Statistics Explained

GDP at regional level



Data extracted in May 2022.

Planned article update: September 2023.

Highlights

In 2020, there were five regions where GDP per inhabitant was more than twice as high as the EU average (29 900 PPS): Southern, and Eastern and Midland (both Ireland), Luxembourg, Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest (Belgium) and Praha (Czechia).

In 2019, Luxembourg had the highest level of disposable income per inhabitant (€34 600) in the EU; it was followed by two regions in Germany – Oberbayern (€28 000) and Stuttgart (€25 700).

Source: Eurostat (nama_10r_2gvagr) and (nama_10_gdp)


At the onset of the COVID-19 crisis, the European Commission, for the first time, activated the general escape clause of the Stability and Growth Pact. By relaxing budgetary rules/requirements, national governments had more freedom to support their economies and mitigate the pandemic’s socioeconomic consequences. Nevertheless, there was a 5.9 % real terms contraction in the European Union’s (EU’s) gross value added between 2019 and 2020. The infographic shows those regions that experienced the largest declines in output: many of them were popular holiday destinations. With extensive stimulus programmes, vaccine rollouts and the gradual easing of restrictions, economic growth resumed across much of the EU in 2021.

The EU’s regional policy aims to support broader socioeconomic priorities such as the European Semester and the European Pillar of Social Rights. Regional accounts are important in this context, as they are used, among others, when deciding upon the regional allocation of cohesion policy expenditure. The main focus of the EU’s cohesion policy is to help regions converge/catch-up. Many of the less-developed and transition regions in the EU may be characterised as having relatively low-growth, low-income (primarily in eastern and southern EU Member States) or pockets of poverty, social exclusion and/or industrial decline (regions that have been ‘left-behind’); these are the regions that receive the bulk of EU regional funds.

The EU’s regional expenditure has historically been allocated on the basis of gross domestic product (GDP) per capita. As of 2021, the rules for allocating funding became simpler: they were tailored to locally-led development strategies that continue to take account of GDP per inhabitant, alongside information on the socioeconomic and environmental situation (for example, youth unemployment, low levels of educational attainment, the reception and integration of migrants, or climate change).

This chapter starts with information on regional GDP, the principal aggregate for measuring economic output (presented in absolute values and per inhabitant ratios), and the related concept of gross value added. It also provides information relating to regional specialisations in distributive trades, transport, accommodation and food service activities, areas of the economy that were particularly vulnerable to the COVID-19 crisis. Having looked at GDP from an output approach, the focus of the second section switches to the income of households: information is presented for primary income (from paid work and self-employment, as well as from interest, dividends and rents) per inhabitant, disposable income per inhabitant, and the compensation of employees per hour worked. The final section looks at another indicator related to labour, namely labour productivity (or gross value added per person employed) in order to assess patterns/developments of regional competitiveness.

Full article


Regional gross domestic product (GDP)

GDP at market prices in the EU was valued at €13.4 trillion in 2020, equivalent to an average of €29 900 per inhabitant. These figures marked a considerable reduction in economic activity when compared with 2019: the direct and indirect impacts of the COVID-19 crisis led to GDP falling by more than €600 billion in current price terms, while GDP per inhabitant fell by €1 400.

Behind these overall figures there are considerable differences between the regions of the EU in terms of their economic performance. Among other factors, these might be explained by: the availability of natural and human resources; changes brought about by globalisation, such as the relocation and outsourcing of manufacturing and some service activities; the legacy of former economic systems; socioeconomic developments; geographic proximity or remoteness to markets.

Measuring the size of an economy

The central measure of national accounts, GDP, summarises the economic position of a country or a region. This well-known balance has traditionally been divided by the total number of inhabitants to create a proxy measure for analysing overall living standards, namely GDP per inhabitant.

While GDP continues to be used for monitoring economic developments, playing an important role in economic decision-making, it is complemented by other indicators as a source of information for informing policy debates on social and environmental issues. This is because GDP does not take account of externalities such as environmental sustainability or issues such as income distribution or social inclusion, which are increasingly seen as important drivers for sustainable development and the overall quality of life.

In order to compensate for price level differences across countries, GDP can be converted using conversion factors known as purchasing power parities (PPPs). The use of PPPs, rather than market exchange rates, results in data being denominated in an artificial common currency unit called a purchasing power standard (PPS). The use of PPS series, rather than euro-based series, tends to have a levelling effect, as countries and regions with very high GDP per inhabitant in euro terms also tend to have relatively high price levels (for example, the cost of living in Luxembourg is generally much higher than the cost of living in Bulgaria).

Statistics are generally reported in current (or ‘nominal’) terms; in other words, their current value during the particular reference year in question. To make comparisons over time, it can be more revealing to make use of data in constant price terms, where a series has been adjusted to take account of price changes. For example, imagine GDP rose from one year to the next from €100.0 billion to €110.0 billion, while inflation was 2 %. In constant price (or real terms), GDP in the second year would be €107.8 billion, reflecting a real terms growth rate of 7.8 %, compared with a 10.0 % growth rate in nominal terms. During periods of inflationary pressure, series that are denoted in current price terms will be higher than constant price series; this situation may be reversed if there is a period of deflation (falling prices).

The 10 EU regions with the highest GDP accounted for more than one fifth of its total economic output

There are 242 NUTS level 2 regions across the EU for which GDP data are available. In 2020, the highest levels of regional GDP were recorded in major hubs of business activity (often within relatively large administrative areas). Ile-de-France – the capital region of France – had, by far, the largest economy (€710 billion of GDP), followed by the northern Italian region of Lombardia (€366 billion) and the southern German region of Oberbayern (€274 billion). There were six more regions in the EU where GDP was within the range of €204–232 billion, all of which could also be characterised as major hubs of business activity: Rhône-Alpes in France; Düsseldorf, Stuttgart and Darmstadt in Germany; Comunidad de Madrid and Cataluña in Spain. Together with Köln (€193 billion of GDP), these 10 regions with the highest levels of regional GDP collectively accounted for 21.2 % of the EU’s total economic output.

These major hubs of economic activity also have some of the largest regional populations, although their economic output is typically boosted by commuters who live in surrounding/neighbouring regions. To give an idea of how concentrated economic activity in the EU was, the combined output of the smallest 69 regions was approximately the same as that of Ile-de-France, while the cumulative output of the smallest 141 regions was approximately the same as that for the 10 largest regions in the EU.

GDP per inhabitant in Southern Ireland was more than nine times as high as in the French archipelago of Mayotte

Map 1 is based on regional GDP per inhabitant (adjusted for purchasing power and then shown as a percentage of the EU average). Note that some of the differences between regions reflect the (sometimes artificial) administrative boundaries that are used to delineate each region.

In 2020, higher than average levels of GDP per inhabitant were primarily found in a band of regions that ran from the Nordic Member States, down through Germany and the Benelux countries into Austria and northern Italy. Otherwise, there were a few isolated pockets of relatively high regional values for GDP per inhabitant, for example, two out of the three regions in Ireland, specific regions in Spain and France, as well as most of the remaining capital regions. The regional distribution of GDP was relatively skewed insofar as only 38 % of regions (92 out of 242) reported a level of GDP per inhabitant that was above the EU average.

Those regions considered as relatively ‘wealthy’ – where GDP per inhabitant was at least 50 % above the EU average – are shown in the darkest shade of blue in Map 1. Among these 20 regions, Southern in Ireland had the highest regional GDP per inhabitant in 2020; its level of economic output was 2.7 times as high as the EU average. There were four other regions where economic output per inhabitant was at least twice as high as the EU average, they were all capital regions: Luxembourg, Eastern and Midland in Ireland, Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest in Belgium, and Praha in Czechia. Note that some regions with very high levels of GDP are characterised by a strong presence of multinational enterprises and/or commuter flows. This may distort their levels of economic activity, especially if capital assets (for example technology patents) are domiciled in a region. Ireland is home to a number of the world’s top technology and pharmaceutical companies.

There were 16 regions across the EU where GDP per inhabitant was less than 50 % of the EU average; they are shown in the darkest shade of yellow in Map 1. They were primarily concentrated in Greece (six regions) and Bulgaria (five regions), while there were also three other regions from eastern EU Member States – Észak-Alföld in Hungary, Nord-Est in Romania, and Panonska Hrvatska in Croatia – as well as Guyane and Mayotte (both Régions Ultrapériphériques Françaises). In 2020, the lowest level of regional GDP per inhabitant was recorded in Mayotte (in France), at just under one third of the EU average. The next lowest levels of GDP per inhabitant (all within the range of 36–39 % of the EU average) were recorded in Severozapaden, Severen tsentralen and Yugoiztochen, all in Bulgaria.

Map 1: GDP per inhabitant in purchasing power standards
(PPS), 2020
(index in relation to the EU average = 100, by NUTS 2 regions)
Source: Eurostat (nama_10r_2gdp) and (nama_10_pc)

Gross value added

When calculated from the output side, the main component of GDP is gross value added. This is defined as output (at basic prices) minus intermediate consumption (at purchaser prices) and is the balancing item of the national accounts’ production account. Value added can be analysed according to activity (for example, manufacturing or transport services) and by institutional sector (for example, government, households, financial corporations and non-financial corporations). The difference between value added and GDP is taxes (mainly value added tax (VAT)) and subsidies on products.

Gross value added fell in 215 out of 219 regions across the EU

Map 2 presents information on the annual change – between 2019 and 2020 – of regional gross value added; it therefore presents an analysis of the (initial) impact of the COVID-19 crisis. Note the information presented is a real rate of change, in other words the effects of inflation have been removed.

Having posted growth rates that were greater than 2.0 % in both 2017 and 2018, the EU’s annual rate of change for value added slowed the following year to 1.8 %. The direct and indirect effects of the COVID-19 crisis resulted in a 5.9 % contraction in 2020. To put this figure into context:

  • it was the first time that value added had fallen (in real terms) since a modest decline of 0.6 % in 2012;
  • the downturn in economic output as a result of the COVID-19 crisis was greater than the losses experienced at the height of the global financial and economic crisis, as output fell by 4.3 % in 2009.

In 2020, the COVID-19 crisis touched every region of the EU. In terms of its economic impact, the annual rate of change for value added was negative in 215 out of 219 regions for which data are available; note statistics presented in this section for Hungary and Poland are only available at a national level.

The largest contraction in value added was in the Greek island region of Notio Aigaio

There were 17 NUTS level 2 regions where value added fell by more than 10.0 % in 2020 (as shown by the lightest shade of yellow in Map 2): they included many of the EU’s most popular tourist destinations, for example: Notio Aigaio and Ionia Nisia in Greece; Illes Balears and Canarias in Spain; Jadranska Hrvatska in Croatia; Tirol in Austria; Algarve and Região Autónoma da Madeira in Portugal. At the onset of the pandemic, restrictions prevented most tourists from travelling and many hospitality businesses from opening. Although the situation improved somewhat during the summer months of 2020 (with a partial re-opening), many holidaymakers decided to stay at home, while business travel was also slow to recover as online meetings became more common. A second wave of the pandemic followed later in the year and acted as a further deterrent to travel.

The largest annual contractions in value added in 2020 were recorded in Notio Aigaio (down 22.2 %), Illes Balears (down 21.7 %) and Ionia Nisia (down 20.5 %); these were the only regions in the EU where value added was at least one fifth lower in 2020. The next largest declines were recorded in Canarias (down 18.1 %), Algarve (down 15.6 %) and Åland in Finland (down 15.5 %).

The economic impact of the COVID-19 crisis was relatively muted – with value added falling by no more than 4.0 % in 2020 – in every region of Denmark, Lithuania, Romania, Slovenia and Finland (except for Åland); this pattern was also observed in Estonia, Latvia, Luxembourg and Poland, where only national data are available.

There were only four regions (out of 219) across the EU where value added increased in 2020. The highest annual growth rate (10.7 %) was recorded in the Irish region of Southern (which was also the ‘richest’ region in the EU, as measured by GDP per inhabitant). Value added also increased in the two other Irish regions, up 3.6 % in Northern and Western and 1.8 % in the capital region of Eastern and Midland. Mayotte in France was the only other region in the EU to record an increase in its value added in 2020 (up 0.7 %). Some of the rapid growth in Ireland during 2020 can be linked to a buoyant pharmaceuticals sectors (one of the few sectors in the EU economy that continued to grow during the COVID-19 crisis).

Map 2: Change in gross value added, 2019–2020
(%, annual change in real terms, by NUTS 2 regions)
Source: Eurostat (nama_10r_2gvagr) and (nama_10_gdp)

Germany and Italy were characterised by a polycentric pattern of economic development

Map 3 is based on absolute values of regional GDP per inhabitant in PPS terms. The size of each circle reflects the level of GDP per inhabitant, while the colour indicates the change in GDP per inhabitant between 2019 and 2020 (based on the change in an index where the EU average = 100).

There are often large differences in the economic performance of regions across individual EU Member States. The vast majority of multi-regional Member States are characterised by their capital region having a much higher level of GDP per inhabitant. In several, the capital region – which often acts as a hub of business (and cultural) activity – was the only region where GDP per inhabitant was above the EU average. This pattern was apparent in most of the eastern Member States: Praha (Czechia), Budapest (Hungary), Warszawski stołeczny (Poland), Bucureşti-Ilfov (Romania), Zahodna Slovenija (Slovenia) and Bratislavský kraj (Slovakia). A similar pattern was observed in one of the Baltic Member States – Sostinės regionas (Lithuania) – while the only regions in France to record a level of GDP per inhabitant above the EU average were Ile-de-France (the capital region) and Rhône-Alpes (that includes Lyon, the third largest metropolitan region (behind Paris and Marseille)).

As such, many of the multi-regional EU Member States are characterised by a monocentric pattern of economic development. The only exceptions were: Germany (where the highest level of GDP per inhabitant was recorded in Hamburg), Ireland (Southern) and Italy (Provincia Autonoma di Bolzano/Bozen). Their situation was atypical insofar as they were characterised by a more polycentric pattern of economic development. For example, GDP per inhabitant in the German capital region of Berlin was lower than in 10 of the 37 other German regions, while a similar analysis for Italy reveals that GDP per inhabitant in Lazio was lower than in 5 of the 20 other Italian regions.

GDP per inhabitant in the EU stood at 31 300 PPS in 2019, while it was 29 900 PPS per inhabitant in 2020. The same information for NUTS level 2 regions may be expressed in the form of an index relative to these EU values, permitting a temporal analysis of GDP per inhabitant in PPS terms. Between 2019 and 2020, the largest increases in GDP per inhabitant – relative to developments in the EU – were concentrated in Denmark, Ireland and the Netherlands. The index rose by at least 4 points in every NUTS level 2 region of Denmark and Ireland, as well as 9 out of the 12 regions in the Netherlands – as shown by the dark blue circles in Map 3 – a similar development was observed in six Polish regions, three Swedish regions and two Finnish regions, as well as single regions from each of Belgium, Bulgaria, Germany, Lithuania, Romania and Luxembourg. The Netherlands was an exception insofar as its capital region was not present among those regions with a considerable increase in GDP per inhabitant (relative to the EU average).

The circles in Map 3 shaded in the darkest shade of yellow experienced the largest reductions in GDP per inhabitant (relative to the EU average) between 2019 and 2020. There were 21 regions across the EU where the index fell by more than 5 points. These were concentrated in southern regions of the EU, with 11 regions in Spain, three regions in Greece, two regions in Portugal, one in Italy and Malta; in addition, there was a single region in each of France, Austria and Finland. Most of the regions with the biggest relative declines were popular international holiday destinations – for example, Illes Balears and Canarias in Spain, Algarve in Portugal, Malta, the Alpine regions of Provincia Autonoma di Bolzano/Bozen in Italy and Tirol in Austria – or capital regions, such as Comunidad de Madrid, Attiki and Ile-de-France.

Map 3: GDP per inhabitant, 2020
(by NUTS 2 regions)
Source: Eurostat (nama_10r_2gdp) and (nama_10_pc)

Potential vulnerability to COVID-19 impacts

There are many reasons that may explain the distribution and concentration of economic activities across the different EU regions. Natural resource endowments may clarify why some regions are particularly specialised in activities such as mining or forest-based activities. In a similar vein, the weather, location and landscape can help explain why others might be specialised in agriculture or tourism-related activities. A critical mass of clients (either other enterprises or households/consumers) or the supply of skilled labour may also explain specialisations: for example, research parks tend to develop near to universities, whereas financial, communications and media services are often concentrated in capital city regions.

Distributive trades, transport, accommodation and food services (NACE Sections G–I) are generally contact-intensive services, with retail, transport and hospitality among the sectors most impacted by the COVID-19 crisis. Containment measures led to rapid shifts in demand, as people were no longer able to go shopping other than for essentials, travel to see family/friends, take a holiday, or visit a restaurant. General uncertainty and a reduction in working hours also led many households to reduce their consumption and/or increase precautionary saving.

Map 4 shows a specialisation index that is based on the share of these activities in regional value added, expressed relative to the same ratio for the whole of the EU; regions that were relatively specialised have positive values. Although the most recent data available are for 2019, these data may be used to analyse those regions that were potentially vulnerable to the impact of the crisis on the selected activities.

In 2019, prior to the pandemic, distributive trades, transport, accommodation and food services accounted for 19.3 % of the EU’s total value added. The relative importance of these service activities was considerably higher in several regions characterised as popular holiday destinations, with their share reaching more than half of all added value in two Greek regions – Notio Aigaio (52.7 %) and Ionia Nisia (50.0 %); the next highest share was recorded in Algarve in Portugal (38.9 %, approximately twice as high as the EU average).

Map 4 identifies those NUTS level 2 regions that had a high degree of relative specialisation for distributive trades, transport, accommodation and food services (as shown by the darkest shade of blue). Aside from tourism-orientated regions in southern EU Member States and in the Alps, this group also included five regions across Poland, both regions in Lithuania, as well as single regions in Belgium, Bulgaria, Croatia and Finland.

Map 4: Regional specialisation in distributive trades, transport, accommodation and food service activities, 2019
(percentage points difference compared with the average share of these activities in the economy for the EU as a whole, by NUTS 2 regions)
Source: Eurostat (nama_10r_3gva) and (nama_10_a10)

Income

The information presented above has already highlighted that wealth creation is often concentrated in capital and other major urban regions across the EU. However, it is likely that part of the income generated in these hubs of business activity may be attributed to commuters who live in surrounding regions where the price of property and cost of living may be lower, among other possible advantages. As a result, GDP per inhabitant in capital and urban regions tends to be relatively high compared with income measures, whereas surrounding regions are often characterised by relatively high levels of income per inhabitant when contrasted with their economic output.

Primary income per inhabitant

Primary income covers income from paid work and self-employment, as well as from interest, dividends and rents. In 2019, EU primary income per inhabitant averaged 20 100 PPS. The use of data in PPS (rather than in euro terms) takes account of price level differences between countries; it also reflects the fact that household expenditure is predominantly related to consumption.

Oberbayern had the highest level of primary income per inhabitant

In 2019, there were 25 regions spread across seven different EU Member States where income per inhabitant was at least 26 800 PPS; these are shown by the darkest shade of blue in Map 5. They were concentrated in Germany (16 regions), with the highest income levels predominantly found in western (rather than eastern) regions. Five more regions were in Benelux Member States and the remaining four in France, Italy, Austria and Romania.

At the other end of the range, there were 24 regions spread across eight different EU Member States where primary income per inhabitant was less than 11 200 PPS in 2019 (as shown by the lightest shade of yellow in Map 5). These regions were mainly concentrated in Greece or eastern Europe – seven of the 13 regions that compose Greece, all but one of the six regions that compose Bulgaria (the exception being the capital region of Yugozapaden), half of the eight regions that compose Romania, three regions in Hungary, one region each from Croatia, Poland and Slovakia – along with two outermost regions of France.

In 2019, primary income per inhabitant ranged from a high of 37 500 PPS in Oberbayern (southern Germany) down to 6 200 PPS in Severozapaden (Bulgaria). As such, the average level of income in Oberbayern was approximately six times as high as the level recorded in Severozapaden. Three more German regions featured at the top of the ranking with the highest levels of income per inhabitant – Stuttgart, Hamburg and Darmstadt – followed by Luxembourg. Note that Luxembourg had the highest level of income in euro terms (€40 300 per inhabitant) – slightly above the figure recorded for Oberbayern (€40 100 per inhabitant) – although Luxembourg’s relatively high cost of living meant that it ranked fifth when analysing the data in PPS terms.

Map 5: Net primary income per inhabitant, 2019
(in purchasing power standards
(PPS), by NUTS 2 regions)
Source: Eurostat (nama_10r_2hhinc)

Disposable income per inhabitant

The previous section analysed regional differences in primary income per inhabitant across EU regions. This section focuses on regional income differences within EU Member States. Rather than using net primary income, a more appropriate measure for this purpose is net disposable income. Disposable income is calculated by deducting income taxes and net social contributions from primary income while net social benefits and net current transfers are added.

Regional differences in income levels tend to be lower when analysed in terms of disposable (rather than net primary) income, due to the redistributive nature of tax and welfare systems. For example, regions with relatively high levels of income may be expected to pay higher / a greater share of taxes and social contributions, whereas regions with higher unemployment, an elderly population or a generally more vulnerable population are likely to receive proportionally more unemployment benefits, pensions and other kinds of monetary benefits. As such, the regional distribution of disposable income per inhabitant depends on the inequalities in primary income as well as inequalities in other factors (such as income tax, social benefits and transfer systems, differences in age structure and unemployment rates between regions).

Although Eurostat collects and publishes regional data on net disposable income, it is not recommended to use this information to analyse income differences across the EU; rather, these statistics are used to analyse regional differences within the same Member State. This is because most national statistical offices do not compile regional data for social transfers in kind. The latter are goods and services provided by government for free or at prices that are not economically significant; they mainly include education, health and some social security services, as well as housing, cultural or recreational services.

Figure 1 contrasts the distribution of net primary income and disposable income per inhabitant; regional data for each of the EU Member States have been converted into an index, based on the national average = 100. The figure shows the regional dispersion of income was lower for disposable rather than net primary income in 2019. This pattern was particularly pronounced across regions in the eastern EU Member States of Bulgaria, Poland, Romania and Slovakia, where the redistributive nature of tax and welfare systems lowered incomes in capital regions.

That said, many of the eastern EU Member States had relatively high levels of disposable income per inhabitant in their capital regions. In 2019, those living in the Romanian capital region of Bucureşti-Ilfov had a level of disposable income that was almost double (193.8 %) the national average. There were five more capital regions in eastern EU Member States where disposable income per inhabitant was at least one third higher than the national average: Bratislavský kraj in Slovakia (153.5 % of the average), Budapest in Hungary (150.6 %), Yugozapaden in Bulgaria (146.0 %), Warszawski stołeczny in Poland (136.3 %) and Praha in Czechia (133.3 %).

By contrast, Belgium, Germany and Austria were the only multi-regional EU Member States in 2019 to report a level of disposable income per inhabitant in their capital region that was below the national average. Oberbayern had the highest disposable income per inhabitant in Germany (122.3 % of the national average), Prov. Vlaams-Brabant in Belgium (115.5 % of the national average), and Vorarlberg in Austria (104.6 % of the national average).

Figure 1: Net primary income and disposable income per inhabitant, 2019
(index in relation to national average = 100, by NUTS 2 regions)
Source: Eurostat (nama_10r_2hhinc)

Compensation of employees

One of the principal areas of interest/concern for many employees is their level of remuneration. Employee compensation is defined (within national accounts) as remuneration, in cash or in kind (such as a company car or vouchers for meals), payable by an employer to an employee in return for work done; it also includes payments linked to social contributions (such as health or pension contributions). The data presented in Figure 2 refer to gross (in other words, before tax) hourly compensation in euro terms.

The highest level of employee compensation was recorded in Luxembourg

In 2019, employees working in the EU received an average of €23.9 in gross compensation for each hour that they worked. The highest level of employee compensation was recorded in Luxembourg (€47.6 per hour), while the lowest levels were registered across three different regions of Bulgaria – Severozapaden, Severen tsentralen and Yuzhen tsentralen (€4.8 per hour). As such, the ratio between the highest and lowest levels of employee compensation was almost 10 : 1.

Capital regions often recorded the highest levels of employee compensation, which is perhaps unsurprising given the relatively high cost of living in many of these regions and the fact that they are often the location for company headquarters and national administrations. This pattern was repeated in a majority of multi-regional EU Member States in 2019: the only exceptions were Oberbayern (that had the highest level of compensation per hour worked in Germany), Dytiki Makedonia (Greece), País Vasco (Spain) and Provincia Autonoma di Bolzano/Bozen (Italy).

It was not uncommon for the capital region to have a notably higher level of average employee compensation per hour worked. This often skewed the regional distribution within individual EU Member States, as the capital was the only region to record an average level of compensation above the national average.

There were eight NUTS level 2 regions in the EU where the average level of employee compensation was above €40.0 per hour in 2019. Aside from Luxembourg (that had the highest level), they included: four regions from Belgium – Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest, Prov. Brabant Wallon, Prov. Vlaams-Brabant and Prov. Antwerpen – with a peak in the capital region (€47.2 per hour); Hovedstaden (the Danish capital region; €45.4); Ile-de-France (the French capital region; €44.1); and Oberbayern in Germany (€40.2).

Figure 2: Compensation of employees, 2019
(€ per hour worked, by NUTS 2 regions)
Source: Eurostat (nama_10r_2lp10) and (nama_10_lp_ulc)

Labour productivity

Labour productivity can be defined as GDP or gross value added divided by a measure of labour input, typically the number of persons employed or the number of hours worked. When based on a simple headcount of labour input, as in Map 6, changes observed for this indicator can, at least to some degree, reflect changes in the structure of the employment market. For instance, the ratio falls if there is a shift from full-time to part-time work, or if working hours are curtailed due to restrictions such as those imposed during the COVID-19 crisis.

High labour productivity may be linked to the efficient use of labour and/or reflect the skills and experience of the labour force. These in turn may result from the specific mix of activities present in each regional economy as some activities – for example, knowledge-intensive industrial activities, business or financial services – tend to be characterised by higher levels of labour productivity (as well as higher average employee compensation).

In 2020, an average of €64 900 of value was added per person employed in the EU. This figure can be used as the basis for deriving a set of nominal labour productivity indices, which are presented relative to the EU average = 100 (see Map 6). Labour productivity was distributed relatively evenly across the EU, insofar as 119 (out of 242) NUTS level 2 regions had an index above the EU average, while 120 regions had an index below the EU average; three regions had the same level of labour productivity as the EU.

The highest regional levels of labour productivity were recorded in western and Nordic regions of the EU. They were particularly concentrated in Belgium, Denmark, Ireland, Germany, Austria and Sweden, where two or more regions had labour productivity indices that were at least 35 % above the EU average; in fact, this was the case in all five regions of Denmark.

At the top end of the range, there were four NUTS level 2 regions where labour productivity was more than twice as high as the EU average in 2020: Southern, and Eastern and Midland in Ireland, Luxembourg, and Prov. Brabant Wallon in Belgium. The highest level of labour productivity, by far, was recorded in Southern (€227 100 per person employed, some three and a half times as high as the EU average), followed by Eastern and Midland (€161 600 per person employed, approximately two and a half times as high as the EU average). As noted above, the relatively high levels of value added in these Irish regions may be linked to the presence of multinational enterprises, which may inflate their levels of labour productivity (especially when capital assets are domiciled in a region). Labour productivity in Luxembourg (€136 000 per person employed) and Prov. Brabant Wallon (€131 100 per person employed) was slightly more than twice as high as the EU average.

At the other end of the range, there were 31 NUTS level 2 regions in the EU where labour productivity was less than 45 % of the EU average in 2020. They were largely concentrated in eastern EU Member States: all six regions of Bulgaria, two regions in Croatia, five regions in Hungary, nine regions in Poland and six regions in Romania; there were also three regions in Greece. The lowest levels of labour productivity were registered in three regions of Bulgaria: Severen tsentralen (€13 100 per person employed, equivalent to one fifth of the EU average), Yuzhen tsentralen (€13 900 per person employed) and Yugoiztochen (€14 000 per person employed).

Map 6: Nominal labour productivity, 2020
(index based on € per person employed in relation to EU average = 100, by NUTS 2 regions)
Source: Eurostat (nama_10r_2nlp), (nama_10_a10) and (nama_10_a10_e)

The information presented in the final map is based on labour productivity per hour worked, which takes account of the sectoral, regional and national differences in working time. The change in real labour productivity per hour worked is based on a volume series of gross value added (in other words, adjusted for price changes), divided by the total number of hours worked. From the resulting ratios, annual average rates of change are compiled for the period 2010–2019. Note that the data presented for Mayotte in France cover the period 2014–2019, while there is no information available for Poland.

During the period studied, annual changes in the EU’s real labour productivity per hour worked were within the range of 0.4–1.9 %. Labour productivity rose, on average, by 1.0 % per year during this period. Map 7 shows that real labour productivity per hour worked increased in the vast majority of NUTS level 2 regions between 2010 and 2019; this was the case in more than four fifths of all regions (191 out of 225 regions for which data are available). There were five regions where real labour productivity per hour worked was the same in 2019 as in 2010, and 29 regions where it fell.

The highest annual average growth rates for real labour productivity per hour worked were principally concentrated in eastern EU Member States. This was particularly notable in Bulgaria and Romania, where a majority of regions had average growth rates of at least 2.0 % per year for the period 2010–2019. They were joined by three regions in Czechia, two regions in eastern Germany, single regions from Ireland, France (Mayotte; 2014–2019), Croatia, Lithuania, Hungary and Slovakia, as well as Estonia and Latvia. The highest productivity growth rates were recorded for the regions of Bucureşti-Ilfov (7.6 %) and Vest (7.4 %) in Romania and for Southern (7.1 %) in Ireland.

The 29 regions where real labour productivity per hour worked decreased between 2010 and 2019 were concentrated in southern regions of the EU, including all 13 regions of Greece and four regions in Italy. Alongside the capital regions of Attiki (Greece) and Lazio (Italy), there were three other capital regions where labour productivity decreased during this period (although by a relatively modest amount): Wien in Austria, Área Metropolitana de Lisboa in Portugal, and Helsinki-Uusimaa in Finland. The lowest rates of change for real labour productivity per hour worked were recorded in two Greek regions: Dytiki Makedonia (an average fall of 4.0 % per year) and Notio Aigaio (an average fall of 3.2 % per year).

Map 7: Change in real labour productivity per hour worked, 2010–2019
(%, average annual rate of change, by NUTS 2 regions)
Source: Eurostat (nama_10r_2rlp)

Source data for figures and maps

Excel.jpg Economy at regional level

Data sources

European system of national and regional accounts

The European system of national and regional accounts (ESA 2010) is the latest internationally compatible accounting framework for a systematic and detailed description of the EU economy. ESA 2010 has been implemented since September 2014 and is consistent with worldwide guidelines on national accounting, as set out in the system of national accounts (2008 SNA).

ESA 2010 provides a framework for consistent, comparable, reliable and up-to-date economic statistics for EU Member States. The legal basis for these statistics is Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013 on the European system of national and regional accounts in the European Union. ESA 2010 is not restricted to annual national accounting, as it also applies to quarterly and shorter or longer period accounts, as well as to regional accounts. It is harmonised with the concepts and classifications used in many other social and economic statistics (for example, statistics on employment, business or international trade) and as such serves as a central reference for socioeconomic statistics.

Regional data

Statistics from regional economic accounts are presented here for NUTS level 2 regions, although a more detailed regional analysis is available for NUTS level 3 regions for GDP, gross value added at basic prices and employment. The data for statistical regions in the EFTA and candidate countries are sometimes unavailable and have been replaced (where appropriate) by national aggregates. Note also that the data for these countries are sometimes less recent than for EU regions; all discrepancies are footnoted under maps or figures.

Indicator definitions

Gross domestic product and value added

Gross domestic product (GDP) is a basic measure of the overall size of an economy. As an aggregate measure of production, GDP is equal to the sum of the gross value added of all resident institutional units engaged in production, plus any taxes on products and minus any subsidies on products.

Gross value added (GVA) is defined as output (at basic prices) minus intermediate consumption (at purchaser prices); it is the balancing item of the national accounts’ production account.

Income

Two types of income are recorded as primary income:

  • primary incomes receivable by virtue of direct participation in the production process, mainly operating surplus and mixed income and the compensation of employees;
  • property incomes receivable by the owner of a financial asset or a tangible non-produced asset in return for providing funds to, or putting the tangible non-produced asset at the disposal of, another institutional unit (interest, dividends, withdrawals from income of quasi-corporations, reinvested earnings of foreign direct investment, rents on land).

Disposable income is the total amount of money that households/individuals have available for spending or saving after subtracting income taxes, contributions and transfers.

Compensation of employees and labour productivity

In national accounts, the compensation of employees is defined as the total remuneration, in cash or in kind, payable by an employer to an employee in return for work done by the latter during an accounting period. It consists of wages and salaries in cash or in kind and employer’s actual and imputed social contributions.

Labour productivity reflects the (average) amount of goods and services produced per member of the labour force or the output per input of labour. It can be measured in a variety of ways. For example, it may be measured by GDP (in terms of purchasing power standards) either relative to the number of employed people or to the number of hours worked. In both cases, it is then expressed as an index.

Context

The COVID-19 crisis severely disrupted production and trade. Lockdowns closed many plants, and disturbances to trading routes still exist today with very high shipping costs. There were also difficulties concerning the supply of strategic items used in industrial supply chains such as the automotive or microprocessor industries. As the EU economy returns to growth and the impact of the pandemic dissipates, the attention of policymakers and economists is turning to a number of longer-term, structural challenges that remain: population ageing, climate change, weak productivity growth, rising income and wealth inequality, or territorial disparities within and among EU Member States.

International interest in sustainable development issues has been led by work conducted under the auspices of the United Nations (UN). Transforming our world: the 2030 agenda for sustainable development was adopted on 25 September 2015 and provides a commitment to eradicate poverty and achieve worldwide sustainable development by 2030. In conjunction, the European Commission adopted a series of communications including A decent life for all: ending poverty and giving the world a sustainable future (COM(2013) 92 final), A decent life for all: from vision to collective action (COM(2014) 335 final) and A Global Partnership for Poverty Eradication and Sustainable Development after 2015 (COM(2015) 44 final).

Following on from the global financial and economic crisis, the European Commission reset its priorities in 2014 as ‘boosting jobs, growth and investment’. This major initiative aimed to unlock public and private investment by targeting infrastructure developments, such as broadband internet, energy networks and transport. Subsequently, with the arrival of a new European Commission, six priorities were identified for the period 2019–2024, including three with a direct impact on the economy: ‘A European Green Deal’, ‘A Europe fit for the digital age’ and ‘An economy that works for people’.

In December 2020, the multiannual financial framework covering the period 2021–2027 was adopted. This provides budget to kick-start the European economy, through boosting the green and digital transitions, and making it fairer, more resilient and more sustainable for future generations. The plan was reinforced by an emergency European Recovery Instrument (also known as Next Generation EU) to facilitate decisive responses to the most urgent challenges, such as the COVID-19 crisis.

In total, €274.3 billion have been allocated in the multiannual financial framework for regional development and cohesion between 2021 and 2027. In addition, a further €50.6 billion has been allocated to regional development and cohesion as part of the European Recovery Instrument. The EU’s regional and cohesion policy will, in the coming years, support broader socioeconomic priorities by focusing on five investment priorities:

  • a smarter Europe (for example, through innovation and digitisation);
  • a greener, carbon free Europe (investing in energy transition, renewables and the fight against climate change);
  • a more connected Europe (highlighting strategic transport and digital networks);
  • a more social Europe (supporting quality employment, education, skills, social inclusion and equal access to healthcare);
  • a Europe closer to its citizens (promoting locally-led development strategies and sustainable urban development).

Alongside the budget for regional development and cohesion, an additional €723.8 billion has been allocated to a Recovery and Resilience Facility, a small majority of which will be disbursed as loans and the rest as non-repayable grants. The general objective of the facility is to promote the EU’s economic, social and territorial cohesion by improving its resilience, crisis preparedness and growth potential, by mitigating the socioeconomic impact of the COVID-19 crisis, through support for green and digital transitions. It is designed to do so by ensuring reforms and investments are in line with the EU’s priorities as identified in country-specific recommendations.

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Regional economic accounts – ESA 2010 (t_reg_eco)
Regional economic accounts – ESA2010 (t_nama_10reg)
Regional economic accounts (reg_eco10)
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Branch and household accounts (reg_eco10brch)
Main GDP aggregates (nama_10_ma)
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Basic breakdowns of main GDP aggregates and employment (by industry and by assets) (nama_10_bbr)
Regional economic accounts (nama_10reg)
Gross domestic product indicators (nama_10r_gdp)
Branch and household accounts (nama_10r_brch)

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This article forms part of Eurostat’s annual flagship publication, the Eurostat regional yearbook.