5. Groups in need of active labour market policies and their obstacles to labour market inclusion
One quarter of 15-64 year-olds in Estonia are only weakly attached to the labour market (they do not work, or work only some months a year, work on unstable employment contracts or have low earnings) and might achieve better labour market outcomes through active labour market policies. While all regions in Estonia are home to a significant share of people with weak attachment to the labour market, counties in the country’s East and South are particularly concerned. Skills obstacles, family-related obstacles and obstacles to integrate into the society (very long periods out of employment, migratory background, etc.) are particularly widespread among groups with weak labour market attachment. Almost all of persons weakly attached to the labour market face at least one labour market obstacle, three-quarters face at least two obstacles and close to 40% face three obstacles or more. The correlation between different labour market obstacle types is overall low, suggesting that “typical” profiles of people with needs for active labour market policies may be insufficient to reflect the diverse life circumstances of people with weak labour market attachment in Estonia.
This chapter identifies groups of people with possible ALMP needs. In particular, people fall into such groups if they are not attached or are only weakly attached to the labour market, but their employment perspectives could significantly improve through ALMPs. The analysis is based on a particularly rich set of linked administrative data permitting to distinguish four groups of people with weak labour market attachment: i) individuals of working age who are entirely out of employment; ii) workers with interrupted employment records; iii) workers on unstable short-term contracts; and iv) people with very low labour income. The linked administrative data used to identify these groups includes a wide range of information, including information on people’s socio-economic background, income, work history, health status and their educational background. Acknowledging that ALMPs are not effective for everybody, the analysis abstracts from groups whose labour market outcomes are very unlikely to react to ALMPs, such as people with particularly severe health issues, students and people living in high-income households.
Following the identification of groups with possible ALMP needs, the chapter defines and discusses common labour market obstacles they face, such as insufficient skills, geographic distance to jobs, family-related challenges, health problems, integrational challenges and motivational obstacles.
Chapter 5 has similarities with Browne et al. (2018[1]), which also studies people with weak labour market attachment and common employment obstacles in Estonia, using the OECD’s Faces of Joblessness methodology (Fernandez et al., 2016[2]). The studies differ in their methodology and data set used. Browne et al. (2018[1]) is based on EU-SILC (European Union Statistics on Income and Living Conditions) data while this chapter uses linked administrative data covering whole Estonian population. The studies differ in the definitions of key variables, e.g. weak labour market attachment and labour market obstacles as the dataset in the current analysis allows to define many variables more precisely. In addition, Browne et al. (2018[1]) is based on data from 2013, reflecting a labour market still recovering from the Great Recession and before the implementation of the Work Ability Reform, while this chapter studies a very healthy labour market in 2018 prior to the outbreak of the COVID-19 crisis. Nonetheless, both studies concur in finding that the number of people with weak labour market attachment is quite large and that many of these people are confronted with multiple labour market obstacles. Most importantly, this chapter builds the grounds for Chapter 6, which establishes a link between the groups with weak labour market attachment and the ALMPs and other services they receive.
ALMPs can be effective policy tools to improve the employment prospects of inactive and unemployed people, but also of other groups with weak attachment to the labour market such as workers with very low earnings and workers on precarious employment contracts (see e.g. Card et al. (2017[3])).
According to 2019 data, 19% of 25-64 year-olds in Estonia are out of employment, i.e. they are either unemployed or inactive (Figure 5.1). Compared internationally, the share of prime-aged adults with no job is lower in Estonia than in most other OECD countries. On average in the OECD, 23% of 25-64 year-olds do not work. Only in seven OECD countries, out of which three are members of the European Union, the level is lower than in Estonia, with 18% in Germany, 17% in the Czech Republic and 16% in Sweden.
Overall, having no job is more frequent among women (22%) than among men (15%), but the pattern is not stable across age groups. Younger women aged 25-34 are far more likely to be out of employment than younger men, at 32% against 8%, in part due to maternity and participation in higher education. Conversely, at older ages, a higher proportion of women than of men work, in particular in the decade preceding retirement. Among 55-64 year-olds, 31% of men have no job, while they are only 25% of women. Overall, the employment gender-gap is comparatively low in Estonia, at 7% among 25-64 year-olds against 13% in the OECD and 10% in OECD countries that are member countries of the EU. However, it is higher than in neighbouring Latvia (4%) and Lithuania (2%).
Note: OECD and EU are unweighted averages. The graph represents the share of 25-64 year-olds out of employment among all 25-64 year-olds. Employment refers to working and earning a salary or, in case of longer absences from work, continuing to receive at least a partial salary.
Source: OECD LFS by Sex and Age – Indicators Database, http://stats.oecd.org//Index.aspx?QueryId=54218.
Precarious employment is less common in Estonia than in most other OECD countries (Figure 5.2). About 1.3% of employees in Estonia are on short-term contracts with a duration of three months or less, against an EU average of 2.2%. However, the incidence of precarious employment in Estonia has been increasing over time, from 0.8% in 2009, in part due to a labour market reform in 2009 that made the use of fixed-term contracts more flexible. While not numerous, workers who are on precarious employment contracts have to cope with frequent job changes and face a higher risk of unemployment.
Note: EU is an unweighted average of the 22 EU OECD member countries.
Source: Eurostat, Precarious employment by sex, age and NACE Rev. 2 activity dataset, https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=lfsa_qoe_4ax1r2&lang=en.
Many workers in Estonia earn low wages. About 22% of full-time workers earn less than two-thirds of the median wage of all full-time workers (Figure 5.3). This share is among the highest in European OECD countries, comparing to an EU average of 14%.
Note: EU is an unweighted average excluding Greece, Ireland and Italy. Only employees of firms with at least 10 employees are included (excluding apprentices).
Source: Eurostat, Low-wage earners as a proportion of all employees (excluding apprentices) by sex dataset, https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=earn_ses_pub1s&lang=en
Taken together, the prevalence of people who are out of employment, earn little or work on precarious short-term contracts, concerning in total about 40%-50% of 15-74 year-olds, point to a considerable need for ALMPs in Estonia. This is especially the case for the large number of workers with low wages and of people who are entirely out of employment.
Nevertheless, ALMPs are not effective for all the people with weak or no labour market attachment. The labour market situation of some groups is unlikely to improve in response to participation in ALMPs while others might need different measures, such as social, health or education services instead of ALMPs, or they need no measures at all. For example, students who do not work because they are enrolled in full-time studies are generally not in need of ALMPs. Similarly, retirees with health problems typically do not need ALMPs, but rather health and social services. The aggregate statistics presented above do not permit to account for these groups that are not available for labour market participation or would not benefit from ALMPs. Therefore, the microdata analysis in the next section refines the groups that are considered to be in need of ALMPs and could be possible ALMP target groups.
This section identifies the population groups that would likely benefit from ALMPs, drawing on a unique set of linked administrative microdata combining data from a wide set of administrative registers, including the employment register, the tax register, the education register and health data from the Health Insurance Fund. In contrast to previous studies, this chapter is not based on surveys, but uses exclusively linked administrative data. The methodology of this analysis as well as the data sources are described in Box 5.1. Most of the discussions in this section focus on 15-64 year-olds as the primary target group for ALMPs. Conversely, the last part of the section also includes a discussion on ALMPs for pensioners, acknowledging that supporting older people to stay in employment or take up a new job may be one way of alleviating labour supply shortages.
Concept and methodology
This analysis identifies four groups of people with weak attachment to the labour market who could potentially benefit from participation in ALMPs:
People who had no registered employment income and no registered employment contract within a given year, i.e. people who were entirely out of employment in a given year.
People who worked for parts of a given year, but were without an employment contract for at least three months.
People who worked on precarious employment contracts (most notably contracts under the Law of Obligations Act, Võlaõigusseadus) on more days than they worked on regular employment contracts within a given year.
People with earnings below 50% of the median wage in the data, in line with one of the definitions of the income-poverty line used by the OECD.1 This group includes people whose total annual income is below 50% of the median annual wage within a given year, as well as people who had, on average, a monthly income below 50% of the median monthly wage. As a result, this group can include people with very low hourly earnings, but also people who work part-time or only for some months per year.
However, for some of these groups, it may be impossible to provide effective support through ALMPs, e.g. because they are in very poor health or because they are unavailable for work for other reasons. Therefore, the following categories are excluded from the group of people with a weak labour market attachment:
Students, i.e. people who are enrolled in the education system.
Mothers who have recently given birth and received a childbirth allowance within the calendar year.
People who live in institutions (e.g. retirement homes or prisons).
People with significant health problems (i.e. people with a diagnosed severe or profound disability; people with more drug prescriptions than 90% of the people with at least 1 prescription).2
People from high-income households with an adjusted household income3 exceeding the adjusted household income of 90% of all households.
Following this methodology, all people in working-age belong to one of the following three mutually exclusive categories:
People who have no solid labour market attachment, but are excluded from the group of people with weak labour market attachment because they are unavailable for work.
While this methodology permits a thorough identification of people who would benefit from ALMPs, it does not account for informality. It is likely that a non-negligible share of individuals who are classified as not working, working in precarious jobs or working with low pay in this analysis have undeclared labour income. Even in these cases, however, ALMPs can be a useful tool to encourage people to enter the formal labour market, with benefits for both workers (e.g. access to insurance) and the state (e.g. tax income).
Data
The core dataset for this analysis is the Estonian EUROMOD dataset for 2017-18, which builds on data from 17 Estonian administrative registers. It uses an elaborate residency indicator – developed by Statistics Estonia – to correct the base of residents for people who have emigrated but are still officially registered in Estonia. The Estonian EUROMOD contains data on household structure, socio-demographic variables, income, social benefits, consumption and assets.
In addition, the following data registers are linked with the EUROMOD data for this analysis:
Employment register – data on starting and ending dates of employment contracts, contract types, reasons for the termination of employment contracts, 2015 to 2018
Data on self-employed – revenues, costs and profits from self-employment, 2006 to 2018
Education register – participation in education system (ISCED levels 4 to 7), 2005 to 2018
Population census 2011 – nationality, mother tongue, migratory background
Computations by Statistics Estonia using Population register data to estimate the distance from a person’s home to the economic centre of the county, 2018
Health Insurance Fund – general data on health conditions (occurrence of medical prescriptions), 2012 to 2018
Dataset for European Social Fund (ESF) monitoring – socio-economic background information for participants in ESF measures, participation in ESF measures
← 1. An alternative definition of the poverty line in 60% of equivalised median household income.
← 2. As of 2018 (2017), this level corresponds to at least 27 (26) medical drug prescriptions.
← 3. Adjusted for household size. Adjusted household income is computed as total household income, divided by the square-root of household size.
5.3.1. A considerable share of the Estonian population could benefit from ALMPs
Overall, 26% of 15-64 year-olds1 are weakly attached to the labour market and would potentially benefit from ALMPs (Figure 5.4). This corresponds to just above 200 000 people. In line with the results of the aggregate data analysis in Section 5.2, there is a large number of people who do not work at all, work with interruptions or earn low salaries while only few workers are on precarious contracts.
Many people face several labour market difficulties simultaneously. For instance, people with unstable careers are also much more likely to have low earnings than workers who work without interruptions. About 65% of people who worked with interruptions in 2018 also had low earnings. Similarly, fewer than half of workers with low earnings in 2018 held stable and uninterrupted contracts. ALMP needs differ across age groups. As of 2018, 21% of the age group 15-24 are weakly attached to the labour market and have a potential need for ALMPs (i.e. excluding students), against 28% among 25-34 year-olds, 27% among 35-44 year-olds, 26% among 45-54 year-olds and 29% among 55-64 year-olds. The comparatively low need for ALMPs among 15-24 year-olds is driven by the fact that many young people are enrolled in the educational system, i.e. they are already engaged in upskilling and are thus not included in the current analysis on needs for ALMPs.
Working with interruptions is relatively common among younger people. The proportion of people who worked only for some months in 2018 was 11% for 15-24 and 25-34 year-olds, against 9% for 35-44 year-olds, 8% for 45-54 year-olds and 7% for 55-64 year-olds. The high frequency of interrupted employment spells among young adults reflects that the transition from studying to work is not always smooth. In addition, it may possibly point to a higher preference for flexible but less stable employment arrangements among younger people.
The analysis shows that a higher share of men than of women are weakly attached to the labour market and could benefit from participating in ALMPs. Among 15-64 year-olds, this is the case for 29% of men, against 24% of women. The lower share among women is due to the fact that more women than men are excluded from the group of people with a weak labour market attachment (e.g. due to maternity, enrolment in the educational system as a student or health issues).
Note: Pensioners are excluded from the calculations, i.e. they are neither counted in the nominator nor in the denominator.
Source: OECD calculations based on linked administrative microdata.
ALMP needs differ largely across counties in Estonia (Figure 5.5). In the economically strongest counties, including the counties around Tallinn (Harju) and Tartu (Tartu), ALMP needs are lower than in the areas of limited economic activity. While 26% of people have a potential need for ALMPs due to their weak labour market attachment on average in Estonia, they are 23% in Harju and Hiiu, and 24% in Tartu. Conversely, the share of persons with weak or no attachment to the labour market is higher in Võru (30%), Valga (31%) and Ida-Viru (32%). Cross-county differences in the size of the groups with potential ALMP needs are closely linked with other employment indicators, such as employment rates and unemployment rates. For instance, the counties with the lowest share of people with potential ALMP needs all have above-average employment rates among 15-64 year-olds, amounting to 75.1% in Tartu, 75.5% in Hiiu and 79.4% in Harju in 2018, against 74.5% on average in Estonia.
Note: The three counties with the highest ALMP needs are marked in light blue; the three counties with the lowest needs in aqua blue. Pensioners are excluded from the calculations, i.e. they are neither counted in the nominator nor in the denominator.
Source: OECD calculations based on administrative microdata.
Self-employed workers (i.e. people registered as self-employed), who account for about 10% of all workers in Estonia, are more likely to have a weak attachment to the labour market than the overall population. On average, 32% of the self-employed could potentially benefit from ALMPs as of 2018, against 26% of people in the overall population, mostly because many self-employed have no or little professional income. A lack of earnings among the self-employed often lasts for long periods: More than 80% of registered self-employed with zero registered earnings in 2017 also had zero earnings in 2018.
People who could significantly benefit from access to ALMPs are not one homogenous group, but have diverse demographic and professional backgrounds, as this analysis shows. Younger people with unstable careers, prime-age adults who are entirely out of employment, people with no solid employment who live in economically feeble areas and self-employed people with no or very low income are all examples of such groups. This diversity is a challenge for providing well-tailored ALMPs to the people who most need them and calls for efficient outreach activities by ALMP providers (see Chapter 6).
5.3.2. Numerous pensioners could benefit from ALMPs
While the statistics and discussions presented above focus on non-pensioners aged 15-64, who are typically the main target group of ALMPs, providing ALMPs to pensioners can have benefits as well. With record-high employment rates prior to the outbreak of the COVID-19 crisis and a shrinking working-age population (see Chapter 2), healthy people in retirement age who retire late or return to work after retiring can be an important pool of workers contributing to limit labour shortages in Estonia. According to the Estonian Labour Force Survey data from 2019, pensioners are the biggest group (25%) among inactive people, who are not actively seeking work, but willing to start working as soon as a job is offered to them. Only about 50 000 inactive 50-64 year-olds were willing to take up employment, against 97 000 inactive 65-74 year-olds.
There are numerous people in retirement age in Estonia who do not work (mostly retirees receiving pensions) but do not face severe individual obstacles (e.g. very bad health) preventing them from working (Figure 5.6), even though employment rates at older ages are higher in Estonia than in many other EU and OECD countries. While 26% of non-pensioners lack a solid labour market attachment and might benefit from ALMPs, they are 47% among pensioners, reflecting the fact that workers commonly retire around the statutory retirement age, even if they are healthy. Although pensioners are not the main target group of ALMPs, the Estonian ALMP system should provide support to pensioners who would like to prolong their working life or re-renter employment. With relative old-age poverty being among the highest in the OECD (OECD, 2019[4]), especially among people who live alone, such type of support could be of particular help for retirees with low pensions who are willing to take up work.
Note: Non-pensioners refers to 15-64 year-olds who do not receive any pension payments and whose main labour market status is not pensioners. Pensioners refers to people aged 65-74 as well as younger people receiving pensions.
Source: OECD calculations based on administrative microdata.
This section analyses common obstacles to labour market inclusion that people with weak attachment to the labour market face in Estonia, thereby providing insights on the type of support that would be needed through ALMPs. The analysis is based on the same set of linked administrative microdata as used in Section 5.3. The following sections first describe the methodology to define labour market obstacles and then present the results.
5.4.1. Methodology to define labour market obstacles
This analysis focuses on supply side labour market obstacles based on microdata covering the labour force and people who could be better integrated to the labour market. Immervoll and Scarpetta (2012[5]) define three types of policies to address labour market barriers – policies that strengthen people’s motivation to look for work, policies that address people’s work capabilities and policies to foster labour demand. This analysis focuses on people’s motivation and capabilities and looks at labour demand from the perspective of (potential) workers – such as geographical distance to job opportunities. Compared to the methodology used by Browne et al. (2018[1]), who also rely on the three broad types of policies defined by Immervoll and Scarpetta (2012[5]) and define employment barriers using SILC data for Estonia, the current analysis defines labour market obstacles in more detail, in particular in the case of obstacles related to people’s capabilities and labour market availability. This high degree of precision is possible because the administrative microdata used in this analysis involves rich information covering the full Estonian population.
Using the set of administrative microdata described in Section 5.3, the analysis defines the following types of labour market obstacles:
Skills and qualification – this refers to obstacles linked to people’s capabilities, recognising that low skills may limit the extent to which people can work in jobs with a high value added. In addition, people with insufficient skills and qualification tend to have fewer job opportunities, i.e. labour demand is lower in this group. This obstacle is captured through three variables: 1) Low qualification, defined as ISCED 2011 levels 0-2; 2) No professional education, defined as no vocational or higher education degree (e.g. only general high-school or basic school education); 3) Mother tongue other than Estonian, which is a proxy for potentially lower Estonian skills. While this methodology might under-estimate Estonian skills, there are no comprehensive administrative data available for language skills for the whole population. Furthermore, this variable might capture additional obstacles on the labour market, such as integration and discrimination issues.
Geographic distance to jobs – this obstacle captures a person’s physical distance from job opportunities and is captured by two variables: 1) Living far from an economic centre, defined as living at least 5 km away from the economic centre of the county, and having no car. Living far from an economic centre implies that the person is likely to need some form of transportation to reach the job location daily. Public transportation being scarce in many parts of Estonia’s rural areas, the combination of living outside of an economic centre and lacking access to a car can be a significant labour market barrier; 2) High ALMP need area – estimates whether a person lives in an area where job opportunities are particularly scarce. High ALMP need areas are defined as municipalities in which the share of people with weak attachment to the labour market in the population is in the top 10% of municipalities.
Family related obstacles – address whether a person is available to take on job search and jobs, defined by two variables: 1) Care obligations, limiting the hours a person is available for work. Estimations are provided for the whole group of people, who could potentially have care obligations, and its subgroups – households with young children (at least one child up to three years old), households with a household member with disabilities, households with an older household member (80 or more years), single parents (only one person in the household 18 or more years old and at least one household member less than 15 years old); 2) Living in a household in which no household member is well-attached to the labour market. Living in such a household limits the financial resources a person can devote to looking for a job (e.g. transportation costs, telephone costs, access to computer and internet, clothing, etc.). No household member has stable and sufficient income from labour in the calendar year in these households.
Health-related obstacles – capture whether a person is less available for work (less hours) as well as less capable of work (less functions that can be performed) due to health reasons. Estimations are provided 1) For all people who have moderate disability, partial work ability or work incapacity between 10% to 80% (as people with more severe health conditions are excluded from this analysis); 2) Alcohol addiction, being tightly connected to health conditions, defined as people who received support to treat their alcohol addiction from the Health Development Institute in 2016-19. This variable indicates only a fraction of people in Estonia that have alcohol addiction and there are no data available to define the group comprehensively.
Integration challenges – circumstances that pose additional challenges to integration into society, potentially hindering labour market integration: 1) Criminal history, defined as having been released from prison (relying on the data about registered unemployed from the Estonian Unemployment Insurance Fund, 2012-19) or having a criminal record (ESF data collection 2015-19); 2) Migratory background, defined as people who were not born in Estonia according to census data from 2011 (might have some overlap with an obstacle of lacking Estonian skills); 3) Homelessness, based on ESF data 2015-19. The variables for criminal history and homelessness are likely to underestimate the size of the population affected by these obstacles as they are only available for a subset of the population.
Motivational challenges – motivation to look for a job and work is captured by two aspects: 1) People whose recent employment contract (between 2015 and 2019) ended due to a breach of duties, damaging significantly employer’s assets, abusing alcohol at the workplace, etc. – potentially indicating a lack of motivation to perform working tasks well; 2) Significant non-labour income – person’s income from benefits, investments, collected rents etc. is at least at the level of minimum wage, potentially hindering the motivation to look for and accept a job.
The analysis aims to cover the main potential obstacles that people face to integrate to the labour market. However, some obstacles are covered for parts of the population only (e.g. addictions, criminal background). Furthermore, additional individual obstacles can be present, for which there are no data in administrative records.
5.4.2. People with a weak labour market attachment often face several obstacles to labour market inclusion
People with a weak labour market attachment and a potential need for ALMPs often face several obstacles preventing them from finding employment in general and high-quality jobs in particular. While numerous individual factors can impinge on people’s labour market outcomes, some employment obstacles are particularly common among people with weak attachment to the labour market.
Table 5.1 displays the occurrence of different labour market obstacles as defined in the previous section for different groups of people with weak attachment to the labour market in 2018. In addition, it provides information on how commonly people face several obstacles simultaneously. For the sake of comparability, the obstacle indicators are also reported for people who are well attached to the labour market (i.e. have stable and sufficient labour income), applying the same criteria for labour market availability as for groups with weak labour market attachment (e.g. at least partial work ability, not engaged in the education system, etc.).
Almost all people (94%) with a weak labour market attachment and potential ALMP needs face at least one type of labour market obstacle (corresponding to 194 000 people), more than two-thirds (72%, corresponding to 148 000 people) at least two types of obstacles and 39% (corresponding to 81 000 people) at least three types of obstacles, out of a maximum of 6 obstacle types. Obstacles to labour market integration are also present among people with a solid labour market attachment, although to a lesser extent, with 73% of them facing at least one labour market obstacle. This underpins that labour market obstacles do not necessarily preclude a good labour market integration, especially if people are supported through ALMPs and have access to social services. Nonetheless, the higher the number of simultaneous obstacles, the harder it is to achieve stable and sufficient labour income. The share of people with at least one obstacle is a fourth higher among people in need of ALMPs than among people well attached to the labour market (94% versus 73%), about twice as high when it comes to the share of people with at least two obstacles (72% versus 34%) and more than four times higher regarding the share of people with at least three obstacles (39% versus 9%).
Although many people with potential ALMP needs face several obstacles simultaneously, the combination of obstacles is very individual. The correlation coefficients between different types of obstacles tend to be low. The highest correlation exists between “health obstacles” and “integration obstacles” (correlation coefficient 0.13), which is partially driven by the strong link between health problems and a long history of inactivity. All other correlation coefficients are below 0.1, pointing to a large number of individual situations and multifaceted need for support.
All different types of labour market obstacles are more prominent among groups that are weakly attached to the labour market than among the well attached. The largest differences concern family-related obstacles (most notably, having no person with a solid and stable income in the household, who could support the job search), integration obstacles (in particular a long history of inactivity) and skills and qualifications. Nevertheless, all of the other types of obstacles as well as most of the more specific variables defining the obstacles are also more widespread among people with potential ALMP needs compared to people that are well-attached to the labour market. The only exception is significant non-labour income (i.e. income on the level of minimum wage). 7.3% of the well attached people receive significant non-labour income, compared to 6.1% of people who are weakly attached to the labour market. This indicates that people who have stable and sufficient labour income, might be more likely to be able to make investments and earn additional revenue (e.g. collecting rent). Although people weakly attached to the labour market are more likely to access benefits, they are often lower than the minimum wage, limiting their disincentive effects on job search.
5.4.3. ALMP needs are particularly widespread among the low-educated
Lack of skills is likely to be a major obstacle to employment. There is a stark link between educational attainment and a weak attachment to the labour market in Estonia (Figure 5.7). While 22% of people with potential ALMP needs are low-educated (ISCED levels 0-2), less than 11% of people with a solid attachment to the labour market have only low education level. Conversely, the share of people with high educational attainment (ISCED levels 5 and above) is much lower among people with weak attachment to the labour market, at 25%, than among people solid attachment, at 45%.
Note: People under 25 are excluded because their highest level of educational attainment is likely to be not final. Retirees are excluded.
Source: OECD calculations based on administrative microdata.
Beyond qualification and skills in general, insufficient knowledge of the Estonian language is a probable obstacle to employment. Among people who are weakly attached to the labour market, the share of non-native Estonian speakers (who may or may not speak Estonian as a second language) is about a quarter higher than among people without ALMP needs, at 37% against 29%, respectively. This pattern is not solely due to labour market differences across regions (i.e. between counties in which Estonian is the sole primary language and counties with a large share of Russian-speakers), but holds also in counties with linguistic pluralism. Even in Ida-Viru, where most people are Russian speakers, being an Estonian native speaker is associated with a higher likelihood of achieving a solid labour market attachment.
5.4.4. Even moderate health problems are associated with higher obstacles to labour market integration
Bad health is a significant barrier to employment. Even people with moderate disabilities and who have been assessed as fully or partially able to work, are much more likely to be in need of ALMPs than people who have no disability: 20% of people with a weak attachment to the labour market have long-term health issues, against 9% among people with solid attachment to the labour market. The share of people with health issues is highest among people who are entirely out of employment, exceeding 24%.
Bad health is not only a barrier to work when it concerns potential workers themselves, but also when one or several of their household members are in bad health, possibly requiring care. 11% of 15-64 year-olds with weak attachment to the labour market have at least one household member with a severe or profound disability, compared to 8% among people with a solid attachment to the labour market.
5.4.5. People weakly attached to the labour market face difficulties in transportation to work
Limited mobility is another obstacle faced by people with potential ALMP needs. Especially for people living outside of bigger cities, transportation to the job can constitute an impediment. About 12% of people who are weakly attached to the labour market live outside of economic centres (at least 5 km away of the economic centre of the county) and do not have access to a family car. Among people with a solid attachment to the labour market, they are only 7% in this situation. The correlation between labour market attachment and the possession of a household car confounds two effects: first, the lack of a household car can be a barrier to access to (good) jobs; second, workers in good jobs and a high pay can afford cars more easily.
5.4.6. Labour market obstacles differ across population groups with weak labour market attachment
Although all major obstacles to labour market inclusion (such as challenges concerning skills and health) are widespread among the different sub-groups with a weak labour market attachment, the patterns of obstacles vary across groups.
People who are entirely out of employment tend to have more problems with being available for work and with accessing job offers. They are much more likely than other groups to have health issues (24% versus 14% to 18% in other groups). This finding suggests that people with health issues are more likely to drop out of employment altogether, rather than remaining in precarious or interrupted employment. People out of employment have also more often a household member with disabilities or an older person in the household, which might give rise to care obligations. In addition, they live more frequently in households in which no member is well-attached to the labour market, implying that the resources might be too tight to look for a job or even to participate in ALMP programmes. They are slightly more likely to live in high joblessness areas and often live far from economic centres while lacking access to a car.
People with interrupted working records frequently face challenges related to skills as well as unique personal obstacles concerning their motivation and health. They have more often a low level of educational attainment than other groups and many of them lack professional education. In this group, the share of people with a recent history of misconduct as the reason for job termination is outstandingly high (10%, compared to 2-8% in the other groups). Although the numbers are low and data incomplete, there is an indication that this group might face more challenges due to alcohol addiction and criminal activities in the past (the different obstacles not necessarily occurring simultaneously).
Precarious contracts concern, relatively speaking, more people who live far from economic centres and have no access to a car. Among the people who have precarious contracts, the share of people with a significant non-labour income is the lowest (3% versus 4% to 7% in the other groups). While this means that the monetary disincentive effect is the lowest for them, it also means that they have lower access to benefits as well as potentially less opportunities to save and invest.
A particularly high share of people with low earnings do not speak Estonian as their primary language (39% versus 28% among the well-attached). Many low-earners have care obligations because they have young children and/or are single parents. This group has also a comparatively high share of people with significant non-labour income, partially driven by child benefits.
Table 5.1 presents also obstacles for pensioners (people in retirement age and younger people receiving pension benefits). While health is in general a major concern for people in older age groups, this is not reflected in Table 5.1, as pensioners who have significant health issues are not included in the analysis. In addition, most people in this group receive non-labour income through pension payments, which is why this is not included as an additional obstacle for this group.
Among the pensioners who could have potential for a better integration to the labour market, the share of people who were not born in Estonia is particularly high, at 31%, much higher than among younger groups. Simultaneously, for 40% of this group, Estonian is not their mother tongue. This means that this group involves relatively more people who immigrated to Estonia during the Soviet era.
The group of pensioners who could have a better labour market attachment has also a high share of people who have no other person in their household who is well attached to the labour market (69%). This result is due to the fact that often both partners in the household are retired or the retiree lives alone. On the other hand, the small size of the households also explains the lower share of people with care obligations.
References
[1] Browne, J. et al. (2018), “Faces of Joblessness in Estonia: A People-centred perspective on employment barriers and policies”, OECD Social, Employment and Migration Working Papers, No. 206, OECD Publishing, Paris, https://dx.doi.org/10.1787/6d9cd656-en.
[3] Card, D., J. Kluve and A. Weber (2017), “What Works? A Meta Analysis of Recent Active Labor Market Program Evaluations”, Journal of the European Economic Association, Vol. 16/3, pp. 894-931, https://doi.org/10.1093/jeea/jvx028.
[2] Fernandez, R. et al. (2016), “Faces of Joblessness: Characterising Employment Barriers to Inform Policy”, OECD Social, Employment and Migration Working Papers, No. 192, OECD Publishing, Paris, https://dx.doi.org/10.1787/5jlwvz47xptj-en.
[5] Immervoll, H. and S. Scarpetta (2012), “Activation and employment support policies in OECD countries. An overview of current approaches”, IZA Journal of Labor Policy, Vol. 1/9, https://doi.org/10.1186/2193-9004-1-9.
[4] OECD (2019), Pensions at a Glance 2019: OECD and G20 Indicators, OECD Publishing, Paris, https://doi.org/10.1787/b6d3dcfc-en.
Note
← 1. This includes all 15-64 year-olds except people receiving pensions.