GDP at regional level
- Data extracted in May 2015. Most recent data: Further Eurostat information, Main tables and Database. Planned article update: June 2016.
This article is part of a set of statistical articles based on the Eurostat regional yearbook publication. It uses a set of regional economic accounts to analyse economic developments within the European Union (EU): the first section is based on gross domestic product (GDP), the principal aggregate for measuring economic developments / growth; the second provides a regional analysis of gross value added by activity (as defined in terms of NACE); while, the article closes with a brief analysis of labour productivity (defined here as gross value added per person employed).
Regional accounts serve as the basis for the allocation of expenditure under the EU’s cohesion policy. Every region of the EU is covered: however, most structural funds are directed to NUTS 2 regions where GDP per capita is less than 75 % of the EU-28 average. The allocation of cohesion funds is currently based on a decision referring to average GDP per capita during the three-year period from 2007 to 2009; more information is provided in an article on regional policies and Europe 2020.
- 1 Main statistical findings
- 2 Data sources and availability
- 3 Context
- 4 See also
- 5 Further Eurostat information
- 6 External links
Main statistical findings
GDP at market prices in the EU-28 was valued at EUR 13.5 trillion in 2013, which equated to an average level of approximately 26.6 thousand PPS per capita.
Regional GDP per capita
Map 1 shows GDP per capita in 2013 for NUTS level 2 regions, with the value for each region expressed as a percentage of the EU-28 average (set to equal 100 %). As such, it portrays relatively ‘rich’ regions (shown in green) where GDP per capita was above the EU average and relatively ‘poor’ regions (shown in red). The map reveals a clear east–west divide. However, this pattern is less pronounced than it was almost a decade before — when the EU underwent its largest expansion with the accession of 10 new Member States — as a result of two principal factors:
- a gradual process of economic convergence, resulting from relatively rapid growth among less developed regions;
- the financial and economic crisis, which had a considerable impact on the economic performance of most EU Member States.
SPOTLIGHT ON THE REGIONS
The most rapid economic growth during the period 2008–13 across NUTS level 2 regions of the EU was recorded in the Polish region of Mazowieckie, which includes the capital of Warsaw. GDP per capita in Mazowieckie was about four fifths of the EU-28 average in 2008, but rose to be 7.1 % higher than the EU-28 average by 2013.
©: Itsmejust / Shutterstock.com
Indeed, many regions in the east of the EU, especially capital regions, have seen their GDP per capita (adjusted for price level differences) rise in absolute terms and in relation to the EU-28 average. By contrast, the impact of the crisis resulted in GDP per capita falling below the EU-28 average in every region of Greece, Cyprus (a single region at this level of analysis), southern Italy, most of Portugal and Spain, and more than half the regions in France and the United Kingdom.
Economic activity — defining GDP
GDP is the central measure of national accounts, summarising the economic position of a country or region. It can be calculated using different approaches: the output approach; the expenditure approach; and the income approach.
GDP is used to analyse economic performance and cycles (such as recessions, recoveries and booms). Data in diverse currencies can be converted into a common currency to make it more easily comparable — for example, converting into euros or dollars. However, exchange rates do not reflect all the differences in price levels between countries. To compensate for this, GDP can be converted using conversion factors known as purchasing power parities (PPPs). By using PPPs (rather than market exchange rates) these indicators are converted into an artificial common currency called a purchasing power standard (PPS); the use of a PPS makes it possible to compare purchasing power across the regions of EU Member States that use different currencies and where price levels are different.
In broad terms, the use of PPS series rather than a euro-based series tends to have a levelling effect, as those regions with very high GDP per capita in euro terms also tend to have relatively high price levels (for example, the cost of living in central Paris or London is generally higher than the cost of living in rural areas of Hungary or Poland).
The highest level of GDP per capita in the EU was recorded in Inner London
In 2013, approximately 15 % of the 250 NUTS level 2 regions for which data are available (see Map 1 for coverage) reported that their GDP per capita was at least 25 % higher than the EU-28 average; they are shown in the darkest shade of green. Many of them were capital regions or regions that neighboured capital regions, while the vast majority of the others were clustered together in the centre of the map, covering southern Germany, western Austria and northern Italy, as well as Switzerland.
There were three regions where GDP per capita in 2013 was more than double the EU-28 average, namely: Inner London, Luxembourg (a single region at this level of analysis) and the Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest.
Measuring wealth and income by place of residence or place of work?
Average GDP per capita fails to provide an indication as to the distribution of wealth between different population groups in the same region, nor does it measure the income ultimately available to private households in a region, as commuter flows may result in employees contributing to the GDP of one region (where they work), and to household income in another region (where they live).
This drawback is particularly relevant when there are significant net commuter flows into or out of a region. Areas that are characterised by a considerable number of inflowing commuters often display regional GDP per capita that is extremely high (when compared with surrounding regions). This pattern is seen in many metropolitan areas of the EU, but principally in capital cities. Because of this anomaly, high levels of GDP per capita that are recorded for some regions with net commuter inflows do not necessarily translate into correspondingly high levels of income for the people living in the same region.
All three of these regions with the highest levels of GDP per capita in 2013 were characterised by high commuter inflows: indeed, many people travel large distances into central London each day for work; the Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest is relatively small in size (covering just over 160 km²) and attracts commuters; while a high proportion of those who work in Luxembourg travel across national borders coming to work from neighbouring Belgium, Germany and France.
Capital regions often recorded the highest levels of GDP per capita
Looking in more detail at those regions with relatively high average levels of GDP per capita, there were 17 regions where this ratio was at least 50 % higher than the EU-28 average. Aside from the three regions already mentioned, these included the capital regions of Slovakia, Sweden, France, the Czech Republic, Austria, the Netherlands and Denmark. The remaining seven regions were spread across Germany (Bremen and Hamburg; note the data for Germany is presented by NUTS level 1 region), the Netherlands (Groningen and Utrecht), Austria (Salzburg) and the United Kingdom (Berkshire, Buckinghamshire and Oxfordshire and North Eastern Scotland).
Figure 1 presents an alternative analysis of the regional distribution of GDP per capita in 2013. It shows that in the majority of the multi-regional EU Member States, capital regions were generally those with the highest average GDP per capita; the only exceptions to this rule were Germany, Italy and the Netherlands. In Germany (note the data are for NUTS level 1 regions), the highest average GDP per capita was recorded in Hamburg, while Berlin was the only capital region that recorded GDP per capita below its national average. The Italian capital region of Lazio had the sixth highest level of GDP per capita among Italian regions, with higher levels recorded in most of the more northerly regions, peaking in the Provincia Autonoma di Bolzano / Bozen. In the Netherlands, Groningen was the only Dutch region to record average GDP per capita that was higher than in the capital region of Noord-Holland.
The capital regions of the Czech Republic, Ireland, Hungary, Poland, Portugal, Romania and Slovakia were the only regions from each of these EU Member States where GDP per capita was higher than the EU-28 average in 2013.
In Inner London, GDP per capita was almost 11 times higher than in Severozapaden
In 2013, average GDP per capita for Inner London (325 % of the EU-28 average) was almost 11 times as high — having taken account of differences in price levels — as in Severozapaden (Bulgaria), where the lowest average GDP per capita was recorded (30 % of the EU-28 average). Note this edition of the Eurostat regional yearbook is based on NUTS 2010 and therefore excludes information on Mayotte (a French overseas territory that became part of the regional classification as of NUTS 2013). The first regional accounts for Mayotte have been received by Eurostat and these suggest that GDP per capita was 27 % of the EU-28 average in 2013 (slightly lower than in Severozapaden).
An analysis for those EU Member States with more than two regions shows that the widest disparities in wealth creation between regions from the same country were recorded within the United Kingdom, as GDP per capita in Inner London was almost five times as high as in West Wales and the Valleys. There were also considerable differences within Romania (a ratio of 3.9 between the capital region of Bucuresti-Ilfov and Nord-Est), Slovakia (a ratio of 3.6 between the capital region of Bratislavský kraj and the eastern region of Východné Slovensko) and France (a ratio of 3.3 between the capital region of Île de France and the overseas South American region of Guyane).
GDP per capita was higher than the EU-28 average in every region of Sweden
By contrast, wealth creation was relatively evenly spread across the Nordic Member States, Austria, Spain, Portugal and Greece. In each of these EU Member States, average GDP per capita in the capital region was never more than double that recorded in the region with the lowest GDP per capita, as was also the case in Norway. Sweden was the only multi-regional EU Member State to report that each of its NUTS level 2 regions had an average level of GDP per capita that was above the EU-28 average in 2013; the same was true for the level 2 regions in Norway.
The 19 regions in the EU where GDP per capita was less than half the EU-28 average were all located in eastern Europe
Those regions which are targeted the most by cohesion funds have an average GDP per capita that is less than 75 % of the EU-28 average; these regions are shown in a dark red shade in Map 1. There were 80 NUTS level 2 regions which fell into this category in 2013. It should be noted that the basis of funding for the 2014–20 programming period has been fixed with respect to average GDP per capita during the three-year period 2007–09.
Almost a quarter (19 regions) of the 80 regions with relatively low GDP per capita has a level of economic output per capita that was less than half the EU-28 average. These regions were all located in eastern Europe and were spread across four of the EU Member States, with five regions from each of Bulgaria, Poland and Romania, and four regions from Hungary. The three Bulgarian regions of Severozapaden, Severen tsentralen and Yuzhen tsentralen reported the lowest average GDP per capita in the EU, with each of these regions having a level of output per capita that was less than one third of the EU-28 average. Note that the data presented in this edition of the Eurostat regional yearbook is based on the NUTS 2010 classification. However, data has already been received for some regions covering the revised classification (NUTS 2013) and this shows that GDP per capita in the French overseas region of Mayotte (in the Indian Ocean) was 27 % of the EU-28 average in 2013; Mayotte became an outermost region of the EU as of 1 January 2014.
In Bulgaria, Greece, Croatia and Slovenia, every region (including the capital region), recorded an average level of GDP per capita that was below the EU-28 average. GDP per capita was also below the EU-28 average in five EU Member States that are single regions at this level of analysis, the Baltic Member States, Cyprus and Malta; this was also the case in the former Yugoslav Republic of Macedonia and Serbia (where there are currently no regional statistics available).
Analysis of regional economic development over time
During the financial and economic crisis, GDP per capita in the EU-28 peaked in 2008 at 25.9 thousand PPS. There was a rapid reduction in activity in 2009 and it was not until 2011 that the average level of GDP per capita had returned (slightly) above its pre-crisis peak. The pace at which GDP per capita was increasing slowed in 2012 and this pattern continued in 2013 when an average of 26.6 thousand PPS of GDP was generated per capita.
GDP per capita increased at a rapid pace in Poland
Map 2 shows the effects of the financial and economic crisis, detailing regional performance for NUTS level 2 regions between 2008 and 2013 (see the footnotes to the map for more information on coverage). Those regions that expanded at a fast pace — as shown by the darkest shade of green — were principally located in Poland (all but 3 of its 16 regions), while — as a percentage of the EU-28 average — GDP per capita also increased by more than eight percentage points in Lithuania (a single region at this level of analysis), Groningen (the Netherlands), Burgenland and Salzburg (Austria), the capital regions of Bucureşti - Ilfov (Romania) and Bratislavský kraj (Slovakia), and the archipelago of Åland (Finland).
National economic fortunes appear to play a significant role in determining regional economic performance
It is interesting to note that, despite wide variations in average levels of GDP per capita between the regions of some EU Member States, there was a relatively uniform pattern to changes in economic activity over the period from 2008 to 2013. Among the multi-regional EU Member States, GDP per capita grew at a faster pace than the EU-28 average in every region of Denmark, Germany (aside from Berlin and Hamburg), Hungary, Austria (aside from Wien), Poland, Romania and Slovakia; there was also growth in every Norwegian region, as well as in Switzerland, the former Yugoslav Republic of Macedonia and Serbia. By contrast, every region in Greece, Spain, Croatia, Italy (with the exception of the Provincia Autonoma di Bolzano / Bozen), Slovenia, Finland (with the exception of Åland) and the United Kingdom saw their average GDP per capita grow at a slower pace than the EU-28 average (usually as a result of slow growth, rather than an absolute decline in GDP per capita).
The fastest regional economic growth during the period 2008–13 was recorded in the Polish and Slovakian capital regions
The highest growth between 2008 and 2013 in GDP per capita relative to the EU-28 average was recorded in the capital regions of Poland and Slovakia, as Mazowieckie and Bratislavský kraj posted increases of 24.0 and 18.8 percentage points. There were eight other regions where GDP per capita relative to the EU-28 average grew by at least 10 percentage points: six of these were located in Poland, while the remaining two regions were Lithuania (a single region at this level of analysis) and Groningen (the Netherlands; note that the growth rate for this region is based on the period 2010–13).
All Greek regions were strongly affected by the financial and economic crisis
At the other end of the range, a total of 36 regions recorded a fall of at least 8 percentage points between 2008 and 2013 in their GDP per capita relative to the EU-28 average, (as shown by the darkest red shade in Map 2). The impact of the financial and economic crisis on the Greek economy was widespread, as 12 of the 14 lowest rates of change were posted by Greek regions; Cyprus (a single region at this level of analysis) and Bedfordshire and Hertfordshire (in the United Kingdom) were the only regions to record similar rates of change.
Gross value added by industry
Maps 3–7 provide a regional analysis of gross value added by activity (as defined in terms of NACE). Each map shows the degree of relative specialisation in 2012, in relation to the EU average (set as 100 %). There are considerable differences as regards the contribution that each activity makes to regional economic output.
SPOTLIGHT ON THE REGIONS
Across most of the EU, the relative weight of agriculture, forestry and fishing in total economic activity has, in recent decades, slowly fallen. Nevertheless, these activities remain a vital part of the local economy in many rural regions. In the north-western Bulgarian region of Severozapaden, the contribution to total gross value from agriculture, forestry and fishing was 7.5 times as high as the EU-28 average.
©: Moni84 / Shutterstock.com
Bulgarian and Hungarian regions were highly specialised in agriculture, forestry and fishing
The relative contribution of agriculture, forestry and fishing (NACE Section A) to the total gross value added of regional economies is unsurprisingly higher in rural areas than in more built-up areas, such as towns and suburbs or cities. Map 3 shows that agriculture, forestry and fishing contributed a relatively high share of total gross value added in the majority of rural regions, in contrast to a low share of activity in capital regions and other densely populated areas (for example, in the Benelux Member States, Germany and the United Kingdom). The contribution of agriculture, forestry and fishing to the gross value added of the regional economies of Inner London, Berlin and the Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest was less than 1 % of the average share for the EU-28 as a whole. By contrast, the share of these activities in total gross value added was 6–7 seven times as high as the EU-28 average in the Hungarian regions of Észak-Alföld, Dél-Dunántúl and Dél-Alföld, as well as in the Bulgarian region of Severen tsentralen, rising to 7.5 times as high in another Bulgarian region, Severozapaden.
Apart from the capital region of Praha, all of the remaining regions in the Czech Republic had a high degree of industrial specialisation
The relatively high contribution of industrial activities (NACE Sections B–E) to regional gross value added was largely concentrated in a cluster of regions — shown by the dark green shade at the centre of Map 4 — that spread over southern Germany, the whole of the Czech Republic (apart from the capital region), up into Poland, and down through several regions of Slovakia, Austria, Hungary and Slovenia; the majority of regions in Bulgaria and Romania also had a very high degree of industrial specialisation. Aside from these two clusters, a relatively high share of regional gross value added — at least 50 % higher than the EU-28 average — was generated within industrial activities in the peripheral industrial economies of Border, Midland and Western (Ireland), Dytiki Makedonia (Greece), the Comunidad Foral de Navarra and La Rioja (Spain), Groningen (the Netherlands), Övre Norrland (Sweden) and North Eastern Scotland (the United Kingdom). There were seven regions where the contribution of industry to regional gross value added was more than double the EU-28 average, three of these were from the Czech Republic (Střední Morava, Střední Čechy and Moravskoslezsko), two were from Hungary (Közép-Dunántúl and Nyugat-Dunántúl), and there was a single region from each of Germany (Braunschweig) and the Netherlands (Groningen). By contrast, the contribution of industrial to total gross value added was relatively low in capital regions (where services are usually the main wealth creator) and a number of regions that may be characterised as tourist destinations, especially prevalent around the Mediterranean coast.
The impact of the financial and economic crisis on construction was still apparent in Ireland and Greece
Map 5 shows those regions which were relatively specialised in construction (NACE Section F). The impact of the financial and economic crisis was still being felt in a number of EU Member States where housing bubbles burst: this was most apparent in Ireland, where the contribution of construction to total gross value added was less than half the EU-28 average in both regions (Border, Midland and Western; Southern and Eastern); this was also the case in three Greek regions (Attiki; Anatoliki Makedonia, Thraki; and Kentriki Makedonia), as well as Hamburg (Germany) and Groningen (the Netherlands). Construction also accounted for a relatively low share of the economic activity taking place in many city regions, which may be attributed to the lack of free space or building consent for new projects in regions that are already highly developed. By contrast, there were three regions where the contribution of construction to total gross value added was more than twice the EU-28 average, Sud-Est (Romania) and the two Slovak regions of Stredné Slovensko and Východné Slovensko.
Map 6 and Map 7 provide a similar analysis for two groups of services. The first group covers NACE Sections G–N: distributive trades, transport, accommodation and food services, information and communication, financial and insurance services, real estate and business services (professional, scientific, technical, administrative and support); these are referred to hereafter as market services. The second group covers NACE Sections O–U, including public administration and public services, arts, entertainment and recreation, the repair of household goods and other services and is referred to hereafter as public administration and other services.
Market services were concentrated in capital regions and regions characterised as tourist destinations
Those regions in the EU characterised by highly developed market services, as seen by the dark green regions in Map 6, were often capitals. This was the case in Praha, Attiki, the Comunidad de Madrid, the Île de France, Luxembourg (a single region at this level of analysis), Noord-Holland and Inner London. The other regions where the contribution of market services to total value added was much higher than the EU-28 average were often characterised as tourist destinations, for example, the Algarve (in Portugal), the Illes Balears (in Spain), and the two Greek regions of Notio Aigaio (which includes among other Kos, Mykonos and Rhodes) and Ionia Nisia (which includes Corfu). There were three other regions where the contribution of market services to total gross value added was at least 25 % higher than the EU-28 average, they were: the Provincie Vlaams-Brabant in Belgium, Hamburg in Germany and Berkshire, Buckinghamshire and Oxfordshire in the United Kingdom. Groningen was the only region where market services contribution to total gross value added was less than half the EU-28 average; due to its relatively large (offshore) gas activities.
Public administration and other services often accounted for a high share of economic activity in peripheral regions
Map 7 shows a relatively clear east–west split in terms of the economic contribution made by public administration and other services. The role of the public administration and other services was often smaller in some of those Member States that joined the EU in 2004 or more recently. The share of public administration and other services was also relatively high in many regions that were touched by high levels of unemployment, which may be the result of the public administration remaining one of the few principal employers; this was particularly the case in peripheral regions, where a lack of proximity to clients may be one factor which deters entrepreneurs and private enterprises from establishing a business.
Across the NUTS level 2 regions of the EU there were 13 regions where the contribution of public administration and other services to total gross value added was at least 50 % higher than the EU-28 average. The highest shares were recorded in the two autonomous Spanish cities of Ceuta and Melilla, followed by the four French overseas regions, while the other regions included two from Belgium (Province Luxembourg and Province Namur), two from Greece (Anatoliki Makedonia, Thraki and Voreio Aigaio), two from France (Limousin and Corse) and a single region from Denmark (Sjælland).
Note that an article on regional structural business statistics provides a similar analysis based on the number of persons employed across different activities within regional business economies.
Within regional accounts, labour productivity is defined as gross value added in euros at basic prices per person employed; Map 8 presents this indicator for NUTS level 2 regions in 2013 with the results shown in relation to the EU-28 average. Regional labour productivity would ideally take account of the total number of hours worked (rather than a simple count of persons employed), however, this measure is currently incomplete for a number of EU Member States.
If there are significant flows of commuters between regions, then it is likely that those regions characterised as having net inflows of commuters will display lower levels of gross value added per person employed than their corresponding ratios for GDP per capita, if the employment data relate to the region of employment rather than residence. In other words, the gap between regions may be narrower when analysing labour productivity than when analysing GDP per capita. That said, the highest level of gross value added per person employed in 2013 was recorded in Inner London (the same region that had the highest level of GDP per capita). Relatively high levels of labour productivity may be linked to the efficient use of labour (without using more inputs), or may result from the mix of activities that make-up a particular economy (as some activities have higher levels of labour productivity than others). For example, the financial services sector plays a particularly important role in the economy of Inner London and this activity is characterised as having particularly high levels of productivity. Southern and Eastern Ireland (which includes Dublin) — which also specialises in financial services — was also present among the top 10 regions for labour productivity. The remainder of the top 10 was constituted by four Belgian regions (Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest; Provincie Antwerpen; Provincie Vlaams-Brabant; Province Brabant Wallon), the Danish, French and Swedish capital regions, and the Dutch region of Groningen.
Labour productivity lower in those Member States that joined the EU in 2004 or more recently
There was not a single region from the Member States that joined the EU in 2004 or more recently that had a level of gross value added per person employed above the EU-28 average. The Slovakian capital region of Bratislavský kraj recorded the highest level of gross value added per person employed among the NUTS 2 regions from these 13 Member States (subject to data availability), at just over 80 % of the EU-28 average in 2013.
There were 43 NUTS level 2 regions where gross value added per person employed was less than half the EU-28 average in 2013 (as shown by the darkest red shade in Map 8). These were spread across eastern regions of the EU, with low labour productivity in every region of Bulgaria, all but two of the regions in the Czech Republic (Střední Čechy and the capital region of Praha), all but two of the regions in Poland (Dolnośląskie and the capital region of Mazowieckie), all but one of the regions in Romania (the capital region of Bucureşti - Ilfov), and two regions in Slovakia (Stredné Slovensko and Východné Slovensko); labour productivity was also less than half the EU-28 average in two of the three Baltic Member States (Latvia and Lithuania).
Data sources and availability
The European system of national and regional accounts (ESA) provides the methodology for national accounts in the EU. The current version, ESA 2010, was adopted in May 2013 and has been implemented since September 2014. As such, this is the first edition of the Eurostat regional yearbook that has used ESA 2010. It is important to note that the move to ESA 2010 was part of a broader worldwide initiative, as ESA 2010 is the counterpart of and fully consistent with the United Nations 2008 system of national accounts (2008 SNA).
ESA 2010 provides a harmonised methodology that should be used for the production of national and regional accounts in the EU. It ensures that economic statistics on the economies of EU Member State are compiled in a consistent, comparable, reliable and up-to-date way. The legal basis for these statistics is a Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union (No 549/2013).
ESA 2010 was revised in order to take account of a number of changes that have impacted economic developments in recent years, in particular: the increasing role of information and communication technologies; the growing importance of intangible assets, intellectual property products and services; and economic globalisation. Among others, the new methodology also takes account of expenditure on weapon systems (counted as investment) and has a more detailed analysis of pension schemes. In many cases, the most significant methodological change in terms of its impact on the headline GDP figure is the capitalisation of research and development (R & D) expenditures.
At a regional level, two types of effects can be distinguished:
- the impact of changes at a national level which do not have a specific regional variation — for example, the inclusion of weapon systems expenditure resulted in changes to regional GDP that affected all regions equally.
- the impact of changes which do have a regional variation — for example, the treatment of R & D expenditure as investment, which is likely to increase regional disparities in GDP per capita as those regions with high levels of R & D expenditure tend to be relatively ‘rich’.
Note that changes linked to the implementation of ESA 2010 have not had any implication on the allocation of structural funds under the multi-annual financial framework for 2014–20; these allocations were initially decided in 2012 on the basis of regional GDP data for the reference years 2007–09.
Further information on the transition from ESA 95 to ESA 2010 is presented on Eurostat’s website.
Statistics from regional economic accounts are largely shown for NUTS level 2 regions. Data for Germany are only available for NUTS level 1 regions, while those for Switzerland are only available at a national level. The latest statistics available for Norwegian regions refer to 2012.
Note that a full time series is not available for all regions: special care should therefore be taken when analysing maps that show developments over time; footnotes are provided specifying any deviations from the standard coverage.
Gross domestic product (GDP)
GDP is a basic measure of a country’s overall economic health. It is an aggregate measure of production, equal to the sum of the gross value added of all resident institutional units engaged in production, plus any taxes, and minus any subsidies, on products not included in the value of their outputs. Gross value added is the difference between output and intermediate consumption.
GDP per person employed is intended to give an overall impression of the competitiveness and the productivity of a national / regional economy. It depends, to some degree, on the structure of total employment and may, for instance, be lowered by a shift from full-time to part-time work.
Gross value added
Gross value added at basic prices is a balancing item of the national accounts’ production account, defined as output at basic prices minus intermediate consumption at purchaser prices. The basic price is the amount receivable by the producer from the purchaser for a unit of a product minus any tax on the product plus any subsidy on the product.
Gross value added can be broken down by activity: the sum of gross value added at basic prices over all activities plus taxes on products minus subsidies on products gives GDP. At the most aggregated level of analysis 10 NACE Rev. 2 headings are identified, although for the purpose of this article these have been aggregated somewhat into the following headings:
- agriculture, hunting, forestry and fishing (NACE Section A);
- industry (NACE Sections B–E);
- construction (NACE Section F);
- distributive trades, transport, accommodation and food services; information and communication services; financial and insurance services; real estate activities; professional, scientific, technical, administrative and support services (NACE Sections G–N), referred to in this article as market services;
- public administration, defence, education, human health and social work; arts, entertainment, recreation, other services and activities of household and extra-territorial organisations and bodies (NACE Sections O–U), referred to in this article as public administration and other services.
Measuring economic development
Economic development is commonly expressed in terms of GDP, which in the regional context may be used to measure macroeconomic activity and growth, as well as providing the basis for comparisons between regions. GDP is also an important indicator from the policy perspective, as it is crucial in determining the extent to which each EU Member State should contribute to the EU’s budget and three-year averages of GDP are used to decide which regions should be eligible to receive support from the EU’s structural funds.
GDP per capita is often regarded as a proxy indicator for overall living standards. However, as a single source of information it should not be relied upon to inform policy debates, as it does not take account of externalities such as environmental sustainability or social inclusion, which are increasingly considered as important drivers for the quality of life.
A number of international initiatives have focused on this issue and in August 2009, the European Commission adopted a communication titled GDP and beyond: measuring progress in a changing world (COM(2009) 433 final), which outlined a range of actions to improve and complement GDP measures. This noted that there was a clear case for complementing GDP with statistics covering other economic, social and environmental issues, on which individuals’ well-being critically depends. Recent developments on these complementary indicators are detailed in a staff working paper called Progress on ‘GDP and beyond’ actions (SWD(2013) 303 final), in which public interest in broader measures of GDP is confirmed, including at regional and local levels. For more information on the quality of life, see this article.
Regional inequalities can be due to many factors, including: geographic remoteness or sparse population, social and economic change, or the legacy of former economic systems. These inequalities may manifest themselves, among others, in the form of social deprivation, poor-quality healthcare or education, higher levels of unemployment, or inadequate infrastructure.
The EU’s regional policy aims to support the broader Europe 2020 agenda. It is designed to foster solidarity and cohesion, such that each region may achieve its full potential, improving competitiveness and employment, and bringing living standards in ‘poorer’ regions up to the EU average as quickly as possible.
More than one third of the EU’s budget is devoted to cohesion policy, which aims to remove economic, social and territorial disparities across the EU, for example, by helping restructure declining industrial areas or diversify rural areas. In doing so, EU regional policy seeks to make regions more competitive, foster economic growth and create new jobs. The EU’s regional policy is an investment policy supporting job creation, competitiveness, economic growth, improved quality of life and sustainable development.
For the period 2014–20, the EU’s cohesion policy has been refocused with the objective of having maximum impact on growth and jobs. During this period, a total of EUR 351 billion will be invested in the EU’s regions. Investment will continue across all regions, but policy reforms have been adopted changing the levels of support according to the following classification:
- less developed regions (GDP < 75 % of the EU-27 average);
- transition regions (GDP 75 % – 90 % of the EU-27 average); and,
- more developed regions (GDP > 90 % of EU-27 average).
The EU’s regional policy seeks to help every region achieve its full potential, through improving competitiveness and raising the living standards of the poorest regions towards the EU average (convergence). Regional economic policy seeks to stimulate investment in the regions by improving accessibility, providing quality services and preserving the environment, thereby encouraging innovation and entrepreneurship and the creation of jobs, while overcoming inequalities that may be manifest in social deprivation, poor housing, education and healthcare, higher unemployment or inadequate infrastructure provisions.
Boosting jobs, growth and investment
In 2014, the European Commission set its top priority as ‘boosting jobs, growth and investment’. This is a major new initiative that will unlock public and private investment by targeting infrastructure developments, such as broadband internet, energy networks and transport. In its Communication titled ‘An investment plan for Europe’ (COM(2014) 0903 final), the European Commission underlined the role that Member States and regional authorities should play to get the maximum impact from EU structural funds by capitalising on a variety of financial instruments in the form of loans, equity and guarantees.
- Economy and finance statistics introduced
- European sector accounts - background (background article)
- European system of national and regional accounts - ESA 2010 (background article)
- GDP per capita, consumption per capita and price level indices
- National accounts and GDP
Further Eurostat information
- Eurostat regional yearbook 2014 — Chapter 5
- Eurostat regional yearbook 2013 — Chapter 1
- Eurostat regional yearbook 2012 — Chapter 1
- Eurostat regional yearbook 2011 — Chapter 7
- Regional economic accounts — ESA2010 (reg_eco10)
Methodology / Metadata
- Gross domestic product (GDP) at current market prices by NUTS 2 regions (ESMS metadata file — nama_r_e2gdp_esms)
Source data for figures and maps (MS Excel)