A New Map Suggests the EU Is a Good Framework for Growth

The Brussels-based think tank Bruegel has published an atlas of economic growth across regions in Europe.

Any Sciences Po student can tell you that economic growth has been very different across EU regions. Now, Bruegel, a Brussels-based think tank has mapped that difference out clearly. Using Eurostat data, Bruegel divided the EU into 1337 regions and measured their respective GDP per capita growth between 2003 and 2015. This period, Bruegel writes, was considered “for data availability reasons, but also with a view to having several years both before and after the most acute phases of the 2008 global and European financial and economic crisis.”

Map 1: GDP per capita growth in EU regions, 2003-2015
Map created by Bruegel, a Think Tank, based on Eurostat data. The colors here refer to different deciles in terms of GDP growth per capita measured at purchasing power standards (PPS). The darker the green, the more rapid the growth and the darker the red, the slower the growth or the harsher the decline.

The fastest-growing regions of the EU between 2003 and 2015 are found in Bulgaria, Poland, Romania, Slovakia the three Baltic countries and in the southern part of Ireland. The slowest or even declining regions are clearly found in Greece which experienced a particularly severe recession, while most regions of Italy and many regions in France, Spain and the United Kingdom were also among the slowest growing regions.

What can we learn from a map like this? Bruegel’s researchers estimate the importance of certain regional growth characteristics. Specifically, they affirm the importance of the following regional characteristics for long-term growth:

  • The initial level of GDP at purchasing power standards (PPS) per capita in 2003: This one may ring familiar for SciencesPo students who understood the Solow growth model of the Core economics course. Less advanced areas should enjoy relatively higher marginal productivity of production factors, thereby advancing towards their long-run GDP per capita equilibrium level. For example, the level of GDP per capita is much lower in Bulgaria than in Germany, which is to a large extent driven by technological differences: production in Germany uses more advanced technologies than in Bulgaria. Thereby, Bulgaria has a higher potential to grow than Germany, because Bulgaria could adopt the existing best technologies and thereby catch up with Germany, while German growth is determined by the development of new technologies, which tends to be a more difficult and slower process.

  • The capital-to-output ratio in 2003: Solow again. A higher proportion of capital over output suggests that the economy is at a more advanced stage of development and therefore has less scope for catching up, lowering the growth potential.

  • The percentage of employment in the services sector in 2003: Similarly, a higher share of services-sector employment suggests a more advanced stage of development, lowering the growth potential.

  • The change of services-sector employment in 2003-2015: Such a change reflects a fundamental structural shift in the economy, lowering the growth potential.

  • Research and development (R&D) personnel in percentage of total employment in 2003: A higher share of R&D suggests a higher stock of human capital, which increases the long-run level of economic growth.

  • The share of working-age people with tertiary education in 2003: Similarly, the higher the share of highly educated workers, the higher the expected long-run level of GDP per capita.

  • Population density in 2003: This indicator is a useful measure of urbanisation, while urban regions with a higher share of employees who work neither in agriculture nor in manufacturing should be more advanced and closer to the technological frontier, and thereby having a lower potential for growth.

  • The growth in population between 2000 and 2003: Higher population growth should imply a lower physical-capital-per-worker ratio and lower long-term GDP per capita.

  • Quality of governance in 2010: Better governance is a reflection of effective, impartial and transparent institutions which enable economic growth.

Two Lessons

But what can we learn from such a map?  Among the 1,337 regions we considered, the top 10% of 133 regions comes from 21 countries, highlighting that there are rather successful regions, in terms of economic growth, in many EU countries. There are only seven EU countries that do not have a single region in the league of top 10% growth performers: Belgium, Cyprus, Finland, Greece, Hungary, Slovenia and Spain. From this Bruegel concludes that there are rather successful regions in many EU countries, suggesting that the EU can provide a good framework for growth.

Additionally, the 133 regions with the worst economic performance, is from 14 countries, suggesting greater concentration. In particular, 36 of the 52 Greek regions (i.e. 69% of Greek regions) are in the bottom decile. Eight more sit in the second-worst decile and a further four in the third-worst decile, highlighting that Greece as a country suffered massively after 2008. There are some other countries too in which a very large share of regions belongs to the bottom 10% of EU regions: Croatia (48%), Slovenia (42%), Bulgaria (32%), Finland (32%), Hungary (30%) and Ireland (25%), suggesting a high-level of concentration of poor economic development and major differences within countries. This, the Think Tank argues, highlights that country-specific factors can play a major role in regional development.

For SciencesPo students who may end up drafting public policy at the European Union or in national governments, the atlas provides an important overview of the impact of the EU on economic growth as well as the importance of country specific factors.


Darvas, Z., Mazza, J. and Midoes, C. (2019). A European atlas of economic success and failure | Bruegel. [online] Bruegel.org. Available at: http://bruegel.org/2019/06/a-european-atlas-of-economic-success-and-failure/ [Accessed 11 Jun. 2019].

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