New results of the Labour Force Survey
Summary
Recently, a new demographic background variable was added to the Labour Force Survey (LFS) that is broader than the traditional variables on nationality and country of birth. This is the variable on the nationality of origin developed from population data, which provides more information on the diversity of the Belgian population.
This contribution zooms in on the labour market situation of eight different origin groups. In the first part, we outline the evolution of the traditional labour market indicators by origin group over a 20-year period, while the second part looks more closely at the economic sector and the type of job of the different origin groups.
While all origin categories have significantly improved both in terms of employment rate and activity rate, we still see large differences depending on the origin group. Overall, the labour market position of persons of EU origin is much more favourable than that of persons of non-EU origin. The origin group of countries from the EU13, i.e. the group of countries that most recently joined the EU, occupies a specific position with an activity and employment rate that has increased remarkably over the past 10 years or so.
Among persons of non-EU origin, the employment rate has significantly increased over a 20-year period, which means that the gap compared to the employment rate of persons of Belgian origin has also narrowed. Nevertheless, the gap among some specific origin groups such as North Africa, sub-Saharan Africa and EU candidate Member States (i.e. mainly Turkey) still remains quite large with differences ranging from 17.6 percentage points to 24.5 percentage points.
The unemployment rate has also evolved positively over the past two decades among each of the origin groups, both within and outside the EU. Yet, despite a halving of the indicator, the unemployment rate among persons originating from North Africa or sub-Saharan Africa remains high with rates exceeding 16%. Among persons originating from an EU candidate Member State, the unemployment rate has fallen more sharply, reaching the 10% level in 2022 But even here, the gap compared to persons of Belgian origin remains large.
Behind these overall figures lie large differences in evolution between the indicators of women and men and the gap between the two genders. A fairly general phenomenon that we observe in every origin group is the increased participation of women in the labour market, combined with the much lower unemployment rate that has caused the female employment rate to rise much more strongly than the male employment rate. Yet here too, we see large differences between origin groups within and outside the EU. While participation in the labour market (as expressed via the activity rate) of women aged 15-64 originating from North Africa or an EU candidate Member State did increase compared to 20 years ago, less than 40% of them on average are employed in the period 2020-2021-2022. Among women from sub-Saharan Africa, the situation is slightly better with 52.0% employed women.
Thanks to the new origin variable, for the first time we can now also start looking at how diverse different occupational groups and economic sectors are composed. For instance, persons with non-European origin appear to be much more likely to be employed as workers and are strongly underrepresented in government jobs. Persons of EU13 origin are more likely to be found in the construction sector and persons of Sub-Saharan African origin appear to be strongly overrepresented in the sector of human health and social work activities.
Statbel wishes to stress that this is an exploratory and descriptive analysis of data based on a sample. The wealth of possible explanatory variables present in the Labour Force Survey and the use of more sophisticated statistical models should allow for more insight into explanations of this complex reality. In this sense, therefore, we see this contribution rather as a starting point for more comprehensive analyses and further scientific research based on the LFS data.
You will find more details here below
Introduction: variable group of nationality of origin
To meet the increased need for numerical data to capture diversity in the labour market, a new variable was recently added to the Labour Force Survey (LFS) that provides more information on the origin of individuals. This variable ‘nationality of origin’ was developed by Statbel in 2021 based on the nationality data from the National Register. It takes into account not only one's own current nationality, but also the first registered nationality, as well as the first registered nationality of both parents. Compared to the existing ‘nationality’ and ‘country of birth’ variables, the new origin variable succeeds in capturing a larger group of persons of foreign origin. The new information on origin could be linked to the Labour Force Survey from the year 2003 onwards, providing a rich source of information on labour market evolutions of different origin groups over a 20-year period.
For more information on the concepts of ‘origin’ and ‘nationality of origin’, please see https://statbel.fgov.be/en/themes/population/structure-population/origin.[1]
Official population figures tell us that in 2022 about one third of the Belgian population has a foreign origin. Some 20 years ago, this share was less than one fifth (19.5%). We can therefore say that the Belgian population has become increasingly diverse over the years. In this contribution, we want to paint a picture of what the labour market situation looks like for some of the most common origin groups in Belgium.
In doing so, we use a classification into eight nationality groups whose size is sufficiently large to allow reliable statements to be made about them and which at the same time differ quite significantly in terms of their labour market position. In addition to the group of people of Belgian origin, we distinguish seven nationality groups of non-Belgian origin. The largest group is by far that of persons originating from one of the EU14 countries (excluding Belgium)[2]. The main countries of origin within this group are Italy, France and the Netherlands. Between 2003 and 2022, this EU14 origin group grew by 34%, currently accounting for 12.6% of the Belgian population.
A second category, called EU13, includes the other countries of the European Union. This group is mainly composed of persons originating from Romania, Poland and Bulgaria. This origin group has experienced tremendous growth over the past two decades, increasing more than fourfold from 2003 to 2022.
A third category includes countries of origin that in 2022 were candidate countries for EU membership. This origin group consists mainly of persons of Turkish origin and has increased by 77% over the past 2 decades, accounting for 2.5% of the current Belgian population in 2022[3].
The fourth group of ‘Other Europeans’ consists mostly of people originating from Russia or the ex-Soviet Union, or the United Kingdom. This group has also more than doubled over the past 20 years.
Furthermore, we distinguish two groups with African origins, namely the North African countries, which include the Maghreb countries, on the one hand, and the countries that make up Sub-Saharan Africa, on the other. Both groups have increased significantly in number. The group originating from North Africa increased by 110% between 2003 and 2022, making it the largest origin group in 2022, after the group from Belgium and the EU14. It accounts for 5.9% of the total Belgian population in 2022. This origin category consists mostly of people of Moroccan origin and also a much smaller proportion originating from Algeria or Tunisia. The group originating from Sub-Saharan Africa has also increased quite sharply by 262% and makes up around 3% of the Belgian population in 2022. The main nationalities of origin are Congo, Cameroon, Guinea and Rwanda.
Finally, there is a residual group ‘Other’ which is very diversely composed of different countries of Asia, North and South America and Oceania. Besides India and China, we also find several Middle Eastern countries of origin in this group in 2022, including Syria, Afghanistan and Iraq. There is also a fairly large group whose exact origin is undetermined or involves a country from the past that cannot be assigned to any of the existing eight origin groups in 2022 (mainly ex-Yugoslavia).
Table 1. Population figures per category of nationality of origin
| 2003 | 2022 | Evolution 2003-2022 | ||||
|---|---|---|---|---|---|---|
| N | % | N | % | N | % | |
| Belgium | 8,336,000 | 80,5% | 7,714,000 | 66,6% | -622,000 | -7.0% |
| EU14 (excl. Belgium) | 1,082,000 | 10,5% | 1,454,000 | 12,6% | +372,000 | +34.0% |
| EU13 | 79,000 | 0,8% | 366,000 | 3,2% | +287,000 | +363.0% |
| EU candidate | 166,000 | 1,6% | 294,000 | 2,5% | +128,000 | +77.0% |
| Other Europe | 64,000 | 0,6% | 150,000 | 1,3% | +86,000 | +134.0% |
| North Africa | 325,000 | 3,1% | 683,000 | 5,9% | +358,000 | +110.0% |
| Sub-Saharan Africa | 95,000 | 0,9% | 344,000 | 3,0% | +249,000 | +262.0% |
| Other | 208,000 | 2,0% | 579,000 | 5,0% | +371,000 | +178.0% |
| Total | 10,355,000 | 100% | 11,584,000 | 100% | +1,229,000 | +12.0% |
So this is the evolution of the figures in the total Belgian population, based on the figures from the ‘Origin’ section of the Statbel webpage. In what follows, we continue with results based on the Labour Force Survey and in particular the population within the age groups 15-64 (for the unemployment and activity rate) and 20-64 (for the employment rate). Despite the fact that the data are weighted and therefore presented as population numbers, it should be kept in mind that these are figures based on a sample survey. Sample data inevitably face biases and chance fluctuations. This is something that should be taken into account when interpreting the figures presented below. As more detail is presented, it means that the uncertainty margin around a figure inevitably also increases and that one should be cautious when comparing groups and evolutions.[4]
Nevertheless, a comparison of the distribution by origin group of the weighted LFS sample (Table 2) with the population distribution shows that the sample can be considered fairly representative and that most groups are fairly well represented in the results. Besides the weighted numbers, Table 2 also shows the effective sample numbers by origin category in the 2022 LFS sample.
Table 2. LFS figures 2022 per category of nationality of origin (weighted numbers and unweighted sample numbers)
| weighted sample numbers | Total sample | Sample 15-64 | ||
|---|---|---|---|---|
| N | % | N | % | |
| Belgium | 7,782,000 | 67.5% | 4,883,000 | 66.0% |
| EU14 (excl. Belgium) | 1,404,000 | 12.2% | 981,000 | 13.3% |
| EU13 | 355,000 | 3.1% | 248,000 | 3.4% |
| EU candidate | 278,000 | 2.4% | 190,000 | 2.6% |
| Other Europe | 154,000 | 1.3% | 103,000 | 1.4% |
| North Africa | 670,000 | 5.8% | 430,000 | 5.8% |
| Sub-Saharan Africa | 316,000 | 2.7% | 207,000 | 2.8% |
| Other | 500,000 | 4.3% | 332,000 | 4.5% |
| Missing | 62,000 | 0.5% | 22,000 | 0.3% |
| Total | 11,521,000 | 100% | 7,396,000 | 100% |
| unweighted sample numbers | Total sample | Sample 15-64 | ||
|---|---|---|---|---|
| N | % | N | % | |
| Belgium | 85,061 | 68.7% | 53,161 | 67.4% |
| EU14 (excl. Belgium) | 15,687 | 12.7% | 10,799 | 13.7% |
| EU13 | 3,196 | 2.6% | 2,282 | 2.9% |
| EU candidate | 2,545 | 2.1% | 1,719 | 2.2% |
| Other Europe | 1,592 | 1.3% | 1,042 | 1.3% |
| North Africa | 6,832 | 5.5% | 4,304 | 5.5% |
| Sub-Saharan Africa | 3,110 | 2.5% | 2,014 | 2.6% |
| Other | 5,092 | 4.1% | 3,303 | 4.2% |
| Missing | 719 | 0.6% | 270 | 0.3% |
| Total | 123,834 | 100% | 78,894 | 100% |
Labour market indicators
Employment rate
A first important labour market indicator is the employment rate of people aged 20-64. In Chart 1, we show the evolution for the various origin groups. While the official Belgian employment rate has increased over the past 20 years from 64.7% in 2003 to 71.9% in 2022, not all origin groups followed the same trend . So we see a rather different evolution for persons originating from the EU13 on the one hand and from the EU14 on the other. Whereas some 20 years ago the employment rate of persons of EU13 origin was still far below the employment rate of persons of Belgian origin, the gap has almost completely closed since 2016. Among the group with EU14 origin, however, the rate remains around 5 percentage points lower than the rate of persons of Belgian origin.
At the bottom of the chart we see the employment rate of persons of North African origin, which has evolved from 40.5% in 2003 to 51.3% in 2022, but the gap with the employment rate of persons of Belgian origin remains large. In 2003, it was 26.8 percentage points and in 2022 it has barely fallen to 24.5 percentage points, or a 9% decrease. A similar picture can be seen in the group of persons originating from one of the countries of Sub-Saharan Africa. The employment rate among this group evolved from 43.0% in 2003 to 54.3% in 2022, while the gap with the Belgian figure fell only slightly by 11%. In the intervening years, however, we see periods where the gap was significantly smaller. Overall, we see larger fluctuations, which may be related to the rather limited sample numbers for this origin group. This also applies to the group of EU candidate countries which, as mentioned above, is largely made up of people of Turkish nationality of origin. Over a 20-year period, the employment rate evolved favourably from 38.6% in 2003 to 58.2% in 2022. This represents a 51% increase, which is the most significant increase among all origin groups. However, given the relatively small sample numbers, we should be cautious about drawing conclusions based on the year 2022 alone. It remains to be seen whether we will also see this effect in the figures of the coming years. But even if we take into account a possible overestimation of the figure, the sharp increase in the employment rate among people originating from an EU candidate country ensures that, although the gap with people of Belgian origin has fallen sharply, with a difference of 17.6 percentage points, it still remains quite large in 2022.
The residual group of other Europeans, which is relatively small and composed mainly of persons from Russia or the ex-Soviet Union on the one hand and the United Kingdom on the other, has an employment rate about 10 percentage points lower than that of persons of Belgian origin. Finally, there is the rather heterogeneous group of other, non-European countries, for which the employment rate in 2022, 61.5%, is also significantly below that of persons of Belgian origin.
| Employment rate | Belgium | EU14 (excl. Belgium) | EU13 | EU candidate | Other Europe | North Africa | Sub-Saharan Africa | Other |
|---|---|---|---|---|---|---|---|---|
| 2003 | 67.3% | 61.2% | 57.1% | 38.6% | 56.4% | 40.5% | 43.0% | 51.2% |
| 2022 | 75.8% | 70.9% | 76.4% | 58.2% | 65.6% | 51.3% | 54.3% | 61.5% |
| Evolution (in %) | +13.0% | +16.0% | +34.0% | +51.0% | +16.0% | +27.0% | +26.0% | +20.0% |
| Gap with BE (in pp) | ||||||||
| 2003 | -6.1 | -10.2 | -28.7 | -10.9 | -26.8 | -24.3 | -16.1 | |
| 2022 | -4.9 | +0.6 | -17.6 | -10.2 | -24.5 | -21.5 | -14.3 | |
| Gap evolution (in %) | -20.0% | -106.0% | -39.0% | -6.0% | -9.0% | -11.0% | -11.0% | |
Unemployment rate
Chart 2 shows the evolution of the unemployment rate of people aged 15 to 64, by origin group over the past 20 years. In this period, the official Belgian figure has decreased from 8.2% in 2003 to 5.6% in 2022. Overall, we see that the unemployment rate has sharply decreased in each of the eight origin groups. The largest decreases are logically seen among the groups where the unemployment rate was very high at the beginning of the period, notably the group of persons of sub-Saharan African origin, where the unemployment rate was still 32.3% in 2003, and the group of persons of North African origin, which had an unemployment rate of 30.4% in 2003. The unemployment rate was also very high at 28.2% among persons originating from an EU candidate country. In each of these three origin groups, the unemployment rate has fallen sharply over a 20-year period by 42% (Sub-Saharan Africa), 46% (North Africa) and even 64% for persons originating from an EU candidate country, respectively. In 2022, we see the highest unemployment rate among persons of Sub-Saharan African origin and those of North African origin: 18.6% and 16.4%, respectively.
The group of people originating from an EU candidate country has been in the middle of the scale in terms of unemployment rate for about 10 years. In 2022, it is 10.0%, hardly different from the group with another European origin (9.4%), or the residual category originating from another non-European country (10.8%).
The lowest unemployment rates are recorded among people of Belgian origin. Over the past 20 years, this rate went from 6.2% to 3.8% in 2022. Until 2015, we saw that the unemployment rate of the group of persons of EU14 origin was closest to the rate of the group of Belgian origin, but since 2016 we see a remarkably favourable evolution in the group of EU13 origin. As we mentioned earlier that the employment rate in this group rose sharply from 2016 onwards, we see that during the same period the unemployment rate fell sharply.
| Unemployment rate | Belgium | EU14 (excl. Belgium) | EU13 | EU candidate | Other Europe | North Africa | Sub-Saharan Africa | Other |
|---|---|---|---|---|---|---|---|---|
| 2003 | 6.2% | 12.4% | 12.9% | 28.2% | 14.4% | 30.4% | 32.3% | 18.9% |
| 2022 | 3.8% | 6.4% | 5.0% | 10.0% | 9.4% | 16.4% | 18.6% | 10.8% |
| Evolution (in %) | -38.0% | -48.0% | -61.0% | -64.0% | -34.0% | -46.0% | -42.0% | -43.0% |
| Gap with BE (in pp) | ||||||||
| 2003 | +6.2 | +6.8 | +22.0 | +8.2 | +24.3 | +26.2 | +12.7 | |
| 2022 | +2.6 | +1.2 | +6.2 | +5.6 | +12.6 | +14.8 | +6.9 | |
| Gap evolution (in %) | -58.0% | -83.0% | -72.0% | -32.0% | -48.0% | -44.0% | -46.0% | |
Economic activity rate
A final important labour market indicator that we will discuss here is the economic activity rate, which gives a picture of the extent to which the population of working age actually enters or wishes to enter the labour market. In other words, this is a good indicator for the participation in the labour market, whether as employed or unemployed.
Chart 3 broadly follows the trends we also saw in the chart on the employment rate, but there are some notable differences. While persons of Belgian origin recorded the highest employment rate over almost the entire period from 2003 to 2022, this is not the case for the economic activity rate. Since 2010, the group coming from an EU13 country has had the highest activity rate, with a figure fluctuating between 72% and 77%. Especially in the period 2010-2019, the economic activity rate was thus always a few percentage points above the rate for people of Belgian origin. There, over the past 20 years, we see a steady increase from 66.5% in 2003 to 73.8% in 2022, the highest level ever.
At the bottom of the chart, we see that the lines of persons of North African origin and persons from an EU candidate Member State are quite similar. In the initial period of the chart, however, the economic activity rate of the EU candidate group was always a few percentage points below that of the group of North African origin. Since 2012, the curves have been more similar, and notable here too is the sharp increase over the past year among persons from EU candidate countries, bringing the economic activity rate to 59.6% in 2022 compared to 53.5% among persons of North African origin. As with the employment rate, we should note here that we should be cautious about such outliers, given the relatively small sample numbers in some origin categories. We should mainly wait and see whether this sharply increased activity rate among persons with origins in an EU candidate country is confirmed in the coming years.
As far as persons with origin from Sub-Saharan Africa are concerned, we see that the economic activity rate over the period 2003-2022 was almost always higher than that of the 'North Africa' and 'EU candidate Member State' origin groups, on average about 5 percentage points, with the exception of a number of year groups and in particular the year 2022, where the 'EU candidate Member State' group records a slightly higher activity rate at 59.6% than the group with origin from Sub-Saharan Africa (57.9%). Overall, the economic activity rate in the latter origin group evolved only slightly. Between the level of 2003 and 2022, we see an evolution of only 2%, which is much lower than all other origin groups.
As with the employment rate, we find the highest activity rates among groups originating from the EU. One difference with the employment rate, however, is that since 2010 it is not the group of people of Belgian origin that records the highest economic activity rate, but rather the group of people of EU13 origin. In 2022, although the figure for Belgium was again just slightly higher, the chart clearly shows that the activity rate for persons of EU13 origin was always a few percentage points higher during the period before. Both figures hover around 73.5% in 2022. Whereas the group with an EU13 origin is doing at least as well as the group of Belgian origin in terms of activity rate, this is not the case for the group with an EU14 origin. As with the employment rate, the activity rate over the entire period of the past 20 years is on average 3 to 5 percentage points lower than the Belgian origin group. Moreover, it should be noted that the gap with persons of Belgian origin has actually widened, something we also observe for both African origin groups. For persons of North African origin, the gap increased from 15.9 percentage points in 2003 to 20.3 percentage points in 2022 (+28%) and for persons of Sub-Saharan African origin, the gap evolved from 9.5 percentage points to 15.9 percentage points (+67%).
| Economic activity rate | Belgium | EU14 (excl. Belgium) | EU13 | EU candidate | Other Europe | North Africa | Sub-Saharan Africa | Other |
|---|---|---|---|---|---|---|---|---|
| 2003 | 66.5% | 63.4% | 60.6% | 47.0% | 59.6% | 50.6% | 57.0% | 55.6% |
| 2022 | 73.8% | 69.1% | 73.4% | 59.6% | 65.8% | 53.5% | 57.9% | 62.5% |
| Evolution (in %) | +11.0% | +9.0% | +21.0% | +27.0% | +10.0% | +6.0% | +2.0% | +12.0% |
| Gap with BE (in pp) | ||||||||
| 2003 | -3.1 | -5.9 | -19.5 | -6.8 | -15.9 | -9.5 | -10.8 | |
| 2022 | -4.7 | -0.4 | -14.1 | -7.9 | -20.3 | -15.9 | -11.3 | |
| Gap evolution (in %) | +50.0% | -93.0% | -27.0% | +16.0% | +28.0% | +67.0% | +4.0% | |
Labour market situation of women with a foreign origin
Women's participation in the labour market in Belgium has significantly evolved over the past two decades. According to the official LFS annual figures, women's economic activity rate evolved from 56.8% in 2003 to 66.8% in 2022, while among men we saw only a slight increase, from 72.9% to 74.2% over the same period. The gap between men and women has therefore significantly narrowed, something we also see in the employment rate and the unemployment rate. In terms of unemployment rate, women are even doing slightly better than men in recent years, as shown in the 2022 figures recently published by Statbel.
To check whether the labour market situation of men and women in Belgium evolved differently depending on the origin over the past 20 years or so, Table 3 compares the 2003-2004-2005 period on the one hand and the 2020-2021-2022 period on the other. By taking three years together, despite the more detailed breakdown of the figures by gender, we still retain sufficiently large samples and thus limit the margin of error. Consequently, the figures presented here are not equal to the official annual figures, but represent averages over three years.
In each origin group, we see proportionally a stronger increase in the female activity rate than in the male activity rate over the past 20 years or so, thus narrowing the gap between men and women. However, there are large differences in the extent to which this gap has narrowed. The largest decrease in the gap is seen among people of Belgian origin. There, the difference in activity rate between men and women is still only 5.0 percentage points for the period 2020-2021-2022, whereas just under 20 years earlier the gap was 14.2 percentage points, i.e. a fall of 65%.
Strong decreases in the gender gap are also seen in the ‘other Europeans’ group (-53%), in the group with origin from EU14 (-46%), in the group with sub-Saharan African origin (-45%) and in the group originating from the EU13 (-31%). The gap in activity rates between men and women is less than 10 percentage points in each of these groups. What is remarkable is that the economic activity rate of men with EU13 origin (79.1%) exceeds that of men with Belgian origin (75.4%).
Interestingly, the groups where the gap between men and women was the largest in the period 2003-2004-2005 are also the groups where the gap has decreased the least over a 20-year period. This means that even in 2020-2021-2022, we still see large differences between male and female activity rates among persons of North African origin (24.7 percentage points in 2020-2021-2022) and persons from an EU candidate country (25.0 percentage points in 2020-2021-2022). For both groups, the gender gap did decrease, but only by 17% (North Africa) and 22% (EU candidate) respectively. For the period 2020-2021-2022, the economic activity rate for women of North African origin stands at 39.4%, an increase of 8% compared to some 20 years ago. For women coming from an EU candidate country, the increase is greater (+25%) and the activity rate for the period 2020-2021-2022 is 41.2%.
Comparing these figures with the evolution of the employment rate, it is particularly striking that the employment rate among women has increased much more than the economic activity rate in these two origin groups, by 63% (EU candidate) and 38% (North Africa) respectively. This strong increase is the result of a combination of two effects, namely the higher participation of women in the labour market on the one hand and the sharp decrease in the female unemployment rate on the other. For men, unemployment falls in roughly equivalent proportions, but because the male activity rate remains rather stable, the increase in the employment rate is less spectacular for men than for women i.e. +18% (North Africa) and +17% (EU candidate) respectively.
This is a fairly general phenomenon that we also see among the other origin groups, namely the greater participation of women in the labour market (as expressed by the higher economic activity rate) combined with the sharply declining unemployment rate among women causes the female employment rate to increase much more than that of men. Nevertheless, there remains a big difference between, on the one hand, the groups of EU origin (either Belgium, EU14 or EU13) where the female employment rate for the period 2020-2021-2022 exceeds 65% and, on the other hand, the groups with origin in an EU candidate country and North Africa, where also in 2020-2021-2022 less than 40% of women are employed. Again, the explanation should be sought in both the lower labour market participation of women and the higher unemployment rate. For women of North African origin, this is even more true than for women with origin in an EU candidate country. As already shown above, the unemployment rate in the former group was noticeably higher than in the latter.
A different picture is seen among women of Sub-Saharan African origin. While we note the second highest unemployment rate in this group (16.6% among women), the higher activity rate (55.2%) does ensure that slightly more than half of women of Sub-Saharan African origin are employed in the period 2020-2021-2022. Thus, the percentage of women aged 20 to 64 that are employed among this origin group is more than 10 percentage points higher than among groups originating from North Africa or an EU candidate Member State. The gap in employment rates between men and women is also significantly smaller with a difference of 6.6 percentage points.
Table 3: Evolution of labour market indicators per gender
| Unemployment rate | 2003/2004/2005 | 2020/2021/2022 | Evolution | |
|---|---|---|---|---|
| Belgium | Man | 5.5% | 4.2% | -25.0% |
| Woman | 7.3% | 3.5% | -52.0% | |
| Gap M/W (in pp) | +1.7 | -0.7 | -140.0% | |
| EU14 (excl. Belgium) | Man | 10.8% | 7.2% | -34.0% |
| Woman | 13.5% | 7.1% | -48.0% | |
| Gap M/W (in pp) | +2.7 | -0.1 | -104.0% | |
| EU13 | Man | 13.1% | 7.3% | -44.0% |
| Woman | 16.6% | 7.2% | -57.0% | |
| Gap M/W (in pp) | +3.6 | -0.1 | -102.0% | |
| EU candidate | Man | 24.5% | 11.2% | -54.0% |
| Woman | 36.5% | 14.3% | -61.0% | |
| Gap M/W (in pp) | +11.9 | +3.1 | -74.0% | |
| Other Europe | Man | 9.1% | 8.8% | -3.0% |
| Woman | 15.8% | 13.3% | -16.0% | |
| Gap M/W (in pp) | +6.7 | +4.5 | -33.0% | |
| North Africa | Man | 30.3% | 16.4% | -46.0% |
| Woman | 34.9% | 17.6% | -50.0% | |
| Gap M/W (in pp) | +4.7 | +1.2 | -74.0% | |
| Sub-Saharan Africa | Man | 30.4% | 18.7% | -39.0% |
| Woman | 34.7% | 16.6% | -52.0% | |
| Gap M/W (in pp) | +4.3 | -2.0 | -147.0% | |
| Other | Man | 19.9% | 12.8% | -36.0% |
| Woman | 19.6% | 11.4% | -42.0% | |
| Gap M/W (in pp) | -0.3 | -1.4 | +367.0% | |
| Total | Man | 7.6% | 6.1% | -19.0% |
| Woman | 9.3% | 5.5% | -41.0% | |
| Gap M/W (in pp) | +1.7 | -0.6 | -137.0% | |
| Employment rate 20-64 | 2003/2004/2005 | 2020/2021/2022 | Evolution | |
| Belgium | Man | 76.0% | 77.3% | +2.0% |
| Woman | 60.2% | 72.5% | +20.0% | |
| Gap M/W (in pp) | -15.8 | -4.8 | -69.0% | |
| EU14 (excl. Belgium) | Man | 70.5% | 73.5% | +4.0% |
| Woman | 54.1% | 65.6% | +21.0% | |
| Gap M/W (in pp) | -16.5 | -7.9 | -52.0% | |
| EU13 | Man | 67.0% | 79.9% | +19.0% |
| Woman | 51.2% | 69.2% | +35.0% | |
| Gap M/W (in pp) | -15.8 | -10.7 | -32.0% | |
| EU candidate | Man | 55.4% | 64.7% | +17.0% |
| Woman | 23.8% | 38.8% | +63.0% | |
| Gap M/W (in pp) | -31.6 | -25.9 | -18.0% | |
| Other Europe | Man | 71.2% | 70.9% | -0.0% |
| Woman | 48.7% | 56.9% | +17.0% | |
| Gap M/W (in pp) | -22.5 | -14.0 | -38.0% | |
| North Africa | Man | 52.3% | 61.6% | +18.0% |
| Woman | 27.0% | 37.1% | +38.0% | |
| Gap M/W (in pp) | -25.3 | -24.4 | -3.0% | |
| Sub-Saharan Africa | Man | 52.5% | 58.7% | +12.0% |
| Woman | 37.0% | 52.0% | +41.0% | |
| Gap M/W (in pp) | -15.5 | -6.6 | -57.0% | |
| Other | Man | 61.5% | 66.5% | +8.0% |
| Woman | 43.7% | 52.5% | +20.0% | |
| Gap M/W (in pp) | -17.8 | -14.0 | -22.0% | |
| Total | Man | 73.8% | 74.8% | +1.0% |
| Woman | 57.4% | 67.0% | +17.0% | |
| Gap M/W (in pp) | -16.4 | -7.8 | -52.0% | |
| Economic activity rate 15-64 | 2003/2004/2005 | 2020/2021/2022 | Evolution | |
| Belgium | Man | 74.4% | 75.4% | +1.0% |
| Woman | 60.2% | 70.4% | +17.0% | |
| Gap M/W (in pp) | -14.2 | -5.0 | -65.0% | |
| EU14 (excl. Belgium) | Man | 71.5% | 71.9% | +1.0% |
| Woman | 56.7% | 63.9% | +13.0% | |
| Gap M/W (in pp) | -14.8 | -8.0 | -46.0% | |
| EU13 | Man | 71.0% | 79.1% | +11.0% |
| Woman | 57.3% | 69.7% | +22.0% | |
| Gap M/W (in pp) | -13.8 | -9.4 | -31.0% | |
| EU candidate | Man | 65.2% | 66.2% | +2.0% |
| Woman | 33.0% | 41.2% | +25.0% | |
| Gap M/W (in pp) | -32.2 | -25.0 | -22.0% | |
| Other Europe | Man | 71.9% | 69.8% | -3.0% |
| Woman | 52.3% | 60.5% | +16.0% | |
| Gap M/W (in pp) | -19.6 | -9.3 | -53.0% | |
| North Africa | Man | 66.3% | 64.2% | -3.0% |
| Woman | 36.4% | 39.4% | +8.0% | |
| Gap M/W (in pp) | -29.9 | -24.7 | -17.0% | |
| Sub-Saharan Africa | Man | 64.9% | 63.0% | -3.0% |
| Woman | 50.6% | 55.2% | +9.0% | |
| Gap M/W (in pp) | -14.2 | -7.8 | -45.0% | |
| Other | Man | 68.1% | 68.9% | +1.0% |
| Woman | 48.6% | 54.9% | +13.0% | |
| Gap M/W (in pp) | -19.5 | -14.1 | -28.0% | |
| Total | Man | 73.4% | 73.5% | +0.0% |
| Woman | 58.2% | 65.7% | +13.0% | |
| Gap M/W (in pp) | -15.2 | -7.8 | -49.0% | |
Employed population per nationality of origin
Professional status
After outlining the labour market situation of the various origin groups in the previous section, in this section we take a closer look at the working population. We get a first picture when we look at the professional status as it was asked in the survey. Here, we make a distinction between self-employed and salaried workers, with the latter group further divided into workers, employees and civil servants. Again, we look at average figures over the most recent three years.
Table 4 shows the distribution within each origin group across those four different statuses. By comparing the percentages horizontally, we get an idea of which nationality groups are over- or underrepresented compared to the population of Belgian origin. Thus, we see that the proportion of self-employed is significantly higher among people of EU13 origin. In this group, 19.2% work as self-employed, while this figure is 14.5% for persons of Belgian origin. Conversely, persons of North African and sub-Saharan African origin are underrepresented with 8.0% and 5.9% self-employed, respectively.
In turn, the share of civil servants is the highest among persons of Belgian (23.6%) or EU14 origin (21.6%). The lowest percentage of civil servants can be observed among people originating from an EU candidate Member State (11.4%).
We also see large differences in the share of workers and employees. Among people of Belgian or EU14 origin, we see the highest percentages of employees, followed by the categories of other European origin and Sub-Saharan African origin. The percentage of employees exceeds 40% in each of these groups. Even among people of North African origin, the proportion of employees is quite high at 36.2%. The lowest percentages are found among people originating from the EU13 (23.1%) and from an EU candidate country (29.1%).
Within the latter two groups, we see a strong overrepresentation of workers’ jobs. Among people originating from an EU candidate country, 43.7% of employed people have a job as a worker and among people of EU13 origin 42.0%. Among persons of North African and Sub-Saharan African origin, the share of workers is also quite high at 39.2% and 36.6%, respectively.
Table 4: Professional status per origin group, average figures for 2020-2021-2022
| Professional status (Column percentages) |
Belgium | EU14 (excl. Belgium) | EU13 | EU candidate | Other Europe | North Africa | Sub-Saharan Africa | Other | Total |
|---|---|---|---|---|---|---|---|---|---|
| Worker | 18.4% | 20.7% | 42.0% | 43.7% | 24.3% | 39.2% | 36.6% | 33.9% | 21.7% |
| Employee | 43.5% | 44.8% | 23.1% | 29.1% | 42.2% | 36.2% | 41.5% | 38.8% | 42.2% |
| Civil servant | 23.6% | 21.6% | 15.6% | 11.4% | 17.2% | 16.6% | 16.0% | 13.0% | 22.0% |
| Self-employed | 14.5% | 13.0% | 19.2% | 15.7% | 16.4% | 8.0% | 5.9% | 14.2% | 14.1% |
| Total | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% |
Occupational category
We get a little more clarity on the nature of the jobs by examining which specific occupational groups are over- or underrepresented among the different origin categories. Table 5 shows the distribution by occupational category for each origin category, classified according to the main categories of the ISCO-08 classification of occupations. By comparing with the average percentage of an occupational category among the total working population (right-hand column), we can see which nationalities are under- or overrepresented compared to the average. Note that the further the categories are disaggregated, the smaller the sample numbers on which the figures are based and the larger the margin of error around the estimates. We leave out the ‘other Europe’ and ‘other’ origin groups because of their rather heterogeneous composition.
Whereas on average 8.3% of employed people have a job from the professional group Managers, we see a clear underrepresentation among people of Sub-Saharan African origin, where only 3.5% have a management job. The percentage is also more than 2 percentage points lower than the average of 8.3% in the North African and EU candidate origin group. Within the occupational group ‘Professionals’, we also see an underrepresentation of the same three origin groups. While almost 30% of employed people of Belgian or EU14 origin hold such a job, for origin groups from an EU candidate country, North Africa and Sub-Saharan Africa it is 15% or less. The group of EU13 origin is also still underrepresented with 19.0%.
The differences are less significant in the category Technicians and associate professionals. Again, we see the highest representation among people of Belgian or EU14 origin, but in addition, people of Sub-Saharan African origin are also quite well represented, with 14.1% of all employed people from that origin group. The lowest percentage is seen among the group with EU13 origin (7.4%). We see a similar pattern for the occupational group ‘Clerical support workers’. Again, it is mainly the group with an EU13 origin that is the least represented here. This is also the case for the category Service and sales workers. Once again, we see relatively few people of EU13 origin there. However, those with Sub-Saharan African origin (18.7%), North African origin (18.0%) and those originating from an EU candidate Member State (15.8%) are more often represented.
In the category ‘Craft and related trades workers’, consisting of building workers, metal workers, electricians, and so on... among others, we find remarkably often persons originating from an EU13 country. Almost one in five have a job from this occupational category, compared to less than one in ten on average among employed people. In addition, we also see there more often than average persons originating from an EU candidate country (14.9%). The category ‘Plant and machine operators, and assemblers’ is a relatively small occupational group, with only 6.0% of all people employed. Nevertheless, we see a slight overrepresentation of those originating from an EU candidate Member State (11.1%) or from North Africa (10.7%).
In the category ‘Elementary occupations’, in which mainly unskilled workers can be found, we see the largest differences between, on the one hand, persons with a Belgian or EU14 origin and, on the other hand, persons originating from outside the EU14 group. In addition, it is notable that one fourth of all persons of EU13 origin have a job from the category of elementary occupations. Similarly, for persons of North African and sub-Saharan African origin, it is almost one in five, followed by 18.2% within the category of EU candidate countries. This contrasts sharply with the only 6.7% of persons of Belgian origin in elementary occupations.
The latter also becomes very clear when looking at the specific composition of the ‘Elementary occupations’ category, according to nationality of origin. Only 53.3% of this occupational group consists of people with a Belgian nationality of origin, whereas the average for all employed people is 71.5%. Almost 10% of elementary occupations are performed by someone of EU13 origin and another almost 10% by someone of North African origin. This while both groups account for about 4% of the total number of employed people (see table 19 (Tab 7B) of the downloadable document NL-FR).
Table 5: Occupational category (ISCO-08) per origin group, average figures for 2020-2021-2022
| ISCO-08 (Column percentages) |
Belgium | EU14 (excl. Belgium) | EU13 | EU candidate | Other Europe | North Africa | Sub-Saharan Africa | Other | Total |
|---|---|---|---|---|---|---|---|---|---|
| Managers | 8.4% | 9.2% | 7.0% | 6.0% | 9.7% | 5.6% | 3.5% | 9.4% | 8.3% |
| Professionals | 29.3% | 29.7% | 19.0% | 13.7% | 25.7% | 13.1% | 15.0% | 20.0% | 27.5% |
| Technicians and associate professionals | 16.0% | 14.3% | 7.4% | 10.0% | 14.7% | 10.6% | 14.1% | 10.2% | 14.9% |
| Clerical support workers | 13.2% | 11.4% | 6.7% | 10.3% | 10.6% | 11.3% | 14.2% | 8.7% | 12.4% |
| Service and sales workers | 11.8% | 13.6% | 7.5% | 15.8% | 10.6% | 18.0% | 18.7% | 18.9% | 12.6% |
| Craft and related trades workers | 9.1% | 8.6% | 19.5% | 14.9% | 7.4% | 10.8% | 6.5% | 8.4% | 9.5% |
| Plant and machine operators, and assemblers | 5.6% | 5.1% | 7.5% | 11.1% | 8.1% | 10.7% | 8.2% | 6.3% | 6.0% |
| Elementary occupations | 6.7% | 8.1% | 25.3% | 18.2% | 13.2% | 19.9% | 19.7% | 18.0% | 8.9% |
| Total | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% |
Economic activity
In this last section, we examine in which economic sectors the various origin groups are over- or underrepresented. Table 6 shows the distribution of the various economic sectors per origin group according to the NACE Rev. 2 classification. There we present the results according to size: we start with the sector employing the most people, and then present the smaller sectors.
The largest sector is that of Human health and social work activities, where 15.6% of all employed people are employed. What is immediately striking is that as many as one in four employed people with origins in Sub-Saharan Africa are employed in this sector, while in each of the other origin groups, with the exception of Belgium, that percentage is below average.
As for the Wholesale and retail trade sector, we do not really see major differences by origin group, with the exception of the EU13 category which is underrepresented with 6.4% compared to an average share of 12.5% working in this sector.
Within the Manufacturing sector, we see rather slight deviations from the average percentage of people employed in manufacturing: a slight overrepresentation of people originating from an EU candidate country (16.2%), and a slight underrepresentation of people of EU13 (9.0%) and Sub-Saharan African origin (7.6%).
As yet, the Education sector does not appear to reflect the total population in terms of origin. Whereas 10.3% of the working population is active in education, for most non-European origin groups it is barely half that percentage or less. The percentage is also very low for persons of EU13 origin: 3.8%. For persons of EU14 origin, however, the percentage is, with 9.2%, closer to that of the group of Belgian origin.
For the Public administration and defence sector, the differences are less pronounced and we mainly see an underrepresentation of the origin categories EU13 and EU candidate country. What immediately stands out for the Construction sector is that the share of employed people with EU13 origin far exceeds the share of the other countries of origin: 19.5% of those employed in that sector are of EU13 origin. In addition, there is also an overrepresentation of people from an EU candidate country.
Professional, scientific and technical activities account on average for 6.3% of the working population, but are strongly underrepresented among all non-European origin groups and among the group with EU13 origin, where the shares are between 2.6% and 3.6%. Exactly the opposite is seen in the sector of Administrative and support service activities. In the groups originating from EU13, an EU candidate Member State and North Africa, two to three times more people work in this sector than the average of 6.0% of the total working population.
In the Transportation and storage sector, the higher percentages are noticeable for the origin groups North Africa and Sub-Saharan Africa, and to a slightly lesser extent also for the origin group of EU candidate Member States. For the other sectors, the numbers are only small numbers in each case, especially for the smaller origin groups. Nevertheless, we still mention the high percentage of persons originating from an EU candidate country in the sector of Accommodation and food service activities (7.2% compared to an average of 3.1% of the total number of employed people), as well as the 4.7% with an EU14 origin and 7.9% with an EU13 origin within the sector of Extraterritorial organisations and bodies (compared to only 1.2% total employment in this sector).
Table 6: Economic activity (NACE Rev.2) per origin group, average figures for 2020-2021-2022
| Nace Rev.2 (Column percentages) |
Belgium | EU14 (excl. Belgium) | EU13 | EU candidate | Other Europe | North Africa | Sub-Saharan Africa | Other | Total |
|---|---|---|---|---|---|---|---|---|---|
| Human health and social work activities | 16.2% | 13.3% | 12.4% | 8.6% | 10.4% | 14.7% | 26.3% | 13.2% | 15.6% |
| Wholesale and retail trade; repair of motor vehicles and motorcycles | 12.5% | 12.6% | 6.4% | 13.3% | 11.1% | 13.8% | 11.4% | 16.8% | 12.5% |
| Manufacturing | 12.7% | 10.9% | 9.0% | 16.2% | 12.4% | 11.5% | 7.6% | 10.7% | 12.2% |
| Education | 11.7% | 9.2% | 3.8% | 4.4% | 7.9% | 5.7% | 4.7% | 6.1% | 10.3% |
| Public administration and defence; compulsory social security | 9.9% | 8.0% | 3.0% | 4.4% | 4.8% | 7.6% | 7.2% | 4.9% | 9.0% |
| Construction | 6.4% | 5.9% | 19.5% | 11.5% | 5.1% | 5.0% | 3.1% | 4.9% | 6.7% |
| Professional, scientific and technical activities | 6.6% | 7.1% | 3.0% | 2.7% | 9.5% | 3.6% | 2.6% | 6.0% | 6.3% |
| Administrative and support service activities | 4.8% | 5.7% | 17.5% | 12.9% | 7.3% | 12.6% | 8.9% | 8.2% | 6.0% |
| Transportation and storage | 5.2% | 5.3% | 5.7% | 9.8% | 8.9% | 11.3% | 11.4% | 6.6% | 5.7% |
| Information and communication | 4.3% | 5.2% | 3.5% | 3.3% | 6.8% | 3.0% | 2.6% | 5.3% | 4.3% |
| Financial and insurance activities | 3.7% | 3.1% | 1.6% | 2.1% | 4.2% | 2.1% | 3.6% | 2.3% | 3.4% |
| Accommodation and food service activities (Horeca) | 2.3% | 4.1% | 3.9% | 7.2% | 3.2% | 5.4% | 5.5% | 9.1% | 3.1% |
| Other service activities | 1.9% | 2.7% | 2.0% | 1.8% | 3.0% | 1.8% | 2.5% | 3.0% | 2.1% |
| Arts, entertainment and recreation | 1.6% | 2.2% | 0.8% | 1.1% | 1.9% | 1.3% | 1.8% | 1.3% | 1.6% |
| Activities of extraterritorial organisations and bodies | 0.4% | 4.7% | 7.9% | 0.7% | 3.4% | 0.6% | 0.8% | 1.6% | 1.2% |
| Total | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% |
Conclusion
In this contribution, Statbel tries to paint a picture of the labour market situation of individuals according to their origin. As usual with official statistics, this involves a description of reality, without going too deeply into the possible explanations behind the figures. At the same time, this also entails a certain risk for wrong conclusions and interpretations. We therefore want to emphasise that the figures presented here are no more than a picture of a very complex reality where various factors play a role and where causal links cannot be unequivocally demonstrated and often play out in different directions. What we observe in the figures is the result of various dynamics, where in particular educational attainment, age, family situation, language skills, etc... often offer underlying explanations.
We therefore see this descriptive analysis rather as a starting point for more comprehensive explanatory analyses and further scientific research. We are convinced that adding this background variable on origin to the Labour Force Survey will be able to contribute to this.
[1] On the Statbel page ‘origin’ under the topic ‘population’, a distinction is made between the terms ‘origin’ and ‘nationality of origin’ and consequently also between ‘origin groups’ and ‘origin nationality groups’ or groups of ‘nationality of origin’. For the sake of readability, this report will often use the term origin group where strictly speaking ‘nationality of origin’ is meant.
[2] For the sake of readability, we will refer to this group below by talking about ‘EU14’ origin, even though this excludes persons of Belgian origin.
[3]This group includes all countries that officially have candidate status on 1/1/2023, thus including Ukraine and Bosnia-Herzegovina. However, in 2022 (reference date 1 January 2022) the numbers are small, so they have little impact on the total figures of the group.
[4] For the sake of readability, no confidence intervals or statistical test are included in this article. However, confidence intervals are available on request for most indicators.
[5] For the official indicators per year, we refer to the figures in the Employment and Unemployment sections https://statbel.fgov.be/en/themes/work-training/labour-market/employmen….