A team of experts, led by CEA, within the framework of the project "Assessing & Streamlining the Potentials of the Open Balkan Initiative" has prepared 3 studies:
Rationale:
The point of TASK 2 is that each of the WB6 countries has its own characteristics, and consequently, there are disparities, but also similarities within and between countries. Therefore, we want to analyze the disparities and similarities in EU NUTS 3 regions depending on the available data. The idea is that, given the OBI MoR and OBI agreements and EU freedom of movement, certain NUTS regions of the WB6 countries may have more similarities among themselves than others. Thus, those NUTS 3 regions that form clusters, for example, show similarities in certain demographic attributes and/or certain socio-economic attributes, could serve as a platform for more effective implementation of EU freedom of movement and the goals of the OBI MoR and OBI agreements. This does not mean that regions with greater disparities cannot achieve the same goals. It only shows that for regions with more similarities, policies could be implemented more effectively because they have similar challenges. Regions that show greater disparities will likely require more resources to achieve convergence and reduce inequalities.
There are three parts to this report on Task 2:
Part 1: Analysis of disparities between countries: Desk research
In Volume 1, we find that there is internal migration to urban centers that attract population. The concentration of the population in the WB6 countries is found in municipalities with a population of up to 30,000, for example, 69% of the total population of all 491 municipalities. In Albania, half of the population lives in 7 cities with more than 100,000 inhabitants, and in Kosovo, similar to Albania, half of the population lives in 8 out of 38 municipalities. In Montenegro, 23 out of 25 municipalities have up to 50,000 inhabitants (half of the population lives in 4 out of 25 municipalities). In BiH, half of the population lives in 84% of municipalities. Regional development is organized at the NUTS 3 level for planning purposes in North Macedonia, Albania, and Kosovo, where disparities have persisted for a decade. In Serbia, NUTS 3 is used for administrative deconcentration, while for development purposes, there are four regions.
WB6 countries do not trade much among themselves when measured by the top five trading partners. Serbia is highlighted as an exporter to all WB6 countries. Albania has a high concentration of exports to Italy (45%), similar to North Macedonia to Germany (47%). Serbia and Albania do not include any WB6 country among their top five importers. Serbia's exports and imports are essentially equal to the sum of the other five countries.
WB6 convergence towards the EU is slow. Namely, the GDP of WB6 countries in PPS relative to the EU-27 increased from 33% to 38% in 10 years. At this rate, it will take the WB6 70 years to reach the EU average (if the EU maintains today's GDP level for 70 years).
WB6 countries remain trapped in mediocrity and are becoming increasingly poorer. Worse still, WB6 countries are at risk of being caught in the talent drain trap (EU 2023). Aging and declining working-age population (inverted age pyramid for North Macedonia, for example), combined with a lack of economic dynamism and a higher share of NEETs, as well as regions experiencing significant emigration of young people, have led to a reduced availability of highly skilled and younger workers.
Regional inequalities within WB6 countries reveal that at the local level (especially NUTS 3 level), inequalities are less pronounced. This means that prioritizing regional potential based on similarities in NUTS 3 regions, instead of addressing convergence with the EU at the NUTS 1 level, could be a more effective policy choice for creating opportunities to equalize the potential of regions, e.g., the focus could be on inclusive economic growth to ensure that benefits are extended to all regions.
Part 3: Analysis of country disparities: Cluster analysis
The similarity of regions in the Western Balkan countries was observed using cluster analysis at the NUTS 3 level of disaggregation (where data was available), navigating specific segments of the Western Balkan economies using one or more indicators for each segment.
In addition, the analysis based on economic activity indicators shows a cluster where entities with a large share of agriculture in the economy have a low GDP per capita, as well as a low share of other analyzed sectors in GDP. On the other hand, entities with the highest total GDP per capita, as observed in the capitals of Serbia, North Macedonia, and Albania, as well as in Montenegro as a whole, are linked to a high share of trade, transport, and tourism in GDP. Another cluster shows that entities dominated by industrial and construction activities generally have an above-average GDP per capita. These findings can be an important factor when designing economic policies at the regional level.
See the maps from the Cluster Analysis here: Maps
Read the reviews and editor's letter for the 3 studies Peer Review & Editor Letter of volumes 1, 2, and 3
A short version of the three studies in Executive summary format.
