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We further use the ESS data to investigate whether TCNs are different from EU nationals in terms of ‘life quality’. Figure 17 presents the results; as in the previous analysis, we control for gender, age, education, country of residence and year of the survey.

Figure 17. Conditional differences in life quality between third-country nationals and mobile EU citizens (nationals, referred to as ‘native population’ in the text, is a reference group)

Source: Authors own calculations, 2018 using ESS, 2002-2016 waves.

made use of the EU-SweLC data (ilc_di01 dataset, Eurostat) on income distribution and computed the difference between the 5th and 4th income percentiles in the EU.

Note: Statistically significant results are in boldface. The sample includes respondents aged 20-55 living in an EU Member State in the years of survey. Numbers below column titles show the average of an outcome for the native population (nationals of their country of residence). All reported differences are conditional on gender, age group, education, country of residence and interview year. In the data, we cannot directly observe nationality of respondents, but know if an individual is a national of the country of residence. If an individual is not national of his/her country of residence, we proxy his/her nationality by the country of birth. Corresponding table: Annex 5: Table 30.

The results give a somewhat mixed picture. For instance, TCNs report lower health380 _{and lower} happiness than mobile EU nationals, however, these differences are very small in magnitude and not statistically significant. There are, however, striking differences between TCNs and EU nationals in terms of self-reported experiences of discrimination. Men TCNs are 18 percentage points more likely to feel discriminated than both the native population and mobile EU nationals. Women TCNs are almost 15 percentage points more likely to report discrimination than native women (9 percentage points more likely if compared to similar mobile EU women). Moreover, the difference in perceived discrimination does not significantly decrease when the sample is limited to employed individuals. While perceived discrimination is a self-reported indicator, such great differences, particularly among workers and potential workers, are alarming. For instance, the recent FRA MIDIS II study highlighted recurrent experiences of discrimination where? of whom? (See Chapter 4). In addition, the tolerance to unequal treatment of employees and a lack of sensitivity to discrimination observed in Chapter 4 indicate the complex social configuration of this phenomenon, which often takes the form of indirect and intersectional discrimination.381

The potential economic impact of discrimination was thoroughly analysed in the comprehensive European Parliament (EPRS) Study on the Cost of Non-Europe in the area of Equality and the Fight against Racism and Xenophobia.382 _{Annex 17 summarizes the available evidence on discrimination of} immigrants in the labour market (see Box 4 in Annex 8 of this Research Paper). While the presented evidence relates more generally to discrimination against immigrants (who can be defined either by country of birth, ethnic background or nationality), the policy implications are important for defining EU legal migration policies toward TCNs. Specicially, wage discrimination against vulnerable groups can be influenced by institutional factors such as or instance collective wage bargaining could diminish wage discrimination against immigrants, while higher accessibility to trade unions and professional organisations for immigrants may improve awareness of their rights.

5.1.4. Differences in intra-EU mobility

Lastly, we investigate to what extent TCNs are different from the EU nationals in terms of their intra- EU mobility.383 _{While EU nationals enjoy free labour mobility within the EU, TCNs face a number of} legal barriers, which increase their intra-EU mobility costs. For the purpose of this analysis, we define intra-EU mobility as including situations when an EU national a) lived in a different EU Member State one year before the survey; b) currently resides and works in two different EU Member States.

As Figure 18 shows, TCNs indeed have lower intra-EU mobility rates compared to EU nationals with the same observable characteristics (age, gender, education and industry of work). These results might appear at odds with the work of Jauer et al., who find that TCNs and nationals of new EU Member

380 _{On average, foreign nationals report slightly better health than the native population. This reflects, however,} positive selection for migration: migrants tend to be in general healthier than non-migrants.

381 _{FRA (2017).}

382 _{Fachathaler et al. (2018).}

383 _{In contrast to previous analysis, we do not distinguish here between the native population and mobile EU} nationals.

States were more likely to be mobile during the 2008-09 crisis than the native population (nationals) of Eurozone countries.384 _{Although the results of Jauer et al. study are not directly comparable with Figure} 18,385 _{they are important as they show that mobility does represent an important adjustment mechanism} to economic shocks in the EU, including for TCNs.

Figure 18. Annual intra-EU mobility rates and conditional differences in intra-EU mobility between third-country nationals and EU nationals

Source: Authors own calculations, 2018, using EU LFS, 2008 and 2014 waves.

Note: Statistically significant results are in boldface. The sample includes respondents aged 20-55 living in an EU Member State in the years of survey. Annual intra-EU mobility rate represents the likelihood that a given individual either resided in another EU Member State one year before the survey or currently works in an EU Member State different the reported country of residence. All reported differences are conditional on gender, age group, education, industry of work, countries of residence (current and one year ago) interacted with time effects. Corresponding table: Annex 5: Table 31. While differences between TCNs and EU nationals are present for individuals of all skill groups, mobility of low- and medium-skilled individuals appears to be particularly constrained (relative to the average mobility rate within these skill groups). Hypothetically, were the gaps fully eliminated, it would mean additional 11,000 low-skilled, 15,000 medium-skilled and 8,000 highly skilled TCNs exercising intra-EU mobility in a given year.386

384 _{Jauer et al. (2018).}

385 _{First, Jauer et al. (2018) define mobility solely as a change of country of residence, whereas we use a broader} definition that defines individuals as mobile if they change a country of residence (only 27% of cases in our data) or work in a different Member State. Second, Jauer et al. (2018) can only observe aggregated net migration flows, whereas we can account for individual characteristics such as age, gender, education and industry of work, which are important determinants of mobility. Third, Jauer et al. (2018) focus on mobility during the crisis period when TCNs are often more likely to lose jobs than the native population and, hence, have lower opportunity costs of moving to another country.

386 _{These numbers are obtained by multiplying the total number of TCNs in each skill group by their respective} mobility gap. Data source on the population of TCNs: lfsa_pganws (Eurostat, 2018). Data source on education

The above results highlight that, relative to EU nationals, TCNs, on average, perform worse in the labour market, hold jobs of lower quality, report higher discrimination and are less mobile within the EU. The observed differences can be driven by multiple reasons. On the one hand, differences can arise due to still unobserved productivity factors: language skills, quality of obtained education, and country- specific work and social experience. Missing country-specific human capital can contribute to the concentration of TCNs in lower job positions and less well-paid occupations. On the other hand, TCNs experience legal gaps and barriers, linked to their administrative status, which often restrict the employment opportunities and bargaining power.

For instance, lower employment rates of TCNs can be associated with restricted access to the labour market, which appears to be particularly harsh on women TCNs. Lower quality of jobs (i.e. lower wage income, higher incidence of overqualification, shorter contract duration and fewer supervisory responsibilities) can be the consequence of insecure residence status, lower job and geographic mobility, and consequently lower bargaining power of TCNs. The presence of these gaps and barriers might also discourage TCNs from improving their human capital and ‘trap’ them in low-income jobs. The next section of this chapter aims at establishing causal links between legal gaps and barriers and outcomes of TCNs in the EU.