Welcome To Statistics Explained
Statistics Explained, your guide to European statistics. Statistics Explained is an official Eurostat website presenting statistical topics in an easily understandable way. Together, the articles make up an encyclopedia of European statistics for everyone, completed by a statistical glossary clarifying all terms used and by numerous links to further information and the latest data and metadata, a portal for occasional and regular users.
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- Unemployment statistics
- Migration and migrant population statistics
- Asylum statistics
- Wages and labour costs
- Energy price statistics
- National accounts and GDP
- Population structure and ageing
- Minimum wage statistics
- GDP per capita, consumption per capita and price level indices
- Electricity and natural gas price statistics
Moreover, the development of specific GDP components and related indicators, such as those for economic output, imports and exports, domestic (private and public) consumption or investments, as well as data on the distribution of income and savings, can give valuable insights into the main drivers of economic activity and thus be the basis for the design, monitoring and evaluation of specific EU policies.
Main statistical findings
Developments in GDP
Growth in the EU-28’s GDP (in current prices) slowed substantially in 2008 and GDP contracted considerably in 2009 as a result of the global financial and economic crisis. There was a recovery in the level of EU-28 GDP in 2010 and this development continued (albeit at a progressively slower pace) in 2011–13, before growth accelerated again in 2014, as current price GDP increased by 3.0 %. By 2014, GDP in the EU-28 had reached EUR 13.9 trillion (EUR 13 900 billion), some 6.2 % more than in the United States (see Figure 1).
The euro area (EA-19) accounted for 72.6 % of the EU-28 GDP in 2014, down from 75.8 % in 2009. In 2014, the sum of the five largest EU Member State economies (Germany, the United Kingdom, France, Italy and Spain) was 71.4 %. Note that cross-country comparisons should be made with caution as notably exchange rate fluctuations may significantly influence the development of nominal GDP figures when converted into a common currency.
To evaluate standards of living, it is more appropriate to use GDP per capita in purchasing power standards (PPS), in other words, adjusted for the size of an economy in terms of population and also for differences in price levels across countries. The average GDP per capita within the EU-28 in 2013 was PPS 26.6 thousand, somewhat above the peak (PPS 25.9 thousand) reached in 2008 prior to the effects of the financial and economic crisis being felt. The relative position of individual countries can be expressed through a comparison with this average, with the EU-28 value set to equal 100. The highest value among the EU Member States was recorded for Luxembourg, where GDP per capita in PPS was more than 2.6 times the EU-28 average in 2013 (which is partly explained by the importance of cross-border workers from Belgium, France and Germany). On the other hand, GDP per capita in PPS was less than half the EU-28 average in Bulgaria in 2013.
Although PPS figures should, in principle, be used for cross-country comparisons in a single year rather than over time, the development of these figures during the past decade suggests that some convergence in living standards took place as most Member States that joined the EU in 2004, 2007 or 2013 moved closer to the EU average despite some setbacks during the financial and economic crisis. Whereas Luxembourg, Germany and Austria moved further ahead of the EU-28 average, comparing the situation in 2013 with that in 2003, several other EU-15 Member States, notably the United Kingdom, Ireland, France and Belgium, moved closer to the EU-28 average (see Figure 2); during the same period while Italy and Spain moved from above or level with the EU-28 average to a position below it. From a position below the EU-28 average in 2003, Lithuania, Romania, Estonia, Slovakia, Latvia, Poland and Bulgaria made the greatest moves towards the EU-28 average by 2013, while Greece fell further below the EU-28 average, as did Cyprus and Slovenia to a much lesser extent.
The global financial and economic crisis resulted in a severe recession in the EU and the United States in 2009 (see Figure 3), followed by a recovery in 2010; the upcoming crisis was already apparent in 2008 when there had been a relatively small reduction in real GDP in the United States and a fall in the rate of increase in the EU-28. Real GDP fell by 4.4 % in the EU-28 in 2009, while there was a contraction of 2.8 % in the United States. The recovery in the EU-28 saw GDP in constant prices increase by 2.1 % in 2010 and this was followed by a further gain of 1.7 % in 2011; subsequently GDP contracted 0.5 % in 2012 and there was no change in 2013 before growth returned in 2014 (1.3 %). In the euro area (EA-19) the corresponding growth rates in 2010 and 2011 were similar to those in the EU-28, while the contraction in 2012 was stronger (-0.8 %) and was sustained into 2013 (-0.4 %), before weaker growth (0.9 %) than that in the EU-28 as a whole returned in 2014. In the United States, the recovery was slightly stronger than in the EU-28 in 2010 and comparable in 2011. Whereas the recovery stalled in the EU-28 in 2012, it continued in the United States, with growth above 2.0 % during the period 2012–14.
Within the EU, real GDP growth varied considerably, both over time and between Member States. After a contraction in all of the EU Member States except Poland in 2009, economic growth resumed in 22 Member States in 2010, a pattern that was continued in 2011 when real GDP growth was registered in 24 of the EU Member States. However, in 2012 this development was reversed, as just under half (13) of the Member States reported economic expansion, while in 2013 this number rose to 17 and in 2014 to 23 (among 27 for which data are available).
The highest growth rates in 2014 were recorded in Ireland (4.8 %), Hungary (3.6 %), Malta (3.5 %) and Poland (3.4 %). Growth in 2014 in Spain (1.4 %) was marginally above the EU-28 average (1.3 %) and this was the first annual growth in the Spanish economy since 2008. While GDP growth in 2014 in Portugal (0.9 %) and Greece (0.8 %) was below the EU-28 average, for Portugal this was the first annual growth since 2010 and for Greece the first since 2007. The Cypriot, Italian and Finnish economies contracted for the third consecutive year in 2014 while in Croatia the run of consecutive annual falls in real GDP extended to six years: in three of these four Member States the contraction in 2014 was relatively small, the exception being Cyprus where GDP fell 2.3 %.
The effects of the financial and economic crisis lowered the overall performance of the EU Member State economies when analysed over the whole of the last decade. The average annual growth rates of the EU-28 and the euro area (EA-19) between 2004 and 2014 were 0.9 % and 0.7 % respectively. The highest growth, by this measure, was recorded for Poland (average growth of 3.9 % per annum) and Slovakia (3.8 % per annum), followed by Romania (2.7 %), Bulgaria, Latvia and Malta (all 2.5 %). By contrast, the overall development of real GDP during the period from 2004 to 2014 in Greece, Italy and Portugal was negative.
Main GDP aggregates
Looking at GDP from the output side, Table 3 gives an overview of the relative importance of 10 activities in terms of their contribution to gross value added. Between 2003 and 2013, industry’s share of EU-28 value added fell 1.2 percentage points to 19.1 %, remaining just ahead of distributive trades, transport, accommodation and food services (19.0 %) which also recorded a fall in its share, down 0.7 percentage points during these 10 years. By contrast, public administration, education and health saw its share increase by 1.0 percentage points to reach 19.4 % in 2013, thereby moving from third position to become the largest activity (at this level of detail) in value added terms. The next largest activities in 2013 were real estate activities (11.2 %), followed by professional, scientific, technical, administrative and support services (hereafter, business services) (10.4 %), construction (5.7 %), financial and insurance services (5.5 %) and information and communication services (4.5 %). The smallest contributions came from entertainment and other services (3.6 %) and agriculture, forestry and fishing (1.7 %).
Services contributed 73.6 % of the EU-28’s total gross value added in 2013 compared with 71.5 % in 2003. The relative importance of services was particularly high in Luxembourg, Cyprus, Malta, Greece, France (2012 data), the United Kingdom, Belgium and Denmark where they accounted for more than three quarters of total value added.
Structural change is, at least in part, a result of phenomena such as technological change, developments in relative prices, outsourcing and globalisation, often resulting in manufacturing activities being moved to lower labour-cost regions, both within and outside the EU. Several activities were particularly affected by the financial and economic crisis and its aftermath. Industry experienced the sharpest contraction between 2007 and 2009, value added in the EU-28 falling overall by 12.6 % (in volume terms); EU-28 industrial output fell by a further 1.2 % between 2011 and 2013. Construction experienced the deepest and longest contraction, with its output falling by 18.4 % between 2007 and 2013, with output falling every year during this period: as such, the 0.7 % increase recorded for construction in 2014 was the first annual growth in seven years. Business services as well as distributive trades, transport, accommodation and food services also experienced relatively strong falls in value added in 2009, -7.1 % and -6.0 % respectively. Distributive trades, transport, accommodation and food services recorded two further, smaller contractions in output in 2012 and 2013. After relative stability in 2009, output from agriculture, forestry and fishing fell in 2010 by 3.1 % and again in 2012 by 4.2 %. Smaller reductions in value added were experienced for other activities during the crisis, most notably in 2009, 2010 and 2013 for financial and insurance services and for arts, entertainment, recreation and other services (see Figure 4). Two of the activities presented in Figures 4 and 5 did not record an annual fall in value added in any year during the crisis: real estate activities; public administration, defence, education, human health and social work activities.
In 2014, all activities reported growth compared with 2013. The activities with the strongest growth were agriculture, forestry and fishing (2.8 %), business services (2.5 %), and distributive trades, transport, accommodation and food services (2.1 %), while growth of just 0.1 % was recorded for financial and insurance activities.
An analysis of labour productivity per person employed over the 10-year period from 2004 to 2014 shows increases (in current prices) for all activities, ranging from 16.9 % for distributive trades, transport, accommodation and food services to 30.9 % for industry, with information and communication services (3.0 %) and business services (8.4 %) lying below this range (see Figure 6).
To eliminate the effects of inflation, labour productivity per person can also be calculated using constant price output figures. Data on the development of productivity measured either per person employed or per hour worked is shown in Table 4. Labour productivity per person employed increased, in real terms, between 2004 and 2014 in nearly all EU Member States, with just Greece, Italy and Luxembourg (2004 to 2012) recording falls; Croatia also recorded a fall but this may, at least in part, be related to a break in series. Over the same period, 2004 to 2014, labour productivity per hour worked increased in all EU Member States except for Greece and Italy. Leaving aside those Member States with a break in series, the largest increases in both of the real labour productivity measures shown in Table 4 were recorded in Bulgaria, Estonia, Lithuania and Slovakia.
Consumption and investment
Turning to an analysis of the development of GDP components from the expenditure side, it can be noted that final consumption expenditure across the EU-28 rose by 9.0 % in volume terms between 2004 and 2014 (see Figure 7), despite slight falls in 2009 and 2012. Final consumption expenditure of general government rose at a somewhat faster pace, up 13.0 % between 2004 and 2014. During the same period, gross capital formation decreased by 1.8 %, due, in large part, to sharp falls in 2009 and 2012 and 2013 while the growth in exports substantially exceeded the growth in imports in recent years.
After its fall in 2009, consumption expenditure by households and non-profit institutions serving households recovered in 2010 (up 0.8 % in volume terms) and increased further in 2011 (0.3 %), before falling again in 2012 (-0.7 %) and 2013 (-0.1 %); in 2014 this expenditure increased by 1.3 %, the largest annual increase in real terms since 2007. In 2010, the pace of growth for EU-28 general government expenditure slowed in volume terms and this rate of change remained relatively stable (within the range of 0.3 % to -0.2 %) between 2011 and 2013, before returning to somewhat stronger growth (1.0 %) in 2014. Despite an increase in 2011 (2.0 %), EU-28 gross fixed capital formation failed to fully recover from its sharp fall in 2009 (-11.9 %) and returned to a negative rate of change in 2012 and 2013; in 2014 gross fixed capital formation increased 2.3 % in real terms, the largest increase since 2007.
In current price terms, consumption expenditure by households and non-profit institutions serving households contributed 56.9 % of the EU-28’s GDP in 2014, while the share of general government expenditure was 20.9 % and that of gross capital formation was 19.3 % (see Figure 9).
Among the EU Member States, there was a wide variation in the overall investment intensity and this may, in part, reflect different stages of economic development as well as growth dynamics over recent years (see Figure 10). In 2014, gross fixed capital formation as a share of GDP was 19.3 % in the EU-28 and 19.5 % in the euro area (EA-19). It was highest in Estonia (25.8 %), the Czech Republic (25.3 %), Belgium, Sweden (both 23.1 %) and Latvia (23.0 %) and lowest in Cyprus (10.8 %) and Greece (11.6 %).
The vast majority of investment was made by the private sector, as can be seen from Table 5: in 2013, investment by businesses and households accounted for 16.7 % of the EU-28’s GDP, whereas the equivalent figure for public sector investment was 3.0 %. In relative terms, Estonia had the highest public investment (5.5 % of GDP) and investment by the business sector (17.8 %), while investment by households was highest in Finland (6.4 %). Investment by households (as a share of GDP) in 2013 was notably lower than in 2003 in Ireland, Spain and Cyprus, while it was notably higher in Romania (comparing 2012 with 2003). A similar comparison shows a relatively large fall in Estonia, Slovenia and Slovakia for business investment.
An analysis of GDP within the EU-28 from the income side shows that the distribution between the production factors of income resulting from the production process was dominated by the compensation of employees, which accounted for 47.9 % of GDP in 2014. The share of gross operating surplus and mixed income was 40.2 % of GDP, while that for taxes on production and imports less subsidies was 11.9 % (see Figure 11). Romania had the lowest share of the compensation of employees in GDP (31.3 %), followed by Greece (33.4 %), while shares of 50.0 % or higher were recorded in seven EU Member States, peaking at 53.1 % in Denmark.
Figure 12 (which is based on current prices) shows that the income aggregates had, by 2011 or 2012, recovered from their losses experienced during the financial and economic crisis. In 2009, compensation of employees fell by 2.9 %, but by 2014 was 8.5 % higher than its corresponding level recorded in 2008. For the gross operating surplus and mixed income, there was already stagnation in 2008, followed by a fall of 7.9 % in 2009; by 2011 this income aggregate had returned to a level above its pre-crisis peak (in 2008) and by 2014 was 4.1 % above that peak level. The fall in taxes on production and imports less subsidies had already started in 2008 (-3.1 %) and accelerated in 2009 (-9.3 %); by 2011 these losses had been recovered and in 2014 this income aggregate stood 9.7 % above its previous peak (2007).
The consumption expenditure of households accounted for at least half of GDP in the majority of EU Member States in 2014; this share was highest in Greece (69.5 %), Cyprus (68.7 %), Portugal (64.0 %) and Lithuania (63.7 %). By contrast, it was lowest in Luxembourg (29.6 %, 2013 data) which had, nevertheless, by far the highest average household consumption expenditure per capita (EUR 24.6 thousand) — see Table 6. In 2014, average household consumption expenditure per capita in Finland was EUR 5.3 thousand higher than 10 years earlier; the smallest increases over the same period were recorded for Greece, Ireland and Hungary.
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. It is fully consistent with worldwide guidelines for national accounts, the 2008 SNA.
GDP and main components
The main aggregates of national accounts are compiled from institutional units, namely non-financial or financial corporations, general government, households, and non-profit institutions serving households (NPISH).
Data within the national accounts domain encompasses information on GDP components, employment, final consumption aggregates and savings. Many of these variables are calculated on an annual and on a quarterly basis.
GDP is the central measure of national accounts, which summarises 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.
An analysis of GDP per capita removes the influence of the absolute size of the population, making comparisons between different countries easier. GDP per capita is a broad economic indicator of living standards. GDP data in national currencies can be converted into purchasing power standards (PPS) using purchasing power parities (PPPs) that reflect the purchasing power of each currency, rather than using market exchange rates; in this way differences in price levels between countries are eliminated. The volume index of GDP per capita in PPS is expressed in relation to the EU-28 average (set to equal 100). If the index of a country is higher / lower than 100, this country’s level of GDP per head is above / below the EU-28 average; this index is intended for cross-country comparisons rather than temporal comparisons.
The calculation of the annual growth rate of GDP at constant prices, in other words the change of GDP in volume terms, is intended to allow comparisons of the dynamics of economic development both over time and between economies of different sizes, irrespective of price levels.
Economic output can also be analysed by activity: at the most aggregated level of analysis 10 NACE Rev. 2 headings are identified: agriculture, hunting, forestry and fishing; industry; construction; 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; public administration, defence, education, human health and social work; arts, entertainment, recreation, other services and activities of household and extra-territorial organisations and bodies. An analysis of output by activity over time can be facilitated by using a volume measure — in other words, by deflating the value of output to remove the impact of price changes; each activity is deflated individually to reflect the changes in the prices of its associated products.
A further set of national accounts data is used within the context of competitiveness analyses, namely indicators relating to the productivity of the workforce, such as labour productivity measures. Productivity measures expressed in PPS are particularly useful for cross-country comparisons. GDP per person employed is intended to give an overall impression of the productivity of national economies. It should be kept in mind, though, that this measure depends on the structure of total employment and may, for instance, be lowered by a shift from full-time to part-time work. GDP per hour worked gives a clearer picture of productivity as the incidence of part-time employment varies greatly between countries and activities.
Annual information on household expenditure is available from national accounts compiled through a macroeconomic approach. An alternative source for analysing household expenditure is the Household budget survey (HBS): this information is obtained by asking households to keep a diary of their purchases and is much more detailed in its coverage of goods and services as well as the types of socioeconomic analysis that are made available. HBS is only carried out and published every five years — the latest reference year currently available is 2010.
European institutions, governments, central banks as well as other economic and social bodies in the public and private sectors need a set of comparable and reliable statistics on which to base their decisions. National accounts can be used for various types of analysis and evaluation. The use of internationally accepted concepts and definitions permits an analysis of different economies, such as the interdependencies between the economies of the EU Member States, or a comparison between the EU and non-member countries.
Business cycle and macroeconomic policy analysis
One of the main uses of national accounts data relates to the need to support European economic policy decisions and the achievement of economic and monetary union (EMU) objectives with high-quality short-term statistics that allow the monitoring of macroeconomic developments and the derivation of macroeconomic policy advice. For instance, one of the most basic and long-standing uses of national accounts is to quantify the rate of growth of an economy, in simple terms the growth of GDP. Core national accounts figures are notably used to develop and monitor macroeconomic policies, while detailed national accounts data can also be used to develop sectoral or industrial policies, particularly through an analysis of input-output tables.
Since the beginning of the EMU in 1999, the European Central Bank (ECB) has been one of the main users of national accounts. The ECB’s strategy for assessing the risks to price stability is based on two analytical perspectives, referred to as the ‘two pillars’: economic analysis and monetary analysis. A large number of monetary and financial indicators are thus evaluated in relation to other relevant data that allow the combination of monetary, financial and economic analysis, for example, key national accounts aggregates. In this way monetary and financial indicators can be analysed within the context of the rest of the economy.
The Directorate-General for Economic and Financial Affairs monitors economic developments and produces two key annual economic reports that help to identify economic problems: an annual growth survey and an alert mechanism report. The former analyses the progress that the EU has made towards its long-term, strategic priorities, and provides an assessment of employment and macroeconomic developments, setting priorities for the year to come, while the latter identifies EU Member States that may be experiencing imbalances, such as declining competitiveness or asset bubbles. The Directorate-General for Economic and Financial Affairs also produces the European Commission’s macroeconomic forecasts twice a year, in the spring and autumn. These forecasts cover all EU Member States in order to derive forecasts for the euro area and the EU, but they also include outlooks for candidate countries, as well as some non-member countries.
The analysis of public finances through national accounts is another well-established use of these statistics. Within the EU a specific application was developed in relation to the convergence criteria for EMU, two of which refer directly to public finances. These criteria have been defined in terms of national accounts figures, namely, government deficit and government debt relative to GDP. See the article on government finance statistics for more information.
Regional, structural and sectoral policies
As well as business cycle and macroeconomic policy analysis, there are other policy-related uses of European national and regional accounts data, notably concerning regional, structural and sectoral issues.
The allocation of expenditure for the structural funds is partly based on regional accounts. Furthermore, regional statistics are used for ex-post assessment of the results of regional and cohesion policy.
Encouraging more growth and more jobs is a strategic priority for both the EU and the Member States, and is part of the Europe 2020 strategy. In support of these strategic priorities, common policies are implemented across all sectors of the EU economy while the Member States implement their own national structural reforms.
The European Commission conducts economic analysis contributing to the development of the common agricultural policy (CAP) by analysing the efficiency of its various support mechanisms and developing a long-term perspective. This includes research, analysis and impact assessments on topics related to agriculture and the rural economy in the EU and non-member countries, in part using the economic accounts for agriculture.
Target setting, benchmarking and contributions
Policies within the EU are increasingly setting medium or long-term targets, whether binding or not. For some of these, the level of GDP is used as a benchmark denominator, for example, setting a target for expenditure on research and development at a level of 3.00 % of GDP.
National accounts are also used to determine EU resources, with the basic rules laid down in a Council Decision. The overall amount of own resources needed to finance the EU budget is determined by total expenditure less other revenue, and the maximum size of the own resources are linked to the gross national income of the EU.
As well as being used to determine budgetary contributions within the EU, national accounts data are also used to determine contributions to other international organisations, such as the United Nations (UN). Contributions to the UN budget are based on gross national income along with a variety of adjustments and limits.
Analysts and forecasters
National accounts are also widely used by analysts and researchers to examine the economic situation and developments. Social partners, such as representatives of businesses (for example, trade associations) or representatives of workers (for example, trade unions), also have an interest in national accounts for the purpose of analysing developments that affect industrial relations. Among other uses, researchers and analysts use national accounts for business cycle analysis and analysing long-term economic cycles and relating these to economic, political or technological developments.
- European sector accounts — background (background article)
- Main users of national accounts (background article)
- Sector accounts
- Update of the 1993 SNA and revision of ESA 95 (background article)
Further Eurostat information
- National accounts (including GDP) (t_na), see:
- Annual national accounts (t_nama)
- National accounts (ESA 2010) (na10), see:
- Annual national accounts (nama_10)
Methodology / Metadata
ESMS metadata files
- Annual national accounts (ESMS metadata file — nama_esms)
- Supply, use and Input-output tables (ESMS metadata file — naio_esms)
- Essential SNA — Building the basics — 2014 edition
- European system of accounts — ESA 2010
- European system of accounts — ESA 2010 — Transmission programme of data (multilingual)
- Eurostat-OECD methodological manual on purchasing power parities
- Handbook on price and volume measures in national accounts
- Manual on the changes between ESA 95 and ESA 2010 — 2014 edition
Other methodological information
- National accounts, see Methodology:
Source data for tables and figures (MS Excel)
- ESA 2010 — Overview
- NACE Rev. 2 — statistical classification of economic activities in the European Community
- European Commission — Economic and Financial Affairs — Index of economic forecasts
- United Nations — Department of Economic and Social Affairs — Statistics Division — SNA implementation