The FUA of Tallinn includes the city of Tallinn in itself (the ‘city’), as well as areas around the city that are closely linked to it from a functional point of view (the ‘commuting zone’). It is the strongest economic region in the country and also is the most populated area in Estonia. Nearly half of the Estonian population (605,019 people in 2021) lives in the Tallinn FUA, which itself forms only about one-tenth of the total land area of Estonia (4,327km2).
Main challenges, trends and policies
Within the domain of housing, the core form of youth inequalities in the Tallinn FUA runs along ethnic and family background dimensions, with these being related to the lower income of young people and fewer opportunities for Russian speakers. The fifteen to the twenty-nine-year-old cohort is in a more difficult situation than other age groups in the housing market. They earn less and do not have the start-up capital required for buying market-priced housing in a situation in which property prices tend to rise at a much faster pace than income levels. The result is that approximately one-quarter of young people have not entered the housing market by the time they are aged thirty. Our analysis also shows that the domain of housing is characterized by weak policy regulations. Until the 2000s, the state had almost withdrawn from housing policy and the housing market operated on market economy principles. Today, the domain of housing needs stronger policies in order to tackle inequalities, such as increasing the share of public housing and increasing the role of the (public) rental market.
Within the domain of employment, the core form of youth inequalities in the Tallinn FUA runs along both ethnic and gender dimensions. Estonia has the largest horizontal and vertical gender segregation levels in the European Union, as well as the largest gender wage gap. Youth unemployment is pretty well covered by national policies, but we judge that ethnic inequality are insufficiently addressed by current policy programmes. One of the core priorities should be to lower barriers for Russian-Estonian youths so that they can more easily enter the labour market.
Within the domain of education, the core form of youth inequalities in the Tallinn FUA runs along the ethnic divide. Information regarding school attendance levels, study results, and higher-obtained education level refers to evident inequalities between Estonians and Estonian-Russians (Estonian-speakers and Russian-speakers). Ethnic inequalities are targeted by policies which aim to improve the situation for young people who use Russian as a mother tongue when it comes to their Estonian language skills, in order to improve their chances of being able to enter into higher education and hence their labour market prospects.
Discussion and main conclusions
- Estonia’s rapid economic development has influenced the younger generation when providing improving incomes and better living conditions.
- However, the country’s relatively homogenous society, as it was during the end of the Soviet period when compared to that of Western Europe, has fast reached the point at which socio-economic segregation is rising at one of the highest speeds in Europe.
- During the post-credit-crisis period (2010 onwards), one of the goals of contemporary educational policy strategies was to increase the use of modern forms of digital technology in learning, teaching, and the improvement of digital skills. As has lately been revealed during the Covid-19 crisis, the selected policy direction towards e-learning has made it possible to switch over to distance learning in relative smoothness.
- Estonia has the largest horizontal and vertical gender segregation levels within the European Union, while also having the largest gender wage gap. According to data from 2013, the horizontal gender segregation rate (the concentration of men and women in different sectors) in those people who are employed was at 37.4% in Estonia. This figure has remained at about the same level, being at 37.0% in 2019. The vertical gender segregation rate (the concentration of men and women in different occupations) was at 40% in 2013, but this has decreased to 34.6%. The hourly wage gap between men and women in 2005 was at 25.4%.
- Gender segregation in the labour market depends upon gender stereotypes and their impact on the educational, vocational, and professional choices of men and women. This often starts in education, where males and females tend to study different professions, with both sides being influenced by the strongly-rooted expectation in the labour market of there being ‘men’s jobs’ and ’women’s jobs’. Gender segregation is addressed mainly through national policies throughout the study period. This has become one of the core targets of recent employment policies. However, there is no single dominant factor which tends to affect the wage gap in Estonia and no single policy available to overcome the issue. This particularly emphasises the need for the integration of research and policymaking within and on the borderline of different domains, such as in terms of education and employment.
- One of the more innovative policies which have been undertaken in order to tackle gender segregation and to increase birth rates has been the reforms in childcare leave which now allow men to take paternity leave and to care for their children during the three first years of that child’s life, putting them on an equal footing with women. As a result, Estonia has become a country which has particularly effective support measures in place for male parental leave, although this option is not yet being fully used due to the gender wage gap and gender roles in society.
- We propose that the domain of education has a higher level of perspective when it comes to reducing youth inequality across all domains. A low level of education is one of the main factors which serves to increase the risk of future unemployment, which also then reduces youth opportunities in the housing market.
Tallinn Urban Story Our storymaps draw together insights on inequalities and policies affecting urban youth, across education, employment and housing, from the WP2 urban reports and data analyses.