National accounts and GDP
- Data extracted in September 2016. Most recent data: Further Eurostat information, Main tables and Database. Planned article update: June 2017.
National accounts are the source for a multitude of well-known economic indicators which are presented in this article. Gross domestic product (GDP) is the most frequently used measure for the overall size of an economy, while derived indicators such as GDP per capita — for example, in euro or adjusted for differences in price levels — are widely used for a comparison of living standards, or to monitor the process of convergence across the European Union (EU).
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.
- 1 Main statistical findings
- 2 Data sources and availability
- 3 Context
- 4 See also
- 5 Further Eurostat information
- 6 External links
Main statistical findings
Developments in GDP
The global financial and economic crisis resulted in a severe recession in the EU, Japan and the United States in 2009 (see Figure 1), followed by a recovery in 2010. The crisis was already apparent in 2008 when there had been a considerable reduction in the rate of increase for GDP in the EU-28 and this was followed by a fall in real GDP of 4.4 % in 2009. The recovery in the EU-28 saw the volume index of GDP based on chain linked volumes increase by 2.1 % in 2010 and there was a further gain of 1.7 % in 2011; subsequently real GDP contracted 0.5 % in 2012, before progressively larger positive rates of change were recorded in 2013 (0.2 %), 2014 (1.5 %) and 2015 (2.2 %). In the euro area (EA-19) the corresponding rates of change were very similar to those in the EU-28 through to 2010, while the growth recorded in 2011 was slightly weaker (1.5 %) and the contraction in 2012 was stronger (-0.9 %) and was sustained into 2013 (-0.3 %). In 2014 and 2015, real GDP growth in the euro area was somewhat weaker than that in the EU-28 as a whole.
Within the EU, real GDP growth varied considerably, both over time and between Member States (see Table 1). 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 23 of the EU Member States. However, in 2012 this development was reversed, as just less than half (13) of the Member States reported economic expansion. In 2013, a majority of Member States again recorded growth, with the number recording a positive rate of change reaching 16 in 2013 and rising to 24 in 2014 and 27 in 2015; the one Member State with a negative rate of change in 2015 was Greece which recorded a fall of 0.2 % after growth of 0.7 % in 2014 and six successive reductions in economic output during the years from 2008 to 2013.
The highest growth rates in 2015 were recorded in Ireland (26.3 %) and Malta (6.2 %). In 2015, Croatia recorded growth of 1.6 %, its first annual growth since 2008. Cyprus also recorded growth of 1.6 % in 2015, its first annual growth since 2011, while a similar situation was observed in Italy and Finland, although their rates of growth were less than 1.0 %. By contrast, Poland recorded positive rates of change throughout the period shown in Table 1, while Bulgaria, Germany, Estonia, France, Lithuania, Malta, Austria, Slovakia and the United Kingdom recorded their sixth consecutive positive annual rate of change in 2015; in other words their last negative annual rate of change was at the height of the crisis in 2009; this was also the case in Norway and Switzerland, as well as in Albania and Kosovo (where the latest data available refer to 2014).
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 growth rates of the EU-28 and the euro area (EA-19) between 2005 and 2015 were 0.9 % per annum and 0.8 % per annum respectively (see Table 1). The highest growth, by this measure, was recorded for Poland (average growth of 3.9 % per annum) and Slovakia (3.6 % per annum), followed by Ireland (3.4 % per annum), Malta (2.9 % per annum), Luxembourg and Romania (both 2.7 % per annum). By contrast, the overall development of real GDP during the period from 2005 to 2015 in Greece, Italy and Portugal was negative.
Cross-country comparisons should be made using purchasing power standards (PPS) which adjust values to account for differences in price levels between countries. Note the data shown in Table 2, Figure 2 and Figure 3 are in current prices and should not be used for comparisons over time because of inflation and exchange rate fluctuations. In 2015, GDP in the EU-28 reached PPS 14.6 trillion (14 600 billion); as such, the EU-28's GDP remained ahead of that for the United States during every year for which the analysis is presented. It is interesting to note that China historically had a lower level of economic output than either the EU-28 or the United States, but that this situation has changed with the rapid transformation and continued expansion of the Chinese economy. In 2014, China's GDP surpassed the level recorded in the United States and in 2015 China's economic output reached PPS 14.9 trillion, a level that was above that recorded in the EU-28.
The euro area (EA-19) accounted for 70.6 % of the EU-28’s GDP in 2015 (when measured in PPS terms), down from 72.0 % in 2008. In 2015, the sum of the five largest EU Member State economies (Germany, the United Kingdom, France, Italy and Spain) accounted for 67.6 % of the EU-28’s GDP (which was identical to their share a decade before in 2005).
To evaluate standards of living, it is commonplace to use GDP per capita in PPS terms (see Table 2), in other words, adjusted for the size of an economy in terms of its population and also for differences in price levels across countries. The average GDP per capita within the EU-28 in 2015 was PPS 28.8 thousand, which was above the previous peak (PPS 26.1 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 about 2.7 times the EU-28 average in 2015 (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 2015.
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. Most Member States that joined the EU in 2004, 2007 or 2013 moved from a position below the EU-28 average in 2005 to one closer to the EU average in 2015, despite some setbacks during the financial and economic crisis. Cyprus and Slovenia were exceptions, insofar as they moved slightly further below the EU-28 average during this period, as did Greece and Portugal among the EU-15 Member States (see Figure 3). Whereas Luxembourg, Ireland, Germany and Austria moved further ahead of the EU-28 average, comparing the situation in 2015 with that in 2005, several other EU-15 Member States, notably the United Kingdom and the Netherlands, moved from a position above the EU-28 average in 2005 to one closer to (but still above) the EU-28 average in 2015. During the same period Italy and Spain moved from above or level with the EU-28 average to a position below it.
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 total gross value added at basic prices. Between 2005 and 2015, industry’s share of EU-28 value added fell 0.9 percentage points to 19.2 %, although it remained slightly higher than the share recorded for distributive trades, transport, accommodation and food services (19.0 %) which also recorded a fall in its share, down 0.2 percentage points during the 10 year period under consideration. By contrast, public administration, education and health saw its share increase by 0.7 percentage points to reach 19.1 % in 2015. The next largest activities in 2015 were real estate activities (11.3 %), followed by professional, scientific, technical, administrative and support services — hereafter, business services — (10.8 %), construction (5.4 %), financial and insurance services (5.2 %) and information and communication services (5.0 %). The smallest contributions came from entertainment and other services (3.5 %) and agriculture, forestry and fishing (1.5 %).
Services contributed 73.9 % of the EU-28’s total gross value added in 2015 compared with 71.9 % in 2005. The relative importance of services was particularly high in Luxembourg, Cyprus, Malta, Greece, the United Kingdom, France, the Netherlands, Belgium, Portugal, Denmark and Spain where they accounted for at least 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 12.7 % (in volume terms); EU-28 industrial output fell by a further 2.3 % between 2011 and 2013, before growing at a relatively fast pace in 2014 and 2015 (with increases of 2.1 % and 3.5 % respectively). Construction experienced the deepest and longest contraction, with its output falling by 19.2 % between 2007 and 2013, with output falling every year during this period: as such, the 1.8 % increase recorded for construction in 2014 was the first annual growth in seven years and was followed by growth of 1.7 % in 2015. Business services as well as distributive trades, transport, accommodation and food services also experienced relatively strong falls in value added in 2009, -7.0 % and -6.1 % respectively, but thereafter they posted positive annual rates of change each year through to 2015. After relative stability (-0.3 %) in 2009, output from agriculture, forestry and fishing fell in 2010 by 3.0 % and again in 2012 by 5.6 %. Relatively small reductions in value added were experienced for other activities during the crisis, most notably in 2009, 2010 and between 2012 and 2014 for financial and insurance services and in 2009, 2010, 2012 and 2013 for arts, entertainment, recreation and other services (see Figure 5). 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 2015, all activities — with the exception of agriculture, forestry and fishing — reported growth in their gross value added compared with 2014. The activities with the strongest growth were information and communication activities (3.9 %), industry (3.5 %), business services (3.2 %), and distributive trades, transport, accommodation and food services (2.4 %).
To eliminate the effects of inflation, labour productivity per person can be calculated using data adjusted for price changes. An analysis of labour productivity per person employed in real terms (based on chain linked volume changes) over the 10-year period from 2005 to 2015 shows increases for most activities, with the largest productivity gains being recorded for agriculture, forestry and fishing (27.9 %), information and communication services (22.8 %) and industry (17.1 %)— see Figure 6. Note that a precise comparison of labour productivity levels between industries can only be analysed for reference year 2010 (rather than 2005 or 2015) due to the non-additivity of chain linked volumes. In 2010, the highest level of labour productivity was observed for financial and insurance activities, closely followed by information and communication services, whereas agriculture, forestry and fishing recorded the lowest level.
Further data on the development of real labour productivity measured either per person employed or per hour worked are shown in Table 4. Labour productivity per person employed increased, in real terms, between 2005 and 2015 in nearly all EU Member States, with Greece, Croatia, Italy, Luxembourg and Finland recording falls (no data are available for Malta). Over the same period, 2005 to 2015, labour productivity per hour worked increased in all EU Member States except for Greece. Leaving aside those Member States with a break in series, the largest increases (in percentage terms) for both of these real labour productivity measures were recorded in Lithuania, Slovakia, Bulgaria and Latvia.
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 8.4 % in volume terms between 2005 and 2015 (see Figure 7), despite slight falls in 2009 and 2012. Final consumption expenditure of general government rose at a somewhat faster pace, up 12.5 % between 2005 and 2015. During the same period, gross capital formation was relatively volatile: it increased strongly in 2006 and 2007, decreased particularly strongly in 2009, and between 2010 and 2015 fluctuated either side of its 2005 value. The growth in exports exceeded the growth in imports most years, the exceptions being 2007, 2009, 2014 and 2015; over the period 2005–2015 exports increased by a total of 42.0 % whereas imports increased by 34.6 %.
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 reported almost no change in 2011 (0.1 %), before falling again in 2012 (-0.5 %) and 2013 (-0.1 %); in 2014 and 2015 this expenditure increased by 1.2 % and 2.0 %, the largest annual increases 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 -0.1 % to 0.3 %) between 2011 and 2013, before returning to somewhat stronger growth in 2014 (0.9 %) and 2015 (1.4 %). Despite an increase in 2011 (1.9 %), EU-28 gross fixed capital formation failed to fully recover from its sharp fall in 2009 (-12.0 %) and returned to a negative rate of change in 2012 and 2013; however, in 2014 and 2015 gross fixed capital formation increased 2.8 % and 3.5 % respectively in real terms, the largest increases since 2007.
In current price terms, consumption expenditure by households and non-profit institutions serving households contributed 56.4 % of the EU-28’s GDP in 2015, while the share of general government expenditure was 20.5 % and that of gross capital formation was 19.8 % (see Figure 9).
Among the EU Member States, there was a wide variation in 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 2015, gross fixed capital formation (in current prices) as a share of GDP was 19.6 % in the EU-28 and 19.8 % in the euro area (EA-19). It was highest in the Czech Republic (26.3 %), Malta (25.4 %), Romania (24.7 %), and Sweden (24.2 %) and lowest in Cyprus (13.4 %) and Greece (11.7 %).
The vast majority of investment was made by the private sector, as can be seen from Table 5: in 2015, investment by businesses and households accounted for 17.1 % of the EU-28’s GDP, whereas the equivalent figure for public sector investment was 3.0 %. In relative terms, Hungary (2014 data) had the highest public investment (5.5 % of GDP), while investment by the business sector was highest in Sweden (17.1 %) and by households was highest in Germany (6.4 %; 2014 data). Investment by households (as a share of GDP) in 2014 was notably lower than in 2005 in Ireland, Greece, Cyprus and Spain, while it was notably higher in Romania (again comparing 2014 with 2005); Germany (2005–2014) and Bulgaria (2005–2013) were the only other EU Member States to report an increase in the share of household investment in GDP. A similar comparison shows a relatively large fall in Latvia, Slovenia, Slovakia, Estonia (all 2005–2014), as well as in Bulgaria (2005–2013) 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 47.4 % of GDP at current market prices in 2015. The share of gross operating surplus and mixed income was 40.7 % of GDP, while that for taxes on production and imports less subsidies was 11.9 % (see Figure 11). Ireland had the lowest share of the compensation of employees in GDP (30.6 %), followed by Romania (32.3 %) and Greece (33.5 %), while shares in excess of 50.0 % were recorded in four EU Member States, peaking at 52.9 % in Denmark.
Figure 12 (which is also based on current market 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 2.8 %, but by 2015 was 13.4 % higher than its corresponding level recorded in 2008. For the gross operating surplus and mixed income, there was already only limited growth in 2008, followed by a fall of 8.2 % in 2009; by 2011 this income aggregate had returned to the same level as its pre-crisis peak (in 2008) and by 2015 was 9.8 % 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 more than recovered and in 2015 this income aggregate stood 15.4 % above its previous peak (2007).
The consumption expenditure of households accounted for at least half of GDP (at current market prices) in three quarters (21) of the EU Member States in 2015; this share was highest in Cyprus (69.3 %), Greece (67.6 %), Lithuania and Portugal (both 63.9 %). By contrast, it was lowest in Luxembourg (27.8 %) which had, nevertheless, by far the highest average household consumption expenditure per capita (PPS 21 700) — see Table 6.
Aside from Luxembourg, average household consumption expenditure per capita (adjusted to take account of differences in price levels) was also relatively high in 2015 in the United Kingdom (PPS 19 600), Germany (PPS 18 800) and Austria (PPS 18 700). By contrast, Croatia, Hungary and Bulgaria were the only EU Member States to report that average household consumption expenditure per capita was below PPS 10 000.
An analysis of real developments in average consumption expenditure per capita in euro terms (based on a chain linked volume index) over the period 2010–2015 shows that the fastest growth was recorded in the Baltic Member States and Romania (note that there was a break in series for the latter). The largest contraction was recorded in Greece, where household consumption expenditure per capita fell, on average, by 3.7 % per annum during the period under consideration. There were also reductions of at least 1.0 % per annum recorded for Italy, Cyprus and Slovenia.
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 using chain linked volume indices (real changes) 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, 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 (real changes) — 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. The EU has yearly cycle of economic policy coordination called the European Semester. Each year, the European Commission conducts a detailed analysis of EU Member States' plans of budgetary, macroeconomic and structural reforms and provides country-specific recommendations for the following 12–18 months.
The Directorate-General for Economic and Financial Affairs also produces the European Commission’s macroeconomic forecasts three times a year (winter, spring and autumn), in coordination with the annual cycle of the European Semester. 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 (which is one of the Europe 2020 targets).
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
- Annual national accounts (t_nama)
- 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
Source data for tables and figures (MS Excel)
- European Commission — Economic and Financial Affairs — Index of economic forecasts
- United Nations — Department of Economic and Social Affairs — Statistics Division — SNA implementation