In international comparison, the European Union is prosperous. On closer inspection, however, there are significant differences between the regions. The map shows one way of measuring these regional disparities. The 10 different types of regions shown represent differences and similarities with regard to the sectoral structure of economic activity, economic performance, the extent of unemployment and natural population development. The map thus shows unequal socio-economic and demographic development patterns in the EU on a sub-national level.
TO THE SELECTED STATISTICAL CHARACTERISTICS
For the present classification of the regions of the EU according to socio-economic and demographic aspects, the following set of characteristics was used:
- the share of employed persons in industry (of the secondary sector) as a percentage of all employed persons (average for the years 2011–2013),
- the share of those in employment in the service sector (of the tertiary sector) as a percentage of all those in employment (average for the years 2011–2013),
- the regional gross domestic product per inhabitant in purchasing power standards (average for the years 2009–2011),
- The share of unemployed in the labor force in percent (average for the years 2011–2013),
- the natural population balance (births minus deaths) per 1000 inhabitants (average for the years 2010-2012).
This selection of characteristics also takes into account the proportion of people employed in agriculture (the primary sector). It results from the difference between the total of all employed persons and that of employed persons in the secondary and tertiary sectors.
With the aim of examining regions of comparable size, the reference areas of the typification are a combination of the levels NUTS 1 and NUTS 2. In Germany, NUTS 1 regions correspond to the federal states; Federal states or small federal states such as Saarland, which are not further subdivided. Check Countryaah to see other countries in European Union.
TO THE RESULTS OF THE ANALYSIS
Against the background of the cluster analysis carried out, ten different regional development patterns can be identified for the 113 NUTS 1 and NUTS 2 regions of the EU. With the deviations of the cluster mean values of the individual examined characteristics from the respective EU average and the inclusion of further characteristics for the population and for the household-related infrastructure as interpretation aids, they can be characterized as follows:
Urban service centers with significantly above average added value, slightly above average unemployment, a comparatively very high natural population balance and a correspondingly young population (cluster 1) or with significantly above average added value, low unemployment and high immigration rates (cluster 2).
- Regions with a slight focus on services, but an overall rather average economic structure and economic efficiency. It is also characterized by a comparatively low unemployment rate, positive net migration and a slightly above-average natural population balance (cluster 3).
Regions with an average economic structure and economic performance can be further subdivided into regions with a slightly above-average natural population balance and a correspondingly young population (cluster 4) and into regions with a below-average natural population balance with few young and many old people and comparatively low unemployment (Cluster 5).
- Regions in crisis with little industry, very high unemployment, emigration tendencies and a rather older population (cluster 6). It mainly includes the regions that have been particularly hard hit by the financial and economic crisis that has persisted since 2008.
In the industrial regions, a distinction must be made between regions with slightly above-average added value, low unemployment, a slightly above-average proportion of older people and immigration trends (cluster 7), and regions with below-average prosperity and emigration trends (cluster 8).
Agricultural regions can be subdivided into regions with below average prosperity, increased unemployment, high emigration and a low natural population balance (cluster 9) as well as strongly agricultural regions with very little service provision, very low prosperity, few old people, but below average natural ones Population balance and emigration tendencies (cluster 10).
As with all types, it should be noted that the present characterization of the EU regions aims to highlight general trends. The individual situation in the individual regions can differ from this.
TO THE CLUSTER ANALYSIS METHOD
From a methodological point of view, this typification of regions in the EU is the result of a cluster analysis.
Cluster-analytical methods make it possible to examine a large number of objects to be examined (in this case the regions of the EU) across several characteristics for similar characteristics and to summarize them in groups that are as homogeneous as possible, the so-called clusters.
In terms of content, the sorting or assignment strategy is based on the idea of merging the respective specific profile of characteristics for each examination object with those profiles that are most similar to it and separating it from those that are most dissimilar to it.
This idea is implemented mathematically and statistically in three steps. First, the (in) similarity of the regions examined is determined (based on the squared Euclidean distance of their indicator values). The lower the calculated distance value between two regions, the more similar they are; the higher the value, the more dissimilar.
The most similar regions are then successively combined into clusters. In the third step, the threshold at which this summary is to be broken off must be determined so that the merging of the regions still guarantees largely homogeneous clusters, while the number of clusters can be interpreted in terms of content and graphically. The ten-cluster solution was chosen for the present typification of the regions of the EU.