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Bulgária

  • Presidente:Rumen Radev
  • Primeiro Ministro:Boyko Borisov
  • Capital:Sofia
  • Línguas:Bulgarian (official) 76.8%, Turkish 8.2%, Roma 3.8%, other 0.7%, unspecified 10.5% (2011 est.)
  • Governo
  • Estatísticas Nacionais Oficias
  • População, pessoas:7.024.216 (2018)
  • Área, km2:108.560
  • PIB per capita, US$:9.273 (2018)
  • PIB, bilhões em US$ atuais:65,1 (2018)
  • Índice de GINI:No data
  • Facilidade para Fazer Negócios:59

Labor

Todos os conjuntos de dados:  A B C D E F G H I J K L M N O P Q R S T U W Y
  • A
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 15 outubro, 2019
      Selecionar Conjunto de dados
      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).
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 14 outubro, 2019
      Selecionar Conjunto de dados
      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).
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 15 outubro, 2019
      Selecionar Conjunto de dados
      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).
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 15 outubro, 2019
      Selecionar Conjunto de dados
      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).
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 15 outubro, 2019
      Selecionar Conjunto de dados
      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).
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 15 outubro, 2019
      Selecionar Conjunto de dados
      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).
    • agosto 2018
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 agosto, 2018
      Selecionar Conjunto de dados
      The labour market policy (LMP) database was developed and maintained by Eurostat till 2013. From 2014, the LMP database is developed and maintained by European Commission's Directorate General for Employment, Social Affairs and Inclusion and LMP data are disseminated by Eurostat. European Commission's LMP database provides information on labour market interventions, which are government actions to help and support the unemployed and other disadvantaged groups in the transition from unemployment or inactivity to work. The scope of the LMP database is limited to interventions that are explicitly targeted at groups of persons with difficulties in the labour market: the unemployed, persons employed but at risk of involuntary job loss and persons currently considered as inactive persons but who would like to enter the labour market. LMP statistics are one of the data sources for monitoring the Employment Guidelines (part II of the Europe 2020 Integrated Guidelines) through the Europe 2020 Joint Assessment Framework (JAF). The guidelines specifically refer to the provision of active labour market policies, which cover LMP measures and LMP services, and adequate social security systems, which include LMP supports. The unit of observation in the LMP database is the labour market intervention and data on the expenditure and participants for each intervention are collected annually from administrative sources in each country. The database also collects extensive qualitative information that describes each intervention, how it works, the main target groups, etc. LMP interventions are classified by type of action into three broad types – services, measures and supports – and into 9 detailed categories (see 3.2 Classification system). The LMP database covers all EU Member States and Norway. Data for the EU-15 countries and Norway are available from 1998 whilst the more recently acceded EU countries started providing data at different times from 2003 onwards. The following data and metadata are available:Summary tables of expenditure and participants by type of actionFor each country: detailed tables of expenditure and participants by interventionLMP based indicators for monitoring the Employment Guidelines (for definitions see annexes below)Reference data on persons registered with Public Employment Services (PES)Qualitative reports describing the interventions in each country
    • agosto 2018
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 agosto, 2018
      Selecionar Conjunto de dados
      Eurostat Dataset Id:lmp_ind_actsup The labour market policy (LMP) database was developed and maintained by Eurostat till 2013. From 2014, the LMP database is developed and maintained by European Commission's Directorate General for Employment, Social Affairs and Inclusion and LMP data are disseminated by Eurostat. European Commission's LMP database provides information on labour market interventions, which are government actions to help and support the unemployed and other disadvantaged groups in the transition from unemployment or inactivity to work. The scope of the LMP database is limited to interventions that are explicitly targeted at groups of persons with difficulties in the labour market: the unemployed, persons employed but at risk of involuntary job loss and persons currently considered as inactive persons but who would like to enter the labour market. LMP statistics are one of the data sources for monitoring the Employment Guidelines (part II of the Europe 2020 Integrated Guidelines) through the Europe 2020 Joint Assessment Framework (JAF). The guidelines specifically refer to the provision of active labour market policies, which cover LMP measures and LMP services, and adequate social security systems, which include LMP supports. The unit of observation in the LMP database is the labour market intervention and data on the expenditure and participants for each intervention are collected annually from administrative sources in each country. The database also collects extensive qualitative information that describes each intervention, how it works, the main target groups, etc. LMP interventions are classified by type of action into three broad types – services, measures and supports – and into 9 detailed categories (see 3.2 Classification system). The LMP database covers all EU Member States and Norway. Data for the EU-15 countries and Norway are available from 1998 whilst the more recently acceded EU countries started providing data at different times from 2003 onwards. The following data and metadata are available:Summary tables of expenditure and participants by type of actionFor each country: detailed tables of expenditure and participants by interventionLMP based indicators for monitoring the Employment Guidelines (for definitions see annexes below)Reference data on persons registered with Public Employment Services (PES)Qualitative reports describing the interventions in each country
    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
      Selecionar Conjunto de dados
      This indicator aims to capture the share of persons in the labour force protected through a contributory pension scheme (with benefits guaranteed but not currently being received). It provides information about the proportion of the labour force that will receive an old age pension once reaching pensionable age. This right to income security in old age is guaranteed by the prior payment of premiums or contributions, i.e. before the occurrence of the insured contingency.
    • setembro 2014
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 31 agosto, 2018
      Selecionar Conjunto de dados
      This indicator aims to capture the share of persons in the labour force protected through a contributory pension scheme (with benefits guaranteed but not currently being received). It provides information about the proportion of the labour force that will receive an old age pension once reaching pensionable age. This right to income security in old age is guaranteed by the prior payment of premiums or contributions, i.e. before the occurrence of the insured contingency.
    • setembro 2014
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 31 agosto, 2018
      Selecionar Conjunto de dados
      This indicator aims to capture the share of persons of working age protected through a contributory pension scheme (with benefits guaranteed but not currently being received). It provides information about the proportion of the working-age population that will receive an old age pension once reaching pensionable age. This right to income security in old age is guaranteed by the prior payment of premiums or contributions, i.e. before the occurrence of the insured contingency.
    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
      Selecionar Conjunto de dados
      This indicator aims to capture the share of persons of working age protected through a contributory pension scheme (with benefits guaranteed but not currently being received). It provides information about the proportion of the working-age population that will receive an old age pension once reaching pensionable age. This right to income security in old age is guaranteed by the prior payment of premiums or contributions, i.e. before the occurrence of the insured contingency.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 novembro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
      Selecionar Conjunto de dados
      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 novembro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 outubro, 2019
      Selecionar Conjunto de dados
      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. The EU-LFS covers the resident population in private households. The MIP scoreboard indicators from the domain are:Unemployment rate, 3 years average. Long-term unemployment rate, % of active population aged 15-74 - 3 years change in p.p.Youth unemployment rate, % of active population aged 15-24 - 3 years change in p.p. For the MIP purposes are published the source data used for the indicator's calculation: annual and quarterly data on unemployment rate and annual figures on youth and long-term unemployment rate.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 outubro, 2019
      Selecionar Conjunto de dados
      The indicator Activity rate is based on the quarterly EU Labour Force Survey (EU-LFS) results. The survey covers the resident population in private households. The MIP scoreboard indicator is Activity rate - % of total population aged 15-64 (3 years change in p.p.). 
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 outubro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 outubro, 2019
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      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.
    • julho 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 24 novembro, 2015
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      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 novembro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
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      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 novembro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 01 novembro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 27 outubro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 01 novembro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 27 outubro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 16 outubro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 outubro, 2019
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      Adult participation in learning (previously named 'lifelong learning') refers to persons aged 25 to 64 who stated that they received education or training in the four weeks preceding the survey (numerator). The denominator consists of the total population of the same age group, excluding those who did not answer to the question 'participation in education and training'. Both the numerator and the denominator come from the EU Labour Force Survey. The information collected relates to all education or training whether or not relevant to the respondent's current or possible future job.
    • novembro 2017
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 05 dezembro, 2017
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      Data in this domain constitute only a small part of the entire National Accounts data range available from Eurostat. Annual and quarterly national accounts are compiled in accordance with the European System of Accounts - ESA 2010as 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. The annual data of this domain consists of the following collections: 1. Main GDP aggregates: main components from the output, expenditure and income side. nama_10_gdp: GDP and main components (output, expenditure and income   The quarterly data of this domain consists of the following collections 1. Main GDP aggregates, main components from the output, expenditure and income side, expenditure breakdowns by industry and assets. namq_10_ma: Main GDP aggregatesnamq_10_gdp: GDP and main components (output, expenditure and incomenamq_10_fcs: Final consumption aggregates by durabilitynamq_10_exi: Exports and imports by Member States of the EU/third countries 2. Breakdowns of GDP aggregates and employment data by main industries and asset classes. namq_10_bbr: Basic breakdowns main GDP aggregates and employment (by industry and assets)namq_10_a10: Gross value added and income by A*10 industrynamq_10_an6: Gross fixed capital formation by AN_F6 asset typenamq_10_a10_e: Employment by A*10 industry breakdowns Geographical entities covered are the European Union, the euro area, EU Member States, Candidate Countries, EFTA countries, US, Japan and possibly other countries on an ad-hoc basis. Data sources: National Statistical Institutes
    • novembro 2017
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 02 dezembro, 2017
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      Data in this domain constitute only a small part of the entire National Accounts data range available from Eurostat. Annual and quarterly national accounts are compiled in accordance with the European System of Accounts - ESA 2010as 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. The annual data of this domain consists of the following collections: 1. Main GDP aggregates: main components from the output, expenditure and income side. nama_10_gdp: GDP and main components (output, expenditure and income   The quarterly data of this domain consists of the following collections 1. Main GDP aggregates, main components from the output, expenditure and income side, expenditure breakdowns by industry and assets. namq_10_ma: Main GDP aggregatesnamq_10_gdp: GDP and main components (output, expenditure and incomenamq_10_fcs: Final consumption aggregates by durabilitynamq_10_exi: Exports and imports by Member States of the EU/third countries 2. Breakdowns of GDP aggregates and employment data by main industries and asset classes. namq_10_bbr: Basic breakdowns main GDP aggregates and employment (by industry and assets)namq_10_a10: Gross value added and income by A*10 industrynamq_10_an6: Gross fixed capital formation by AN_F6 asset typenamq_10_a10_e: Employment by A*10 industry breakdowns Geographical entities covered are the European Union, the euro area, EU Member States, Candidate Countries, EFTA countries, US, Japan and possibly other countries on an ad-hoc basis. Data sources: National Statistical Institutes
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 08 novembro, 2019
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      The Economic Accounts for Agriculture (EAA) provide detailed information on income in the agricultural sector. The purpose is to analyse the production process of the agricultural industry and the primary income generated by this production. The accounts are therefore based on the industry concept. The EAA accounts are detailed data on value of output (producer prices and basic prices), intermediate consumption, subsidies and taxes, consumption of fixed capital, rent and interests, capital formation etc. The values are in current as well as in constant prices. Agricultural Labour Input (ALI) and Unit Values (UV) are an integrated part of the overall concept of Economic Accounts for Agriculture. The Economic accounts for agriculture (EAA) are a satellite account of the European System of Accounts (ESA2010), providing complementary information and concepts adapted to the particular nature of the agricultural industry. Although their structure very closely matches that of the national accounts, their compilation requires the formulation of appropriate rules and methods. National Statistical Institutes or Ministries of Agriculture are responsible for data collection and calculation of national EAA, in accordance with EC Regulations. Eurostat is responsible for the EU aggregations. Regional data EAA accounts are compiled at regional level (NUTS2), but only in values in current prices. The labour input data and Unit values are not broken down to regional level. 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. Frequency of data collection for data under Regulation (EC) 138/2004 and gentlemen's agreement, deadline for transmission for years 2015-2016.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 08 novembro, 2019
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      The Economic Accounts for Agriculture (EAA) provide detailed information on income in the agricultural sector. The purpose is to analyse the production process of the agricultural industry and the primary income generated by this production. The accounts are therefore based on the industry concept. The EAA accounts are detailed data on value of output (producer prices and basic prices), intermediate consumption, subsidies and taxes, consumption of fixed capital, rent and interests, capital formation etc. The values are in current as well as in constant prices. Agricultural Labour Input (ALI) and Unit Values (UV) are an integrated part of the overall concept of Economic Accounts for Agriculture. The Economic accounts for agriculture (EAA) are a satellite account of the European System of Accounts (ESA2010), providing complementary information and concepts adapted to the particular nature of the agricultural industry. Although their structure very closely matches that of the national accounts, their compilation requires the formulation of appropriate rules and methods. National Statistical Institutes or Ministries of Agriculture are responsible for data collection and calculation of national EAA, in accordance with EC Regulations. Eurostat is responsible for the EU aggregations. Regional data EAA accounts are compiled at regional level (NUTS2), but only in values in current prices. The labour input data and Unit values are not broken down to regional level. 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. Frequency of data collection for data under Regulation (EC) 138/2004 and gentlemen's agreement, deadline for transmission for years 2015-2016.   Reg. CE 138/2004 Gentlemen's agreement Web Form in eDamis Excel SDTT file in CIRCA Transmission date via eDamis Edamis DATASET to use   EAA Second Estimates 2015   X - - X 31 January 2016 COSAEA_AGR2_A EAA Constant N-1 prices Final - 2014   X - - X 30 September 2015   COSAEA_AGR3CON_A EAA at current prices Final - 2014   X - - X COSAEA_AGR3CUR_A   UV (unit Values) 2014   - X X - COSAEA_UV_A   EAA Regional data 2013   - X - X COSAEA_REGION_A   ALI (Labour Input) final 2014   X - X - COSAEA_ALI3_A   ALI (Labour Input)1st estimates 2015   X - X - 30 November 2015 COSAEA_ALI3_A   ALI (Labour Input) 2nd estimates 2015   X - X - 31 January 2016 COSAEA_ALI3_A   EAA First Estimates 2015   X - - X 30 November 2015 COSAEA_AGR1_A
    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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      Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.
    • fevereiro 2016
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 25 fevereiro, 2016
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      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.
    • agosto 2017
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 agosto, 2017
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      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 2014 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 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 countries (where applicable) and regional metadata is identical to that provided for national data.
    • janeiro 2017
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 05 fevereiro, 2017
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      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.
    • fevereiro 2016
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 25 fevereiro, 2016
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      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.
    • agosto 2017
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 agosto, 2017
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      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 2014 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 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 countries (where applicable) and regional metadata is identical to that provided for national data.
    • dezembro 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 27 maio, 2014
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      Eurostat Dataset Id:educ_bo_ou_attd The Bologna declaration was signed in 1999 by 29 European ministers responsible for higher education. Today, 46 signatory countries are engaged in the process towards a European Higher Education Area (EHEA). The Bologna Process is an intergovernmental initiative which also involves the European Commission, the Council of Europe and UNESCO-CEPES, as well as representatives of higher education institutions, students, staff, employers and quality assurance agencies. It aims to create a European Higher Education Area by 2010, and to promote the European system of higher education worldwide. More information on the Bologna process is available on http://ec.europa.eu/education/higher-education/doc1290_en.htm. In the framework of the indicators for the monitoring of the social dimension and mobility of the Bologna Process, the EU-SILC (EU Statistics on Income and Living Conditions) data of interest cover individual's educational attainment, income and, from the intergenerational transmission of poverty ad hoc module, educational attainment of the parents. The following data-sets, having EU-SILC as source, on the Bologna Process are available: A. Widening access educ_bo_ac_sobs: Individuals having completed tertiary education (ISCED 5-6), according to the educational background of their parents, by sexeduc_bo_ac_soba: Individuals having completed tertiary education (ISCED 5-6), according to the educational background of their parents, by age D. Effective outcomes and employability educ_bo_ou_attd: Annual gross income of workers by educational attainment (2006)educ_bo_ou_terd: Annual gross income of workers with tertiary education (ISCED 5-6) , by sex (2006) The general aim of the EU-SILC domain is to provide comparable statistics and indicators on key aspects of the citizens' living conditions across Europe. This domain actually contains a range of social statistics and indicators relating to the risks of income poverty and social exclusion. There are both conceptual and methodological problems in defining and measuring income poverty and social exclusion. Since a 1984 decision of the European Council, the following are regarded as poor: "those persons, families and groups of persons whose resources (material, cultural and social) are so limited as to exclude them from the minimum acceptable way of life in the Member State to which they belong". On this basis, measures of poverty at EU level adopt an approach which is both multi-dimensional and relative. In June 2006, a new set of common indicators for the social protection and social inclusion process was adopted. (For more details and definitions of these indicators: Indicators 2006). To investigate particular areas of policy interest in more detail, target secondary areas, to be collected every four years or less frequently, are added to the cross-sectional component of EU-SILC. "The intergenerational transmission of poverty" was chosen as the area to be implemented for 2005. This specific module, collected in 2005, had as purpose to collect and compile relevant and robust information on background factors linked to adult social exclusion, minimising the burden of respondents to provide accurate detailed indicators sufficiently comparable across the EU capturing the effects of childhood experiences on poverty risk. More general information on EU-SILC is available on ilc_base.htm
    • junho 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 02 julho, 2019
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      Information on net earnings (net pay taken home, in absolute figures) and related tax-benefit rates (in %) complements gross‑earnings data with respect to disposable earnings. The transition from gross to net earnings requires the deduction of income taxes and employee's social security contributions from the gross amounts and the addition of family allowances, if appropriate. The amount of these components and therefore the ratio of net to gross earnings depend on the individual situation. A number of different family situations are considered, all referring to an average worker. Differences exist with respect to marital status (single vs. married), number of workers (only in the case of couples), number of dependent children, and level of gross earnings, expressed as a percentage of the gross earnings of an average worker (AW).  All the data are based on a widely acknowledged model developed by the OECD, which figures are obtained from national sources. The collection contains, for selected situations, data for the following variables and indicators : a)      gross and net earnings, including the transition components "income taxes", "employee's social security contributions" and "family allowances", if appropriate; b)      tax rate, defined as the income tax on gross wage earnings plus the employee's social security contributions less universal cash benefits, expressed as a percentage of gross wage earnings; c)      tax wedge on labour costs, defined as income tax on gross wage earnings plus the employee's and the employer's social security contributions, expressed as a percentage of the total labour costs of the earner. The total labour costs of the earner are defined as his/her gross earnings plus the employer's social security contributions plus payroll taxes (where applicable). The tax wedge on labour costs structural indicator is available only for single persons without children earning 67% of the AW. d)      unemployment trap, measuring the percentage of gross earnings which is taxed away through higher tax and social security contributions and the withdrawal of unemployment, and other, benefits when an unemployed person returns to employment. This structural indicator is available only for single persons without children earning 67% of the AW when in work. e)      low wage trap, measuring the percentage of gross earnings which is taxed away through the combined effects of income taxes, social security contributions and any withdrawal of benefits when gross earnings increase from 33% to 67% of AW. This structural indicator is available for single persons without children and one-earner couples with two children.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 30 outubro, 2019
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      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 26 outubro, 2019
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      Residence permits statistics refers to third-country nationals (persons who are not EU citizens) receiving a residence permits or an authorisation to reside in one of the EU or EFTA Member States. The definitions used for residence permits and other concepts (e.g. first permit) are presented in the section 3.4. Statistical concepts and definitions. The detailed data collection methodology is presented in Annex 8 of this metadta file. LEGAL FRAMEWORK - Residence data contain statistical information based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007.  This legal framework refers to the initial residence permits data colection with 2008 first reference period (e.g. first residence permits; change of immigration status or reason to stay; all valid residence permits in the end of the year and long-term residence permits valid in the end of the year) and it provides also a general framework for newer data collections based on speciffic European legal acts (e.g. statistics on EU Blue Cards and statistics on single permits) or provided on voluntary basis (e.g. new long-term residence permits issued during the year and residence permits issued for family reunification with beneficiaries of  protection status). DATA SOURCE - Data are entirely based on administrative sources with the exception of the United Kingdom1 and are provided mainly by the Ministries of Interior or related Immigration Agencies. Data are generally disseminated in June and July in the year following the reference year. AVAILABLE DATASETS I. Residence permits statistics by reason to stay, citizenship and permit's lenght of validity based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007. These statistics are avilable from 2008 reference year.     First Permits - see the definition in the section 3.4. Statistical concepts and definitions. First permits by reason, length of validity and citizenship (migr_resfirst)2. The totals presented in this tables are depended on data availability in the following four tables migr_resfam + migr_resedu+ migr_resocc+ migr_resoth.First permits issued for family reasons by reason, length of validity and citizenship (migr_resfam)First permits issued for education reasons by reason, length of validity and citizenship (migr_resedu)First permits issued for remunerated activities by reason, length of validity and citizenship (migr_resocc)First permits issued for other reasons by reason, length of validity and citizenship (migr_resoth)     Residence Permits issued with the occasion of changing the immigration status or reason to stay Change of immigration status permits by reason and citizenship (migr_reschange)               Residence permits valid in the end of the year All valid permits by reason, length of validity and citizenship on 31 December of each year (migr_resvalid)Long-term residents by citizenship on 31 December of each year (migr_reslong)     Share of long term residence permitsLong-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%) (migr_resshare) II. Residence permits statistics by age (5-year age groups) and sex collected on voluntary basis. These statistics are avilable from 2010 reference year. First permits by reason, age, sex and citizenship (migr_resfas)  All valid permits by age, sex and citizenship on 31 December of each year (migr_resvas)               Long-term residents by age, sex and citizenship on 31 December of each year (migr_reslas) III. EU Blue Cards data collection based on Article 20 of the Directive 2009/50/EC. These statistics are avilable from 2012 reference year2. EU Blue Cards by type of decision, occupation and citizenship (migr_resbc1)       Admitted family members of EU Blue Cards holders by type of decision and citizenship (migr_resbc2)EU Blue Cards holders and family members by Member State of previous residence (migr_resbc3) IV. Single Permit data collection based on Art 15 Directive 2011/98/EU. These statistics are avilable from 2013 reference year. Single Permits issued by type of decision, length of validity (migr_ressing)  V. Pilot data collections collected on voluntary basis. These statistics are avilable from 2016 reference year and the data quality assesment is ongoing. Long-term residence permits issued during the year (migr_resltr)First permits issued for family reunification with a beneficiary of protection status (migr_resfrps1)Permits valid at the end of the year for family reunification with a beneficiary of protection status (migr_resfrps2) VI. New statistics on Intra-Corporate Transfers and Seasonal Workers New data collections with 2017 first reference period are in the preparetion phase to be released in 2018: Intra-Corporate Transfers data collection under Art 24 of Directive 2014/66/EU and Seasonal Workers data collection under Art 26 Directive 2014/36/EU. Share of long-tem residence permits The indicators presented in the table 'Long-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%)' are produced within the framework of the pilot study related to the integration of migrants in the Member States, following the Zaragoza Declaration. The Zaragoza Declaration, adopted in April 2010 by EU Ministers responsible for immigrant integration issues, and approved at the Justice and Home Affairs Council on 3-4 June 2010, called upon the Commission to undertake a pilot study to examine proposals for common integration indicators and to report on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators. In June 2010 the ministers agreed "to promote the launching of a pilot project with a view to the evaluation of integration policies, including examining the indicators and analysing the significance of the defined indicators taking into account the national contexts, the background of diverse migrant populations and different migration and integration policies of the Member States, and reporting on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators". These indicators are produced on the basis of residence permit statistics collected by Eurostat on the basis of Article 6 of the Migration Statistics Regulation 862/2007. As a denominator data on the stock of all valid permits to stay at the end of each reporting year are used. As a numerator data on the stock of long-term residents are used.  Two types of long term residents are distinguished in accordance with the residence permit statistics: EU long-term resident status (as regulated by the Council Directive 2003/109/EC) and the National long-term resident status (as regulated by the national legislation in the Member States). Data for some countries may be a subject of revisions due to certain inconsistencies between categories. Data consistency between tables The data providers should use the same methodological specifications provided by Eurostat and some tables from Resper statistics should be consistent between them according to this methodology.  However, consistency issues between tables exist due to some technical limitations (e.g. different data sources) or different methodology applied to each table (see the quality information from below or the national metadata files) or different point in time of producing each tables. 1Please note that the statistics for the United Kingdom use different data sources to those used in other Member States. For that reason, the statistics on residence permits published by Eurostat for UK may not be fully comparable with the statistics reported by other countries. Statistics for the United Kingdom are not based on records of residence permits issued (as the United Kingdom does not operate a system of residence permits), but instead relate to the numbers of arriving non-EU citizens permitted to enter the country under selected immigration categories. According to the United Kingdom authorities, data are estimated from a combination of information due to be published in the Home Office Statistical Bulletin 'Control of Immigration: Statistics, United Kingdom' and unpublished management information. The 'Other reasons' category includes: diplomat, consular officer treated as exempt from control; retired persons of independent means; all other passengers given limited leave to enter who are not included in any other category; non-asylum discretionary permissions. 2 The EU Blue cards issued during the year are collected in two datasets: 1. in the table migr_resocc countig the EU Blue Cards issued as "first permits" and 2. in the EU Blue Cards counting all EU Blue Cards issued. The diference between these two categories is represented by the EU Blue cards that are not first permits. However these two tables might be updated/revised at a different point in time and the consistency between tables might be affected.
    • agosto 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 09 agosto, 2019
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      Residence permits statistics refers to third-country nationals (persons who are not EU citizens) receiving a residence permits or an authorisation to reside in one of the EU or EFTA Member States. The definitions used for residence permits and other concepts (e.g. first permit) are presented in the section 3.4. Statistical concepts and definitions. The detailed data collection methodology is presented in Annex 8 of this metadta file. LEGAL FRAMEWORK - Residence data contain statistical information based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007.  This legal framework refers to the initial residence permits data colection with 2008 first reference period (e.g. first residence permits; change of immigration status or reason to stay; all valid residence permits in the end of the year and long-term residence permits valid in the end of the year) and it provides also a general framework for newer data collections based on speciffic European legal acts (e.g. statistics on EU Blue Cards and statistics on single permits) or provided on voluntary basis (e.g. new long-term residence permits issued during the year and residence permits issued for family reunification with beneficiaries of  protection status). DATA SOURCE - Data are entirely based on administrative sources with the exception of the United Kingdom1 and are provided mainly by the Ministries of Interior or related Immigration Agencies. Data are generally disseminated in June and July in the year following the reference year. AVAILABLE DATASETS I. Residence permits statistics by reason to stay, citizenship and permit's lenght of validity based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007. These statistics are avilable from 2008 reference year.     First Permits - see the definition in the section 3.4. Statistical concepts and definitions. First permits by reason, length of validity and citizenship (migr_resfirst)2. The totals presented in this tables are depended on data availability in the following four tables migr_resfam + migr_resedu+ migr_resocc+ migr_resoth.First permits issued for family reasons by reason, length of validity and citizenship (migr_resfam)First permits issued for education reasons by reason, length of validity and citizenship (migr_resedu)First permits issued for remunerated activities by reason, length of validity and citizenship (migr_resocc)First permits issued for other reasons by reason, length of validity and citizenship (migr_resoth)     Residence Permits issued with the occasion of changing the immigration status or reason to stay Change of immigration status permits by reason and citizenship (migr_reschange)               Residence permits valid in the end of the year All valid permits by reason, length of validity and citizenship on 31 December of each year (migr_resvalid)Long-term residents by citizenship on 31 December of each year (migr_reslong)     Share of long term residence permitsLong-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%) (migr_resshare) II. Residence permits statistics by age (5-year age groups) and sex collected on voluntary basis. These statistics are avilable from 2010 reference year. First permits by reason, age, sex and citizenship (migr_resfas)  All valid permits by age, sex and citizenship on 31 December of each year (migr_resvas)               Long-term residents by age, sex and citizenship on 31 December of each year (migr_reslas) III. EU Blue Cards data collection based on Article 20 of the Directive 2009/50/EC. These statistics are avilable from 2012 reference year2. EU Blue Cards by type of decision, occupation and citizenship (migr_resbc1)       Admitted family members of EU Blue Cards holders by type of decision and citizenship (migr_resbc2)EU Blue Cards holders and family members by Member State of previous residence (migr_resbc3) IV. Single Permit data collection based on Art 15 Directive 2011/98/EU. These statistics are avilable from 2013 reference year. Single Permits issued by type of decision, length of validity (migr_ressing)  V. Pilot data collections collected on voluntary basis. These statistics are avilable from 2016 reference year and the data quality assesment is ongoing. Long-term residence permits issued during the year (migr_resltr)First permits issued for family reunification with a beneficiary of protection status (migr_resfrps1)Permits valid at the end of the year for family reunification with a beneficiary of protection status (migr_resfrps2) VI. New statistics on Intra-Corporate Transfers and Seasonal Workers New data collections with 2017 first reference period are in the preparetion phase to be released in 2018: Intra-Corporate Transfers data collection under Art 24 of Directive 2014/66/EU and Seasonal Workers data collection under Art 26 Directive 2014/36/EU. Share of long-tem residence permits The indicators presented in the table 'Long-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%)' are produced within the framework of the pilot study related to the integration of migrants in the Member States, following the Zaragoza Declaration. The Zaragoza Declaration, adopted in April 2010 by EU Ministers responsible for immigrant integration issues, and approved at the Justice and Home Affairs Council on 3-4 June 2010, called upon the Commission to undertake a pilot study to examine proposals for common integration indicators and to report on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators. In June 2010 the ministers agreed "to promote the launching of a pilot project with a view to the evaluation of integration policies, including examining the indicators and analysing the significance of the defined indicators taking into account the national contexts, the background of diverse migrant populations and different migration and integration policies of the Member States, and reporting on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators". These indicators are produced on the basis of residence permit statistics collected by Eurostat on the basis of Article 6 of the Migration Statistics Regulation 862/2007. As a denominator data on the stock of all valid permits to stay at the end of each reporting year are used. As a numerator data on the stock of long-term residents are used.  Two types of long term residents are distinguished in accordance with the residence permit statistics: EU long-term resident status (as regulated by the Council Directive 2003/109/EC) and the National long-term resident status (as regulated by the national legislation in the Member States). Data for some countries may be a subject of revisions due to certain inconsistencies between categories. Data consistency between tables The data providers should use the same methodological specifications provided by Eurostat and some tables from Resper statistics should be consistent between them according to this methodology.  However, consistency issues between tables exist due to some technical limitations (e.g. different data sources) or different methodology applied to each table (see the quality information from below or the national metadata files) or different point in time of producing each tables. 1Please note that the statistics for the United Kingdom use different data sources to those used in other Member States. For that reason, the statistics on residence permits published by Eurostat for UK may not be fully comparable with the statistics reported by other countries. Statistics for the United Kingdom are not based on records of residence permits issued (as the United Kingdom does not operate a system of residence permits), but instead relate to the numbers of arriving non-EU citizens permitted to enter the country under selected immigration categories. According to the United Kingdom authorities, data are estimated from a combination of information due to be published in the Home Office Statistical Bulletin 'Control of Immigration: Statistics, United Kingdom' and unpublished management information. The 'Other reasons' category includes: diplomat, consular officer treated as exempt from control; retired persons of independent means; all other passengers given limited leave to enter who are not included in any other category; non-asylum discretionary permissions. 2 The EU Blue cards issued during the year are collected in two datasets: 1. in the table migr_resocc countig the EU Blue Cards issued as "first permits" and 2. in the EU Blue Cards counting all EU Blue Cards issued. The diference between these two categories is represented by the EU Blue cards that are not first permits. However these two tables might be updated/revised at a different point in time and the consistency between tables might be affected.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 05 junho, 2014
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      Eurostat Dataset Id:lfso_06finiagps Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 05 junho, 2014
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      Eurostat Dataset Id:lfso_06otbnagps Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 30 junho, 2014
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      Eurostat Dataset Id:lfso_06stafagps 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 …).  
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 05 junho, 2014
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      Eurostat Dataset Id:lfso_06reasagps Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'.
    • abril 2013
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 dezembro, 2015
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      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.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 junho, 2014
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      Eurostat Dataset Id:earn_gr_nace2 This data collection has been discontinued in 2012. Data is only available up to reference year 2011. Annual data on average gross earnings and related employment are included in the Gross earnings - Annual data collection. Data are available for EU Member States, Norway, Iceland and Switzerland. Data are also broken down by: From reference year 2008 onwards average gross annual earnings per employee are providedby economic activity (NACE Rev.2 aggregates and sections B, C, D, E, F, G, H, I, J, K, L, M, N, O, P, Q, R, S, B_TO_E, B_TO_F, B_TO_N, B_TO_S_NOT_O, B_TO_S, G_TO_J, G_TO_N, G_TO_S_NOT_O, K_TO_N, P_TO_S and O_TO_S)for enterprises with 1+ and for enterprises with 10+ employees for the following breakdowns:FTU= full-time units, FT=full-time workers, PT=part-time workers by Total, Men and Women. Before 2008: data is broken down by economic activity (NACE Rev. 1.1 for Sections C to K and the C-E, C-F, G-I, J-K, G-K, C-K and for some Member States L, M-O, L-O and also C-O aggregates)FTU= full-time units, FT=full-time workers, PT=part-time workersgenderoccupation (ISCO-88 classification, one-digit level and the 1-5 and 7-9 aggregates)The data relate to the staff of enterprises having at least 10 employees in most countries. Countries provide these annual data using several statistical sources mainly the four-yearly SES, the EU Labour Force Survey and/or administrative data.
    • novembro 2013
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 junho, 2014
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      Eurostat Dataset Id:earn_gr_isco This data collection has been discontinued in 2012. Data is only available up to reference year 2011. Annual data on average gross earnings and related employment are included in the Gross earnings - Annual data collection. Data are available for EU Member States, Norway, Iceland and Switzerland. Data are also broken down by: From reference year 2008 onwards average gross annual earnings per employee are providedby economic activity (NACE Rev.2 aggregates and sections B, C, D, E, F, G, H, I, J, K, L, M, N, O, P, Q, R, S, B_TO_E, B_TO_F, B_TO_N, B_TO_S_NOT_O, B_TO_S, G_TO_J, G_TO_N, G_TO_S_NOT_O, K_TO_N, P_TO_S and O_TO_S)for enterprises with 1+ and for enterprises with 10+ employees for the following breakdowns:FTU= full-time units, FT=full-time workers, PT=part-time workers by Total, Men and Women. Before 2008: data is broken down by economic activity (NACE Rev. 1.1 for Sections C to K and the C-E, C-F, G-I, J-K, G-K, C-K and for some Member States L, M-O, L-O and also C-O aggregates)FTU= full-time units, FT=full-time workers, PT=part-time workersgenderoccupation (ISCO-88 classification, one-digit level and the 1-5 and 7-9 aggregates)The data relate to the staff of enterprises having at least 10 employees in most countries. Countries provide these annual data using several statistical sources mainly the four-yearly SES, the EU Labour Force Survey and/or administrative data.
    • outubro 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 21 junho, 2019
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      The average effective age of retirement is calculated as a weighted average of (net) withdrawals from the labour market at different ages over a 5-year period for workers initially aged 40 and over. In order to abstract from compositional effects in the age structure of the population, labour force withdrawals are estimated based on changes in labour force participation rates rather than labour force levels. These changes are calculated for each (synthetic) cohort divided into 5-year age groups. The estimates shown in red are less reliable as they have been derived from interpolations of census data rather than from annual labour force surveys. The estimates for women in Turkey are based on 3-yearly moving averages of participation rates for each 5-year age group. OECD estimates based on the results of national labour force surveys, the European Union Labour Force Survey and, for earlier years in some countries, national censuses.
    • junho 2012
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 dezembro, 2015
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      Eurostat Dataset Id:lfsi_exi_a The indicator 'average exit age from the labour force' gives the average age of withdrawal from labour market. While based on European Union Labour Force Survey (EU-LFS) data, the indicator is calculated with special methods and periodidicty which justify the present page. The indicator is estimated with a probabilistic model, documented below, fed with data from the European Union Labour Force Survey (EU-LFS). The input data are activity rates by single age group. The indicator of 'Average exit age from the labour market' is published in the section 'LFS main indicators', which is a collection of the main statistics on the labour market. 'Population in jobless households' is also a Structural Indicator and a Sustainable Development Indicator. There are mainly two reasons to estimate the indicator with this probabilistic model instead of using a method based on self-reported retirement age, or based on people receiving pensions benefits: 1. EU-LFS data used follows definitions of employment and unemployment after the International Labour Organisation, as opposed to the notion of "being retired". There is no internationally harmonized statistical definition of retirement. 2. The method used allows to (indirectly) count definitive exits from the labour market. Instead, a retired person could potentially decide to return to the labour market, hence his/her exit would not be definitive.
    • maio 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 22 maio, 2019
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      Gross earnings are remuneration (wages and salaries) in cash paid directly to the employee, before any deductions for income tax and social security contributions paid by the employee. Data is presented for full-time employees in "industry and services".
    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 11 novembro, 2019
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      This indicator presents data by sex on employees' average hourly earnings. The concept of earnings, as applied in wage statistics, relates to gross remuneration in cash and in kind paid to employees, as a rule at regular intervals, for time worked or work done together with remuneration for time not worked, such as annual vacation, other type of paid leave or holidays. Earnings exclude employers' contributions in respect of their employees paid to social security and pension schemes and also the benefits received by employees under these schemes. Earnings also exclude severance and termination pay. Data are also disaggregated by occupation. Statistics on average hourly earnings by sex are the basis for the calculation of the gender pay gap. For further information, see the SDG Indicators Metadata Repository or ILOSTAT's indicator description.
    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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    • setembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 02 outubro, 2019
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      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.
    • julho 2018
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 17 julho, 2018
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      This table presents data on average monthly earnings converted to a common currency. Data in U.S. dollars are converted from local currency using exchange rates, while data in constant 2011 U.S. dollars are converted using 2011 purchasing power parities (PPPs)   Dataset splitted into below datasets:-   Local Currency (Total) - https://knoema.com/EAR_TEAR_NOC_NB   Local Currency (Men) - https://knoema.com/EAR_MEAR_NOC_NB   Local Currency (Women) - https://knoema.com/EAR_FEAR_NOC_NB   Constant 2011 PPP $ (Total) - https://knoema.com/EAR_4MPT_NOC_NB   Constant 2011 PPP $ (Men) - https://knoema.com/EAR_4MPM_NOC_NB   Constant 2011 PPP $ (Women) - https://knoema.com/EAR_4MPW_NOC_NB
    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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      The concept of earnings, as applied in wages statistics, relates to gross remuneration in cash and in kind paid to employees, as a rule at regular intervals, for time worked or work done together with remuneration for time not worked, such as annual vacation, other type of paid leave or holidays. This indicator is presented in terms of the average monthly earnings per employee, in local currency.
    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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      The concept of earnings, as applied in wages statistics, relates to gross remuneration in cash and in kind paid to employees, as a rule at regular intervals, for time worked or work done together with remuneration for time not worked, such as annual vacation, other type of paid leave or holidays. This indicator is presented in terms of the average monthly earnings per employee, in local currency. Manufacturing refers to ISIC-Rev. 4 Section C; ISIC-Rev. 3 Category D; or ISIC-Rev. 2 Major Division 2.
    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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      The concept of earnings, as applied in wages statistics, relates to gross remuneration in cash and in kind paid to employees, as a rule at regular intervals, for time worked or work done together with remuneration for time not worked, such as annual vacation, other type of paid leave or holidays. This indicator is presented in terms of the average monthly earnings per employee, in local currency, for men.
    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
      Selecionar Conjunto de dados
      The concept of earnings, as applied in wages statistics, relates to gross remuneration in cash and in kind paid to employees, as a rule at regular intervals, for time worked or work done together with remuneration for time not worked, such as annual vacation, other type of paid leave or holidays. This indicator is presented in terms of the average monthly earnings per employee, in local currency, for women.
    • agosto 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 15 agosto, 2019
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      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.
    • agosto 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 agosto, 2019
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      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 novembro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 01 novembro, 2019
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      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 novembro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 01 novembro, 2019
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      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.
    • agosto 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 agosto, 2019
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      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.
    • agosto 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 15 agosto, 2019
      Selecionar Conjunto de dados
      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 novembro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 01 novembro, 2019
      Selecionar Conjunto de dados
      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.
    • abril 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 25 abril, 2019
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      The data collection 'LFS - specific topics, household statistics' covers a range of statistics on number, characteristics and typologies of households, based on the European Union Labour Force Survey (EU-LFS). The data collection also encompasses some labour market indicators broken down by household composition. Only annual data are available. 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.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 26 novembro, 2015
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      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.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 08 junho, 2014
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      Eurostat Dataset Id:lfso_04avovisco Results from the 2004 LFS (Labour Force Survey) ad hoc module on 'work organisation and working time arrangements'.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 26 novembro, 2015
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      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.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 08 junho, 2014
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      Eurostat Dataset Id:lfso_04avpoisco Results from the 2004 LFS (Labour Force Survey) ad hoc module on 'work organisation and working time arrangements'.
    • abril 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 26 abril, 2019
      Selecionar Conjunto de dados
      The data collection 'LFS - specific topics, household statistics' covers a range of statistics on number, characteristics and typologies of households, based on the European Union Labour Force Survey (EU-LFS). The data collection also encompasses some labour market indicators broken down by household composition. Only annual data are available. 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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 30 outubro, 2019
      Selecionar Conjunto de dados
      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.
    • agosto 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 14 agosto, 2019
      Selecionar Conjunto de dados
      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.
    • agosto 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 agosto, 2019
      Selecionar Conjunto de dados
      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 novembro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 01 novembro, 2019
      Selecionar Conjunto de dados
      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 novembro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 01 novembro, 2019
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      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.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 05 junho, 2014
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      Eurostat Dataset Id:lfso_06finiyrsp Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
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      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.
    • abril 2013
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 dezembro, 2015
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      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.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 08 junho, 2014
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      Eurostat Dataset Id:lfso_05nowreh Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 08 junho, 2014
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      Eurostat Dataset Id:lfso_05typech Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 08 junho, 2014
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      Eurostat Dataset Id:lfso_05regch Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 08 junho, 2014
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      Eurostat Dataset Id:lfso_05changh Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 08 junho, 2014
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      Eurostat Dataset Id:lfso_04vawkhwus Results from the 2004 LFS (Labour Force Survey) ad hoc module on 'work organisation and working time arrangements'.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 08 junho, 2014
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      Eurostat Dataset Id:lfso_04vahrhwus Results from the 2004 LFS (Labour Force Survey) ad hoc module on 'work organisation and working time arrangements'.
  • B
    • outubro 2018
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 03 novembro, 2018
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      The labour market policy (LMP) database was developed and maintained by Eurostat till 2013. From 2014, the LMP database is developed and maintained by European Commission's Directorate General for Employment, Social Affairs and Inclusion and LMP data are disseminated by Eurostat. European Commission's LMP database provides information on labour market interventions, which are government actions to help and support the unemployed and other disadvantaged groups in the transition from unemployment or inactivity to work. The scope of the LMP database is limited to interventions that are explicitly targeted at groups of persons with difficulties in the labour market: the unemployed, persons employed but at risk of involuntary job loss and persons currently considered as inactive persons but who would like to enter the labour market. LMP statistics are one of the data sources for monitoring the Employment Guidelines (part II of the Europe 2020 Integrated Guidelines) through the Europe 2020 Joint Assessment Framework (JAF). The guidelines specifically refer to the provision of active labour market policies, which cover LMP measures and LMP services, and adequate social security systems, which include LMP supports. The unit of observation in the LMP database is the labour market intervention and data on the expenditure and participants for each intervention are collected annually from administrative sources in each country. The database also collects extensive qualitative information that describes each intervention, how it works, the main target groups, etc. LMP interventions are classified by type of action into three broad types – services, measures and supports – and into 9 detailed categories (see 3.2 Classification system). The LMP database covers all EU Member States and Norway. Data for the EU-15 countries and Norway are available from 1998 whilst the more recently acceded EU countries started providing data at different times from 2003 onwards. The following data and metadata are available:Summary tables of expenditure and participants by type of actionFor each country: detailed tables of expenditure and participants by interventionLMP based indicators for monitoring the Employment Guidelines (for definitions see annexes below)Reference data on persons registered with Public Employment Services (PES)Qualitative reports describing the interventions in each country
    • junho 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 23 junho, 2019
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      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
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 14 outubro, 2019
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      Data on cultural enterprises come from 2 data collections and are summarised in 4 Tables : a) SBS (Structural Business Statistics) Table 1. Number and average size of enterprises in the cultural sectors by NACE Rev. 2 activity (cult_ent_num) Table 2. Value added and turnover of enterprises in the cultural sectors by NACE Rev. 2 activity (cult_ent_val), in millions of EUR and as a percentage of services except trade and financial and insurance activities (i.e. NACE Rev. 2 sections H to N, without K) Table 3. Services by employment size class (NACE Rev. 2, H-N, S95) (sbs_sc_1b_se_r2)   b) Business Demography (BD) Table 4. Business demography by size class (from 2004 onwards, NACE Rev. 2) (bd_9bd_sz_cl_r2)   The data focus on culture-related sectors of activity, as identified by international experts in the final report of the European Statistical System Network on Culture (ESS-Net Culture Report 2012).   The cultural sphere in business statistics is therefore captured through the following NACE Rev. 2 codes, when they are covered (see 3.3. Sector coverage for details): J58.11 Book publishing J58.13 Publishing of newspapers J58.14 Publishing of journals and periodicals J58.21 Publishing of computer games J59 Motion picture, video and television programme production, sound recording and music publishing activities J60 Programming and broadcasting activities J63.91 News agency activities M71.11 Architectural activities M74.1 Specialised design activities R90 Creative, arts and entertainment activities R91 Libraries, archives, museums and other cultural activities
    • junho 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 23 junho, 2019
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      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
    • março 2019
      Fonte: World Bank
      Carregamento por: Knoema
      Acesso em 20 março, 2019
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      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Jobs Publication: https://datacatalog.worldbank.org/dataset/jobs License: http://creativecommons.org/licenses/by/4.0/   The World Bank Jobs Statistics Over 150 indicators on labor-related topics, covering over 200 economies from 1990 to present.
  • C
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 11 novembro, 2019
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      A case of occupational injury is the case of a worker incurring an occupational injury as a result of an occupational accident. An occupational injury that is fatal is the result of an occupational accident where death occurred within one year from the day of the accident. Data are disaggregated by economic activity according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Economic activity refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works.
    • outubro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 13 outubro, 2019
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      A case of occupational injury is the case of a worker incurring an occupational injury as a result of an occupational accident. An occupational injury that is fatal is the result of an occupational accident where death occurred within one year from the day of the accident.
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 11 novembro, 2019
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      A case of non-fatal occupational injury is the case of a worker incurring an occupational injury as a result of an occupational accident not leading to death. The non-fatal occupational injury entails a loss of working time. Data are disaggregated by economic activity according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Economic activity refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works.
    • outubro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 13 outubro, 2019
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      A case of non-fatal occupational injury is the case of a worker incurring an occupational injury as a result of an occupational accident not leading to death. The non-fatal occupational injury entails a loss of working time.
    • outubro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 13 outubro, 2019
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      A case of non-fatal occupational injury is the case of a worker incurring a non-fatal occupational injury as a result of an occupational accident, which entailed a loss of working time. Incapacity for work is the inability of the victim of an occupational accident, due to an occupational injury, to perform the normal duties of work in the job or post occupied at the time of the occupational accident. The incapacity for work can be permanent, when the persons injured were never able to perform again the normal duties of work in the job or post occupied at the time of the occupational accident causing the injury, or temporary, when the workers injured were unable to work from the day after the day of the accident, but were later able to perform again the normal duties of work in the job or post occupied at the time of the occupational accident causing the injury within a period of one year from the day of the accident.
    • outubro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 13 outubro, 2019
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      A case of non-fatal occupational injury is the case of a worker incurring a non-fatal occupational injury as a result of an occupational accident, which entailed a loss of working time. Incapacity for work is the inability of the victim of an occupational accident, due to an occupational injury, to perform the normal duties of work in the job or post occupied at the time of the occupational accident. The incapacity for work can be permanent, when the persons injured were never able to perform again the normal duties of work in the job or post occupied at the time of the occupational accident causing the injury, or temporary, when the workers injured were unable to work from the day after the day of the accident, but were later able to perform again the normal duties of work in the job or post occupied at the time of the occupational accident causing the injury within a period of one year from the day of the accident. Data are disaggregated by economic activity according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Economic activity refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 15 novembro, 2019
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      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.
    • abril 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 21 maio, 2019
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      The collective bargaining coverage rate conveys the number of employees whose pay and/or conditions of employment are determined by one or more collective agreement(s) as a percentage of the total number of employees. Collective bargaining coverage includes, to the extent possible, workers covered by collective agreements in virtue of their extension. Collective bargaining coverage rates are adjusted for the possibility that some workers do not have the right to bargain collectively over wages (e.g. workers in the public services who have their wages determined by state regulation or other methods involving consultation), unless otherwise stated in the notes. The statistics presented in this table result from an ILO data compilation effort (including an annual questionnaire and numerous special enquiries), with contributions from J. Visser.
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
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    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
      Selecionar Conjunto de dados
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
      Selecionar Conjunto de dados
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
      Selecionar Conjunto de dados
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
      Selecionar Conjunto de dados
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
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    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 14 novembro, 2019
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    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 14 novembro, 2019
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      The indicator Compensation of employees sources from the National accounts domain. Under the MIP context it is used for the calculation of the indicator Unit labour cost index. 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 data. 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 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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 15 novembro, 2019
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      Compensation of employees (at current prices) (ESA 2010, 4.02) is defined as the total remuneration, in cash or in kind, payable by an employer to an employee in return for work done by the latter during the accounting period. Compensation of employees consists of wages and salaries, and of employers' social contributions. Seasonally and calendar adjusted data (SCA).
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 15 novembro, 2019
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      The indicator Compensation of employees sources from the National accounts domain. Under the MIP context it is used for the calculation of the indicator Unit labour cost index. 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 data. 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 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.
    • fevereiro 2015
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 agosto, 2015
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    • outubro 2018
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 03 novembro, 2018
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      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.
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
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    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
      Selecionar Conjunto de dados
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
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    • março 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 08 junho, 2014
      Selecionar Conjunto de dados
      Eurostat Dataset Id:trng_inf7 General description of the ad hoc modules supplementing the Labour Force Survey (LFS)
    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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      Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.
    • outubro 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 28 novembro, 2015
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      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.
    • setembro 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 dezembro, 2015
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      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.
    • abril 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 dezembro, 2015
      Selecionar Conjunto de dados
      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.
    • setembro 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 dezembro, 2015
      Selecionar Conjunto de dados
      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.
    • outubro 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 28 novembro, 2015
      Selecionar Conjunto de dados
      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.
    • setembro 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 dezembro, 2015
      Selecionar Conjunto de dados
      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.
    • abril 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 dezembro, 2015
      Selecionar Conjunto de dados
      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.
    • janeiro 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 julho, 2014
      Selecionar Conjunto de dados
      Eurostat Dataset Id:trng_cvts62 CVTS2, CVTS3 and CVTS4 data were collected with reference year 1999, 2005 and 2010 in order to provide harmonised, reliable and relevant statistical information on continuing vocational training in enterprises.CVT stands for continuing vocational training i.e. education and training occurring during paid working time or paid at least partially by employers (if training activities are organised outside paid working time). CVTS 2, 3 and 4 provide statistics on incidence of training in enterprises, participation of employees and volume of CVT courses, CVT costs as well as CVT strategies of enterprises including on Initial vocational training (IVT, i.e. apprenticeship). The section "past series on lifelong learning" presents tables which are no longer available in the same format or at the same level of precision as CVTS 4. The CVTS1 was the first survey on continuing vocational training in enterprises carried out on the EU level in a co-ordinated form (outline questionnaire, common definitions, and common recommendations with the respect to the fieldwork). The survey was of pioneering nature, and is not any longer disseminated due to lack of comparability with the following waves.
    • outubro 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 28 novembro, 2015
      Selecionar Conjunto de dados
      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.
    • setembro 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 dezembro, 2015
      Selecionar Conjunto de dados
      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.
    • abril 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 dezembro, 2015
      Selecionar Conjunto de dados
      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.
    • fevereiro 2011
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 28 novembro, 2015
      Selecionar Conjunto de dados
      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.
    • setembro 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 dezembro, 2015
      Selecionar Conjunto de dados
      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.
    • abril 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 dezembro, 2015
      Selecionar Conjunto de dados
      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.
    • setembro 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 dezembro, 2015
      Selecionar Conjunto de dados
      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.
    • outubro 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 28 novembro, 2015
      Selecionar Conjunto de dados
      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.
    • setembro 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 dezembro, 2015
      Selecionar Conjunto de dados
      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.
    • abril 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 dezembro, 2015
      Selecionar Conjunto de dados
      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.
    • setembro 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 dezembro, 2015
      Selecionar Conjunto de dados
      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.
    • novembro 2019
      Fonte: United Nations Economic Commission for Europe
      Carregamento por: Knoema
      Acesso em 07 novembro, 2019
      Selecionar Conjunto de dados
      Source: UNECE Statistical Database, compiled from national and international official sources. Area data exclude overseas departments and territories. For population footnotes click here. For life expectancy footnotes click here. For fertility rate footnotes click here. For population by marital status footnotes click here. For female members of parliament footnotes click here. For female government ministers footnotes click here. For female central bank board members footnotes click here. For female tertiary students footnotes click here. For economic activity rate footnotes click here. For gender pay gap footnotes click here. For employment growth rate footnotes click here. For unemployment rate footnotes click here. For youth unemployment rate footnotes click here. For employment by economic sector footnotes click here. For economic indicator footnotes click here. For road accident footnotes click here. For total length of motorways footnotes click here. For total length of railway lines footnotes click here. Key indicators in maps .. - data not availableIndicatorGDP in agriculture (ISIC4 A): output approach, index, 2010=100If the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP in industry (incl. construction) (ISIC4 B-F): output approach, index, 2010=100If the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP in services (ISIC4 G-U): output approach, index, 2010=100If the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in agriculture etc. (ISIC4 A), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in industry etc. (ISIC4 B-E), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in construction (ISIC4 F), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in trade, hospitality, transport and communication (ISIC4 G-J), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in finance and business services (ISIC4 K-N), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in public administration, education and health (ISIC4 O-Q), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in other service activities (ISIC4 R-U), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in agriculture, hunting, forestry and fishing (ISIC Rev. 4 A), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in industry and energy (ISIC Rev. 4 B-E), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in construction (ISIC Rev. 4 F), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in trade, hotels, restaurants, transport and communications (ISIC Rev. 4 G-J), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in finance, real estate and business services (ISIC Rev. 4 K-N), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in public administration, education and health (ISIC Rev. 4 O-Q), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in other service activities (ISIC Rev. 4 R-U), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.
    • maio 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 28 maio, 2019
      Selecionar Conjunto de dados
      This domain covers statistics and indicators on key aspects of the education systems across Europe. The data show entrants and enrolments in education levels, education personnel and the cost and type of resources dedicated to education. The standards on international statistics on education and training systems are set by the three international organisations jointly administering the annual UOE data collection: The United Nations Educational, Scientific, and Cultural Organisation Institute for Statistics (UNESCO-UIS),The Organisation for Economic Co-operation and Development (OECD) and,The Statistical Office of the European Union (EUROSTAT). The following topics are covered: Pupils and students – Enrolments and Entrants,Learning mobility,Education personnel,Education finance,Graduates,Language learning. Data and indicators disseminated include e.g. participation rates at different levels of education, shares of pupils and students by programme orientation (general/academic and vocational/professional) and in combined school and work-based programmes, enrolments in public and private institutions, tertiary education graduates, degree mobile students enrolled and graduates, pupil-teacher ratios, foreign language learning, expenditure on education per student and relative GDP etc.
    • junho 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 22 junho, 2019
      Selecionar Conjunto de dados
      This domain covers statistics and indicators on key aspects of the education systems across Europe. The data show entrants and enrolments in education levels, education personnel and the cost and type of resources dedicated to education. The standards on international statistics on education and training systems are set by the three international organisations jointly administering the annual UOE data collection: The United Nations Educational, Scientific, and Cultural Organisation Institute for Statistics (UNESCO-UIS),The Organisation for Economic Co-operation and Development (OECD) and,The Statistical Office of the European Union (EUROSTAT). The following topics are covered: Pupils and students – Enrolments and Entrants,Learning mobility,Education personnel,Education finance,Graduates,Language learning. Data and indicators disseminated include e.g. participation rates at different levels of education, shares of pupils and students by programme orientation (general/academic and vocational/professional) and in combined school and work-based programmes, enrolments in public and private institutions, tertiary education graduates, degree mobile students enrolled and graduates, pupil-teacher ratios, foreign language learning, expenditure on education per student and relative GDP etc.
    • junho 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 26 junho, 2019
      Selecionar Conjunto de dados
      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).
    • junho 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 26 junho, 2019
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      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).
    • novembro 2018
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 23 novembro, 2018
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      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
  • D
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 11 novembro, 2019
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      Days lost due to temporary incapacity refers to the total number of calendar days during which those persons temporarily incapacitated were unable to work, excluding the day of the accident, up to a maximum of one year. Temporary absences from work of less than one day for medical treatment are not included. Data are disaggregated by economic activity according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Economic activity refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works.
    • setembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
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      Days lost due to temporary incapacity refers to the total number of calendar days during which those persons temporarily incapacitated were unable to work, excluding the day of the accident, up to a maximum of one year. Temporary absences from work of less than one day for medical treatment are not included.
    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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      Time lost per occupational injury is defined as the average number of calendar days lost per new cases of non-fatal occupational injury resulting in temporary incapacity.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 09 julho, 2019
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      This dataset contains three earnings-dispersion measures - ratio of 9th-to-1st, 9th-to-5th and 5th-to-1st - where ninth, fifth (or median) and first deciles are upper-earnings decile limits, unless otherwise indicated, of gross earnings of full-time dependent employees. The dataset also includes series on: the incidence of low-paid workers defined as the share of full-time workers earning less than two-thirds of gross median earnings of all full-time workers; the incidence of high of high-paid workers defined as the share of full-time workers earning more than one-and-half time gross median earnings of all full-time workers; gender wage gap unadjusted and defined as the difference between median wages of men and women relative to the median wages of men.
    • setembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 23 setembro, 2019
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      Dublin statistics contain information based on Article 4.4 of the Council Regulation 862/2007 with reference to: The number of requests for taking back or taking charge of an asylum seeker.The provisions on which the requests for taking back or taking charge are based.The decisions taken in response to the requests for taking back or taking charge.The numbers of transfers to which the decisions taken in response to the requests for taking back or taking charge lead.The number of requests for information. Data is presented country by country and for groups of country: the European Union (EU-27) and the European Economic Area (EEA).
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
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      Discouraged job-seekers refer to those persons of working age who during a specified reference period were without work and available for work, but did not look for work in the recent past for specific reasons (for example, believing that there were no jobs available, believing there were none for which they would qualify, or having given up hope of finding employment). The working age population is commonly defined as persons aged 15 years and older, but this varies from country to country. In addition to using a minimum age threshold, certain countries also apply a maximum age limit.
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 05 novembro, 2019
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    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
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    • julho 2015
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2015
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      This table contains data on discouraged workers who are persons not in the labour force who believe that there is no work available due to various reasons and who desire to work. Data are broken down by sex and standardised age groups (15-24, 15-64, 25-54, 55-64, 65+, total).
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 outubro, 2019
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      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-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.
    • março 2018
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 27 março, 2018
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 outubro, 2019
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      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.
    • dezembro 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 27 maio, 2014
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      Eurostat Dataset Id:educ_bo_ou_mism The Bologna declaration was signed in 1999 by 29 European ministers responsible for higher education. Today, 46 signatory countries are engaged in the process towards a European Higher Education Area (EHEA). The Bologna Process is an intergovernmental initiative which also involves the European Commission, the Council of Europe and UNESCO-CEPES, as well as representatives of higher education institutions, students, staff, employers and quality assurance agencies. It aims to create a European Higher Education Area by 2010, and to promote the European system of higher education worldwide. More information on the Bologna process is available on http://ec.europa.eu/education/higher-education/doc1290_en.htm. In the framework of the indicators for the monitoring of the social dimension and mobility of the Bologna Process, the EU-SILC (EU Statistics on Income and Living Conditions) data of interest cover individual's educational attainment, income and, from the intergenerational transmission of poverty ad hoc module, educational attainment of the parents. The following data-sets, having EU-SILC as source, on the Bologna Process are available: A. Widening access educ_bo_ac_sobs: Individuals having completed tertiary education (ISCED 5-6), according to the educational background of their parents, by sexeduc_bo_ac_soba: Individuals having completed tertiary education (ISCED 5-6), according to the educational background of their parents, by age D. Effective outcomes and employability educ_bo_ou_attd: Annual gross income of workers by educational attainment (2006)educ_bo_ou_terd: Annual gross income of workers with tertiary education (ISCED 5-6) , by sex (2006) The general aim of the EU-SILC domain is to provide comparable statistics and indicators on key aspects of the citizens' living conditions across Europe. This domain actually contains a range of social statistics and indicators relating to the risks of income poverty and social exclusion. There are both conceptual and methodological problems in defining and measuring income poverty and social exclusion. Since a 1984 decision of the European Council, the following are regarded as poor: "those persons, families and groups of persons whose resources (material, cultural and social) are so limited as to exclude them from the minimum acceptable way of life in the Member State to which they belong". On this basis, measures of poverty at EU level adopt an approach which is both multi-dimensional and relative. In June 2006, a new set of common indicators for the social protection and social inclusion process was adopted. (For more details and definitions of these indicators: Indicators 2006). To investigate particular areas of policy interest in more detail, target secondary areas, to be collected every four years or less frequently, are added to the cross-sectional component of EU-SILC. "The intergenerational transmission of poverty" was chosen as the area to be implemented for 2005. This specific module, collected in 2005, had as purpose to collect and compile relevant and robust information on background factors linked to adult social exclusion, minimising the burden of respondents to provide accurate detailed indicators sufficiently comparable across the EU capturing the effects of childhood experiences on poverty risk. More general information on EU-SILC is available on ilc_base.htm
    • março 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 março, 2019
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      The Adult Education Survey (AES) covers adults’ participation in education and training (formal, non-formal and informal learning) and is one of the main data sources for EU lifelong learning statistics. The AES covers the resident population aged 25-64. The reference period for the participation in education and training is the twelve months prior to the interview. The following information is available from the AES:Participation in formal education, non-formal education and training and informal learning (respectively labelled FED, NFE and INF)Volume of instruction hoursCharacteristics of the learning activitiesReasons for participatingObstacles to participationAccess to information on learning possibilitiesEmployer financing and costs of learningSelf-reported language skills Three waves of the survey have been implemented so far (2007 AES, 2011 AES and 2016 AES). The first AES – referred to as 2007 AES – was a pilot exercise and carried out on a voluntary basis in 29 countries in the EU, EFTA (European Free Trade Association) and candidate countries between 2005 and 2008. The 2011 AES was underpinned by a European legal act and thus carried out in all Member States on a mandatory basis. The 2016 AES was carried out in 2016/2017 and the dissemination of results is ongoing with the available countries. Comparable data for the three waves can be found in the following folders:Participation in education and training (last 12 months) (trng_aes_12m0)Participation in informal learning (last 12 months) (trng_aes_12m4)Access to information on education and training (last 12 months) (trng_aes_12m1)Time spent on education and training (last 12 months) (trng_aes_12m2)           Obstacles to participation in education and training (last 12 months) (trng_aes_12m3)Self-reported language skills (educ_lang_00)
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 26 outubro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 26 outubro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 01 novembro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 01 novembro, 2019
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      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.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Sandeep Reddy
      Acesso em 14 outubro, 2019
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      The OECD FSE database is intended to be the best source of information on fisheries policies in OECD members and participating non-OECD economies. It is designed to monitor and quantify developments in fisheries policy, to establish a common basis for policy dialogue among countries, and to provide economic data to assess the effectiveness and efficiency of policies. These tables report country programmes data aggregated according to the main categories presented in the FSE Manual. More detailed documentation on country programmes can be found in country-level metadata; more data on country programmes can be found in the full dataset (Excel Format - link provided below). Statistics are organized in pivot tables to make possible cross-country comparisons and to filter disaggregated policy-level data by policy implementation criteria and country.
    • abril 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 05 maio, 2019
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      The duration of working life indicator (DWL) measures the number of years a person aged 15 is expected to be active in the labour market throughout his/her life. This indicator has been developed and produced for analysis and monitoring under the Europe 2020 employment strategy. The indicator should complement other indicators by focussing on the entire life cycle of active persons and persons in employment rather than on specific states in the life cycle, such as youth unemployment or early withdrawal from the labour force. The development of life course policies is important in order to achieve more flexibility in the working life according to different stages of the life cycle. This indicator is derived from demographic data (life tables published in Eurostat online dataset demo_mlifetable) and labour market data (activity rates defined as in the online dataset lfsi_act_a but with unpublished detail by single age groups).
    • março 2018
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 27 março, 2018
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      20.1. Source data
  • E
    • março 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 22 março, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 outubro, 2019
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      The indicator is defined as the percentage of the population aged 18-24 with at most lower secondary education and who were not in further education or training during the last four weeks preceding the survey. Lower secondary education refers to ISCED (International Standard Classification of Education) 2011 level 0-2 for data from 2014 onwards and to ISCED 1997 level 0-3C short for data up to 2013. The indicator is based on the EU Labour Force Survey.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 outubro, 2019
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      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
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      This ad-hoc module "transition from work to retirement" aimed at answering the following main questions: how people leave the labour market,why they left the labour market,why they did not stay longer and,how long the active population, aged 50 to 69, expects to be in the labour market.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 30 outubro, 2019
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      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.
    • dezembro 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 dezembro, 2018
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      This table contains data on economic short-time workers by professional status (employees or total employment). Economic short-time workers comprise workers who are working less than usual due to business slack, plant stoppage, or technical reasons. However, the definitions are not harmonised which hampers the comparison across countries. Data are broken down professional status - employees, total employment - by sex and by standardised age groups (15-24, 25-54, 55+, total).
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 30 outubro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 12 outubro, 2019
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      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
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 30 outubro, 2019
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      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
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      This ad-hoc module "transition from work to retirement" aimed at answering the following main questions: how people leave the labour market,why they left the labour market,why they did not stay longer and,how long the active population, aged 50 to 69, expects to be in the labour market.
    • outubro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 24 outubro, 2019
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    • agosto 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 15 agosto, 2019
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      '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.
    • agosto 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 13 agosto, 2019
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    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 30 outubro, 2019
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    • agosto 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 15 agosto, 2019
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      '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 patentsare 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.
    • outubro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 24 outubro, 2019
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    • julho 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 28 novembro, 2015
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      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.
    • março 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 29 novembro, 2015
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      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.
    • março 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 29 novembro, 2015
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      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.
    • março 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 dezembro, 2015
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 26 outubro, 2019
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      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 14 novembro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 26 outubro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
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      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
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      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 14 novembro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 26 outubro, 2019
      Selecionar Conjunto de dados
      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 14 novembro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • março 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 26 maio, 2014
      Selecionar Conjunto de dados
      Eurostat Dataset Id:cens_01reisco The tables presented in the topic of educational level 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.
    • abril 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 08 maio, 2019
      Selecionar Conjunto de dados
      The ad-hoc module "young people on the labour market" provides supplementary information on the correlation between work-based learning and labour market outcomes.
    • abril 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 maio, 2019
      Selecionar Conjunto de dados
      The ad-hoc module "young people on the labour market" provides supplementary information on the correlation between work-based learning and labour market outcomes.
    • abril 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 07 maio, 2019
      Selecionar Conjunto de dados
      The ad-hoc module "young people on the labour market" provides supplementary information on the correlation between work-based learning and labour market outcomes.
    • abril 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 08 maio, 2019
      Selecionar Conjunto de dados
      The ad-hoc module "young people on the labour market" provides supplementary information on the correlation between work-based learning and labour market outcomes.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 14 novembro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 26 outubro, 2019
      Selecionar Conjunto de dados
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 novembro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
      Selecionar Conjunto de dados
      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 novembro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 26 outubro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 01 novembro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 01 novembro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
      Selecionar Conjunto de dados
      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.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 05 junho, 2014
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      Eurostat Dataset Id:lfso_06yrspisco Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'.
    • março 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 28 novembro, 2015
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      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 …).
    • abril 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 28 novembro, 2015
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      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.
    • junho 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 29 novembro, 2015
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      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)
    • junho 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 29 novembro, 2015
      Selecionar Conjunto de dados
      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)
    • maio 2016
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 20 maio, 2016
      Selecionar Conjunto de dados
      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)
    • março 2009
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 29 novembro, 2015
      Selecionar Conjunto de dados
      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)
    • junho 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 27 novembro, 2015
      Selecionar Conjunto de dados
      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)
    • maio 2016
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 20 maio, 2016
      Selecionar Conjunto de dados
      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)
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
      Selecionar Conjunto de dados
      Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
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      Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are disaggregated by economic activity and occupation, according to the latest versions of the International Standard Industrial Classification of All Economic Activities (ISIC) and International Standard Classification of Occupations (ISCO), respectively. Economic activity refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works. Information on occupation provides a description of the set of tasks and duties which are carried out by, or can be assigned to, one person.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 16 outubro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • março 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 09 abril, 2019
      Selecionar Conjunto de dados
      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.
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
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      Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are disaggregated by economic activity according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Economic activity refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works.
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
      Selecionar Conjunto de dados
      Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are disaggregated by economic activity according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year, and presented for categories at the 2-digit level of the classification. Economic activity refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works.
    • agosto 2018
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 03 setembro, 2018
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      Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are disaggregated by economic activity according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year, and presented for a selection of categories at the 2-digit level of the classification. Economic activity refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works.
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
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      Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are provided by institutional sector, which refers to disaggregations by public and private sector employment. Public sector employment covers employment in the government sector plus employment in publicly-owned resident enterprises and companies, operating at central, state (or regional) and local levels of government. It covers all persons employed directly by those institutions, regardless of the particular type of employment contract. Private sector employment comprises employment in all resident units operated by private enterprises, that is, it excludes enterprises controlled or operated by the government sector.
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
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      Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are disaggregated by occupation according to the latest version of the International Standard Classification of Occupations (ISCO) available for that year and presented for categories at the 2-digit level of the classification. Information on occupation provides a description of the set of tasks and duties which are carried out by, or can be assigned to, one person.
    • agosto 2018
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 03 setembro, 2018
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      Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are disaggregated by occupation according to the latest version of the International Standard Classification of Occupations (ISCO) available for that year and presented for a selection of categories at the 2-digit level of the classification. Information on occupation provides a description of the set of tasks and duties which are carried out by, or can be assigned to, one person.
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
      Selecionar Conjunto de dados
      Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are disaggregated by occupation according to the latest version of the International Standard Classification of Occupations (ISCO) available for that year. Information on occupation provides a description of the set of tasks and duties which are carried out by, or can be assigned to, one person.
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
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      Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are disaggregated by weekly hours actually worked, on the basis of the mean number of hours of work per week, and with reference to hours worked in all jobs of employed persons and in all types of working time arrangements (e.g. full-time and part-time). Hours actually worked include (a) direct hours or the time spent carrying out the tasks and duties of a job, (b) related hours, or the time spent maintaining, facilitating or enhancing productive activities (c) down time, or time when a person in a job cannot work due to machinery or process breakdown, accident, lack of supplies or power or Internet access and (d) resting time, or time spent in short periods of rest, relief or refreshment, including tea, coffee or prayer breaks, generally practised by custom or contract according to established norms and/or national circumstances. Hours actually worked excludes time not worked during activities such as: (a) Annual leave, public holidays, sick leave, parental leave or maternity/paternity leave, other leave for personal or family reasons or civic duty, (b) Commuting time between work and home when no productive activity for the job is performed; for paid employment, even when paid by the employer; (c) Time spent in certain educational activities; for paid employment, even when authorized, paid or provided by the employer; (d) Longer breaks distinguished from short resting time when no productive activity is performed (such as meal breaks or natural repose during long trips); for paid employment, even when paid by the employer.
    • agosto 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 14 agosto, 2019
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      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.
    • agosto 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 agosto, 2019
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      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 novembro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
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      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 novembro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
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      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.
    • novembro 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 12 novembro, 2019
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    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 11 novembro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
      Selecionar Conjunto de dados
      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.
    • abril 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 09 maio, 2019
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      The ad-hoc module "young people on the labour market" provides supplementary information on the correlation between work-based learning and labour market outcomes.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
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      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 31 outubro, 2019
      Selecionar Conjunto de dados
      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.
    • fevereiro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 fevereiro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 10 outubro, 2019
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      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.
    • novembro 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 15 novembro, 2019
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      In the MIP context the indicators Employment and Employees are used for the calculation of the Unit labour cost index. Both Employment and Employees source from the National accounts domain. 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 data. 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 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.
    • junho 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 23 junho, 2019
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      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
    • junho 2019
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 23 junho, 2019
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      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
    • julho 2019
      Fonte: International Labour Organization
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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      Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 28 outubro, 2019
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      Compared to men, women are less likely to work full-time, more likely to be employed in lower-paid occupations, and less likely to progress in their careers. As a result gender pay gaps persist and women are more likely to end their lives in poverty. This data looks at how many men and women are in paid work, who works full-time, and how having children and growing older affect women’s work patterns and earnings differently to men’s. It looks at how women bear the brunt of domestic and family responsibilities, even when working full-time. It also considers the benefits for businesses of keeping skilled women in the workplace, and encouraging them to sit on company boards. It looks at women’s representation in parliaments, judicial systems, and the senior civil service. It examines male and female employment in the wake of the crisis, and how women tend to be confined to the most vulnerable categories within the informal sector in developing countries.
    • agosto 2014
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 28 novembro, 2015
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      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.
    • janeiro 2015
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 18 agosto, 2015
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    • junho 2012
      Fonte: Eurostat
      Carregamento por: Knoema
      Acesso em 28 novembro, 2015
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      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
    • outubro 2014
      Fonte: United Nations Economic Commission for Europe
      Carregamento por: Knoema
      Acesso em 21 novembro, 2018
      Selecionar Conjunto de dados
      General note on the UNECE MDG Database: The database aims to show the official national estimates of MDG-indicators used for monitoring progress towards the Millennium Development Goals. Data is shown alongside official international estimates of MDG-indicators (as published on the official United Nations site for the MDG Indicators: http://unstats.un.org/unsd/mdg). Besides the international MDG-indicators, other indicators and disaggregates that are relevant for the UNECE-region are included. At present, the tables include data from the latest official MDG-report of each country. Currently, data from official dedicated MDG-websites and previous official national MDG-reports are being added. Additionally, more detailed metadata is being added to the footnotes. Additional indicators might be added if they are used generally across the region. Please note that some indicators are also available in the Gender Statistics Database of UNECE. Figures might differ due to the use of different sources. Definition of the indicators: Explanations on the indicators are listed below. Deviations from the standard definitions provided here are specified in the country-specific footnotes. Indicator Growth rate of GDP per person employed (%) Definition: The growth rate of gross domestic product (GDP) per person employed is defined as the growth rate of output per unit of labour input. The growth rate of GDP per person employed is expressed in units of percentage. Employment-to-population ratio, total (%) Definition: The employment-to-population ratio is the proportion of a country’s working-age population that is employed. The working-age population is defined as persons aged 15 years and older. Employed people living below the national poverty line (%) Definition: The proportion of employed persons living below the national povery line, or working poor, is the proportion of individuals who are in the labour force, but nonetheless live in a household whose members are estimated to be living below the national poverty line. This indicator is not monitored in The official United Nations site for the MDG Indicators. Own-account and contributing family workers in total employment, total (%) Definition: The proportion of own-account workers and contributing family workers in total employment is defined as the proportion of workers in self-employment who do not have employees, and unpaid family workers in total employment. Male own-account and contributing family workers in total employment (%) Definition: The proportion of male own-account workers and contributing family workers in total (male) employment is defined as the proportion of male workers in self-employment who do not have employees, and unpaid male family workers in total (male) employment. Female own-account and contributing family workers in total employment (%) Definition: The proportion of female own-account workers and contributing family workers in total (male) employment is defined as the proportion of female workers in self-employment who do not have employees, and unpaid male family workers in total (female) employment. Youth unemployment rate (aged 15-24), both sexes Definition: The youth unemployment rate is the proportion of the youth labour force that is unemployed. Young people are defined as persons aged between 15 and 24. The unemployed comprise all persons above a specified age who, during the reference period, were: (a) without work; (b) currently available for work; and (c) actively seeking work. The labour force is the sum of the number of persons employed and the number of persons unemployed. Male youth unemployment rate (aged 15-24) Definition: The male youth unemployment rate is the proportion of the male youth labour force that is unemployed. Young people are defined as persons aged between 15 and 24. The unemployed comprise all persons above a specified age who, during the reference period, were: (a) without work; (b) currently available for work; and (c) actively seeking work. The labour force is the sum of the number of persons Female youth unemployment rate (aged 15-24) Definition: The female youth unemployment rate is the proportion of the female youth labour force that is unemployed. Young people are defined as persons aged between 15 and 24. The unemployed comprise all persons above a specified age who, during the reference period, were: (a) without work; (b) currently available for work; and (c) actively seeking work. The labour force is the sum of the number of persons Youth unemployment rate to adult unemployment rate, total (ratio) Definition: This indicator is the ratio of the youth to adult unemployment rates. The youth unemployment rate is the proportion of the youth labour force that is unemployed; the adult unemployment rate is the proportion of the adult labour force that is unemployed. Young people are defined as persons aged between 15 and 24; adults are those aged 25 and above. Male youth unemployment rate to adult unemployment rate (ratio) Definition: This indicator is the ratio of the youth to adult unemployment rates for males. The youth unemployment rate is the proportion of the youth labour force that is unemployed; the adult unemployment rate is the proportion of the adult labour force that is unemployed. Young people are defined as persons aged between 15 and 24; adults are those aged 25 and above. Female youth unemployment rate to adult unemployment rate (ratio) Definition: This indicator is the ratio of the youth to adult unemployment rates for females. The youth unemployment rate is the proportion of the youth labour force that is unemployed; the adult unemployment rate is the proportion of the adult labour force that is unemployed. Young people are defined as persons aged between 15 and 24; adults are those aged 25 and above. Youth unemployed in total unemployed (%) Definition: The youth unemployment rate is the proportion of the youth labour force that is unemployed. Young people are defined as persons aged between 15 and 24; adults are those aged 25 and above. Male youth unemployed in total unemployed (%) Definition: The male youth unemployment rate is the proportion of the male youth labour force that is unemployed. Young people are defined as persons aged between 15 and 24; adults are those aged 25 and above. Female youth unemployed in total unemployed (%) Definition: The female youth unemployment rate is the proportion of the female youth labour force that is unemployed. Young people are defined as persons aged between 15 and 24; adults are those aged 25 and above. Youth unemployed in youth population, total Definition: Youth unemployment as a proportion of the youth population is defined as the proportion of the total youth population that is unemployed. Young people are defined as persons aged between 15 and 24. Male youth unemployed in male youth population ratio Definition: Male youth unemployment as a proportion of the youth population is defined as the proportion of the total male youth population that is unemployed. Young people are defined as persons aged between 15 and 24. Female youth unemployed in female youth population Definition: Female youth unemployment as a proportion of the youth population is defined as the proportion of the total female youth population that is unemployed. Young people are defined as persons aged between 15 and 24. Unemployment rate Definition: The unemployment rate is the ratio of the total number of unemployed relative to the corresponding labour force, which itself is the sum of the total persons employed and unemployed in the group. Male unemployment rate Definition: The male unemployment rate is the ratio of the total number of unemployed males relative to the corresponding male labour force, which itself is the sum of the total male persons employed and unemployed in the group. Female unemployment rate Definition: The female unemployment rate is the ratio of the total number of unemployed females relative to the corresponding female labour force, which itself is the sum of the total female persons employed and unemployed in the group. Long-term unemployment rate Definition: The long-term unemployment rate is the ratio of the total number of long termed unemployed (unemployed for 12 months or more) relative to the corresponding labour force. Indicator: Employment-to-population ratio, total (%) , Country: Albania International Series: 2001: Reference period: April.; 2001, 2004, 2007 to 2010: Coverage: Total.; 2007 to 2010: Age: 15-64.; 2001: Type of source: Population census.; 2004: Type of source: Household or labour force survey.; 2001, 2004: Age: 15+.; 2007 to 2010: Type of source: Labour force survey.; Indicator: Male employment-to-population ratio (%) , Country: Albania International Series: 2001: Reference period: April.; 2001, 2004, 2007 to 2010: Coverage: Total.; 2007 to 2010: Age: 15-64.; 2001: Type of source: Population census.; 2004: Type of source: Household or labour force survey.; 2001, 2004: Age: 15+.; 2007 to 2010: Type of source: Labour force survey.; Indicator: Female employment-to-population ratio (%) , Country: Albania International Series: 2001: Reference period: April.; 2001, 2004, 2007 to 2010: Coverage: Total.; 2007 to 2010: Age: 15-64.; 2001: Type of source: Population census.; 2004: Type of source: Household or labour force survey.; 2001, 2004: Age: 15+.; 2007 to 2010: Type of source: Labour force survey.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Albania National Series Reference: 2002: MDG Report 2004; Definition: 2002: Age group 14-25; Source in Reference: 2002: NSO; International Series: 2001: Reference period: April.; 2001, 2007 to 2010: Coverage: Total.; 2007 to 2010: Age: 15-29.; 2001: Age: 15-24.; 2001: Type of source: Population census.; 2007 to 2010: Type of source: Labour force survey.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Albania International Series: 2001: Reference period: April.; 2001, 2007 to 2010: Coverage: Total.; 2007 to 2010: Age: 15-29.; 2001: Age: 15-24.; 2001: Type of source: Population census.; 2007 to 2010: Type of source: Labour force survey.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Albania International Series: 2001: Reference period: April.; 2001, 2007 to 2010: Coverage: Total.; 2007 to 2010: Age: 15-29.; 2001: Age: 15-24.; 2001: Type of source: Population census.; 2007 to 2010: Type of source: Labour force survey.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Albania International Series: 2001: Reference period: April.; 2001, 2007 to 2010: Coverage: Total.; 2007 to 2010: Age: 15-29.; 2001: Age: 15-24.; 2001: Type of source: Population census.; 2007 to 2010: Type of source: Labour force survey.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Albania International Series: 2001: Reference period: April.; 2001, 2007 to 2010: Coverage: Total.; 2007 to 2010: Age: 15-29.; 2001: Age: 15-24.; 2001: Type of source: Population census.; 2007 to 2010: Type of source: Labour force survey.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Albania International Series: 2001: Reference period: April.; 2001, 2007 to 2010: Coverage: Total.; 2007 to 2010: Age: 15-29.; 2001: Age: 15-24.; 2001: Type of source: Population census.; 2007 to 2010: Type of source: Labour force survey.; Indicator: Youth unemployed in total unemployed (%) , Country: Albania International Series: 2001: Reference period: April.; 2001: Coverage: Total.; 2001: Age: 15-24.; 2001: Type of source: Population census.; Indicator: Male youth unemployed in total unemployed (%) , Country: Albania International Series: 2001: Reference period: April.; 2001: Coverage: Total.; 2001: Age: 15-24.; 2001: Type of source: Population census.; Indicator: Female youth unemployed in total unemployed (%) , Country: Albania International Series: 2001: Reference period: April.; 2001: Coverage: Total.; 2001: Age: 15-24.; 2001: Type of source: Population census.; Indicator: Youth unemployed in youth population, total , Country: Albania International Series: 2001: Reference period: April.; 2001: Coverage: Total.; 2001: Age: 15-24.; 2001: Type of source: Population census.; Indicator: Male youth unemployed in male youth population ratio , Country: Albania International Series: 2001: Reference period: April.; 2001: Coverage: Total.; 2001: Age: 15-24.; 2001: Type of source: Population census.; Indicator: Female youth unemployed in female youth population , Country: Albania International Series: 2001: Reference period: April.; 2001: Coverage: Total.; 2001: Age: 15-24.; 2001: Type of source: Population census.; Indicator: Unemployment rate , Country: Albania National Series Reference: 2002 to 2009: MDG Progress Report 2010; Source in Reference: 2002 to 2009: INSTAT / MoLSAEO ; Primary Source in Reference: 2002 to 2009: LFS; Indicator: Male unemployment rate , Country: Albania National Series Reference: 2008: MDG Progress Report 2010; Source in Reference: 2008: INSTAT / MoLSAEO ; Indicator: Female unemployment rate , Country: Albania National Series Reference: 2008: MDG Progress Report 2010; Source in Reference: 2008: INSTAT / MoLSAEO ; Indicator: Long-term unemployment rate , Country: Albania National Series Reference: 2000 to 2005: MDG Report 2005; Source in Reference: 2000 to 2005: NSO; Indicator: Growth rate of GDP per person employed (%) , Country: Armenia National Series Reference: 2004 to 2008: MDG Progress Report 2005-2009; Note: 2008: Preliminary data; International Series: 2001: Reference period: October.; 2001, 2008 to 2011: Coverage: Total.; 2002: Survey limitation: Methodology revised; data not strictly comparable.; 2004: Age: 16+.; 2004: Type of source: Living standards survey.; 2001: Type of source: Population census.; 2004: Coverage: Not available.; 2008 to 2011: Type of source: Household or labour force survey.; 1994 to 2000, 2002, 2003, 2005 to 2007: Type of source: Official estimates.; 1994 to 2003, 2005 to 2007: Age: 15+.; 1994 to 2000, 2002, 2003, 2005 to 2007: Coverage: Civilian.; 2008 to 2011: Age: 15-75.; Indicator: Employment-to-population ratio, total (%) , Country: Armenia National Series Reference: 1999 to 2008: MDG Progress Report 2005-2009; Note: 1999 to 2007: Official statistics; 2008: Official statistics - Preliminary data; Source in Reference: 1999 to 2008: NSO; Primary Source in Reference: 1999 to 2007: Administrative data; International Series: 2001: Reference period: October.; 2001, 2008 to 2011: Coverage: Total.; 2004: Age: 16+.; 2004: Type of source: Living standards survey.; 2001: Type of source: Population census.; 2004: Coverage: Not available.; 2008 to 2011: Type of source: Household or labour force survey.; 2006: Type of source: Official estimates.; 2001, 2006: Age: 15+.; 2006: Coverage: Civilian.; 2008 to 2011: Age: 15-75.; Indicator: Male employment-to-population ratio (%) , Country: Armenia National Series Reference: 1999 to 2008: MDG Progress Report 2005-2009; Note: 1999 to 2007: Official statistics; 2008: Official statistics - Preliminary data; Source in Reference: 1999 to 2008: NSO; Primary Source in Reference: 1999 to 2007: Administrative data; International Series: 2001: Reference period: October.; 2001, 2008 to 2011: Coverage: Total.; 2004: Age: 16+.; 2004: Type of source: Living standards survey.; 2001: Type of source: Population census.; 2004: Coverage: Not available.; 2008 to 2011: Type of source: Household or labour force survey.; 2006: Type of source: Official estimates.; 2001, 2006: Age: 15+.; 2006: Coverage: Civilian.; 2008 to 2011: Age: 15-75.; Indicator: Female employment-to-population ratio (%) , Country: Armenia National Series Reference: 1999 to 2008: MDG Progress Report 2005-2009; Note: 1999 to 2007: Official statistics; 2008: Official statistics - Preliminary data; Source in Reference: 1999 to 2008: NSO; Primary Source in Reference: 1999 to 2007: Administrative data; International Series: 2001: Reference period: October.; 2001, 2008 to 2011: Coverage: Total.; 2004: Age: 16+.; 2004: Type of source: Living standards survey.; 2001: Type of source: Population census.; 2004: Coverage: Not available.; 2008 to 2011: Type of source: Household or labour force survey.; 2006: Type of source: Official estimates.; 2001, 2006: Age: 15+.; 2006: Coverage: Civilian.; 2008 to 2011: Age: 15-75.; Indicator: Employed people living below the national poverty line (%) , Country: Armenia National Series Reference: 1999 to 2008: MDG Progress Report 2005-2009; Definition: 1999 to 2008: National poverty line; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Armenia International Series: 2007 to 2011: Coverage: Total.; 2007: Coverage limitation: Excluding conscripts.; 2007: Age: 16+.; 2007 to 2011: Type of source: Household or labour force survey.; 2008 to 2011: Age: 15-75.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Armenia International Series: 2008 to 2011: Coverage: Total.; 2008 to 2011: Type of source: Household or labour force survey.; 2008 to 2011: Age: 15-75.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Armenia International Series: 2008 to 2011: Coverage: Total.; 2008 to 2011: Type of source: Household or labour force survey.; 2008 to 2011: Age: 15-75.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Armenia National Series Reference: 2001: MDG Progress Report 2005-2009; 2002 to 2003: ArmeniaInfo at: http://www.armdevinfo.am/ (accessed: 15 June 2011); 2004 to 2007: MDG Progress Report 2005-2009; 2008 to 2009: ArmeniaInfo at: http://www.armdevinfo.am/ (accessed: 15 June 2011); 2010 to 2012: Armenia MDGs Indicators (http://www.armstat.am/) 06/02/2014; Definition: 2001: Age group 16-24; 2004 to 2007: Age group 16-24; Note: 2001 to 2007: ILO extended definition of unemployment; 2008 to 2012: ILO standard definition of unemployment; 2001: Also includes those who failed to search for a job during 4 weeks preceding the survey for various reasons, but were ready to immediately start to work.; 2004 to 2007: Also includes those who failed to search for a job during 4 weeks preceding the survey for various reasons, but were ready to immediately start to work.; 2008 to 2009: ILO standard definition of unemployment used; Source in Reference: 2001 to 2012: NSO; Primary Source in Reference: 2001: ILCMS; 2002 to 2006: LFS; 2007: Integrated Living Conditions Survey; 2008 to 2012: LFS; International Series: 2001: Reference period: October.; 2001, 2007 to 2011: Coverage: Total.; 2007: Age: 16-24.; 2007: Coverage limitation: Excluding conscripts.; 2001, 2008 to 2011: Age: 15-24.; 2001: Type of source: Population census.; 2007 to 2011: Type of source: Household or labour force survey.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Armenia National Series Reference: 2001 to 2007: ArmeniaInfo at: http://www.armdevinfo.am/ (accessed: 15 June 2011); 2008 to 2012: Armenia MDGs Indicators (http://www.armstat.am/) 06/02/2014; Definition: 2001 to 2007: Age group 16-24; Note: 2001 to 2012: ILO standard definition of unemployment; 2001 to 2007: Also includes those who failed to search for a job during 4 weeks preceding the survey for various reasons, but were ready to immediately start to work.; Source in Reference: 2001 to 2012: NSO; Primary Source in Reference: 2001: ILCMS; 2002 to 2012: LFS; International Series: 2001: Reference period: October.; 2001, 2007 to 2011: Coverage: Total.; 2007: Age: 16-24.; 2007: Coverage limitation: Excluding conscripts.; 2001, 2008 to 2011: Age: 15-24.; 2001: Type of source: Population census.; 2007 to 2011: Type of source: Household or labour force survey.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Armenia National Series Reference: 2001 to 2007: ArmeniaInfo at: http://www.armdevinfo.am/ (accessed: 15 June 2011); 2008 to 2012: Armenia MDGs Indicators (http://www.armstat.am/) 06/02/2014; Definition: 2001 to 2007: Age group 16-24; Note: 2001 to 2012: ILO standard definition of unemployment; 2001 to 2007: Also includes those who failed to search for a job during 4 weeks preceding the survey for various reasons, but were ready to immediately start to work.; Source in Reference: 2001 to 2012: NSO; Primary Source in Reference: 2001: ILCMS; 2002 to 2012: LFS; International Series: 2001: Reference period: October.; 2001, 2007 to 2011: Coverage: Total.; 2007: Age: 16-24.; 2007: Coverage limitation: Excluding conscripts.; 2001, 2008 to 2011: Age: 15-24.; 2001: Type of source: Population census.; 2007 to 2011: Type of source: Household or labour force survey.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Armenia International Series: 2001: Reference period: October.; 2001, 2007 to 2011: Coverage: Total.; 2007: Age: 16-24.; 2007: Coverage limitation: Excluding conscripts.; 2001, 2008 to 2011: Age: 15-24.; 2001: Type of source: Population census.; 2007 to 2011: Type of source: Household or labour force survey.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Armenia International Series: 2001: Reference period: October.; 2001, 2007 to 2011: Coverage: Total.; 2007: Age: 16-24.; 2007: Coverage limitation: Excluding conscripts.; 2001, 2008 to 2011: Age: 15-24.; 2001: Type of source: Population census.; 2007 to 2011: Type of source: Household or labour force survey.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Armenia International Series: 2001: Reference period: October.; 2001, 2007 to 2011: Coverage: Total.; 2007: Age: 16-24.; 2007: Coverage limitation: Excluding conscripts.; 2001, 2008 to 2011: Age: 15-24.; 2001: Type of source: Population census.; 2007 to 2011: Type of source: Household or labour force survey.; Indicator: Youth unemployed in total unemployed (%) , Country: Armenia International Series: 2001: Reference period: October.; 2001, 2007 to 2011: Coverage: Total.; 2007: Age: 16-24.; 2007: Coverage limitation: Excluding conscripts.; 2001, 2008 to 2011: Age: 15-24.; 2001: Type of source: Population census.; 2007 to 2011: Type of source: Household or labour force survey.; Indicator: Male youth unemployed in total unemployed (%) , Country: Armenia International Series: 2001: Reference period: October.; 2001, 2007 to 2011: Coverage: Total.; 2007: Age: 16-24.; 2007: Coverage limitation: Excluding conscripts.; 2001, 2008 to 2011: Age: 15-24.; 2001: Type of source: Population census.; 2007 to 2011: Type of source: Household or labour force survey.; Indicator: Female youth unemployed in total unemployed (%) , Country: Armenia International Series: 2001: Reference period: October.; 2001, 2007 to 2011: Coverage: Total.; 2007: Age: 16-24.; 2007: Coverage limitation: Excluding conscripts.; 2001, 2008 to 2011: Age: 15-24.; 2001: Type of source: Population census.; 2007 to 2011: Type of source: Household or labour force survey.; Indicator: Youth unemployed in youth population, total , Country: Armenia International Series: 2001: Reference period: October.; 2001, 2008 to 2011: Coverage: Total.; 2001, 2008 to 2011: Age: 15-24.; 2001: Type of source: Population census.; 2008 to 2011: Type of source: Household or labour force survey.; Indicator: Male youth unemployed in male youth population ratio , Country: Armenia International Series: 2001: Reference period: October.; 2001, 2008 to 2011: Coverage: Total.; 2001, 2008 to 2011: Age: 15-24.; 2001: Type of source: Population census.; 2008 to 2011: Type of source: Household or labour force survey.; Indicator: Female youth unemployed in female youth population , Country: Armenia International Series: 2001: Reference period: October.; 2001, 2008 to 2011: Coverage: Total.; 2001, 2008 to 2011: Age: 15-24.; 2001: Type of source: Population census.; 2008 to 2011: Type of source: Household or labour force survey.; Indicator: Unemployment rate , Country: Armenia National Series Reference: 2001 to 2007: MDG Progress Report 2005-2009; Source in Reference: 2001 to 2007: NSO; Primary Source in Reference: 2001 to 2007: Integrated Living Conditions Survey; Indicator: Male unemployment rate , Country: Armenia National Series Reference: 2001 to 2007: MDG Progress Report 2005-2009; Source in Reference: 2001 to 2007: Social Snapshot and Poverty in the Republic of Armenia, NSS, Yerevan 2001; Indicator: Female unemployment rate , Country: Armenia National Series Reference: 2001 to 2007: MDG Progress Report 2005-2009; Source in Reference: 2001 to 2007: Social Snapshot and Poverty in the Republic of Armenia, NSS, Yerevan 2001; Indicator: Growth rate of GDP per person employed (%) , Country: Azerbaijan National Series Reference: 2003 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 2003 to 2010: NSO; International Series: 2009 to 2012: Reference period: December.; 2007, 2008: Type of source: Household or labour force survey.; 1991 to 2006: Type of source: Official estimates.; 1991 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; 1991 to 2012: Coverage: Civilian.; Indicator: Employment-to-population ratio, total (%) , Country: Azerbaijan National Series Reference: 1990 to 2012: NSO MDG data; Note: 2000 to 2012: Recalculated based on data of 2009 population census; Source in Reference: 1990 to 2012: NSO; Primary Source in Reference: 1990 to 2012: Sample Statistical Survey of Economic Active Population; International Series: 2009 to 2011: Reference period: December.; 2007, 2008: Type of source: Household or labour force survey.; 2002 to 2006: Type of source: Official estimates.; 2002 to 2011: Age: 15+.; 2009 to 2011: Type of source: Labour force survey.; 2002 to 2011: Coverage: Civilian.; Indicator: Male employment-to-population ratio (%) , Country: Azerbaijan International Series: 2009 to 2011: Reference period: December.; 2007, 2008: Type of source: Household or labour force survey.; 2002 to 2006: Type of source: Official estimates.; 2002 to 2011: Age: 15+.; 2009 to 2011: Type of source: Labour force survey.; 2002 to 2011: Coverage: Civilian.; Indicator: Female employment-to-population ratio (%) , Country: Azerbaijan International Series: 2009 to 2011: Reference period: December.; 2007, 2008: Type of source: Household or labour force survey.; 2002 to 2006: Type of source: Official estimates.; 2002 to 2011: Age: 15+.; 2009 to 2011: Type of source: Labour force survey.; 2002 to 2011: Coverage: Civilian.; Indicator: Employed people living below the national poverty line (%) , Country: Azerbaijan National Series Reference: 2003: MDG Progress Report 2003/2004; Definition: 2003: National poverty line; Source in Reference: 2003: NSO; Primary Source in Reference: 2003: HBS; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Azerbaijan International Series: 2003 to 2005: Type of source: Official estimates.; 2003 to 2008: Age: 15+.; 2006 to 2008: Type of source: Labour force survey.; 2003 to 2008: Coverage: Civilian.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Azerbaijan International Series: 2003 to 2005: Type of source: Official estimates.; 2003 to 2008: Age: 15+.; 2006 to 2008: Type of source: Labour force survey.; 2003 to 2008: Coverage: Civilian.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Azerbaijan International Series: 2003 to 2005: Type of source: Official estimates.; 2003 to 2008: Age: 15+.; 2006 to 2008: Type of source: Labour force survey.; 2003 to 2008: Coverage: Civilian.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Azerbaijan National Series Reference: 2003 to 2012: NSO MDG data; Source in Reference: 2003 to 2012: NSO; International Series: 2009 to 2012: Reference period: December.; 1999: Reference period: January.; 1999: Coverage: Total.; 1999: Age: 16-24.; 2007 to 2012: Age: 15-24.; 1999: Type of source: Population census.; 2007 to 2012: Type of source: Labour force survey.; 2007 to 2012: Coverage: Civilian.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Azerbaijan National Series Reference: 2003 to 2012: NSO MDG data; Source in Reference: 2003 to 2012: NSO; International Series: 2009 to 2012: Reference period: December.; 1999: Reference period: January.; 1999: Coverage: Total.; 1999: Age: 16-24.; 2007 to 2012: Age: 15-24.; 1999: Type of source: Population census.; 2007 to 2012: Type of source: Labour force survey.; 2007 to 2012: Coverage: Civilian.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Azerbaijan National Series Reference: 2003 to 2012: NSO MDG data; Source in Reference: 2003 to 2012: NSO; International Series: 2009 to 2012: Reference period: December.; 1999: Reference period: January.; 1999: Coverage: Total.; 1999: Age: 16-24.; 2007 to 2012: Age: 15-24.; 1999: Type of source: Population census.; 2007 to 2012: Type of source: Labour force survey.; 2007 to 2012: Coverage: Civilian.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Azerbaijan National Series Reference: 2003 to 2012: NSO MDG data; Source in Reference: 2003 to 2012: NSO; International Series: 2009 to 2012: Reference period: December.; 1999: Reference period: January.; 1999: Coverage: Total.; 1999: Age: 16-24.; 2007 to 2012: Age: 15-24.; 1999: Type of source: Population census.; 2007 to 2012: Type of source: Labour force survey.; 2007 to 2012: Coverage: Civilian.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Azerbaijan National Series Reference: 2003 to 2012: NSO MDG data; Source in Reference: 2003 to 2012: NSO; International Series: 2009 to 2012: Reference period: December.; 1999: Reference period: January.; 1999: Coverage: Total.; 1999: Age: 16-24.; 2007 to 2012: Age: 15-24.; 1999: Type of source: Population census.; 2007 to 2012: Type of source: Labour force survey.; 2007 to 2012: Coverage: Civilian.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Azerbaijan National Series Reference: 2003 to 2012: NSO MDG data; Source in Reference: 2003 to 2012: NSO; International Series: 2009 to 2012: Reference period: December.; 1999: Reference period: January.; 1999: Coverage: Total.; 1999: Age: 16-24.; 2007 to 2012: Age: 15-24.; 1999: Type of source: Population census.; 2007 to 2012: Type of source: Labour force survey.; 2007 to 2012: Coverage: Civilian.; Indicator: Youth unemployed in total unemployed (%) , Country: Azerbaijan National Series Reference: 2003 to 2012: NSO MDG data; Source in Reference: 2003 to 2012: NSO; International Series: 2009 to 2012: Reference period: December.; 1999: Reference period: January.; 1999: Coverage: Total.; 1999: Age: 16-24.; 2003 to 2012: Age: 15-24.; 1999: Type of source: Population census.; 2004, 2005: Type of source: Official estimates.; 2003, 2006 to 2012: Type of source: Labour force survey.; 2003 to 2012: Coverage: Civilian.; Indicator: Male youth unemployed in total unemployed (%) , Country: Azerbaijan National Series Reference: 2003 to 2012: NSO MDG data; Source in Reference: 2003 to 2012: NSO; International Series: 2009 to 2012: Reference period: December.; 1999: Reference period: January.; 1999: Coverage: Total.; 1999: Age: 16-24.; 2003 to 2012: Age: 15-24.; 1999: Type of source: Population census.; 2004, 2005: Type of source: Official estimates.; 2003, 2006 to 2012: Type of source: Labour force survey.; 2003 to 2012: Coverage: Civilian.; Indicator: Female youth unemployed in total unemployed (%) , Country: Azerbaijan National Series Reference: 2003 to 2012: NSO MDG data; Source in Reference: 2003 to 2012: NSO; International Series: 2009 to 2012: Reference period: December.; 1999: Reference period: January.; 1999: Coverage: Total.; 1999: Age: 16-24.; 2003 to 2012: Age: 15-24.; 1999: Type of source: Population census.; 2004, 2005: Type of source: Official estimates.; 2003, 2006 to 2012: Type of source: Labour force survey.; 2003 to 2012: Coverage: Civilian.; Indicator: Youth unemployed in youth population, total , Country: Azerbaijan National Series Reference: 2003 to 2012: NSO MDG data; Source in Reference: 2003 to 2012: NSO; International Series: 2009 to 2011: Reference period: December.; 1999: Reference period: January.; 1999: Coverage: Total.; 1999: Age: 16-24.; 2007 to 2011: Age: 15-24.; 1999: Type of source: Population census.; 2007 to 2011: Type of source: Labour force survey.; 2007 to 2011: Coverage: Civilian.; Indicator: Male youth unemployed in male youth population ratio , Country: Azerbaijan National Series Reference: 2003 to 2012: NSO MDG data; Source in Reference: 2003 to 2012: NSO; International Series: 2009 to 2011: Reference period: December.; 1999: Reference period: January.; 1999: Coverage: Total.; 1999: Age: 16-24.; 2007 to 2011: Age: 15-24.; 1999: Type of source: Population census.; 2007 to 2011: Type of source: Labour force survey.; 2007 to 2011: Coverage: Civilian.; Indicator: Female youth unemployed in female youth population , Country: Azerbaijan National Series Reference: 2003 to 2012: NSO MDG data; Source in Reference: 2003 to 2012: NSO; International Series: 2009 to 2011: Reference period: December.; 1999: Reference period: January.; 1999: Coverage: Total.; 1999: Age: 16-24.; 2007 to 2011: Age: 15-24.; 1999: Type of source: Population census.; 2007 to 2011: Type of source: Labour force survey.; 2007 to 2011: Coverage: Civilian.; Indicator: Unemployment rate , Country: Azerbaijan National Series Reference: 2003: MDG Progress Report 2003/2004; Source in Reference: 2003: NSO; Primary Source in Reference: 2003: LFS 2003; Indicator: Male unemployment rate , Country: Azerbaijan National Series Reference: 2003: MDG Progress Report 2003/2004; Source in Reference: 2003: NSO; Primary Source in Reference: 2003: LFS 2003; Indicator: Female unemployment rate , Country: Azerbaijan National Series Reference: 2003: MDG Progress Report 2003/2004; Source in Reference: 2003: NSO; Primary Source in Reference: 2003: LFS 2003; Indicator: Growth rate of GDP per person employed (%) , Country: Belarus International Series: 1991 to 2009: Coverage: Total.; 2007: Survey limitation: Methodology revised; data not strictly comparable.; 1991 to 2008: Age: 16+.; 2009: Type of source: Population census.; 1991 to 2008: Type of source: Labour-related establishment survey.; 2009: Age: 15+.; Indicator: Employment-to-population ratio, total (%) , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Type of source: Population census.; 2009: Age: 15+.; Indicator: Male employment-to-population ratio (%) , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Type of source: Population census.; 2009: Age: 15+.; Indicator: Female employment-to-population ratio (%) , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Type of source: Population census.; 2009: Age: 15+.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Type of source: Population census.; 2009: Age: 15+.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Type of source: Population census.; 2009: Age: 15+.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Type of source: Population census.; 2009: Age: 15+.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Age: 15-24.; 2009: Type of source: Population census.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Age: 15-24.; 2009: Type of source: Population census.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Age: 15-24.; 2009: Type of source: Population census.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Age: 15-24.; 2009: Type of source: Population census.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Age: 15-24.; 2009: Type of source: Population census.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Age: 15-24.; 2009: Type of source: Population census.; Indicator: Youth unemployed in total unemployed (%) , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Age: 15-24.; 2009: Type of source: Population census.; Indicator: Male youth unemployed in total unemployed (%) , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Age: 15-24.; 2009: Type of source: Population census.; Indicator: Female youth unemployed in total unemployed (%) , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Age: 15-24.; 2009: Type of source: Population census.; Indicator: Youth unemployed in youth population, total , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Age: 15-24.; 2009: Type of source: Population census.; Indicator: Male youth unemployed in male youth population ratio , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Age: 15-24.; 2009: Type of source: Population census.; Indicator: Female youth unemployed in female youth population , Country: Belarus International Series: 2009: Coverage: Total.; 2009: Age: 15-24.; 2009: Type of source: Population census.; Indicator: Unemployment rate , Country: Belarus National Series Reference: 2000 to 2009: MDG progress 2010; Source in Reference: 2000 to 2009: Statistical Annual Publication 2010; Indicator: Growth rate of GDP per person employed (%) , Country: Bosnia and Herzegovina International Series: 2007, 2010 to 2012: Reference period: April.; 2008, 2009: Reference period: May.; 2007 to 2012: Coverage: Total.; 2007 to 2012: Age: 15+.; 2007 to 2012: Type of source: Labour force survey.; Indicator: Employment-to-population ratio, total (%) , Country: Bosnia and Herzegovina National Series Reference: 2001 to 2010: MDG progress report 2010; 2012: MDG Report 2013; Source in Reference: 2001 to 2012: NSO; Primary Source in Reference: 2001: Living in BiH - Wave 4 2004; 2006 to 2010: LFS; International Series: 2006, 2007, 2010 to 2012: Reference period: April.; 2008, 2009: Reference period: May.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15+.; 2006 to 2012: Type of source: Labour force survey.; Indicator: Male employment-to-population ratio (%) , Country: Bosnia and Herzegovina National Series Reference: 2006 to 2009: MDG progress report 2010; Source in Reference: 2006 to 2009: NSO; Primary Source in Reference: 2006 to 2009: LFS; International Series: 2006, 2007, 2010 to 2012: Reference period: April.; 2008, 2009: Reference period: May.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15+.; 2006 to 2012: Type of source: Labour force survey.; Indicator: Female employment-to-population ratio (%) , Country: Bosnia and Herzegovina National Series Reference: 2006 to 2009: MDG progress report 2010; Source in Reference: 2006 to 2009: NSO; Primary Source in Reference: 2006 to 2009: LFS; International Series: 2006, 2007, 2010 to 2012: Reference period: April.; 2008, 2009: Reference period: May.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15+.; 2006 to 2012: Type of source: Labour force survey.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Bosnia and Herzegovina International Series: 2010 to 2012: Reference period: April.; 2009: Reference period: May.; 2009 to 2012: Coverage: Total.; 2009 to 2012: Classification remark: Includes employers.; 2009 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Bosnia and Herzegovina International Series: 2010 to 2012: Reference period: April.; 2009: Reference period: May.; 2009 to 2012: Coverage: Total.; 2009 to 2012: Classification remark: Includes employers.; 2009 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Bosnia and Herzegovina International Series: 2010 to 2012: Reference period: April.; 2009: Reference period: May.; 2009 to 2012: Coverage: Total.; 2009 to 2012: Classification remark: Includes employers.; 2009 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Bosnia and Herzegovina National Series Reference: 2000 to 2009: MDG progress report 2010; 2010 to 2012: MDG Report 2013; Definition: 2000: Age group 19-24; Reference period: 2000: 2000-2001; Source in Reference: 2000: World Bank 2003; 2007 to 2009: NSO; Primary Source in Reference: 2000: LSMS 2000-2001; 2007 to 2012: LFS; International Series: 2006, 2007, 2010 to 2012: Reference period: April.; 2008, 2009: Reference period: May.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15-24.; 2006 to 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Bosnia and Herzegovina National Series Reference: 2012: MDG Report 2013; Primary Source in Reference: 2012: LFS; International Series: 2006, 2007, 2010 to 2012: Reference period: April.; 2008, 2009: Reference period: May.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15-24.; 2006 to 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Bosnia and Herzegovina National Series Reference: 2012: MDG Report 2013; Primary Source in Reference: 2012: LFS; International Series: 2006, 2007, 2010 to 2012: Reference period: April.; 2008, 2009: Reference period: May.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15-24.; 2006 to 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Bosnia and Herzegovina International Series: 2006, 2007, 2010 to 2012: Reference period: April.; 2008, 2009: Reference period: May.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15-24.; 2006 to 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Bosnia and Herzegovina International Series: 2006, 2007, 2010 to 2012: Reference period: April.; 2008, 2009: Reference period: May.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15-24.; 2006 to 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Bosnia and Herzegovina International Series: 2006, 2007, 2010 to 2012: Reference period: April.; 2008, 2009: Reference period: May.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15-24.; 2006 to 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployed in total unemployed (%) , Country: Bosnia and Herzegovina International Series: 2006, 2007, 2010 to 2012: Reference period: April.; 2008, 2009: Reference period: May.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15-24.; 2006 to 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployed in total unemployed (%) , Country: Bosnia and Herzegovina International Series: 2006, 2007, 2010 to 2012: Reference period: April.; 2008, 2009: Reference period: May.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15-24.; 2006 to 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployed in total unemployed (%) , Country: Bosnia and Herzegovina International Series: 2006, 2007, 2010 to 2012: Reference period: April.; 2008, 2009: Reference period: May.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15-24.; 2006 to 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployed in youth population, total , Country: Bosnia and Herzegovina International Series: 2006, 2007, 2010 to 2012: Reference period: April.; 2008, 2009: Reference period: May.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15-24.; 2006 to 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployed in male youth population ratio , Country: Bosnia and Herzegovina International Series: 2006, 2007, 2010 to 2012: Reference period: April.; 2008, 2009: Reference period: May.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15-24.; 2006 to 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployed in female youth population , Country: Bosnia and Herzegovina International Series: 2006, 2007, 2010 to 2012: Reference period: April.; 2008, 2009: Reference period: May.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15-24.; 2006 to 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; Indicator: Unemployment rate , Country: Bosnia and Herzegovina National Series Reference: 2000 to 2010: MDG progress report 2010; 2011 to 2012: MDG Report 2013; Source in Reference: 2000 to 2011: NSO; 2012: NSO (BHAS); Primary Source in Reference: 2000: Living in BiH - Wave 4 2004; 2007 to 2011: LFS; Indicator: Male unemployment rate , Country: Bosnia and Herzegovina National Series Reference: 2012: MDG Report 2013; Source in Reference: 2012: NSO (BHAS); Indicator: Female unemployment rate , Country: Bosnia and Herzegovina National Series Reference: 2000 to 2013: MDG Report 2013; Definition: 2000 to 2009: Registered; 2013: Registered; Source in Reference: 2000 to 2013: NSO (BHAS); Indicator: Long-term unemployment rate , Country: Bosnia and Herzegovina National Series Reference: 2009: MDG progress report 2010; Source in Reference: 2009: NSO; Primary Source in Reference: 2009: LFS; Indicator: Growth rate of GDP per person employed (%) , Country: Bulgaria International Series: 1993 to 1996: Reference period: September.; 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1993 to 2012: Coverage: Total.; 1993 to 1996: Coverage limitation: Excluding conscripts.; 1993 to 1999: Type of source: Household or labour force survey.; 1991, 1992: Type of source: Official estimates.; 1991 to 2012: Age: 15+.; 1991, 1992: Coverage: Civilian.; 1991: Remarks: State and cooperative sector.; Indicator: Employment-to-population ratio, total (%) , Country: Bulgaria National Series Reference: 2001 to 2007: MDG report 2010; Definition: 2001 to 2007: Age 15-64; International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997 to 1999: Type of source: Household or labour force survey.; 1997 to 2012: Age: 15+.; Indicator: Male employment-to-population ratio (%) , Country: Bulgaria International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997 to 1999: Type of source: Household or labour force survey.; 1997 to 2012: Age: 15+.; Indicator: Female employment-to-population ratio (%) , Country: Bulgaria International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997 to 1999: Type of source: Household or labour force survey.; 1997 to 2012: Age: 15+.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Bulgaria International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15+.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Bulgaria International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15+.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Bulgaria International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15+.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Bulgaria National Series Reference: 2001 to 2007: MDG report 2010; International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Bulgaria International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Bulgaria International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Bulgaria International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Bulgaria International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Bulgaria International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Youth unemployed in total unemployed (%) , Country: Bulgaria International Series: 1997 to 1999: Reference period: June.; 1993 to 1996: Reference period: September.; 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1993 to 2012: Coverage: Total.; 1993 to 1999: Coverage limitation: Excluding conscripts.; 1993 to 2012: Age: 15-24.; 1993 to 1999: Type of source: Household or labour force survey.; Indicator: Male youth unemployed in total unemployed (%) , Country: Bulgaria International Series: 1997 to 1999: Reference period: June.; 1993 to 1996: Reference period: September.; 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1993 to 2012: Coverage: Total.; 1993 to 1999: Coverage limitation: Excluding conscripts.; 1993 to 2012: Age: 15-24.; 1993 to 1999: Type of source: Household or labour force survey.; Indicator: Female youth unemployed in total unemployed (%) , Country: Bulgaria International Series: 1997 to 1999: Reference period: June.; 1993 to 1996: Reference period: September.; 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1993 to 2012: Coverage: Total.; 1993 to 1999: Coverage limitation: Excluding conscripts.; 1993 to 2012: Age: 15-24.; 1993 to 1999: Type of source: Household or labour force survey.; Indicator: Youth unemployed in youth population, total , Country: Bulgaria International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Male youth unemployed in male youth population ratio , Country: Bulgaria International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Female youth unemployed in female youth population , Country: Bulgaria International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Unemployment rate , Country: Bulgaria National Series Reference: 2001 to 2007: MDG report 2010; Source in Reference: 2001 to 2007: NSO / EuroStat ; Indicator: Female unemployment rate , Country: Bulgaria National Series Reference: 2002 to 2007: MDG report 2010; Indicator: Long-term unemployment rate , Country: Bulgaria National Series Reference: 2001 to 2007: MDG report 2010; Source in Reference: 2001 to 2007: NSO / EuroStat ; Indicator: Growth rate of GDP per person employed (%) , Country: Croatia International Series: 2001: Reference period: March.; 1997: Reference period: June.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997 to 2000: Coverage limitation: Excluding conscripts.; 2001: Type of source: Population census.; 1997 to 2000: Type of source: Household or labour force survey.; 1997 to 2012: Age: 15+.; Indicator: Employment-to-population ratio, total (%) , Country: Croatia International Series: 2001: Reference period: March.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1998, 2001 to 2012: Coverage: Total.; 1998: Coverage limitation: Excluding conscripts.; 2001: Type of source: Population census.; 1998: Type of source: Household or labour force survey.; 1998, 2001 to 2012: Age: 15+.; Indicator: Male employment-to-population ratio (%) , Country: Croatia International Series: 2001: Reference period: March.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1998, 2001 to 2012: Coverage: Total.; 1998: Coverage limitation: Excluding conscripts.; 2001: Type of source: Population census.; 1998: Type of source: Household or labour force survey.; 1998, 2001 to 2012: Age: 15+.; Indicator: Female employment-to-population ratio (%) , Country: Croatia International Series: 2001: Reference period: March.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1998, 2001 to 2012: Coverage: Total.; 1998: Coverage limitation: Excluding conscripts.; 2001: Type of source: Population census.; 1998: Type of source: Household or labour force survey.; 1998, 2001 to 2012: Age: 15+.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Croatia International Series: 1997: Reference period: June.; 1996: Reference period: November.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996 to 2001: Coverage limitation: Excluding conscripts.; 1996 to 2001: Type of source: Household or labour force survey.; 1996 to 2012: Age: 15+.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Croatia International Series: 1997: Reference period: June.; 1996: Reference period: November.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996 to 2001: Coverage limitation: Excluding conscripts.; 1996 to 2001: Type of source: Household or labour force survey.; 1996 to 2012: Age: 15+.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Croatia International Series: 1997: Reference period: June.; 1996: Reference period: November.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996 to 2001: Coverage limitation: Excluding conscripts.; 1996 to 2001: Type of source: Household or labour force survey.; 1996 to 2012: Age: 15+.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Croatia National Series Reference: 2002 to 2005: MDG Progress Report 2005; International Series: 1991, 2001: Reference period: March.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1991, 1998, 2001 to 2012: Coverage: Total.; 1998: Coverage limitation: Excluding conscripts.; 1991, 1998, 2001 to 2012: Age: 15-24.; 1991, 2001: Type of source: Population census.; 1998: Type of source: Household or labour force survey.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Croatia International Series: 1991, 2001: Reference period: March.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1991, 1998, 2001 to 2012: Coverage: Total.; 1998: Coverage limitation: Excluding conscripts.; 1991, 1998, 2001 to 2012: Age: 15-24.; 1991, 2001: Type of source: Population census.; 1998: Type of source: Household or labour force survey.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Croatia International Series: 1991, 2001: Reference period: March.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1991, 1998, 2001 to 2012: Coverage: Total.; 1998: Coverage limitation: Excluding conscripts.; 1991, 1998, 2001 to 2012: Age: 15-24.; 1991, 2001: Type of source: Population census.; 1998: Type of source: Household or labour force survey.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Croatia International Series: 1991, 2001: Reference period: March.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1991, 1998, 2001 to 2012: Coverage: Total.; 1998: Coverage limitation: Excluding conscripts.; 1991, 1998, 2001 to 2012: Age: 15-24.; 1991, 2001: Type of source: Population census.; 1998: Type of source: Household or labour force survey.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Croatia International Series: 1991, 2001: Reference period: March.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1991, 1998, 2001 to 2012: Coverage: Total.; 1998: Coverage limitation: Excluding conscripts.; 1991, 1998, 2001 to 2012: Age: 15-24.; 1991, 2001: Type of source: Population census.; 1998: Type of source: Household or labour force survey.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Croatia International Series: 1991, 2001: Reference period: March.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1991, 1998, 2001 to 2012: Coverage: Total.; 1998: Coverage limitation: Excluding conscripts.; 1991, 1998, 2001 to 2012: Age: 15-24.; 1991, 2001: Type of source: Population census.; 1998: Type of source: Household or labour force survey.; Indicator: Youth unemployed in total unemployed (%) , Country: Croatia International Series: 1991, 2001: Reference period: March.; 1997: Reference period: June.; 1996: Reference period: November.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1991, 1996 to 2012: Coverage: Total.; 1996 to 2000: Coverage limitation: Excluding conscripts.; 1991, 1996 to 2012: Age: 15-24.; 1991, 2001: Type of source: Population census.; 1996 to 2000: Type of source: Household or labour force survey.; Indicator: Male youth unemployed in total unemployed (%) , Country: Croatia International Series: 1991, 2001: Reference period: March.; 1997: Reference period: June.; 1996: Reference period: November.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1991, 1996 to 2012: Coverage: Total.; 1996 to 2000: Coverage limitation: Excluding conscripts.; 1991, 1996 to 2012: Age: 15-24.; 1991, 2001: Type of source: Population census.; 1996 to 2000: Type of source: Household or labour force survey.; Indicator: Female youth unemployed in total unemployed (%) , Country: Croatia International Series: 1991, 2001: Reference period: March.; 1997: Reference period: June.; 1996: Reference period: November.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1991, 1996 to 2012: Coverage: Total.; 1996 to 2000: Coverage limitation: Excluding conscripts.; 1991, 1996 to 2012: Age: 15-24.; 1991, 2001: Type of source: Population census.; 1996 to 2000: Type of source: Household or labour force survey.; Indicator: Youth unemployed in youth population, total , Country: Croatia International Series: 1991, 2001: Reference period: March.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1991, 1998, 2001 to 2012: Coverage: Total.; 1998: Coverage limitation: Excluding conscripts.; 1991, 1998, 2001 to 2012: Age: 15-24.; 1991, 2001: Type of source: Population census.; 1998: Type of source: Household or labour force survey.; Indicator: Male youth unemployed in male youth population ratio , Country: Croatia International Series: 1991, 2001: Reference period: March.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1991, 1998, 2001 to 2012: Coverage: Total.; 1998: Coverage limitation: Excluding conscripts.; 1991, 1998, 2001 to 2012: Age: 15-24.; 1991, 2001: Type of source: Population census.; 1998: Type of source: Household or labour force survey.; Indicator: Female youth unemployed in female youth population , Country: Croatia International Series: 1991, 2001: Reference period: March.; 2002 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1991, 1998, 2001 to 2012: Coverage: Total.; 1998: Coverage limitation: Excluding conscripts.; 1991, 1998, 2001 to 2012: Age: 15-24.; 1991, 2001: Type of source: Population census.; 1998: Type of source: Household or labour force survey.; Indicator: Female unemployment rate , Country: Croatia National Series Reference: 2007 to 2009: MDG report 2010; Indicator: Growth rate of GDP per person employed (%) , Country: Cyprus International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 1991 to 1995: Type of source: Official estimates.; 1991 to 1995, 2000 to 2012: Age: 15+.; 1991 to 1995: Coverage: Civilian.; Indicator: Employment-to-population ratio, total (%) , Country: Cyprus International Series: 1999 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1999 to 2012: Coverage: Total.; 1990 to 1992, 1995: Type of source: Official estimates.; 1990 to 1992, 1995, 1999 to 2012: Age: 15+.; 1990 to 1992, 1995: Coverage: Civilian.; Indicator: Male employment-to-population ratio (%) , Country: Cyprus International Series: 1999 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1999 to 2012: Coverage: Total.; 1990 to 1992, 1995: Type of source: Official estimates.; 1990 to 1992, 1995, 1999 to 2012: Age: 15+.; 1990 to 1992, 1995: Coverage: Civilian.; Indicator: Female employment-to-population ratio (%) , Country: Cyprus International Series: 1999 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1999 to 2012: Coverage: Total.; 1990 to 1992, 1995: Type of source: Official estimates.; 1990 to 1992, 1995, 1999 to 2012: Age: 15+.; 1990 to 1992, 1995: Coverage: Civilian.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Cyprus International Series: 1999 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1999 to 2012: Coverage: Total.; 1999 to 2012: Age: 15+.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Cyprus International Series: 1999 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1999 to 2012: Coverage: Total.; 1999 to 2012: Age: 15+.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Cyprus International Series: 1999 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1999 to 2012: Coverage: Total.; 1999 to 2012: Age: 15+.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Cyprus International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Cyprus International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Cyprus International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Cyprus International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Cyprus International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Cyprus International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Youth unemployed in total unemployed (%) , Country: Cyprus International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Male youth unemployed in total unemployed (%) , Country: Cyprus International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Female youth unemployed in total unemployed (%) , Country: Cyprus International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Youth unemployed in youth population, total , Country: Cyprus International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Male youth unemployed in male youth population ratio , Country: Cyprus International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Female youth unemployed in female youth population , Country: Cyprus International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Growth rate of GDP per person employed (%) , Country: Czechia International Series: 1997 to 2012: Reference period: Continuous survey.; 1994 to 2012: Coverage: Total.; 1994 to 1996: Reference period: Average of quarterly estimates.; 1997: Survey limitation: Continuous survey introduced.; 1994 to 2012: Age: 15+.; 1994 to 2012: Type of source: Labour force survey.; Indicator: Employment-to-population ratio, total (%) , Country: Czechia International Series: 1997 to 2012: Reference period: Continuous survey.; 1993 to 2012: Coverage: Total.; 1993 to 1996: Reference period: Average of quarterly estimates.; 1997: Survey limitation: Continuous survey introduced.; 1993 to 2012: Age: 15+.; 1993 to 2012: Type of source: Labour force survey.; Indicator: Male employment-to-population ratio (%) , Country: Czechia International Series: 1997 to 2012: Reference period: Continuous survey.; 1993 to 2012: Coverage: Total.; 1993 to 1996: Reference period: Average of quarterly estimates.; 1997: Survey limitation: Continuous survey introduced.; 1993 to 2012: Age: 15+.; 1993 to 2012: Type of source: Labour force survey.; Indicator: Female employment-to-population ratio (%) , Country: Czechia International Series: 1997 to 2012: Reference period: Continuous survey.; 1993 to 2012: Coverage: Total.; 1993 to 1996: Reference period: Average of quarterly estimates.; 1997: Survey limitation: Continuous survey introduced.; 1993 to 2012: Age: 15+.; 1993 to 2012: Type of source: Labour force survey.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Czechia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1993 to 2012: Coverage: Total.; 1993 to 1996: Type of source: Household or labour force survey.; 1993 to 2012: Age: 15+.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Czechia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1993 to 2012: Coverage: Total.; 1993 to 1996: Type of source: Household or labour force survey.; 1993 to 2012: Age: 15+.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Czechia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1993 to 2012: Coverage: Total.; 1993 to 1996: Type of source: Household or labour force survey.; 1993 to 2012: Age: 15+.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Czechia International Series: 1991: Reference period: March.; 1997 to 2012: Reference period: Continuous survey.; 1991, 1993 to 2012: Coverage: Total.; 1993 to 1996: Reference period: Average of quarterly estimates.; 1997: Survey limitation: Continuous survey introduced.; 1991, 1993 to 2012: Age: 15-24.; 1991: Type of source: Population census.; 1993 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Czechia International Series: 1991: Reference period: March.; 1997 to 2012: Reference period: Continuous survey.; 1991, 1993 to 2012: Coverage: Total.; 1993 to 1996: Reference period: Average of quarterly estimates.; 1997: Survey limitation: Continuous survey introduced.; 1991, 1993 to 2012: Age: 15-24.; 1991: Type of source: Population census.; 1993 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Czechia International Series: 1991: Reference period: March.; 1997 to 2012: Reference period: Continuous survey.; 1991, 1993 to 2012: Coverage: Total.; 1993 to 1996: Reference period: Average of quarterly estimates.; 1997: Survey limitation: Continuous survey introduced.; 1991, 1993 to 2012: Age: 15-24.; 1991: Type of source: Population census.; 1993 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Czechia International Series: 1991: Reference period: March.; 1997 to 2012: Reference period: Continuous survey.; 1991, 1993 to 2012: Coverage: Total.; 1993 to 1996: Reference period: Average of quarterly estimates.; 1997: Survey limitation: Continuous survey introduced.; 1991, 1993 to 2012: Age: 15-24.; 1991: Type of source: Population census.; 1993 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Czechia International Series: 1991: Reference period: March.; 1997 to 2012: Reference period: Continuous survey.; 1991, 1993 to 2012: Coverage: Total.; 1993 to 1996: Reference period: Average of quarterly estimates.; 1997: Survey limitation: Continuous survey introduced.; 1991, 1993 to 2012: Age: 15-24.; 1991: Type of source: Population census.; 1993 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Czechia International Series: 1991: Reference period: March.; 1997 to 2012: Reference period: Continuous survey.; 1991, 1993 to 2012: Coverage: Total.; 1993 to 1996: Reference period: Average of quarterly estimates.; 1997: Survey limitation: Continuous survey introduced.; 1991, 1993 to 2012: Age: 15-24.; 1991: Type of source: Population census.; 1993 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployed in total unemployed (%) , Country: Czechia International Series: 1991: Reference period: March.; 1997 to 2012: Reference period: Continuous survey.; 1991, 1993 to 2012: Coverage: Total.; 1993 to 1996: Reference period: Average of quarterly estimates.; 1997: Survey limitation: Continuous survey introduced.; 1991, 1993 to 2012: Age: 15-24.; 1991: Type of source: Population census.; 1993 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployed in total unemployed (%) , Country: Czechia International Series: 1991: Reference period: March.; 1997 to 2012: Reference period: Continuous survey.; 1991, 1993 to 2012: Coverage: Total.; 1993 to 1996: Reference period: Average of quarterly estimates.; 1997: Survey limitation: Continuous survey introduced.; 1991, 1993 to 2012: Age: 15-24.; 1991: Type of source: Population census.; 1993 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployed in total unemployed (%) , Country: Czechia International Series: 1991: Reference period: March.; 1997 to 2012: Reference period: Continuous survey.; 1991, 1993 to 2012: Coverage: Total.; 1993 to 1996: Reference period: Average of quarterly estimates.; 1997: Survey limitation: Continuous survey introduced.; 1991, 1993 to 2012: Age: 15-24.; 1991: Type of source: Population census.; 1993 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployed in youth population, total , Country: Czechia International Series: 1991: Reference period: March.; 1997 to 2012: Reference period: Continuous survey.; 1991, 1993 to 2012: Coverage: Total.; 1993 to 1996: Reference period: Average of quarterly estimates.; 1997: Survey limitation: Continuous survey introduced.; 1991, 1993 to 2012: Age: 15-24.; 1991: Type of source: Population census.; 1993 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployed in male youth population ratio , Country: Czechia International Series: 1991: Reference period: March.; 1997 to 2012: Reference period: Continuous survey.; 1991, 1993 to 2012: Coverage: Total.; 1993 to 1996: Reference period: Average of quarterly estimates.; 1997: Survey limitation: Continuous survey introduced.; 1991, 1993 to 2012: Age: 15-24.; 1991: Type of source: Population census.; 1993 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployed in female youth population , Country: Czechia International Series: 1991: Reference period: March.; 1997 to 2012: Reference period: Continuous survey.; 1991, 1993 to 2012: Coverage: Total.; 1993 to 1996: Reference period: Average of quarterly estimates.; 1997: Survey limitation: Continuous survey introduced.; 1991, 1993 to 2012: Age: 15-24.; 1991: Type of source: Population census.; 1993 to 2012: Type of source: Labour force survey.; Indicator: Unemployment rate , Country: Czechia National Series Reference: 1993 to 2002: MDG report 2004; Source in Reference: 1993 to 2002: NSO; Primary Source in Reference: 1993 to 2002: LFS; Indicator: Female unemployment rate , Country: Czechia National Series Reference: 2001: MDG report 2004; Source in Reference: 2001: NSO; Indicator: Long-term unemployment rate , Country: Czechia National Series Reference: 1994 to 2002: MDG report 2004; Source in Reference: 1994 to 2002: NSO; Primary Source in Reference: 1994 to 2002: LFS; Indicator: Growth rate of GDP per person employed (%) , Country: Estonia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1994 to 2012: Coverage: Total.; 1994 to 1996: Coverage limitation: Excluding conscripts.; 1997 to 2012: Age: 15-74.; 1994 to 1996: Age: 15-69.; 1994 to 1996: Type of source: Household or labour force survey.; Indicator: Employment-to-population ratio, total (%) , Country: Estonia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1995, 1997 to 2012: Coverage: Total.; 1995: Coverage limitation: Excluding conscripts.; 1997 to 2012: Age: 15-74.; 1995: Age: 15-69.; 1995: Type of source: Household or labour force survey.; Indicator: Male employment-to-population ratio (%) , Country: Estonia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1995, 1997 to 2012: Coverage: Total.; 1995: Coverage limitation: Excluding conscripts.; 1997 to 2012: Age: 15-74.; 1995: Age: 15-69.; 1995: Type of source: Household or labour force survey.; Indicator: Female employment-to-population ratio (%) , Country: Estonia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1995, 1997 to 2012: Coverage: Total.; 1995: Coverage limitation: Excluding conscripts.; 1997 to 2012: Age: 15-74.; 1995: Age: 15-69.; 1995: Type of source: Household or labour force survey.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Estonia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1990 to 2012: Coverage: Total.; 1990 to 1996: Coverage limitation: Excluding conscripts.; 1997 to 2012: Age: 15-74.; 1990 to 1996: Age: 15-69.; 1990 to 1996: Type of source: Household or labour force survey.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Estonia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1990 to 2012: Coverage: Total.; 1990 to 1996: Coverage limitation: Excluding conscripts.; 1997 to 2012: Age: 15-74.; 1990 to 1996: Age: 15-69.; 1990 to 1996: Type of source: Household or labour force survey.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Estonia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1990 to 2012: Coverage: Total.; 1990 to 1996: Coverage limitation: Excluding conscripts.; 1997 to 2012: Age: 15-74.; 1990 to 1996: Age: 15-69.; 1990 to 1996: Type of source: Household or labour force survey.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Estonia International Series: 1995: Reference period: First quarter.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1995, 1997 to 2012: Coverage: Total.; 1995: Coverage limitation: Excluding conscripts.; 1995, 1997 to 2012: Age: 15-24.; 1995: Type of source: Household or labour force survey.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Estonia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997 to 2012: Age: 15-24.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Estonia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997 to 2012: Age: 15-24.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Estonia International Series: 1995: Reference period: First quarter.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1995, 1997 to 2012: Coverage: Total.; 1995: Coverage limitation: Excluding conscripts.; 1995, 1997 to 2012: Age: 15-24.; 1995: Type of source: Household or labour force survey.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Estonia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997 to 2012: Age: 15-24.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Estonia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997 to 2012: Age: 15-24.; Indicator: Youth unemployed in total unemployed (%) , Country: Estonia International Series: 1995: Reference period: First quarter.; 1993, 1994, 1996: Reference period: Second quarter.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1993 to 2012: Coverage: Total.; 1993 to 1996: Coverage limitation: Excluding conscripts.; 1993 to 2012: Age: 15-24.; 1993 to 1996: Type of source: Household or labour force survey.; Indicator: Male youth unemployed in total unemployed (%) , Country: Estonia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997 to 2012: Age: 15-24.; Indicator: Female youth unemployed in total unemployed (%) , Country: Estonia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997 to 2012: Age: 15-24.; Indicator: Youth unemployed in youth population, total , Country: Estonia International Series: 1995: Reference period: First quarter.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1995, 1997 to 2012: Coverage: Total.; 1995: Coverage limitation: Excluding conscripts.; 1995, 1997 to 2012: Age: 15-24.; 1995: Type of source: Household or labour force survey.; Indicator: Male youth unemployed in male youth population ratio , Country: Estonia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997 to 2012: Age: 15-24.; Indicator: Female youth unemployed in female youth population , Country: Estonia International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997 to 2012: Age: 15-24.; Indicator: Growth rate of GDP per person employed (%) , Country: Georgia International Series: 1999 to 2012: Type of source: Household or labour force survey.; 1999 to 2012: Age: 15+.; 1999 to 2012: Coverage: Civilian.; Indicator: Employment-to-population ratio, total (%) , Country: Georgia National Series Reference: 1999 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1999 to 2010: NSO; Primary Source in Reference: 1999 to 2010: Integrated Household Survey; International Series: 1998 to 2012: Type of source: Household or labour force survey.; 1998 to 2012: Age: 15+.; 1998 to 2012: Coverage: Civilian.; Indicator: Male employment-to-population ratio (%) , Country: Georgia National Series Reference: 1999 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1999 to 2010: NSO; Primary Source in Reference: 1999 to 2010: Integrated Household Survey; International Series: 1998 to 2012: Type of source: Household or labour force survey.; 1998 to 2012: Age: 15+.; 1998 to 2012: Coverage: Civilian.; Indicator: Female employment-to-population ratio (%) , Country: Georgia National Series Reference: 1999 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1999 to 2010: NSO; Primary Source in Reference: 1999 to 2010: Integrated Household Survey; International Series: 1998 to 2012: Type of source: Household or labour force survey.; 1998 to 2012: Age: 15+.; 1998 to 2012: Coverage: Civilian.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Georgia National Series Reference: 1998 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1998 to 2010: NSO; Primary Source in Reference: 1998 to 2010: Integrated Household Survey; International Series: 1998 to 2010: Type of source: Household or labour force survey.; 1998 to 2010: Age: 15+.; 1998 to 2010: Coverage: Civilian.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Georgia National Series Reference: 1998 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1998 to 2010: NSO; Primary Source in Reference: 1998 to 2010: Integrated Household Survey; International Series: 1998 to 2005, 2008 to 2010: Type of source: Household or labour force survey.; 1998 to 2005, 2008 to 2010: Age: 15+.; 1998 to 2005, 2008 to 2010: Coverage: Civilian.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Georgia National Series Reference: 1998 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1998 to 2010: NSO; Primary Source in Reference: 1998 to 2010: Integrated Household Survey; International Series: 1998 to 2005, 2008 to 2010: Type of source: Household or labour force survey.; 1998 to 2005, 2008 to 2010: Age: 15+.; 1998 to 2005, 2008 to 2010: Coverage: Civilian.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Georgia National Series Reference: 1999 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1999 to 2010: NSO; Primary Source in Reference: 1999 to 2010: Integrated Household Survey; International Series: 1999 to 2012: Age: 15-24.; 1999 to 2012: Type of source: Household or labour force survey.; 1999 to 2012: Coverage: Civilian.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Georgia National Series Reference: 1999 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1999 to 2010: NSO; Primary Source in Reference: 1999 to 2010: Integrated Household Survey; International Series: 1999 to 2008: Age: 15-24.; 1999 to 2008: Type of source: Household or labour force survey.; 1999 to 2008: Coverage: Civilian.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Georgia National Series Reference: 1999 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1999 to 2010: NSO; Primary Source in Reference: 1999 to 2010: Integrated Household Survey; International Series: 1999 to 2008: Age: 15-24.; 1999 to 2008: Type of source: Household or labour force survey.; 1999 to 2008: Coverage: Civilian.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Georgia National Series Reference: 1999 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1999 to 2010: NSO; Primary Source in Reference: 1999 to 2010: Integrated Household Survey; International Series: 1999 to 2012: Age: 15-24.; 1999 to 2012: Type of source: Household or labour force survey.; 1999 to 2012: Coverage: Civilian.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Georgia National Series Reference: 1999 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1999 to 2010: NSO; Primary Source in Reference: 1999 to 2010: Integrated Household Survey; International Series: 1999 to 2008: Age: 15-24.; 1999 to 2008: Type of source: Household or labour force survey.; 1999 to 2008: Coverage: Civilian.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Georgia National Series Reference: 1999 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1999 to 2010: NSO; Primary Source in Reference: 1999 to 2010: Integrated Household Survey; International Series: 1999 to 2008: Age: 15-24.; 1999 to 2008: Type of source: Household or labour force survey.; 1999 to 2008: Coverage: Civilian.; Indicator: Youth unemployed in total unemployed (%) , Country: Georgia National Series Reference: 1998 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1998 to 2010: NSO; Primary Source in Reference: 1998 to 2010: Integrated Household Survey; International Series: 1998 to 2012: Age: 15-24.; 1998 to 2012: Type of source: Household or labour force survey.; 1998 to 2012: Coverage: Civilian.; Indicator: Male youth unemployed in total unemployed (%) , Country: Georgia National Series Reference: 1998 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1998 to 2010: NSO; Primary Source in Reference: 1998 to 2010: Integrated Household Survey; International Series: 1998 to 2008: Age: 15-24.; 1998 to 2008: Type of source: Household or labour force survey.; 1998 to 2008: Coverage: Civilian.; Indicator: Female youth unemployed in total unemployed (%) , Country: Georgia National Series Reference: 1998 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1998 to 2010: NSO; Primary Source in Reference: 1998 to 2010: Integrated Household Survey; International Series: 1998 to 2008: Age: 15-24.; 1998 to 2008: Type of source: Household or labour force survey.; 1998 to 2008: Coverage: Civilian.; Indicator: Youth unemployed in youth population, total , Country: Georgia National Series Reference: 1999 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1999 to 2010: NSO; Primary Source in Reference: 1999 to 2010: Integrated Household Survey; International Series: 1999 to 2012: Age: 15-24.; 1999 to 2012: Type of source: Household or labour force survey.; 1999 to 2012: Coverage: Civilian.; Indicator: Male youth unemployed in male youth population ratio , Country: Georgia National Series Reference: 1999 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1999 to 2010: NSO; Primary Source in Reference: 1999 to 2010: Integrated Household Survey; International Series: 1999 to 2006: Age: 15-24.; 1999 to 2006: Type of source: Household or labour force survey.; 1999 to 2006: Coverage: Civilian.; Indicator: Female youth unemployed in female youth population , Country: Georgia National Series Reference: 1999 to 2010: UNECE Questionnaire Sept 2011; Source in Reference: 1999 to 2010: NSO; Primary Source in Reference: 1999 to 2010: Integrated Household Survey; International Series: 1999 to 2006: Age: 15-24.; 1999 to 2006: Type of source: Household or labour force survey.; 1999 to 2006: Coverage: Civilian.; Indicator: Unemployment rate , Country: Georgia National Series Reference: 1997 to 2003: MDG in Georgia 2004; Definition: 1997 to 2003: Official national; Source in Reference: 1997 to 2003: NSO; Indicator: Growth rate of GDP per person employed (%) , Country: Hungary International Series: 2006 to 2012: Reference period: Continuous survey.; 1991 to 2012: Coverage: Total.; 1992 to 2005: Reference period: Average of quarterly estimates.; 1992 to 2012: Age: 15-74.; 2006: Survey limitation: Continuous survey introduced.; 1991: Type of source: Official estimates.; 1991: Age: 15+.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Employment-to-population ratio, total (%) , Country: Hungary International Series: 2006 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 2005: Reference period: Average of quarterly estimates.; 1992 to 2012: Age: 15-74.; 2006: Survey limitation: Continuous survey introduced.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Male employment-to-population ratio (%) , Country: Hungary International Series: 2006 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 2005: Reference period: Average of quarterly estimates.; 1992 to 2012: Age: 15-74.; 2006: Survey limitation: Continuous survey introduced.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Female employment-to-population ratio (%) , Country: Hungary International Series: 2006 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 2005: Reference period: Average of quarterly estimates.; 1992 to 2012: Age: 15-74.; 2006: Survey limitation: Continuous survey introduced.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Hungary International Series: 1996 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1992 to 2012: Coverage: Total.; 1992 to 1995: Coverage limitation: Excluding conscripts.; 1992 to 2012: Age: 15-74.; 1992 to 1995: Type of source: Household or labour force survey.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Hungary International Series: 1996 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1992 to 2012: Coverage: Total.; 1992 to 1995: Coverage limitation: Excluding conscripts.; 1992 to 2012: Age: 15-74.; 1992 to 1995: Type of source: Household or labour force survey.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Hungary International Series: 1996 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1992 to 2012: Coverage: Total.; 1992 to 1995: Coverage limitation: Excluding conscripts.; 1992 to 2012: Age: 15-74.; 1992 to 1995: Type of source: Household or labour force survey.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Hungary International Series: 2006 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 2005: Reference period: Average of quarterly estimates.; 2006: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Hungary International Series: 2006 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 2005: Reference period: Average of quarterly estimates.; 2006: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Hungary International Series: 2006 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 2005: Reference period: Average of quarterly estimates.; 2006: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Hungary International Series: 2006 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 2005: Reference period: Average of quarterly estimates.; 2006: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Hungary International Series: 2006 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 2005: Reference period: Average of quarterly estimates.; 2006: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Hungary International Series: 2006 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 2005: Reference period: Average of quarterly estimates.; 2006: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployed in total unemployed (%) , Country: Hungary International Series: 2006 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 2005: Reference period: Average of quarterly estimates.; 2006: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployed in total unemployed (%) , Country: Hungary International Series: 2006 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 2005: Reference period: Average of quarterly estimates.; 2006: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployed in total unemployed (%) , Country: Hungary International Series: 2006 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 2005: Reference period: Average of quarterly estimates.; 2006: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployed in youth population, total , Country: Hungary International Series: 2006 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 2005: Reference period: Average of quarterly estimates.; 2006: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployed in male youth population ratio , Country: Hungary International Series: 2006 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 2005: Reference period: Average of quarterly estimates.; 2006: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployed in female youth population , Country: Hungary International Series: 2006 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 2005: Reference period: Average of quarterly estimates.; 2006: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Growth rate of GDP per person employed (%) , Country: Kazakhstan National Series Reference: 1999 to 2011: UNECE Questionnaire Sept 2011; Note: 1999 to 2011: National Accounts; Source in Reference: 1999 to 2011: NSO; Primary Source in Reference: 1999 to 2011: LFS; International Series: 1994 to 2000: Coverage: Total.; 2001 to 2008: Type of source: Household or labour force survey.; 1994 to 2000: Type of source: Official estimates.; 1994 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; 2001 to 2012: Coverage: Civilian.; Indicator: Employment-to-population ratio, total (%) , Country: Kazakhstan National Series Reference: 2001 to 2011: UNECE Questionnaire Sept 2011; 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Note: 2011: Data for the 2nd quarter of 2011; Source in Reference: 2001 to 2012: NSO; International Series: 2002 to 2004, 2008: Type of source: Household or labour force survey.; 2002 to 2004, 2008 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; 2002 to 2004, 2008 to 2012: Coverage: Civilian.; Indicator: Male employment-to-population ratio (%) , Country: Kazakhstan National Series Reference: 2001 to 2011: UNECE Questionnaire Sept 2011; 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Note: 2011: Data for the 2nd quarter of 2011; Source in Reference: 2001 to 2012: NSO; International Series: 2002 to 2004, 2008: Type of source: Household or labour force survey.; 2002 to 2004, 2008 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; 2002 to 2004, 2008 to 2012: Coverage: Civilian.; Indicator: Female employment-to-population ratio (%) , Country: Kazakhstan National Series Reference: 2001 to 2011: UNECE Questionnaire Sept 2011; 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Note: 2011: Data for the 2nd quarter of 2011; Source in Reference: 2001 to 2012: NSO; International Series: 2002 to 2004, 2008: Type of source: Household or labour force survey.; 2002 to 2004, 2008 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; 2002 to 2004, 2008 to 2012: Coverage: Civilian.; Indicator: Employed people living below the national poverty line (%) , Country: Kazakhstan National Series Reference: 2001 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Definition: 2001 to 2012: Basic needs based; Source in Reference: 2001 to 2012: NSO; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Kazakhstan National Series Reference: 2001 to 2011: UNECE Questionnaire Sept 2011; Note: 2011: Data for the 2nd quarter of 2011; Source in Reference: 2001 to 2011: NSO; International Series: 2001 to 2008: Type of source: Household or labour force survey.; 2001 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; 2001 to 2012: Coverage: Civilian.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Kazakhstan National Series Reference: 2001 to 2011: UNECE Questionnaire Sept 2011; Note: 2011: Data for the 2nd quarter of 2011; Source in Reference: 2001 to 2011: NSO; International Series: 2001 to 2008: Type of source: Household or labour force survey.; 2001 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; 2001 to 2012: Coverage: Civilian.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Kazakhstan National Series Reference: 2001 to 2011: UNECE Questionnaire Sept 2011; Note: 2011: Data for the 2nd quarter of 2011; Source in Reference: 2001 to 2011: NSO; International Series: 2001 to 2008: Type of source: Household or labour force survey.; 2001 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; 2001 to 2012: Coverage: Civilian.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Kazakhstan National Series Reference: 2001 to 2010: UNECE Questionnaire Sept 2011; 2011 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Source in Reference: 2001 to 2012: NSO; International Series: 2002, 2003: Coverage: Total.; 2002 to 2004, 2008 to 2012: Age: 15-24.; 2002 to 2004, 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; 2004, 2008 to 2012: Coverage: Civilian.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Kazakhstan National Series Reference: 2001 to 2010: UNECE Questionnaire Sept 2011; 2011 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Source in Reference: 2001 to 2012: NSO; International Series: 2002, 2003: Coverage: Total.; 2002 to 2004, 2008 to 2012: Age: 15-24.; 2002 to 2004, 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; 2004, 2008 to 2012: Coverage: Civilian.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Kazakhstan National Series Reference: 2001 to 2010: UNECE Questionnaire Sept 2011; 2011 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Source in Reference: 2001 to 2012: NSO; International Series: 2002, 2003: Coverage: Total.; 2002 to 2004, 2008 to 2012: Age: 15-24.; 2002 to 2004, 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; 2004, 2008 to 2012: Coverage: Civilian.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Kazakhstan National Series Reference: 2001 to 2009: UNECE Questionnaire Sept 2011; 2010 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Source in Reference: 2001 to 2012: NSO; International Series: 2002, 2003: Coverage: Total.; 2002 to 2004, 2008, 2009: Age: 15-24.; 2002 to 2004, 2008: Type of source: Household or labour force survey.; 2009: Type of source: Labour force survey.; 2004, 2008, 2009: Coverage: Civilian.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Kazakhstan National Series Reference: 2001 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Source in Reference: 2001 to 2012: NSO; International Series: 2002, 2003: Coverage: Total.; 2002 to 2004, 2008, 2009: Age: 15-24.; 2002 to 2004, 2008: Type of source: Household or labour force survey.; 2009: Type of source: Labour force survey.; 2004, 2008, 2009: Coverage: Civilian.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Kazakhstan National Series Reference: 2001 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Source in Reference: 2001 to 2012: NSO; International Series: 2002, 2003: Coverage: Total.; 2002 to 2004, 2008, 2009: Age: 15-24.; 2002 to 2004, 2008: Type of source: Household or labour force survey.; 2009: Type of source: Labour force survey.; 2004, 2008, 2009: Coverage: Civilian.; Indicator: Youth unemployed in total unemployed (%) , Country: Kazakhstan National Series Reference: 2001: Poverty assessment in Kazakhstan: current status and prospects for development; 2002 to 2010: UNECE Questionnaire Sept 2011; 2011 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Source in Reference: 2001 to 2012: NSO; International Series: 2001 to 2003: Coverage: Total.; 2001 to 2009: Age: 15-24.; 2001 to 2008: Type of source: Household or labour force survey.; 2009: Type of source: Labour force survey.; 2004 to 2009: Coverage: Civilian.; Indicator: Male youth unemployed in total unemployed (%) , Country: Kazakhstan National Series Reference: 2001: Poverty assessment in Kazakhstan: current status and prospects for development; 2002 to 2010: UNECE Questionnaire Sept 2011; 2011 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Source in Reference: 2001 to 2012: NSO; International Series: 2001 to 2003: Coverage: Total.; 2001 to 2009: Age: 15-24.; 2001 to 2008: Type of source: Household or labour force survey.; 2009: Type of source: Labour force survey.; 2004 to 2009: Coverage: Civilian.; Indicator: Female youth unemployed in total unemployed (%) , Country: Kazakhstan National Series Reference: 2001: Poverty assessment in Kazakhstan: current status and prospects for development; 2002 to 2010: UNECE Questionnaire Sept 2011; 2011 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Source in Reference: 2001 to 2012: NSO; International Series: 2001 to 2003: Coverage: Total.; 2001 to 2009: Age: 15-24.; 2001 to 2008: Type of source: Household or labour force survey.; 2009: Type of source: Labour force survey.; 2004 to 2009: Coverage: Civilian.; Indicator: Youth unemployed in youth population, total , Country: Kazakhstan National Series Reference: 2001 to 2010: UNECE Questionnaire Sept 2011; 2011 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Source in Reference: 2001 to 2012: NSO; International Series: 2002, 2003: Coverage: Total.; 2002 to 2004, 2008: Age: 15-24.; 2002 to 2004, 2008: Type of source: Household or labour force survey.; 2004, 2008: Coverage: Civilian.; Indicator: Male youth unemployed in male youth population ratio , Country: Kazakhstan National Series Reference: 2001 to 2010: UNECE Questionnaire Sept 2011; 2011 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Source in Reference: 2001 to 2012: NSO; International Series: 2002, 2003: Coverage: Total.; 2002 to 2004, 2008: Age: 15-24.; 2002 to 2004, 2008: Type of source: Household or labour force survey.; 2004, 2008: Coverage: Civilian.; Indicator: Female youth unemployed in female youth population , Country: Kazakhstan National Series Reference: 2001 to 2010: UNECE Questionnaire Sept 2011; 2011 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Source in Reference: 2001 to 2012: NSO; International Series: 2002, 2003: Coverage: Total.; 2002 to 2004, 2008: Age: 15-24.; 2002 to 2004, 2008: Type of source: Household or labour force survey.; 2004, 2008: Coverage: Civilian.; Indicator: Unemployment rate , Country: Kazakhstan National Series Reference: 1997 to 2001: MDG in Kazakhstan 2002; 2002: Poverty assessment in Kazakhstan: current status and prospects for development; 2003 to 2008: MDG Report 2010; 2009 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Source in Reference: 1997 to 2012: NSO; Indicator: Male unemployment rate , Country: Kazakhstan National Series Reference: 2001 to 2002: Poverty assessment in Kazakhstan: current status and prospects for development; 2003 to 2008: MDG Report 2010; 2009 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Source in Reference: 2001 to 2012: NSO; Indicator: Female unemployment rate , Country: Kazakhstan National Series Reference: 2001 to 2002: Poverty assessment in Kazakhstan: current status and prospects for development; 2003 to 2008: MDG Report 2010; 2009 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Source in Reference: 2001 to 2012: NSO; Indicator: Growth rate of GDP per person employed (%) , Country: Kyrgyzstan National Series Reference: 1991 to 2012: NSO MDG database as on 2014-07-08; International Series: 2002 to 2008: Reference period: November.; 1991 to 2008: Coverage: Total.; 2002 to 2008: Type of source: Household or labour force survey.; 1991 to 2001: Type of source: Official estimates.; 1991 to 2008: Age: 15+.; Indicator: Employment-to-population ratio, total (%) , Country: Kyrgyzstan National Series Reference: 1990 to 2009: NSO MDG database as on 2014-07-08; 2010: UNECE Questionnaire Sept 2011; 2011 to 2012: NSO MDG database as on 2014-07-08; Source in Reference: 2002 to 2010: NSO; Primary Source in Reference: 2002 to 2010: Integrated Household Survey; International Series: 2002, 2004, 2006: Reference period: November.; 2002, 2004, 2006: Coverage: Total.; 2002, 2004, 2006: Type of source: Household or labour force survey.; 2002, 2004, 2006: Age: 15+.; Indicator: Male employment-to-population ratio (%) , Country: Kyrgyzstan National Series Reference: 1996 to 2001: NSO MDG database as on 2014-07-08; 2002 to 2010: UNECE Questionnaire Sept 2011; 2011 to 2012: NSO MDG database as on 2014-07-08; Source in Reference: 2002 to 2010: NSO; Primary Source in Reference: 2002 to 2010: Integrated Household Survey; International Series: 2002, 2004, 2006: Reference period: November.; 2002, 2004, 2006: Coverage: Total.; 2002, 2004, 2006: Type of source: Household or labour force survey.; 2002, 2004, 2006: Age: 15+.; Indicator: Female employment-to-population ratio (%) , Country: Kyrgyzstan National Series Reference: 1996 to 2001: NSO MDG database as on 2014-07-08; 2002 to 2010: UNECE Questionnaire Sept 2011; 2011 to 2012: NSO MDG database as on 2014-07-08; Source in Reference: 2002 to 2010: NSO; Primary Source in Reference: 2002 to 2010: Integrated Household Survey; International Series: 2002, 2004, 2006: Reference period: November.; 2002, 2004, 2006: Coverage: Total.; 2002, 2004, 2006: Type of source: Household or labour force survey.; 2002, 2004, 2006: Age: 15+.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Kyrgyzstan National Series Reference: 2002 to 2012: NSO MDG database as on 2014-07-08; International Series: 2002 to 2006: Reference period: November.; 2002 to 2006: Coverage: Total.; 2002 to 2006: Type of source: Household or labour force survey.; 2002 to 2006: Age: 15+.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Kyrgyzstan National Series Reference: 2002 to 2012: NSO MDG database as on 2014-07-08; International Series: 2002 to 2006: Reference period: November.; 2002 to 2006: Coverage: Total.; 2002 to 2006: Type of source: Household or labour force survey.; 2002 to 2006: Age: 15+.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Kyrgyzstan National Series Reference: 2002 to 2012: NSO MDG database as on 2014-07-08; International Series: 2002 to 2006: Reference period: November.; 2002 to 2006: Coverage: Total.; 2002 to 2006: Type of source: Household or labour force survey.; 2002 to 2006: Age: 15+.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Kyrgyzstan National Series Reference: 2002 to 2012: NSO MDG database as on 2014-07-08; Source in Reference: 2002 to 2009: NSO; Primary Source in Reference: 2002 to 2009: Integrated Household Survey; International Series: 2002, 2004, 2005: Reference period: November.; 2002, 2004 to 2006: Coverage: Total.; 2002, 2004 to 2006: Age: 15-24.; 2002, 2004 to 2006: Type of source: Household or labour force survey.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Kyrgyzstan National Series Reference: 2002 to 2010: UNECE Questionnaire Sept 2011; 2011 to 2012: NSO MDG database as on 2014-07-08; Source in Reference: 2002 to 2010: NSO; Primary Source in Reference: 2003 to 2010: Integrated Household Survey; International Series: 2002, 2004, 2005: Reference period: November.; 2002, 2004 to 2006: Coverage: Total.; 2002, 2004 to 2006: Age: 15-24.; 2002, 2004 to 2006: Type of source: Household or labour force survey.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Kyrgyzstan National Series Reference: 2002 to 2010: UNECE Questionnaire Sept 2011; 2011 to 2012: NSO MDG database as on 2014-07-08; Source in Reference: 2002 to 2010: NSO; Primary Source in Reference: 2003 to 2010: Integrated Household Survey; International Series: 2002, 2004, 2005: Reference period: November.; 2002, 2004 to 2006: Coverage: Total.; 2002, 2004 to 2006: Age: 15-24.; 2002, 2004 to 2006: Type of source: Household or labour force survey.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Kyrgyzstan National Series Reference: 2002 to 2012: NSO MDG database as on 2014-07-08; International Series: 2002, 2004, 2005: Reference period: November.; 2002, 2004 to 2006: Coverage: Total.; 2002, 2004 to 2006: Age: 15-24.; 2002, 2004 to 2006: Type of source: Household or labour force survey.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Kyrgyzstan National Series Reference: 2002 to 2012: NSO MDG database as on 2014-07-08; International Series: 2002, 2004, 2005: Reference period: November.; 2002, 2004 to 2006: Coverage: Total.; 2002, 2004 to 2006: Age: 15-24.; 2002, 2004 to 2006: Type of source: Household or labour force survey.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Kyrgyzstan National Series Reference: 2002 to 2012: NSO MDG database as on 2014-07-08; International Series: 2002, 2004, 2005: Reference period: November.; 2002, 2004 to 2006: Coverage: Total.; 2002, 2004 to 2006: Age: 15-24.; 2002, 2004 to 2006: Type of source: Household or labour force survey.; Indicator: Youth unemployed in total unemployed (%) , Country: Kyrgyzstan National Series Reference: 2002 to 2012: NSO MDG database as on 2014-07-08; International Series: 2002 to 2005: Reference period: November.; 2002 to 2006: Coverage: Total.; 2002 to 2006: Age: 15-24.; 2002 to 2006: Type of source: Household or labour force survey.; Indicator: Male youth unemployed in total unemployed (%) , Country: Kyrgyzstan National Series Reference: 2002 to 2012: NSO MDG database as on 2014-07-08; International Series: 2002 to 2005: Reference period: November.; 2002 to 2006: Coverage: Total.; 2002 to 2006: Age: 15-24.; 2002 to 2006: Type of source: Household or labour force survey.; Indicator: Female youth unemployed in total unemployed (%) , Country: Kyrgyzstan National Series Reference: 2002 to 2012: NSO MDG database as on 2014-07-08; International Series: 2002 to 2005: Reference period: November.; 2002 to 2006: Coverage: Total.; 2002 to 2006: Age: 15-24.; 2002 to 2006: Type of source: Household or labour force survey.; Indicator: Youth unemployed in youth population, total , Country: Kyrgyzstan National Series Reference: 2002 to 2012: NSO MDG database as on 2014-07-08; International Series: 2002, 2004: Reference period: November.; 2002, 2004, 2006: Coverage: Total.; 2002, 2004, 2006: Age: 15-24.; 2002, 2004, 2006: Type of source: Household or labour force survey.; Indicator: Male youth unemployed in male youth population ratio , Country: Kyrgyzstan National Series Reference: 2002 to 2012: NSO MDG database as on 2014-07-08; International Series: 2002, 2004: Reference period: November.; 2002, 2004, 2006: Coverage: Total.; 2002, 2004, 2006: Age: 15-24.; 2002, 2004, 2006: Type of source: Household or labour force survey.; Indicator: Female youth unemployed in female youth population , Country: Kyrgyzstan National Series Reference: 2002 to 2012: NSO MDG database as on 2014-07-08; International Series: 2002, 2004: Reference period: November.; 2002, 2004, 2006: Coverage: Total.; 2002, 2004, 2006: Age: 15-24.; 2002, 2004, 2006: Type of source: Household or labour force survey.; Indicator: Unemployment rate , Country: Kyrgyzstan National Series Reference: 1992 to 2012: NSO MDG database as on 2014-07-08; Definition: 1992 to 1997: Registered; 2010 to 2012: Registered; Source in Reference: 1998 to 2009: NSO; Indicator: Male unemployment rate , Country: Kyrgyzstan National Series Reference: 1996 to 2012: NSO MDG database as on 2014-07-08; Definition: 1996 to 1997: Registered; 2010 to 2012: Registered; Source in Reference: 1998 to 2009: NSO; Indicator: Female unemployment rate , Country: Kyrgyzstan National Series Reference: 1996 to 2012: NSO MDG database as on 2014-07-08; Definition: 1996 to 1997: Registered; 2010 to 2012: Registered; Source in Reference: 1998 to 2009: NSO; Indicator: Growth rate of GDP per person employed (%) , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-74.; 1997: Type of source: Household or labour force survey.; 1997: Age: 15+.; Indicator: Employment-to-population ratio, total (%) , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-74.; 1996, 1997: Type of source: Household or labour force survey.; 1996, 1997: Age: 15+.; Indicator: Male employment-to-population ratio (%) , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-74.; 1996, 1997: Type of source: Household or labour force survey.; 1996, 1997: Age: 15+.; Indicator: Female employment-to-population ratio (%) , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-74.; 1996, 1997: Type of source: Household or labour force survey.; 1996, 1997: Age: 15+.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-74.; 1996, 1997: Type of source: Household or labour force survey.; 1996, 1997: Age: 15+.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-74.; 1996, 1997: Type of source: Household or labour force survey.; 1996, 1997: Age: 15+.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-74.; 1996, 1997: Type of source: Household or labour force survey.; 1996, 1997: Age: 15+.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1996 to 2012: Age: 15-24.; 1996, 1997: Type of source: Household or labour force survey.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1996 to 2012: Age: 15-24.; 1996, 1997: Type of source: Household or labour force survey.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1996 to 2012: Age: 15-24.; 1996, 1997: Type of source: Household or labour force survey.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1996 to 2012: Age: 15-24.; 1996, 1997: Type of source: Household or labour force survey.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1996 to 2012: Age: 15-24.; 1996, 1997: Type of source: Household or labour force survey.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1996 to 2012: Age: 15-24.; 1996, 1997: Type of source: Household or labour force survey.; Indicator: Youth unemployed in total unemployed (%) , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1996 to 2012: Age: 15-24.; 1996, 1997: Type of source: Household or labour force survey.; Indicator: Male youth unemployed in total unemployed (%) , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1996 to 2012: Age: 15-24.; 1996, 1997: Type of source: Household or labour force survey.; Indicator: Female youth unemployed in total unemployed (%) , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1996 to 2012: Age: 15-24.; 1996, 1997: Type of source: Household or labour force survey.; Indicator: Youth unemployed in youth population, total , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1996 to 2012: Age: 15-24.; 1996, 1997: Type of source: Household or labour force survey.; Indicator: Male youth unemployed in male youth population ratio , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1996 to 2012: Age: 15-24.; 1996, 1997: Type of source: Household or labour force survey.; Indicator: Female youth unemployed in female youth population , Country: Latvia International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1996 to 2012: Age: 15-24.; 1996, 1997: Type of source: Household or labour force survey.; Indicator: Growth rate of GDP per person employed (%) , Country: Lithuania International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1995 to 2012: Coverage: Total.; 1995 to 1997: Coverage limitation: Excluding conscripts.; 1995 to 1997: Type of source: Household or labour force survey.; 1998 to 2012: Age: 15+.; 1995 to 1997: Age: 14+.; Indicator: Employment-to-population ratio, total (%) , Country: Lithuania National Series Reference: 1997 to 2001: MDG Assessment 2002; Primary Source in Reference: 1997 to 2001: LFS; International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1996 to 2012: Coverage: Total.; 1996, 1997: Coverage limitation: Excluding conscripts.; 1996, 1997: Type of source: Household or labour force survey.; 1998 to 2012: Age: 15+.; 1996, 1997: Age: 14+.; Indicator: Male employment-to-population ratio (%) , Country: Lithuania National Series Reference: 1997 to 2001: MDG Assessment 2002; Primary Source in Reference: 1997 to 2001: LFS; International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997: Coverage limitation: Excluding conscripts.; 1997: Type of source: Household or labour force survey.; 1998 to 2012: Age: 15+.; 1997: Age: 14+.; Indicator: Female employment-to-population ratio (%) , Country: Lithuania National Series Reference: 1997 to 2001: MDG Assessment 2002; Primary Source in Reference: 1997 to 2001: LFS; International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997: Coverage limitation: Excluding conscripts.; 1997: Type of source: Household or labour force survey.; 1998 to 2012: Age: 15+.; 1997: Age: 14+.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Lithuania International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1998 to 2012: Coverage: Total.; 1998 to 2012: Age: 15+.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Lithuania International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1998 to 2012: Coverage: Total.; 1998 to 2012: Age: 15+.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Lithuania International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1998 to 2012: Coverage: Total.; 1998 to 2012: Age: 15+.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Lithuania National Series Reference: 1997 to 2001: MDG Assessment 2002; Primary Source in Reference: 1997 to 2001: LFS; International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-24.; 1997: Age: 14-24.; 1997: Type of source: Household or labour force survey.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Lithuania National Series Reference: 1997 to 2001: MDG Assessment 2002; Primary Source in Reference: 1997 to 2001: LFS; International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-24.; 1997: Age: 14-24.; 1997: Type of source: Household or labour force survey.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Lithuania National Series Reference: 1997 to 2001: MDG Assessment 2002; Primary Source in Reference: 1997 to 2001: LFS; International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-24.; 2006: Remarks: Female calculated as the residual of total and male.; 1997: Age: 14-24.; 1997: Type of source: Household or labour force survey.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Lithuania International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-24.; 1997: Age: 14-24.; 1997: Type of source: Household or labour force survey.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Lithuania International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-24.; 2006: Remarks: Female calculated as the residual of total and male.; 1997: Age: 14-24.; 1997: Type of source: Household or labour force survey.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Lithuania International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-24.; 1997: Age: 14-24.; 1997: Type of source: Household or labour force survey.; Indicator: Youth unemployed in total unemployed (%) , Country: Lithuania International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-24.; 1997: Age: 14-24.; 1997: Type of source: Household or labour force survey.; Indicator: Male youth unemployed in total unemployed (%) , Country: Lithuania International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-24.; 2006: Remarks: Female calculated as the residual of total and male.; 1997: Age: 14-24.; 1997: Type of source: Household or labour force survey.; Indicator: Female youth unemployed in total unemployed (%) , Country: Lithuania International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-24.; 1997: Age: 14-24.; 1997: Type of source: Household or labour force survey.; Indicator: Youth unemployed in youth population, total , Country: Lithuania International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-24.; 1997: Age: 14-24.; 1997: Type of source: Household or labour force survey.; Indicator: Male youth unemployed in male youth population ratio , Country: Lithuania International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-24.; 2006: Remarks: Female calculated as the residual of total and male.; 1997: Age: 14-24.; 1997: Type of source: Household or labour force survey.; Indicator: Female youth unemployed in female youth population , Country: Lithuania International Series: 1998 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1997 to 2012: Coverage: Total.; 1997: Coverage limitation: Excluding conscripts.; 1998 to 2012: Age: 15-24.; 1997: Age: 14-24.; 1997: Type of source: Household or labour force survey.; Indicator: Unemployment rate , Country: Lithuania National Series Reference: 1997 to 2001: MDG Assessment 2002; Primary Source in Reference: 1997 to 2001: LFS; Indicator: Male unemployment rate , Country: Lithuania National Series Reference: 1997 to 2001: MDG Assessment 2002; Primary Source in Reference: 1997 to 2001: LFS; Indicator: Female unemployment rate , Country: Lithuania National Series Reference: 1997 to 2001: MDG Assessment 2002; Primary Source in Reference: 1997 to 2001: LFS; Indicator: Growth rate of GDP per person employed (%) , Country: Malta International Series: 2001 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2001 to 2012: Coverage: Total.; 2001 to 2012: Age: 15+.; Indicator: Employment-to-population ratio, total (%) , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15+.; Indicator: Male employment-to-population ratio (%) , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15+.; Indicator: Female employment-to-population ratio (%) , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15+.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15+.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15+.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15+.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Youth unemployed in total unemployed (%) , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Male youth unemployed in total unemployed (%) , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Female youth unemployed in total unemployed (%) , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Youth unemployed in youth population, total , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Male youth unemployed in male youth population ratio , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Female youth unemployed in female youth population , Country: Malta International Series: 2000 to 2012: Type of source: European Labour Force Survey (Eurostat).; 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; Indicator: Growth rate of GDP per person employed (%) , Country: Moldova, Republic of International Series: 1999 to 2012: Coverage: Total.; 1991 to 1998: Type of source: Official estimates.; 1991 to 2012: Age: 15+.; 1999 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 2000 to 2005, 2007 to 2012: Remarks: Calculated using labour force and inactive population.; 1999 to 2012: Type of source: Labour force survey.; 1991 to 1998: Coverage: Civilian.; 2006: Remarks: Methodology revised. Population calculated using labour force and inactive population.; Indicator: Employment-to-population ratio, total (%) , Country: Moldova, Republic of National Series Reference: 2001 to 2011: UNECE Questionnaire Sept 2011; Source in Reference: 2001 to 2011: NSO; Primary Source in Reference: 2001 to 2011: LFS; International Series: 2000 to 2012: Coverage: Total.; 2006: Remarks: Methodology revised.; 2000 to 2012: Age: 15+.; 2000 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 2000 to 2012: Type of source: Labour force survey.; Indicator: Male employment-to-population ratio (%) , Country: Moldova, Republic of International Series: 2000 to 2012: Coverage: Total.; 2006: Remarks: Methodology revised.; 2000 to 2012: Age: 15+.; 2000 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 2000 to 2012: Type of source: Labour force survey.; Indicator: Female employment-to-population ratio (%) , Country: Moldova, Republic of International Series: 2000 to 2012: Coverage: Total.; 2006: Remarks: Methodology revised.; 2000 to 2012: Age: 15+.; 2000 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 2000 to 2012: Type of source: Labour force survey.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Moldova, Republic of National Series Reference: 2000 to 2011: UNECE Questionnaire Sept 2011; Source in Reference: 2000 to 2011: NSO; Primary Source in Reference: 2000 to 2011: LFS; International Series: 1999 to 2012: Coverage: Total.; 2006: Remarks: Methodology revised.; 1999 to 2012: Age: 15+.; 1999 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 1999 to 2012: Type of source: Labour force survey.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Moldova, Republic of International Series: 1999 to 2012: Coverage: Total.; 2006: Remarks: Methodology revised.; 1999 to 2012: Age: 15+.; 1999 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 1999 to 2012: Type of source: Labour force survey.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Moldova, Republic of International Series: 1999 to 2012: Coverage: Total.; 2006: Remarks: Methodology revised.; 1999 to 2012: Age: 15+.; 1999 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 1999 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Moldova, Republic of National Series Reference: 2000 to 2010: Statbank of the National Bureau of Statistics of the Republic of Moldova as on 08-08-2012; 2011: Moldova Statbank (http://statbank.statistica.md) 11-11-2013; 2012: Third MDG Report 2013; Note: 2000 to 2011: Information is presented without the data from the left side of the river Nistru and municipality Bender.; Source in Reference: 2000 to 2012: NSO; Primary Source in Reference: 2000 to 2010: LFS; International Series: 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; 2006: Remarks: Methodology revised.; 2000 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 2000 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Moldova, Republic of International Series: 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; 2006: Remarks: Methodology revised.; 2000 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 2000 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Moldova, Republic of International Series: 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; 2006: Remarks: Methodology revised.; 2000 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 2000 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Moldova, Republic of National Series Reference: 2000 to 2011: UNECE Questionnaire Sept 2011; Source in Reference: 2000 to 2011: NSO; Primary Source in Reference: 2000 to 2011: LFS; International Series: 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; 2006: Remarks: Methodology revised.; 2000 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 2000 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Moldova, Republic of International Series: 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; 2006: Remarks: Methodology revised.; 2000 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 2000 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Moldova, Republic of International Series: 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; 2006: Remarks: Methodology revised.; 2000 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 2000 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployed in total unemployed (%) , Country: Moldova, Republic of International Series: 1999 to 2012: Coverage: Total.; 1999 to 2012: Age: 15-24.; 2006: Remarks: Methodology revised.; 1999 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 1999 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployed in total unemployed (%) , Country: Moldova, Republic of National Series Reference: 2000 to 2011: UNECE Questionnaire Sept 2011; Source in Reference: 2000 to 2011: NSO; Primary Source in Reference: 2000 to 2011: LFS; International Series: 1999 to 2012: Coverage: Total.; 1999 to 2012: Age: 15-24.; 2006: Remarks: Methodology revised.; 1999 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 1999 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployed in total unemployed (%) , Country: Moldova, Republic of International Series: 1999 to 2012: Coverage: Total.; 1999 to 2012: Age: 15-24.; 2006: Remarks: Methodology revised.; 1999 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 1999 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployed in youth population, total , Country: Moldova, Republic of International Series: 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; 2006: Remarks: Methodology revised.; 2000 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 2000 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployed in male youth population ratio , Country: Moldova, Republic of National Series Reference: 2000 to 2011: UNECE Questionnaire Sept 2011; Source in Reference: 2000 to 2011: NSO; Primary Source in Reference: 2000 to 2011: LFS; International Series: 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; 2006: Remarks: Methodology revised.; 2000 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 2000 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployed in female youth population , Country: Moldova, Republic of International Series: 2000 to 2012: Coverage: Total.; 2000 to 2012: Age: 15-24.; 2006: Remarks: Methodology revised.; 2000 to 2012: Geographic Limitation: Excluding the Transnistria region and Bender.; 2000 to 2012: Type of source: Labour force survey.; Indicator: Unemployment rate , Country: Moldova, Republic of National Series Reference: 2009: MDG Report 2010; Source in Reference: 2009: NSO; Indicator: Growth rate of GDP per person employed (%) , Country: Montenegro International Series: 2008 to 2012: Coverage: Total.; 2008: Reference period: October to December.; 2008 to 2012: Age: 15+.; 2012: Remarks: Calculated using labour force and inactive population.; 2008 to 2012: Type of source: Labour force survey.; Indicator: Employment-to-population ratio, total (%) , Country: Montenegro International Series: 2005, 2007: Reference period: October.; 2005, 2007 to 2012: Coverage: Total.; 2012: Remarks: Calculated by the ILO.; 2005: Age: 15-64.; 2008: Reference period: October to December.; 2005: Type of source: Household or labour force survey.; 2007 to 2012: Age: 15+.; 2007 to 2012: Type of source: Labour force survey.; Indicator: Male employment-to-population ratio (%) , Country: Montenegro International Series: 2005, 2007: Reference period: October.; 2005, 2007 to 2012: Coverage: Total.; 2012: Remarks: Calculated by the ILO.; 2005: Age: 15-64.; 2008: Reference period: October to December.; 2005: Type of source: Household or labour force survey.; 2007 to 2012: Age: 15+.; 2007 to 2012: Type of source: Labour force survey.; Indicator: Female employment-to-population ratio (%) , Country: Montenegro National Series Reference: 2004 to 2012: MDG Report 2013; Source in Reference: 2004 to 2012: NSO; International Series: 2005, 2007: Reference period: October.; 2005, 2007 to 2012: Coverage: Total.; 2012: Remarks: Calculated by the ILO.; 2005: Age: 15-64.; 2008: Reference period: October to December.; 2005: Type of source: Household or labour force survey.; 2007 to 2012: Age: 15+.; 2007 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Montenegro National Series Reference: 1990 to 2005: MDG Report 2004; Note: 2005: Estimate; International Series: 2007: Reference period: October.; 2007 to 2012: Coverage: Total.; 2007 to 2012: Age: 15-24.; 2008: Reference period: October to December.; 2007 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Montenegro International Series: 2007: Reference period: October.; 2007 to 2012: Coverage: Total.; 2007 to 2012: Age: 15-24.; 2008: Reference period: October to December.; 2007 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Montenegro International Series: 2007: Reference period: October.; 2007 to 2012: Coverage: Total.; 2007 to 2012: Age: 15-24.; 2008: Reference period: October to December.; 2007 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Montenegro International Series: 2007: Reference period: October.; 2007 to 2012: Coverage: Total.; 2007 to 2012: Age: 15-24.; 2008: Reference period: October to December.; 2007 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Montenegro International Series: 2007: Reference period: October.; 2007 to 2012: Coverage: Total.; 2007 to 2012: Age: 15-24.; 2008: Reference period: October to December.; 2007 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Montenegro International Series: 2007: Reference period: October.; 2007 to 2012: Coverage: Total.; 2007 to 2012: Age: 15-24.; 2008: Reference period: October to December.; 2007 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployed in total unemployed (%) , Country: Montenegro International Series: 2007: Reference period: October.; 2007 to 2012: Coverage: Total.; 2007 to 2012: Age: 15-24.; 2008: Reference period: October to December.; 2007 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployed in total unemployed (%) , Country: Montenegro International Series: 2007: Reference period: October.; 2007 to 2012: Coverage: Total.; 2007 to 2012: Age: 15-24.; 2008: Reference period: October to December.; 2007 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployed in total unemployed (%) , Country: Montenegro International Series: 2007: Reference period: October.; 2007 to 2012: Coverage: Total.; 2007 to 2012: Age: 15-24.; 2008: Reference period: October to December.; 2007 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployed in youth population, total , Country: Montenegro International Series: 2007: Reference period: October.; 2007 to 2012: Coverage: Total.; 2007 to 2012: Age: 15-24.; 2008: Reference period: October to December.; 2007 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployed in male youth population ratio , Country: Montenegro International Series: 2007: Reference period: October.; 2007 to 2012: Coverage: Total.; 2007 to 2012: Age: 15-24.; 2008: Reference period: October to December.; 2007 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployed in female youth population , Country: Montenegro International Series: 2007: Reference period: October.; 2007 to 2012: Coverage: Total.; 2007 to 2012: Age: 15-24.; 2008: Reference period: October to December.; 2007 to 2012: Type of source: Labour force survey.; Indicator: Unemployment rate , Country: Montenegro National Series Reference: 2009 to 2012: MDG Report 2013; Source in Reference: 2009 to 2012: NSO; Primary Source in Reference: 2009 to 2012: LFS; Indicator: Male unemployment rate , Country: Montenegro National Series Reference: 2009 to 2012: MDG Report 2013; Source in Reference: 2009 to 2012: NSO; Primary Source in Reference: 2009 to 2012: LFS; Indicator: Female unemployment rate , Country: Montenegro National Series Reference: 2009 to 2012: MDG Report 2013; Source in Reference: 2009 to 2012: NSO; Primary Source in Reference: 2009 to 2012: LFS; Indicator: Long-term unemployment rate , Country: Montenegro National Series Reference: 2004 to 2012: MDG Report 2013; Source in Reference: 2004 to 2012: NSO; Primary Source in Reference: 2004 to 2012: LFS; Indicator: Growth rate of GDP per person employed (%) , Country: Poland International Series: 2000 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 1999: Reference period: Average of quarterly estimates.; 2001 to 2012: Age: 15-74.; 2000: Survey limitation: Continuous survey introduced.; 1991: Type of source: Official estimates.; 1991 to 2000: Age: 15+.; 1992 to 2012: Type of source: Labour force survey.; 1991: Coverage: Civilian.; Indicator: Employment-to-population ratio, total (%) , Country: Poland International Series: 2000 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 1999: Reference period: Average of quarterly estimates.; 2001 to 2012: Age: 15-74.; 2000: Survey limitation: Continuous survey introduced.; 1992 to 2000: Age: 15+.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Male employment-to-population ratio (%) , Country: Poland International Series: 2000 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 1999: Reference period: Average of quarterly estimates.; 2001 to 2012: Age: 15-74.; 2000: Survey limitation: Continuous survey introduced.; 1992 to 2000: Age: 15+.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Female employment-to-population ratio (%) , Country: Poland International Series: 2000 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 1999: Reference period: Average of quarterly estimates.; 2001 to 2012: Age: 15-74.; 2000: Survey limitation: Continuous survey introduced.; 1992 to 2000: Age: 15+.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Poland International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1993 to 2012: Coverage: Total.; 1993 to 1996: Coverage limitation: Excluding conscripts and regular military living in barracks.; 1993 to 1996: Type of source: Household or labour force survey.; 1993 to 2012: Age: 15+.; 1993 to 1996: Classification remark: Includes members of producers' cooperatives.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Poland International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1993 to 2012: Coverage: Total.; 1993 to 1996: Coverage limitation: Excluding conscripts and regular military living in barracks.; 1993 to 1996: Type of source: Household or labour force survey.; 1993 to 2012: Age: 15+.; 1993 to 1996: Classification remark: Includes members of producers' cooperatives.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Poland International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1993 to 2012: Coverage: Total.; 1993 to 1996: Coverage limitation: Excluding conscripts and regular military living in barracks.; 1993 to 1996: Type of source: Household or labour force survey.; 1993 to 2012: Age: 15+.; 1993 to 1996: Classification remark: Includes members of producers' cooperatives.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Poland International Series: 2000 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 1999: Reference period: Average of quarterly estimates.; 2000: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Poland International Series: 2000 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 1999: Reference period: Average of quarterly estimates.; 2000: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Poland International Series: 2000 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 1999: Reference period: Average of quarterly estimates.; 2000: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Poland International Series: 2000 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 1999: Reference period: Average of quarterly estimates.; 2000: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Poland International Series: 2000 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 1999: Reference period: Average of quarterly estimates.; 2000: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Poland International Series: 2000 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 1999: Reference period: Average of quarterly estimates.; 2000: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployed in total unemployed (%) , Country: Poland International Series: 2000 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 1999: Reference period: Average of quarterly estimates.; 2000: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployed in total unemployed (%) , Country: Poland International Series: 2000 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 1999: Reference period: Average of quarterly estimates.; 2000: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployed in total unemployed (%) , Country: Poland International Series: 2000 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 1999: Reference period: Average of quarterly estimates.; 2000: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployed in youth population, total , Country: Poland International Series: 2000 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 1999: Reference period: Average of quarterly estimates.; 2000: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployed in male youth population ratio , Country: Poland International Series: 2000 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 1999: Reference period: Average of quarterly estimates.; 2000: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployed in female youth population , Country: Poland International Series: 2000 to 2012: Reference period: Continuous survey.; 1992 to 2012: Coverage: Total.; 1992 to 1999: Reference period: Average of quarterly estimates.; 2000: Survey limitation: Continuous survey introduced.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Growth rate of GDP per person employed (%) , Country: Romania National Series Reference: 2001 to 2009: MDG Report 2010; Source in Reference: 2001 to 2009: NSO; International Series: 1995: Reference period: March.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1994 to 2012: Coverage: Total.; 1991 to 1993: Reference period: 31 December.; 1994 to 1996: Type of source: Household or labour force survey.; 1991 to 1993: Type of source: Official estimates.; 1991 to 2012: Age: 15+.; 1991 to 1993: Coverage: Civilian.; 1991: Remarks: State and cooperative sector.; Indicator: Employment-to-population ratio, total (%) , Country: Romania International Series: 1995: Reference period: March.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1995 to 2012: Coverage: Total.; 1990: Reference period: 31 December.; 1995, 1996: Type of source: Household or labour force survey.; 1990: Type of source: Official estimates.; 1990, 1995 to 2012: Age: 15+.; 1990: Coverage: Civilian.; 1990: Remarks: State and cooperative sector.; Indicator: Male employment-to-population ratio (%) , Country: Romania International Series: 1995: Reference period: March.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1995 to 2012: Coverage: Total.; 1990: Reference period: 31 December.; 1995, 1996: Type of source: Household or labour force survey.; 1990: Type of source: Official estimates.; 1990, 1995 to 2012: Age: 15+.; 1990: Coverage: Civilian.; 1990: Remarks: State and cooperative sector.; Indicator: Female employment-to-population ratio (%) , Country: Romania International Series: 1995: Reference period: March.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1995 to 2012: Coverage: Total.; 1990: Reference period: 31 December.; 1995, 1996: Type of source: Household or labour force survey.; 1990: Type of source: Official estimates.; 1990, 1995 to 2012: Age: 15+.; 1990: Coverage: Civilian.; 1990: Remarks: State and cooperative sector.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Romania National Series Reference: 2001 to 2009: MDG Report 2010; Source in Reference: 2001 to 2009: NSO; International Series: 1994, 1995: Reference period: March.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1994 to 2012: Coverage: Total.; 1991 to 1993: Reference period: 31 December.; 1994 to 1996: Type of source: Household or labour force survey.; 1991 to 1993: Type of source: Official estimates.; 1991 to 1993: Age: ...; 1996 to 2012: Age: 15+.; 1991 to 1993: Coverage: Civilian.; 1994, 1995: Age: 14+.; 1991: Remarks: State and cooperative sector.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Romania International Series: 1994, 1995: Reference period: March.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1994 to 2012: Coverage: Total.; 1991 to 1993: Reference period: 31 December.; 1994 to 1996: Type of source: Household or labour force survey.; 1991 to 1993: Type of source: Official estimates.; 1991 to 1993: Age: ...; 1996 to 2012: Age: 15+.; 1991 to 1993: Coverage: Civilian.; 1994, 1995: Age: 14+.; 1991: Remarks: State and cooperative sector.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Romania International Series: 1994, 1995: Reference period: March.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1994 to 2012: Coverage: Total.; 1991 to 1993: Reference period: 31 December.; 1994 to 1996: Type of source: Household or labour force survey.; 1991 to 1993: Type of source: Official estimates.; 1991 to 1993: Age: ...; 1996 to 2012: Age: 15+.; 1991 to 1993: Coverage: Civilian.; 1994, 1995: Age: 14+.; 1991: Remarks: State and cooperative sector.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Romania National Series Reference: 1995 to 2002: MDG Report 2003; Definition: 1995 to 1996: Age group 14-25; Source in Reference: 1995 to 2002: NSO; Primary Source in Reference: 1995 to 2002: LFS (AMIGO); International Series: 1995: Reference period: March.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1992, 1995 to 2012: Coverage: Total.; 1992, 1996 to 2012: Age: 15-24.; 1995: Age: 14-24.; 1992: Type of source: Population census.; 1995, 1996: Type of source: Household or labour force survey.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Romania National Series Reference: 1995 to 2002: MDG Report 2003; Definition: 1995 to 1996: Age group 14-25; Source in Reference: 1995 to 2002: NSO; Primary Source in Reference: 1995 to 2002: LFS (AMIGO); International Series: 1995: Reference period: March.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1992, 1995 to 2012: Coverage: Total.; 1992, 1996 to 2012: Age: 15-24.; 1995: Age: 14-24.; 1992: Type of source: Population census.; 1995, 1996: Type of source: Household or labour force survey.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Romania National Series Reference: 1995 to 2002: MDG Report 2003; Definition: 1995 to 1996: Age group 14-25; Source in Reference: 1995 to 2002: NSO; Primary Source in Reference: 1995 to 2002: LFS (AMIGO); International Series: 1995: Reference period: March.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1992, 1995 to 2012: Coverage: Total.; 1992, 1996 to 2012: Age: 15-24.; 1995: Age: 14-24.; 1992: Type of source: Population census.; 1995, 1996: Type of source: Household or labour force survey.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Romania International Series: 1995: Reference period: March.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1992, 1995 to 2012: Coverage: Total.; 1992, 1996 to 2012: Age: 15-24.; 1995: Age: 14-24.; 1992: Type of source: Population census.; 1995, 1996: Type of source: Household or labour force survey.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Romania International Series: 1995: Reference period: March.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1992, 1995 to 2012: Coverage: Total.; 1992, 1996 to 2012: Age: 15-24.; 1995: Age: 14-24.; 1992: Type of source: Population census.; 1995, 1996: Type of source: Household or labour force survey.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Romania International Series: 1995: Reference period: March.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1992, 1995 to 2012: Coverage: Total.; 1992, 1996 to 2012: Age: 15-24.; 1995: Age: 14-24.; 1992: Type of source: Population census.; 1995, 1996: Type of source: Household or labour force survey.; Indicator: Youth unemployed in total unemployed (%) , Country: Romania International Series: 1994, 1995: Reference period: March.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1992, 1994 to 2012: Coverage: Total.; 1992, 1996 to 2012: Age: 15-24.; 1994, 1995: Age: 14-24.; 1992: Type of source: Population census.; 1994 to 1996: Type of source: Household or labour force survey.; Indicator: Male youth unemployed in total unemployed (%) , Country: Romania International Series: 1994, 1995: Reference period: March.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1992, 1994 to 2012: Coverage: Total.; 1992, 1996 to 2012: Age: 15-24.; 1994, 1995: Age: 14-24.; 1992: Type of source: Population census.; 1994 to 1996: Type of source: Household or labour force survey.; Indicator: Female youth unemployed in total unemployed (%) , Country: Romania International Series: 1994, 1995: Reference period: March.; 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1992, 1994 to 2012: Coverage: Total.; 1992, 1996 to 2012: Age: 15-24.; 1994, 1995: Age: 14-24.; 1992: Type of source: Population census.; 1994 to 1996: Type of source: Household or labour force survey.; Indicator: Youth unemployed in youth population, total , Country: Romania International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1992, 1996 to 2012: Coverage: Total.; 1992, 1996 to 2012: Age: 15-24.; 1992: Type of source: Population census.; 1996: Type of source: Household or labour force survey.; Indicator: Male youth unemployed in male youth population ratio , Country: Romania International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1992, 1996 to 2012: Coverage: Total.; 1992, 1996 to 2012: Age: 15-24.; 1992: Type of source: Population census.; 1996: Type of source: Household or labour force survey.; Indicator: Female youth unemployed in female youth population , Country: Romania International Series: 1997 to 2012: Type of source: European Labour Force Survey (Eurostat).; 1992, 1996 to 2012: Coverage: Total.; 1992, 1996 to 2012: Age: 15-24.; 1992: Type of source: Population census.; 1996: Type of source: Household or labour force survey.; Indicator: Unemployment rate , Country: Romania National Series Reference: 1995 to 2001: MDG Report 2003; Note: 1995 to 2001: ILO standard definition of unemployment; 1995: 14 years and older; Source in Reference: 1995 to 2001: NSO; Primary Source in Reference: 1995 to 2001: LFS (AMIGO); Indicator: Male unemployment rate , Country: Romania National Series Reference: 1995 to 2001: MDG Report 2003; Note: 1995 to 2001: ILO standard definition of unemployment; 1995: 14 years and older; Source in Reference: 1995 to 2001: NSO; Primary Source in Reference: 1995 to 2001: LFS (AMIGO); Indicator: Female unemployment rate , Country: Romania National Series Reference: 1995 to 2001: MDG Report 2003; Note: 1995 to 2001: ILO standard definition of unemployment; 1995: 14 years and older; Source in Reference: 1995 to 2001: NSO; Primary Source in Reference: 1995 to 2001: LFS (AMIGO); Indicator: Growth rate of GDP per person employed (%) , Country: Russian Federation International Series: 1991 to 2012: Coverage: Total.; 1992 to 2012: Age: 15-72.; 1991: Type of source: Official estimates.; 1991: Age: ...; 1992 to 2012: Type of source: Labour force survey.; Indicator: Employment-to-population ratio, total (%) , Country: Russian Federation International Series: 1992 to 2012: Coverage: Total.; 1992 to 2012: Age: 15-72.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Male employment-to-population ratio (%) , Country: Russian Federation International Series: 1992 to 2012: Coverage: Total.; 1992 to 2012: Age: 15-72.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Female employment-to-population ratio (%) , Country: Russian Federation International Series: 1992 to 2012: Coverage: Total.; 1992 to 2012: Age: 15-72.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Russian Federation International Series: 1996: Reference period: March.; 1998: Reference period: October.; 1992 to 2008: Coverage: Total.; 1992 to 2008: Age: 15-72.; 1992 to 2008: Type of source: Household or labour force survey.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Russian Federation International Series: 1996: Reference period: March.; 1998: Reference period: October.; 1992 to 2008: Coverage: Total.; 1992 to 2008: Age: 15-72.; 1992 to 2008: Type of source: Household or labour force survey.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Russian Federation International Series: 1996: Reference period: March.; 1998: Reference period: October.; 1992 to 2008: Coverage: Total.; 1992 to 2008: Age: 15-72.; 1992 to 2008: Type of source: Household or labour force survey.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Russian Federation International Series: 1992 to 2012: Coverage: Total.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Russian Federation International Series: 1992 to 2012: Coverage: Total.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Russian Federation International Series: 1992 to 2012: Coverage: Total.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Russian Federation International Series: 1992 to 2012: Coverage: Total.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployment rate to adult unemployment rate (ratio) , Country: Russian Federation International Series: 1992 to 2012: Coverage: Total.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployment rate to adult unemployment rate (ratio) , Country: Russian Federation International Series: 1992 to 2012: Coverage: Total.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployed in total unemployed (%) , Country: Russian Federation International Series: 1992 to 2012: Coverage: Total.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployed in total unemployed (%) , Country: Russian Federation International Series: 1992 to 2012: Coverage: Total.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployed in total unemployed (%) , Country: Russian Federation International Series: 1992 to 2012: Coverage: Total.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Youth unemployed in youth population, total , Country: Russian Federation International Series: 1992 to 2012: Coverage: Total.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Male youth unemployed in male youth population ratio , Country: Russian Federation International Series: 1992 to 2012: Coverage: Total.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Female youth unemployed in female youth population , Country: Russian Federation International Series: 1992 to 2012: Coverage: Total.; 1992 to 2012: Age: 15-24.; 1992 to 2012: Type of source: Labour force survey.; Indicator: Growth rate of GDP per person employed (%) , Country: Serbia International Series: 2005 to 2009: Reference period: October.; 2005 to 2012: Coverage: Total.; 2005 to 2008: Type of source: Household or labour force survey.; 2005 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; 2010 to 2012: Reference period: Average of semi-annual estimates.; Indicator: Employment-to-population ratio, total (%) , Country: Serbia International Series: 2006 to 2009: Reference period: October.; 2006 to 2012: Coverage: Total.; 2006 to 2008: Type of source: Household or labour force survey.; 2006 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; 2010 to 2012: Reference period: Average of semi-annual estimates.; Indicator: Male employment-to-population ratio (%) , Country: Serbia National Series Reference: 2005 to 2009: MDG progress report 2009; Source in Reference: 2005 to 2009: NSO ; Primary Source in Reference: 2005: LFS 2005; 2009: LFS 2009; International Series: 2006 to 2009: Reference period: October.; 2006 to 2012: Coverage: Total.; 2006 to 2008: Type of source: Household or labour force survey.; 2006 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; 2010 to 2012: Reference period: Average of semi-annual estimates.; Indicator: Female employment-to-population ratio (%) , Country: Serbia National Series Reference: 2005 to 2009: MDG progress report 2009; Source in Reference: 2005 to 2009: NSO ; Primary Source in Reference: 2005: LFS 2005; 2009: LFS 2009; International Series: 2006 to 2009: Reference period: October.; 2006 to 2012: Coverage: Total.; 2006 to 2008: Type of source: Household or labour force survey.; 2006 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; 2010 to 2012: Reference period: Average of semi-annual estimates.; Indicator: Employed people living below the national poverty line (%) , Country: Serbia National Series Reference: 2007: MDG progress report 2009; Definition: 2007: National poverty line; Source in Reference: 2007: Krsti?, G. (2008), Poverty profile in Serbia from 2002 to 2007, LSMS, National Statistical Office.; Primary Source in Reference: 2007: Living Standard Measurement Survey 2007; Indicator: Own-account and contributing family workers in total employment, total (%) , Country: Serbia International Series: 2004 to 2009: Reference period: October.; 2004 to 2012: Coverage: Total.; 2004 to 2008: Type of source: Household or labour force survey.; 2004 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; 2010 to 2012: Reference period: Average of semi-annual estimates.; Indicator: Male own-account and contributing family workers in total employment (%) , Country: Serbia International Series: 2004 to 2009: Reference period: October.; 2004 to 2012: Coverage: Total.; 2004 to 2008: Type of source: Household or labour force survey.; 2004 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; 2010 to 2012: Reference period: Average of semi-annual estimates.; Indicator: Female own-account and contributing family workers in total employment (%) , Country: Serbia International Series: 2004 to 2009: Reference period: October.; 2004 to 2012: Coverage: Total.; 2004 to 2008: Type of source: Household or labour force survey.; 2004 to 2012: Age: 15+.; 2009 to 2012: Type of source: Labour force survey.; 2010 to 2012: Reference period: Average of semi-annual estimates.; Indicator: Youth unemployment rate (aged 15-24), both sexes , Country: Serbia National Series Reference: 2005 to 2009: MDG progress report 2009; Source in Reference: 2005 to 2009: NSO ; Primary Source in Reference: 2005: LFS 2005; 2009: LFS 2009; International Series: 2006, 2008, 2009: Reference period: October.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15-24.; 2006 to 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; 2010 to 2012: Reference period: Average of semi-annual estimates.; Indicator: Male youth unemployment rate (aged 15-24) , Country: Serbia International Series: 2006, 2008: Reference period: October.; 2006 to 2008: Coverage: Total.; 2006 to 2008: Age: 15-24.; 2006 to 2008: Type of source: Household or labour force survey.; Indicator: Female youth unemployment rate (aged 15-24) , Country: Serbia International Series: 2006, 2008: Reference period: October.; 2006 to 2008: Coverage: Total.; 2006 to 2008: Age: 15-24.; 2006 to 2008: Type of source: Household or labour force survey.; Indicator: Youth unemployment rate to adult unemployment rate, total (ratio) , Country: Serbia International Series: 2006, 2008, 2009: Reference period: October.; 2006 to 2012: Coverage: Total.; 2006 to 2012: Age: 15-24.; 2006 to 2008: Type of source: Household or labour force survey.; 2009 to 2012: Type of source: Labour force survey.; 2010 to