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Исландия

  • Население, человек:353 574 (2018)
  • Площадь, кв км:100 250
  • ВВП на душу населения, долл. США:73 191 (2018)
  • ВВП, млрд. долл. США:25,9 (2018)
  • Индекс Джини:No data
  • Рейтинг Ease of Doing Business:21

NACE Rev 2

Все наборы данных:  A B C D E F G H I J L M N O P R S T V W
  • A
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 15 октября, 2019
      Выбрать
      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).
    • Август 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 августа, 2019
      Выбрать
      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).
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 15 октября, 2019
      Выбрать
      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).
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 15 октября, 2019
      Выбрать
      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).
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 15 октября, 2019
      Выбрать
      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).
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 14 октября, 2019
      Выбрать
      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).
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 15 октября, 2019
      Выбрать
      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).
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 15 октября, 2019
      Выбрать
      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).
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 октября, 2019
      Выбрать
      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).
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 14 октября, 2019
      Выбрать
      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).
    • Май 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 23 мая, 2016
      Выбрать
      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)
    • Февраль 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 февраля, 2019
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      This metadata refers to three datasets based on the data collection on air emissions accounts (AEA): 1.Air emissions accounts by NACE Rev. 2 activity [env_ac_ainah_r2] This data set reports the emissions of greenhouse gases and air pollutants broken down by 64 industries (classified by NACE Rev. 2) plus households. Concepts and principles are the same as in national accounts. Complete data starts from reference year 2008. 2. Air emissions intensities by NACE Rev. 2 activity [env_ac_aeint_r2] This data set presents intensity-ratios relating AEA emissions (see previous) to economic parameters (value added, production output) for 64 industries (classified by NACE Rev. 2). 3. Air emissions accounts totals bridging to emission inventory totals [env_ac_aibrid_r2] This data set includes so-called bridging items showing the differences between the national totals as derived from two internationally established approaches/methods for reporting emissions of greenhouse gases and air pollutants: a) Air emissions accounts (AEA), i.e. the dataset mentioned above under 1. The AEA national totals refer to the residents of the reporting country (so-called residence principle as established in national accounts). b) National emission inventories, i.e. greenhouse gas inventories (providing emission data under the United Nations Framework Convention on Climate Change (UNFCCC)) and air pollutant inventories (providing emission data under the United Nations Economic Commission for Europe (UNECE), Convention on Long-range Transboundary Air Pollution (CLRTAP) and the EU National Emission Ceilings Directive (NEC). The national totals refer widely to the territory of the reporting country. The European Environment Agency (EEA) collects national inventories for greenhouse gases and other air pollutants and compiles the EU aggregates. Eurostat republishes the most relevant data from these inventories in [env_air_emis] and [env_air_gge]. The two methodologies are based on slightly different concepts and principles and the totals at national and EU level correspondingly differ. The bridging items explicitly present these differences.
    • Июль 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 30 июля, 2019
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      This metadata refers to three datasets based on the data collection on air emissions accounts (AEA): 1.Air emissions accounts by NACE Rev. 2 activity [env_ac_ainah_r2] This data set reports the emissions of greenhouse gases and air pollutants broken down by 64 industries (classified by NACE Rev. 2) plus households. Concepts and principles are the same as in national accounts. Complete data starts from reference year 2008. 2. Air emissions intensities by NACE Rev. 2 activity [env_ac_aeint_r2] This data set presents intensity-ratios relating AEA emissions (see previous) to economic parameters (value added, production output) for 64 industries (classified by NACE Rev. 2). 3. Air emissions accounts totals bridging to emission inventory totals [env_ac_aibrid_r2] This data set includes so-called bridging items showing the differences between the national totals as derived from two internationally established approaches/methods for reporting emissions of greenhouse gases and air pollutants: a) Air emissions accounts (AEA), i.e. the dataset mentioned above under 1. The AEA national totals refer to the residents of the reporting country (so-called residence principle as established in national accounts). b) National emission inventories, i.e. greenhouse gas inventories (providing emission data under the United Nations Framework Convention on Climate Change (UNFCCC)) and air pollutant inventories (providing emission data under the United Nations Economic Commission for Europe (UNECE), Convention on Long-range Transboundary Air Pollution (CLRTAP) and the EU National Emission Ceilings Directive (NEC). The national totals refer widely to the territory of the reporting country. The European Environment Agency (EEA) collects national inventories for greenhouse gases and other air pollutants and compiles the EU aggregates. Eurostat republishes the most relevant data from these inventories in [env_air_emis] and [env_air_gge]. The two methodologies are based on slightly different concepts and principles and the totals at national and EU level correspondingly differ. The bridging items explicitly present these differences.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 сентября, 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 in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech 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 in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 октября, 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 октября, 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 октября, 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 октября, 2019
      Выбрать
      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.
    • Февраль 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 февраля, 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.
    • Август 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 августа, 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.
    • Февраль 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 февраля, 2016
      Выбрать
      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.
    • Август 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 августа, 2017
      Выбрать
      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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 октября, 2019
      Выбрать
      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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 октября, 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 17 октября, 2019
      Выбрать
      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.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 июня, 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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 02 октября, 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 13 октября, 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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 сентября, 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 14 октября, 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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 сентября, 2019
      Выбрать
      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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 13 октября, 2019
      Выбрать
      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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 сентября, 2019
      Выбрать
      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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 17 октября, 2019
      Выбрать
      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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 октября, 2019
      Выбрать
      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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 сентября, 2019
      Выбрать
      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.
  • B
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 12 октября, 2019
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      The annual Business demography data collection covers variables which explain the characteristics and demography of the business population. The methodology allows for the production of data on enterprise births (and deaths), that is, enterprise creations (cessations) that amount to the creation (dissolution) of a combination of production factors and where no other enterprises are involved. In other words, enterprises created or closed solely as a result of e.g. restructuring, merger or break-up are not considered. The data are drawn from business registers, although some countries improve the availability of data on employment and turnover by integrating other sources. Until 2010 reference year the harmonised data collection is carried out to satisfy the requirements for the Structural Indicators, used for monitoring progress of the Lisbon process, regarding business births, deaths and survival. Currently, business demography delivers key information for policy decision-making and for the indicators to support the Europe 2020 strategy. It also provides key data for the joint OECD-Eurostat "Entrepreneurship Indicators Programme". In summary, the collected indicators are as follows:Population of active enterprisesNumber of enterprise birthsNumber of enterprise survivals up to five yearsNumber of enterprise deathsRelated variables on employmentDerived indicators such as birth rates, death rates, survival rates and employment sharesAn additional set of indicators on high-growth enterprises and 'gazelles' (high-growth enterprises that are up to five years old) The complete list of the basic variables, delivered from the data providers (National Statistical Institutes) and the derived indicators, calculated by Eurostat, is attached in the Annexes of this document (see Business demography indicators).  Geographically EU Member States and EFTA countries are covered. In practice not all Member States have participated in the first harmonised data collection exercises. The methodology laid down in the Eurostat-OECD Manual on Business Demography Statistics  is followed closely by most of the countries (see Country specific notes in the Annexes).
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 14 октября, 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
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 октября, 2019
      Выбрать
      The annual Business demography data collection covers variables which explain the characteristics and demography of the business population. The methodology allows for the production of data on enterprise births (and deaths), that is, enterprise creations (cessations) that amount to the creation (dissolution) of a combination of production factors and where no other enterprises are involved. In other words, enterprises created or closed solely as a result of e.g. restructuring, merger or break-up are not considered. The data are drawn from business registers, although some countries improve the availability of data on employment and turnover by integrating other sources. Until 2010 reference year the harmonised data collection is carried out to satisfy the requirements for the Structural Indicators, used for monitoring progress of the Lisbon process, regarding business births, deaths and survival. Currently, business demography delivers key information for policy decision-making and for the indicators to support the Europe 2020 strategy. It also provides key data for the joint OECD-Eurostat "Entrepreneurship Indicators Programme". In summary, the collected indicators are as follows:Population of active enterprisesNumber of enterprise birthsNumber of enterprise survivals up to five yearsNumber of enterprise deathsRelated variables on employmentDerived indicators such as birth rates, death rates, survival rates and employment sharesAn additional set of indicators on high-growth enterprises and 'gazelles' (high-growth enterprises that are up to five years old) The complete list of the basic variables, delivered from the data providers (National Statistical Institutes) and the derived indicators, calculated by Eurostat, is attached in the Annexes of this document.  Geographically EU Member States and EFTA countries are covered. In practice not all Member States have participated in the first harmonised data collection exercises. The methodology laid down in the Eurostat-OECD Manual on Business Demography Statistics  is followed closely by most of the countries (see Country specific notes in the Annexes).
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 октября, 2019
      Выбрать
      The annual Business demography data collection covers variables which explain the characteristics and demography of the business population. The methodology allows for the production of data on enterprise births (and deaths), that is, enterprise creations (cessations) that amount to the creation (dissolution) of a combination of production factors and where no other enterprises are involved. In other words, enterprises created or closed solely as a result of e.g. restructuring, merger or break-up are not considered. The data are drawn from business registers, although some countries improve the availability of data on employment and turnover by integrating other sources. Until 2010 reference year the harmonised data collection is carried out to satisfy the requirements for the Structural Indicators, used for monitoring progress of the Lisbon process, regarding business births, deaths and survival. Currently, business demography delivers key information for policy decision-making and for the indicators to support the Europe 2020 strategy. It also provides key data for the joint OECD-Eurostat "Entrepreneurship Indicators Programme". In summary, the collected indicators are as follows:Population of active enterprisesNumber of enterprise birthsNumber of enterprise survivals up to five yearsNumber of enterprise deathsRelated variables on employmentDerived indicators such as birth rates, death rates, survival rates and employment sharesAn additional set of indicators on high-growth enterprises and 'gazelles' (high-growth enterprises that are up to five years old) The complete list of the basic variables, delivered from the data providers (National Statistical Institutes) and the derived indicators, calculated by Eurostat, is attached in the Annexes of this document.  Geographically EU Member States and EFTA countries are covered. In practice not all Member States have participated in the first harmonised data collection exercises. The methodology laid down in the Eurostat-OECD Manual on Business Demography Statistics  is followed closely by most of the countries (see Country specific notes in the Annexes).
    • Июнь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 июня, 2019
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      This collection provides users with data concerning R&D expenditure and R&D personnel broken down by following institutional sectors: business enterprise (BES), government (GOV), higher education (HES), private non-profit (PNP) with the total of sectors. All data are broken down by the above mentioned sectors of performance. The R&D expenditure is further broken down by source of funds, by type of costs, by economic activity (NACE Rev.2), by size class, by type of R&D, by fields of science, by socio-economic objectives and by regions (NUTS 2 level). Besides R&D expenditures in basic unit National currency (MIO_NAC) the following units are available: Euro (MIO_EUR), Euro per inhabitant (EUR_HAB) Purchasing Power Standard (MIO_PPS), Purchasing Power Standard at 2005 prices (MIO_PPS_KP05), Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_KP05_HAB), Percentage of GDP (PC_GDP) and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds). R&D personnel data is available in full-time equivalent (FTE), in head count (HC), as a % of employment and as a % of labour force. The data is further broken down by occupation, by qualification, by gender, by size class, by citizenship, by age groups, by fields of science, by economic activity (NACE Rev.2) and by regions (NUTS 2 level). The periodicity of R&D data is biennial except for the key R&D indicators (R&D expenditure, R&D personnel and Researchers by sectors of performance) which are transmitted annually by the EU Member States on the basis of a legal obligation from 2003 onwards. Some other breakdowns of the data may appear on annual basis based on voluntary data provisions. The data are collected through sample or census surveys, from administrative registers or through a combination of sources. R&D data are available for following countries and country groups: - All EU Member States, plus Candidate Countries, EFTA Countries, the Russian Federation, China, Japan, the United States and South Korea. - Country groups: EU-28, EU-15 and EA-18. R&D data are compiled in accordance to the guidelines laid down in the Proposed standard practice for surveys of research and experimental development - Frascati Manual (FM), OECD, 2002 .
    • Июнь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 30 июня, 2019
      Выбрать
      This collection provides users with data concerning R&D expenditure and R&D personnel broken down by following institutional sectors: business enterprise (BES), government (GOV), higher education (HES), private non-profit (PNP) with the total of sectors. All data are broken down by the above mentioned sectors of performance. The R&D expenditure is further broken down by source of funds, by type of costs, by economic activity (NACE Rev.2), by size class, by type of R&D, by fields of science, by socio-economic objectives and by regions (NUTS 2 level). Besides R&D expenditures in basic unit National currency (MIO_NAC) the following units are available: Euro (MIO_EUR), Euro per inhabitant (EUR_HAB) Purchasing Power Standard (MIO_PPS), Purchasing Power Standard at 2005 prices (MIO_PPS_KP05), Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_KP05_HAB), Percentage of GDP (PC_GDP) and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds). R&D personnel data is available in full-time equivalent (FTE), in head count (HC), as a % of employment and as a % of labour force. The data is further broken down by occupation, by qualification, by gender, by size class, by citizenship, by age groups, by fields of science, by economic activity (NACE Rev.2) and by regions (NUTS 2 level). The periodicity of R&D data is biennial except for the key R&D indicators (R&D expenditure, R&D personnel and Researchers by sectors of performance) which are transmitted annually by the EU Member States on the basis of a legal obligation from 2003 onwards. Some other breakdowns of the data may appear on annual basis based on voluntary data provisions. The data are collected through sample or census surveys, from administrative registers or through a combination of sources. R&D data are available for following countries and country groups: - All EU Member States, plus Candidate Countries, EFTA Countries, the Russian Federation, China, Japan, the United States and South Korea. - Country groups: EU-28, EU-15 and EA-18. R&D data are compiled in accordance to the guidelines laid down in the Proposed standard practice for surveys of research and experimental development - Frascati Manual (FM), OECD, 2002 .
    • Июнь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 июня, 2019
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      This collection provides users with data concerning R&D expenditure and R&D personnel broken down by following institutional sectors: business enterprise (BES), government (GOV), higher education (HES), private non-profit (PNP) with the total of sectors. All data are broken down by the above mentioned sectors of performance. The R&D expenditure is further broken down by source of funds, by type of costs, by economic activity (NACE Rev.2), by size class, by type of R&D, by fields of science, by socio-economic objectives and by regions (NUTS 2 level). Besides R&D expenditures in basic unit National currency (MIO_NAC) the following units are available: Euro (MIO_EUR), Euro per inhabitant (EUR_HAB) Purchasing Power Standard (MIO_PPS), Purchasing Power Standard at 2005 prices (MIO_PPS_KP05), Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_KP05_HAB), Percentage of GDP (PC_GDP) and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds). R&D personnel data is available in full-time equivalent (FTE), in head count (HC), as a % of employment and as a % of labour force. The data is further broken down by occupation, by qualification, by gender, by size class, by citizenship, by age groups, by fields of science, by economic activity (NACE Rev.2) and by regions (NUTS 2 level). The periodicity of R&D data is biennial except for the key R&D indicators (R&D expenditure, R&D personnel and Researchers by sectors of performance) which are transmitted annually by the EU Member States on the basis of a legal obligation from 2003 onwards. Some other breakdowns of the data may appear on annual basis based on voluntary data provisions. The data are collected through sample or census surveys, from administrative registers or through a combination of sources. R&D data are available for following countries and country groups: - All EU Member States, plus Candidate Countries, EFTA Countries, the Russian Federation, China, Japan, the United States and South Korea. - Country groups: EU-28, EU-15 and EA-18. R&D data are compiled in accordance to the guidelines laid down in the Proposed standard practice for surveys of research and experimental development - Frascati Manual (FM), OECD, 2002 .
    • Июнь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 июня, 2019
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      This collection provides users with data concerning R&D expenditure and R&D personnel broken down by following institutional sectors: business enterprise (BES), government (GOV), higher education (HES), private non-profit (PNP) with the total of sectors. All data are broken down by the above mentioned sectors of performance. The R&D expenditure is further broken down by source of funds, by type of costs, by economic activity (NACE Rev.2), by size class, by type of R&D, by fields of science, by socio-economic objectives and by regions (NUTS 2 level). Besides R&D expenditures in basic unit National currency (MIO_NAC) the following units are available: Euro (MIO_EUR), Euro per inhabitant (EUR_HAB), Purchasing Power Standard (MIO_PPS), Purchasing Power Standard at 2005 prices (MIO_PPS_KP05), Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_KP05_HAB), Percentage of GDP (PC_GDP) and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds). R&D personnel data is available in full-time equivalent (FTE), in head count (HC), as a % of employment and as a % of labour force. The data is further broken down by occupation, by qualification, by gender, by size class, by citizenship, by age groups, by fields of science, by economic activity (NACE Rev.2) and by regions (NUTS 2 level). The periodicity of R&D data is biennial except for the key R&D indicators (R&D expenditure, R&D personnel and Researchers by sectors of performance) which are transmitted annually by the EU Member States on the basis of a legal obligation from 2003 onwards. Some other breakdowns of the data may appear on annual basis based on voluntary data provisions. The data are collected through sample or census surveys, from administrative registers or through a combination of sources. R&D data are available for following countries and country groups: - All EU Member States, plus Candidate Countries, EFTA Countries, the Russian Federation, China, Japan, the United States and South Korea. - Country groups: EU-28, EU-15 and EA-18. R&D data are compiled in accordance to the guidelines laid down in the Proposed standard practice for surveys of research and experimental development - Frascati Manual (FM), OECD, 2002 .
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 марта, 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.
  • C
    • Февраль 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 августа, 2015
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    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 сентября, 2019
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      International trade in goods statistics are an important data source for many public and private sector decision-makers at international, European Union and national level. For example, at the European Union level, international trade data are extensively used for multilateral and bilateral negotiations within the framework of the common commercial policy, to define and implement anti-dumping policy, to evaluate the progress of the Single Market and many other policies. Moreover, they constitute an essential source for the compilation of balance of payments statistics and national accounts. International trade in goods statistics cover both extra- and intra-EU trade: Extra-EU trade statistics cover the trading of goods between Member States and a non-member countries. Intra-EU trade statistics cover the trading of goods between Member States. "Goods" means all movable property including electricity. Detailed and aggregated data are published for the Euro area, the European Union and for each Member State separately. Main components: Data record the monthly trade between Member States in terms of arrivals and dispatches of goods as well as the monthly trade in terms of imports and exports between Member States and non-member countries. However, in publications only the term “exports” for all outward flows and “imports” for all inward flows are applied for both intra-EU trade and extra-EU trade. Extra-EU trade imports and exports are recorded in the Member State where the goods are placed under the customs procedures. Extra-EU trade statistics do not record goods in transit, goods placed into customs warehouses or goods for temporary admission. Data sources: The statistical information is mainly provided by the traders on the basis of Customs (extra-EU) and Intrastat (intra-EU) declarations. Data are collected by the competent national authorities of the Member States and compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Classification systems: - Product classification: For detailed data, products are disseminated according to the Combined Nomenclature (CN8), which first six digit codes coincide with the Harmonized Commodity Description and Coding System (HS), products are disseminated as well according to the Standard International Trade Classification (SITC) and the Broad Economic Categories (BEC). - Country classification: The Geonomenclature is used for classifying reporting countries and trading partners. Nomenclatures and correspondence tables are available at the Eurostat’s classification server RAMON. The following basic information is provided by Eurostat: - reporting country, - reference period, - trade flow, - product, - trading partner - mode of transport. Detailed data are disseminated according to the Combined Nomenclature (HS2, HS4, HS6 and CN8 levels) for the following indicators: - trade value (in Euro), - trade quantity in 100 kg, - trade quantity in supplementary units (published for some goods according to the Combined Nomenclature). Aggregated data cover both short and long term indicators. Short term indicators are disseminated according to major SITC and BEC groups for the following indicators: - gross and seasonally adjusted trade value (in million Euro), - unit-value indices, - gross and seasonally adjusted volume indices, - growth rates of trade values and indices. Long term indicators are disseminated according to major SITC groups for the following indicators: - trade value (in billion Euro), - shares of Member States in EU and world trade, - shares of main trading partners in EU trade, - volume indices. Adjustments are applied by the Member States to compensate the impact of exemption thresholds, which release the information providers from statistical formalities, as well as, to take into account the late or not response of the providers. In addition, Eurostat applies seasonal adjustments to aggregated time series.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 19 октября, 2019
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      Industry, Trade and Services statistics are part of Short-term statistics (STS), they give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification(Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are presented in the following forms:UnadjustedCalendar adjustedSeasonally-adjusted Depending on the STS regulation, data are accessible monthly and quarterly. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction Index*Turnover IndexProducer Prices (Domestic Output Prices index)*Import Prices Index*: Total, Euro area market, Non euro area market (euro area countries only)Labour Input Indicators: Number of Persons Employed, Hours Worked, Gross Wages and Salaries CONSTRUCTIONProduction Index*: Total of the construction sector, Building construction, Civil EngineeringLabour input indicators: Number of Persons Employed, Hours Worked, Gross Wages and SalariesConstruction costs IndexBuilding permits indicators*: Number of dwellings WHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (in value)Labour input indicators: Number of Persons Employed SERVICES Turnover Index*Producer prices (Ouput prices)*
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 19 октября, 2019
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      Industry, Trade and Services statistics are part of Short-term statistics (STS), they give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification(Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are presented in the following forms: UnadjustedCalendar adjustedSeasonally-adjusted Depending on the STS regulation, data are accessible monthly and quarterly. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction Index*Turnover IndexProducer Prices (Domestic Output Prices index)*Import Prices Index*: Total, Euro area market, Non euro area market (euro area countries only)Labour Input Indicators: Number of Persons Employed, Hours Worked, Gross Wages and SalariesCONSTRUCTIONProduction Index*: Total of the construction sector, Building construction, Civil EngineeringLabour input indicators: Number of Persons Employed, Hours Worked, Gross Wages and SalariesConstruction costs IndexBuilding permits indicators*: Number of dwellingsWHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (in value)Labour input indicators: Number of Persons EmployedSERVICES  Turnover Index* Producer prices (Ouput prices)*
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 октября, 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.
    • Июнь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 26 июня, 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).
  • D
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 октября, 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.
  • E
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 сентября, 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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 сентября, 2019
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    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 сентября, 2019
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      The Human Resources in Science and Technology (HRST) domain provides data on stocks and flows (where flows in turn are divided into job-to-job mobility and education inflows). Stocks and flows are the main statistics for HRST. Their methodologies interlink and are therefore presented together in one single metadata-file. This metadata-file is duplicated in the structure of Eurostat's online database, while statistics for stocks and flows are found in separate folders. Several breakdowns are available for stocks and flows indicators: sex, age, region, sector of economic activity, occupation, educational attainment, fields of education, although not all combinations are possible. The data on stocks and job-to-job mobility are obtained from the European Union Labour Force Survey (EU LFS). The National Statistical Institutes are responsible for conducting the surveys and forwarding the results to Eurostat. The data on education inflows are obtained from Eurostat's Education database and in turn obtained via the UNESCO/OECD/Eurostat questionnaire on education. The National Statistical Institutes are responsible for conducting the surveys, compiling the results and forwarding the results to Eurostat. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 октября, 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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 сентября, 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 октября, 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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 сентября, 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 октября, 2019
      Выбрать
      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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 сентября, 2019
      Выбрать
      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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 сентября, 2019
      Выбрать
      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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 октября, 2019
      Выбрать
      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.
    • Май 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 20 мая, 2016
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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)
    • Май 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 20 мая, 2016
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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)
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 октября, 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 13 октября, 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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 сентября, 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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 29 сентября, 2019
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      The annual Business demography data collection covers variables which explain the characteristics and demography of the business population. The methodology allows for the production of data on enterprise births (and deaths), that is, enterprise creations (cessations) that amount to the creation (dissolution) of a combination of production factors and where no other enterprises are involved. In other words, enterprises created or closed solely as a result of e.g. restructuring, merger or break-up are not considered. The data are drawn from business registers, although some countries improve the availability of data on employment and turnover by integrating other sources. Until 2010 reference year the harmonised data collection is carried out to satisfy the requirements for the Structural Indicators, used for monitoring progress of the Lisbon process, regarding business births, deaths and survival. Currently, business demography delivers key information for policy decision-making and for the indicators to support the Europe 2020 strategy. It also provides key data for the joint OECD-Eurostat "Entrepreneurship Indicators Programme". In summary, the collected indicators are as follows:Population of active enterprisesNumber of enterprise birthsNumber of enterprise survivals up to five yearsNumber of enterprise deathsRelated variables on employmentDerived indicators such as birth rates, death rates, survival rates and employment sharesAn additional set of indicators on high-growth enterprises and 'gazelles' (high-growth enterprises that are up to five years old) The complete list of the basic variables, delivered from the data providers (National Statistical Institutes) and the derived indicators, calculated by Eurostat, is attached in the Annexes of this document (see Business demography indicators).  Geographically EU Member States and EFTA countries are covered. In practice not all Member States have participated in the first harmonised data collection exercises. The methodology laid down in the Eurostat-OECD Manual on Business Demography Statistics  is followed closely by most of the countries (see Country specific notes in the Annexes).
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 29 сентября, 2019
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      Eurostat Dataset Id:bd_9fh_sz_cl_r2 The data category covers a group of variables which explain the characteristics and demography of the business population. The methodology allows for the production of data on enterprise births (and deaths), that is, enterprise creations (cessations) that amount to the creation (dissolution) of a combination of production factors and where no other enterprises are involved. In other words, enterprises created or closed solely as a result of e.g. restructuring, merger or break-up are not included in this data. Until 2010 reference year the harmonised data collection is carried out to satisfy the requirements for the Structural Indicators, used for monitoring progress of the Lisbon process, regarding business births, deaths and survival. It also provides key data for the joint OECD-Eurostat "Entrepreneurship Indicators Programme". In summary, the collected indicators are as follows:Population of active enterprisesNumber of enterprise birthsNumber of enterprise survivals up to five yearsNumber of enterprise deathsRelated variables on employmentDerived indicators such as birth rates, death rates, survival rates and employment sharesAn additional set of indicators on high-growth enterprises and 'gazelles' (high-growth enterprises that are up to five years old) The data are drawn from business registers, although some individual countries improve the availability or freshness of data on employment and turnover by integrating other sources. Geographically EU Member States and EFTA countries are covered. In practice not all Member States have participated in the first harmonised data collection exercises.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 сентября, 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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 сентября, 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 октября, 2019
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      Employment consists of both employees and self-employed, who are engaged in some productive activity that falls within the production boundary of the system (ESA 2010, 11.11). Employment covers employees and self-employed working for production units resident on the economic territory (i.e. the domestic employment concept). Employment is measured in number of persons without distinction according to full-time or part-time work. Growth rates with respect to the previous quarter (Q/Q-1) are calculated from seasonally adjusted figures while growth rates with respect to the same quarter of the previous year (Q/Q-4) are calculated from non-seasonal adjusted data.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 октября, 2019
      Выбрать
      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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 сентября, 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 09 октября, 2019
      Выбрать
      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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 сентября, 2019
      Выбрать
      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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 октября, 2019
      Выбрать
      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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 сентября, 2019
      Выбрать
      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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 октября, 2019
      Выбрать
      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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 сентября, 2019
      Выбрать
      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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 сентября, 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 in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech 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 in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 сентября, 2019
      Выбрать
      'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech 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 in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 сентября, 2019
      Выбрать
      'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech 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 in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 сентября, 2019
      Выбрать
      'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech 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 in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 сентября, 2019
      Выбрать
      'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech 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 in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 сентября, 2019
      Выбрать
      'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech 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 in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.
    • Февраль 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 20 февраля, 2017
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    • Май 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 20 мая, 2016
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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)
    • Май 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 23 мая, 2016
      Выбрать
      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)
    • Декабрь 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 декабря, 2017
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      The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to provide information on the innovativeness of sectors by type of enterprises, on the different types of innovation and on various aspects of the development of an innovation, such as objectives, sources of information, public funding or expenditures. The CIS provides statistics broken down by countries, types of innovators, economic activities and size classes. The survey is currently carried out every two years across the European Union, EFTA countries and EU candidate countries. In order to ensure comparability across countries, Eurostat together with the countries developed a standard core questionnaire (see in Annex) accompanied by a set of definitions and methodological recommendations. CIS 2014 concepts and its underlying methodology are also based on the Oslo Manual (2005) 3rd edition (see link at the bottom of the page). CIS 2014 results were collected under Commission Regulation No 995/2012. This Regulation defines the mandatory target population of the survey referring to enterprises in the Core NACE categories (see section 3.3.) with at least 10 employees. Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period 2012-2014, but some use only one calendar year (2012 or 2014). CIS 2014 includes an ad-hoc module on innovations with environmental benefits. While European innovation statistics use aggregated national data, the microdata sets can be consulted by researchers via the SAFE Centre of Eurostat in Luxembourg or via CD-ROM releases in a more anonymised form; some countries also provide access to their microdata through national Safe Centres. Since the provision of microdata is voluntary, microdatasets do not cover all countries.
    • Сентябрь 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 декабря, 2015
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    • Май 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 мая, 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.
    • Май 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 20 мая, 2016
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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)
    • Май 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 20 мая, 2016
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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)
    • Май 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 20 мая, 2016
      Выбрать
      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)
    • Декабрь 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 декабря, 2017
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      The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to provide information on the innovativeness of sectors by type of enterprises, on the different types of innovation and on various aspects of the development of an innovation, such as objectives, sources of information, public funding or expenditures. The CIS provides statistics broken down by countries, types of innovators, economic activities and size classes. The survey is currently carried out every two years across the European Union, EFTA countries and EU candidate countries. In order to ensure comparability across countries, Eurostat together with the countries developed a standard core questionnaire (see in Annex) accompanied by a set of definitions and methodological recommendations. CIS 2014 concepts and its underlying methodology are also based on the Oslo Manual (2005) 3rd edition (see link at the bottom of the page). CIS 2014 results were collected under Commission Regulation No 995/2012. This Regulation defines the mandatory target population of the survey referring to enterprises in the Core NACE categories (see section 3.3.) with at least 10 employees. Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period 2012-2014, but some use only one calendar year (2012 or 2014). CIS 2014 includes an ad-hoc module on innovations with environmental benefits. While European innovation statistics use aggregated national data, the microdata sets can be consulted by researchers via the SAFE Centre of Eurostat in Luxembourg or via CD-ROM releases in a more anonymised form; some countries also provide access to their microdata through national Safe Centres. Since the provision of microdata is voluntary, microdatasets do not cover all countries.
    • Апрель 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 декабря, 2015
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      Data show environmental protection expenditure (EPE). Environmental protection includes all activities directly aimed at the prevention, reduction and elimination of pollution or any other degradation of the environment. Data on expenditure encompasses different types of investment and current expenditure by several sectors and detail by economic activity (see details in sections 3.2 to 3.4 below).
    • Июль 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 03 декабря, 2015
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      Eurostat uses as a base for its work the OECD Benchmark Definition of Foreign Direct Investment Third Edition, a detailed operational definition fully consistent with the IMF Balance of Payments Manual, Fifth Edition, BPM5. Foreign direct investment (FDI) is the category of international investment made by an entity resident in one economy (direct investor) to acquire a lasting interest in an enterprise operating in another economy (direct investment enterprise). The lasting interest is deemed to exist if the direct investor acquires at least 10% of the voting power of the direct investment enterprise. FDI statistics record separately: 1) Inward FDI (or FDI in the reporting economy), namely investment by foreigners in enterprises resident in the reporting economy. 2) Outward FDI (or FDIabroad), namely investment by residents entities in affiliated enterprises abroad. FDI statistics record both the initial investment and all subsequent investment made by the direct investor, either in the form of equity capital, or in the form of loans, or in the form of reinvesting earnings. Investment made through other affiliated enterprises of the same group of the direct investor should also be recorded according to the international methodology. There are three main indicators: FDI flows, stocks and income. The indicators described in more detail below are presented in the complete tables with a breakdown by partner country or region and a breakdown by the kind of activity in which FDI is made. In the table called "Main indicators" there is a reduced breakdown by partners and data for total activity only. See the part on classification system for more detail. See also the User's guideon the structure on the database and for practical information on data downloading. 1) FDI flows denote the new investment made during the period. FDI flows are recorded in the Balance of Payments financial account. Total FDI flows are broken down by kind of instrument used for making the investment: Equity capital comprises equity in branches, all shares in subsidiaries and associates (except non-participating, preferred shares that are treated as debt securities and are included under other FDI capital) and other contributions such as the provision of machinery. Reinvested earnings consist of the direct investor's share (in proportion to equity participation) of earnings not distributed by the direct investment enterprise. Reinvested earnings are an imputed transaction. Reinvested earnings are also recorded with opposite sign among FDI income (see below). This recording represents not distributed income as being earned by the direct investor and reinvested in the direct investment enterprise at the same time. Other FDI capital (loans) covers the borrowing and lending of funds, including debt securities and trade credits between direct investors and direct investment enterprises. Debt transactions between affiliated financial intermediaries recorded under direct investment flows are limited to permanent debt. 2) FDI stocks (or positions) denote the value of the investment at the end of the period. FDI stocks are recorded in the International Investment Position. Outward FDI stocks are recorded as assets of the reporting economy, inward FDI stocks as liabilities. Similarly with flows, FDI stocks are broken down by kind of instrument. However, there are only two categories instead of three: Equity capital and reinvested earnings is the value of the own capital of the enterprise, including the value of own reserves that are accumulated from past reinvested earnings. Reserves corresponding to reinvested earnings are not shown separately from other equity capital as in the case of flows. Other FDI capital is the stock of debts (assets or liabilities) between the direct investors and the direct investment enterprise. 3) FDI income is the income accruing to direct investors during the period. FDI income is recorded in the current account of the Balance of Payments. Total FDI income is broken down by kind of income. The categories of FDI income available are linked to the breakdown of FDI flows and stocks by kind of instrument, namely: Dividends Dividends payable in the period and branch profits remitted to the direct investor, gross of any withholding taxes. Dividends include payments due on common and preferred shares. Reinvested earnings See definition under FDI flows. Interest on loans Interest accrued in the period on loans (other FDI capital) with affiliated enterprises, gross of any withholding tax. 4) FDI intensity Out of FDI annual data, an indicator useful to measure EU market integration is also calculated and disseminated in the domain Structural Indicators: FDI intensity as % of GDP: Average of inward and outward FDI flows divided by GDP. A higher index indicates higher new FDI during the period in relation to the size of the economy as measured by GDP. If this index increases over time, then the country/zone is becoming more integrated with the international economy.
    • Июль 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 12 августа, 2015
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      Eurostat Dataset Id:bop_fdi_pos_r2 Eurostat uses as a base for its work the OECD Benchmark Definition of Foreign Direct Investment Third Edition, a detailed operational definition fully consistent with the IMF Balance of Payments Manual, Fifth Edition, BPM5. Foreign direct investment (FDI) is the category of international investment made by an entity resident in one economy (direct investor) to acquire a lasting interest in an enterprise operating in another economy (direct investment enterprise). The lasting interest is deemed to exist if the direct investor acquires at least 10% of the voting power of the direct investment enterprise. FDI statistics record separately: 1) Inward FDI (or FDI in the reporting economy), namely investment by foreigners in enterprises resident in the reporting economy. 2) Outward FDI (or FDI abroad), namely investment by residents entities in affiliated enterprises abroad. FDI statistics record both the initial investment and all subsequent investment made by the direct investor, either in the form of equity capital, or in the form of loans, or in the form of reinvesting earnings. Investment made through other affiliated enterprises of the same group of the direct investor should also be recorded according to the international methodology. There are three main indicators: FDI flows, stocks and income. The indicators described in more detail below are presented in the complete tables with a breakdown by partner country or region and a breakdown by the kind of activity in which FDI is made. In the table called "Main indicators" there is a reduced breakdown by partners and data for total activity only. See the part on classification system for more detail. See also the User's guideon the structure on the database and for practical information on data downloading. 1) FDI flows denote the new investment made during the period. FDI flows are recorded in the Balance of Payments financial account. Total FDI flows are broken down by kind of instrument used for making the investment:Equity capital comprises equity in branches, all shares in subsidiaries and associates (except non-participating, preferred shares that are treated as debt securities and are included under other FDI capital) and other contributions such as the provision of machinery.Reinvested earnings consist of the direct investor's share (in proportion to equity participation) of earnings not distributed by the direct investment enterprise. Reinvested earnings are an imputed transaction. Reinvested earnings are also recorded with opposite sign among FDI income (see below). This recording represents not distributed income as being earned by the direct investor and reinvested in the direct investment enterprise at the same time.Other FDI capital (loans) covers the borrowing and lending of funds, including debt securities and trade credits between direct investors and direct investment enterprises. Debt transactions between affiliated financial intermediaries recorded under direct investment flows are limited to permanent debt. 2) FDI stocks (or positions) denote the value of the investment at the end of the period. FDI stocks are recorded in the International Investment Position. Outward FDI stocks are recorded as assets of the reporting economy, inward FDI stocks as liabilities. Similarly with flows, FDI stocks are broken down by kind of instrument. However, there are only two categories instead of three:Equity capital and reinvested earnings is the value of the own capital of the enterprise, including the value of own reserves that are accumulated from past reinvested earnings. Reserves corresponding to reinvested earnings are not shown separately from other equity capital as in the case of flows.Other FDI capital is the stock of debts (assets or liabilities) between the direct investors and the direct investment enterprise. 3) FDI income is the income accruing to direct investors during the period. FDI income is recorded in the current account of the Balance of Payments. Total FDI income is broken down by kind of income. The categories of FDI income available are linked to the breakdown of FDI flows and stocks by kind of instrument, namely:Dividends Dividends payable in the period and branch profits remitted to the direct investor, gross of any withholding taxes. Dividends include payments due on common and preferred shares.Reinvested earnings See definition under FDI flows.Interest on loans Interest accrued in the period on loans (other FDI capital) with affiliated enterprises, gross of any withholding tax. 4) FDI intensity Out of FDI annual data, an indicator useful to measure EU market integration is also calculated and disseminated in the domain Structural Indicators:FDI intensity as % of GDP: Average of inward and outward FDI flows divided by GDP. A higher index indicates higher new FDI during the period in relation to the size of the economy as measured by GDP. If this index increases over time, then the country/zone is becoming more integrated with the international economy.
  • F
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 сентября, 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 09 октября, 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 below in section 'related metadata'). Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.
    • Август 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 02 сентября, 2019
      Выбрать
      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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 сентября, 2019
      Выбрать
      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.
  • G
    • Февраль 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 04 марта, 2019
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      Eurostat Dataset Id:earn_gr_gpgr2ag The unadjusted Gender Pay Gap (GPG) represents the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees. From reference year 2006 onwards, the new GPG data is based on the methodology of the Structure of Earnings Survey (COUNCIL REGULATION EC No 530/1999 of 9 March 1999 concerning structural statistics on earnings and on labour costs) which is carried out every four years. The most recent available data refers to reference years 2002, 2006 and 2010. Whereas the GPG figures for 2006 and 2010 are directly computed from the 4-yearly SES, for the intermediate years countries provide annual estimates which every 4 years are revised, benchmarked on the SES results in the two respective years. Some countries calculate the annual GPG on a yearly SES and hence their data needs no further adjustment or revisions as the majority of the others. Data are broken down by economic activity (NACE: Statistical Classification of Economic Activities in the European Community), form of economic and financial control (public/private) of the enterprise, working profile (full-time / part-time) and age classes (six age groups) of employees.
    • Февраль 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 04 марта, 2019
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      The unadjusted gender pay gap (GPG) represents the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees. The GPG is calculated on the basis of: - the four-yearly Structure of Earnings Survey (SES) 2002, 2006, 2010, etc., and with the scope as required by the SES regulation,  - national estimates based on national sources for the years between the SES years, from reference year 2007 onwards, with the same coverage as the SES. Data are broken down by economic activity (Statistical Classification of Economic Activities in the European Community - NACE), economic control (public/private) of the enterprise as well as working time (full-time/part-time) and age (six age groups) of employees. Data are released in February/March on the basis of information provided by national statistical institutes.
    • Февраль 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 04 марта, 2019
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      Eurostat Dataset Id:earn_gr_gpgr2wt The unadjusted Gender Pay Gap (GPG) represents the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees. From reference year 2006 onwards, the new GPG data is based on the methodology of the Structure of Earnings Survey (COUNCIL REGULATION EC No 530/1999 of 9 March 1999 concerning structural statistics on earnings and on labour costs) which is carried out every four years. The most recent available data refers to reference years 2002, 2006 and 2010. Whereas the GPG figures for 2006 and 2010 are directly computed from the 4-yearly SES, for the intermediate years countries provide annual estimates which every 4 years are revised, benchmarked on the SES results in the two respective years. Some countries calculate the annual GPG on a yearly SES and hence their data needs no further adjustment or revisions as the majority of the others. Data are broken down by economic activity (NACE: Statistical Classification of Economic Activities in the European Community), form of economic and financial control (public/private) of the enterprise, working profile (full-time / part-time) and age classes (six age groups) of employees.
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 марта, 2019
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      The unadjusted gender pay gap (GPG) represents the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees. The GPG is calculated on the basis of: - the four-yearly Structure of Earnings Survey (SES) 2002, 2006, 2010, etc., and with the scope as required by the SES regulation,  - national estimates based on national sources for the years between the SES years, from reference year 2007 onwards, with the same coverage as the SES. Data are broken down by economic activity (Statistical Classification of Economic Activities in the European Community - NACE), economic control (public/private) of the enterprise as well as working time (full-time/part-time) and age (six age groups) of employees. Data are released in February/March on the basis of information provided by national statistical institutes.
    • Декабрь 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 декабря, 2017
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      The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to provide information on the innovativeness of sectors by type of enterprises, on the different types of innovation and on various aspects of the development of an innovation, such as objectives, sources of information, public funding or expenditures. The CIS provides statistics broken down by countries, types of innovators, economic activities and size classes. The survey is currently carried out every two years across the European Union, EFTA countries and EU candidate countries. In order to ensure comparability across countries, Eurostat together with the countries developed a standard core questionnaire (see in Annex) accompanied by a set of definitions and methodological recommendations. CIS 2014 concepts and its underlying methodology are also based on the Oslo Manual (2005) 3rd edition (see link at the bottom of the page). CIS 2014 results were collected under Commission Regulation No 995/2012. This Regulation defines the mandatory target population of the survey referring to enterprises in the Core NACE categories (see section 3.3.) with at least 10 employees. Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period 2012-2014, but some use only one calendar year (2012 or 2014). CIS 2014 includes an ad-hoc module on innovations with environmental benefits. While European innovation statistics use aggregated national data, the microdata sets can be consulted by researchers via the SAFE Centre of Eurostat in Luxembourg or via CD-ROM releases in a more anonymised form; some countries also provide access to their microdata through national Safe Centres. Since the provision of microdata is voluntary, microdatasets do not cover all countries.
    • Июнь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 21 июня, 2019
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      On the basis of the Regulation on waste statistics (EC) No. 2150/2002, amended by Commission Regulation (EU) No. 849/2010, data on the generation and treatment of waste is collected from the Member States. The information on waste generation has a breakdown in sources (19 business activities according to the NACE classification and household activities) and in waste categories (according to the European Waste Classification for statistical purposes). The information on waste treatment is broken down to five treatment types (recovery, incineration with energy recovery, other incineration, disposal on land and land treatment) and in waste categories. All values are measured in tonnes of waste and in kg per capita, based on the annual average of the population. The Member States are free to decide on the data collection methods. The general options are: surveys, administrative sources, statistical estimations or some combination of methods. For the first reference year 2004 Member States could apply for permission not to deliver part of the information: waste generated by agriculture and fishing and waste generated in the services sector. For this reason this information is missing for some of the countries. Previously data on waste was collected on a voluntary basis with the joint OECD/Eurostat questionnaire on waste.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 17 октября, 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.
  • H
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 14 октября, 2019
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      The annual Business demography data collection covers variables which explain the characteristics and demography of the business population. The methodology allows for the production of data on enterprise births (and deaths), that is, enterprise creations (cessations) that amount to the creation (dissolution) of a combination of production factors and where no other enterprises are involved. In other words, enterprises created or closed solely as a result of e.g. restructuring, merger or break-up are not considered. The data are drawn from business registers, although some countries improve the availability of data on employment and turnover by integrating other sources. Until 2010 reference year the harmonised data collection is carried out to satisfy the requirements for the Structural Indicators, used for monitoring progress of the Lisbon process, regarding business births, deaths and survival. Currently, business demography delivers key information for policy decision-making and for the indicators to support the Europe 2020 strategy. It also provides key data for the joint OECD-Eurostat "Entrepreneurship Indicators Programme". In summary, the collected indicators are as follows: Population of active enterprisesNumber of enterprise birthsNumber of enterprise survivals up to five yearsNumber of enterprise deathsRelated variables on employmentDerived indicators such as birth rates, death rates, survival rates and employment sharesAn additional set of indicators on high-growth enterprises and 'gazelles' (high-growth enterprises that are up to five years old) The complete list of the basic variables, delivered from the data providers (National Statistical Institutes) and the derived indicators, calculated by Eurostat, is attached in the Annexes of this document.  Geographically EU Member States and EFTA countries are covered. In practice not all Member States have participated in the first harmonised data collection exercises. The methodology laid down in the Eurostat-OECD Manual on Business Demography Statistics  is followed closely by most of the countries (see Country specific notes in the Annexes).
    • Июль 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 06 июля, 2019
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      Accommodation statistics are a key part of the system of tourism statistics in the EU and have a long history of data collection. Annex I of the Regulation (EU) 692/2011 of the European Parliament and of the Council deals with accommodation statistics and includes 4 sections focusing on accommodation statistics of which sections 1 and 2 include the requirements concerning rented accommodation (capacity and occupancy respectively). Data are collected by the competent national authorities of the Member States and are compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Most of the time, data are collected via sample or census surveys. However, in a few cases data are compiled from a demand-side perspective (i.e. via visitor surveys or border surveys). Surveys on the occupancy of accommodation establishments are generally conducted on a monthly basis. The concepts and definitions used in the collection of data shall conform to the specifications described in the Methodological manual for tourism statistics. Accommodation statistics comprise the following information: Monthly data on tourism industries (NACE 55.1, 55.2 and 55.3) Monthly occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Net occupancy rate of bed-places and bedrooms in hotels and similar accommodation Annual data on tourism industries(NACE 55.1, 55.2 and 55.3) Occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Capacity of tourist accommodation establishments: number of establishments, bedrooms and bed places Regional data  Annual occupancy (arrivals and nights spent by residents and non-residents) of tourist accommodation establishments at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Annual data on number of establishments, bedrooms and bed places at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Data on number of establishments, bedrooms and bed places are available by activity at NUTS 3 level until 2011. 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.
    • Март 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 июня, 2014
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      Eurostat Dataset Id:lc_n08hour_r2 Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Structural information on labour costs is collected through four-yearly Labour Cost Surveys (LCSs), which provides details on level and structure of labour cost data, hours worked and hours paid. LCS results are available for the reference years 2000, 2004 and 2008. All EU Member States together with Norway, Iceland and Croatia (2004, 2008), Turkey and Macedonia (2008) 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 (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 (if different) and Purchasing Power Standards (PPS). Labour costs are quoted in total and per year, per month and per hour, as well as per capita and per full-time equivalents (FTE). Information on staff, hours worked and hours paid is quoted in aggregate and separately for full- and part-time employees. Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 02 октября, 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.
  • I
    • Декабрь 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 декабря, 2017
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      The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to provide information on the innovativeness of sectors by type of enterprises, on the different types of innovation and on various aspects of the development of an innovation, such as objectives, sources of information, public funding or expenditures. The CIS provides statistics broken down by countries, types of innovators, economic activities and size classes. The survey is currently carried out every two years across the European Union, EFTA countries and EU candidate countries. In order to ensure comparability across countries, Eurostat together with the countries developed a standard core questionnaire (see in Annex) accompanied by a set of definitions and methodological recommendations. CIS 2014 concepts and its underlying methodology are also based on the Oslo Manual (2005) 3rd edition (see link at the bottom of the page). CIS 2014 results were collected under Commission Regulation No 995/2012. This Regulation defines the mandatory target population of the survey referring to enterprises in the Core NACE categories (see section 3.3.) with at least 10 employees. Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period 2012-2014, but some use only one calendar year (2012 or 2014). CIS 2014 includes an ad-hoc module on innovations with environmental benefits. While European innovation statistics use aggregated national data, the microdata sets can be consulted by researchers via the SAFE Centre of Eurostat in Luxembourg or via CD-ROM releases in a more anonymised form; some countries also provide access to their microdata through national Safe Centres. Since the provision of microdata is voluntary, microdatasets do not cover all countries.
    • Август 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 01 сентября, 2017
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      The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to provide information on the innovativeness of sectors by type of enterprises, on the different types of innovation and on various aspects of the development of an innovation, such as objectives, sources of information, public funding or expenditures. The CIS provides statistics broken down by countries, types of innovators, economic activities and size classes. The survey is currently carried out every two years across the European Union, EFTA countries and EU candidate countries. In order to ensure comparability across countries, Eurostat together with the countries developed a standard core questionnaire (see in Annex) accompanied by a set of definitions and methodological recommendations. CIS 2014 concepts and its underlying methodology are also based on the Oslo Manual (2005) 3rd edition (see link at the bottom of the page). CIS 2014 results were collected under Commission Regulation No 995/2012. This Regulation defines the mandatory target population of the survey referring to enterprises in the Core NACE categories (see section 3.3.) with at least 10 employees. Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period 2012-2014, but some use only one calendar year (2012 or 2014). CIS 2014 includes an ad-hoc module on innovations with environmental benefits. While European innovation statistics use aggregated national data, the microdata sets can be consulted by researchers via the SAFE Centre of Eurostat in Luxembourg or via CD-ROM releases in a more anonymised form; some countries also provide access to their microdata through national Safe Centres. Since the provision of microdata is voluntary, microdatasets do not cover all countries.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 17 октября, 2019
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      Industry, Trade and Services statistics are part of Short-term statistics (STS), they give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification (Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are presented in the following forms: UnadjustedCalendar adjustedSeasonally-adjusted Depending on the STS regulation, data are accessible monthly and quarterly. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction (volume)*Turnover: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic turnover into euro area and non euro area is available for the euro area countriesProducer prices (output prices)*: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic producer prices into euro area and non euro area is available for the euro area countriesImport prices*: Total, Euro area market, Non euro area market (euro area countries only)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries CONSTRUCTIONProduction (volume)*: Total of the construction sector, Building construction, Civil EngineeringLabour input indicators: Number of Persons Employed, Hours Worked, Gross Wages and SalariesConstruction costs IndexBuilding permits indicators*: Number of dwellings WHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (in value)Labour input indicators: Number of Persons Employed SERVICES Turnover (in value)*Producer prices (Ouput prices)*
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 октября, 2019
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      Industry, Trade and Services statistics are part of Short-term statistics (STS), they give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification(Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are presented in the following forms:UnadjustedCalendar adjustedSeasonally-adjusted Depending on the STS regulation, data are accessible monthly and quarterly. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction Index*Turnover IndexProducer Prices (Domestic Output Prices index)*Import Prices Index*: Total, Euro area market, Non euro area market (euro area countries only)Labour Input Indicators: Number of Persons Employed, Hours Worked, Gross Wages and Salaries CONSTRUCTIONProduction Index*: Total of the construction sector, Building construction, Civil EngineeringLabour input indicators: Number of Persons Employed, Hours Worked, Gross Wages and SalariesConstruction costs IndexBuilding permits indicators*: Number of dwellings WHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (in value)Labour input indicators: Number of Persons Employed SERVICES Turnover Index*Producer prices (Ouput prices)*
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 октября, 2019
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      Eurostat Dataset Id:sbs_sc_ind_r2 SBS covers the Nace Rev.2 Section B to N and division S95 which are organized in four annexes, covering Industry (sections B-E), Construction (F), Trade (G) and Services (H, I, J, L, M, N and S95). Financial services are covered in three specific annexes and separate metadata files have been compiled. Up to reference year 2007 data was presented using the NACE Rev.1.1 classification. The SBS coverage was limited to NACE Rev.1.1 Sections C to K. Starting from the reference year 2008 data is available in NACE Rev.2. Double reported data in NACE Rev.1.1 for the reference year 2008 will be available in the first and second quarter of 2011. 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) Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. 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' in NACE Rev 1.1 sections H, I, K 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 Rev2 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 for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 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 N°1614/2002 and N°1669/2003. SBS data are collected primarily by National Statistical Institutes (NSI). Regulatory or controlling national offices for financial institutions or central banks often provides the information required for the financial sector (NACE Rev 2 Section K / NACE  Rev 1.1 Section J). 
    • Сентябрь 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 декабря, 2015
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    • Май 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 мая, 2016
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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)
    • Май 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 23 мая, 2016
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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)
    • Декабрь 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 декабря, 2017
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      The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to provide information on the innovativeness of sectors by type of enterprises, on the different types of innovation and on various aspects of the development of an innovation, such as objectives, sources of information, public funding or expenditures. The CIS provides statistics broken down by countries, types of innovators, economic activities and size classes. The survey is currently carried out every two years across the European Union, EFTA countries and EU candidate countries. In order to ensure comparability across countries, Eurostat together with the countries developed a standard core questionnaire (see in Annex) accompanied by a set of definitions and methodological recommendations. CIS 2014 concepts and its underlying methodology are also based on the Oslo Manual (2005) 3rd edition (see link at the bottom of the page). CIS 2014 results were collected under Commission Regulation No 995/2012. This Regulation defines the mandatory target population of the survey referring to enterprises in the Core NACE categories (see section 3.3.) with at least 10 employees. Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period 2012-2014, but some use only one calendar year (2012 or 2014). CIS 2014 includes an ad-hoc module on innovations with environmental benefits. While European innovation statistics use aggregated national data, the microdata sets can be consulted by researchers via the SAFE Centre of Eurostat in Luxembourg or via CD-ROM releases in a more anonymised form; some countries also provide access to their microdata through national Safe Centres. Since the provision of microdata is voluntary, microdatasets do not cover all countries.
    • Май 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 23 мая, 2016
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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)
  • J
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 17 сентября, 2019
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      The job vacancy rate (JVR) measures the proportion of total posts that are vacant, according to the definition of job vacancy above, expressed as a percentage as follows: JVR = number of job vacancies / (number of occupied posts + number of job vacancies) * 100. Job vacancy rates for DK, FR, IT and MT are probably under-estimated due to a partial coverage of the respective economies.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 сентября, 2019
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      This domain includes national statistics on the number of job vacancies, number of occupied jobs and job vacancy rates in the enterprises belonging to NACE, the European classification of economic activities. NACE Rev. 2 sections A to S and divisions 87 and 88 are covered. Activities of households, and extra-territorial organisations and bodies are excluded. The longest time series are available for the UK (from 2001). All countries are available from 2010, when the JVS regulation came into force. EU aggregates are also avaiable from here. Most countries base their JVS on business surveys. Data are published quarterly, with a flash release around 50 days after the end of the quarter and a news release around 80 days after the end of the quarter.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 сентября, 2019
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      Job vacancy statistics (JVS) provide information on the level and structure of labour demand. Eurostat publishes quarterly data on the number of job vacancies and the number of occupied posts which are collected under the JVS framework regulation and the two implementing regulations: the implementing regulation on the definition of a job vacancy, the reference dates for data collection, data transmission specifications and feasibility studies, as well as the implementing regulation on seasonal adjustment procedures and quality reports. Eurostat disseminates also the job vacancy rate which is calculated on the basis of the data provided by the countries. Eurostat publishes also the annual data which are calculated on the basis of the quarterly data.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 сентября, 2019
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      The Human Resources in Science and Technology (HRST) domain provides data on stocks and flows (where flows in turn are divided into job-to-job mobility and education inflows). Stocks and flows are the main statistics for HRST. Their methodologies interlink and are therefore presented together in one single metadata-file. This metadata-file is duplicated in the structure of Eurostat's online database, while statistics for stocks and flows are found in separate folders. Several breakdowns are available for stocks and flows indicators: sex, age, region, sector of economic activity, occupation, educational attainment, fields of education, although not all combinations are possible. The data on stocks and job-to-job mobility are obtained from the European Union Labour Force Survey (EU LFS). The National Statistical Institutes are responsible for conducting the surveys and forwarding the results to Eurostat. The data on education inflows are obtained from Eurostat's Education database and in turn obtained via the UNESCO/OECD/Eurostat questionnaire on education. The National Statistical Institutes are responsible for conducting the surveys, compiling the results and forwarding the results to Eurostat. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.
  • L
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 19 сентября, 2019
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      Labour cost index shows the short-term development of the total cost, on an hourly basis, for employers of employing the labour force. The index covers all market economic activities except agriculture, forestry, fisheries, education, health, community, social and personal service activities. Labour costs include gross wages and salaries, employers social contributions and taxes net of subsidies connected to employment. The labour cost index is compiled as a "chain-linked Laspeyres cost-index" using a common index reference period (2012 = 100). The index is presented in calendar and seasonally adjusted form. Growth rates with respect to the previous quarter (Q/Q-1) are calculated from seasonally and calendar adjusted figures while growth rates with respect to the same quarter of the previous year (Q/Q-4) are calculated from calendar adjusted figures.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 19 сентября, 2019
      Выбрать
      Labour cost index shows the short-term development of the total cost, on an hourly basis, for employers of employing the labour force. The index covers all market economic activities except agriculture, forestry, fisheries, education, health, community, social and personal service activities. Labour costs include gross wages and salaries, employers social contributions and taxes net of subsidies connected to employment. The labour cost index is compiled as a "chain-linked Laspeyres cost-index" using a common index reference period (2012 = 100). The index is presented in calendar and seasonally adjusted form. Growth rates with respect to the previous quarter (Q/Q-1) are calculated from seasonally and calendar adjusted figures while growth rates with respect to the same quarter of the previous year (Q/Q-4) are calculated from calendar adjusted figures.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 14 сентября, 2019
      Выбрать
      Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. The quarterly Labour Cost Index (LCI) is a Euro Indicator which measures the cost pressure arising from the production factor "labour". The data covered in the LCI collection relate to total average hourly labour costs and to the labour cost categories "wages and salaries" and "employers' social security contributions plus taxes paid minus subsidies received by the employer". Data - also broken down by economic activity, are available for the EU aggregates and EU Member States (NACE Rev 1.1 Sections C to K (1996Q1-2008Q4) and NACE Rev 2 Sections B to S), in working day and seasonally adjusted form. The data on the Labour Cost Index are given in the form of index numbers (current reference year: 2012) and of annual and quarterly growth rates (comparison with the previous quarter, or the same quarter of the previous year). On annual basis the labour cost levels (in Euro and national currency) are also published, based on the latest Labour Cost Survey inflated by the LCI. In contrast to the information collected for the other Labour Cost domains, the labour costs covered in the LCI do not include vocational training costs and other expenditure such as recruitment costs and working clothes expenditure. The data are estimated by the National Statistical Institutes on the basis of available structural and short-term information from samples and administrative records for enterprises of all sizes. The labour cost index (LCI) shows the short-term development of the labour cost, the total cost on an hourly basis of employing labour. In other words, the LCI measures the cost pressure arising from the production factor “labour”.  In addition, Eurostat estimates of the annual labour cost per hour in euros are provided for EU Member States as well as the whole EU; they were obtained by combining the four-yearly Labour cost survey (LCS) with the quarterly labour cost index. 
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 14 сентября, 2019
      Выбрать
      Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. The quarterly Labour Cost Index (LCI) is a Euro Indicator which measures the cost pressure arising from the production factor "labour". The data covered in the LCI collection relate to total average hourly labour costs and to the labour cost categories "wages and salaries" and "employers' social security contributions plus taxes paid minus subsidies received by the employer". Data - also broken down by economic activity, are available for the EU aggregates and EU Member States (NACE Rev 1.1 Sections C to K (1996Q1-2008Q4) and NACE Rev 2 Sections B to S), in working day and seasonally adjusted form. The data on the Labour Cost Index are given in the form of index numbers (current reference year: 2012) and of annual and quarterly growth rates (comparison with the previous quarter, or the same quarter of the previous year). On annual basis the labour cost levels (in Euro and national currency) are also published, based on the latest Labour Cost Survey inflated by the LCI. In contrast to the information collected for the other Labour Cost domains, the labour costs covered in the LCI do not include vocational training costs and other expenditure such as recruitment costs and working clothes expenditure. The data are estimated by the National Statistical Institutes on the basis of available structural and short-term information from samples and administrative records for enterprises of all sizes. The labour cost index (LCI) shows the short-term development of the labour cost, the total cost on an hourly basis of employing labour. In other words, the LCI measures the cost pressure arising from the production factor “labour”.  In addition, Eurostat estimates of the annual labour cost per hour in euros are provided for EU Member States as well as the whole EU; they were obtained by combining the four-yearly Labour cost survey (LCS) with the quarterly labour cost index. 
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 23 сентября, 2019
      Выбрать
      Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. The quarterly Labour Cost Index (LCI) is a Euro Indicator which measures the cost pressure arising from the production factor "labour". The data covered in the LCI collection relate to total average hourly labour costs and to the labour cost categories "wages and salaries" and "employers' social security contributions plus taxes paid minus subsidies received by the employer". Data - also broken down by economic activity, are available for the EU aggregates and EU Member States (NACE Rev 1.1 Sections C to K (1996Q1-2008Q4) and NACE Rev 2 Sections B to S), in working day and seasonally adjusted form. The data on the Labour Cost Index are given in the form of index numbers (current base year: 2016) and of annual and quarterly growth rates (comparison with the previous quarter, or the same quarter of the previous year). On annual basis the labour cost levels (in Euro and national currency) are also published, based on the latest Labour Cost Survey inflated by the LCI. In contrast to the information collected for the other Labour Cost domains, the labour costs covered in the LCI do not include vocational training costs and other expenditure such as recruitment costs and working clothes expenditure. The data are estimated by the National Statistical Institutes on the basis of available structural and short-term information from samples and administrative records for enterprises of all sizes. The labour cost index (LCI) shows the short-term development of the labour cost, the total cost on an hourly basis of employing labour. In other words, the LCI measures the cost pressure arising from the production factor “labour”.  In addition, Eurostat estimates of the annual labour cost per hour in euros are provided for EU Member States as well as the whole EU; they were obtained by combining the four-yearly Labour cost survey (LCS) with the quarterly labour cost index. 
    • Июнь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 19 июня, 2019
      Выбрать
      Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. The labour cost levels are based on the latest Labour Cost Survey (currently 2012) and an extrapolation based on the quarterly Labour Cost Index (LCI). The levels are available in euro and national currency. The Labour Cost Survey is a four-yearly survey that collects levels of labour costs at a very detailed level. For the purpose of extrapolating with the LCI, data are only used at a very aggregated level. The quarterly LCI is a Euro Indicator which measures the cost pressure arising from the production factor "labour". The data covered in the LCI collection relate to total average hourly labour costs and to the labour cost categories "wages and salaries" and "employers' social security contributions plus taxes paid minus subsidies received by the employer". Data - also broken down by economic activity, are available for the EU aggregates and EU Member States (NACE Rev 2 Sections B to S), in working day and seasonally adjusted form. The data on the Labour Cost Index are given in the form of index numbers (current reference year: 2012) and of annual and quarterly growth rates (comparison with the previous quarter, or the same quarter of the previous year). The data are estimated by the National Statistical Institutes on the basis of available structural and short-term information from samples and administrative records for enterprises of all sizes.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 02 октября, 2019
      Выбрать
      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.
    • Август 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 июня, 2014
      Выбрать
      Eurostat Dataset Id:lc_n08costot_r2 Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Structural information on labour costs is collected through four-yearly Labour Cost Surveys (LCSs), which provides details on level and structure of labour cost data, hours worked and hours paid. LCS results are available for the reference years 2000, 2004 and 2008. All EU Member States together with Norway, Iceland and Croatia (2004, 2008), Turkey and Macedonia (2008) 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 (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 (if different) and Purchasing Power Standards (PPS). Labour costs are quoted in total and per year, per month and per hour, as well as per capita and per full-time equivalents (FTE). Information on staff, hours worked and hours paid is quoted in aggregate and separately for full- and part-time employees. Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 02 октября, 2019
      Выбрать
      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.
    • Ноябрь 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 01 июля, 2014
      Выбрать
      Eurostat Dataset Id:lc_an_cost_r2 Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Annual labour cost data published here cover the core labour cost variables "average hourly labour costs" and "average monthly labour costs" as well as the breakdown of labour costs by main categories (wages and salaries; other labour costs). Average hourly and monthly labour costs as well as the structure of total annual labour costs per employee by economic activity are provided for enterprises with 1+ and for enterprises with 10+ employees.Data  are available for the EU Member States and partly for Iceland and Switzerland. The data are either collected by the National Statistical Institutes or, more frequently, estimated by them on the basis of their four-yearly Labour Cost Surveys (LCS), the Labour Cost Index (LCI) and additional up-to-date - though sometimes partial - information. Coverage of statistical units, thresholds and other methodological aspects are identical to that of the four yearly LCS.
    • Июнь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 19 июня, 2019
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      This table contains data on Average hourly labour costs which are defined as total labour costs divided by the corresponding number of hours worked by the yearly average number of employees, expressed in full-time units." Labour Costs (D) cover Wages and Salaries (D11) and non-wage costs (Employers’ social contributions plus taxes less subsidies: D12+D4-D5)
  • M
    • Январь 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 февраля, 2017
      Выбрать
      The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data. The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 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.
    • Август 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 августа, 2017
      Выбрать
      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.
    • Февраль 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 февраля, 2016
      Выбрать
      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.
    • Август 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 августа, 2017
      Выбрать
      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.
    • Январь 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 04 февраля, 2017
      Выбрать
      The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data. The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 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.
    • Август 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 09 августа, 2017
      Выбрать
      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.
    • Январь 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 февраля, 2017
      Выбрать
      The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data. The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 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.
    • Август 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 09 августа, 2017
      Выбрать
      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.
    • Февраль 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 февраля, 2016
      Выбрать
      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.
    • Август 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 августа, 2017
      Выбрать
      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.
    • Июнь 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 июня, 2016
      Выбрать
      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.
    • Август 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 09 августа, 2017
      Выбрать
      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.
    • Июнь 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 июня, 2016
      Выбрать
      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.
    • Август 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 09 августа, 2017
      Выбрать
      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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 октября, 2019
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      SBS series on Intangible investment and subcontracting in industry are closely related to other SBS domains for which separate metadata files have been compiled (See annex at the bottom of the page). They cover the NACE Rev 1.1 sections C to F. The information has been collected once every three years. A few characteristics on Intangible investment and subcontracting have been defined. 15 42 0 Gross investment in concessions, patents, licences and trade marks and similar rights 15 44 1 Investment in purchased software 15 44 2 Investment in software produced by the enterprise (optional) 23 11 0 Payments to subcontractors 23 12 0 Income from subcontracting (only required for construction - NACE Rev 1.1 section F) For Industry (NACE C-E) the breakdown is detailed to the NACE class level (4-digits). For Construction (NACE F) intangible investments are collected only on NACE group level (3-digits), whereas payments to and income from subcontracting are detailed on NACE class level.
  • N
    • Июль 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 09 июля, 2019
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      Accommodation statistics are a key part of the system of tourism statistics in the EU and have a long history of data collection. Annex I of the Regulation (EU) 692/2011 of the European Parliament and of the Council deals with accommodation statistics and includes 4 sections focusing on accommodation statistics of which sections 1 and 2 include the requirements concerning rented accommodation (capacity and occupancy respectively). Data are collected by the competent national authorities of the Member States and are compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Most of the time, data are collected via sample or census surveys. However, in a few cases data are compiled from a demand-side perspective (i.e. via visitor surveys or border surveys). Surveys on the occupancy of accommodation establishments are generally conducted on a monthly basis. The concepts and definitions used in the collection of data shall conform to the specifications described in the Methodological manual for tourism statistics. Accommodation statistics comprise the following information: Monthly data on tourism industries (NACE 55.1, 55.2 and 55.3) Monthly occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Net occupancy rate of bed-places and bedrooms in hotels and similar accommodation Annual data on tourism industries(NACE 55.1, 55.2 and 55.3) Occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Capacity of tourist accommodation establishments: number of establishments, bedrooms and bed places Regional data  Annual occupancy (arrivals and nights spent by residents and non-residents) of tourist accommodation establishments at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Annual data on number of establishments, bedrooms and bed places at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Data on number of establishments, bedrooms and bed places are available by activity at NUTS 3 level until 2011. 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 октября, 2019
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      The occupancy rate of bed places in reference period is obtained by dividing the total number of overnight stays by the number of the bed places on offer (excluding extra beds) and the number of days when the bed places are actually available for use (net of seasonal closures and other temporary closures). The result is multiplied by 100 to express the occupancy rate as a percentage. The occupancy rate of bedrooms in reference period is obtained by dividing the total number of bedrooms used during the reference period (i.e. the sum of the bedrooms in use per day) by the total number of bedrooms available for the reference period (i.e. the sum of bedrooms available per day). The result is multiplied by 100 to express the occupancy rate as a percentage. Both variables concern establishments classified as NACE 55.1 only.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 октября, 2019
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      Accommodation statistics are a key part of the system of tourism statistics in the EU and have a long history of data collection. Annex I of the Regulation (EU) 692/2011 of the European Parliament and of the Council deals with accommodation statistics and includes 4 sections focusing on accommodation statistics of which sections 1 and 2 include the requirements concerning rented accommodation (capacity and occupancy respectively). Data are collected by the competent national authorities of the Member States and are compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Most of the time, data are collected via sample or census surveys. However, in a few cases data are compiled from a demand-side perspective (i.e. via visitor surveys or border surveys). Surveys on the occupancy of accommodation establishments are generally conducted on a monthly basis. The concepts and definitions used in the collection of data shall conform to the specifications described in the Methodological manual for tourism statistics. Accommodation statistics comprise the following information: Monthly data on tourism industries (NACE 55.1, 55.2 and 55.3) Monthly occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Net occupancy rate of bed-places and bedrooms in hotels and similar accommodation Annual data on tourism industries(NACE 55.1, 55.2 and 55.3) Occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Capacity of tourist accommodation establishments: number of establishments, bedrooms and bed places Regional data  Annual occupancy (arrivals and nights spent by residents and non-residents) of tourist accommodation establishments at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Annual data on number of establishments, bedrooms and bed places at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Data on number of establishments, bedrooms and bed places are available by activity at NUTS 3 level until 2011. 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 октября, 2019
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      Accommodation statistics are a key part of the system of tourism statistics in the EU and have a long history of data collection. Annex I of the Regulation (EU) 692/2011 of the European Parliament and of the Council deals with accommodation statistics and includes 4 sections focusing on accommodation statistics of which sections 1 and 2 include the requirements concerning rented accommodation (capacity and occupancy respectively). Data are collected by the competent national authorities of the Member States and are compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Most of the time, data are collected via sample or census surveys. However, in a few cases data are compiled from a demand-side perspective (i.e. via visitor surveys or border surveys). Surveys on the occupancy of accommodation establishments are generally conducted on a monthly basis. The concepts and definitions used in the collection of data shall conform to the specifications described in the Methodological manual for tourism statistics. Accommodation statistics comprise the following information: Monthly data on tourism industries (NACE 55.1, 55.2 and 55.3) Monthly occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Net occupancy rate of bed-places and bedrooms in hotels and similar accommodation Annual data on tourism industries(NACE 55.1, 55.2 and 55.3) Occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Capacity of tourist accommodation establishments: number of establishments, bedrooms and bed places Regional data  Annual occupancy (arrivals and nights spent by residents and non-residents) of tourist accommodation establishments at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Annual data on number of establishments, bedrooms and bed places at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Data on number of establishments, bedrooms and bed places are available by activity at NUTS 3 level until 2011. 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.
    • Июль 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 19 июля, 2019
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      The occupancy rate of bed places in reference period is obtained by dividing the total number of overnight stays by the number of the bed places on offer (excluding extra beds) and the number of days when the bed places are actually available for use (net of seasonal closures and other temporary closures). The result is multiplied by 100 to express the occupancy rate as a percentage. The occupancy rate of bedrooms in reference period is obtained by dividing the total number of bedrooms used during the reference period (i.e. the sum of the bedrooms in use per day) by the total number of bedrooms available for the reference period (i.e. the sum of bedrooms available per day). The result is multiplied by 100 to express the occupancy rate as a percentage. Both variables concern establishments classified as NACE 55.1 only.
    • Июль 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 06 июля, 2019
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      Accommodation statistics are a key part of the system of tourism statistics in the EU and have a long history of data collection. Annex I of the Regulation (EU) 692/2011 of the European Parliament and of the Council deals with accommodation statistics and includes 4 sections focusing on accommodation statistics of which sections 1 and 2 include the requirements concerning rented accommodation (capacity and occupancy respectively). Data are collected by the competent national authorities of the Member States and are compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Most of the time, data are collected via sample or census surveys. However, in a few cases data are compiled from a demand-side perspective (i.e. via visitor surveys or border surveys). Surveys on the occupancy of accommodation establishments are generally conducted on a monthly basis. The concepts and definitions used in the collection of data shall conform to the specifications described in the Methodological manual for tourism statistics. Accommodation statistics comprise the following information: Monthly data on tourism industries (NACE 55.1, 55.2 and 55.3) Monthly occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Net occupancy rate of bed-places and bedrooms in hotels and similar accommodation Annual data on tourism industries(NACE 55.1, 55.2 and 55.3) Occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Capacity of tourist accommodation establishments: number of establishments, bedrooms and bed places Regional data  Annual occupancy (arrivals and nights spent by residents and non-residents) of tourist accommodation establishments at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Annual data on number of establishments, bedrooms and bed places at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Data on number of establishments, bedrooms and bed places are available by activity at NUTS 3 level until 2011. 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.
    • Апрель 2018
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 11 апреля, 2018
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      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).
    • Май 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 мая, 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
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 26 сентября, 2019
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      The number of bed places in a tourist accommodation establishment is determined by the number of persons who can stay overnight in the beds set up in the establishment, ignoring any extra beds that may be set up upon customer request. The term bed place applies to a single bed; a double bed is counted as two bed places. A bed place is also a place on a pitch or on a mooring in a boat to accommodate one person. One pitch for camping/tent, caravan or similar shelter and one mooring for boat should be counted for 4 bed places if the actual number of bed places is not known.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 июня, 2014
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      Eurostat Dataset Id:earn_gr_empnac2 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.
    • Февраль 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 февраля, 2016
      Выбрать
      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.
    • Август 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 августа, 2017
      Выбрать
      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.
    • Март 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 01 июля, 2014
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      Eurostat Dataset Id:lc_n08num1_r2 Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Structural information on labour costs is collected through four-yearly Labour Cost Surveys (LCSs), which provides details on level and structure of labour cost data, hours worked and hours paid. LCS results are available for the reference years 2000, 2004 and 2008. All EU Member States together with Norway, Iceland and Croatia (2004, 2008), Turkey and Macedonia (2008) 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 (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 (if different) and Purchasing Power Standards (PPS). Labour costs are quoted in total and per year, per month and per hour, as well as per capita and per full-time equivalents (FTE). Information on staff, hours worked and hours paid is quoted in aggregate and separately for full- and part-time employees. Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 02 октября, 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.
    • Март 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 09 июля, 2014
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      Eurostat Dataset Id:lc_n08num2_r2 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.
    • Март 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 июня, 2014
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      Eurostat Dataset Id:lc_n08stu_r2 Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Structural information on labour costs is collected through four-yearly Labour Cost Surveys (LCSs), which provides details on level and structure of labour cost data, hours worked and hours paid. LCS results are available for the reference years 2000, 2004 and 2008. All EU Member States together with Norway, Iceland and Croatia (2004, 2008), Turkey and Macedonia (2008) 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 (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 (if different) and Purchasing Power Standards (PPS). Labour costs are quoted in total and per year, per month and per hour, as well as per capita and per full-time equivalents (FTE). Information on staff, hours worked and hours paid is quoted in aggregate and separately for full- and part-time employees. Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 02 октября, 2019
      Выбрать
      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.
  • O
    • Декабрь 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 декабря, 2017
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      The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to provide information on the innovativeness of sectors by type of enterprises, on the different types of innovation and on various aspects of the development of an innovation, such as objectives, sources of information, public funding or expenditures. The CIS provides statistics broken down by countries, types of innovators, economic activities and size classes. The survey is currently carried out every two years across the European Union, EFTA countries and EU candidate countries. In order to ensure comparability across countries, Eurostat together with the countries developed a standard core questionnaire (see in Annex) accompanied by a set of definitions and methodological recommendations. CIS 2014 concepts and its underlying methodology are also based on the Oslo Manual (2005) 3rd edition (see link at the bottom of the page). CIS 2014 results were collected under Commission Regulation No 995/2012. This Regulation defines the mandatory target population of the survey referring to enterprises in the Core NACE categories (see section 3.3.) with at least 10 employees. Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period 2012-2014, but some use only one calendar year (2012 or 2014). CIS 2014 includes an ad-hoc module on innovations with environmental benefits. While European innovation statistics use aggregated national data, the microdata sets can be consulted by researchers via the SAFE Centre of Eurostat in Luxembourg or via CD-ROM releases in a more anonymised form; some countries also provide access to their microdata through national Safe Centres. Since the provision of microdata is voluntary, microdatasets do not cover all countries.
  • P
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 октября, 2019
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      Lifelong learning encompasses all learning activities undertaken throughout life (after the end of initial education) with the aim of improving knowledge, skills and competences, within personal, civic, social or employment-related perspectives. The intention or aim to learn is the critical point that distinguishes these activities from non-learning activities, such as cultural or sporting activities. Participation in education and training is a measure of lifelong learning. The participation rate in education and training covers participation in formal and non-formal education and training. The reference period for the participation in education and training is the four weeks prior to the interview. Participation rates in education and training for various age groups and by different breakdowns are presented. The data shown are calculated as annual averages of quarterly EU Labour Force Survey data (EU-LFS). The strategic framework for European cooperation in education and training sets a benchmark on adult participation in lifelong learning, namely that an average of at least 15 % of adults aged 25 to 64 years old should participate in lifelong learning. Accordingly, the indicator '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'. For data see online table trng_lfse_01 and tsdsc440. For data published in the folder 'Main indicators on lifelong learning - LFS data from 1992 onwards (trng_lfs_4w0)' the data source (EU-LFS) is up to the reference year 2008, 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. Tables shown in the following folders are not adjusted and therefore the results in these tables might differ.Participation in education and training (last 4 weeks) - population aged 18+ (trng_lfs_4w1)Participation in education and training (last 4 weeks) - employed persons aged 18+ (trng_lfs_4w2)Participation in education and training (last 4 weeks) - population aged 15+, by type of education (trng_lfs_4w3)
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 марта, 2019
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      Patents reflect a country's inventive activity. Patents also show the country's capacity to exploit knowledge and translate it into potential economic gains. In this context, indicators based on patent statistics are widely used to assess the inventive performance of countries. This domain provides users with data concerning patent applications to the European Patent Office - EPO, patents granted by the United States Patent and Trademark Office - USPTO and triadic patent families. EPO data refer to all patent applications by priority year as opposed to patents granted by priority year, which is the case of USPTO data.Patents reflect a country's inventive activity. Patents also show the country's capacity to exploit knowledge and translate it into potential economic gains. In this context, indicators based on patent statistics are widely used to assess the inventive performance of countries.
    • Январь 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 января, 2017
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      Patents reflect a country's inventive activity. Patents also show the country's capacity to exploit knowledge and translate it into potential economic gains. In this context, indicators based on patent statistics are widely used to assess the inventive performance of countries. This domain provides users with data concerning patent applications to the European Patent Office - EPO, patents granted by the United States Patent and Trademark Office - USPTO and triadic patent families. EPO data refer to all patent applications by priority year as opposed to patents granted by priority year, which is the case of USPTO data.Patents reflect a country's inventive activity. Patents also show the country's capacity to exploit knowledge and translate it into potential economic gains. In this context, indicators based on patent statistics are widely used to assess the inventive performance of countries.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 октября, 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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 сентября, 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 17 октября, 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.
    • Май 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 20 мая, 2016
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      The objective of these data is to provide information for benchmarking and monitoring developments in ICT sector. ICT sector statistics is used largely in the context of the 2011 - 2015 benchmarking framework(endorsed by i2010 High Level Group in November 2009) via the Digital Agenda Scoreboard to monitor progress of the European digital economy according to the objectives set out in the Digital Agenda for Europe, a Europe 2020 Initiative. This conceptual framework follows the i2010 Benchmarking Framework which itself followed-up the eEurope 2005 Action Plan. ICT sector indicators are compiled using the secondary statistical analysis. This approach has a virtue of ensuring cost-efficient and high-quality data collection. At the same time, this approach has limited options for designing new indicators, as well as for control over data quality and over data release timing. Data from the Structural Business Statistics (SBS), National Accounts (NA) and Research and Development (R&D) Statistics sections of the Eurostat database are used. For this reason, Metadata guidelines on SBS, on NA and on R&D Statistics are applicable to the data that has been extracted from the respective primary statistics sources. Representation ICT sector statistics contains five indicators in the country/year dimensions, which are updated on an annual basis: (1) Share of the ICT sector in GDP (2) Share of the ICT sector personnel in total employment (3) Growth of the ICT sector value added (4) Share of the ICT sector in the R&D expenditure of businesses (5) Share of the ICT sector in R&D personnel In tables (1)-(3), data for NACE economic activity codes is grouped into three aggregates:ICT sector - total,ICT manufacturingICT Services. Tables (4) and (5) report disaggregated NACE economic activities. Definition ICT sector, ICT manufacturing and ICT services are defined according to the OECD official definition (see OECD, 2011 for details). The 2002 OECD definition in terms of NACE Rev. 1.1 is used on data prior to 2009, while the 2006 OECD definition in terms of NACE Rev. 2 is applied to the data from 2009 onwards. Since the impact of the break in series related to the revision of NACE is minimised due to the compatibility between the two OECD ICT sector definitions, data for each of the indicators (1)-(3) is presented in respective single tables, and not in separate tables for each revision of NACE (as it is done in the source SBS and NA data). Data for the indicators (4) and (5) is based on the NACE Rev. 2 codes of economic activity, with the data for the years prior to 2009 being recalculated using the official correspondence tables between NACE Rev. 2 and NAVE Rev. 1.1. Time coverage Data covers all years starting from 2000 until the latest year available. Following the approach set by the source primary statistics data files, the publication year is calculated as (t+1), with t being the reference year. Data for the indicators (1)-(5) are updated yearly from 2008 until the latest year available (as opposed to simply adding one additional year) to incorporate the latest revisions made on the source data (SBS, NA and R&D statistics). Data prior to 2008 is left unchanged following the approach used in the source data domains.
    • Июль 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 ноября, 2015
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      The 2011 Population and Housing Census marks a milestone in census exercises in Europe. For the first time, European legislation defined in detail a set of harmonised high-quality data from the population and housing censuses conducted in the EU Member States. As a result, the data from the 2011 round of censuses offer exceptional flexibility to cross-tabulate different variables and to provide geographically detailed data. EU Member States have developed different methods to produce these census data.  The national differences reflect the specific national situations in terms of data source availability, as well as the administrative practices and traditions of that country. The EU census legislation respects this diversity. The Regulation of the European Parliament and of the Council on population and housing censuses (Regulation (EC) No 763/2008) is focussed on output harmonisation rather than input harmonisation. Member States are free to assess for themselves how to conduct their 2011 censuses and which data sources, methods and technology should be applied given the national context. This gives the Member States flexibility, in line with the principles of subsidiarity and efficiency, and with the competences of the statistical institutes in the Member States. However, certain important conditions must be met in order to achieve the objective of comparability of census data from different Member States and to assess the data quality: Regulation (EC) No 1201/20092 contains definitions and technical specifications for the census topics (variables) and their breakdowns that are required to achieve Europe-wide comparability. The specifications are based closely on international recommendations and have been designed to provide the best possible information value. The census topics include geographic, demographic, economic and educational characteristics of persons, international and internal migration characteristics as well as household, family and housing characteristics. Regulation (EU) No 519/2010 requires the data outputs that Member States transmit to the Eurostat to comply with a defined programme of statistical data (tabulation) and with set rules concerning the replacement of statistical data. The content of the EU census programme serves major policy needs of the European Union. Regionally, there is a strong focus on the NUTS 2 level. The data requirements are adapted to the level of regional detail. The Regulation does not require transmission of any data that the Member States consider to be confidential. The statistical data must be completed by metadata that will facilitate interpretation of the numerical data, including country-specific definitions plus information on the data sources and on methodological issues. This is necessary in order to achieve the transparency that is a condition for valid interpretation of the data. Users of output-harmonised census data from the EU Member States need to have detailed information on the quality of the censuses and their results. Regulation (EU) No 1151/2010) therefore requires transmission of a quality report containing a systematic description of the data sources used for census purposes in the Member States and of the quality of the census results produced from these sources. A comparably structured quality report for all EU Member States will support the exchange of experience from the 2011 round and become a reference for future development of census methodology (EU legislation on the 2011 Population and Housing Censuses - Explanatory Notes ). In order to ensure proper transmission of the data and metadata and provide user-friendly access to this information, a common technical format is set for transmission for all Member States and for the Commission (Eurostat). The Regulation therefore requires the data to be transmitted in a harmonised structure and in the internationally established SDMX format from every Member State. In order to achieve this harmonised transmission, a new system has been developed – the CENSUS HUB. The Census Hub is a conceptually new system used for the dissemination of the 2011 Census. It is based on the concept of data sharing, where a group of partners (Eurostat on one hand and National Statistical Institutes on the other) agree to provide access to their data according to standard processes, formats and technologies. The Census Hub is a readily-accessible system that provided the following functions: • Data providers (the NSIs) can make data available directly from their systems through a querying system. In parallel, • Data users browse the hub to define a dataset of interest via the above structural metadata and retrieve the dataset from the NSIs. From the data management point of view, the hub is based on agreed hypercubes (data-sets in the form of multi-dimensional aggregations). The hypercubes are not sent to the central system. Instead the following process operates: 1. a user defines a dataset through the web interface of the central hub and requests it; 2. the central hub translates the user request in one or more queries and sends them to the related NSIs’ systems; 3. NSIs’ systems process the query and send the result to the central hub in a standard format; 4. the central hub puts together all the results sent by the NSI systems and presents them in a user-specified format. Â
    • Июль 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 31 декабря, 2015
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      The 2011 Population and Housing Census marks a milestone in census exercises in Europe. For the first time, European legislation defined in detail a set of harmonised high-quality data from the population and housing censuses conducted in the EU Member States. As a result, the data from the 2011 round of censuses offer exceptional flexibility to cross-tabulate different variables and to provide geographically detailed data. EU Member States have developed different methods to produce these census data.  The national differences reflect the specific national situations in terms of data source availability, as well as the administrative practices and traditions of that country. The EU census legislation respects this diversity. The Regulation of the European Parliament and of the Council on population and housing censuses (Regulation (EC) No 763/2008) is focussed on output harmonisation rather than input harmonisation. Member States are free to assess for themselves how to conduct their 2011 censuses and which data sources, methods and technology should be applied given the national context. This gives the Member States flexibility, in line with the principles of subsidiarity and efficiency, and with the competences of the statistical institutes in the Member States. However, certain important conditions must be met in order to achieve the objective of comparability of census data from different Member States and to assess the data quality: Regulation (EC) No 1201/20092 contains definitions and technical specifications for the census topics (variables) and their breakdowns that are required to achieve Europe-wide comparability. The specifications are based closely on international recommendations and have been designed to provide the best possible information value. The census topics include geographic, demographic, economic and educational characteristics of persons, international and internal migration characteristics as well as household, family and housing characteristics. Regulation (EU) No 519/2010 requires the data outputs that Member States transmit to the Eurostat to comply with a defined programme of statistical data (tabulation) and with set rules concerning the replacement of statistical data. The content of the EU census programme serves major policy needs of the European Union. Regionally, there is a strong focus on the NUTS 2 level. The data requirements are adapted to the level of regional detail. The Regulation does not require transmission of any data that the Member States consider to be confidential. The statistical data must be completed by metadata that will facilitate interpretation of the numerical data, including country-specific definitions plus information on the data sources and on methodological issues. This is necessary in order to achieve the transparency that is a condition for valid interpretation of the data. Users of output-harmonised census data from the EU Member States need to have detailed information on the quality of the censuses and their results. Regulation (EU) No 1151/2010) therefore requires transmission of a quality report containing a systematic description of the data sources used for census purposes in the Member States and of the quality of the census results produced from these sources. A comparably structured quality report for all EU Member States will support the exchange of experience from the 2011 round and become a reference for future development of census methodology (EU legislation on the 2011 Population and Housing Censuses - Explanatory Notes ). In order to ensure proper transmission of the data and metadata and provide user-friendly access to this information, a common technical format is set for transmission for all Member States and for the Commission (Eurostat). The Regulation therefore requires the data to be transmitted in a harmonised structure and in the internationally established SDMX format from every Member State. In order to achieve this harmonised transmission, a new system has been developed – the CENSUS HUB. The Census Hub is a conceptually new system used for the dissemination of the 2011 Census. It is based on the concept of data sharing, where a group of partners (Eurostat on one hand and National Statistical Institutes on the other) agree to provide access to their data according to standard processes, formats and technologies. The Census Hub is a readily-accessible system that provided the following functions: • Data providers (the NSIs) can make data available directly from their systems through a querying system. In parallel, • Data users browse the hub to define a dataset of interest via the above structural metadata and retrieve the dataset from the NSIs. From the data management point of view, the hub is based on agreed hypercubes (data-sets in the form of multi-dimensional aggregations). The hypercubes are not sent to the central system. Instead the following process operates: 1. a user defines a dataset through the web interface of the central hub and requests it; 2. the central hub translates the user request in one or more queries and sends them to the related NSIs’ systems; 3. NSIs’ systems process the query and send the result to the central hub in a standard format; 4. the central hub puts together all the results sent by the NSI systems and presents them in a user-specified format.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 сентября, 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 11 октября, 2019
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      This data collection presents summary tables intended to give an overview of the uptake of organic farming within the whole European Union and in each several country, plus Norway and Switzerland. Organic farming has to be understood as a part of a sustainable farming system and a viable alternative to the more traditional approaches to agriculture. Data are available for the following indicators: 1. Number of registered organic operators (table 'Food_act2') 2. Number of registered operators processing and importing products issued from organic farming (table 'Food_act3') 3. Organic crop area (table 'Food_in_porg1') 4. Organic crop production and yields from fully converted areas (table 'Food_in_porg2') 5. Organic livestock (table 'Food_in_porg3') 6. Production of organic animal products (table 'Food_pd_dmorg') Detailed information on the indicators provided in this collection may be found in the document 'Organic farming_additional information' (please see under 'Annex' at the bottom of this page).
    • Декабрь 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 декабря, 2017
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      The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to provide information on the innovativeness of sectors by type of enterprises, on the different types of innovation and on various aspects of the development of an innovation, such as objectives, sources of information, public funding or expenditures. The CIS provides statistics broken down by countries, types of innovators, economic activities and size classes. The survey is currently carried out every two years across the European Union, EFTA countries and EU candidate countries. In order to ensure comparability across countries, Eurostat together with the countries developed a standard core questionnaire (see in Annex) accompanied by a set of definitions and methodological recommendations. CIS 2014 concepts and its underlying methodology are also based on the Oslo Manual (2005) 3rd edition (see link at the bottom of the page). CIS 2014 results were collected under Commission Regulation No 995/2012. This Regulation defines the mandatory target population of the survey referring to enterprises in the Core NACE categories (see section 3.3.) with at least 10 employees. Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period 2012-2014, but some use only one calendar year (2012 or 2014). CIS 2014 includes an ad-hoc module on innovations with environmental benefits. While European innovation statistics use aggregated national data, the microdata sets can be consulted by researchers via the SAFE Centre of Eurostat in Luxembourg or via CD-ROM releases in a more anonymised form; some countries also provide access to their microdata through national Safe Centres. Since the provision of microdata is voluntary, microdatasets do not cover all countries.
    • Декабрь 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 декабря, 2017
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      The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to provide information on the innovativeness of sectors by type of enterprises, on the different types of innovation and on various aspects of the development of an innovation, such as objectives, sources of information, public funding or expenditures. The CIS provides statistics broken down by countries, types of innovators, economic activities and size classes. The survey is currently carried out every two years across the European Union, EFTA countries and EU candidate countries. In order to ensure comparability across countries, Eurostat together with the countries developed a standard core questionnaire (see in Annex) accompanied by a set of definitions and methodological recommendations. CIS 2014 concepts and its underlying methodology are also based on the Oslo Manual (2005) 3rd edition (see link at the bottom of the page). CIS 2014 results were collected under Commission Regulation No 995/2012. This Regulation defines the mandatory target population of the survey referring to enterprises in the Core NACE categories (see section 3.3.) with at least 10 employees. Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period 2012-2014, but some use only one calendar year (2012 or 2014). CIS 2014 includes an ad-hoc module on innovations with environmental benefits. While European innovation statistics use aggregated national data, the microdata sets can be consulted by researchers via the SAFE Centre of Eurostat in Luxembourg or via CD-ROM releases in a more anonymised form; some countries also provide access to their microdata through national Safe Centres. Since the provision of microdata is voluntary, microdatasets do not cover all countries.
  • R
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 октября, 2019
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      The objective of these data is to provide information for benchmarking and monitoring developments in ICT sector. ICT sector statistics is used largely in the context of the Monitoring the Digital Economy & Society  2016-2021 (endorsed by the Digital Agenda High Level Group) that follows the 2011 - 2015 benchmarking framework via the Digital Agenda Scoreboard to monitor progress of the European digital economy according to the objectives set out in the Digital Agenda for Europe, a Europe 2020 Initiative. This conceptual framework follows the i2010 Benchmarking Framework which itself followed-up the eEurope 2005 Action Plan. ICT sector indicators are compiled using the secondary statistical analysis. This approach has a virtue of ensuring cost-efficient and high-quality data collection. At the same time, this approach has limited options for designing new indicators, as well as for control over data quality and over data release timing. Data from the Structural Business Statistics (SBS), National Accounts (NA) and Research and Development (R&D) Statistics sections of the Eurostat database are used. For this reason, Metadata guidelines on SBS, on NA and on R&D Statistics are applicable to the data that has been extracted from the respective primary statistics sources. Representation ICT sector statistics contains five indicators in the country/year dimensions, which are updated on an annual basis: (1) Share of the ICT sector in GDP (2) Share of the ICT sector personnel in total employment (3) Growth of the ICT sector value added (4) Share of the ICT sector in the R&D expenditure of businesses (5) Share of the ICT sector in R&D personnel In tables (1)-(3), data for NACE economic activity codes is grouped into three aggregates: ICT sector - total,ICT manufacturingICT Services. Tables (4) and (5) report disaggregated NACE economic activities. Definition ICT sector, ICT manufacturing and ICT services are defined according to the OECD official definition (see OECD, 2011 for details). The 2002 OECD definition in terms of NACE Rev. 1.1 is used on data prior to 2009, while the 2006 OECD definition in terms of NACE Rev. 2 is applied to the data from 2009 onwards. Since the impact of the break in series related to the revision of NACE is minimised due to the compatibility between the two OECD ICT sector definitions, data for each of the indicators (1)-(3) is presented in respective single tables, and not in separate tables for each revision of NACE (as it is done in the source SBS and NA data). Data for the indicators (4) and (5) is based on the NACE Rev. 2 codes of economic activity, with the data for the years prior to 2009 being recalculated using the official correspondence tables between NACE Rev. 2 and NAVE Rev. 1.1. Time coverage Data covers all years starting from 2000 until the latest year available. Following the approach set by the source primary statistics data files, the publication year is calculated as (t+1), with t being the reference year. Data for the indicators (1)-(5) are updated yearly from 2008 until the latest year available (as opposed to simply adding one additional year) to incorporate the latest revisions made on the source data (SBS, NA and R&D statistics). Data prior to 2008 is left unchanged following the approach used in the source data domains.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 октября, 2019
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      The objective of these data is to provide information for benchmarking and monitoring developments in ICT sector. ICT sector statistics is used largely in the context of the Monitoring the Digital Economy & Society  2016-2021 (endorsed by the Digital Agenda High Level Group) that follows the 2011 - 2015 benchmarking framework via the Digital Agenda Scoreboard to monitor progress of the European digital economy according to the objectives set out in the Digital Agenda for Europe, a Europe 2020 Initiative. This conceptual framework follows the i2010 Benchmarking Framework which itself followed-up the eEurope 2005 Action Plan. ICT sector indicators are compiled using the secondary statistical analysis. This approach has a virtue of ensuring cost-efficient and high-quality data collection. At the same time, this approach has limited options for designing new indicators, as well as for control over data quality and over data release timing. Data from the Structural Business Statistics (SBS), National Accounts (NA) and Research and Development (R&D) Statistics sections of the Eurostat database are used. For this reason, Metadata guidelines on SBS, on NA and on R&D Statistics are applicable to the data that has been extracted from the respective primary statistics sources. Representation ICT sector statistics contains five indicators in the country/year dimensions, which are updated on an annual basis: (1) Share of the ICT sector in GDP (2) Share of the ICT sector personnel in total employment (3) Growth of the ICT sector value added (4) Share of the ICT sector in the R&D expenditure of businesses (5) Share of the ICT sector in R&D personnel In tables (1)-(3), data for NACE economic activity codes is grouped into three aggregates:ICT sector - total,ICT manufacturingICT Services. Tables (4) and (5) report disaggregated NACE economic activities. Definition ICT sector, ICT manufacturing and ICT services are defined according to the OECD official definition (see OECD, 2011 for details). The 2002 OECD definition in terms of NACE Rev. 1.1 is used on data prior to 2009, while the 2006 OECD definition in terms of NACE Rev. 2 is applied to the data from 2009 onwards. Since the impact of the break in series related to the revision of NACE is minimised due to the compatibility between the two OECD ICT sector definitions, data for each of the indicators (1)-(3) is presented in respective single tables, and not in separate tables for each revision of NACE (as it is done in the source SBS and NA data). Data for the indicators (4) and (5) is based on the NACE Rev. 2 codes of economic activity, with the data for the years prior to 2009 being recalculated using the official correspondence tables between NACE Rev. 2 and NAVE Rev. 1.1. Time coverage Data covers all years starting from 2000 until the latest year available. Following the approach set by the source primary statistics data files, the publication year is calculated as (t+1), with t being the reference year. Data for the indicators (1)-(5) are updated yearly from 2008 until the latest year available (as opposed to simply adding one additional year) to incorporate the latest revisions made on the source data (SBS, NA and R&D statistics). Data prior to 2008 is left unchanged following the approach used in the source data domains.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 октября, 2019
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      Industry, Trade and Services statistics are part of Short-term statistics (STS), they give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification (Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are presented in the following forms: UnadjustedCalendar adjustedSeasonally-adjusted Depending on the STS regulation, data are accessible monthly and quarterly. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction (volume)*Turnover: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic turnover into euro area and non euro area is available for the euro area countriesProducer prices (output prices)*: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic producer prices into euro area and non euro area is available for the euro area countriesImport prices*: Total, Euro area market, Non euro area market (euro area countries only)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries CONSTRUCTIONProduction (volume)*: Total of the construction sector, Building construction, Civil EngineeringLabour input indicators: Number of Persons Employed, Hours Worked, Gross Wages and SalariesConstruction costs IndexBuilding permits indicators*: Number of dwellings WHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (in value)Labour input indicators: Number of Persons Employed SERVICES Turnover (in value)*Producer prices (Ouput prices)*
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 октября, 2019
      Выбрать
      Industry, Trade and Services statistics are part of Short-term statistics (STS), they give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification(Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are presented in the following forms:UnadjustedCalendar adjustedSeasonally-adjusted Depending on the STS regulation, data are accessible monthly and quarterly. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction Index*Turnover IndexProducer Prices (Domestic Output Prices index)*Import Prices Index*: Total, Euro area market, Non euro area market (euro area countries only)Labour Input Indicators: Number of Persons Employed, Hours Worked, Gross Wages and Salaries CONSTRUCTIONProduction Index*: Total of the construction sector, Building construction, Civil EngineeringLabour input indicators: Number of Persons Employed, Hours Worked, Gross Wages and SalariesConstruction costs IndexBuilding permits indicators*: Number of dwellings WHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (in value)Labour input indicators: Number of Persons Employed SERVICES Turnover Index*Producer prices (Ouput prices)*
  • S
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 сентября, 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 октября, 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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 сентября, 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.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 октября, 2019
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      Eurostat Dataset Id:sbs_sc_1b_se_r2 SBS covers the Nace Rev.2 Section B to N and division S95 which are organized in four annexes, covering Industry (sections B-E), Construction (F), Trade (G) and Services (H, I, J, L, M, N and S95). Financial services are covered in three specific annexes and separate metadata files have been compiled. Up to reference year 2007 data was presented using the NACE Rev.1.1 classification. The SBS coverage was limited to NACE Rev.1.1 Sections C to K. Starting from the reference year 2008 data is available in NACE Rev.2. Double reported data in NACE Rev.1.1 for the reference year 2008 will be available in the first and second quarter of 2011. 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) Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. 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' in NACE Rev 1.1 sections H, I, K 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 Rev2 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 for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 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 N°1614/2002 and N°1669/2003. SBS data are collected primarily by National Statistical Institutes (NSI). Regulatory or controlling national offices for financial institutions or central banks often provides the information required for the financial sector (NACE Rev 2 Section K / NACE  Rev 1.1 Section J). 
    • Март 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 11 июня, 2014
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      Eurostat Dataset Id:lc_n08struc_r2 Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Structural information on labour costs is collected through four-yearly Labour Cost Surveys (LCSs), which provides details on level and structure of labour cost data, hours worked and hours paid. LCS results are available for the reference years 2000, 2004 and 2008. All EU Member States together with Norway, Iceland and Croatia (2004, 2008), Turkey and Macedonia (2008) 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 (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 (if different) and Purchasing Power Standards (PPS). Labour costs are quoted in total and per year, per month and per hour, as well as per capita and per full-time equivalents (FTE). Information on staff, hours worked and hours paid is quoted in aggregate and separately for full- and part-time employees. Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 02 октября, 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.
    • Май 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 12 декабря, 2015
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      Eurostat Dataset Id:lc_an_struc_r2 Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Annual labour cost data published here cover the core labour cost variables "average hourly labour costs" and "average monthly labour costs" as well as the breakdown of labour costs by main categories (wages and salaries; other labour costs). Average hourly and monthly labour costs as well as the structure of total annual labour costs per employee by economic activity are provided for enterprises with 1+ and for enterprises with 10+ employees.Data  are available for the EU Member States and partly for Iceland and Switzerland. The data are either collected by the National Statistical Institutes or, more frequently, estimated by them on the basis of their four-yearly Labour Cost Surveys (LCS), the Labour Cost Index (LCI) and additional up-to-date - though sometimes partial - information. Coverage of statistical units, thresholds and other methodological aspects are identical to that of the four yearly LCS.
  • T
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 13 октября, 2019
      Выбрать
      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.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 сентября, 2019
      Выбрать
      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.
    • Июнь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 июня, 2019
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      This collection provides users with data concerning R&D expenditure and R&D personnel broken down by following institutional sectors: business enterprise (BES), government (GOV), higher education (HES), private non-profit (PNP) with the total of sectors. All data are broken down by the above mentioned sectors of performance. The R&D expenditure is further broken down by source of funds, by type of costs, by economic activity (NACE Rev.2), by size class, by type of R&D, by fields of science, by socio-economic objectives and by regions (NUTS 2 level). Besides R&D expenditures in basic unit National currency (MIO_NAC) the following units are available: Euro (MIO_EUR), Euro per inhabitant (EUR_HAB), Purchasing Power Standard (MIO_PPS), Purchasing Power Standard at 2005 prices (MIO_PPS_KP05), Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_KP05_HAB), Percentage of GDP (PC_GDP) and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds). R&D personnel data is available in full-time equivalent (FTE), in head count (HC), as a % of employment and as a % of labour force. The data is further broken down by occupation, by qualification, by gender, by size class, by citizenship, by age groups, by fields of science, by economic activity (NACE Rev.2) and by regions (NUTS 2 level). The periodicity of R&D data is biennial except for the key R&D indicators (R&D expenditure, R&D personnel and Researchers by sectors of performance) which are transmitted annually by the EU Member States on the basis of a legal obligation from 2003 onwards. Some other breakdowns of the data may appear on annual basis based on voluntary data provisions. The data are collected through sample or census surveys, from administrative registers or through a combination of sources. R&D data are available for following countries and country groups: - All EU Member States, plus Candidate Countries, EFTA Countries, the Russian Federation, China, Japan, the United States and South Korea. - Country groups: EU-28, EU-15 and EA-18. R&D data are compiled in accordance to the guidelines laid down in the Proposed standard practice for surveys of research and experimental development - Frascati Manual (FM), OECD, 2002 .
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 сентября, 2019
      Выбрать
      International trade in goods statistics are an important data source for many public and private sector decision-makers at international, European Union and national level. For example, at the European Union level, international trade data are extensively used for multilateral and bilateral negotiations within the framework of the common commercial policy, to define and implement anti-dumping policy, to evaluate the progress of the Single Market and many other policies. Moreover, they constitute an essential source for the compilation of balance of payments statistics and national accounts. International trade in goods statistics cover both extra- and intra-EU trade: Extra-EU trade statistics cover the trading of goods between Member States and a non-member countries. Intra-EU trade statistics cover the trading of goods between Member States. "Goods" means all movable property including electricity. Detailed and aggregated data are published for the Euro area, the European Union and for each Member State separately. Main components: Data record the monthly trade between Member States in terms of arrivals and dispatches of goods as well as the monthly trade in terms of imports and exports between Member States and non-member countries. However, in publications only the term “exports” for all outward flows and “imports” for all inward flows are applied for both intra-EU trade and extra-EU trade. Extra-EU trade imports and exports are recorded in the Member State where the goods are placed under the customs procedures. Extra-EU trade statistics do not record goods in transit, goods placed into customs warehouses or goods for temporary admission. Data sources: The statistical information is mainly provided by the traders on the basis of Customs (extra-EU) and Intrastat (intra-EU) declarations. Data are collected by the competent national authorities of the Member States and compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Classification systems: - Product classification: For detailed data, products are disseminated according to the Combined Nomenclature (CN8), which first six digit codes coincide with the Harmonized Commodity Description and Coding System (HS), products are disseminated as well according to the Standard International Trade Classification (SITC) and the Broad Economic Categories (BEC). - Country classification: The Geonomenclature is used for classifying reporting countries and trading partners. Nomenclatures and correspondence tables are available at the Eurostat’s classification server RAMON. The following basic information is provided by Eurostat: - reporting country, - reference period, - trade flow, - product, - trading partner - mode of transport. Detailed data are disseminated according to the Combined Nomenclature (HS2, HS4, HS6 and CN8 levels) for the following indicators: - trade value (in Euro), - trade quantity in 100 kg, - trade quantity in supplementary units (published for some goods according to the Combined Nomenclature). Aggregated data cover both short and long term indicators. Short term indicators are disseminated according to major SITC and BEC groups for the following indicators: - gross and seasonally adjusted trade value (in million Euro), - unit-value indices, - gross and seasonally adjusted volume indices, - growth rates of trade values and indices. Long term indicators are disseminated according to major SITC groups for the following indicators: - trade value (in billion Euro), - shares of Member States in EU and world trade, - shares of main trading partners in EU trade, - volume indices. Adjustments are applied by the Member States to compensate the impact of exemption thresholds, which release the information providers from statistical formalities, as well as, to take into account the late or not response of the providers. In addition, Eurostat applies seasonal adjustments to aggregated time series.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 21 сентября, 2019
      Выбрать
      International trade in goods statistics are an important data source for many public and private sector decision-makers at international, European Union and national level. For example, at the European Union level, international trade data are extensively used for multilateral and bilateral negotiations within the framework of the common commercial policy, to define and implement anti-dumping policy, to evaluate the progress of the Single Market and many other policies. Moreover, they constitute an essential source for the compilation of balance of payments statistics and national accounts. International trade in goods statistics cover both extra- and intra-EU trade: Extra-EU trade statistics cover the trading of goods between Member States and a non-member countries. Intra-EU trade statistics cover the trading of goods between Member States. "Goods" means all movable property including electricity. Detailed and aggregated data are published for the Euro area, the European Union and for each Member State separately. Main components: Data record the monthly trade between Member States in terms of arrivals and dispatches of goods as well as the monthly trade in terms of imports and exports between Member States and non-member countries. However, in publications only the term “exports” for all outward flows and “imports” for all inward flows are applied for both intra-EU trade and extra-EU trade. Extra-EU trade imports and exports are recorded in the Member State where the goods are placed under the customs procedures. Extra-EU trade statistics do not record goods in transit, goods placed into customs warehouses or goods for temporary admission. Data sources: The statistical information is mainly provided by the traders on the basis of Customs (extra-EU) and Intrastat (intra-EU) declarations. Data are collected by the competent national authorities of the Member States and compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Classification systems: - Product classification: For detailed data, products are disseminated according to the Combined Nomenclature (CN8), which first six digit codes coincide with the Harmonized Commodity Description and Coding System (HS), products are disseminated as well according to the Standard International Trade Classification (SITC) and the Broad Economic Categories (BEC). - Country classification: The Geonomenclature is used for classifying reporting countries and trading partners. Nomenclatures and correspondence tables are available at the Eurostat’s classification server RAMON. The following basic information is provided by Eurostat: - reporting country, - reference period, - trade flow, - product, - trading partner - mode of transport. Detailed data are disseminated according to the Combined Nomenclature (HS2, HS4, HS6 and CN8 levels) for the following indicators: - trade value (in Euro), - trade quantity in 100 kg, - trade quantity in supplementary units (published for some goods according to the Combined Nomenclature). Aggregated data cover both short and long term indicators. Short term indicators are disseminated according to major SITC and BEC groups for the following indicators: - gross and seasonally adjusted trade value (in million Euro), - unit-value indices, - gross and seasonally adjusted volume indices, - growth rates of trade values and indices. Long term indicators are disseminated according to major SITC groups for the following indicators: - trade value (in billion Euro), - shares of Member States in EU and world trade, - shares of main trading partners in EU trade, - volume indices. Adjustments are applied by the Member States to compensate the impact of exemption thresholds, which release the information providers from statistical formalities, as well as, to take into account the late or not response of the providers. In addition, Eurostat applies seasonal adjustments to aggregated time series.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 сентября, 2019
      Выбрать
      International trade in goods statistics are an important data source for many public and private sector decision-makers at international, European Union and national level. For example, at the European Union level, international trade data are extensively used for multilateral and bilateral negotiations within the framework of the common commercial policy, to define and implement anti-dumping policy, to evaluate the progress of the Single Market and many other policies. Moreover, they constitute an essential source for the compilation of balance of payments statistics and national accounts. International trade in goods statistics cover both extra- and intra-EU trade: Extra-EU trade statistics cover the trading of goods between Member States and a non-member countries. Intra-EU trade statistics cover the trading of goods between Member States. "Goods" means all movable property including electricity. Detailed and aggregated data are published for the Euro area, the European Union and for each Member State separately. Main components: Data record the monthly trade between Member States in terms of arrivals and dispatches of goods as well as the monthly trade in terms of imports and exports between Member States and non-member countries. However, in publications only the term “exports” for all outward flows and “imports” for all inward flows are applied for both intra-EU trade and extra-EU trade. Extra-EU trade imports and exports are recorded in the Member State where the goods are placed under the customs procedures. Extra-EU trade statistics do not record goods in transit, goods placed into customs warehouses or goods for temporary admission. Data sources: The statistical information is mainly provided by the traders on the basis of Customs (extra-EU) and Intrastat (intra-EU) declarations. Data are collected by the competent national authorities of the Member States and compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Classification systems: - Product classification: For detailed data, products are disseminated according to the Combined Nomenclature (CN8), which first six digit codes coincide with the Harmonized Commodity Description and Coding System (HS), products are disseminated as well according to the Standard International Trade Classification (SITC) and the Broad Economic Categories (BEC). - Country classification: The Geonomenclature is used for classifying reporting countries and trading partners. Nomenclatures and correspondence tables are available at the Eurostat’s classification server RAMON. The following basic information is provided by Eurostat: - reporting country, - reference period, - trade flow, - product, - trading partner - mode of transport. Detailed data are disseminated according to the Combined Nomenclature (HS2, HS4, HS6 and CN8 levels) for the following indicators: - trade value (in Euro), - trade quantity in 100 kg, - trade quantity in supplementary units (published for some goods according to the Combined Nomenclature). Aggregated data cover both short and long term indicators. Short term indicators are disseminated according to major SITC and BEC groups for the following indicators: - gross and seasonally adjusted trade value (in million Euro), - unit-value indices, - gross and seasonally adjusted volume indices, - growth rates of trade values and indices. Long term indicators are disseminated according to major SITC groups for the following indicators: - trade value (in billion Euro), - shares of Member States in EU and world trade, - shares of main trading partners in EU trade, - volume indices. Adjustments are applied by the Member States to compensate the impact of exemption thresholds, which release the information providers from statistical formalities, as well as, to take into account the late or not response of the providers. In addition, Eurostat applies seasonal adjustments to aggregated time series.
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 сентября, 2019
      Выбрать
      International trade in goods statistics are an important data source for many public and private sector decision-makers at international, European Union and national level. For example, at the European Union level, international trade data are extensively used for multilateral and bilateral negotiations within the framework of the common commercial policy, to define and implement anti-dumping policy, to evaluate the progress of the Single Market and many other policies. Moreover, they constitute an essential source for the compilation of balance of payments statistics and national accounts. International trade in goods statistics cover both extra- and intra-EU trade: Extra-EU trade statistics cover the trading of goods between Member States and a non-member countries. Intra-EU trade statistics cover the trading of goods between Member States. "Goods" means all movable property including electricity. Detailed and aggregated data are published for the Euro area, the European Union and for each Member State separately. Main components: Data record the monthly trade between Member States in terms of arrivals and dispatches of goods as well as the monthly trade in terms of imports and exports between Member States and non-member countries. However, in publications only the term “exports” for all outward flows and “imports” for all inward flows are applied for both intra-EU trade and extra-EU trade. Extra-EU trade imports and exports are recorded in the Member State where the goods are placed under the customs procedures. Extra-EU trade statistics do not record goods in transit, goods placed into customs warehouses or goods for temporary admission. Data sources: The statistical information is mainly provided by the traders on the basis of Customs (extra-EU) and Intrastat (intra-EU) declarations. Data are collected by the competent national authorities of the Member States and compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Classification systems: - Product classification: For detailed data, products are disseminated according to the Combined Nomenclature (CN8), which first six digit codes coincide with the Harmonized Commodity Description and Coding System (HS), products are disseminated as well according to the Standard International Trade Classification (SITC) and the Broad Economic Categories (BEC). - Country classification: The Geonomenclature is used for classifying reporting countries and trading partners. Nomenclatures and correspondence tables are available at the Eurostat’s classification server RAMON. The following basic information is provided by Eurostat: - reporting country, - reference period, - trade flow, - product, - trading partner - mode of transport. Detailed data are disseminated according to the Combined Nomenclature (HS2, HS4, HS6 and CN8 levels) for the following indicators: - trade value (in Euro), - trade quantity in 100 kg, - trade quantity in supplementary units (published for some goods according to the Combined Nomenclature). Aggregated data cover both short and long term indicators. Short term indicators are disseminated according to major SITC and BEC groups for the following indicators: - gross and seasonally adjusted trade value (in million Euro), - unit-value indices, - gross and seasonally adjusted volume indices, - growth rates of trade values and indices. Long term indicators are disseminated according to major SITC groups for the following indicators: - trade value (in billion Euro), - shares of Member States in EU and world trade, - shares of main trading partners in EU trade, - volume indices. Adjustments are applied by the Member States to compensate the impact of exemption thresholds, which release the information providers from statistical formalities, as well as, to take into account the late or not response of the providers. In addition, Eurostat applies seasonal adjustments to aggregated time series.
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 17 октября, 2019
      Выбрать
      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.
  • V
    • Сентябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 19 сентября, 2019
      Выбрать
      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
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 17 октября, 2019
      Выбрать
      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.
  • W
    • Октябрь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 17 октября, 2019
      Выбрать
      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.
    • Август 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 августа, 2019
      Выбрать
      Yearly data on freshwater resources, water abstraction and use, wastewater treatment (connection rates of resident population to wastewater treatment and treatment capacities of wastewater treatment plants), sewage sludge production and disposal, generation and discharge of wastewater collected biennially by means of the OECD/Eurostat Joint Questionnaire - Inland Waters. Data aggregation: national territories.
    • Август 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 августа, 2019
      Выбрать
      Yearly data on freshwater resources, water abstraction and use, wastewater treatment (connection rates of resident population to wastewater treatment and treatment capacities of wastewater treatment plants), sewage sludge production and disposal, generation and discharge of wastewater collected biennially by means of the OECD/Eurostat Joint Questionnaire - Inland Waters. Data aggregation: national territories.

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