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Greece

  • President:Prokopis Pavlopoulos
  • Prime Minister:Alexis Tsipras
  • Capital city:Athens
  • Languages:Greek (official) 99%, other (includes English and French) 1%
  • Government
  • National statistics office
  • Population:10,746,740 (2016)
  • Area:128,900 (2016)
  • GDP per capita:18,104 (2016)
  • GDP, billion current US$:194.6 (2016)
  • GINI index:36.68 (2012)
  • Ease of Doing Business rank:61 (2016)
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
  • 1
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      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
    • February 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 01 August, 2017
      Select Dataset
      This dataset contains the main results of the 2014 Eurostat-OECD PPP comparison for the 47 countries that participated in the 2014 round of the Eurostat-OECD Purchasing Power Parity (PPP) Programme. The dataset is organised in 23 tables which show results both in US dollars and OECD as reference (Table 1.1 to Table 1.12) and in euros and European Union as reference (Table 2.1 to Table 2.11) calculated with the EKS method. The tables contain the following information: Table 1.1 to 1.12The dollar serves as numeraire and the OECD as reference country (except for Table 1.12 where theUnited States are the reference country). Table 1.1 and Table 1.2 present the data on which thefollowing ten tables are based.• Table 1.1 gives nominal expenditure in national currency of the participating countries.• Table 1.2 presents PPPs (OECD=1.00) that have been calculated for the participating countriesusing the price and expenditure data collected during the 2014 round. The PPPs were obtainedby the EKS method of calculation and aggregation.• Table 1.3 shows nominal expenditure of Table 1.1 converted to US dollars. Exchange rates donot reflect the relative purchasing power of different currencies and the converted expenditure isstill expressed at national prices. As such, it remains nominal measures, the spatial equivalent ofa time series of GDP for a single country at current prices. Hence, they are called “nominalexpenditure”. The nominal expenditure in the table reflects both differences in the quantities ofgoods and services purchased in the countries and differences in the price levels of the countries.• Table 1.4 gives nominal expenditure of Table 1.3 expressed on a per capita basis using the midyearpopulation data.• Table 1.5 and Table 1.6 present the nominal expenditure from Table 1.3 and the nominalexpenditure per head from Table 1.4 as indices with OECD=100.• Table 1.7 shows real expenditure converted to US dollar using the PPPs from Table 1.2. PPPsequalise the purchasing power of different currencies during the process of conversion and theconverted expenditures are expressed at international prices (that is at the same price level). Assuch, they are real measures, the spatial equivalent of a time series of GDP for a single countryat constant prices. Hence, they are called “real expenditures”. The real final expenditures in thetable reflect only differences in the volumes of goods and services purchased in the countries.• Table 1.8 gives the real expenditure of Table 1.7 expressed on a per capita basis using the midyearpopulation data. Again, the real expenditures per head in this table are not additive nor arethey subject to the Gerschenkron effect.• Table 1.9 and Table 1.10 present the real expenditure on GDP from Table 1.7 and the real finalexpenditure per head on GDP from Table 1.8 as indices with OECD=100.• Table 1.11 gives the price levels which are computed as ratios of the PPPs in Table 1.2 to theexchange rates and are expressed as indices with OECD=100. For a given aggregate, theyindicate the number of units of the common currency needed to buy the same volume of the aggregate in each country. Price levels that exceed 100 indicate that the level of prices in thatcountry and for that analytical category is higher than the average price level for the OECD.• Table 1.12 present PPPs as in Table 1.2 (see description above) but with the United States asreference country (US=1.00).Table 2.1 to 2.11The euro serves as numeraire and the European Union as reference country. Table 2.1 and Table 2.2present the data on which the following nine tables are based. Table 2.1 to 2.11 contain the sameinformation as Table 1.1 to 1.11 with a different basis. For explanation on the contents, please seedescription above.
  • 3
  • A
    • October 2011
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 May, 2014
      Select Dataset
      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
    • March 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 29 June, 2014
      Select Dataset
      Eurostat Dataset Id:hsw_ij_svinj 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.
    • March 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 June, 2014
      Select Dataset
      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.
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 August, 2017
      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).
    • July 2016
      Source: Knoema
      Uploaded by: Knoema
      Select Dataset
      Accuracy of annual economic forecasts of international organizations - European Commission, IMF, OECD, World Bank, UN LINK
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
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    • July 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 July, 2017
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      The annual Eurostat's collection on statistics on acquisitions of citizenship is structured as follows:   l
    • July 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 July, 2017
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      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
    • July 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 31 July, 2017
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      The labour market policy (LMP) database was developed and maintained by Eurostat till 2013. From 2014, the LMP database is developed and maintained by European Commission's Directorate General for Employment, Social Affairs and Inclusion and LMP data are disseminated by Eurostat. European Commission's LMP database provides information on labour market interventions, which are government actions to help and support the unemployed and other disadvantaged groups in the transition from unemployment or inactivity to work. The scope of the LMP database is limited to interventions that are explicitly targeted at groups of persons with difficulties in the labour market: the unemployed, persons employed but at risk of involuntary job loss and persons currently considered as inactive persons but who would like to enter the labour market. LMP statistics are one of the data sources for monitoring the Employment Guidelines (part II of the Europe 2020 Integrated Guidelines) through the Europe 2020 Joint Assessment Framework (JAF). The guidelines specifically refer to the provision of active labour market policies, which cover LMP measures and LMP services, and adequate social security systems, which include LMP supports. The unit of observation in the LMP database is the labour market intervention and data on the expenditure and participants for each intervention are collected annually from administrative sources in each country. The database also collects extensive qualitative information that describes each intervention, how it works, the main target groups, etc. LMP interventions are classified by type of action into three broad types – services, measures and supports – and into 9 detailed categories (see 3.2 Classification system). The LMP database covers all EU Member States and Norway. Data for the EU-15 countries and Norway are available from 1998 whilst the more recently acceded EU countries started providing data at different times from 2003 onwards. The following data and metadata are available:Summary tables of expenditure and participants by type of actionFor each country: detailed tables of expenditure and participants by interventionLMP based indicators for monitoring the Employment Guidelines (for definitions see annexes below)Reference data on persons registered with Public Employment Services (PES)Qualitative reports describing the interventions in each country
    • June 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 June, 2017
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      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
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
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      The Unemployment - LFS adjusted series (including also Harmonised long-term unemployment) is a collection of monthly, quarterly and annual series based on the quarterly results of the EU Labour Force Survey (EU-LFS), which are, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator. The EU-LFS covers the resident population in private households. The MIP scoreboard indicators from the domain are:Unemployment rate, 3 years average. Long-term unemployment rate, % of active population aged 15-74 - 3 years change in p.p.Youth unemployment rate, % of active population aged 15-24 - 3 years change in p.p. For the MIP purposes are published the source data used for the indicator's calculation: annual and quarterly data on unemployment rate and annual figures on youth and long-term unemployment rate.
    • February 2017
      Source: Bureau of Economic Analysis
      Uploaded by: Knoema
      Accessed On: 13 February, 2017
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      Activities of U.S. MNEs: Majority-Owned Foreign Affiliates, Selected Indicators, 2014.
    • April 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 May, 2017
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    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
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      The indicator Activity rate is based on the quarterly EU Labour Force Survey (EU-LFS) results. The survey covers the resident population in private households. The MIP scoreboard indicator is Activity rate - % of total population aged 15-64 (3 years change in p.p.). 
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
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      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
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      The indicator is defined as the percentage of the population aged 15-64 who are economically active. According to the definitions of the International Labour Organisation (ILO) people are classified as employed, unemployed and economically inactive for the purposes of labour market statistics. The economically active population (also called labour force) is the sum of employed and unemployed persons. Inactive persons are those who, during the reference week, were neither employed nor unemployed. The indicator is based on the EU Labour Force Survey.
    • June 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 June, 2016
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      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
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      In 2011, the European Union Labour Force Survey (EU-LFS) included an ad hoc module (AHM) on employment of disabled people. The module consisted of 11 variables dealing with:Health problems and difficulties in basic activities;Limitations in work caused by health problems/difficulties in basic activities;Special assistance needed or used by people with health problems/difficulties in basic activities;Limitation in work because of other reasons. On the basis of how the module was operationalised, the following two main definitions for disability were considered for presenting the results:Disabled persons = People having a basic activity difficulty (such as seeing, hearing, walking, communicating);Disabled persons = People having a work limitation caused by a longstanding health condition and/or a basic activity difficulty. 32 countries have implemented this module: the EU 28 Member States plus Turkey, Iceland, Norway and Switzerland. The Norwegian data are not disseminated because the AHM questionnaire in Norway only partly complies with the Commission Regulation (EU) No 317/2010 and consequently, the data are incomplete and partly comparable. Missing values, don't know and refusal answers are not considered in the calculations. It means the indicators have been worked out on the respondents and validated answers only.
    • November 2016
      Source: United Nations Economic Commission for Europe
      Uploaded by: Knoema
      Accessed On: 12 November, 2016
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      Adolescent fertility covers live births to women aged 15-19.A live birth is the complete expulsion or extraction from its mother of a product of conception, irrespective of the duration of pregnancy, which after such separation breathes or shows any other evidence of life such as beating of the heart, pulsation of the umbilical cord or definite movement of voluntary muscles, whether or not the umbilical cord has been cut or the placenta is attached.The adolescent fertility rate is the number of live births to women aged 15-19 per 1000 women aged 15-19.
    • March 2013
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 24 November, 2013
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      Eurostat Dataset Id:demo_r_mdthrt 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.   
    • May 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 August, 2017
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    • May 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 August, 2017
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    • May 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 August, 2017
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    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
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      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 20 September, 2017
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      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
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      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
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      The domain "Income and living conditions" covers four topics: people at risk of poverty or social exclusion, income distribution and monetary poverty, living conditions and material deprivation, which are again structured into collections of indicators on specific topics. The collection "People at risk of poverty or social exclusion" houses main indicator on risk of poverty or social inclusion included in the Europe 2020 strategy as well as the intersections between sub-populations of all Europe 2020 indicators on poverty and social exclusion. The collection "Income distribution and monetary poverty" houses collections of indicators relating to poverty risk, poverty risk of working individuals as well as the distribution of income. The collection "Living conditions" hosts indicators relating to characteristics and living conditions of households, characteristics of the population according to different breakdowns, health and labour conditions, housing conditions as well as childcare related indicators. The collection "Material deprivation" covers indicators relating to economic strain, durables, housing deprivation and environment of the dwelling.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
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      The domain "Income and living conditions" covers four topics: people at risk of poverty or social exclusion, income distribution and monetary poverty, living conditions and material deprivation, which are again structured into collections of indicators on specific topics. The collection "People at risk of poverty or social exclusion" houses main indicator on risk of poverty or social inclusion included in the Europe 2020 strategy as well as the intersections between sub-populations of all Europe 2020 indicators on poverty and social exclusion. The collection "Income distribution and monetary poverty" houses collections of indicators relating to poverty risk, poverty risk of working individuals as well as the distribution of income. The collection "Living conditions" hosts indicators relating to characteristics and living conditions of households, characteristics of the population according to different breakdowns, health and labour conditions, housing conditions as well as childcare related indicators. The collection "Material deprivation" covers indicators relating to economic strain, durables, housing deprivation and environment of the dwelling.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
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      Data in this domain constitute only a small part of the entire National Accounts data range available from Eurostat. Annual and quarterly national accounts are compiled in accordance with the European System of Accounts - ESA 2010as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013. The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. The annual data of this domain consists of the following collections: 1. Main GDP aggregates: main components from the output, expenditure and income side. nama_10_gdp: GDP and main components (output, expenditure and income   The quarterly data of this domain consists of the following collections 1. Main GDP aggregates, main components from the output, expenditure and income side, expenditure breakdowns by industry and assets. namq_10_ma: Main GDP aggregatesnamq_10_gdp: GDP and main components (output, expenditure and incomenamq_10_fcs: Final consumption aggregates by durabilitynamq_10_exi: Exports and imports by Member States of the EU/third countries 2. Breakdowns of GDP aggregates and employment data by main industries and asset classes. namq_10_bbr: Basic breakdowns main GDP aggregates and employment (by industry and assets)namq_10_a10: Gross value added and income by A*10 industrynamq_10_an6: Gross fixed capital formation by AN_F6 asset typenamq_10_a10_e: Employment by A*10 industry breakdowns Geographical entities covered are the European Union, the euro area, EU Member States, Candidate Countries, EFTA countries, US, Japan and possibly other countries on an ad-hoc basis. Data sources: National Statistical Institutes
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 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
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 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
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
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      Data in this domain constitute only a small part of the entire National Accounts data range available from Eurostat. Annual and quarterly national accounts are compiled in accordance with the European System of Accounts - ESA 2010as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013. The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. The annual data of this domain consists of the following collections: 1. Main GDP aggregates: main components from the output, expenditure and income side.nama_10_gdp: GDP and main components (output, expenditure and income   The quarterly data of this domain consists of the following collections 1. Main GDP aggregates, main components from the output, expenditure and income side, expenditure breakdowns by industry and assets. namq_10_ma: Main GDP aggregatesnamq_10_gdp: GDP and main components (output, expenditure and incomenamq_10_fcs: Final consumption aggregates by durabilitynamq_10_exi: Exports and imports by Member States of the EU/third countries 2. Breakdowns of GDP aggregates and employment data by main industries and asset classes. namq_10_bbr: Basic breakdowns main GDP aggregates and employment (by industry and assets)namq_10_a10: Gross value added and income by A*10 industrynamq_10_an6: Gross fixed capital formation by AN_F6 asset typenamq_10_a10_e: Employment by A*10 industry breakdowns Geographical entities covered are the European Union, the euro area, EU Member States, Candidate Countries, EFTA countries, US, Japan and possibly other countries on an ad-hoc basis. Data sources: National Statistical Institutes
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
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      Data in this domain constitute only a small part of the entire National Accounts data range available from Eurostat. Annual and quarterly national accounts are compiled in accordance with the European System of Accounts - ESA 2010as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013. The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. The annual data of this domain consists of the following collections: 1. Main GDP aggregates: main components from the output, expenditure and income side.nama_10_gdp: GDP and main components (output, expenditure and income   The quarterly data of this domain consists of the following collections 1. Main GDP aggregates, main components from the output, expenditure and income side, expenditure breakdowns by industry and assets. namq_10_ma: Main GDP aggregatesnamq_10_gdp: GDP and main components (output, expenditure and incomenamq_10_fcs: Final consumption aggregates by durabilitynamq_10_exi: Exports and imports by Member States of the EU/third countries 2. Breakdowns of GDP aggregates and employment data by main industries and asset classes. namq_10_bbr: Basic breakdowns main GDP aggregates and employment (by industry and assets)namq_10_a10: Gross value added and income by A*10 industrynamq_10_an6: Gross fixed capital formation by AN_F6 asset typenamq_10_a10_e: Employment by A*10 industry breakdowns Geographical entities covered are the European Union, the euro area, EU Member States, Candidate Countries, EFTA countries, US, Japan and possibly other countries on an ad-hoc basis. Data sources: National Statistical Institutes
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 16 August, 2017
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      The Economic Accounts for Agriculture (EAA) provide detailed information on income in the agricultural sector. The purpose is to analyse the production process of the agricultural industry and the primary income generated by this production. The accounts are therefore based on the industry concept. The EAA accounts are detailed data on value of output (producer prices and basic prices), intermediate consumption, subsidies and taxes, consumption of fixed capital, rent and interests, capital formation etc. The values are in current as well as in constant prices. Agricultural Labour Input (ALI) and Unit Values (UV) are an integrated part of the overall concept of Economic Accounts for Agriculture. The Economic accounts for agriculture (EAA) are a satellite account of the European System of Accounts (ESA2010), providing complementary information and concepts adapted to the particular nature of the agricultural industry. Although their structure very closely matches that of the national accounts, their compilation requires the formulation of appropriate rules and methods. National Statistical Institutes or Ministries of Agriculture are responsible for data collection and calculation of national EAA, in accordance with EC Regulations. Eurostat is responsible for the EU aggregations. Regional data EAA accounts are compiled at regional level (NUTS2), but only in values in current prices. The labour input data and Unit values are not broken down to regional level. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data. Frequency of data collection for data under Regulation (EC) 138/2004 and gentlemen's agreement, deadline for transmission for years 2015-2016.
    • March 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 15 March, 2016
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    • March 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 March, 2016
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      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
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      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 September, 2017
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      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 September, 2017
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      The farm manager is the natural person responsible for the normal daily financial and production routines of running the holding.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 21 September, 2017
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    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 September, 2017
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    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 21 September, 2017
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      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
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      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
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      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
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      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
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      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
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      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 September, 2017
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    • March 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 15 March, 2017
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      The Economic Accounts for Agriculture (EAA) provide detailed information on income in the agricultural sector. The purpose is to analyse the production process of the agricultural industry and the primary income generated by this production. The accounts are therefore based on the industry concept. The EAA accounts are detailed data on value of output (producer prices and basic prices), intermediate consumption, subsidies and taxes, consumption of fixed capital, rent and interests, capital formation etc. The values are in current as well as in constant prices. Agricultural Labour Input (ALI) and Unit Values (UV) are an integrated part of the overall concept of Economic Accounts for Agriculture. The Economic accounts for agriculture (EAA) are a satellite account of the European System of Accounts (ESA2010), providing complementary information and concepts adapted to the particular nature of the agricultural industry. Although their structure very closely matches that of the national accounts, their compilation requires the formulation of appropriate rules and methods. National Statistical Institutes or Ministries of Agriculture are responsible for data collection and calculation of national EAA, in accordance with EC Regulations. Eurostat is responsible for the EU aggregations. Regional data EAA accounts are compiled at regional level (NUTS2), but only in values in current prices. The labour input data and Unit values are not broken down to regional level. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data. Frequency of data collection for data under Regulation (EC) 138/2004 and gentlemen's agreement, deadline for transmission for years 2015-2016.   Reg. CE 138/2004 Gentlemen's agreement Web Form in eDamis Excel SDTT file in CIRCA Transmission date via eDamis Edamis DATASET to use   EAA Second Estimates 2015   X - - X 31 January 2016 COSAEA_AGR2_A EAA Constant N-1 prices Final - 2014   X - - X 30 September 2015   COSAEA_AGR3CON_A EAA at current prices Final - 2014   X - - X COSAEA_AGR3CUR_A   UV (unit Values) 2014   - X X - COSAEA_UV_A   EAA Regional data 2013   - X - X COSAEA_REGION_A   ALI (Labour Input) final 2014   X - X - COSAEA_ALI3_A   ALI (Labour Input)1st estimates 2015   X - X - 30 November 2015 COSAEA_ALI3_A   ALI (Labour Input) 2nd estimates 2015   X - X - 31 January 2016 COSAEA_ALI3_A   EAA First Estimates 2015   X - - X 30 November 2015 COSAEA_AGR1_A
    • June 2016
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 10 February, 2017
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      Agriculture Total contains all the emissions produced in the different agricultural emissions sub-domains (enteric fermentation, manure management, rice cultivation, synthetic fertilizers, manure applied to soils, manure left on pastures, crop residues, cultivation of organic soils, burning of crop residues, burning of savanna, energy use), providing a picture of the contribution to the total amount of GHG emissions from agriculture. GHG emissions from agriculture consist of non-CO2 gases, namely methane (CH4) and nitrous oxide (N2O), produced by crop and livestock production and management activities. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/index.html). GHG emissions are provided by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed as Gg CO2 and CO2eq (from CH4 and N2O), by underlying agricultural emission sub-domain and by aggregate (agriculture total, agriculture total plus energy, agricultural soils).
    • May 2013
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 29 July, 2015
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    • July 2017
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 17 August, 2017
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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 2014
    • July 2017
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 17 August, 2017
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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.
    • July 2017
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
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      Agri-Environmental Indicators - Livestock (1961-2014)
    • July 2017
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 16 August, 2017
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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: 29 July, 2015
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    • May 2013
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 29 July, 2015
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    • December 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 August, 2017
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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.
    • December 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 August, 2017
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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.
    • June 2015
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 August, 2015
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    • June 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 28 June, 2017
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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.
    • June 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 June, 2017
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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.
    • November 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 August, 2017
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      Air Emission Accounts are available for European countries and a few non-European countries.The System of Environmental-Economic Accounting (SEEA) Central Framework is an accounting system developed around two objectives: "understanding the interactions between the economy and the environment" and describing "stocks and changes in stocks of environmental assets". The SEEA combines national accounts and environmental statistics in a statistical framework with consistent definitions, classifications and concepts allowing policy makers to evaluate environmental pressures from economic activities at macro- and meso-levels.Data refer to total emissions of CO2 (CO2 emissions from energy use and industrial processes, e.g. cement production), CH4 (methane emissions from solid waste, livestock, mining of hard coal and lignite, rice paddies, agriculture and leaks from natural gas pipelines), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs) and sulphur hexafluoride (SF6) for GHG and for other pollutants emissions data refer to emisions of sulphur oxides (SOx), nitrogen oxides (NOx), carbon monoxide (CO), non-methane volatile organic compounds (VOC) and particulates (PM2.5).
    • May 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 May, 2017
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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 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 May, 2017
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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 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 May, 2017
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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
    • July 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 30 July, 2017
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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 6 air pollutants: sulphur oxides (SOx), ammonia (NH3), nitrogen oxides (NOx), non-methane volatile organic compounds (NMVOCs), particulate matters (PM10, PM2.5), 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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
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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 differnce in the methodologies applied, the data for air and maritime transport at regional level up to 2002 refernce 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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • March 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 11 December, 2015
      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 differnce in the methodologies applied, the data for air and maritime transport at regional level up to 2002 refernce 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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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 differnce in the methodologies applied, the data for air and maritime transport at regional level up to 2002 refernce 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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 September, 2017
      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 the Member States of the European Union as well as the Candidate Countries, Iceland, Norway and Switzerland. 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.
    • April 2017
      Source: Akamai
      Uploaded by: Knoema
      Accessed On: 07 June, 2017
      Select Dataset
    • October 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 October, 2016
      Select Dataset
      The “ALFS Summary tables” dataset is a subset of the Annual Labour Force Statistics database which presents annual labour force statistics and broad population series for 34 OECD member countries plus Brazil, Columbia and Russian Federation and 4 geographical areas (Major Seven, Euro area, European Union and OECD-Total). Data are presented in thousands of persons, in percentage or as indices with base year 2010=100.This dataset contains estimates from the OECD Secretariat for the latest years when countries did not provide data. These estimates are necessary to compile aggregated statistics for the geographical areas for a complete span of time. Since 2003, employment data by sector for the United States are compiled following the North American Industrial Classification System (NAICS); therefore they are not strictly comparable with other countries’ data.Euro area and European Union data were extracted from Eurostat (LFS Series, Detailed annual survey results in New Cronos). Euro area refer to Euro area with 17 countries (geo = ea17). European Union refers to European Union with 27 countries (geo = eu27).
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      Data on causes of death (COD) provide information on mortality patterns and form a major element of public health information. COD 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". Causes of death are classified by the 86 causes of the "European shortlist" of causes of death. This shortlist is based on the International Statistical Classification of Diseases and Related Health Problems (ICD). COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. Countries code the information provided in the medical certificate of cause of death into ICD codes according to the rules specified in the ICD. Data are broken down by sex, 5-year age groups, cause of death and by residency and country of occurrence. For stillbirths and neonatal deaths additional breakdows might include age of mother. Data are available for EU-28, the former Yugoslav Republic of Macedonia, Albania, Iceland, Norway, Liechtenstein and Switzerland. Regional data (NUTS level 2) are available for most of the countries. Annual national data are provided in absolute number, crude death rates and standardised death rates. At regional level (NUTS level 2) the same is provided in form of 3 years averages. Annual crude death rates are also available at NUTS level 2.
    • June 2013
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 21 November, 2014
      Select Dataset
      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).
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 03 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      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.
    • April 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 28 June, 2017
      Select Dataset
      OECD Taxing Wages. Taxing Wages provides unique information on income tax paid by workers and social security contributions levied on employees and their employers in OECD countries. In addition, this annual publication specifies family benefits paid as cash transfers. Amounts of taxes and benefits are detailed program by program, for eight household types which differ by income level and household composition. Results reported include the marginal and effective tax burden for one- and two-earner families, and total labour costs of employers.
    • March 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 15 April, 2014
      Select Dataset
      Eurostat Dataset Id:nama_r_ehh2p Household accounts include data for individuals or groups of individuals as consumers and possibly as producers of goods for own use as well as non-profit institutions serving households. Data on household accounts include 11 indicators. The most important are primary income and disposable income. Geographic coverage comprises all EU Member States and some Candidate countries down to the Nuts 2 level breakdown (Nuts = "Nomenclature of territorial units for statistics" - see Eurostat's classification server "RAMON").
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 08 August, 2017
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    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      Select Dataset
      This indicator tracks trends in anthropogenic atmospheric emissions of ammonia by agriculture.
    • July 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 August, 2017
      Select Dataset
      Residential Property Prices Indices (RPPIs) – also named House price indices (HPIs), are index numbers that measure the prices of residential properties over time. RPPIs are key statistics not only for citizens and households across the world, but also for economic and monetary policy makers. They can help, for example, to monitor potential macroeconomic imbalances and the risk exposure of the household and financial sectors. This dataset covers the 34 OECD member countries and some non-member countries. In addition to the nominal RPPIs it contains information on real house prices, rental prices and the ratios of nominal prices to rents and to disposable household income per capita. This dataset contains quarterly statistics for each country. House prices differ widely across OECD countries, both with respect to recent changes and to valuation levels. The OECD has identified one main nominal index for each country that covers the prices for the sale of newly-built and existing dwellings. The datasets “Analytical house price indicators” and “Residential Property Price Indices (RPPIs) – Headline Indicators” refer to the same price indices for all countries apart from Brazil, Canada, China, the United States and the Euro area. These differences are further documented in country-specific metadata. For the United States, the series used in “Analytical house price indicators” is included in the dataset called “Residential Property Price Indices (RPPIs) – Complete database”, but is not the headline indicator. For all other countries, non-seasonally adjusted price indices in both datasets are identical in the period in which they overlap. This research dataset provides extended time series coverage for many countries. The objective is to provide information on the long term trend of house prices and develop indicators which can be used to help track and analyse macroeconomic developments and risks. The extended data supplement the OECD RPPI data with historical data from a variety of sources, including other international organisations, central banks and national statistical offices. The methodological basis on the historical data and the types of geographical areas and dwellings they cover can differ from those used in the OECD RPPI data. The database contains a number of additional series. Real house prices are given by the ratio of seasonally adjusted nominal house prices to the seasonally adjusted consumers’ expenditure deflator in each country, from the OECD national accounts database. This provides information on how nominal house prices have changed over time relative to prices in the general economy. The rental prices come from the OECD Main Economic Indicators database and refer to Consumer Price Indices (CPIs) for Actual rentals for housing (COICOP 04.1). If this indicator is missing for a country, another indicator is chosen. The chosen indicator are usually those corresponding to the CPI aggregate for Housing including Actual rentals for housing (COICOP 04.1), imputed rentals for housing (COICOP 04.2) and Maintenance and repair of the dwelling (COICOP 04.3). The disposable income indicators come from the OECD national accounts database. Net household disposable income is used. The population data come from the OECD national accounts database. The price-to-rent ratio is given by the ratio of nominal house prices to rental prices. This is a measure of the profitability of owning a house. The price-to-income ratio is given by the ratio of nominal house prices to nominal household disposable income per capita. This is a measure of the affordability of purchasing a house. An indication that house prices may be overvalued is provided if either of these ratios is above their long-term averages. The standardised price-rent and price-income ratios show the current price-rent and price-income ratios relative to their respective long-term averages. The long-term average, which is used as a reference value, is calculated over the whole period available when the indicator begins after 1980 or 1980 if the indicator is available over a longer time period. The standardised ratio is indexed to a reference value equal to 100 over the full sample period. Values over 100 indicate that the present price-rent ratio, or price-income ratio, is above its long-run norms. This provides an indication of possible housing market pressures.
    • October 2013
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 November, 2015
      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.
    • September 2013
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 October, 2015
      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: 12 April, 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: 12 April, 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.
    • October 2013
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 March, 2014
      Select Dataset
      Eurostat Dataset Id:ef_pmhouspigec 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 onwardsStandard Gross Margin (SGM) and Standard Output (SO) coefficients.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:one general overview with the key variables,and other specialized groups containing detailed data onland uselivestockspecial interest topics: farm labour force, rural development issues as well as management and practices.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 31/2001 amending the NUTS classification from January 2012.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.Regional DataData 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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 September, 2017
      Select Dataset
      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 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      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 <
    • March 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 April, 2014
      Select Dataset
      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
    • July 2012
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 11 November, 2013
      Select Dataset
      Eurostat Dataset Id:road_go_cta7gtt 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 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      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 patentsare defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition). Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.
    • 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.
    • 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.
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 August, 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 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.
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 August, 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 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: 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).  
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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).
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 September, 2017
      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_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
    • June 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 21 August, 2017
      Select Dataset
      The dataset includes a detailed breakdown of Investment funds, Insurance companies and Pension funds, and Other forms of institutional savings, as institutional sectors. This finer breakdown by type of investors has been established with reference to the System of National Accounts (SNA), when possible. Within Investment funds, one distinguishes Open-end companies, further broken down into Money market funds and Other mutual funds, and Closed-end companies, of which Real estate funds. Within Insurance companies and pension funds one distinguishes Insurance companies, further broken down into Life insurance companies and Non-life insurance companies, and Autonomous pension funds. Financial assets included correspond to the assets requested in the previous database on Institutional Investors, i.e. Currency and deposits, Securities other than shares, Loans, Shares and other equities and Other financial assets. Moreover, Total non-financial assets are also included. While the sub-classification of the above financial assets corresponds to SNA93, a further breakdown between assets issued by residents and assets issued by non-residents is reported.
    • April 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 19 July, 2017
      Select Dataset
      The "ALFS Summary tables" dataset is a subset of the Annual Labor Force Statistics database which presents annual labor force statistics and broad population series for 34 OECD member countries plus Brazil and 4 geographical areas (Major Seven, Euro zone, European Union and OECD-Total). Note that Chile became a member of the OECD on 7 May 2010, Slovenia on 21 July 2010, Israel on 7 September 2010 and Estonia on 9 December 2010. Chile, Estonia, Israel and Slovenia have been included in this dataset. Data are presented in thousands of persons, in percentage or as indices with base year 2010=100.
    • May 2017
      Source: European Commission
      Uploaded by: Knoema
      Accessed On: 08 June, 2017
      Select Dataset
      AMECO is the annual macro-economic database of the European Commission's Directorate General for Economic and Financial Affairs (DG ECFIN). The database is regularly cited in DG ECFIN's publications and is indispensable for DG ECFIN's analyses and reports. To ensure that DG ECFIN's analyses are verifiable and transparent to the public, AMECO data is made available free of charge. AMECO contains data for EU-27, the euro area, EU Member States, candidate countries and other OECD countries (United States, Japan, Canada, Switzerland, Norway, Iceland, Mexico, Korea, Australia and New Zealand).
    • June 2017
      Source: International Tropical Timber Organization
      Uploaded by: Knoema
      Accessed On: 24 July, 2017
      Select Dataset
      ITTO's Annual Review and Assessment of the World Timber Situation compiles the most up-to-date and reliable international statistics available on global production and trade of timber, with an emphasis on the tropics. It also provides information on trends in forest area, forest management and the economies of ITTO member countries.
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 06 September, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 06 September, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 August, 2017
      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).
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 August, 2017
      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).
    • July 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 August, 2017
      Select Dataset
      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 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 June, 2017
      Select Dataset
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 14 September, 2017
      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 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 24 November, 2015
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    • July 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 24 November, 2015
      Select Dataset
    • July 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 24 November, 2015
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    • July 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 November, 2015
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    • July 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 November, 2015
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    • July 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 November, 2015
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    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 24 September, 2017
      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 2014
      Source: World Resources Institute
      Uploaded by: Knoema
      Accessed On: 07 December, 2015
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      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.
    • May 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 21 May, 2017
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    • June 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 June, 2017
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      Eurostat Dataset Id:mare_d3area
    • June 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 June, 2017
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      Eurostat Dataset Id:urt_d3area
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
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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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 September, 2017
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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 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 April, 2014
      Select Dataset
      Eurostat Dataset Id:vit_bs4_el 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: 31 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.
    • October 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 April, 2014
      Select Dataset
      Eurostat Dataset Id:vit_an6 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 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 April, 2014
      Select Dataset
      Eurostat Dataset Id:agr_r_crops
    • April 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 08 June, 2015
      Select Dataset
      Eurostat Id: agr_r_crops   Crop statistics refer to the following types of annual data: area, production harvested and yield for cereals and for other main field crops (mainly dried pulses, root crops, fodder and industrial crops); area, production harvested and yield for a large number of fruits and vegetables humidity of the harvested crop (humidity content in %) agricultural land use. The statistics provide, for a given product, the area, the yield and the production harvested during the crop year at national level. For some products regional figures (NUTS 1 or 2) are available too. The data refer to areas under cultivation (expressed in 1 000 hectares), the quantity harvested (expressed in 1 000 tonnes) and the yield (expressed in 100kg/ha). The information concerns more than 100 crop products. The earliest data are available from 1955 for cereals and from the early 1960's for fruits and vegetables. However most Member States have started to send in data in the 1970's and 1980's. The statistical system has progressively improved and enlarged. The current Regulation (EC) No 543/2009 entered into force in January 2010. It simplified the data collection and reduced the number of crop sub-classes. At present Eurostat receives and publishes harmonised statistical data from 28 Member States broken down in: 17 categories and subcategories for cereals; 30 categories and subcategories for other main crops (mainly Dried pulses, Root crops and Industrial crops); 40 categories and subcategories for vegetables; 41 categories and subcategories for fruits; 18 categories and subcategories for UAA (Utilised Agricultural Area). For the full list of crops, please consult Annex 1 . Some data are available also for Iceland, Norway, Switzerland, Albania, Montenegro. Former Yugoslav Republic of Macedonia, Serbia, Kosovo (under United Nations Security Council Resolution 1244/99), Bosnia Herzegovina and Turkey as well. Some additional crops are covered bya Gentlemen's agreement. These data is provided on voluntary basis by the Member States. The list of crops collected under the gentlemen's agreements is included in Annex 1. The main data sources are administrative records, surveys and expert estimates. National Statistical Institutes or Ministries of Agriculture are responsible for the national data collection in accordance with EC Regulations. Eurostat is responsible for drawing the EU aggregations. Regional metadata Please note that for paragraphs where no metadata for regional data has been specified the regional metadata is identical to the metadata for the national data.  
    • June 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 December, 2015
      Select Dataset
      Eurostat Dataset Id:ilc_mdes05h 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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      Accommodation statistics is a key part of the system of tourism statistics in the EU and has a long history of data collection. Annex I of the Regulation (EU) 692/2011 of the European Parliament and of the Council deals with accommodation statistics and includes 4 sections focusing on accommodation statistics of which sections 1 and 2 include the requirements concerning rented accommodation (capacity and occupancy respectively). Data are collected by the competent national authorities of the Member States and are compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Most of the time, data are collected via sample or census surveys. However, in a few cases the data is compiled from a demand-side perspective (i.e. via visitor surveys or border surveys). Surveys on the occupancy of accommodation establishments are generally conducted on a monthly basis. The concepts and definitions used in the collection of data shall conform to the specifications described in the Methodological manual for tourism statistics. Accommodation statistics comprise the following information: Monthly data on tourism industries (NACE 55.1, 55.2 and 55.3) Monthly occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Net occupancy rate of bed-places and bedrooms in hotels and similar accommodation Annual data on tourism industries(NACE 55.1, 55.2 and 55.3) Occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Capacity of tourist accommodation establishments: number of establishments, bedrooms and bed places Regional data  Annual occupancy (arrivals and nights spent by residents and non-residents) of tourist accommodation establishments at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Annual data on number of establishments, bedrooms and bed places at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Data on number of establishments, bedrooms and bed places are available by activity at NUTS 3 level until 2011. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 06 September, 2017
      Select Dataset
      Accommodation statistics is a key part of the system of tourism statistics in the EU and has a long history of data collection. Annex I of the Regulation (EU) 692/2011 of the European Parliament and of the Council deals with accommodation statistics and includes 4 sections focusing on accommodation statistics of which sections 1 and 2 include the requirements concerning rented accommodation (capacity and occupancy respectively). Data are collected by the competent national authorities of the Member States and are compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Most of the time, data are collected via sample or census surveys. However, in a few cases the data is compiled from a demand-side perspective (i.e. via visitor surveys or border surveys). Surveys on the occupancy of accommodation establishments are generally conducted on a monthly basis. The concepts and definitions used in the collection of data shall conform to the specifications described in the Methodological manual for tourism statistics. Accommodation statistics comprise the following information: Monthly data on tourism industries (NACE 55.1, 55.2 and 55.3) Monthly occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Net occupancy rate of bed-places and bedrooms in hotels and similar accommodation Annual data on tourism industries(NACE 55.1, 55.2 and 55.3) Occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Capacity of tourist accommodation establishments: number of establishments, bedrooms and bed places Regional data  Annual occupancy (arrivals and nights spent by residents and non-residents) of tourist accommodation establishments at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Annual data on number of establishments, bedrooms and bed places at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Data on number of establishments, bedrooms and bed places are available by activity at NUTS 3 level until 2011. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.
    • October 2013
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 June, 2014
      Select Dataset
      Eurostat Dataset Id:tour_occ_arnrmw National data Monthly and annual data on arrivals, nights spent and occupancy rates at tourist accommodation establishments. Regional data Annual arrivals, nights spent at tourist accommodation establishments at NUTS 2 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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 20 September, 2017
      Select Dataset
      An arrival is defined as a person (tourist) who arrives at a tourist accommodation establishment and checks in. The arrivals of same-day visitors spending only a few hours during the day (no overnight stay, the date of arrival and departure are the same) at the establishment are excluded.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      20.1. Source data
    • June 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 June, 2017
      Select Dataset
      The datasets are composed by baseline population projections and the following sensitivity tests: •           Lower fertility; •           Lower mortality; •           Higher migration; •           Lower migration; •           No migration. For each of them, data is available as follows: •           Projected population on 1 January by age and sex, and by single year time interval; •           Assumptions on future age-specific fertility rates, age-specific mortality rates and international net migration levels (including statistical adjustment); •           Corresponding approximated values of the life expectancy by age and sex. Moreover, for the baseline projections, the following demographic balances and indicators are available: •           Total numbers of the projected live births and deaths; •           Projected population structure indicators: proportions of broad age groups in total population, age dependency ratios and median age of the population. The time horizon covered is: •           From 2015 to 2081 for the projected population; and •           From 2015 to 2080 for the assumptions dataset.
    • June 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 June, 2017
      Select Dataset
      The datasets are composed by baseline population projections and the following sensitivity tests: •           Lower fertility; •           Lower mortality; •           Higher migration; •           Lower migration; •           No migration. For each of them, data is available as follows: •           Projected population on 1 January by age and sex, and by single year time interval; •           Assumptions on future age-specific fertility rates, age-specific mortality rates and international net migration levels (including statistical adjustment); •           Corresponding approximated values of the life expectancy by age and sex. Moreover, for the baseline projections, the following demographic balances and indicators are available: •           Total numbers of the projected live births and deaths; •           Projected population structure indicators: proportions of broad age groups in total population, age dependency ratios and median age of the population. The time horizon covered is: •           From 2015 to 2081 for the projected population; and •           From 2015 to 2080 for the assumptions dataset.
    • June 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 June, 2017
      Select Dataset
      The datasets are composed by baseline population projections and the following sensitivity tests: •           Lower fertility; •           Lower mortality; •           Higher migration; •           Lower migration; •           No migration. For each of them, data is available as follows: •           Projected population on 1 January by age and sex, and by single year time interval; •           Assumptions on future age-specific fertility rates, age-specific mortality rates and international net migration levels (including statistical adjustment); •           Corresponding approximated values of the life expectancy by age and sex. Moreover, for the baseline projections, the following demographic balances and indicators are available: •           Total numbers of the projected live births and deaths; •           Projected population structure indicators: proportions of broad age groups in total population, age dependency ratios and median age of the population. The time horizon covered is: •           From 2015 to 2081 for the projected population; and •           From 2015 to 2080 for the assumptions dataset.
    • June 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 June, 2017
      Select Dataset
      The datasets are composed by baseline population projections and the following sensitivity tests: •           Lower fertility; •           Lower mortality; •           Higher migration; •           Lower migration; •           No migration. For each of them, data is available as follows: •           Projected population on 1 January by age and sex, and by single year time interval; •           Assumptions on future age-specific fertility rates, age-specific mortality rates and international net migration levels (including statistical adjustment); •           Corresponding approximated values of the life expectancy by age and sex. Moreover, for the baseline projections, the following demographic balances and indicators are available: •           Total numbers of the projected live births and deaths; •           Projected population structure indicators: proportions of broad age groups in total population, age dependency ratios and median age of the population. The time horizon covered is: •           From 2015 to 2081 for the projected population; and •           From 2015 to 2080 for the assumptions dataset.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 20 September, 2017
      Select Dataset
      Data series on asylum applications contain statistical information based on Article 4 of the Council Regulation (EC) No 862/2007 with reference to:Asylum and first time asylum applicants by age, sex and citizenshipPersons subject to applications pending at the end of reference period by age, sex and citizenshipApplications for asylum withdrawn by age, sex and citizenshipAsylum applicants considered to be unaccompanied minors by age, sex and citizenship These data are supplied to Eurostat by the national Ministries of Interior and related official agencies. Data is presented by country and for groups of countries: the European Union (EU28, EU27) and the European Free Trade Association (EFTA). Data has been rounded to the nearest 5.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 September, 2017
      Select Dataset
      Data series on asylum applications contain statistical information based on Article 4 of the Council Regulation (EC) No 862/2007 with reference to: Asylum and first time asylum applicants by age, sex and citizenshipPersons subject to applications pending at the end of reference period by age, sex and citizenshipApplications for asylum withdrawn by age, sex and citizenshipAsylum applicants considered to be unaccompanied minors by age, sex and citizenship These data are supplied to Eurostat by the national Ministries of Interior and related official agencies. Data is presented by country and for groups of countries: the European Union (EU28, EU27) and the European Free Trade Association (EFTA). Data has been rounded to the nearest 5.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      Data series on asylum applications contain statistical information based on Article 4 of the Council Regulation (EC) No 862/2007 with reference to: Asylum and first time asylum applicants by age, sex and citizenshipPersons subject to applications pending at the end of reference period by age, sex and citizenshipApplications for asylum withdrawn by age, sex and citizenshipAsylum applicants considered to be unaccompanied minors by age, sex and citizenship These data are supplied to Eurostat by the national Ministries of Interior and related official agencies. Data is presented by country and for groups of countries: the European Union (EU28, EU27) and the European Free Trade Association (EFTA). Data has been rounded to the nearest 5.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      Data series on asylum applications contain statistical information based on Article 4 of the Council Regulation (EC) No 862/2007 with reference to: Asylum and first time asylum applicants by age, sex and citizenshipPersons subject to applications pending at the end of reference period by age, sex and citizenshipApplications for asylum withdrawn by age, sex and citizenshipAsylum applicants considered to be unaccompanied minors by age, sex and citizenship These data are supplied to Eurostat by the national Ministries of Interior and related official agencies. Data is presented by country and for groups of countries: the European Union (EU28, EU27) and the European Free Trade Association (EFTA). Data has been rounded to the nearest 5.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      The indicator is defined as the percentage of people aged 25 to 64 who have successfully completed at most lower secondary education. This educational attainment refers to ISCED (International Standard Classification of Education) 2011 level 0-2 for data from 2014 onwards and to ISCED 1997 level 0-3C short for data up to 2013.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      Select Dataset
      The sum of elderly (65+) who are: at-risk-of-poverty or severely materially deprived or living in (quasi-)jobless households (i.e. with very low work intensity) as a share of the total population in the same age group.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 20 September, 2017
      Select Dataset
      Share of persons aged (0-59) with an equivalised disposable income below 60% of the national equivalised median income who live in households where working-age adults (18-59) work less than 20% of their total work potential during the past year.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 20 September, 2017
      Select Dataset
      The indicator measures persons (aged 18 year or over) who are unemployed with an equivalised disposable income below the risk-of-poverty threshold as a % of total unemployment. The risk-of-poverty threshold is set at 60 % of the national median equivalised disposable income (after social transfers). The indicator is based on the EU SILC.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      Select Dataset
      The at-risk-of-poverty rate is the share of people with an equivalised disposable income (after social transfer) below the at-risk-of-poverty threshold, which is set at 60 % of the national median equivalised disposable income after social transfers. This indicator does not measure wealth or poverty, but low income in comparison to other residents in that country, which does not necessarily imply a low standard of living.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 21 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 June, 2014
      Select Dataset
      Eurostat Dataset Id:ilc_li20 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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 20 September, 2017
      Select Dataset
      The share of persons with an equivalised disposable income, before social transfers, below the risk-of-poverty threshold, which is set at 60 % of the national median equivalised disposable income (after social transfers). Retirement and survivor's pensions are counted as income before transfers and not as social transfers.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      Select Dataset
      The indicator is defined as the share of persons with an equivalised disposable income below the risk-of-poverty threshold, which is set at 60 % of the national median equivalised disposable income (after social transfers).
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 June, 2014
      Select Dataset
      Eurostat Dataset Id:ilc_li05 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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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 2012
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 June, 2014
      Select Dataset
      Eurostat Dataset Id:ilc_li06h 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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      Select Dataset
      The share of persons with an equivalised disposable income, before social transfers, below the risk-of-poverty threshold, which is set at 60 % of the national median equivalised disposable income (after social transfers). Retirement and survivor's pensions are counted as income before transfers and not as social transfers.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 20 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 20 September, 2017
      Select Dataset
      The at-risk-of-poverty threshold is set at 60 % of national median equivalised disposable income.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      Eurostat Dataset Id:ilc_li01 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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      Select Dataset
      People at risk of poverty after social transfers by highest level of education attained.  Persons are at risk of poverty if their equivalised disposable income is below the risk-of-poverty threshold, which is set at 60 % of the national median after social transfers.
    • October 2014
      Source: LMC Automotive
      Uploaded by: Knoema
      Accessed On: 09 January, 2015
      Select Dataset
      Automative Industry, 2014
    • July 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 24 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.
    • December 2014
      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).  
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      Non-expenditure health care data provide information on institutions providing health care in countries, on resources used and on output produced in the framework of health care provision. Data on health care form a major element of public health information as they describe the capacities available for different types of health care provision as well as potential 'bottlenecks' observed. The quantity and quality of health care services provided and the work sharing established between the different institutions are a subject of ongoing debate in all countries. Sustainability - continuously providing the necessary monetary and personal resources needed - and meeting the challenges of ageing societies are the primary perspectives used when analysing and using the data. The resource-related data refer to both human and technical resources, i.e. they relate to: - 'Health care staff': 'manpower' active in the health care sector (doctors, dentists, nurses, etc.); - 'Health care facilities': technical capacity dimensions (hospital beds, beds in nursing and residential care facilities, etc.). Annual national and regional data are provided in absolute numbers and in population-standardised rates (per 100 000 inhabitants). Wherever applicable, the definitions and classifications of the System of Health Accounts (SHA) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). For hospital discharges, the International Shortlist for Hospital Morbidity Tabulation (ISHMT) is used. Health care data on resources are largely based on administrative data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable.
    • March 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 June, 2014
      Select Dataset
      Eurostat Dataset Id:lfso_06finiagps Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'.
    • March 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 June, 2014
      Select Dataset
      Eurostat Dataset Id:lfso_06otbnagps Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'.
    • March 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 30 June, 2014
      Select Dataset
      Eurostat Dataset Id:lfso_06stafagps Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'. The aim of the ad hoc module was to know how the transition at the end of the career towards full retirement is expected to take place, takes place or took place: • plans for transitions/past transitions towards full retirement • plans for exit from work Another aim was to know which factors would be/were at play in determining the exit from work, and which factors could make/could have made persons postpone the exit from work: • working conditions factors (health and safety at the workplace, flexible working time arrangements …) • other factors linked to work (training/obsolescence of skills …) • financial factors (financial incentives to remain at work or to exit) • personal factors (health, family reasons …).  
    • March 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 June, 2014
      Select Dataset
      Eurostat Dataset Id:lfso_06reasagps Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'.
    • March 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 June, 2014
      Select Dataset
      Eurostat Dataset Id:earn_gr_nace2 This data collection has been discontinued in 2012. Data is only available up to reference year 2011. Annual data on average gross earnings and related employment are included in the Gross earnings - Annual data collection. Data are available for EU Member States, Norway, Iceland and Switzerland. Data are also broken down by: From reference year 2008 onwards average gross annual earnings per employee are providedby economic activity (NACE Rev.2 aggregates and sections B, C, D, E, F, G, H, I, J, K, L, M, N, O, P, Q, R, S, B_TO_E, B_TO_F, B_TO_N, B_TO_S_NOT_O, B_TO_S, G_TO_J, G_TO_N, G_TO_S_NOT_O, K_TO_N, P_TO_S and O_TO_S)for enterprises with 1+ and for enterprises with 10+ employees for the following breakdowns:FTU= full-time units, FT=full-time workers, PT=part-time workers by Total, Men and Women. Before 2008: data is broken down by economic activity (NACE Rev. 1.1 for Sections C to K and the C-E, C-F, G-I, J-K, G-K, C-K and for some Member States L, M-O, L-O and also C-O aggregates)FTU= full-time units, FT=full-time workers, PT=part-time workersgenderoccupation (ISCO-88 classification, one-digit level and the 1-5 and 7-9 aggregates)The data relate to the staff of enterprises having at least 10 employees in most countries. Countries provide these annual data using several statistical sources mainly the four-yearly SES, the EU Labour Force Survey and/or administrative data.
    • November 2013
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 June, 2014
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      Eurostat Dataset Id:earn_gr_isco This data collection has been discontinued in 2012. Data is only available up to reference year 2011. Annual data on average gross earnings and related employment are included in the Gross earnings - Annual data collection. Data are available for EU Member States, Norway, Iceland and Switzerland. Data are also broken down by: From reference year 2008 onwards average gross annual earnings per employee are providedby economic activity (NACE Rev.2 aggregates and sections B, C, D, E, F, G, H, I, J, K, L, M, N, O, P, Q, R, S, B_TO_E, B_TO_F, B_TO_N, B_TO_S_NOT_O, B_TO_S, G_TO_J, G_TO_N, G_TO_S_NOT_O, K_TO_N, P_TO_S and O_TO_S)for enterprises with 1+ and for enterprises with 10+ employees for the following breakdowns:FTU= full-time units, FT=full-time workers, PT=part-time workers by Total, Men and Women. Before 2008: data is broken down by economic activity (NACE Rev. 1.1 for Sections C to K and the C-E, C-F, G-I, J-K, G-K, C-K and for some Member States L, M-O, L-O and also C-O aggregates)FTU= full-time units, FT=full-time workers, PT=part-time workersgenderoccupation (ISCO-88 classification, one-digit level and the 1-5 and 7-9 aggregates)The data relate to the staff of enterprises having at least 10 employees in most countries. Countries provide these annual data using several statistical sources mainly the four-yearly SES, the EU Labour Force Survey and/or administrative data.
    • December 2015
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 November, 2016
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      The concept used is the total number of hours worked over the year divided by the average number of people in employment. The data are intended for comparisons of trends over time; they are unsuitable for comparisons of the level of average annual hours of work for a given year, because of differences in their sources. Part-time workers are covered as well as full-time workers.The series on annual hours actually worked per person in total employment presented in this table for all 34 OECD countries are consistent with the series retained for the calculation of productivity measures in the OECD Productivity database (www.oecd.org/statistics/productivity/compendium). However, there may be some differences for some countries given that the main purpose of the latter database is to report data series on labour input (i.e. total hours worked) and also because the updating of databases occur at different moments of the year.Hours Hours actually worked per person in employment are according to National Accounts concepts for 18 countries: Austria, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Italy, Korea, the Netherlands, Norway, the Slovak Republic, Spain, Sweden, Switzerland and Turkey. OECD estimates for Belgium, Ireland, Luxembourg and Portugal for annual hours worked are based on the European Labour Force Survey, as are estimates for dependent employment only for Austria, Estonia, Greece, the Slovak Republic and Slovenia. The table includes labour-force-survey-based estimates for the Russian Federation.countries: For further details and country specfic notes see: www.oecd.org/employment/outlook and www.oecd.org/employment/emp/ANNUAL-HOURS-WORKED.pdf
    • March 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 30 March, 2017
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    • March 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 14 April, 2014
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      Eurostat Dataset Id:nama_r_e3popgdp National accounts are a coherent and consistent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. Eurostat publishes annual and quarterly national accounts, annual and quarterly sector accounts as well as supply, use and input-output tables, which are each presented with associated metadata. Annual national accounts are compiled in accordance with the European System of Accounts - ESA 1995 (Council Regulation 2223/96). Annex B of the Regulation consists of a comprehensive list of the variables to be transmitted for Community purposes within specified time limits. This transmission programme has been updated by Regulation (EC) N° 1392/2007 of the European Parliament and of the Council. Meanwhile, the ESA95 has been reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. Further information on the transition from ESA 95 to ESA 2010 is presented on the Eurostat website. The domain consists of the following collections: GDP and main aggregates. The data are recorded at current and constant prices and include the corresponding implicit price indices. Final consumption aggregates, including the split into household and government consumption. The data are recorded at current and constant prices and include the corresponding implicit price indices. Income, saving and net lending / net borrowing at current prices. Disposable income is also shown in real terms. Exports and imports by Member States of the EU/third countries. The data are recorded at current and constant prices and include the corresponding implicit price indices. Breakdowns of gross value added, compensation of employees, wages and salaries, operating surplus, employment (domestic scope), gross fixed capital formation (GFCF) and fixed assets and other main aggregates by industry; investment by products and household final consumption expenditure by consumption purposes (COICOP). The data are recorded at current and constant prices and include the corresponding implicit price indices. Auxiliary indicators: Population and employment national data, purchasing power parities, contributions to GDP growth, labour productivity, unit labour cost and GDP per capita. Geographical entities covered are the European Union, the euro area, EU Member States, Candidate Countries, EFTA countries, US, Japan and possibly other countries on an ad-hoc basis. The data are published: - in ECU/euro, in national currencies (including euro converted from former national currencies using the irrevocably fixed rate for all years) and in Purchasing Power Standards (PPS); - at current prices and in volume terms; - Population and employment are measured in persons. Employment is also measured in total hours worked. Data sources: National Statistical Institutes
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 August, 2017
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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
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 August, 2017
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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 2015
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 October, 2016
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      This dataset contains data on average annual wages per full-time and full-year equivalent employee in the total economy. Average annual wages per full-time equivalent dependent employee are obtained by dividing the national-accounts-based total wage bill by the average number of employees in the total economy, which is then multiplied by the ratio of average usual weekly hours per full-time employee to average usually weekly hours for all employees. The data, from 1990 to 2012 are available in : 2012 USD exchange rates and 2012 constant prices Aggregation and consolidation Average wages are converted in USD PPPs using 2012 USD PPPs for private consumption and are deflated by a price deflator for private final consumption expenditures in 2012 prices. in 2012 constant prices and NCU in 2012 USD PPPs and 2012 constant prices in 2012 USD exchange rates and 2012
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      20.1. Source data
    • January 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 22 March, 2017
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      Average Electricity, Gas and Spark Spread prices for industrial consumers - bi-annual data (from 2007 onwards) - Data upto 2016 H2   Note: The Average value for Electricity, Gas and Spark Spread Prices are calculated from below datasets. "Spark Spread" = Avg.Electricity (-) Avg.Gas Electricity: https://knoema.com/nrg_pc_205-20160316/ Gas: https://knoema.com/nrg_pc_203/
    • June 2012
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 December, 2015
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      Eurostat Dataset Id:lfsi_exi_a The indicator 'average exit age from the labour force' gives the average age of withdrawal from labour market. While based on European Union Labour Force Survey (EU-LFS) data, the indicator is calculated with special methods and periodidicty which justify the present page. The indicator is estimated with a probabilistic model, documented below, fed with data from the European Union Labour Force Survey (EU-LFS). The input data are activity rates by single age group. The indicator of 'Average exit age from the labour market' is published in the section 'LFS main indicators', which is a collection of the main statistics on the labour market. 'Population in jobless households' is also a Structural Indicator and a Sustainable Development Indicator. There are mainly two reasons to estimate the indicator with this probabilistic model instead of using a method based on self-reported retirement age, or based on people receiving pensions benefits: 1. EU-LFS data used follows definitions of employment and unemployment after the International Labour Organisation, as opposed to the notion of "being retired". There is no internationally harmonized statistical definition of retirement. 2. The method used allows to (indirectly) count definitive exits from the labour market. Instead, a retired person could potentially decide to return to the labour market, hence his/her exit would not be definitive.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 21 September, 2017
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      The total consumption expenditure made by a visitor or on behalf of a visitor for and during his/her trip and stay at destination.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 24 September, 2017
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      This collection covers national tourism.  Data is collected by the competent national authorities of the Member States and is compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Most of the time, data on domestic and outbound trips (where "outbound tourism" means residents of a country travelling in another country) is collected via sample surveys. However, in a few cases the data are compiled from border surveys. Surveys are generally conducted on a monthly or quarterly basis.   The concepts and definitions used in the collection of data shall conform to the specifications described in the Methodological manual for tourism statistics. With the entry into force of the Regulation (EU) 692/2011 of the European Parliament and of the Council, Member States are transmitting microdata to Eurostat, which enables that data to be disseminated far more widely (since reference period 2012). The information on tourism demand concerns trips (for the population aged 15 years and over) of which the main purpose is holidays or business and which involve at least one or more consecutive nights spent away from the usual place of residence (See annex at the bottom of the page). Aggregated data on participation in tourim is also transmitted to Eurostat and covers the resident population aged 15 or over, participating in tourism for personal purpose during the reference year. Microdata on trips of EU residents as well as participation data are transmitted to Eurostat one time per year. Data are disseminated when they respect agreed validation rules and other quality criteria.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 21 September, 2017
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      The total consumption expenditure made by a visitor or on behalf of a visitor for and during his/her trip and stay at destination.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 24 September, 2017
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      This collection covers national tourism.  Data is collected by the competent national authorities of the Member States and is compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Most of the time, data on domestic and outbound trips (where "outbound tourism" means residents of a country travelling in another country) is collected via sample surveys. However, in a few cases the data are compiled from border surveys. Surveys are generally conducted on a monthly or quarterly basis.   The concepts and definitions used in the collection of data shall conform to the specifications described in the Methodological manual for tourism statistics. With the entry into force of the Regulation (EU) 692/2011 of the European Parliament and of the Council, Member States are transmitting microdata to Eurostat, which enables that data to be disseminated far more widely (since reference period 2012). The information on tourism demand concerns trips (for the population aged 15 years and over) of which the main purpose is holidays or business and which involve at least one or more consecutive nights spent away from the usual place of residence (See annex at the bottom of the page). Aggregated data on participation in tourim is also transmitted to Eurostat and covers the resident population aged 15 or over, participating in tourism for personal purpose during the reference year. Microdata on trips of EU residents as well as participation data are transmitted to Eurostat one time per year. Data are disseminated when they respect agreed validation rules and other quality criteria.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
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      Gross earnings are remuneration (wages and salaries) in cash paid directly to the employee, before any deductions for income tax and social security contributions paid by the employee. Data is presented for full-time employees in "industry and services".
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
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      The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '20.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.
    • March 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 08 June, 2014
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      Eurostat Dataset Id:lfso_04avovisco Results from the 2004 LFS (Labour Force Survey) ad hoc module on 'work organisation and working time arrangements'.
    • March 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 08 June, 2014
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      Eurostat Dataset Id:lfso_04avpoisco Results from the 2004 LFS (Labour Force Survey) ad hoc module on 'work organisation and working time arrangements'.
    • November 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 June, 2014
      Select Dataset
      Eurostat Dataset Id:ilc_lvho03h 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.
    • November 2009
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 June, 2014
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      Eurostat Dataset Id:ilc_lvho04h 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.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 20 September, 2017
      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 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 June, 2014
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      Eurostat Dataset Id:lfso_06finiyrsp Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 14 September, 2017
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      Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category:Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below:Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.
    • February 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 February, 2017
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    • February 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 February, 2017
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      The domain "Personal well-being" covers overall life experience, satisfaction with different areas of life, trust in others and in institutions and social support (having someone to rely on in case of need).  
    • February 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 February, 2017
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    • February 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 February, 2017
      Select Dataset
      The domain "Personal well-being" covers overall life experience, satisfaction with different areas of life, trust in others and in institutions and social support (having someone to rely on in case of need).  
    • June 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 June, 2017
      Select Dataset
      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.
    • February 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 February, 2017
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    • February 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 February, 2017
      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 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 08 June, 2014
      Select Dataset
      Eurostat Dataset Id:lfso_05nowreh Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • March 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 08 June, 2014
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      Eurostat Dataset Id:lfso_05typech Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • March 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 08 June, 2014
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      Eurostat Dataset Id:lfso_05regch Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • March 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 08 June, 2014
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      Eurostat Dataset Id:lfso_05changh Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • March 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 08 June, 2014
      Select Dataset
      Eurostat Dataset Id:lfso_04vawkhwus Results from the 2004 LFS (Labour Force Survey) ad hoc module on 'work organisation and working time arrangements'.
    • March 2014
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 08 June, 2014
      Select Dataset
      Eurostat Dataset Id:lfso_04vahrhwus Results from the 2004 LFS (Labour Force Survey) ad hoc module on 'work organisation and working time arrangements'.
    • April 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 April, 2017
      Select Dataset
      Data given in this domain are collected annually by the National Statistical Institutes and are based on Eurostat's annual model questionnaires on ICT (Information and Communication Technologies) usage in households and by individuals. Large part of the data collected are used in the context of the follow up of the Digital Single Market process (Monitoring the Digital Economy & Society  2016-2021). This conceptual framework follows the 2011 - 2015 benchmarking framework, the i2010 Benchmarking Framework and the eEurope 2005 Action Plan. ICT usage data are also used in the Consumer Conditions Scoreboard (purchases over the Internet) and in the Employment Guidelines (e-skills of individuals). The aim of the European ICT surveys is the timely provision of statistics on individuals and households on the use of Information and Communication Technologies at European level. Data for this collection are supplied directly from the surveys with no separate treatment. Coverage: The characteristics to be provided are drawn from the following list of subjects:access to and use of ICTs by individuals and/or in households,use of the Internet and other electronic networks for different purposes by individuals and/or in households,ICT security and trust,ICT competence and skills,barriers to the use of ICT and the Internet,perceived effects of ICT usage on individuals and/or on households,use of ICT by individuals to exchange information and services with governments and public administrations (e-government),access to and use of technologies enabling connection to the Internet or other networks from anywhere at any time (ubiquitous connectivity). Breakdowns (see details of available breakdowns): Relating to households:by region of residence (NUTS 1, optional: NUTS 2)by geographical location: less developed regions, transition regions, more developed regionsby degree of urbanisation (till 2012: densely/intermediate/sparsely populated areas; from 2012: densely/thinly populated area, intermediate density area) by type of householdby households net monthly income (optional) Relating to individuals:by region of residence (NUTS1, optional: NUTS 2)by geographical location: less developed regions, transition regions, more developed regionsby degree of urbanisation: (till 2012: densely/intermediate/sparsely populated areas; from 2012: densely/thinly populated area, intermediate density area)by genderby country of birth, country of citizenship (as of 2010, optional in 2010)by educational level: ISCED 1997 up to 2013 and ISCED 2011 from 2014 onwards.by occupation: manual, non-manual; ICT (coded by 2-digit ISCO categories)/non-ICT (optional: all 2-digit ISCO categories)by employment situationby age (in completed years and by groups)legal / de facto marital status (2011-2014, optional) Regional breakdowns (NUTS) are available only for a selection of indicators disseminated in the regional tables in Eurobase (Regional Information society statistics by NUTS regions (isoc_reg):Households with access to the internet at homeHouseholds with broadband accessIndividuals who have never used a computerIndividuals who used the internet, frequency of use and activitiesIndividuals who used the internet for interaction with public authoritiesIndividuals who ordered goods or services over the internet for private useIndividuals who accessed the internet away from home or work
  • B
    • September 2017
      Source: Baker Hughes
      Uploaded by: Knoema
      Accessed On: 10 September, 2017
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    • July 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 09 July, 2016
      Select Dataset
      The Balance of Payments (BoP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of a economic area during a given period. The Balance of payments provides harmonized information on international transactions which are part of the current account (goods, services, income, current transfers), but also on transactions which fall in the capital and the financial account. BoP is an important macro-economic indicator used to assess the position of an economy (of credit or debit) towards the external world. Data on International Trade in Services (ITS), a component of BoP current account, are used, alongside with data on Foreign Direct Investment (a component of BoP financial account), to monitor the external commercial performance of different economies. Balance of Payments data are used for calculation of indicators needed for monitoring of macroenomic imbalances such as share of main BoP and International Investment Position (IIP) items in GDP and export market shares calculated as the EU Member States' shares in total world exports. Out of BoP data, some indicators of EU market integration are also derived. Data are in millions of Euro/ECU and in millions of national currency. Several statistical adjustments are applied to the original data provided by the Member States. These are described in the International Trade in Services EU 1992-2001 - Compilation guide. The International Monetary Fund Balance of Payments Manual (BPM5) classification is used for the compilation of the BoP. The BoP data are collected through national surveys and administrative sources.
    • July 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 July, 2016
      Select Dataset
      The Balance of Payments (BoP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of a economic area during a given period. The Balance of payments provides harmonized information on international transactions which are part of the current account (goods, services, income, current transfers), but also on transactions which fall in the capital and the financial account. BoP is an important macro-economic indicator used to assess the position of an economy (of credit or debit) towards the external world. Data on International Trade in Services (ITS), a component of BoP current account, are used, alongside with data on Foreign Direct Investment (a component of BoP financial account), to monitor the external commercial performance of different economies. Balance of Payments data are used for calculation of indicators needed for monitoring of macroenomic imbalances such as share of main BoP and International Investment Position (IIP) items in GDP and export market shares calculated as the EU Member States' shares in total world exports. Out of BoP data, some indicators of EU market integration are also derived. Data are in millions of Euro/ECU and in millions of national currency. Several statistical adjustments are applied to the original data provided by the Member States. These are described in the International Trade in Services EU 1992-2001 - Compilation guide. The International Monetary Fund Balance of Payments Manual (BPM5) classification is used for the compilation of the BoP. The BoP data are collected through national surveys and administrative sources.
    • September 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 11 September, 2017
      Select Dataset
      The balance of payments is a statistical statement that provides a systematic summary of economic transactions of an economy with the rest of the world, for a specific time period. The transactions are for the most part between residents and non-residents of the economy. A transaction is defined as an economic flow that reflects the creation, transformation, exchange, transfer, or extinction of economic value and involves changes in ownership, of goods or assets, the provision of services, labour or capital. This dataset presents countries compiling balance of payments statistics in accordance with the 6th edition of the Balance of Payments and International Investment Position Manual published by the IMF (BPM6). Transactions include: the goods and services accounts, the primary income account (income account in BPM5), the secondary income account (transfers in BPM5), the capital account, and the financial account.Changes in BPM6 compared to BPM5 are often a consequence of a stricter application of the change of ownership principle in particular in the goods and services accounts. They relate to transactions on goods and services (merchanting, goods for processing, Insurance), income (investment income), and financial operations (direct investment) .
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 August, 2017
      Select Dataset
      The Balance of Payments (BOP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of an economic area during a given period. The Balance of payments provides harmonized information on international transactions which are part of the current account (goods, services, primary and secondary income), as well as on transactions which fall in the capital and the financial account. International investment position presents value of financial assets owned outside the economy and indebtedness of the economy to the rest of the world. BOP is an important macro-economic indicator used to assess the position of an economy (of credit or debit for current and capital acount, net acquisition of financial assets or net incurrence of liabilities for BOP financial account and international investment position) towards the external world. Out of BOP data, some indicators on international position of the EU and Member States are derived. Indicators on Main Balance of Payments and International Investment Position items as share of GDP are presented as percentage of GDP for given year or quarter and moving average for 3 consecutive years for:balance, credit and debit flows of current and capital accounts and of main current account  items: goods, services, primary and secondary income,net flows, net acquisition of financial assets and net incurrence of liabilities for total financial account and foreign direct investment, international investment position and net external debt at the end of reference quarter or year.   Indicators on export market shares present shares of each EU Member State in total world exports of goods and services for given year, and 1-year and 5-year percentage changes of these shares, as well as shares in OECD exports and 5-year percentage changes of these shares.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
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      The Balance of Payments is the statistical statement that systematically summarises transactions between residents and non-residents. It consists of the goods and services account, the primary income account, the secondary income account, the capital account and the financial account (BPM6 – 2.12) The capital account in the international accounts shows a) capital transfers receivable and payable between residents and nonresidents and b) the acquisition and disposal of nonproduced, nonfinancial assets between residents and nonresidents (BPM6- 13.1). The capital transfers are transfers in which the ownership of an asset (other than cash or inventories) changes from one party to another. The sum of the balances on the current and capital accounts represents the net lending (surplus) or net borrowing (deficit) by the economy with the rest of the world (BPM6 – 2.18). Source of euro area data: European Central Bank (ECB).
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      The Balance of Payments (BoP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of a geographical region during a given period. The Balance of payments provides harmonized information on international transactions which are part of the current account (goods, services, income, current transfers), but also on transactions which fall in the capital and the financial account. BoP is an important macro-economic indicator used to assess the position of an economy (of credit or debit) towards the external world. Data on International Trade in Services, a component of BoP current account, and data on Foreign Direct Investment, a component of BoP financial account, are used to monitor the external commercial performance of different economies. Outward Foreign Affiliates Statistics (FATS) measure the commercial presence, as defined by the General Agreement on Trade in Services (GATS), through affiliates in foreign markets. Balance of Payments data are used for calculation of indicators needed for monitoring of macroenomic imbalances such as share of main BoP and International Investment Position (IIP) items in GDP and export market shares calculated as the EU Member States' shares in total world exports.  Out of BoP data, some indicators of EU market integration are also derived. Data are in millions of Euro/ECU or in millions of national currency. Balance of Payments data coverage varies according to the collection. Some collections refer only to Euro area or EU countries, while some others' coverage includes also EU partner countries.   Several statistical adjustments are applied to the original data provided by the Member States. The International Monetary Fund Balance of Payments Manual (BPM5) classification is used for the compilation of the BoP. The BoP data are collected through national surveys and administrative sources.    More information on BoP is available for each specific collection: Quarterly BoP, ITS, FDI, Outward FATS, BoP of EU Institutions.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      The Balance of Payments is the statistical statement that systematically summarises transactions between residents and non-residents. It consists of the goods and services account, the primary income account, the secondary income account, the capital account and the financial account (BPM6 – 2.12) The current account is an important grouping of accounts within the Balance of Payments. The current account balance shows the difference between the sum of exports and income receivable and the sum of imports and income payable (exports and imports refer to both goods and services, while income refers to both primary and secondary income). The value of current account balance equals the saving-investment gap for the economy. The balance of current account is thus related to understanding domestic transactions (BPM6 – 2.15). Data are expressed in million euros. Data are presented in raw form. Source of euro area data: European Central Bank (ECB).
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      The Balance of Payments is the statistical statement that systematically summarises transactions between residents and non-residents. It consists of the goods and services account, the primary income account, the secondary income account, the capital account and the financial account (BPM6 – 2.12) The current account is an important grouping of accounts within the Balance of Payments. The current account balance shows the difference between the sum of exports and income receivable and the sum of imports and income payable (exports and imports refer to both goods and services, while income refers to both primary and secondary income). The value of current account balance equals the saving-investment gap for the economy. The balance of current account is thus related to understanding domestic transactions (BPM6 – 2.15). Data are expressed in million euros. Data are presented in raw form. Source of euro area data: European Central Bank (ECB).
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 September, 2017
      Select Dataset
      The Balance of Payments (BOP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of an economic area during a given period. The Balance of payments provides harmonized information on international transactions which are part of the current account (goods, services, primary and secondary income), as well as on transactions which fall in the capital and the financial account. International investment position presents value of financial assets owned outside the economy and indebtedness of the economy to the rest of the world. BOP is an important macro-economic indicator used to assess the position of an economy (of credit or debit for current and capital acount, net acquisition of financial assets or net incurrence of liabilities for BOP financial account and international investment position) towards the external world. Out of BOP data, some indicators on international position of the EU and Member States are derived. Indicators on Main Balance of Payments and International Investment Position items are presented for given quarter for:balance, credit and debit flows of current and capital accounts and of main current account  items: goods, services, primary and secondary income,net flows, net acquisition of financial assets and net incurrence of liabilities for total financial account and foreign direct investment, international investment position and net external debt at the end of reference quarter.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      The Balance of Payments is the statistical statement that systematically summarises transactions between residents and non-residents. It consists of the goods and services account, the primary income account, the secondary income account, the capital account and the financial account (BPM6 – 2.12) The capital account in the international accounts shows a) capital transfers receivable and payable between residents and nonresidents and b) the acquisition and disposal of nonproduced, nonfinancial assets between residents and nonresidents (BPM6- 13.1). The capital transfers are transfers in which the ownership of an asset (other than cash or inventories) changes from one party to another. The sum of the balances on the current and capital accounts represents the net lending (surplus) or net borrowing (deficit) by the economy with the rest of the world (BPM6 – 2.18). Source of euro area data: European Central Bank (ECB).
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      The Balance of Payments (BoP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of a geographical region during a given period. The Balance of payments provides harmonized information on international transactions which are part of the current account (goods, services, income, current transfers), but also on transactions which fall in the capital and the financial account. BoP is an important macro-economic indicator used to assess the position of an economy (of credit or debit) towards the external world. Data on International Trade in Services, a component of BoP current account, and data on Foreign Direct Investment, a component of BoP financial account, are used to monitor the external commercial performance of different economies. Outward Foreign Affiliates Statistics (FATS) measure the commercial presence, as defined by the General Agreement on Trade in Services (GATS), through affiliates in foreign markets. Balance of Payments data are used for calculation of indicators needed for monitoring of macroenomic imbalances such as share of main BoP and International Investment Position (IIP) items in GDP and export market shares calculated as the EU Member States' shares in total world exports.  Out of BoP data, some indicators of EU market integration are also derived. Data are in millions of Euro/ECU or in millions of national currency. Balance of Payments data coverage varies according to the collection. Some collections refer only to Euro area or EU countries, while some others' coverage includes also EU partner countries.   Several statistical adjustments are applied to the original data provided by the Member States. The International Monetary Fund Balance of Payments Manual (BPM5) classification is used for the compilation of the BoP. The BoP data are collected through national surveys and administrative sources.    More information on BoP is available for each specific collection: Quarterly BoP, ITS, FDI, Outward FATS, BoP of EU Institutions.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      The Balance of Payments is the statistical statement that systematically summarises transactions between residents and non-residents. It consists of the goods and services account, the primary income account, the secondary income account, the capital account and the financial account (BPM6 – 2.12) The financial account shows net acquisition and disposal of financial assets and liabilities The financial account indicates the functional categories, sectors, instruments, and maturities used for net international financing transactions. (BPM6 – 8.1). Five functional categories of investment are distinguished in the international accounts: a) direct investment, b) portfolio investment, c) financial derivatives and employee stock options, d) other investment and e) reserve assets. (BPM6 – 6.1). Source of euro area data: European Central Bank (ECB).
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      The Balance of Payments is the statistical statement that systematically summarises transactions between residents and non-residents. It consists of the goods and services account, the primary income account, the secondary income account, the capital account and the financial account (BPM6 – 2.12) The financial account shows net acquisition and disposal of financial assets and liabilities The financial account indicates the functional categories, sectors, instruments, and maturities used for net international financing transactions. (BPM6 – 8.1). Five functional categories of investment are distinguished in the international accounts: a) direct investment, b) portfolio investment, c) financial derivatives and employee stock options, d) other investment and e) reserve assets. (BPM6 – 6.1). Source of euro area data: European Central Bank (ECB).
    • June 2012
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 14 June, 2012
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      Note: Not seasonally adjusted data in Millions of euro (from 1.1.1999)/ECU (up to 31.12.1998)
    • July 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 09 July, 2016
      Select Dataset
      The Balance of Payments (BoP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of a economic area during a given period. The Balance of payments provides harmonized information on international transactions which are part of the current account (goods, services, income, current transfers), but also on transactions which fall in the capital and the financial account. BoP is an important macro-economic indicator used to assess the position of an economy (of credit or debit) towards the external world. Data on International Trade in Services (ITS), a component of BoP current account, are used, alongside with data on Foreign Direct Investment (a component of BoP financial account), to monitor the external commercial performance of different economies. Balance of Payments data are used for calculation of indicators needed for monitoring of macroenomic imbalances such as share of main BoP and International Investment Position (IIP) items in GDP and export market shares calculated as the EU Member States' shares in total world exports. Out of BoP data, some indicators of EU market integration are also derived. Data are in millions of Euro/ECU and in millions of national currency. Several statistical adjustments are applied to the original data provided by the Member States. These are described in the International Trade in Services EU 1992-2001 - Compilation guide. The International Monetary Fund Balance of Payments Manual (BPM5) classification is used for the compilation of the BoP. The BoP data are collected through national surveys and administrative sources.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 September, 2017
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       International trade in goods statistics are an important data source for many public and private sector decision-makers at international, European Union and national level. For example, at the European Union level, external trade data are extensively used for multilateral and bilateral negotiations within the framework of the common commercial policy, to define and implement anti-dumping policy, to evaluate the progress of the Single Market and many other policies. Moreover, they constitute an essential source for the compilation of balance of payments statistics and national accounts. International trade in goods statistics cover both extra- and intra-EU trade: Extra-EU trade statistics cover the trading of goods between Member States and a non-member countries. Intra-EU trade statistics cover the trading of goods between Member States. "Goods" means all movable property including electricity. Detailed and aggregated data are published for the Euro area, the European Union and for each Member State separately. Main components: Data record the monthly trade between Member States in terms of arrivals and dispatches of goods as well as the monthly trade in terms of imports and exports between Member States and non-member countries. However, in publications only the term “exports” for all outward flows and “imports” for all inward flows are applied for both intra-EU trade and extra-EU trade. Extra-EU trade imports and exports are recorded in the Member State where the goods are placed under the customs procedures. Extra-EU trade statistics do not record goods in transit, goods placed into customs warehouses or goods for temporary admission. Data sources: The statistical information is mainly provided by the traders on the basis of Customs (extra-EU) and Intrastat (intra-EU) declarations. Data are collected by the competent national authorities of the Member States and compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Classification systems: - Product classification: For detailed data, products are disseminated according to the Combined Nomenclature (CN8), which first six digit codes coincide with the Harmonized Commodity Description and Coding System (HS), products are disseminated as well according to the Standard International Trade Classification (SITC) and the Broad Economic Categories (BEC). - Country classification: The Geonomenclature is used for classifying reporting countries and trading partners. Nomenclatures and correspondence tables are available at the Eurostat’s classification server RAMON. The following basic information is provided by Eurostat: - reporting country, - reference period, - trade flow, - product, - trading partner, - mode of transport. Detailed data are disseminated according to the Combined Nomenclature (HS2, HS4, HS6 and CN8 levels) for the following indicators: - trade value (in Euro), - trade quantity in 100 kg, - trade quantity in supplementary units (published for some goods according to the Combined Nomenclature). Aggregated data cover both short and long term indicators. Short term indicators are disseminated according to major SITC and BEC groups for the following indicators: - gross and seasonally adjusted trade value (in million Euro), - unit-value indices, - gross and seasonally adjusted volume indices, - growth rates of trade values and indices. Adjustments are applied by the Member States to compensate the impact of exemption thresholds, which release the information providers from statistical formalities, as well as, to take into account the late or not response of the providers. In addition, Eurostat applies seasonal adjustments to aggregated time series.
    • February 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 15 February, 2017
      Select Dataset
      Since the collection of 2009 data, the scope of the OECD Global Insurance Statistics questionnaire has been expanded. These changes led to the collection of key balance sheet and income statement items for direct insurance and reinsurance sectors, such as: gross claims paid, outstanding claims provision (changes), gross operating expenses, commissions, total assets, gross technical provisions (of which: unit-linked), shareholder equity, net income.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 23 September, 2017
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      This table includes the areas, productions and humidity of Winter barley sown before or during winter and Spring barley sown in the spring. Cereal grains harvested just before maturity are also included in this table. Cereals harvested green or yellow as whole plant for fodder or renewable energy use are not included in this table. This indicator uses the concepts of "area under cultivation", "harvested production" and "humidity". 1) The "area under cultivation" corresponds: • before the harvest, to the sown area; • after the harvest, to the sown area excluding the non-harvested area (e.g. area ruined by natural disasters, area not harvested for economic reasons, etc.) 2) The "harvested production" corresponds to the production for which harvesting started in year N, even thought harvesting may finish in year N+1. So N is the reference year for data published by Eurostat. 3) In order to facilitate the comparisons of production between the Members States, the publication of "humidity" for each country is needed. Only the EU-aggregate for the production is published with a standard EU humidity.
    • June 2015
      Source: Barro-Lee
      Uploaded by: Knoema
      Accessed On: 12 October, 2015
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    • August 2015
      Source: Barro-Lee
      Uploaded by: Knoema
      Accessed On: 12 October, 2015
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    • July 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 July, 2017
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      The Community Innovation Survey (CIS) is a survey of innovation activity in enterprises. The survey is designed to provide information on the innovativeness of sectors by type of enterprises, on the different types of innovation and on various aspects of the development of an innovation, such as the objectives, the sources of information, the public funding or the expenditures. The CIS provides statistics broke down by countries, types of innovators, economic activities and size classes. The survey is currently carried out every two years across the European Union, some EFTA countries and EU candidate countries. In order to ensure comparability across countries, Eurostat together with the countries developed a standard core questionnaire (see in Annex) accompanied by a set of definitions and methodological recommendations. CIS 2012 concepts and underlying methodology are also based on the Oslo Manual third edition of 2005 (see link at the bottom of the page). CIS 2012 results were collected under Commission Regulation No 995/2012. This Regulation sets the mandatory target population of the survey that refers to enterprises in the Core NACE categories (see section 3.3.) with at least 10 employees. Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period 2010-2012, but some use only one calendar year (2010 or 2012). CIS 2012 includes an ad-hoc module on growth that consists of a set of questions focusing more specifically on the strategies and obstacles for reaching the enterprises' goals. While the European innovation statistics use the aggregated national data, the microdata sets can be accessed by researchers via the SAFE Centre of Eurostat in Luxembourg or via CD-ROM releases in more anonymised form; some countries also provide access to their microdata through national Safe Centres. Since the provision of the microdata is voluntary, microdatasets do not cover all countries.
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 September, 2017
      Select Dataset
      The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to provide information on the innovativeness of sectors by type of enterprises, on the different types of innovation and on various aspects of the development of an innovation, such as objectives, sources of information, public funding or expenditures. The CIS provides statistics broken down by countries, types of innovators, economic activities and size classes. The survey is currently carried out every two years across the European Union, EFTA countries and EU candidate countries. In order to ensure comparability across countries, Eurostat together with the countries developed a standard core questionnaire (see in Annex) accompanied by a set of definitions and methodological recommendations. CIS 2014 concepts and its underlying methodology are also based on the Oslo Manual (2005) 3rd edition (see link at the bottom of the page). CIS 2014 results were collected under Commission Regulation No 995/2012. This Regulation defines the mandatory target population of the survey referring to enterprises in the Core NACE categories (see section 3.3.) with at least 10 employees. Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period 2012-2014, but some use only one calendar year (2012 or 2014). CIS 2014 includes an ad-hoc module on innovations with environmental benefits. While European innovation statistics use aggregated national data, the microdata sets can be consulted by researchers via the SAFE Centre of Eurostat in Luxembourg or via CD-ROM releases in a more anonymised form; some countries also provide access to their microdata through national Safe Centres. Since the provision of microdata is voluntary, microdatasets do not cover all countries.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 26 September, 2017
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      The labour market policy (LMP) database was developed and maintained by Eurostat till 2013. From 2014, the LMP database is developed and maintained by European Commission's Directorate General for Employment, Social Affairs and Inclusion and LMP data are disseminated by Eurostat. European Commission's LMP database provides information on labour market interventions, which are government actions to help and support the unemployed and other disadvantaged groups in the transition from unemployment or inactivity to work. The scope of the LMP database is limited to interventions that are explicitly targeted at groups of persons with difficulties in the labour market: the unemployed, persons employed but at risk of involuntary job loss and persons currently considered as inactive persons but who would like to enter the labour market. LMP statistics are one of the data sources for monitoring the Employment Guidelines (part II of the Europe 2020 Integrated Guidelines) through the Europe 2020 Joint Assessment Framework (JAF). The guidelines specifically refer to the provision of active labour market policies, which cover LMP measures and LMP services, and adequate social security systems, which include LMP supports. The unit of observation in the LMP database is the labour market intervention and data on the expenditure and participants for each intervention are collected annually from administrative sources in each country. The database also collects extensive qualitative information that describes each intervention, how it works, the main target groups, etc. LMP interventions are classified by type of action into three broad types – services, measures and supports – and into 9 detailed categories (see 3.2 Classification system). The LMP database covers all EU Member States and Norway. Data for the EU-15 countries and Norway are available from 1998 whilst the more recently acceded EU countries started providing data at different times from 2003 onwards. The following data and metadata are available:Summary tables of expenditure and participants by type of actionFor each country: detailed tables of expenditure and participants by interventionLMP based indicators for monitoring the Employment Guidelines (for definitions see annexes below)Reference data on persons registered with Public Employment Services (PES)Qualitative reports describing the interventions in each country
    • May 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 21 May, 2016
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      Data given in this domain are collected on a yearly basis by the National Statistical Institutes or Ministries and are based on the annual Eurostat Model Questionnaires on ICT (Information and Communication Technologies) usage and e-commerce in enterprises. Large part of the data collected are used in the context of the 2011 - 2015 benchmarking framework (endorsed by i2010 High Level Group in November 2009) for the Digital Agenda Scoreboard, Europe's strategy for a flourishing digital economy by 2020. This conceptual framework follows the i2010 Benchmarking Framework which itself followed-up the eEurope 2005 Action Plan. The aim of the European ICT usage surveys is to collect and disseminate harmonised and comparable information on the use of Information and Communication Technologies in enterprises and e-commerce at European level. Coverage: The characteristics to be provided are drawn from the following list of subjects: ICT systems and their usage in enterprises,use of the Internet and other electronic networks by enterprises,e-commerce,e-business processes and organisational aspects,use of ICT by enterprises to exchange information and services with governments and public administrations (e-government),ICT competence in the enterprise and the need for ICT skills,barriers to the use of ICT, the Internet and other electronic networks, e-commerce and e-business processes,ICT expenditure and investment,ICT security and trust,use of ICT and its impact on the environment (Green ICT),access to and use of the Internet and other network technologies for connecting objects and devices (Internet of Things),access to and use of technologies providing the ability to connect to the Internet or other networks from anywhere at any time (ubiquitous connectivity).Breakdowns:by size class,by NACE categories,by region (until 2010)
    • August 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 November, 2016
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      Better Life Index aims to involve citizens in the debate on measuring the well-being of societies, and to empower them to become more informed and engaged in the policy-making process that shapes all our lives. Each of the 11 topics of the Index is currently based on one to three indicators. Within each topic, the indicators are averaged with equal weights. The indicators have been chosen on the basis of a number of statistical criteria such as relevance (face-validity, depth, policy relevance) and data quality (predictive validity, coverage, timeliness, cross-country comparability etc.) and in consultation with OECD member countries. These indicators are good measures of the concepts of well-being, in particular in the context of a country comparative exercise. Other indicators will gradually be added to each topic.
    • September 2016
      Source: National Statistics Bureau, Bhutan
      Uploaded by: Knoema
      Accessed On: 12 January, 2017
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      Bhutan : Tourism Statistics, 2015
    • May 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 15 May, 2017
      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 follow up of the Digital Single Market process (Monitoring the Digital Economy & Society 2016-2021). This conceptual framework follows the 2011 - 2015 benchmarking framework, the i2010 Benchmarking Framework and 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,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 security and trust,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)
    • April 2014
      Source: United Nations Conference on Trade and Development
      Uploaded by: Knoema
      Accessed On: 08 February, 2016
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      UNCTAD's Bilateral FDI Statistics provides up-to-date and systematic FDI data for 206 economies around the world, covering inflows (table 1), outflows (table 2), inward stock (table 3) and outward stock (table 4) by region and economy. Data are in principle collected from national sources. In order to cover the entire world, where data are not available from national sources, data from partner countries (mirror data) as well as from other international organizations have also been used.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
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      20.1. Source data
    • October 2016
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 11 November, 2016
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      This data set provides a snapshot of migration and remittances for all countries, regions and income groups of the world, compiled from available data from various sources
    • August 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 08 August, 2017
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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
    • April 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 May, 2016
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    • July 2017
      Source: Bank for International Settlements
      Uploaded by: Knoema
      Accessed On: 01 September, 2017
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      Measure for all Combinations - Amounts Outstanding / Stocks   Note: Under "Reporting country" they have removed "Euro Area".
    • September 2017
      Source: Bank for International Settlements
      Uploaded by: Knoema
      Accessed On: 20 September, 2017
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      Below Parameters are common for all combinations : Frequency - Quarterly Measure -Amounts Outstanding / Stocks CBS Bank Type - Domestic Banks CBS Reporting Basis - Immediate Counterparty Basis Balance Sheet Position - Total Claims Type of Instruments - All Instruments Remaining Maturity - All Maturities Currency Type of Booking Location - All Currencies Counterparty Sector - All Sectors
    • September 2017
      Source: Bank for International Settlements
      Uploaded by: Knoema
      Accessed On: 16 September, 2017
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    • August 2017
      Source: Bank for International Settlements
      Uploaded by: Knoema
      Accessed On: 01 September, 2017
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      The residential property price statistics collect data from different countries. The BIS has obtained permission from various national data providers, with the assistance of its member central banks, to disseminate these statistics. The topic ‘Property prices: Selected series,’ contains nominal and real quarterly values for 58 countries, both in levels and in growth rates (ie four series per country). Real series are the nominal price series deflated by the consumer price index. The BIS has made the selection based on the Handbook on Residential Property Prices and the experience and metadata of central banks.
    • September 2017
      Source: Bank for International Settlements
      Uploaded by: Knoema
      Accessed On: 19 September, 2017
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      >>All series on credit to the non-financial sector cover 44 economies, both advanced and emerging. They capture the outstanding amount of credit at the end of the reference quarter. Credit is provided by domestic banks, all other sectors of the economy and non-residents. In terms of financial instruments, credit covers the core debt, defined as loans, debt securities and currency & deposits.   >>All series are published in local currency, in US dollars and as percentages of nominal GDP. The regional aggregates as percentages of GDP are calculated based on conversion to the US dollar at market and at purchasing power parity (PPP) exchange rates.
    • April 2017
      Source: Bloom Consulting
      Uploaded by: Knoema
      Accessed On: 24 May, 2017
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      Bloom Consulting was founded in 2003 as a Nation Branding consultancy. Our Headquarters are located in Madrid, with offices in Lisbon and São Paulo. Bloom Consulting has been interviewed by The Economist, Forbes and CNN . According to Country Branding Central www.countrybrandingwiki.org, our CEO José Filipe Torres, a recurrent lecturer in Universities such as Harvard, is considered one of the top 3 international experts in the field of Nation Branding, Region and City Branding, providing advisory for the OECD.In addition, Bloom Consulting publishes the Bloom Consulting Country Brand Ranking © annually for both Trade and Tourism, to extensively analyze the brand performance of 193 countries and territories worldwide and the Digital Country Index - Measuring the Brand appeal of countries and territories in the Digital World.
    • January 2017
      Source: Bloomberg
      Uploaded by: Knoema
      Accessed On: 23 January, 2017
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      Bloomberg innovation index ranks countries and sovereigns based on their overall ability to innovate. It considers six equally weighted metrics, and their scores are combined to provide an overall score for each country from zero to 100.1. Research & Development: Research and development expenditure as a percentage of GDP2. Manufacturing: Manufacturing value-added per capita3. Productivity: GDP and GNI per employed person age 15+4. High-tech companies: Number of domestically domiciled high-tech public companies—such as aerospace and defense, biotechnology, hardware, software, semiconductors, Internet software and services, and renewable energy companies – as a share of world's total high-tech public companies5. Tertiary efficiency: Total enrolment in tertiary education, regardless of age, as a percentage of postsecondary cohort; minimum share of labor force with at least tertiary degrees; annual new science and engineering graduates as a percentage of the labor force and as a percentage of total tertiary graduates6. Researcher concentration: Professionals, including Ph.D. students, engaged in R&D per 1 million population7. Patents: Resident utility patent filings per 1 million population and per $1 million of R&D spent; utility patents granted as a percentage of world totalBloomberg innovation index evaluated more than 200 countries of which only 78 had data for at least six of the seven factors. Postsecondary education and patent activity consisted of multiple factors that were weighted equally. Weights were rescaled for countries with some but not all of the factors in those two metrics. The ranking shows only those countries included in the top 50.
    • March 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 28 June, 2017
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      The European Health Interview Survey (EHIS) aims at measuring on a harmonised basis and with a high degree of comparability among MS the health status (including disability), health determinants (including environment) and use and limitations in access to health care services of the EU citizens. The general coverage of the survey is the population aged 15 or over living in private households residing in the territory of the country. EHIS was developed between 2003 and 2006. It consists of four modules on health status, health determinants, health care, and background variables. The first wave of EHIS (EHIS wave 1 or EHIS round 2008) was conducted between 2006 and 2009 in 17 EU Member States as well as Switzerland and Turkey. The second wave (EHIS wave 2 or EHIS round 2014) was conducted between 2013 and 2015 in all EU Member States, Iceland and Norway. Some other countries conducted their national health interview surveys using the second wave of EHIS questionnaire such as Turkey or Serbia. EHIS includes the following topics: Health status This topic includes different dimensions of health status and health-related activity limitations: General health status (Minimum European health module): self-perceived health, chronic morbidity and activity limitationDisease-specific morbidityAccidents and injuriesHealth-related absenteeism from workPhysical and sensory functional limitationsDifficulties in personal care activities / activities of daily living (such as eating and washing) and help received/neededHousehold activities / Instrumental activities of daily living (such as preparing meals and shopping) and help received/neededPainAspect of mental health (psychological distress and mental well-being in the first wave, depressive symptoms in the second wave)Work-related health problems (only in the first wave).Health care This topic covers the use of different types of medicines and formal and informal health and social care services, which are complemented by data on health-related expenditure, and limitations in access to and satisfaction with health care services: Hospitalisation (in-patient and day care)Consultations with doctors and dentistsVisits to specific health professionals (such as physiotherapists or psychologists)Use of home care and home help servicesUse of medicines (prescribed and non-prescribed)Healthcare preventive actions (such as influenza vaccination, breast examination, cervical smear test and blood tests)Unmet needs for health careOut-of-pocket payments for medical care (only in the first wave)Satisfaction with services provided by healthcare providers (only in the first wave)Visits to specific categories of alternative medicine practitioners (only in the first wave).Health determinants This topic includes various individual and environmental health determinants: Height and weightPhysical activityConsumption of fruits, vegetables and juiceSmoking behaviour and exposure to tobacco smokeAlcohol consumptionSocial supportProvision of informal care or assistance (only in the second wave)Illicit drug use (only in the first wave)Environment (home and workplace exposures, criminality exposure) (only in the first wave).Background variables on demography and socio-economic status. All indicators are expressed as percentages within the population and statistics are broken down by age and sex and one other dimension such as educational attainment level, income quintile group or labour status.
    • May 2017
      Source: BP
      Uploaded by: Knoema
      Accessed On: 22 June, 2017
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      The BP Statistical Review of World Energy has provided high-quality, objective and globally consistent data on world energy markets. The Review is one of the most widely respected and authoritative publications in the field of energy economics, used for reference by the media, academia, world governments and energy companies. A new edition is published every June. Historical data from 1965 for many sections.
    • June 2017
      Source: BP
      Uploaded by: Knoema
      Accessed On: 02 August, 2017
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      The BP Statistical Review of World Energy has provided high-quality, objective and globally consistent data on world energy markets. The Review is one of the most widely respected and authoritative publications in the fi eld of energy economics, used for reference by the media, academia, world governments and energy companies. A new edition is published every June. Historical data from 1965 for many sections.
    • December 2016
      Source: Times Higher Education
      Uploaded by: Knoema
      Accessed On: 05 January, 2017
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      The Times Higher Education BRICS & Emerging Economies Rankings 2017, provides institutions ranking and Score (performance indicators). The rankings use 13 performance indicators to provide the most comprehensive and balanced comparisons, trusted by students, academics, university leaders, industry and even governments – but the weightings are specially recalibrated to reflect the characteristics of emerging economy universities.The performance indicators are grouped into five areas:1. Teaching (the learning environment)2. Research (volume, income and reputation)3. Citations (research influence)4. International outlook (staff, students and research)5. Industry income (knowledge transfer)Note: The ranking of institutions, after 200, have been given in range like 201-250 and 251-300.The rank has been taken as 201, 202, 203……..250 as the same order as they appear in the source.
    • May 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 May, 2017
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      Data given in this domain are collected on a yearly basis by the National Statistical Institutes or Ministries and are based on the annual Eurostat Model Questionnaires on ICT (Information and Communication Technologies) usage and e-commerce in enterprises. Large part of the data collected are used in the context of the 2011 - 2015 benchmarking framework (endorsed by i2010 High Level Group in November 2009) for the Digital Agenda Scoreboard, Europe's strategy for a flourishing digital economy by 2020. This conceptual framework follows the i2010 Benchmarking Framework which itself followed-up the eEurope 2005 Action Plan. The aim of the European ICT usage surveys is to collect and disseminate harmonised and comparable information on the use of Information and Communication Technologies in enterprises and e-commerce at European level. Coverage: The characteristics to be provided are drawn from the following list of subjects: ICT systems and their usage in enterprises,use of the Internet and other electronic networks by enterprises,e-commerce,e-business processes and organisational aspects,use of ICT by enterprises to exchange information and services with governments and public administrations (e-government),ICT competence in the enterprise and the need for ICT skills,barriers to the use of ICT, the Internet and other electronic networks, e-commerce and e-business processes,ICT expenditure and investment,ICT security and trust,use of ICT and its impact on the environment (Green ICT),access to and use of the Internet and other network technologies for connecting objects and devices (Internet of Things),access to and use of technologies providing the ability to connect to the Internet or other networks from anywhere at any time (ubiquitous connectivity).Breakdowns:by size class,by NACE categories,by region (until 2010)
    • April 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 May, 2017
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      Data given in this domain are collected annually by the National Statistical Institutes and are based on Eurostat's annual model questionnaires on ICT (Information and Communication Technologies) usage in households and by individuals. Large part of the data collected are used in the context of the follow up of the Digital Single Market process (Monitoring the Digital Economy & Society  2016-2021). This conceptual framework follows the 2011 - 2015 benchmarking framework, the i2010 Benchmarking Framework and the eEurope 2005 Action Plan. ICT usage data are also used in the Consumer Conditions Scoreboard (purchases over the Internet) and in the Employment Guidelines (e-skills of individuals). The aim of the European ICT surveys is the timely provision of statistics on individuals and households on the use of Information and Communication Technologies at European level. Data for this collection are supplied directly from the surveys with no separate treatment. Coverage: The characteristics to be provided are drawn from the following list of subjects:access to and use of ICTs by individuals and/or in households,use of the Internet and other electronic networks for different purposes by individuals and/or in households,ICT security and trust,ICT competence and skills,barriers to the use of ICT and the Internet,perceived effects of ICT usage on individuals and/or on households,use of ICT by individuals to exchange information and services with governments and public administrations (e-government),access to and use of technologies enabling connection to the Internet or other networks from anywhere at any time (ubiquitous connectivity). Breakdowns (see details of available breakdowns): Relating to households:by region of residence (NUTS 1, optional: NUTS 2)by geographical location: less developed regions, transition regions, more developed regionsby degree of urbanisation (till 2012: densely/intermediate/sparsely populated areas; from 2012: densely/thinly populated area, intermediate density area) by type of householdby households net monthly income (optional) Relating to individuals:by region of residence (NUTS1, optional: NUTS 2)by geographical location: less developed regions, transition regions, more developed regionsby degree of urbanisation: (till 2012: densely/intermediate/sparsely populated areas; from 2012: densely/thinly populated area, intermediate density area)by genderby country of birth, country of citizenship (as of 2010, optional in 2010)by educational level: ISCED 1997 up to 2013 and ISCED 2011 from 2014 onwards.by occupation: manual, non-manual; ICT (coded by 2-digit ISCO categories)/non-ICT (optional: all 2-digit ISCO categories)by employment situationby age (in completed years and by groups)legal / de facto marital status (2011-2014, optional) Regional breakdowns (NUTS) are available only for a selection of indicators disseminated in the regional tables in Eurobase (Regional Information society statistics by NUTS regions (isoc_reg):Households with access to the internet at homeHouseholds with broadband accessIndividuals who have never used a computerIndividuals who used the internet, frequency of use and activitiesIndividuals who used the internet for interaction with public authoritiesIndividuals who ordered goods or services over the internet for private useIndividuals who accessed the internet away from home or work
    • April 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 May, 2017
      Select Dataset
      Data given in this domain are collected annually by the National Statistical Institutes and are based on Eurostat's annual model questionnaires on ICT (Information and Communication Technologies) usage in households and by individuals. Large part of the data collected are used in the context of the follow up of the Digital Single Market process (Monitoring the Digital Economy & Society  2016-2021). This conceptual framework follows the 2011 - 2015 benchmarking framework, the i2010 Benchmarking Framework and the eEurope 2005 Action Plan. ICT usage data are also used in the Consumer Conditions Scoreboard (purchases over the Internet) and in the Employment Guidelines (e-skills of individuals). The aim of the European ICT surveys is the timely provision of statistics on individuals and households on the use of Information and Communication Technologies at European level. Data for this collection are supplied directly from the surveys with no separate treatment. Coverage: The characteristics to be provided are drawn from the following list of subjects:access to and use of ICTs by individuals and/or in households,use of the Internet and other electronic networks for different purposes by individuals and/or in households,ICT security and trust,ICT competence and skills,barriers to the use of ICT and the Internet,perceived effects of ICT usage on individuals and/or on households,use of ICT by individuals to exchange information and services with governments and public administrations (e-government),access to and use of technologies enabling connection to the Internet or other networks from anywhere at any time (ubiquitous connectivity). Breakdowns (see details of available breakdowns): Relating to households:by region of residence (NUTS 1, optional: NUTS 2)by geographical location: less developed regions, transition regions, more developed regionsby degree of urbanisation (till 2012: densely/intermediate/sparsely populated areas; from 2012: densely/thinly populated area, intermediate density area) by type of householdby households net monthly income (optional) Relating to individuals:by region of residence (NUTS1, optional: NUTS 2)by geographical location: less developed regions, transition regions, more developed regionsby degree of urbanisation: (till 2012: densely/intermediate/sparsely populated areas; from 2012: densely/thinly populated area, intermediate density area)by genderby country of birth, country of citizenship (as of 2010, optional in 2010)by educational level: ISCED 1997 up to 2013 and ISCED 2011 from 2014 onwards.by occupation: manual, non-manual; ICT (coded by 2-digit ISCO categories)/non-ICT (optional: all 2-digit ISCO categories)by employment situationby age (in completed years and by groups)legal / de facto marital status (2011-2014, optional) Regional breakdowns (NUTS) are available only for a selection of indicators disseminated in the regional tables in Eurobase (Regional Information society statistics by NUTS regions (isoc_reg):Households with access to the internet at homeHouseholds with broadband accessIndividuals who have never used a computerIndividuals who used the internet, frequency of use and activitiesIndividuals who used the internet for interaction with public authoritiesIndividuals who ordered goods or services over the internet for private useIndividuals who accessed the internet away from home or work
    • May 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 May, 2017
      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 follow up of the Digital Single Market process (Monitoring the Digital Economy & Society 2016-2021). This conceptual framework follows the 2011 - 2015 benchmarking framework, the i2010 Benchmarking Framework and 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,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 security and trust,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)
    • June 2015
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 March, 2016
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      The OECD broadband portal provides access to a range of broadband-related statistics gathered by the OECD. Policy makers must examine a range of indicators which reflect the status of individual broadband markets. The OECD broadband speed tests by country show the official measurements of actual access network broadband speed. The OECD broadband map shows national broadband statistics in OECD countries. Mobile broadband penetration has risen to 85.4% in the OECD area, meaning more than four wireless subscriptions for every five inhabitants, according to data for June 2015 released by the OECD .
    • July 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 August, 2017
      Select Dataset
      The OECD broadband portal provides access to a range of broadband-related statistics gathered by the OECD. Policy makers must examine a range of indicators which reflect the status of individual broadband markets. The OECD broadband speed tests by country show the official measurements of actual access network broadband speed. The OECD broadband map shows national broadband statistics in OECD countries. Mobile broadband penetration has risen to 85.4% in the OECD area, meaning more than four wireless subscriptions for every five inhabitants, according to data for June 2015 released by the OECD .
    • June 2015
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 March, 2016
      Select Dataset
      The OECD broadband portal provides access to a range of broadband-related statistics gathered by the OECD. Policy makers must examine a range of indicators which reflect the status of individual broadband markets. The OECD broadband speed tests by country show the official measurements of actual access network broadband speed. The OECD broadband map shows national broadband statistics in OECD countries. Mobile broadband penetration has risen to 85.4% in the OECD area, meaning more than four wireless subscriptions for every five inhabitants, according to data for June 2015 released by the OECD .
    • June 2015
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 March, 2016
      Select Dataset
      The OECD broadband portal provides access to a range of broadband-related statistics gathered by the OECD. Policy makers must examine a range of indicators which reflect the status of individual broadband markets. The OECD broadband speed tests by country show the official measurements of actual access network broadband speed. The OECD broadband map shows national broadband statistics in OECD countries. Mobile broadband penetration has risen to 85.4% in the OECD area, meaning more than four wireless subscriptions for every five inhabitants, according to data for June 2015 released by the OECD .
    • June 2014
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 23 March, 2016
      Select Dataset
      The OECD broadband portal provides access to a range of broadband-related statistics gathered by the OECD. Policy makers must examine a range of indicators which reflect the status of individual broadband markets. The OECD broadband speed tests by country show the official measurements of actual access network broadband speed. The OECD broadband map shows national broadband statistics in OECD countries. Mobile broadband penetration has risen to 85.4% in the OECD area, meaning more than four wireless subscriptions for every five inhabitants, according to data for June 2015 released by the OECD . Note: unit of measure of indicators related to Internet selling and purchasing by industry is percentage of businesses with 10 or more employees in each industry group.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
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      Short-term statistics (STS) give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification (Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are generally presented in the following forms:UnadjustedCalendar adjustedSeasonally adjusted Depending on the STS regulation data are accessible as monthly, quarterly and annual data. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction (volume)*Turnover: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic turnover into euro area and non euro area is available for the euro area countriesProducer prices (output prices)*: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic producer prices into euro area and non euro area is available for the euro area countriesImport prices*: Total, Euro area market, Non euro area market (euro area countries only)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries CONSTRUCTIONProduction (volume)*: Total of the construction sector, Building construction, Civil EngineeringBuilding permits indicators*: Number of dwellings, Square meters of useful floor (or alternative size measure)Construction costs or prices: Construction costs, Material costs, Labour costs (if not available, they may be approximated by the Output prices variable)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries WHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (value)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries SERVICESTurnover (in value)*Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesProducer prices (Output prices )* National reference metadata of the reporting countries can be found in the Annexes of this metadata file.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 18 September, 2017
      Select Dataset
      Short-term statistics (STS) give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification (Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are generally presented in the following forms:UnadjustedCalendar adjustedSeasonally adjusted Depending on the STS regulation data are accessible as monthly, quarterly and annual data. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction (volume)*Turnover: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic turnover into euro area and non euro area is available for the euro area countriesProducer prices (output prices)*: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic producer prices into euro area and non euro area is available for the euro area countriesImport prices*: Total, Euro area market, Non euro area market (euro area countries only)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries CONSTRUCTIONProduction (volume)*: Total of the construction sector, Building construction, Civil EngineeringBuilding permits indicators*: Number of dwellings, Square meters of useful floor (or alternative size measure)Construction costs or prices: Construction costs, Material costs, Labour costs (if not available, they may be approximated by the Output prices variable)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries WHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (value)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries SERVICESTurnover (in value)*Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesProducer prices (Output prices )* National reference metadata of the reporting countries can be found in the Annexes of this metadata file.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      Short-term statistics (STS) give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification (Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are generally presented in the following forms:UnadjustedCalendar adjustedSeasonally adjusted Depending on the STS regulation data are accessible as monthly, quarterly and annual data. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction (volume)*Turnover: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic turnover into euro area and non euro area is available for the euro area countriesProducer prices (output prices)*: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic producer prices into euro area and non euro area is available for the euro area countriesImport prices*: Total, Euro area market, Non euro area market (euro area countries only)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries CONSTRUCTIONProduction (volume)*: Total of the construction sector, Building construction, Civil EngineeringBuilding permits indicators*: Number of dwellings, Square meters of useful floor (or alternative size measure)Construction costs or prices: Construction costs, Material costs, Labour costs (if not available, they may be approximated by the Output prices variable)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries WHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (value)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries SERVICESTurnover (in value)*Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesProducer prices (Output prices )* National reference metadata of the reporting countries can be found in the Annexes of this metadata file.
    • April 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 30 April, 2016
      Select Dataset
      Short-term statistics (STS) give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification (Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are generally presented in the following forms: UnadjustedCalendar adjustedSeasonally adjusted Depending on the STS regulation data are accessible as monthly, quarterly and annual data. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction (volume)*Turnover: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic turnover into euro area and non euro area is available for the euro area countriesProducer prices (output prices)*: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic producer prices into euro area and non euro area is available for the euro area countriesImport prices*: Total, Euro area market, Non euro area market (euro area countries only)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesCONSTRUCTIONProduction (volume)*: Total of the construction sector, Building construction, Civil EngineeringBuilding permits indicators*: Number of dwellings, Square meters of useful floor (or alternative size measure)Construction costs or prices: Construction costs, Material costs, Labour costs (if not available, they may be approximated by the Output prices variable)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesWHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (value)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesSERVICESTurnover (in value)*Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesProducer prices (Output prices )* National reference metadata of the reporting countries can be found in the Annexes of this metadata file.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      Short-term statistics (STS) give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification (Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are generally presented in the following forms:UnadjustedCalendar adjustedSeasonally adjusted Depending on the STS regulation data are accessible as monthly, quarterly and annual data. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction (volume)*Turnover: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic turnover into euro area and non euro area is available for the euro area countriesProducer prices (output prices)*: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic producer prices into euro area and non euro area is available for the euro area countriesImport prices*: Total, Euro area market, Non euro area market (euro area countries only)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries CONSTRUCTIONProduction (volume)*: Total of the construction sector, Building construction, Civil EngineeringBuilding permits indicators*: Number of dwellings, Square meters of useful floor (or alternative size measure)Construction costs or prices: Construction costs, Material costs, Labour costs (if not available, they may be approximated by the Output prices variable)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries WHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (value)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries SERVICESTurnover (in value)*Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesProducer prices (Output prices )* National reference metadata of the reporting countries can be found in the Annexes of this metadata file.
    • April 2016
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 30 April, 2016
      Select Dataset
      Short-term statistics (STS) give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification (Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are generally presented in the following forms: UnadjustedCalendar adjustedSeasonally adjusted Depending on the STS regulation data are accessible as monthly, quarterly and annual data. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction (volume)*Turnover: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic turnover into euro area and non euro area is available for the euro area countriesProducer prices (output prices)*: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic producer prices into euro area and non euro area is available for the euro area countriesImport prices*: Total, Euro area market, Non euro area market (euro area countries only)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesCONSTRUCTIONProduction (volume)*: Total of the construction sector, Building construction, Civil EngineeringBuilding permits indicators*: Number of dwellings, Square meters of useful floor (or alternative size measure)Construction costs or prices: Construction costs, Material costs, Labour costs (if not available, they may be approximated by the Output prices variable)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesWHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (value)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesSERVICESTurnover (in value)*Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesProducer prices (Output prices )* National reference metadata of the reporting countries can be found in the Annexes of this metadata file.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
      Select Dataset
      20.1. Source data
    • June 2016
      Source: Food and Agriculture Organization
      Uploaded by: Knoema
      Accessed On: 10 February, 2017
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      Greenhouse Gas (GHG) emissions from burning crop residues consist of methane (CH4) and nitrous oxide (N2O) gases produced by the combustion of a percentage of crop residues burnt on-site. The mass of fuel available for burning should be estimated taking into account the fractions removed before burning due to animal consumption, decay in the field, and use in other sectors (e.g., biofuel, domestic livestock feed, building materials, etc.). FAOSTAT emission estimates are computed at Tier 1 following the IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, reguions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed both as Gg CH4, Gg N2O, Gg CO2eq and CO2eq from CH4 and N2O, by crop (maize, rice, sugarcane and wheat) and by aggregates. Implied emission factors for N2O and CH4 as well activity data (biomass burned) are also provided.
    • January 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 09 January, 2017
      Select Dataset
      Eurostat Dataset Id:htec_sti_pers2 Data description'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data).The sectoral approach:The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries.Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level.The sectoral approach is used for all indicators except data on high-tech trade and patents.Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors under 21.3.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 under 21.3.The product approach:The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC).The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. . For more details, see definition of high-tech products under 21.3.High-tech patents:High-tech patents are defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition).Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents under 21.3.The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by 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.
    • May 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 June, 2017
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    • April 2015
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 21 August, 2015
      Select Dataset
      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2005 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics performed in the business enterprise sector by industry according to the International Standard Industrial Classification (ISIC) revision 3.1. Data at the industry level are presented beginning 1987, year when most of the countries converted from ISIC rev.2 to the current ISIC rev. 3 classification. This breakdown between industries is, in principle, made at the enterprise level, although some countries are able to break down R&D data for multi product enterprises between their main lines of business. National statistical regulations prevent publication of results where there are very few firms in the given category, hence the many gaps in the tables. Depending on the country, R&D institutes serving enterprises are either classified with the industry concerned, or grouped under “Research and Development” (ISIC rev.3.1, Division 73). When these R&D institutes are classified with the industry served, the evaluation of R&D in these industries is more complete and more comparable between countries for the industries concerned. This results, however, in an underestimation of the percentage of BERD performed by the service sector as compared with other countries. The Frascati Manual recommendation concerning data on R&D by industry is to report BERD on an enterprise basis (see FM section 3.4). When this is interpreted strictly, all the BERD of a diversified enterprise will be allocated to the industrial class of its principal activity. In circumstances where a few large firms dominate R&D spending in several areas, this can and does lead to underestimates of R&D associated with the secondary activities of the firms. Overall, R&D is therefore overestimated for some industries and underestimated for others. However, not all countries follow a strict enterprise basis for allocating R&D expenditures to industrial classes. Some countries make a disaggregation of the R&D of their largest, diversified firms into a number of different activities. In other countries, the enterprise approach has been abandoned and data are reported on a product field basis. This is why two classification criteria for BERD by industry are included in this view of “BERD by industry” (see the variable CLASSIFICATION CRITERIA: Main activity or Product field) depending on which approach is more closely followed by each country (only a few countries currently collect these data both ways and are therefore included according to both criteria)). The two tables that follow, “BERD by industry and source of funds” and “BERD by industry and type of costs” present data for only one of the criteria, depending on the country.
    • May 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 June, 2017
      Select Dataset
      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2005 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics performed in the business enterprise sector by industry according to the International Standard Industrial Classification (ISIC) revision 3.1. and by source of funds (business enterprise, government, other national funds, and funds from abroad). Data at the industry level are presented beginning 1987, year when most of the countries converted from ISIC rev.2 to the current ISIC rev. 3 classification. This breakdown between industries is, in principle, made at the enterprise level, although some countries are able to break down R&D data for multi product enterprises between their main lines of business. National statistical regulations prevent publication of results where there are very few firms in the given category, hence the many gaps in the tables. Depending on the country, R&D institutes serving enterprises are either classified with the industry concerned, or grouped under “Research and Development” (ISIC rev.3.1, Division 73). When these R&D institutes are classified with the industry served, the evaluation of R&D in these industries is more complete and more comparable between countries for the industries concerned. This results, however, in an underestimation of the percentage of BERD performed by the service sector as compared with other countries. The Frascati Manual recommendation concerning data on R&D by industry is to report BERD on an enterprise basis (see FM section 3.4). When this is interpreted strictly, all the BERD of a diversified enterprise will be allocated to the industrial class of its principal activity. In circumstances where a few large firms dominate R&D spending in several areas, this can and does lead to underestimates of R&D associated with the secondary activities of the firms. Overall, R&D is therefore overestimated for some industries and underestimated for others. However, not all countries follow a strict enterprise basis for allocating R&D expenditures to industrial classes. Some countries make a disaggregation of the R&D of their largest, diversified firms into a number of different activities. In other countries, the enterprise approach has been abandoned and data are reported on a product field basis. This is why two classification criteria for BERD by industry are included in the table “BERD by industry” (see the variable CLASSIFICATION CRITERIA: Main activity or Product field) depending on which approach is more closely followed by each country (only a few countries currently collect these data both ways and are therefore included according to both criteria). However, this table “BERD by industry and source of funds” and the one that follows, “BERD by industry and type of costs” present data for only one of the criteria, depending on the country.
    • May 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 June, 2017
      Select Dataset
      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2000 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics performed in the business enterprise sector by industry according to the International Standard Industrial Classification (ISIC) revision 3.1. and by type of costs (current expenditure, capital expenditure). Data at the industry level are presented beginning 1987, year when most of the countries converted from ISIC rev.2 to the current ISIC rev. 3 classification. This breakdown between industries is, in principle, made at the enterprise level, although some countries are able to break down R&D data for multi product enterprises between their main lines of business. National statistical regulations prevent publication of results where there are very few firms in the given category, hence the many gaps in the tables. Depending on the country, R&D institutes serving enterprises are either classified with the industry concerned, or grouped under “Research and Development” (ISIC rev.3.1, Division 73). When these R&D institutes are classified with the industry served, the evaluation of R&D in these industries is more complete and more comparable between countries for the industries concerned. This results, however, in an underestimation of the percentage of BERD performed by the service sector as compared with other countries. The Frascati Manual recommendation concerning data on R&D by industry is to report BERD on an enterprise basis (see FM section 3.4). When this is interpreted strictly, all the BERD of a diversified enterprise will be allocated to the industrial class of its principal activity. In circumstances where a few large firms dominate R&D spending in several areas, this can and does lead to underestimates of R&D associated with the secondary activities of the firms. Overall, R&D is therefore overestimated for some industries and underestimated for others. However, not all countries follow a strict enterprise basis for allocating R&D expenditures to industrial classes. Some countries make a disaggregation of the R&D of their largest, diversified firms into a number of different activities. In other countries, the enterprise approach has been abandoned and data are reported on a product field basis. This is why two classification criteria for BERD by industry are included in the table “BERD by industry” (see the variable CLASSIFICATION CRITERIA: Main activity or Product field) depending on which approach is more closely followed by each country (only a few countries currently collect these data both ways and are therefore included according to both criteria). However, this table “BERD by industry and type of costs” and the preceding one “BERD by industry and source of funds” present data for only one of the criteria, depending on the country.
    • May 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 June, 2017
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      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2010 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics performed in the business enterprise sector. Data include total business enterprise intramural expenditure on R&D by size class and source of funds.
    • May 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 21 June, 2017
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      This table presents research and development (R&D) statistics on personnel in the business enterprise sector. Measured in full-time equivalent are the number of total R&D personnel and researchers in the business enterprise sector by industry according to the International Standard Industrial Classification (ISIC) revision 3.1. Data at the industry level are presented beginning 1987, year when most of the countries converted from ISIC rev.2 to the current ISIC rev. 3 classification.
    • August 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 September, 2017
      Select Dataset
      The business tendency survey indicators cover a standard set of indicators for four economic sectors: manufacturing, construction, retail trade and other services. This includes an indicator of overall business conditions or business confidence in each sector. The consumer opinion survey indicators cover a restricted set of indicators on consumer confidence, expected economic situation and price expectations.Business and consumer opinion (tendency) surveys provide qualitative information that has proved useful for monitoring the current economic situation. Typically they are based on a sample of enterprises or households and respondents are asked about their assessments of the current situation and expectations for the immediate future. For enterprise surveys this concerns topics such as production, orders, stocks etc. and in the case of consumer surveys their intentions concerning major purposes, economic situation now compared with the recent past and expectations for the immediate future. Many survey series provide advance warning of turning points in aggregate economic activity as measured by GDP or industrial production. Such series are known as leading indicators in cyclical analysis. These types of survey series are widely used as component series in composite leading indicators. The main characteristic of these types of surveys is that instead of asking for exact figures, they usually ask for the direction of change e.g. a question on tendency by reference to a “normal” state, e.g. of production level. Possible answers are generally of the three point scale type e.g. up/same/down or above normal/normal/below normal for enterprise surveys and of the five point scale type e.g. increase sharply/increase slightly/remain the same/fall slightly/fall sharply for consumer surveys. In presenting the results as a time series, only the balance is shown. That is “same” or “normal” answers are ignored and the balance is obtained by taking the difference between percentages of respondents giving favourable and unfavourable answers.Virtually all business tendency and consumer opinion survey data are presented as time series of balances in this dataset, either in raw or seasonally adjusted form. Very few series are presented as indices, and where these exist they have generally been converted from underlying balances by countries before submitting the data to the OECD.  
    • August 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 August, 2017
      Select Dataset
      Institutional coverage As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Item coverage Business written in the reporting country on a gross and net premium basis. It contains a breakdown between domestic companies, foreign-controlled companies and branches and agencies or foreign companies.
    • February 2012
      Source: Federal State Statistics Service, Russia
      Uploaded by: Knoema
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      Внешняя торговля товарами Российской Федерации по странам партнерам, 1995-2011
  • C
    • February 2017
      Source: World Resources Institute
      Uploaded by: Knoema
      Accessed On: 26 June, 2017
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      CAIT Historic allows for easy access, analysis and visualization of the latest available international greenhouse gas emissions data. It includes information for 186 countries, 50 U.S. states, 6 gases, multiple economic sectors, and 160 years - carbon dioxide emissions for 1850-2012 and multi-sector greenhouse gas emission for 1990-2012.
    • March 2017
      Source: United Nations Economic Commission for Europe
      Uploaded by: Knoema
      Accessed On: 07 April, 2017
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    • March 2017
      Source: United Nations Economic Commission for Europe
      Uploaded by: Knoema
      Accessed On: 05 April, 2017
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    • March 2017
      Source: United Nations Economic Commission for Europe
      Uploaded by: Knoema
      Accessed On: 05 April, 2017
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    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
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      The Balance of Payments (BoP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of an economic area during a given period. The BoP provides harmonized information on international transactions which are part of the current, capital and financial accounts. The Current account provides information about the transactions of a country with the rest of the world. It covers all transactions (other than those in financial items) in goods, services, primary income and secondary income, which occur between resident and non-resident units. The MIP scoreboard indicator is 3 years average of Current account balance as % of GDP. In addition annual and quarterly data on the BoP sub-balances and its components are published under the MIP domain.
    • September 2017
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 25 September, 2017
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      The Balance of Payments (BoP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of an economic area during a given period. The BoP provides harmonized information on international transactions which are part of the current, capital and financial accounts. The Current account provides information about the transactions of a country with the rest of the world. It covers all transactions (other than those in financial items) in goods, services, primary income and secondary income, which occur between resident and non-resident units. The MIP scoreboard indicator is 3 years average of Current account balance as % of GDP. In addition annual and quarterly data on the BoP sub-balances and its components are published under the MIP domain.
    • August 2013
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 September, 2014
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      Transactions within the international production network and imports and exports of final goods and services can be estimated by using an inter-country economic model based on multi-regional input-output (MRIO) modelling techniques. In order to achieve this, national Input-Output tables are first converted to a common currency (nominal USD) and the import matrices are disaggregated to separate bilateral flows of goods and services. A range of adjustments to deal with measurement issues such as re-exports; unspecified partners and commodities; and missing data, particularly for trade in services, are necessary before the analysis.
    • January 2013
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 10 November, 2013
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      Eurostat Dataset Id:pipe_if_capac The data in this dataset comes from the Common Questionnaire for Transport Statistics, developed and surveyed in co-operation between the United Nations Economic Commission for Europe (UNECE), the International Transport Forum (ITF) and Eurostat. The Common Questionnaire is not supported by a legal act, but is based on a gentlemen's agreement with the participating countries; the completeness varies from country to country. Eurostat’s datasets based on the Common Questionnaire cover annual data for the EU Member States, EFTA states and Candidate countries to the EU. Data for other participating countries are available through the ITFand the UNECE. In total, comparable transport data collected through the Common Questionnaire is available for close to 60 countries worldwide. The Common Questionnaire collects aggregated annual data on:Railway transportRoad transportInland waterways transportOil pipelines transportGas pipelines transport For each mode of transport, the Common Questionnaire cover some or all of the following sub-modules (the number of questions/variables within each sub-module varies between the different modes of transport):Infrastructure (All modes)Transport equipment (RAIL, ROAD and INLAND WATERWAYS)Enterprises, economic performance and employment (All modes)Traffic (RAIL, ROAD and INLAND WATERWAYS)Transport measurement (All modes) Accidents (ROAD only) The Common Questionnaire is completed by the competent national authorities. The responsibility for completing specific modules (e.g. Transport by Rail) or part of modules (e.g. Road Infrastructure) may be delegated to other national authorities in charge of specific fields.