National accounts and GDP
Data extracted in July 2018.
Planned article update: July 2019.
Real GDP growth, 2007-2017
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 (as expressed in purchasing power standards, PPS) — are widely used for a comparison of living standards, or to monitor economic convergence or divergence within 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.
Developments in GDP in the EU: growth since 2013
The global financial and economic crisis resulted in a severe recession in the EU in 2009 (see Figure 1), followed by a recovery in 2010. The crisis started earlier in Japan and the United States, with negative annual rates of change for GDP (in real terms) already recorded in 2008, deepening in 2009, before rebounding in 2010. By contrast, economic output in China continued to grow at a relatively rapid pace during the crisis (close to 10 % each year), slowing somewhat in subsequent years, but remaining considerably higher than in any of the other economies shown in Figure 1. The crisis was already apparent in the EU-28 in 2008 when there had been a considerable reduction in the rate of increase for GDP and this was followed by a fall in real GDP of 4.3 % in 2009. The recovery in the EU-28 saw the index of GDP (based on chain linked volumes) increase by 2.1 % in 2010 and there was a further gain of 1.8 % in 2011. Subsequently, GDP contracted 0.4 % in 2012, before progressively larger positive rates of change were recorded in 2013 (0.3 %), 2014 (1.7 %) and 2015 (2.3 %). In 2016 growth continued, but at a slower rate (1.9 %) and in 2017 the previous series of accelerating growth returned, as GDP increased by 2.4 %, the highest annual rate of change since the onset of the crisis. 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 (1.6 %) and the contraction in 2012 was stronger (-0.9 %) and was sustained into 2013 (-0.2 %). During the period 2014-2016, real GDP growth in the euro area was somewhat weaker than that in the EU-28 as a whole, although in 2017 this pattern changed as both aggregates had the same rate of change.
Within the EU, real GDP growth varied considerably, both over time and between EU Member States (see Table 1). After a contraction in all of the Member States except Poland in 2009, economic growth resumed in 23 of the Member States in 2010 (and was unchanged in Spain), while there was growth recorded in 24 of the Member States in 2011. However, in 2012 this development changed, as half (14) of the Member States reported economic expansion, while there was no change in the level of economic activity in Bulgaria and falling output in the remaining Member States. In 2013, a majority of Member States once again recorded growth, with the number recording a positive rate of change reaching 17 in 2013 and rising to 25 in 2014 and 27 in 2015 and 2016, while all 28 Member States recorded a positive rate of change in 2017 (this first time this had occurred since 2007). The one Member State with a negative rate of change in 2015 and 2016 was Greece which recorded falls of 0.3 % and 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 annual growth rates for real GDP in 2017 were recorded in Ireland (7.2 %), Romania (6.9 %), Malta (6.4 %) and Slovenia (5.0 %), while the lowest rates of change were registered in Belgium and the United Kingdom (both 1.7 %), Italy (1.5 %) and Greece (1.4 %).
Average annual GDP growth below 1 % over the last decade in the EU and the euro area
Poland consistently recorded positive rates of change throughout the period shown in Table 1, as did Albania, Kosovo (UNSCR 1244; data from 2009 to 2016) and China (latest data also for 2016) among the non-member countries shown. Belgium, Denmark, Germany, Estonia, Ireland, France, Lithuania, Malta, Slovakia and the United Kingdom recorded their eighth consecutive positive annual rate of change in 2017; this was also the case in Norway, Switzerland and the United States, while Turkey recorded its seventh consecutive positive annual rate of change in 2016.
The effects of the global financial and economic crisis lowered the overall performance of the EU Member State economies when analysed during the last decade. The annual average growth rates of the EU-28 and the euro area (EA-19) between 2007 and 2017 were 0.8 % and 0.6 % respectively (see Table 1). The highest growth among the Member States, by this measure, between 2007 and 2017 was recorded for Malta (average annual growth of 4.2 %), followed by Ireland (4.1 %) and Poland (3.3 %). By contrast, the overall development of real GDP was negative during the period from 2007 to 2017 in Greece, Italy, Croatia and Portugal.
In 2017, Germany accounted for approximately one fifth of the EU-28’s GDP in PPS terms
Cross-country comparisons are often made using purchasing power standards (PPS) which adjust values to account for differences in price levels between countries. Note the data shown in Figure 2 and Figure 3 and in Table 2 are in current prices and should not be used for comparisons over time because of inflation and exchange rate fluctuations. In 2017, GDP in the EU-28 reached PPS 15.3 trillion (15 300 billion) — note that for the EU-28 one PPS equals one euro; as such, the EU-28’s GDP in PPS 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 2013, China’s GDP in PPS was for the first time higher than the level recorded in the United States and in 2015 China’s economic output reached a level that was higher than that recorded in the EU-28 (a situation that was maintained in 2016 and 2017).
The euro area (EA-19) accounted for 70.7 % of the EU-28’s GDP in 2017 (when measured in PPS terms), down from 72.6 % in 2007. In 2017, the sum of the five largest EU Member State economies (Germany, France, the United Kingdom, Italy and Spain) accounted for just over two thirds (66.8 %) of the EU-28’s GDP, which was 1.8 percentage points lower than their share a decade earlier (in 2007).
In 2017, GDP per capita averaged EUR 29 900 across the EU-28
To evaluate standards of living, it is commonplace to use GDP per capita, in other words, adjusted for the size of an economy in terms of its population. In 2017, average GDP per capita for the EU-28 (in current price terms) was EUR 29.9 thousand. Values expressed in PPS have been adjusted for differences in price levels across countries. The relative position of individual countries can be expressed through a comparison with the EU-28 average, with this set to equal 100 (see Table 2). Based on this measure, the highest value among the EU Member States was recorded for Luxembourg, where GDP per capita in PPS was about 2.5 times as high as the EU-28 average in 2017 (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 just less than half the EU-28 average in Bulgaria.
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 some way below the EU-28 average in 2007 to one closer to the EU-28 average in 2017, despite some setbacks during the global financial and economic crisis. Slovenia and Cyprus were exceptions, insofar as Slovenia 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). Cyprus moved from above the EU-28 average to a position below it, as did Italy and Spain. Whereas Ireland, Germany, Austria and Denmark moved further ahead of the EU-28 average, comparing the situation in 2017 with that in 2007, several other EU-15 Member States, namely Luxembourg, Finland, the Netherlands, the United Kingdom, Sweden and France, moved from a position above the EU-28 average in 2007 to one closer to (but still above) the EU-28 average in 2017. During the same period, Belgium and Croatia recorded no change in their level of GDP per capita in PPS with respect to the EU-28 average.
Gross value added in the EU by economic activity
Approximately three quarters of the EU-28’s total value added in 2017 was generated within the services sector
Looking at GDP from the output side, Table 3 gives an overview of the relative importance of 10 economic activities (as measured by NACE Rev. 2) in terms of their contribution to total gross value added at basic prices. Between 2007 and 2017, industry’s share of EU-28 value added fell 0.5 percentage points to 19.6 %, although it remained slightly larger than distributive trades, transport, accommodation and food services, whose share of total gross value added was identical in 2007 and 2017 (at 19.0 %). By contrast, public administration, education and health saw its share of total value added increase by 0.8 percentage points to reach 18.6 % in 2017. The next largest activities in 2017 — as measured by gross value added — were real estate activities (11.3 %), followed by professional, scientific, technical, administrative and support services — hereafter, business services — (11.2 %; whose share rose by 1.0 points between 2007 and 2017), construction (5.4 %; whose share fell by 1.0 points over the same period), information and communication services (5.0 %) and financial and insurance services (4.9 %). The smallest contributions came from the arts, entertainment and other services (3.5 %) and agriculture, forestry and fishing (1.6 %).
Services contributed 73.5 % of the EU-28’s total gross value added in 2017 compared with 71.9 % in 2007. The relative importance of services was particularly high in Luxembourg, Cyprus, Malta, the United Kingdom, Greece, France, the Netherlands, Belgium, Denmark and Portugal where they accounted for more than three quarters of total value added. By contrast, the share of services was close to three fifths in the Czech Republic and Ireland.
Diverging developments of economic activities over the last decade
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 and some services (those that can be provided remotely, such as through call centres) being moved to lower labour-cost regions, both within and outside the EU. Furthermore, several activities were particularly affected by the global 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 12.5 % (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, 2015 and 2017 (with annual increases of 2.7 %, 3.2 % and 3.2 %respectively) and a more subdued pace (1.9 %) in 2016. Construction experienced the deepest and longest contraction, with its output falling by 19.0 % between 2007 and 2013, with output falling every year during this period: as such, the 1.3 % increase recorded for construction in 2014 was the first annual growth in seven years and was followed by growth of 2.0 % in 2015, 1.5 % in 2016 and 4.2 % in 2017. Business services as well as distributive trades, transport, accommodation and food services also experienced relatively large reductions in value added in 2009, -6.9 % and -5.9 % respectively, but thereafter they posted positive annual rates of change each year through to 2017 (with the exception of a modest decline of 0.1 % for distributive trades, transport, accommodation and food services in 2013). After relative stability (no change) in 2009, output from agriculture, forestry and fishing fell in 2010 by 3.6 % and again in 2012 by 5.5 %; after growth of 3.7 %, 3.0 % and 1.5 % in 2013, 2014 and 2015, output from agriculture, forestry and fishing fell by 1.1 % in 2016 before rebounding with growth of 1.0 % in 2017. Two of the activities presented in Figures 4 and 5 did not record an annual fall in value added in any year during the period under consideration: real estate activities; public administration, defence, education, human health and social work activities.
In 2017, all activities — with the exception of agriculture, forestry and fishing — reported growth in their gross value added compared with 2016. The activities with the strongest growth were information and communication activities (4.6 %), construction (4.2 %) and business services (4.1 %).
To eliminate the effects of inflation, labour productivity per person employed 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 2007 to 2017 shows increases for most economic activities, with the largest productivity gains being recorded for agriculture, forestry and fishing (up overall by 28.9 %), information and communication services (20.0 %) and industry (13.7 %)— see Figure 6. Note that a precise comparison of labour productivity levels between activities can only be analysed for reference year 2010 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, by far, 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 2007 and 2017 in nearly all EU Member States, with Luxembourg, Greece, Italy and Finland recording falls (no data are available for Malta and no change in Austria). Over the same period, 2007 to 2017, labour productivity per hour worked increased in all EU Member States except for Luxembourg and Greece (data not available for Malta). 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 Bulgaria, Latvia, Lithuania, Slovakia, Spain and the Czech Republic.
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 8.1 % in volume terms between 2007 and 2017 (see Figure 7), despite slight falls in 2009 and 2012. Final consumption expenditure of general government rose at a somewhat faster pace, up 11.1 % between 2007 and 2017. During the same period, gross capital formation was relatively volatile: it decreased at a rapid pace in 2009, while between 2010 and 2013 it fluctuated, before following an upward path through to 2017. The growth in exports exceeded the growth in imports most years, the exceptions being 2009 and 2014-2016; over the period 2007-2017 exports increased by a total of 33.4 % whereas imports increased by 26.5 %.
After its fall in 2009, consumption expenditure by households and non-profit institutions serving households (NPISH) recovered in 2010 (up 0.8 % in volume terms) and then reported no change in 2011 (0.0 %), before falling again in 2012 (-0.6 %) and 2013 (-0.1 %); thereafter, this expenditure increased during four consecutive years, rising by 1.2 %, 2.1 %, 2.4 % and 1.9 %.
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 0.4 %) between 2011 and 2013, before returning to somewhat stronger growth thereafter, rising by 1.1 % in 2014, 1.4 % in 2015, 1.6 % in 2016 and 1.0 % in 2017.
Despite an increase in 2011 (1.9 %), EU-28 gross fixed capital formation failed to fully recover from its sharp fall in 2009 (-11.8 %) and returned to a negative rate of change in 2012 and 2013; however, gross fixed capital formation in the EU-28 increased during the period 2014-2017, rising by 2.8 %, 4.8 %, 2.9 % and 3.1 % respectively.
In current price terms, consumption expenditure by households and non-profit institutions serving households contributed 55.7 % of the EU-28’s GDP in 2017, while the share of gross capital formation was 20.5 % and that of general government expenditure 20.1 % (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 2017, gross fixed capital formation (in current prices) as a share of GDP was 20.1 % in the EU-28 and 20.5 % in the euro area (EA-19).It was highest in Sweden (24.9 %), the Czech Republic (24.7 %), Estonia (23.7 %), Ireland and Austria (both 23.5 %) and lowest in Portugal (16.2 %) and Greece (12.6 %).
The vast majority of investment in the EU-28 was made by the private sector, as can be seen from Table 5: in 2017, investment by businesses and households accounted for 17.9 % of the EU-28’s GDP, whereas the equivalent figure for public sector investment was 2.8 %. In relative terms, Hungary (6.6 % of GDP) and Estonia (4.8 %; 2016 data) had the highest public investment, while investment by the business sector was highest in Ireland (27.2 %; 2016 data) and Sweden (17.2 %) and by households was highest in Finland (6.5 %) and Germany (6.0 % ; 2016 data). Investment by households (as a share of GDP) in 2016 was notably lower than in 2007 in Greece, Ireland, Cyprus and Spain, while it was notably higher in Romania; Bulgaria, Lithuania and Germany were the only other EU Member States to report an increase in their share of household investment in GDP.
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 47.3 % of GDP at current market prices in 2017. The share of gross operating surplus and mixed income was 40.8 % 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 (29.4 %), followed by Greece (33.6 %) and Romania (36.0 %), while shares in excess of 50.0 % were recorded in four EU Member States, including Luxembourg, Germany and Denmark, but peaking at 52.2 % in France. In the case of Ireland this is however related to globalisation related effects.
Figure 12 (which is also based on data in 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 in the EU-28 fell by 2.8 %, but by 2017 was 18.1 % higher than its corresponding level recorded in 2008.
For the gross operating surplus and mixed income, there was already only limited growth across the EU-28 in 2008, followed by a fall of 8.2 % in 2009; by 2012 this income aggregate had returned to a similar level as its pre-crisis peak (in 2008) and by 2017 was 14.3 % above that peak level.
The fall in taxes on production and imports less subsidies in the EU-28 had already started in 2008 (-3.1 %) and accelerated in 2009 (-9.2 %); by 2011 these losses had been more than recovered and in 2016 this income aggregate stood 20.4 % above its pre-crisis peak (2007).
Consumption expenditure of households accounted for at least half of GDP (at current market prices) in around two thirds (19) of the EU Member States in 2017; this share was highest in Cyprus (67.7 %), Greece (66.6 %), Lithuania (63.8 %), Portugal (63.1 %) and the United Kingdom (63.0 %). By contrast, it was lowest in Luxembourg (28.6 %) which had, nevertheless, by far the highest average household consumption expenditure per capita (PPS 21 700) — see Table 6 — even after adjusting for price level differences between Member States.
Aside from Luxembourg, average household consumption expenditure per capita in PPS terms was also relatively high in 2017 in the United Kingdom (PPS 19 800), Austria (PPS 19 100) and Germany (PPS 18 900). By contrast, 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 2012-2017 shows that the fastest growth was recorded in the Baltic Member States and Romania. Austria was the only EU Member State to report that household consumption expenditure per capita fell, down on average by 0.2 % each year during the period under consideration, while there was no change in Greece.
Source data for tables and graphs
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 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. The HBS is only carried out and published every five years — the latest reference year for which data are currently available is 2015, although data are ,not yet available for all EU Member States.
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 four times a year (autumn, winter, spring and summer), 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 article)
- European system of national and regional accounts — ESA 2010 (background article)
- Main users of national accounts (background article)
- Sector accounts
- Annual national accounts (t_nama), see:
- GDP and main components (t_nama_10_gdp)
- Exports and imports by Member States of the EU/third countries (t_nama_10_exi)
- Final consumption expenditure of households by consumption purpose (COICOP) (t_nama_10_co)
- Auxiliary indicators to national accounts - annual data (t_nama_10_aux)
- Regional economic accounts (t_nama_10_reg)
- Annual national accounts (nama_10), see:
- Main GDP aggregates (nama_10_ma)
- Auxiliary indicators (population, GDP per capita and productivity) (nama_10_aux)
- Basic breakdowns of main GDP aggregates and employment (by industry and by assets) (nama_10_bbr)
- Detailed breakdowns of main GDP aggregates (by industry and consumption purpose) (nama_10_dbr)
- Breakdown of non)-financial assets by type, industry and sector (nama_10_nfa)
- Regional economic accounts - ESA 2010 (nama_10_reg)
- Quarterly national accounts (namq_10)
- National accounts - international data cooperation (naid_10)
ESMS metadata files
- Annual national accounts (ESMS metadata file — nama10_esms)
- Supply, use and Input-output tables (ESMS metadata file — naio_10_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 prices and volume measures in national accounts
- Manual on the changes between ESA 95 and ESA 2010 — 2014 edition
Other methodological information