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Orkestra: Instituto Vasco de Competitividad (Fundación Deusto)

Comunidad Autónoma del País Vasco (CAPV)

GDP per capita 35,300 PPP-€
Population 2,167,323 people
Unemployment rate 11.3 % of working pop. aged ≥15

Competitiveness indicators panel updated to 25.09.2018

The panel is organised into four levels that determine competitive performance. Learn more about the panel's development methodology.

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Level 2. Intermediate performance indicators (position and evolution since 1 year)Levers of growth: productivity, employment, innovation

The second level features intermediate performance indicators, which, although they are note the ultimate goals to be achieved in the region, they are important to achieve these final results.

Employment rate (% of working pop. aged 15-64; 2017)

Female unemployment rate (% of working pop. aged 15-64; 2017)

Unemployment rate (% of working pop. aged ≥15; 2017)

Youth unemployment rate (% of working pop. aged ≥15; 2017)

Apparent productivity per employee (PPP-€; 2016)

PCT patents per million population (4 year window) (patents; 2015)

European Union Trade Mark applications per million population (applications/Mpop; 2015)

Community designs per million population (designs/Mpop; 2015)

Level 3. Indicators of competitiveness (position and evolution since 1 year)Firm behaviour, regional and cluster specialization and quality of the business environment

The third level is made of the determinants of competitiveness, that is, the elements that affect the results of the two higher levels. This level is particularly relevant because it is one in which policies can have a clearer impact. Determinants are grouped into three categories that show company behaviour, that specialization of the territory and its clusters, and the quality of the business environment.

Business behaviour

Firm R&D personnel (% of total employment; 2015)

Firm R&D expenditure (% GDP; 2015)

PCT Patent co-invention (4 year window) (% total patents; 2015)

PCT Patents with foreign collaboration (4 year window) (% total patents; 2015)


Employment in high- and medium-high-tech manufacturing (% of total employment; 2017)

Employment in knowledge-intensive services (% of total employment; 2017)

Business environment

Human resources in science and technology (% total pop.; 2017)

Population aged 25-64 with upper secondary or tertiary education (% of pop. aged 25-64; 2017)

Tertiary education students (% of pop. aged 20-24; 2016)

Vocational education students (% of pop. aged 10-19; 2016)

Population aged 25-64 enrolled in continuing education courses (% of pop. aged 25-64; 2017)

R&D personnel at public institutions (% of total employment; 2015)

Public R&D expenditure (% GDP; 2015)

Total R&D personnel (% of total employment; 2015)

Total R&D expenditure (% GDP; 2015)

Households with broadband access (%; 2017)

Individuals who ordered goods or services over the internet (% total pop.; 2017)

Level 4. Fundamentals

Finally, last but not least, the foundations of the framework refer to certain characteristics of the territory that have an impact on competitiveness, but they come more or less given, and can not be easily modified in the short term (location of the territory, natural resources, size of the region, institutions ...).

These structural characteristics of the regions are what we use to benchmark each region in order to find the ones most similar to each other within the European Union: this is what we call the reference regions. You can learn more about this methodology and access an interactive tool on the site of the project developed by Orkestra with the support of the European Commission.