3. Descriptive statistics

In this chapter, various descriptive statistics are presented. First, we show the share of the working-age population belonging to the group of individuals with no or weak labour market attachment in each of the Nordic countries. Second, we move our attention to the operationalised employment barriers, where we demonstrate the prevalence of the employment barriers in the Nordic countries, how the employment barriers are related to the traditional target groups, the number of barriers typically faced, and how the barriers coexist.

As described earlier, the population of interest in this analysis is individuals with no or weak labour market attachment (see Section 2.2 for further description of this group).

Figure 3.1 shows the share of individuals with no or weak labour market attachment in the Nordic Countries as a fraction of the working-age population in each Nordic country (excluding students and individuals enrolled in compulsory military service). The figure shows that 11 pct. of the working-age population in the Nordic countries are out of work and that 10 pct. have a weak labour market attachment. Further, the figure shows some interesting cross-country variation. For example, Iceland has a lower share of their working-age population out of work compared to the other Nordic countries, with Finland having a slightly higher share out of work.

Figure 3.1 Individuals with no or weak labour market attachment, pct. of working-age population (excluding individuals enrolled in education or compulsory military services)

Further, it should be noted that a relatively large fraction of Iceland’s persons with no or weak labour market attachment, compared to the other Nordic countries, consists of individuals with weak labour market attachment. In Iceland, the persons with weak labour market attachment constitute 65 pct. of the group with no or weak labour market attachment, whereas the share in Norway is 42 pct. This is worth keeping in mind when we look into the cross-Nordic differences in the prevalence of barriers.

These findings are somewhat consistent with findings in the first report in this project. Based on Eurostat’s labour force survey, we also demonstrated in this report that Iceland has a higher employment rate and Finland a lower employment rate compared to the other Nordic countries (Højbjerre et al., 2022).

Note that Figure 3.1, however, is not completely comparable to our previous work for a number of reasons. First, this report is based on Eurostat’s EU-SILC, whereas the previous report was based on Eurostat’s labour force survey. Second, we use different populations. In this report, we consider the working-age population excluding individuals in education and compulsory military service. In the previous report, we studied the entire working-age population, and this fact contributes to explain why, in the first report, we found a labour force participation rate which was lower compared to what Figure 3.1 suggests. Third, we study different time periods. In this report, we used the most recent EU-SILC for each Nordic country, whereas we used the most recent labour force survey accessible in the previous report.

In the next sections, we will only focus on the individuals who have no or weak labour market attachment since the purpose of this report is to further understand the employment barriers this group faces and group them according to the barriers that they face.

In this subsection, we examine the prevalence of the employment barriers in the Nordic countries. Figure 3.2 shows which of the 10 barriers are most common in the Nordic countries.

Several interesting patterns can be highlighted. First, barriers related to individual characteristics (BIC) seem to be relatively important. In particular, health issues, lack of education, and no recent experience are widespread barriers. For example, 43 pct. of the individuals with no or weak labour market attachment are limited in their daily activities to some degree due to either physical or mental health issues, whereas 31 pct. lack education. However, other barriers (e.g., care responsibilities) are also present in the Nordic countries even though they seem less important.

Figure 3.2 Prevalence of employment barriers among individuals with no or weak labour market attachment, pct. of individuals with no or weak labour market attachment

Second, barriers related to economic incentives and motivation (BIM), the employer and labour market structures (BEL), and public services (BPS) are also present but less important. For example, 11 pct. of the individuals with no or weak labour market attachment lack contact with the public employment services to some degree, whereas only 2 pct. of the individuals in this group have lacking incentives due to high non-labour income (which include, e.g., both high partner income as well as high passive income from return on shares).

Figure 3.2 shows how prevalent the employment barriers are in the entire Nordic region. We also find interesting cross-Nordic variation in how prevalent the employ­ment barriers are in the Nordic countries. Figure 3.3 shows the prevalence of the employment barriers in each of the Nordic countries. In general, the figure shows that there are great similarities between the countries in terms of the prevalence of barriers. However, there are some interesting cross-country variations.

Figure 3.3 Prevalence of employment barriers among individuals with no or weak labour market attachment in each of the Nordic countries, pct. of individuals with no or weak labour market attachment

For example, 56 pct. of the individuals with no or weak labour market attachment in Denmark struggle with some degree of health issues, whereas only 35 pct. in Sweden struggle with health issues. Similarly, care responsibilities are more prevalent in Sweden and Iceland, where 16 pct. and 20 pct., respectively, of the individuals with no or weak labour market attachment face this barrier. In the other Nordic countries, 4–6 pct. face this barrier.

Further, high earnings replacement (benefits) seems to constitute a relatively important employment barrier in Norway and Iceland, where 27 pct. and 18 pct., respectively, of the individuals with no or weak labour market attachment face this barrier. This is consistent with previous work in OECD’s Faces of Joblessness project, where it is shown that approximately 30 pct. of the individuals with no or weak labour market attachment face this employment barrier in Norway, based on EU-SILC from 2017 (Fernandez et al., 2020).

In the previous research report, we found indications of high similarity in the barriers faced by the traditional demographic target groups, i.e., young, seniors, etc. (Højbjerre et al., 2023). These were only indications, but we are able to confirm in this section that there is a high degree of similarity in the barriers which the traditional target groups face. This is demonstrated in Figure 3.4, which shows the prevalence of the employment barriers among the traditional demographic target groups. In general, the figure shows that there is a high degree of similarity in the barriers which the traditional target groups face. For example, among individuals with no or weak labour market attachment, lack of education is faced by 32 pct. of the young people, 31 pct. of the seniors, 40 pct. of the immigrants, and 35 pct. of the persons with disabilities.

Figure 3.4 Prevalence of employment barriers among individuals with no or weak labour market attachment, pct. of individuals with no or weak labour market attachment

On the other hand, Figure 3.4 also demonstrates that some barriers are still more prevalent among certain traditional demographic target groups than others. For example, 90 pct. of the seniors and 84 pct. of the persons with disabilities have no recent experience, which might be explained by, for example, early retirement. Further, the figure shows that high earnings replacement is prevalent especially among persons with disabilities, where 16 pct. of the individuals face this barrier. Lastly, young people stand out as regards the barrier related to low job opportunities as well as the barrier related to low contact with the public employment services (PES). 57 pct. of the young individuals face a barrier related to low job opportunities, whereas no young people face a barrier related to lack of contact with PES.

Further, it is worth mentioning that one of the reasons for the high degree of similarity in the barriers that the traditional target groups face is also a result of the barriers we have been able to identify in data. For example, in the framework, an employment barrier that hinders some immigrants from participating in the labour market is lack of language skills. This constitutes an employment barrier only for immigrants. However, there are no language skill variables in EU-SILC, and it is not possible to construct a proxy for language skills since the origin-of-birth variable in EU-SILC is also deficient.

In the previous section, we studied how prevalent each of the employment barriers is in the Nordic countries. However, another interesting perspective is how many barriers each individual faces, hence how complex the person’s situation is. In this section, we dig deeper into this topic by first examining the number of barriers the individuals with no or weak labour market attachment in the Nordic countries face, then how the barriers coexist.

Figure 3.5 shows the number of identified employment barriers that persons with no or weak labour market attachment face in each of the Nordic countries as well as in the Nordic countries as a whole. Looking at the Nordic countries as a whole, two interesting conclusions can be drawn. First, the figure shows that two-thirds of the population of interest in the Nordic countries face two or more barriers, highlighting the complexity in this policy area.

Second, the figure shows that 14 pct. face a highly complex set of barriers, with a total of four or more barriers, indicating that these individuals face wicked problems characterised by many interdependent factors.

The fact that many vulnerable individuals face a complex set of barriers is consistent with previous findings in this project, where we have shown that the barrier set is typically complex and intertwined, which highlights the complexity in this policy area (Højbjerre et al., 2023). Later in this chapter, we will further examine which concrete set of employment barriers is the most common.

Looking at the barrier complexity across the Nordic countries, there are some differences and similarities. For example, Figure 3.5 shows that the barrier complexity is left-skewed in Norway and Iceland, meaning that more individuals face a more complex set of barriers in these countries. In Norway, 6 pct. of the population of interest face five or more barriers, while 5 pct. in Iceland do so. In the other Nordic countries, 1–2 pct. face five or more barriers. That the barrier complexity is significantly left-skewed in Norway and Iceland could be a result of fewer individuals having no or weak labour market attachment in these countries (as demonstrated in Figure 3.1). When comparing the complexity of employment barriers in Sweden, Denmark, and Finland, it appears that individuals in Finland generally face fewer barriers, while individuals in Sweden and Denmark seem to exhibit similarities to some degree. However, a larger share of individuals face four barriers in Denmark, while a larger share face one barrier in Sweden.

Again, it is worth mentioning that these results are most likely bottom-edge estimates of the complexity of barriers in the Nordic countries since we are only able to operationalise 10 barriers related to 9 out of the 24 employment barriers identified in previous work in this project (Højbjerre et al., 2023).

Having established that numerous individuals in the Nordic countries encounter multiple employment barriers that affect their chances of employment, we will now delve deeper into the most prevalent combinations of these barriers. Table 3.1 provides a two-dimensional representation showcasing the relationship between various employment barriers and their overlap. The table must be read column by column, with each column showing the percentage of individuals facing the barrier at the top of the column while also facing one of the other barriers. For example, all the individuals in Column 1 have physical/mental health issues, and 33 pct. of these individuals also lack education, 69 pct. also have no recent experience, etc. Again, this table underlines the fact that many individuals experience several employment barriers affecting their employment chances. The barriers that most often coincide with the other barriers are health issues, lack of education, and having no recent employment experience. For example, at least 23 pct. of the individuals facing one of the ten barriers also face a barrier related to health issues, while at least 35 pct. of the individuals facing one of the ten barriers also face barriers related to no recent experience.

Table 3.1 Coexistence of barriers, pct. of individuals facing one of the barriers in the columns

Another interesting point that can be deduced from Table 3.1 is that individuals who lack education and individuals who have low job opportunities in the respective labour market segments only and to a very little degree (1 pct. and 0 pct., respectively) experience low contact with the public employment services. Further, individuals with high non-labour income (i.e., income that is independent of the individual’s own work effort) relatively often have low contact with the public employment services (32 pct.).

Table 3.1 is only a two-dimensional representation of the relationship between the different employment barriers. However, Figure 3.5 showed that 14 pct. of the individuals with no or weak labour market attachment face four or more barriers. In the last part of this section, we investigate which sets of barriers are typical among these 14 pct. Table 3.2 shows the most prominent sets of barriers among individuals facing four or more barriers, and it reveals several interesting results. First, barriers related to individual characteristics (such as health issues, lack of education, and lack of experience) are the most prominent, which might not come as a surprise since they were also the most prevalent among the individuals with no or weak labour market attachment in the Nordic countries.

Second, the table shows that 18 pct. of the individuals facing four or more barriers face the following complex set of barriers: health issues, lack of education, no recent experience, and lack of skills. 17 pct. of the individuals face almost the same set of barriers, except that lack of skills is replaced by never worked.

This highlights that a relatively significant part of the individuals with no or weak labour market attachment faces a complex set of barriers, where no simple solutions exist. For instance, how can individuals in the first column (who have health issues, lack of education, lack of skills, and no recent work experience) be helped into the labour market in the best way possible? Do you follow the JobFirst strategy – as has been done in Denmark, for example – where vulnerable individuals are offered business internships to include them in the labour market, thereby overcoming their lack of recent experience and skills to some degree? Do you start by helping these individuals with their health issues? Or do you help them get into education? These questions are complex and difficult to answer, but we will try to approach an answer in the next phase of this research project.