Eurostat

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).

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 20.6 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 20.6 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 20.6 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 20.6 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 20.6 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.

'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.

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 indicator is defined as the percentage of people aged 20-24 who have successfully completed at least upper secondary education. This educational attainment refers to ISCED (International Standard Classification of Education) 2011 level 3-8 for data from 2014 onwards and to ISCED 1997 level 3-6 for data up to 2013. The indicator is based on the EU Labour Force Survey. The indicator aims to measure the share of the population that is likely to have the minimum necessary qualifications to actively participate in social and economic life. It should be noted that completion of upper secondary education can be achieved in European countries after varying lengths of study, according to different national educational systems.

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 ad hoc module on work organisation and working time arrangements was included in the Labour Force Survey (LFS) and carried out in 2004. For a detailed evaluation of the ad hoc module see the publication, Eurostat (2006):"Final report of the task force for evaluating the 2004 LFS ad hoc module on work organisation and working time arrangements". The data cover all employees aged 25-49. The totals for the EU-25 referred to in the text and included in the figures and tables exclude Bulgaria and Romania since the data relate to period before these two joined the EU. There are no data for Bulgaria, the Czech Republic, Latvia, Lithuania, Poland, Sweden, and Croatia. In addition, there are no data in the following cases: a) Working arrangements by household circumstances: Denmark, Finland, Sweden, Norway and Switzerland; b) Employees working weekends and at night and convenience for personal life situation: Germany, Netherlands, Romania, Sweden, Norway and Switzerland.

The ad hoc module on work organisation and working time arrangements was included in the Labour Force Survey (LFS) and carried out in 2004. For a detailed evaluation of the ad hoc module see the publication, Eurostat (2006):"Final report of the task force for evaluating the 2004 LFS ad hoc module on work organisation and working time arrangements". The data cover all employees aged 25-49. The totals for the EU-25 referred to in the text and included in the figures and tables exclude Bulgaria and Romania since the data relate to period before these two joined the EU. There are no data for Bulgaria, the Czech Republic, Latvia, Lithuania, Poland, Sweden, and Croatia. In addition, there are no data in the following cases: a) Working arrangements by household circumstances: Denmark, Finland, Sweden, Norway and Switzerland; b) Employees working weekends and at night and convenience for personal life situation: Germany, Netherlands, Romania, Sweden, Norway and Switzerland.

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 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 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 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.

The Continuing Vocational Training Survey (CVTS) collects information on enterprises’ investment in the continuing vocational training of their staff. Continuing vocational training (CVT) refers to education or training measures or activities which are financed in total or at least partly by the enterprise (directly or indirectly). Part financing could include the use of work-time for the training activity as well as financing of training equipment. Information available from the CVTS is grouped around the following topics: Training/non-training enterprisesParticipation in continuing vocational trainingPlanning and assessment of continuing vocational trainingCosts of continuing vocational training coursesTime spent on continuing vocational training courses Four waves of the CVTS have been carried out by now: CVTS 1 – reference year 1993CVTS 2 – reference year 1999CVTS 3 – reference year 2005CVTS 4 – reference year 2010 The domain "Vocational training in enterprises (trng_cvts)" presents data for 2010 and 2005 which are comparable between the two waves. 2005 data which are not comparable with 2010 data are shown in the folder "Continuing vocational training - reference year 2005 (trng_cvts3)" and 1999 data are available in the folder "Continuing vocational training - reference year 1999 (trng_cvts2)". Both folders can be found in the domain "Past series (trng_h)". The first survey (CVTS 1) was carried out in the then 12 Member States of the European Union. CVTS 1 was of pioneering nature and due to lack of comparability with the following waves data are not available in Eurostat's online database but main results are available here. The next CVTS is due for reference year 2015.

The Continuing Vocational Training Survey (CVTS) collects information on enterprises’ investment in the continuing vocational training of their staff. Continuing vocational training (CVT) refers to education or training measures or activities which are financed in total or at least partly by the enterprise (directly or indirectly). Part financing could include the use of work-time for the training activity as well as financing of training equipment. Information available from the CVTS is grouped around the following topics: Training/non-training enterprisesParticipation in continuing vocational trainingPlanning and assessment of continuing vocational trainingCosts of continuing vocational training coursesTime spent on continuing vocational training courses Four waves of the CVTS have been carried out by now: CVTS 1 – reference year 1993CVTS 2 – reference year 1999CVTS 3 – reference year 2005CVTS 4 – reference year 2010 The domain "Vocational training in enterprises (trng_cvts)" presents data for 2010 and 2005 which are comparable between the two waves. 2005 data which are not comparable with 2010 data are shown in the folder "Continuing vocational training - reference year 2005 (trng_cvts3)" and 1999 data are available in the folder "Continuing vocational training - reference year 1999 (trng_cvts2)". Both folders can be found in the domain "Past series (trng_h)". The first survey (CVTS 1) was carried out in the then 12 Member States of the European Union. CVTS 1 was of pioneering nature and due to lack of comparability with the following waves data are not available in Eurostat's online database but main results are available here. The next CVTS is due for reference year 2015.

The Continuing Vocational Training Survey (CVTS) collects information on enterprises’ investment in the continuing vocational training of their staff. Continuing vocational training (CVT) refers to education or training measures or activities which are financed in total or at least partly by the enterprise (directly or indirectly). Part financing could include the use of work-time for the training activity as well as financing of training equipment. Information available from the CVTS is grouped around the following topics: Training/non-training enterprisesParticipation in continuing vocational trainingPlanning and assessment of continuing vocational trainingCosts of continuing vocational training coursesTime spent on continuing vocational training courses Four waves of the CVTS have been carried out by now: CVTS 1 – reference year 1993CVTS 2 – reference year 1999CVTS 3 – reference year 2005CVTS 4 – reference year 2010 The domain "Vocational training in enterprises (trng_cvts)" presents data for 2010 and 2005 which are comparable between the two waves. 2005 data which are not comparable with 2010 data are shown in the folder "Continuing vocational training - reference year 2005 (trng_cvts3)" and 1999 data are available in the folder "Continuing vocational training - reference year 1999 (trng_cvts2)". Both folders can be found in the domain "Past series (trng_h)". The first survey (CVTS 1) was carried out in the then 12 Member States of the European Union. CVTS 1 was of pioneering nature and due to lack of comparability with the following waves data are not available in Eurostat's online database but main results are available here. The next CVTS is due for reference year 2015.

The Continuing Vocational Training Survey (CVTS) collects information on enterprises’ investment in the continuing vocational training of their staff. Continuing vocational training (CVT) refers to education or training measures or activities which are financed in total or at least partly by the enterprise (directly or indirectly). Part financing could include the use of work-time for the training activity as well as financing of training equipment. Information available from the CVTS is grouped around the following topics: Training/non-training enterprisesParticipation in continuing vocational trainingPlanning and assessment of continuing vocational trainingCosts of continuing vocational training coursesTime spent on continuing vocational training courses Four waves of the CVTS have been carried out by now: CVTS 1 – reference year 1993CVTS 2 – reference year 1999CVTS 3 – reference year 2005CVTS 4 – reference year 2010 The domain "Vocational training in enterprises (trng_cvts)" presents data for 2010 and 2005 which are comparable between the two waves. 2005 data which are not comparable with 2010 data are shown in the folder "Continuing vocational training - reference year 2005 (trng_cvts3)" and 1999 data are available in the folder "Continuing vocational training - reference year 1999 (trng_cvts2)". Both folders can be found in the domain "Past series (trng_h)". The first survey (CVTS 1) was carried out in the then 12 Member States of the European Union. CVTS 1 was of pioneering nature and due to lack of comparability with the following waves data are not available in Eurostat's online database but main results are available here. The next CVTS is due for reference year 2015.

The Continuing Vocational Training Survey (CVTS) collects information on enterprises’ investment in the continuing vocational training of their staff. Continuing vocational training (CVT) refers to education or training measures or activities which are financed in total or at least partly by the enterprise (directly or indirectly). Part financing could include the use of work-time for the training activity as well as financing of training equipment. Information available from the CVTS is grouped around the following topics: Training/non-training enterprisesParticipation in continuing vocational trainingPlanning and assessment of continuing vocational trainingCosts of continuing vocational training coursesTime spent on continuing vocational training courses Four waves of the CVTS have been carried out by now: CVTS 1 – reference year 1993CVTS 2 – reference year 1999CVTS 3 – reference year 2005CVTS 4 – reference year 2010 The domain "Vocational training in enterprises (trng_cvts)" presents data for 2010 and 2005 which are comparable between the two waves. 2005 data which are not comparable with 2010 data are shown in the folder "Continuing vocational training - reference year 2005 (trng_cvts3)" and 1999 data are available in the folder "Continuing vocational training - reference year 1999 (trng_cvts2)". Both folders can be found in the domain "Past series (trng_h)". The first survey (CVTS 1) was carried out in the then 12 Member States of the European Union. CVTS 1 was of pioneering nature and due to lack of comparability with the following waves data are not available in Eurostat's online database but main results are available here. The next CVTS is due for reference year 2015.

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

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.

Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category: Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below: Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.

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 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 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.

'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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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.

The Human Resources in Science and Technology (HRST) domain provides data on stocks and flows (where flows in turn are divided into job-to-job mobility and education inflows). Stocks and flows are the main statistics for HRST. Their methodologies interlink and are therefore presented together in one single metadata-file. This metadata-file is duplicated in the structure of Eurostat's online database, while statistics for stocks and flows are found in separate folders. Several breakdowns are available for stocks and flows indicators: sex, age, region, sector of economic activity, occupation, educational attainment, fields of education, although not all combinations are possible. The data on stocks and job-to-job mobility are obtained from the European Union Labour Force Survey (EU LFS). The National Statistical Institutes are responsible for conducting the surveys and forwarding the results to Eurostat. The data on education inflows are obtained from Eurostat's Education database and in turn obtained via the UNESCO/OECD/Eurostat questionnaire on education. The National Statistical Institutes are responsible for conducting the surveys, compiling the results and forwarding the results to Eurostat. 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.

The Human Resources in Science and Technology (HRST) domain provides data on stocks and flows (where flows in turn are divided into job-to-job mobility and education inflows). Stocks and flows are the main statistics for HRST. Their methodologies interlink and are therefore presented together in one single metadata-file. This metadata-file is duplicated in the structure of Eurostat's online database, while statistics for stocks and flows are found in separate folders. Several breakdowns are available for stocks and flows indicators: sex, age, region, sector of economic activity, occupation, educational attainment, fields of education, although not all combinations are possible. The data on stocks and job-to-job mobility are obtained from the European Union Labour Force Survey (EU LFS). The National Statistical Institutes are responsible for conducting the surveys and forwarding the results to Eurostat. The data on education inflows are obtained from Eurostat's Education database and in turn obtained via the UNESCO/OECD/Eurostat questionnaire on education. The National Statistical Institutes are responsible for conducting the surveys, compiling the results and forwarding the results to Eurostat. 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.

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 tables presented in the topic of active population cover the total population for 31 countries (for more information on received tables and geographic coverage, see "2001 Census Round - Tables Received" in the Annex at the bottom of the page). The level of completeness of the tables depends largely on the availability of data at the respective national statistical institutes. There are four ways of collecting census data, namely: - the traditional method of using census questionnaires (exhaustive census); - the method of using registers and/or other administrative sources; - a combination of registers and/or other administrative sources and - surveys (complete enumerations or sample surveys). Other methods (other mixed census or micro-census) can be used as well. Details for the method employed by each country are provided in "2001 Census Method"in the Annex at the bottom of the page. In the same table you can find the dates on which the census was carried out in each country.

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

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 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 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 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 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 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 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 '20.5 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.

Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'. The aim of the ad hoc module was to know how the transition at the end of the career towards full retirement is expected to take place, takes place or took place: • plans for transitions/past transitions towards full retirement • plans for exit from work Another aim was to know which factors would be/were at play in determining the exit from work, and which factors could make/could have made persons postpone the exit from work: • working conditions factors (health and safety at the workplace, flexible working time arrangements …) • other factors linked to work (training/obsolescence of skills …) • financial factors (financial incentives to remain at work or to exit) • personal factors (health, family reasons …).

Introduction Key available data are presented on population and housing based on the decennial census rounds 1981-2011. Separate tables cover: - Population by sex and major age group - Population by educational attainment - Population by activity status - Population by citizenship - Households by household size - Occupied conventional dwellings by number of rooms Data availability varies between census rounds. The countries covered by the data vary between different census rounds. There are also differences in definitions and disaggregations between countries and between census rounds.

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.

Data given in this domain are collected on a yearly basis by the National Statistical Institutes or Ministries and are based on the annual Eurostat Model Questionnaires on ICT (Information and Communication Technologies) usage and e-commerce in enterprises. Large part of the data collected are used in the context of the 2011 - 2015 benchmarking framework (endorsed by i2010 High Level Group in November 2009) for the Digital Agenda Scoreboard, Europe's strategy for a flourishing digital economy by 2020. This conceptual framework follows the i2010 Benchmarking Framework which itself followed-up the eEurope 2005 Action Plan. The aim of the European ICT usage surveys is to collect and disseminate harmonised and comparable information on the use of Information and Communication Technologies in enterprises and e-commerce at European level. Coverage: The characteristics to be provided are drawn from the following list of subjects: - ICT systems and their usage in enterprises, - use of the Internet and other electronic networks by enterprises, - e-commerce, - e-business processes and organisational aspects, - use of ICT by enterprises to exchange information and services with governments and public administrations (e-government), - ICT competence in the enterprise and the need for ICT skills, - barriers to the use of ICT, the Internet and other electronic networks, e-commerce and e-business processes, - ICT expenditure and investment, - ICT security and trust, - use of ICT and its impact on the environment (Green ICT), - access to and use of the Internet and other network technologies for connecting objects and devices (Internet of Things), - access to and use of technologies providing the ability to connect to the Internet or other networks from anywhere at any time (ubiquitous connectivity). Breakdowns: - by size class, - by NACE categories, - by region (until 2010)

Data given in this domain are collected on a yearly basis by the National Statistical Institutes or Ministries and are based on the annual Eurostat Model Questionnaires on ICT (Information and Communication Technologies) usage and e-commerce in enterprises. Large part of the data collected are used in the context of the 2011 - 2015 benchmarking framework (endorsed by i2010 High Level Group in November 2009) for the Digital Agenda Scoreboard, Europe's strategy for a flourishing digital economy by 2020. This conceptual framework follows the i2010 Benchmarking Framework which itself followed-up the eEurope 2005 Action Plan. The aim of the European ICT usage surveys is to collect and disseminate harmonised and comparable information on the use of Information and Communication Technologies in enterprises and e-commerce at European level. Coverage: The characteristics to be provided are drawn from the following list of subjects: - ICT systems and their usage in enterprises, - use of the Internet and other electronic networks by enterprises, - e-commerce, - e-business processes and organisational aspects, - use of ICT by enterprises to exchange information and services with governments and public administrations (e-government), - ICT competence in the enterprise and the need for ICT skills, - barriers to the use of ICT, the Internet and other electronic networks, e-commerce and e-business processes, - ICT expenditure and investment, - ICT security and trust, - use of ICT and its impact on the environment (Green ICT), - access to and use of the Internet and other network technologies for connecting objects and devices (Internet of Things), - access to and use of technologies providing the ability to connect to the Internet or other networks from anywhere at any time (ubiquitous connectivity). Breakdowns: - by size class, - by NACE categories, - by region (until 2010)

Data given in this domain are collected on a yearly basis by the National Statistical Institutes or Ministries and are based on the annual Eurostat Model Questionnaires on ICT (Information and Communication Technologies) usage and e-commerce in enterprises. Large part of the data collected are used in the context of the 2011 - 2015 benchmarking framework (endorsed by i2010 High Level Group in November 2009) for the Digital Agenda Scoreboard, Europe's strategy for a flourishing digital economy by 2020. This conceptual framework follows the i2010 Benchmarking Framework which itself followed-up the eEurope 2005 Action Plan. The aim of the European ICT usage surveys is to collect and disseminate harmonised and comparable information on the use of Information and Communication Technologies in enterprises and e-commerce at European level. Coverage: The characteristics to be provided are drawn from the following list of subjects: - ICT systems and their usage in enterprises, - use of the Internet and other electronic networks by enterprises, - e-commerce, - e-business processes and organisational aspects, - use of ICT by enterprises to exchange information and services with governments and public administrations (e-government), - ICT competence in the enterprise and the need for ICT skills, - barriers to the use of ICT, the Internet and other electronic networks, e-commerce and e-business processes, - ICT expenditure and investment, - ICT security and trust, - use of ICT and its impact on the environment (Green ICT), - access to and use of the Internet and other network technologies for connecting objects and devices (Internet of Things), - access to and use of technologies providing the ability to connect to the Internet or other networks from anywhere at any time (ubiquitous connectivity). Breakdowns: - by size class, - by NACE categories, - by region (until 2010)

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.

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 tables Population 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 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 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 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 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 '20.5 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 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 '20.5 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 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 '20.5 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 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.

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.

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.

Persons in employment are those who, during the reference week, did any work for pay or profit, or were not working but had a job from which they were temporarily absent. Anyone who receives a wage for on-the-job training that involves the production of goods or services is also considered as being in employment. Self-employed and family workers are also included. Employment is measured in number of persons without distinction according to full-time or part-time work. Employment growth rates are based on employed persons. They are expressed as percentage change comparing year Y with year Y-1 and in 1000 persons. Data are sourced from National accounts data. The ESA 2010 distinguishes two employment concepts depending on the geographical coverage: resident persons in employment (i.e. the national scope of employment) and employment in resident production units irrespective of the place of residence of the employed person (i.e. domestic scope). The table presents total employment, according to the domestic concept.

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).

The data in this domain is collected by Eurostat in close cooperation with DG MARKT in the context of the annual "EU Postal Survey" (voluntary data collection). The partners in the data collection are the National Regulatory Authorities (NRAs) in the participating countries. The list of indicators/questionnaires and the definitions (Glossary) were agreed in cooperation with the European Postal Regulators in the project group "Assistance and development of EU statistics" of the European Committee for Postal Regulation (CERP). The data presented cover the companies operating under the Universal Service obligation (Universal Service Providers - USP). For countries where a USP no longer exists, the company which was the USP prior to liberalisation is referred to. "Universal service" refers here to the set of general interest demands to which services such as the mail should be subject throughout the Community.  The collection of 'Postal Services' includes data on employment, turnover, access points, traffic, prices and quality of service.

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 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 focus of this domain is on the European Neighbourhood Policy (ENP) countries on the southern and eastern shores of the Mediterranean (ENP-South), namely: Algeria (DZ),Egypt (EG),Israel (IL),Jordan (JO),Lebanon (LB),Libya (LY),Morocco (MA),Palestine (PS),Syria (SY) andTunisia (TN). An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. The data and their denomination in no way constitute the expression of an opinion by the European Commission on the legal status of a country or territory or on the delimitation of its borders.

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:

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 '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 '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 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 and calendar 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.

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. 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 non adjusted data (NSA).

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 '20.5 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 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 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.

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 '20.5 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 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 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 '20.5 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 '20.5 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 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 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 '20.5 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 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 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 '20.5 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 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 '20.5 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 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 '20.5 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.

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.

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.

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.

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.

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.

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.

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 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.

Eurostat's database covers: 1) Production and trade in roundwood and wood products, including primary and secondary products; 2) Economic data on forestry and logging, including employment data; 3) Sustainable forest management, comprising forest resources (assets) and environmental data. The main types of primary forest products included in (1) are: roundwood, sawnwood, wood-based panels, pulp, and paper and paperboard. Secondary products include further processed wood and paper products. These products are presented in greater detail; definitions are available. All of the data are compiled from the Joint Forest Sector Questionnaire (JFSQ), except for table (e), which is directly extracted from Eurostat's international trade database COMEXT (HS/CN Chapter 44). The tables in (1) cover details of the following topics: - Roundwood removals and production by type of wood and assortment (a) - Roundwood production by type of ownership (b) - Production and trade in roundwood, fuelwood and other basic products (c) - Trade in industrial roundwood by assortment and species (d) - Tropical wood imports to the EU from Chapter 44 of the Harmonised System (e) - Production and trade in sawnwood, panels and other primary products (f) - Sawnwood trade by species (g) - Production and trade in pulp and paper & paperboard (h) - Trade in secondary wood and paper products (i) Data in (2) include the output, intermediate consumption, gross value added, fixed capital consumption, gross fixed capital formation and different measures of income of forestry and logging. The data are in current basic prices and are compatible with National Accounts. They are collected as part of Intergrated environmental and economic accounting for forests (IEEAF), which also covers labour input in annual work units (AWU). Under (2), two separate tables cover the number of employees of forestry and logging, the manufacture of wood and products of wood and cork, and the manufacture of paper and paper products, as estimated from the Labour Force Survey results. There are two separate tables because of the change in the EU's classification of economic activities from NACE Rev. 1.1 to NACE Rev. 2 in 2008. More detailed information on wood products and accounting, including definitions and questionnaires, can be found on our open-access communication platform under the interest group 'Forestry statistics and accounts'. Data in (3) are not collected by Eurostat, but by the FAO, UNECE, Forest Euope, the European Commission's departments for Environment and the Joint Research Centre. They include forest area, wood volume, defoliation on sample plots, fires and areas with protective functions.

Eurostat's database covers 1) Production and trade in roundwood and wood products, including primary and secondary products 2) Economic data on forestry and logging, including employment data 3) Sustainable forest management, comprising forest resources (assets) and environmental data. The main types of primary forest products included in (1) are: roundwood, sawnwood, wood-based panels, pulp, and paper and paperboard. Secondary products include further processed wood and paper products. These products are presented in greater detail; definitions are available. All of the data are compiled from the Joint Forest Sector Questionnaire (JFSQ), except for table (e), which is directly extracted from Eurostat's international trade database COMEXT (HS/CN Chapter 44). The tables in (1) cover details of the following topics: - Roundwood removals and production by type of wood and assortment (a) - Roundwood production by type of ownership (b) - Production and trade in roundwood, fuelwood and other basic products (c) - Trade in industrial roundwood by assortment and species (d) - Tropical wood imports to the EU from Chapter 44 of the Harmonised System (e) - Production and trade in sawnwood, panels and other primary products (f) - Sawnwood trade by species (g) - Production and trade in pulp and paper & paperboard (h) - Trade in secondary wood and paper products (i) Data in (2) include the output, intermediate consumption, gross value added, fixed capital consumption, gross fixed capital formation and different measures of income of forestry and logging.  The data are in current basic prices and are compatible with National Accounts. They are collected as part of Intergrated environmental and economic accounting for forests (IEEAF), which also covers labour input in annual work units (AWU).  Under (2), two separate tables cover the number of employees of forestry and logging, the manufacture of wood and products of wood and cork, and the manufacture of paper and paper products, as estimated from the Labour Force Survey results. There are two separate tables because of the change in the EU's classification of economic activities from NACE Rev. 1.1 to NACE Rev. 2 in 2008. More detailed information on wood products and accounting, including definitions and questionnaires, can be found on our open-access communication platform under the interest group 'Forestry statistics and accounts'.  Data in (3) are not collected by Eurostat, but by the FAO, UNECE, Forest Euope, the European Commission's departments for Environment and the Joint Research Centre. They include forest area, wood volume, defoliation on sample plots, fires and areas with protective functions.

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 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 data shows the employment in high- and medium-high technology manufacturing sectors (code C_HTC_MH) and in knowledge-intensive service sectors (code KIS) 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 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.

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 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 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 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 ITFand 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.

Sport employment statistics are derived from data on employment based on the results of the European Labour Force Survey (EU-LFS). Employment in sport statistics aim at investigating on the dimension of the contribution of sport employment to the overall employment. The EU-LFS is the main source of information about the situation and trends on the labour market in the European Union . The methodology for the design and development of sport employment statistics is based on the one proposed by the final report of the European Statistical System Network on Culture (ESS-Net Culture Report 2012) which takes into account two reference classifications: the NACE classification (‘Nomenclature générale des Activités économiques dans les Communautés Européennes’) which classifies the main economic  activitiesthe ISCO classification (‘International Standard Classification of Occupations’) which classifies occupations. Results from the EU-LFS allow characterizing employment in sport by different variables such as gender, age, educational attainment by cross-tabulating ISCO and NACE selected sport codes.

Sport employment statistics are derived from data on employment based on the results of the European Labour Force Survey (EU-LFS). Employment in sport statistics aim at investigating on the dimension of the contribution of sport employment to the overall employment. The EU-LFS is the main source of information about the situation and trends on the labour market in the European Union . The methodology for the design and development of sport employment statistics is based on the one proposed by the final report of the European Statistical System Network on Culture (ESS-Net Culture Report 2012) which takes into account two reference classifications: the NACE classification (‘Nomenclature générale des Activités économiques dans les Communautés Européennes’) which classifies the main economic  activitiesthe ISCO classification (‘International Standard Classification of Occupations’) which classifies occupations. Results from the EU-LFS allow characterizing employment in sport by different variables such as gender, age, educational attainment by cross-tabulating ISCO and NACE selected sport codes.

Sport employment statistics are derived from data on employment based on the results of the European Labour Force Survey (EU-LFS). Employment in sport statistics aim at investigating on the dimension of the contribution of sport employment to the overall employment. The EU-LFS is the main source of information about the situation and trends on the labour market in the European Union . The methodology for the design and development of sport employment statistics is based on the one proposed by the final report of the European Statistical System Network on Culture (ESS-Net Culture Report 2012) which takes into account two reference classifications: the NACE classification (‘Nomenclature générale des Activités économiques dans les Communautés Européennes’) which classifies the main economic  activitiesthe ISCO classification (‘International Standard Classification of Occupations’) which classifies occupations. Results from the EU-LFS allow characterizing employment in sport by different variables such as gender, age, educational attainment by cross-tabulating ISCO and NACE selected sport codes.

'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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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 low skilled persons is calculated by dividing the number of persons in employment with at most lower secondary education (i.e. ISCED 0-2) and aged 20-64 by the total population in the same age and skill group. The indicator is based on the EU Labour Force Survey.

The employment rate of non-EU nationals is calculated by dividing the number of citizens of countries outside the EU27 (from 2020) in employment and aged 20-64 by the total number of citizens of countries outside the EU27 (from 2020) in the same age group. The indicator is based on the EU Labour Force Survey.

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.

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.

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 European Union Labour Force Survey (EU-LFS) provides population estimates for the main labour market characteristics, such as employment, unemployment, inactivity, hours of work, occupation, economic activity and much else, as well as important socio-demographic characteristics, such as sex, age, education, households and regions of residence. Since 1999 an inherent part of the European Union labour force survey (LFS) are the so called 'ad-hoc modules' (AHM). Council Regulation No 577/98 specifies that a further set of variables (the AHM) may be added to supplement the information obtained from the core questionnaire of the LFS. The topic covered by the ad hoc module change every year, although some of them have been repeated.

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 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 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 ‘employment rates of recent graduates’ presents 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.

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 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.

'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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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 under Annexes section. 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.

Persons in employment are those who, during the reference week, did any work for pay or profit, or were not working but had a job from which they were temporarily absent. Anyone who receives a wage for on-the-job training that involves the production of goods or services is also considered as being in employment. Self-employed and family workers are also included. Employment is measured in number of persons without distinction according to full-time or part-time work. Employment growth rates are based on employed persons. They are expressed as percentage change comparing year Y with year Y-1 and in 1000 persons. Data are sourced from National accounts data. The ESA 2010 distinguishes two employment concepts depending on the geographical coverage: resident persons in employment (i.e. the national scope of employment) and employment in resident production units irrespective of the place of residence of the employed person (i.e. domestic scope). The table presents total employment, according to the domestic concept.

Persons in employment are those who, during the reference week, did any work for pay or profit, or were not working but had a job from which they were temporarily absent. Anyone who receives a wage for on-the-job training that involves the production of goods or services is also considered as being in employment. Self-employed and family workers are also included. Employment is measured in number of persons without distinction according to full-time or part-time work. The data are expressed in 1000 persons. The quarterly data are not seasonally adjusted. Data are sourced from National accounts data. The ESA 2010 distinguishes two employment concepts depending on the geographical coverage: resident persons in employment (i.e. the national scope of employment) and employment in resident production units irrespective of the place of residence of the employed person (i.e. domestic scope). The table presents total employment, according to the domestic concept.

Table tec00112 presents data on employment, based on the domestic concept. Employment covers all persons engaged in some productive activity that falls within the production boundary of the national accounts. Employed persons are either employees (persons who work by agreement, work for a resident institutional unit and receive a remuneration recorded as compensation of employees) or self-employed (persons who are the sole owners, or joint owners, of the unincorporated enterprises in which they work, excluding those unincorporated enterprises that are classified as quasi-corporations).The domestic concept of employment includes both the residents and the non-residents who work for resident producer units.

The Continuing Vocational Training Survey (CVTS) collects information on enterprises’ investment in the continuing vocational training of their staff. Continuing vocational training (CVT) refers to education or training measures or activities which are financed in total or at least partly by the enterprise (directly or indirectly). Part financing could include the use of work-time for the training activity as well as financing of training equipment. Information available from the CVTS is grouped around the following topics: Training/non-training enterprisesParticipation in continuing vocational trainingPlanning and assessment of continuing vocational trainingCosts of continuing vocational training coursesTime spent on continuing vocational training courses Four waves of the CVTS have been carried out by now: CVTS 1 – reference year 1993CVTS 2 – reference year 1999CVTS 3 – reference year 2005CVTS 4 – reference year 2010 The domain "Vocational training in enterprises (trng_cvts)" presents data for 2010 and 2005 which are comparable between the two waves. 2005 data which are not comparable with 2010 data are shown in the folder "Continuing vocational training - reference year 2005 (trng_cvts3)" and 1999 data are available in the folder "Continuing vocational training - reference year 1999 (trng_cvts2)". Both folders can be found in the domain "Past series (trng_h)". The first survey (CVTS 1) was carried out in the then 12 Member States of the European Union. CVTS 1 was of pioneering nature and due to lack of comparability with the following waves data are not available in Eurostat's online database but main results are available here. The next CVTS is due for reference year 2015.

Applications to see open job positions, request annual leave, view or download payslips, or other services. In January of the survey year.

Data given in this domain are collected on a yearly basis by the National Statistical Institutes or Ministries and are based on the annual Eurostat Model Questionnaires on ICT (Information and Communication Technologies) usage and e-commerce in enterprises. Large part of the data collected are used in the context of the 2011 - 2015 benchmarking framework (endorsed by i2010 High Level Group in November 2009) for the Digital Agenda Scoreboard, Europe's strategy for a flourishing digital economy by 2020. This conceptual framework follows the i2010 Benchmarking Framework which itself followed-up the eEurope 2005 Action Plan. The aim of the European ICT usage surveys is to collect and disseminate harmonised and comparable information on the use of Information and Communication Technologies in enterprises and e-commerce at European level. Coverage: The characteristics to be provided are drawn from the following list of subjects: - ICT systems and their usage in enterprises, - use of the Internet and other electronic networks by enterprises, - e-commerce, - e-business processes and organisational aspects, - use of ICT by enterprises to exchange information and services with governments and public administrations (e-government), - ICT competence in the enterprise and the need for ICT skills, - barriers to the use of ICT, the Internet and other electronic networks, e-commerce and e-business processes, - ICT expenditure and investment, - ICT security and trust, - use of ICT and its impact on the environment (Green ICT), - access to and use of the Internet and other network technologies for connecting objects and devices (Internet of Things), - access to and use of technologies providing the ability to connect to the Internet or other networks from anywhere at any time (ubiquitous connectivity). Breakdowns: - by size class, - by NACE categories, - by region (until 2010)

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 '20.5 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 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 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 '20.5 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 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 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 '20.5 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 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 '20.5 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 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 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 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 '20.5 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 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.

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 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.

Data given in this domain are collected on a yearly basis by the National Statistical Institutes or Ministries and are based on the annual Eurostat Model Questionnaires on ICT (Information and Communication Technologies) usage and e-commerce in enterprises. Large part of the data collected are used in the context of the 2011 - 2015 benchmarking framework (endorsed by i2010 High Level Group in November 2009) for the Digital Agenda Scoreboard, Europe's strategy for a flourishing digital economy by 2020. This conceptual framework follows the i2010 Benchmarking Framework which itself followed-up the eEurope 2005 Action Plan. The aim of the European ICT usage surveys is to collect and disseminate harmonised and comparable information on the use of Information and Communication Technologies in enterprises and e-commerce at European level. Coverage: The characteristics to be provided are drawn from the following list of subjects: - ICT systems and their usage in enterprises, - use of the Internet and other electronic networks by enterprises, - e-commerce, - e-business processes and organisational aspects, - use of ICT by enterprises to exchange information and services with governments and public administrations (e-government), - ICT competence in the enterprise and the need for ICT skills, - barriers to the use of ICT, the Internet and other electronic networks, e-commerce and e-business processes, - ICT expenditure and investment, - ICT security and trust, - use of ICT and its impact on the environment (Green ICT), - access to and use of the Internet and other network technologies for connecting objects and devices (Internet of Things), - access to and use of technologies providing the ability to connect to the Internet or other networks from anywhere at any time (ubiquitous connectivity). Breakdowns: - by size class, - by NACE categories, - by region (until 2010)

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 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)*

Persons employed - Life: employees plus working proprietors, partners and unpaid family members, paid persons outside the enterprise, e.g. salespersons, delivery persons and repair/maintenance teams. Also included are persons absent on leave, those on strike but not those on indefinite absence. Part-time, seasonal, apprentices and home-workers are included. Not included are those employed by other enterprises, repair/maintenance teams employed by other companies and those on military service.

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.

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.

This domain includes national statistics on the number of job vacancies, number of occupied jobs and job vacancy rates in the enterprises belonging to NACE, the European classification of economic activities. NACE Rev. 2 sections A to S and divisions 87 and 88 are covered. Activities of households, and extra-territorial organisations and bodies are excluded. The longest time series are available for the UK (from 2001). All countries are available from 2010, when the JVS regulation came into force. EU aggregates are also avaiable from here. Most countries base their JVS on business surveys. Data are published quarterly, with a flash release around 50 days after the end of the quarter and a news release around 80 days after the end of the quarter.

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.

The Human Resources in Science and Technology (HRST) domain provides data on stocks and flows (where flows in turn are divided into job-to-job mobility and education inflows). Stocks and flows are the main statistics for HRST. Their methodologies interlink and are therefore presented together in one single metadata-file. This metadata-file is duplicated in the structure of Eurostat's online database, while statistics for stocks and flows are found in separate folders. Several breakdowns are available for stocks and flows indicators: sex, age, region, sector of economic activity, occupation, educational attainment, fields of education, although not all combinations are possible. The data on stocks and job-to-job mobility are obtained from the European Union Labour Force Survey (EU LFS). The National Statistical Institutes are responsible for conducting the surveys and forwarding the results to Eurostat. The data on education inflows are obtained from Eurostat's Education database and in turn obtained via the UNESCO/OECD/Eurostat questionnaire on education. The National Statistical Institutes are responsible for conducting the surveys, compiling the results and forwarding the results to Eurostat. 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.

The Human Resources in Science and Technology (HRST) domain provides data on stocks and flows (where flows in turn are divided into job-to-job mobility and education inflows). Stocks and flows are the main statistics for HRST. Their methodologies interlink and are therefore presented together in one single metadata-file. This metadata-file is duplicated in the structure of Eurostat's online database, while statistics for stocks and flows are found in separate folders. Several breakdowns are available for stocks and flows indicators: sex, age, region, sector of economic activity, occupation, educational attainment, fields of education, although not all combinations are possible. The data on stocks and job-to-job mobility are obtained from the European Union Labour Force Survey (EU LFS). The National Statistical Institutes are responsible for conducting the surveys and forwarding the results to Eurostat. The data on education inflows are obtained from Eurostat's Education database and in turn obtained via the UNESCO/OECD/Eurostat questionnaire on education. The National Statistical Institutes are responsible for conducting the surveys, compiling the results and forwarding the results to Eurostat. 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.

The Human Resources in Science and Technology (HRST) domain provides data on stocks and flows (where flows in turn are divided into job-to-job mobility and education inflows). Stocks and flows are the main statistics for HRST. Their methodologies interlink and are therefore presented together in one single metadata-file. This metadata-file is duplicated in the structure of Eurostat's online database, while statistics for stocks and flows are found in separate folders. Several breakdowns are available for stocks and flows indicators: sex, age, region, sector of economic activity, occupation, educational attainment, fields of education, although not all combinations are possible. The data on stocks and job-to-job mobility are obtained from the European Union Labour Force Survey (EU LFS). The National Statistical Institutes are responsible for conducting the surveys and forwarding the results to Eurostat. The data on education inflows are obtained from Eurostat's Education database and in turn obtained via the UNESCO/OECD/Eurostat questionnaire on education. The National Statistical Institutes are responsible for conducting the surveys, compiling the results and forwarding the results to Eurostat. 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.

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. 

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.

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).

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 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. 

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 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 '20.5 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.

Data given in this domain are collected on a yearly basis by the National Statistical Institutes or Ministries and are based on the annual Eurostat Model Questionnaires on ICT (Information and Communication Technologies) usage and e-commerce in enterprises. Large part of the data collected are used in the context of the 2011 - 2015 benchmarking framework (endorsed by i2010 High Level Group in November 2009) for the Digital Agenda Scoreboard, Europe's strategy for a flourishing digital economy by 2020. This conceptual framework follows the i2010 Benchmarking Framework which itself followed-up the eEurope 2005 Action Plan. The aim of the European ICT usage surveys is to collect and disseminate harmonised and comparable information on the use of Information and Communication Technologies in enterprises and e-commerce at European level. Coverage: The characteristics to be provided are drawn from the following list of subjects: - ICT systems and their usage in enterprises, - use of the Internet and other electronic networks by enterprises, - e-commerce, - e-business processes and organisational aspects, - use of ICT by enterprises to exchange information and services with governments and public administrations (e-government), - ICT competence in the enterprise and the need for ICT skills, - barriers to the use of ICT, the Internet and other electronic networks, e-commerce and e-business processes, - ICT expenditure and investment, - ICT security and trust, - use of ICT and its impact on the environment (Green ICT), - access to and use of the Internet and other network technologies for connecting objects and devices (Internet of Things), - access to and use of technologies providing the ability to connect to the Internet or other networks from anywhere at any time (ubiquitous connectivity). Breakdowns: - by size class, - by NACE categories, - by region (until 2010)

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 '20.5 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 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 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 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.

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 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 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 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 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 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.

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. Annual labour cost data published here cover the core labour cost variables "average hourly labour costs" and "average monthly labour costs" as well as the breakdown of labour costs by main categories (wages and salaries; other labour costs). Average hourly and monthly labour costs as well as the structure of total annual labour costs per employee by economic activity are provided for enterprises with 1+ and for enterprises with 10+ employees.Data  are available for the EU Member States and partly for Iceland and Switzerland. The data are either collected by the National Statistical Institutes or, more frequently, estimated by them on the basis of their four-yearly Labour Cost Surveys (LCS), the Labour Cost Index (LCI) and additional up-to-date - though sometimes partial - information. Coverage of statistical units, thresholds and other methodological aspects are identical to that of the four yearly LCS.

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. <

This indicator measures the share of people in current job for 12 months or less, in total employment. 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.

Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'. The aim of the ad hoc module was to know how the transition at the end of the career towards full retirement is expected to take place, takes place or took place: • plans for transitions/past transitions towards full retirement • plans for exit from work Another aim was to know which factors would be/were at play in determining the exit from work, and which factors could make/could have made persons postpone the exit from work: • working conditions factors (health and safety at the workplace, flexible working time arrangements …) • other factors linked to work (training/obsolescence of skills …) • financial factors (financial incentives to remain at work or to exit) • personal factors (health, family reasons …).

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 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 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 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.