A study of the employment and earnings outcomes of secondgeneration migrants

Das, Utsoree; Dellaferrera, Giulia; Ananian, Sevane Working Paper A study of the employment and earnings outcomes of secondgeneration migrants ILO Working Paper, No. 141 Provided in Cooperation with: International Labour Organization (ILO), Geneva Suggested Citation: Das, Utsoree; Dellaferrera, Giulia; Ananian, Sevane (2025) : A study of the employment and earnings outcomes of secondgeneration migrants, ILO Working Paper, No. 141, ISBN 978-92-2-042172-7, International Labour Organization (ILO), Geneva, https://doi.org/10.54394/MTEQ0041 This Version is available at: https://hdl.handle.net/10419/324175 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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A study of the employment and earnings outcomes of second-generation migrants, ILO Working Paper 141 (Geneva, ILO). https://doi.org/10.54394/ MTEQ0041 01 ILO Working Paper 141 Abstract This study examines the labour market outcomes of second-generation migrants in 32 countries (30 European countries, Australia and the United States of America). Drawing on data from labour force surveys and other household surveys contained in the ILO Microdata Repository, it focuses on labour force participation, unemployment, status in employment, wages and self-employment income. The results of the analysis reveal differences between second-generation migrants and other people born in the same country once the specific composition of that population group in terms of age and educational attainment is taken into account. Second-generation migrants generally exhibit lower labour market participation and higher unemployment rates, and they appear more likely to be employees than self-employed in several of the countries studied. With regard to earnings, on average across the countries studied, a small wage gap is observed between second-generation migrant workers and the rest of native-born workers, with wage premiums existing only in a few countries. The final chapter discusses relevant legal frameworks dealing with non-discrimination and employment that affect second-generation migrants. About the authors Utsoree Das is a PhD candidate at the Institute of Economics and Econometrics, University of Geneva. She is a researcher in applied microeconomics. Her work focuses on environmental and resource economics, climate shocks, migration, development, political economy, and sustainability and transformative change. Giulia Dellaferrera works for the promotion of domestic workers’ rights in Tanzania with CVM, after having analysed work-related inequalities at ILO Research Department. Previously, she worked at UNHCR, ICRC and Genocide Watch. She is specialised in human rights and international humanitarian law. Sevane Ananian is an economist in the Research Department of the International Labour Organization (ILO), where he has worked since September 2021. His work focuses on wages and working conditions, inequality, and the transition to a green economy. 02 ILO Working Paper 141 Abstract 01 About the authors 01 XIntroduction 07 X1 Literature review 09 X2 Data and methodology 13 2.1. Defining second-generation migrants 13 2.2. A sample of household surveys from 32 countries 14 X3 Descriptive statistics 16 X4 Employment of second-generation migrants 19 4.1. A methodology for analysing the differences in employment outcomes between second-generation migrants and other native born people 19 4.2. Employment outcomes of second-generation migrants 21 On average across countries, second-generation migrants are less likely to participate in the labour force and more likely to be unemployed 21 Second-generation migrants tend to work as employees 25 X5 Earnings of second-generation migrants 27 5.1. A methodology for analysing the differences in earnings outcomes between second-generation migrants and other native-born people 27 5.2. Wages of second-generation migrants 29 5.3. Self-employment income of second-generation migrants 31 X6 Legal frameworks shaping the labour market experience of second-generation migrants 33 6.1. International legal standards ensuring equal employment opportunities and treatment 33 International labour standards dealing with non-discrimination and equal treatment 35 The supervisory practice of the Committee of Experts on the Application of Conventions and Recommendations 36 6.2. National practices regarding non-discrimination and equal treatment of second-generation migrants 38 Table of contents 03 ILO Working Paper 141 XConclusion 43 Annex 44 Figures 44 Tables 49 References 57 Acknowledgements 65 04 ILO Working Paper 141 List of Figures Figure 3.1. Share of second-generation migrants in the working-age population in each of the sampled countries 16 Figure 3.2. Age composition of working-age second-generation migrants and the rest of the native-born working-age population, by sex (percentage) 17 Figure 3.3. Distribution of working-age second-generation migrants and the rest of the native-born working-age population by education level and sex (percentage) 17 Figure 3.4. Distribution of second-generation migrant workers and other native-born workers in employment by occupational category and sex (percentage) 18 Figure A1. Share of second-generation migrants (based on alternative definition) in the working-age population in each of the sampled countries 44 Figure A2. Age composition of working-age second-generation migrants (based on alternative definition) and the rest of the native-born working-age population, by sex (percentage) 45 Figure A3. Distribution of working-age second-generation migrants (based on alternative definition) and the rest of the native-born working-age population by education level and sex (percentage) 45 Figure A4. Distribution of second-generation migrant workers (based on alternative definition) and other native-born workers in employment by occupational category and sex (percentage) 46 Figure A5. Earnings distribution (based on hourly wages) of second-generation migrant wage employees, by region or country (percentage) 46 Figure A6. Earnings distribution (based on monthly self-employment income) of self-employed second-generation migrants, by region or country (percentage) 47 Figure A7. Average number of weekly hours worked by second-generation migrants who are wage employees versus other native born wage employees, by sex and country 48 05 ILO Working Paper 141 List of Tables Table 4.1. Effect of being a second-generation migrant on the probability of labour force participation, unemployment and wage employment, by country (percentage points) 23 Table 5.1. Effect of being a second-generation migrant on hourly wages (percentage) 30 Table 5.2. Effect of being a second-generation migrant on monthly self-employment income (percentage) 31 Table A1. National data sources used to analyse the employment and earnings outcomes of second-generation migrants 49 Table A2. Effect of being a second-generation migrant (based on alternative definition) on the probability of labour force participation, unemployment and wage employment, by country (percentage points) 50 Table A3. Effect of being a second-generation migrant on monthly wages (percentage) 52 Table A4. Effect of being a second-generation migrant (based on alternative definition) on hourly wages (percentage) 53 Table A5. Effect of being a second-generation migrant (based on alternative definition) on monthly wages (percentage) 54 Table A6. Effect of being a second-generation migrant (based on alternative definition) on monthly self-employment income (percentage) 55 12 ILO Working Paper 141 Finally, there is a divergence between public perceptions and the actual extent of economic and social integration of migrants. The general public tend to hold negative views about the integration level of migrants that are not borne out by statistics, especially when it comes to employment, crime rates and social assimilation (Fertig and Schmidt 2001). On the other hand, more immigration-restrictive policies can lead to reduced assimilation of second-generation migrants by reinforcing cultural identities that are distinct from mainstream society (Galli and Russo 2019). 13 ILO Working Paper 141 X2 Data and methodology 2.1. Defining second-generation migrants There is no universally accepted definition of second-generation migrants. However, the most common definitions are those widely used by organizations such as Eurostat and the OECD. As defined in the European Migration Network’s Asylum and Migration Glossary, a second-generation migrant is “a person who was born in and is residing in a country that at least one of their parents previously entered as a migrant”. 4 Put slightly differently, second-generation migrants are persons who are native-born and who either have one foreign-born parent and one native-born parent or have two foreign-born parents (Eurostat 2011; Falcke, Meng and Nollen 2020). Within the framework of its Programme for International Student Assessment (PISA), the OECD (2023) defines a “second-generation immigrant student” as a child born in the country of assessment with at least one parent born outside that country. In a study dealing with Switzerland, Ruspini (2010) points out that the notion of “second-generation migrants” was first introduced into Swiss political discourse in the 1980s following a report by the Federal Commission for Foreigners that stated: “The ‘second generation of foreigners’ shall be understood to mean children born in Switzerland of foreign parents who came here as immigrants, and also children who entered Switzerland for the purposes of family reunification, insofar as they have completed the greater part of their schooling in our country.”5 For the purposes of statistical identification, two definitions of “second-generation migrant” are used in this paper. According to the first, an individual is considered a second-generation migrant if their country of birth matches the host country, but their mother’s country of birth is different from the host country. This is used as our main specification in the various analyses, and the corresponding results are presented in the main text. The decision to focus primarily on maternal country of birth is guided by the fact that a mother’s identification with the host country was found to significantly influence some of the life outcomes of her children, in particular those related to educational attainment and even earnings (Schüller 2015; Ramakrishnan 2004). The robustness of the estimates obtained was checked by using a second definition that applies the same criterion to the father’s country of birth. The corresponding results, presented in the appendix, are consistent with those based on the definition using the mother’s country of birth. In the quantitative analysis presented in Chapters 4 and 5, second-generation migrants are compared with the rest of the population born in the same country. This makes it easier to assess the relative situation of second-generation migrants, as people born abroad are likely to have encountered very different experiences and challenges in terms of labour market integration. In addition to having to overcome the legal hurdles associated with settling in the country of destination, many of those born abroad may have received part of their education in education 4The Asylum and Migration Glossary includes the following note: “This term is not defined in legislation but has a more sociological context; a broad definition encompassing the concept of a ‘second-generation migrant’ has been used.” 5Switzerland, Federal Commission for Foreigners, Les jeunes étrangers. La deuxième génération. Problèmes et solutions possibles, 1980. Translated from the French original quoted in Ruspini (2010, 2): “Par deuxième génération d’étrangers, il faut entendre les enfants nés en Suisse de parents étrangers ayant immigré, de même que les enfants entrés en Suisse dans le cadre du regroupement familial, dans la mesure où ils ont accompli dans notre pays la plus partie de leur scolarité.” 14 ILO Working Paper 141 systems that are different from those in their country of destination, which gives rise to further obstacles (for example, with regard to the recognition of qualifications). 2.2. A sample of household surveys from 32 countries Employing the criteria described in the previous section, we identified second-generation migrants from 32 countries using data from labour force surveys and other household surveys contained in the ILO Microdata Repository,6 which covers more than 160 countries. The surveys selected include information on the employment status and earnings of household members, in addition to the country of birth of individuals and their parents. With regard to job characteristics and earnings, the estimates reported in this paper are for the main jobs of individuals. Given that second-generation migrants are likely to also work part-time,7 the analysis focuses on gross hourly wages as well as monthly wages in order to eliminate variation in earnings due to differences in working time. Our final working database comprises 32 countries, drawn from different regions of the world, though most of them are developed and high-income countries. There are 30 European countries, 8 along with Australia and the United States, in the database. Among the countries included, 27 are OECD member countries, 3 are OECD accession candidate countries and 2 are non-OECD countries.9 Overall, our analysis covers six non-members of the European Union. Table A1 in the appendix provides a detailed breakdown of the countries selected and the corresponding survey years. The analysis of wages and income from self-employment is restricted to countries with surveys that include the earnings of workers and feature a sufficient number of respondents (specifically wage employees and the self-employed) who are second-generation migrants to allow these dimensions to be studied properly. When averages are estimated for the whole sample, or by country income group, each country is weighted equally. This makes it possible to focus on the role of national institutions and policies. Weighting each country by its working population would have caused the results to be driven mainly by the more populous countries. In view of certain short-term disruptions linked to the COVID-19 pandemic, surveys conducted in 2020 were not considered to avoid possible discrepancies in data collection processes. During that period, many national statistical offices adapted their methods to conform to the social distancing measures implemented in their countries. Accordingly, most of the surveys selected are from 2022 (28 countries), with only a few from 2021 (3 countries) and 2023 (1 country). Finally, it is worth noting that the countries in the sample apply various policies based on either jus soli (birthright citizenship) or jus sanguinis (citizenship by descent). The different approaches adopted with regard to these two principles may influence the labour market integration of 6For more information, see the ILOSTAT website, https://ilostat.ilo.org/about/data-collection-and-production/. 7Fernández-Reino, Radl and Ramos (2018) examine the degree of underutilization of human capital among firstand second-generation migrants in Spain by measuring, inter alia, the incidence of involuntary part-time employment. 8 The relatively high coverage of European countries is possible thanks to the use of data from the European Union Statistics on Income and Living Conditions (EU-SILC) survey, made available by Eurostat, which covers 28 countries in the sample (26 Member States of the European Union and 2 non-members). 9See the OECD web page on member countries and partners for further information: https://www.oecd.org/en/about/memberspartners.html. 15 ILO Working Paper 141 second-generation migrants – in particular, through the impact that citizenship has on social integration and on access to employment (for example, some countries restrict access to public employment to national citizens). In Europe, the principle of jus sanguinis is broadly implemented. Reviewing citizenship policies in several European countries, Bauböck et al. (2013) found that jus sanguinis citizenship was available in each country surveyed and was the main channel for acquiring citizenship. In contrast, the authors observed significant differences in the application of jus soli across Europe. Countries such as Belgium, France, Germany, Greece, Ireland, Luxembourg, the Netherlands, Portugal and Spain were found to provide jus soli citizenship either at birth or after birth for those born on their territory, while at the other end of the spectrum, Iceland, Latvia, Lithuania, Montenegro, North Macedonia, the Republic of Moldova, Sweden and Türkiye were found to have no jus soli provisions apart from those for foundlings and stateless children. The situation in Europe stands in stark contrast with that in North America, where Canada and the United States offer citizenship to all children born on their territory. In Australia, jus solis was the prevailing principle until 1986, when amendments were introduced to qualify the acquisition of birthright citizenship (Thwaytes 2017). 16 ILO Working Paper 141 X3 Descriptive statistics Across the sampled countries, the average share of second-generation migrants in the working-age population is 8.2 per cent (8.5 per cent when applying our second working definition from section 2.1, which uses paternal rather than maternal country of birth), with sex-disaggregated values of 8.5 per cent for men and 8.0 per cent for women. However, as can be seen from an “intensity map” showing the share of second-generation migrants in the working-age population in each country studied (figure 3.1), there are notable differences between countries. Applying the second working definition gives similar results (see figure A1 in the appendix). XFigure 3.1. Share of second-generation migrants in the working-age population in each of the sampled countries Source: ILO Harmonized Microdata collection (ILOSTAT), 2022 or the latest available year. Figure 3.2 compares the age composition of second-generation male and female migrants across all countries in the sample with that of the rest of the native-born working-age population. As can be seen, young people (those aged between 15 and 24 years) account for a larger proportion of the population group of second-generation migrants than for the rest of the working-age population born in the same country. Similarly, figure 3.3 compares the distribution of second-generation male and female migrants by education level with that of other native-born people of working age. As can be seen, second-generation migrants tend to exhibit lower educational attainment than the rest of the native-born population. In particular, a larger share of the second-generation migrant population has a basic education only. 17 ILO Working Paper 141 Figures A2 and A3 in the appendix present the same comparisons using our second working definition of “second-generation migrant”. XFigure 3.2. Age composition of working-age second-generation migrants and the rest of the native-born working-age population, by sex (percentage) Note: The values reported are averages for the 32 countries in the sample. Source: ILO Harmonized Microdata collection (ILOSTAT), 2022 or the latest available year. XFigure 3.3. Distribution of working-age second-generation migrants and the rest of the native-born working-age population by education level and sex (percentage) Note: The values reported are averages for the 32 countries in the sample. Source: ILO Harmonized Microdata collection (ILOSTAT), 2022 or the latest available year. Lastly, figure 3.4 compares the distribution of second-generation male and female migrants by occupational category with that of other native-born people of working age. On average across the countries studied, there is a higher share of clerical, service and sales workers among second-generation migrants than among the rest of native-born workers. Managers, professionals and technicians also appear to be slightly over-represented among second-generation male migrants. The estimates obtained using the definition of second-generation migrants based on paternal country of birth are similar, as can be seen in figure A4 in the appendix. 18 ILO Working Paper 141 XFigure 3.4. Distribution of second-generation migrant workers and other native-born workers in employment by occupational category and sex (percentage) Note: The values reported are averages for the 32 countries in the sample. Source: ILO Harmonized Microdata collection (ILOSTAT), 2022 or the latest available year. These simple descriptive statistics highlight the socio-demographic particularities of the population group of second-generation migrants. Since labour market outcomes are likely to be impacted by specific characteristics, especially those related to age and education, taking the socio-demographic composition of second-generation migrants into account is essential when comparing their outcomes with those of the rest of the native-born population. In section 4.1, we accordingly discuss a methodology for comparing the labour market outcomes of second-generation migrants with those of the rest of the population while controlling for factors that could potentially skew the results. 19 ILO Working Paper 141 X4 Employment of second-generation migrants 4.1. A methodology for analysing the differences in employment outcomes between second-generation migrants and other native born people The labour market outcomes observed for second-generation migrants may differ from those of the rest of the population born in the same country because of differences in socio-demographic characteristics between the two population groups. For instance, lower educational attainment may reduce their chances of securing a job. On the other hand, the over-representation of young people among second-generation migrants could also have an impact on labour force participation rates. When analysing discrepancies in labour market outcomes, it is therefore crucial to take into account the socio-demographic structure of the second-generation migrant population. To that end, the econometric technique of logistic regression was applied to the data set constructed from the pooled country surveys selected for our analysis (see box 4.1 for details of the technique). This makes it possible to assess how being a second-generation migrant influences the likelihood of various labour market outcomes, while simultaneously disentangling this effect from other observed factors such as educational attainment and age.10 In other words, the analysis aims to assess the differences in labour market outcomes between second-generation migrants and the rest of the native-born population, controlling for educational attainment and age. Such a methodology is critical for proper analysis, as existing studies have emphasized the role played by human capital variables, such as education, in the labour market integration of migrants and their descendants. While certain other variables are also likely to drive the labour market outcomes of second-generation migrants to some extent, they were not included in the present regression analysis. In particular, as noted in our literature review (see Chapter 1), ethnicity and country of origin may help to explain some of the observed differences between second-generation migrants and the rest of the native-born population. However, such information was not available in every country survey included in the sample.11 The average values presented in this paper may therefore not necessarily reflect the situation of each subgroup of second-generation migrants when broken down by country of origin. To ensure maximum comparability across countries, only variables indicating education and experience were used when estimating the regressions.12 Thus, it is important to emphasize that the estimates presented here do not take into account potential unobservable characteristics that could influence the labour market participation of second-generation migrants. A further caveat has to do with the issue of endogeneity due to selection bias. When estimating the probability of unemployment (or the probability of being a wage employee), we considered only people participating in the labour market (or those employed when estimating the probability of being a wage employee), which may have skewed the results. 10 Controlling for education is essential here, as the existing literature indicates that second-generation migrants from low-skilled waves of migration are more likely to enter lower vocational tracks and to have an early transition into working-class occupations. This has, in particular, been observed in Switzerland (Laganà, Chevillard and Gauthier 2014). 11 For example, the information available to the ILO on the country of birth of a respondent’s mother in the EU-SILC surveys refers to only two options in the case of birth abroad: “European Union” and “Other countries”. 12 In the estimation of the probability of wage employment, however, the occupational category was also added to these variables. 20 ILO Working Paper 141 Consequently, we can only deduce controlled association, but not pure causality, between being a second-generation migrant and the various labour market outcomes studied. XBox 4.1. Estimating the effect of being a second-generation migrant on the probability of selected labour outcomes To quantify the effect of being a second-generation migrant on the probability of labour force participation, unemployment and wage employment, a logistic regression model is estimated separately for the whole population, for men and for women for each country in the sample (listed in table A1 in the appendix). This econometric approach involves estimating the parameters α, γ and β in the following equation: where P(Y) is the probability that Y happens, with Y referring, variously, to labour force participation, unemployment and being a wage employee (as opposed to being self-employed). In equation (1), α is a constant, SGM is a dummy indicating whether a survey respondent is a second-generation migrant or not, and X denotes a set of control variables. For labour market participation and unemployment, the control variables are educational attainment (lower secondary level or below = “basic”; upper secondary level = “intermediate”; and above secondary level = “advanced”) and age group (15–24 years, 25–55 years and 55+ years). When estimating the probability of wage employment, the control variables also include the respondent’s occupation according to the International Standard Classification of Occupations (ISCO 08), with the ISCO-08 major groups aggregated into six categories (“Managers, professionals and technicians”, “Clerical support, services and sales workers”, “Skilled agricultural, forestry, fishery, craft and related trades workers”, “Plant and machine operators, and assemblers”, “Elementary occupations” and “Armed forces”). This allows one to control for possible differences in employment status that could be due to the type of occupation pursued. The above model is used to estimate the results reported in table 4.1 for each country, which are presented in the form of “average marginal effects”. They correspond to the average increase (or decrease) in the likelihood of the event Y (that is, labour force participation, unemployment or wage employment) induced by the event “SGM = 1” (being a second-generation migrant). We also perform a pooled analysis covering all the 32 countries in our sample and another pooled analysis covering just the European countries. This estimation additionally uses a country dummy to allow for country-fixed effects. These results are presented in the two rows with all values in bold in table 4.1, again as average marginal effects. 21 ILO Working Paper 141 4.2. Employment outcomes of second-generation migrants On average across countries, second-generation migrants are less likely to participate in the labour force and more likely to be unemployed In most countries, being a second-generation migrant has a negative impact on the likelihood of labour market participation compared with other people born in the same country, even after controlling for age and educational attainment. As may be seen in table 4.1, in all the 16 countries with statistically significant estimates, except for Austria, Czechia, Sweden and Switzerland, second-generation migrants are less likely to participate in the labour force than other native-born people. This pattern is also strongly reflected in the sex-disaggregated estimates. On average across countries, being a second-generation migrant reduces the likelihood of labour market participation by 7.5 percentage points in the overall population, with a decrease of 9.5 percentage points for men and 5.8 percentage points for women (see the very last row in table 4.1). This trend can be observed both for European countries as a whole and in the United States. Considerable heterogeneity is nevertheless observable across countries where second-generation migrants are less likely to participate in the labour market. For example, compared with other such countries, second-generation migrants in Poland, Iceland, Norway and Denmark appear much less likely to participate in the labour market than other native-born individuals. This appears to be in line with previous analysis based on a sample of OECD countries, which showed, in particular, that Scandinavian countries (in this case including Sweden) had a relatively large gap between the employment rates of natives and second-generation migrants, even after controlling for educational attainment (OECD 2007). Several reasons may be adduced to explain the lower participation rates of second-generation migrants. In particular, labour market barriers created by factors such as discrimination, relatively low returns to participation in the workforce and specific institutional arrangements could all negatively affect their labour market attachment and deter some of them from participating, analogously to the mechanisms that have been described for groups such as women and older workers (Winkler 2016; Watermann, Fasbender and Klehe 2023). Automatic birthright citizenship in Australia and the United States could be one reason why being a second-generation migrant in those two countries is slightly less detrimental to the likelihood of participating in the labour market than is the case in Europe on average, where such schemes are rarely used. However, low labour force participation may also be explained by additional factors. For instance, the fact that the likelihood of second-generation migrants in Denmark being unemployed is relatively similar to that of other native-born workers (see the middle panel in table 4.1) despite their being less likely to participate in the labour force could suggest that the latter phenomenon is partly due to factors such as their enrolment in education or training. In that regard, recent analysis has found that the descendants of migrants are over-represented in Danish universities and business schools (European Commission 2021). As a robustness check, we performed a similar analysis using our second definition of “second-generation migrant” (that is, where paternal country of origin is used to identify migrant background). Table A2 in the appendix shows the results. When it comes to unemployment, being a second-generation migrant appears to have a positive impact on unemployment outcomes in most countries. Indeed, the likelihood of being unemployed increases in a statistically significant manner when the respondent is a second-generation 28 ILO Working Paper 141 to examine the effect of being a second-generation migrant on earnings by incorporating age, educational attainment and occupational category as controls. As with second-generation migrants’ employment outcomes in Chapter 4, it is important to note that the estimates related to their earnings outcomes presented here do not account for potential unobservable characteristics that could influence those outcomes. Therefore, only controlled association and not pure causality can be established through this analysis. XBox 5.1. Estimating the effect of being a second-generation migrant on the earnings from wage employment and self-employment To further explore inequalities in the labour market, we estimate the relationship between being a second-generation migrant and earnings separately for the entire population of employees (or self-employed) and for the male and female populations across our subsample of countries (29 countries for wage employment and 21 for self-employment), using the following Mincer model: This econometric approach involves estimating the parameters α, γ and β, where γ is our parameter of interest. The dependent variable is ln Y, where Y stands for the outcome examined: ●hourly wages ●monthly wages ●monthly income from self-employment.1 In equation (2), α is a constant, SG Miis a dummy variable equal to 1 if a survey respondent is a second-generation migrant, and Xi′ denotes a vector of observable characteristics that are used as control variables. In our specification, the control variables are educational attainment (lower secondary school or below = “basic”; upper secondary school = “intermediate”; and above secondary level = “advanced”), age and age squared, and the respondent’s occupation according to the International Standard Classification of Occupations (ISCO-08), with the ISCO-08 major groups aggregated into six categories (“Managers, professionals and technicians”, “Clerical support, services and sales workers”, “Skilled agricultural, forestry, fishery, craft and related trades workers”, “Plant and machine operators, and assemblers”, “Elementary occupations” and “Armed forces”). When estimating averages across countries, we also use country dummies to allow for country-fixed effects. The model is estimated using the method of ordinary least squares. 2 As already mentioned, the coefficient of interest is γ, which provides an estimate of the difference in earnings 29 ILO Working Paper 141 between second-generation migrants and other native-born workers. Its estimated values are reported in the tables of chapter 5. 1 For income from self-employment, we only look at monthly income, as the quality of the information on hours worked is often lower for this subset of the population. However, analysis of hourly income has also been undertaken and the trends look very similar. These results are available upon request. 2 Ordinary Least Squares (OLS) is an econometric technique that allows the parameters α, γ and β of equation (2) above to be estimated. 5.2. Wages of second-generation migrants The results of estimating equation (2) are presented in table 5.1 below for hourly wages as the outcome examined (see box 5.1).18 The estimates in the table correspond to the effect of being a second-generation migrant on hourly wages. On average across the countries studied, a small hourly wage gap between second-generation migrants and other native-born employees can be observed, with the former being paid slightly less than the latter once their socio-demographic characteristics are taken into account (specifically 4.6 per cent less on average). This result is essentially driven by the wage penalty observed across the European countries in the sample (-5.1 per cent on average). However, at the country level, the estimates are not statistically significant in most cases, which is probably due in part to the small number of observations used in the analysis. The wage penalty is nevertheless statistically significant in Belgium, Estonia, Portugal and Slovakia, as well as in Austria and Ireland for men only, and in Cyprus for women only. In the United States, a statistically significant wage premium is observed, with second-generation migrants earning 4.8 per cent higher hourly wages than other native-born employees. Thus, from the survey data analysed here it emerges that there is a wage penalty for either male or female second-generation migrants in several countries, while a wage premium is observed only in the United States and – with a lower statistical significance – also in Hungary. Table A3 in the appendix presents the result of the estimation for monthly wages as the outcome examined instead of hourly wages. As with hourly wages, an average wage penalty is observed for Europe, namely 4.4 per cent, contrasting with a wage premium of 4.9 per cent for the United States. The slight differences between the values in tables 5.1 and A3 may potentially be accounted for by certain specificities in the working time of second-generation migrants (see box 4.2 in Chapter 4). The pay gaps observed between second-generation migrants and their peers born in the same country are due to various factors not taken into account in the analysis through the use of educational attainment, age and occupational category as control variables. In particular, wage penalties among second-generation migrants may reflect the challenges faced by this group that are often highlighted in the literature on migration, such as poor integration, lack of networks, limited proficiency in the majority language and discrimination (Devos et al. 2025). As for the wage premium observed in the United States, the available evidence points to how second-generation migrants there are relatively well endowed in terms of education and skills. Indeed, a US study based on longitudinal childhood data indicates that the initial gap in mathematics scores between second-generation migrants and natives closes by the end of primary school, while for 18 Descriptive statistics related to the earnings distribution can be found in two figures in the appendix. Figure A5 shows the share of second-generation migrant wage employees in the different quintiles for hourly wages. On average, second-generation migrants tend to be over-represented at the bottom end of their country’s wage distribution. Figure A6 shows the corresponding distribution for the monthly self-employment income of self-employed second-generation migrants. In Europe, an over-representation of the self-employed at the lower end of the income distribution can also be observed. 30 ILO Working Paper 141 non-cognitive, or “soft”, skills there is a positive gap in favour of second-generation migrants by the third year of primary school (Hull and Norris 2020). This could help to explain the slightly higher wages earned later in life by second-generation migrants, consistent with the estimates presented in table 5.1. In that regard, the relatively high performance of second-generation migrants in the United States when it comes to education and wages has been emphasized by a number of previous studies (Card 2005). As a robustness check, we applied the same econometric methodology using our second definition of “second-generation migrant”. The results are presented in tables A4 and A5 in the appendix. XTable 5.1. Effect of being a second-generation migrant on hourly wages (percentage) Country All Men Women Europe Austria -3.3 -4.5* -1.0 Belgium -8.7** -7.3 -11.0** Bulgaria -18.2 25.1 -33.3 Croatia 2.1 -2.6 3.8 Cyprus -7.1 6.4 -30.5* Czechia 1.5 2.7 -0.6 Denmark 0.1 2.3 -3.1 Estonia -11.0** -8.0 -13.6** Finland 11.4 -0.5 21.2 France 4.0 5.8 2.2 Germany 1.3 2.6 -1.7 Greece -1.9 -6.7 4.7 Hungary 18.0* 10.3 25.6* Ireland -6.1 -16.7* 5.0 Italy -1.1 5.1 -8.8 Latvia -1.7 -3.2 -0.3 Lithuania 9.5 11.2 9.5 Luxembourg -6.9 -9.3 -3.0 Netherlands -1.9 -4.1 -0.4 Poland 3.5 1.5 5.7 Portugal -5.2* -0.7 -11.1** Serbia 3.0 0.6 3.2 Slovakia -9.1** -18.0*** 1.1 Slovenia -1.1 -5.9 5.8 Spain -7.1 -10.0 -3.9 Sweden -1.6 -2.5 -1.7 Switzerland 2.2 -0.8 2.8 Europe -5.1*** -6.5*** -3.8*** Rest of the world 31 ILO Working Paper 141 Country All Men Women Australia 2.3 1.3 2.1 United States 4.8*** 2.0** 7.3*** All countries -4.6*** -6.0*** -3.4*** Note: ***, ** and * indicate that the result is statistically different from zero at the 1%, 5% and 10% level of significance, respectively. Source: Analysis based on ILO Harmonized Microdata collection (ILOSTAT), 2022 or the latest available year. See table A1 in the appendix for more details. 5.3. Self-employment income of second-generation migrants Estimates of the effect of being a second-generation migrant on monthly self-employment income (obtained using equation (2) from box 5.1 with monthly self-employment income as the outcome examined) are presented in table 5.2 for a subsample of countries for which relevant data are available.19 It appears that almost all the statistically significant estimates point to an earnings penalty for second-generation migrants who are self-employed. For European countries, we observe an average penalty of 22.3 per cent for second-generation migrants (16.5 per cent among male entrepreneurs and 27.5 per cent among their female counterparts). Overall, these results tend to confirm the potential challenges that second-generation migrants face in setting themselves up as self-employed, as discussed in Chapter 4.20 A robustness check was performed by applying the same methodology to our second definition of “second-generation migrant”. Table A6 in the appendix shows the results. XTable 5.2. Effect of being a second-generation migrant on monthly self-employment income (percentage) Country All Men Women Europe Austria -14.6 8.1 -54.5** Belgium -10.7 -27.1 42.7 Czechia 6.7 2.5 15.5 Denmark -21.2 -32.8 -3.8 France -9.4 -6.7 -18.0 Germany -20.1** -23.9** -15.6 Hungary -79.1 50.6 -281.7* Ireland -24.3 -33.4 -7.2 Italy -36.2 -3.0 -142.2*** Latvia -7.1 -22.1 7.6 Lithuania -16 -15.7 1.6 19 Not all national surveys contain reliable data on self-employment income on a monthly/hourly basis. Some countries were therefore excluded from this analysis, especially if the sample size was too small. 20 In line with these results, Bijedić and Piper (2018), using data from the German Socio-Economic Panel, found that first-generation migrant entrepreneurs had lower rates of job satisfaction than the native population. A similar pattern was observed for second-generation male migrant entrepreneurs. 32 ILO Working Paper 141 Country All Men Women Luxembourg -33.1 -15.9 -144.8 Netherlands -100.3* -74.2 -141.4 Poland -5.2 -1.5 -24.1 Portugal -29.4** -23.6 -34.5 Serbia 22.5 8.8 102.3*** Slovenia -30.8 -57.7 -14.8 Spain -27.3 8.7 -59.4 Sweden 8.8 -1.6 19.0 Switzerland -0.3 3.3 -6.2 Europe -22.3*** -16.5* -27.5** Rest of the world Australia 13.7 11.1 6.1 All countries -20.0*** -14.6* -25.7** Note: ***, ** and * indicate that the result is statistically different from zero at the 1%, 5% and 10% level of significance, respectively. Source: Analysis based on ILO Harmonized Microdata collection (ILOSTAT), 2022 or the latest available year. See table A1 in the appendix for more details. 33 ILO Working Paper 141 X6 Legal frameworks shaping the labour market experience of second-generation migrants In the previous chapter we analysed the labour market outcomes of second-generation migrants in a large number of countries, focusing on labour force participation, unemployment, status in employment, wages and self-employment income. Although we cannot assert a direct causal relationship between being a second-generation migrant and these outcomes, the controlled associations that we have established provide a picture of their labour market experience. Specifically, a lower rate of labour force participation compared with the rest of the native-born population has been highlighted. Similarly, second-generation migrants seem, on average, to be more likely to be unemployed. Furthermore, except in a few countries, second-generation migrants tend to be wage employees rather than self-employed when they are in employment, which is probably due to a lack of integration and limited access to the networks that are necessary to operate as an entrepreneur. With regard to earnings, statistically significant wage penalties were observed for second-generation migrants in a number of European countries, whereas a wage premium was noted in the United States. Building on this analysis, it is essential to understand how legal frameworks can act as a further influence on the labour market experience of second-generation migrants. Such frameworks, which include international labour standards21 and national laws, play a crucial role in establishing the rights and protections afforded to workers, thereby shaping their opportunities and treatment in the job market. This chapter will explore key standards that lay the foundation for inclusive labour markets which can benefit both second-generation migrants and the rest of the population. Section 6.1 first outlines the various sets of international labour standards relevant to promoting equality of opportunity and fair labour market outcomes. These instruments are then analysed in detail, together with the related supervisory work of the Committee of Experts on the Application of Conventions and Recommendations (CEACR).22 Finally, national practices aimed at ensuring equal employment opportunities and treatment are examined in section 6.2, which provides a brief overview of how international standards are applied in different countries. 6.1. International legal standards ensuring equal employment opportunities and treatment Before embarking on our analysis of relevant legal frameworks, it is important to clarify that second-generation migrants are not considered to be migrant workers. Indeed, they do not meet the definition of “migrant worker” contained in the Migrant Workers (Supplementary Provisions) 21 Conventions, together with any Protocols thereto, are legally binding international treaties that may be ratified by Member States, while Recommendations serve as non-binding guidelines. In many cases, a Convention lays down the basic principles to be implemented by ratifying countries, and the related Recommendation supplements the Convention by providing more details on how it could be applied. However, Recommendations can also be autonomous – that is, not linked to a Convention. 22 The CEACR is one of the two bodies comprising the regular system of supervision developed by the ILO to help ensure that countries implement the Conventions they ratify. It examines the reports that governments are required to submit regularly on the implementation of ratified Conventions, along with the comments of employers’ and workers’ organizations on these reports. The Committee makes two kinds of comments on the reports received – “observations” and “direct requests” – and issues an annual report, which includes a General Survey on a specific subject selected by the Governing Body of the International Labour Office. The comments of the CEACR are non-binding, being intended to guide the actions of national authorities. They derive their persuasive value from the legitimacy and rationality of the Committee’s work based on its impartiality, experience and expertise. For more information, see the web page entitled “ILO supervisory system/mechanism”. 34 ILO Working Paper 141 Convention, 1975 (No. 143), namely “a person who migrates or who has migrated from one country to another with a view to being employed otherwise than on his own account”, which “includes any person regularly admitted as a migrant worker” (Art. 11(1)). However, second-generation migrants have a migration background and they are often perceived as “foreigners” by a vast majority of the population, as a consequence of their belonging to ethnic minorities and, in some cases, not possessing the nationality of the country where they live and work (Bhimji 2008; Beaman 2017). These factors can lead to discriminatory treatment, creating challenges for second-generation migrants when it comes to both social integration and labour market participation, as outlined in the quantitative analysis in Chapters 4 and 5. As discussed further down, the Discrimination (Employment and Occupation) Convention (No. 111) and Recommendation (No. 111), 1958,23 provide crucial orientation on how to tackle discrimination and improve integration into the labour market. Other international labour standards are relevant in addressing the discrimination and inequalities that second-generation migrants may face at work – for instance, the Employment Policy Convention (No. 122) and Recommendation (No. 122), 1964,24 and the Human Resources Development Convention, 1975 (No. 142). Alongside the above-mentioned instruments, international labour standards dealing with wages are key to ensuring equality of treatment in employment for second-generation migrants. These include the Minimum Wage-Fixing Machinery Convention, 1928 (No. 26), the Minimum Wage Fixing Convention (No. 131) and Recommendation (No. 135), 1970, and the Protection of Wages Convention, 1949 (No. 95) (see box 6.1).25 The focus of this section will be mainly on standards related to non-discrimination and equal treatment, given the role that they play in shaping the employment outcomes of second-generation migrants. Finally, it is important to look at the supervisory work of the CEACR as it supports the implementation of international labour standards at the national level. The category of workers considered in this study falls within the scope of the Committee’s comments concerning workers in general. On some occasions, the CEACR has explicitly referred to second-generation migrants and workers with a migration background in its observations and direct requests. Such references have occurred mainly when the Committee is reviewing the application of provisions on non-discrimination and equality of opportunity and treatment. 23 International labour standards of general application concern second-generation migrants as well as the rest of the population. Among these standards, a central role is played by the 11 “fundamental” instruments, which cover subjects considered to be fundamental principles and rights at work. Convention No. 111 is one such instrument. 24 Convention No. 122 is one of the four Conventions designated by the Governing Body of the International Labour Office as “governance” (or “priority”) instruments. Consequently, Member States are encouraged to ratify it because of its importance for the functioning of the international labour standards system. 25 Minimum wages have been an important topic at the ILO ever since its inception. Indeed, the original ILO Constitution of 1919 called in its Preamble for an urgent improvement of conditions of labour, including “the provision of an adequate living wage”. In 1944, the Declaration of Philadelphia referred to the importance of ensuring “a minimum living wage to all employed and in need of such protection”. This was reiterated in the ILO Declaration on Social Justice for a Fair Globalization (2008). In addition to international labour standards, a relevant tool for the design, implementation and review of minimum wages is the Minimum Wage Policy Guide (ILO 2016), which emphasizes key principles of good practice and provides examples to illustrate the pros and cons of different policy options. 35 ILO Working Paper 141 XBox 6.1. International labour standards dealing with non-discrimination, equal treatment and wages Non-discrimination and equal treatment Discrimination (Employment and Occupation) Convention, 1958 (No. 111) Employment Policy Convention, 1964 (No. 122) Human Resources Development Convention, 1975 (No. 142) Discrimination (Employment and Occupation) Recommendation, 1958 (No. 111) Employment Policy Recommendation, 1964 (No. 122) Wages Minimum Wage-Fixing Machinery Convention, 1928 (No. 26)* Minimum Wage Fixing Convention, 1970 (No. 131) Protection of Wages Convention, 1949 (No. 95) Minimum Wage Fixing Machinery (Agriculture) Convention, 1951 (No. 99)* Minimum Wage Fixing Recommendation, 1970 (No. 135) Minimum Wage-Fixing Machinery (Agriculture) Recommendation, 1951 (No. 89)* * Instrument with interim status. Source: ILO NORMLEX database. International labour standards dealing with non-discrimination and equal treatment Second-generation migrants tend to experience poor integration and face discriminatory treatment, which may partly explain their lower labour market participation and slightly higher unemployment rates on average, although outcomes vary substantially across countries, as described in section 4.2. International labour standards aimed at countering discrimination on the grounds of race, colour and national extraction play a crucial role in enabling the participation and equal treatment of second-generation migrants in the labour market, particularly in countries with a pattern of ethnic discrimination and citizenship schemes based on descent. The Discrimination (Employment and Occupation) Convention, 1958 (No. 111), provides significant guidance on this score. It seeks to eliminate any discrimination in respect of employment and occupation and to promote equality of opportunity and treatment (Art. 2). Discrimination on the basis of “race, colour, sex, religion, political opinion, national extraction or social origin” is covered (Art. 1(1)(a)). Convention No. 111 also stipulates that special measures designed to meet the particular needs of persons who, for reasons such as social or cultural status, require special protection or assistance shall not be regarded as discrimination (Art. 5(2)). The accompanying Discrimination (Employment and Occupation) Recommendation, 1958 (No. 111), recommends that all persons should, without discrimination, enjoy equality of opportunity and treatment in respect of, inter alia, remuneration for work of equal value (para. 2(b)(v)). The same principles are reiterated in the Employment Policy Convention (No. 122) and Recommendation (No. 122), 1964. These instruments call upon Member States to pursue an active policy aimed at ensuring “freedom of choice of employment and the fullest possible opportunity for each worker to qualify for, and to use his skills and endowments in, a job for which he is well suited, irrespective of race, colour, sex, religion, political opinion, national extraction or social origin” (Arts 1(1) and 1(2)(c) of the Convention and paras 1(1) and 1(2)(c) of the Recommendation). 36 ILO Working Paper 141 Finally, the Human Resources Development Convention, 1975 (No. 142), promotes non-discrimination in the field of vocational guidance and training. It specifically requires Member States to adopt vocational guidance and training policies and programmes that “encourage and enable all persons, on an equal basis and without any discrimination whatsoever, to develop and use their capabilities for work” (Art. 1(5)). Moreover, it stipulates that comprehensive employment information and guidance are to be made available to everyone (Art. 3). The supervisory practice of the Committee of Experts on the Application of Conventions and Recommendations The CEACR has dealt with inequalities at work affecting second-generation migrants mainly in the context of Convention No. 111, when considering discrimination against individuals with a migration background26 on the grounds of race, colour or national extraction (see box 6.2). The selection of comments related to Convention No. 111 offered here is based on the results presented in section 4.2, with a particular focus on comments addressed to those countries where being a second-generation migrant was associated with a reduction in the likelihood of labour market participation (table 4.1). Among these, relevant comments expressly mentioning second-generation migrants or individuals with a migration background were found, in particular, for Denmark, Germany and the Netherlands. XBox 6.2. How “race, colour and national extraction” are understood in the supervisory practice of the Committee of Experts on the Application of Conventions and Recommendations related to the Discrimination (Employment and Occupation) Convention, 1958 (No. 111) In a general observation on discrimination based on race, colour and national extraction adopted in 2018, the Committee of Experts on the Application of Conventions and Recommendations (CEACR) explained the meaning of the grounds of “race, colour and national extraction” in the context of the Discrimination (Employment and Occupation) Convention, 1958 (No. 111). Furthermore, it provided examples of people affected by discrimination in employment on grounds that fall within the scope of the Convention. In particular, the CEACR recalled that, under Convention No. 111, “the term ‘race’ includes any discrimination against linguistic communities or minority groups whose identity is based on religious or cultural characteristics or national or ethnic origin.” Additionally, it specified that discrimination on the basis of race and colour were generally examined together, as “colour” was one of the ethnic characteristics of human beings. The Committee also reiterated that national extraction covered “distinctions made on the basis of a person’s place of birth, ancestry or foreign origin”. When reviewing the application of Convention No. 111, the Committee has therefore been seeking to address discrimination in the workplace experienced, inter alia, by “ethnic minorities, indigenous and tribal peoples, migrant workers, including migrant domestic workers, afro-descendants, national minorities and Roma people” (CEACR 2019a). 26 The expression “person with a migration background” is being used with growing frequency, especially in German-speaking European countries (Kuptsch and Mieres 2021). This notion encompasses firstand second-generation migrants. As a result, national legal frameworks often do not directly address the situation of second-generation migrants at work and the CEACR, too, has mainly considered that issue indirectly, through the prism of the broader category of “individuals with a migration background”, with specific references to second-generation migrants being rare. 37 ILO Working Paper 141 In its observations and direct requests related to Convention No. 111 that expressly mention second-generation migrants or individuals with a migration background, the CEACR has called upon States to strengthen their efforts to effectively address discrimination and ensure equality of opportunity and treatment. In an observation, it notably urged the Government of the Netherlands to provide information on the measures implemented to that end (CEACR 2024a). In a direct request addressed to the same Government, the Committee noted that various steps needed to be taken,27 including positive action measures (CEACR 2024b). In the same vein, the CEACR requested the German Government to provide information on the specific affirmative measures taken to ensure improved access to employment opportunities for “persons with a minority or migrant background”, including information on the impact of such measures (CEACR 2019b). Among the concrete measures to be adopted by Germany to tackle discrimination based on ethnic origin or national extraction affecting second-generation migrants, the Committee referred to recruitment and selection processes. In particular, it acknowledged the introduction of pilot projects on depersonalized job applications in private enterprises and public administration with a view to reducing discrimination in recruitment, and noted the Government’s statement that, compared to the traditional process, depersonalized applications ensured that applicants with a migration background had a better chance of being invited to an interview. The Committee requested further information on these anonymous application methods and their results (CEACR 2019c, 2021a). Taking up another aspect related to labour market outcomes, the CEACR inquired about equality of opportunity in training, skills development and career guidance when considering the situation of individuals with a migration background in Denmark and the Netherlands (CEACR 2018, 2016). In that regard, it has welcomed initiatives taken to improve the qualifications and skills of that population group, such as the establishment of regional skilled worker networks in Germany (CEACR 2021b). In its most recent direct request on Convention No. 111 addressed to the Netherlands, the Committee also referred to the concern expressed by the United Nations Committee on the Elimination of Racial Discrimination about the stigmatization of people of African descent and the lack of disaggregated data on their social and economic situation. Subsequently, it asked for information on any assessment made of the impact of the measures undertaken to promote equality of opportunity and treatment of persons of African descent, and on cases of discrimination in employment and occupation against them dealt with by the national authorities (CEACR 2024b). Furthermore, to address discrimination in employment and occupation effectively, the Committee has requested or welcomed on several occasions the gathering of information on workers with a migration background in Denmark, particularly through the collection of employment and unemployment statistics disaggregated by origin (CEACR 2016, 2013a). In addition to calling for specific measures to advance equality in the workplace, when assessing the situation of workers with a migration background in the light of Convention No. 111, the Committee has also addressed the root causes of discrimination. It thus encouraged the German and Dutch Governments to take action to combat racial stereotypes and prejudices and tackle systemic and structural discrimination against minority groups (CEACR 2021b, 2018). In particular, the Committee has noted the adoption of national programmes in Germany seeking to raise awareness of xenophobia and racism in the labour market and in society more broadly (CEACR 2013b). 27 In its 2012 General Survey, the CEACR emphasized that a range of measures had to be adopted to effectively respond to “the complex realities and varieties of ways in which discrimination occurs” (ILO 2012, para. 731). 44 ILO Working Paper 141 Annex Figures XFigure A1. Share of second-generation migrants (based on alternative definition) in the working-age population in each of the sampled countries Note: This figure was prepared using our second working definition of a “second generation migrant”, that is, where a native-born individual has a foreign-born father (see section 2.1). Source: ILO Harmonized Microdata collection (ILOSTAT), 2022 or the latest available year. 45 ILO Working Paper 141 XFigure A2. Age composition of working-age second-generation migrants (based on alternative definition) and the rest of the native-born working-age population, by sex (percentage) Note: This figure was prepared using our second working definition of a “second-generation migrant”, that is, where a native-born individual has a foreign-born father (see section 2.1). The values reported are averages for the 32 countries in the sample. Source: ILO Harmonized Microdata collection (ILOSTAT), 2022 or the latest available year. XFigure A3. Distribution of working-age second-generation migrants (based on alternative definition) and the rest of the native-born working-age population by education level and sex (percentage) Note: This figure was prepared using our second working definition of a “second generation migrant”, that is, where a native-born individual has a foreign-born father (see section 2.1). The values reported are averages for the 32 countries in the sample. Source: ILO Harmonized Microdata collection (ILOSTAT), 2022 or the latest available year. 46 ILO Working Paper 141 XFigure A4. Distribution of second-generation migrant workers (based on alternative definition) and other native-born workers in employment by occupational category and sex (percentage) Note: This figure was prepared using our second working definition of a “second generation migrant”, that is, where a native-born individual has a foreign-born father (see section 2.1). The values reported are averages for the 32 countries in the sample. Source: ILO Harmonized Microdata collection (ILOSTAT), 2022 or the latest available year. XFigure A5. Earnings distribution (based on hourly wages) of second-generation migrant wage employees, by region or country (percentage) Note: The European average refers to the following countries: Austria, Belgium, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Poland, Portugal, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland. Source: ILO Harmonized Microdata collection (ILOSTAT), 2022 or the latest available year. 47 ILO Working Paper 141 XFigure A6. Earnings distribution (based on monthly self-employment income) of self-employed second-generation migrants, by region or country (percentage) Note: The European average refers to the following countries: Austria, Belgium, Czechia, Denmark, France, Germany, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Poland, Portugal, Serbia, Slovenia, Spain, Sweden, Switzerland. Source: ILO Harmonized Microdata collection (ILOSTAT), 2022 or the latest available year. 48 ILO Working Paper 141 XFigure A7. Average number of weekly hours worked by second-generation migrants who are wage employees versus other native born wage employees, by sex and country Note: Only countries are shown for which there are sufficient observations to estimate the mean number of weekly hours worked by second-generation migrants (according to our main working definition, that is, where a native-born individual has a foreign-born mother – see section 2.1). Source: ILO Harmonized Microdata collection (ILOSTAT), 2022 or the latest available year. 49 ILO Working Paper 141 Tables XTable A1. National data sources used to analyse the employment and earnings outcomes of second-generation migrants Country Survey Year OECD status EU status Australia HILDA 2021 OECD member Non-EU Austria EU-SILC 2022 OECD member EU member Belgium EU-SILC 2022 OECD member EU member Bulgaria EU-SILC 2022 OECD candidate EU member Croatia EU-SILC 2022 OECD candidate EU member Cyprus EU-SILC 2022 Non-OECD EU member Czechia EU-SILC 2022 OECD member EU member Denmark EU-SILC 2022 OECD member EU member Estonia EU-SILC 2022 OECD member EU member Finland EU-SILC 2022 OECD member EU member France EU-SILC 2022 OECD member EU member Germany EU-SILC 2022 OECD member EU member Greece EU-SILC 2022 OECD member EU member Hungary EU-SILC 2022 OECD member EU member Iceland EU-LFS 2022 OECD member Non-EU Ireland EU-SILC 2022 OECD member EU member Italy EU-SILC 2022 OECD member EU member Latvia EU-SILC 2022 OECD member EU member Lithuania EU-SILC 2022 OECD member EU member Luxembourg EU-SILC 2022 OECD member EU member Netherlands EU-SILC 2022 OECD member EU member Norway EU-LFS 2022 OECD member Non-EU Poland EU-SILC 2022 OECD member EU member Portugal EU-SILC 2022 OECD member EU member Romania EU-SILC 2022 OECD candidate EU member Serbia EU-SILC 2021 Non-OECD Non-EU Slovakia EU-SILC 2022 OECD member EU member Slovenia EU-SILC 2022 OECD member EU member Spain EU-SILC 2022 OECD member EU member Sweden EU-SILC 2022 OECD member EU member Switzerland EU-SILC 2021 OECD member Non-EU United States CPS 2023 OECD member Non-EU CPS = Current Population Survey. EU-LFS = European Union Labour Force Survey. EU-SILC = European Union Statistics on Income and Living Conditions. HILDA = Household, Income and Labour Dynamics in Australia. Source: ILO Harmonized Microdata collection (ILOSTAT), 2022 or the latest available year. 50 ILO Working Paper 141 XTable A2. Effect of being a second-generation migrant (based on alternative definition) on the probability of labour force participation, unemployment and wage employment, by country (percentage points) Country Labour force participation Unemployment Wage employment All Men Women All Men Women All Men Women Europe Austria 1.2 0.1 2.5* -0.8 -0.9 -0.7 14.0*** 13.5*** 14.6*** Belgium -3.5** -2.5 -4.3* 4.3*** 2.5** 6.1*** 3.6* 5.1* 1.7 Bulgaria -0.2 2.4 -6.2 -1.8 -9.8 3.7 4.5 0*** -7.3 Croatia 0.5 -0.5 1.1 7.1** 9.7** 3.3 -2.6 -1.6 -3.9 Cyprus 0.7 4.2 -1.3 -2.1 -4.3 0.8 6.2 9.3 5.3 Czechia 3.9** 1.1 6.3** 1.6 0.9 2.5 1.9 1.2 2.0 Denmark -12.0*** -13.0*** -10.1*** 0.3 2.0 -1.7 -1.3 -1.9 -0.8 Estonia -10.2*** -14.7*** -4.9** 1.2 2.5 -0.1 -0.9 2.3 -3.6* Finland -10.4** -10.3* -9.8 3.3 2.1 4.1 -5.6 -0.6 -9.1* France -0.6 0.7 -1.6 4.5*** 5.9*** 3.0*** 0.1 2.1 -1.7 Germany -2.5*** -2.7*** -2.7*** 1.1*** 1.1** 1.0* 0.7 2.1** -0.8 Greece -3.8 -5.7 -1.3 5.7 1.1 10.7* 13.0* 25.8** -0.8 Hungary -5.3* -9.9** -0.3 -3.3 -2.8 -4.1 -9.2*** -11.2** -7.4* Iceland -27.2*** -26.0*** -27.2*** -0.2 -1.0 0.5 -5.7*** -9.2*** -0.3 Ireland -7.2*** -9.6*** -6.3* 1.5 1.5 1.7 2.7 7.9** -2.1 Italy -0.1 2.7 -4.2 -1.2 3.0 -9.1 30.5*** 48.6*** 16.1** Latvia -5.0*** -0.9 -6.5*** 1.8* 2.0 1.6 -0.8 -1.7 -0.1 Lithuania -2.0 3.7 -4.9 4.1 2.1 5.4 -7.1** -11.8** -3.2 Luxembourg -0.6 1.2 -1.6 0.8 0.3 1.3 -0.7 1.8 -2.6 Netherlands -0.4 -1.9 1.0 1.8* 0.8 2.6** 0.6 -2.9 3.7 Norway -25.1*** -26.3*** -23.2*** -0.3 0-0.8 1.5 3.2 0 Poland -35.4*** -39.8*** -28*** -3.5** -2.9* -4.4 -1.2 -4.0 2.4 Portugal -7.7*** -7.4*** -8.0*** 2.8*** 5.6*** 0.1 0.5 0.5 0.6 Romania 0.7 -14.5 22.0 0*** 0*** 0*** -1.2 0*** -8.4 Serbia -3.1* -2.3 -3.9* -0.8 -0.7 0.1 -0.7 -0.3 0.8 Slovakia 10.7* 8.1 13.4 01.7 -4.3 13.5* 40.0** -4.2 Slovenia 1.9 -5.1* 9.3*** 1.7* -0.2 2.9** -2.0 -2.9 -1.9 Spain -1.5 -4.1 1.2 1.1 2.5 -1.0 -1.7 -1.3 -1.6 Sweden 5.3*** 4.5** 5.8*** 0.6 1.7 -0.8 1.9 2.7 0.5 Switzerland 6.3*** 8.2*** 4.7** 1.4* 1.6 1.2 0.3 3.6* -2.5 Europe -7.1*** -9.0*** -5.4*** 1.5*** 1.8** 1.1** 1.8*** 2.7*** 0.8 Rest of the world 51 ILO Working Paper 141 Country Labour force participation Unemployment Wage employment All Men Women All Men Women All Men Women Australia -0.7 0.1 -1.6 -0.5 0.7 -2.2** 0 0 0.4 United States -2.6*** -2.3*** -2.9*** 0.8*** 1.1*** 0.5*** 0.9*** 0.6*** 1.2*** All countries -6.7*** -8.3*** -5.2*** 1.4*** 1.8** 0.9** 1.6*** 2.4*** 0.8* Note 1: This table was prepared using our second working definition of a “second-generation migrant”, that is, where a native-born individual has a foreign-born father (see section 2.1). Note 2: ***, ** and * indicate that the result is statistically different from zero at the 1%, 5% and 10% level of significance, respectively. Note 3: The results for labour force participation refer to the whole working-age population. Those for unemployment refer to the population in the labour force. Those for status in employment (wage employment versus self-employment) refer to the employed population. Note 4: The labour force participation and unemployment models control for age and education. The model used to analyse status in employment (wage employment versus self employment) features occupational category as an additional control. Source: Analysis based on ILO Harmonized Microdata collection (ILOSTAT), 2022 or the latest available year. See table A1 for more details. 52 ILO Working Paper 141 XTable A3. Effect of being a second-generation migrant on monthly wages (percentage) Country All Men Women Europe Austria -1.2 -0.4 0.2 Belgium -9.3** -9.2 -11.5* Bulgaria -16.9 26.5 -31.9 Croatia 3.9 -0.2 4.6 Cyprus -3.0 10.4 -26.5 Czechia -3.2 -1.3 -6.4 Denmark 2.3 3.3 -0.3 Estonia -10.5** -7.3 -13.3** Finland 1.6 0.6 -2.5 France 2.6 5.1 0.1 Germany 2.0 1.9 -0.8 Greece 2.0 -8.1 15.3 Hungary 6.5 -1.6 16.2 Ireland -5.2 -20.8** 9.2 Italy 2.9 12.4 -9.7 Latvia -2.6 -2.0 -2.5 Lithuania 7.4 9.7 6.5 Luxembourg -6.4 -9.9 -3.0 Netherlands 0.1 -5.3 4.5 Poland 3.7 -0.5 8.1* Portugal -5.3* -1.1 -11.4** Serbia 4.6 2.5 4.4 Slovakia -5.7 -13.1** 2.2 Slovenia -0.7 -4.8 5.6 Spain -6.0 -8.3 -3.5 Sweden -0.6 -1.3 -1.5 Switzerland 9.1*** 0.1 10.1** Europe -4.4*** -6.6*** -2.8** Rest of the world Australia -0.1 -4.0 1.9 United States 4.9*** 1.0 8.0*** All countries -3.7*** -6.0*** -2.0 Note: ***, ** and * indicate that the result is statistically different from zero at the 1%, 5% and 10% level of significance, respectively. Source: Analysis based on ILO Harmonized Microdata collection (ILOSTAT), 2022 or the latest available year. See table A1 for more details. 53 ILO Working Paper 141 XTable A4. Effect of being a second-generation migrant (based on alternative definition) on hourly wages (percentage) Country All Men Women Europe Austria -3.2 -4.6* -0.4 Belgium -6.6** -4.6 -9.5*** Bulgaria 36.6*** 39.5*** 15.5 Croatia -4.4 -21.7*** 13.9*** Cyprus -1.4 -6.5 -3.5 Czechia 1.1 -4.2 7.0* Denmark -4.9* -8.6** -1.1 Estonia -9.8** -8.0 -10.9** Finland 11.3 -9.6 44.1 France 0.9 1.0 1.4 Germany 0.9 2.8 -2.0 Greece 4.9 8.1 -3.4 Hungary 3.3 -2.6 10.3 Ireland -4.1 -9.0 0.9 Italy -12.0 10.9 -37.1 Latvia -2.7 2.1 -7.9*** Lithuania 3.9 -8.3 13.4* Luxembourg -10.9** -16.0** -2.6 Netherlands -1.4 -2.0 0.2 Poland 1.1 4.3 -1.6 Portugal -3.6 1.2 -8.2 Serbia 8.2** 6.0 6.4 Slovakia 2.3 3.6 -17.2* Slovenia 2.6 4.1 2.9 Spain 6.2 8.5 1.5 Sweden -5.7** -9.6*** -2.0 Switzerland 1.4 1.1 0 Europe -4.7*** -5.6*** -3.6*** Rest of the world Australia -0.4 -1.5 0.1 United States 3.7*** 1.0 6.5*** 60 ILO Working Paper 141 Chiswick, Barry R. 1977. “Sons of Immigrants: Are They at an Earnings Disadvantage?” The American Economic Review 67 (1): 376–380. https://www.jstor.org/stable/1815933. 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Winkler, Anne. 2016. “Women’s Labor Force Participation”, IZA World of Labor, No. 289. https:// doi.org/10.15185/izawol.289. 65 ILO Working Paper 141 Acknowledgements We are grateful to Fabiola Mieres, Anil Duman, Tahmina Karimova, Catherine Saget, and Caroline Fredrickson for their thoughtful comments and valuable insights, which significantly enriched this paper. Research Department (RESEARCH) International Labour Organization Route des Morillons 4 1211 Geneva 22 Switzerland T +41 22 799 6530 resear[email protected] www.ilo.org/research XAdvancing social justice, promoting decent work The International Labour Organization is the United Nations agency for the world of work. We bring together governments, employers and workers to improve the working lives of all people, driving a human-centred approach to the future of work through employment creation, rights at work, social protection and social dialogue. I S B N 9789220421710 9HSTCMA*ecbhba+ 9 789220 421710 Contact details