Philippines

  • President:Bongbong Marcos
  • Vice President:Sara Duterte
  • Capital city:Manila
  • Languages:Filipino (official; based on Tagalog) and English (official); eight major dialects - Tagalog, Cebuano, Ilocano, Hiligaynon or Ilonggo, Bicol, Waray, Pampango, and Pangasinan
  • Government
  • National statistics office
  • Population, persons:118,223,042 (2024)
  • Area, sq km:298,170
  • GDP per capita, US$:3,499 (2022)
  • GDP, billion current US$:404.3 (2022)
  • GINI index:40.7 (2021)
  • Ease of Doing Business rank:95
All datasets: 1 2 3 A B C D E F G H I J K L M N O P Q R S T U V W Y В К М Н П Р С Т Ч
  • 1
    • October 2018
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 03 November, 2018
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      This indicator gives the percentage of all 18-year-olds who are still in any kind of school (all ISCED levels). It gives an indication of the number of young people who have not abandoned their efforts to improve their skills through initial education and it includes both those who had a regular education career without any delays as well as those who are continuing even if they had to repeat some steps in the past.
  • 2
  • 3
    • April 2021
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 April, 2021
      Select Dataset
      The data are three-month interbank rates which are no longer updated. The series represent interest rates of countries which have now joined the euro area.
    • April 2021
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 April, 2021
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      The data are three-month interbank rates which are no longer updated. The series represent interest rates of countries which have now joined the euro area.
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 April, 2024
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      The 3-months interest rate is a representative short-term interest rate series for the domestic money market. From January 1999, the euro area rate is the 3-month "EURo InterBank Offered Rate" (EURIBOR) EURIBOR is the benchmark rate of the large euro money market that has emerged since 1999. It is the rate at which euro InterBank term deposits are offered by one prime bank to another prime bank. The contributors to EURIBOR are the banks with the highest volume of business in the euro area money markets. The panel of banks consists of banks from EU countries participating in the euro from the outset, banks from EU countries not participating in the euro from the outset, and large international banks from non-EU countries but with important euro area operations. Monthly data are calculated as averages of daily values. Data are presented in raw form. Source: European Central Bank (ECB)
    • October 2016
      Source: Philipps-University of Marburg, Empirical Institutional Economics
      Uploaded by: Knoema
      Accessed On: 07 December, 2016
      Select Dataset
      The 3P Anti-trafficking Policy Index evaluates governmental anti-trafficking efforts in the three main policy dimensions (3Ps), based on the requirements prescribed by the United Nations Protocol to Prevent, Suppress and Punish Trafficking in Persons, especially Women and Children (2000).   The three main policy dimensions (3Ps) are:Prosecution of perpetrators of human traffickingPrevention of human traffickingProtection of the victims of human trafficking Each of the 3P areas is evaluated on a 5-point scale and each index is aggregated to the overall 3P Anti-trafficking Index as the  sum (score 3-15).Prosecution Index Score: 1 (no compliance) - 5 (full compliance)Prevention Index Score: 1 (no compliance) - 5 (full compliance)Protection Index Score: 1 (no compliance) - 5 (full compliance)3P Anti-trafficking Policy Index Score: 3 (no compliance for any of the three areas) - 15 (full compliance for all of the three areas) The 3P Anti-trafficking Policy Index is available for each country and each year and currently includes up to 189 countries for the preiod from 2000 to 2015.
  • A
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 20 April, 2024
      Select Dataset
      The domain "Income and living conditions" covers four topics: people at risk of poverty or social exclusion, income distribution and monetary poverty, living conditions and material deprivation, which are again structured into collections of indicators on specific topics. The collection "People at risk of poverty or social exclusion" houses main indicator on risk of poverty or social inclusion included in the Europe 2020 strategy as well as the intersections between sub-populations of all Europe 2020 indicators on poverty and social exclusion. The collection "Income distribution and monetary poverty" houses collections of indicators relating to poverty risk, poverty risk of working individuals as well as the distribution of income. The collection "Living conditions" hosts indicators relating to characteristics and living conditions of households, characteristics of the population according to different breakdowns, health and labour conditions, housing conditions as well as childcare related indicators. The collection "Material deprivation" covers indicators relating to economic strain, durables, housing deprivation and environment of the dwelling.
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 19 April, 2024
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      Not applicable
    • October 2022
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 October, 2022
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    • March 2022
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 March, 2022
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    • October 2022
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 October, 2022
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    • January 2020
      Source: Editorial Projects in Education
      Uploaded by: Knoema
      Accessed On: 09 June, 2020
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      Post Secondary Education of United States, 2015
    • September 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
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      The data in this domain is collected by Eurostat in close cooperation with DG MARKT in the context of the annual "EU Postal Survey" (voluntary data collection). The partners in the data collection are the National Regulatory Authorities (NRAs) in the participating countries. The list of indicators/questionnaires and the definitions (Glossary) were agreed in cooperation with the European Postal Regulators in the project group "Assistance and development of EU statistics" of the European Committee for Postal Regulation (CERP). The data presented cover the companies operating under the Universal Service obligation (Universal Service Providers - USP). For countries where a USP no longer exists, the company which was the USP prior to liberalisation is referred to. "Universal service" refers here to the set of general interest demands to which services such as the mail should be subject throughout the Community.  The collection of 'Postal Services' includes data on employment, turnover, access points, traffic, prices and quality of service.
    • May 2020
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 June, 2020
      Select Dataset
      Eurostat Dataset Id:med_ps32 The focus of this domain is on the following countries:Algeria, Egypt, Israel, Jordan, Lebanon, Morocco, Palestinian Authority, Syria, Tunisia. Data are provided for over 1000 indicators depending on the country.   The data for the Mediterranean partner countries are supplied by and under the responsibility of the national statistical authorities  of each of the countries or territories. The data and their denomination in no way constitute the  expression of an opinion by the European Commission on the  legal status of a country or territory or on the delimitation of its frontiers. Â
    • September 2023
      Source: International Energy Agency
      Uploaded by: Knoema
      Accessed On: 06 October, 2023
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      World Electricity access database Hundreds of millions of people have gained access to modern energy over the last two decades, especially in China and India. Rapid economic development in several developing countries, increasing urbanisation and ongoing energy access programmes have been important factors in this achievement. The IEA Access to Energy database provides a snapshot of progress made toward meeting the ultimate goal of universal access. Note: For indicator population without access, value 1 represent <1 except Botswana, Guatemala countries
    • October 2011
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 May, 2014
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      Eurostat Dataset Id:trng_aes_185 The Adult Education Survey (AES) is part of the EU Statistics on lifelong learning. There has been two waves of data collection so far. The first wave (pilot) of the survey - also named 2006 AES - has been carried out by countries in the EU, EFTA and candidate countries between 2005 and 2008: for the first time, it set up a common EU framework including standard questionnaire, tools and quality reporting. The second wave, which is the most recent data collection also named 2011 AES, has been conducted by EU countries and EFTA countries between July 2011 and June 2012. The first 2006 AES results were released in autumn 2008. The first 2011 AES results have been released in February 2013: this new release comprise main indicators on participation in education and training (formal and non-formal learning) and main characteristics of learning activities. A second set of indicators based on the 2011 AES will be released later on. Both 2006 and 2011 results are now displayed within the same tables. The whole survey covers participation in education and lifelong learning activities (formal, non-formal and informal learning) including job-related activities, characteristics of learning activities, self-reported skills as well as modules on social and cultural participation, foreign language skills, IT skills and background variables related to main characteristics of the respondents. Parameters and main variables The AES focused on the following parameters:Participation in formal, non-formal and informal education (FED, NFE, INF)Non-participation and obstacles to participation in trainingParticipation in FED, NFE and INF activities by field of education/learningShare of the job related NFEVolume of instruction hours in FED and NFEEmployer financing and costs of learning in FED and NFEModule on language and ICT skills of the populationModule on social and cultural participation of the population
    • August 2021
      Source: Lao Statistics Bureau
      Uploaded by: Knoema
      Accessed On: 12 September, 2021
      Select Dataset
      TRANSLATE with xEnglishArabicHebrewPolishBulgarianHindiPortugueseCatalanHmong DawRomanianChinese SimplifiedHungarianRussianChinese TraditionalIndonesianSlovakCzechItalianSlovenianDanishJapaneseSpanishDutchKlingonSwedishEnglishKoreanThaiEstonianLatvianTurkishFinnishLithuanianUkrainianFrenchMalayUrduGermanMalteseVietnameseGreekNorwegianWelshHaitian CreolePersian  TRANSLATE with COPY THE URL BELOW BackEMBED THE SNIPPET BELOW IN YOUR SITEEnable collaborative features and customize widget: Bing Webmaster PortalBack
    • March 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 June, 2014
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      Eurostat Dataset Id:hsw_ij_nuse An ad hoc module on "Work-related health problems and accidental injuries" was included in the 1999 Labour Force Survey (LFS), in order to act as a complementary data source to ESAW (European Statistics on accidents at Work) and EODS (European Occupational Diseases Statistics) and give a broader view on Health and Safety at Work.. This module provided complementary information on accidents occurring at work and resulting in less than 4 days' absence from work, on return to work after the accident at work and on health problems caused or made worse by work. The data refer to self-reported accidental injuries at work during a 12 month period before the survey and to self-reported non-accidental health problems caused or made worse by work and from which the respondent had suffered during a 12 month period before the survey. The indicators used for accidental injuries are the percentage distributions of accidents and the relative incidence rate of accidents (relative to the rate in the total of all participating countries, which is marked with 100). The incidence rate is the number of accidents at work per 100 000 employed workers. The indicators used for non-accidental health problems are the percentage distribution, number, prevalence rate and relative prevalence rate of health problems (relative to the rate in the total of all participating countries, which is marked with 100). The prevalence rate is the number of people suffering from the health problem during the last 12 months per 100 000 employed workers (see the link to summary methodology at the bottom of the page). Statistical adjustments: Because the frequency of work accidents is higher in some branches (high-risk sectors), an adjustment is performed to get more standardised incidence rates. Similarly, the prevalence rates for non-accidental health problems are standardised for economic activity and for age, as age influences importantly the prevalence of health problems. For more details, please see the link to the summary methodology at the bottom of the page. Geographical coverage: Denmark, Germany, Greece, Spain, Hungary, Ireland, Italy, Luxembourg, Portugal, Finland, Sweden, United Kingdom. Sector coverage: All sectors of economic activity are covered. The specification of sectors is given according to the NACE classification (NACE = Nomenclature statistique des activités économiques dans la Communauté européenne). The incidence and prevalence rates are calculated for the total of all branches.
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      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).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      Harmonised data on accidents at work are collected in the framework of the administrative data collection 'European Statistics on Accidents at Work (ESAW)', on the basis of a methodology developed first in 1990. An accident at work is defined as 'a discrete occurrence in the course of work which leads to physical or mental harm'. The data include only fatal and non-fatal accidents involving more than 3 calendar days of absence from work. If the accident does not lead to the death of the victim it is called a 'non-fatal' (or 'serious') accident. A fatal accident at work is defined as an accident which leads to the death of a victim within one year of the accident. The variables collected on accidents at work include: Economic activity of the employer and size of the enterpriseEmployment status, occupation, age, sex and nationality of victimGeographical location, date and time of the accidentType of injury, body part injured and the severity of the accident (number of full calendar days during which the victim is unfit for work excluding the day of the accident, permanent incapacity or death within one year of the accident).Variables on causes and circumstances of the accident: workstation, working environment, working process, specific physical activity, material agent of the specific physical activity, deviation and material agent of deviation, contact - mode of injury and material agent of contact - mode of injury. The national ESAW sources are the declarations of accidents at work, either to the accident insurance of the national social security system, a private insurance for accidents at work or to other relevant national authorities (labour inspection etc.). As an exception, accident data for the Netherlands are based on survey data. On the Eurostat website, ESAW data are disseminated in two sections: 'Main Indicators' and 'Details by economic sector (NACE Rev2, 2008 onwards)'. Depending on the table, data are broken down by: economic activity (NACE 'main sectors' (1 digit code) or more detailed NACE divisions (2 digit codes)); the occupation of the victim (ISCO-08 code); country; severity of the accident, sex, age, employment status, size of the enterprise, body part injured and type of injury. The data is presented in form of numbers, percentages, incidence rates and standardised incidence rates of non-fatal and fatal accidents at work, either for EU aggregates, countries or certain breakdowns by dimensions such as age, sex etc. Numbers correspond to a simple count of all non-fatal and fatal accidents for the entirety or certain breakdowns of the data;Percentages represent shares of breakdowns;The incidence rate of non-fatal or fatal accidents at work is the number of serious or fatal accidents per 100,000 persons in employment;The standardised incidence rates of non-fatal or fatal accidents at work aim to eliminate differences in the structures of countries' economies (see section 18.6 Adjustment for more details). The incidence rate indicates the relative importance of non-fatal or fatal accidents at work in the working population. For both types of accidents at work the numerator is the number of accidents that occurred during the year. The denominator is the reference population (i.e. the number of persons in employment) expressed in 100,000 persons. The reference population (or number of persons in employment) related to the national ESAW reporting system is provided by the Member States, either from administrative sources related to accidents at work or from the EU Labour Force Survey (LFS).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      Harmonised data on accidents at work are collected in the framework of the administrative data collection 'European Statistics on Accidents at Work (ESAW)', on the basis of a methodology developed first in 1990. An accident at work is defined as 'a discrete occurrence in the course of work which leads to physical or mental harm'. The data include only fatal and non-fatal accidents involving more than 3 calendar days of absence from work. If the accident does not lead to the death of the victim it is called a 'non-fatal' (or 'serious') accident. A fatal accident at work is defined as an accident which leads to the death of a victim within one year of the accident. The variables collected on accidents at work include: Economic activity of the employer and size of the enterpriseEmployment status, occupation, age, sex and nationality of victimGeographical location, date and time of the accidentType of injury, body part injured and the severity of the accident (number of full calendar days during which the victim is unfit for work excluding the day of the accident, permanent incapacity or death within one year of the accident).Variables on causes and circumstances of the accident: workstation, working environment, working process, specific physical activity, material agent of the specific physical activity, deviation and material agent of deviation, contact - mode of injury and material agent of contact - mode of injury. The national ESAW sources are the declarations of accidents at work, either to the accident insurance of the national social security system, a private insurance for accidents at work or to other relevant national authorities (labour inspection etc.). As an exception, accident data for the Netherlands are based on survey data. On the Eurostat website, ESAW data are disseminated in two sections: 'Main Indicators' and 'Details by economic sector (NACE Rev2, 2008 onwards)'. Depending on the table, data are broken down by: economic activity (NACE 'main sectors' (1 digit code) or more detailed NACE divisions (2 digit codes)); the occupation of the victim (ISCO-08 code); country; severity of the accident, sex, age, employment status, size of the enterprise, body part injured and type of injury. The data is presented in form of numbers, percentages, incidence rates and standardised incidence rates of non-fatal and fatal accidents at work, either for EU aggregates, countries or certain breakdowns by dimensions such as age, sex etc. Numbers correspond to a simple count of all non-fatal and fatal accidents for the entirety or certain breakdowns of the data;Percentages represent shares of breakdowns;The incidence rate of non-fatal or fatal accidents at work is the number of serious or fatal accidents per 100,000 persons in employment;The standardised incidence rates of non-fatal or fatal accidents at work aim to eliminate differences in the structures of countries' economies (see section 18.6 Adjustment for more details). The incidence rate indicates the relative importance of non-fatal or fatal accidents at work in the working population. For both types of accidents at work the numerator is the number of accidents that occurred during the year. The denominator is the reference population (i.e. the number of persons in employment) expressed in 100,000 persons. The reference population (or number of persons in employment) related to the national ESAW reporting system is provided by the Member States, either from administrative sources related to accidents at work or from the EU Labour Force Survey (LFS).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      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).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      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).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      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).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      Harmonised data on accidents at work are collected in the framework of the administrative data collection 'European Statistics on Accidents at Work (ESAW)', on the basis of a methodology developed first in 1990. An accident at work is defined as 'a discrete occurrence in the course of work which leads to physical or mental harm'. The data include only fatal and non-fatal accidents involving more than 3 calendar days of absence from work. If the accident does not lead to the death of the victim it is called a 'non-fatal' (or 'serious') accident. A fatal accident at work is defined as an accident which leads to the death of a victim within one year of the accident. The variables collected on accidents at work include: Economic activity of the employer and size of the enterpriseEmployment status, occupation, age, sex and nationality of victimGeographical location, date and time of the accidentType of injury, body part injured and the severity of the accident (number of full calendar days during which the victim is unfit for work excluding the day of the accident, permanent incapacity or death within one year of the accident).Variables on causes and circumstances of the accident: workstation, working environment, working process, specific physical activity, material agent of the specific physical activity, deviation and material agent of deviation, contact - mode of injury and material agent of contact - mode of injury. The national ESAW sources are the declarations of accidents at work, either to the accident insurance of the national social security system, a private insurance for accidents at work or to other relevant national authorities (labour inspection etc.). As an exception, accident data for the Netherlands are based on survey data. On the Eurostat website, ESAW data are disseminated in two sections: 'Main Indicators' and 'Details by economic sector (NACE Rev2, 2008 onwards)'. Depending on the table, data are broken down by: economic activity (NACE 'main sectors' (1 digit code) or more detailed NACE divisions (2 digit codes)); the occupation of the victim (ISCO-08 code); country; severity of the accident, sex, age, employment status, size of the enterprise, body part injured and type of injury. The data is presented in form of numbers, percentages, incidence rates and standardised incidence rates of non-fatal and fatal accidents at work, either for EU aggregates, countries or certain breakdowns by dimensions such as age, sex etc. Numbers correspond to a simple count of all non-fatal and fatal accidents for the entirety or certain breakdowns of the data;Percentages represent shares of breakdowns;The incidence rate of non-fatal or fatal accidents at work is the number of serious or fatal accidents per 100,000 persons in employment;The standardised incidence rates of non-fatal or fatal accidents at work aim to eliminate differences in the structures of countries' economies (see section 18.6 Adjustment for more details). The incidence rate indicates the relative importance of non-fatal or fatal accidents at work in the working population. For both types of accidents at work the numerator is the number of accidents that occurred during the year. The denominator is the reference population (i.e. the number of persons in employment) expressed in 100,000 persons. The reference population (or number of persons in employment) related to the national ESAW reporting system is provided by the Member States, either from administrative sources related to accidents at work or from the EU Labour Force Survey (LFS).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      Harmonised data on accidents at work are collected in the framework of the administrative data collection 'European Statistics on Accidents at Work (ESAW)', on the basis of a methodology developed first in 1990. An accident at work is defined as 'a discrete occurrence in the course of work which leads to physical or mental harm'. The data include only fatal and non-fatal accidents involving more than 3 calendar days of absence from work. If the accident does not lead to the death of the victim it is called a 'non-fatal' (or 'serious') accident. A fatal accident at work is defined as an accident which leads to the death of a victim within one year of the accident. The variables collected on accidents at work include:Economic activity of the employer and size of the enterpriseEmployment status, occupation, age, sex and nationality of victimGeographical location, date and time of the accidentType of injury, body part injured and the severity of the accident (number of full calendar days during which the victim is unfit for work excluding the day of the accident, permanent incapacity or death within one year of the accident).Variables on causes and circumstances of the accident: workstation, working environment, working process, specific physical activity, material agent of the specific physical activity, deviation and material agent of deviation, contact - mode of injury and material agent of contact - mode of injury. The national ESAW sources are the declarations of accidents at work, either to the accident insurance of the national social security system, a private insurance for accidents at work or to other relevant national authorities (labour inspection etc.). As an exception, accident data for the Netherlands are based on survey data. On the Eurostat website, ESAW data are disseminated in two sections: 'Main Indicators' and 'Details by economic sector (NACE Rev2, 2008 onwards)'. Depending on the table, data are broken down by: economic activity (NACE 'main sectors' (1 digit code) or more detailed NACE divisions (2 digit codes)); the occupation of the victim (ISCO-08 code); country; severity of the accident, sex, age, employment status, size of the enterprise, body part injured and type of injury. The data is presented in form of numbers, percentages, incidence rates and standardised incidence rates of non-fatal and fatal accidents at work, either for EU aggregates, countries or certain breakdowns by dimensions such as age, sex etc.Numbers correspond to a simple count of all non-fatal and fatal accidents for the entirety or certain breakdowns of the data;Percentages represent shares of breakdowns;The incidence rate of non-fatal or fatal accidents at work is the number of serious or fatal accidents per 100,000 persons in employment;The standardised incidence rates of non-fatal or fatal accidents at work aim to eliminate differences in the structures of countries' economies (see section 18.6 Adjustment for more details). The incidence rate indicates the relative importance of non-fatal or fatal accidents at work in the working population. For both types of accidents at work the numerator is the number of accidents that occurred during the year. The denominator is the reference population (i.e. the number of persons in employment) expressed in 100,000 persons. The reference population (or number of persons in employment) related to the national ESAW reporting system is provided by the Member States, either from administrative sources related to accidents at work or from the EU Labour Force Survey (LFS).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      Harmonised data on accidents at work are collected in the framework of the administrative data collection 'European Statistics on Accidents at Work (ESAW)', on the basis of a methodology developed first in 1990. An accident at work is defined as 'a discrete occurrence in the course of work which leads to physical or mental harm'. The data include only fatal and non-fatal accidents involving more than 3 calendar days of absence from work. If the accident does not lead to the death of the victim it is called a 'non-fatal' (or 'serious') accident. A fatal accident at work is defined as an accident which leads to the death of a victim within one year of the accident. The variables collected on accidents at work include: Economic activity of the employer and size of the enterpriseEmployment status, occupation, age, sex and nationality of victimGeographical location, date and time of the accidentType of injury, body part injured and the severity of the accident (number of full calendar days during which the victim is unfit for work excluding the day of the accident, permanent incapacity or death within one year of the accident).Variables on causes and circumstances of the accident: workstation, working environment, working process, specific physical activity, material agent of the specific physical activity, deviation and material agent of deviation, contact - mode of injury and material agent of contact - mode of injury. The national ESAW sources are the declarations of accidents at work, either to the accident insurance of the national social security system, a private insurance for accidents at work or to other relevant national authorities (labour inspection etc.). As an exception, accident data for the Netherlands are based on survey data. On the Eurostat website, ESAW data are disseminated in two sections: 'Main Indicators' and 'Details by economic sector (NACE Rev2, 2008 onwards)'. Depending on the table, data are broken down by: economic activity (NACE 'main sectors' (1 digit code) or more detailed NACE divisions (2 digit codes)); the occupation of the victim (ISCO-08 code); country; severity of the accident, sex, age, employment status, size of the enterprise, body part injured and type of injury. The data is presented in form of numbers, percentages, incidence rates and standardised incidence rates of non-fatal and fatal accidents at work, either for EU aggregates, countries or certain breakdowns by dimensions such as age, sex etc. Numbers correspond to a simple count of all non-fatal and fatal accidents for the entirety or certain breakdowns of the data;Percentages represent shares of breakdowns;The incidence rate of non-fatal or fatal accidents at work is the number of serious or fatal accidents per 100,000 persons in employment;The standardised incidence rates of non-fatal or fatal accidents at work aim to eliminate differences in the structures of countries' economies (see section 18.6 Adjustment for more details). The incidence rate indicates the relative importance of non-fatal or fatal accidents at work in the working population. For both types of accidents at work the numerator is the number of accidents that occurred during the year. The denominator is the reference population (i.e. the number of persons in employment) expressed in 100,000 persons. The reference population (or number of persons in employment) related to the national ESAW reporting system is provided by the Member States, either from administrative sources related to accidents at work or from the EU Labour Force Survey (LFS).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      Harmonised data on accidents at work are collected in the framework of the administrative data collection 'European Statistics on Accidents at Work (ESAW)', on the basis of a methodology developed first in 1990. An accident at work is defined as 'a discrete occurrence in the course of work which leads to physical or mental harm'. The data include only fatal and non-fatal accidents involving more than 3 calendar days of absence from work. If the accident does not lead to the death of the victim it is called a 'non-fatal' (or 'serious') accident. A fatal accident at work is defined as an accident which leads to the death of a victim within one year of the accident. The variables collected on accidents at work include: Economic activity of the employer and size of the enterpriseEmployment status, occupation, age, sex and nationality of victimGeographical location, date and time of the accidentType of injury, body part injured and the severity of the accident (number of full calendar days during which the victim is unfit for work excluding the day of the accident, permanent incapacity or death within one year of the accident).Variables on causes and circumstances of the accident: workstation, working environment, working process, specific physical activity, material agent of the specific physical activity, deviation and material agent of deviation, contact - mode of injury and material agent of contact - mode of injury. The national ESAW sources are the declarations of accidents at work, either to the accident insurance of the national social security system, a private insurance for accidents at work or to other relevant national authorities (labour inspection etc.). As an exception, accident data for the Netherlands are based on survey data. On the Eurostat website, ESAW data are disseminated in two sections: 'Main Indicators' and 'Details by economic sector (NACE Rev2, 2008 onwards)'. Depending on the table, data are broken down by: economic activity (NACE 'main sectors' (1 digit code) or more detailed NACE divisions (2 digit codes)); the occupation of the victim (ISCO-08 code); country; severity of the accident, sex, age, employment status, size of the enterprise, body part injured and type of injury. The data is presented in form of numbers, percentages, incidence rates and standardised incidence rates of non-fatal and fatal accidents at work, either for EU aggregates, countries or certain breakdowns by dimensions such as age, sex etc. Numbers correspond to a simple count of all non-fatal and fatal accidents for the entirety or certain breakdowns of the data;Percentages represent shares of breakdowns;The incidence rate of non-fatal or fatal accidents at work is the number of serious or fatal accidents per 100,000 persons in employment;The standardised incidence rates of non-fatal or fatal accidents at work aim to eliminate differences in the structures of countries' economies (see section 18.6 Adjustment for more details). The incidence rate indicates the relative importance of non-fatal or fatal accidents at work in the working population. For both types of accidents at work the numerator is the number of accidents that occurred during the year. The denominator is the reference population (i.e. the number of persons in employment) expressed in 100,000 persons. The reference population (or number of persons in employment) related to the national ESAW reporting system is provided by the Member States, either from administrative sources related to accidents at work or from the EU Labour Force Survey (LFS).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      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).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      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).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      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).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      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).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      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).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      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).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      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).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      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).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      Harmonised data on accidents at work are collected in the framework of the administrative data collection 'European Statistics on Accidents at Work (ESAW)', on the basis of a methodology developed first in 1990. An accident at work is defined as 'a discrete occurrence in the course of work which leads to physical or mental harm'. The data include only fatal and non-fatal accidents involving more than 3 calendar days of absence from work. If the accident does not lead to the death of the victim it is called a 'non-fatal' (or 'serious') accident. A fatal accident at work is defined as an accident which leads to the death of a victim within one year of the accident. The variables collected on accidents at work include: Economic activity of the employer and size of the enterpriseEmployment status, occupation, age, sex and nationality of victimGeographical location, date and time of the accidentType of injury, body part injured and the severity of the accident (number of full calendar days during which the victim is unfit for work excluding the day of the accident, permanent incapacity or death within one year of the accident).Variables on causes and circumstances of the accident: workstation, working environment, working process, specific physical activity, material agent of the specific physical activity, deviation and material agent of deviation, contact - mode of injury and material agent of contact - mode of injury. The national ESAW sources are the declarations of accidents at work, either to the accident insurance of the national social security system, a private insurance for accidents at work or to other relevant national authorities (labour inspection etc.). As an exception, accident data for the Netherlands are based on survey data. On the Eurostat website, ESAW data are disseminated in two sections: 'Main Indicators' and 'Details by economic sector (NACE Rev2, 2008 onwards)'. Depending on the table, data are broken down by: economic activity (NACE 'main sectors' (1 digit code) or more detailed NACE divisions (2 digit codes)); the occupation of the victim (ISCO-08 code); country; severity of the accident, sex, age, employment status, size of the enterprise, body part injured and type of injury. The data is presented in form of numbers, percentages, incidence rates and standardised incidence rates of non-fatal and fatal accidents at work, either for EU aggregates, countries or certain breakdowns by dimensions such as age, sex etc. Numbers correspond to a simple count of all non-fatal and fatal accidents for the entirety or certain breakdowns of the data;Percentages represent shares of breakdowns;The incidence rate of non-fatal or fatal accidents at work is the number of serious or fatal accidents per 100,000 persons in employment;The standardised incidence rates of non-fatal or fatal accidents at work aim to eliminate differences in the structures of countries' economies (see section 18.6 Adjustment for more details). The incidence rate indicates the relative importance of non-fatal or fatal accidents at work in the working population. For both types of accidents at work the numerator is the number of accidents that occurred during the year. The denominator is the reference population (i.e. the number of persons in employment) expressed in 100,000 persons. The reference population (or number of persons in employment) related to the national ESAW reporting system is provided by the Member States, either from administrative sources related to accidents at work or from the EU Labour Force Survey (LFS).
    • October 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
      Select Dataset
      Harmonised data on accidents at work are collected in the framework of the administrative data collection 'European Statistics on Accidents at Work (ESAW)', on the basis of a methodology developed first in 1990. An accident at work is defined as 'a discrete occurrence in the course of work which leads to physical or mental harm'. The data include only fatal and non-fatal accidents involving more than 3 calendar days of absence from work. If the accident does not lead to the death of the victim it is called a 'non-fatal' (or 'serious') accident. A fatal accident at work is defined as an accident which leads to the death of a victim within one year of the accident. The variables collected on accidents at work include: Economic activity of the employer and size of the enterpriseEmployment status, occupation, age, sex and nationality of victimGeographical location, date and time of the accidentType of injury, body part injured and the severity of the accident (number of full calendar days during which the victim is unfit for work excluding the day of the accident, permanent incapacity or death within one year of the accident).Variables on causes and circumstances of the accident: workstation, working environment, working process, specific physical activity, material agent of the specific physical activity, deviation and material agent of deviation, contact - mode of injury and material agent of contact - mode of injury. The national ESAW sources are the declarations of accidents at work, either to the accident insurance of the national social security system, a private insurance for accidents at work or to other relevant national authorities (labour inspection etc.). As an exception, accident data for the Netherlands are based on survey data. On the Eurostat website, ESAW data are disseminated in two sections: 'Main Indicators' and 'Details by economic sector (NACE Rev2, 2008 onwards)'. Depending on the table, data are broken down by: economic activity (NACE 'main sectors' (1 digit code) or more detailed NACE divisions (2 digit codes)); the occupation of the victim (ISCO-08 code); country; severity of the accident, sex, age, employment status, size of the enterprise, body part injured and type of injury. The data is presented in form of numbers, percentages, incidence rates and standardised incidence rates of non-fatal and fatal accidents at work, either for EU aggregates, countries or certain breakdowns by dimensions such as age, sex etc. Numbers correspond to a simple count of all non-fatal and fatal accidents for the entirety or certain breakdowns of the data;Percentages represent shares of breakdowns;The incidence rate of non-fatal or fatal accidents at work is the number of serious or fatal accidents per 100,000 persons in employment;The standardised incidence rates of non-fatal or fatal accidents at work aim to eliminate differences in the structures of countries' economies (see section 18.6 Adjustment for more details). The incidence rate indicates the relative importance of non-fatal or fatal accidents at work in the working population. For both types of accidents at work the numerator is the number of accidents that occurred during the year. The denominator is the reference population (i.e. the number of persons in employment) expressed in 100,000 persons. The reference population (or number of persons in employment) related to the national ESAW reporting system is provided by the Member States, either from administrative sources related to accidents at work or from the EU Labour Force Survey (LFS).
    • May 2020
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 June, 2020
      Select Dataset
      The focus of this domain is on the European Neighbourhood Policy (ENP) countries on the southern and eastern shores of the Mediterranean (ENP-South), namely: Algeria (DZ),Egypt (EG),Israel (IL),Jordan (JO),Lebanon (LB),Libya (LY),Morocco (MA),Palestine (PS),Syria (SY) andTunisia (TN). An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. The data and their denomination in no way constitute the expression of an opinion by the European Commission on the legal status of a country or territory or on the delimitation of its borders.
    • March 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      Select Dataset
      Eurostat collects rail transport statistics by two means: 1. Voluntary data collection. Data are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF). Full details are set out in another document (see link to 21.3. Annex, at the bottom of the page). The following Eurostat dissemination tables are based on this data collection: all tables in subsection: Railway transport infrastructure (rail_if)all tables in subsection: Railway transport equipment (rail_eq)all tables in subsection: Railway transport - enterprises, economic performance and employment (rail_ec)all tables in subsection: Railway traffic (rail_tf) but table Train movements (rail_tf_trainmv)table Railway transport - Number of victims by type of injury (rail_ac_inj) in subsection Railway transport - Accidents (rail_ac)  Additionally, one table in the regional transport section is based on a different voluntary data collection (REGWeb questionnaire) and contains information on railway infrastructure (length of railway lines - total, electrified and with double or more tracks) by NUTS 2 regions. 2. Mandatory data collection based on the legal act. Data collection on goods and passenger transport, and on rail accidents is based on Regulation EC 91/2003 from the beginning of 2003. The freight data from 1982 until 2002 are based on Directive 80/1177/EEC. Compared to the Directive, Regulation 91/2003 covers the transport of passengers and statistics on accidents in addition to the transport of goods. A detailed description of the source of each dissemination table can be found in the section 21.3Annex (Legal acts and corresponding dissemination tables) at the bottom of this page.
    • June 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 November, 2015
      Select Dataset
      Eurostat collects rail transport statistics by two means: 1. Voluntary data collection. Data are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF). Full details are set out in another document (see link to 21.3. Annex, at the bottom of the page). The following Eurostat dissemination tables are based on this data collection:all tables in subsection: Railway transport infrastructure (rail_if)all tables in subsection: Railway transport equipment (rail_eq)all tables in subsection: Railway transport - enterprises, economic performance and employment (rail_ec)all tables in subsection: Railway traffic (rail_tf) but table Train movements (rail_tf_trainmv)table Railway transport - Number of victims by type of injury (rail_ac_inj) in subsection Railway transport - Accidents (rail_ac)  Additionally, one table in the regional transport section is based on a different voluntary data collection (REGWeb questionnaire) and contains information on railway infrastructure (length of railway lines - total, electrified and with double or more tracks) by NUTS 2 regions. 2. Mandatory data collection based on the legal act. Data collection on goods and passenger transport, and on rail accidents is based on Regulation EC 91/2003 from the beginning of 2003. The freight data from 1982 until 2002 are based on Directive 80/1177/EEC. Compared to the Directive, Regulation 91/2003 covers the transport of passengers and statistics on accidents in addition to the transport of goods.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 March, 2024
      Select Dataset
      The supplementary table on accrued-to-date  pension entitlements in social insurance (pensions in National Accounts) is compiled in accordance with the European System of Accounts (ESA 2010) and is transmitted by EU Member States, EEA Members (Norway, Iceland) and Switzerland following the ESA2010 transmission programme (Table 29) established by the Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013 on the European system of national and regional accounts in the European Union, annexes A and B respectively). By introducing this table, ESA 2010 added enhanced reporting on pensions, covering both entitlements of pension schemes recorded in the core national accounts, and unfunded "pay-as-you-go" pension schemes managed by general government. The latters' entitlements are excluded from the core national accounts and are considered as contingent liabilities. However, full coverage of all pension schemes in one table provides a complete overview of organisation of pension social insurance in a given country and enhances cross-country analysis of pension entitlements of households. At the same time, it should be stressed that accrued-to-date pension entitlements in social insurance are not a measure of the sustainability of public finances and not part of government debt. The European reporting system on age-related expenditure is multifaceted. National accountants focus in this dataset on already earned (accrued-to-date) pension entitlements of current persons employed and current pensioners, whereas the Economic Policy Committee (EPC) is analysing the impact of ageing on European societies from a wider angle. The EPC'S Ageing Report includes estimates for pension entitlements (and related contributions) being accrued in the future. Data are presented by means of two tables: 1.  "Accrued-to-date pension entitlements in social insurance" (nasa_10_pens1) The table gives an overview of accumulation of pension entitlements by all types of social insurance pension schemes (defined contribution vs. defined benefit schemes, private vs. general government schemes, core accounts schemes vs. social security schemes) in a given period due to pension contributions, payment of pension benefits and other changes. 2. "Sensitivity analysis of accrued-to-date pension entitlements in general government pension schemes outside of core national accounts" (nasa_10_pens2) The data on unfunded general government pension schemes outside of core national accounts are based on actuarial calculations. Thus, the results for pension entitlements depend to a large extent on the underlying assumptions. To ensure a consistent approach and cross-country data comparability, actuarial assumptions for these schemes in ESA 2010 Table 29 are aligned with those proposed by the EPC Ageing Working group (AWG), including the discount rate to calculate present value of pension entitlements. Actuarial assumptions are regularly reviewed by the AWG in the framework of 3-yearly Ageing reports. Analysis shows that the discount rate is the most important parameter that impacts on the resulting value of pension entitlements. Therefore, table 2 shows how the outcome of actuarial calculations varies based on a different choice of discount rate. Three scenarios are presented as follows under SECTOR dimension: S13_BC – base case scenario with current discount rate 5% in nominal terms (3% in real terms) S13_SC1 –scenario with discount rate 1 percentage point less than in base case S13_SC3 –scenario with discount rate 1 percentage point higher than in base case Data, as far as they are available, are expressed in national currency and millions of euro in current prices. In line with ESA2010 Transmission programme requirements data series start from 2015 and are to be transmitted on 3-yearly basis. Countries may transmit longer time series or transmit data annually on voluntary basis.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 March, 2024
      Select Dataset
      Number of grants of citizenship of the reporting country to persons usually resident in the reporting country who have previously been citizens of another country or who have been stateless.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 April, 2024
      Select Dataset
      The annual Eurostat's collection on statistics on acquisitions of citizenship is structured as follows:   l
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 April, 2024
      Select Dataset
      The annual Eurostat's collection on statistics on acquisitions of citizenship is structured as follows:   Data Collection Info & Legislation UNIDEMO Unified Demographic The most extended annual collection on demography and migration, collecting data at national and regional level for population, births, deaths, immigrants, emigrants, acquisition and loss of citizenship, marriages and divorces by a large number of breakdowns. (Art. 3 of the Regulation (EU) No 1260/2013 and Art. 3 of the Regulation (EC) No 862/2007)   The annual demography data collections aim at collecting from the National Statistical Institutes both mandatory data and voluntary data. The mandatory data are those defined by the legislation listed on "6.1. Institutional Mandate - legal acts and other agreements". The demographic data collected on voluntary basis depend on the availability and on the quality of information available in the National Statistical Institutes. For more specific information on mandatory/voluntary data collection see 6.1. Institutional Mandate - legal acts and other agreements.   The following data on acquisition and loss of citizenship are collected:Acquisitions of  citizenship by age, sex and former citizenshipLoss of citizenship by sex and new citizenship   Naturalisation rates: based on the different breakdowns of data on acquisition of citizenship and migrant population received, Eurostat produces the following:Statistics available in migr_acqs:                  a.   share of foreign citizens who have acquired citizenship                  b.   share of EU citizens who have acquired citizenship                  c.   share of  non-EU citizens who have acquired citizenship
    • August 2018
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 August, 2018
      Select Dataset
      The labour market policy (LMP) database was developed and maintained by Eurostat till 2013. From 2014, the LMP database is developed and maintained by European Commission's Directorate General for Employment, Social Affairs and Inclusion and LMP data are disseminated by Eurostat. European Commission's LMP database provides information on labour market interventions, which are government actions to help and support the unemployed and other disadvantaged groups in the transition from unemployment or inactivity to work. The scope of the LMP database is limited to interventions that are explicitly targeted at groups of persons with difficulties in the labour market: the unemployed, persons employed but at risk of involuntary job loss and persons currently considered as inactive persons but who would like to enter the labour market. LMP statistics are one of the data sources for monitoring the Employment Guidelines (part II of the Europe 2020 Integrated Guidelines) through the Europe 2020 Joint Assessment Framework (JAF). The guidelines specifically refer to the provision of active labour market policies, which cover LMP measures and LMP services, and adequate social security systems, which include LMP supports. The unit of observation in the LMP database is the labour market intervention and data on the expenditure and participants for each intervention are collected annually from administrative sources in each country. The database also collects extensive qualitative information that describes each intervention, how it works, the main target groups, etc. LMP interventions are classified by type of action into three broad types – services, measures and supports – and into 9 detailed categories (see 3.2 Classification system). The LMP database covers all EU Member States and Norway. Data for the EU-15 countries and Norway are available from 1998 whilst the more recently acceded EU countries started providing data at different times from 2003 onwards. The following data and metadata are available:Summary tables of expenditure and participants by type of actionFor each country: detailed tables of expenditure and participants by interventionLMP based indicators for monitoring the Employment Guidelines (for definitions see annexes below)Reference data on persons registered with Public Employment Services (PES)Qualitative reports describing the interventions in each country
    • August 2018
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 August, 2018
      Select Dataset
      Eurostat Dataset Id:lmp_ind_actsup The labour market policy (LMP) database was developed and maintained by Eurostat till 2013. From 2014, the LMP database is developed and maintained by European Commission's Directorate General for Employment, Social Affairs and Inclusion and LMP data are disseminated by Eurostat. European Commission's LMP database provides information on labour market interventions, which are government actions to help and support the unemployed and other disadvantaged groups in the transition from unemployment or inactivity to work. The scope of the LMP database is limited to interventions that are explicitly targeted at groups of persons with difficulties in the labour market: the unemployed, persons employed but at risk of involuntary job loss and persons currently considered as inactive persons but who would like to enter the labour market. LMP statistics are one of the data sources for monitoring the Employment Guidelines (part II of the Europe 2020 Integrated Guidelines) through the Europe 2020 Joint Assessment Framework (JAF). The guidelines specifically refer to the provision of active labour market policies, which cover LMP measures and LMP services, and adequate social security systems, which include LMP supports. The unit of observation in the LMP database is the labour market intervention and data on the expenditure and participants for each intervention are collected annually from administrative sources in each country. The database also collects extensive qualitative information that describes each intervention, how it works, the main target groups, etc. LMP interventions are classified by type of action into three broad types – services, measures and supports – and into 9 detailed categories (see 3.2 Classification system). The LMP database covers all EU Member States and Norway. Data for the EU-15 countries and Norway are available from 1998 whilst the more recently acceded EU countries started providing data at different times from 2003 onwards. The following data and metadata are available:Summary tables of expenditure and participants by type of actionFor each country: detailed tables of expenditure and participants by interventionLMP based indicators for monitoring the Employment Guidelines (for definitions see annexes below)Reference data on persons registered with Public Employment Services (PES)Qualitative reports describing the interventions in each country
    • May 2020
      Source: International Labour Organization
      Uploaded by: Knoema
      Accessed On: 08 May, 2020
      Select Dataset
      This indicator aims to capture the share of persons in the labour force protected through a contributory pension scheme (with benefits guaranteed but not currently being received). It provides information about the proportion of the labour force that will receive an old age pension once reaching pensionable age. This right to income security in old age is guaranteed by the prior payment of premiums or contributions, i.e. before the occurrence of the insured contingency. For more information, refer to our resources on methods.
    • September 2014
      Source: International Labour Organization
      Uploaded by: Knoema
      Accessed On: 31 August, 2018
      Select Dataset
      This indicator aims to capture the share of persons in the labour force protected through a contributory pension scheme (with benefits guaranteed but not currently being received). It provides information about the proportion of the labour force that will receive an old age pension once reaching pensionable age. This right to income security in old age is guaranteed by the prior payment of premiums or contributions, i.e. before the occurrence of the insured contingency.
    • September 2014
      Source: International Labour Organization
      Uploaded by: Knoema
      Accessed On: 31 August, 2018
      Select Dataset
      This indicator aims to capture the share of persons of working age protected through a contributory pension scheme (with benefits guaranteed but not currently being received). It provides information about the proportion of the working-age population that will receive an old age pension once reaching pensionable age. This right to income security in old age is guaranteed by the prior payment of premiums or contributions, i.e. before the occurrence of the insured contingency.
    • May 2020
      Source: International Labour Organization
      Uploaded by: Knoema
      Accessed On: 08 May, 2020
      Select Dataset
      This indicator aims to capture the share of persons of working age protected through a contributory pension scheme (with benefits guaranteed but not currently being received). It provides information about the proportion of the working-age population that will receive an old age pension once reaching pensionable age. This right to income security in old age is guaranteed by the prior payment of premiums or contributions, i.e. before the occurrence of the insured contingency. For more information, refer to our resources on methods.
    • January 2010
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      Select Dataset
      The tables presented in the Census 1990/91 round cover the total population and housing for 19 countries. Five main topics are covered: structure of population, active population, education level, households and dwellings. The level of completeness of the tables depends largely on the availability of data at the respective national statistical institutes.
    • March 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 29 November, 2015
      Select Dataset
      The tables presented in the Census 1990/91 round cover the total population and housing for 19 countries. Five main topics are covered: structure of population, active population, education level, households and dwellings. The level of completeness of the tables depends largely on the availability of data at the respective national statistical institutes.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 19 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2024
      Select Dataset
      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.
    • March 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 29 November, 2015
      Select Dataset
      The tables presented in the Census 1990/91 round cover the total population and housing for 19 countries. Five main topics are covered: structure of population, active population, education level, households and dwellings. The level of completeness of the tables depends largely on the availability of data at the respective national statistical institutes.
    • March 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 29 November, 2015
      Select Dataset
      The tables presented in the Census 1990/91 round cover the total population and housing for 19 countries. Five main topics are covered: structure of population, active population, education level, households and dwellings. The level of completeness of the tables depends largely on the availability of data at the respective national statistical institutes.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 March, 2024
      Select Dataset
      According to the definitions of the International Labour Organisation (ILO) for the purposes of the labour market statistics people are classified as employed, unemployed and economically inactive. The economically active population is the sum of employed and unemployed persons. Inactive persons are those who, during the reference week, were neither employed nor unemployed. The data source from the quarterly EU Labour Force Survey (EU LFS).
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 14 March, 2024
      Select Dataset
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2024
      Select Dataset
      The indicator is defined as the percentage of the population in a given age group who are economically active. According to the definitions of the International Labour Organisation (ILO) people are classified as employed, unemployed and economically inactive for the purposes of labour market statistics. The economically active population (also called labour force) is the sum of employed and unemployed persons. Inactive persons are those who, during the reference week, were neither employed nor unemployed. The indicator is based on the EU Labour Force Survey.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2024
      Select Dataset
      The indicator is defined as the percentage of the population aged 15-64 who are economically active. According to the definitions of the International Labour Organisation (ILO) people are classified as employed, unemployed and economically inactive for the purposes of labour market statistics. The economically active population (also called labour force) is the sum of employed and unemployed persons. Inactive persons are those who, during the reference week, were neither employed nor unemployed. The indicator is based on the EU Labour Force Survey.
    • March 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 15 April, 2019
      Select Dataset
      The ad-hoc module "labour market situation of migrants and their immediate descendants" aimed at comparing the situation on the labour market for first generation immigrants, second generation immigrants, and nationals, and further to analyse the factors affecting the integration in and adaptation to the labour market.
    • July 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 24 November, 2015
      Select Dataset
      In 2011, the European Union Labour Force Survey (EU-LFS) included an ad hoc module (AHM) on employment of disabled people. The module consisted of 11 variables dealing with:Health problems and difficulties in basic activities;Limitations in work caused by health problems/difficulties in basic activities;Special assistance needed or used by people with health problems/difficulties in basic activities;Limitation in work because of other reasons. On the basis of how the module was operationalised, the following two main definitions for disability were considered for presenting the results:Disabled persons = People having a basic activity difficulty (such as seeing, hearing, walking, communicating);Disabled persons = People having a work limitation caused by a longstanding health condition and/or a basic activity difficulty. 32 countries have implemented this module: the EU 28 Member States plus Turkey, Iceland, Norway and Switzerland. The Norwegian data are not disseminated because the AHM questionnaire in Norway only partly complies with the Commission Regulation (EU) No 317/2010 and consequently, the data are incomplete and partly comparable. Missing values, don't know and refusal answers are not considered in the calculations. It means the indicators have been worked out on the respondents and validated answers only.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 March, 2024
      Select Dataset
      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.
    • September 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 15 September, 2023
      Select Dataset
      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.
    • October 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 November, 2016
      Select Dataset
      Eurostat Dataset Id:med_ec0 The focus of this domain is on the following countries:Algeria, Egypt, Israel, Jordan, Lebanon, Morocco, Palestinian Authority, Syria, Tunisia. Data are provided for over 1000 indicators depending on the country.   The data for the Mediterranean partner countries are supplied by and under the responsibility of the national statistical authorities  of each of the countries or territories. The data and their denomination in no way constitute the  expression of an opinion by the European Commission on the  legal status of a country or territory or on the delimitation of its frontiers. Â
    • April 2024
      Source: World Bank
      Uploaded by: Shylesh Naik
      Accessed On: 12 April, 2024
      Select Dataset
      Adequacy of Social Assistance and Social Insurance benefits by quintiles of per capita welfare Impacts on poverty and inequality of Social Assistance and Social Insurance programs
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 19 April, 2024
      Select Dataset
      The indicator reflects the purchasing power of households and their ability to invest in goods and services or save for the future, by accounting for taxes and social contributions and monetary in-kind social benefits. It is calculated as the adjusted gross disposable income of households and Non-Profit Institutions Serving Households (NPISH) divided by the purchasing power parities (PPP) of the actual individual consumption of households and by the total resident population. The values are also offered as an index calculated in relation to the European Union average set to equal 100. If the index of a country is higher than 100, this country's level of adjusted gross disposable income of households per person is higher than the EU average and vice versa. Please note that this index is intended for cross-country comparisons rather than for temporal comparisons. Finally, the disparities indicator offered for EU27 (from 2020) is calculated as the coefficient of variation of the national figures. This time series offers a measure of the convergence of household income between the Member States of the EU.
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 April, 2024
      Select Dataset
      Residence permits data contain statistical information based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007 with reference to: first permits granted to third-country nationals during the reference year, disaggregated by citizenship, reason for the permit being issued and by the length of validity of the permit; permits granted during the reference period on the occasion of person changing immigration status or reason to stay, disaggregated by citizenship, reason for the permit being issued and by the length of validity; permits valid at the end of the reference period, disaggregated by citizenship, reasons for the permit being issued and by the length of validity; number of long-term residents at the end of reference period. Statistics on EU Blue Cards contain information based on the Article 20 of the Council Directive 2009/50/EC of 25 May 2009 on: EU Blue Cards granted, renewed and withdrawn;Admitted family members of EU Blue Cards holders;EU Blue Cards holders and family members by Member State of previous residenceStatistics on Single permits contain information based on the Article 15 (2) Directive 2011/98/EU of the European Parliament and of the Council of 13 December 2011 on a single application procedure for a single permit for third-country nationals to reside and work in the territory of a Member State and on a common set of rights for third-country workers legally residing in a Member State. Eurostat collects data on first permits granted to third-country nationals (persons who are not EU citizens) during the reference year and data on permits valid at the end of the reference period. Statistics are disaggregated by citizenship, reason for the permit being issued and by the length of validity of the permit. In addition, Eurostat collects data on permits granted during the reference period on the occasion of the person changing immigration status or reason for stay (disaggregated by reason for the new permit being issued) and on the number of long-term residents at the end of the reference period. Since the 2010 reference year, data on first permits issued, stock of all valid permits and the number of long-term residents are additionally collected with a voluntary disaggregation by age (5-year age groups) and sex. These statistics are collected by Eurostat on an annual basis. Data are entirely based on administrative sources with the exception of the United Kingdom1 and are provided mainly by the Ministries of Interior or related Immigration Agencies. Data are generally disseminated in June and July in the year following  the  reference year. The indicators presented in the table 'Long-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%)' are produced within the framework of the pilot study related to the integration of migrants in the Member States, following the Zaragoza Declaration. The Zaragoza Declaration, adopted in April 2010 by EU Ministers responsible for immigrant integration issues, and approved at the Justice and Home Affairs Council on 3-4 June 2010, called upon the Commission to undertake a pilot study to examine proposals for common integration indicators and to report on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators. In June 2010 the ministers agreed "to promote the launching of a pilot project with a view to the evaluation of integration policies, including examining the indicators and analysing the significance of the defined indicators taking into account the national contexts, the background of diverse migrant populations and different migration and integration policies of the Member States, and reporting on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators". These indicators are produced on the basis of residence permit statistics collected by Eurostat on the basis of Article 6 of the Migration Statistics Regulation 862/2007. As a denominator data on the stock of all valid permits to stay at the end of each reporting year are used. As a numerator data on the stock of long-term residents are used.  Two types of long term residents are distinguished in accordance with the residence permit statistics: EU long-term resident status (as regulated by the Council Directive 2003/109/EC) and the National long-term resident status (as regulated by the national legislation in the Member States). Data for some countries may be a subject of revisions due to certain inconsistencies between categories. 1Please note that the statistics for the United Kingdom use different data sources to those used in other Member States. For that reason, the statistics on residence permits published by Eurostat for UK may not be fully comparable with the statistics reported by other countries. Statistics for the United Kingdom are not based on records of residence permits issued (as the United Kingdom does not operate a system of residence permits), but instead relate to the numbers of arriving non-EU citizens permitted to enter the country under selected immigration categories. According to the United Kingdom authorities, data are estimated from a combination of information due to be published in the Home Office Statistical Bulletin 'Control of Immigration: Statistics, United Kingdom' and unpublished management information. The 'Other reasons' category includes: diplomat, consular officer treated as exempt from control; retired persons of independent means; all other passengers given limited leave to enter who are not included in any other category; non-asylum discretionary permissions.
    • June 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      Select Dataset
      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)
    • May 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 May, 2016
      Select Dataset
      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)
    • January 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 January, 2024
      Select Dataset
      The indicator measures the share of people aged 25 to 64 who stated that they received formal or non-formal education and 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'. Adult learning covers both general and vocational formal and non-formal learning activities. Adult learning usually refers to learning activities after the end of initial education. Data stem from the EU Labour Force Survey (EU-LFS).
    • January 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 January, 2024
      Select Dataset
    • February 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 February, 2019
      Select Dataset
      This ad-hoc module "transition from work to retirement" aimed at answering the following main questions: how people leave the labour market,why they left the labour market,why they did not stay longer and,how long the active population, aged 50 to 69, expects to be in the labour market.
    • October 2021
      Source: Chief Executives Board for Coordination, UN
      Uploaded by: Knoema
      Accessed On: 20 October, 2021
      Select Dataset
      Agency Revenue By Government Donor for assessed revenue type
    • April 2021
      Source: Ministry of Tourism, Government of India
      Uploaded by: Knoema
      Accessed On: 11 May, 2021
      Select Dataset
      This dataset provides data for foreign tourist arrivals distributed by age  group.
    • February 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 February, 2024
      Select Dataset
    • February 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 February, 2024
      Select Dataset
    • November 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 29 November, 2023
      Select Dataset
    • November 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2023
      Select Dataset
      The aggregate replacement ratio is gross median individual pension income of the population aged 65–74 relative to gross median individual earnings from work of the population aged 50–59, excluding other social benefits.
    • May 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 June, 2017
      Select Dataset
      The indicator is defined as the ratio of the median individual gross pensions of 65-74 age category relative to median individual gross earnings of 50-59 age category, excluding other social benefits. For 2004-2005 data, aggregate income replacement ratio is based on net income components for ES, EL, IT, LV, PT. EU aggregate figures are calculated as population-weighted averages of national values.
    • March 2018
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 March, 2018
      Select Dataset
      Ratio of the median individual gross pensions of 65-74 age category relative to median individual gross earnings of 50-59 age category, excluding other social benefits.
    • November 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2023
      Select Dataset
      The indicator is defined as the ratio of the median individual gross pensions of 65-74 age category relative to median individual gross earnings of 50-59 age category, excluding other social benefits. The indicator is based on the EU-SILC (statistics on income, social inclusion and living conditions).
    • November 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2023
      Select Dataset
      The domain "Income and living conditions" covers four topics: people at risk of poverty or social exclusion, income distribution and monetary poverty, living conditions and material deprivation, which are again structured into collections of indicators on specific topics. The collection "People at risk of poverty or social exclusion" houses main indicator on risk of poverty or social inclusion included in the Europe 2020 strategy as well as the intersections between sub-populations of all Europe 2020 indicators on poverty and social exclusion. The collection "Income distribution and monetary poverty" houses collections of indicators relating to poverty risk, poverty risk of working individuals as well as the distribution of income. The collection "Living conditions" hosts indicators relating to characteristics and living conditions of households, characteristics of the population according to different breakdowns, health and labour conditions, housing conditions as well as childcare related indicators. The collection "Material deprivation" covers indicators relating to economic strain, durables, housing deprivation and environment of the dwelling.
    • March 2018
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 March, 2018
      Select Dataset
      The 'current aggregate measurement of support' (AMS) is the measure for domestic subsidies for agriculture under the WTO Agreement of Agriculture. It consists of the so-called Amber Box which includes all internal support measures considered to distort production and trade that are not excluded pursuant to other provisions of the Agreement. The data shown in this table is AMS after de minimis, i.e. after deduction of the permitted minimal support of 5% of agricultural production for developed countries. AMS is only calculated for the EU as a whole, because there is only one common reduction commitment (support ceiling) for the EU in the Agreement and not separate ones for each Member State. Switzerland and Liechtenstein have a common reduction commitment, data for Switzerland thus shows the combined AMS of Liechtenstein and Switzerland.
    • November 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 December, 2017
      Select Dataset
      Data in this domain constitute only a small part of the entire National Accounts data range available from Eurostat. Annual and quarterly national accounts are compiled in accordance with the European System of Accounts - ESA 2010as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013. The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. The annual data of this domain consists of the following collections: 1. Main GDP aggregates: main components from the output, expenditure and income side.nama_10_gdp: GDP and main components (output, expenditure and income   The quarterly data of this domain consists of the following collections 1. Main GDP aggregates, main components from the output, expenditure and income side, expenditure breakdowns by industry and assets. namq_10_ma: Main GDP aggregatesnamq_10_gdp: GDP and main components (output, expenditure and incomenamq_10_fcs: Final consumption aggregates by durabilitynamq_10_exi: Exports and imports by Member States of the EU/third countries 2. Breakdowns of GDP aggregates and employment data by main industries and asset classes. namq_10_bbr: Basic breakdowns main GDP aggregates and employment (by industry and assets)namq_10_a10: Gross value added and income by A*10 industrynamq_10_an6: Gross fixed capital formation by AN_F6 asset typenamq_10_a10_e: Employment by A*10 industry breakdowns Geographical entities covered are the European Union, the euro area, EU Member States, Candidate Countries, EFTA countries, US, Japan and possibly other countries on an ad-hoc basis. Data sources: National Statistical Institutes
    • November 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 December, 2017
      Select Dataset
      Data in this domain constitute only a small part of the entire National Accounts data range available from Eurostat. Annual and quarterly national accounts are compiled in accordance with the European System of Accounts - ESA 2010as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013. The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. The annual data of this domain consists of the following collections: 1. Main GDP aggregates: main components from the output, expenditure and income side. nama_10_gdp: GDP and main components (output, expenditure and income   The quarterly data of this domain consists of the following collections 1. Main GDP aggregates, main components from the output, expenditure and income side, expenditure breakdowns by industry and assets. namq_10_ma: Main GDP aggregatesnamq_10_gdp: GDP and main components (output, expenditure and incomenamq_10_fcs: Final consumption aggregates by durabilitynamq_10_exi: Exports and imports by Member States of the EU/third countries 2. Breakdowns of GDP aggregates and employment data by main industries and asset classes. namq_10_bbr: Basic breakdowns main GDP aggregates and employment (by industry and assets)namq_10_a10: Gross value added and income by A*10 industrynamq_10_an6: Gross fixed capital formation by AN_F6 asset typenamq_10_a10_e: Employment by A*10 industry breakdowns Geographical entities covered are the European Union, the euro area, EU Member States, Candidate Countries, EFTA countries, US, Japan and possibly other countries on an ad-hoc basis. Data sources: National Statistical Institutes
    • November 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 December, 2017
      Select Dataset
      Data in this domain constitute only a small part of the entire National Accounts data range available from Eurostat. Annual and quarterly national accounts are compiled in accordance with the European System of Accounts - ESA 2010as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013. The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. The annual data of this domain consists of the following collections: 1. Main GDP aggregates: main components from the output, expenditure and income side.nama_10_gdp: GDP and main components (output, expenditure and income   The quarterly data of this domain consists of the following collections 1. Main GDP aggregates, main components from the output, expenditure and income side, expenditure breakdowns by industry and assets. namq_10_ma: Main GDP aggregatesnamq_10_gdp: GDP and main components (output, expenditure and incomenamq_10_fcs: Final consumption aggregates by durabilitynamq_10_exi: Exports and imports by Member States of the EU/third countries 2. Breakdowns of GDP aggregates and employment data by main industries and asset classes. namq_10_bbr: Basic breakdowns main GDP aggregates and employment (by industry and assets)namq_10_a10: Gross value added and income by A*10 industrynamq_10_an6: Gross fixed capital formation by AN_F6 asset typenamq_10_a10_e: Employment by A*10 industry breakdowns Geographical entities covered are the European Union, the euro area, EU Member States, Candidate Countries, EFTA countries, US, Japan and possibly other countries on an ad-hoc basis. Data sources: National Statistical Institutes
    • November 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 December, 2017
      Select Dataset
      Data in this domain constitute only a small part of the entire National Accounts data range available from Eurostat. Annual and quarterly national accounts are compiled in accordance with the European System of Accounts - ESA 2010as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013. The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. The annual data of this domain consists of the following collections: 1. Main GDP aggregates: main components from the output, expenditure and income side.nama_10_gdp: GDP and main components (output, expenditure and income   The quarterly data of this domain consists of the following collections 1. Main GDP aggregates, main components from the output, expenditure and income side, expenditure breakdowns by industry and assets. namq_10_ma: Main GDP aggregatesnamq_10_gdp: GDP and main components (output, expenditure and incomenamq_10_fcs: Final consumption aggregates by durabilitynamq_10_exi: Exports and imports by Member States of the EU/third countries 2. Breakdowns of GDP aggregates and employment data by main industries and asset classes. namq_10_bbr: Basic breakdowns main GDP aggregates and employment (by industry and assets)namq_10_a10: Gross value added and income by A*10 industrynamq_10_an6: Gross fixed capital formation by AN_F6 asset typenamq_10_a10_e: Employment by A*10 industry breakdowns Geographical entities covered are the European Union, the euro area, EU Member States, Candidate Countries, EFTA countries, US, Japan and possibly other countries on an ad-hoc basis. Data sources: National Statistical Institutes
    • November 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 December, 2017
      Select Dataset
      Data in this domain constitute only a small part of the entire National Accounts data range available from Eurostat. Annual and quarterly national accounts are compiled in accordance with the European System of Accounts - ESA 2010as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013. The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. The annual data of this domain consists of the following collections: 1. Main GDP aggregates: main components from the output, expenditure and income side. nama_10_gdp: GDP and main components (output, expenditure and income   The quarterly data of this domain consists of the following collections 1. Main GDP aggregates, main components from the output, expenditure and income side, expenditure breakdowns by industry and assets. namq_10_ma: Main GDP aggregatesnamq_10_gdp: GDP and main components (output, expenditure and incomenamq_10_fcs: Final consumption aggregates by durabilitynamq_10_exi: Exports and imports by Member States of the EU/third countries 2. Breakdowns of GDP aggregates and employment data by main industries and asset classes. namq_10_bbr: Basic breakdowns main GDP aggregates and employment (by industry and assets)namq_10_a10: Gross value added and income by A*10 industrynamq_10_an6: Gross fixed capital formation by AN_F6 asset typenamq_10_a10_e: Employment by A*10 industry breakdowns Geographical entities covered are the European Union, the euro area, EU Member States, Candidate Countries, EFTA countries, US, Japan and possibly other countries on an ad-hoc basis. Data sources: National Statistical Institutes
    • March 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 15 March, 2016
      Select Dataset
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 14 March, 2024
      Select Dataset
      The indicator is a partial labour productivity measure of the agricultural sector. Agricultural factor income measures the income generated by farming, which is used to remunerate borrowed or rented factors of production (capital, wages and land rents) as well as own production factors (own labour, capital and land). Factor income corresponds to the deflated (real) net value added at factor cost of agriculture. The implicit price index of GDP is used as deflator. Annual work units (AWUs) are defined as full-time equivalent employment (corresponding to the number of full-time equivalent jobs), i.e. as total hours worked divided by the average annual number of hours worked in full-time jobs within the economic territory
    • March 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 March, 2016
      Select Dataset
      The farm holder is the legal or physical person taking benefit of the agricultural activity. They are only accounted for as the individual holders and not the holders of group holdings.
    • March 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 March, 2016
      Select Dataset
      The farm holder is the legal or physical person taking benefit of the agricultural activity. They are only accounted the individual holders and not the holders of group holdings.
    • December 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 January, 2024
      Select Dataset
      The farm holder is the natural person, on whose account and in whose name the holding is operated and who is legally and economically responsible for the holding. If the holder is a group holding, the data relates to the person considered holder.
    • December 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 January, 2024
      Select Dataset
      The farm manager is the natural person responsible for the normal daily financial and production routines of running the holding.
    • February 2021
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 09 February, 2021
      Select Dataset
      Agricultural holding: a single unit both technically and economically, which has single management and which produces agricultural products. The total area of the holding consists of the agricultural area utilized by the holding (arable land, kitchen gardens, permanent grassland and permanent crops) and other land.
    • December 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 January, 2024
      Select Dataset
      The total area of the holding consists of the agricultural area utilized by the holding (arable land, kitchen gardens, permanent grassland and permanent crops) and other land (unutilised agricultural land, wooded land and other land).
    • December 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 January, 2024
      Select Dataset
      The monetary economic size of the farm is expressed in Standard Output (SO). The SO is the average monetary value of the agricultural output at farm-gate price, in euro per hectare or per head of livestock.
    • March 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 March, 2016
      Select Dataset
      The total area of the holding consists of the agricultural area utilized by the holding (arable land, kitchen gardens, permanent grassland and meadow and permanent crops) and other land. The agricultural area utilized for farming includes the area under main crops for harvest in the year of the survey.
    • March 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 March, 2016
      Select Dataset
      The total area of the holding consists of the agricultural area utilized by the holding (arable land, kitchen gardens, permanent grassland and meadow and permanent crops) and other land. The agricultural area utilized for farming includes the area under main crops for harvest in the year of the survey.
    • March 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 March, 2016
      Select Dataset
      The total area of the holding consists of the agricultural area utilized by the holding (arable land, kitchen gardens, permanent grassland and meadow and permanent crops) and other land. The agricultural area utilized for farming includes the area under main crops for harvest in the year of the survey.
    • March 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 March, 2016
      Select Dataset
      The total area of the holding consists of the agricultural area utilized by the holding (arable land, kitchen gardens, permanent grassland and meadow and permanent crops) and other land. The agricultural area utilized for farming includes the area under main crops for harvest in the year of the survey.
    • March 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 March, 2016
      Select Dataset
      Other gainful activity is an activity that do not comprise any farm work but which directly related to the holding using its resources (area, machinery, buildings, etc.) or the products of the holding and which have an economic impact on the holding. It is carried out by the holder, his/hers family members or one or more partners on a group holding. For example such activities are: providing accommodation, processing of farm products, renewable energy production, etc.
    • December 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 January, 2024
      Select Dataset
      Livestock are the production animals that are in direct possession or management of the holding on the reference day of the survey.
    • December 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 21 December, 2023
      Select Dataset
      The Economic Accounts for Agriculture (EAA) provide detailed information on income in the agricultural sector. The purpose is to analyse the production process of the agricultural industry and the primary income generated by this production. The accounts are therefore based on the industry concept. The EAA accounts are detailed data on value of output (producer prices and basic prices), intermediate consumption, subsidies and taxes, consumption of fixed capital, rent and interests, capital formation etc. The values are in current as well as in constant prices. Agricultural Labour Input (ALI) and Unit Values (UV) are an integrated part of the overall concept of Economic Accounts for Agriculture. The Economic accounts for agriculture (EAA) are a satellite account of the European System of Accounts (ESA2010), providing complementary information and concepts adapted to the particular nature of the agricultural industry. Although their structure very closely matches that of the national accounts, their compilation requires the formulation of appropriate rules and methods. National Statistical Institutes or Ministries of Agriculture are responsible for data collection and calculation of national EAA, in accordance with EC Regulations. Eurostat is responsible for the EU aggregations. Regional data EAA accounts are compiled at regional level (NUTS2), but only in values in current prices. The labour input data and Unit values are not broken down to regional level. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data. Frequency of data collection for data under Regulation (EC) 138/2004 and gentlemen's agreement, deadline for transmission for years 2015-2016.
    • December 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 21 December, 2023
      Select Dataset
      The Economic Accounts for Agriculture (EAA) provide detailed information on income in the agricultural sector. The purpose is to analyse the production process of the agricultural industry and the primary income generated by this production. The accounts are therefore based on the industry concept. The EAA accounts are detailed data on value of output (producer prices and basic prices), intermediate consumption, subsidies and taxes, consumption of fixed capital, rent and interests, capital formation etc. The values are in current as well as in constant prices. Agricultural Labour Input (ALI) and Unit Values (UV) are an integrated part of the overall concept of Economic Accounts for Agriculture. The Economic accounts for agriculture (EAA) are a satellite account of the European System of Accounts (ESA2010), providing complementary information and concepts adapted to the particular nature of the agricultural industry. Although their structure very closely matches that of the national accounts, their compilation requires the formulation of appropriate rules and methods. National Statistical Institutes or Ministries of Agriculture are responsible for data collection and calculation of national EAA, in accordance with EC Regulations. Eurostat is responsible for the EU aggregations. Regional data EAA accounts are compiled at regional level (NUTS2), but only in values in current prices. The labour input data and Unit values are not broken down to regional level. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data. Frequency of data collection for data under Regulation (EC) 138/2004 and gentlemen's agreement, deadline for transmission for years 2015-2016.   Reg. CE 138/2004 Gentlemen's agreement Web Form in eDamis Excel SDTT file in CIRCA Transmission date via eDamis Edamis DATASET to use   EAA Second Estimates 2015   X - - X 31 January 2016 COSAEA_AGR2_A EAA Constant N-1 prices Final - 2014   X - - X 30 September 2015   COSAEA_AGR3CON_A EAA at current prices Final - 2014   X - - X COSAEA_AGR3CUR_A   UV (unit Values) 2014   - X X - COSAEA_UV_A   EAA Regional data 2013   - X - X COSAEA_REGION_A   ALI (Labour Input) final 2014   X - X - COSAEA_ALI3_A   ALI (Labour Input)1st estimates 2015   X - X - 30 November 2015 COSAEA_ALI3_A   ALI (Labour Input) 2nd estimates 2015   X - X - 31 January 2016 COSAEA_ALI3_A   EAA First Estimates 2015   X - - X 30 November 2015 COSAEA_AGR1_A
    • January 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 19 January, 2024
      Select Dataset
      The agricultural land prices and rents methodology intends to collect comparable statistics on the prices and rents of agricultural land for agricultural use in the European Union, as land is a primary resource for agricultural production. The EU enlargements increased the need for data on agricultural land prices and rents. The main uses of these statistics are comparisons among the Member States and their regions and analyses of the trends in agricultural land prices and rents.
    • December 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 April, 2018
      Select Dataset
      The agricultural land prices and rents methodology intends to collect comparable statistics on the prices and rents of agricultural land for agricultural use in the European Union, as land is a primary resource for agricultural production. The EU enlargements increased the need for data on agricultural land prices and rents. The main uses of these statistics are comparisons among the Member States and their regions and analyses of the trends in agricultural land prices and rents.
    • February 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 February, 2024
      Select Dataset
      The agricultural land prices and rents methodology intends to collect comparable statistics on the prices and rents of agricultural land for agricultural use in the European Union, as land is a primary resource for agricultural production. The EU enlargements increased the need for data on agricultural land prices and rents. The main uses of these statistics are comparisons among the Member States and their regions and analyses of the trends in agricultural land prices and rents.
    • December 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 April, 2018
      Select Dataset
      The agricultural land prices and rents methodology intends to collect comparable statistics on the prices and rents of agricultural land for agricultural use in the European Union, as land is a primary resource for agricultural production. The EU enlargements increased the need for data on agricultural land prices and rents. The main uses of these statistics are comparisons among the Member States and their regions and analyses of the trends in agricultural land prices and rents.
    • January 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 January, 2017
      Select Dataset
      The domain EUROFARM (ef) contains information (statistical tables) on structure of agricultural holdings collected through agricultural structure surveys. The data of the domain have been organised into two collections: Results of the farm structure surveys contains data from 1990 onwards based on the 1988 legislation andResults of the farm structure surveys based on the legislation from 2008. This collection contains the data from the 2010 Census onwards as well as the data for the surveys 2007 and 2005. Farm Structure Survey data are used to collect information on agricultural holdings in the Member States at different geographic levels (Member States, regions, districts) and over periods (follow up the changes in agricultural sector), thus provide a base for decision making in the Common Agricultural Policy. Two kinds of Farm Structure Survey (FSS) are carried out by Member States: a basic survey (full scope Agricultural Census - AC) every 10 years,several sample based intermediate surveys between them. However for certain characteristics the Member States may use sample base for every survey. The calendar for the surveys to be held in all Member States is agreed by the Agricultural Statistics Committee of the European Commission. For a given survey year, Member States have to conduct their surveys within the agreed time-frame, thus all the data are as comparable as possible. The FSS are organised in all Member States on a harmonised base. Whereas the characteristics are based on community legislation, the same data are available for all countries in case of each survey. The data on individual agricultural holdings are collected by all Member States and sent to Eurostat. The aggregated results are disseminated through statistical tables. The variables are arranged into groups: general overview with key variables,and other specialized groups containing detailed data onland uselivestockfarm labour forcerural development issues as well as management and practices. The 2010 survey additionally provides the results of the survey on agricultural production methods (SAPM). The scope of the survey is agriculture, while the survey unit is the agricultural holding (farm). Data for basic surveys are available in a three-level geographical breakdown of the whole country, the regions and the district; while data for intermediate surveys are only available upon the two-levels of country and regions. Since FSS 1999/2000 information about local farm location is collected in most countries, so that the data can also be disseminated by NUTS and are robust regarding the changes in the NUTS definition. The FSS 2009/2010 information is inline with the NUTS 2010 classification: Regulation (EU) No 31/2011 amending the NUTS classification from January 2003. The Eurofarm domain does not cover the whole territory only the land covered by the agricultural holdings. So the land use data without link with other farm characteristics should be downloaded by the user from the relevant domain. Specific national data about crops, animals or agricultural labour force can be found in other domains, without link between the other information at farm level. For a comprehensive description of the domain, please consult detailed structure (See annex at the bottom of the page). Regional Data Data for basic surveys are available in a three-level geographical breakdown of the whole country, the regions and the district; while data for intermediate surveys are only available upon the two-levels of country and regions. Since FSS 1999/2000 information about local farm location is collected in most countries, so that the data can also be disseminated by NUTS classification and are robust regarding the changes in the NUTS definition. The FSS 2009/2010 information is inline with the NUTS 2010 classification: Regulation (EU) No 31/2001 amending the NUTS classification from January 2012. 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.
    • January 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 January, 2017
      Select Dataset
      The domain EUROFARM (ef) contains information (statistical tables) on structure of agricultural holdings collected through agricultural structure surveys. The data of the domain have been organised into two collections: Results of the farm structure surveys contains data from 1990 onwards based on the 1988 legislation andResults of the farm structure surveys based on the legislation from 2008. This collection contains the data from the 2010 Census onwards as well as the data for the surveys 2007 and 2005. Farm Structure Survey data are used to collect information on agricultural holdings in the Member States at different geographic levels (Member States, regions, districts) and over periods (follow up the changes in agricultural sector), thus provide a base for decision making in the Common Agricultural Policy. Two kinds of Farm Structure Survey (FSS) are carried out by Member States: a basic survey (full scope Agricultural Census - AC) every 10 years,several sample based intermediate surveys between them. However for certain characteristics the Member States may use sample base for every survey. The calendar for the surveys to be held in all Member States is agreed by the Agricultural Statistics Committee of the European Commission. For a given survey year, Member States have to conduct their surveys within the agreed time-frame, thus all the data are as comparable as possible. The FSS are organised in all Member States on a harmonised base. Whereas the characteristics are based on community legislation, the same data are available for all countries in case of each survey. The data on individual agricultural holdings are collected by all Member States and sent to Eurostat. The aggregated results are disseminated through statistical tables. The variables are arranged into groups: general overview with key variables,and other specialized groups containing detailed data onland uselivestockfarm labour forcerural development issues as well as management and practices. The 2010 survey additionally provides the results of the survey on agricultural production methods (SAPM). The scope of the survey is agriculture, while the survey unit is the agricultural holding (farm). Data for basic surveys are available in a three-level geographical breakdown of the whole country, the regions and the district; while data for intermediate surveys are only available upon the two-levels of country and regions. Since FSS 1999/2000 information about local farm location is collected in most countries, so that the data can also be disseminated by NUTS and are robust regarding the changes in the NUTS definition. The FSS 2009/2010 information is inline with the NUTS 2010 classification: Regulation (EU) No 31/2011 amending the NUTS classification from January 2003. The Eurofarm domain does not cover the whole territory only the land covered by the agricultural holdings. So the land use data without link with other farm characteristics should be downloaded by the user from the relevant domain. Specific national data about crops, animals or agricultural labour force can be found in other domains, without link between the other information at farm level. For a comprehensive description of the domain, please consult detailed structure (See annex at the bottom of the page). Regional Data Data for basic surveys are available in a three-level geographical breakdown of the whole country, the regions and the district; while data for intermediate surveys are only available upon the two-levels of country and regions. Since FSS 1999/2000 information about local farm location is collected in most countries, so that the data can also be disseminated by NUTS classification and are robust regarding the changes in the NUTS definition. The FSS 2009/2010 information is inline with the NUTS 2010 classification: Regulation (EU) No 31/2001 amending the NUTS classification from January 2012. 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.
    • March 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 30 March, 2023
      Select Dataset
      The domain EUROFARM (ef) contains information (statistical tables) on structure of agricultural holdings collected through agricultural structure surveys. The data of the domain have been organised into two collections: Results of the farm structure surveys contains data from 1990 onwards based on the 1988 legislation andResults of the farm structure surveys based on the legislation from 2008. This collection contains the data from the 2010 Census onwards as well as the data for the surveys 2007 and 2005. Farm Structure Survey data are used to collect information on agricultural holdings in the Member States at different geographic levels (Member States, regions, districts) and over periods (follow up the changes in agricultural sector), thus provide a base for decision making in the Common Agricultural Policy. Two kinds of Farm Structure Survey (FSS) are carried out by Member States: a basic survey (full scope Agricultural Census - AC) every 10 years,several sample based intermediate surveys between them. However for certain characteristics the Member States may use sample base for every survey. The calendar for the surveys to be held in all Member States is agreed by the Agricultural Statistics Committee of the European Commission. For a given survey year, Member States have to conduct their surveys within the agreed time-frame, thus all the data are as comparable as possible. The FSS are organised in all Member States on a harmonised base. Whereas the characteristics are based on community legislation, the same data are available for all countries in case of each survey. The data on individual agricultural holdings are collected by all Member States and sent to Eurostat. The aggregated results are disseminated through statistical tables. The variables are arranged into groups: general overview with key variables,and other specialized groups containing detailed data onland uselivestockfarm labour forcerural development issues as well as management and practices. The 2010 survey additionally provides the results of the survey on agricultural production methods (SAPM). The scope of the survey is agriculture, while the survey unit is the agricultural holding (farm). Data for basic surveys are available in a three-level geographical breakdown of the whole country, the regions and the district; while data for intermediate surveys are only available upon the two-levels of country and regions. Since FSS 1999/2000 information about local farm location is collected in most countries, so that the data can also be disseminated by NUTS and are robust regarding the changes in the NUTS definition. The FSS 2009/2010 information is inline with the NUTS 2010 classification: Regulation (EU) No 31/2011 amending the NUTS classification from January 2003. The Eurofarm domain does not cover the whole territory only the land covered by the agricultural holdings. So the land use data without link with other farm characteristics should be downloaded by the user from the relevant domain. Specific national data about crops, animals or agricultural labour force can be found in other domains, without link between the other information at farm level. For a comprehensive description of the domain, please consult detailed structure (See annex at the bottom of the page). Regional Data Data for basic surveys are available in a three-level geographical breakdown of the whole country, the regions and the district; while data for intermediate surveys are only available upon the two-levels of country and regions. Since FSS 1999/2000 information about local farm location is collected in most countries, so that the data can also be disseminated by NUTS classification and are robust regarding the changes in the NUTS definition. The FSS 2009/2010 information is inline with the NUTS 2010 classification: Regulation (EU) No 31/2001 amending the NUTS classification from January 2012. 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.
    • April 2024
      Source: John Deere
      Uploaded by: Knoema
      Accessed On: 22 April, 2024
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    • May 2020
      Source: International Labour Organization
      Uploaded by: Knoema
      Accessed On: 08 May, 2020
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      Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.
    • May 2013
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 22 March, 2019
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    • July 2022
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 23 August, 2023
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      The data describe the average use of chemical and mineral fertilizers per area of cropland (arable land and permanent crops) at national, regional, and global level in a time series from 2002 to 2014The data describe the average use of chemical and mineral fertilizers per area of cropland (arable land and permanent crops) at national, regional, and global level in a time series from 2002 to 2015
    • July 2022
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 22 August, 2023
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      The Agri-environmental Indicators—Land domain provides information on the annual evolution of the distribution of agricultural and forest areas, and their sub-components, including irrigated areas, at national, regional and global levels.
    • November 2023
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 11 November, 2023
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      The Livestock Patterns domain of the FAOSTAT Agri-Environmental Indicators contains data on livestock numbers, shares of major livestock species and livestock densities in the agricultural area. Values are calculated using Livestock Units (LSU), which facilitate aggregating information for different livestock types. Data are available by country, with global coverage, for the period 1961–2014. This methodology applies the LSU coefficients reported in the "Guidelines for the preparation of livestock sector reviews" (FAO, 2011). From this publication, LSU coefficients are computed by livestock type and by country. The reference unit used for the calculation of livestock units (=1 LSU) is the grazing equivalent of one adult dairy cow producing 3000 kg of milk annually, fed without additional concentrated foodstuffs. FAOSTAT agri-environmental indicators on livestock patterns closely follow the structure of the indicators in EUROSTAT.
    • July 2022
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 22 August, 2023
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      The data describe the average use of pesticides per area of cropland (arable land and permanent crops) at national level in a time series from 1990 to 2014. 
    • May 2013
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 22 March, 2019
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    • August 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 August, 2023
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      The gross nutrient balances (N and P) are calculated as the difference between the total quantity of nutrient inputs entering an agricultural system (mainly fertilisers, livestock manure), and the quantity of nutrient outputs leaving the system (mainly uptake of nutrients by crops and grassland). Gross nutrient balances are expressed in tonnes of nutrient surplus (when positive) or deficit (when negative). This calculation can be used as a proxy to reveal the status of environmental pressures, such as declining soil fertility in the case of a nutrient deficit, or for a nutrient surplus the risk of polluting soil, water and air. The nutrient balance indicator is also expressed in terms of kilogrammes of nutrient surplus per hectare of agricultural land to facilitate the comparison of the relative intensity of nutrients in agricultural systems between countries.
    • May 2013
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 22 March, 2019
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    • October 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 October, 2023
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      The gross nutrient balances (N and P) are calculated as the difference between the total quantity of nutrient inputs entering an agricultural system (mainly fertilizers, livestock manure), and the quantity of nutrient outputs leaving the system (mainly uptake of nutrients by crops and grassland). Gross nutrient balances are expressed in tonnes of nutrient surplus (when positive) or deficit (when negative). This calculation can be used as a proxy to reveal the status of environmental pressures, such as declining soil fertility in the case of a nutrient deficit, or for a nutrient surplus the risk of polluting soil, water and air. The nutrient balance indicator is also expressed in terms of kilogrammes of nutrient surplus per hectare of agricultural land to facilitate the comparison of the relative intensity of nutrients in agricultural systems between countries.
    • October 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 October, 2023
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      commitment is a firm written obligation by a government or official agency, backed by the appropriation or availability of the necessary funds, to provide resources of a specified amount under specified financial terms and conditions and for specified purposes for the benefit of a recipient country or a multilateral agency. Members unable to comply with this definition should explain the definition that they use. -- Commitments are considered to be made at the date a loan or grant agreement is signed or the obligation is otherwise made known to the recipient (e.g. in the case of budgetary allocations to overseas territories, the final vote of the budget should be taken as the date of commitment). For certain special expenditures, e.g. emergency aid, the date of disbursement may be taken as the date of commitment. -- Bilateral commitments comprise new commitments and additions to earlier commitments, excluding any commitments cancelled during the same year. Cancellations and reductions in the year reported on of commitments made in earlier years are reported in the CRS, but not in the DAC questionnaire. -- In contrast to bilateral commitments, commitments of capital subscriptions, grants and loans to multilateral agencies should show the sum of amounts which are expected to be disbursed before the end of the next year and amounts disbursed in the year reported on but not previously reported as a commitment. For capital subscriptions in the form of notes payable at sight, enter the expected amount of deposits of such notes as the amount committed.
    • October 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 October, 2023
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      Destination of Official Development Assistance Disbursements. Geographical breakdown by donor, recipient and for some types of aid (e.g. grant, loan, technical co-operation) on a disbursement basis (i.e. actual expenditures). The data cover flows from bilateral and multilateral donors which focus on flows from DAC member countries and the EU Institutions.
    • April 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 May, 2023
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      This dataset contains bilateral commitment data on aid in support of environment sustainability and aid to biodiversity, climate change mitigation, climate change adaptation and desertification from the Development Assistance Committee (DAC) Creditor Reporting System (CRS) database. In their reporting to the DAC CRS, donors are requested to indicate for each activity whether or not it targets environment and the Rio Conventions (biodiversity, climate change mitigation, climate change adaptation and desertification). A scoring system of three values is used, in which aid activities are "marked" as targeting environment as the "principal objective" or a "significant objective", or as not targeting the objective. The environment marker identifies activities that are "intended to produce an improvement in the physical and/or biological environment of the recipient country, area or target group concerned" or "include specific action to integrate environmental concerns with a range of development objectives through institution building and/or capacity development". A large majority of activities targeting the objectives of the Rio Conventions fall under the DAC definition of "aid to environment". The Rio markers permit their specific identification.
    • January 2021
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 September, 2022
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      This dataset contains commitment data (since 2002) and disbursement data (since 2009) on aid in support of gender equality from the CRS database. In their reporting to the Development Assistance Committee (DAC) Creditor Reporting System (CRS), donors are requested to indicate for each activity whether or not it targets gender equality as one of its policy objectives. To qualify as “gender equality focussed,” an activity must explicitly promote gender equality and women’s empowerment. An activity can either target gender equality as its “principal objective” or as a “significant objective”. A “principal” score (2) is assigned if gender equality was an explicit objective of the activity and fundamental to its design - i.e. the activity would not have been undertaken without this objective. A “significant” score (1) is assigned if gender equality was an important, but secondary, objective of the activity - i.e. it was not the principal reason for undertaking the activity. A “not targeted” score (0) is assigned if, after being screened against the gender equality policy marker, an activity is not found to target gender equality. Activities assigned a “principal objective” score should not be considered better than activities assigned a “significant objective” score, as donors that mainstream gender equality - and thus integrate it into their projects across a range of sectors - are more likely to allocate the marker score “significant” to their aid activities. The gender equality marker allows an approximate quantification of aid flows that target gender equality as a policy objective. In marker data presentations the figures for principal and significant objectives should be shown separately and the sum referred to as the “estimate” or “upper bound” of gender equality-focussed aid. An activity can have more than one principal or significant objective. Therefore, total amounts targeting the different objectives should not be added-up to avoid double-counting. Policy markers seek information on the donor’s policy objectives which can be best assessed at the design stage of projects. This is why policy markers are applied to commitments. Policy marker data on a disbursement basis can also be compiled, but it is important to note that this does not mean the policy objectives of projects under implementation would have been re-assessed. Rather, the disbursements are linked to the qualitative information on the original commitment through project identifiers. Consequently, a project marked as gender equality focussed at the commitment stage will be flagged as gender equality focussed throughout its lifetime, unless the qualitative information was changed. Activity-level gender equality marker data that underlie the aggregate figures presented in this dataset are available for consultation and download: see “Export”, “Related files”.
    • September 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 07 September, 2023
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      The air accident data are provided to Eurostat by the European Aviation Safety Agency (EASA). EASA as an Agency is responsible for providing common standards of safety and environmental protection in civil aviation in Europe and worldwide. It is the centrepiece of regulations creating a single European market in the aviation industry. The Agency’s responsibilities include aviation safety analysis and research for which it also collects statistics on European and worldwide aviation safety. The statistics are grouped according to type of operation, such as commercial air transport or general aviation, and aircraft category, such as aeroplanes, helicopters or gliders. The EASA manages and is responsible for the entire data collection. The selection of data made available to Eurostat does not differ from those available through the EASA (http://easa.europa.eu). In Eurobase, the following data are available: Air accident victims in commercial air transport, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaca); Air accident victims in aerial works, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaaw); Air accident victims in general aviation, by country of occurrence and country of registry of aircraft – maximum take-off mass above 2250 kg (EASA data) (tran_sf_aviagah); Air accident victims in general aviation by country of occurrence and country of registry of aircraft – maximum take-off mass under 2250 kg (EASA data) (tran_sf_aviagal).
    • September 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 07 September, 2023
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      The air accident data are provided to Eurostat by the European Aviation Safety Agency (EASA). EASA as an Agency is responsible for providing common standards of safety and environmental protection in civil aviation in Europe and worldwide. It is the centrepiece of regulations creating a single European market in the aviation industry. The Agency’s responsibilities include aviation safety analysis and research for which it also collects statistics on European and worldwide aviation safety. The statistics are grouped according to type of operation, such as commercial air transport or general aviation, and aircraft category, such as aeroplanes, helicopters or gliders. The EASA manages and is responsible for the entire data collection. The selection of data made available to Eurostat does not differ from those available through the EASA (http://easa.europa.eu). In Eurobase, the following data are available: Air accident victims in commercial air transport, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaca); Air accident victims in aerial works, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaaw); Air accident victims in general aviation, by country of occurrence and country of registry of aircraft – maximum take-off mass above 2250 kg (EASA data) (tran_sf_aviagah); Air accident victims in general aviation by country of occurrence and country of registry of aircraft – maximum take-off mass under 2250 kg (EASA data) (tran_sf_aviagal).
    • January 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 January, 2024
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      The air accident data are provided to Eurostat by the European Aviation Safety Agency (EASA). EASA as an Agency is responsible for providing common standards of safety and environmental protection in civil aviation in Europe and worldwide. It is the centrepiece of regulations creating a single European market in the aviation industry. The Agency’s responsibilities include aviation safety analysis and research for which it also collects statistics on European and worldwide aviation safety. The statistics are grouped according to type of operation, such as commercial air transport or general aviation, and aircraft category, such as aeroplanes, helicopters or gliders. The EASA manages and is responsible for the entire data collection. The selection of data made available to Eurostat does not differ from those available through the EASA (http://easa.europa.eu). In Eurobase, the following data are available: Air accident victims in commercial air transport, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaca); Air accident victims in aerial works, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaaw); Air accident victims in general aviation, by country of occurrence and country of registry of aircraft – maximum take-off mass above 2250 kg (EASA data) (tran_sf_aviagah); Air accident victims in general aviation by country of occurrence and country of registry of aircraft – maximum take-off mass under 2250 kg (EASA data) (tran_sf_aviagal).
    • January 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 January, 2024
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      The air accident data are provided to Eurostat by the European Aviation Safety Agency (EASA). EASA as an Agency is responsible for providing common standards of safety and environmental protection in civil aviation in Europe and worldwide. It is the centrepiece of regulations creating a single European market in the aviation industry. The Agency’s responsibilities include aviation safety analysis and research for which it also collects statistics on European and worldwide aviation safety. The statistics are grouped according to type of operation, such as commercial air transport or general aviation, and aircraft category, such as aeroplanes, helicopters or gliders. The EASA manages and is responsible for the entire data collection. The selection of data made available to Eurostat does not differ from those available through the EASA (http://easa.europa.eu). In Eurobase, the following data are available: Air accident victims in commercial air transport, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaca); Air accident victims in aerial works, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaaw); Air accident victims in general aviation, by country of occurrence and country of registry of aircraft – maximum take-off mass above 2250 kg (EASA data) (tran_sf_aviagah); Air accident victims in general aviation by country of occurrence and country of registry of aircraft – maximum take-off mass under 2250 kg (EASA data) (tran_sf_aviagal).
    • January 2022
      Source: Department of Statistics, Singapore
      Uploaded by: Knoema
      Accessed On: 31 January, 2022
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    • January 2022
      Source: Department of Statistics, Singapore
      Uploaded by: Knoema
      Accessed On: 31 January, 2022
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      Refers to Changi Airport only. Data exclude passenger baggage, diplomatic cargo and aircraft stores. Data breakdown is only available for the 11 countries listed above, and they do not sum up to the total of the respective regions.
    • March 2022
      Source: Department of Statistics, Singapore
      Uploaded by: Knoema
      Accessed On: 30 March, 2022
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    • November 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 November, 2015
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    • December 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 21 December, 2023
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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.
    • December 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 21 December, 2023
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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.
    • May 2020
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 June, 2020
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      The focus of this domain is on the European Neighbourhood Policy (ENP) countries on the southern and eastern shores of the Mediterranean (ENP-South), namely: Algeria (DZ),Egypt (EG),Israel (IL),Jordan (JO),Lebanon (LB),Libya (LY),Morocco (MA),Palestine (PS) (1),Syria (SY) andTunisia (TN). An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Generally, only annual data are published in this domain. The data and their denomination in no way constitute the expression of an opinion by the European Commission on the legal status of a country or territory or on the delimitation of its borders. (1) This designation shall not be construed as recognition of a State of Palestine and is without prejudice to the individual positions of the Member States on this issue.
    • January 2022
      Source: Department of Statistics, Singapore
      Uploaded by: Knoema
      Accessed On: 31 January, 2022
      Select Dataset
      Data exclude transit passengers who continued their journey on the same flight. Figures from January 1989 refer to Changi Airport only. Data breakdown is only available for the 11 countries listed above, and they do not sum up to the total of the respective regions.
    • August 2020
      Source: Department of Statistics, Singapore
      Uploaded by: Knoema
      Accessed On: 21 September, 2020
      Select Dataset
      Data exclude transit passengers who continued their journey on the same flight. Figures from January 1989 refer to Changi Airport only. Data breakdown is only available for the 11 countries listed above, and they do not sum up to the total of the respective regions.
    • January 2022
      Source: Department of Statistics, Singapore
      Uploaded by: Knoema
      Accessed On: 31 January, 2022
      Select Dataset
      Data exclude transit passengers who continued their journey on the same flight. Figures from January 1989 refer to Changi Airport only. Data breakdown is only available for the 11 countries listed above, and they do not sum up to the total of the respective regions.
    • August 2020
      Source: Department of Statistics, Singapore
      Uploaded by: Knoema
      Accessed On: 21 September, 2020
      Select Dataset
      Data exclude transit passengers who continued their journey on the same flight. Figures from January 1989 refer to Changi Airport only. Data breakdown is only available for the 11 countries listed above, and they do not sum up to the total of the respective regions.
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 April, 2024
      Select Dataset
      The Air transport domain contains national and international intra and extra-EU data. This provides air transport data for passengers (in number of passengers) and for freight and mail (in 1 000 tonnes) as well as air traffic data by airports, airlines and aircraft. Data are transmitted to Eurostat by EU Member States, EFTA countries and some other reporting cuntries. Data are compiled following the provisions of the Regulation (EC) N°1358/2003, implementing Regulation N°437/2003 of the European Parliament and of the Council on statistical returns in respect of the carriage of passengers, freight and mail by air.  The air transport data are collected at airport level. As from 2003 reference year the data are provided according to the legal act (some countries were given derogation until 2005). Until 2002 partial information (passenger transport only) are available for some countries and airports. Airports handling less than 15 000 passenger units annually are excluded from the scope of the Regulation. Datasets A1 and B1 are provided on monthly basis, while dataset C1 can be provided either on monthly or annual basis. For some countries optional variable - total number of transfer passengers - is provided as well. The data are disseminated by Eurostat in on-line database in four sub-domains:Air Transport measurement - PassengersAir Transport measurement - Freight and mailAir Transport measurement - Traffic data by airports, aircraft and airlinesAir Transport measurement - Data aggregated at standard regional levels (NUTS). The two first domains contain several data collections:Overview of the air transport by country and airport,National air transport by country and airport,International intra-EU air transport by country and airport,International extra-EU air transport by country and airport,Detailed air transport by reporting country and routes. In the tables of the sub-domain "Transport measurement - Passengers", data are broken down by passengers on board (arrivals, departures and total), passengers carried (arrivals, departures and total) and passenger commercial air flights (arrival, departures and total). Additionally, the tables of collection "Detailed air transport by reporting country and routes" provide data on seats available (arrival, departures and total). The data is presented at monthly, quarterly and annual level. In the tables of the sub-domain "Transport measurement - Freight and mail", data are broken down by freight and mail on board (arrival, departures and total), freight and mail loaded/unloaded (loaded, unloaded and total) and all-freight and mail commercial air flights (arrival, departures and total). The data is presented at monthly, quarterly and annual level. In the tables of the sub-domain "Transport measurement - Traffic by airports, aircraft and airlines": - Data by type of aircraft are broken down by total passengers on board, total freight and mail on board in tonnes, total passengers seats available, total commercial air flights (passengers + all-freight and mail), passenger commercial air flights, all-freight and mail commercial air flights. The data is presented at annual level since 2003. - Data by type of airline are broken down by total passengers on board, total passengers carried, total freight and mail on board, total freight and mail loaded/unloaded, total passengers seats available, total commercial air flights (passengers + all-freight and mail), passenger commercial air flights, all-freight and mail commercial air flights. The data is presented at annual level since 2003. - Data by airport are  broken down by total passengers carried, total transit passengers, total transfer passengers, total freight and mail loaded/unloaded, total commercial aircraft movements, total aircrafts movements. the data is presented at monthly, quarterly and annual level. The sub-domain "Transport measurement - Data aggregated at standard regional levels (NUTS)", contains two tables:Air transport of passengers at regional levelAir transport of freight at regional level The tables present the evolution of the number of passengers carried (if not available passengers on board) and the volume of freight and mail loaded or unloaded (if not available freight and mail on board) to/from the NUTS regions (level 2, 1 and 0) since 1999. The data is presented at annual level. The air transport regional data have been calculated using data collected at the airport level in the frame of the regulatory data collection on air transport. More information can be found in Regional transport statistics metadata file. For more details on datasets, data validation and issemination refer also to  Reference Manual on Air Transport Statistics available in the Annex part of the metadata.
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 April, 2024
      Select Dataset
      The Air transport domain contains national and international intra and extra-EU data. This provides air transport data for passengers (in number of passengers) and for freight and mail (in 1 000 tonnes) as well as air traffic data by airports, airlines and aircraft. Data are transmitted to Eurostat by EU Member States, EFTA countries and some other reporting cuntries. Data are compiled following the provisions of the Regulation (EC) N°1358/2003, implementing Regulation N°437/2003 of the European Parliament and of the Council on statistical returns in respect of the carriage of passengers, freight and mail by air.  The air transport data are collected at airport level. As from 2003 reference year the data are provided according to the legal act (some countries were given derogation until 2005). Until 2002 partial information (passenger transport only) are available for some countries and airports. Airports handling less than 15 000 passenger units annually are excluded from the scope of the Regulation. Datasets A1 and B1 are provided on monthly basis, while dataset C1 can be provided either on monthly or annual basis. For some countries optional variable - total number of transfer passengers - is provided as well. The data are disseminated by Eurostat in on-line database in four sub-domains:Air Transport measurement - PassengersAir Transport measurement - Freight and mailAir Transport measurement - Traffic data by airports, aircraft and airlinesAir Transport measurement - Data aggregated at standard regional levels (NUTS). The two first domains contain several data collections:Overview of the air transport by country and airport,National air transport by country and airport,International intra-EU air transport by country and airport,International extra-EU air transport by country and airport,Detailed air transport by reporting country and routes. In the tables of the sub-domain "Transport measurement - Passengers", data are broken down by passengers on board (arrivals, departures and total), passengers carried (arrivals, departures and total) and passenger commercial air flights (arrival, departures and total). Additionally, the tables of collection "Detailed air transport by reporting country and routes" provide data on seats available (arrival, departures and total). The data is presented at monthly, quarterly and annual level. In the tables of the sub-domain "Transport measurement - Freight and mail", data are broken down by freight and mail on board (arrival, departures and total), freight and mail loaded/unloaded (loaded, unloaded and total) and all-freight and mail commercial air flights (arrival, departures and total). The data is presented at monthly, quarterly and annual level. In the tables of the sub-domain "Transport measurement - Traffic by airports, aircraft and airlines": - Data by type of aircraft are broken down by total passengers on board, total freight and mail on board in tonnes, total passengers seats available, total commercial air flights (passengers + all-freight and mail), passenger commercial air flights, all-freight and mail commercial air flights. The data is presented at annual level since 2003. - Data by type of airline are broken down by total passengers on board, total passengers carried, total freight and mail on board, total freight and mail loaded/unloaded, total passengers seats available, total commercial air flights (passengers + all-freight and mail), passenger commercial air flights, all-freight and mail commercial air flights. The data is presented at annual level since 2003. - Data by airport are  broken down by total passengers carried, total transit passengers, total transfer passengers, total freight and mail loaded/unloaded, total commercial aircraft movements, total aircrafts movements. the data is presented at monthly, quarterly and annual level. The sub-domain "Transport measurement - Data aggregated at standard regional levels (NUTS)", contains two tables:Air transport of passengers at regional levelAir transport of freight at regional level The tables present the evolution of the number of passengers carried (if not available passengers on board) and the volume of freight and mail loaded or unloaded (if not available freight and mail on board) to/from the NUTS regions (level 2, 1 and 0) since 1999. The data is presented at annual level. The air transport regional data have been calculated using data collected at the airport level in the frame of the regulatory data collection on air transport. More information can be found in Regional transport statistics metadata file. For more details on datasets, data validation and issemination refer also to  Reference Manual on Air Transport Statistics available in the Annex part of the metadata.
    • July 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 11 July, 2023
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      The European Union (EU) as a party to the Convention on Long-range Transboundary Air Pollution (LRTAP Convention) reports annually its air pollution inventory for the year t-2 and within the area covered by its Member States. Under the Convention, parties are obliged to report emissions data for numerous air pollutants. This dataset includes data on air pollutants: sulphur oxides (SOx), ammonia (NH3), nitrogen oxides (NOx), non-methane volatile organic compounds (NMVOCs), particulate matters (PM10, PM2.5), Lead (Pb), Cadmium (Cd), Mercury (Hg), Arsenic (As), Chromium (Cr) Copper (Cu), Nickel (Ni), Selenium (Se) and Zinc (Zn), as reported to the European Environment Agency (EEA). The EU inventory is fully consistent with national air pollution inventories compiled by the EU Member States. Note that Eurostat is not the producer of these data, only re-publishes them. The producer of the data is the European Environment Agency.    Remarks: (1) Data for EL, PL, MT, RO and EU contain incosistencies (sum of components does not equal to total).   
    • November 2020
      Source: Health Effects Institute
      Uploaded by: Knoema
      Accessed On: 17 December, 2020
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    • February 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 March, 2024
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      This database includes annual, quarterly and monthly information on carbon dioxide (CO2) emissions related to commercial passenger, freight, and general aviation flights, on both a territory and a residence basis, for 186 countries. These CO2 emissions are estimated by the OECD, based on a consistent methodology across countries. The main source used for the estimation of these CO2 emissions is a database compiled by the International Civil Aviation Organisation (ICAO) with all commercial passenger and freight flights around the world.
    • May 2020
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 June, 2020
      Select Dataset
      The focus of this domain is on the European Neighbourhood Policy (ENP) countries on the southern and eastern shores of the Mediterranean (ENP-South), namely: Algeria (DZ),Egypt (EG),Israel (IL),Jordan (JO),Lebanon (LB),Libya (LY),Morocco (MA),Palestine (PS) (1),Syria (SY) andTunisia (TN). An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Generally, only annual data are published in this domain. The data and their denomination in no way constitute the expression of an opinion by the European Commission on the legal status of a country or territory or on the delimitation of its borders. (1) This designation shall not be construed as recognition of a State of Palestine and is without prejudice to the individual positions of the Member States on this issue.
    • May 2020
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 June, 2020
      Select Dataset
      The focus of this domain is on the European Neighbourhood Policy (ENP) countries on the southern and eastern shores of the Mediterranean (ENP-South), namely: Algeria (DZ),Egypt (EG),Israel (IL),Jordan (JO),Lebanon (LB),Libya (LY),Morocco (MA),Palestine (PS) (1),Syria (SY) andTunisia (TN). An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Generally, only annual data are published in this domain. The data and their denomination in no way constitute the expression of an opinion by the European Commission on the legal status of a country or territory or on the delimitation of its borders. (1) This designation shall not be construed as recognition of a State of Palestine and is without prejudice to the individual positions of the Member States on this issue.
    • June 2018
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 August, 2018
      Select Dataset
      The focus of this domain is on the European Neighbourhood Policy (ENP) countries on the southern and eastern shores of the Mediterranean (ENP-South), namely: Algeria (DZ),Egypt (EG),Israel (IL),Jordan (JO),Lebanon (LB),Libya (LY),Morocco (MA),Palestine (PS),Syria (SY) andTunisia (TN). An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Generally, only annual data are published in this domain; monthly data are only provided for exchange rates. The data and their denomination in no way constitute the expression of an opinion by the European Commission on the legal status of a country or territory or on the delimitation of its borders.
    • February 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 February, 2024
      Select Dataset
      The air transport regional data have been calculated using data collected at the airport level in the frame of Commission Regulation (EC) No 1358/2003. They are aggregated at regional level (NUTS 1 and NUTS 2) and also at national level (NUTS0), excluding double counting within each region.
    • February 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 February, 2024
      Select Dataset
      Due to the nature of transport, a spatial reference is built into most legal acts dealing with transport statistics. In a few cases, these sources can be directly used for the derivation of regional transport indicators, while other indicators are collected on a voluntary basis. This is the case of the regional transport data collection in which both data types are used. Three types of regional data can be distinguished depending on their source: two are based on data collections performed on the basis of legal acts (the Maritime and Aviation data) and one is a voluntary data collection (infrastructures, vehicles and road accidents). Regional data collected on voluntary basis: The current regional data collection taking place on a voluntary basis comprises a set of transport indicators at NUTS 0, 1 and 2[1] levels for the road, railways, inland waterways (infrastructure), vehicle stocks, road accidents. The information collected is then disseminated in Eurostat dissemination database (Eurobase) under “General and regional statistics/Regional statistics by NUTS classification/Regional transport statistics” theme and also mirrored under “Transport/Multimodal data/Regional transport statistics” theme. Annual data collection for infrastructure, vehicle stocks and road accidents was launched at the beginning of 2002 covering both Member States and Candidate countries. Since 2007, it includes EFTA countries as well. Regional data are collected directly from the countries using a questionnaire: data on transport infrastructure, vehicle stocks and road accidents (collected previously – till 2006 – on Excel sheets and then – till 2012 – using on-line questionnaires). Currently regional datasets are provided via EDAMIS application. For the voluntary data collection via EDAMIS portal, the definitions from the 4th edition of the Illustrated Glossary for Transport Statistics (jointly elaborated by Eurostat, ECMT, UNECE) were proposed and countries should use them when transmitting data. Regional data based on legal acts: For the collection based on legal acts, regional data are actually derived from the information provided by the participating countries in the frame of the legal data collections at port and airport level. Maritime transport data collection is legally based – Directive 2009/42/EC of the European Parliament and of the Council of 6 May 2009 on statistical returns in respect of carriage of goods and passengers by sea (OJ L141 of 6.6.2009, page 29), which is the recast of the original Council Directive 95/64/EC of 8 December 1995. The air transport regional data have been calculated using data collected at the airport level in the frame of draft Council and Parliament Regulation (Regulation (EC) No 437/2003 of the European Parliament and of the Council of 27 February 2003 on statistical returns in respect of the carriage of passengers, freight and mail by air). Within the collection Maritime transport - data aggregated at standard regional levels (NUTS) there are two tables: Maritime transport of passengers at regional level (new methodology);Maritime transport of freight at regional level (new methodology). Within the collection Air transport - data aggregated at standard regional levels (NUTS) there are two tables: Air transport of passengers at regional levelAir transport of freight at regional level The tables present the evolution of the number of passengers carried (if not available passengers on board) and the volume of freight and mail loaded or unloaded (if not available freight and mail on board) to/from the NUTS regions (level 2, 1 and 0) since 1999. The data is presented at annual level. Before the legal act on air transport statistics was introduced (2003 with 3 years transitional period), air transport statistics have been collected using the statistical questionnaire (voluntary basis). Some countries provided figures for passenger transport taking into account “passengers on board” and some “passenger carried”. Until 2007 reference year, the disseminated numbers of passengers aggregated at regional level are actually a mixture of passengers on board and passengers carried data. The air transport regional data have been calculated using data collected at the airport level in the frame of the regulatory data collection on air transport. Only airports with more than 150 000 passenger units serviced annually are taken into account when aggregating the data at regional levels, because they provide statistics detailed enough to solve the problem of double counting. For each aggregate it is necessary to start at the airport level in order to identify the mirror declarations, i.e. the airport routes for which both airports report the volume, since these constitute the routes where the problem of double counting occurs. When calculating the total volume in such cases, only the departure declarations of the concerned airports have been taken into account. The problem of the double counting only appears for the calculation of the total passengers but not for the total arrivals (respectively total departures), which corresponds to the sum of the arrivals (respectively departures) at each domestic airport. For the tables presenting maritime data at regional level the same aggregation method (exclusion of double counting) is applied taking into account main ports only. Only for these ports (handling more than one million tonnes of goods or recording more than 200 000 passenger movements annually ) the detailed statistics allow such aggregation. For some Member States (up to 1998 data) and for others that joint the EU more recently (up to 2002) transport flows through ports and airports had been collected, via questionnaire. Because of the difference in the methodologies applied, the data for air and maritime transport at regional level up to 2002 reference year are available in separate tablesor some Member States (up to 1998 data) and for others that joint the EU more recently (up to 2002) transport flows through ports and airports had been collected, via questionnaire. Because of the difference in the methodologies applied, the data for air and maritime transport at regional level up to 2002 reference year are avilable in separate tables (listed below) and are no longer updated: Maritime transport of passengers by NUTS 2 regions (questionnaire) (tran_r_mapa_om).Maritime transport of freight by NUTS 2 regions (questionnaire) (tran_r_mago_om).Air transport of passengers by NUTS 2 regions (questionnaire) (tran_r_avpa_om).Air transport of freight by NUTS 2 regions (questionnaire) (tran_r_avgo_om). [1] Regulation (EC) No 1059/2003 of the European Parliament and of the Council of 26 May 2003 on the establishment of a common classification of territorial units for statistics (NUTS) and its amendments. More information on NUTS classification can be found under the following link.
    • March 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 21 April, 2014
      Select Dataset
      Eurostat Dataset Id:tran_r_avgo_om Due to the nature of transport, a spatial reference is built into most legal acts dealing with transport statistics. In a few cases, these sources can be directly used for the derivation of regional transport indicators, while other indicators are collected on a voluntary basis. This is the case of the regional transport data collection in which both data types are used. Three types of regional data can be distinguished depending on their source: two are based on data collections performed on the basis of legal acts (the Maritime and Aviation data) and one is a voluntary data collection (infrastructures, vehicles and road accidents). Regional data collected on voluntary basis: The current regional data collection taking place on a voluntary basis comprises a set of transport indicators at NUTS 0, 1 and 2[1] levels for the road, railways, inland waterways (infrastructure), vehicle stocks, road accidents. The information collected is then disseminated in Eurostat dissemination database (Eurobase) under “General and regional statistics/Regional statistics/Regional transport statistics” theme and also mirrored under “Transport/Regional transport statistics” theme. Annual data collection for infrastructure, vehicle stocks and road accidents was launched at the beginning of 2002 covering both Member States and Candidate countries. Since 2007, it includes EFTA countries as well. Regional data are collected directly from the countries using a questionnaire: data on transport infrastructure, vehicle stocks and road accidents (collected previously – till 2006 – on Excel sheets and then – till 2012- using on-line questionnaires). Currently regional datasets are provided via eDAMIS application. For the voluntary data collection via eDAMIS portal, the definitions from the 4th edition of the Glossary for transport statistics(jointly elaborated by Eurostat, ECMT, UNECE) were proposed and countries should use them when transmitting data. Regional data based on legal acts: For the collection based on legal acts, regional data are actually derived from the information provided by the participating countries in the frame of the legal data collections at port and airport level. Maritime transport data collection is legally based – Directive 2009/42/EC of the European Parliament and of the Council of 6 May 2009 on statistical returns in respect of carriage of goods and passengers by sea (OJ L141 of 6.6.2009, page 29), which is the recast of the original Council Directive 95/64/EC of 8 December 1995. Within the collection Maritime transport - data aggregated at standard regional levels (NUTS) there are two tables:Maritime transport of passengers at regional level (new methodology);Maritime transport of freight at regional level (new methodology).   Within the collection Air transport - data aggregated at standard regional levels (NUTS) there are two tables:Air transport of passengers at regional levelAir transport of freight at regional level   The tables present the evolution of the number of passengers carried (if not available passengers on board) and the volume of freight and mail loaded or unloaded (if not available freight and mail on board) to/from the NUTS regions (level 2, 1 and 0) since 1999. The data is presented at annual level. The air transport regional data have been calculated using data collected at the airport level in the frame of draft Council and Parliament Regulation (Regulation 95/C 325/08 on statistical returns in respect of carriage of passenger, freight and mail by air). [1] Regulation (EC) No 1059/2003 of the European Parliament and of the Council of 26 May 2003 on the establishment of a common classification of territorial units for statistics (NUTS) and its amendments. More information on NUTS clasiffication can be found under the following link.
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 April, 2024
      Select Dataset
      The indicator shows the volume of goods transported in Europe (in tonnes), broken down by country and by year. The data covers the total volume of freight and mail loaded/unloaded.
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 April, 2024
      Select Dataset
      The indicator shows the total number of passengers carried in Europe (arrivals plus departures), broken down by country and by year. Passengers carried: - are all passengers on a particular flight (with one flight number) counted once only and not repeatedly on each individual stage of that flight. - are all revenue and non-revenue passengers whose journey begins or terminates at the reporting airport and transfer passengers joining or leaving the flight at the reporting airport. - excludes direct transit passengers.
    • May 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 30 May, 2023
      Select Dataset
      The air transport regional data have been calculated using data collected at the airport level in the frame of Commission Regulation (EC) No 1358/2003. They are aggregated at regional level (NUTS 1 and NUTS 2) and also at national level (NUTS0), excluding double counting within each region.
    • February 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 04 March, 2024
      Select Dataset
      Due to the nature of transport, a spatial reference is built into most legal acts dealing with transport statistics. In a few cases, these sources can be directly used for the derivation of regional transport indicators, while other indicators are collected on a voluntary basis. This is the case of the regional transport data collection in which both data types are used. Three types of regional data can be distinguished depending on their source: two are based on data collections performed on the basis of legal acts (the Maritime and Aviation data) and one is a voluntary data collection (infrastructures, vehicles and road accidents). Regional data collected on voluntary basis: The current regional data collection taking place on a voluntary basis comprises a set of transport indicators at NUTS 0, 1 and 2[1] levels for the road, railways, inland waterways (infrastructure), vehicle stocks, road accidents. The information collected is then disseminated in Eurostat dissemination database (Eurobase) under “General and regional statistics/Regional statistics by NUTS classification/Regional transport statistics” theme and also mirrored under “Transport/Multimodal data/Regional transport statistics” theme. Annual data collection for infrastructure, vehicle stocks and road accidents was launched at the beginning of 2002 covering both Member States and Candidate countries. Since 2007, it includes EFTA countries as well. Regional data are collected directly from the countries using a questionnaire: data on transport infrastructure, vehicle stocks and road accidents (collected previously – till 2006 – on Excel sheets and then – till 2012 – using on-line questionnaires). Currently regional datasets are provided via EDAMIS application. For the voluntary data collection via EDAMIS portal, the definitions from the 4th edition of the Illustrated Glossary for Transport Statistics (jointly elaborated by Eurostat, ECMT, UNECE) were proposed and countries should use them when transmitting data. Regional data based on legal acts: For the collection based on legal acts, regional data are actually derived from the information provided by the participating countries in the frame of the legal data collections at port and airport level. Maritime transport data collection is legally based – Directive 2009/42/EC of the European Parliament and of the Council of 6 May 2009 on statistical returns in respect of carriage of goods and passengers by sea (OJ L141 of 6.6.2009, page 29), which is the recast of the original Council Directive 95/64/EC of 8 December 1995. The air transport regional data have been calculated using data collected at the airport level in the frame of draft Council and Parliament Regulation (Regulation (EC) No 437/2003 of the European Parliament and of the Council of 27 February 2003 on statistical returns in respect of the carriage of passengers, freight and mail by air). Within the collection Maritime transport - data aggregated at standard regional levels (NUTS) there are two tables: Maritime transport of passengers at regional level (new methodology);Maritime transport of freight at regional level (new methodology). Within the collection Air transport - data aggregated at standard regional levels (NUTS) there are two tables: Air transport of passengers at regional levelAir transport of freight at regional level The tables present the evolution of the number of passengers carried (if not available passengers on board) and the volume of freight and mail loaded or unloaded (if not available freight and mail on board) to/from the NUTS regions (level 2, 1 and 0) since 1999. The data is presented at annual level. Before the legal act on air transport statistics was introduced (2003 with 3 years transitional period), air transport statistics have been collected using the statistical questionnaire (voluntary basis). Some countries provided figures for passenger transport taking into account “passengers on board” and some “passenger carried”. Until 2007 reference year, the disseminated numbers of passengers aggregated at regional level are actually a mixture of passengers on board and passengers carried data. The air transport regional data have been calculated using data collected at the airport level in the frame of the regulatory data collection on air transport. Only airports with more than 150 000 passenger units serviced annually are taken into account when aggregating the data at regional levels, because they provide statistics detailed enough to solve the problem of double counting. For each aggregate it is necessary to start at the airport level in order to identify the mirror declarations, i.e. the airport routes for which both airports report the volume, since these constitute the routes where the problem of double counting occurs. When calculating the total volume in such cases, only the departure declarations of the concerned airports have been taken into account. The problem of the double counting only appears for the calculation of the total passengers but not for the total arrivals (respectively total departures), which corresponds to the sum of the arrivals (respectively departures) at each domestic airport. For the tables presenting maritime data at regional level the same aggregation method (exclusion of double counting) is applied taking into account main ports only. Only for these ports (handling more than one million tonnes of goods or recording more than 200 000 passenger movements annually ) the detailed statistics allow such aggregation. For some Member States (up to 1998 data) and for others that joint the EU more recently (up to 2002) transport flows through ports and airports had been collected, via questionnaire. Because of the difference in the methodologies applied, the data for air and maritime transport at regional level up to 2002 reference year are available in separate tablesor some Member States (up to 1998 data) and for others that joint the EU more recently (up to 2002) transport flows through ports and airports had been collected, via questionnaire. Because of the difference in the methodologies applied, the data for air and maritime transport at regional level up to 2002 reference year are avilable in separate tables (listed below) and are no longer updated: Maritime transport of passengers by NUTS 2 regions (questionnaire) (tran_r_mapa_om).Maritime transport of freight by NUTS 2 regions (questionnaire) (tran_r_mago_om).Air transport of passengers by NUTS 2 regions (questionnaire) (tran_r_avpa_om).Air transport of freight by NUTS 2 regions (questionnaire) (tran_r_avgo_om). [1] Regulation (EC) No 1059/2003 of the European Parliament and of the Council of 26 May 2003 on the establishment of a common classification of territorial units for statistics (NUTS) and its amendments. More information on NUTS classification can be found under the following link.
    • March 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 21 April, 2014
      Select Dataset
      Eurostat Dataset Id:tran_r_avpa_om Due to the nature of transport, a spatial reference is built into most legal acts dealing with transport statistics. In a few cases, these sources can be directly used for the derivation of regional transport indicators, while other indicators are collected on a voluntary basis. This is the case of the regional transport data collection in which both data types are used. Three types of regional data can be distinguished depending on their source: two are based on data collections performed on the basis of legal acts (the Maritime and Aviation data) and one is a voluntary data collection (infrastructures, vehicles and road accidents). Regional data collected on voluntary basis: The current regional data collection taking place on a voluntary basis comprises a set of transport indicators at NUTS 0, 1 and 2[1] levels for the road, railways, inland waterways (infrastructure), vehicle stocks, road accidents. The information collected is then disseminated in Eurostat dissemination database (Eurobase) under “General and regional statistics/Regional statistics/Regional transport statistics” theme and also mirrored under “Transport/Regional transport statistics” theme. Annual data collection for infrastructure, vehicle stocks and road accidents was launched at the beginning of 2002 covering both Member States and Candidate countries. Since 2007, it includes EFTA countries as well. Regional data are collected directly from the countries using a questionnaire: data on transport infrastructure, vehicle stocks and road accidents (collected previously – till 2006 – on Excel sheets and then – till 2012- using on-line questionnaires). Currently regional datasets are provided via eDAMIS application. For the voluntary data collection via eDAMIS portal, the definitions from the 4th edition of the Glossary for transport statistics(jointly elaborated by Eurostat, ECMT, UNECE) were proposed and countries should use them when transmitting data. Regional data based on legal acts: For the collection based on legal acts, regional data are actually derived from the information provided by the participating countries in the frame of the legal data collections at port and airport level. Maritime transport data collection is legally based – Directive 2009/42/EC of the European Parliament and of the Council of 6 May 2009 on statistical returns in respect of carriage of goods and passengers by sea (OJ L141 of 6.6.2009, page 29), which is the recast of the original Council Directive 95/64/EC of 8 December 1995. Within the collection Maritime transport - data aggregated at standard regional levels (NUTS) there are two tables: Maritime transport of passengers at regional level (new methodology);Maritime transport of freight at regional level (new methodology). Within the collection Air transport - data aggregated at standard regional levels (NUTS) there are two tables: Air transport of passengers at regional levelAir transport of freight at regional level The tables present the evolution of the number of passengers carried (if not available passengers on board) and the volume of freight and mail loaded or unloaded (if not available freight and mail on board) to/from the NUTS regions (level 2, 1 and 0) since 1999. The data is presented at annual level. The air transport regional data have been calculated using data collected at the airport level in the frame of draft Council and Parliament Regulation (Regulation 95/C 325/08 on statistical returns in respect of carriage of passenger, freight and mail by air). [1] Regulation (EC) No 1059/2003 of the European Parliament and of the Council of 26 May 2003 on the establishment of a common classification of territorial units for statistics (NUTS) and its amendments. More information on NUTS clasiffication can be found under the following link.
    • May 2020
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 June, 2020
      Select Dataset
      The focus of this domain is on the European Neighbourhood Policy (ENP) countries on the southern and eastern shores of the Mediterranean (ENP-South), namely: Algeria (DZ),Egypt (EG),Israel (IL),Jordan (JO),Lebanon (LB),Libya (LY),Morocco (MA),Palestine (PS),Syria (SY) andTunisia (TN). An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. The data and their denomination in no way constitute the expression of an opinion by the European Commission on the legal status of a country or territory or on the delimitation of its borders.
    • August 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 September, 2016
      Select Dataset
      The focus of this domain is on the European Neighbourhood Policy (ENP) countries on the southern and eastern shores of the Mediterranean (ENP-South), namely: Algeria (DZ),Egypt (EG),Israel (IL),Jordan (JO),Lebanon (LB),Libya (LY),Morocco (MA),Palestine (PS),Syria (SY) andTunisia (TN). An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. The data and their denomination in no way constitute the expression of an opinion by the European Commission on the legal status of a country or territory or on the delimitation of its borders.
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 April, 2024
      Select Dataset
      The Air transport domain contains national and international intra and extra-EU data. This provides air transport data for passengers (in number of passengers) and for freight and mail (in tonnes) as well as air traffic data by airports, airlines and aircraft. Data are transmitted to Eurostat by the Member States of the European Union as well as by Iceland, Norway, Switzerland, Turkey, FYROM and Montenegro. The air transport data have been calculated using data collected at airport level. The data are presented in four sub-domains:Air Transport measurement - PassengersAir Transport measurement - Freight and mailAir Transport measurement - Traffic data by airports, aircraft and airlinesAir Transport measurement - Data aggregated at standard regional levels (NUTS). The two first domains contain several data collections:Overview of the air transport by country and airport,National air transport by country and airport,International intra-EU air transport by country and airport,International extra-EU air transport by country and airport,Detailed air transport by reporting country and routes. In the tables of the sub-domain "Transport measurement - Passengers", data are broken down by passengers on board (arrivals, departures and total), passengers carried (arrivals, departures and total) and passenger commercial air flights (arrival, departures and total). Additionally, the tables of collection "Detailed air transport by reporting country and routes" provide data on seats available (arrival, departures and total). The data is presented at monthly, quarterly and annual level. In the tables of the sub-domain "Transport measurement - Freight and mail", data are broken down by freight and mail on board (arrival, departures and total), freight and mail loaded/unloaded (loaded, unloaded and total) and all-freight and mail commercial air flights (arrival, departures and total). The data is presented at monthly, quarterly and annual level. In the tables of the sub-domain "Transport measurement - Traffic by airports, aircraft and airlines": - Data by type of aircraft are broken down by total passengers on board, total freight and mail on board in tonnes, total passengers seats available, total commercial air flights (passengers + all-freight and mail), passenger commercial air flights, all-freight and mail commercial air flights. The data is presented at annual level since 2003. - Data by type of airline are broken down by total passengers on board, total passengers carried, total freight and mail on board, total freight and mail loaded/unloaded, total passengers seats available, total commercial air flights (passengers + all-freight and mail), passenger commercial air flights, all-freight and mail commercial air flights. The data is presented at annual level since 2003. - Data by airport are  broken down by total passengers carried, total transit passengers, total transfer passengers, total freight and mail loaded/unloaded, total commercial aircraft movements, total aircrafts movements. The data is presented at monthly, quarterly and annual level. The sub-domain "Transport measurement - Data aggregated at standard regional levels (NUTS)", contains two tables:Air transport of passengers at regional levelAir transport of freight at regional level The tables present the evolution of the number of passengers carried (if not available passengers on board) and the volume of freight and mail loaded or unloaded (if not available freight and mail on board) to/from the NUTS regions (level 2, 1 and 0) since 1999. The data is presented at annual level. The air transport regional data have been calculated using data collected at the airport level in the frame of the regulatory data collection on air transport. More information can be found in Regional transport statistics metadata file.
    • October 2023
      Source: Boeing Global Services
      Uploaded by: Knoema
      Accessed On: 10 October, 2023
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    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 April, 2024
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      Causes of Death data refer to the underlying cause which - according to the World Health Organisation (WHO) - is the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury"."
    • June 2013
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 21 November, 2014
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      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: All The Ginis Dataset Publication: https://datacatalog.worldbank.org/dataset/all-ginis-dataset License: http://creativecommons.org/licenses/by/4.0/   This dataset includes combined and standardized Gini data from eight original sources: Luxembourg Income Study (LIS), Socio-Economic Database for Latin America (SEDLAC), Survey of Living Conditions (SILC) by Eurostat, World Income Distribution (WYD; the full data set is available here), World Bank Europe and Central Asia dataset, World Institute for Development Research (WIDER), World Bank Povcal, and Ginis from individual long-term inequality studies (just introduced in this version).
    • February 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 03 February, 2024
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      Residence permits statistics refers to third-country nationals (persons who are not EU citizens) receiving a residence permits or an authorisation to reside in one of the EU or EFTA Member States. The definitions used for residence permits and other concepts (e.g. first permit) are presented in the section 3.4. Statistical concepts and definitions. The detailed data collection methodology is presented in Annex 8 of this metadta file. LEGAL FRAMEWORK - Residence data contain statistical information based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007.  This legal framework refers to the initial residence permits data colection with 2008 first reference period (e.g. first residence permits; change of immigration status or reason to stay; all valid residence permits in the end of the year and long-term residence permits valid in the end of the year) and it provides also a general framework for newer data collections based on speciffic European legal acts (e.g. statistics on EU Blue Cards and statistics on single permits) or provided on voluntary basis (e.g. new long-term residence permits issued during the year and residence permits issued for family reunification with beneficiaries of  protection status). DATA SOURCE - Data are entirely based on administrative sources with the exception of the United Kingdom1 and are provided mainly by the Ministries of Interior or related Immigration Agencies. Data are generally disseminated in June and July in the year following the reference year. AVAILABLE DATASETS I. Residence permits statistics by reason to stay, citizenship and permit's lenght of validity based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007. These statistics are avilable from 2008 reference year.     First Permits - see the definition in the section 3.4. Statistical concepts and definitions. First permits by reason, length of validity and citizenship (migr_resfirst)2. The totals presented in this tables are depended on data availability in the following four tables migr_resfam + migr_resedu+ migr_resocc+ migr_resoth.First permits issued for family reasons by reason, length of validity and citizenship (migr_resfam)First permits issued for education reasons by reason, length of validity and citizenship (migr_resedu)First permits issued for remunerated activities by reason, length of validity and citizenship (migr_resocc)First permits issued for other reasons by reason, length of validity and citizenship (migr_resoth)     Residence Permits issued with the occasion of changing the immigration status or reason to stay Change of immigration status permits by reason and citizenship (migr_reschange)               Residence permits valid in the end of the year All valid permits by reason, length of validity and citizenship on 31 December of each year (migr_resvalid)Long-term residents by citizenship on 31 December of each year (migr_reslong)     Share of long term residence permitsLong-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%) (migr_resshare) II. Residence permits statistics by age (5-year age groups) and sex collected on voluntary basis. These statistics are avilable from 2010 reference year. First permits by reason, age, sex and citizenship (migr_resfas)  All valid permits by age, sex and citizenship on 31 December of each year (migr_resvas)               Long-term residents by age, sex and citizenship on 31 December of each year (migr_reslas) III. EU Blue Cards data collection based on Article 20 of the Directive 2009/50/EC. These statistics are avilable from 2012 reference year2. EU Blue Cards by type of decision, occupation and citizenship (migr_resbc1)       Admitted family members of EU Blue Cards holders by type of decision and citizenship (migr_resbc2)EU Blue Cards holders and family members by Member State of previous residence (migr_resbc3) IV. Single Permit data collection based on Art 15 Directive 2011/98/EU. These statistics are avilable from 2013 reference year. Single Permits issued by type of decision, length of validity (migr_ressing)  V. Pilot data collections collected on voluntary basis. These statistics are avilable from 2016 reference year and the data quality assesment is ongoing. Long-term residence permits issued during the year (migr_resltr)First permits issued for family reunification with a beneficiary of protection status (migr_resfrps1)Permits valid at the end of the year for family reunification with a beneficiary of protection status (migr_resfrps2) VI. New statistics on Intra-Corporate Transfers and Seasonal Workers New data collections with 2017 first reference period are in the preparetion phase to be released in 2018: Intra-Corporate Transfers data collection under Art 24 of Directive 2014/66/EU and Seasonal Workers data collection under Art 26 Directive 2014/36/EU.   Share of long-tem residence permits The indicators presented in the table 'Long-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%)' are produced within the framework of the pilot study related to the integration of migrants in the Member States, following the Zaragoza Declaration. The Zaragoza Declaration, adopted in April 2010 by EU Ministers responsible for immigrant integration issues, and approved at the Justice and Home Affairs Council on 3-4 June 2010, called upon the Commission to undertake a pilot study to examine proposals for common integration indicators and to report on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators. In June 2010 the ministers agreed "to promote the launching of a pilot project with a view to the evaluation of integration policies, including examining the indicators and analysing the significance of the defined indicators taking into account the national contexts, the background of diverse migrant populations and different migration and integration policies of the Member States, and reporting on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators". These indicators are produced on the basis of residence permit statistics collected by Eurostat on the basis of Article 6 of the Migration Statistics Regulation 862/2007. As a denominator data on the stock of all valid permits to stay at the end of each reporting year are used. As a numerator data on the stock of long-term residents are used.  Two types of long term residents are distinguished in accordance with the residence permit statistics: EU long-term resident status (as regulated by the Council Directive 2003/109/EC) and the National long-term resident status (as regulated by the national legislation in the Member States). Data for some countries may be a subject of revisions due to certain inconsistencies between categories.   Data consistency between tables The data providers should use the same methodological specifications provided by Eurostat and some tables from Resper statistics should be consistent between them according to this methodology.  However, consistency issues between tables exist due to some technical limitations (e.g. different data sources) or different methodology applied to each table (see the quality information from below or the national metadata files) or different point in time of producing each tables.   1Please note that the statistics for the United Kingdom use different data sources to those used in other Member States. For that reason, the statistics on residence permits published by Eurostat for UK may not be fully comparable with the statistics reported by other countries. Statistics for the United Kingdom are not based on records of residence permits issued (as the United Kingdom does not operate a system of residence permits), but instead relate to the numbers of arriving non-EU citizens permitted to enter the country under selected immigration categories. According to the United Kingdom authorities, data are estimated from a combination of information due to be published in the Home Office Statistical Bulletin 'Control of Immigration: Statistics, United Kingdom' and unpublished management information. The 'Other reasons' category includes: diplomat, consular officer treated as exempt from control; retired persons of independent means; all other passengers given limited leave to enter who are not included in any other category; non-asylum discretionary permissions. 2 The EU Blue cards issued during the year are collected in two datasets: 1. in the table migr_resocc countig the EU Blue Cards issued as "first permits" and 2. in the EU Blue Cards counting all EU Blue Cards issued. The diference between these two categories is represented by the EU Blue cards that are not first permits. However these two tables might be updated/revised at a different point in time and the consistency between tables might be affected.
    • February 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 03 February, 2024
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      Residence permit means any authorisation valid for at least 3 months issued by the authorities of a Member State allowing a third country national to stay legally on its territory. All valid permits on 31st December (end of the year). This data include statistics on all valid permits at the end of reference period, therefore including first permits, change of status or reasons to stay and renewed permits.
    • February 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 03 February, 2024
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      Residence permits data contain statistical information based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007 with reference to:first permits granted to third-country nationals during the reference year, disaggregated by citizenship, reason for the permit being issued and by the length of validity of the permit; permits granted during the reference period on the occasion of person changing immigration status or reason to stay, disaggregated by citizenship, reason for the permit being issued and by the length of validity; permits valid at the end of the reference period, disaggregated by citizenship, reasons for the permit being issued and by the length of validity; number of long-term residents at the end of reference period. Statistics on EU Blue Cards contain information based on the Article 20 of the Council Directive 2009/50/EC of 25 May 2009 on:EU Blue Cards granted, renewed and withdrawn;Admitted family members of EU Blue Cards holders;EU Blue Cards holders and family members by Member State of previous residenceStatistics on Single permits contain information based on the Article 15 (2) Directive 2011/98/EU of the European Parliament and of the Council of 13 December 2011 on a single application procedure for a single permit for third-country nationals to reside and work in the territory of a Member State and on a common set of rights for third-country workers legally residing in a Member State. Eurostat collects data on first permits granted to third-country nationals (persons who are not EU citizens) during the reference year and data on permits valid at the end of the reference period. Statistics are disaggregated by citizenship, reason for the permit being issued and by the length of validity of the permit. In addition, Eurostat collects data on permits granted during the reference period on the occasion of the person changing immigration status or reason for stay (disaggregated by reason for the new permit being issued) and on the number of long-term residents at the end of the reference period. Since the 2010 reference year, data on first permits issued, stock of all valid permits and the number of long-term residents are additionally collected with a voluntary disaggregation by age (5-year age groups) and sex. These statistics are collected by Eurostat on an annual basis. Data are entirely based on administrative sources with the exception of the United Kingdom1 and are provided mainly by the Ministries of Interior or related Immigration Agencies. Data are generally disseminated in June and July in the year following  the  reference year. The indicators presented in the table 'Long-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%)' are produced within the framework of the pilot study related to the integration of migrants in the Member States, following the Zaragoza Declaration. The Zaragoza Declaration, adopted in April 2010 by EU Ministers responsible for immigrant integration issues, and approved at the Justice and Home Affairs Council on 3-4 June 2010, called upon the Commission to undertake a pilot study to examine proposals for common integration indicators and to report on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators. In June 2010 the ministers agreed "to promote the launching of a pilot project with a view to the evaluation of integration policies, including examining the indicators and analysing the significance of the defined indicators taking into account the national contexts, the background of diverse migrant populations and different migration and integration policies of the Member States, and reporting on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators". These indicators are produced on the basis of residence permit statistics collected by Eurostat on the basis of Article 6 of the Migration Statistics Regulation 862/2007. As a denominator data on the stock of all valid permits to stay at the end of each reporting year are used. As a numerator data on the stock of long-term residents are used.  Two types of long term residents are distinguished in accordance with the residence permit statistics: EU long-term resident status (as regulated by the Council Directive 2003/109/EC) and the National long-term resident status (as regulated by the national legislation in the Member States). Data for some countries may be a subject of revisions due to certain inconsistencies between categories. 1Please note that the statistics for the United Kingdom use different data sources to those used in other Member States. For that reason, the statistics on residence permits published by Eurostat for UK may not be fully comparable with the statistics reported by other countries. Statistics for the United Kingdom are not based on records of residence permits issued (as the United Kingdom does not operate a system of residence permits), but instead relate to the numbers of arriving non-EU citizens permitted to enter the country under selected immigration categories. According to the United Kingdom authorities, data are estimated from a combination of information due to be published in the Home Office Statistical Bulletin 'Control of Immigration: Statistics, United Kingdom' and unpublished management information. The 'Other reasons' category includes: diplomat, consular officer treated as exempt from control; retired persons of independent means; all other passengers given limited leave to enter who are not included in any other category; non-asylum discretionary permissions.
    • February 2024
      Source: National Institute of Statistics, Italy
      Uploaded by: Knoema
      Accessed On: 13 February, 2024
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      Data source(s) used: Crimes reported to the Judicial authorities by the State Police, Carabinieri and Guardia di Finanza: Are processed the data on felonies and people who were reported by police to the court Other data characteristics: Data referring to social demographic characteristics of alleged offenders could not coincide with data on reports because of the different timing of extraction from police forces database.The sum of the crimes by province could not coincide with the total of the region, and that of the regions with the total Italy, because of the missed precise statement, for some crimes, of the place where they have been committed (or of the region of the committed crime but not of the province).
    • March 2018
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2018
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    • January 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 January, 2024
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      This indicator tracks trends in anthropogenic atmospheric emissions of ammonia by agriculture.
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 20 April, 2024
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      The indicator measures the amount of ammonia (NH3) emissions as a result of the agricultural production. The EU inventory on air pollution compiled by the European Environment Agency (EEA) under the Convention on Long-range Transboundary Air Pollution (LRTAP Convention) is fully consistent with national air pollution inventories compiled by the EU Member States. Ammonia emissions per hectare are calculated using the total utilised agricultural area (UAA) of the relevant year as denominator.
    • January 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 April, 2017
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      The domain EUROFARM (ef) contains information (statistical tables) on structure of agricultural holdings collected through agricultural structure surveys. The data of the domain have been organised into two collections:Results of the farm structure surveys contains data from 1990 onwards based on the 1988 legislation andResults of the farm structure surveys based on the legislation from 2008. This collection contains the data from the 2010 Census onwards as well as the data for the surveys 2007 and 2005. Farm Structure Survey data are used to collect information on agricultural holdings in the Member States at different geographic levels (Member States, regions, districts) and over periods (follow up the changes in agricultural sector), thus provide a base for decision making in the Common Agricultural Policy. Two kinds of Farm Structure Survey (FSS) are carried out by Member States:a basic survey (full scope Agricultural Census - AC) every 10 years,several sample based intermediate surveys between them. However for certain characteristics the Member States may use sample base for every survey. The calendar for the surveys to be held in all Member States is agreed by the Agricultural Statistics Committee of the European Commission. For a given survey year, Member States have to conduct their surveys within the agreed time-frame, thus all the data are as comparable as possible. The FSS are organised in all Member States on a harmonised base. Whereas the characteristics are based on community legislation, the same data are available for all countries in case of each survey. The data on individual agricultural holdings are collected by all Member States and sent to Eurostat. The aggregated results are disseminated through statistical tables. The variables are arranged into groups:general overview with key variables,and other specialized groups containing detailed data onland uselivestockfarm labour forcerural development issues as well as management and practices. The 2010 survey additionally provides the results of the survey on agricultural production methods (SAPM). The scope of the survey is agriculture, while the survey unit is the agricultural holding (farm). Data for basic surveys are available in a three-level geographical breakdown of the whole country, the regions and the district; while data for intermediate surveys are only available upon the two-levels of country and regions. Since FSS 1999/2000 information about local farm location is collected in most countries, so that the data can also be disseminated by NUTS and are robust regarding the changes in the NUTS definition. The FSS 2009/2010 information is inline with the NUTS 2010 classification: Regulation (EU) No 31/2011 amending the NUTS classification from January 2003. The Eurofarm domain does not cover the whole territory only the land covered by the agricultural holdings. So the land use data without link with other farm characteristics should be downloaded by the user from the relevant domain. Specific national data about crops, animals or agricultural labour force can be found in other domains, without link between the other information at farm level. For a comprehensive description of the domain, please consult detailed structure (See annex at the bottom of the page). Regional Data Data for basic surveys are available in a three-level geographical breakdown of the whole country, the regions and the district; while data for intermediate surveys are only available upon the two-levels of country and regions. Since FSS 1999/2000 information about local farm location is collected in most countries, so that the data can also be disseminated by NUTS classification and are robust regarding the changes in the NUTS definition. The FSS 2009/2010 information is inline with the NUTS 2010 classification: Regulation (EU) No 31/2001 amending the NUTS classification from January 2012. 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.
    • January 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 April, 2017
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      The domain EUROFARM (ef) contains information (statistical tables) on structure of agricultural holdings collected through agricultural structure surveys. The data of the domain have been organised into two collections:Results of the farm structure surveys contains data from 1990 onwards based on the 1988 legislation andResults of the farm structure surveys based on the legislation from 2008. This collection contains the data from the 2010 Census onwards as well as the data for the surveys 2007 and 2005. Farm Structure Survey data are used to collect information on agricultural holdings in the Member States at different geographic levels (Member States, regions, districts) and over periods (follow up the changes in agricultural sector), thus provide a base for decision making in the Common Agricultural Policy. Two kinds of Farm Structure Survey (FSS) are carried out by Member States:a basic survey (full scope Agricultural Census - AC) every 10 years,several sample based intermediate surveys between them. However for certain characteristics the Member States may use sample base for every survey. The calendar for the surveys to be held in all Member States is agreed by the Agricultural Statistics Committee of the European Commission. For a given survey year, Member States have to conduct their surveys within the agreed time-frame, thus all the data are as comparable as possible. The FSS are organised in all Member States on a harmonised base. Whereas the characteristics are based on community legislation, the same data are available for all countries in case of each survey. The data on individual agricultural holdings are collected by all Member States and sent to Eurostat. The aggregated results are disseminated through statistical tables. The variables are arranged into groups:general overview with key variables,and other specialized groups containing detailed data onland uselivestockfarm labour forcerural development issues as well as management and practices. The 2010 survey additionally provides the results of the survey on agricultural production methods (SAPM). The scope of the survey is agriculture, while the survey unit is the agricultural holding (farm). Data for basic surveys are available in a three-level geographical breakdown of the whole country, the regions and the district; while data for intermediate surveys are only available upon the two-levels of country and regions. Since FSS 1999/2000 information about local farm location is collected in most countries, so that the data can also be disseminated by NUTS and are robust regarding the changes in the NUTS definition. The FSS 2009/2010 information is inline with the NUTS 2010 classification: Regulation (EU) No 31/2011 amending the NUTS classification from January 2003. The Eurofarm domain does not cover the whole territory only the land covered by the agricultural holdings. So the land use data without link with other farm characteristics should be downloaded by the user from the relevant domain. Specific national data about crops, animals or agricultural labour force can be found in other domains, without link between the other information at farm level. For a comprehensive description of the domain, please consult detailed structure (See annex at the bottom of the page). Regional Data Data for basic surveys are available in a three-level geographical breakdown of the whole country, the regions and the district; while data for intermediate surveys are only available upon the two-levels of country and regions. Since FSS 1999/2000 information about local farm location is collected in most countries, so that the data can also be disseminated by NUTS classification and are robust regarding the changes in the NUTS definition. The FSS 2009/2010 information is inline with the NUTS 2010 classification: Regulation (EU) No 31/2001 amending the NUTS classification from January 2012. 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.
    • February 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 03 February, 2024
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      Animal output is valued at basic prices. The basic price is defined as the price received by the producer, after deduction of all taxes on products but including all subsidies on products. The concept of output comprises sales, changes in stocks, and products used for processing and own final use by the producers.
    • September 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 September, 2023
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      Animal production statistics cover three main sub-domains based on three pieces of relevant legislation and related gentlemen’s agreements. Livestock and meat statistics are collected under Regulation (EC) No 1165/2008. They cover meat production, as activity of slaughterhouses (monthly) and as other slaughtering (annual), meat production (gross indigenous production) forecast (semi-annual or quarterly), livestock statistics, including regional statistics. A quality report is also collected every third year.Milk and milk product statistics are collected under Decision 97/80/EC implementing Directive 96/16/EC. They cover farm production and utilisation of milk (annual), collection (monthly for cows’ milk) and production activity by dairies (annual) and statistics on the structure of dairies (every third year). An annual methodological report is also collected.Statistics on eggs for hatching and farmyard poultry chicks are collected under Regulation (EC) No 617/2008, implementing Regulation (EC) No 1234/2007 (Single CMO Regulation). They cover statistics on the structure (annual) and the activity (monthly) of hatcheries as well as reports on the external trade of chicks. European Economic Area countries (EEA, Iceland, Liechtenstein and Norway) are requested to provide milk statistics, with the exception of those related to home consumption, as stated in Annex XXI of the EEA Agreement. As Iceland is now a candidate country and Liechtenstein is exempted in the Agreement, only Norway is concerned. The Agreement between the European Community and the Swiss Confederation on cooperation in the field of statistics states that Switzerland must provide Eurostat with national milk statistics. It has been amended in 2013 for covering also some livestock and meat statistics. The same statistics are requested from the candidate countries as acquis communautaire. Further data about the same topics refer to repealed legal acts or agreements. The tables on animal product supply balance sheets (apro_mk_bal, apro_mt_bal and apro_ec_bal), statistics on the structure of rearing (apro_mt_str) and the number of laying hens (apro_ec_lshen) are therefore no longer updated. The same applies to some variables (external trade of animals and meat), periods (surveys in April or August) or items (number of horses) included in other tables. The statistical tables disseminated by Eurostat are organised into three groups of tables on Agricultural products (apro), i.e. Milk and milk products (apro_mk), Livestock and meat (apro_mt) and Poultry farming (apro_ec). This last label covers statistics on hatcheries and on trade in chicks. The regional animal production statistics collected on livestock (agr_r_animal) and on cows’ milk production on farms (agr_r_milk_pr) are disseminated separately. Due to the change in the legal basis or in the methodology, the time series may be broken. This is indicated by a flag in the tables. The detailed content of each table and the reference to its legal definition is provided in the table below.   Table 3.1: Data tables disseminated regarding animal production statistics
    • September 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 September, 2023
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      Livestock numbers are derived from surveys of farms or from administrative sources in November or December for each Member State.
    • May 2020
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 June, 2020
      Select Dataset
      Eurostat Dataset Id:med_ag42 The focus of this domain is on the following countries:Algeria, Egypt, Israel, Jordan, Lebanon, Morocco, Palestinian Authority, Syria, Tunisia. Data are provided for over 1000 indicators depending on the country.   The data for the Mediterranean partner countries are supplied by and under the responsibility of the national statistical authorities  of each of the countries or territories. The data and their denomination in no way constitute the  expression of an opinion by the European Commission on the  legal status of a country or territory or on the delimitation of its frontiers. Â
    • March 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 April, 2014
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      Eurostat Dataset Id:demo_r_d3avg The regional demographic statistics provides annual data on population, vital events (live births and deaths), total and land areas of the regions and key demographic indicators for regions and statistical regions at NUTS2 and NUTS3 levels for 35 countries: each EU-27 Member State, Acceding, Candidate and EFTA countries. The completeness of the tables depends on the availability of data received from the responsible national statistical institutes (NSIs).  The label of each table indicates the lowest NUTS level for which data are available; for the upper NUTS levels data are included as well. Starting with March 2013, demographic statistics at regional level reflect the new NUTS-2010 classification for EU-27 Member States and the new statistical regions for Croatia. Countries affected by the NUTS-2010 changes are expected to transmit to Eurostat the time series for the new regional breakdown. As a general approach, the regions with no data available are not listed in the tables. For a calendar year T, the deadline of the regional demographic data collection is 15 December, and data included have a different degree of detail for regions at NUTS2 and NUTS3 levels: NUTS2 level - high level of data detail: Population by sex and single year of age at 1st January: years T and T-1Live births by single year of age and year of birth of the mother: year T-1 Deaths by sex and single years of age and year of birth: year T-1  NUTS3 level - low level of data detail: Surface area in km2 at 1st January (total area including inland waters and land area): year TPopulation by sex and broad age groups at 1st January, namely for 0-14 (0 up to 14 years), 15-64 (15 up to 64 years) and 65+ (persons of 65 years and older): years T and T-1 Live births and deaths (total number of demographic events): year T-1  Tables are updated mainly during March of the next year (T+1), but also along the year whenever revised data are sent by the official data providers. Demographic indicators at regional level are computed by Eurostat using a harmonised methodology and common concepts for all regions of all countries, namely: average population on 1st January (in thousands), population density;demographic balance and crude rates (population change, natural change, net migration including statistical adjustments, crude birth rate, crude death rate, crude rate of population change, crude rate of natural change, crude rate of net migration (including statistical adjustments));age-specific-fertility rates and Total Fertility Rates;life tables that include age-specific-mortality-rates and life expectancy at given exact age;infant mortality and crude rate of infant mortality. At national level a larger number of demographic indicators are computed, as more detailed demographic data are collected only at this level.Â
    • May 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 09 June, 2014
      Select Dataset
      Eurostat Dataset Id:earn_ses10_rbns 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.
    • May 2020
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 June, 2020
      Select Dataset
      The focus of this domain is on the European Neighbourhood Policy (ENP) countries on the southern and eastern shores of the Mediterranean (ENP-South), namely: Algeria (DZ),Egypt (EG),Israel (IL),Jordan (JO),Lebanon (LB),Libya (LY),Morocco (MA),Palestine (PS),Syria (SY) andTunisia (TN). An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. The data and their denomination in no way constitute the expression of an opinion by the European Commission on the legal status of a country or territory or on the delimitation of its borders.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2024
      Select Dataset
      'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech patents are defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition). Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.
    • February 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 February, 2023
      Select Dataset
      'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE)  at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created , named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech patents are defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition). Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 04 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 March, 2024
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 March, 2024
      Select Dataset
      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.
    • September 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 06 October, 2016
      Select Dataset
      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.
    • October 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 29 October, 2016
      Select Dataset
      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.
    • October 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 29 October, 2016
      Select Dataset
      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.
    • October 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 29 October, 2016
      Select Dataset
      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.
    • October 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 29 October, 2016
      Select Dataset
      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) N2701/98 and amended by Commission Regulation N1614/2002 and Commission Regulation N1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values.
    • October 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 October, 2016
      Select Dataset
      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.
    • October 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 October, 2016
      Select Dataset
      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.
    • August 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      Select Dataset
      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.
    • February 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 February, 2016
      Select Dataset
      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.
    • October 2020
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 October, 2020
      Select Dataset
      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.
    • January 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 February, 2017
      Select Dataset
      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.
    • February 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 February, 2016
      Select Dataset
      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.
    • October 2020
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 October, 2020
      Select Dataset
      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.
    • January 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      Select Dataset
      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.
    • January 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      Select Dataset
      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.
    • June 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 November, 2015
      Select Dataset
      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) N2701/98 and amended by Commission Regulation N1614/2002 and Commission Regulation N1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values.
    • October 2010
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      Select Dataset
      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.
    • August 2010
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      Select Dataset
      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.
    • March 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 30 March, 2023
      Select Dataset
      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.
    • January 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      Select Dataset
      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.
    • February 2012
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      Select Dataset
      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.
    • July 2010
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      Select Dataset
      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.
    • September 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 December, 2015
      Select Dataset
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 March, 2024
      Select Dataset
      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.
    • January 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 September, 2016
      Select Dataset
      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).  
    • January 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 September, 2016
      Select Dataset
      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).  
    • March 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 29 March, 2023
      Select Dataset
      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.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 March, 2024
      Select Dataset
      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.
    • September 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      Select Dataset
      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.
    • July 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 31 July, 2023
      Select Dataset
      This domain covers statistics and indicators on key aspects of the education systems across Europe. The data show entrants and enrolments in education levels, education personnel and the cost and type of resources dedicated to education. The standards on international statistics on education and training systems are set by the three international organisations jointly administering the annual UOE data collection: the United Nations Educational, Scientific, and Cultural Organisation Institute for Statistics (UNESCO-UIS),the Organisation for Economic Co-operation and Development (OECD) and,the Statistical Office of the European Union (EUROSTAT). The following topics are covered: Pupils and students – Enrolments and EntrantsLearning mobilityEducation personnelEducation financeGraduatesLanguage learningData and indicators disseminated include e.g. participation rates at different levels of education,  shares of pupils and students by programme orientation (general/academic and vocational/professional) and in combined school and work-based programmes, enrolments in public and private institutions, tertiary education graduates, degree mobile students enrolled and graduates, pupil-teacher ratios, foreign language learning, expenditure on education per student and relative GDP etc.
    • October 2018
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 03 November, 2018
      Select Dataset
      The annual expenditure on public and private educational institutions per pupil/student compared to GDP per capita relates the resources (e.g. expenditure for personnel, other current and capital expenditure) being devoted to education in public and private educational institutions to the overall economic welfare of a country. It is based on full-time equivalent enrolment. The use of GDP per capita allows the comparison of levels of economic activity of different sized economies (per capita) irrespective of their price levels (in PPS).
    • October 2018
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 03 November, 2018
      Select Dataset
      Expenditure per pupil/student in public and private institutions measures how much central, regional and local levels of government, private households, religious institutions and firms spent per pupil/student. It includes expenditure for personnel, other current and capital expenditure.
    • January 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 January, 2024
      Select Dataset
      The data correspond to quarterly financial accounts for the general government sector and follows the ESA2010 methodology. The data covers financial transactions and balance sheet items for general government (consolidated and non-consolidated) and its subsectors. This includes a number of financial instruments (F.1, F.2, F.3, F.4, ...) as well as some balancing items such as net financial transactions, net financial worth and net financial assets and liabilties. Data are available in million of euro, million of national currency (average exchange rates are used for transactions and end of period exchange rates are used for stocks) and as a percentage of GDP (for transactions quarterly GDP is used; for stocks a rolling sum of the last four quarters is used). In the table gov_10a_ggfa, annualised quarterly financial accounts for general government are presented. For financial transactions, data is summed over the four quarters of each year. For the conversion from national currency into euro, the yearly average exchange rate is used. For balance sheet items (stocks), the annualised data corresponds to the data of the fourth quarter. The percentage of GDP data of annualised data uses annual GDP transmitted by the Member States. In the course of the annualisation, small rounding differences may be amplified. Geographic coverage: EU and euro area. Main data sources are the tables provided according to the European Parliament and Council Regulation (EU) N° 549/2013 of 21 May 2013 (OJ No L174/1).
    • July 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 29 July, 2023
      Select Dataset
      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.
    • December 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 May, 2014
      Select Dataset
      Eurostat Dataset Id:educ_bo_ou_terd The Bologna declaration was signed in 1999 by 29 European ministers responsible for higher education. Today, 46 signatory countries are engaged in the process towards a European Higher Education Area (EHEA). The Bologna Process is an intergovernmental initiative which also involves the European Commission, the Council of Europe and UNESCO-CEPES, as well as representatives of higher education institutions, students, staff, employers and quality assurance agencies. It aims to create a European Higher Education Area by 2010, and to promote the European system of higher education worldwide. More information on the Bologna process is available on http://ec.europa.eu/education/higher-education/doc1290_en.htm. In the framework of the indicators for the monitoring of the social dimension and mobility of the Bologna Process, the EU-SILC (EU Statistics on Income and Living Conditions) data of interest cover individual's educational attainment, income and, from the intergenerational transmission of poverty ad hoc module, educational attainment of the parents. The following data-sets, having EU-SILC as source, on the Bologna Process are available: A. Widening access educ_bo_ac_sobs: Individuals having completed tertiary education (ISCED 5-6), according to the educational background of their parents, by sexeduc_bo_ac_soba: Individuals having completed tertiary education (ISCED 5-6), according to the educational background of their parents, by age D. Effective outcomes and employability educ_bo_ou_attd: Annual gross income of workers by educational attainment (2006)educ_bo_ou_terd: Annual gross income of workers with tertiary education (ISCED 5-6) , by sex (2006) The general aim of the EU-SILC domain is to provide comparable statistics and indicators on key aspects of the citizens' living conditions across Europe. This domain actually contains a range of social statistics and indicators relating to the risks of income poverty and social exclusion. There are both conceptual and methodological problems in defining and measuring income poverty and social exclusion. Since a 1984 decision of the European Council, the following are regarded as poor: "those persons, families and groups of persons whose resources (material, cultural and social) are so limited as to exclude them from the minimum acceptable way of life in the Member State to which they belong". On this basis, measures of poverty at EU level adopt an approach which is both multi-dimensional and relative. In June 2006, a new set of common indicators for the social protection and social inclusion process was adopted. (For more details and definitions of these indicators: Indicators 2006). To investigate particular areas of policy interest in more detail, target secondary areas, to be collected every four years or less frequently, are added to the cross-sectional component of EU-SILC. "The intergenerational transmission of poverty" was chosen as the area to be implemented for 2005. This specific module, collected in 2005, had as purpose to collect and compile relevant and robust information on background factors linked to adult social exclusion, minimising the burden of respondents to provide accurate detailed indicators sufficiently comparable across the EU capturing the effects of childhood experiences on poverty risk. More general information on EU-SILC is available on ilc_base.htm
    • December 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 May, 2014
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      Eurostat Dataset Id:educ_bo_ou_attd The Bologna declaration was signed in 1999 by 29 European ministers responsible for higher education. Today, 46 signatory countries are engaged in the process towards a European Higher Education Area (EHEA). The Bologna Process is an intergovernmental initiative which also involves the European Commission, the Council of Europe and UNESCO-CEPES, as well as representatives of higher education institutions, students, staff, employers and quality assurance agencies. It aims to create a European Higher Education Area by 2010, and to promote the European system of higher education worldwide. More information on the Bologna process is available on http://ec.europa.eu/education/higher-education/doc1290_en.htm. In the framework of the indicators for the monitoring of the social dimension and mobility of the Bologna Process, the EU-SILC (EU Statistics on Income and Living Conditions) data of interest cover individual's educational attainment, income and, from the intergenerational transmission of poverty ad hoc module, educational attainment of the parents. The following data-sets, having EU-SILC as source, on the Bologna Process are available: A. Widening access educ_bo_ac_sobs: Individuals having completed tertiary education (ISCED 5-6), according to the educational background of their parents, by sexeduc_bo_ac_soba: Individuals having completed tertiary education (ISCED 5-6), according to the educational background of their parents, by age D. Effective outcomes and employability educ_bo_ou_attd: Annual gross income of workers by educational attainment (2006)educ_bo_ou_terd: Annual gross income of workers with tertiary education (ISCED 5-6) , by sex (2006) The general aim of the EU-SILC domain is to provide comparable statistics and indicators on key aspects of the citizens' living conditions across Europe. This domain actually contains a range of social statistics and indicators relating to the risks of income poverty and social exclusion. There are both conceptual and methodological problems in defining and measuring income poverty and social exclusion. Since a 1984 decision of the European Council, the following are regarded as poor: "those persons, families and groups of persons whose resources (material, cultural and social) are so limited as to exclude them from the minimum acceptable way of life in the Member State to which they belong". On this basis, measures of poverty at EU level adopt an approach which is both multi-dimensional and relative. In June 2006, a new set of common indicators for the social protection and social inclusion process was adopted. (For more details and definitions of these indicators: Indicators 2006). To investigate particular areas of policy interest in more detail, target secondary areas, to be collected every four years or less frequently, are added to the cross-sectional component of EU-SILC. "The intergenerational transmission of poverty" was chosen as the area to be implemented for 2005. This specific module, collected in 2005, had as purpose to collect and compile relevant and robust information on background factors linked to adult social exclusion, minimising the burden of respondents to provide accurate detailed indicators sufficiently comparable across the EU capturing the effects of childhood experiences on poverty risk. More general information on EU-SILC is available on ilc_base.htm
    • April 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 20 April, 2023
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      Information on net earnings (net pay taken home, in absolute figures) and related tax-benefit rates (in %) complements gross‑earnings data with respect to disposable earnings. The transition from gross to net earnings requires the deduction of income taxes and employee's social security contributions from the gross amounts and the addition of family allowances, if appropriate. The amount of these components and therefore the ratio of net to gross earnings depend on the individual situation. A number of different family situations are considered, all referring to an average worker. Differences exist with respect to marital status (single vs. married), number of workers (only in the case of couples), number of dependent children, and level of gross earnings, expressed as a percentage of the gross earnings of an average worker (AW).  All the data are based on a widely acknowledged model developed by the OECD, which figures are obtained from national sources. The collection contains, for selected situations, data for the following variables and indicators : a)      gross and net earnings, including the transition components "income taxes", "employee's social security contributions" and "family allowances", if appropriate; b)      tax rate, defined as the income tax on gross wage earnings plus the employee's social security contributions less universal cash benefits, expressed as a percentage of gross wage earnings; c)      tax wedge on labour costs, defined as income tax on gross wage earnings plus the employee's and the employer's social security contributions, expressed as a percentage of the total labour costs of the earner. The total labour costs of the earner are defined as his/her gross earnings plus the employer's social security contributions plus payroll taxes (where applicable). The tax wedge on labour costs structural indicator is available only for single persons without children earning 67% of the AW. d)      unemployment trap, measuring the percentage of gross earnings which is taxed away through higher tax and social security contributions and the withdrawal of unemployment, and other, benefits when an unemployed person returns to employment. This structural indicator is available only for single persons without children earning 67% of the AW when in work. e)      low wage trap, measuring the percentage of gross earnings which is taxed away through the combined effects of income taxes, social security contributions and any withdrawal of benefits when gross earnings increase from 33% to 67% of AW. This structural indicator is available for single persons without children and one-earner couples with two children.
    • March 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 March, 2019
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    • March 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 March, 2019
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    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 09 March, 2024
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      Eurostat collects rail transport statistics by two means: 1. Voluntary data collection. Data are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF). Full details are set out in another document (see link to 21.3. Annex, at the bottom of the page). The following Eurostat dissemination tables are based on this data collection: all tables in subsection: Railway transport infrastructure (rail_if)all tables in subsection: Railway transport equipment (rail_eq)all tables in subsection: Railway transport - enterprises, economic performance and employment (rail_ec)all tables in subsection: Railway traffic (rail_tf) but table Train movements (rail_tf_trainmv)table Railway transport - Number of victims by type of injury (rail_ac_inj) in subsection Railway transport - Accidents (rail_ac)  Additionally, one table in the regional transport section is based on a different voluntary data collection (REGWeb questionnaire) and contains information on railway infrastructure (length of railway lines - total, electrified and with double or more tracks) by NUTS 2 regions. 2. Mandatory data collection based on the legal act. Data collection on goods and passenger transport, and on rail accidents is based on Regulation EC 91/2003 from the beginning of 2003. The freight data from 1982 until 2002 are based on Directive 80/1177/EEC. Compared to the Directive, Regulation 91/2003 covers the transport of passengers and statistics on accidents in addition to the transport of goods. A detailed description of the source of each dissemination table can be found in the section 21.3Annex (Legal acts and corresponding dissemination tables) at the bottom of this page.
    • February 2018
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 06 March, 2018
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    • June 2021
      Source: Philippine Statistics Authority
      Uploaded by: Knoema
      Accessed On: 03 July, 2021
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      a/ Caution in utilizing the estimate for these provinces due to its very small sample size.b/ NCR is grouped into the four districts: 1st District: City of Manila; 2nd District: Mandaluyong City, Marikina City, Pasig City, Quezon City, San Juan City; 3rd District: Caloocan City, Malabon City, Navotas City, Valenzuela City; and 4th District: Las Pinas City, Makati City, Muntinlupa City, Paranaque City, Pasay City, Pateros , and Taguig City.
    • June 2021
      Source: Philippine Statistics Authority
      Uploaded by: Knoema
      Accessed On: 03 July, 2021
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      a/ Provincial estimates were not generated due to limitations of the sampling design of the 1991 Family Income and Expenditure Survey.b/ Coefficient of variation of 2015 subsistence incidence among families is greater than 20%. c/ Caution in utilizing the estimate for these provinces due to its very small sample size. d/ NCR is grouped into the four districts: 1st District: City of Manila; 2nd District: Mandaluyong City, Marikina City, Pasig City, Quezon City, San Juan City; 3rd District: Caloocan City, Malabon City, Navotas City, Valenzuela City; and 4th District: Las Pinas City, Makati City, Muntinlupa City, Paranaque City, Pasay City, Pateros , and Taguig City.
    • June 2021
      Source: Philippine Statistics Authority
      Uploaded by: Knoema
      Accessed On: 03 July, 2021
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      a/ Provincial estimates were not generated due to limitations of the sampling design of the 1991 Family Income and Expenditure Survey.b/ Coefficient of variation of 2015 subsistence incidence among population is greater than 20%. c/ Caution in utilizing the estimate for these provinces due to its very small sample size. d/ NCR is grouped into the four districts: 1st District: City of Manila; 2nd District: Mandaluyong City, Marikina City, Pasig City, Quezon City, San Juan City; 3rd District: Caloocan City, Malabon City, Navotas City, Valenzuela City; and 4th District: Las Pinas City, Makati City, Muntinlupa City, Paranaque City, Pasay City, Pateros , and Taguig City.
    • June 2021
      Source: Philippine Statistics Authority
      Uploaded by: Knoema
      Accessed On: 03 July, 2021
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      a/ Provincial estimates were not generated due to limitations of the sampling design of the 1991 Family Income and Expenditure Survey.b/ Coefficient of variation of 2015 poverty incidence among families is greater than 20%. c/ Caution in utilizing the estimate for these provinces due to its very small sample size. d/ NCR is grouped into the four districts: 1st District: City of Manila; 2nd District: Mandaluyong City, Marikina City, Pasig City, Quezon City, San Juan City; 3rd District: Caloocan City, Malabon City, Navotas City, Valenzuela City; and 4th District: Las Pinas City, Makati City, Muntinlupa City, Paranaque City, Pasay City, Pateros , and Taguig City.
    • June 2021
      Source: Philippine Statistics Authority
      Uploaded by: Knoema
      Accessed On: 03 July, 2021
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      a/ Provincial estimates were not generated due to limitations of the sampling design of the 1991 Family Income and Expenditure Survey.b/ Coefficient of variation of 2015 poverty incidence among families is greater than 20%. c/ Caution in utilizing the estimate for these provinces due to its very small sample size. d/ NCR is grouped into the four districts: 1st District: City of Manila; 2nd District: Mandaluyong City, Marikina City, Pasig City, Quezon City, San Juan City; 3rd District: Caloocan City, Malabon City, Navotas City, Valenzuela City; and 4th District: Las Pinas City, Makati City, Muntinlupa City, Paranaque City, Pasay City, Pateros , and Taguig City.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2024
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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.
    • June 2020
      Source: United Nations Office on Drugs and Crime
      Uploaded by: Knoema
      Accessed On: 18 September, 2020
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    • August 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 September, 2016
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      Eurostat Dataset Id:med_ag32 The focus of this domain is on the following countries:Algeria, Egypt, Israel, Jordan, Lebanon, Morocco, Palestinian Authority, Syria, Tunisia. Data are provided for over 1000 indicators depending on the country.   The data for the Mediterranean partner countries are supplied by and under the responsibility of the national statistical authorities  of each of the countries or territories. The data and their denomination in no way constitute the  expression of an opinion by the European Commission on the�  legal status of a country or territory or on the delimitation of its frontiers. Â
    • February 2010
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
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      Eurostat collects rail transport statistics by two means: 1. Voluntary data collection. Data are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF). Full details are set out in another document (see link to 21.3. Annex, at the bottom of the page). The following Eurostat dissemination tables are based on this data collection: all tables in subsection: Railway transport infrastructure (rail_if)all tables in subsection: Railway transport equipment (rail_eq)all tables in subsection: Railway transport - enterprises, economic performance and employment (rail_ec)all tables in subsection: Railway traffic (rail_tf) but table Train movements (rail_tf_trainmv)table Railway transport - Number of victims by type of injury (rail_ac_inj) in subsection Railway transport - Accidents (rail_ac)  Additionally, one table in the regional transport section is based on a different voluntary data collection (REGWeb questionnaire) and contains information on railway infrastructure (length of railway lines - total, electrified and with double or more tracks) by NUTS 2 regions. 2. Mandatory data collection based on the legal act. Data collection on goods and passenger transport, and on rail accidents is based on Regulation EC 91/2003 from the beginning of 2003. The freight data from 1982 until 2002 are based on Directive 80/1177/EEC. Compared to the Directive, Regulation 91/2003 covers the transport of passengers and statistics on accidents in addition to the transport of goods. A detailed description of the source of each dissemination table can be found in the section 21.3Annex (Legal acts and corresponding dissemination tables) at the bottom of this page.
    • September 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 07 September, 2023
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      Eurostat collects rail transport statistics by two means: 1. Voluntary data collection. Data are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF). Full details are set out in another document (see link to 21.3. Annex, at the bottom of the page). The following Eurostat dissemination tables are based on this data collection: all tables in subsection: Railway transport infrastructure (rail_if)all tables in subsection: Railway transport equipment (rail_eq)all tables in subsection: Railway transport - enterprises, economic performance and employment (rail_ec)all tables in subsection: Railway traffic (rail_tf) but table Train movements (rail_tf_trainmv)table Railway transport - Number of victims by type of injury (rail_ac_inj) in subsection Railway transport - Accidents (rail_ac)  Additionally, one table in the regional transport section is based on a different voluntary data collection (REGWeb questionnaire) and contains information on railway infrastructure (length of railway lines - total, electrified and with double or more tracks) by NUTS 2 regions. 2. Mandatory data collection based on the legal act. Data collection on goods and passenger transport, and on rail accidents is based on Regulation EC 91/2003 from the beginning of 2003. The freight data from 1982 until 2002 are based on Directive 80/1177/EEC. Compared to the Directive, Regulation 91/2003 covers the transport of passengers and statistics on accidents in addition to the transport of goods. A detailed description of the source of each dissemination table can be found in the section 21.3Annex (Legal acts and corresponding dissemination tables) at the bottom of this page.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 09 March, 2024
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      Eurostat collects rail transport statistics by two means: 1. Voluntary data collection. Data are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF). Full details are set out in another document (see link to 21.3. Annex, at the bottom of the page). The following Eurostat dissemination tables are based on this data collection: all tables in subsection: Railway transport infrastructure (rail_if)all tables in subsection: Railway transport equipment (rail_eq)all tables in subsection: Railway transport - enterprises, economic performance and employment (rail_ec)all tables in subsection: Railway traffic (rail_tf) but table Train movements (rail_tf_trainmv)table Railway transport - Number of victims by type of injury (rail_ac_inj) in subsection Railway transport - Accidents (rail_ac)  Additionally, one table in the regional transport section is based on a different voluntary data collection (REGWeb questionnaire) and contains information on railway infrastructure (length of railway lines - total, electrified and with double or more tracks) by NUTS 2 regions. 2. Mandatory data collection based on the legal act. Data collection on goods and passenger transport, and on rail accidents is based on Regulation EC 91/2003 from the beginning of 2003. The freight data from 1982 until 2002 are based on Directive 80/1177/EEC. Compared to the Directive, Regulation 91/2003 covers the transport of passengers and statistics on accidents in addition to the transport of goods. A detailed description of the source of each dissemination table can be found in the section 21.3Annex (Legal acts and corresponding dissemination tables) at the bottom of this page.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2024
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      Eurostat collects rail transport statistics by two means: 1. Voluntary data collection. Data are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF). Full details are set out in another document (see link to 21.3. Annex, at the bottom of the page). The following Eurostat dissemination tables are based on this data collection: all tables in subsection: Railway transport infrastructure (rail_if)all tables in subsection: Railway transport equipment (rail_eq)all tables in subsection: Railway transport - enterprises, economic performance and employment (rail_ec)all tables in subsection: Railway traffic (rail_tf) but table Train movements (rail_tf_trainmv)table Railway transport - Number of victims by type of injury (rail_ac_inj) in subsection Railway transport - Accidents (rail_ac)  Additionally, one table in the regional transport section is based on a different voluntary data collection (REGWeb questionnaire) and contains information on railway infrastructure (length of railway lines - total, electrified and with double or more tracks) by NUTS 2 regions. 2. Mandatory data collection based on the legal act. Data collection on goods and passenger transport, and on rail accidents is based on Regulation EC 91/2003 from the beginning of 2003. The freight data from 1982 until 2002 are based on Directive 80/1177/EEC. Compared to the Directive, Regulation 91/2003 covers the transport of passengers and statistics on accidents in addition to the transport of goods. A detailed description of the source of each dissemination table can be found in the section 21.3Annex (Legal acts and corresponding dissemination tables) at the bottom of this page.
    • February 2023
      Source: Statistics Bureau of Japan
      Uploaded by: Knoema
      Accessed On: 16 February, 2023
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      Statistics Name: Current Survey of Supply and Demand for Petroleum Products
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 April, 2024
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      Eurostat collects road transport statistics by two means: 1. Data on infrastructure, transport equipment, enterprises, economic performance, employment, traffic, aggregated data on transport of passengers and goods as well as data on accidents are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF, in the framework of OECD). The method of the Common Questionnaire data collection is presented in a separate document. 2. Data on carriage of goods by road, using heavy goods vehicles, are based on a continuum of legal acts: 2.1 Data collection on carriage of goods by road until 1998 (included) was based on Directives 78/546/EEC and 89/462/EEC and covered tonnes and tonne-kilometres only. 2.2 Data since the reference period 1999 are derived from micro-data collected in the framework of Regulation (EU) No 70/2012 of the European parliament and of the council on statistical returns in respect of the carriage of goods by road, a recast ofCouncil Regulation (EC) 1172/98 which has replaced the previous Directives. The figures are aggregated on the basis of sample surveys carried out by the reporting countries. The data cover tonnes, tonne-kilometres, vehicle-kilometres and numbers of journeys. These metadata pages only refer to road freight statistics based on the European Union's legal acts (point 2 above) and, in particular, to the data for reference years 1999 and after (2.2).
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 April, 2024
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      Eurostat collects road transport statistics by two means: 1. Data on infrastructure, transport equipment, enterprises, economic performance, employment, traffic, aggregated data on transport of passengers and goods as well as data on accidents are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF, in the framework of OECD). The method of the Common Questionnaire data collection is presented in a separate document. 2. Data on carriage of goods by road, using heavy goods vehicles, are based on a continuum of legal acts: 2.1 Data collection on carriage of goods by road until 1998 (included) was based on Directives 78/546/EEC and 89/462/EEC and covered tonnes and tonne-kilometres only. 2.2 Data since the reference period 1999 are derived from micro-data collected in the framework of Regulation (EU) No 70/2012 of the European parliament and of the council on statistical returns in respect of the carriage of goods by road, a recast ofCouncil Regulation (EC) 1172/98 which has replaced the previous Directives. The figures are aggregated on the basis of sample surveys carried out by the reporting countries. The data cover tonnes, tonne-kilometres, vehicle-kilometres and numbers of journeys. These metadata pages only refer to road freight statistics based on the European Union's legal acts (point 2 above) and, in particular, to the data for reference years 1999 and after (2.2).
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 April, 2024
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      Eurostat collects road transport statistics by two means: 1. Data on infrastructure, transport equipment, enterprises, economic performance, employment, traffic, aggregated data on transport of passengers and goods as well as data on accidents are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF, in the framework of OECD). The method of the Common Questionnaire data collection is presented in a separate document. 2. Data on carriage of goods by road, using heavy goods vehicles, are based on a continuum of legal acts: 2.1 Data collection on carriage of goods by road until 1998 (included) was based on Directives 78/546/EEC and 89/462/EEC and covered tonnes and tonne-kilometres only. 2.2 Data since the reference period 1999 are derived from micro-data collected in the framework of Regulation (EU) No 70/2012 of the European parliament and of the council on statistical returns in respect of the carriage of goods by road, a recast of Council Regulation (EC) 1172/98 which has replaced the previous Directives. The figures are aggregated on the basis of sample surveys carried out by the reporting countries. The data cover tonnes, tonne-kilometres, vehicle-kilometres and numbers of journeys. These metadata pages only refer to road freight statistics based on the European Union's legal acts (point 2 above) and, in particular, to the data for reference years 1999 and after (2.2).
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 April, 2024
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      Eurostat collects road transport statistics by two means: 1. Data on infrastructure, transport equipment, enterprises, economic performance, employment, traffic, aggregated data on transport of passengers and goods as well as data on accidents are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF, in the framework of OECD). The method of the Common Questionnaire data collection is presented in a separate document. 2. Data on carriage of goods by road, using heavy goods vehicles, are based on a continuum of legal acts: 2.1 Data collection on carriage of goods by road until 1998 (included) was based on Directives 78/546/EEC and 89/462/EEC and covered tonnes and tonne-kilometres only. 2.2 Data since the reference period 1999 are derived from micro-data collected in the framework of Regulation (EU) No 70/2012 of the European parliament and of the council on statistical returns in respect of the carriage of goods by road, a recast ofCouncil Regulation (EC) 1172/98 which has replaced the previous Directives. The figures are aggregated on the basis of sample surveys carried out by the reporting countries. The data cover tonnes, tonne-kilometres, vehicle-kilometres and numbers of journeys. These metadata pages only refer to road freight statistics based on the European Union's legal acts (point 2 above) and, in particular, to the data for reference years 1999 and after (2.2).
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 April, 2024
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      Due to the nature of transport, a spatial reference is built into most legal acts dealing with transport statistics. In a few cases, these sources can be directly used for the derivation of regional transport indicators, while other indicators are collected on a voluntary basis. This is the case of the regional transport data collection in which both data types are used. Three types of regional data can be distinguished depending on their source: two are based on data collections performed on the basis of legal acts (the Maritime and Aviation data) and one is a voluntary data collection (infrastructures, vehicles and road accidents). Regional data collected on voluntary basis: The current regional data collection taking place on a voluntary basis comprises a set of transport indicators at NUTS 0, 1 and 2[1] levels for the road, railways, inland waterways (infrastructure), vehicle stocks, road accidents. The information collected is then disseminated in Eurostat dissemination database (Eurobase) under “General and regional statistics/Regional statistics by NUTS classification/Regional transport statistics” theme and also mirrored under “Transport/Multimodal data/Regional transport statistics” theme. Annual data collection for infrastructure, vehicle stocks and road accidents was launched at the beginning of 2002 covering both Member States and Candidate countries. Since 2007, it includes EFTA countries as well. Regional data are collected directly from the countries using a questionnaire: data on transport infrastructure, vehicle stocks and road accidents (collected previously – till 2006 – on Excel sheets and then – till 2012 – using on-line questionnaires). Currently regional datasets are provided via EDAMIS application. For the voluntary data collection via EDAMIS portal, the definitions from the 4th edition of the Illustrated Glossary for Transport Statistics (jointly elaborated by Eurostat, ECMT, UNECE) were proposed and countries should use them when transmitting data. Regional data based on legal acts: For the collection based on legal acts, regional data are actually derived from the information provided by the participating countries in the frame of the legal data collections at port and airport level. Maritime transport data collection is legally based – Directive 2009/42/EC of the European Parliament and of the Council of 6 May 2009 on statistical returns in respect of carriage of goods and passengers by sea (OJ L141 of 6.6.2009, page 29), which is the recast of the original Council Directive 95/64/EC of 8 December 1995. The air transport regional data have been calculated using data collected at the airport level in the frame of draft Council and Parliament Regulation (Regulation (EC) No 437/2003 of the European Parliament and of the Council of 27 February 2003 on statistical returns in respect of the carriage of passengers, freight and mail by air). Within the collection Maritime transport - data aggregated at standard regional levels (NUTS) there are two tables: Maritime transport of passengers at regional level (new methodology);Maritime transport of freight at regional level (new methodology). Within the collection Air transport - data aggregated at standard regional levels (NUTS) there are two tables: Air transport of passengers at regional levelAir transport of freight at regional level The tables present the evolution of the number of passengers carried (if not available passengers on board) and the volume of freight and mail loaded or unloaded (if not available freight and mail on board) to/from the NUTS regions (level 2, 1 and 0) since 1999. The data is presented at annual level. Before the legal act on air transport statistics was introduced (2003 with 3 years transitional period), air transport statistics have been collected using the statistical questionnaire (voluntary basis). Some countries provided figures for passenger transport taking into account “passengers on board” and some “passenger carried”. Until 2007 reference year, the disseminated numbers of passengers aggregated at regional level are actually a mixture of passengers on board and passengers carried data. The air transport regional data have been calculated using data collected at the airport level in the frame of the regulatory data collection on air transport. Only airports with more than 150 000 passenger units serviced annually are taken into account when aggregating the data at regional levels, because they provide statistics detailed enough to solve the problem of double counting. For each aggregate it is necessary to start at the airport level in order to identify the mirror declarations, i.e. the airport routes for which both airports report the volume, since these constitute the routes where the problem of double counting occurs. When calculating the total volume in such cases, only the departure declarations of the concerned airports have been taken into account. The problem of the double counting only appears for the calculation of the total passengers but not for the total arrivals (respectively total departures), which corresponds to the sum of the arrivals (respectively departures) at each domestic airport. For the tables presenting maritime data at regional level the same aggregation method (exclusion of double counting) is applied taking into account main ports only. Only for these ports (handling more than one million tonnes of goods or recording more than 200 000 passenger movements annually ) the detailed statistics allow such aggregation. For some Member States (up to 1998 data) and for others that joint the EU more recently (up to 2002) transport flows through ports and airports had been collected, via questionnaire. Because of the difference in the methodologies applied, the data for air and maritime transport at regional level up to 2002 reference year are available in separate tablesor some Member States (up to 1998 data) and for others that joint the EU more recently (up to 2002) transport flows through ports and airports had been collected, via questionnaire. Because of the difference in the methodologies applied, the data for air and maritime transport at regional level up to 2002 reference year are avilable in separate tables (listed below) and are no longer updated: Maritime transport of passengers by NUTS 2 regions (questionnaire) (tran_r_mapa_om).Maritime transport of freight by NUTS 2 regions (questionnaire) (tran_r_mago_om).Air transport of passengers by NUTS 2 regions (questionnaire) (tran_r_avpa_om).Air transport of freight by NUTS 2 regions (questionnaire) (tran_r_avgo_om). [1] Regulation (EC) No 1059/2003 of the European Parliament and of the Council of 26 May 2003 on the establishment of a common classification of territorial units for statistics (NUTS) and its amendments. More information on NUTS classification can be found under the following link.
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 April, 2024
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      Due to the nature of transport, a spatial reference is built into most legal acts dealing with transport statistics. In a few cases, these sources can be directly used for the derivation of regional transport indicators, while other indicators are collected on a voluntary basis. This is the case of the regional transport data collection in which both data types are used. Three types of regional data can be distinguished depending on their source: two are based on data collections performed on the basis of legal acts (the Maritime and Aviation data) and one is a voluntary data collection (infrastructures, vehicles and road accidents). Regional data collected on voluntary basis: The current regional data collection taking place on a voluntary basis comprises a set of transport indicators at NUTS 0, 1 and 2[1] levels for the road, railways, inland waterways (infrastructure), vehicle stocks, road accidents. The information collected is then disseminated in Eurostat dissemination database (Eurobase) under “General and regional statistics/Regional statistics by NUTS classification/Regional transport statistics” theme and also mirrored under “Transport/Multimodal data/Regional transport statistics” theme. Annual data collection for infrastructure, vehicle stocks and road accidents was launched at the beginning of 2002 covering both Member States and Candidate countries. Since 2007, it includes EFTA countries as well. Regional data are collected directly from the countries using a questionnaire: data on transport infrastructure, vehicle stocks and road accidents (collected previously – till 2006 – on Excel sheets and then – till 2012 – using on-line questionnaires). Currently regional datasets are provided via EDAMIS application. For the voluntary data collection via EDAMIS portal, the definitions from the 4th edition of the Illustrated Glossary for Transport Statistics (jointly elaborated by Eurostat, ECMT, UNECE) were proposed and countries should use them when transmitting data. Regional data based on legal acts: For the collection based on legal acts, regional data are actually derived from the information provided by the participating countries in the frame of the legal data collections at port and airport level. Maritime transport data collection is legally based – Directive 2009/42/EC of the European Parliament and of the Council of 6 May 2009 on statistical returns in respect of carriage of goods and passengers by sea (OJ L141 of 6.6.2009, page 29), which is the recast of the original Council Directive 95/64/EC of 8 December 1995. The air transport regional data have been calculated using data collected at the airport level in the frame of draft Council and Parliament Regulation (Regulation (EC) No 437/2003 of the European Parliament and of the Council of 27 February 2003 on statistical returns in respect of the carriage of passengers, freight and mail by air). Within the collection Maritime transport - data aggregated at standard regional levels (NUTS) there are two tables: Maritime transport of passengers at regional level (new methodology);Maritime transport of freight at regional level (new methodology). Within the collection Air transport - data aggregated at standard regional levels (NUTS) there are two tables: Air transport of passengers at regional levelAir transport of freight at regional level The tables present the evolution of the number of passengers carried (if not available passengers on board) and the volume of freight and mail loaded or unloaded (if not available freight and mail on board) to/from the NUTS regions (level 2, 1 and 0) since 1999. The data is presented at annual level. Before the legal act on air transport statistics was introduced (2003 with 3 years transitional period), air transport statistics have been collected using the statistical questionnaire (voluntary basis). Some countries provided figures for passenger transport taking into account “passengers on board” and some “passenger carried”. Until 2007 reference year, the disseminated numbers of passengers aggregated at regional level are actually a mixture of passengers on board and passengers carried data. The air transport regional data have been calculated using data collected at the airport level in the frame of the regulatory data collection on air transport. Only airports with more than 150 000 passenger units serviced annually are taken into account when aggregating the data at regional levels, because they provide statistics detailed enough to solve the problem of double counting. For each aggregate it is necessary to start at the airport level in order to identify the mirror declarations, i.e. the airport routes for which both airports report the volume, since these constitute the routes where the problem of double counting occurs. When calculating the total volume in such cases, only the departure declarations of the concerned airports have been taken into account. The problem of the double counting only appears for the calculation of the total passengers but not for the total arrivals (respectively total departures), which corresponds to the sum of the arrivals (respectively departures) at each domestic airport. For the tables presenting maritime data at regional level the same aggregation method (exclusion of double counting) is applied taking into account main ports only. Only for these ports (handling more than one million tonnes of goods or recording more than 200 000 passenger movements annually ) the detailed statistics allow such aggregation. For some Member States (up to 1998 data) and for others that joint the EU more recently (up to 2002) transport flows through ports and airports had been collected, via questionnaire. Because of the difference in the methodologies applied, the data for air and maritime transport at regional level up to 2002 reference year are available in separate tablesor some Member States (up to 1998 data) and for others that joint the EU more recently (up to 2002) transport flows through ports and airports had been collected, via questionnaire. Because of the difference in the methodologies applied, the data for air and maritime transport at regional level up to 2002 reference year are avilable in separate tables (listed below) and are no longer updated: Maritime transport of passengers by NUTS 2 regions (questionnaire) (tran_r_mapa_om).Maritime transport of freight by NUTS 2 regions (questionnaire) (tran_r_mago_om).Air transport of passengers by NUTS 2 regions (questionnaire) (tran_r_avpa_om).Air transport of freight by NUTS 2 regions (questionnaire) (tran_r_avgo_om). [1] Regulation (EC) No 1059/2003 of the European Parliament and of the Council of 26 May 2003 on the establishment of a common classification of territorial units for statistics (NUTS) and its amendments. More information on NUTS classification can be found under the following link.
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 April, 2024
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      Eurostat collects road transport statistics by two means: 1. Data on infrastructure, transport equipment, enterprises, economic performance, employment, traffic, aggregated data on transport of passengers and goods as well as data on accidents are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF, in the framework of OECD). The method of the Common Questionnaire data collection is presented in a separate document. 2. Data on carriage of goods by road, using heavy goods vehicles, are based on a continuum of legal acts: 2.1 Data collection on carriage of goods by road until 1998 (included) was based on Directives 78/546/EEC and 89/462/EEC and covered tonnes and tonne-kilometres only. 2.2 Data since the reference period 1999 are derived from micro-data collected in the framework of Regulation (EU) No 70/2012 of the European parliament and of the council on statistical returns in respect of the carriage of goods by road, a recast ofCouncil Regulation (EC) 1172/98 which has replaced the previous Directives. The figures are aggregated on the basis of sample surveys carried out by the reporting countries. The data cover tonnes, tonne-kilometres, vehicle-kilometres and numbers of journeys. These metadata pages only refer to road freight statistics based on the European Union's legal acts (point 2 above) and, in particular, to the data for reference years 1999 and after (2.2).
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 April, 2024
      Select Dataset
      Eurostat collects road transport statistics by two means: 1. Data on infrastructure, transport equipment, enterprises, economic performance, employment, traffic, aggregated data on transport of passengers and goods as well as data on accidents are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF, in the framework of OECD). The method of the Common Questionnaire data collection is presented in a separate document. 2. Data on carriage of goods by road, using heavy goods vehicles, are based on a continuum of legal acts: 2.1 Data collection on carriage of goods by road until 1998 (included) was based on Directives 78/546/EEC and 89/462/EEC and covered tonnes and tonne-kilometres only. 2.2 Data since the reference period 1999 are derived from micro-data collected in the framework of Regulation (EU) No 70/2012 of the European parliament and of the council on statistical returns in respect of the carriage of goods by road, a recast ofCouncil Regulation (EC) 1172/98 which has replaced the previous Directives. The figures are aggregated on the basis of sample surveys carried out by the reporting countries. The data cover tonnes, tonne-kilometres, vehicle-kilometres and numbers of journeys. These metadata pages only refer to road freight statistics based on the European Union's legal acts (point 2 above) and, in particular, to the data for reference years 1999 and after (2.2).
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 April, 2024
      Select Dataset
      Eurostat collects road transport statistics by two means: 1. Data on infrastructure, transport equipment, enterprises, economic performance, employment, traffic, aggregated data on transport of passengers and goods as well as data on accidents are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF, in the framework of OECD). The method of the Common Questionnaire data collection is presented in a separate document. 2. Data on carriage of goods by road, using heavy goods vehicles, are based on a continuum of legal acts: 2.1 Data collection on carriage of goods by road until 1998 (included) was based on Directives 78/546/EEC and 89/462/EEC and covered tonnes and tonne-kilometres only. 2.2 Data since the reference period 1999 are derived from micro-data collected in the framework of Regulation (EU) No 70/2012 of the European parliament and of the council on statistical returns in respect of the carriage of goods by road, a recast of Council Regulation (EC) 1172/98 which has replaced the previous Directives. The figures are aggregated on the basis of sample surveys carried out by the reporting countries. The data cover tonnes, tonne-kilometres, vehicle-kilometres and numbers of journeys. These metadata pages only refer to road freight statistics based on the European Union's legal acts (point 2 above) and, in particular, to the data for reference years 1999 and after (2.2).
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 April, 2024
      Select Dataset
      Eurostat collects road transport statistics by two means: 1. Data on infrastructure, transport equipment, enterprises, economic performance, employment, traffic, aggregated data on transport of passengers and goods as well as data on accidents are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF, in the framework of OECD). The method of the Common Questionnaire data collection is presented in a separate document. 2. Data on carriage of goods by road, using heavy goods vehicles, are based on a continuum of legal acts: 2.1 Data collection on carriage of goods by road until 1998 (included) was based on Directives 78/546/EEC and 89/462/EEC and covered tonnes and tonne-kilometres only. 2.2 Data since the reference period 1999 are derived from micro-data collected in the framework of Regulation (EU) No 70/2012 of the European parliament and of the council on statistical returns in respect of the carriage of goods by road, a recast ofCouncil Regulation (EC) 1172/98 which has replaced the previous Directives. The figures are aggregated on the basis of sample surveys carried out by the reporting countries. The data cover tonnes, tonne-kilometres, vehicle-kilometres and numbers of journeys. These metadata pages only refer to road freight statistics based on the European Union's legal acts (point 2 above) and, in particular, to the data for reference years 1999 and after (2.2).
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 April, 2024
      Select Dataset
      Eurostat collects road transport statistics by two means: 1. Data on infrastructure, transport equipment, enterprises, economic performance, employment, traffic, aggregated data on transport of passengers and goods as well as data on accidents are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF, in the framework of OECD). The method of the Common Questionnaire data collection is presented in a separate document. 2. Data on carriage of goods by road, using heavy goods vehicles, are based on a continuum of legal acts: 2.1 Data collection on carriage of goods by road until 1998 (included) was based on Directives 78/546/EEC and 89/462/EEC and covered tonnes and tonne-kilometres only. 2.2 Data since the reference period 1999 are derived from micro-data collected in the framework of Regulation (EU) No 70/2012 of the European parliament and of the council on statistical returns in respect of the carriage of goods by road, a recast ofCouncil Regulation (EC) 1172/98 which has replaced the previous Directives. The figures are aggregated on the basis of sample surveys carried out by the reporting countries. The data cover tonnes, tonne-kilometres, vehicle-kilometres and numbers of journeys. These metadata pages only refer to road freight statistics based on the European Union's legal acts (point 2 above) and, in particular, to the data for reference years 1999 and after (2.2).
    • September 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      Select Dataset
      This data collection covers data on the steel industry, which is defined as group 27.1 of the Statistical classification of economic activities in the European Community (NACE Rev.1.1). For the first reference year 2003 the Commission will accept that the population covered refers to group 27.1 of NACE Rev.1. The statistics collected on the steel industry are: Annual statistics on the steel and cast iron scrap balance sheetAnnual statistics on the fuel and energy consumption broken down by type of plantAnnual statistics on the balance sheet for electrical energy in the steel industryAnnual statistics on investment expenditure in the iron and steel industryAnnual statistics on the maximum possible (and actual) production in the iron and steel industry The characteristics are defined in the Commission Regulation No 772/2005 of 20 May 2005 concerning the specifications for the coverage of the characteristics and the definition of the technical format for the production of annual Community statistics on steel for the reference years 2003 to 2009 (See annex at the bottom of the page). Member States of which the Steel industry (NACE Rev.1.1 27.1) represents less than 1% of the Community total need not to collect the characteristics of European Parliament and Council Regulation No 48/2004 (See annex at the bottom of the page). Steel Statistics data are collected by National Statistical Institutes (NSI) or by national federations of the Steel industry. Iron and steel data collection was discontinued from 2010 onwards.
    • September 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
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      This data collection covers data on the steel industry, which is defined as group 27.1 of the Statistical classification of economic activities in the European Community (NACE Rev.1.1). For the first reference year 2003 the Commission will accept that the population covered refers to group 27.1 of NACE Rev.1. The statistics collected on the steel industry are: Annual statistics on the steel and cast iron scrap balance sheetAnnual statistics on the fuel and energy consumption broken down by type of plantAnnual statistics on the balance sheet for electrical energy in the steel industryAnnual statistics on investment expenditure in the iron and steel industryAnnual statistics on the maximum possible (and actual) production in the iron and steel industry The characteristics are defined in the Commission Regulation No 772/2005 of 20 May 2005 concerning the specifications for the coverage of the characteristics and the definition of the technical format for the production of annual Community statistics on steel for the reference years 2003 to 2009 (See annex at the bottom of the page). Member States of which the Steel industry (NACE Rev.1.1 27.1) represents less than 1% of the Community total need not to collect the characteristics of European Parliament and Council Regulation No 48/2004 (See annex at the bottom of the page). Steel Statistics data are collected by National Statistical Institutes (NSI) or by national federations of the Steel industry. Iron and steel data collection was discontinued from 2010 onwards.
    • September 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      Select Dataset
      This data collection covers data on the steel industry, which is defined as group 27.1 of the Statistical classification of economic activities in the European Community (NACE Rev.1.1). For the first reference year 2003 the Commission will accept that the population covered refers to group 27.1 of NACE Rev.1. The statistics collected on the steel industry are: Annual statistics on the steel and cast iron scrap balance sheetAnnual statistics on the fuel and energy consumption broken down by type of plantAnnual statistics on the balance sheet for electrical energy in the steel industryAnnual statistics on investment expenditure in the iron and steel industryAnnual statistics on the maximum possible (and actual) production in the iron and steel industry The characteristics are defined in the Commission Regulation No 772/2005 of 20 May 2005 concerning the specifications for the coverage of the characteristics and the definition of the technical format for the production of annual Community statistics on steel for the reference years 2003 to 2009 (See annex at the bottom of the page). Member States of which the Steel industry (NACE Rev.1.1 27.1) represents less than 1% of the Community total need not to collect the characteristics of European Parliament and Council Regulation No 48/2004 (See annex at the bottom of the page). Steel Statistics data are collected by National Statistical Institutes (NSI) or by national federations of the Steel industry. Iron and steel data collection was discontinued from 2010 onwards.
    • September 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      Select Dataset
      This data collection covers data on the steel industry, which is defined as group 27.1 of the Statistical classification of economic activities in the European Community (NACE Rev.1.1). For the first reference year 2003 the Commission will accept that the population covered refers to group 27.1 of NACE Rev.1. The statistics collected on the steel industry are: Annual statistics on the steel and cast iron scrap balance sheetAnnual statistics on the fuel and energy consumption broken down by type of plantAnnual statistics on the balance sheet for electrical energy in the steel industryAnnual statistics on investment expenditure in the iron and steel industryAnnual statistics on the maximum possible (and actual) production in the iron and steel industry The characteristics are defined in the Commission Regulation No 772/2005 of 20 May 2005 concerning the specifications for the coverage of the characteristics and the definition of the technical format for the production of annual Community statistics on steel for the reference years 2003 to 2009 (See annex at the bottom of the page). Member States of which the Steel industry (NACE Rev.1.1 27.1) represents less than 1% of the Community total need not to collect the characteristics of European Parliament and Council Regulation No 48/2004 (See annex at the bottom of the page). Steel Statistics data are collected by National Statistical Institutes (NSI) or by national federations of the Steel industry. Iron and steel data collection was discontinued from 2010 onwards.
    • June 2023
      Source: Statistics Denmark
      Uploaded by: Knoema
      Accessed On: 09 June, 2023
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    • June 2023
      Source: Statistics Denmark
      Uploaded by: Knoema
      Accessed On: 09 June, 2023
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    • January 2020
      Source: Philippine Statistics Authority
      Uploaded by: Knoema
      Accessed On: 25 January, 2020
      Select Dataset
        This data set consists data of valuation of agricultural production in Philippines. 
    • December 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 19 December, 2023
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      Eurostat's database covers 1) Production and trade in roundwood and wood products, including primary and secondary products 2) Economic data on forestry and logging, including employment data 3) Sustainable forest management, comprising forest resources (assets) and environmental data. The main types of primary forest products included in (1) are: roundwood, sawnwood, wood-based panels, pulp, and paper and paperboard. Secondary products include further processed wood and paper products. These products are presented in greater detail; definitions are available. All of the data are compiled from the Joint Forest Sector Questionnaire (JFSQ), except for table (e), which is directly extracted from Eurostat's international trade database COMEXT (HS/CN Chapter 44). The tables in (1) cover details of the following topics: - Roundwood removals and production by type of wood and assortment (a) - Roundwood production by type of ownership (b) - Production and trade in roundwood, fuelwood and other basic products (c) - Trade in industrial roundwood by assortment and species (d) - Tropical wood imports to the EU from Chapter 44 of the Harmonised System (e) - Production and trade in sawnwood, panels and other primary products (f) - Sawnwood trade by species (g) - Production and trade in pulp and paper & paperboard (h) - Trade in secondary wood and paper products (i) Data in (2) include the output, intermediate consumption, gross value added, fixed capital consumption, gross fixed capital formation and different measures of income of forestry and logging.  The data are in current basic prices and are compatible with National Accounts. They are collected as part of Intergrated environmental and economic accounting for forests (IEEAF), which also covers labour input in annual work units (AWU).  Under (2), two separate tables cover the number of employees of forestry and logging, the manufacture of wood and products of wood and cork, and the manufacture of paper and paper products, as estimated from the Labour Force Survey results. There are two separate tables because of the change in the EU's classification of economic activities from NACE Rev. 1.1 to NACE Rev. 2 in 2008. More detailed information on wood products and accounting, including definitions and questionnaires, can be found on our open-access communication platform under the interest group 'Forestry statistics and accounts'.  Data in (3) are not collected by Eurostat, but by the FAO, UNECE, Forest Euope, the European Commission's departments for Environment and the Joint Research Centre. They include forest area, wood volume, defoliation on sample plots, fires and areas with protective functions.
    • June 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 20 June, 2023
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      Data are the result of the annual structure of government debt survey and cover the EU countries as well as Norway. The following series are available: Central government gross debt by initital maturity and sector of debt holder; State government gross debt by initital maturity and sector of debt holder; Local government gross debt by initital maturity and sector of debt holder; Social security funds gross debt by initital maturity and sector of debt holder; General government gross debt by initital maturity and sector of debt holder; Debt by currency of issuance; Government guarantees (contingent liabilities); Average remaining maturity of debt; Apparent cost of the debt; Market value of debt.
    • March 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 March, 2023
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      Apparent labour productivity is defined as value added at factor costs divided by the number of persons employed. This ratio is generally presented in thousands of euros per person employed.
    • March 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 April, 2019
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    • March 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 April, 2019
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    • March 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 April, 2019
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    • July 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 November, 2015
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    • October 2018
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 21 October, 2018
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    • October 2018
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 21 October, 2018
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    • September 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 September, 2023
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      Data source used: The aquaculture production data collection is part of the more comprehensive data gathering carried out on an annual basis by the Fisheries Committee (COFI) of the Trade and Agriculture Directorate (TAD) from OECD members and participating non-OECD economies. Data on marine landings, aquaculture production, inland fisheries catch, fleet, employment, total allowable catch (TAC) and fisheries support estimate (FSE) are collected from Fisheries Ministries, National Statistics Offices and other institutions designated as an official data source. The surveys used for this exercise are the OECD Fisheries questionnaires.
    • October 2013
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
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      Aquaculture, also known as aquafarming, refers to the farming of aquatic (freshwater or saltwater) organisms, such as fish, molluscs, crustaceans and plants, for human use or consumption, under controlled conditions. Aquaculture implies some form of intervention in the natural rearing process to enhance production, including regular stocking, feeding and protection from predators. Farming also implies individual or corporate ownership of, or contractual rights to, the stock being cultivated. European data on the quantity of aquaculture production, in tonnes life weight (TLW), have been recorded since 1950 [fish_aq_q]. Since 1984, data on the total value of the production in Thousand Euro are also available [fish_aq_v]. With the entry into force of the new Regulation (EC) No 762/2008 on the submission of aquaculture statistics, since the reference year 2008 aquaculture production data are collected and disseminated annually in 5 tables: Production from aquaculture excluding hatcheries and nurseries [fish_aq2a] by species, by FAO major area, by production method, by aquatic environment in TLW (tonnes live weight) and in Euro.Production of fish eggs for human consumption from aquaculture [fish_aq2b] by species, by FAO major area, by aquatic environment in TLW, Euro and Euro/Tonne.Input to capture-based aquaculture [fish_aq3] by species in Number, TLW, Euro and Euro/Tonne.Production of hatcheries and nurseries at eggs stage in life cycle [fish_aq4a] by species and intended uses in Millions.Production of hatcheries and nurseries at juveniles stage in life cycle [fish_aq4b] by species and intended uses in Millions. Every three years, these data are complemented by Data on the structure of the aquaculture sector [fish_aq5] by species, by FAO major area, by production method, by aquatic environment in Meters, 1000 of M3 and Hectares. In addition, annual methodological reports of the national systems for aquaculture statistics [fish_aq6] are provided by the EEA Member States with details on the organisation of the national systems for aquacuture statistics and the respective methods of collecting, processing and compiling the aquaculture data as well as quality aspects in line with the 'Code of Practice for the European Statistical System'. According to the Regulation (EC) No 762/2008, aquaculture production means the output from aquaculture at first sale (including production from hatcheries and nurseries offered for sale). Non-commercial leisure aquaculture is thus not accounted for. Moreover, aquaculture production of aquarium and ornamental species is excluded. Data are submitted by all Member States of the European Economic Area by the 31st of December for the preceeding year (reporting year -1). They are compiled by the respective competent authorities of the Member States, usually either the National Statistical Institute or the Ministry of Agriculture.
    • April 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 20 April, 2024
      Select Dataset
      Total production of fish, crustaceans, molluscs and other aquatic organisms from aquaculture ("fish-farming") from 2008 onwards, excluding hatcheries and nurseries. The data are expressed in Tonnes Live Weight (TLW, incl. shells, skeletons, etc.), Euro and Euro/Tonne. Production data from hatcheries and nurseries can be found in the fish_aq2b, fish_aq4a and fish_aq4b tables. Older data (1950-2007), excluding production from hatcheries and nurseries, are contained in the "Aquaculture production until 2007 (fish_aq08)" database.
    • October 2013
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      Select Dataset
      Aquaculture, also known as aquafarming, refers to the farming of aquatic (freshwater or saltwater) organisms, such as fish, molluscs, crustaceans and plants, for human use or consumption, under controlled conditions. Aquaculture implies some form of intervention in the natural rearing process to enhance production, including regular stocking, feeding and protection from predators. Farming also implies individual or corporate ownership of, or contractual rights to, the stock being cultivated. European data on the quantity of aquaculture production, in tonnes life weight (TLW), have been recorded since 1950 [fish_aq_q]. Since 1984, data on the total value of the production in Thousand Euro are also available [fish_aq_v]. With the entry into force of the new Regulation (EC) No 762/2008 on the submission of aquaculture statistics, since the reference year 2008 aquaculture production data are collected and disseminated annually in 5 tables: Production from aquaculture excluding hatcheries and nurseries [fish_aq2a] by species, by FAO major area, by production method, by aquatic environment in TLW (tonnes live weight) and in Euro.Production of fish eggs for human consumption from aquaculture [fish_aq2b] by species, by FAO major area, by aquatic environment in TLW, Euro and Euro/Tonne.Input to capture-based aquaculture [fish_aq3] by species in Number, TLW, Euro and Euro/Tonne.Production of hatcheries and nurseries at eggs stage in life cycle [fish_aq4a] by species and intended uses in Millions.Production of hatcheries and nurseries at juveniles stage in life cycle [fish_aq4b] by species and intended uses in Millions. Every three years, these data are complemented by Data on the structure of the aquaculture sector [fish_aq5] by species, by FAO major area, by production method, by aquatic environment in Meters, 1000 of M3 and Hectares. In addition, annual methodological reports of the national systems for aquaculture statistics [fish_aq6] are provided by the EEA Member States with details on the organisation of the national systems for aquacuture statistics and the respective methods of collecting, processing and compiling the aquaculture data as well as quality aspects in line with the 'Code of Practice for the European Statistical System'. According to the Regulation (EC) No 762/2008, aquaculture production means the output from aquaculture at first sale (including production from hatcheries and nurseries offered for sale). Non-commercial leisure aquaculture is thus not accounted for. Moreover, aquaculture production of aquarium and ornamental species is excluded. Data are submitted by all Member States of the European Economic Area by the 31st of December for the preceeding year (reporting year -1). They are compiled by the respective competent authorities of the Member States, usually either the National Statistical Institute or the Ministry of Agriculture.
    • January 2024
      Source: Philippine Statistics Authority
      Uploaded by: Knoema
      Accessed On: 02 February, 2024
      Select Dataset
      Aquaculture refers to production in enclosures whether ponds, pens, cages or on substrates such as stakes, ropes, lines, nets, shells, or on a demarcated natural bed using seedstock, which may be naturally occurring, or artificially produced in hatcheries.   Aquafarm is a body of water, usually a tract of shallow water along the shore of a bay or inlet, used for aquaculture.
    • January 2024
      Source: Philippine Statistics Authority
      Uploaded by: Knoema
      Accessed On: 31 January, 2024
      Select Dataset
      Aquaculture refers to production in enclosures whether ponds, pens, cages or on substrates such as stakes, ropes, lines, nets, shells, or on a demarcated natural bed using seedstock, which may be naturally occurring, or artificially produced in hatcheries.
    • January 2024
      Source: Philippine Statistics Authority
      Uploaded by: Knoema
      Accessed On: 31 January, 2024
      Select Dataset
      Aquaculture refers to production in enclosures whether ponds, pens, cages or on substrates such as stakes, ropes, lines, nets, shells, or on a demarcated natural bed using seedstock, which may be naturally occurring, or artificially produced in hatcheries. Aquafarm is a body of water, usually a tract of shallow water along the shore of a bay or inlet, used for aquaculture.
    • January 2024
      Source: Philippine Statistics Authority
      Uploaded by: Knoema
      Accessed On: 31 January, 2024
      Select Dataset
      Aquaculture refers to production in enclosures whether ponds, pens, cages or on substrates such as stakes, ropes, lines, nets, shells, or on a demarcated natural bed using seedstock, which may be naturally occurring, or artificially produced in hatcheries.
    • April 2024
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 07 April, 2024
      Select Dataset
      AQUASTAT is FAO's global information system on water and agriculture, developed by the Land and Water Division. The main mandate of the program is to collect, analyze and disseminate information on water resources, water uses, and agricultural water management with an emphasis on countries in Africa, Asia, Latin America and the Caribbean. This allows interested users to find comprehensive and regularly updated information at global, regional, and national levels.
    • January 2014
      Source: World Resources Institute
      Uploaded by: Knoema
      Accessed On: 07 December, 2015
      Select Dataset
      This dataset shows countries and river basins' average exposure to five of Aqueduct's water risk indicators: baseline water stress, interannual variability, seasonal variability, flood occurrence, and drought severity. Risk exposure scores are available for every country (except Greenland and Antarctica), the 100 most populous river basins, and the 100 largest river basins by area. Scores are also available for all industrial, agricultural, and domestic users' average exposure to each indicator in each country and river basin. Citation: Gassert, F., P. Reig, T. Luo, and A. Maddocks. 2013. “Aqueduct country and river basin rankings: a weighted aggregation of spatially distinct hydrological indicators.” Working paper. Washington, DC: World Resources Institute, November 2013. Available online at http://wri.org/publication/aqueduct-country-river-basin-rankings.
    • December 2019
      Source: World Resources Institute
      Uploaded by: Knoema
      Accessed On: 29 January, 2020
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    • August 2015
      Source: World Resources Institute
      Uploaded by: Knoema
      Accessed On: 25 March, 2019
      Select Dataset
      Recent Stress Ranking can be checked here: https://knoema.com/WRINWS2020/national-water-stress-rankings Suggested citation: Luo, T., R. Young, and P. Reig. 2015. "Aqueduct projected water stress rankings." Technical note. Washington, DC: World Resources Institute, August 215. Available online at http://www.wri.org/publication/aqueduct-projected-water-stress-country-rankings.    Supplemental Materials: Country Scores                         WRI projected future country-level water stress for 2020, 2030, and 2040 under business-as-usual (BAU), optimistic, and pessimistic scenarios. Each tab lists country projected water stress scores for each scenario and year, weighted by overall water withdrawals. Scores weighted by individual sectors (agricultural, domestic, and industrial) are provided as well.   These global projections are best suited to making comparisons among countries for the same year and among scenarios and decades for the same region. More detailed and localized data or scenarios can better estimate potential outcomes for specific regions and expose large sub-national variations that are subsumed under countrywide water-stress values. The country indicators face persistent limitations in attempting to simplify complex information, such as spatial and temporal variations, into a single number. They also do not account for the governance and investment structure of the water sector in different countries.    It is important to note the inherent uncertainty in estimating any future conditions, particularly those associated with climate change, future population and economic trends, and water demand. Additionally, care should be taken when examining the change rates of a country’s projected stress levels between one year and another, because the risk-score thresholds are not linear. For more information on these limitations, see the technical note.   Projections are described in further detail in: Luck, M., M. Landis, and F. Gassert, “Aqueduct Water Stress Projections: Decadal Projections of Water Supply and Demand Using CMIP5 GCMs,” Technical note (Washington, DC: World Resources Institute, April 2015), http://www.wri.org/publication/aqueduct-water-stress-projections.   Water Stress withdrawals / available flow Water stress measures total annual water withdrawals (municipal, industrial, and agricultural) expressed as a percentage of the total annual available blue water. Higher values indicate more competition among users. Score Value [0-1) Low (<10%) [1-2) Low to medium (10-20%) [2-3) Medium to high (20-40%) [3-4) High (40-80%) [4-5] Extremely high (>80%)    
    • March 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 30 March, 2023
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      The domain EUROFARM (ef) contains information (statistical tables) on structure of agricultural holdings collected through agricultural structure surveys. The data of the domain have been organised into two collections: Results of the farm structure surveys contains data from 1990 onwards based on the 1988 legislation andResults of the farm structure surveys based on the legislation from 2008. This collection contains the data from the 2010 Census onwards as well as the data for the surveys 2007 and 2005. Farm Structure Survey data are used to collect information on agricultural holdings in the Member States at different geographic levels (Member States, regions, districts) and over periods (follow up the changes in agricultural sector), thus provide a base for decision making in the Common Agricultural Policy. Two kinds of Farm Structure Survey (FSS) are carried out by Member States: a basic survey (full scope Agricultural Census - AC) every 10 years,several sample based intermediate surveys between them. However for certain characteristics the Member States may use sample base for every survey. The calendar for the surveys to be held in all Member States is agreed by the Agricultural Statistics Committee of the European Commission. For a given survey year, Member States have to conduct their surveys within the agreed time-frame, thus all the data are as comparable as possible. The FSS are organised in all Member States on a harmonised base. Whereas the characteristics are based on community legislation, the same data are available for all countries in case of each survey. The data on individual agricultural holdings are collected by all Member States and sent to Eurostat. The aggregated results are disseminated through statistical tables. The variables are arranged into groups: general overview with key variables,and other specialized groups containing detailed data onland uselivestockfarm labour forcerural development issues as well as management and practices. The 2010 survey additionally provides the results of the survey on agricultural production methods (SAPM). The scope of the survey is agriculture, while the survey unit is the agricultural holding (farm). Data for basic surveys are available in a three-level geographical breakdown of the whole country, the regions and the district; while data for intermediate surveys are only available upon the two-levels of country and regions. Since FSS 1999/2000 information about local farm location is collected in most countries, so that the data can also be disseminated by NUTS and are robust regarding the changes in the NUTS definition. The FSS 2009/2010 information is inline with the NUTS 2010 classification: Regulation (EU) No 31/2011 amending the NUTS classification from January 2003. The Eurofarm domain does not cover the whole territory only the land covered by the agricultural holdings. So the land use data without link with other farm characteristics should be downloaded by the user from the relevant domain. Specific national data about crops, animals or agricultural labour force can be found in other domains, without link between the other information at farm level. For a comprehensive description of the domain, please consult detailed structure (See annex at the bottom of the page). Regional Data Data for basic surveys are available in a three-level geographical breakdown of the whole country, the regions and the district; while data for intermediate surveys are only available upon the two-levels of country and regions. Since FSS 1999/2000 information about local farm location is collected in most countries, so that the data can also be disseminated by NUTS classification and are robust regarding the changes in the NUTS definition. The FSS 2009/2010 information is inline with the NUTS 2010 classification: Regulation (EU) No 31/2001 amending the NUTS classification from January 2012. 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.
    • January 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 January, 2017
      Select Dataset
      The domain EUROFARM (ef) contains information (statistical tables) on structure of agricultural holdings collected through agricultural structure surveys. The data of the domain have been organised into two collections: Results of the farm structure surveys contains data from 1990 onwards based on the 1988 legislation andResults of the farm structure surveys based on the legislation from 2008. This collection contains the data from the 2010 Census onwards as well as the data for the surveys 2007 and 2005. Farm Structure Survey data are used to collect information on agricultural holdings in the Member States at different geographic levels (Member States, regions, districts) and over periods (follow up the changes in agricultural sector), thus provide a base for decision making in the Common Agricultural Policy. Two kinds of Farm Structure Survey (FSS) are carried out by Member States: a basic survey (full scope Agricultural Census - AC) every 10 years,several sample based intermediate surveys between them. However for certain characteristics the Member States may use sample base for every survey. The calendar for the surveys to be held in all Member States is agreed by the Agricultural Statistics Committee of the European Commission. For a given survey year, Member States have to conduct their surveys within the agreed time-frame, thus all the data are as comparable as possible. The FSS are organised in all Member States on a harmonised base. Whereas the characteristics are based on community legislation, the same data are available for all countries in case of each survey. The data on individual agricultural holdings are collected by all Member States and sent to Eurostat. The aggregated results are disseminated through statistical tables. The variables are arranged into groups: general overview with key variables,and other specialized groups containing detailed data onland uselivestockfarm labour forcerural development issues as well as management and practices. The 2010 survey additionally provides the results of the survey on agricultural production methods (SAPM). The scope of the survey is agriculture, while the survey unit is the agricultural holding (farm). Data for basic surveys are available in a three-level geographical breakdown of the whole country, the regions and the district; while data for intermediate surveys are only available upon the two-levels of country and regions. Since FSS 1999/2000 information about local farm location is collected in most countries, so that the data can also be disseminated by NUTS and are robust regarding the changes in the NUTS definition. The FSS 2009/2010 information is inline with the NUTS 2010 classification: Regulation (EU) No 31/2011 amending the NUTS classification from January 2003. The Eurofarm domain does not cover the whole territory only the land covered by the agricultural holdings. So the land use data without link with other farm characteristics should be downloaded by the user from the relevant domain. Specific national data about crops, animals or agricultural labour force can be found in other domains, without link between the other information at farm level. For a comprehensive description of the domain, please consult detailed structure (See annex at the bottom of the page). Regional Data Data for basic surveys are available in a three-level geographical breakdown of the whole country, the regions and the district; while data for intermediate surveys are only available upon the two-levels of country and regions. Since FSS 1999/2000 information about local farm location is collected in most countries, so that the data can also be disseminated by NUTS classification and are robust regarding the changes in the NUTS definition. The FSS 2009/2010 information is inline with the NUTS 2010 classification: Regulation (EU) No 31/2001 amending the NUTS classification from January 2012. 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.
    • January 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 January, 2017
      Select Dataset
      The domain EUROFARM (ef) contains information (statistical tables) on structure of agricultural holdings collected through agricultural structure surveys. The data of the domain have been organised into two collections: Results of the farm structure surveys contains data from 1990 onwards based on the 1988 legislation andResults of the farm structure surveys based on the legislation from 2008. This collection contains the data from the 2010 Census onwards as well as the data for the surveys 2007 and 2005. Farm Structure Survey data are used to collect information on agricultural holdings in the Member States at different geographic levels (Member States, regions, districts) and over periods (follow up the changes in agricultural sector), thus provide a base for decision making in the Common Agricultural Policy. Two kinds of Farm Structure Survey (FSS) are carried out by Member States: a basic survey (full scope Agricultural Census - AC) every 10 years,several sample based intermediate surveys between them. However for certain characteristics the Member States may use sample base for every survey. The calendar for the surveys to be held in all Member States is agreed by the Agricultural Statistics Committee of the European Commission. For a given survey year, Member States have to conduct their surveys within the agreed time-frame, thus all the data are as comparable as possible. The FSS are organised in all Member States on a harmonised base. Whereas the characteristics are based on community legislation, the same data are available for all countries in case of each survey. The data on individual agricultural holdings are collected by all Member States and sent to Eurostat. The aggregated results are disseminated through statistical tables. The variables are arranged into groups: general overview with key variables,and other specialized groups containing detailed data onland uselivestockfarm labour forcerural development issues as well as management and practices. The 2010 survey additionally provides the results of the survey on agricultural production methods (SAPM). The scope of the survey is agriculture, while the survey unit is the agricultural holding (farm). Data for basic surveys are available in a three-level geographical breakdown of the whole country, the regions and the district; while data for intermediate surveys are only available upon the two-levels of country and regions. Since FSS 1999/2000 information about local farm location is collected in most countries, so that the data can also be disseminated by NUTS and are robust regarding the changes in the NUTS definition. The FSS 2009/2010 information is inline with the NUTS 2010 classification: Regulation (EU) No 31/2011 amending the NUTS classification from January 2003. The Eurofarm domain does not cover the whole territory only the land covered by the agricultural holdings. So the land use data without link with other farm characteristics should be downloaded by the user from the relevant domain. Specific national data about crops, animals or agricultural labour force can be found in other domains, without link between the other information at farm level. For a comprehensive description of the domain, please consult detailed structure (See annex at the bottom of the page). Regional Data Data for basic surveys are available in a three-level geographical breakdown of the whole country, the regions and the district; while data for intermediate surveys are only available upon the two-levels of country and regions. Since FSS 1999/2000 information about local farm location is collected in most countries, so that the data can also be disseminated by NUTS classification and are robust regarding the changes in the NUTS definition. The FSS 2009/2010 information is inline with the NUTS 2010 classification: Regulation (EU) No 31/2001 amending the NUTS classification from January 2012. 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.
    • January 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 January, 2024
      Select Dataset
      Total Surface Area (TSA)  – Total Surface Area is defined as the area of any given statistical area and includes land area and inland waters (lakes, rivers etc.). The sub-national areas (e.g. LAU and NUTS areas) defined by statistical and/or administrative boundaries are the building blocks for calculating both concepts. By definition Total Surface Area does not cover areas that are not statistical areas. Total Land Area (TLA) is defined as TSA excluding lakes, rivers, transitional and coastal waters. Mountainous regions, glaciers, forests, wetlands and other tempoarily or permanently uninhabitable regions are included in TLA. Both TSA and TLA are provided per Member State and for all statistical units from NUTS level 1 to NUTS level 3. TSA and TLA are the denominator in area based indicators, such as population density. Both datasets have the same reference date as the current valid NUTS classification (2013). A more generalised version (scale 1: 1 000 000) of the NUTS areas than used for the calculation of TSA and TLA can be downloaded from the Eurostat website http://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units/nuts
    • August 2020
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 29 August, 2020
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    • June 2021
      Source: Philippine Statistics Authority
      Uploaded by: Knoema
      Accessed On: 03 July, 2021
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      Data are tabulated by residence of Holder/Operator. Area planted is in hectares. Details may not add up to total due to rounding
    • June 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 June, 2017
      Select Dataset
      Eurostat Dataset Id:mare_d3area
    • February 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 February, 2024
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      The source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview
    • December 2023
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 19 December, 2023
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      Eurostat's database covers 1) Production and trade in roundwood and wood products, including primary and secondary products 2) Economic data on forestry and logging, including employment data 3) Sustainable forest management, comprising forest resources (assets) and environmental data. The main types of primary forest products included in (1) are: roundwood, sawnwood, wood-based panels, pulp, and paper and paperboard. Secondary products include further processed wood and paper products. These products are presented in greater detail; definitions are available. All of the data are compiled from the Joint Forest Sector Questionnaire (JFSQ), except for table (e), which is directly extracted from Eurostat's international trade database COMEXT (HS/CN Chapter 44). The tables in (1) cover details of the following topics: - Roundwood removals and production by type of wood and assortment (a) - Roundwood production by type of ownership (b) - Production and trade in roundwood, fuelwood and other basic products (c) - Trade in industrial roundwood by assortment and species (d) - Tropical wood imports to the EU from Chapter 44 of the Harmonised System (e) - Production and trade in sawnwood, panels and other primary products (f) - Sawnwood trade by species (g) - Production and trade in pulp and paper & paperboard (h) - Trade in secondary wood and paper products (i) Data in (2) include the output, intermediate consumption, gross value added, fixed capital consumption, gross fixed capital formation and different measures of income of forestry and logging.  The data are in current basic prices and are compatible with National Accounts. They are collected as part of Intergrated environmental and economic accounting for forests (IEEAF), which also covers labour input in annual work units (AWU).  Under (2), two separate tables cover the number of employees of forestry and logging, the manufacture of wood and products of wood and cork, and the manufacture of paper and paper products, as estimated from the Labour Force Survey results. There are two separate tables because of the change in the EU's classification of economic activities from NACE Rev. 1.1 to NACE Rev. 2 in 2008. More detailed information on wood products and accounting, including definitions and questionnaires, can be found on our open-access communication platform under the interest group 'Forestry statistics and accounts'.  Data in (3) are not collected by Eurostat, but by the FAO, UNECE, Forest Euope, the European Commission's departments for Environment and the Joint Research Centre. They include forest area, wood volume, defoliation on sample plots, fires and areas with protective functions.
    • March 2021
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 March, 2021
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    • March 2018
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 11 March, 2018
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      This indicator monitors trends in agricultural land enrolled in agri-environmental measures (AEM) as the share of total utilised agricultural area (UAA). For EU15, the data include agri-environmental contracts under Regulation (EC) 2078/1992 and contracts signed in 2000-2005 under the Regulation (EC) 1257/1999. For countries from the 2004 enlargement, agri-environmental contracts under regulation (EC) 1257/1999 started from their accession to the EU.
    • October 2022
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 October, 2022
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      The indicator is defined as the share of total utilised agricultural area (UAA) occupied by organic farming (existing organically-farmed areas and areas in process of conversion). Organic farming is a method of production, which puts the highest emphasis on environmental protection and, with regard to livestock production, animal welfare considerations. It avoids or largely reduces the use of synthetic chemical inputs such as fertilisers, pesticides, additives and medical products. Farming is only considered to be organic at the EU level if it complies with Council Regulation (EC) No 834/2007, which has set up a comprehensive framework for the organic production of crops and livestock and for the labelling, processing and marketing of organic products, while also governing imports of organic products into the EU. The detailed rules for the implementation of this Regulation are laid down in Commission Regulation (EC) No 889/2008.
    • March 2024
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 March, 2024
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      The indicator measures the share of total utilised agricultural area (UAA) occupied by organic farming (existing organically-farmed areas and areas in process of conversion). Farming is recognised to be organic if it complies with Council Regulation (EC) No 834/2007, which has set up a comprehensive framework for the organic production of crops and livestock and for the labelling, processing and marketing of organic products, as well as for governing imports of organic products into the EU. The detailed rules for the implementation of this Regulation are laid down in Commission Regulation (EC) No 889/2008.
    • March 2018
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 March, 2018
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      The indicator is defined as the share of total utilised agricultural area (UAA) occupied by organic farming (existing organically-farmed areas and areas in process of conversion). Organic farming is a method of production, which puts the highest emphasis on environmental protection and, with regard to livestock production, animal welfare considerations. It avoids or largely reduces the use of synthetic chemical inputs such as fertilisers, pesticides, additives and medical products. Farming is only considered to be organic at the EU level if it complies with Council Regulation (EC) No 834/2007, which has set up a comprehensive framework for the organic production of crops and livestock and for the labelling, processing and marketing of organic products, while also governing imports of organic products into the EU. The detailed rules for the implementation of this Regulation are laid down in Commission Regulation (EC) No 889/2008. The indicator is a Sustainable Development Indicator (SDI). It has been chosen for the assessment of the progress towards the objectives and targets of the EU Sustainable Development Strategy. The indicator is also a Resource Efficiency Indicator, as it has been chosen as a dashboard indicator presented in the Resource Efficiency Scoreboard for the assessment of progress towards the objectives and targets of the Europe 2020 flagship iniciative on Resoure Efficiency. tsdpc440´s table: Eurobase > Tables by themes > Agriculture, forestry and fisheries > Food: From farm to fork statistics > Inputs to the food chain > Area under organic farming (tsdpc440) tsdpc440´s table within the SDI set: Eurobase > Tables on EU policy > Sustainable Development indicators > Sustainable consumption and production > Production patterns > Area under organic farming (tsdpc440) tsdpc440´s table within the Europe 2020 set: Eurobase > Tables on EU policy > Europe 2020 Indicators > Resource efficiency > Natural capital and ecosystem services > Biodiversity > Area under organic farming (tsdpc440)
    • June 2013
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 August, 2015
      Select Dataset
      Eurostat Dataset Id:vit_bs5 The domain VIT contains the results of surveys of areas under vines in statistical tables. The data of the domain have been organised into two collections: - vit_an contains all available data from annual intermediate surveys. These surveys collect only data on areas under vines of wine grape varieties.  - vit_bs includes the data collected via basic surveys every ten years. The scope of these surveys is the area under all type of vines. Surveys on vineyards are used to collect information on vines and wine production in the Member States at different geographic levels (Member States and regions) and over time (follow up the changes); thus they provide basic information in framework of the common market organisation of wine. The intermediate annual surveys  cover the area under vines of wine grape varieties in the holdings and relate to changes which have taken place in that area during the preceding wine-growing year. Information regarding the following characteristics is available: - area under vines for wine grape varieties, - area under vines grubbed or no longer cultivated, - area under vines replanted, - area under vines newly planted. All of these are broken down according to their normal use for the production of - quality wines psr (produced in specific regions), - other wines (including wines compulsorily intended for the manufacture of certain potable spirits obtained from wine with a registered designation of origin). The areas under vines cultivated with wine grape varieties are also broken down into yield classes based upon the potential and (optionally) effective yield per hectare (hl/ha of grape must or wine).   The basic surveys cover all holdings having a cultivated area under vines normally intended for the production for sale of grapes, grape must, wine or vegetative propagation material for vines. Information regarding the following characteristics is available for each unit: - agricultural area in use, - area under vines cultivated; broken down according to its normal production into:area under wine grape varieties (separate the quality wines produced in special regions  and the other wines),area under table grape varieties,area planted with root-stock for future grafting,area cultivated solely for production of vegetative propagation material for vines (subdivided into nurseries and parent vines for root-stock areas),area under grapes intended for drying (raisins). The areas under vines cultivated with wine grape varieties as recorded in the basic surveys are broken down into yield classes based upon the potential and (optionally) effective yield per hectare (hl/ha of grape must or wine). Data are available for different territorial breakdowns for each country (wine-growing regions). Data is available for the following EU Member States: Germany, Greece, Spain, France, Italy, Luxembourg, Austria, Portugal, United Kingdom.
    • March 2012
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 April, 2014
      Select Dataset
      Eurostat Dataset Id:vit_bs4_at The domain VIT contains the results of surveys of areas under vines in statistical tables. The data of the domain have been organised into two collections: - vit_an contains all available data from annual intermediate surveys. These surveys collect only data on areas under vines of wine grape varieties.  - vit_bs includes the data collected via basic surveys every ten years. The scope of these surveys is the area under all type of vines. Surveys on vineyards are used to collect information on vines and wine production in the Member States at different geographic levels (Member States and regions) and over time (follow up the changes); thus they provide basic information in framework of the common market organisation of wine. The intermediate annual surveys  cover the area under vines of wine grape varieties in the holdings and relate to changes which have taken place in that area during the preceding wine-growing year. Information regarding the following characteristics is available: - area under vines for wine grape varieties, - area under vines grubbed or no longer cultivated, - area under vines replanted, - area under vines newly planted. All of these are broken down according to their normal use for the production of - quality wines psr (produced in specific regions), - other wines (including wines compulsorily intended for the manufacture of certain potable spirits obtained from wine with a registered designation of origin). The areas under vines cultivated with wine grape varieties are also broken down into yield classes based upon the potential and (optionally) effective yield per hectare (hl/ha of grape must or wine).   The basic surveys cover all holdings having a cultivated area under vines normally intended for the production for sale of grapes, grape must, wine or vegetative propagation material for vines. Information regarding the following characteristics is available for each unit: - agricultural area in use, - area under vines cultivated; broken down according to its normal production into:area under wine grape varieties (separate the quality wines produced in special regions  and the other wines),area under table grape varieties,area planted with root-stock for future grafting,area cultivated solely for production of vegetative propagation material for vines (subdivided into nurseries and parent vines for root-stock areas),area under grapes intended for drying (raisins). The areas under vines cultivated with wine grape varieties as recorded in the basic surveys are broken down into yield classes based upon the potential and (optionally) effective yield per hectare (hl/ha of grape must or wine). Data are available for different territorial breakdowns for each country (wine-growing regions). Data is available for the following EU Member States: Germany, Greece, Spain, France, Italy, Luxembourg, Austria, Portugal, United Kingdom.
    • March 2012
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 December, 2015
      Select Dataset
      The domain VIT contains the results of surveys of areas under vines in statistical tables. The data of the domain have been organised into two collections: - vit_an contains all available data from annual intermediate surveys. These surveys collect only data on areas under vines of wine grape varieties.  - vit_bs includes the data collected via basic surveys every ten years. The scope of these surveys is the area under all type of vines. Surveys on vineyards are used to collect information on vines and wine production in the Member States at different geographic levels (Member States and regions) and over time (follow up the changes); thus they provide basic information in framework of the common market organisation of wine. The intermediate annual surveys  cover the area under vines of wine grape varieties in the holdings and relate to changes which have taken place in that area during the preceding wine-growing year. Information regarding the following characteristics is available: - area under vines for wine grape varieties, - area under vines grubbed or no longer cultivated, - area under vines replanted, - area under vines newly planted. All of these are broken down according to their normal use for the production of - quality wines psr (produced in specific regions), - other wines (including wines compulsorily intended for the manufacture of certain potable spirits obtained from wine with a registered designation of origin). The areas under vines cultivated with wine grape varieties are also broken down into yield classes based upon the potential and (optionally) effective yield per hectare (hl/ha of grape must or wine).   The basic surveys cover all holdings having a cultivated area under vines normally intended for the production for sale of grapes, grape must, wine or vegetative propagation material for vines. Information regarding the following characteristics is available for each unit: - agricultural area in use, - area under vines cultivated; broken down according to its normal production into: area under wine grape varieties (separate the quality wines produced in special regions  and the other wines),area under table grape varieties,area planted with root-stock for future grafting,area cultivated solely for production of vegetative propagation material for vines (subdivided into nurseries and parent vines for root-stock areas),area under grapes intended for drying (raisins). The areas under vines cultivated with wine grape varieties as recorded in the basic surveys are broken down into yield classes based upon the potential and (optionally) effective yield per hectare (hl/ha of grape must or wine). Data are available for different territorial breakdowns for each country (wine-growing regions). Data is available for the following EU Member States: Germany, Greece, Spain, France, Italy, Luxembourg, Austria, Portugal, United Kingdom.
    • March 2012
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 December, 2015
      Select Dataset
      The domain VIT contains the results of surveys of areas under vines in statistical tables. The data of the domain have been organised into two collections: - vit_an contains all available data from annual intermediate surveys. These surveys collect only data on areas under vines of wine grape varieties.  - vit_bs includes the data collected via basic surveys every ten years. The scope of these surveys is the area under all type of vines. Surveys on vineyards are used to collect information on vines and wine production in the Member States at different geographic levels (Member States and regions) and over time (follow up the changes); thus they provide basic information in framework of the common market organisation of wine. The intermediate annual surveys  cover the area under vines of wine grape varieties in the holdings and relate to changes which have taken place in that area during the preceding wine-growing year. Information regarding the following characteristics is available: - area under vines for wine grape varieties, - area under vines grubbed or no longer cultivated, - area under vines replanted, - area under vines newly planted. All of these are broken down according to their normal use for the production of - quality wines psr (produced in specific regions), - other wines (including wines compulsorily intended for the manufacture of certain potable spirits obtained from wine with a registered designation of origin). The areas under vines cultivated with wine grape varieties are also broken down into yield classes based upon the potential and (optionally) effective yield per hectare (hl/ha of grape must or wine).   The basic surveys cover all holdings having a cultivated area under vines normally intended for the production for sale of grapes, grape must, wine or vegetative propagation material for vines. Information regarding the following characteristics is available for each unit: - agricultural area in use, - area under vines cultivated; broken down according to its normal production into: area under wine grape varieties (separate the quality wines produced in special regions  and the other wines),area under table grape varieties,area planted with root-stock for future grafting,area cultivated solely for production of vegetative propagation material for vines (subdivided into nurseries and parent vines for root-stock areas),area under grapes intended for drying (raisins). The areas under vines cultivated with wine grape varieties as recorded in the basic surveys are broken down into yield classes based upon the potential and (optionally) effective yield per hectare (hl/ha of grape must or wine). Data are available for different territorial breakdowns for each country (wine-growing regions). Data is available for the following EU Member States: Germany, Greece, Spain, France, Italy, Luxembourg, Austria, Portugal, United Kingdom.
    • March 2012
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 December, 2015
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      The domain VIT contains the results of surveys of areas under vines in statistical tables. The data of the domain have been organised into two collections: - vit_an contains all available data from annual intermediate surveys. These surveys collect only data on areas under vines of wine grape varieties.  - vit_bs includes the data collected via basic surveys every ten years. The scope of these surveys is the area under all type of vines. Surveys on vineyards are used to collect information on vines and wine production in the Member States at different geographic levels (Member States and regions) and over time (follow up the changes); thus they provide basic information in framework of the common market organisation of wine. The intermediate annual surveys