Focus on the 2015 inflow of refugees
5. A macro analysis to explain Belgium’s bad performance
5.3 Main results
The percentage of immigrants among the population is an indicator of the country’s history of migration but also its openness and the potential network effect for newcomers. Results for both labour market participation and employment (and also for men) show that while it seems statistically significant and positive for the total first‑generation immigrants, in line with the theory of the network effects, previous immigrants in the host country help newcomers to find a job or to be better integrated in general, when we focus on non‑EU immigrants the statement is no longer true. The coefficient remains statistically significant but becomes negative.
The more non‑EU immigrants present in the country, the higher the negative gap between them and natives in terms of labour market integration. Results, however, are not robust to the inclusion of a country fixed effect as all specifications provide non‑significant coefficients.
The personal characteristics of immigrants provide the expected signs, even though coefficients are not always statistically significant to the inclusion of country fixed effect, especially regarding non‑EU first‑generation immigrants.
If immigrants are more likely to be of working age than natives, they tend to integrate better into the labour market with a larger statistically significant positive impact for non‑EU immigrants (but not for men). The gender effect seems
1 As a robustness test, we also tested for country random effects which could be a better estimator for the inclusion of time‑invariant variables. We also test for the endogeneity of some variables, namely the percentage of immigrants in the population, EPL, public employment and MIPEX, by using lag values as instruments. The percentage of immigrants is obtained using the lag 5 and lag 10 values of the variable. When controlling for personal characteristics, the variable is found to be endogenous (better labour market integration of immigrants induces more inflows) and the instruments pass various tests. However, once we include the unemployment rate in the regression the variable is no longer endogenous, the phenomenon being captured by the unemployment variable (a more prosperous economic environment brings more immigrants). EPL and public employment are obtained using lag 1 and 2, which are always found to be endogenous and the instruments pass the tests. MIPEX indicators are also obtained using lag 1 and 2 but the results show that those variables are not endogenous. All estimated regressions can be found in annex II.5.
very limited with almost always non‑significant impact for non‑EU immigrants (both total and men) and a statistically significant positive impact of being more likely to be men for total immigrants in OLS and YFE specifications.
The educational level of immigrants also plays a significant role. If the percentage of high-educated immigrants exceeds that of natives, the gaps between them tend to decrease in terms of both employment and participation.
However, focusing on non‑EU immigrants only, the positive effect is more limited and shows insignificant results when considering country fixed effects. Since our dataset is based on self‑reported level of education, the diploma recognition can partly explain this less robust finding for non‑EU immigrants. Conversely, if first‑
generation immigrants are more likely to be low educated than natives then the effect is negative, meaning that the negative gaps widen. Nevertheless, this detrimental effect is smaller for men, and particularly for non‑
EU immigrant men where it becomes insignificant. The potential explanation could be that they are more active in low‑skilled sectors and are more inclined to accept lower wages than natives. This increases their chance of getting a job compared to natives.
The economic environment does not seem to play a significant role to explain the integration of immigrants into the labour market compared to natives. The lag of the unemployment rate is insignificant in all specifications, except for total immigrants where the coefficient is slightly significant (at 90 %) and negative (YFE, CFE and CYFE specifications). The hypothesis of higher sensitivity to the economic environment is thus not verified here.
Given the restricted access to the public sector and the predominance of natives in this sector, countries with a higher share of public employment could also show greater discrepancies between immigrants and natives.
While this is not the case for the regression on total first‑generation immigrants, the results are negative and significant for non‑EU immigrants, even after controlling for country fixed effects. However, the findings are less robust for men, which could imply that the effect is more detrimental to women. Restricted access to the public sector could have a negative influence on the integration of immigrant women, whereas it is a major sector of employment for native women (usually seen as a sector allowing for an easier combination between work and family life). Unrestricted access to the public sector could thus be potentially more beneficial for immigrant women.
As previously mentioned, self-employment can be viewed as a way to avoid the difficulties of finding a salaried job. However, results highlight detrimental impact instead. While coefficients are statistically significant and positive for labour market participation of men, the effect becomes insignificant for them in terms of employment. Furthermore, having a higher share of self‑employed within the country is even detrimental to immigrant employment (including non‑EU immigrants). Since we control for specific policies in terms of access to self‑employment (MIPEX and ALMP measures), the analysis shows that it is not really the country’s more pronounced entrepreneurship culture that matters, but more the easing of access to this type of jobs. Moreover, if there are already many self‑employed workers in the country, that could become an obstacle as the sector is more crowded.
Regarding employment protection on regular contracts, our findings support the view expressed by Sa (2011) and Bisin et al. (2011) that a higher level of protection reduces the gap in labour market integration between immigrants and natives. Immigrants, usually less aware of employment protection regulations, are thus also less likely to claim their rights, and this makes it cheaper for employers to hire immigrants than to hire natives. In our estimations, this is particularly true for non‑EU immigrants who are more positively impacted when employment protection on regular contracts increases. They are probably more likely to accept temporary contracts, which become more spread over the labour market as the regulation becomes too strict for regular contract, than natives.
Table 2
Econometric results for employment gap between (non‑EU) immigrants and natives
Total first‑generation immigrants Non‑EU first‑generation immigrants
OLS YFE CFE CYFE OLS YFE CFE CYFE
Share among population 0.22*** Unemployment rate t − 1 −0.10
(0.11) −0.15* ALMP measures (in % of GDP) −5.02***
(0.00) −5.07***
Sources : Eurostat (LFS), EC, MIPEX, OECD, Visser, NBB calculations.
Note : (standard errors), * significant at 90 %, ** significant at 95 %, *** significant at 99 %.
Table 2 (continued)
Econometric results for employment gap between (non‑EU) immigrants and natives
Total first‑generation immigrants Non‑EU first‑generation immigrants
OLS YFE CFE CYFE OLS YFE CFE CYFE
MIPEX
Observations 276 276 276 276 248 248 248 248
R‑squared 0.89 0.89 0.61 0.65 0.92 0.92 0.54 0.61
Number of countries 24 24 24 24 23 23 23 23
Number of years 13 13 13 13 13 13 13 13
Sources : Eurostat (LFS), EC, MIPEX, OECD, Visser, NBB calculations.
Note : (standard errors), * significant at 90 %, ** significant at 95 %, *** significant at 99 %.
Table 3
Econometric results for participation gap between (non‑EU) immigrants and natives
Total first‑generation immigrants Non‑EU first‑generation immigrants
OLS YFE CFE CYFE OLS YFE CFE CYFE
Share among population 0.24*** ALMP measures (in % of GDP) −4.02***
(0.01) −4.24***
Sources : Eurostat (LFS), EC, MIPEX, OECD, Visser, NBB calculations.
Note : (standard errors), * significant at 90 %, ** significant at 95 %, *** significant at 99 %.
Table 3 (continued)
Econometric results for participation gap between (non‑EU) immigrants and natives
Total first‑generation immigrants Non‑EU first‑generation immigrants
OLS YFE CFE CYFE OLS YFE CFE CYFE
MIPEX
Observations 276 276 276 276 248 248 248 248
R‑squared 0.84 0.85 0.61 0.66 0.92 0.92 0.49 0.61
Number of countries 24 24 24 24 23 23 23 23
Number of years 13 13 13 13 13 13 13 13
Sources : Eurostat (LFS), EC, MIPEX, OECD, Visser, NBB calculations.
Note : (standard errors), * significant at 90 %, ** significant at 95 %, *** significant at 99 %.
Table 4
Econometric results for employment gap between (non‑EU) immigrants and natives – specific analysis for men
Total first‑generation immigrants men Non‑EU first‑generation immigrants men
OLS YFE CFE CYFE OLS YFE CFE CYFE
Share among population 0.26*** Unemployment rate t − 1 −0.12
(0.12) −0.14 ALMP measures (in % of GDP) −5.42***
(0.00) −5.52***
Sources : Eurostat (LFS), EC, MIPEX, OECD, Visser, NBB calculations.
Note : (standard errors), * significant at 90 %, ** significant at 95 %, *** significant at 99 %.
Table 4 (continued)
Econometric results for employment gap between (non‑EU) immigrants and natives – specific analysis for men
Total first‑generation immigrants men Non‑EU first‑generation immigrants men
OLS YFE CFE CYFE OLS YFE CFE CYFE
MIPEX
Observations 257 257 257 257 231 231 231 231
R‑squared 0.85 0.86 0.47 0.50 0.87 0.88 0.43 0.48
Number of countries 22 22 22 22 21 21 21 21
Number of years 13 13 13 13 13 13 13 13
Sources : Eurostat (LFS), EC, MIPEX, OECD, Visser, NBB calculations.
Note : (standard errors), * significant at 90 %, ** significant at 95 %, *** significant at 99 %.
Table 5
Econometric results for participation gap between (non‑EU) immigrants and natives – specific analysis for men
Total first‑generation immigrants men Non‑EU first‑generation immigrants men
OLS YFE CFE CYFE OLS YFE CFE CYFE
Share among population 0.25*** ALMP measures (in % of GDP) −4.11***
(0.01) −3.74**
Sources : Eurostat (LFS), EC, MIPEX, OECD, Visser, NBB calculations.
Note : (standard errors), * significant at 90 %, ** significant at 95 %, *** significant at 99 %.
Table 5 (continued)
Econometric results for participation gap between (non‑EU) immigrants and natives – specific analysis for men
Total first‑generation immigrants men Non‑EU first‑generation immigrants men
OLS YFE CFE CYFE OLS YFE CFE CYFE
MIPEX
Observations 257 257 257 257 231 231 231 231
R‑squared 0.84 0.85 0.35 0.46 0.91 0.91 0.32 0.43
Number of countries 22 22 22 22 21 21 21 21
Number of years 13 13 13 13 13 13 13 13
Sources : Eurostat (LFS), EC, MIPEX, OECD, Visser, NBB calculations.
Note : (standard errors), * significant at 90 %, ** significant at 95 %, *** significant at 99 %.
Labour market rigidities 1 are also captured by the proportion of people working for the same employer for more than 10 years (‘job tenure’ in the regressions). In our analysis, we find that job tenure has a negative impact on employment and participation gaps (though it is not always significant). This is in line in the theory that, for a given segment of the economy, if the labour market is more rigid it decreases turnover and thus disadvantages outsiders 2 (where immigrants are over‑represented).
The negative impact of union density and the net replacement income rate in the event of unemployment, previously stated in the literature (see chapter 4), is verified in our own analysis. A higher level of union density favours insiders (employed workers who obtained a sustainable position at the labour market) as unions tend to protect established workers. It is thus detrimental to immigrants who are more often out of the labour market.
Moreover, a high replacement income in the event of unemployment increases the effect of the unemployment trap among immigrants (for those eligible for unemployment benefits), who are more often in low‑skilled and low‑paid jobs. Note also that the effect of the net income replacement rate is more pronounced for non‑EU immigrants, who are particularly over‑represented in low‑paid jobs (HCE, 2018).
The active labour market policy (ALMP) measures provide interesting results since a higher percentage of GDP devoted to those activation policies seems to be detrimental to immigrants, and the effect is larger for non‑EU born individuals. The reasoning is that those types of policies rarely reach immigrants unless they specifically target them, whereas they are efficient for natives, who therefore benefit for them. Specifications including country fixed effects, however, provide insignificant results.
As highlighted by Bilgili et al. (2015), migrant integration policies may have a varying impact on different types of migrants ; this may make the analysis of the global impact irrelevant, so that controlling for immigrants’
personal characteristics may provide more robust results. MIPEX sub‑indicators, having not been updated since 2014, are almost time‑invariant. This makes the analysis including country fixed effects more complicated as cross‑country variation is entirely absorbed by the country fixed effect. As a result, few indicators keep a significant impact when controlling for other time‑invariant factors. The index update, planned at the end of this year, could help in that respect.
The labour market mobility results confirm our finding on ALMPs : regressions show a negative coefficient for all indicators except for targeted support, which is beneficial for the employment of non‑EU immigrants (in the OLS and YFE specifications, insignificant for the rest). While this type of policies can help migrants to increase their employment rate (see section 3.3), the effect is less pronounced than for natives so that the impact on the gap remains negative. This statement supposes that countries with more policies on labour market mobility for immigrants are also those with the same type of policies for natives. Finding similar results, Bredtmann and Otten (2013) emphasise that targeted employment policies must be suited to the country’s specific immigration populations and labour markets. Moreover, across all specifications and for all studied groups, the impact of workers’ rights is always statistically significant and negative. This finding highlights the somehow perverse effect of verifying if both natives and immigrants have the same rights in terms of work and social security access. The effect of being less informed about their rights disappear and with it the advantage of immigrant population with respect to natives.
Access to education is significantly positively associated with the labour market integration of immigrants compared to natives, and this result is true for all types of immigrants. Targeting needs is also beneficial even after controlling for country and year fixed effects. The positive impact disappears however when looking at
1 We also tested for minimum wage (using Visser database) as an explanatory factor in a bivariate estimation. Results (provided in annex II.5) show that the introduction of a minimum wage in the country reduces the gap between immigrants and natives, especially in terms of employment, and the effect is larger for non‑EU immigrants. When a minimum wage is implemented, natives are more likely to end up in the unemployment trap. Immigrants, however, who often do not have direct access to unemployment benefits, are more likely to accept low‑paid jobs. Nevertheless, for the multivariate analysis, we decided to drop the minimum wage variable from the regression. First of all, the presence of a minimum wage in a country is closely correlated with the degree of unionisation (66 %), and secondly, there are very few variations in the database within countries; it is therefore difficult to present conclusive results.
2 Unemployed workers with higher difficulties to get a new job.
employment of non‑EU immigrants. Non‑EU immigrants showing larger gaps compared to natives in terms of education and skills, perhaps because they cannot get recognition for their qualifications in the host country are more likely to be enrolled in education – and for longer periods – if access is made easier. In the short‑term this can keep them away from the labour market to upgrade their skills. Results on education are more robust in terms of labour market participation than regarding employment. While a larger access to education increases their willingness to be active, this does not necessarily translate in an easier access to jobs.
Analysis of permanent residence MIPEX scores confirms the argument that immigrants who enter the country to stay for a long period are more inclined to invest in human and cultural capital specific to the host country, and then to have higher employment and participation rates. Countries which facilitate access to permanent residence seem to have smaller gaps between immigrants and natives in terms of integration into the labour market. This is in line with the literature (see for example Bisin et al., 2011).
While family reunion provides similar results, the impact become insignificant when we include a country fixed effect and even significantly negative for total first‑generation immigrants. The argument on human capital could hold but allowing family reunion also induces a higher share of immigrants who potentially do not have adequate characteristics to enter the labour market (in comparison to immigrants coming for work who directly get their contract).
Access to nationality gives more ambiguous results, almost always not significant. This implies that it is not the access to nationality in itself which matters, but more the prospect of long‑term residence in the country.
Moreover, if restricted access to nationality implies a certain level of economic integration (as in Belgium with the 2013 reform), then immigrants could have a higher incentive to work in stricter countries
Anti-discrimination policies seem to be efficient in reducing labour market integration gaps between immigrants and natives on average. Coefficients when controlling for country and year fixed effects are statistically significant and positive for both employment and participation gaps. However, our analysis show that those policies do not significantly influence labour market outcomes of non‑EU immigrants. As for other policy indexes, they are potentially not enough targeted to specificities of immigrants. In fact, anti‑discrimination policies are often broader than discrimination against origin. Note also that some reverse causality could appear here. Anti‑discrimination policies might be started especially in countries and regions where discrimination is perceived to be high. Then this index might be correlated with the a priori importance of discrimination.