Eurostat

The data are three-month interbank rates which are no longer updated. The series represent interest rates of countries which have now joined the euro area.

The data are three-month interbank rates which are no longer updated. The series represent interest rates of countries which have now joined the euro area.

The 3-months interest rate is a representative short-term interest rate series for the domestic money market. From January 1999, the euro area rate is the 3-month "EURo InterBank Offered Rate" (EURIBOR) EURIBOR is the benchmark rate of the large euro money market that has emerged since 1999. It is the rate at which euro InterBank term deposits are offered by one prime bank to another prime bank. The contributors to EURIBOR are the banks with the highest volume of business in the euro area money markets. The panel of banks consists of banks from EU countries participating in the euro from the outset, banks from EU countries not participating in the euro from the outset, and large international banks from non-EU countries but with important euro area operations. Monthly data are calculated as averages of daily values. Data are presented in raw form. Source: European Central Bank (ECB)

Harmonised data on accidents at work are collected in the framework of the administrative data collection 'European Statistics on Accidents at Work (ESAW)', on the basis of a methodology developed first in 1990. An accident at work is defined as 'a discrete occurrence in the course of work which leads to physical or mental harm'. The data include only fatal and non-fatal accidents involving more than 3 calendar days of absence from work. If the accident does not lead to the death of the victim it is called a 'non-fatal' (or 'serious') accident. A fatal accident at work is defined as an accident which leads to the death of a victim within one year of the accident. The variables collected on accidents at work include: Economic activity of the employer and size of the enterpriseEmployment status, occupation, age, sex and nationality of victimGeographical location, date and time of the accidentType of injury, body part injured and the severity of the accident (number of full calendar days during which the victim is unfit for work excluding the day of the accident, permanent incapacity or death within one year of the accident).Variables on causes and circumstances of the accident: workstation, working environment, working process, specific physical activity, material agent of the specific physical activity, deviation and material agent of deviation, contact - mode of injury and material agent of contact - mode of injury. The national ESAW sources are the declarations of accidents at work, either to the accident insurance of the national social security system, a private insurance for accidents at work or to other relevant national authorities (labour inspection etc.). As an exception, accident data for the Netherlands are based on survey data. On the Eurostat website, ESAW data are disseminated in two sections: 'Main Indicators' and 'Details by economic sector (NACE Rev2, 2008 onwards)'. Depending on the table, data are broken down by: economic activity (NACE 'main sectors' (1 digit code) or more detailed NACE divisions (2 digit codes)); the occupation of the victim (ISCO-08 code); country; severity of the accident, sex, age, employment status, size of the enterprise, body part injured and type of injury. The data is presented in form of numbers, percentages, incidence rates and standardised incidence rates of non-fatal and fatal accidents at work, either for EU aggregates, countries or certain breakdowns by dimensions such as age, sex etc. Numbers correspond to a simple count of all non-fatal and fatal accidents for the entirety or certain breakdowns of the data;Percentages represent shares of breakdowns;The incidence rate of non-fatal or fatal accidents at work is the number of serious or fatal accidents per 100,000 persons in employment;The standardised incidence rates of non-fatal or fatal accidents at work aim to eliminate differences in the structures of countries' economies (see section 18.6 Adjustment for more details). The incidence rate indicates the relative importance of non-fatal or fatal accidents at work in the working population. For both types of accidents at work the numerator is the number of accidents that occurred during the year. The denominator is the reference population (i.e. the number of persons in employment) expressed in 100,000 persons. The reference population (or number of persons in employment) related to the national ESAW reporting system is provided by the Member States, either from administrative sources related to accidents at work or from the EU Labour Force Survey (LFS).

Harmonised data on accidents at work are collected in the framework of the administrative data collection 'European Statistics on Accidents at Work (ESAW)', on the basis of a methodology developed first in 1990. An accident at work is defined as 'a discrete occurrence in the course of work which leads to physical or mental harm'. The data include only fatal and non-fatal accidents involving more than 3 calendar days of absence from work. If the accident does not lead to the death of the victim it is called a 'non-fatal' (or 'serious') accident. A fatal accident at work is defined as an accident which leads to the death of a victim within one year of the accident. The variables collected on accidents at work include: Economic activity of the employer and size of the enterpriseEmployment status, occupation, age, sex and nationality of victimGeographical location, date and time of the accidentType of injury, body part injured and the severity of the accident (number of full calendar days during which the victim is unfit for work excluding the day of the accident, permanent incapacity or death within one year of the accident).Variables on causes and circumstances of the accident: workstation, working environment, working process, specific physical activity, material agent of the specific physical activity, deviation and material agent of deviation, contact - mode of injury and material agent of contact - mode of injury. The national ESAW sources are the declarations of accidents at work, either to the accident insurance of the national social security system, a private insurance for accidents at work or to other relevant national authorities (labour inspection etc.). As an exception, accident data for the Netherlands are based on survey data. On the Eurostat website, ESAW data are disseminated in two sections: 'Main Indicators' and 'Details by economic sector (NACE Rev2, 2008 onwards)'. Depending on the table, data are broken down by: economic activity (NACE 'main sectors' (1 digit code) or more detailed NACE divisions (2 digit codes)); the occupation of the victim (ISCO-08 code); country; severity of the accident, sex, age, employment status, size of the enterprise, body part injured and type of injury. The data is presented in form of numbers, percentages, incidence rates and standardised incidence rates of non-fatal and fatal accidents at work, either for EU aggregates, countries or certain breakdowns by dimensions such as age, sex etc. Numbers correspond to a simple count of all non-fatal and fatal accidents for the entirety or certain breakdowns of the data;Percentages represent shares of breakdowns;The incidence rate of non-fatal or fatal accidents at work is the number of serious or fatal accidents per 100,000 persons in employment;The standardised incidence rates of non-fatal or fatal accidents at work aim to eliminate differences in the structures of countries' economies (see section 18.6 Adjustment for more details). The incidence rate indicates the relative importance of non-fatal or fatal accidents at work in the working population. For both types of accidents at work the numerator is the number of accidents that occurred during the year. The denominator is the reference population (i.e. the number of persons in employment) expressed in 100,000 persons. The reference population (or number of persons in employment) related to the national ESAW reporting system is provided by the Member States, either from administrative sources related to accidents at work or from the EU Labour Force Survey (LFS).

The section 'LFS series - detailed quarterly survey results' reports detailed quarterly results going beyond the EU-LFS main aggregates, which have a separate data domain and some methodological differences. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The indicator is defined as the percentage of the population in a given age group who are economically active. According to the definitions of the International Labour Organisation (ILO) people are classified as employed, unemployed and economically inactive for the purposes of labour market statistics. The economically active population (also called labour force) is the sum of employed and unemployed persons. Inactive persons are those who, during the reference week, were neither employed nor unemployed. The indicator is based on the EU Labour Force Survey.

The indicator is defined as the percentage of the population aged 15-64 who are economically active. According to the definitions of the International Labour Organisation (ILO) people are classified as employed, unemployed and economically inactive for the purposes of labour market statistics. The economically active population (also called labour force) is the sum of employed and unemployed persons. Inactive persons are those who, during the reference week, were neither employed nor unemployed. The indicator is based on the EU Labour Force Survey.

The section 'LFS series - detailed quarterly survey results' reports detailed quarterly results going beyond the EU-LFS main aggregates, which have a separate data domain and some methodological differences. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.

The source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview

Labour cost statistics provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Structural information on labour costs is collected through four-yearly Labour Cost Surveys (LCS), which provides details on the level and structure of labour cost data, hours worked and hours paid. LCS results are available for the reference years 2000, 2004, 2008 and 2012. All EU Member States together with Norway and Iceland (2004 onwards), Turkey and Macedonia (2008), as well as Serbia (2012) participated in the LCS. As far as available data and confidentiality rules permit, all variables and proportions are further broken down by enterprise size category, economic activity and region (for larger countries only). The data are collected by the National Statistical Institutes in most cases on the basis of stratified random samples of enterprises or local units, restricted in most countries to units with at least 10 employees. The stratification is based on economic activity, size category and region (where appropriate). Regional metadata is identical to the metadata provided for national data. Some countries also complement the survey results with administrative data. Monetary variables are expressed in EUR, national currencies (for non-euro-area countries) and Purchasing Power Standards (PPS). Labour costs are quoted in total per year, per month and per hour, as well as per capita and per full-time equivalents (FTE). Information on staff, hours worked and hours paid is quoted in aggregate and separately for full- and part-time employees.

Labour cost statistics provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Structural information on labour costs is collected through four-yearly Labour Cost Surveys (LCS), which provides details on the level and structure of labour cost data, hours worked and hours paid. LCS results are available for the reference years 2000, 2004, 2008 and 2012. All EU Member States together with Norway and Iceland (2004 onwards), Turkey and Macedonia (2008), as well as Serbia (2012) participated in the LCS. As far as available data and confidentiality rules permit, all variables and proportions are further broken down by enterprise size category, economic activity and region (for larger countries only). The data are collected by the National Statistical Institutes in most cases on the basis of stratified random samples of enterprises or local units, restricted in most countries to units with at least 10 employees. The stratification is based on economic activity, size category and region (where appropriate). Regional metadata is identical to the metadata provided for national data. Some countries also complement the survey results with administrative data. Monetary variables are expressed in EUR, national currencies (for non-euro-area countries) and Purchasing Power Standards (PPS). Labour costs are quoted in total per year, per month and per hour, as well as per capita and per full-time equivalents (FTE). Information on staff, hours worked and hours paid is quoted in aggregate and separately for full- and part-time employees.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

Data on cultural enterprises come from 2 data collections and are summarised in 4 Tables : a) SBS (Structural Business Statistics) Table 1. Number and average size of enterprises in the cultural sectors by NACE Rev. 2 activity (cult_ent_num) Table 2. Value added and turnover of enterprises in the cultural sectors by NACE Rev. 2 activity (cult_ent_val), in millions of EUR and as a percentage of services except trade and financial and insurance activities (i.e. NACE Rev. 2 sections H to N, without K) Table 3. Services by employment size class (NACE Rev. 2, H-N, S95) (sbs_sc_1b_se_r2)   b) Business Demography (BD) Table 4. Business demography by size class (from 2004 onwards, NACE Rev. 2) (bd_9bd_sz_cl_r2)   The data focus on culture-related sectors of activity, as identified by international experts in the final report of the European Statistical System Network on Culture (ESS-Net Culture Report 2012).   The cultural sphere in business statistics is therefore captured through the following NACE Rev. 2 codes, when they are covered (see 3.3. Sector coverage for details): J58.11 Book publishing J58.13 Publishing of newspapers J58.14 Publishing of journals and periodicals J58.21 Publishing of computer games J59 Motion picture, video and television programme production, sound recording and music publishing activities J60 Programming and broadcasting activities J63.91 News agency activities M71.11 Architectural activities M74.1 Specialised design activities R90 Creative, arts and entertainment activities R91 Libraries, archives, museums and other cultural activities

Intellectual property refers broadly to the creations of the human mind. Intellectual property rights protect the interests of creators by giving them property rights over their creations. Designs constitute means by which creators seek protection for their industrial property. Designs reflect the non-technological innovation in every sector of economic life, including services. In this context, indicators based on Design data can provide a link between innovation and the market. A design is the outward appearance of a product or part of it, resulting from the lines, contours, colours, shape, texture, materials and/or its ornamentation. The design or shape of a product can be synonymous with the branding and image of a company and can become an asset with increasing monetary value. This domain provides users with data concerning Community Designs. Community Designs refer to design protections throughout the European Union, which covers 28 countries. The Office for Harmonization in the Internal Market (EUIPO) is the official office of the European Union for the registration of Community Trade marks and Designs. A registered Community design (RCD) is an exclusive right that covers the outward appearance of a product or part of it. The fact that the right is registered confers on the design great certainty should infringement occur. An RCD initially has a life of five years from the filing date and can be renewed in blocks of five years up to a maximum of 25 years. Applicants may market a design for up to 12 months before filing for an RCD without destroying its novelty (Source: EUIPO).

The indicator presents the average compensation of employee received by hour worked, expressed in euro. It is calculated by dividing national accounts data on compensation of employees for the total economy, which include wages and salaries as well as employers' social contributions, by the total number of hours worked by all employees (domestic concept). The indicator is based on European national accounts.

National accounts are a coherent and consistent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. Eurostat publishes annual and quarterly national accounts, annual and quarterly sector accounts as well as supply, use and input-output tables, which are each presented with associated metadata. Even though consistency checks are a major aspect of data validation, temporary (usually limited) inconsistencies between datasets may occur, mainly due to vintage effects. Annual national accounts are compiled in accordance with the European System of Accounts - ESA 2010 as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013.   The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. Further information (including actual communications) is presented on the Eurostat website. The domain consists of the following collections:   1. Main GDP aggregates: main components from the output, expenditure and income side, expenditure breakdowns by durability and exports and imports by origin. <

Statistics on culture cover many aspects of economic and social life. According to the Europe 2020 strategy, the role of culture is crucial for achieving the goal of a "smart, sustainable and inclusive" growth. Employment in cultural sector statistics aim at investigating on the dimension of the contribution of cultural employment to the overall employment. Cultural employment statistics are derived from data on employment based on the results of the European Labour Force Survey (see EU-LFS metadata) that is the main source of information about the situation and trends on the labour market in the European Union. The final report of the European Statistical System Network on Culture (ESS-Net Culture Report 2012, in particular pp. 129-226) deals with the methodology applied to cultural statistics, including the scope of the 'cultural economic activities' and 'cultural occupations' based on two reference classifications: the NACE classification (‘Nomenclature générale des Activités économiques dans les Communautés Européennes’) which classifies the employer’s main activity, andthe ISCO classification(‘International Standard Classification of Occupations’) which classifies occupations. Results from the EU-LFS allow to characterize cultural employment by different variables such as gender, age, employment status, working time, educational attainment, permanency of jobs by cross-tabulating ISCO and NACE cultural codes as defined in the ESS-Net Culture Report 2012 (Annex 3 – Table 26 and Annex 4 – Table 27).

Culture statistics cover many aspects of economic and social life. According to the Europe 2020 strategy, the role of culture is crucial for achieving the goal of a "smart, sustainable and inclusive" growth. Statistics on cultural employment show the contribution of cultural employment to the overall employment and present different characteristics of the employment in this field of economy. Cultural employment statistics are derived from data on employment based on the results of the European Labour Force Survey (see EU-LFS metadata) that is the main source of information about the situation and trends on the labour market in the European Union. The final report of the European Statistical System Network on Culture (ESS-net Culture report 2012, in particular pp. 129-226) deals with the methodology applied to cultural statistics, including the scope of the 'cultural economic activities' and 'cultural occupations' based on two reference classifications: the NACE classification (‘Nomenclature générale des Activités économiques dans les Communautés Européennes’) which classifies the employer’s main activity, andthe ISCO classification (‘International Standard Classification of Occupations’) which classifies occupations. Results from the EU-LFS allow to characterize cultural employment by some core social variables (sex, age, educational attainment) and by selected labour market characteristics (self-employment, full-time work, permanent jobs and persons with one job only), by cross-tabulating ISCO and NACE cultural codes as defined in the ESS-net Culture report 2012 (Annex 3 – Table 26 and Annex 4 – Table 27). In 2016, an extension of the cultural scope was agreed upon by the Working Group 'Culture statistics' and implemented after in cultural employment statistics for reference years 2011 onwards. The publication "Culture statistics - 2016 edition" from the "Statistical books" series was based on the previous scope. Previous scope data are available here, for reference years 2008-2015: cultural employment by sexcultural employment by agecultural employment by educational attainmentcultural employment by NACE rev. 2

Euro-zone series: Until December 1998 it is an aggregate of interbank deposit bid rates weighted by country GDP (Gross Domestic Product). Thereafter the rate is the EONIA (Euro OverNight Index Average), the effective overnight reference rate for the euro, computed as a weighted average of all overnight unsecured lending transactions in the interbank market, initiated within the euro area by the contributing panel banks. EONIA is computed with the help of the European Central Bank. EU15 series: Until December 1998, this is a theoretical rate based on an aggregation of day-to-day rates weighted by country GDP. Thereafter the rate is an average of the EONIA and the rates of the non-euro-zone countries, weighted by country GDP. National series: broadly speaking, these are day-to-day interbank rates. Source: European Central Bank.

The data comprise day-to-day money rates which are no longer updated. These interest rates no longer exist once a country joins the euro area.

Foreign direct investment (FDI) is a category of investment that reflects the objective of establishing a lasting interest by a resident enterprise in one economy (direct investor) in an enterprise (direct investment enterprise) that is resident in an economy other than that of the direct investor. The lasting interest implies the existence of a long-term relationship between the direct investor and the direct investment enterprise and a significant degree of influence on the management of the enterprise. The lasting interest is deemed to exist if the investor acquires at least 10% of the voting power of the direct investment enterprise. Data are expressed in millions of national currency. FDI comprises: - Equity capital comprises equity in branches as well as all shares in subsidiaries and associates. - Reinvested earnings consist of the offsetting entry to the direct investor’s share of earnings not distributed as dividends by subsidiaries or associates, and earnings of branches not remitted to the direct investor and which are recorded under Investment income. - debt instruments Direct investment is classified primarily on a directional basis: 1) Resident direct investment abroad (Outward direct investment) 2) Non-resident investment in the reporting economy (Inward direct investment). The Inward direct investment is investment by a non-resident direct investor in a direct investment enterprise resident in the host economy; the direction of the influence by the direct investor is inward for the reporting economy. Starting from October 2014 definitions are based on the IMF's Sixth Balance of Payments Manual (BPM6).

Foreign direct investment (FDI) is a category of investment that reflects the objective of establishing a lasting interest by a resident enterprise in one economy (direct investor) in an enterprise (direct investment enterprise) that is resident in an economy other than that of the direct investor. The lasting interest implies the existence of a long-term relationship between the direct investor and the direct investment enterprise and a significant degree of influence on the management of the enterprise. The lasting interest is deemed to exist if the investor acquires at least 10% of the voting power of the direct investment enterprise. FDI flows comprise: - Equity capital including equity in branches as well as all shares in subsidiaries and associates; - Reinvested earnings consisting of the offsetting entry to the direct investor’s share of earnings not distributed as dividends by subsidiaries or associates, and earnings of branches not remitted to the direct investor and which are recorded under Investment income; - Debt instruments Data are presented according to the asset/liability principle, compiled in the framework of balance of payments and are consistent with the components of national accounts statistics. Inward FDI flows represent the value of FDI liabilities from all countries of the world in the reporting economy in the reference period. Data are expressed as % of GDP to remove the effect of differences in the size of the economies of the reporting countries. Definitions are based on the IMF's Sixth Balance of Payments Manual (BPM6).

Foreign direct investment (FDI) is a category of investment that reflects the objective of establishing a lasting interest by a resident enterprise in one economy (direct investor) in an enterprise (direct investment enterprise) that is resident in an economy other than that of the direct investor. The lasting interest implies the existence of a long-term relationship between the direct investor and the direct investment enterprise and a significant degree of influence on the management of the enterprise. The lasting interest is deemed to exist if the investor acquires at least 10% of the voting power of the direct investment enterprise. Data are expressed in Million units of national currency. FDI comprises: - Equity capital comprises equity in branches as well as all shares in subsidiaries and associates. - Reinvested earnings consist of the offsetting entry to the direct investor’s share of earnings not distributed as dividends by subsidiaries or associates, and earnings of branches not remitted to the direct investor and which are recorded under Investment income. - debt instruments Direct investment is classified primarily on a directional basis: 1) Resident direct investment abroad (Outward direct investment) 2) Non-resident investment in the reporting economy (Inward direct investment). The Inward direct investment is investment by a non-resident direct investor in a direct investment enterprise resident in the host economy; the direction of the influence by the direct investor is inward for the reporting economy. Definitions are based on the IMF's Sixth Balance of Payments Manual (BPM6).

Foreign direct investment (FDI) is a category of investment that reflects the objective of establishing a lasting interest by a resident enterprise in one economy (direct investor) in an enterprise (direct investment enterprise) that is resident in an economy other than that of the direct investor. The lasting interest implies the existence of a long-term relationship between the direct investor and the direct investment enterprise and a significant degree of influence on the management of the enterprise. The lasting interest is deemed to exist if the investor acquires at least 10% of the voting power of the direct investment enterprise. Data are expressed in Million units of national currency. FDI comprises: - Equity capital comprises equity in branches as well as all shares in subsidiaries and associates. - Reinvested earnings consist of the offsetting entry to the direct investor’s share of earnings not distributed as dividends by subsidiaries or associates, and earnings of branches not remitted to the direct investor and which are recorded under Investment income. - debt instruments Direct investment is classified primarily on a directional basis: 1) Resident direct investment abroad (Outward direct investment) 2) Non-resident investment in the reporting economy (Inward direct investment). The Inward direct investment is investment by a non-resident direct investor in a direct investment enterprise resident in the host economy; the direction of the influence by the direct investor is inward for the reporting economy. Starting from October 2014 definitions are based on the IMF's Sixth Balance of Payments Manual (BPM6).

Dispersion of regional employment rates (total, females, males) measures the regional (NUTS level 2) differences in employment within countries and groups of countries (EU-25, euro area). The dispersion is expressed by the coefficient of variation of employment rates of the age group 15-64. It is zero when the employment rates in all regions are identical, and it will rise if there is an increase in the differences between employment rates among regions. Employment rate of the age group 15-64 represents employed persons aged 15-64 as a percentage of the population of the same age group. The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The industrial domestic output price index measures the average price development of all goods and related services resulting from the activity of the industry sector and sold on the domestic market. The domestic output price index shows the monthly development of transaction prices of economic activities. The domestic market is defined as customers resident in the same national territory as the observation unit. Data are compiled according to the Statistical classification of economic activities in the European Community, (NACE Rev. 2, Eurostat). Industrial producer prices are compiled as a "fixed base year Laspeyres type price-index". The current base year is 2015 (Index 2015 =100). Indexes, as well as both growth rates with respect to the previous month (M/M-1) and with respect to the corresponding month of the previous year (M/M-12) are presented in raw form.

In 2011, the European Union Labour Force Survey (EU-LFS) included an ad hoc module (AHM) on employment of disabled people. The module consisted of 11 variables dealing with: Health problems and difficulties in basic activities;Limitations in work caused by health problems/difficulties in basic activities;Special assistance needed or used by people with health problems/difficulties in basic activities;Limitation in work because of other reasons. On the basis of how the module was operationalised, the following two main definitions for disability were considered for presenting the results: Disabled persons = People having a basic activity difficulty (such as seeing, hearing, walking, communicating);Disabled persons = People having a work limitation caused by a longstanding health condition and/or a basic activity difficulty. 32 countries have implemented this module: the EU 28 Member States plus Turkey, Iceland, Norway and Switzerland. The Norwegian data are not disseminated because the AHM questionnaire in Norway only partly complies with the Commission Regulation (EU) No 317/2010 and consequently, the data are incomplete and partly comparable. Missing values, don't know and refusal answers are not considered in the calculations. It means the indicators have been worked out on the respondents and validated answers only.

The folder 'population by educational attainment level (edat1)' presents data on the highest level of education successfully completed by the individuals of a given population. The folder 'transition from education to work (edatt)' covers data on young people neither in employment nor in education and training – NEET, early leavers from education and training and the labour status of young people by years since completion of highest level of education. The data shown are calculated as annual averages of quarterly EU Labour Force Survey data (EU-LFS). Up to the reference year 2008, the data source (EU-LFS) is, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator, including the following:correction of the main breaks in the LFS series,estimation of the missing values, i.e. in case of missing quarters, annual results and EU aggregates are estimated using adjusted quarterly national labour force survey data or interpolations of the EU-LFS data with reference to the available quarter(s). Details on the adjustments are available in CIRCABC. The adjustments are applied in the following online tables:Population by educational attainment level (edat1) - Population by educational attainment level, sex and age (%) - main indicators (edat_lfse_03) - Population aged 25-64 by educational attainment level, sex and NUTS 2 regions (%) (edat_lfse_04) - Population aged 30-34 by educational attainment level, sex and NUTS 2 regions (%) (edat_lfse_12) (Other tables shown in the folder 'population by educational attainment level (edat1)' are not adjusted and therefore the results in these tables might differ).Young people by educational and labour status (incl. neither in employment nor in education and training - NEET) (edatt0) – all tablesEarly leavers from education and training (edatt1) – all tablesLabour status of young people by years since completion of highest level of education (edatt2) – all tables LFS ad-hoc module data available in the folder 'transition from education to work (edatt)' are not adjusted.

The folder 'population by educational attainment level (edat1)' presents data on the highest level of education successfully completed by the individuals of a given population. The folder 'transition from education to work (edatt)' covers data on young people neither in employment nor in education and training – NEET, early leavers from education and training and the labour status of young people by years since completion of highest level of education. The data shown are calculated as annual averages of quarterly EU Labour Force Survey data (EU-LFS). Up to the reference year 2008, the data source (EU-LFS) is, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator, including the following:correction of the main breaks in the LFS series,estimation of the missing values, i.e. in case of missing quarters, annual results and EU aggregates are estimated using adjusted quarterly national labour force survey data or interpolations of the EU-LFS data with reference to the available quarter(s). Details on the adjustments are available in CIRCABC. The adjustments are applied in the following online tables:Population by educational attainment level (edat1) - Population by educational attainment level, sex and age (%) - main indicators (edat_lfse_03) - Population aged 25-64 by educational attainment level, sex and NUTS 2 regions (%) (edat_lfse_04) - Population aged 30-34 by educational attainment level, sex and NUTS 2 regions (%) (edat_lfse_12) (Other tables shown in the folder 'population by educational attainment level (edat1)' are not adjusted and therefore the results in these tables might differ).Young people by educational and labour status (incl. neither in employment nor in education and training - NEET) (edatt0) – all tablesEarly leavers from education and training (edatt1) – all tablesLabour status of young people by years since completion of highest level of education (edatt2) – all tables LFS ad-hoc module data available in the folder 'transition from education to work (edatt)' are not adjusted.

Population by educational attainment level presents data on the highest level of education successfully completed by the individuals of a given population. Transition from education to work covers data on young people neither in employment nor in education and training – NEET, early leavers from education and training and the labour status of young people by years since completion of highest level of education. The data shown are calculated as annual averages of quarterly EU Labour Force Survey data (EU-LFS). Up to the reference year 2008, the data source (EU-LFS) is, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator, including the following:correction of the main breaks in the LFS series,estimation of the missing values, i.e. in case of missing quarters, annual results and EU aggregates are estimated using adjusted quarterly national labour force survey data or interpolations of the EU-LFS data with reference to the available quarter(s). Details on the adjustments are available in CIRCABC. The adjustments are applied in the following online tablesPopulation by educational attainment level (edat1)   - Population with lower secondary education attainment by sex and age (edat_lfse_05) - Population with upper secondary education attainment by sex and age (edat_lfse_06) - Population with tertiary education attainment by sex and age (edat_lfse_07) - Population with upper secondary or tertiary education attainment by sex and age (edat_lfse_08) - Population aged 25-64 with lower secondary education attainment by sex and NUTS 2 regions (edat_lfse_09) - Population aged 25-64 with upper secondary education attainment by sex and NUTS 2 regions (edat_lfse_10) - Population aged 25-64 with tertiary education attainment by sex and NUTS 2 regions (edat_lfse_11) - Population aged 30-34 with tertiary education attainment by sex and NUTS 2 regions (edat_lfse_12) - Population aged 25-64 with upper secondary or tertiary education attainment by sex and NUTS 2 regions (edat_lfse_13) (Other tables shown in the folder 'population by educational attainment level (edat1)' are not adjusted and therefore the results in these tables might differ).Young people by educational and labour status (incl. neither in employment nor in education and training - NEET) (edatt0) – all tablesEarly leavers from education and training (edatt1) – all tablesLabour status of young people by years since completion of highest level of education (edatt2) – all tables  LFS ad-hoc module data available in the folder 'transition from education to work (edatt)' are not adjusted.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

The source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

The source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

Percentage of self-employed without employees as a share of all persons in employment.

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The ad-hoc module "young people on the labour market" provides supplementary information on the correlation between work-based learning and labour market outcomes.

The ad-hoc module "young people on the labour market" provides supplementary information on the correlation between work-based learning and labour market outcomes.

The ad-hoc module "young people on the labour market" provides supplementary information on the correlation between work-based learning and labour market outcomes.

The ad-hoc module "young people on the labour market" provides supplementary information on the correlation between work-based learning and labour market outcomes.

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The section 'LFS series - detailed quarterly survey results' reports detailed quarterly results going beyond the EU-LFS main aggregates, which have a separate data domain and some methodological differences. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self-employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, population in employment working during unsocial hours, working time, total unemployment, inactivity and quality of employment. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed quarterly survey results' reports detailed quarterly results going beyond the EU-LFS main aggregates, which have a separate data domain and some methodological differences. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self-employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, population in employment working during unsocial hours, working time, total unemployment, inactivity and quality of employment. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

Percentage of persons with more than one job as a share of all persons in employment. The indicator refers to persons who had more than one job or business during the reference week, not due to change of job or business (persons having changed job or business during the reference week are not considered as having more than one job).

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The indicator, 'employed persons with a second job' refers only to persons with more than one job at the same time. Consequently, persons having changed job during the reference week are not covered.

The ICT education statistics make part of the domain ICT training, which in its term is one of the domains in the wider concept of Digital skills. ICT education indicators are constructed using the secondary statistical approach. This approach has a virtue of ensuring cost-efficient and high-quality data production. At the same time, this approach has limited options for designing new indicators, as well as for control over data quality and over data release timing. ICT education indicators are based on the microdata from the EU Labour Force Survey (EU-LFS). For this reason, the EU-LFS reference metadata need to be consulted for all questions related to the underlying primary source data. Following the underlying EU-LFS microdata, the ICT education indicators set the lower bound on the age at 15 years. The upper age bound is set at 74 years to align these data with other indicator on digital skills derived from the Community Survey on ICT Usage in Households and by Individuals. ICT education indicators are presented in four tables:Employed and unemployed persons with ICT education (isoc_ski_itemp)Employed persons with ICT education by sex (isoc_ski_itsex)Employed persons with ICT education by educational attainment level (isoc_ski_itedu)Employed persons with ICT education by age (isoc_ski_itage) The first table (isoc_ski_itemp) describes persons with ICT education in labour force by their employment status. The rest of tables (isoc_ski_itsex, isoc_ski_itedu and isoc_ski_itage) present different breakdowns of the persons with ICT education in employment. Each indicator is presented in the country/year dimensions and is measured in absolute (in 1000s) and relative (in %) terms. Data cover all years starting from 2004 until the latest year available. Following the release practice of the EU-LFS, the publication year is calculated as (Y+1), with Y being the reference year. Yearly data release depends on the EU-LFS release practice and normally takes place in April-May. Data for all indicators are regularly updated and revised to incorporate the latest revisions made in the source data, usually once a week.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

Percentage of women in the occupational group of managerial positions as a share of all employed persons in that group. The occupational group of managerial positions is defined as the ISCO major group 1.

The main aim of 2017 ad-hoc module is to provide information on the self-employed and on persons in an ambivalent professional status (at the border between employment and self-employment). The module includes 11 variables, split in 3 sub-modules. Sub-module 1: Economically dependent self-employed The first sub-module aims to measure the degree of economic/organisational dependency of the self-employed, in terms of the number of clients and the percentage of income coming from a client as well as in terms of control over working hours. This sub-module includes 2 variables: MAINCLNT: Economic dependencyWORKORG: Organisational dependencySub-module 2: Working conditions for self-employed The aim of the second sub-module is to investigate the working conditions of the self-employed, like working with partners or using employees. It also collects factors that motivated or forced a person to become self-employed, as well as the main difficulty they face working as self-employed. This sub-module includes 5 variables: REASSE: Main reason for becoming self-employed               SEDIFFIC: Main difficulty as self-employed                         REASNOEM: Main reason for not having employees                        BPARTNER:  Working with business partners                                    PLANEMPL:  Planning hiring of employees or subcontracting           Sub-module 3: Comparing employees and self-employed The third sub-module targets the comparison between self-employed, employees and family workers in terms of job satisfaction and autonomy. It also gathers information on the preferred professional status. This sub-module includes 4 variables: JBSATISFQ:  Job satisfaction                                                AUTONOMY: Job autonomy                                                PREFSTAP: Preferred professional status in the main job      OBSTACSE: Main reason for not becoming self-employed  Detailed information on the relevant methodology for the ad-hoc module (including the Commission regulation and explanatory notes) as well as documentation from each participating country (national questionnaires and interviewers instructions) can be found on EU-LFS (Statistics Explained) - Ad-hoc modules.

The folder 'population by educational attainment level (edat1)' presents data on the highest level of education successfully completed by the individuals of a given population. The folder 'transition from education to work (edatt)' covers data on young people neither in employment nor in education and training – NEET, early leavers from education and training and the labour status of young people by years since completion of highest level of education. The data shown are calculated as annual averages of quarterly EU Labour Force Survey data (EU-LFS). Up to the reference year 2008, the data source (EU-LFS) is, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator, including the following: correction of the main breaks in the LFS series,estimation of the missing values, i.e. in case of missing quarters, annual results and EU aggregates are estimated using adjusted quarterly national labour force survey data or interpolations of the EU-LFS data with reference to the available quarter(s). Details on the adjustments are available in CIRCABC. The adjustments are applied in the following online tables: Population by educational attainment level (edat1) - Population by educational attainment level, sex and age (%) - main indicators (edat_lfse_03) - Population aged 25-64 by educational attainment level, sex and NUTS 2 regions (%) (edat_lfse_04) - Population aged 30-34 by educational attainment level, sex and NUTS 2 regions (%) (edat_lfse_12) (Other tables shown in the folder 'population by educational attainment level (edat1)' are not adjusted and therefore the results in these tables might differ).Young people by educational and labour status (incl. neither in employment nor in education and training - NEET) (edatt0) – all tablesEarly leavers from education and training (edatt1) – all tablesLabour status of young people by years since completion of highest level of education (edatt2) – all tables LFS ad-hoc module data available in the folder 'transition from education to work (edatt)' are not adjusted. The folder 'transition from education to work (edatt)' also presents one table with quarterly NEET data for the age group 15-24 (lfsi_neet_q). Deviating from the NEET indicator calculation as provided in 3.4, the denominator in this table is the total population of the same age group and sex which explains differences in results. For further information, see the ESMS on "Unemployment - LFS adjusted series".

The folder 'population by educational attainment level (edat1)' presents data on the highest level of education successfully completed by the individuals of a given population. The folder 'transition from education to work (edatt)' covers data on young people neither in employment nor in education and training – NEET, early leavers from education and training and the labour status of young people by years since completion of highest level of education. The data shown are calculated as annual averages of quarterly EU Labour Force Survey data (EU-LFS). Up to the reference year 2008, the data source (EU-LFS) is, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator, including the following:correction of the main breaks in the LFS series,estimation of the missing values, i.e. in case of missing quarters, annual results and EU aggregates are estimated using adjusted quarterly national labour force survey data or interpolations of the EU-LFS data with reference to the available quarter(s). Details on the adjustments are available in CIRCABC. The adjustments are applied in the following online tables:Population by educational attainment level (edat1) - Population by educational attainment level, sex and age (%) - main indicators (edat_lfse_03) - Population aged 25-64 by educational attainment level, sex and NUTS 2 regions (%) (edat_lfse_04) - Population aged 30-34 by educational attainment level, sex and NUTS 2 regions (%) (edat_lfse_12) (Other tables shown in the folder 'population by educational attainment level (edat1)' are not adjusted and therefore the results in these tables might differ).Young people by educational and labour status (incl. neither in employment nor in education and training - NEET) (edatt0) – all tablesEarly leavers from education and training (edatt1) – all tablesLabour status of young people by years since completion of highest level of education (edatt2) – all tables LFS ad-hoc module data available in the folder 'transition from education to work (edatt)' are not adjusted.

Results from the 2010 LFS (Labour Force Survey) ad hoc module on the reconciliation between work and family life. The aims of the module is to establish how far persons participate in the labour force as they wish and if not, whether the reasons are connected with a lack of suitable care services for children and dependant persons: 1. identification of care responsibilities (children and dependants) 2. analysis of the consequences on labour market participation taking into account the options and constraints given 3. in case of constraints, identification of those linked with the lack or unsuitability of care services A further aim is to analyse the degree of flexibility offered at work in terms of reconciliation with family life as well as to estimate how often career breaks occur and how far leave of absence is taken.

Results from the 2010 LFS (Labour Force Survey) ad hoc module on the reconciliation between work and family life. The aims of the module is to establish how far persons participate in the labour force as they wish and if not, whether the reasons are connected with a lack of suitable care services for children and dependant persons: 1. identification of care responsibilities (children and dependants) 2. analysis of the consequences on labour market participation taking into account the options and constraints given 3. in case of constraints, identification of those linked with the lack or unsuitability of care services A further aim is to analyse the degree of flexibility offered at work in terms of reconciliation with family life as well as to estimate how often career breaks occur and how far leave of absence is taken.

The ad-hoc module "labour market situation of migrants and their immediate descendants" aimed at comparing the situation on the labour market for first generation immigrants, second generation immigrants, and nationals, and further to analyse the factors affecting the integration in and adaptation to the labour market.

The ad-hoc module "young people on the labour market" provides supplementary information on the correlation between work-based learning and labour market outcomes.

Results from the 2010 LFS (Labour Force Survey) ad hoc module on the reconciliation between work and family life. The aims of the module is to establish how far persons participate in the labour force as they wish and if not, whether the reasons are connected with a lack of suitable care services for children and dependant persons: 1. identification of care responsibilities (children and dependants) 2. analysis of the consequences on labour market participation taking into account the options and constraints given 3. in case of constraints, identification of those linked with the lack or unsuitability of care services A further aim is to analyse the degree of flexibility offered at work in terms of reconciliation with family life as well as to estimate how often career breaks occur and how far leave of absence is taken.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

Percentage of employees who have flexible work schedule as a share of all employees. Flexible means that employees can decide on their work schedule, at least to a certain extent, like start and end of working day.

The annual Business demography data collection covers variables which explain the characteristics and demography of the business population. The methodology allows for the production of data on enterprise births (and deaths), that is, enterprise creations (cessations) that amount to the creation (dissolution) of a combination of production factors and where no other enterprises are involved. In other words, enterprises created or closed solely as a result of e.g. restructuring, merger or break-up are not considered. The data are drawn from business registers, although some countries improve the availability of data on employment and turnover by integrating other sources. Until 2010 reference year the harmonised data collection is carried out to satisfy the requirements for the Structural Indicators, used for monitoring progress of the Lisbon process, regarding business births, deaths and survival. Currently, business demography delivers key information for policy decision-making and for the indicators to support the Europe 2020 strategy. It also provides key data for the joint OECD-Eurostat "Entrepreneurship Indicators Programme". In summary, the collected indicators are as follows:Population of active enterprisesNumber of enterprise birthsNumber of enterprise survivals up to five yearsNumber of enterprise deathsRelated variables on employmentDerived indicators such as birth rates, death rates, survival rates and employment sharesAn additional set of indicators on high-growth enterprises and 'gazelles' (high-growth enterprises that are up to five years old) The complete list of the basic variables, delivered from the data providers (National Statistical Institutes) and the derived indicators, calculated by Eurostat, is attached in the Annexes of this document (see Business demography indicators).  Geographically EU Member States and EFTA countries are covered. In practice not all Member States have participated in the first harmonised data collection exercises. The methodology laid down in the Eurostat-OECD Manual on Business Demography Statistics  is followed closely by most of the countries (see Country specific notes in the Annexes).

Regional accounts are a regional specification of the national accounts and therefore based on the same concepts and definitions as national accounts (see domain nama10). The main specific regional issues are addressed in chapter 13 of ESA2010, but not practically specified. For practical rules and recommendations on sources and methods see the publication "Manual on regional accounts methods": http://ec.europa.eu/eurostat/en/web/products-manuals-and-guidelines/-/KS-GQ-13-001 . Gross domestic product (GDP) at market prices is the final result of the production activity of resident producer units. It can be defined in three ways: 1. Output approach GDP is the sum of gross value added of the various institutional sectors or the various industries plus taxes and less subsidies on products (which are not allocated to sectors and industries). It is also the balancing item in the total economy production account. 2. Expenditure approach GDP is the sum of final uses of goods and services by resident institutional units (final consumption expenditure and gross capital formation), plus exports and minus imports of goods and services. At regional level the expenditure approach cannot be used in the EU, because there is no data on regional exports and imports.  3. Income approach GDP is the sum of uses in the total economy generation of income account: compensation of employees plus gross operating surplus and mixed income plus taxes on products less subsidies plus consumption of fixed capital. The different measures for the regional GDP are absolute figures in € and Purchasing Power Standards (PPS), figures per inhabitant and relative data compared to the EU28 average.

The source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview

Regional accounts are a regional specification of the national accounts and therefore based on the same concepts and definitions as national accounts (see domain nama10). The main specific regional issues are addressed in chapter 13 of ESA2010, but not practically specified. For practical rules and recommendations on sources and methods see the publication "Manual on regional accounts methods": http://ec.europa.eu/eurostat/en/web/products-manuals-and-guidelines/-/KS-GQ-13-001 . Gross domestic product (GDP) at market prices is the final result of the production activity of resident producer units. It can be defined in three ways: 1. Output approach GDP is the sum of gross value added of the various institutional sectors or the various industries plus taxes and less subsidies on products (which are not allocated to sectors and industries). It is also the balancing item in the total economy production account. 2. Expenditure approach GDP is the sum of final uses of goods and services by resident institutional units (final consumption expenditure and gross capital formation), plus exports and minus imports of goods and services. At regional level the expenditure approach cannot be used in the EU, because there is no data on regional exports and imports.  3. Income approach GDP is the sum of uses in the total economy generation of income account: compensation of employees plus gross operating surplus and mixed income plus taxes on products less subsidies plus consumption of fixed capital. The different measures for the regional GDP are absolute figures in € and Purchasing Power Standards (PPS), figures per inhabitant and relative data compared to the EU28 average.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU, the United Kingdom, EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU-LFS (Statistics Explained) webpage. The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However, many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation by territorial typologies, i.e. urban-rural, metropolitan, coastal, mountain, borders and island typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

National accounts are a coherent and consistent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. Eurostat publishes annual and quarterly national accounts, annual and quarterly sector accounts as well as supply, use and input-output tables, which are each presented with associated metadata. Even though consistency checks are a major aspect of data validation, temporary (usually limited) inconsistencies between datasets may occur, mainly due to vintage effects. Annual national accounts are compiled in accordance with the European System of Accounts - ESA 2010 as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013.   The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. Further information (including actual communications) is presented on the Eurostat website. The domain consists of the following collections:   1. Main GDP aggregates: main components from the output, expenditure and income side, expenditure breakdowns by durability and exports and imports by origin. <

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The ad-hoc module "labour market situation of migrants and their immediate descendants" aimed at comparing the situation on the labour market for first generation immigrants, second generation immigrants, and nationals, and further to analyse the factors affecting the integration in and adaptation to the labour market.

The source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

Employment consists of both employees and self-employed, who are engaged in some productive activity that falls within the production boundary of the system (ESA 2010, 11.11). Employment covers employees and self-employed working for production units resident on the economic territory (i.e. the domestic employment concept). Employment is measured in number of persons without distinction according to full-time or part-time work. Growth rates with respect to the previous quarter (Q/Q-1) are calculated from seasonally adjusted figures while growth rates with respect to the same quarter of the previous year (Q/Q-4) are calculated from non-seasonal adjusted data. The following countries provide employment data seasonally adjusted, without calendar adjustment: CZ, GR, FR, MT, PL, PT, SK and CH. The remaining countries provide employment data seasonally and calendar adjusted.

Employment consists of both employees and self-employed, who are engaged in some productive activity that falls within the production boundary of the system (ESA 2010, 11.11). Employment covers employees and self-employed working for production units resident on the economic territory (i.e. the domestic employment concept). Employment is measured in number of persons without distinction according to full-time or part-time work. The following countries provide employment data seasonally adjusted, without calendar adjustment: CZ, GR, FR, MT, PL, PT, SK and CH. The remaining countries provide employment data seasonally and calendar adjusted.

The source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview

The section 'LFS series - detailed quarterly survey results' reports detailed quarterly results going beyond the EU-LFS main aggregates, which have a separate data domain and some methodological differences. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

The source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The 'LFS main indicators' section presents a selection of the main statistics on the labour market. They encompass indicators of activity employment and unemployment. Those indicators are based on the results of the European Labour Force Survey (EU-LFS), in few cases integrated with data sources like national accounts employment or registered unemployment. As a result of the application of adjustments, corrections and reconciliation of EU Labour Force Survey (EU-LFS), 'LFS main indicators' is the most complete and reliable collection of employment and unemployment data available in the sub-domain ' Employment and unemployment'. The EU-LFS data used for 'LFS main indicators' are, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator.  The most common adjustments cover: - correction of the main breaks in the LFS series - estimation of the missing values, (i.e. in case of missing quarters, annual results and EU aggregates are estimated using adjusted quarterly national labour force survey data or interpolations of the EU Labour Force Survey data with reference to the available quarter(s)) - reconciliations of the LFS data with other sources, mainly National Accounts (for Employment growth and activity branches) and national statistics on monthly unemployment (for Harmonised unemployment series). - for a number of indicators (employment, activity, unemployment, supplementary indicators) seasonally adjusted data are available Those adjustments may produce some differences between data published under 'LFS main indicators' and 'LFS series - Detailed survey results', particularly for back data. For the most recent years these two series converge, due to the implementation of a continuous quarterly survey and the improved quality of the data. This page focuses on the particularities of 'LFS main indicators' in general. There are special pages for indicators 'employment growth', 'population in jobless households', 'average exit age of labour market' and 'education indicators: life-long learning, early school leavers and youth education attainment level. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The indicator shows the percentage distribution of persons in employment aged 20-64 by job duration, i.e. for how many months they have been in their current job. Persons in employment are those who, during the reference week, performed work, even for just one hour a week, for pay, profit or family gain or who were not at work but had a job or business from which they were temporarily absent because of something like illness, holiday, industrial dispute or education and training. The indicator is based on the EU Labour Force Survey.

The indicator measures the employment in high- and medium-high technology manufacturing sectors and in knowledge-intensive service sectors as a share of total employment. Data source is the European Labour force survey (LFS). The definition of high- and medium-high technology manufacturing sectors and of knowledge-intensive services is based on a selection of relevant items of NACE Rev. 2 on 2-digit level and is oriented on the ratio of highly qualified working in these areas.

The data shows the employment in high-tech sectors (code HTC) as a percentage of total employment. The data are aggregated according to the sectoral approach at NACE Rev.2 on 2-digit level and is oriented on the ratio of highly qualified working in these areas.

'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech patents are defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition). Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech patents are defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition). Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech patents are defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition). Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech patents are defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition). Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech patents are defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition). Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

This dataset provides estimates of the production, value added, exports and employment of the environmental goods and services sector (EGSS). The EGSS is the part of the economy that generate environmental products, i.e. those produced for the purpose of environmental protection and resource management. Environmental protection includes all activities and actions which have as their main purpose the prevention, reduction and elimination of pollution and of any other degradation of the environment. Those activities and actions include all measures taken in order to restore the environment after it has been degraded. Resource management includes the preservation, maintenance and enhancement of the stock of natural resources and therefore the safeguarding of those resources against depletion. The EGSS accounts are produced in accordance with the statistical concepts and definitions set out in the system of environmental economic accounting 2012 – central framework (SEEA CF 2012, see annex). Datasets env_ac_egss1 and env_ac_egss2 consist of country data produced by the Member States, who transmit the data to Eurostat and further disseminates it. The EU estimates in datasets env_ac_egss1, env_ac_egss2 and env_ac_egss3 are produced by Eurostat not as a sum of available countries but using methods documented in the Eurostat EGSS practical guide (see methodology page) and data sources publicly available. In addition, Eurostat produces output and gross value added volume estimates, i.e. discounting changes in prices, for all countries published in dataset env_ac_egss2.

The indicator presents employment rates by age. The employment rate is calculated by dividing the number of persons in employment in a given age group by the total population of the same age group. The indicator is based on the EU Labour Force Survey.

% of age group 20-64 yearsThe indicator is calculated by dividing the number of employed people within the age group 20-64 years having attained a specific level of education by the total population of the same age group. The educational attainment level is coded according to the International Standard Classification of Education (ISCED). Data until 2013 are classified according to ISCED 1997 and data as from 2014 according to ISCED 2011.- Less than primary, primary and lower secondary education (ISCED levels 0-2) -Upper secondary and post-secondary non-tertiary education (ISCED levels 3 and 4) -Tertiary education (ISCED levels 5-8) (ISCED 1997: levels 5 and 6) The indicator is based on the EU Labour Force Survey (LFS), covering the population living in private households. Employment rate (total, females, males): The number of persons (females, males) aged 20-64 in employment as a share of the total population (females, males) of the same age group.

The indicator is calculated by dividing the number of employed people within the age group 20-64 years having attained a specific level of education by the total population of the same age group and with the same educational attainment level. The educational attainment level is coded according to the International Standard Classification of Education (ISCED). Data until 2013 are classified according to ISCED 1997 and data as from 2014 according to ISCED 2011. - Less than primary, primary and lower secondary education (ISCED levels 0-2) -Upper secondary and post-secondary non-tertiary education (ISCED levels 3 and 4) -Tertiary education (ISCED levels 5-8) (ISCED 1997: levels 5 and 6) The indicator is based on the EU Labour Force Survey (LFS), covering the population living in private households.

The employment rate is calculated by dividing the number of persons aged 20 to 64 in employment by the total population of the same age group. The indicator is based on the EU Labour Force Survey. The survey covers the entire population living in private households and excludes those in collective households such as boarding houses, halls of residence and hospitals. Employed population consists of those persons who during the reference week did any work for pay or profit for at least one hour, or were not working but had jobs from which they were temporarily absent. (i) More information on national targets can be found here

The ad-hoc module "young people on the labour market" provides supplementary information on the correlation between work-based learning and labour market outcomes.

The ad-hoc module "labour market situation of migrants and their immediate descendants" aimed at comparing the situation on the labour market for first generation immigrants, second generation immigrants, and nationals, and further to analyse the factors affecting the integration in and adaptation to the labour market.

The employment rate of older workers is calculated by dividing the number of persons in employment and aged 55 to 64 by the total population of the same age group. The indicator is based on the EU Labour Force Survey. The survey covers the entire population living in private households and excludes those in collective households such as boarding houses, halls of residence and hospitals. Employed population consists of those persons who during the reference week did any work for pay or profit for at least one hour, or were not working but had jobs from which they were temporarily absent.

The employment rate of older workers is calculated by dividing the number of persons in employment and aged 55 to 64 by the total population of the same age group. The indicator is based on the EU Labour Force Survey.

Regional (NUTS level 2) employment rate of the age group 15-64 represents employed persons aged 15-64 as a percentage of the population of the same age group. The indicator is based on the EU Labour Force Survey. The survey covers the entire population living in private households and excludes those in collective households such as boarding houses, halls of residence and hospitals. The employed persons are those aged 15-64, who during the reference week did any work for pay, profit or family gain for at least one hour, or were not at work but had a job or business from which they were temporarily absent.

Regional (NUTS level 2) employment rate of the age group 20-64 represents employed persons aged 20-64 as a percentage of the population of the same age group. The indicator is based on the EU Labour Force Survey. The survey covers the entire population living in private households and excludes those in collective households such as boarding houses, halls of residence and hospitals. The employed persons are those aged 20-64, who during the reference week did any work for pay, profit or family gain for at least one hour, or were not at work but had a job or business from which they were temporarily absent.

Regional (NUTS level 2) employment rate of the age group 55-64 represents employed persons aged 55-64 as a percentage of the population of the same age group. Employed persons are those who, during the reference week, did any work for pay, profit or family gain for at least one hour, or were not at work but had a job or business from which they were temporarily absent.

The employment rate of the total population is calculated by dividing the number of person aged 20 to 64 in employment by the total population of the same age group. The employment rate of men is calculated by dividing the number of men aged 20 to 64 in employment by the total male population of the same age group. The employment rate of women is calculated by dividing the number of women aged 20 to 64 in employment by the total female population of the same age group. The indicators are based on the EU Labour Force Survey.

The source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed quarterly survey results' reports detailed quarterly results going beyond the EU-LFS main aggregates, which have a separate data domain and some methodological differences. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

The source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

The indicator measures the employment rates of persons aged 20 to 34 fulfilling the following conditions: first, being employed according to the ILO definition, second, having attained at least upper secondary education (ISCED 3) as the highest level of education, third, not having received any education or training in the four weeks preceding the survey and four, having successfully completed their highest educational attainment 1, 2 or 3 years before the survey. The indicator is calculated based on data from the EU Labour Force Survey (EU-LFS).

The folder 'population by educational attainment level (edat1)' presents data on the highest level of education successfully completed by the individuals of a given population. The folder 'transition from education to work (edatt)' covers data on young people neither in employment nor in education and training – NEET, early leavers from education and training and the labour status of young people by years since completion of highest level of education. The data shown are calculated as annual averages of quarterly EU Labour Force Survey data (EU-LFS). Up to the reference year 2008, the data source (EU-LFS) is, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator, including the following:correction of the main breaks in the LFS series,estimation of the missing values, i.e. in case of missing quarters, annual results and EU aggregates are estimated using adjusted quarterly national labour force survey data or interpolations of the EU-LFS data with reference to the available quarter(s). Details on the adjustments are available in CIRCABC. The adjustments are applied in the following online tables:Population by educational attainment level (edat1) - Population by educational attainment level, sex and age (%) - main indicators (edat_lfse_03) - Population aged 25-64 by educational attainment level, sex and NUTS 2 regions (%) (edat_lfse_04) - Population aged 30-34 by educational attainment level, sex and NUTS 2 regions (%) (edat_lfse_12) (Other tables shown in the folder 'population by educational attainment level (edat1)' are not adjusted and therefore the results in these tables might differ).Young people by educational and labour status (incl. neither in employment nor in education and training - NEET) (edatt0) – all tablesEarly leavers from education and training (edatt1) – all tablesLabour status of young people by years since completion of highest level of education (edatt2) – all tables LFS ad-hoc module data available in the folder 'transition from education to work (edatt)' are not adjusted.

The folder 'population by educational attainment level (edat1)' presents data on the highest level of education successfully completed by the individuals of a given population. The folder 'transition from education to work (edatt)' covers data on young people neither in employment nor in education and training – NEET, early leavers from education and training and the labour status of young people by years since completion of highest level of education. The data shown are calculated as annual averages of quarterly EU Labour Force Survey data (EU-LFS). Up to the reference year 2008, the data source (EU-LFS) is, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator, including the following:correction of the main breaks in the LFS series,estimation of the missing values, i.e. in case of missing quarters, annual results and EU aggregates are estimated using adjusted quarterly national labour force survey data or interpolations of the EU-LFS data with reference to the available quarter(s). Details on the adjustments are available in CIRCABC. The adjustments are applied in the following online tables:Population by educational attainment level (edat1) - Population by educational attainment level, sex and age (%) - main indicators (edat_lfse_03) - Population aged 25-64 by educational attainment level, sex and NUTS 2 regions (%) (edat_lfse_04) - Population aged 30-34 by educational attainment level, sex and NUTS 2 regions (%) (edat_lfse_12) (Other tables shown in the folder 'population by educational attainment level (edat1)' are not adjusted and therefore the results in these tables might differ).Young people by educational and labour status (incl. neither in employment nor in education and training - NEET) (edatt0) – all tablesEarly leavers from education and training (edatt1) – all tablesLabour status of young people by years since completion of highest level of education (edatt2) – all tables LFS ad-hoc module data available in the folder 'transition from education to work (edatt)' are not adjusted.

The aim of this section is to provide comparable statistics and indicators on education in the 27 Member States of the European Union, at the regional level NUTS 2. In order to facilitate comparison between countries, data from each Member State are allocated to the various education levels of the International Standard Classification of Education (ISCED), UNESCO 1997.

Maastricht criterion bond yields (mcby): definition used for the convergence criterion for EMU for long-term interest rates (central government bond yields on the secondary market, gross of tax, with around 10 years' residual maturity).

Maastricht criterion bond yields (mcby) are long-term interest rates, used as a convergence criterion for the European Monetary Union, based on the Maastricht Treaty.

Maastricht criterion bond yields (mcby) are long-term interest rates, used as a convergence criterion for the European Monetary Union, based on the Maastricht Treaty

Maastricht criterion bond yields (mcby) are long-term interest rates, used as a convergence criterion for the European Monetary Union, based on the Maastricht Treaty

Maastricht criterion bond yields (mcby) are long-term interest rates, used as a convergence criterion for the European Monetary Union, based on the Maastricht Treaty

6.1. Reference area

Eurostat Dataset Id:enpr_ecnagdp The domain focuses on the Eastern European Neighbourhood Policy countries (ENP): Armenia (AM), Azerbaijan (AZ), Belarus (BY), Georgia (GE), Moldova (MD) and the Ukraine (UA). Data are provided for 200 to 300 indicators.

 Foreign Direct Investment (FDI) encompasses all kind of cross-border investment made by an entity resident in one economy (direct investor) to acquire a lasting interest in an enterprise operating in another economy (direct investment enterprise). FDI is one of the five main functional categories of investment used in international accounts to classify either the Internal Investment Positions (IIP) or the Balance of Payment (BOP) statements of a given economy (vis-à-vis the rest of the world). Foreign Direct Investment positions show at a point in time (generally, end of a reference year) the value of financial direct investment assets of residents of an economy on non-residents, and financial direct investment liabilities of residents of an economy to non-resident. The net FDI position is the difference between assets and liabilities, which is also equivalent (under the directional principle presentation) to the difference between FDI positions abroad and in the reporting economy. The net FDI position represents either a net FDI claim or a net FDI liability to the rest of the world.        Foreign direct investment transactions summarize all economic direct investment interactions between the residents and the non-residents during a given period. Two types of FDI transactions can be identified (within the BOP framework) according to the economic meaning they convey: FDI income is a distributive transaction showing amounts payable and receivable between resident and non-resident entities in return for providing financial direct investment assets to the rest of the world, or incurring direct investment liabilities vis-à-vis the rest of the world.FDI flows refer to financial transactions showing the net acquisition or disposal of financial assets and liabilities involved in direct investment relationships.FDI positions, FDI income and FDI flows are disseminated by Eurostat together with estimated EU FDI aggregates (directly produced by Eurostat).  Other FDI changes that are not transaction changes, such as volume, value or prices changes, are not treated by Eurostat under the scope of annual FDI statistics. Annual FDI data are disseminated by Eurostat according to the directional principle (see sub section 3.4 below). The geographical allocation is made according to the economic residence of the immediate direct investor or immediate direct investment company (immediate counterparts). FDI data classified according to ultimate investor or host economy are not yet available at Eurostat (see 12.1).  International Guides recommend the classification of FDI data both according to the activity of the direct investor and the activity of the direct investment enterprise. In practice, it is very difficult for national compilers to have both classifications. In that case, the recommended classification by activity is that of the direct investment enterprise. On the outward side, national compilers are not always able to classify their FDI data according to the activity of the direct investment enterprise. In that case, the classification used as a proxy is the activity of the direct investor.  Alongside with International Trade in Services Statistics (ITSS) and Foreign Affiliates Trade Statistics (FATS), FDI data are relevant to monitor the overall effectiveness and competitiveness of different economies in the globalised world.

 Foreign Direct Investment (FDI) encompasses all kind of cross-border investment made by an entity resident in one economy (direct investor) to acquire a lasting interest in an enterprise operating in another economy (direct investment enterprise). FDI is one of the five main functional categories of investment used in international accounts to classify either the Internal Investment Positions (IIP) or the Balance of Payment (BOP) statements of a given economy (vis-à-vis the rest of the world). Foreign Direct Investment positions show at a point in time (generally, end of a reference year) the value of financial direct investment assets of residents of an economy on non-residents, and financial direct investment liabilities of residents of an economy to non-resident. The net FDI position is the difference between assets and liabilities, which is also equivalent (under the directional principle presentation) to the difference between FDI positions abroad and in the reporting economy. The net FDI position represents either a net FDI claim or a net FDI liability to the rest of the world.        Foreign direct investment transactions summarize all economic direct investment interactions between the residents and the non-residents during a given period. Two types of FDI transactions can be identified (within the BOP framework) according to the economic meaning they convey: FDI income is a distributive transaction showing amounts payable and receivable between resident and non-resident entities in return for providing financial direct investment assets to the rest of the world, or incurring direct investment liabilities vis-à-vis the rest of the world.FDI flows refer to financial transactions showing the net acquisition or disposal of financial assets and liabilities involved in direct investment relationships.FDI positions, FDI income and FDI flows are disseminated by Eurostat together with estimated EU FDI aggregates (directly produced by Eurostat).  Other FDI changes that are not transaction changes, such as volume, value or prices changes, are not treated by Eurostat under the scope of annual FDI statistics. Annual FDI data are disseminated by Eurostat according to the directional principle (see sub section 3.4 below). The geographical allocation is made according to the economic residence of the immediate direct investor or immediate direct investment company (immediate counterparts). FDI data classified according to ultimate investor or host economy are not yet available at Eurostat (see 12.1).  International Guides recommend the classification of FDI data both according to the activity of the direct investor and the activity of the direct investment enterprise. In practice, it is very difficult for national compilers to have both classifications. In that case, the recommended classification by activity is that of the direct investment enterprise. On the outward side, national compilers are not always able to classify their FDI data according to the activity of the direct investment enterprise. In that case, the classification used as a proxy is the activity of the direct investor.  Alongside with International Trade in Services Statistics (ITSS) and Foreign Affiliates Trade Statistics (FATS), FDI data are relevant to monitor the overall effectiveness and competitiveness of different economies in the globalised world.

Eurostat uses as a base for its work the OECD Benchmark Definition of Foreign Direct Investment Third Edition, a detailed operational definition fully consistent with the IMF Balance of Payments Manual, Fifth Edition, BPM5. Foreign direct investment (FDI) is the category of international investment made by an entity resident in one economy (direct investor) to acquire a lasting interest in an enterprise operating in another economy (direct investment enterprise). The lasting interest is deemed to exist if the direct investor acquires at least 10% of the voting power of the direct investment enterprise. FDI statistics record separately: 1) Inward FDI (or FDI in the reporting economy), namely investment by foreigners in enterprises resident in the reporting economy. 2) Outward FDI (or FDIabroad), namely investment by residents entities in affiliated enterprises abroad. FDI statistics record both the initial investment and all subsequent investment made by the direct investor, either in the form of equity capital, or in the form of loans, or in the form of reinvesting earnings. Investment made through other affiliated enterprises of the same group of the direct investor should also be recorded according to the international methodology. There are three main indicators: FDI flows, stocks and income. The indicators described in more detail below are presented in the complete tables with a breakdown by partner country or region and a breakdown by the kind of activity in which FDI is made. In the table called "Main indicators" there is a reduced breakdown by partners and data for total activity only. See the part on classification system for more detail. See also the User's guideon the structure on the database and for practical information on data downloading. 1) FDI flows denote the new investment made during the period. FDI flows are recorded in the Balance of Payments financial account. Total FDI flows are broken down by kind of instrument used for making the investment:Equity capital comprises equity in branches, all shares in subsidiaries and associates (except non-participating, preferred shares that are treated as debt securities and are included under other FDI capital) and other contributions such as the provision of machinery.Reinvested earnings consist of the direct investor's share (in proportion to equity participation) of earnings not distributed by the direct investment enterprise. Reinvested earnings are an imputed transaction. Reinvested earnings are also recorded with opposite sign among FDI income (see below). This recording represents not distributed income as being earned by the direct investor and reinvested in the direct investment enterprise at the same time.Other FDI capital (loans) covers the borrowing and lending of funds, including debt securities and trade credits between direct investors and direct investment enterprises. Debt transactions between affiliated financial intermediaries recorded under direct investment flows are limited to permanent debt. 2) FDI stocks (or positions) denote the value of the investment at the end of the period. FDI stocks are recorded in the International Investment Position. Outward FDI stocks are recorded as assets of the reporting economy, inward FDI stocks as liabilities. Similarly with flows, FDI stocks are broken down by kind of instrument. However, there are only two categories instead of three:Equity capital and reinvested earnings is the value of the own capital of the enterprise, including the value of own reserves that are accumulated from past reinvested earnings. Reserves corresponding to reinvested earnings are not shown separately from other equity capital as in the case of flows.Other FDI capital is the stock of debts (assets or liabilities) between the direct investors and the direct investment enterprise. 3) FDI income is the income accruing to direct investors during the period. FDI income is recorded in the current account of the Balance of Payments. Total FDI income is broken down by kind of income. The categories of FDI income available are linked to the breakdown of FDI flows and stocks by kind of instrument, namely:Dividends Dividends payable in the period and branch profits remitted to the direct investor, gross of any withholding taxes. Dividends include payments due on common and preferred shares.Reinvested earnings See definition under FDI flows.Interest on loans Interest accrued in the period on loans (other FDI capital) with affiliated enterprises, gross of any withholding tax. 4) FDI intensity Out of FDI annual data, an indicator useful to measure EU market integration is also calculated and disseminated in the domain Structural Indicators:FDI intensity as % of GDP: Average of inward and outward FDI flows divided by GDP. A higher index indicates higher new FDI during the period in relation to the size of the economy as measured by GDP. If this index increases over time, then the country/zone is becoming more integrated with the international economy.

Eurostat uses as a base for its work the OECD Benchmark Definition of Foreign Direct Investment Third Edition, a detailed operational definition fully consistent with the IMF Balance of Payments Manual, Fifth Edition, BPM5. Foreign direct investment (FDI) is the category of international investment made by an entity resident in one economy (direct investor) to acquire a lasting interest in an enterprise operating in another economy (direct investment enterprise). The lasting interest is deemed to exist if the direct investor acquires at least 10% of the voting power of the direct investment enterprise. FDI statistics record separately: 1) Inward FDI (or FDI in the reporting economy), namely investment by foreigners in enterprises resident in the reporting economy. 2) Outward FDI (or FDIabroad), namely investment by residents entities in affiliated enterprises abroad. FDI statistics record both the initial investment and all subsequent investment made by the direct investor, either in the form of equity capital, or in the form of loans, or in the form of reinvesting earnings. Investment made through other affiliated enterprises of the same group of the direct investor should also be recorded according to the international methodology. There are three main indicators: FDI flows, stocks and income. The indicators described in more detail below are presented in the complete tables with a breakdown by partner country or region and a breakdown by the kind of activity in which FDI is made. In the table called "Main indicators" there is a reduced breakdown by partners and data for total activity only. See the part on classification system for more detail. See also the User's guideon the structure on the database and for practical information on data downloading. 1) FDI flows denote the new investment made during the period. FDI flows are recorded in the Balance of Payments financial account. Total FDI flows are broken down by kind of instrument used for making the investment:Equity capital comprises equity in branches, all shares in subsidiaries and associates (except non-participating, preferred shares that are treated as debt securities and are included under other FDI capital) and other contributions such as the provision of machinery.Reinvested earnings consist of the direct investor's share (in proportion to equity participation) of earnings not distributed by the direct investment enterprise. Reinvested earnings are an imputed transaction. Reinvested earnings are also recorded with opposite sign among FDI income (see below). This recording represents not distributed income as being earned by the direct investor and reinvested in the direct investment enterprise at the same time.Other FDI capital (loans) covers the borrowing and lending of funds, including debt securities and trade credits between direct investors and direct investment enterprises. Debt transactions between affiliated financial intermediaries recorded under direct investment flows are limited to permanent debt. 2) FDI stocks (or positions) denote the value of the investment at the end of the period. FDI stocks are recorded in the International Investment Position. Outward FDI stocks are recorded as assets of the reporting economy, inward FDI stocks as liabilities. Similarly with flows, FDI stocks are broken down by kind of instrument. However, there are only two categories instead of three:Equity capital and reinvested earnings is the value of the own capital of the enterprise, including the value of own reserves that are accumulated from past reinvested earnings. Reserves corresponding to reinvested earnings are not shown separately from other equity capital as in the case of flows.Other FDI capital is the stock of debts (assets or liabilities) between the direct investors and the direct investment enterprise. 3) FDI income is the income accruing to direct investors during the period. FDI income is recorded in the current account of the Balance of Payments. Total FDI income is broken down by kind of income. The categories of FDI income available are linked to the breakdown of FDI flows and stocks by kind of instrument, namely:Dividends Dividends payable in the period and branch profits remitted to the direct investor, gross of any withholding taxes. Dividends include payments due on common and preferred shares.Reinvested earnings See definition under FDI flows.Interest on loans Interest accrued in the period on loans (other FDI capital) with affiliated enterprises, gross of any withholding tax. 4) FDI intensity Out of FDI annual data, an indicator useful to measure EU market integration is also calculated and disseminated in the domain Structural Indicators:FDI intensity as % of GDP: Average of inward and outward FDI flows divided by GDP. A higher index indicates higher new FDI during the period in relation to the size of the economy as measured by GDP. If this index increases over time, then the country/zone is becoming more integrated with the international economy.

Eurostat uses as a base for its work the OECD Benchmark Definition of Foreign Direct Investment Third Edition, a detailed operational definition fully consistent with the IMF Balance of Payments Manual, Fifth Edition, BPM5. Foreign direct investment (FDI) is the category of international investment made by an entity resident in one economy (direct investor) to acquire a lasting interest in an enterprise operating in another economy (direct investment enterprise). The lasting interest is deemed to exist if the direct investor acquires at least 10% of the voting power of the direct investment enterprise. FDI statistics record separately: 1) Inward FDI (or FDI in the reporting economy), namely investment by foreigners in enterprises resident in the reporting economy. 2) Outward FDI (or FDIabroad), namely investment by residents entities in affiliated enterprises abroad. FDI statistics record both the initial investment and all subsequent investment made by the direct investor, either in the form of equity capital, or in the form of loans, or in the form of reinvesting earnings. Investment made through other affiliated enterprises of the same group of the direct investor should also be recorded according to the international methodology. There are three main indicators: FDI flows, stocks and income. The indicators described in more detail below are presented in the complete tables with a breakdown by partner country or region and a breakdown by the kind of activity in which FDI is made. In the table called "Main indicators" there is a reduced breakdown by partners and data for total activity only. See the part on classification system for more detail. See also the User's guideon the structure on the database and for practical information on data downloading. 1) FDI flows denote the new investment made during the period. FDI flows are recorded in the Balance of Payments financial account. Total FDI flows are broken down by kind of instrument used for making the investment:Equity capital comprises equity in branches, all shares in subsidiaries and associates (except non-participating, preferred shares that are treated as debt securities and are included under other FDI capital) and other contributions such as the provision of machinery.Reinvested earnings consist of the direct investor's share (in proportion to equity participation) of earnings not distributed by the direct investment enterprise. Reinvested earnings are an imputed transaction. Reinvested earnings are also recorded with opposite sign among FDI income (see below). This recording represents not distributed income as being earned by the direct investor and reinvested in the direct investment enterprise at the same time.Other FDI capital (loans) covers the borrowing and lending of funds, including debt securities and trade credits between direct investors and direct investment enterprises. Debt transactions between affiliated financial intermediaries recorded under direct investment flows are limited to permanent debt. 2) FDI stocks (or positions) denote the value of the investment at the end of the period. FDI stocks are recorded in the International Investment Position. Outward FDI stocks are recorded as assets of the reporting economy, inward FDI stocks as liabilities. Similarly with flows, FDI stocks are broken down by kind of instrument. However, there are only two categories instead of three:Equity capital and reinvested earnings is the value of the own capital of the enterprise, including the value of own reserves that are accumulated from past reinvested earnings. Reserves corresponding to reinvested earnings are not shown separately from other equity capital as in the case of flows.Other FDI capital is the stock of debts (assets or liabilities) between the direct investors and the direct investment enterprise. 3) FDI income is the income accruing to direct investors during the period. FDI income is recorded in the current account of the Balance of Payments. Total FDI income is broken down by kind of income. The categories of FDI income available are linked to the breakdown of FDI flows and stocks by kind of instrument, namely:Dividends Dividends payable in the period and branch profits remitted to the direct investor, gross of any withholding taxes. Dividends include payments due on common and preferred shares.Reinvested earnings See definition under FDI flows.Interest on loans Interest accrued in the period on loans (other FDI capital) with affiliated enterprises, gross of any withholding tax. 4) FDI intensity Out of FDI annual data, an indicator useful to measure EU market integration is also calculated and disseminated in the domain Structural Indicators:FDI intensity as % of GDP: Average of inward and outward FDI flows divided by GDP. A higher index indicates higher new FDI during the period in relation to the size of the economy as measured by GDP. If this index increases over time, then the country/zone is becoming more integrated with the international economy.

Eurostat uses as a base for its work the OECD Benchmark Definition of Foreign Direct Investment Third Edition, a detailed operational definition fully consistent with the IMF Balance of Payments Manual, Fifth Edition, BPM5. Foreign direct investment (FDI) is the category of international investment made by an entity resident in one economy (direct investor) to acquire a lasting interest in an enterprise operating in another economy (direct investment enterprise). The lasting interest is deemed to exist if the direct investor acquires at least 10% of the voting power of the direct investment enterprise. FDI statistics record separately: 1) Inward FDI (or FDI in the reporting economy), namely investment by foreigners in enterprises resident in the reporting economy. 2) Outward FDI (or FDIabroad), namely investment by residents entities in affiliated enterprises abroad. FDI statistics record both the initial investment and all subsequent investment made by the direct investor, either in the form of equity capital, or in the form of loans, or in the form of reinvesting earnings. Investment made through other affiliated enterprises of the same group of the direct investor should also be recorded according to the international methodology. There are three main indicators: FDI flows, stocks and income. The indicators described in more detail below are presented in the complete tables with a breakdown by partner country or region and a breakdown by the kind of activity in which FDI is made. In the table called "Main indicators" there is a reduced breakdown by partners and data for total activity only. See the part on classification system for more detail. See also the User's guideon the structure on the database and for practical information on data downloading. 1) FDI flows denote the new investment made during the period. FDI flows are recorded in the Balance of Payments financial account. Total FDI flows are broken down by kind of instrument used for making the investment:Equity capital comprises equity in branches, all shares in subsidiaries and associates (except non-participating, preferred shares that are treated as debt securities and are included under other FDI capital) and other contributions such as the provision of machinery.Reinvested earnings consist of the direct investor's share (in proportion to equity participation) of earnings not distributed by the direct investment enterprise. Reinvested earnings are an imputed transaction. Reinvested earnings are also recorded with opposite sign among FDI income (see below). This recording represents not distributed income as being earned by the direct investor and reinvested in the direct investment enterprise at the same time.Other FDI capital (loans) covers the borrowing and lending of funds, including debt securities and trade credits between direct investors and direct investment enterprises. Debt transactions between affiliated financial intermediaries recorded under direct investment flows are limited to permanent debt. 2) FDI stocks (or positions) denote the value of the investment at the end of the period. FDI stocks are recorded in the International Investment Position. Outward FDI stocks are recorded as assets of the reporting economy, inward FDI stocks as liabilities. Similarly with flows, FDI stocks are broken down by kind of instrument. However, there are only two categories instead of three:Equity capital and reinvested earnings is the value of the own capital of the enterprise, including the value of own reserves that are accumulated from past reinvested earnings. Reserves corresponding to reinvested earnings are not shown separately from other equity capital as in the case of flows.Other FDI capital is the stock of debts (assets or liabilities) between the direct investors and the direct investment enterprise. 3) FDI income is the income accruing to direct investors during the period. FDI income is recorded in the current account of the Balance of Payments. Total FDI income is broken down by kind of income. The categories of FDI income available are linked to the breakdown of FDI flows and stocks by kind of instrument, namely:Dividends Dividends payable in the period and branch profits remitted to the direct investor, gross of any withholding taxes. Dividends include payments due on common and preferred shares.Reinvested earnings See definition under FDI flows.Interest on loans Interest accrued in the period on loans (other FDI capital) with affiliated enterprises, gross of any withholding tax. 4) FDI intensity Out of FDI annual data, an indicator useful to measure EU market integration is also calculated and disseminated in the domain Structural Indicators:FDI intensity as % of GDP: Average of inward and outward FDI flows divided by GDP. A higher index indicates higher new FDI during the period in relation to the size of the economy as measured by GDP. If this index increases over time, then the country/zone is becoming more integrated with the international economy.

Eurostat Dataset Id:bop_fdi_pos_r2 Eurostat uses as a base for its work the OECD Benchmark Definition of Foreign Direct Investment Third Edition, a detailed operational definition fully consistent with the IMF Balance of Payments Manual, Fifth Edition, BPM5. Foreign direct investment (FDI) is the category of international investment made by an entity resident in one economy (direct investor) to acquire a lasting interest in an enterprise operating in another economy (direct investment enterprise). The lasting interest is deemed to exist if the direct investor acquires at least 10% of the voting power of the direct investment enterprise. FDI statistics record separately: 1) Inward FDI (or FDI in the reporting economy), namely investment by foreigners in enterprises resident in the reporting economy. 2) Outward FDI (or FDI abroad), namely investment by residents entities in affiliated enterprises abroad. FDI statistics record both the initial investment and all subsequent investment made by the direct investor, either in the form of equity capital, or in the form of loans, or in the form of reinvesting earnings. Investment made through other affiliated enterprises of the same group of the direct investor should also be recorded according to the international methodology. There are three main indicators: FDI flows, stocks and income. The indicators described in more detail below are presented in the complete tables with a breakdown by partner country or region and a breakdown by the kind of activity in which FDI is made. In the table called "Main indicators" there is a reduced breakdown by partners and data for total activity only. See the part on classification system for more detail. See also the User's guideon the structure on the database and for practical information on data downloading. 1) FDI flows denote the new investment made during the period. FDI flows are recorded in the Balance of Payments financial account. Total FDI flows are broken down by kind of instrument used for making the investment:Equity capital comprises equity in branches, all shares in subsidiaries and associates (except non-participating, preferred shares that are treated as debt securities and are included under other FDI capital) and other contributions such as the provision of machinery.Reinvested earnings consist of the direct investor's share (in proportion to equity participation) of earnings not distributed by the direct investment enterprise. Reinvested earnings are an imputed transaction. Reinvested earnings are also recorded with opposite sign among FDI income (see below). This recording represents not distributed income as being earned by the direct investor and reinvested in the direct investment enterprise at the same time.Other FDI capital (loans) covers the borrowing and lending of funds, including debt securities and trade credits between direct investors and direct investment enterprises. Debt transactions between affiliated financial intermediaries recorded under direct investment flows are limited to permanent debt. 2) FDI stocks (or positions) denote the value of the investment at the end of the period. FDI stocks are recorded in the International Investment Position. Outward FDI stocks are recorded as assets of the reporting economy, inward FDI stocks as liabilities. Similarly with flows, FDI stocks are broken down by kind of instrument. However, there are only two categories instead of three:Equity capital and reinvested earnings is the value of the own capital of the enterprise, including the value of own reserves that are accumulated from past reinvested earnings. Reserves corresponding to reinvested earnings are not shown separately from other equity capital as in the case of flows.Other FDI capital is the stock of debts (assets or liabilities) between the direct investors and the direct investment enterprise. 3) FDI income is the income accruing to direct investors during the period. FDI income is recorded in the current account of the Balance of Payments. Total FDI income is broken down by kind of income. The categories of FDI income available are linked to the breakdown of FDI flows and stocks by kind of instrument, namely:Dividends Dividends payable in the period and branch profits remitted to the direct investor, gross of any withholding taxes. Dividends include payments due on common and preferred shares.Reinvested earnings See definition under FDI flows.Interest on loans Interest accrued in the period on loans (other FDI capital) with affiliated enterprises, gross of any withholding tax. 4) FDI intensity Out of FDI annual data, an indicator useful to measure EU market integration is also calculated and disseminated in the domain Structural Indicators:FDI intensity as % of GDP: Average of inward and outward FDI flows divided by GDP. A higher index indicates higher new FDI during the period in relation to the size of the economy as measured by GDP. If this index increases over time, then the country/zone is becoming more integrated with the international economy.

 Foreign Direct Investment (FDI) encompasses all kind of cross-border investment made by an entity resident in one economy (direct investor) to acquire a lasting interest in an enterprise operating in another economy (direct investment enterprise). FDI is one of the five main functional categories of investment used in international accounts to classify either the Internal Investment Positions (IIP) or the Balance of Payment (BOP) statements of a given economy (vis-à-vis the rest of the world). Foreign Direct Investment positions show at a point in time (generally, end of a reference year) the value of financial direct investment assets of residents of an economy on non-residents, and financial direct investment liabilities of residents of an economy to non-resident. The net FDI position is the difference between assets and liabilities, which is also equivalent (under the directional principle presentation) to the difference between FDI positions abroad and in the reporting economy. The net FDI position represents either a net FDI claim or a net FDI liability to the rest of the world.        Foreign direct investment transactions summarize all economic direct investment interactions between the residents and the non-residents during a given period. Two types of FDI transactions can be identified (within the BOP framework) according to the economic meaning they convey: FDI income is a distributive transaction showing amounts payable and receivable between resident and non-resident entities in return for providing financial direct investment assets to the rest of the world, or incurring direct investment liabilities vis-à-vis the rest of the world.FDI flows refer to financial transactions showing the net acquisition or disposal of financial assets and liabilities involved in direct investment relationships.FDI positions, FDI income and FDI flows are disseminated by Eurostat together with estimated EU FDI aggregates (directly produced by Eurostat).  Other FDI changes that are not transaction changes, such as volume, value or prices changes, are not treated by Eurostat under the scope of annual FDI statistics. Annual FDI data are disseminated by Eurostat according to the directional principle (see sub section 3.4 below). The geographical allocation is made according to the economic residence of the immediate direct investor or immediate direct investment company (immediate counterparts). FDI data classified according to ultimate investor or host economy are not yet available at Eurostat (see 12.1).  International Guides recommend the classification of FDI data both according to the activity of the direct investor and the activity of the direct investment enterprise. In practice, it is very difficult for national compilers to have both classifications. In that case, the recommended classification by activity is that of the direct investment enterprise. On the outward side, national compilers are not always able to classify their FDI data according to the activity of the direct investment enterprise. In that case, the classification used as a proxy is the activity of the direct investor.  Alongside with International Trade in Services Statistics (ITSS) and Foreign Affiliates Trade Statistics (FATS), FDI data are relevant to monitor the overall effectiveness and competitiveness of different economies in the globalised world.

A yield curve (which is known as the term structure of interest rates) represents the relationship between market remuneration (interest) rates and the remaining time to maturity of debt securities. The zero coupon yield curves and their corresponding time series are calculated using "AAA-rated" euro area central government bonds, i.e. debt securities with the most favourable credit risk assessment. They represent the yields to maturity of hypothetical zero coupon bonds. Source: European Central Bank.

 A yield curve, also known as term structure of interest rates, represents the relationship between market remuneration (interest) rates and the remaining time to maturity of debt securities. The information content of a yield curve reflects the asset pricing process on financial markets. When buying and selling bonds, investors include their expectations of  future inflation, real interest rates and their assessment of risks. An investor calculates the price of a bond by discounting the expected future cash flows (coupon payments and/or redemption). The European Central Bank estimates zero-coupon yield curves for the euro area and also derives forward and par yield curves. A zero coupon bond is a bond that pays no coupon and is sold at a discount from its face value. The zero coupon curve represents the yield to maturity of hypothetical zero coupon bonds, since they are not directly observable in the market for a wide range of maturities. They must therfore be estimated from existing zero coupon bonds and fixed coupon bond prices or yields.  The forward curve shows the short-term (instantaneous) interest rate for future periods implied in the yield curve. The par yield reflects hypothetical yields, namely the interest rates the bonds would have yielded had they been priced at par (i.e. at 100). An outlier removal mechanism is applied to bonds that have passed the selection criteria described in 11.1. Bonds are removed if their yields deviate by more than twice the standard deviation from the average yield in the same maturity bracket. Afterwards, the same procedure is repeated. 

A yield curve, also known as term structure of interest rates, represents the relationship between market remuneration (interest) rates and the remaining time to maturity of debt securities. The information content of a yield curve reflects the asset pricing process on financial markets. When buying and selling bonds, investors include their expectations of  future inflation, real interest rates and their assessment of risks. An investor calculates the price of a bond by discounting the expected future cash flows (coupon payments and/or redemption). ECB estimates zero-coupon yield curves for the euro area and also derives forward and par yield curves. A zero coupon bond is a bond that pays no cupon and is sold at a discount from its face value. The zero coupon curve represents the yield to maturity of hypothetical zero coupon bonds, since they are not directly observable in the market for a wide range of maturities. They must therfore be estimatedfrom existing zero coupon bonds and fixed coupon bond prices or yields.  The forward curve shows the short-term (instantaneous) interest rate for future periods implied in the yield curve. The par yield reflects hypothetical yields, namely the interest rates the bonds would have yielded had they been priced at par (i.e. at 100).

Intellectual property refers broadly to the creations of the human mind. Intellectual property rights protect the interests of creators by giving them property rights over their creations. Trade marks constitute means by which creators seek protection for their industrial property. Trade marks reflect the non-technological innovation in every sector of economic life, including services. In this context, indicators based on Trade mark data can provide a link between innovation and the market. Trade marks such as words or figurative marks are an essential part of the “identity” of goods and services. They help deliver brand recognition, in logos for example, and play an important role in marketing and communication. It is possible to register a variety of Trade marks including words, other graphical representations, and even sounds. Rights owners have a choice of obtaining protection on a country-by-country basis, or using international systems. This domain provides users with data concerning European Union Trade marks. European Union Trade marks refer to trade mark protections throughout the European Union, which covers 28 countries. The European Union Intellectual Property Office (EUIPO) is the official office of the European Union for the registration of European Union Trade marks and Designs. A European Union Trade mark is an exclusive right that protects distinctive signs, valid across the EU, registered directly with EUIPO in Alicante in accordance with the conditions specified in the EUTM Regulations (Source: EUIPO).

Average of inward and outward Foreign Direct Investment (FDI) flows divided by gross domestic product (GDP). The index measures the intensity of investment integration within the international economy. The direct investment refers to the international investment made by a resident entity (direct investor) to acquire a lasting interest in an entity operating in an economy other than that of the investor (direct investment enterprise). Direct investment involves both the initial transactions between the two entities and all subsequent capital transactions between them and among affiliated enterprises, both incorporated and unincorporated. Data are expressed as percentage of GDP to remove the effect of differences in the size of the economies of the reporting countries.

Eurostat Dataset Id:ei_bsfs_m Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published: as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)

Eurostat Dataset Id:ei_bsfs_q Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published: as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)

The Harmonised Index of Consumer Prices (HICP) gives comparable measures of inflation for the countries and country groups for which it is produced. It is an economic indicator that measures the change over time of the prices of consumer goods and services acquired by households. In other words, it is a set of consumer price indices (CPI) calculated according to a harmonised approach and a set of definitions as laid down in Regulations and recommendations. In addition, the HICP provides the official measure of consumer price inflation in the euro area for the purposes of monetary policy and the assessment of inflation convergence as required under the Maastricht criteria for accession to the euro. The HICP is available for all EU Member States, Iceland, Norway and Switzerland. In addition to the individual country series there are three key country-group aggregate indices: the euro area, the European Union (EU), and the European Economic Area (EEA), which, in addition to the EU, also covers Iceland and Norway, but not Liechtenstein. The official country-group aggregates reflect the changing country composition of the EA, the EU and the EEA. The HICP for new Member States is chained into the aggregate indices at the time of accession. For analytical purposes Eurostat also computes country-group aggregates with stable country composition over time. For example, the EU28 aggregate shows price indices covering all current 28 Member States since 1997. The HICP for Serbia and Turkey (candidate countries) are also published. That data are flagged 'd' ('definition differs'). A proxy-HICP for the all-items and main aggregates is available for the USA. National HICPs are produced by National Statistical Institutes (NSIs), while the country-group aggregates are produced by Eurostat. The data released monthly on Eurostat's free dissemination database include price indices and rates of change (monthly, annual and 12-month moving average changes). In addition to the headline figure 'all-items HICP', around four hundred sub-indices for different goods and services and over thirty special aggregates are available, including the HICP at administered prices (HICP-AP). Once a year, with the release of the January data, the relative weights for the indices and the special aggregates, are published for the individual countries and for the European aggregates. The composition of the HICP-AP aggregates, i.e. which sub-indices are classified as mainly or fully administered by each Member State, is also updated at the same time. Eurostat publishes early estimates, called 'HICP flash estimates', of the euro area overall inflation rate and selected components. They are published monthly, usually on the last working day of the reference month, and disseminated in a news release, in the database and in a Statistics Explained article. The HICP at constant tax rates (HICP-CT) follows the same computation principles as the HICP, but is based on prices at constant tax rates. The comparison with the standard HICP can show the potential impact of changes in indirect taxes, such as VAT and excise duties, on the overall inflation (more information). Flags Flags provide information about the 'status' of the data or a specific data value. The following flags are used for the HICP data in the Eurostat online database: p = provisional data: Data is flagged as provisional by the National Statistical Institutes to signal that data are still being treated or validated. The 'p' flag remains attached to the HICP data values in question for one month only. r = revised data. In the case when the most recent figures published differ from previously disseminated data, they are flagged with 'r'. Countries are allowed to revise their HICP figures at any point and, therefore, revised figures may appear in historic data. The 'r' flag remains attached to the HICP data values in question for one month only. e = estimated data. All the figures of the HICP flash estimate are marked with the 'e' flag. d = definition differs, meaning that the national definition of a series differs from the ECOICOP (European Classification of Individual Consumption according to Purpose) definition. It is also used for data values from countries for which conformity with the requirements of the HICP methodology has not yet been evaluated by Eurostat, including candidate countries, pre-candidate countries, new EU Member States and the United States of America. u = unreliable data. Data is flagged as unreliable by the National Statistical Institutes.

The Food Price Monitoring Tool intends to analyse the available data on price developments through the supply chain. The supply chain is a series of economic activities that are performed by different economic actors that contribute to the production and distribution of one consumer product or a group of consumer products. The Food Price Monitoring Tool monitors 15 supply chains. It compares the price indices of four stages of the supply chain:Retail sector: the harmonised index of consumer prices (HICP)Domestic food industry: the domestic producer price index (PPId)Imported products: the import price index based on unit values from international trade in goods statisticsAgricultural commodities: the agricultural commodity prices index (ACP)

The section 'LFS series - detailed quarterly survey results' reports detailed quarterly results going beyond the EU-LFS main aggregates, which have a separate data domain and some methodological differences. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self-employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)' (see link below in section 'related metadata'). Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed quarterly survey results' reports detailed quarterly results going beyond the EU-LFS main aggregates, which have a separate data domain and some methodological differences. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self-employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)' (see link below in section 'related metadata'). Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

Consumer price indices (CPIs) measure inflation as price changes of a representative basket of goods and services typically purchased by households. The G20 CPI aggregate reflects national CPIs for all G20 countries (with the exception of Turkey) that are not part of the European Union (EU) while it reflects the Harmonised Indices of Consumer Prices (HICP) for the EU, its Member States and for Turkey. It is an annual chain-linked Laspeyres-type index. The weights for each country in each link are based on the previous year’s relative share of individual final consumption expenditure of households and non-profit institutions serving households expressed in Purchasing Power Parities (PPPs). The table presents the data for all non-EU countries. The HICP tables for France, Germany, Italy, the United Kingdom, and the euro area and European Union can be found under the HICP tables.

National accounts are a coherent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. The data presented in this collection are the results of a pilot exercise on the sharing selected main GDP aggregates, population and employment data collected by different international organisations. It wasconducted by the Task Force in International Data Collection (TFIDC) which was established by the  Inter-Agency Group on Economic and Financial Statistics (IAG).  The goal of this pilot is to develop a set of commonly shared principles and working arrangements for data cooperation that could be implemented by the international agencies. The data sets are an experimental exercise to present national accounts data form various countries across the globe in one coherent folder, but users should be aware that these data are collected and validated by different organisations and not fully harmonised from a methodological point of view.  The domain consists of the following collections:

Data in this domain constitute only a small part of the entire National Accounts data range available from Eurostat. Annual and quarterly national accounts are compiled in accordance with the European System of Accounts - ESA 2010 as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013. The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. Further information on the transition from ESA 95 to ESA 2010 is presented on the Eurostat website. The annual data of this domain consists of the following collections: 1. Main GDP aggregates: main components from the output, expenditure and income side. nama_10_gdp: GDP and main components (output, expenditure and income) The quarterly data of this domain consists of the following collections 1. Main GDP aggregates, main components from the output, expenditure and income side, expenditure breakdowns by industry and assets. namq_10_ma: Main GDP aggregatesnamq_10_gdp: GDP and main components (output, expenditure and income)namq_10_fcs: Final consumption aggregates by durabilitynamq_10_exi: Exports and imports by Member States of the EU/third countries 2. Breakdowns of GDP aggregates and employment data by main industries and asset classes. namq_10_bbr: Basic breakdowns main GDP aggregates and employment (by industry and assets)namq_10_a10: Gross value added and income by A*10 industrynamq_10_an6: Gross fixed capital formation by AN_F6 asset typenamq_10_a10_e: Employment by A*10 industry breakdowns Geographical entities covered are the European Union, the euro area, EU Member States, Candidate Countries, EFTA countries, US, Japan and possibly other countries on an ad-hoc basis. Data sources: National Statistical Institutes.

Data from 1st of December 2019. For most recent GDP data, consult dataset nama_10_gdp. Gross domestic product (GDP) is a measure for the economic activity. It is defined as the value of all goods and services produced less the value of any goods or services used in their creation. The volume index of GDP per capita in Purchasing Power Standards (PPS) is expressed in relation to the European Union average set to equal 100. If the index of a country is higher than 100, this country's level of GDP per head is higher than the EU average and vice versa. Basic figures are expressed in PPS, i.e. a common currency that eliminates the differences in price levels between countries allowing meaningful volume comparisons of GDP between countries. Please note that the index, calculated from PPS figures and expressed with respect to EU27_2020 = 100, is intended for cross-country comparisons rather than for temporal comparisons."

The gender employment gap is defined as the difference between the employment rates of men and women aged 20-64. The employment rate is calculated by dividing the number of persons aged 20 to 64 in employment by the total population of the same age group. The indicator is based on the EU Labour Force Survey.

10-year government bond yields are reference rates, based on government bonds with a maturity close to 10 years.

10-year government bond yields are reference rates, based on government bonds with a maturity close to 10 years.

The source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview

Eurostat Dataset Id:nama_r_e2gdp Gross domestic product - GDP at market prices - is the final result of the production activity of resident producer units (ESA 1995, 8.89). It can be defined in three ways: 1. Output approach GDP is the sum of gross value added of the various institutional sectors or the various industries plus taxes and less subsidies on products (which are not allocated to sectors and industries). It is also the balancing item in the total economy production account. 2. Expenditure approach GDP is the sum of final uses of goods and services by resident institutional units (final consumption expenditure and gross capital formation), plus exports and minus imports of goods and services. At regional level the expediture approach is not used in the EU, because there is no data on regional exports and imports.  3. Income approach GDP is the sum of uses in the total economy generation of income account: compensation of employees, taxes on production, less subsidies, gross operating surplus and mixed income of the total economy. The different measures for the regional GDP are absolute figures in € and Purchasing Power Standards (PPS), figures per inhabitant and relative data compared to the EU27 average.

Eurostat Dataset Id:nama_r_e3gdp National accounts are a coherent and consistent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. Eurostat publishes annual and quarterly national accounts, annual and quarterly sector accounts as well as supply, use and input-output tables, which are each presented with associated metadata. Annual national accounts are compiled in accordance with the European System of Accounts - ESA 1995 (Council Regulation 2223/96). Annex B of the Regulation consists of a comprehensive list of the variables to be transmitted for Community purposes within specified time limits. This transmission programme has been updated by Regulation (EC) N° 1392/2007 of the European Parliament and of the Council. Meanwhile, the ESA95 has been reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. Further information on the transition from ESA 95 to ESA 2010 is presented on the Eurostat website. The domain consists of the following collections: GDP and main aggregates. The data are recorded at current and constant prices and include the corresponding implicit price indices. Final consumption aggregates, including the split into household and government consumption. The data are recorded at current and constant prices and include the corresponding implicit price indices. Income, saving and net lending / net borrowing at current prices. Disposable income is also shown in real terms. Exports and imports by Member States of the EU/third countries. The data are recorded at current and constant prices and include the corresponding implicit price indices. Breakdowns of gross value added, compensation of employees, wages and salaries, operating surplus, employment (domestic scope), gross fixed capital formation (GFCF) and fixed assets and other main aggregates by industry; investment by products and household final consumption expenditure by consumption purposes (COICOP). The data are recorded at current and constant prices and include the corresponding implicit price indices. Auxiliary indicators: Population and employment national data, purchasing power parities, contributions to GDP growth, labour productivity, unit labour cost and GDP per capita. Geographical entities covered are the European Union, the euro area, EU Member States, Candidate Countries, EFTA countries, US, Japan and possibly other countries on an ad-hoc basis. The data are published: - in ECU/euro, in national currencies (including euro converted from former national currencies using the irrevocably fixed rate for all years) and in Purchasing Power Standards (PPS); - at current prices and in volume terms; - Population and employment are measured in persons. Employment is also measured in total hours worked. Data sources: National Statistical Institutes

The source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview

Eurostat Dataset Id:urt_e3gdp

The source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview

Gross domestic product (GDP) at market prices is the final result of the production activity of resident producer units (ESA 2010, 8.89). It can be defined in three ways: a production approach, an income approach and an expenditure approach. Values are seasonally adjusted (SA). The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

Gross domestic product (GDP) at market prices is the final result of the production activity of resident producer units (ESA 2010, 8.89). It can be defined in three ways: a production approach, an income approach and an expenditure approach. Data are calculated as chain-linked volumes (i.e. data at previous year's prices, linked over the years via appropriate growth rates). Growth rates 'q/q-1 (sca)' with respect to the previous quarter and 'q/q-4 (sca)' with respect to the same quarter of the previous year are calculated from calendar and seasonally adjusted figures while growth rates 'q/q-4 (nsa)' with respect to the same quarter of the previous year are calculated from raw data.

National accounts are a coherent and consistent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. Eurostat publishes annual and quarterly national accounts, annual and quarterly sector accounts as well as supply, use and input-output tables, which are each presented with associated metadata. Even though consistency checks are a major aspect of data validation, temporary (usually limited) inconsistencies between datasets may occur, mainly due to vintage effects. Annual national accounts are compiled in accordance with the European System of Accounts - ESA 2010 as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013.   The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. Further information (including actual communications) is presented on the Eurostat website. The domain consists of the following collections:   1. Main GDP aggregates: main components from the output, expenditure and income side, expenditure breakdowns by durability and exports and imports by origin. <

Gross fixed capital formation (GFCF, ESA 2010, 3.124) consists of resident producers' acquisitions, less disposals, of fixed assets during a given period plus certain additions to the value of non-produced assets realised by the productive activity of producer or institutional units. GFCF includes acquisition less disposals of, e.g. buildings, structures, machinery and equipment, mineral exploration, computer software, literary or artistic originals and major improvements to land such as the clearance of forests. Values are seasonally and calendar adjusted (SCA). The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

The Unemployment - LFS adjusted series (including also Harmonised long-term unemployment) is a collection of monthly, quarterly and annual series based on the quarterly results of the EU Labour Force Survey (EU-LFS), which are, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator. Harmonised unemployment is published in the section 'LFS main indicators', which is a collection of the main statistics on the labour market. However the harmonized unemployment indicators are calculated with special methods and periodicity which justify the present page. This page focuses on the particularities of the estimation of harmonised unemployment (including unemployment rates). Other information on 'LFS main indicators' can be found in the respective ESMS page, see link in section 'related metadata'. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)'.  Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

Unemployed persons comprise persons aged 15 to 74 who were without work during the reference week, were currently available for work and were either actively seeking work in the past four weeks or had already found a job to start within the next three months.

Unemployed persons comprise here persons aged 15 to 24 who were without work during the reference week, were currently available for work and were either actively seeking work in the past four weeks or had already found a job to start within the next three months.

Unemployed persons comprise here persons aged 25 to 74 who were without work during the reference week, were currently available for work and were either actively seeking work in the past four weeks or had already found a job to start within the next three months.

The unemployment rate represents unemployed persons as a percentage of the labour force based on International Labour Office (ILO) definition. The labour force is the total number of people employed and unemployed. Unemployed persons comprise persons aged 15 to 74 who: - are without work during the reference week; - are available to start work within the next two weeks; - and have been actively seeking work in the past four weeks or had already found a job to start within the next three months. Data are presented in seasonally adjusted form.

The unemployment rate represents unemployed persons as a percentage of the labour force based on International Labour Office (ILO) definition, which here refers to the total number of employed and unemployed persons aged 15 to 24. Unemployed persons comprise here persons aged 15 to 24 who: - are without work; - are available to start work within the next two weeks; - and have been actively seeking work in the past four weeks or had already found a job to start within the next three months. Data are presented in seasonally adjusted form.

The unemployment rate represents unemployed persons, based on International Labour Office (ILO) definition, as a percentage of the labour force, which here refers to the total number of employed and unemployed persons aged 25 to 74. Unemployed persons comprise here persons aged 25 to 74 who: - are without work; - are available to start work within the next two weeks; - and have been actively seeking work in the past four weeks or had already found a job to start within the next three months. Data are presented in seasonally adjusted form.

The Unemployment - LFS adjusted series (including also Harmonised long-term unemployment) is a collection of monthly, quarterly and annual series based on the quarterly results of the EU Labour Force Survey (EU-LFS), which are, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator. Harmonised unemployment is published in the section 'LFS main indicators', which is a collection of the main statistics on the labour market. However the harmonized unemployment indicators are calculated with special methods and periodidicty which justify the present page. This page focuses on the particularities of the estimation of harmonised unemployment (including unemployment rates). Other information on 'LFS main indicators' can be found in the respective ESMS page, see link in section 'related metadata'. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)'.  Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The Harmonised Index of Consumer Prices (HICP) gives comparable measures of inflation for the countries and country groups for which it is produced. It is an economic indicator that measures the change over time of the prices of consumer goods and services acquired by households. In other words, it is a set of consumer price indices (CPI) calculated according to a harmonised approach and a set of definitions as laid down in Regulations and recommendations. In addition, the HICP provides the official measure of consumer price inflation in the euro area for the purposes of monetary policy and the assessment of inflation convergence as required under the Maastricht criteria for accession to the euro. The HICP is available for all EU Member States, Iceland, Norway and Switzerland. In addition to the individual country series there are three key country-group aggregate indices: the euro area, the European Union (EU), and the European Economic Area (EEA), which, in addition to the EU, also covers Iceland and Norway, but not Liechtenstein. The official country-group aggregates reflect the changing country composition of the EA, the EU and the EEA. The HICP for new Member States is chained into the aggregate indices at the time of accession. For analytical purposes Eurostat also computes country-group aggregates with stable country composition over time. For example, the EU28 aggregate shows price indices covering all current 28 Member States since 1997. The HICP for Serbia and Turkey (candidate countries) are also published. That data are flagged 'd' ('definition differs'). A proxy-HICP for the all-items and main aggregates is available for the USA. National HICPs are produced by National Statistical Institutes (NSIs), while the country-group aggregates are produced by Eurostat. The data released monthly on Eurostat's free dissemination database include price indices and rates of change (monthly, annual and 12-month moving average changes). In addition to the headline figure 'all-items HICP', around four hundred sub-indices for different goods and services and over thirty special aggregates are available, including the HICP at administered prices (HICP-AP). Once a year, with the release of the January data, the relative weights for the indices and the special aggregates, are published for the individual countries and for the European aggregates. The composition of the HICP-AP aggregates, i.e. which sub-indices are classified as mainly or fully administered by each Member State, is also updated at the same time. Eurostat publishes early estimates, called 'HICP flash estimates', of the euro area overall inflation rate and selected components. They are published monthly, usually on the last working day of the reference month, and disseminated in a news release, in the database and in a Statistics Explained article. The HICP at constant tax rates (HICP-CT) follows the same computation principles as the HICP, but is based on prices at constant tax rates. The comparison with the standard HICP can show the potential impact of changes in indirect taxes, such as VAT and excise duties, on the overall inflation (more information). Flags Flags provide information about the 'status' of the data or a specific data value. The following flags are used for the HICP data in the Eurostat online database: p = provisional data: Data is flagged as provisional by the National Statistical Institutes to signal that data are still being treated or validated. The 'p' flag remains attached to the HICP data values in question for one month only. r = revised data. In the case when the most recent figures published differ from previously disseminated data, they are flagged with 'r'. Countries are allowed to revise their HICP figures at any point and, therefore, revised figures may appear in historic data. The 'r' flag remains attached to the HICP data values in question for one month only. e = estimated data. All the figures of the HICP flash estimate are marked with the 'e' flag. d = definition differs, meaning that the national definition of a series differs from the ECOICOP (European Classification of Individual Consumption according to Purpose) definition. It is also used for data values from countries for which conformity with the requirements of the HICP methodology has not yet been evaluated by Eurostat, including candidate countries, pre-candidate countries, new EU Member States and the United States of America. u = unreliable data. Data is flagged as unreliable by the National Statistical Institutes.

Harmonised Indices of Consumer Prices (HICP) are designed for international comparisons of consumer price inflation. HICPs are used for the assessment of the inflation convergence criterion as required under Article 121 of the Treaty of Amsterdam and by the ECB for assessing price stability for monetary policy purposes. The ECB defines price stability on the basis of the annual rate of change of the euro area HICP. HICPs are compiled on the basis of harmonised standards, binding for all Member States. Conceptually, the HICP are Laspeyres-type price indices and are computed as annual chain-indices allowing for weights changing each year. The common classification for Harmonized Indices of Consumer Prices is the COICOP (Classification Of Individual COnsumption by Purpose). A version of this classification (COICOP/HICP) has been specially adapted for the HICP. Sub-indices published by Eurostat are based on this classification. HICP are produced and published using a common index reference period (2015 = 100). Growth rates are calculated from published index levels. Indexes, as well as both growth rates with respect to the previous month (M/M-1) and with respect to the corresponding month of the previous year (M/M-12) are neither calendar nor seasonally adjusted.

Harmonised Indices of Consumer Prices (HICP) are designed for international comparisons of consumer price inflation. HICPs are used for the assessment of the inflation convergence criterion as required under Article 121 of the Treaty of Amsterdam and by the ECB for assessing price stability for monetary policy purposes. The ECB defines price stability on the basis of the annual rate of change of the euro area HICP. HICPs are compiled on the basis of harmonised standards, binding for all Member States. Conceptually, the HICP are Laspeyres-type price indices and are computed as annual chain-indices allowing for weights changing each year. The common classification for Harmonized Indices of Consumer Prices is the COICOP (Classification Of Individual COnsumption by Purpose). A version of this classification (COICOP/HICP) has been specially adapted for the HICP. Sub-indices published by Eurostat are based on this classification. HICP are produced and published using a common index reference period (2015 = 100). Growth rates are calculated from published index levels. Indexes, as well as both growth rates with respect to the previous month (M/M-1) and with respect to the corresponding month of the previous year (M/M-12) are neither calendar nor seasonally adjusted.

Harmonised Indices of Consumer Prices (HICP) are designed for international comparisons of consumer price inflation. HICPs are used for the assessment of the inflation convergence criterion as required under Article 121 of the Treaty of Amsterdam and by the ECB for assessing price stability for monetary policy purposes. The ECB defines price stability on the basis of the annual rate of change of the euro area HICP. HICPs are compiled on the basis of harmonised standards, binding for all Member States. Conceptually, the HICP are Laspeyres-type price indices and are computed as annual chain-indices allowing for weights changing each year. The common classification for Harmonized Indices of Consumer Prices is the COICOP (Classification Of Individual COnsumption by Purpose). A version of this classification (COICOP/HICP) has been specially adapted for the HICP. Sub-indices published by Eurostat are based on this classification. HICP are produced and published using a common index reference period (2015 = 100). Growth rates are calculated from published index levels. Indexes, as well as both growth rates with respect to the previous month (M/M-1) and with respect to the corresponding month of the previous year (M/M-12) are neither calendar nor seasonally adjusted.

The Harmonised Index of Consumer Prices (HICP) gives comparable measures of inflation for the countries and country groups for which it is produced. It is an economic indicator that measures the change over time of the prices of consumer goods and services acquired by households. In other words, it is a set of consumer price indices (CPI) calculated according to a harmonised approach and a set of definitions as laid down in Regulations and recommendations. In addition, the HICP provides the official measure of consumer price inflation in the euro area for the purposes of monetary policy and the assessment of inflation convergence as required under the Maastricht criteria for accession to the euro. The HICP is available for all EU Member States, Iceland, Norway and Switzerland. In addition to the individual country series there are three key country-group aggregate indices: the euro area, the European Union (EU), and the European Economic Area (EEA), which, in addition to the EU, also covers Iceland and Norway, but not Liechtenstein. The official country-group aggregates reflect the changing country composition of the EA, the EU and the EEA. The HICP for new Member States is chained into the aggregate indices at the time of accession. For analytical purposes Eurostat also computes country-group aggregates with stable country composition over time. For example, the EU28 aggregate shows price indices covering all current 28 Member States since 1997. The HICP for Serbia and Turkey (candidate countries) are also published. That data are flagged 'd' ('definition differs'). A proxy-HICP for the all-items and main aggregates is available for the USA. National HICPs are produced by National Statistical Institutes (NSIs), while the country-group aggregates are produced by Eurostat. The data released monthly on Eurostat's free dissemination database include price indices and rates of change (monthly, annual and 12-month moving average changes). In addition to the headline figure 'all-items HICP', around four hundred sub-indices for different goods and services and over thirty special aggregates are available, including the HICP at administered prices (HICP-AP). Once a year, with the release of the January data, the relative weights for the indices and the special aggregates, are published for the individual countries and for the European aggregates. The composition of the HICP-AP aggregates, i.e. which sub-indices are classified as mainly or fully administered by each Member State, is also updated at the same time. Eurostat publishes early estimates, called 'HICP flash estimates', of the euro area overall inflation rate and selected components. They are published monthly, usually on the last working day of the reference month, and disseminated in a news release, in the database and in a Statistics Explained article. The HICP at constant tax rates (HICP-CT) follows the same computation principles as the HICP, but is based on prices at constant tax rates. The comparison with the standard HICP can show the potential impact of changes in indirect taxes, such as VAT and excise duties, on the overall inflation (more information). Flags Flags provide information about the 'status' of the data or a specific data value. The following flags are used for the HICP data in the Eurostat online database: p = provisional data: Data is flagged as provisional by the National Statistical Institutes to signal that data are still being treated or validated. The 'p' flag remains attached to the HICP data values in question for one month only. r = revised data. In the case when the most recent figures published differ from previously disseminated data, they are flagged with 'r'. Countries are allowed to revise their HICP figures at any point and, therefore, revised figures may appear in historic data. The 'r' flag remains attached to the HICP data values in question for one month only. e = estimated data. All the figures of the HICP flash estimate are marked with the 'e' flag. d = definition differs, meaning that the national definition of a series differs from the ECOICOP (European Classification of Individual Consumption according to Purpose) definition. It is also used for data values from countries for which conformity with the requirements of the HICP methodology has not yet been evaluated by Eurostat, including candidate countries, pre-candidate countries, new EU Member States and the United States of America. u = unreliable data. Data is flagged as unreliable by the National Statistical Institutes.

The Harmonised Index of Consumer Prices (HICP) gives comparable measures of inflation for the countries and country groups for which it is produced. It is an economic indicator that measures the change over time of the prices of consumer goods and services acquired by households. In other words, it is a set of consumer price indices (CPI) calculated according to a harmonised approach and a set of definitions as laid down in Regulations and recommendations. In addition, the HICP provides the official measure of consumer price inflation in the euro area for the purposes of monetary policy and the assessment of inflation convergence as required under the Maastricht criteria for accession to the euro. The HICP is available for all EU Member States, Iceland, Norway and Switzerland. In addition to the individual country series there are three key country-group aggregate indices: the euro area, the European Union (EU), and the European Economic Area (EEA), which, in addition to the EU, also covers Iceland and Norway, but not Liechtenstein. The official country-group aggregates reflect the changing country composition of the EA, the EU and the EEA. The HICP for new Member States is chained into the aggregate indices at the time of accession. For analytical purposes Eurostat also computes country-group aggregates with stable country composition over time. For example, the EU28 aggregate shows price indices covering all current 28 Member States since 1997. The HICP for Serbia and Turkey (candidate countries) are also published. That data are flagged 'd' ('definition differs'). A proxy-HICP for the all-items and main aggregates is available for the USA. National HICPs are produced by National Statistical Institutes (NSIs), while the country-group aggregates are produced by Eurostat. The data released monthly on Eurostat's free dissemination database include price indices and rates of change (monthly, annual and 12-month moving average changes). In addition to the headline figure 'all-items HICP', around four hundred sub-indices for different goods and services and over thirty special aggregates are available, including the HICP at administered prices (HICP-AP). Once a year, with the release of the January data, the relative weights for the indices and the special aggregates, are published for the individual countries and for the European aggregates. The composition of the HICP-AP aggregates, i.e. which sub-indices are classified as mainly or fully administered by each Member State, is also updated at the same time. Eurostat publishes early estimates, called 'HICP flash estimates', of the euro area overall inflation rate and selected components. They are published monthly, usually on the last working day of the reference month, and disseminated in a news release, in the database and in a Statistics Explained article. The HICP at constant tax rates (HICP-CT) follows the same computation principles as the HICP, but is based on prices at constant tax rates. The comparison with the standard HICP can show the potential impact of changes in indirect taxes, such as VAT and excise duties, on the overall inflation (more information). Flags Flags provide information about the 'status' of the data or a specific data value. The following flags are used for the HICP data in the Eurostat online database: p = provisional data: Data is flagged as provisional by the National Statistical Institutes to signal that data are still being treated or validated. The 'p' flag remains attached to the HICP data values in question for one month only. r = revised data. In the case when the most recent figures published differ from previously disseminated data, they are flagged with 'r'. Countries are allowed to revise their HICP figures at any point and, therefore, revised figures may appear in historic data. The 'r' flag remains attached to the HICP data values in question for one month only. e = estimated data. All the figures of the HICP flash estimate are marked with the 'e' flag. d = definition differs, meaning that the national definition of a series differs from the ECOICOP (European Classification of Individual Consumption according to Purpose) definition. It is also used for data values from countries for which conformity with the requirements of the HICP methodology has not yet been evaluated by Eurostat, including candidate countries, pre-candidate countries, new EU Member States and the United States of America. u = unreliable data. Data is flagged as unreliable by the National Statistical Institutes.

The Harmonised Index of Consumer Prices (HICP) gives comparable measures of inflation for the countries and country groups for which it is produced. It is an economic indicator that measures the change over time of the prices of consumer goods and services acquired by households. In other words, it is a set of consumer price indices (CPI) calculated according to a harmonised approach and a set of definitions as laid down in Regulations and recommendations. In addition, the HICP provides the official measure of consumer price inflation in the euro area for the purposes of monetary policy and the assessment of inflation convergence as required under the Maastricht criteria for accession to the euro. The HICP is available for all EU Member States, Iceland, Norway and Switzerland. In addition to the individual country series there are three key country-group aggregate indices: the euro area, the European Union (EU), and the European Economic Area (EEA), which, in addition to the EU, also covers Iceland and Norway, but not Liechtenstein. The official country-group aggregates reflect the changing country composition of the EA, the EU and the EEA. The HICP for new Member States is chained into the aggregate indices at the time of accession. For analytical purposes Eurostat also computes country-group aggregates with stable country composition over time. For example, the EU28 aggregate shows price indices covering all current 28 Member States since 1997. The HICP for Serbia and Turkey (candidate countries) are also published. That data are flagged 'd' ('definition differs'). A proxy-HICP for the all-items and main aggregates is available for the USA. National HICPs are produced by National Statistical Institutes (NSIs), while the country-group aggregates are produced by Eurostat. The data released monthly on Eurostat's free dissemination database include price indices and rates of change (monthly, annual and 12-month moving average changes). In addition to the headline figure 'all-items HICP', around four hundred sub-indices for different goods and services and over thirty special aggregates are available, including the HICP at administered prices (HICP-AP). Once a year, with the release of the January data, the relative weights for the indices and the special aggregates, are published for the individual countries and for the European aggregates. The composition of the HICP-AP aggregates, i.e. which sub-indices are classified as mainly or fully administered by each Member State, is also updated at the same time. Eurostat publishes early estimates, called 'HICP flash estimates', of the euro area overall inflation rate and selected components. They are published monthly, usually on the last working day of the reference month, and disseminated in a news release, in the database and in a Statistics Explained article. The HICP at constant tax rates (HICP-CT) follows the same computation principles as the HICP, but is based on prices at constant tax rates. The comparison with the standard HICP can show the potential impact of changes in indirect taxes, such as VAT and excise duties, on the overall inflation (more information). Flags Flags provide information about the 'status' of the data or a specific data value. The following flags are used for the HICP data in the Eurostat online database: p = provisional data: Data is flagged as provisional by the National Statistical Institutes to signal that data are still being treated or validated. The 'p' flag remains attached to the HICP data values in question for one month only. r = revised data. In the case when the most recent figures published differ from previously disseminated data, they are flagged with 'r'. Countries are allowed to revise their HICP figures at any point and, therefore, revised figures may appear in historic data. The 'r' flag remains attached to the HICP data values in question for one month only. e = estimated data. All the figures of the HICP flash estimate are marked with the 'e' flag. d = definition differs, meaning that the national definition of a series differs from the ECOICOP (European Classification of Individual Consumption according to Purpose) definition. It is also used for data values from countries for which conformity with the requirements of the HICP methodology has not yet been evaluated by Eurostat, including candidate countries, pre-candidate countries, new EU Member States and the United States of America. u = unreliable data. Data is flagged as unreliable by the National Statistical Institutes. The p, e, d and u flags described here do not affect the higher level of aggregation when assigned to a figure.

The Harmonised Index of Consumer Prices (HICP) gives comparable measures of inflation for the countries and country groups for which it is produced. It is an economic indicator that measures the change over time of the prices of consumer goods and services acquired by households. In other words, it is a set of consumer price indices (CPI) calculated according to a harmonised approach and a set of definitions as laid down in Regulations and recommendations. In addition, the HICP provides the official measure of consumer price inflation in the euro area for the purposes of monetary policy and the assessment of inflation convergence as required under the Maastricht criteria for accession to the euro. The HICP is available for all EU Member States, Iceland, Norway and Switzerland. In addition to the individual country series there are three key country-group aggregate indices: the euro area, the European Union (EU), and the European Economic Area (EEA), which, in addition to the EU, also covers Iceland and Norway, but not Liechtenstein. The official country-group aggregates reflect the changing country composition of the EA, the EU and the EEA. The HICP for new Member States is chained into the aggregate indices at the time of accession. For analytical purposes Eurostat also computes country-group aggregates with stable country composition over time. For example, the EU28 aggregate shows price indices covering all current 28 Member States since 1997. The HICP for Serbia and Turkey (candidate countries) are also published. That data are flagged 'd' ('definition differs'). A proxy-HICP for the all-items and main aggregates is available for the USA. National HICPs are produced by National Statistical Institutes (NSIs), while the country-group aggregates are produced by Eurostat. The data released monthly on Eurostat's free dissemination database include price indices and rates of change (monthly, annual and 12-month moving average changes). In addition to the headline figure 'all-items HICP', around four hundred sub-indices for different goods and services and over thirty special aggregates are available, including the HICP at administered prices (HICP-AP). Once a year, with the release of the January data, the relative weights for the indices and the special aggregates, are published for the individual countries and for the European aggregates. The composition of the HICP-AP aggregates, i.e. which sub-indices are classified as mainly or fully administered by each Member State, is also updated at the same time. Eurostat publishes early estimates, called 'HICP flash estimates', of the euro area overall inflation rate and selected components. They are published monthly, usually on the last working day of the reference month, and disseminated in a news release, in the database and in a Statistics Explained article. The HICP at constant tax rates (HICP-CT) follows the same computation principles as the HICP, but is based on prices at constant tax rates. The comparison with the standard HICP can show the potential impact of changes in indirect taxes, such as VAT and excise duties, on the overall inflation (more information). Flags Flags provide information about the 'status' of the data or a specific data value. The following flags are used for the HICP data in the Eurostat online database: p = provisional data: Data is flagged as provisional by the National Statistical Institutes to signal that data are still being treated or validated. The 'p' flag remains attached to the HICP data values in question for one month only. r = revised data. In the case when the most recent figures published differ from previously disseminated data, they are flagged with 'r'. Countries are allowed to revise their HICP figures at any point and, therefore, revised figures may appear in historic data. The 'r' flag remains attached to the HICP data values in question for one month only. e = estimated data. All the figures of the HICP flash estimate are marked with the 'e' flag. d = definition differs, meaning that the national definition of a series differs from the ECOICOP (European Classification of Individual Consumption according to Purpose) definition. It is also used for data values from countries for which conformity with the requirements of the HICP methodology has not yet been evaluated by Eurostat, including candidate countries, pre-candidate countries, new EU Member States and the United States of America. u = unreliable data. Data is flagged as unreliable by the National Statistical Institutes.

The Harmonised Index of Consumer Prices (HICP) gives comparable measures of inflation for the countries and country groups for which it is produced. It is an economic indicator that measures the change over time of the prices of consumer goods and services acquired by households. In other words, it is a set of consumer price indices (CPI) calculated according to a harmonised approach and a set of definitions as laid down in Regulations and recommendations. In addition, the HICP provides the official measure of consumer price inflation in the euro area for the purposes of monetary policy and the assessment of inflation convergence as required under the Maastricht criteria for accession to the euro. The HICP is available for all EU Member States, Iceland, Norway and Switzerland. In addition to the individual country series there are three key country-group aggregate indices: the euro area, the European Union (EU), and the European Economic Area (EEA), which, in addition to the EU, also covers Iceland and Norway, but not Liechtenstein. The official country-group aggregates reflect the changing country composition of the EA, the EU and the EEA. The HICP for new Member States is chained into the aggregate indices at the time of accession. For analytical purposes Eurostat also computes country-group aggregates with stable country composition over time. For example, the EU28 aggregate shows price indices covering all current 28 Member States since 1997. The HICP for Serbia and Turkey (candidate countries) are also published. That data are flagged 'd' ('definition differs'). A proxy-HICP for the all-items and main aggregates is available for the USA. National HICPs are produced by National Statistical Institutes (NSIs), while the country-group aggregates are produced by Eurostat. The data released monthly on Eurostat's free dissemination database include price indices and rates of change (monthly, annual and 12-month moving average changes). In addition to the headline figure 'all-items HICP', around four hundred sub-indices for different goods and services and over thirty special aggregates are available, including the HICP at administered prices (HICP-AP). Once a year, with the release of the January data, the relative weights for the indices and the special aggregates, are published for the individual countries and for the European aggregates. The composition of the HICP-AP aggregates, i.e. which sub-indices are classified as mainly or fully administered by each Member State, is also updated at the same time. Eurostat publishes early estimates, called 'HICP flash estimates', of the euro area overall inflation rate and selected components. They are published monthly, usually on the last working day of the reference month, and disseminated in a news release, in the database and in a Statistics Explained article. The HICP at constant tax rates (HICP-CT) follows the same computation principles as the HICP, but is based on prices at constant tax rates. The comparison with the standard HICP can show the potential impact of changes in indirect taxes, such as VAT and excise duties, on the overall inflation (more information). Flags Flags provide information about the 'status' of the data or a specific data value. The following flags are used for the HICP data in the Eurostat online database: p = provisional data: Data is flagged as provisional by the National Statistical Institutes to signal that data are still being treated or validated. The 'p' flag remains attached to the HICP data values in question for one month only. r = revised data. In the case when the most recent figures published differ from previously disseminated data, they are flagged with 'r'. Countries are allowed to revise their HICP figures at any point and, therefore, revised figures may appear in historic data. The 'r' flag remains attached to the HICP data values in question for one month only. e = estimated data. All the figures of the HICP flash estimate are marked with the 'e' flag. d = definition differs, meaning that the national definition of a series differs from the ECOICOP (European Classification of Individual Consumption according to Purpose) definition. It is also used for data values from countries for which conformity with the requirements of the HICP methodology has not yet been evaluated by Eurostat, including candidate countries, pre-candidate countries, new EU Member States and the United States of America. u = unreliable data. Data is flagged as unreliable by the National Statistical Institutes. The p, e, d and u flags described here do not affect the higher level of aggregation when assigned to a figure.

The Harmonised Index of Consumer Prices (HICP) gives comparable measures of inflation for the countries and country groups for which it is produced. It is an economic indicator that measures the change over time of the prices of consumer goods and services acquired by households. In other words, it is a set of consumer price indices (CPI) calculated according to a harmonised approach and a set of definitions as laid down in Regulations and recommendations. In addition, the HICP provides the official measure of consumer price inflation in the euro area for the purposes of monetary policy and the assessment of inflation convergence as required under the Maastricht criteria for accession to the euro. The HICP is available for all EU Member States, Iceland, Norway and Switzerland. In addition to the individual country series there are three key country-group aggregate indices: the euro area, the European Union (EU), and the European Economic Area (EEA), which, in addition to the EU, also covers Iceland and Norway, but not Liechtenstein. The official country-group aggregates reflect the changing country composition of the EA, the EU and the EEA. The HICP for new Member States is chained into the aggregate indices at the time of accession. For analytical purposes Eurostat also computes country-group aggregates with stable country composition over time. For example, the EU28 aggregate shows price indices covering all current 28 Member States since 1997. The HICP for Serbia and Turkey (candidate countries) are also published. That data are flagged 'd' ('definition differs'). A proxy-HICP for the all-items and main aggregates is available for the USA. National HICPs are produced by National Statistical Institutes (NSIs), while the country-group aggregates are produced by Eurostat. The data released monthly on Eurostat's free dissemination database include price indices and rates of change (monthly, annual and 12-month moving average changes). In addition to the headline figure 'all-items HICP', around four hundred sub-indices for different goods and services and over thirty special aggregates are available, including the HICP at administered prices (HICP-AP). Once a year, with the release of the January data, the relative weights for the indices and the special aggregates, are published for the individual countries and for the European aggregates. The composition of the HICP-AP aggregates, i.e. which sub-indices are classified as mainly or fully administered by each Member State, is also updated at the same time. Eurostat publishes early estimates, called 'HICP flash estimates', of the euro area overall inflation rate and selected components. They are published monthly, usually on the last working day of the reference month, and disseminated in a news release, in the database and in a Statistics Explained article. The HICP at constant tax rates (HICP-CT) follows the same computation principles as the HICP, but is based on prices at constant tax rates. The comparison with the standard HICP can show the potential impact of changes in indirect taxes, such as VAT and excise duties, on the overall inflation (more information). Flags Flags provide information about the 'status' of the data or a specific data value. The following flags are used for the HICP data in the Eurostat online database: p = provisional data: Data is flagged as provisional by the National Statistical Institutes to signal that data are still being treated or validated. The 'p' flag remains attached to the HICP data values in question for one month only. r = revised data. In the case when the most recent figures published differ from previously disseminated data, they are flagged with 'r'. Countries are allowed to revise their HICP figures at any point and, therefore, revised figures may appear in historic data. The 'r' flag remains attached to the HICP data values in question for one month only. e = estimated data. All the figures of the HICP flash estimate are marked with the 'e' flag. d = definition differs, meaning that the national definition of a series differs from the ECOICOP (European Classification of Individual Consumption according to Purpose) definition. It is also used for data values from countries for which conformity with the requirements of the HICP methodology has not yet been evaluated by Eurostat, including candidate countries, pre-candidate countries, new EU Member States and the United States of America. u = unreliable data. Data is flagged as unreliable by the National Statistical Institutes. The p, e, d and u flags described here do not affect the higher level of aggregation when assigned to a figure.

The Harmonised Index of Consumer Prices (HICP) gives comparable measures of inflation for the countries and country groups for which it is produced. It is an economic indicator that measures the change over time of the prices of consumer goods and services acquired by households. In other words, it is a set of consumer price indices (CPI) calculated according to a harmonised approach and a set of definitions as laid down in Regulations and recommendations. In addition, the HICP provides the official measure of consumer price inflation in the euro area for the purposes of monetary policy and the assessment of inflation convergence as required under the Maastricht criteria for accession to the euro. The HICP is available for all EU Member States, Iceland, Norway and Switzerland. In addition to the individual country series there are three key country-group aggregate indices: the euro area, the European Union (EU), and the European Economic Area (EEA), which, in addition to the EU, also covers Iceland and Norway, but not Liechtenstein. The official country-group aggregates reflect the changing country composition of the EA, the EU and the EEA. The HICP for new Member States is chained into the aggregate indices at the time of accession. For analytical purposes Eurostat also computes country-group aggregates with stable country composition over time. For example, the EU28 aggregate shows price indices covering all current 28 Member States since 1997. The HICP for Serbia and Turkey (candidate countries) are also published. That data are flagged 'd' ('definition differs'). A proxy-HICP for the all-items and main aggregates is available for the USA. National HICPs are produced by National Statistical Institutes (NSIs), while the country-group aggregates are produced by Eurostat. The data released monthly on Eurostat's free dissemination database include price indices and rates of change (monthly, annual and 12-month moving average changes). In addition to the headline figure 'all-items HICP', around four hundred sub-indices for different goods and services and over thirty special aggregates are available, including the HICP at administered prices (HICP-AP). Once a year, with the release of the January data, the relative weights for the indices and the special aggregates, are published for the individual countries and for the European aggregates. The composition of the HICP-AP aggregates, i.e. which sub-indices are classified as mainly or fully administered by each Member State, is also updated at the same time. Eurostat publishes early estimates, called 'HICP flash estimates', of the euro area overall inflation rate and selected components. They are published monthly, usually on the last working day of the reference month, and disseminated in a news release, in the database and in a Statistics Explained article. The HICP at constant tax rates (HICP-CT) follows the same computation principles as the HICP, but is based on prices at constant tax rates. The comparison with the standard HICP can show the potential impact of changes in indirect taxes, such as VAT and excise duties, on the overall inflation (more information). Flags Flags provide information about the 'status' of the data or a specific data value. The following flags are used for the HICP data in the Eurostat online database: p = provisional data: Data is flagged as provisional by the National Statistical Institutes to signal that data are still being treated or validated. The 'p' flag remains attached to the HICP data values in question for one month only. r = revised data. In the case when the most recent figures published differ from previously disseminated data, they are flagged with 'r'. Countries are allowed to revise their HICP figures at any point and, therefore, revised figures may appear in historic data. The 'r' flag remains attached to the HICP data values in question for one month only. e = estimated data. All the figures of the HICP flash estimate are marked with the 'e' flag. d = definition differs, meaning that the national definition of a series differs from the ECOICOP (European Classification of Individual Consumption according to Purpose) definition. It is also used for data values from countries for which conformity with the requirements of the HICP methodology has not yet been evaluated by Eurostat, including candidate countries, pre-candidate countries, new EU Member States and the United States of America. u = unreliable data. Data is flagged as unreliable by the National Statistical Institutes. The p, e, d and u flags described here do not affect the higher level of aggregation when assigned to a figure.

The annual Business demography data collection covers variables which explain the characteristics and demography of the business population. The methodology allows for the production of data on enterprise births (and deaths), that is, enterprise creations (cessations) that amount to the creation (dissolution) of a combination of production factors and where no other enterprises are involved. In other words, enterprises created or closed solely as a result of e.g. restructuring, merger or break-up are not considered. The data are drawn from business registers, although some countries improve the availability of data on employment and turnover by integrating other sources. Until 2010 reference year the harmonised data collection is carried out to satisfy the requirements for the Structural Indicators, used for monitoring progress of the Lisbon process, regarding business births, deaths and survival. Currently, business demography delivers key information for policy decision-making and for the indicators to support the Europe 2020 strategy. It also provides key data for the joint OECD-Eurostat "Entrepreneurship Indicators Programme". In summary, the collected indicators are as follows: Population of active enterprisesNumber of enterprise birthsNumber of enterprise survivals up to five yearsNumber of enterprise deathsRelated variables on employmentDerived indicators such as birth rates, death rates, survival rates and employment sharesAn additional set of indicators on high-growth enterprises and 'gazelles' (high-growth enterprises that are up to five years old) The complete list of the basic variables, delivered from the data providers (National Statistical Institutes) and the derived indicators, calculated by Eurostat, is attached in the Annexes of this document.  Geographically EU Member States and EFTA countries are covered. In practice not all Member States have participated in the first harmonised data collection exercises. The methodology laid down in the Eurostat-OECD Manual on Business Demography Statistics  is followed closely by most of the countries (see Country specific notes in the Annexes).

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.

The House Price Index (HPI) measures inflation in the residential property market. The HPI captures price changes of all kinds of residential property purchased by households (flats, detached houses, terraced houses, etc.), both new and existing. Only market prices are considered, self-build dwellings are therefore excluded. The land component of the residential property is included. These indices are the result of the work that National Statistical Institutes (NSIs) have been doing mostly within the framework of the Owner-Occupied Housing (OOH) pilot project coordinated by Eurostat. HPI is available for EU Member States, Iceland and Norway. In addition to the individual country series Eurostat produces indices for the euro area and for the EU. The national HPIs are produced by NSIs, while the European aggregates are computed by Eurostat, by aggregating the national indices. The data released quarterly on Eurostat's website include price indices themselves as well as their rates of change compared to the same quarter of the previous year. House Sales cover the total value of dwellings transactions at national level (both houses and flats) where the purchaser is a household. House Sales indicators complement the data on the HPI in order to offer a more comprehensive picture of the housing market. At this moment Eurostat is publishing the annual index for the value of housing transactions and the annual rate of change.

The section 'LFS series - detailed quarterly survey results' reports detailed quarterly results going beyond the EU-LFS main aggregates, which have a separate data domain and some methodological differences. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The ad-hoc module "young people on the labour market" provides supplementary information on the correlation between work-based learning and labour market outcomes.

The harmonised data on accidents at work are collected in the framework of the European Statistics on Accidents at Work (ESAW), on the basis of a methodology developed in 1990. The data refer to accidents at work resulting in more than 3 days' absence from work (serious accidents) and fatal accidents. A fatal accident is defined as an accident which leads to the death of a victim within one year of the accident. The indicators used are the number and incidence rate of serious and fatal accidents at work. The incidence rate of serious accidents at work is the number of persons involved in accidents at work with more than 3 days' absence per 100,000 persons in employment. The incidence rate of fatal accidents at work is the number of persons with fatal accidents at work per 100,000 persons in employment. The national ESAW sources are the declarations of accidents at work, either to the public (Social Security) or private specific insurance for accidents at work, or to other relevant national authority (Labour Inspection, etc.) for countries having a "universal" Social Security system. For the Netherlands only survey data are available for the non-fatal accidents at work (a special module in the national labour force survey). Sector coverage: In general the private sector is covered by all national reporting systems. However some important sectors are not covered by all Member States. The specification of sectors is given according to the NACE classification (NACE = Nomenclature statistique des activités économiques dans la Communauté européenne). The incidence rate is calculated for the total of the so-called 9 common branches (See point 3.6). For a structured metadata overview on variables, coverage of sectors and professional status please see also the annex Metadata_overview_2007.Statistical adjustments: Because the frequency of work accidents is higher in some branches (high-risk sectors), an adjustment is performed to get more standardised incidence rates. For more details, please see the summary methodology (link at the bottom of the page). Geographical coverage: For accidents at work, data are available for all old EU-Member States (EU 15) and Norway. The methodology has also been implemented in the New Member States and Switzerland with first data being available for the reference year 2004.

The basic or above basic overall digital skills represent the two highest levels of the overall digital skills indicator, which is a composite indicator based on selected activities performed by individuals aged 16-74 on the internet in the four specific areas (information, communication, problem solving, content creation). It is assumed that individuals having performed certain activities have the corresponding skills; therefore the indicator can be considered as a proxy of the digital competences and skills of individuals. The indicator is based on the EU survey on the ICT usage in households and by individuals and is available for the years 2015 and 2016 (it will be compiled in 2017 as well).

Industry, Trade and Services statistics are part of Short-term statistics (STS), they give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification (Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are presented in the following forms: UnadjustedCalendar adjustedSeasonally-adjusted Depending on the STS regulation, data are accessible monthly and quarterly. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction (volume)*Turnover: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic turnover into euro area and non euro area is available for the euro area countriesProducer prices (output prices)*: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic producer prices into euro area and non euro area is available for the euro area countriesImport prices*: Total, Euro area market, Non euro area market (euro area countries only)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries CONSTRUCTIONProduction (volume)*: Total of the construction sector, Building construction, Civil EngineeringLabour input indicators: Number of Persons Employed, Hours Worked, Gross Wages and SalariesConstruction costs IndexBuilding permits indicators*: Number of dwellings WHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (in value)Labour input indicators: Number of Persons Employed SERVICES Turnover (in value)*Producer prices (Ouput prices)*

The data in this dataset comes from the Common Questionnaire for Transport Statistics, developed and surveyed in co-operation between the United Nations Economic Commission for Europe (UNECE), the International Transport Forum (ITF) and Eurostat. The Common Questionnaire is not supported by a legal act, but is based on a gentlemen's agreement with the participating countries; the completeness varies from country to country. Eurostat’s datasets based on the Common Questionnaire cover annual data for the EU Member States, EFTA states and Candidate countries to the EU. Data for other participating countries are available through the ITF and the UNECE. In total, comparable transport data collected through the Common Questionnaire is available for close to 60 countries worldwide. The Common Questionnaire collects aggregated annual data on:Railway transportRoad transportInland waterways transportOil pipelines transportGas pipelines transport For each mode of transport, the Common Questionnaire cover some or all of the following sub-modules (the number of questions/variables within each sub-module varies between the different modes of transport):Infrastructure (All modes)Transport equipment (RAIL, ROAD and INLAND WATERWAYS)Enterprises, economic performance and employment (All modes)Traffic (RAIL, ROAD and INLAND WATERWAYS)Transport measurement (All modes) Accidents (ROAD only) The Common Questionnaire is completed by the competent national authorities. The responsibility for completing specific modules (e.g. Transport by Rail) or part of modules (e.g. Road Infrastructure) may be delegated to other national authorities in charge of specific fields.

The present data collection consists of the following indicators:Interest rates : Day-to-day money market interest rates, 3-month interest rates, Euro yields and Long term government bond yields - Maastricht definitionEuro/Ecu exchange rates: Exchange rates against the ECU/euroEffective exchange rates indices : Nominal Effective Exchange Rate, Real Effective Exchange Rate Â

The Balance of Payments (BOP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of an economic area during a given period. The Balance of payments provides harmonized information on international transactions which are part of the current account (goods, services, primary and secondary income), as well as on transactions which fall in the capital and the financial account. International investment position presents value of financial assets owned outside the economy and indebtedness of the economy to the rest of the world. BOP is an important macro-economic indicator used to assess the position of an economy (of credit or debit for current and capital acount, net acquisition of financial assets or net incurrence of liabilities for BOP financial account and international investment position) towards the external world. Out of BOP data, some indicators on international position of the EU and Member States are derived. Indicators on Main Balance of Payments and International Investment Position items as share of GDP are presented as percentage of GDP for given year or quarter and moving average for 3 consecutive years for:Balance, credit and debit flows of current and capital accounts and of main current account  items: goods, services, primary and secondary income,Net flows, net acquisition of financial assets and net incurrence of liabilities for total financial account and foreign direct investment,International investment position and net external debt at the end of reference quarter or year. Indicators on export market shares present shares of each EU Member State in total world exports of goods and services for given year, and 1-year and 5-year percentage changes of these shares, as well as shares in OECD exports and 5-year percentage changes of these shares.

The Balance of Payments is the statistical statement that systematically summarises transactions between residents and non-residents. It consists of the goods and services account, the primary income account, the secondary income account, the capital account and the financial account (BPM6 – 2.12). The international investment position (IIP) is a statistical statement that shows, at a specific point in time, the value and composition of: a) financial assets of residents of an economy that are claims on non-residents and gold bullion held as reserve assets , and b) liabilities of residents of an economy to non-residents. The difference between an economy's external financial assets and liabilities is the economy's net IIP, which may be positive or negative (BPM6 – 7.1). As with the financial account, financial assets and liabilities can be grouped into five functional categories: a) direct investment, b) portfolio investment, c) financial derivatives and employee stock options, d) other investment and e) reserve assets. (BPM6 – 7.12). The data presented are the "Net positions at the end of the period" and the partner is the "rest of world". Source of euro area data: European Central Bank (ECB).

Eurostat uses as a base for its work the OECD Benchmark Definition of Foreign Direct Investment Third Edition, a detailed operational definition fully consistent with the IMF Balance of Payments Manual, Fifth Edition, BPM5. Foreign direct investment (FDI) is the category of international investment made by an entity resident in one economy (direct investor) to acquire a lasting interest in an enterprise operating in another economy (direct investment enterprise). The lasting interest is deemed to exist if the direct investor acquires at least 10% of the voting power of the direct investment enterprise. FDI statistics record separately: 1) Inward FDI (or FDI in the reporting economy), namely investment by foreigners in enterprises resident in the reporting economy. 2) Outward FDI (or FDIabroad), namely investment by residents entities in affiliated enterprises abroad. FDI statistics record both the initial investment and all subsequent investment made by the direct investor, either in the form of equity capital, or in the form of loans, or in the form of reinvesting earnings. Investment made through other affiliated enterprises of the same group of the direct investor should also be recorded according to the international methodology. There are three main indicators: FDI flows, stocks and income. The indicators described in more detail below are presented in the complete tables with a breakdown by partner country or region and a breakdown by the kind of activity in which FDI is made. In the table called "Main indicators" there is a reduced breakdown by partners and data for total activity only. See the part on classification system for more detail. See also the User's guideon the structure on the database and for practical information on data downloading. 1) FDI flows denote the new investment made during the period. FDI flows are recorded in the Balance of Payments financial account. Total FDI flows are broken down by kind of instrument used for making the investment:Equity capital comprises equity in branches, all shares in subsidiaries and associates (except non-participating, preferred shares that are treated as debt securities and are included under other FDI capital) and other contributions such as the provision of machinery.Reinvested earnings consist of the direct investor's share (in proportion to equity participation) of earnings not distributed by the direct investment enterprise. Reinvested earnings are an imputed transaction. Reinvested earnings are also recorded with opposite sign among FDI income (see below). This recording represents not distributed income as being earned by the direct investor and reinvested in the direct investment enterprise at the same time.Other FDI capital (loans) covers the borrowing and lending of funds, including debt securities and trade credits between direct investors and direct investment enterprises. Debt transactions between affiliated financial intermediaries recorded under direct investment flows are limited to permanent debt. 2) FDI stocks (or positions) denote the value of the investment at the end of the period. FDI stocks are recorded in the International Investment Position. Outward FDI stocks are recorded as assets of the reporting economy, inward FDI stocks as liabilities. Similarly with flows, FDI stocks are broken down by kind of instrument. However, there are only two categories instead of three:Equity capital and reinvested earnings is the value of the own capital of the enterprise, including the value of own reserves that are accumulated from past reinvested earnings. Reserves corresponding to reinvested earnings are not shown separately from other equity capital as in the case of flows.Other FDI capital is the stock of debts (assets or liabilities) between the direct investors and the direct investment enterprise. 3) FDI income is the income accruing to direct investors during the period. FDI income is recorded in the current account of the Balance of Payments. Total FDI income is broken down by kind of income. The categories of FDI income available are linked to the breakdown of FDI flows and stocks by kind of instrument, namely:Dividends Dividends payable in the period and branch profits remitted to the direct investor, gross of any withholding taxes. Dividends include payments due on common and preferred shares.Reinvested earnings See definition under FDI flows.Interest on loans Interest accrued in the period on loans (other FDI capital) with affiliated enterprises, gross of any withholding tax. 4) FDI intensity Out of FDI annual data, an indicator useful to measure EU market integration is also calculated and disseminated in the domain Structural Indicators:FDI intensity as % of GDP: Average of inward and outward FDI flows divided by GDP. A higher index indicates higher new FDI during the period in relation to the size of the economy as measured by GDP. If this index increases over time, then the country/zone is becoming more integrated with the international economy.

The data in this dataset comes from the Common Questionnaire for Transport Statistics, developed and surveyed in co-operation between the United Nations Economic Commission for Europe (UNECE), the International Transport Forum (ITF) and Eurostat. The Common Questionnaire is not supported by a legal act, but is based on a gentlemen's agreement with the participating countries; the completeness varies from country to country. Eurostat’s datasets based on the Common Questionnaire cover annual data for the EU Member States, EFTA states and Candidate countries to the EU. Data for other participating countries are available through the ITF and the UNECE. In total, comparable transport data collected through the Common Questionnaire is available for close to 60 countries worldwide. The Common Questionnaire collects aggregated annual data on:Railway transportRoad transportInland waterways transportOil pipelines transportGas pipelines transport For each mode of transport, the Common Questionnaire cover some or all of the following sub-modules (the number of questions/variables within each sub-module varies between the different modes of transport):Infrastructure (All modes)Transport equipment (RAIL, ROAD and INLAND WATERWAYS)Enterprises, economic performance and employment (All modes)Traffic (RAIL, ROAD and INLAND WATERWAYS)Transport measurement (All modes)Accidents (ROAD only) The Common Questionnaire is completed by the competent national authorities. The responsibility for completing specific modules (e.g. Transport by Rail) or part of modules (e.g. Road Infrastructure) may be delegated to other national authorities in charge of specific fields.

This indicator shows the investment for the total economy, government, business as well as household sectors. The indicator gives the share of GDP that is used for gross investment (rather than being used for e.g. consumption or exports). It is defined as gross fixed capital formation (GFCF) expressed as a percentage of GDP for the government, business and households sectors. GFCF consists of resident producers' acquisitions, less disposals of fixed assets plus certain additions to the value of non-produced assets realised by productive activity, such as improvements to land. Fixed assets comprise, for example, dwellings, other buildings and structures (roads, bridges etc.), machinery and equipment, but also intangible assets such as computer software.

This indicator shows the investment for the total economy, government, business as well as household sectors. The indicator gives the share of GDP that is used for gross investment (rather than being used for e.g. consumption or exports). It is defined as gross fixed capital formation (GFCF) expressed as a percentage of GDP for the government, business and households sectors. GFCF consists of resident producers' acquisitions, less disposals of fixed assets plus certain additions to the value of non-produced assets realised by productive activity, such as improvements to land. Fixed assets comprise, for example, dwellings, other buildings and structures (roads, bridges etc.), machinery and equipment, but also intangible assets such as computer software and other intellectual property.

The indicator 'involuntary temporary employment' represents employees who could not find permanent job as a percentage of total employees. The indicator is based on the EU Labour Force Survey.

Indicator refers to employees aged 20 to 64 working on fixed-term contracts because they were unable to find a permanent job, expressed as share of total employees. Employees with temporary contracts are those who declare themselves as having a fixed term employment contract or a job which will terminate if certain objective criteria are met, such as completion of an assignment or return of the employee who was temporarily replaced.

Foreign direct investment (FDI) is the category of international investment made by a resident entity (direct investor) to acquire a lasting interest in an entity operating in an economy other than that of the investor (direct investment enterprise). The lasting interest is deemed to exist if the investor acquires at least 10% of the equity capital of the enterprise. For this indicator stocks of FDI in the reporting economy are expressed as percentage of GDP to remove the effect of differences in the size of the economies of the reporting countries.

Eurostat Dataset Id:yth_incl_130 The domain "Income and living conditions" covers four topics: people at risk of poverty or social exclusion, income distribution and monetary poverty, living conditions and material deprivation, which are again structured into collections of indicators on specific topics. The collection "People at risk of poverty or social exclusion" houses main indicator on risk of poverty or social inclusion included in the Europe 2020 strategy as well as the intersections between sub-populations of all Europe 2020 indicators on poverty and social exclusion. The collection "Income distribution and monetary poverty" houses collections of indicators relating to poverty risk, poverty risk of working individuals as well as the distribution of income. The collection "Living conditions" hosts indicators relating to characteristics and living conditions of households, characteristics of the population according to different breakdowns, health and labour conditions, housing conditions as well as childcare related indicators. The collection "Material deprivation" covers indicators relating to economic strain, durables, housing deprivation and environment of the dwelling.

The job vacancy rate (JVR) measures the proportion of total posts that are vacant, according to the definition of job vacancy above, expressed as a percentage as follows: JVR = number of job vacancies / (number of occupied posts + number of job vacancies) * 100. Data for Denmark, France, Italy, Malta are available in table jvs_q_nace2.

Job vacancy statistics (JVS) provide information on the level and structure of labour demand. Eurostat publishes quarterly data on the number of job vacancies and the number of occupied posts which are collected under the JVS framework regulation and the two implementing regulations: the implementing regulation on the definition of a job vacancy, the reference dates for data collection, data transmission specifications and feasibility studies, as well as the implementing regulation on seasonal adjustment procedures and quality reports. Eurostat disseminates also the job vacancy rate which is calculated on the basis of the data provided by the countries. Eurostat publishes also the annual data which are calculated on the basis of the quarterly data.

Flow statistics are experimental statistics derived from the longitudinal component of the EU-LFS data. They identify the flows between different labour market statuses between consecutive quarters. Flow statistics are published in the section 'LFS main indicators', which is a collection of the main statistics on the labour market derived from the EU-Labour Force Survey (EU-LFS). However, the flow indicators are calculated with special methods which justify the present page. Please note that countries may publish nationally slightly different results due to the use of more sophisticated methods. This page focuses on the particularities of the estimation of flow statistics. Other information on 'LFS main indicators' can be found in the respective ESMS page, see link in section 'related metadata'. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)'.  Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

Labour cost index shows the short-term development of the total cost, on an hourly basis, for employers of employing the labour force. The index covers all market economic activities except agriculture, forestry, fisheries, education, health, community, social and personal service activities. Labour costs include gross wages and salaries, employers social contributions and taxes net of subsidies connected to employment. The labour cost index is compiled as a "chain-linked Laspeyres cost-index" using a common index reference period (2016 = 100). The index is presented in calendar and seasonally adjusted form. Growth rates with respect to the previous quarter (Q/Q-1) are calculated from seasonally and calendar adjusted figures while growth rates with respect to the same quarter of the previous year (Q/Q-4) are calculated from calendar adjusted figures.

Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. The quarterly Labour Cost Index (LCI) is a Euro Indicator which measures the cost pressure arising from the production factor "labour". The data covered in the LCI collection relate to total average hourly labour costs and to the labour cost categories "wages and salaries" and "employers' social security contributions plus taxes paid minus subsidies received by the employer". Data - also broken down by economic activity, are available for the EU aggregates and EU Member States (NACE Rev 1.1 Sections C to K (1996Q1-2008Q4) and NACE Rev 2 Sections B to S), in working day and seasonally adjusted form. The data on the Labour Cost Index are given in the form of index numbers (current reference year: 2012) and of annual and quarterly growth rates (comparison with the previous quarter, or the same quarter of the previous year). On annual basis the labour cost levels (in Euro and national currency) are also published, based on the latest Labour Cost Survey inflated by the LCI. In contrast to the information collected for the other Labour Cost domains, the labour costs covered in the LCI do not include vocational training costs and other expenditure such as recruitment costs and working clothes expenditure. The data are estimated by the National Statistical Institutes on the basis of available structural and short-term information from samples and administrative records for enterprises of all sizes. The labour cost index (LCI) shows the short-term development of the labour cost, the total cost on an hourly basis of employing labour. In other words, the LCI measures the cost pressure arising from the production factor “labour”.  In addition, Eurostat estimates of the annual labour cost per hour in euros are provided for EU Member States as well as the whole EU; they were obtained by combining the four-yearly Labour cost survey (LCS) with the quarterly labour cost index. 

This table contains data on Average hourly labour costs which are defined as total labour costs divided by the corresponding number of hours worked by the yearly average number of employees, expressed in full-time units." Labour Costs (D) cover Wages and Salaries (D11) and non-wage costs (Employers’ social contributions plus taxes less subsidies: D12+D4-D5)

This table presents 3 indexes showing the development of labour input in the sector of industry (excluding construction): Number of persons employed, the hours worked and the wages and salaries. The number of person employed shows the development of employment in Industry. It can be defined as the total number of persons who work in the observation unit as well as persons who work outside the unit who belong to it and are paid by it. The hours worked show the development in the volume of work. The total number of hours worked represents the aggregate number of hours actually worked for the output of the observation unit during the reference period. The wages and salaries index approximate the development of the wage and salaries bill. Wages and salaries are defined as the total remuneration, in cash or in kind, payable to all persons counted on the payroll (including home workers), in return for work done during the accounting period, regardless of whether it is paid on the basis of working time, output or piecework and whether it is paid regularly. These three indexes are presented for the industrial sector (excluding construction) section B to E of NACE Rev.2 (E37, E38 and E39 not included). The indexes are presented in calendar and seasonally adjusted form.

The domain "Income and living conditions" covers four topics: people at risk of poverty or social exclusion, income distribution and monetary poverty, living conditions and material deprivation, which are again structured into collections of indicators on specific topics. The collection "People at risk of poverty or social exclusion" houses main indicator on risk of poverty or social inclusion included in the Europe 2020 strategy as well as the intersections between sub-populations of all Europe 2020 indicators on poverty and social exclusion. The collection "Income distribution and monetary poverty" houses collections of indicators relating to poverty risk, poverty risk of working individuals as well as the distribution of income. The collection "Living conditions" hosts indicators relating to characteristics and living conditions of households, characteristics of the population according to different breakdowns, health and labour conditions, housing conditions as well as childcare related indicators. The collection "Material deprivation" covers indicators relating to economic strain, durables, housing deprivation and environment of the dwelling.

This indicator shows the percentage of persons aged 16-64 having a temporary contract who moved to a permanent contract between two consecutive years. Figures are averaged over three years. The indicator is based on the EU-SILC (statistics on income, social inclusion and living conditions).

Long term government bond yields are calculated as monthly averages (non seasonally adjusted data). They refer to central government bond yields on the secondary market, gross of tax, with a residual maturity of around 10 years. The bond or the bonds of the basket have to be replaced regularly to avoid any maturity drift. This definition is used in the convergence criteria of the Economic and Monetary Union for long-term interest rates, as required under Article 121 of the Treaty of Amsterdam and the Protocol on the convergence criteria. Data are presented in raw form. Source: European Central Bank (ECB)

The long-term unemployment rate expresses the number of long-term unemployed aged 15-74 as a percentage of the active population of the same age. Long-term unemployed (12 months and more) comprise persons aged at least 15, who are not living in collective households, who will be without work during the next two weeks, who would be available to start work within the next two weeks and who are seeking work (have actively sought employment at some time during the previous four weeks or are not seeking a job because they have already found a job to start later). The total active population (labour force) is the total number of the employed and unemployed population. The duration of unemployment is defined as the duration of a search for a job or as the period of time since the last job was held (if this period is shorter than the duration of the search for a job). The indicator is based on the EU Labour Force Survey.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The Unemployment - LFS adjusted series (including also Harmonised long-term unemployment) is a collection of monthly, quarterly and annual series based on the quarterly results of the EU Labour Force Survey (EU-LFS), which are, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator. Harmonised unemployment is published in the section 'LFS main indicators', which is a collection of the main statistics on the labour market. However the harmonized unemployment indicators are calculated with special methods and periodicity which justify the present page. This page focuses on the particularities of the estimation of harmonised unemployment (including unemployment rates). Other information on 'LFS main indicators' can be found in the respective ESMS page, see link in section 'related metadata'. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)'.  Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The Unemployment - LFS adjusted series (including also Harmonised long-term unemployment) is a collection of monthly, quarterly and annual series based on the quarterly results of the EU Labour Force Survey (EU-LFS), which are, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator. Harmonised unemployment is published in the section 'LFS main indicators', which is a collection of the main statistics on the labour market. However the harmonized unemployment indicators are calculated with special methods and periodicity which justify the present page. This page focuses on the particularities of the estimation of harmonised unemployment (including unemployment rates). Other information on 'LFS main indicators' can be found in the respective ESMS page, see link in section 'related metadata'. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)'.  Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The indicator measures the share of the economically active population aged 15 to 74 who has been unemployed for 12 months or more. Unemployed persons are defined as all persons who were without work during the reference week, were currently available for work and were either actively seeking work in the last four weeks or had already found a job to start within the next three months. The unemployment period is defined as the duration of a job search, or as the length of time since the last job was held (if shorter than the time spent on a job search). The economically active population comprises employed and unemployed persons. The indicator is part of the adjusted, break-corrected main indicators series and should not be compared with the annual and quarterly non-adjusted series, which have slightly different results.

Long-term unemployed (12 months and more) comprise persons aged at least 15, who are not living in collective households, who will be without work during the next two weeks, who would be available to start work within the next two weeks and who are seeking work (have actively sought employment at some time during the previous four weeks or are not seeking a job because they have already found a job to start later). The total active population (labour force) is the total number of the employed and unemployed population. The duration of unemployment is defined as the duration of a search for a job or as the period of time since the last job was held (if this period is shorter than the duration of the search for a job).

The Structure of Earnings Survey (SES) provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is to provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES provides detailed and comparable information on the relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Unlike the other Structure of Earnings Survey tables, this dataset presents the main indicators of the several vintages of SES (SES2002 / SES2006 / SES2010 / SES2014) merged into one table. 

The Balance of Payments (BOP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of an economic area during a given period. The Balance of payments provides harmonized information on international transactions which are part of the current account (goods, services, primary and secondary income), as well as on transactions which fall in the capital and the financial account. International investment position presents value of financial assets owned outside the economy and indebtedness of the economy to the rest of the world. BOP is an important macro-economic indicator used to assess the position of an economy (of credit or debit for current and capital acount, net acquisition of financial assets or net incurrence of liabilities for BOP financial account and international investment position) towards the external world. Out of BOP data, some indicators on international position of the EU and Member States are derived. Indicators on Main Balance of Payments and International Investment Position items as share of GDP are presented as percentage of GDP for given year or quarter and moving average for 3 consecutive years for: Balance, credit and debit flows of current and capital accounts and of main current account  items: goods, services, primary and secondary income,Net flows, net acquisition of financial assets and net incurrence of liabilities for total financial account and foreign direct investment,International investment position and net external debt at the end of reference quarter or year. Indicators on export market shares present shares of each EU Member State in total world exports of goods and services for given year, and 1-year and 5-year percentage changes of these shares, as well as shares in OECD exports and 5-year percentage changes of these shares.

Results from the 2010 LFS (Labour Force Survey) ad hoc module on the reconciliation between work and family life. The aims of the module is to establish how far persons participate in the labour force as they wish and if not, whether the reasons are connected with a lack of suitable care services for children and dependant persons: 1. identification of care responsibilities (children and dependants) 2. analysis of the consequences on labour market participation taking into account the options and constraints given 3. in case of constraints, identification of those linked with the lack or unsuitability of care services A further aim is to analyse the degree of flexibility offered at work in terms of reconciliation with family life as well as to estimate how often career breaks occur and how far leave of absence is taken.

Results from the 2010 LFS (Labour Force Survey) ad hoc module on the reconciliation between work and family life. The aims of the module is to establish how far persons participate in the labour force as they wish and if not, whether the reasons are connected with a lack of suitable care services for children and dependant persons: 1. identification of care responsibilities (children and dependants) 2. analysis of the consequences on labour market participation taking into account the options and constraints given 3. in case of constraints, identification of those linked with the lack or unsuitability of care services A further aim is to analyse the degree of flexibility offered at work in terms of reconciliation with family life as well as to estimate how often career breaks occur and how far leave of absence is taken.

National accounts are a coherent and consistent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. Eurostat publishes annual and quarterly national accounts, annual and quarterly sector accounts as well as supply, use and input-output tables, which are each presented with associated metadata. Even though consistency checks are a major aspect of data validation, temporary (usually limited) inconsistencies between datasets may occur, mainly due to vintage effects. Quarterly national accounts are compiled in accordance with the European System of Accounts - ESA 2010 as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013.   The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. Further information (including actual communications) is presented on the Eurostat website.   The domain consists of the following collections: 1. Main GDP aggregates main components from the output, expenditure and income side, expenditure breakdowns by durability and exports and imports by origin.

National accounts are a coherent and consistent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. Eurostat publishes annual and quarterly national accounts, annual and quarterly sector accounts as well as supply, use and input-output tables, which are each presented with associated metadata. Even though consistency checks are a major aspect of data validation, temporary (usually limited) inconsistencies between datasets may occur, mainly due to vintage effects. Annual national accounts are compiled in accordance with the European System of Accounts - ESA 2010 as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013.   The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. Further information (including actual communications) is presented on the Eurostat website. The domain consists of the following collections:   1. Main GDP aggregates: main components from the output, expenditure and income side, expenditure breakdowns by durability and exports and imports by origin. <

The Balance of Payments (BoP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of a geographical region during a given period. The Balance of payments provides harmonized information on international transactions which are part of the current account (goods, services, income, current transfers), but also on transactions which fall in the capital and the financial account. BoP is an important macro-economic indicator used to assess the position of an economy (of credit or debit) towards the external world. Data on International Trade in Services, a component of BoP current account, and data on Foreign Direct Investment, a component of BoP financial account, are used to monitor the external commercial performance of different economies. Outward Foreign Affiliates Statistics (FATS) measure the commercial presence, as defined by the General Agreement on Trade in Services (GATS), through affiliates in foreign markets. Balance of Payments data are used for calculation of indicators needed for monitoring of macroenomic imbalances such as share of main BoP and International Investment Position (IIP) items in GDP and export market shares calculated as the EU Member States' shares in total world exports.  Out of BoP data, some indicators of EU market integration are also derived. Data are in millions of Euro/ECU or in millions of national currency. Balance of Payments data coverage varies according to the collection. Some collections refer only to Euro area or EU countries, while some others' coverage includes also EU partner countries.   Several statistical adjustments are applied to the original data provided by the Member States. The International Monetary Fund Balance of Payments Manual (BPM5) classification is used for the compilation of the BoP. The BoP data are collected through national surveys and administrative sources.    More information on BoP is available for each specific collection: Quarterly BoP, ITS, FDI, Outward FATS, BoP of EU Institutions.

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.

The Structure of Earnigns Survey is a 4-yearly survey conducted by the National Statistical Institutes (NSI). The tables published present data on number of employees, mean hourly earnings and hourly overtime pay, mean monthly earnings and overtime & shift pay, mean annual earnings and total annual bonuses, mean monthly hours paid and mean annual holidays. Details of available indicators and tables can be found under Annexes Tables 2002 at the bottom of this page. Regional metadata is identical to metadata provided for the national data.

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.

The Structure of Earnigns Survey is a 4-yearly survey conducted by the National Statistical Institutes (NSI). The tables published present data on number of employees, mean hourly earnings and hourly overtime pay, mean monthly earnings and overtime & shift pay, mean annual earnings and total annual bonuses, mean monthly hours paid and mean annual holidays. Details of available indicators and tables can be found under Annexes Tables 2002 at the bottom of this page. Regional metadata is identical to metadata provided for the national data.

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.

The Structure of Earnigns Survey is a 4-yearly survey conducted by the National Statistical Institutes (NSI). The tables published present data on number of employees, mean hourly earnings and hourly overtime pay, mean monthly earnings and overtime & shift pay, mean annual earnings and total annual bonuses, mean monthly hours paid and mean annual holidays. Details of available indicators and tables can be found under Annexes Tables 2002 at the bottom of this page. Regional metadata is identical to metadata provided for the national data.

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.

The Structure of Earnigns Survey is a 4-yearly survey conducted by the National Statistical Institutes (NSI). The tables published present data on number of employees, mean hourly earnings and hourly overtime pay, mean monthly earnings and overtime & shift pay, mean annual earnings and total annual bonuses, mean monthly hours paid and mean annual holidays. Details of available indicators and tables can be found under Annexes Tables 2002 at the bottom of this page. Regional metadata is identical to metadata provided for the national data.

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.

The Structure of Earnigns Survey is a 4-yearly survey conducted by the National Statistical Institutes (NSI). The tables published present data on number of employees, mean hourly earnings and hourly overtime pay, mean monthly earnings and overtime & shift pay, mean annual earnings and total annual bonuses, mean monthly hours paid and mean annual holidays. Details of available indicators and tables can be found under Annexes Tables 2002 at the bottom of this page. Regional metadata is identical to metadata provided for the national data.

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.