Estonian Human Development Report

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6.5. Cities as development engines Today over 70% of the population in the European Union lives in cities and metropolitan areas [Fostering the urban..., 2008.]. The majority of innovation takes place in cities. The international competition between cities decides, to a great extent, which region or even country will be able to keep pace with the expanding possibilities of today’s international division of labour, and which not. Moreover, it should be emphasized that since the borders of the city have increasingly started to blur (a large number of people working in cities, especially those earning higher incomes, live outside the city; some industrial manufacturing plants and service providers e.g. transport and warehousing, which require larger territory, are moving to the outskirts of cities; in some countries, multi-centred metropolitan areas are consciously designed, etc.), the territorial economic unit is no longer a city that is treated separately from its surroundings, but a city together with its outskirts, i.e. an urban or metropolitan region. The differences between the developmental indicators (level of education, ratio of more complex production and service, income per capita, etc.) of the metropolitan regions that have achieved international success and the indicators of the remaining parts of the country may be surprisingly large in today’s Europe. Therefore, turning our attention to the cities, especially to the role of Tallinn and Tartu in Estonia’s regional development, in the following subchapter is justified. By comparing the developmental indicators of Northern Estonia (Tallinn with Harju County that surrounds it) with the average in EU regions, we see more or less comparable numbers. And with respect to the ratios of people with higher education, if we leave aside the issue of the structure of higher education, “Greater Tallinn” and actually all of Estonia significantly surpass the average for EU regions (Table 6.5.1.). While the Northern Estonia region can actually be construed as an agglomeration of Tallinn, in the generalized indicators for Southern Estonia, it is not the indicators for Tartu but those of the rural counties that dominate. Therefore, great differences between the two <strong>Estonian</strong> regions stand out. However, if we compared the Northern Estonia indicators not with all of Southern Estonia, but only with Table 6.5.1. <strong>Development</strong>al indicators for Estonia’s regions compared to the average for EU regions Indicator Ratio of people with higher education Participants in lifelong learning, % Ratio of employment in high-tech services Ratio of employment in mid- and high-tech manufacturing Ratio of professionals/ experts in the workforce (HRST) Source: Eurostat, Statistics Estonia. Average of EU regions 2005 Northern Estonia Southern Estonia 2005 2007 2005 2007 23.59 42.2 43.4 29.3 28.3 10.25 7.0 8.6 7.0 7.5 3.21 3.5 3.7 2.6 2.4 6.45 5.3 4.4 1.8 2.9 36.31 41.9 42.9 28.3 29.3 the indicators for Tartu County (which can be treated as an agglomeration of Tartu with a certain, but greater conditionally, than it can be done in the case of Harju County and Tallinn), we get a significantly different picture. We see that the ratio of those employed in mid- and hightech (industrial) manufacturing and knowledge-intensive high-tech services is practically the same in Tartu County as it is in Northern Estonia (the former between 4% and 5% and the latter between 3% and 4%, although if it is compared not to the average for EU regions, but to the metropolitan areas at the forefront, these numbers are not anything for either to be proud of), and the gap in the ratio of professionals and experts (HRST) is not hopelessly large compared with Northern Estonia (about 38–39% in Tartu County) while the percentage of those participating in lifelong learning (about 10%) is higher than in Northern Estonia. It’s true that the ratio of people with higher education is 6% lower in Tartu County than in Harju County, but a partial reason for this may be the large concentration of public sector jobs requiring higher education in Tallinn. A high-tech manufacturing city or a knowledge-based city It is clear that at least in the European Union context, becoming one of the successful cities/metropolitan areas is not possible without a large part of employment being concentrated in the more complicated niches that are highly valued in the international market. In many cases, this means an ability to participate in high-tech developmental and production processes or at least to operate modern high-technology. However, the picture appears quite confused with regard to which specialization options that might represent such success and how typical they are. Some clarity is provided by the results of the recently completed Crossworks cooperation project under the EU’s 6 th Framework Program, with the participation of researchers from the Netherlands, Belgium, Germany, Estonia and Finland. In the course of the project, a statistical analysis was made based on existing developmental indicators (technological, educational and economic) of the variables of the most successful regions in the European Union. More than 50 European Union regions were classified as successful based on higher-than-average level of economic development as well as positive dynamics. It should be emphasized that there are not grounds to compare the current developmental indicators of Estonia’s regions, i.e. the Tallinn and Tartu regions with the indicators of the top regions in the EU; Estonia’s market economy is still too young and its EU membership too new. However, from Estonia’s viewpoint, the situation of the EU’s leading regions can serve as objectives for setting long-term goals. The survey, which was primarily conducted by Bart van Looy and Catherine Lecocq of the University of Leuven, demonstrated that successful regions possessed both similar and dissimilar traits. Two types of successful regions could be distinguished based on the structure of employment: firstly, a type that has a relatively large number of mid- and high-tech industrial enterprises, and a second | 148
type, where the leading role was played by high-tech services (Crossworks, 2008: 9–21). The authors of the survey named these metropolitan areas high-tech manufacturing regions and leading knowledge regions respectively. A very high number of patents is typical of high-tech manufacturing regions. A generally high level education of the workforce is typical of both high-tech manufacturing regions and leading knowledge regions, whereas, the latter has an especially large percentage of workers with university education. Successful high-tech manufacturing regions also require the existence of quite a large well-educated “blue-collar” workforce with vocational education. The high intensity of lifelong learning is necessary for the success of both types of regions. The statistical analysis shows that there are slightly more knowledge regions than high-tech manufacturing regions among Europe’s successful regions. What is more important, the knowledge regions have recently prospered better than the high-tech manufacturing cities, and their economic growth has been faster. For the Tallinn and Tartu regions, the news about the prospects for the knowledge region/city model is probably positive since this enables the better implementation of their greatest advantage, the high percentage of people with higher education and it somewhat reduces Estonia’s greatest disadvantage, the small number of patents compared to other developmental factors. One can also presume that movement in the direction of a hightech manufacturing region/city model, which would definitely assume a strong emphasis on vocational learning and higher education engineering studies would be more difficult to combine with the value orientations predominant among young people in Estonia than the movement towards a knowledge region model. However, it must also be considered that the goal to become a leading knowledge region even in the distant future assumes a significant increase in the number of people working in mid- and high-tech sectors (industrial and service combined) from the current level of 10% to at least 15% (and even higher in the future). It also assumes the existence of internationally competitive universities that cooperate with the economic environment as well as significantly more intensive activity in the field of lifelong learning. The surveys of the European cities prove that successful economic development at the middle and higher developmental levels is not possible without a diverse and attractive cultural environment that stimulates general creative growth. Since an international search for talent is typical at higher developmental levels – for top information technologists, designers or investment bankers – the attractiveness and creativity of the urban environment is one of the key factors for the quality of life that will attract an international level of top people (and their families). In the course of the Crossworks survey, interviews were conducted in five cities where the knowledge city model is considered to be an important developmental prospect (Leuven, Endhoven, Aachen, Tallinn and Helsinki). It was found that in all the cities issues related to the attractiveness of the cultural life, creative economy and urban environment arose in connection with the development of high-tech-based manufacturing and service. Moreover, these aspects were very critical in cities with less than 200 thousand residents, in which case attracting talented people was hindered by the fear that while the city may be convenient and secure, the cultural life may not be sufficiently diverse or interesting enough to set down roots for a longer period. Traits of a creative knowledge city In the EU 6 th Framework project entitled “Accommodating Creative Knowledge Competitiveness of European Metropolitan Regions within the Enlarged Union – ACRE” the future development opportunities for 13 cities to become creative knowledge cities was examined. Based on this analysis, in which factors related to culture and creativity were a focal point, it was found that the following types of cities have the best prerequisites for becoming knowledge cities: 1. Cities that are known as national or international political and economic decision-making centres have better preconditions for innovative restructuring (into a creative and/or knowledge city) than do cities where significant decision-making does not take place. 2. Tolerant and multicultural cities where everyone is welcome have greater potential to attract people with various lifestyles and cultural backgrounds and thereby to increase innovativeness than closed cities. 3. Cities where small businesses and high-tech manufacturing dominate and which have been service-based early on and never had large manufacturing have better preconditions for transitioning to a creative knowledge-based economy. 4. Internationally renowned historical-cultural cities are attractive to the creative class and thereby they have the prerequisite to become creative cities. 5. Well-managed cities with financial and organizational resources are more able to provide suitable environments for a creative economy. 6. It was emphasized that a well-formulated, wellfinanced and achievable city/region innovation and technology policy is an important factor in its movement on the described path. Based on the survey and an assessment of the aforementioned compendium of criteria, the following cities could be considered to be creative cities: Amsterdam, Barcelona, Dublin, Munich and Helsinki with certain reservations. The qualifications of smaller cities and those that are not capitals is made more difficult due already to the first criterion. Nevertheless two cities that were examined – Toulouse and Birmingham – which are not among the capitals of countries, autonomous units or states collected relatively good scores, based on which they are at least approaching the ideals described above. The example of Birmingham is interesting because it is not a city with great historical-cultural value and in previous periods has not been considered to be a multifaceted city. Its success has been achieved recently by developing and realizing conscious policies directed at promoting creativity and a creative economy. Attempting to assess Tallinn and Tartu based on the aforementioned aspects, it seems that Tallinn has relatively good prerequisites regarding most of the criteria. Although, like most other cities it was over-industrialized (“Fordized”) during the socialist period, its restructuring into a modern service economy has occurred quite 149 |
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Estonian Human Development Report
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Estonian Human Development Report T
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4.2. Ethnic differentiations in sat
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Preface This year, the Estonian Hum
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CHAPTER 1 Estonian Human Developmen
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Figure 1.1.3. Life expectancy in co
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Figure 1.2.2. Life expectancy at bi
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to reality. The greatest inaccuracy
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Figure 1.2.9. Internal migration ev
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12. Marksoo, A. 1992. “Dynamics o
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Table 1.3.1. PISA 2006 study result
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Table 1.3.2. Number of students in
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1.4. The gross domestic product and
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Figure 1.4.3. Estonian GDP (right a
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1.5. Changes in the Estonian Human
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2.2. Health of Estonian residents i
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Table 2.2.4. Differences in life ex
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Figure 2.4.1. Healthy life years of
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Figure 2.4.4. Various accidents, tr
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2.5. Lifestyle and behaviour as a s
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Figure 2.5.5. Smoking in Estonia in
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Figure 2.6.1. Overview of the compo
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Table 2.6.2. Use of specialized med
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dren. The majority of services are
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Figure 2.8.2. How much a health dis
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2.10. Policy recommendations aimed
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CHAPTER 3 Quality of life and life
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Table 3.2.1. Characteristics of liv
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Table 3.2.4. An assessment of the e
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Figure 3.2.4. Difference in the job
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Table 3.2.6. Agreement with stateme
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Figure 3.3.1. Satisfaction with lif
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Figure 3.3.4. Percentage of people
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Figure 3.4.1. Types of quality of l
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Figure 3.5.1. Percentage of teenage
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Figure 3.5.4. Percentage of respond
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Arieh A., Conti C., Kutsar D., Nicg
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Figure 3.6.2. Subjective quality of
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Pieper, A. Sixsmith, Care related q
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Figure 3.7.1. The placement of Euro
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Figure 4.2.1. Life satisfaction by
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Table 4.2.1. Factors forming genera
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Annexes Annex 4.2.1. Socio-demograp
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Figure 4.3.1. Changes in the assess
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Figure 4.3.4. Attitudes of the Esto
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olds considered themselves to be pa
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Table 4.4.3. Agreement of the Russi
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Table 4.5.2. The prospects of non-E
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Page 102 and 103: mote equal opportunities. At the (e
Page 104 and 105: CHAPTER 5 Quality of life in a cons
Page 106 and 107: Figure 5.2.1. GDP and AIC per capit
Page 108 and 109: Figure 5.2.3. Distribution of consu
Page 110 and 111: Figure 5.2.4. Indexes of environmen
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Page 122 and 123: Figure 5.4.6. Time spent on the con
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Page 138 and 139: Figure 6.3.8. Percentage of social
Page 140 and 141: References 1. Aaviksoo, A., G. Paat
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Page 152 and 153: Table 6.5.2. Existence of developme
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Page 156 and 157: Table 7.1. Factors that favour and
Page 158 and 159: Table 7.2. Potential economic devel
Page 160 and 161: Authors Chapter 1 Ene-Margit Tiit,
Page 162 and 163: Margit Keller (PhD) is a Senior Res
Page 164 and 165: Special prizes Estonian Human Devel
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Page 172 and 173: Honorable mentions Estonian Human D
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Estonian Human Development Report

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