Stefan Fina, Bastian Heider, Märt Masso Unequal Estonia Regional socio-economic disparities in Estonia

FRIEDRICH-EBERT-STIFTUNG – POLITICS FOR EUROPE Europe needs social democracy! Why do we need Europe? Can we demonstrate to European citizens the opportunities offered by social politics and a strong social democracy in Europe? This is the aim of the new Friedrich-Ebert-Stiftung project“Politics for Europe”. It shows that European integration can be done in a democratic, economic and socially balanced way and with a reliable foreign policy. The following issues will be particularly important: – Democratic Europe – Social and ecological transformation – Economic and social policy in Europe – Foreign and security policy in Europe We focus on these issues in our events and publications. We provide impetus and offer advice to decision-makers in politics and trade unions. Our aim is to drive the debate on the future of Europe forward and to develop specific proposals to shape central policy areas. With this publication series we want to engage you in the debate on the“Politics for Europe”! About this publication In recent years Estonia has been among the fastest growing economies of the EU and has successfully established itself on the global mind map as a land of opportunity for digital transformation. However, a closer look reveals an uneven picture of the Estonian growth story. Similar to other European countries, economic, digital and ecological transitions have amplified structural change. The capability to adapt to these changes in society and economy is unequally spread, with some regions benefiting from change and others falling behind. The Estonian regional disparity report identifies current spatial variations of strengths and weaknesses in light of future risks and challenges for the country and calls for new national and European policies to address the issue. About the Authors Stefan Fina is a Geography Professor at RWTH Aachen University and Head of the Geoinformation and Monitoring section at ILS – Research Institute of Regional and Urban Development Dortmund. Bastian Heider is an economic geographer and co-manages the Geoinformation and Monitoring section at ILS – Research Institute of Regional and Urban Development Dortmund. Märt Masso has been a senior labour and social policy analyst since 2012, and Labour and Social Policy Programme Manager since 2015 with the Praxis Center for Policy Studies. He is also national correspondent and coordinates the Estonian team in the European Social Policy Network. Responsible for this publication within the FES Dr. Philipp Fink, Director Friedrich-Ebert-Stiftung Nordic Countries. Peer Krumrey, Director Friedrich-Ebert-Stiftung Baltic States. With the financial support of the European Parliament. The present report does not represent the European Parliament’s views. Additional information and supplementary materials can be found at https://fes.de/unequal-estonia

Stefan Fina, Bastian Heider, Märt Masso Unequal Estonia Regional socio-economic disparities in Estonia FOREWORD 2 1. INEQUALITY OF LIVING STANDARDS IN ESTONIAN REGIONS 4 2. ESTONIA TODAY 6 2.1 Diverging developments in the“European Silicon Valley” 7 2.2 Four Estonias 9 3. NEW POLICIES FOR EQUALITY OF LIVING CONDITIONS AND SOCIAL COHESION 13 3.1 Diluting concentration 13 3.2 Redistribution of public resources 13 3.3 Fluid administrative units 14 ANNEX A  Indicator documentation 15 ANNEX B  Methodological notes 16 ANNEX C  Indicator value ranges 17 Literature 18 List of figures and tables 19

FRIEDRICH-EBERT-STIFTUNG – POLITICS FOR EUROPE 2 FOREWORD Estonia has successfully established itself on the global mind map as the land of opportunity for the digital transformation. When the small Baltic state regained its independence in the early 1990s it set out immediately on a path of restructuring its economy and society which in turn led to an impressive transformation success story. Within only 30 years the former Soviet republic has largely closed the gap to other European nations in almost all relevant indicators like income, wealth or education of its citizens. It has overcome its forceful integration into the Soviet planned economy and has taken up its historical ties to Finland and other European countries. This, however, was done under the liberal zeitgeist of the time. Thus, actively counteracting social cleavages has not been a top priority and, like its Baltic neighbours, Estonia pursued largely a catch-up paradigm instead. For instance, the country was the first in the world to introduce a flat tax system and focused largely on building up economic powerhouses instead of fostering regional coherence. Although the indicators for uneven distribution of wealth and opportunities have been converging in the wake of Estonia’s advancement, critical voices can be heard from within the country. While opening the fall session of the Riigikogu(parliament) in 2020, president Kersti Kaljulaid pointed out that while the level of prosperity in the Tallinn region is at 135 per cent of the EU average, the rest of Estonia has reached only 55 per cent. While the country scores highly in introducing policies aimed at achieving the UN sustainable development goals and ranked 10th worldwide in 2019, other societal indicators are clearly lagging behind. Estonia has, for instance, a very low level of union density and the worst gender pay gap of all European Union member states. Though the country pioneered many digital developments and became synonymous for a small and open economy, it is an open question whether technical change can be utilised for further social progress. Causing some turmoil in the Estonian party system, the rise of the newly(re-)established party EKRE is widely explained by an increasingly fractured society in terms of access to welfare and personal development potential. Consequently, a closer look reveals an uneven picture of the Estonian growth story. Similar to other European countries, economic, digital and ecological transitions have amplified structural change. The capability to adapt to these changes in society and economy is unequally distributed, with some regions benefiting from change and others falling behind. There is more and more evidence that social inequalities are increasingly linked to regional disparities. It appears difficult to fight inequalities without addressing the regional divide. Estonia is a diverse country, in which the inhabitants are often faced with different living circumstances based on their place of residence. The cluster analysis undertaken in this report by Stefan Fina and his team at the Research Institute for Regional and Urban Development(ILS) Dortmund in collaboration with our Estonian partners shows that in terms of living conditions, economic indicators and social well-being, Estonia can be divided into four distinct regions that we call the“Four Estonias”. Roughly half of the population lives in dynamic urban regions, while the other half lives in areas that do not reach the same level of welfare. At the same time, the latter category consists of two-thirds of Estonian municipalities with higher rates of unemployment and poverty, higher dependency ratios and lower income levels as well as a lower provision of public services. The success of the Estonian development model and the ability of public institutions to guarantee equal living standards and equal chances for individuals crucially depend on the way in which non-urban areas and small cities will be integrated into the development strategy. There is a vicious circle that needs to be diffused: on the one hand, some“forgotten areas” are falling behind in economic activity, resulting in highly skilled people to move away. This in turn results in worsening infrastructure and public services. On the other hand, highly urbanised areas, where economic activity is concentrated, attract more and more people, resulting in greater competition for jobs, higher living and housing costs and a higher risk of social exclusion. Can we think of a development model that offers equal opportunities and high standards of living regardless of one’s place of residence? The challenge we want to highlight, for national as well as for European policymakers is that it is impossible to provide opportunities and equality for all individuals regardless of their economic and social background unless regional inequalities are addressed. The results of this report underline the need to overhaul economic and social policies at the national as well as at the

Foreword 3 EU level. The authors point to the importance of an equal level of welfare provision throughout the country. In order to achieve that, they suggest changing the way regional disparities are thought of. Policies should be directed towards investing in people and not in administrative structures. Without the intervention of the public sector, no opportunities are going to be generated. It is not only a matter of placing a stronger emphasis on the needs of lagging regions, it is rather the need to understand economic development as sustainable over time only if all areas develop and attain higher levels of well-being. tioning democratic and political institutions. To diffuse rising dissatisfaction, EU member states and EU institutions need to address these inequalities and to cater for a more even development path. PEER KRUMREY Director Friedrich-Ebert-Stiftung Office for the Baltic States DR. DAVID RINALDI Director of Studies and Policy Foundation for European Progressive Studies The same approach should be taken at the EU level. The example of Estonia shows the need to adjust the scope of EU cohesion policies and understand that many other European policies can help addressing social and regional divides: the EU green deal, the EU strategy for the rights of the child, the EU gender equality strategy, to name a few. Regional and structural policies should be more intertwined with other policy programmes such as research and development, innovation, and industrial policy. A broader approach towards creating economic and social well-being needs to be followed, with the EU addressing the issue of social and economic inequalities in all their dimensions. Possible social and economic push-and-pull factors of regional development should be considered in programme and policy designs. Rather than focussing on the spatial concentration of growth and employment effects, the aim should be to attain a more balanced growth picture by forging links between dynamic growth centres and lagging regions. This study, which was written with the support of the Estonian research centre Praxis, is part of a joint FES and FEPS project on regional socioeconomic disparities in five EU member states(Estonia, Finland, Sweden, Italy and Romania). The findings of the national disparity studies form the basis for a European analysis aiming to put forward proposals to reform of the EU approach to regional policy and enhance the EU’s ability to fine tune its cohesion policies. Local development and well-being in all areas of a country are not only a goal for economic policy, rather it is a matter of strengthening democracy and ensuring opportunities and participation for all. Growing spatial inequalities in many EU member states have been fuelling the rise of anti-democratic movements and forces, which are ques-

FRIEDRICH-EBERT-STIFTUNG – POLITICS FOR EUROPE 4 1 INEQUALITY OF LIVING STANDARDS IN ESTONIAN REGIONS Since it regained independence in 1991, Estonia has achieved serious upward socio-economic development, thanks to both agile socio-political reforms and the resilience of the Estonian people. Since Estonia’s transition to a liberal market economy, its economic growth has been among the fastest in the world. Although the global financial crisis in 2008 triggered a severe recession in Europe, by 2010 the economic situation in Estonia had improved and already by 2012 the country had experienced one of the fastest recoveries in the European Union. This good economic performance has contributed to some convergence with richer European countries(Eurofound 2019). During the past decade, Estonia has closed the gap on most social and economic indicators, including real GDP per capita, nominal wages, employment rate, and at-risk-of-poverty rate or social exclusion. As hinted, however, this small, open economy has also been very dynamic over economic cycles. This underlines the nature of the challenge: catching up with more socio-economically developed European regions occurs when the economy is growing, but when it experiences a downturn, there is a risk of increased disparities or a slowdown in the catch-up process(see also Eurofound 2020). This is a warning signal to Estonian society to avoid history repeating itself in the face of the Covid-19 crisis, which could lead to a decline in living standards and divergence or a slowing down of convergence with better performing member states. Many features of Estonia’s socio-economic institutions, notably the governance of the labour market, the welfare state, education and training are very similar to those of liberal market economies, although there are also some features that do not fit the classical model, notably its corporate governance institution and resemblance to a coordinated market economy(Feldman 2017). In particular, the Estonian social protection system combines several models, but it is probably closest to the economic liberal social protection system, characterised by low redistribution, contributory social security schemes and the aim of stimulating the labour supply(Masso et al. 2019). The share of expenditure devoted to social protection has always been considerably lower in Estonia than in other EU member states; according to Eurostat, in 2019, it was 27 per cent in the EU28 but only 16 per cent in Estonia. Also, despite the upward convergence with more generous social protection systems before the global financial crisis, during the past decade convergence has been slow or even absent. The discussion above already indicates that general government expenditure makes up a smaller share of GDP(38.9 per cent in 2018) in Estonia than in a great majority of EU countries(EU28 average in 2018 – 45.8 per cent)(Eurostat). Out of this, the central government’s share is remarkably large, at 87 per cent. In terms of municipal expenditure as a percentage of general government expenditure, Estonia is below the OECD average(OECD 2016). Municipal finan‑ ces are very centralised, with approximately 80 per cent of municipal revenues centrally regulated(for example, personal income tax, grants, and an adjustable land tax). Over the decades, Estonian administrative organisation has been in a constant state of change as society itself has been constantly changing. Administrative organisation must keep pace with that. In 2016, the Administrative Reform Act was adopted in the Riigikogu. Most importantly, enforcement of the reforms has led to a noticeable decline in the number of self-governing cities and rural municipalities in Estonia: the number of municipalities was reduced from 213 in 2012 to 79 in 2017. The upshot of this is local government units with a bigger area, population, economic activity, infrastructure and other institutional frameworks. Currently it is not clear what the outcome for regional development, including regional disparities, will be. However, the expectation is that the government’s institutional capacity will considerably improve, which will also lead to upward convergence in social and economic development and living conditions across Estonia’s regions. Clearly, the road to balanced regional development is complex and influenced by a number of factors. These include general demographic trends of population ageing and risk of population decline, and, more importantly, the increasing population share in Harju county and Tallinn out of the total population. In fact, the biggest municipality in Estonia, Tallinn, is roughly 4.5 times bigger than the second largest municipality, Tartu(and about 3,000 times bigger than the smallest municipality, Ruhnu). This reminds us that regional development programmes that address development disparities and support laggards in catching up are crucial. Since the 1990s, a number of initiatives have emerged. In recent decades, the key national regional development documents include: – Concept of Regional Policy(1994); – Estonian Regional Development Strategy(1999);

Inequality of living standards in Estonian regions 5 – Estonian Regional Development Strategy 2005–2015 (2005); – Estonian Regional Development Strategy 2014–2020 (2014). The regional policy is part of the government’s initiatives to improve living conditions in all regions, including access to public services, capacity for economic participation and growth, regional balance of population and settlement trends, territorial integrity, and sustainable development. The latest development strategy is concerned with the persistence of“differences within Estonia in terms of regional socio-economic development[that] are rather big compared to Europe and other developed economies, considering the small size of the country. With this strategy, the Government of Estonia wishes to harmonise regional development so that each region may rely on its specific character and strength and increase the competitiveness of the country as a whole, so that people will have access to good jobs, services, opportunities for self-realisation and a living environment that allows a range of activities.” However, most studies and reviews of regional development point out that:(i) internal migration has been widening demographic disparities, including increased urbanisation;(ii) as a result of this, economic activity also tends to concentrate in major urban areas, such as Tallinn and Tartu; and(iii) as a consequence, GDP per capita, labour force participation, and productivity have been modest outside Harju and Tartu counties(Servinski et al. 2016; Estonian Cooperation Assembly 2020; Arenguseire 2019). In this report, regional disparities in Estonia will be described further, and some ways forward will be suggested at the end.

FRIEDRICH-EBERT-STIFTUNG – POLITICS FOR EUROPE 6 2 ESTONIA TODAY “Growth is strong, although slowing.” This is the headline of an economic survey on Estonia conducted in 2019(OECD 2020). In comparison with other OECD countries, Estonia has managed impressive convergence of socio-economic development since the restoration of independence in 1991, more recently with an internationally renowned advance in digital business opportunities. At the same time, the OECD report highlights that socioeconomic challenges persist: inefficiencies in productivity, inequalities of income and health levels, poor environmental quality and demographic ageing are among them. The OECD assessment looks at national trends that condition and are conditioned by regional developments. Within the country, twenty-first century transformation pressures in a globalised world expose regional economies to new drivers of inequality and diverging living conditions. Development is therefore challenged by problems of growing regional polarisation and a new form of peripheralisation(Estonian Cooperation Assembly 2020). Since 2020, socio-economic development has been strongly affected by the Covid-19 pand­ emic, which has made economic and living conditions volatile, and will also influence the recovery and future national and regional development. When analysing socioeconomic development trends across 79 Estonian municipalities using data from before the Covid-19 pandemic, the following key findings emerge: – Municipalities in commuting distance of the capital Tallinn fare best. They are home to large segments of highly qualified and high-income workers and have the highest surplus of people moving to the area from other regions. Very good living conditions can also be found in the sparsely populated Alutaguse national park in the Northeast and the island resorts of Kihnu and Ruhnu in the Gulf of Riga. – The largest Estonian cities – Tallinn, Tartu, Narva, Pärnu – drive economic development in Estonia. On average, living conditions in the cities are therefore better than the Estonian average. Coastal regions of the North, the island of Hiiuma and inland regions like Viljandi, PõhjaSakala, Kastre and Nõo vald show similar advantages. However, not everyone benefits equally from good socioeconomic framing conditions. A considerable gender pay gap and limited government revenues, as well as below average health services are among the indicators on which these regions show average or below average values compared with the rest of Estonia. – Large areas in inland Estonia are challenged by the persistent problems of demographic ageing, out-migration and related problems: educational opportunities are limited as are local government investment capacities. Limited business opportunities and incomes, as well as lower levels of participation are the main challenges here. – A limited number of administrative areas in the Northeast show the most significant disadvantages. The city of Narva and surrounding municipalities are confronted with very high unemployment rates, comparatively low incomes and a very high gender pay gap in comparison with the rest of Estonia, although the workforce has a fairly high educational level on average. Long-standing structural disadvantages in these municipalities lead to very low participation levels and out-migration. The disparities in these areas remain a major challenge for the convergence of Estonian development trends. – A countrywide assessment of socioeconomic disparities identifies demographic ageing and migration patterns as a significant risk to the socioeconomic stability of outlying regions in Estonia. Areas with a significant loss of younger people are exposed to follow-on problems of shrinkage. Estonia currently faces a turning point in its socioeconomic development. Recent achievements in sectors such as information technology are increasingly being challenged by global competition for business opportunities and the prospects they offer for a highly educated workforce. Continued political support is needed to improve the outlook for young and talented people. Fossil fuel–dependant economic activities need to be transformed in the direction of clean and renewable energy options(OECD 2020). At the same time, disadvantaged areas require investments to develop business opportunities and the infrastructural backbone for attractive living conditions across regions. The analysis of socioeconomic disparities in this report thus constitutes a regionally differentiated presentation of Estonia’s framing conditions for future development. It discusses current spatial variations in terms of strengths and weakness-

Estonia today 7 es, in light of future risks and challenges. Selected indicators cover(i) the economy, employment and the labour market; (ii) educational opportunities and life chances;(iii) prosperity and health;(iv) state action and participation; and(v) internal migration patterns. 2.1 DIVERGING DEVELOPMENTS IN THE “EUROPEAN SILICON VALLEY” The strengths and weaknesses of Estonia’s socioeconomic geography are diverse. Indicators used to capture their spatial variation and differences were chosen for their explanatory power in relation to selected topics. They stand as proxies for unequal developments that can be associated with geographical framing conditions and interpreted in comparison with developments elsewhere in the country. Next to the choice of indicators the spatial granularity for input data is important. Values for indicators can more clearly be attributed to the policy environment if the area of observation accurately represents a sphere of influence for political action and governance. Even though national and state policies, as well as local decisions, always interact to some degree, values for the municipal level 1 are more informative in this context than overarching administrative levels, at which data are aggregated and resulting averages can lead to a blurring of spatial patterns. The novelty of this report is the integrated analysis of a comprehensive set of indicators at the municipal level in a geostatistical procedure known as cluster analysis. Single-indicator maps are combined into areas with similar strengths and weaknesses in comparison with the national average. The resulting map provides information about the spatial typology of disparities in Estonia, the so-called disparity map of Estonia. It is important to read the map in conjunction with the statistical information that characterises a cluster. Moreover, a brief textual interpretation describes the visible spatial patterns with a view towards uncovering explanatory factors. 2 1. Unemployment rate, demographic dependency ratio(Economy, employment, and labour market): Employment is the foundation of economic activity. Higher rates demonstrate a successful match between the job opportunities a region has to offer and the skill levels and preferences of the local and regional workforce. Employed people usually generate income for their households and for dependent people through their earnings and social insurance contributions. The demographic dependency ratio indicates the ratio of dependant people to working age people. Higher values pinpoint higher demand on the part of dependent people and higher pressure on private and public funds to support them. High values are frequently an implication of demographic ageing and out-migration of working-age people. 1 LAU 2(local administrative unit level 2 defined by the European Union). 2 In bold: indicator name; in italics: topic group. 2. School dropout rate, highly qualified people(Educational opportunities and life chances): A high school dropout rate indicates limited prospects for affected people in a transforming labour market. Many studies have shown that education is the one decisive factor enabling people to succeed in the labour market and to improve their life chances. High values therefore signify problem areas even if unemployment is low. The share of highly qualified people further emphasises the importance of education. Higher values show where more people have the prerequisites to compete in an increasingly competitive labour market if matching job opportunities exist. The current match, however, is only part of the picture. Higher education levels are also associated with higher potential for personal development and reorientation in a transforming labour market. 3. Average gross income, gender pay gap, family doctors(Prosperity and health): Income is fundamental to covering the cost of living. Insufficient income leads to exclusion and pressure on families and/or government to cover living costs for dependent people. The number of family doctors per 10,000 inhabitants is used as a proxy for the availability of health services in a region. Higher shares can be the result of high demand, for example in regions with high shares of elderly people, or high demand for specialised health services. Regional variations in the gender pay gap show where women’s salaries deviate from men’s average salaries. High values (meaning women earn less than men) can frequently be found in highly qualified jobs where issues of gender equality are not regulated. 4. Voter turnout, local government revenues per capita(State action and participation): The share of people who vote at local elections shows people’s interest in democratic participation. Higher shares are frequently attributed to higher levels of education and wealth, affluent and educated people are more likely to vote. Especially in local elections certain“hot” topics and the local appeal of certain personalities can also motivate people to vote. This can also be seen as a positive contribution to participation. Local government revenues per capita(in euro) are a key component of local government budgets. Higher revenues allow higher investments in infrastructure and services. Higher levels are associated with higher quality infrastructure and services that are more likely to match the demands of local users. 5. Internal migration balance(Migration): The balance of in- and out-migration can be interpreted as an early-warning indication of spatial mismatches between people’s expectations regarding their life chances, on the one hand, and the significance of shortcomings that may motivate migration, on the other. Demand and supply of infrastructure, stability of the labour market, and many cultural and societal inequalities are associated with migration patterns and the resulting population base. In this context, internal migration can be interpreted as an expression of locational preferences and

FRIEDRICH-EBERT-STIFTUNG – POLITICS FOR EUROPE 8 the perceptions of desirable living conditions among the Estonian population. Figure 1 shows the resulting spatial typology for Estonia in the national disparity map. The clusters are framed semantically, with labels derived from the interpretation of indicator values and additional information on the geography of their delineation. Table 1 provides a summary overview of indicators that characterise the single spatial types. Arrows are used to symbolise the mathematical value of indicator values (very high: ↑ ; high: ↗ ; average: o ; low: ↘ ; very low: ↓ ). In some cases, high values stand for a positive locational factor (high values for average incomes, high employment rates), in others they are rather negative for life chances(high school dropout rates or a high dependency ratio). For this reason, an additional colour background(shades of green= rather positive or very positive; light grey= average; shades of red= rather negative or very negative) is used to indicate the assessment of values in terms of a region’s strengths or weaknesses – always to be interpreted in comparison with national averages. The combination of the disparity map and its constitutive statistical values aims to aid interpretation. An interactive web map allows further investigation of values for all input variables and their combined effect in the disparity map: https://fes.de/unequal-estonia. Figure 1 The Estonian disparity map Tallinn ! Keila ! ! Maardu ! Rakvere Kohtla-Järve ! Sillamäe ! ! Jõhvi Narva ! ! Haapsalu Kuressaare ! Pärnu ! Viljandi ! ! Tartu Cities(inhabitants) ! City > 400,000 ! City > 100,000 ! City > 10,000 primary road system 0 50 km Cluster ! Valga ! Võru Flourishing regions and islands of prosperity Low population density Better-off Estonia Shrinking regions with socioeconomic problems Hot spots of long-standing structural disadvantage excluded Data Geodata: EuroGeographics, Geofabrik GmbH, OpenStreetMap Contributors 2018 Source: Authors’ illustration. Data: Estonia Statistics, Estonian Unemployment Insurance Board, National Institute for Health Development Estonia, Eurostat.

Estonia today 9 2.2 FOUR ESTONIAS The disparity map shows that Estonia can be differentiated into four spatial types with distinct socioeconomic advantages and disadvantages. The legend uses associative colours: shades of green show areas that are currently faring better by overall assessment and seem to be better prepared for the challenges of the future, at least for the majority of people. Ochre indicates areas that frequently have indicator values close to the national average. Violet is used to map out areas with a majority of negative indicator values – areas in need of dedicated policy attention. Based on this colour interpretation the map shows basically three settings for socioeconomic disparities: average, above average, and below average. tion of Estonian independence. The below average regions are populated by 0.65 million people(49 per cent of the Estonian population) in 48 municipalities(61 per cent of all Estonian municipalities). This summary characterises and visualises the patterns of disparities at a glance. The definition of such spatial types also lends itself to the evaluation of social and economic policies in the future. For this purpose, Table 2 shows the current bandwidths of indicator values accompanied by the names of the respective municipalities, with minimum and maximum values within each cluster. 1. Above average: With the exception of the special cases of the islands of wealth(including the“metaphorical island” of Alutaguse), the prospering regions and better-off Estonia(light and darker green in Figure 1) form adjacent delineations, with an urban core as the nucleus for growth and prosperity. These two clusters are populated by 0.68 million people(51 per cent of the Estonian population) in 31 municipalities(39 per cent of all 79 Estonian municipalities). Despite their decisive role in economic dynamics, the cities of Tallinn and Tartu are not among the most prosperous regions. This can be explained by the fairly large share of disadvantaged households that also reside in the capital and in Tartu, European Capital of Culture in 2024. Spatial extent can be understood as the area of reach for functional relationships between core and suburban or ex-urban commutersheds, on one hand, and other spillover effects from the urban core, on the other. Economies of scale play a decisive role in explaining these areas’ economic attractiveness: high quality infrastructure and services, human resources and proximity to regional and supra-regional markets are economic advantages that frequently outweigh higher locational costs for businesses. 2. Below average: Socioeconomic development in Estonia’s shrinking regions with socioeconomic problems (ochre in Figure 1) contrasts with developments in urbanised areas and their catchments. This is where young people are leaving the countryside in large numbers, for educational purposes, searching for job opportunities and/or affluent urban lifestyles. The remaining population is therefore older on average, in need of a good health system that matches the high demand, and social transfers to support more dependent people. Prospects in the shrinking regions can become problematic if old industries, such as mining, run out of resources and are phased out, and/or(digital) automation processes lead to the replacement of workers and to continued shrinkage. Improving education levels and developing new job opportunities are key challenges for future development. The three municipalities in the cluster minority areas of significant structural disadvantage have been subject to long-standing disadvantages of a similar kind, even though the explanatory factors are deeply rooted in the transformation dynamics after the restora-

FRIEDRICH-EBERT-STIFTUNG – POLITICS FOR EUROPE Table 1 Spatial typology of socioeconomic disparities in Estonia Value key: very high values:  ↑ high values:  ↗ average values:  o low values:  ↘ very low values:  ↓ How to interpret: very positive positive average negative very negative  Characterisation Flourishing regions and islands of prosperity (8+2 municipalities 3 ; 0.1 million inhabitants) Indicator assessment Spatial delineation Estonia’s regions with the best socioeconomic framing conditions for a high quality of life are located in suburban locations close to the capital Tallinn, offshore islands in the Baltic Sea and the Gulf of Riga, and in a sparsely populated but large national park region in the East(Alutaguse). This is where the largest share of highly qualified people earn the highest incomes compared with the national average, local government revenues are highest, people participate in larger numbers in local elections, and the migration balance has the highest surplus. As a consequence, unemployment is comparatively low, fewer people rely on working-age people to support them(low dependency ratio), and school dropouts are few. On the downside, health services as expressed by the number of doctors per capi­ta can be stretched, and women have less chance of equal pay. This cluster comprises a small number of municipalities with only 0.1 million residents. Unemployment rate: 4.2% ↘ Dependency ratio: 56.3% ↘ Highly qualified: 40.8% ↑ School dropout rate: 3.8% ↘ Gross income: 1,604 EUR ↑ Gender pay gap: 78.1% o Family doctors: 2.9 per ↘ 10,000 inh. Local government ­ ↑ revenues: 1,801 EUR Voter turnout: 61.3% ↑ Internal migration balance: ↑ 92.3 inh. per 1,000 Better-off Estonia (21 municipalities; 0.58 million inhabitants) The second-best cluster in Estonia comprises a larger area of 21 municipalities with 0.58 million residents. In comparison with the previous cluster, incomes and qualifications, unemployment, and the dependency ratio, as well as the school dropout rate and in-migration surplus are slightly above the national average. Local government revenues are significantly lower, close to the national average. Fewer people participate in local elections. Family doctors have more patients to care for than the national average, and women earn considerably less than men. Explanatory factors point towards a more diversified social spectrum in this cluster: the urban population of the largest cities, Tallinn and Tartu, are home to disadvantaged, as well as affluent households. More remote areas benefit from stronger local economies, as well as their proximity to the lucrative labour markets of larger cities. At the same time, they are home to a significant share of lower income households. Unemployment rate: 4.6% ↘ Dependency ratio: 55.9% ↘ Highly qualified: 30.6% ↗ School dropout rate: 4.4% ↘ Gross income: 1,305 EUR ↗ Gender pay gap: 79.1% o Family doctors: 3.2 per ↘ 10,000 inh. Local government o ­revenues: 1,460 EUR Voter turnout: 56.1% o Internal migration balance: ↗ 44.6 inh. per 1,000 3 Kihnu and Ruhnu in the Gulf of Riga were not included in the cluster analysis because of their exceptional socioeconomic conditions as island resorts, with many statistical outlier values. They have subsequently been added to this cluster by manual comparison of indicator values. 10 >

Estonia today 11 Value key: very high values:  ↑ high values:  ↗ average values:  o low values:  ↘ very low values:  ↓ How to interpret: very positive positive average negative very negative  Characterisation Indicator assessment Shrinking regions with socioeconomic problems (45 municipalities; 0.55 million inhabitants) Spatial delineation The largest spatial cluster with a majority of Estonia’s municipalities is sparsely populated. Despite the considerable extent of this cluster, it is home to fewer people than better-off Estonia(0.55 million). In addition, this cluster shows significant signs of population loss as expressed by the out-migration surplus. The high dependency ratio shows that it is mainly working age people who leave the area, and older people and younger children need to be supported by the remaining workforce. It is likely that the higher demand of elderly people for medical services explains the higher number of family doctors per capi‑ ta. The socioeconomic prospects in this cluster are strongly reliant on employment opportunities and matching skill levels. In this respect, the below average rate of highly qualified people, as well as the higher number of school dropouts are reason for concern, as are the lower income levels in this cluster. Local government revenues are average, likewise the unemployment rate and the voter turnout. Due to the dynamics of shrinkage this cluster faces significant challenges at the crossroads of twenty-first century transformation pressures. Unemployment rate: 5.3% o Dependency ratio: 60.3% ↗ Highly qualified: 25.1% ↘ School dropout rate: 6.0% ↗ Gross income: 1,156 EUR ↘ Gender pay gap: 79.0% o Family doctors: 5.7 per ↗ 10,000 inh. Local government ­ o revenues: 1,442 EUR Voter turnout: 55.3% o Internal migration balance: ↘ −28.9 inh. per 1,000 Hot spots of long-standing structural disadvantage (3 municipalities; 0.1 million inhabitants) The by far smallest cluster, with only three municipalities, including the border town of Narva and two nearby communities, has 0.1 million inhabitants mainly of Russian descent. The socioeconomic disadvantages of this cluster are striking: unemployment rates are highest in comparison with the Estonian national average, incomes are lowest, as are government revenues and voter turnouts at local elections. Women earn significantly less than men, and a very high number of people leave the area. The fairly high number of qualified people can be seen as a relic of former living conditions that have long passed since the restoration of Estonian independence in 1991. The formerly privileged Russian minority experienced a massive decline in job opportunities in a transforming labour market. Overall, disparities in the municipalities of Narva, Kohtla-Järve and Sillamäe have advanced in recent years to form framing conditions that are clearly problematic for future socioeconomic development. Unemployment rate: 9.7% ↑ Dependency ratio: 62.9% ↗ Highly qualified: 33.2% ↗ School dropout rate: 5.0% o Gross income: 1,029 EUR ↓ Gender pay gap: 72.4% ↓ Family doctors: 7.1 per ↗ 10,000 inh. Local government ­ ↓ revenues: 1,239 EUR Voter turnout: 45.4% ↓ Internal migration balance: ↓ −50.8 inh. per 1,000 Source: Authors’ illustration. Data: stonia Statistics, Estonian Unemployment Insurance Board, National Institute for Health Development Estonia, Eurostat.

FRIEDRICH-EBERT-STIFTUNG – POLITICS FOR EUROPE 12 Table 2 Bandwidth of indicator values for spatial types Indicator Value ­Flourishing ­regions and ­islands of ­prosperity Better-off ­Estonia Shrinking ­regions with socioeconomic problems Hot spots of ­long-standing ­structural ­disadvantage Unemployment rate (%) Demographic ­dependency ratio(%) Share of people with higher education(%) School dropout rate (%) Average monthly gross ­income per ­employee(in EUR) Gender pay gap(%) Number of family ­doctors per 10,000 ­inhabitants Local government ­revenues per capita (in EUR) Voter turnout at local elections(%) Overall internal net ­migration balance per 1,000 inhabitants Min. 3.4(Kiili vald) 3.0(Hiiumaa vald) 3.6 vald) 9.1(Sillamäe linn) Max. 5.7(Alutaguse vald) 7.7 linn) 8.2(Valga vald) 10.4(Narva linn) Min. 45.1 vald) 48.2(Luunja vald) 52.3 linn) 62.4(Sillamäe linn) Max. 59.5 vald) 60.7 linn; PõhjaSakala vald) 68.0 linn) 63.5(Narva linn) Min. 29.2 vald) 21.9(Viljandi vald) 18.8(­Põhja-Pärnumaa vald) 31.4 linn) Max. 51.5 vald) 45.2(Tallinn) 42.1(Tartu linn) 35.9(Sillamäe linn) Min. 0.0(Vormsi vald) 1.5(Kuusalu vald) 2.3 vald) 4.6(Sillamäe linn) Max. 7.3( Viimsi vald) 7.7(Nõo vald) 13.5(Loksa linn) 5.6(Narva linn) Min. 1,171 vald) 1,048 linn) 1,036 vald) 989(Narva linn) Max. 1,819(Viimsi vald) 1,482(Keila linn) 1,341(Tartu linn) 1,054 linn) Min. 75.4(Viimsi vald) 73.8(Hiiumaa vald) 70.0 vald) 70.7(Sillamäe linn) Max. 82.5 vald) 85.4(Toila vald) 85.9 vald) 74.6(Narva linn) Min. 0.0(Vormsi vald) 0.7(Viljandi vald) 1.1(Järva vald) 6.2(Narva linn) Max. 5.7(Saku vald) 8.0(Keila linn) 11.1(Saarde vald) 8.0(Sillamäe linn) Min. 1,506(Saue vald) 1,250(Luunja vald) 1,222(Jõhvi vald) 1,189(Narva linn) Max. 2,607 vald) 1,706 linn) 1,695 vald) 1,275 linn) Min. 58.5(Saku vald) 49.2(Kohila vald) 43.1(Loksa linn) 40.7 linn) Max. 69.5(Vormsi vald) 61.7 linn) 65.9(Tõrva vald) 51.0(Sillamäe linn) Min. –33.8 vald) –33.0 vald) −58.8 vald) –59.4(Sillamäe linn) Max. 243.1(Rae vald) 208.2(Luunja vald) 22.2(Tori vald) − 38.9(Narva linn) Source: Authors’ illustration. Data: stonia Statistics, Estonian Unemployment Insurance Board, National Institute for Health Development Estonia, Eurostat.

New policies to foster equality of living conditions and social cohesion 13 3 NEW POLICIES TO FOSTER EQUALITY OF LIVING CONDITIONS AND SOCIAL COHESION 3.1 DILUTING CONCENTRATION Analysis of inequality of living standards across Estonia’s regions highlights that, despite the rapid upward socio-economic convergence of Estonia with other European countries, internal regional disparities persist. The current regional disparities mapped in the report reflect the trend of enduring spatial concentration of economic activity and population to a few regional centres. Similar to the current analysis, previous research has characterised Estonian regional development as follows: Tallinn(and to a lesser degree other cities) is the centre of gravity, at which people, economic activity and services are concentrating, while the rest of Estonia has lagged behind and is shrinking(Estonian Human Development Report 2019/2020). The regional cohesion policy has not been able to prevent the increasing concentration of economic activities in specific regions or to increase cohesion across regions significantly. The way forward, as has been suggested by regional development scenarios, is either to pursue a more energetic regional policy and support growth centres across the country, or to adapt to the spatially extremely concentrated economic model(Arenguseire 2019). The latter option would mean that only market forces could reverse the current state of regional disparities, but it is unlikely that market forces alone could foster the optimal employment of human and economic resources, as well as decent living conditions and opportunities in different geographic and administrative regions. The capacity to design and deliver public policies across regions has been contingent on the number and size of munici‑ palities in this small country. By 2017 Estonia had reformed the administrative division of local authorities, and the number of municipalities were reduced from 213 in 2012 to 79. The reform was expected to improve the capacity to provide public services of high quality, and in the end to support the cohesive development of living and employment conditions across regions. The administrative reform may be seen as the first building block of addressing the regional differences in administrative capacity, and further policymaking steps are required to figure out a reasonable balance between concentration and equal life and economic opportunities across the regions. The concentration of people and competences hinders the provision of public services. This, in turn, feeds into differences in socio-economic development levels across regions. That includes essential services for regions, such as health care and education. There are regional disparities in access to health care, as in the north-eastern region, where people report poorer access to health care due to longer waiting times(Kasekamp 2021). Regarding skills, it has been found that regional disparities in participation in education tend to widen as the level of education increases, although the largest differences between subnational regions are observed in enrolment in early childhood education and care for children under the age of three(OECD 2018). In this regard, the National Audit Office has suggested that the provision of primary public services outside Harju and Tartu counties needs restructuring. Lack of financial resources, but more importantly, the growing labour shortage in the regions as a result of workforce ageing and migration, constrain access and quality of public services. It has been argued that the way forward to cohesion is to introduce technical and organi‑ sational innovations that would reduce the need for labour or create incentives to attract people and employment to the regions. In a number of policy fields, promising practices are emerging. In employment policy, for instance, since April 2020, the unemployed can consult public employment services virtually, including through IT tools, such as Skype(EC 2021). Decoupling service design and implementation from physical and territorial contingencies could give a considerable boost to reducing regional disparities. Also, as always, the key to process innovation is cooperation, and for instance in the field of social protection central government has designed a consultation process for local governments to support local professionals in social services design and implementation. Similarly, local governments themselves have been cooperating in sharing knowhow on service design, but also cooperating in service delivery. 3.2 REDISTRIBUTION OF PUBLIC RESOURCES Turning a new page in regional cohesion policymaking might require paying more attention to the redistribution of public resources. First, research and development and innovation in Estonia are characterised by a large regional development gap. Companies in the Harju County and Tartu region are at the forefront of introducing Industry 4.0, integrating into global value chains, and implementing R&D-based innovation(Eljas-Taal et al. 2019). Furthermore, government busi-

FRIEDRICH-EBERT-STIFTUNG – POLITICS FOR EUROPE 14 ness and innovation support schemes are more likely to reinforce the current concentration of economic activity than to reduce disparities, and new incentives are needed to support regionally balanced socio-economic development(Männasoo et al. 2020). Reconsidering R&D schemes could play a key role in fostering convergence in regional development, but at the same time it might be challenging to avoid slowing down catchup with the more rapidly developing regions in Europe. Second, redistributing public resources between central and local government might also be needed. In terms of municipal expenditure as a percentage of general government expenditure, Estonia is below the OECD average. More equal redistribution of resources could empower local authorities to catch up with well-developed regions and incentivise cooperation among regions. Especially incentives that promote cooperation between the regions could encourage people to look beyond administrative borders and work together to support economic activity across the regions and guarantee high quality public service delivery. Estonian socio-economic cooperation with European countries near and far has been one of the development factors that have helped in upward convergence with more prosperous regions in Europe. It includes participation in European and global value chains, which has helped private sector companies and employees to develop Estonia and its regions. Also, institutional cooperation with European member state governments and accession to the European Union have opened up new potentials in institutional policy learning and redistribution of collectively created financial resources. had to accept an investment volume below 5 per cent. In conclusion, EU and national policies require further attention so that the periphery and diverging regions are not abandoned. 3.3 FLUID ADMINISTRATIVE UNITS In a small country like Estonia, the regional administrative units are not and should not be seen as clearly demarcated socio-economic spaces. Often, it is more important to look into connections and cooperation than administrative distinctions. That also means that cohesion policy needs to take multilocality and mobility into account. Administrative arrangements, spatial planning and public policy provisions should consider that Estonia has enabled living and working in more than one administrative region and thus commuting between regions(Estonian Human Development Report 2019/2020). That helps people and organisations to utilise the comparative advantages of different regions. For instance, someone could work in a region with good employment opportunities and live in a(different) region with good living conditions. Social cohesion also needs regionally aware policies across the public policy sphere. This functional approach is required to build links that would allow wealth and opportunities to spread from richer to poorer regions(European Semester: Country Report—Estonia. 2019). The cohesion policy framework should investigate not only administrative boundaries but also actual spaces of governance, the economy, and life. EU policies have helped Estonia with transnational convergence, but also with addressing its regional disparities. In this regard, the recent Operational Programme for European Union(EU) Cohesion Policy Funds 2014–2020 specifically redistributes resources for regional development. The mid-term evaluation in general concludes that a significant positive impact was also identified in realising the objectives of the Regional Development Strategy and the country-specific recommendations(Eljas-Taal et al. 2019). The Regional Development Strategy has made the greatest contribution to developing social and health care infrastructure and services across regions, improving access to jobs and economic competitiveness in different regions, while the development of transport links plays an important role in deepening connections within, between and across borders, but also the creation of a living environment that is environmentally friendly and conducive to the international competitiveness of larger urban areas. But the mid-term evaluation of funding also points to challenges in the ambitious plan to increase economic activity and welfare opportunities outside Harju County, namely the “share of GDP created outside Harju County and Tartu County in Estonia’s GDP”, which also shows a downward trend (2012: 29.7 per cent; 2018: 25.8 per cent; goal 2023: 30 per cent)(Eljas-Taal et al. 2019). The investment gap between Harju County and the other counties is still considerable; nearly 50 per cent of EU grants have gone to Harju and Tartu counties, while the majority of the remaining counties have In addition to the holistic cohesion policy, the details of regional disparities must be examined. The strengths and opportunities of different regions need to be identified to promote catchup and convergence with forerunners. For instance, Ida-Viru county and south-east Estonia are mostly similar in terms of the disadvantages that have circumscribed socio-economic development. Among other things, these include structural employment challenges, including skill mismatch and emigration, access to infrastructure such as airports or business services, spatial segregation from markets, more modest investment capacity among companies(due to a lack of collateral or lower liquidity), and fragmentation of local government and access to public services(see, for instance, Eljas-Taal et al. 2019). To support regionally balanced development, it is important not only to address commonalities but to take advantage of opportunities. For instance, industrial restructuring in north-east Estonia has increased skill mismatch in the region and outward migration. However, a Just Transition could enable development toward climate neutrality in a way that is prosperous for the region and its people. Similarly, south-east Estonia is on a path to use the research and development centre Tartu as its engine of development and its proximity to Latvia as a potential spatial advantage for cross-border cooperation. Tailored development plans are required to turn regional advantages into socio-economic development that increases cohesion across regions.

ANNEX A 15 ANNEX A: Indicator documentation Indicator Unemployment rate Demographic dependency ratio Highly qualified people School dropout rate Average gross income(EUR) Gender pay gap Number of family doctors Local government revenues Voter turnout Internal net migration balance Definition Source Unemployment rate – ratio of unemployed persons aged 18 to 64 to the population of the same age in per cent http://andmebaas.stat.ee/Index.aspx?DataSetCode=TT65 Dependency ratio – share of dependents aged zero to 14 and over the age of 65, compared with the total population aged 15 to 64 in per cent http://andmebaas.stat.ee/Index.aspx?DataSetCode=RV063 Share of people with higher education in per cent http://andmebaas.stat.ee/Index.aspx?DataSetCode=RV0232U Proportion of school leavers without school-leaving qualifications – early school leavers without general secondary education in per cent http://andmebaas.stat.ee/Index.aspx?DataSetCode=NH05 Average monthly gross income per employee in euros http://andmebaas.stat.ee/Index.aspx?DataSetCode=ST004 Gender pay gap – Ratio female income to male income in per cent http://andmebaas.stat.ee/Index.aspx?DataSetCode=ST004 Number of family doctors per 10,000 inhabitants https://www.haigekassa.ee/en/inimesele/ arsti-ja-oendusabi/haigekassa-lepingupartnerid Local government revenues per capita in euros http://andmebaas.stat.ee/Index.aspx?DataSetCode=RR30# Voter turnout local election in per cent https://kov2017.valimised.ee/valimistulemus-vald.html#0000 Internal net migration balance per thousand ­inhabitants http://andmebaas.stat.ee/Index.aspx?DataSetCode=RVR02

FRIEDRICH-EBERT-STIFTUNG – POLITICS FOR EUROPE 16 ANNEX B: Methodological notes The spatial typology of Estonia was computed in a combined statistical procedure consisting of a principal component and a cluster analysis. This procedure involves three steps. In the first step all variables were standardized by z-score transformation. Then, since many of the ten selected disparity indicators are potentially correlated, a principal component analysis was conducted in order to reduce complexity and to avoid any potential bias caused by multicollinearity. The principal component analysis merges the initial selection of indicators to a lower number of uncorrelated“super-variables”, socalled principal components. The amount of principal components chosen for the cluster analysis explains more than 90 per cent of total variance in the data. In the final step, a hierarchical cluster analysis using the Ward method was conducted. In this procedure, the initial observations are hierarchically merged using a minimum variance criterion. The point where to stop the clustering procedure, and hence the resulting number of clusters, is chosen by the data analyst. Several solutions have been tested and discussed within the research team. The final typology of four clusters was selected based on its intuitiveness and relevance to identify spatial disparities in Estonia.

ANNEX 17 ANNEX C: Indicator value ranges Indicator Year Value range from... to... Unemployment rate(%) 2020 3.0(Hiiumaa vald) to 10.4(Narva linn) Demographic dependency ratio(%) 2020 45.1(Vormsi vald) to 68.0(Viljandi linn) Share of people with higher education(%) 2019 18.8(Põhja-Pärnumaa vald) to 51.5(Viimsi vald) School dropout rate(%) 2020 0.0(Vormsi vald) to 13.5(Loksa linn) Average monthly gross income per employee(EUR) 2013–2019 989(Narva linn) to 1,819(Viimsi vald) Gender pay gap(%) 2019 70.0(Viru-Nigula vald) to 85.9(Setomaa vald) Number of family doctors per 10,000 inhabitants 2020 0.0(Vormsi vald) to 11.1(Saarde vald) Local government revenues per capita(EUR) mean 2018/2019 1,189(Narva linn) to 2,607(Alutaguse vald) Voter turnout at local elections(%) 2017 40.7(Kohtla-Järve linn) to 69.5(Vormsi vald) Overall internal net migration balance per 1,000 inhabitants 2015–2019 –59.4(Sillamäe linn) to 243.1(Rae vald)

FRIEDRICH-EBERT-STIFTUNG – POLITICS FOR EUROPE 18 Literature Arenguseire, Keskus(2019): Eesti regionaalse majanduse s­ tsenaariumid 2035, Tallinn. Estonian Cooperation Assembly(2020): Estonian Human Development Report. Estonian Human Development Report 2019/2020. Spatial Choices for an Urbanised Society, Tallinn, https://www.inimareng.ee/en/ estonian-human-development-report-20192020.html(02.03.2021). Eurofound(2019): Upward Convergence in Employment and Socioeconomic Factors, Luxembourg. Eurofound(2020): Upward Convergence in Material Well-Being: Is a COVID-19 Setback Inevitable?, Luxembourg. European Commission(2021): Joint Employment Report 2021 as Adopted by the Council on 9 March 2021, Brussels. European Commission(2020): Country Report Estonia 2020, Communication from the Commission to the European Parliament, the European Council, the Council, the European Central Bank and the Eurogroup, 2020 European Semester: Assessment of Progress on Structural Reforms, Prevention and Correction of Macroeconomic Imbalances, and Results of In-Depth Reviews under Regulation(EU) No 1176/2011 SWD/2020/505 final, Commission Staff Working Document, Brussels. Feldmann, Magnus(2017): Crisis and Opportunity: Varieties of Capitalism and Varieties of Crisis Responses in Estonia and Slovenia, in: European Journal of Industrial Relations 23(1), pp. 33–46, https://ec.europa. eu/social/main.jsp?catId=738&langId=en&pubId=8351&furtherPubs=yes (07.03.2021). Kasekamp, Kaija(2021): Arstiabi kättesaadavuse peamiseks takistuseks on ravijärjekorrad. Eesti Arst, 2021: Märts, https://doi.org/10.15157/ EA.VI.17177(03.03.2021). Eljas-Taal, Katre; Tatar, Merit; Käger, Maarja; Tiits, Marek; Kalvet, Tarmo; Tambur, Merle; Kosk, Aija; Friedenthal, Keiu; Kert, Karmen; Toots, Maarja; Kask, Ülo; Kikas, Martin; Raagmaa, Garri; Masso, Märt; Osila, Liina; Kadarik, Indrek; Aaben,Laura; Haaristo, Hanna-Stella; Melesk, Kirsti(2019): Mid-Term Evaluation of the Operational Programme for Cohesion Policy Funds 2014–2020, Final report, Tallinn, https://www.ibs.ee/wp-content/uploads/ESIF_final_report.pdf (10.03.2021). Masso, Märt; Järve, Janno; Laurimäe, Merilen; Piirits, Magnus; Koppe, Kaupo; Anspal Sten; Kivi, Laura Helena(2018): Tööga s­ eotud sotsiaalkaitse mudelid ja nende sobivus alternatiivsete ­tööturuarengute korral Eestis, Tallinn. OECD(2017): OECD Economic Surveys, Estonia 2019, Paris. OECD(2018): Education at a Glance 2018: OECD Indicators, OECD, Paris, https://doi.org/10.1787/eag-2018-en(15.03.2021). Riigikontrolli 2020: Esmatähtsate avalike teenuste tulevik. Kes meid peatselt ravib ja õpetab ning kes hoiab korda ja päästab? Milline on ­realistlik avalike teenuste osutamise tase väljaspool Harju- ja Tartumaad? Riigikontrolli aastaaruanne Riigikogule, Tallinn. Männasoo, Kadri; Karo, Erkki; Merle, Reidolf; Merle, ­Küttem (2020): Ühtekuuluvuspoliitika fondide rakenduskava 2014–2020 ettevõtlus- ja i­nnovatsioonitoetuste tulemuslikkuse hindamine (26.06.2019−1.04.2020), Tallinna Tehnikaülikool, Majandusteaduskond, Ärikorralduse instituut, ­Tallinna Tehnikaülikool, Majandusteaduskond, Ragnar Nurkse innovatsiooni ja valitsemise instituut. Servinski, Mihkel(2016): Eesti piirkondlik areng 1991–2016, Tallinn http://www.digar.ee/id/nlib-digar:293893(20.03.2021).

Literature/List of figures and tables 19 List of figures and tables 8 Figure 1 The Estonian disparity map 10 Table 1 Spatial typology of socioeconomic disparities in Estonia 12 Table 2 Bandwidth of indicator values for spatial types

Friedrich-Ebert-Stiftung(FES) www.fes.de The Friedrich-Ebert-Stiftung(FES) is the oldest political foundation in Germany with a rich tradition dating back to its foundation in 1925. Today, it remains loyal to the legacy of its namesake and campaigns for the core ideas and values of social democracy: freedom, justice and solidarity. It has close ties to social democracy and the free trade unions. FES promotes the advancement of social democracy, in particular through: – political educational work to strengthen civil society; – think tanks; – international cooperation with our network of offices in more than 100 countries; – support for talented young people; – maintaining the collective memory of social democracy with archives, libraries and more. Foundation for European Progressive Studies(FEPS) www.feps-europe.eu The Foundation for European Progressive Studies(FEPS) is the think tank of the social democratic political family at EU level. Its mission is to develop innovative research, policy advice, training and debates to inspire and inform progressive politics and policies across Europe. FEPS operates as a hub for thinking to facilitate the emergence of progressive answers to the challenges that Europe faces. Today, FEPS benefits from a solid network of 68 member organisations. In addition to this network of organisations that are active in the promotion of progressive values, FEPS also has an extensive network of partners, including renowned universities, scholars, policymakers and activists. ILS – Research Institute for Regional and Urban ­Development gGmbH www.ils-forschung.de/en/ The ILS is an urban research institute which explores the dynamics and diversity of urban change in international comparison. The aim of research is a better understanding of transformation processes, in order to gain insights into the sustainable development and design of urban areas of different size and scale. IMPRINT © 2021 Friedrich-Ebert-Stiftung Baltic States Peer Krumrey The views expressed in this publication are not necessarily those of the FriedrichEbert-Stiftung and the partner organisations for this publication. Commercial use of all media published by the Friedrich-Ebert-Stiftung(FES) is not permitted without the written consent of the FES. Front cover:© Heike Wächter Design concept: www.bergsee-blau.de Design/ Typesetting: Heike Wächter

More equality in Europe! The inability of democratic actors and procedures to provide rapid responses to social-economic issues has led to widespread disenchantment of political and democratic systems across Europe. As the benefits of economic growth and increasing employment have been unequally spread, creating regional disparities, perceived and experienced social-economic inequalities and injustices have deepened and played into the hands of right-wing populists. But what are the answers to these challenges? How should policies in the EU-member states and the EU tackle regional socio-economic disparities? With the project“Unequal Europe – Tackling Regional Disparities in Europe”, the Friedrich-Ebert-Stiftung and the Foundation for European Progressive Studies(FEPS), put forward progressive policy recommendations based on the disparity reports for several European countries for both the respective national and European level. https://fes.de/unequal-estonia