GDP at regional level
- Data extracted in March 2016. Most recent data: Further Eurostat information, Main tables and Database. Planned article update: June 2017.
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 brief analysis of labour productivity (defined here as gross value added per person employed); while, the article closes with a regional analysis of private household income and disposable income.
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 level 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; a mid-term review of cohesion policy allocations is taking place during the course of 2016 and will likely result in some changes to the system — 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 14.0 trillion in 2014, which equated to an average level of approximately 27.5 thousand purchasing power standards (PPS) per capita.
Regional GDP per capita
Map 1 shows GDP per capita in 2014 for NUTS level 2 regions, with the value for each region first calculated in purchasing power standards (PPS) and then expressed as a percentage of the EU-28 average (set to equal 100 %). As such, it portrays relatively ‘rich’ regions (shown in blue) where GDP per capita was above the EU-28 average and relatively ‘poor’ regions (shown in purple); the use of PPSs makes it possible to compare purchasing power across the regions of EU Member States that use different currencies and where price levels are different. The map reveals a clear east–west divide. However, this pattern is less pronounced than it was just over a decade ago— 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.
Indeed, many regions in eastern parts of the EU, especially capital city 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 financial and economic crisis resulted in GDP per capita in 2014 being below the EU-28 average in several NUTS 2 regions where it had previously (in 2008) been above it: this was the case in four British regions, three Dutch regions, two regions in each of Greece, Italy and Finland, and one region each in Spain, Cyprus (which is one region at this level of detail), Slovenia and Sweden. By contrast, three regions in Germany and one each in France and Poland moved from below the EU-28 average in 2008 to above it by 2014.
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 or regions. 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 Bulgaria or Romania).
The highest level of GDP per capita in the EU was recorded in Inner London - West
There were five regions where GDP per capita in 2014 was more than double the EU-28 average, namely: Inner London - West, Luxembourg (a single region at this level of analysis), the Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest, Hamburg and Inner London - East. All five of these regions with the highest levels of GDP per capita in 2014 were characterised by considerable commuter inflows: for example, many people travel large distances into central London each day for work, while the Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest is relatively small in size (covering just over 160 km²) and also attracts a considerable number of commuters from its surrounding regions. While the highest absolute numbers were usually recorded for national flows of commuters into regions containing some of Europe’s largest cities, it is also interesting to note that in some regions there was a relatively high share of international commuters. For example, a high proportion of those who work in Luxembourg travel across national borders coming to work from neighbouring Belgium, Germany and France.
For more information: please refer to an article on commuting patterns.
Measuring wealth and income by place of residence or place of work?
Average GDP per capita does not 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 regions 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.
In 2014, approximately 15 % of the 276 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 blue. Many of them were capital city regions or a cluster of regions that neighboured capital city regions, while the vast majority of the others were grouped together in the centre of the map, covering western and southern Germany, western Austria and northern Italy, as well as Switzerland. The remaining regions were the Finnish island region of Åland and two regions associated with North Sea oil and gas production, namely Groningen in the Netherlands and North Eastern Scotland in the United Kingdom. Despite having the largest number of regions with GDP per capita at least 25 % higher than the EU-28 average, the German capital city region — Berlin — was not among them.
Nearly all of the 21 regions in the EU where GDP per capita was less than half the EU-28 average were 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 shade of purple in Map 1. There were 78 NUTS level 2 regions which fell into this category in 2014. 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.
More than a quarter (21 regions) of the 78 regions with relatively low levels of GDP per capita had a level of economic output per capita that was less than half the EU-28 average. Among these 21 regions, 19 were 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 two remaining regions were the French overseas region of Mayotte and the Greek region of Anatoliki Makedonia, Thraki. The two Bulgarian regions of Severozapaden and Yuzhen tsentralen and the French island region of Mayotte reported the lowest levels of 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.
In Inner London - West, GDP per capita was 18 times as high as in Severozapaden
In 2014, average GDP per capita for Inner London - West (539 % of the EU-28 average) was 18 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).
GDP per capita was higher than the EU-28 average in every region of Norway
In all of the multi-regional EU Member States there was at least one NUTS level 2 region that had an average level of GDP per capita that was below the EU-28 average in 2014, although this was not the case for the level 2 regions in Norway, as all seven recorded values above the EU-28 average. GDP per capita was above the EU-28 average in only one of the EU Member States that are single regions at this level of analysis, namely Luxembourg; this was also the case in Iceland as well as in Switzerland (for which only national data are available).
In the Czech Republic, Ireland, Hungary, Poland, Portugal, Romania and Slovakia the capital city region was the only region where GDP per capita was above the EU-28 average. Bulgaria, Greece, Croatia and Slovenia were the only multi-regional EU Member States where all NUTS level 2 regions had average GDP per capita below the EU-28 average. GDP per capita was also below the EU-28 average in the five other 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 as well as in Albania and Serbia (only national data are available for both of these countries).
Capital city regions were generally those with the highest average GDP per capita within most Member States
Figure 1 presents an alternative analysis of the regional distribution of GDP per capita in 2014. It shows that in a majority of the multi-regional EU Member States, capital city 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, the highest average GDP per capita was recorded in Hamburg, while Berlin was the only capital city region that recorded GDP per capita below its national average. The Italian capital city 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 region to record average GDP per capita that was higher than in the capital city region of Noord-Holland.
The capital city regions of Bulgaria, the Czech Republic, Denmark, Ireland, France, Croatia, Portugal, Slovenia, Slovakia and Sweden were the only regions from each of these EU Member States where GDP per capita was higher than the national average in 2014.
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 - West was almost eight times as high as in West Wales and the Valleys. There were also considerable differences in levels of GDP per capita between the regions of France, Romania and Slovakia. By contrast, wealth creation was relatively evenly spread across Croatia, Slovenia, the Nordic Member States, Portugal, Ireland, the Netherlands, Austria, Spain and Greece. In each of these EU Member States, average GDP per capita in the region with the highest value was never more than double that recorded in the region with the lowest value; this was also the case in Norway.
Analysis of regional economic development over time
During the financial and economic crisis, GDP per capita in the EU-28 peaked in 2008 at 26.0 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 2013 when an average of 26.7 thousand PPS of GDP was generated per capita, before accelerating again in 2014 to 27.5 thousand PPS per capita.
GDP per capita increased at a rapid pace in several Polish, German and Austrian regions, Lithuania and Luxembourg
Map 2 shows the effects of the financial and economic crisis, detailing regional performance for NUTS level 2 regions between 2008 and 2014. Those regions that expanded at a fast pace — as shown by the darkest shade of blue — were principally located in Poland (7 of its 16 regions), Austria (three of its nine regions), Germany (12 of its 38 regions), Lithuania and Luxembourg (both single regions at this level of detail), while — as a percentage of the EU-28 average — GDP per capita also increased by more than 10.0 percentage points in Nyugat-Dunántúl (Hungary), Sud-Est (Romania), Bratislavský kraj (Slovakia), and Inner London - East.
SPOTLIGHT ON THE REGIONS
The fastest growing region, as measured by the change in GDP per inhabitant during the period 2008–14, was Mazowieckie (the Polish capital city region). It also recorded the highest increase among NUTS level 2 regions for disposable income per inhabitant between 2008 and 2013.
The most rapid economic growth relative to the EU-28 average during the period 2008–14 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 17.1 % below the EU-28 average in 2008, but rose to be 8.4 % higher than the EU-28 average by 2014.
At the other end of the range, a total of 38 regions recorded a fall of at least 10.0 percentage points between 2008 and 2014 in their GDP per capita relative to the EU-28 average, (as shown by the darkest shade of purple in Map 2). The impact of the financial and economic crisis on the Greek and Spanish economies was widespread, as 12 of these regions were Greek and 14 Spanish; Cyprus (a single region at this level of analysis) was also in this group of regions, as were seven mainly northern Italian regions, two Dutch regions and one region each from Finland (the capital city region) and the United Kingdom (Bedfordshire and Hertfordshire). The most rapid economic decline relative to the EU-28 average during the period 2008–14 across NUTS level 2 regions of the EU was recorded in three Greek regions (Attiki, Notio Aigaio and Ionia Nisia), where GDP per capita fell by more than 26.0 percentage points relative to the EU-28 average. For example, in the capital city region of Attiki, it fell from 25.4 % above the EU-28 average to 1.2 % below it.
National economic fortunes appear to play a significant role in determining regional economic performance, with widespread growth in several eastern Member States
It can be noted 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 2014. Among the multi-regional EU Member States, GDP per capita grew at a faster pace than the EU-28 average in every region of Bulgaria, Hungary, Poland, Romania and Slovakia, as well as every region except for the capital city region in Belgium, the Czech Republic and Austria, and every region except for one (not the capital city region) in Denmark and Germany. By contrast, every region in Greece, Spain, Croatia, Italy, the Netherlands, Slovenia, Finland (with the exception of Åland) and Sweden 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). In Ireland, one region grew faster than the EU-28 average and one slower, while only in France, Portugal and the United Kingdom was the situation more mixed, with a majority of regions growing slower than the EU-28 average.
Within regional accounts, labour productivity is defined as gross value added in euros at basic prices per person employed; Map 3 presents this indicator for NUTS level 2 regions in 2014 with the results shown as a percentage of 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.
SPOTLIGHT ON THE REGIONS
In 2014, Luxembourg had the highest level of gross value added per person employed among NUTS level 2 regions in the EU, its labour productivity was twice as high as the EU-28 average. Luxembourg also recorded the second highest level of GDP per inhabitant (behind Inner London - West). Note that GDP per capita does not necessarily provide a clear indication as to the income that is ultimately available for private households, 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).
©: nicrob 77
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 2014 was recorded in Luxembourg which had one of the highest levels of GDP per capita; note that data for London are not available.
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 Luxembourg 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 three regions with the highest levels of labour productivity. The remainder of the top 10 was constituted by three Belgian regions (the capital city region and its neighbouring regions), the Danish, French and Swedish capital city regions, as well as two regions associated with North Sea oil and gas production (which were already noted as having high GDP per capita), namely Groningen and North Eastern Scotland.
Labour productivity lower in those EU 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 2014.
There were 64 NUTS level 2 regions where gross value added per person employed was less than three quarters the EU-28 average in 2014 (as shown by the darkest shade of purple in Map 3). Among these, there were 46 regions where this ratio was less than half the EU-28 average: they were spread across two of the Baltic Member States (Latvia and Lithuania, each one region at this level of detail) and eastern regions of the EU, with low labour productivity ratios in every region of Bulgaria, Croatia and Hungary, all but two of the regions in the Czech Republic and in Poland, all but one of the regions in Romania, and one region in Slovakia. The only southern region with labour productivity below half the EU-28 average in 2014 was Norte in Portugal.
Primary household income
In recent years there has been growing discussion over the quality of life in Europe, with many people of the opinion that their overall standard of living has deteriorated since the onset of the financial and economic crisis, in particular as a result of falling real wages, increased unemployment, additional burdens of taxes or social charges, lower levels of benefits, or rising prices.
Map 4 provides an overview of primary income per inhabitant in NUTS level 2 regions for 26 of the EU Member States: there are no data available for Luxembourg or Malta. Data are presented in purchasing power consumption standards (PPCS) which adjust for price differences between regions. In 2013, primary income ranged from a high of 51.2 thousand PPCS per inhabitant in Inner London - West down to 4.8 thousand PPCS in Severozapaden, a factor of 10.6 to 1; as such, the highest and lowest values were recorded in the same regions that reported the highest and lowest levels of GDP per capita.
High levels of primary income in many German regions and more generally in and around capital cities
There were 52 regions which recorded primary income per inhabitant that was at least 22.5 thousand PPCS in 2013. The majority (27) of these regions were located in Germany, including the second, third and fourth highest figures which were recorded in Oberbayern, Stuttgart and Hamburg. Aside from Inner London - West, there were seven other British regions, mainly in the south-east of England with one region in Scotland (North Eastern Scotland). Other EU Member States with multiple regions in this group were Austria (five regions) Belgium (four regions, clustered around but not including the capital city region), Italy, the Netherlands and Finland (two regions each), while there was one French and one Swedish region. As with the information already shown for GDP per capita, one of the most striking features of Map 4 is the relatively high level of primary income per inhabitant that is registered in regions either containing or surrounding capital cities.
At the other end of the range, there were 36 NUTS level 2 regions that reported primary income per inhabitant that was less than 10 thousand PPCS. These regions were mainly located in Latvia (one region at this level of detail), Greece and eastern EU Member States, specifically Bulgaria (all six regions), Croatia (both regions), Hungary (six of seven regions), Romania (six of eight regions), Poland (8 of 16 regions) and Slovakia (one of four regions); in addition there was one French region.
Figure 2 and Map 5 present information on disposable incomes of private households, in other words, ‘in-pocket’ income that people can spend or save (once they have paid their taxes and social security contributions and after they have received their social benefits). The highest disposable income per inhabitant in 2013 was recorded in Inner London - West, at 37.9 thousand PPCS; note that no data are available for Luxembourg or Malta. The other 9 regions in the top 10 were all located in Germany, the highest level of disposable income being recorded in the Bavarian region of Oberbayern (which includes München).
The highest level of disposable income per inhabitant in Inner London - West was 7.7 times as high as that in the French overseas region of Mayotte (4.9 thousand PPCS); as such, when compared with the same ratio for primary income (10.6 to 1), the range between highest and lowest region narrowed considerably. Indeed, the disposable income per inhabitant of most regions is generally lower than the corresponding figure for primary income per inhabitant as a result of state intervention (redistribution). This is particularly true in regions which are characterised as having some of the highest earners (often capital city regions), as tax and social security contributions usually increase as a function of income.
Figure 2 shows that capital city regions often accounted for the highest levels of disposable income, although this pattern was less apparent among a few of the EU Member States with the highest levels of disposable income: in Belgium, Germany and Austria, disposable income per inhabitant for the capital city region was below the national average. The capital city regions of Spain, Italy, Hungary and Finland recorded disposable income per inhabitant that was above their respective national averages, although there was at least one other region in each of these EU Member States which recorded a higher level of disposable income per inhabitant.
Other than in capital city regions, there was a relatively uniform distribution to disposable income across the regions of most EU Member States
Aside from capital city regions, the distribution of disposable income per inhabitant was often within a relatively narrow range across the remaining regions in most of the EU Member State. This was particularly true in Denmark, Sweden and Austria, which displayed quite uniform distributions. By contrast, and again excluding capital city regions, the largest variations in disposable income per inhabitant across regions of the same EU Member State were recorded in Italy, France and Spain; in France this was in large part due to relatively low values for some of its overseas regions, while in Italy and Spain the differences reflected north–south divides (with higher levels of disposable income in northern regions).
Although most NUTS level 2 regions reported that disposable income per inhabitant was lower than primary income per inhabitant, there were 46 regions which benefitted from social benefits and other transfers to such a degree that their disposable income per inhabitant was higher than their primary income. Such a situation occurred in 10 of the 13 Greek regions, all six Bulgarian regions, five of the eight Romanian regions, five of the seven Portuguese regions, four of the seven Hungarian regions, three regions each from Spain, Italy and the United Kingdom, two regions from Poland and one region each from Germany, France, Croatia and Slovakia, as well as in Cyprus (which is one region at this level of detail).
Highest gains in disposable income were recorded in many regions of Germany, Poland and Romania
Map 5 shows the change in disposable income per inhabitant across NUTS level 2 regions between 2008 and 2013; note that the data for Spain refer to the change between 2010 and 2013 and that there is no information available for Croatia, Luxembourg and Malta. The most visible pattern in the map is the relatively high gains made in disposable incomes across Germany, Poland and Romania during the period under consideration. The highest increases in disposable income across any of the NUTS level 2 regions for which data are available were recorded for the Polish capital city region of Mazowieckie and the Romanian region of Vest. Polish and Romanian regions, along with the Slovakian capital city region, filled all of the top 10 places.
Disposable income fell by more than one thousand PPCS in all Greek regions
The biggest contractions in disposable income were felt in some of the EU Member States most affected by the financial and economic crisis. There were 38 regions across the EU-28 where disposable income per inhabitant fell by more than one thousand PPCS between 2008 and 2013 (as shown by the darkest shade of purple in Map 5). All 13 Greek regions were among this group and the nine regions with the largest falls across the whole of the EU-28 were all Greek, with the single largest reduction in the Greek capital city region (Attiki). Elsewhere, this group of 38 regions was otherwise composed of 11 regions from Italy, 10 from the United Kingdom and both Irish regions, as well as one of the two Slovenian regions and Cyprus( which is one region at this level of detail).
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.
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).
Further information on the transition from ESA 95 to ESA 2010 is presented on Eurostat’s website.
The data presented in this article are based exclusively on the 2013 version of NUTS.
Statistics from regional economic accounts are largely shown for NUTS level 2 regions. Data for Switzerland, Albania and Serbia are only available at a national level. The latest statistics available for Norwegian regions refer to 2013, although 2014 national data are available.
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) 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 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 analysed by activity: the sum of gross value added at basic prices over all activities plus taxes on products minus subsidies on products gives GDP.
The primary income of private households is that generated directly from market transactions. This generally includes income from paid work and self-employment, as well as income received in the form of interest, dividends and rents; interest and rents payable are recorded as negative items.
Disposable income is derived from primary income by adding all social benefits and monetary transfers (from state redistribution) and subtracting taxes on income and wealth as well as social contributions and similar transfers; as such, it reflects ‘in-pocket’ income.
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: see an article on the quality of life from the Eurostat regional yearbook — 2015 edition.
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 housing, 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 aims to 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) 903 final), the European Commission underlined the role that EU Member States and regional authorities should play to get the maximum impact from structural funds by capitalising on a variety of financial instruments in the form of loans, equity and guarantees. In January 2015, the European Commission adopted a Communication on making the best use of the flexibility within the existing rules of the stability and growth pact (COM(2015) 12 final). This Communication aims to strengthen the link between investment, structural reforms and fiscal responsibility.
- 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
- Regional economic accounts — ESA2010 (t_nama_reg)
- 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)
- Household accounts - ESA95 (ESMS metadata file — reg_ecohh_esms)
Source data for figures and maps (MS Excel)