 | 0.8 | 0.8 | 0.9 | 1.0
Romania | 14.6 | 15.7 | 16.7 | 17.1 | 19.0 | 19.8
Slovak Republic | 5.3 | 6.3 | 18.7 | 48.7 | 41.8 | 43.8
Slovenia | 24.0 | 29.0 | 44.2 | 47.4 | 50.2 | 54.3
Spain | 0.3 | 0.7 | 66.8 | 70.8 | 66.2 | 66.8
Sweden | 0.1 | 0.1 | 0.2 | 0.2 | 0.0 | 0.0
EU total (28) | 7.7 | 9.2 | 24.4 | 31.8 | 32.1 | 31.7
Switzerland | .. | .. | .. | .. | 65.4 | ..
StatLink  http://dx.doi.org/10.1787/888933214358

Notes and sources are to be found at the end of the chapter.

Section 14.13. Voter participation

Background

Indicator

Self-reported participation in elections is measured here through surveys which ask respondents if they voted in the most recent parliamentary elections in their host country. For further information, see Indicator 11.2.

Coverage

Any person aged 18 years old and above who is entitled to vote in national elections. No country confers the right to vote in such elections on foreigners apart from the United Kingdom and Portugal, and even then only for certain nationalities. This indicator therefore applies to people born in a third country who have taken the nationality of the host country.

Only seven out of ten nationals born in a third country took part in the latest national elections between 2002 and 2012 (Figure 14.28), compared to eight out of ten native-born nationals. In fact, host-country nationals who were born in a third or other EU country tend generally to vote less than native-born host-country citizens. Voter turnout among citizens born outside the European Union is 10 percentage points lower than among the native-born in southern Europe, the Nordic countries, Ireland, Germany and Austria. Turnout between the two groups is broadly similar in Belgium and France, by contrast.

Turnout among third-country-born host-country nationals is higher than among non-migrant nationals in a number of countries that have experienced border changes, e.g. Lithuania, Croatia, Poland. In the United Kingdom, people born outside the European Union vote in elections in the same proportions as the native-born. Commonwealth citizens may have something to do with such turnout. As they are allowed to vote in national elections, they might seek to familiarise themselves with the voting system on arriving in the United Kingdom, which might account for their high turnout.

Nationals born in another EU country generally turn out to vote in higher proportions than the third-country-born. They also participate in higher proportions than the native-born nationals in France and in countries that have been through border changes. By contrast, Croatia, the Netherlands and the United Kingdom are the member countries where the highest proportions of non-EU-born people vote in comparison to nationals born in other EU countries.

Figure 14.28. Self-reported turnout of national population in the most recent elections by country of birth, 2002-12

Percentage of national population aged 18 years old or more

StatLink  http://dx.doi.org/10.1787/888933213797

Notes and sources are to be found at the end of the chapter.

Section 14.14. Acquisition of nationality

Background

Indicator

This indicator measures the rate of acquisition of nationality, considered as the proportion of immigrants who have resided for at least ten years in a host country and have become citizens. For further information, see Indicator 11.1.

Coverage

Immigrants (i.e. born abroad) aged 15 years old or more who have lived in a host country for at least ten years. Beyond that time, most immigrants are entitled to apply for naturalisation. Immigrants who automatically acquire the nationality of a host country at birth (e.g. the children of expatriates) are included because they cannot be distinguished.

In 2012-13, an average of 62% of immigrants born outside the European Union but who had lived in the host country for at least 10 years (long-settled immigrants) had taken the nationality of this host country. By contrast, only 48% of EU immigrants had done so (Figure 14.29). Freedom of movement within the European Union may well have diminished the incentive to seek the citizenship of the host country.

Nine out of ten long-settled immigrants born outside the European Union are nationals in countries that, after they were born, broke away from or experienced border changes with political entities that are now mostly third countries. Examples are Croats born in other parts of the former Yugoslavia and Lithuanians born in other parts of the former Soviet Union. On independence, they were often given the choice between taking up citizenship in the host country or keeping the nationality of their place of birth. Three in four long-settled immigrants have also acquired citizenship in countries where the process is easier, e.g. Sweden, the Netherlands, Portugal and the United Kingdom. By contrast, one-third of settled immigrants born in a non-EU country have kept their nationality at birth because the naturalisation process is more difficult or dual nationality mostly not allowed in their EU host countries – e.g. the Baltic states (save Lithuania), southern Europe and Luxembourg.

EU immigrants generally acquire host country citizenship less often than do their third-country-born peers, as in Benelux, Denmark and Sweden, for example. By contrast, higher proportions of EU-born than third-country-born immigrants have taken host-country nationality in some central European countries that have a shared history with neighbouring EU member states – e.g. the Czech Republic, the Slovak Republic and Slovenia. Higher rates of EU-immigrants who have host-country nationality are also found in some southern European countries like Italy and Greece, as well as in Finland and Austria.

With an average naturalisation rate of 73% across the European Union, a higher proportion of third-country-born immigrants with higher education degrees have host-country nationality than their less well educated peers, only 52% of whom have become citizens (Figure 14.30).

Immigrants with low or no qualifications are more likely to run into problems of language or knowledge of the host country’s culture, which are often prerequisites for obtaining citizenship. Disparities between low-educated immigrants and their highly educated counterparts can be as wide as 20 percentage points in countries where immigration is recent (e.g. Greece, Italy and Spain) and chiefly from low-income countries. The gap is wide in France, too. It has a relatively low-educated immigrant population, made up largely of people from North Africa who have been in the country for over 30 years. Many have dual nationality and may choose not to mention their French citizenship when questioned, which artificially reduces the naturalisation rate.

Figure 14.29. Share of nationals aged 15 years old or more by country of birth, 2012-13

Percentages of the foreign-born population with at least ten years of residence

StatLink  http://dx.doi.org/10.1787/888933213805

Figure 14.30. Share of nationals among third-country-born immigrants aged 15 years old or more by level of education, 2012-13

Percentages of the foreign-born population with at least ten years of residence

StatLink  http://dx.doi.org/10.1787/888933213827

Notes and sources are to be found at the end of the chapter.

Section 14.15. Perceived discrimination

Background

Indicator

“Ethnic” discrimination is generally thought of as unfairly treating someone differently because of their ethnicity, origin, or nationality. Here it measures the proportions of third-country nationals who claim to belong to a group that suffers from discrimination on the grounds of ethnicity, nationality, or race. For further information, see Indicator 12.1.

Coverage

Individuals of foreign nationality aged between 15 and 64 years old.

Across the European Union in 2002-12, 23% of third-country immigrants felt they belonged to a group that was discriminated against on the grounds of ethnicity, nationality, or race (Figure 14.31). With only 9% reporting such discrimination, however, EU-national foreign residents felt it much less acutely.

The sentiment of discrimination is particularly keen in Austria and Greece, where two in five non-EU nationals report experiencing it. It is generally more widespread in southern Europe (apart from Spain), the Netherlands and France. By contrast, less than one person in five reports being discriminated against in the Nordic countries, Luxembourg and the United Kingdom. Although the level of EU nationals claiming discrimination is low across the European Union, more than one in four feels discriminated against in Greece, and over one in ten in Austria, Ireland and Spain.

Across the European Union, fewer third-country nationals feel discriminated against on ethnic grounds than in the recent past. Perceived discrimination for reasons of ethnicity fell 4 percentage points between 2002-06 and 2008-12, from 25% to 21% between 2008 and 2012 (Figure 14.A1.5). All groups of non-EU foreigners experienced a decline, save those who were unemployed.

Over the period 2008-12, third-country males seemed more sensitive than females to discrimination. The figures were 22% among men and 20% of women. The under-55s – whether with a nationality from inside or outside the European Union – complained of it more often than their elder peers, although it is impossible to determine if the higher rate can be attributed to age, duration of residence, or generation.

What is clear, however, is that the lower a persons’ level of education, the keener their sense of discrimination – 23% of low-educated non-EU nationals believe they belong to a group that is singled out, while among the highly educated the rate is 16% (Figure 14.32). At 27%, more unemployed third-country nationals say they are come in for discrimination than those who are in work (23%) or economically inactive (15%).

Between 2002 and 2006, EU and non-EU foreign nationals felt discrimination was worse when their native tongue was different from the host country’s language. In 2008-2012, third-country nationals no longer share that sentiment, however and – unlike their foreign EU peers – there is no difference in perceived discrimination along the lines of native language. On the downside, however, being born in the host country is not enough to spare third-country nationals from the sentiment of discrimination. They feel it as acutely as their foreign-born co-nationals. Like them, they still have a sense of belonging to an ethnic group and perceive it as the target of discriminatory behaviour.

Figure 14.31. Share of third-country and EU nationals aged 15-64 years old who state that they belong to a group that is discriminated against on the grounds of ethnicity, nationality or race, 2002-12

StatLink  http://dx.doi.org/10.1787/888933213836

Figure 14.32. Share of third-country and EU nationals aged 15-64 years old across all EU countries who state that they belong to a group that is discriminated against based on ethnicity, nationality or race, by several characteristics, 2008-12

StatLink  http://dx.doi.org/10.1787/888933213845

Notes and sources are to be found at the end of the chapter.

Data limitations

See “Data limitations” in Chapters 5 to 12.

Long-term residence

The long-term resident indicator should be handled with care as it does not always reflect to what extent third-country nationals enjoy permanent residence. Some host countries may grant non-EU nationals residence status that affords them higher degrees of protection, which means that the long-term residence indicator does not encompass all forms of permanent residence. In countries that grant such protective statuses, the low proportion of long-term residents in the immigrant population does not mean, therefore, that only a few foreigners enjoy the same rights as EU citizens. Comparison between countries is further complicated by the fact that some countries require to meet additional criteria before granting them long-term residence status.

Notes, sources, and further reading

Notes to figures and tables

Averages factor in rates that cannot be published individually because the data samples are too small.

Figure 14.1: For Portugal read 2003 instead of 2005.

Figure 14.20: “TC” refers to third-country nationals and “NA” nationals.

Figures 14.26 and 14.27: Adjusted rates refer to the hypothetical situation if third-country nationals had the same age distribution as nationals.

Indicators 14.8,  14.9,  14.10,  14.11: German data are originated from another data source and are not, therefore, comparable with the data considered in Chapters 8,  9 and 10.

Indicator 14.15: Not counting no answers and “don’t knows”.

The greyed bars denote differences that are not statistically different from zero with a probability of 0.05.

Notes to Cyprus1, 2

1. Note by Turkey:

The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Turkey recognizes the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of United Nations, Turkey shall preserve its position concerning the “Cyprus issue”.

2. Note by all the European Union Member States of the OECD and the European Union:

The Republic of Cyprus is recognized by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus.”

Sources

European Union Labour Force Surveys (EU-LFS) 2006-07 and 2012-13.

Indicators 14.1 and 14.12: Eurostat Database on International Migration and Asylum 2005-13.

Indicators 14.2,  14.3,  14.4,  14.5,  14.6,  14.7 and 14.14: European Union Labour Force Surveys (EU-LFS) 2006-07 and 2012-13.

Indicators 14.8,  14.9,  14.10,  14.11: European Union Statistics on Income and Living Conditions (EU-SILC) 2012. German Socio Economic Panel (G-SOEP 2012 95% sample).

Indicators 14.13,  14.15: European Social Survey (ESS) 2002-12.

Further reading

Eurostat (2014), “Non-EU Citizens Twice as Likely to Be at Risk of Poverty or Social Exclusion as Nationals in 2013”, Eurostat News Release, No. 177/2014, European Commission, Luxembourg.

Eurostat (2011), “Migrants in Europe: A Statistical Portrait of the First and Second Generation”, Statistical Books, European Commission, Luxembourg.

Annex 14.A1.

Additional tables and figures

Figure 14.A1.1. Third-country and EU nationals, 2013

Percentage of the total population

Source: Eurostat Database on International Migration and Asylum (2013).

StatLink  http://dx.doi.org/10.1787/888933213918

Figure 14.A1.2. Average literacy scores by place of birth among 16-64 year-olds, 2012

1, 2: See “Notes, sources, and further reading” section.

Source: OECD Programme for the International Assessment of Adult Competencies (PIAAC) 2012.

StatLink  http://dx.doi.org/10.1787/888933213929

Figure 14.A1.3. Adjusted mean literacy score by country of birth and native language, 16-64 years old, 2012

Differences in percentage points with the native-born

Note: Differences are adjusted for age, gender and educational attainment.

1, 2: See “Notes, sources, and further reading” section.

Source: OECD Programme for the International Assessment of Adult Competencies (PIAAC) 2012.

StatLink  http://dx.doi.org/10.1787/888933213939

Figure 14.A1.4. Differences in equivalised disposable median incomes between third-country and national households before and after social transfers (other than old-age and survivors transfers), 2012

Gap in euros between third-country nationals and nationals

Note: Old-age and survivors tranfers are included in all figures.

1, 2: See “Notes, sources, and further reading” section.

Source: European Union Survey on Income and Living Conditions (EU-SILC) 2012. German Socio Economic Panel (G-SOEP 2012 95% sample).

StatLink  http://dx.doi.org/10.1787/888933213943

Figure 14.A1.5. Share of third country nationals aged 15-64 years old across all 28 EU countries who state they belong to a group that is discriminated against based on ethnicity, nationality or race, by several characteristics, 2002-06 and 2008-12

Source: European Social Surveys (ESS) 2002-12.

StatLink  http://dx.doi.org/10.1787/888933213952

Glossary

Active: Active, or economically active, people are those who are in employment or seeking employment.

Adjusted rates: Adjusted rates show what outcomes would be for immigrants and immigrant offspring if their socio-demographic attributes were the same as those of the reference population. Adjustments are made using the Oaxaca-Blinder decomposition method and selected attributes are chosen depending on the topic covered.

Employed person: In this publication, the definition drawn up by the International Labour Organization (ILO) is used. Employed persons are all those who worked at least one hour in the course of the reference week and those who had a job but were absent from work. One exception is the Indicator 8.3 where an employed person must have been in employment for at least seven months of the year.

EU average: When it is not possible to calculate the EU total, the unweighted EU average is used. It considers each EU country as a single entity with equal weight. The “EU average” is thus the arithmetical average derived from the statistics of the countries whose data are available. The number of those whose data are used in calculations is shown in brackets.

EU total: The EU total is the summary statistic generally used for EU countries. It takes differences in population size into account, i.e. as if the EU were one single country. The number of those whose data are used in calculations is shown in brackets.

Foreign language: A language which is not one of the official languages of the country of residence.

High-income countries: The World Bank defines high-income countries as those with a gross per capita national income of EUR 12 746 or more. For further information, see http://data.worldbank.org/about/country-and-lending-groups#High_income.

Highly educated person: People falling into ISCED groups 5-6 are those having tertiary education degrees. They have completed the first stage of tertiary education at least.

Household immigration status: It is determined by heads of household’s country of birth. An immigrant household is one in which all maintainers (one or two people) were born abroad. A native-born household is one in which at least one native-born person is a maintainer. Among native-born households, a mixed household is one in which one maintainer was born abroad.

Household: A person who resides alone or two or more people who usually reside together and share facilities (e.g. eating and cooking spaces, bathroom, toilet, and living area).

Immigrant household: A household in which all maintainers (one or two persons) were born abroad.

Immigrant: Person born abroad.

Immigrant who arrived as adults: Immigrant who arrived at the age of 15 or after.

Immigrant who arrived as children: Immigrant who arrived before the age of 15.

Inactive person: A person without work who is not unemployed.

International Standard Classification of Education (ISCED): A classification developed by the UNESCO to facilitate comparisons of education statistics and indicators across countries on the basis of uniform and internationally agreed definitions, www.uis.unesco.org/Education/Pages/international-standard-classification-of-education.aspx.

International Standard Classification of Occupations (ISCO-88): ISCO is a tool developed by the International Labour Organization for organising jobs into a clearly defined set of groups according to the tasks and duties undertaken in the job. It is intended for use in statistical applications and lends itself to international comparisons, www.ilo.org/public/english/bureau/stat/isco/isco88/.

Labour force: People available for work and who are either employed or unemployed.

Low-educated person: People falling into ISCED groups 0-2 are described as having no or low education. They have no more than a lower-secondary level of education.

Lower-income countries: All countries which are not classified as high-income countries as defined by the World Bank (see “High-income countries”).

Maintainer: See reference person.

Migrant background: A person with a migrant background is either foreign-born or native-born with at least one foreign-born parent, unless stated otherwise.

Nationality of a household: A third-country-national household is one in which all maintainers have the nationality of a non-EU country. An EU-national household is one in which all maintainers have the nationality of an EU country (other than the host-country nationality), or one in which one maintainer is of an EU nationality and the other is a third-country national. A national household is a household in which at least one maintainer is a host-country national.

Native-born children of immigrants: Minors born in the current country of residence to two foreign-born parents and who still live in the same household as their parent(s).

Native-born children of native-born parents: Minors born in the current country of residence to two native-born parents and who still live in the same household as their parent(s).

Native-born children with mixed background: Minors born in the current country of residence to one native-born and one foreign-born parent and who still live in the same household as their parent(s).

Native-born household: A household in which at least one maintainer is born in the current country of residence. Native-born households include mixed households, ones in which one of the responsible persons was born abroad.

Native-born offspring of immigrants: Persons born in the current country of residence to two foreign-born parents.

Native-born offspring of native-born: Persons born in the current country of residence to two native-born parents.

Native-born offspring with mixed background: Persons born in the current country of residence to one native-born and one foreign-born parent.

New member states (NMS): Those countries entered the European Union in 2004 or thereafter. NMSs are Bulgaria, Croatia, Cyprus,1, 2 the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Romania, the Slovak Republic, and Slovenia.

OECD average: When it is not possible to calculate the OECD total, the unweighted OECD average is calculated instead. It takes each OECD country as a single entity with equal weight. The “OECD average” is thus the arithmetical mean derived from the statistics of the countries whose data are available. The number of countries that are factored into calculation is shown in brackets.

OECD total: The OECD total is the summary statistic generally used for OECD countries. It takes differences in population size into account. The number of those whose data are factored into calculations is shown in brackets.

Offspring of immigrants: See n“ative-born offspring of immigrants”.

Ordinary residence: An ordinary residence or dwelling in this publication is a place of residence that is not a hostel, group home, retirement home, military barracks, encampment, hospital, or prison, etc.

PISA index of Economic, Social and Cultural Status (ESCS): The social and economic environment of a student is a vague concept that is difficult to measure. The OECD Programme for International Student Assessment (PISA) assesses it through the ESCS index. The variables that it factors in are the education level and occupation of the parents, an estimate of the family’s monetary wealth, and the number and nature of the cultural assets available in the household. Students are considered socially privileged if they belong to the 25% of students with the highest ESCS index. They are considered socially underprivileged if they are among the 25% of students with the lowest ESCS index.

Recent immigrants: Immigrants who entered the host country within the last five years unless otherwise specified. For some indicators, however, a period of ten years is considered.

reference person: Defined differently depending on the data source. The EU Survey of Income and Living Conditions (EU-SILC) identifies one or two persons “responsible for the household”. It considers that they are the person(s) owning or renting the accommodation or the person(s) to whom the accommodation is provided if it is provided free. If more than two persons share the responsibility, only the oldest two are registered.

Israeli Labour Force Survey: The reference person is the one who fills in the household questionnaire. His/her partner (if any) is the second reference person.

US Current Population Survey: The term “householder” refers to the person (or one of the persons) in whose name the housing unit is owned or rented (maintained) or, if there is no such person, any adult member, excluding roomers, boarders, or paid employees. If the house is owned or rented jointly by a married couple, the householder may be either the husband or the wife.

The concept of head of household or reference person is not used in Australia, New Zealand or Canada. Instead, the person with the highest wage and his/her partner (if any) are identified as the reference person in this publication.

Resilient student: A student that the PISA ESCS index considers being from a socially underprivileged family (i. e., from bottom quartile of the ESCS) but who performs in the top quartile of all students in the country where they are schooled.

Settled – or long-settled – immigrants: Immigrants who have lived in the host country for at least 10 years. Also referred to as “long-term immigrants”.

Third countries: All countries that are not members of the European Union in 2015. The EU comprises Austria, Belgium, Bulgaria, Croatia, Cyprus,1, 2 the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, the Netherlands, Poland, Portugal, the Slovak Republic, Spain, Romania, Slovenia, Sweden and the United Kingdom.

Third-country national: A third-country national, a notion be understood in the context of the European Union, is a non-EU national who resides legally in the European Union.

Unemployed person: A person without work who has been actively seeking work for the last four weeks and would be available for work within two weeks.

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