Произошла ошибка. Подробности Скрыть
У вас есть несохраненные страницы. Восстановить Отмена

Германия

  • Население, человек:82 695 000 (2017)
  • Площадь, кв км:348 900 (2017)
  • ВВП на душу населения, долл. США:44 470 (2017)
  • ВВП, млрд. долл. США:3 677,4 (2017)
  • Индекс Джини:31,7 (2015)
  • Рейтинг Ease of Doing Business:20 (2017)
Все наборы данных:  2 A B C D E F G H I K L M N O P Q R S T U V W Y
  • 2
    • Февраль 2015
      Источник: American Institute of Stress
      Загружен: Knoema
      Дата обращения к источнику: 28 апреля, 2015
      Выбрать
  • A
    • Октябрь 2011
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 мая, 2014
      Выбрать
      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
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 29 июня, 2014
      Выбрать
      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.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 26 июня, 2014
      Выбрать
      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.
    • Август 2018
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 августа, 2018
      Выбрать
      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
    • Март 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 ноября, 2013
      Выбрать
      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.   
    • Май 2013
      Источник: Food and Agriculture Organization
      Загружен: Knoema
      Дата обращения к источнику: 22 марта, 2019
      Выбрать
    • Май 2013
      Источник: Food and Agriculture Organization
      Загружен: Knoema
      Дата обращения к источнику: 22 марта, 2019
      Выбрать
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 21 апреля, 2014
      Выбрать
      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.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 21 апреля, 2014
      Выбрать
      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.
    • Апрель 2017
      Источник: Akamai
      Загружен: Knoema
      Дата обращения к источнику: 07 июня, 2017
      Выбрать
    • Июнь 2013
      Источник: World Bank
      Загружен: Knoema
      Дата обращения к источнику: 21 ноября, 2014
      Выбрать
      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: All The Ginis Dataset Publication: https://datacatalog.worldbank.org/dataset/all-ginis-dataset License: http://creativecommons.org/licenses/by/4.0/   This dataset includes combined and standardized Gini data from eight original sources: Luxembourg Income Study (LIS), Socio-Economic Database for Latin America (SEDLAC), Survey of Living Conditions (SILC) by Eurostat, World Income Distribution (WYD; the full data set is available here), World Bank Europe and Central Asia dataset, World Institute for Development Research (WIDER), World Bank Povcal, and Ginis from individual long-term inequality studies (just introduced in this version).
    • Апрель 2014
      Источник: United Nations COMTRADE
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2014
      Выбрать
      Angola trade with selected countries by commodity 04 HS, 2013
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 13 апреля, 2014
      Выбрать
      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
    • Май 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 09 июня, 2014
      Выбрать
      Eurostat Dataset Id:earn_ses10_rbns The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.
    • Июль 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 11 ноября, 2013
      Выбрать
      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).
    • Декабрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 мая, 2014
      Выбрать
      Eurostat Dataset Id:educ_bo_ou_terd The Bologna declaration was signed in 1999 by 29 European ministers responsible for higher education. Today, 46 signatory countries are engaged in the process towards a European Higher Education Area (EHEA). The Bologna Process is an intergovernmental initiative which also involves the European Commission, the Council of Europe and UNESCO-CEPES, as well as representatives of higher education institutions, students, staff, employers and quality assurance agencies. It aims to create a European Higher Education Area by 2010, and to promote the European system of higher education worldwide. More information on the Bologna process is available on http://ec.europa.eu/education/higher-education/doc1290_en.htm. In the framework of the indicators for the monitoring of the social dimension and mobility of the Bologna Process, the EU-SILC (EU Statistics on Income and Living Conditions) data of interest cover individual's educational attainment, income and, from the intergenerational transmission of poverty ad hoc module, educational attainment of the parents. The following data-sets, having EU-SILC as source, on the Bologna Process are available: A. Widening access educ_bo_ac_sobs: Individuals having completed tertiary education (ISCED 5-6), according to the educational background of their parents, by sexeduc_bo_ac_soba: Individuals having completed tertiary education (ISCED 5-6), according to the educational background of their parents, by age D. Effective outcomes and employability educ_bo_ou_attd: Annual gross income of workers by educational attainment (2006)educ_bo_ou_terd: Annual gross income of workers with tertiary education (ISCED 5-6) , by sex (2006) The general aim of the EU-SILC domain is to provide comparable statistics and indicators on key aspects of the citizens' living conditions across Europe. This domain actually contains a range of social statistics and indicators relating to the risks of income poverty and social exclusion. There are both conceptual and methodological problems in defining and measuring income poverty and social exclusion. Since a 1984 decision of the European Council, the following are regarded as poor: "those persons, families and groups of persons whose resources (material, cultural and social) are so limited as to exclude them from the minimum acceptable way of life in the Member State to which they belong". On this basis, measures of poverty at EU level adopt an approach which is both multi-dimensional and relative. In June 2006, a new set of common indicators for the social protection and social inclusion process was adopted. (For more details and definitions of these indicators: Indicators 2006). To investigate particular areas of policy interest in more detail, target secondary areas, to be collected every four years or less frequently, are added to the cross-sectional component of EU-SILC. "The intergenerational transmission of poverty" was chosen as the area to be implemented for 2005. This specific module, collected in 2005, had as purpose to collect and compile relevant and robust information on background factors linked to adult social exclusion, minimising the burden of respondents to provide accurate detailed indicators sufficiently comparable across the EU capturing the effects of childhood experiences on poverty risk. More general information on EU-SILC is available on ilc_base.htm
    • Декабрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 мая, 2014
      Выбрать
      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
    • Июнь 2017
      Источник: International Tropical Timber Organization
      Загружен: Pallavi S
      Дата обращения к источнику: 24 июля, 2017
      Выбрать
      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.
    • Сентябрь 2018
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 01 октября, 2018
      Выбрать
    • Июнь 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 01 июня, 2017
      Выбрать
      Eurostat Dataset Id:mare_d3area
    • Июнь 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 августа, 2015
      Выбрать
      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.
    • Март 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 апреля, 2014
      Выбрать
      Eurostat Dataset Id:vit_bs4_de 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.
    • Октябрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 апреля, 2014
      Выбрать
      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.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 13 апреля, 2014
      Выбрать
      Eurostat Dataset Id:agr_r_crops
    • Июнь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 12 декабря, 2015
      Выбрать
      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.
    • Октябрь 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 июня, 2014
      Выбрать
      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.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 июня, 2014
      Выбрать
      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.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 июня, 2014
      Выбрать
      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.
    • Март 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 июня, 2014
      Выбрать
      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.
    • Июль 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 июля, 2019
      Выбрать
      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.
    • Октябрь 2014
      Источник: LMC Automotive
      Загружен: Knoema
      Дата обращения к источнику: 09 января, 2015
      Выбрать
      Automotive Industry, 2014
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_06finiagps Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_06otbnagps Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 30 июня, 2014
      Выбрать
      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 …).  
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_06reasagps Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 июня, 2014
      Выбрать
      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.
    • Ноябрь 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 июня, 2014
      Выбрать
      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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
      Выбрать
      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
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 14 апреля, 2014
      Выбрать
      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
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 16 июля, 2019
      Выбрать
      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.   Average wages are converted in USD PPPs using 2017 USD PPPs for private consumption and are deflated by a price deflator for private final consumption expenditures in 2017 prices.   Real compensation per employee (instead of real wages) are considered for Chile, Iceland, Mexico and New Zealand.
    • Апрель 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 мая, 2019
      Выбрать
      Average Electricity, Gas and Spark Spread prices for industrial consumers - bi-annual data (from 2007 onwards) - Data upto 2018 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/
    • Июнь 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 12 декабря, 2015
      Выбрать
      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.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_04avovisco Results from the 2004 LFS (Labour Force Survey) ad hoc module on 'work organisation and working time arrangements'.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_04avpoisco Results from the 2004 LFS (Labour Force Survey) ad hoc module on 'work organisation and working time arrangements'.
    • Ноябрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 17 июня, 2014
      Выбрать
      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.
    • Ноябрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 17 июня, 2014
      Выбрать
      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.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_06finiyrsp Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_05nowreh Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_05typech Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_05regch Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_05changh Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_04vawkhwus Results from the 2004 LFS (Labour Force Survey) ad hoc module on 'work organisation and working time arrangements'.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_04vahrhwus Results from the 2004 LFS (Labour Force Survey) ad hoc module on 'work organisation and working time arrangements'.
  • B
    • Июль 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 июля, 2012
      Выбрать
      This Dataset contains 3 Tables. Banks' balance sheet assets and liabilities - Annual data (mny_agg_a) Banks' balance sheet assets and liabilities - Quarterly data (mny_agg_q) Banks' balance sheet assets and liabilities - Monthly data (mny_agg_m). Note: Eurostat Hierarchy: Economy and finance > Monetary and other financial statistics (mny) > Monetary aggregates, counterparts, and other banks' balance sheet items (mny_agg).
    • Май 2017
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 12 июня, 2017
      Выбрать
      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.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 05 марта, 2019
      Выбрать
      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.
    • Май 2017
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 09 июня, 2017
      Выбрать
      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.
    • Май 2017
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 21 июня, 2017
      Выбрать
      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.
    • Февраль 2012
      Источник: Federal State Statistics Service, Russia
      Загружен: Knoema
      Выбрать
      Внешняя торговля товарами Российской Федерации по странам партнерам, 1995-2011
  • C
    • Март 2019
      Источник: International Organization of Motor Vehicle Manufacturers
      Загружен: Knoema
      Дата обращения к источнику: 11 апреля, 2019
      Выбрать
      OICA Car Production Statistics 1999-2018 contains world motor vehicle production statistics, obtained from national trade organisations, OICA members or correspondents. Passenger cars are motor vehicles with at least four wheels, used for the transport of passengers, and comprising no more than eight seats in addition to the driver's seat. Commercial vehicles include light commercial vehicles, heavy trucks, coaches and buses.
    • Декабрь 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 20 января, 2014
      Выбрать
      Eurostat Dataset Id:fish_ca_00 Catches of fish, crustaceans, molluscs and other aquatic organisms by species and fishing area for EU and associated countries (in live weight equivalent of the landings). The concepts and definitions used in the compilation of catch statistics are those laid down by the Coordinating Working Party on Fishery Statistics (CWP), of which Eurostat is one of the member organizations. These concepts and definitions have been in force since the late 1950's and are applied uniformly worldwide by the CWP and by the national authorities reporting to its member organizations. Therefore, though the quality of the data varies from country to country (being in many cases a function of the general characteristics of the national fishing industry), there is a high degree of comparability between countries and over time.  Nominal catch  The data refer to the catch of freshwater, brackish water and marine species of fish, crustaceans, molluscs and other aquatic animals and plants, killed, caught, trapped or collected for all commercial, industrial, recreational and subsistence purposes. In view of the importance of recreational fishing regarding some stocks and for certain countries, as well as the difficulty of distinguishing between recreational and subsistence fishing, the data should include the catches from recreational fisheries as well. However, it is recognised that certain countries are unable to supply the data for recreational fisheries. The catches are expressed in the live weight equivalent of the landings. As such they exclude all quantities caught but not landed (for example: discarded fish, fish consumed on board). The unit used is generally the metric ton. Data for marine mammals (e.g. whales) and certain other animals (e.g. crocodiles) are expressed in the number caught. The nominal catch data are normally derived from the landed quantities of the fishery products. For this purpose, the landed weight is converted to the live weight equivalent (nominal catch) by the application of factors. Species: All species for which catches are reported to international organizations are included in the Eurostat's database. They are identified by the internationally assigned three letter identifier (e.g. COD = Atlantic cod, PLE = European plaice) according to the FAO ASFIS (Aquatic Sciences and Fishery Information System) list of Species for Fishery Statistics Purposes. Fishing areas/regions: The catches are sub-divided by the area in which they occur. The methodologies vary from country to country depending on the nature of their fishing industries. Basic documentation used in collecting the data from EU fisheries are fishing log-books, landings declarations and sales notes used in the management of catch quota and market management systems within the Common Fisheries Policy. The methodologies used by EEA member countries have been described in the Eurostat publication "Fisheries: The collection and compilation of fish catch and landing statistics in member countries of the European Economic Area". Those used by the New Member States are described in a working document "Fisheries: The collection and compilation of fishery statistics in European Union Candidate Countries"
    • Январь 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 мая, 2014
      Выбрать
      Eurostat Dataset Id:hlth_cd_ynrf 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, and cause of death. 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.
    • Январь 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 мая, 2014
      Выбрать
      Eurostat Dataset Id:hlth_cd_ynrm 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, and cause of death. 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.
    • Январь 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 мая, 2014
      Выбрать
      Eurostat Dataset Id:hlth_cd_ynrt 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, and cause of death. 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.
    • Июнь 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 21 августа, 2013
      Выбрать
      Notes: Eurostat Hierarchy: General and regional statistics > Population and social conditions > Health (health) > Public health (hlth) > Causes of death (hlth_cdeath).
    • Апрель 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 мая, 2014
      Выбрать
      Eurostat Dataset Id:hlth_cd_ycdrt 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, and cause of death. 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.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 03 декабря, 2018
      Выбрать
      Note:  The updates and revisions for the OECD Central Government Debt Database have been suspended. This dataset is no longer updated. For more info, please read http://stats.oecd.org/Index.aspx?DataSetCode=GOV_DEBT   Statistical population The focus of this dataset is to provide comprehensive quantitative information on marketable and non-marketable central government debt instruments in all OECD member countries. The coverage of the data is limited to central government debt issuance and excludes therefore state and local government debt and social security funds.
    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 28 февраля, 2019
      Выбрать
      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 Commissions in the reporting country, containing a breakdown between domestic companies, foreign-controlled companies and branches and agencies of foreign companies.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 03 декабря, 2018
      Выбрать
      The OECD Science, Technology and Industry Outlook 2012 presents, in a series of country profiles, the main features, strengths and weaknesses of national STI systems and major recent changes in national STI policy. The statistical dimension of the country profiles has drawn on the work and empirical research conducted by the OECD on the measurement of innovation and the development of internationally comparable STI indicators for policy analysis.   
    • Декабрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 мая, 2014
      Выбрать
      Eurostat Dataset Id:educ_bo_ou_comp 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. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The completion rate (educ_bo_ou_comp) was computed in the framework of the UOE data collection (jointly carried out by Unesco, OECD and Eurostat), but is usually disseminated by OECD only. The methodology for estimating completion rates varies across countries. They can use three methods: the cross-section method, the true cohort method, or the synthetic cohort method (see section 11.1 below for more details). The year of reference gives the reference year for the number of graduates. The estimation assumes constant student flows at the tertiary level, owing to the need for consistency between the graduate cohort in the reference year and the entrant cohort n years before. This assumption may be an oversimplification. Results are less reliable in systems in which enrolments fluctuate markedly, or students are faced with many different options as regards the length of courses for which they may enrol or in which there are many changes in programmes between the years of admission and graduation respectively. The inclusion of foreign students in the new entrant questionnaire can have an impact on the completion rates indicator. In some countries, the proportion of foreign students represents a large part of tertiary population, and all of them are considered as new entrants in tertiary education (as advised in UOE Guidelines) whereas most of them won't be graduated at this level of education. The consequence is to underestimate the completion rates in those countries with relatively large proportions of foreign students enrolled in tertiary education.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_inf7 General description of the ad hoc modules supplementing the Labour Force Survey (LFS)
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_inf6 General description of the ad hoc modules supplementing the Labour Force Survey (LFS)
    • Март 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 14 ноября, 2013
      Выбрать
      Eurostat Dataset Id:iww_go_actygf07 Eurostat collects the following statistics on inland waterway transport:Transport of goods (annual and quarterly mandatory data provision).Vessel traffic (annual optional data provision);Transport of dangerous goods (annual voluntary data provision)Number of accidents (annual voluntary data provision) The data collection of inland waterways freight transport statistics is based on the framework Regulation 1365/2006 of the European Parliament and the Council and on the implementing Commission Regulations 425/2007 and 1304/2007. This legislation has come into force on 1 January 2007. Before that time, the data collection of inland waterways transport statistics was based on Council Directive 80/1119/EEC, which followed a similar but not identical methodology. For this reason, only time series with good data compatibility between the old and the new legislation are shown in this domain. According to the current Regulation, Member States where the total volume of goods transported annually by inland waterways as national, international or transit transport exceeds one million tons have to transmit the requested information. Member States where there is no international or transit inland waterways transport but where the total volume of goods transported annually by inland waterways as national transport exceeds one million tons have to transmit a reduced amount of data.
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 марта, 2019
      Выбрать
      Eurostat Dataset Id:educ_igen The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes by pupils and students, personnel in education and the cost and type of resources dedicated to education. The standards on international statistics on education and training systems are set by the three international organisations jointly administering the UOE data collection:the United Nations Educational, Scientific, and Cultural Organisation Institute for Statistics (UNESCO-UIS),the Organisation for Economic Co-operation and Development (OECD) and,the Statistical Office of the European Union (EUROSTAT). The following topics are covered:Context - School-aged population, overall participation rates in educationDistribution of pupils/students by levelParticipation/enrolment in education (ISCED 0-4)Tertiary education participationTertiary education graduatesTeaching staff (ISCED 1-3)Pupil/students-teacher ratio and average class size (ISCED 1-3)Language learning (ISCED 1-3)Regional enrolmentsExpenditure on education in current pricesExpenditure on education in constant pricesExpenditure on education as % of GDP or public expenditureExpenditure on public and private educational institutionsFinancial aid to studentsFunding of education Other tables, used to measure progress towards the Lisbon objectives in education and training, are gathered in the Thematic indicators tables. They contain the following indicators: - Teachers and trainers - Mathematics, science and technology enrolments and graduates - Investments in education and training - Participation rates in education by age and sex - Foreign language learning - Student mobility
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 апреля, 2014
      Выбрать
      Eurostat Dataset Id:orch_appothus The Orchard survey domain (orch) contains the results of the surveys of areas under certain species of fruit trees (apple, pear, peach, apricot, orange, lemon, small citrus fruit). The statistical surveys on orchards are carried out every five years by the Member States in order to determine the production potential of plantations of certain species of fruit trees. These surveys have been carried out since 1977. The results presented in this database provide areas (in hectares) by variety and age and density classes by country and by production region.Data are grouped in tables by fruit tree species. The following species are surveyed: a) apple trees for dessert apples (in the 27 EU member states, except Malta), b) pear trees for dessert pears (in the 27 EU member states, except Estonia, Ireland, Malta and Finland), c) peache trees (in Bulgaria, Czech republic, Greece, Spain, France, Italy, Cyprus, Hungary, Malta, Austria, Poland, Portugal, Romania, Slovenia and Slovakia only), d) apricot trees (in Bulgaria, Czech republic, Greece, Spain, France, Italy, Cyprus, Hungary, Austria, Poland, Portugal, Romania, Slovenia and Slovakia only), e) orange trees (in Greece, Spain, France, Italy, Cyprus and Portugal only), f) lemon trees (in Greece, Spain, France, Italy, Cyprus and Portugal only), g) small-citrus fruit trees (in Greece, Spain, France, Italy, Cyprus and Portugal only). The latter group (small-citrus fruit trees, including tangerines and satsumas; clementines, wilkings and other similar citrus hybrids) is considered as a single species. Data on plantations producing apples and pears for uses other than dessert fruit were sent optionally by some countries from 1987 onwards. The species of fruit and the varieties are listed in Annex III to Commission Decision (EC) No 38/2002.
    • Январь 2019
      Источник: Transparency International
      Загружен: Pallavi S
      Дата обращения к источнику: 01 февраля, 2019
      Выбрать
      Data cited at CORRUPTION PERCEPTIONS INDEX 2018 by Transparency International is licensed under CC-BY-ND 4.0. Global Corruption Barometer is the largest world-wide public opinion survey on corruption. see more at https://www.transparency.org/cpi2018 Transparency International(TI) defines corruption as the abuse of entrusted power for private gain. This definition encompasses corrupt practices in both the public and private sectors. The Corruption Perceptions Index (CPI) ranks countries according to the perception of corruption in the public sector. The CPI is an aggregate indicator that combines different sources of information about corruption, making it possible to compare countries. The CPI ranks almost 200 countries by their perceived levels of corruption, as determined by expert assessments and opinion surveys.
    • Январь 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 11 июля, 2014
      Выбрать
      Eurostat Dataset Id:trng_cvts62 CVTS2, CVTS3 and CVTS4 data were collected with reference year 1999, 2005 and 2010 in order to provide harmonised, reliable and relevant statistical information on continuing vocational training in enterprises.CVT stands for continuing vocational training i.e. education and training occurring during paid working time or paid at least partially by employers (if training activities are organised outside paid working time). CVTS 2, 3 and 4 provide statistics on incidence of training in enterprises, participation of employees and volume of CVT courses, CVT costs as well as CVT strategies of enterprises including on Initial vocational training (IVT, i.e. apprenticeship). The section "past series on lifelong learning" presents tables which are no longer available in the same format or at the same level of precision as CVTS 4. The CVTS1 was the first survey on continuing vocational training in enterprises carried out on the EU level in a co-ordinated form (outline questionnaire, common definitions, and common recommendations with the respect to the fieldwork). The survey was of pioneering nature, and is not any longer disseminated due to lack of comparability with the following waves.
    • Январь 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 06 июля, 2014
      Выбрать
      Eurostat Dataset Id:trng_cvts64 CVTS2, CVTS3 and CVTS4 data were collected with reference year 1999, 2005 and 2010 in order to provide harmonised, reliable and relevant statistical information on continuing vocational training in enterprises.CVT stands for continuing vocational training i.e. education and training occurring during paid working time or paid at least partially by employers (if training activities are organised outside paid working time). CVTS 2, 3 and 4 provide statistics on incidence of training in enterprises, participation of employees and volume of CVT courses, CVT costs as well as CVT strategies of enterprises including on Initial vocational training (IVT, i.e. apprenticeship). The section "past series on lifelong learning" presents tables which are no longer available in the same format or at the same level of precision as CVTS 4. The CVTS1 was the first survey on continuing vocational training in enterprises carried out on the EU level in a co-ordinated form (outline questionnaire, common definitions, and common recommendations with the respect to the fieldwork). The survey was of pioneering nature, and is not any longer disseminated due to lack of comparability with the following waves.
    • Ноябрь 2014
      Источник: Central Agency for Public Mobilization and Statistics of Egypt
      Загружен: Knoema
      Дата обращения к источнику: 10 декабря, 2014
      Выбрать
    • Июль 2016
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 29 июля, 2016
      Выбрать
      Country Programmable Aid (CPA), outlined in our Development Brief  and also known as “core” aid, is the portion of aid donors programme for individual countries, and over which partner countries could have a significant say. CPA is much closer than ODA to capturing the flows of aid that goes to the partner country, and has been proven in several studies to be a good proxy of aid recorded at country level. CPA was developed in 2007 in close collaboration with DAC members. It is derived on the basis of DAC statistics and was retroactively calculated from 2000 onwards
    • Март 2012
      Источник: Knoema
      Загружен: Knoema
      Выбрать
      Country Risk Assessment Database, 2012. Source: Multiple Sources - EuroStat, WB, IMF, OECD, UNCTAD
    • Декабрь 2018
      Источник: United Nations Office on Drugs and Crime
      Загружен: Knoema
      Дата обращения к источнику: 05 апреля, 2019
      Выбрать
      UNODC Assaults, Kidnapping, Robbery, Sexual Offences, Sexual Rape, Total Sexual Violence   Statistics reported to the United Nations in the context of its various surveys on crime levels and criminal justice trends are incidents of victimization that have been reported to the authorities in any given country. That means that this data is subject to the problems of accuracy of all official crime data.
    • Декабрь 2018
      Источник: European Commission
      Загружен: Shakthi Krishnan
      Дата обращения к источнику: 02 апреля, 2019
      Выбрать
      Notes: 1.Cost of crude oil imports and deliveries from other Member States, for purposes other than transit and intended to cover the needs of a Member State, and crude oil produced and refined in a Member State, whose production is more than 15 % of its annual crude oil supply. 2.The cif price includes the fob price (the price actually invoiced at the port of loading), the cost of transport, insurance and certain charges linked to crude oil transfer operations. The import value of the crude oil produced in a Member State is to be calculated free at port of discharge or free at frontier.
  • D
    • Март 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 июля, 2012
      Выбрать
      This dataset contains 12 tables. Debt securities of euro area residents: euro-denominated issues - Annual data (mny_bmk_erseu_a); Debt securities of euro area residents: euro-denominated issues - Quarterly data (mny_bmk_erseu_q); Debt securities of euro area residents: euro-denominated issues - Monthly data (mny_bmk_erseu_m); Debt securities of euro area residents: issues in other currencies - Annual data (mny_bmk_erscu_a); Debt securities of euro area residents: issues in other currencies - Quarterly data (mny_bmk_erscu_q); Debt securities of euro area residents: issues in other currencies - Monthly data (mny_bmk_erscu_m); Debt securities of euro area residents: issues in all currencies - Annual data (mny_bmk_ersto_a); Debt securities of euro area residents: issues in all currencies - Quarterly data (mny_bmk_ersto_q); Debt securities of euro area residents: issues in all currencies - Monthly data (mny_bmk_ersto_m); Debt securities of non-euro area residents: euro-denominated issues - Annual data (mny_bmk_ners_a); Debt securities of non-euro area residents: euro-denominated issues - Quarterly data (mny_bmk_ners_q); Debt securities of non-euro area residents: euro-denominated issues - Monthly data (mny_bmk_ners_m). Note: Eurostat Hierarchy : Economy and finance > Monetary and other financial statistics (mny) > Debt securities of euro area residents (mny_bmk_ers)
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 апреля, 2014
      Выбрать
      Eurostat Dataset Id:med_ec7 The focus of this domain is on the following countries:Algeria, Egypt, Israel, Jordan, Lebanon, Morocco, Palestinian Authority, Syria, Tunisia. Data are provided for over 1000 indicators depending on the country.   The data for the Mediterranean partner countries are supplied by and under the responsibility of the national statistical authorities  of each of the countries or territories. The data and their denomination in no way constitute the  expression of an opinion by the European Commission on the  legal status of a country or territory or on the delimitation of its frontiers. Â
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 09 июля, 2019
      Выбрать
      This dataset contains three earnings-dispersion measures - ratio of 9th-to-1st, 9th-to-5th and 5th-to-1st - where ninth, fifth (or median) and first deciles are upper-earnings decile limits, unless otherwise indicated, of gross earnings of full-time dependent employees. The dataset also includes series on: the incidence of low-paid workers defined as the share of full-time workers earning less than two-thirds of gross median earnings of all full-time workers; the incidence of high of high-paid workers defined as the share of full-time workers earning more than one-and-half time gross median earnings of all full-time workers; gender wage gap unadjusted and defined as the difference between median wages of men and women relative to the median wages of men.
    • Декабрь 2007
      Источник: International Telecommunication Union
      Загружен: Knoema
      Дата обращения к источнику: 23 мая, 2019
      Выбрать
      The Digital Opportunity Index (DOI) is the only index that includes price data for 181 economies, which is vital in assessing effective market demand. The Digital Opportunity Index (DOI) has been designed to as a tool for tracking progress in bridging the digital divide and the implementa- tion of the outcomes of the World Summit on the Information Society (WSIS). As such, it provides a powerful policy tool for exploring the global and regional trends in infrastructure, opportu- nity and usage that are shaping the Information Society.
    • Июль 2015
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 08 октября, 2015
      Выбрать
      This table contains data on discouraged workers who are persons not in the labour force who believe that there is no work available due to various reasons and who desire to work. Data are broken down by sex and standardised age groups (15-24, 15-64, 25-54, 55-64, 65+, total).
    • Декабрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 мая, 2014
      Выбрать
      Eurostat Dataset Id:educ_bo_ou_mism The Bologna declaration was signed in 1999 by 29 European ministers responsible for higher education. Today, 46 signatory countries are engaged in the process towards a European Higher Education Area (EHEA). The Bologna Process is an intergovernmental initiative which also involves the European Commission, the Council of Europe and UNESCO-CEPES, as well as representatives of higher education institutions, students, staff, employers and quality assurance agencies. It aims to create a European Higher Education Area by 2010, and to promote the European system of higher education worldwide. More information on the Bologna process is available on http://ec.europa.eu/education/higher-education/doc1290_en.htm. In the framework of the indicators for the monitoring of the social dimension and mobility of the Bologna Process, the EU-SILC (EU Statistics on Income and Living Conditions) data of interest cover individual's educational attainment, income and, from the intergenerational transmission of poverty ad hoc module, educational attainment of the parents. The following data-sets, having EU-SILC as source, on the Bologna Process are available: A. Widening access educ_bo_ac_sobs: Individuals having completed tertiary education (ISCED 5-6), according to the educational background of their parents, by sexeduc_bo_ac_soba: Individuals having completed tertiary education (ISCED 5-6), according to the educational background of their parents, by age D. Effective outcomes and employability educ_bo_ou_attd: Annual gross income of workers by educational attainment (2006)educ_bo_ou_terd: Annual gross income of workers with tertiary education (ISCED 5-6) , by sex (2006) The general aim of the EU-SILC domain is to provide comparable statistics and indicators on key aspects of the citizens' living conditions across Europe. This domain actually contains a range of social statistics and indicators relating to the risks of income poverty and social exclusion. There are both conceptual and methodological problems in defining and measuring income poverty and social exclusion. Since a 1984 decision of the European Council, the following are regarded as poor: "those persons, families and groups of persons whose resources (material, cultural and social) are so limited as to exclude them from the minimum acceptable way of life in the Member State to which they belong". On this basis, measures of poverty at EU level adopt an approach which is both multi-dimensional and relative. In June 2006, a new set of common indicators for the social protection and social inclusion process was adopted. (For more details and definitions of these indicators: Indicators 2006). To investigate particular areas of policy interest in more detail, target secondary areas, to be collected every four years or less frequently, are added to the cross-sectional component of EU-SILC. "The intergenerational transmission of poverty" was chosen as the area to be implemented for 2005. This specific module, collected in 2005, had as purpose to collect and compile relevant and robust information on background factors linked to adult social exclusion, minimising the burden of respondents to provide accurate detailed indicators sufficiently comparable across the EU capturing the effects of childhood experiences on poverty risk. More general information on EU-SILC is available on ilc_base.htm
    • Ноябрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 23 июня, 2014
      Выбрать
      Eurostat Dataset Id:ilc_lvph02h 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.
    • Декабрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 мая, 2014
      Выбрать
      Eurostat Dataset Id:educ_bo_ou_mity 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. The REFLEX project (standing for 'Research into Employment and professional FLEXibility') is a large scale international project that has been carried out in 16 different countries. It focuses on the demands that the modern knowledge society places on higher education graduates, and the degree to which higher education equips gradu­ates with the competencies to meet these demands. Specifically, it consists of a follow-up of the careers of highly skilled professionals who graduated in 2000. Data reported here refer to the 2005 survey and therefore focus on graduates from higher education (ISCED 5A, bachelor's and master's degree or equivalent) with more or less 5 years of experience since leaving higher education. This includes foreign students who graduated in the reference country, students who after graduation moved to another country, part-time students, distance learners, etc. For operational reasons, graduation cohorts instead of outflow cohorts were sampled, due to the lack of good registers in countries on who stayed in education and who did not. Some graduates continue their studies in higher education and enter the labour market a few years later. They will therefore have less than 5 years of experience and cannot directly be compared with graduates who entered the labour market immediately after graduation. The project focused on the careers of highly skilled professionals. The first ten years of these careers follow more or less the following pattern: an initial phase of transition to the labour market in which the focus is on searching for a job and integrating the labour market, a second phase in which essential professional expertise is gained and career patterns start to crystallise and a third phase in which graduates assume greater responsibility on the basis of their increasing professional expertise. Appropriate moments to survey these careers should correspond more or less with the transitions between these phases. Specifically, mismatch between qualification and occupation was measured in self report (what the respondent thinks about his/her job), and indirectly assessed through the two following questions: -         What type of education do you feel was most appropriate for this work? -         What field of study do you feel was most appropriate for this work? The first one was considered with regard to the achieved level of education in order to measure the vertical mismatch (between the actual skill level and the required one), while the second one was used to determine the horizontal mismatch (being at the relevant skill level, but in another field than that of graduation).
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 марта, 2019
      Выбрать
      Eurostat Dataset Id:educ_ilev The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes by pupils and students, personnel in education and the cost and type of resources dedicated to education. The standards on international statistics on education and training systems are set by the three international organisations jointly administering the UOE data collection:the United Nations Educational, Scientific, and Cultural Organisation Institute for Statistics (UNESCO-UIS),the Organisation for Economic Co-operation and Development (OECD) and,the Statistical Office of the European Union (EUROSTAT). The following topics are covered:Context - School-aged population, overall participation rates in educationDistribution of pupils/students by levelParticipation/enrolment in education (ISCED 0-4)Tertiary education participationTertiary education graduatesTeaching staff (ISCED 1-3)Pupil/students-teacher ratio and average class size (ISCED 1-3)Language learning (ISCED 1-3)Regional enrolmentsExpenditure on education in current pricesExpenditure on education in constant pricesExpenditure on education as % of GDP or public expenditureExpenditure on public and private educational institutionsFinancial aid to studentsFunding of education Other tables, used to measure progress towards the Lisbon objectives in education and training, are gathered in the Thematic indicators tables. They contain the following indicators: - Teachers and trainers - Mathematics, science and technology enrolments and graduates - Investments in education and training - Participation rates in education by age and sex - Foreign language learning - Student mobility
    • Сентябрь 2012
      Источник: Americans for Divorce Reform
      Загружен: Knoema
      Выбрать
      Divorce Indicators across countries
    • Декабрь 2008
      Источник: Institute for Health Metrics and Evaluation
      Загружен: Peter Speyer
      Выбрать
      IHME research, published in the Lancet in 2008. The study, Tracking progress towards universal childhood immunizations and the impact of global initiatives, provides estimates with confidence intervals of the coverage of three-dose diphtheria, tetanus, and pertussis (DTP3) vaccination. The estimates take into account all publicly available data, including data from routine reporting systems and nationally representative surveys.
  • E
    • Июль 2013
      Источник: Earth Policy Institute
      Загружен: Knoema
      Дата обращения к источнику: 08 июля, 2013
      Выбрать
      Contains annual data series on water consumption, irrigated area, solar water and space heating area, countries overpumping aquifers and water deficits for the countries and regions through the time period from 1961 to 2013.
    • Январь 2010
      Источник: European Commission
      Загружен: Knoema
      Выбрать
      EU Energy in figures 2010, CO2 Emissions by Sector and from Transport by mode.
    • Июнь 2014
      Источник: European Commission
      Загружен: Knoema
      Дата обращения к источнику: 29 августа, 2014
      Выбрать
      This dataset provides an overview of the most recent and pertinent annual energy related statistics in Europe. The data is drawn from several sources: the European Commission’s services; international organisations, such as the European Environment Agency and the International Energy Agency and, where no data is currently available, from the European Commission’s estimations. The indicator calculations follow the methodology established by the European Commission - DG Energy.
    • Январь 2010
      Источник: European Commission
      Загружен: Knoema
      Выбрать
      EU Energy in figures 2010, GHG Emissions by Sector and from Transport by mode.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 03 декабря, 2018
      Выбрать
      This table contains data on economic short-time workers by professional status (employees or total employment). Economic short-time workers comprise workers who are working less than usual due to business slack, plant stoppage, or technical reasons. However, the definitions are not harmonised which hampers the comparison across countries. Data are broken down professional status - employees, total employment - by sex and by standardised age groups (15-24, 25-54, 55+, total).
    • Декабрь 2012
      Источник: Liberia Institute of Statistics & Geo-Information Services
      Загружен: Knoema
      Дата обращения к источнику: 21 мая, 2013
      Выбрать
    • Декабрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 мая, 2014
      Выбрать
      Eurostat Dataset Id:educ_bo_ou_att 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. Bologna indicators on tertiary education attainment, occupational mismatch and unemployment are based for most of the countries on the results of the European Labour Force Survey (EU-LFS). For some countries not participating in the EU-LFS data collection, data were provided by their NSI and rely upon national household surveys.   The EU-LFS is a quarterly household sample survey carried out in the Member States of the European Union, Candidate Countries and EFTA countries (except for Liechtenstein). It is the main source of information about the situation and trends on the labour market in the European Union. The EU-LFS is organised in 12 modules covering demographic background, labour status, employment characteristics of the main job, atypical work, working time, employment characteristics of the second job, previous work experience of persons not in employment, search for employment, main labour status, education and training, situation one year before the survey and income. The survey's target population consists of all persons in private households, although the variables related to labour market are only collected for persons aged 15 years or older. For details see Council Regulation (EC) No 577/98 of 9 March 1998 on the organisation of a labour force sample survey in the Community (OJ No L 77/3). Since 1999 an inherent part of the European Union EU-LFS are the so called 'ad-hoc modules'. Detailed information regarding the survey methods, organization and comparability issues is available on the EU-LFS webpage. The following datasets are available with indicators on tertiary education attainment, occupational mismatch and unemployment used for the monitoring of the Bologna Process namely on effective outcomes and employability: educ_bo_ou_att: Population with tertiary education (ISCED 5-6), by sex and ageeduc_bo_ou_attf: Population with tertiary education (ISCED 5-6) aged 25-39, by field of study and sexeduc_bo_ou_ured: Unemployment rate of people aged 20-34, by sex and educational attainmenteduc_bo_ou_ursy: Unemployment rate of people with tertiary education (ISCED 5-6) aged 20-34, by sex and number of years since graduationeduc_bo_ou_urfi: Unemployment rate of people with tertiary education (ISCED 5-6), by field of study and ageeduc_bo_ou_mism: People with tertiary education (ISCED 5-6) aged 25-34 and employed in ISCO 1 or 2, in ISCO3, and not in ISCO 1|2|3, by sexeduc_bo_ou_mifi: People aged 25-34 with tertiary education (ISCED 5-6) being vertically mismatched, by field of study and sex As regards some countries, data on tertiary education attainment, occupational mismatch and unemployment were provided outside the framework of the LFS data collection and therefore cannot be considered to be always fully comparable due to differences in the underlying data sources and definitions. This parallel collection was carried out in January 2009 with some Bologna countries that have not participated in the EU-LFS data collection. Data, as well as some metadata, were collected in Armenia (AM), Moldova (MD), Serbia (RS) and Russia (RU): Armenia (AM): (indicators educ_bo_ou_att, educ_bo_ou_ured). Data provided by the National Statistical Service. Surveys: "LFS" and "ILCS". LFS for 2007 has been conducted within the frame of ILCS with a reduced number of questions;Moldova (MD): (indicators educ_bo_ou_att, educ_bo_ou_ured, educ_bo_ou_mism). Data provided by the National Bureau of Statistics. Survey: "LFS";Serbia (RS): (indicators educ_bo_ou_att, educ_bo_ou_attf, educ_bo_ou_ured, educ_bo_ou_ursy, educ_bo_ou_urfi, educ_bo_ou_mism). Data provided by the Statistical Office of the Republic of Serbia. Survey: "LFS";Russia (RU): (indicators educ_bo_ou_urgaed, educ_bo_ou_mism). Data provided by the Federal State Statistics Service. Survey: "Survey on employment".
    • Декабрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 мая, 2014
      Выбрать
      Eurostat Dataset Id:educ_bo_ou_attf 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. Bologna indicators on tertiary education attainment, occupational mismatch and unemployment are based for most of the countries on the results of the European Labour Force Survey (EU-LFS). For some countries not participating in the EU-LFS data collection, data were provided by their NSI and rely upon national household surveys.   The EU-LFS is a quarterly household sample survey carried out in the Member States of the European Union, Candidate Countries and EFTA countries (except for Liechtenstein). It is the main source of information about the situation and trends on the labour market in the European Union. The EU-LFS is organised in 12 modules covering demographic background, labour status, employment characteristics of the main job, atypical work, working time, employment characteristics of the second job, previous work experience of persons not in employment, search for employment, main labour status, education and training, situation one year before the survey and income. The survey's target population consists of all persons in private households, although the variables related to labour market are only collected for persons aged 15 years or older. For details see Council Regulation (EC) No 577/98 of 9 March 1998 on the organisation of a labour force sample survey in the Community (OJ No L 77/3). Since 1999 an inherent part of the European Union EU-LFS are the so called 'ad-hoc modules'. Detailed information regarding the survey methods, organization and comparability issues is available on the EU-LFS webpage. The following datasets are available with indicators on tertiary education attainment, occupational mismatch and unemployment used for the monitoring of the Bologna Process namely on effective outcomes and employability: educ_bo_ou_att: Population with tertiary education (ISCED 5-6), by sex and ageeduc_bo_ou_attf: Population with tertiary education (ISCED 5-6) aged 25-39, by field of study and sexeduc_bo_ou_ured: Unemployment rate of people aged 20-34, by sex and educational attainmenteduc_bo_ou_ursy: Unemployment rate of people with tertiary education (ISCED 5-6) aged 20-34, by sex and number of years since graduationeduc_bo_ou_urfi: Unemployment rate of people with tertiary education (ISCED 5-6), by field of study and ageeduc_bo_ou_mism: People with tertiary education (ISCED 5-6) aged 25-34 and employed in ISCO 1 or 2, in ISCO3, and not in ISCO 1|2|3, by sexeduc_bo_ou_mifi: People aged 25-34 with tertiary education (ISCED 5-6) being vertically mismatched, by field of study and sex As regards some countries, data on tertiary education attainment, occupational mismatch and unemployment were provided outside the framework of the LFS data collection and therefore cannot be considered to be always fully comparable due to differences in the underlying data sources and definitions. This parallel collection was carried out in January 2009 with some Bologna countries that have not participated in the EU-LFS data collection. Data, as well as some metadata, were collected in Armenia (AM), Moldova (MD), Serbia (RS) and Russia (RU): Armenia (AM): (indicators educ_bo_ou_att, educ_bo_ou_ured). Data provided by the National Statistical Service. Surveys: "LFS" and "ILCS". LFS for 2007 has been conducted within the frame of ILCS with a reduced number of questions;Moldova (MD): (indicators educ_bo_ou_att, educ_bo_ou_ured, educ_bo_ou_mism). Data provided by the National Bureau of Statistics. Survey: "LFS";Serbia (RS): (indicators educ_bo_ou_att, educ_bo_ou_attf, educ_bo_ou_ured, educ_bo_ou_ursy, educ_bo_ou_urfi, educ_bo_ou_mism). Data provided by the Statistical Office of the Republic of Serbia. Survey: "LFS";Russia (RU): (indicators educ_bo_ou_urgaed, educ_bo_ou_mism). Data provided by the Federal State Statistics Service. Survey: "Survey on employment".
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 19 марта, 2019
      Выбрать
      Eurostat Dataset Id:educ_regind The aim of this section is to provide comparable statistics and indicators on education in the 27 Member States of the European Union, at the regional level NUTS 2. In order to facilitate comparison between countries, data from each Member State are allocated to the various education levels of the International Standard Classification of Education (ISCED), UNESCO 1997.
    • Декабрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 мая, 2014
      Выбрать
      Eurostat Dataset Id:educ_bo_ou_mifi 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. Bologna indicators on tertiary education attainment, occupational mismatch and unemployment are based for most of the countries on the results of the European Labour Force Survey (EU-LFS). For some countries not participating in the EU-LFS data collection, data were provided by their NSI and rely upon national household surveys.   The EU-LFS is a quarterly household sample survey carried out in the Member States of the European Union, Candidate Countries and EFTA countries (except for Liechtenstein). It is the main source of information about the situation and trends on the labour market in the European Union. The EU-LFS is organised in 12 modules covering demographic background, labour status, employment characteristics of the main job, atypical work, working time, employment characteristics of the second job, previous work experience of persons not in employment, search for employment, main labour status, education and training, situation one year before the survey and income. The survey's target population consists of all persons in private households, although the variables related to labour market are only collected for persons aged 15 years or older. For details see Council Regulation (EC) No 577/98 of 9 March 1998 on the organisation of a labour force sample survey in the Community (OJ No L 77/3). Since 1999 an inherent part of the European Union EU-LFS are the so called 'ad-hoc modules'. Detailed information regarding the survey methods, organization and comparability issues is available on the EU-LFS webpage. The following datasets are available with indicators on tertiary education attainment, occupational mismatch and unemployment used for the monitoring of the Bologna Process namely on effective outcomes and employability: educ_bo_ou_att: Population with tertiary education (ISCED 5-6), by sex and ageeduc_bo_ou_attf: Population with tertiary education (ISCED 5-6) aged 25-39, by field of study and sexeduc_bo_ou_ured: Unemployment rate of people aged 20-34, by sex and educational attainmenteduc_bo_ou_ursy: Unemployment rate of people with tertiary education (ISCED 5-6) aged 20-34, by sex and number of years since graduationeduc_bo_ou_urfi: Unemployment rate of people with tertiary education (ISCED 5-6), by field of study and ageeduc_bo_ou_mism: People with tertiary education (ISCED 5-6) aged 25-34 and employed in ISCO 1 or 2, in ISCO3, and not in ISCO 1|2|3, by sexeduc_bo_ou_mifi: People aged 25-34 with tertiary education (ISCED 5-6) being vertically mismatched, by field of study and sex As regards some countries, data on tertiary education attainment, occupational mismatch and unemployment were provided outside the framework of the LFS data collection and therefore cannot be considered to be always fully comparable due to differences in the underlying data sources and definitions. This parallel collection was carried out in January 2009 with some Bologna countries that have not participated in the EU-LFS data collection. Data, as well as some metadata, were collected in Armenia (AM), Moldova (MD), Serbia (RS) and Russia (RU): Armenia (AM): (indicators educ_bo_ou_att, educ_bo_ou_ured). Data provided by the National Statistical Service. Surveys: "LFS" and "ILCS". LFS for 2007 has been conducted within the frame of ILCS with a reduced number of questions;Moldova (MD): (indicators educ_bo_ou_att, educ_bo_ou_ured, educ_bo_ou_mism). Data provided by the National Bureau of Statistics. Survey: "LFS";Serbia (RS): (indicators educ_bo_ou_att, educ_bo_ou_attf, educ_bo_ou_ured, educ_bo_ou_ursy, educ_bo_ou_urfi, educ_bo_ou_mism). Data provided by the Statistical Office of the Republic of Serbia. Survey: "LFS";Russia (RU): (indicators educ_bo_ou_urgaed, educ_bo_ou_mism). Data provided by the Federal State Statistics Service. Survey: "Survey on employment".
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 02 июля, 2019
      Выбрать
      The classification of personnel is based on functions and organises staff into four main functional categories: 1) Instructional Personnel; including two sub-groups: A. Classroom Teachers (ISCED 0-4) and Academic Staff (ISCED 5-6); and B. Teacher Aides (ISCED 0-4) and Teaching / Research Assistants (ISCED 5-6); 2) Professional Support for Students; including two sub-groups: A. Pedagogical Support (ISCED 0-4) and Academic Support (ISCED 5-6); B. Health and Social Support (ISCED 0-6); 3) Management/Quality Control/Administration; including four subgroups: A. School Level Management (ISCED 0-6); B. Higher Level Management (ISCED 0-6); C. School Level Administrative Personnel (ISCED 0-6); and D. Higher Level Administrative Personnel (ISCED 0-6); 4) Maintenance and Operations Personnel.
    • Июль 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 05 августа, 2014
      Выбрать
      The Pensions at a Glance indicators, covering all 34 OECD countries, are designed to show future entitlements for workers who entered the labour market in 2008 and spend their entire working lives under the same set of rules. The results presented here include all mandatory pension schemes for private-sector workers, regardless of whether they are public or private.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_06yrspisco Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'.
    • Июнь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2019
      Выбрать
      Eurostat Dataset Id:bd_9fh_sz_cl_r2 The data category covers a group of variables which explain the characteristics and demography of the business population. The methodology allows for the production of data on enterprise births (and deaths), that is, enterprise creations (cessations) that amount to the creation (dissolution) of a combination of production factors and where no other enterprises are involved. In other words, enterprises created or closed solely as a result of e.g. restructuring, merger or break-up are not included in this data. Until 2010 reference year the harmonised data collection is carried out to satisfy the requirements for the Structural Indicators, used for monitoring progress of the Lisbon process, regarding business births, deaths and survival. It also provides key data for the joint OECD-Eurostat "Entrepreneurship Indicators Programme". In summary, the collected indicators are as follows:Population of active enterprisesNumber of enterprise birthsNumber of enterprise survivals up to five yearsNumber of enterprise deathsRelated variables on employmentDerived indicators such as birth rates, death rates, survival rates and employment sharesAn additional set of indicators on high-growth enterprises and 'gazelles' (high-growth enterprises that are up to five years old) The data are drawn from business registers, although some individual countries improve the availability or freshness of data on employment and turnover by integrating other sources. Geographically EU Member States and EFTA countries are covered. In practice not all Member States have participated in the first harmonised data collection exercises.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
      Выбрать
      This table contains data on permanent and temporary workers based on the type of work contract of their main job. Data are further broken down by professional status - employees, total employment - by sex and by standardised age groups (15-19, 15-24, 20-24, 25-54, 55-64, 65+, total). Unit of measure used - Data are expressed in thousands of persons.
    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 21 мая, 2019
      Выбрать
    • Октябрь 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 03 декабря, 2015
      Выбрать
      Eurostat Dataset Id:htec_emp_sbs2 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.
    • Июль 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
      Выбрать
      Eurostat Dataset Id:ei_isen_m Industry, Trade and Services statistics are part of Short-term statistics (STS), they give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification(Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are presented in the following forms: :Unadjusted :Working-day adjusted (Production, Turnover in wholesale and retail trade and other services, Hours worked) :Seasonally-adjusted Data are accessible as monthly and quarterly data. This heading covers the indicators listed below in four different sectors. INDUSTRY Production IndexTurnover Index Producer Prices (Domestic Output Prices index) Import Prices Index: Total, Euro area market, Non euro area market (euro area countries only) Labour Input Indicators: Number of Persons Employed, Hours Worked, Gross Wages and Salaries CONSTRUCTION Production Index: Total of the construction sector, Building construction, Civil Engineering Labour input indicators: Number of Persons Employed, Hours Worked, Gross Wages and Salaries Construction costs Index Building permits indicators: Number of dwellings WHOLESALE AND RETAIL TRADE Volume of sales (deflated turnover) Turnover (in value) Labour input indicators: Number of Persons Employed SERVICES Turnover Index
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent07n There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent07s There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent06n There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent06s There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Январь 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 29 декабря, 2013
      Выбрать
      Eurostat Dataset Id:inn_cis7_type The Community Innovation Survey (CIS) is a survey of innovation activity in enterprises. The harmonised 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, type 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, in close cooperation with the countries, has developed a standard core questionnaire starting with the CIS3 data collection, along with an accompanying set of definitions and methodological recommendations. The concepts and underlying methodology of the CIS are also based on the Oslo Manual — second edition of 1997 and third edition of 2005 . Up to CIS 2010, CIS results were collected under Commission Regulation (EC) No 1450/2004. A new Regulation will apply from CIS 2012 (EC No 995/2012). The data presented in these tables refer to enterprises with ‘10 employees or more’ active in the sectors to be covered under the Regulation (cf. NACE CORE). Further activities may be covered on a voluntary basis. Most statistics are based on a reference period of three years, but some use one calendar year. Since CIS 2008, the survey has included an ad-hoc module. It consists of a set of questions focusing on a special theme. The themes are different in each survey wave, allowing data to be obtained on specific issues beyond the data usually collected. Overview over time: Initially, the CIS data collection was carried out every four years. The first collection (CIS Light) was launched in 1993 as a pilot exercise and the second (CIS2) was carried out in 1997/1998 for most countries except Greece and Ireland, where it was launched in 1999. The third survey (CIS3) was conducted in 2000/2001 for most participating countries with the exception of Norway, Iceland, Luxembourg and Greece, where it was launched in 2002. As from 2004, the survey has been carried out every two years. CIS4 was conducted in the 25 EU Member States (as for 2004), Iceland, Norway, Bulgaria and Romania. The survey was launched in 2005 with a three-year reference period 2002 to 2004 for most indicators. The fifth survey CIS 2006 was carried out in all 25 EU Member States (as for 2006), Norway, Bulgaria, Romania, Croatia and Turkey. It was launched in 2007, mostly for the reference period 2004 to 2006. As regards CIS 2008, 26 Member States (all except Greece), Iceland, Norway, Croatia and Turkey took part in the survey. CIS 2008 was launched in 2009 with a three-year reference period 2006 to 2008 for most indicators. Changes were made to the CIS 2008 questionnaire to bring it into line with the third revision of the Oslo Manual, 2005 edition, by giving greater weight to organisational and marketing innovation. CIS 2008 was complemented by an ad-hoc module on innovation with environmental benefits. The seventh Community Innovation Survey, CIS 2010, had 31 participating countries (all the EU 27 Member States (except Greece), Iceland, Norway, Croatia, Serbia and Turkey) and reported most results for the reference period 2008-2010. CIS 2010 also follows the recommendations of the Oslo Manual and reports indicators on four types of innovation: product, process, organisational and marketing. However, despite implementation of the recommendations of the third edition of the Oslo Manual, the question on innovation expenditures is still limited to product and process innovation in order to maintain continuity with earlier versions of the CIS. Furthermore, generally fewer questions are asked about organisational and marketing innovation than about product and process innovation. 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 the microdata on CD-ROM releases in more anonymised form; some countries also provide access to their micro-data at similar safe centres.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent15n There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent15s There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Январь 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 06 июля, 2014
      Выбрать
      Eurostat Dataset Id:trng_cvts18 CVTS2, CVTS3 and CVTS4 data were collected with reference year 1999, 2005 and 2010 in order to provide harmonised, reliable and relevant statistical information on continuing vocational training in enterprises.CVT stands for continuing vocational training i.e. education and training occurring during paid working time or paid at least partially by employers (if training activities are organised outside paid working time). CVTS 2, 3 and 4 provide statistics on incidence of training in enterprises, participation of employees and volume of CVT courses, CVT costs as well as CVT strategies of enterprises including on Initial vocational training (IVT, i.e. apprenticeship). The section "past series on lifelong learning" presents tables which are no longer available in the same format or at the same level of precision as CVTS 4. The CVTS1 was the first survey on continuing vocational training in enterprises carried out on the EU level in a co-ordinated form (outline questionnaire, common definitions, and common recommendations with the respect to the fieldwork). The survey was of pioneering nature, and is not any longer disseminated due to lack of comparability with the following waves.
    • Август 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 08 сентября, 2014
      Выбрать
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent03bs There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent25 There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent23 There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent24 There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent21 There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent08an There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent08as There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Январь 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 28 мая, 2014
      Выбрать
      Eurostat Dataset Id:trng_cvts07 CVTS2, CVTS3 and CVTS4 data were collected with reference year 1999, 2005 and 2010 in order to provide harmonised, reliable and relevant statistical information on continuing vocational training in enterprises.CVT stands for continuing vocational training i.e. education and training occurring during paid working time or paid at least partially by employers (if training activities are organised outside paid working time). CVTS 2, 3 and 4 provide statistics on incidence of training in enterprises, participation of employees and volume of CVT courses, CVT costs as well as CVT strategies of enterprises including on Initial vocational training (IVT, i.e. apprenticeship). The section "past series on lifelong learning" presents tables which are no longer available in the same format or at the same level of precision as CVTS 4. The CVTS1 was the first survey on continuing vocational training in enterprises carried out on the EU level in a co-ordinated form (outline questionnaire, common definitions, and common recommendations with the respect to the fieldwork). The survey was of pioneering nature, and is not any longer disseminated due to lack of comparability with the following waves.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent12n There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent12s There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_cvts3_12 There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent13n There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent13s There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_cvts3_14 There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent09n There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent09s There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_cvts3_10 There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent14s There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent14n There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_cvts3_16 There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent20n There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_ent20s There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Декабрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 мая, 2014
      Выбрать
      Eurostat Dataset Id:educ_bo_ac_gent 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. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes, personnel in education and the cost and type of resources dedicated to education. The main source of data is the joint UIS (UNESCO Institute of Statistics)/OECD/Eurostat (UOE) questionnaires on education statistics, which constitute the core database on education. Data on regional enrolments and foreign language learning are collected additionally by Eurostat. Countries provide data, coming from administrative records, on the basis of commonly agreed definitions. From the UOE data collection, the following datasets on the Bologna Process are available: A. Widening access educ_bo_ac_ent2: Net entry rate (ISCED 5A) by age and sexeduc_bo_ac_ent3: Female entrants by field of education (ISCED 5A)educ_bo_ac_gent: Entrants at ISCED 5A and qualifying graduates of secondary schooling (ISCED 3A - 4A)educ_bo_ac_el1t: Students (ISCED 5A) studying part-time, by age B. Study framework educ_bo_fi_fgdp: Public expenditure on tertiary education (ISCED 5-6), as % of GDP or total public expenditureeduc_bo_fi_ftot: Annual total expenditure on educational institutions (ISCED 5-6) per full-time equivalent student with and without expenditure on research and ancillary serviceseduc_bo_fi_ffun: Tertiary education institutions' income from private sources (households and other private entities) as % of all public and private sourceseduc_bo_fi_fiaid: Public financial aid to tertiary students (ISCED 5-6), by type of aid, as % of public expenditure on tertiary education C. Student and staff mobility educ_bo_mo_el8o: Students (ISCED 5A and 6) who are nationals of a given country, studying in another country (EU-27, EFTA and CC) as % of the total enrolment in that countryeduc_bo_mo_el8i: Number of foreign students (world and Bologna Area) studying in a given country, as % of the total enrolment in that country, ISCED 5A and 6educ_bo_mo_gr4: Graduates (ISCED 5A and 6) from abroad (non-citizens, permanent residence and prior education outside the country) D. Effective outcomes and employability educ_bo_ou_gren: Gross graduation rate and net entry rate, ISCED 5A   The data for some countries which do not participate in the UOE data collection were provided to Eurostat specifically for the monitoring of the Bologna Process. Not being fully integrated in the UOE, the data sometimes might not be as comparable as the data for the remaining countries, due to differences in the underlying data sources and definitions. These data were provided by the following entities: Andorra (AD): data provided by the University of Andorra (indicators educ_bo_ac_ent3, educ_bo_fi_ffun, educ_bo_mo_el8i, educ_bo_mo_gr4)Armenia (AM): data provided by the Ministry of Education and Science (educ_bo_ac_gent, educ_bo_ac_el1t, educ_bo_mo_gr4, educ_bo_ou_gren)Georgia (GE): data provided by the NSI, Statistics Georgia (educ_bo_ac_ent3, educ_bo_ac_el1t, educ_bo_fi_fgdp, educ_bo_mo_gr4)Serbia (RS): data provided by the NSI, Statistical Office of the Republic of Serbia (educ_bo_mo_el8i)Ukraine (UA): data provided by the NSI, State Statistics Committee for Ukraine (educ_bo_ou_gren, educ_bo_ac_el1t, educ_bo_mo_el8i, educ_bo_mo_gr4, educ_bo_ou_gren)
    • Апрель 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 апреля, 2014
      Выбрать
      Eurostat Dataset Id:env_ac_exp4r2 Data show environmental protection expenditure (EPE). Environmental protection includes all activities directly aimed at the prevention, reduction and elimination of pollution or any other degradation of the environment. Data on regional EPE were collected from the European countries for the first time in 2010 through the Eurostat Questionnaire on Regional Environmental Data Collection (REQ) based on a Gentlemen's Agreement. The scope of environmental protection is defined according to the Classification of Environmental Protection Activities (CEPA 2000), which distinguishes nine environmental domains: protection of ambient air and climate; wastewater management; waste management; protection and remediation of soil, groundwater and surface water; noise and vibration abatement; protection of biodiversity and landscape; protection against radiation; research and development and other environmental protection activities. The data cover three economic sectors (public sector, specialised producers and industry), one economic variable (total environmental protection expenditure) and the nine environmental domains mentioned above. Data are published for years 2000-2009.
    • Июнь 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 30 июля, 2012
      Выбрать
      General and regional statistics > Regional environment and energy statistics > Other regional environment statistics > Environmental protection expenditure by NUTS 2 regions (NACE Rev. 2).
    • Август 2011
      Источник: Multiple Sources
      Загружен: Knoema
      Выбрать
      A compilation of monthly closing stock indices for major stock exchanges across the World. This dataset is updated on a monthly basis.
    • Июль 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 12 августа, 2015
      Выбрать
      Eurostat Dataset Id:bop_fdi_pos_r2 Eurostat uses as a base for its work the OECD Benchmark Definition of Foreign Direct Investment Third Edition, a detailed operational definition fully consistent with the IMF Balance of Payments Manual, Fifth Edition, BPM5. Foreign direct investment (FDI) is the category of international investment made by an entity resident in one economy (direct investor) to acquire a lasting interest in an enterprise operating in another economy (direct investment enterprise). The lasting interest is deemed to exist if the direct investor acquires at least 10% of the voting power of the direct investment enterprise. FDI statistics record separately: 1) Inward FDI (or FDI in the reporting economy), namely investment by foreigners in enterprises resident in the reporting economy. 2) Outward FDI (or FDI abroad), namely investment by residents entities in affiliated enterprises abroad. FDI statistics record both the initial investment and all subsequent investment made by the direct investor, either in the form of equity capital, or in the form of loans, or in the form of reinvesting earnings. Investment made through other affiliated enterprises of the same group of the direct investor should also be recorded according to the international methodology. There are three main indicators: FDI flows, stocks and income. The indicators described in more detail below are presented in the complete tables with a breakdown by partner country or region and a breakdown by the kind of activity in which FDI is made. In the table called "Main indicators" there is a reduced breakdown by partners and data for total activity only. See the part on classification system for more detail. See also the User's guideon the structure on the database and for practical information on data downloading. 1) FDI flows denote the new investment made during the period. FDI flows are recorded in the Balance of Payments financial account. Total FDI flows are broken down by kind of instrument used for making the investment:Equity capital comprises equity in branches, all shares in subsidiaries and associates (except non-participating, preferred shares that are treated as debt securities and are included under other FDI capital) and other contributions such as the provision of machinery.Reinvested earnings consist of the direct investor's share (in proportion to equity participation) of earnings not distributed by the direct investment enterprise. Reinvested earnings are an imputed transaction. Reinvested earnings are also recorded with opposite sign among FDI income (see below). This recording represents not distributed income as being earned by the direct investor and reinvested in the direct investment enterprise at the same time.Other FDI capital (loans) covers the borrowing and lending of funds, including debt securities and trade credits between direct investors and direct investment enterprises. Debt transactions between affiliated financial intermediaries recorded under direct investment flows are limited to permanent debt. 2) FDI stocks (or positions) denote the value of the investment at the end of the period. FDI stocks are recorded in the International Investment Position. Outward FDI stocks are recorded as assets of the reporting economy, inward FDI stocks as liabilities. Similarly with flows, FDI stocks are broken down by kind of instrument. However, there are only two categories instead of three:Equity capital and reinvested earnings is the value of the own capital of the enterprise, including the value of own reserves that are accumulated from past reinvested earnings. Reserves corresponding to reinvested earnings are not shown separately from other equity capital as in the case of flows.Other FDI capital is the stock of debts (assets or liabilities) between the direct investors and the direct investment enterprise. 3) FDI income is the income accruing to direct investors during the period. FDI income is recorded in the current account of the Balance of Payments. Total FDI income is broken down by kind of income. The categories of FDI income available are linked to the breakdown of FDI flows and stocks by kind of instrument, namely:Dividends Dividends payable in the period and branch profits remitted to the direct investor, gross of any withholding taxes. Dividends include payments due on common and preferred shares.Reinvested earnings See definition under FDI flows.Interest on loans Interest accrued in the period on loans (other FDI capital) with affiliated enterprises, gross of any withholding tax. 4) FDI intensity Out of FDI annual data, an indicator useful to measure EU market integration is also calculated and disseminated in the domain Structural Indicators:FDI intensity as % of GDP: Average of inward and outward FDI flows divided by GDP. A higher index indicates higher new FDI during the period in relation to the size of the economy as measured by GDP. If this index increases over time, then the country/zone is becoming more integrated with the international economy.
    • Январь 2010
      Источник: European Commission
      Загружен: Knoema
      Выбрать
      This dataset provides an overview of the most recent and pertinent annual energy related statistics in Europe. The data is drawn from several sources: the European Commission’s services; international organisations, such as the European Environment Agency and the International Energy Agency and, where no data is currently available, from the European Commission’s estimations. The indicator calculations follow the methodology established by the European Commission - DG Energy.
    • Январь 2010
      Источник: European Commission
      Загружен: Knoema
      Дата обращения к источнику: 01 января, 2011
      Выбрать
      The database provides an overview of the most recent and pertinent annual energy related statistics in Europe. It covers the European Union and its 27 Member States. The content of this collection is based on a range of sources, including Eurostat, DG ECFIN, and EEA. The statistics include Eurostat Energy Statistics 1990-2009, after its complete revision in early 2011.
    • Январь 2011
      Источник: Eurostat
      Загружен: Knoema
      Выбрать
      This dataset contains common birds index and protected areas for biodiversity statistics for EU member countries.
    • Сентябрь 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 04 октября, 2014
      Выбрать
      Countries report expenditures by sources of funds: Governement (central, regional, local); International agencies and other foreign sources; Households and Other private entities (including firms and religious institutions and other non-profit organisations). Three types of financial transactions can be distinguished: -direct expenditure/payments on educational institutions -Intergovernmental transfers for education -Transfers to students or households and to other private entities.
    • Декабрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 06 июля, 2014
      Выбрать
      Eurostat Dataset Id:educ_bo_fi_ftot 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. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes, personnel in education and the cost and type of resources dedicated to education. The main source of data is the joint UIS (UNESCO Institute of Statistics)/OECD/Eurostat (UOE) questionnaires on education statistics, which constitute the core database on education. Data on regional enrolments and foreign language learning are collected additionally by Eurostat. Countries provide data, coming from administrative records, on the basis of commonly agreed definitions. From the UOE data collection, the following datasets on the Bologna Process are available: A. Widening accesseduc_bo_ac_ent2: Net entry rate (ISCED 5A) by age and sexeduc_bo_ac_ent3: Female entrants by field of education (ISCED 5A)educ_bo_ac_gent: Entrants at ISCED 5A and qualifying graduates of secondary schooling (ISCED 3A - 4A)educ_bo_ac_el1t: Students (ISCED 5A) studying part-time, by age   B. Study frameworkeduc_bo_fi_fgdp: Public expenditure on tertiary education (ISCED 5-6), as % of GDP or total public expenditureeduc_bo_fi_ftot: Annual total expenditure on educational institutions (ISCED 5-6) per full-time equivalent student with and without expenditure on research and ancillary serviceseduc_bo_fi_ffun: Tertiary education institutions' income from private sources (households and other private entities) as % of all public and private sourceseduc_bo_fi_fiaid: Public financial aid to tertiary students (ISCED 5-6), by type of aid, as % of public expenditure on tertiary education   C. Student and staff mobilityeduc_bo_mo_el8o: Students (ISCED 5A and 6) who are nationals of a given country, studying in another country (EU-27, EFTA and CC) as % of the total enrolment in that countryeduc_bo_mo_el8i: Number of foreign students (world and Bologna Area) studying in a given country, as % of the total enrolment in that country, ISCED 5A and 6educ_bo_mo_gr4: Graduates (ISCED 5A and 6) from abroad (non-citizens, permanent residence and prior education outside the country)   D. Effective outcomes and employabilityeduc_bo_ou_gren: Gross graduation rate and net entry rate, ISCED 5A     The data for some countries which do not participate in the UOE data collection were provided to Eurostat specifically for the monitoring of the Bologna Process. Not being fully integrated in the UOE, the data sometimes might not be as comparable as the data for the remaining countries, due to differences in the underlying data sources and definitions. These data were provided by the following entities:Andorra (AD): data provided by the University of Andorra (indicators educ_bo_ac_ent3, educ_bo_fi_ffun, educ_bo_mo_el8i, educ_bo_mo_gr4)Armenia (AM): data provided by the Ministry of Education and Science (educ_bo_ac_gent, educ_bo_ac_el1t, educ_bo_mo_gr4, educ_bo_ou_gren)Georgia (GE): data provided by the NSI, Statistics Georgia (educ_bo_ac_ent3, educ_bo_ac_el1t, educ_bo_fi_fgdp, educ_bo_mo_gr4)Serbia (RS): data provided by the NSI, Statistical Office of the Republic of Serbia (educ_bo_mo_el8i)Ukraine (UA): data provided by the NSI, State Statistics Committee for Ukraine (educ_bo_ou_gren, educ_bo_ac_el1t, educ_bo_mo_el8i, educ_bo_mo_gr4, educ_bo_ou_gren)
    • Май 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 24 мая, 2015
      Выбрать
      Eurostat Dataset Id:hlth_sha3p Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003.
    • Май 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 июля, 2015
      Выбрать
      Eurostat Dataset Id:hlth_sha3m Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. 3.2. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003. 3.3. Coverage - sector Public Health
    • Май 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 июля, 2015
      Выбрать
      Eurostat Dataset Id:hlth_sha3h Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. 3.2. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003. 3.3. Coverage - sector Public Health
    • Май 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 июля, 2015
      Выбрать
      Eurostat Dataset Id:hlth_sha2p Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea.
    • Май 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 июля, 2015
      Выбрать
      Eurostat Dataset Id:hlth_sha2m Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003.
    • Май 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 июля, 2015
      Выбрать
      Eurostat Dataset Id:hlth_sha2h Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea.
    • Май 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 июля, 2015
      Выбрать
      Eurostat Dataset Id:hlth_sha1p Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003.
    • Май 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 мая, 2015
      Выбрать
      Eurostat Dataset Id:hlth_sha1m Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. 3.2. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003. 3.3. Coverage - sector Public Health
    • Май 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 июля, 2015
      Выбрать
      Eurostat Dataset Id:hlth_sha1h Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. 3.2. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003. 3.3. Coverage - sector Public Health
    • Июль 2012
      Источник: Knoema
      Загружен: Knoema
      Выбрать
      Source : United States Department of Agriculture; International Monetary Fund; UN Department of Economic and Social Affairs; Food and Agriculture Organization, The World Bank
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 марта, 2019
      Выбрать
      Eurostat Dataset Id:educ_fitotin The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes by pupils and students, personnel in education and the cost and type of resources dedicated to education. The standards on international statistics on education and training systems are set by the three international organisations jointly administering the UOE data collection:the United Nations Educational, Scientific, and Cultural Organisation Institute for Statistics (UNESCO-UIS),the Organisation for Economic Co-operation and Development (OECD) and,the Statistical Office of the European Union (EUROSTAT). The following topics are covered:Context - School-aged population, overall participation rates in educationDistribution of pupils/students by levelParticipation/enrolment in education (ISCED 0-4)Tertiary education participationTertiary education graduatesTeaching staff (ISCED 1-3)Pupil/students-teacher ratio and average class size (ISCED 1-3)Language learning (ISCED 1-3)Regional enrolmentsExpenditure on education in current pricesExpenditure on education in constant pricesExpenditure on education as % of GDP or public expenditureExpenditure on public and private educational institutionsFinancial aid to studentsFunding of education Other tables, used to measure progress towards the Lisbon objectives in education and training, are gathered in the Thematic indicators tables. They contain the following indicators: - Teachers and trainers - Mathematics, science and technology enrolments and graduates - Investments in education and training - Participation rates in education by age and sex - Foreign language learning - Student mobility
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 марта, 2019
      Выбрать
      Eurostat Dataset Id:educ_fipubin The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes by pupils and students, personnel in education and the cost and type of resources dedicated to education. The standards on international statistics on education and training systems are set by the three international organisations jointly administering the UOE data collection:the United Nations Educational, Scientific, and Cultural Organisation Institute for Statistics (UNESCO-UIS),the Organisation for Economic Co-operation and Development (OECD) and,the Statistical Office of the European Union (EUROSTAT). The following topics are covered:Context - School-aged population, overall participation rates in educationDistribution of pupils/students by levelParticipation/enrolment in education (ISCED 0-4)Tertiary education participationTertiary education graduatesTeaching staff (ISCED 1-3)Pupil/students-teacher ratio and average class size (ISCED 1-3)Language learning (ISCED 1-3)Regional enrolmentsExpenditure on education in current pricesExpenditure on education in constant pricesExpenditure on education as % of GDP or public expenditureExpenditure on public and private educational institutionsFinancial aid to studentsFunding of education Other tables, used to measure progress towards the Lisbon objectives in education and training, are gathered in the Thematic indicators tables. They contain the following indicators: - Teachers and trainers - Mathematics, science and technology enrolments and graduates - Investments in education and training - Participation rates in education by age and sex - Foreign language learning - Student mobility
    • Октябрь 2017
      Источник: U.S. Department of Agriculture
      Загружен: Knoema
      Дата обращения к источнику: 30 октября, 2017
      Выбрать
      Percent of household final consumption expenditures spent on food, alcoholic beverages, and tobacco that were consumed at home, 2009-2016. The data are computed by Birgit Meade (202-694-5159), ERS/USDA, EUROMONITOR data, June 2015.
    • Октябрь 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 октября, 2012
      Выбрать
      Experimental House Price Index for the Euro area and the EU for the period 2005 Q1 until 2012 Q2
  • F
    • Июнь 2012
      Источник: Food and Agriculture Organization
      Загружен: Knoema
      Дата обращения к источнику: 18 июля, 2012
      Выбрать
      This dataset represents Food Consumption, Food Production and Trade by various Food items. Note: data represent values for time periods (1990-1992, 1995-97, 2000-02, 2005-07) and is shown as data for the last year of time period (1992, 1997, 2002, 2007).
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 01 января, 2014
      Выбрать
      Eurostat Dataset Id:ef_lu_ovcropaa 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 Standard 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 on land use livestock special 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 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.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 18 июня, 2019
      Выбрать
      Source: OECD International direct investment database, IMF Reference:Benchmark Definition of Foreign Direct Investment, 3rd edition   Foreign direct investment reflects the objective of obtaining a lasting interest by a resident entity in one economy (‘‘direct investor'') in anentity resident in an economy other than that of the investor (‘‘direct investment enterprise''). The lasting interest implies the existence of a long-term relationship between the direct investor and the enterprise and a significant degree of influence on the management of the enterprise. Direct investment involves both the initial transaction between the two entities and all subsequent capital transactions between them and among affiliated enterprises, both incorporated and unincorporated.
    • Декабрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 мая, 2014
      Выбрать
      Eurostat Dataset Id:educ_bo_ac_ent3 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. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes, personnel in education and the cost and type of resources dedicated to education. The main source of data is the joint UIS (UNESCO Institute of Statistics)/OECD/Eurostat (UOE) questionnaires on education statistics, which constitute the core database on education. Data on regional enrolments and foreign language learning are collected additionally by Eurostat. Countries provide data, coming from administrative records, on the basis of commonly agreed definitions. From the UOE data collection, the following datasets on the Bologna Process are available: A. Widening access educ_bo_ac_ent2: Net entry rate (ISCED 5A) by age and sexeduc_bo_ac_ent3: Female entrants by field of education (ISCED 5A)educ_bo_ac_gent: Entrants at ISCED 5A and qualifying graduates of secondary schooling (ISCED 3A - 4A)educ_bo_ac_el1t: Students (ISCED 5A) studying part-time, by age B. Study framework educ_bo_fi_fgdp: Public expenditure on tertiary education (ISCED 5-6), as % of GDP or total public expenditureeduc_bo_fi_ftot: Annual total expenditure on educational institutions (ISCED 5-6) per full-time equivalent student with and without expenditure on research and ancillary serviceseduc_bo_fi_ffun: Tertiary education institutions' income from private sources (households and other private entities) as % of all public and private sourceseduc_bo_fi_fiaid: Public financial aid to tertiary students (ISCED 5-6), by type of aid, as % of public expenditure on tertiary education C. Student and staff mobility educ_bo_mo_el8o: Students (ISCED 5A and 6) who are nationals of a given country, studying in another country (EU-27, EFTA and CC) as % of the total enrolment in that countryeduc_bo_mo_el8i: Number of foreign students (world and Bologna Area) studying in a given country, as % of the total enrolment in that country, ISCED 5A and 6educ_bo_mo_gr4: Graduates (ISCED 5A and 6) from abroad (non-citizens, permanent residence and prior education outside the country) D. Effective outcomes and employability educ_bo_ou_gren: Gross graduation rate and net entry rate, ISCED 5A   The data for some countries which do not participate in the UOE data collection were provided to Eurostat specifically for the monitoring of the Bologna Process. Not being fully integrated in the UOE, the data sometimes might not be as comparable as the data for the remaining countries, due to differences in the underlying data sources and definitions. These data were provided by the following entities: Andorra (AD): data provided by the University of Andorra (indicators educ_bo_ac_ent3, educ_bo_fi_ffun, educ_bo_mo_el8i, educ_bo_mo_gr4)Armenia (AM): data provided by the Ministry of Education and Science (educ_bo_ac_gent, educ_bo_ac_el1t, educ_bo_mo_gr4, educ_bo_ou_gren)Georgia (GE): data provided by the NSI, Statistics Georgia (educ_bo_ac_ent3, educ_bo_ac_el1t, educ_bo_fi_fgdp, educ_bo_mo_gr4)Serbia (RS): data provided by the NSI, Statistical Office of the Republic of Serbia (educ_bo_mo_el8i)Ukraine (UA): data provided by the NSI, State Statistics Committee for Ukraine (educ_bo_ou_gren, educ_bo_ac_el1t, educ_bo_mo_el8i, educ_bo_mo_gr4, educ_bo_ou_gren)
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_fed8 General description of the ad hoc modules supplementing the Labour Force Survey (LFS)
    • Октябрь 2018
      Источник: International Federation of Association Football
      Загружен: Knoema
      Дата обращения к источнику: 25 марта, 2019
      Выбрать
      Monthly updates of FIFA World Football Men's Ranking 
    • Июль 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 июля, 2012
      Выбрать
      Note:i) All the Data Present in this dataset are "Not seasonally adjusted data (NSA)". ii)Eurostat Hierarchy: General and regional statistics > European and national short term indicators (euroind) > Monetary and financial indicators (ei_mf).
    • Сентябрь 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 04 октября, 2014
      Выбрать
      The number of students enrolled refers to the count of students studying in the reference period. Each student enrolled in the education programmes covered by the corresponding category is counted once and only once. National data collection systems permitting, the statistics reflect the number of students enrolled at the beginning of the school / academic year. Preferably, the end (or near-end) of the first month of the school / academic year is chosen (special arrangements are made for part-year students who may not start studies at the beginning of the school year). Students are classified as foreign students (non-citizens) if they are not citizens of the country in which the data are collected. While pragmatic and operational, this classification is inappropriate for capturing student mobility because of differing national policies regarding the naturalisation of immigrants. Countries that have lower propensity to grant permanent residence to its immigrant populations are likely to report second generation immigrants as foreign students. Therefore, for student mobility and bilateral comparisons, interpretations of data based on the concept of foreign students should be made with caution. Students are classified as international students if they left their country of origin and moved to another country for the purpose of study. Depending on country-specific immigration legislation, mobility arrangements, and data availability, international students may be defined as students who are not permanent or usual residents of their country of study or alternatively as students who obtained their prior education in a different country, including another EU country.
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 марта, 2019
      Выбрать
      Eurostat Dataset Id:educ_mofo_grd Statistics on student/graduate mobility and foreigners in tertiary education collected through the UOE data collection on education and training systems. Data concerning mobility and foreigners are collected as follows:Number of mobile and foreign enrolled students by level of education, programme destination and field of education.Number of mobile and foreign enrolled students by level of education, programme destination, EU/non EU/unknown membership and gender.Number of foreign enrolled students by level of education, programme destination and country of citizenship.Number of mobile enrolled students by level of education, programme destination, and country of origin (usual residence and/or country of prior education).Number of mobile and foreign graduates by level of education, programme destination, cumulative duration and gender. Data by both country of origin and country of destination of the students are disseminated. The absolute figures along with indicators are published.
    • Май 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 мая, 2019
      Выбрать
      Eurostat Dataset Id:educ_thfrlan The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes by pupils and students, personnel in education and the cost and type of resources dedicated to education. The standards on international statistics on education and training systems are set by the three international organisations jointly administering the UOE data collection:the United Nations Educational, Scientific, and Cultural Organisation Institute for Statistics (UNESCO-UIS),the Organisation for Economic Co-operation and Development (OECD) and,the Statistical Office of the European Union (EUROSTAT). The following topics are covered:Context - School-aged population, overall participation rates in educationDistribution of pupils/students by levelParticipation/enrolment in education (ISCED 0-4)Tertiary education participationTertiary education graduatesTeaching staff (ISCED 1-3)Pupil/students-teacher ratio and average class size (ISCED 1-3)Language learning (ISCED 1-3)Regional enrolmentsExpenditure on education in current pricesExpenditure on education in constant pricesExpenditure on education as % of GDP or public expenditureExpenditure on public and private educational institutionsFinancial aid to studentsFunding of education Other tables, used to measure progress towards the Lisbon objectives in education and training, are gathered in the Thematic indicators tables. They contain the following indicators: - Teachers and trainers - Mathematics, science and technology enrolments and graduates - Investments in education and training - Participation rates in education by age and sex - Foreign language learning - Student mobility
    • Июнь 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 июля, 2012
      Выбрать
      This Dataset contains 5 Tables. Foreign official reserves - Annual data (mny_for_a); Foreign official reserves - Quarterly data (mny_for_q); Foreign official reserves - Monthly data (mny_for_m); Monetary gold in fine troy ounces - Yearly data (mny_for_gold_a); Monetary gold in fine troy ounces - Monthly data (mny_for_gold_m). Note: i) All data in the datasets represents 'Value at the end of the period (END)'. ii): Eurostat Hierarchy: Economy and finance > Monetary and other financial statistics (mny) > Foreign official reserves (mny_for).
    • Декабрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 мая, 2014
      Выбрать
      Eurostat Dataset Id:educ_bo_mo_el8i 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. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes, personnel in education and the cost and type of resources dedicated to education. The main source of data is the joint UIS (UNESCO Institute of Statistics)/OECD/Eurostat (UOE) questionnaires on education statistics, which constitute the core database on education. Data on regional enrolments and foreign language learning are collected additionally by Eurostat. Countries provide data, coming from administrative records, on the basis of commonly agreed definitions. From the UOE data collection, the following datasets on the Bologna Process are available: A. Widening access educ_bo_ac_ent2: Net entry rate (ISCED 5A) by age and sexeduc_bo_ac_ent3: Female entrants by field of education (ISCED 5A)educ_bo_ac_gent: Entrants at ISCED 5A and qualifying graduates of secondary schooling (ISCED 3A - 4A)educ_bo_ac_el1t: Students (ISCED 5A) studying part-time, by age B. Study framework educ_bo_fi_fgdp: Public expenditure on tertiary education (ISCED 5-6), as % of GDP or total public expenditureeduc_bo_fi_ftot: Annual total expenditure on educational institutions (ISCED 5-6) per full-time equivalent student with and without expenditure on research and ancillary serviceseduc_bo_fi_ffun: Tertiary education institutions' income from private sources (households and other private entities) as % of all public and private sourceseduc_bo_fi_fiaid: Public financial aid to tertiary students (ISCED 5-6), by type of aid, as % of public expenditure on tertiary education C. Student and staff mobility educ_bo_mo_el8o: Students (ISCED 5A and 6) who are nationals of a given country, studying in another country (EU-27, EFTA and CC) as % of the total enrolment in that countryeduc_bo_mo_el8i: Number of foreign students (world and Bologna Area) studying in a given country, as % of the total enrolment in that country, ISCED 5A and 6educ_bo_mo_gr4: Graduates (ISCED 5A and 6) from abroad (non-citizens, permanent residence and prior education outside the country) D. Effective outcomes and employability educ_bo_ou_gren: Gross graduation rate and net entry rate, ISCED 5A   The data for some countries which do not participate in the UOE data collection were provided to Eurostat specifically for the monitoring of the Bologna Process. Not being fully integrated in the UOE, the data sometimes might not be as comparable as the data for the remaining countries, due to differences in the underlying data sources and definitions. These data were provided by the following entities: Andorra (AD): data provided by the University of Andorra (indicators educ_bo_ac_ent3, educ_bo_fi_ffun, educ_bo_mo_el8i, educ_bo_mo_gr4)Armenia (AM): data provided by the Ministry of Education and Science (educ_bo_ac_gent, educ_bo_ac_el1t, educ_bo_mo_gr4, educ_bo_ou_gren)Georgia (GE): data provided by the NSI, Statistics Georgia (educ_bo_ac_ent3, educ_bo_ac_el1t, educ_bo_fi_fgdp, educ_bo_mo_gr4)Serbia (RS): data provided by the NSI, Statistical Office of the Republic of Serbia (educ_bo_mo_el8i)Ukraine (UA): data provided by the NSI, State Statistics Committee for Ukraine (educ_bo_ou_gren, educ_bo_ac_el1t, educ_bo_mo_el8i, educ_bo_mo_gr4, educ_bo_ou_gren)
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 19 марта, 2019
      Выбрать
      Eurostat Dataset Id:educ_mofo_fld Statistics on student/graduate mobility and foreigners in tertiary education collected through the UOE data collection on education and training systems. Data concerning mobility and foreigners are collected as follows:Number of mobile and foreign enrolled students by level of education, programme destination and field of education.Number of mobile and foreign enrolled students by level of education, programme destination, EU/non EU/unknown membership and gender.Number of foreign enrolled students by level of education, programme destination and country of citizenship.Number of mobile enrolled students by level of education, programme destination, and country of origin (usual residence and/or country of prior education).Number of mobile and foreign graduates by level of education, programme destination, cumulative duration and gender. Data by both country of origin and country of destination of the students are disseminated. The absolute figures along with indicators are published.
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 21 марта, 2019
      Выбрать
      Eurostat Dataset Id:educ_mofo_dst Statistics on student/graduate mobility and foreigners in tertiary education collected through the UOE data collection on education and training systems. Data concerning mobility and foreigners are collected as follows:Number of mobile and foreign enrolled students by level of education, programme destination and field of education.Number of mobile and foreign enrolled students by level of education, programme destination, EU/non EU/unknown membership and gender.Number of foreign enrolled students by level of education, programme destination and country of citizenship.Number of mobile enrolled students by level of education, programme destination, and country of origin (usual residence and/or country of prior education).Number of mobile and foreign graduates by level of education, programme destination, cumulative duration and gender. Data by both country of origin and country of destination of the students are disseminated. The absolute figures along with indicators are published.
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 20 марта, 2019
      Выбрать
      Eurostat Dataset Id:educ_mofo_orig Statistics on student/graduate mobility and foreigners in tertiary education collected through the UOE data collection on education and training systems. Data concerning mobility and foreigners are collected as follows:Number of mobile and foreign enrolled students by level of education, programme destination and field of education.Number of mobile and foreign enrolled students by level of education, programme destination, EU/non EU/unknown membership and gender.Number of foreign enrolled students by level of education, programme destination and country of citizenship.Number of mobile enrolled students by level of education, programme destination, and country of origin (usual residence and/or country of prior education).Number of mobile and foreign graduates by level of education, programme destination, cumulative duration and gender. Data by both country of origin and country of destination of the students are disseminated. The absolute figures along with indicators are published.
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 марта, 2019
      Выбрать
      Eurostat Dataset Id:educ_mofo_gen Statistics on student/graduate mobility and foreigners in tertiary education collected through the UOE data collection on education and training systems. Data concerning mobility and foreigners are collected as follows:Number of mobile and foreign enrolled students by level of education, programme destination and field of education.Number of mobile and foreign enrolled students by level of education, programme destination, EU/non EU/unknown membership and gender.Number of foreign enrolled students by level of education, programme destination and country of citizenship.Number of mobile enrolled students by level of education, programme destination, and country of origin (usual residence and/or country of prior education).Number of mobile and foreign graduates by level of education, programme destination, cumulative duration and gender. Data by both country of origin and country of destination of the students are disseminated. The absolute figures along with indicators are published.
    • Июнь 2019
      Источник: National Bureau of Statistics, Nigeria
      Загружен: Knoema
      Дата обращения к источнику: 03 июля, 2019
      Выбрать
      1. Nigeria Trade Statistics by Region and Major Trading Partners, 2019 March 2. 2019 annual value is up to 2019 January to 2019 March Nigeria: Trade Statistics by Region and Major Trading Partners
    • Апрель 2019
      Источник: Fund for Peace
      Загружен: Knoema
      Дата обращения к источнику: 15 мая, 2019
      Выбрать
      Data cited at: Fragile States Index - https://fragilestatesindex.org/ The FSI focuses on the indicators of risk and is based on thousands of articles and reports that are processed by our CAST Software from electronically available sources. Measures of fragility, like Demographic Pressures,Refugees and IDPs and etc., have been scaled on 0 to 10 where 10 is highest fragility and 0 no fragility.
    • Апрель 2012
      Источник: Agi Data
      Загружен: Knoema
      Выбрать
      Experts commonly support the notion that access to information is integral to the promotion of participation, transparency and accountability in any given society. A freedom of information framework aims at improving the efficiency of the government and increasing the transparency of its functioning by: 1. Regularly and reliably providing government documents to the public; 2. Educating the public on the significance of transparent government;3. Facilitating appropriate and relevant use of information in the lives of individuals
    • Январь 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 31 мая, 2014
      Выбрать
      Eurostat Dataset Id:yth_part_020 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.
    • Январь 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 31 мая, 2014
      Выбрать
      Eurostat Dataset Id:yth_part_010 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.
    • Январь 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 31 мая, 2014
      Выбрать
      Eurostat Dataset Id:yth_cult_010 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.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июля, 2019
      Выбрать
      This table contains data on full-time and part-time employment based on a common definition of 30-usual weekly hours of work in the main job. Data are broken down by professional status - employees, total employment - sex and standardised age groups (15-24, 25-54, 55+, total). Unit of measure used - Data are expressed in thousands of persons.
  • G
    • Июнь 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 14 июня, 2012
      Выбрать
      GDP and main components dataset contains both Quarterly & Annual data for ; Current prices, volumes and Price indices
    • Февраль 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 04 марта, 2019
      Выбрать
      Eurostat Dataset Id:earn_gr_gpgr2ag The unadjusted Gender Pay Gap (GPG) represents the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees. From reference year 2006 onwards, the new GPG data is based on the methodology of the Structure of Earnings Survey (COUNCIL REGULATION EC No 530/1999 of 9 March 1999 concerning structural statistics on earnings and on labour costs) which is carried out every four years. The most recent available data refers to reference years 2002, 2006 and 2010. Whereas the GPG figures for 2006 and 2010 are directly computed from the 4-yearly SES, for the intermediate years countries provide annual estimates which every 4 years are revised, benchmarked on the SES results in the two respective years. Some countries calculate the annual GPG on a yearly SES and hence their data needs no further adjustment or revisions as the majority of the others. Data are broken down by economic activity (NACE: Statistical Classification of Economic Activities in the European Community), form of economic and financial control (public/private) of the enterprise, working profile (full-time / part-time) and age classes (six age groups) of employees.
    • Февраль 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 04 марта, 2019
      Выбрать
      Eurostat Dataset Id:earn_gr_gpgr2wt The unadjusted Gender Pay Gap (GPG) represents the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees. From reference year 2006 onwards, the new GPG data is based on the methodology of the Structure of Earnings Survey (COUNCIL REGULATION EC No 530/1999 of 9 March 1999 concerning structural statistics on earnings and on labour costs) which is carried out every four years. The most recent available data refers to reference years 2002, 2006 and 2010. Whereas the GPG figures for 2006 and 2010 are directly computed from the 4-yearly SES, for the intermediate years countries provide annual estimates which every 4 years are revised, benchmarked on the SES results in the two respective years. Some countries calculate the annual GPG on a yearly SES and hence their data needs no further adjustment or revisions as the majority of the others. Data are broken down by economic activity (NACE: Statistical Classification of Economic Activities in the European Community), form of economic and financial control (public/private) of the enterprise, working profile (full-time / part-time) and age classes (six age groups) of employees.
    • Август 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 12 декабря, 2015
      Выбрать
      Eurostat Dataset Id:earn_gr_hgpg The gender pay gap is given as the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees. The gender pay gap is based on several data sources, including the European Community Household Panel (ECHP), the EU Survey on Income and Living Conditions (EU-SILC) and national sources.
    • Ноябрь 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 29 декабря, 2013
      Выбрать
      Eurostat Dataset Id:inn_cis7_gen The Community Innovation Survey (CIS) is a survey of innovation activity in enterprises. The harmonised 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, type 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, in close cooperation with the countries, has developed a standard core questionnaire starting with the CIS3 data collection, along with an accompanying set of definitions and methodological recommendations. The concepts and underlying methodology of the CIS are also based on the Oslo Manual — second edition of 1997 and third edition of 2005 . Up to CIS 2010, CIS results were collected under Commission Regulation (EC) No 1450/2004. A new Regulation will apply from CIS 2012 (EC No 995/2012). The data presented in these tables refer to enterprises with ‘10 employees or more’ active in the sectors to be covered under the Regulation (cf. NACE CORE). Further activities may be covered on a voluntary basis. Most statistics are based on a reference period of three years, but some use one calendar year. Since CIS 2008, the survey has included an ad-hoc module. It consists of a set of questions focusing on a special theme. The themes are different in each survey wave, allowing data to be obtained on specific issues beyond the data usually collected. Overview over time: Initially, the CIS data collection was carried out every four years. The first collection (CIS Light) was launched in 1993 as a pilot exercise and the second (CIS2) was carried out in 1997/1998 for most countries except Greece and Ireland, where it was launched in 1999. The third survey (CIS3) was conducted in 2000/2001 for most participating countries with the exception of Norway, Iceland, Luxembourg and Greece, where it was launched in 2002. As from 2004, the survey has been carried out every two years. CIS4 was conducted in the 25 EU Member States (as for 2004), Iceland, Norway, Bulgaria and Romania. The survey was launched in 2005 with a three-year reference period 2002 to 2004 for most indicators. The fifth survey CIS 2006 was carried out in all 25 EU Member States (as for 2006), Norway, Bulgaria, Romania, Croatia and Turkey. It was launched in 2007, mostly for the reference period 2004 to 2006. As regards CIS 2008, 26 Member States (all except Greece), Iceland, Norway, Croatia and Turkey took part in the survey. CIS 2008 was launched in 2009 with a three-year reference period 2006 to 2008 for most indicators. Changes were made to the CIS 2008 questionnaire to bring it into line with the third revision of the Oslo Manual, 2005 edition, by giving greater weight to organisational and marketing innovation. CIS 2008 was complemented by an ad-hoc module on innovation with environmental benefits. The seventh Community Innovation Survey, CIS 2010, had 31 participating countries (all the EU 27 Member States (except Greece), Iceland, Norway, Croatia, Serbia and Turkey) and reported most results for the reference period 2008-2010. CIS 2010 also follows the recommendations of the Oslo Manual and reports indicators on four types of innovation: product, process, organisational and marketing. However, despite implementation of the recommendations of the third edition of the Oslo Manual, the question on innovation expenditures is still limited to product and process innovation in order to maintain continuity with earlier versions of the CIS. Furthermore, generally fewer questions are asked about organisational and marketing innovation than about product and process innovation. 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 the microdata on CD-ROM releases in more anonymised form; some countries also provide access to their micro-data at similar safe centres.
    • Май 2013
      Источник: Multiple Sources
      Загружен: Knoema
      Дата обращения к источнику: 13 мая, 2013
      Выбрать
      For latest data, please visit here: Federal Statistical Office of Germany-  https://knoema.com/atlas/sources/Federal-Statistical-Office-of-Germany Eurostat - https://knoema.com/atlas/sources/Eurostat  
    • Декабрь 2013
      Источник: Transparency International
      Загружен: Knoema
      Дата обращения к источнику: 20 февраля, 2014
      Выбрать
      Data cited at: Global Corruption Barometer (2013) by Transparency International is licensed under CC-BY-ND 4.0 Global Corruption Barometer is the largest world-wide public opinion survey on corruption - See more at: http://www.transparency.org/gcb2013/in_detail#sthash.hey9okGH.dpuf
    • Июль 2017
      Источник: International Telecommunication Union
      Загружен: Shakthi Krishnan
      Дата обращения к источнику: 13 сентября, 2017
      Выбрать
        The Global Cybersecurity Index (GCI) is a survey that measures the commitment of Member States to cybersecurity in order to raise awareness. The GCI revolves around the ITU Global Cybersecurity Agenda (GCA) and its five pillars (legal, technical, organizational, capacity building and cooperation). For each of these pillars, questions were developed to assess commitment. Through consultation with a group of experts, these questions were weighted in order to arrive at an overall GCI score. The survey was administered through an online platform through which supporting evidence was also collected. One-hundred and thirty-four Member States responded to the survey throughout 2016. Member States who did not respond were invited to validate responses determined from open-source research. As such, the GCI results reported herein cover all 193 ITU Member States. The 2017 publication of the GCI continues to show the commitment to cybersecurity of countries around the world. The overall picture shows improvement and strengthening of all five elements of the cybersecurity agenda in various countries in all regions. However, there is space for further improvement in cooperation at all levels, capacity building and organizational measures. As well, the gap in the level of cybersecurity engagement between different regions is still present and visible. The level of development of the different pillars varies from country to country in the regions, and while commitment in Europe remains very high in the legal and technical fields in particular, the challenging situation in the Africa and Americas regions shows the need for continued engagement and support. In addition to providing the GCI score, this report also provides a set of illustrative practices that give insight into the achievements of certain countries.
    • Март 2017
      Источник: World Economic Forum
      Загружен: Knoema
      Дата обращения к источнику: 19 апреля, 2017
      Выбрать
      Data cited at: The World Economic Forum https://www.weforum.org/ Topic: Global Energy Architecture Performance Index Report 2017 Publication URL: https://www.weforum.org/reports/global-energy-architecture-performance-index-report-2017 License: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode   The Energy Architecture Performance Index (EAPI) uses a set of indicators to highlight the performance of various countries across each facet of their energy architecture, determining to what extent nations have been able to create affordable, sustainable and secure energy systems   1)Economic growth and development: The extent to which energy architecture supports, rather than detracts from, economic growth and development 2) Environmental sustainability: The extent to which energy architecture has been constructed to minimize negative environmental externalities 3) Energy access and security: The extent to which energy architecture is at risk of an energy security impact, and whether adequate access to energy is provided to all parts of the population   Note: For detail methodology please visit:"http://www3.weforum.org/docs/WEF_GlobalEnergyArchitecturePerformance_Index_2017.pdf"
    • Январь 2014
      Источник: Oxfam
      Загружен: Knoema
      Дата обращения к источнику: 30 мая, 2014
      Выбрать
      Around the world, one in eight people go to bed hungry every night, even though there is enough food for everyone. Our graph illustrates how overconsumption, misuse of resources and waste are common elements of a system that leaves hundreds of millions without enough to eat.
    • Декабрь 2018
      Источник: World Economic Forum
      Загружен: Shakthi Krishnan
      Дата обращения к источнику: 03 января, 2019
      Выбрать
      Data cited at: The World Economic Forum https://www.weforum.org/ Topic:  The Global Gender Gap Report 2018 Publication URL: https://www.weforum.org/reports/the-global-gender-gap-report-2018 License: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode   Gender parity is fundamental to whether and how economies and societies thrive. Ensuring the full development and appropriate deployment of half of the world’s total talent pool has a vast bearing on the growth, competitiveness and future-readiness of economies and businesses worldwide. The Global Gender Gap Report benchmarks 149 countries on their progress towards gender parity across four thematic dimensions: Economic Participation and Opportunity, Educational Attainment, Health and Survival, and Political Empowerment. In addition, this year’s edition studies skills gender gaps related to Artificial Intelligence (AI)
    • Декабрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 мая, 2014
      Выбрать
      Eurostat Dataset Id:educ_bo_mo_gr4 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. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes, personnel in education and the cost and type of resources dedicated to education. The main source of data is the joint UIS (UNESCO Institute of Statistics)/OECD/Eurostat (UOE) questionnaires on education statistics, which constitute the core database on education. Data on regional enrolments and foreign language learning are collected additionally by Eurostat. Countries provide data, coming from administrative records, on the basis of commonly agreed definitions. From the UOE data collection, the following datasets on the Bologna Process are available: A. Widening access educ_bo_ac_ent2: Net entry rate (ISCED 5A) by age and sexeduc_bo_ac_ent3: Female entrants by field of education (ISCED 5A)educ_bo_ac_gent: Entrants at ISCED 5A and qualifying graduates of secondary schooling (ISCED 3A - 4A)educ_bo_ac_el1t: Students (ISCED 5A) studying part-time, by age B. Study framework educ_bo_fi_fgdp: Public expenditure on tertiary education (ISCED 5-6), as % of GDP or total public expenditureeduc_bo_fi_ftot: Annual total expenditure on educational institutions (ISCED 5-6) per full-time equivalent student with and without expenditure on research and ancillary serviceseduc_bo_fi_ffun: Tertiary education institutions' income from private sources (households and other private entities) as % of all public and private sourceseduc_bo_fi_fiaid: Public financial aid to tertiary students (ISCED 5-6), by type of aid, as % of public expenditure on tertiary education C. Student and staff mobility educ_bo_mo_el8o: Students (ISCED 5A and 6) who are nationals of a given country, studying in another country (EU-27, EFTA and CC) as % of the total enrolment in that countryeduc_bo_mo_el8i: Number of foreign students (world and Bologna Area) studying in a given country, as % of the total enrolment in that country, ISCED 5A and 6educ_bo_mo_gr4: Graduates (ISCED 5A and 6) from abroad (non-citizens, permanent residence and prior education outside the country) D. Effective outcomes and employability educ_bo_ou_gren: Gross graduation rate and net entry rate, ISCED 5A   The data for some countries which do not participate in the UOE data collection were provided to Eurostat specifically for the monitoring of the Bologna Process. Not being fully integrated in the UOE, the data sometimes might not be as comparable as the data for the remaining countries, due to differences in the underlying data sources and definitions. These data were provided by the following entities: Andorra (AD): data provided by the University of Andorra (indicators educ_bo_ac_ent3, educ_bo_fi_ffun, educ_bo_mo_el8i, educ_bo_mo_gr4)Armenia (AM): data provided by the Ministry of Education and Science (educ_bo_ac_gent, educ_bo_ac_el1t, educ_bo_mo_gr4, educ_bo_ou_gren)Georgia (GE): data provided by the NSI, Statistics Georgia (educ_bo_ac_ent3, educ_bo_ac_el1t, educ_bo_fi_fgdp, educ_bo_mo_gr4)Serbia (RS): data provided by the NSI, Statistical Office of the Republic of Serbia (educ_bo_mo_el8i)Ukraine (UA): data provided by the NSI, State Statistics Committee for Ukraine (educ_bo_ou_gren, educ_bo_ac_el1t, educ_bo_mo_el8i, educ_bo_mo_gr4, educ_bo_ou_gren)
    • Февраль 2016
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 18 марта, 2016
      Выбрать
      Graduates are those who successfully complete an educational programme during the reference year of the data collection. One condition of a successful completion is that students should have enrolled in, and successfully completed, the final year of the corresponding educational programme, although not necessarily in the year of reference. Students who do not complete the final year of an educational programme, but later successfully complete a recognised "equivalency" examination based on knowledge learned outside of the education system, should not be counted as graduates. Successful completion is defined according to the graduation requirements established by each country: in some countries, completion occurs as a result of passing a final, curriculum-based examination or series of examinations. In other countries, completion occurs after a specific number of teaching hours has been accumulated (although completion of some or all of the course hours may also involve examinations).
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 02 июля, 2019
      Выбрать
      Graduates are those who successfully complete an educational programme during the reference year of the data collection. One condition of a successful completion is that students should have enrolled in, and successfully completed, the final year of the corresponding educational programme, although not necessarily in the year of reference. Students who do not complete the final year of an educational programme, but later successfully complete a recognised "equivalency" examination based on knowledge learned outside of the education system, should not be counted as graduates. Successful completion is defined according to the graduation requirements established by each country: in some countries, completion occurs as a result of passing a final, curriculum-based examination or series of examinations. In other countries, completion occurs after a specific number of teaching hours has been accumulated (although completion of some or all of the course hours may also involve examinations).
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 марта, 2019
      Выбрать
      Eurostat Dataset Id:educ_momo_grd Statistics on student/graduate mobility and foreigners in tertiary education collected through the UOE data collection on education and training systems. Data concerning mobility and foreigners are collected as follows:Number of mobile and foreign enrolled students by level of education, programme destination and field of education.Number of mobile and foreign enrolled students by level of education, programme destination, EU/non EU/unknown membership and gender.Number of foreign enrolled students by level of education, programme destination and country of citizenship.Number of mobile enrolled students by level of education, programme destination, and country of origin (usual residence and/or country of prior education).Number of mobile and foreign graduates by level of education, programme destination, cumulative duration and gender. Data by both country of origin and country of destination of the students are disseminated. The absolute figures along with indicators are published.
    • Сентябрь 2010
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 12 декабря, 2015
      Выбрать
      Eurostat Dataset Id:vit_an7 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.
    • Январь 2015
      Источник: University of Groningen, Netherlands
      Загружен: Pallavi S
      Дата обращения к источнику: 25 февраля, 2016
      Выбрать
      The GGDC 10-Sector Database provides a long-run internationally comparable dataset on sectoral productivity performance in Asia, Europe, Latin America and the US. Variables covered in the data set are annual series of value added, output deflators, and persons employed for 10 broad sectors. It gives sectoral detail to the historical macro data in Maddison (2003) from 1950 onwards. It consists of series for 10 countries in Asia, 9 in Latin-America and 9 in Europe and the US. The data for Asia and Latin-America are based on Marcel P. Timmer and Gaaitzen J. de Vries (2007), 'A Cross-Country Database For Sectoral Employment And Productivity In Asia And Latin America, 1950-2005', GGDC Research memorandum GD-98, Groningen Growth and Development Centre, August 2007. Data for Europe and the US is based on an update of Bart van Ark (1996), Sectoral Growth Accounting and Structural Change in Post-War Europe, in B. van Ark and N.F.R. Crafts, eds., Quantitative Aspects of Post-War European Economic Growth, CEPR/Cambridge University Press, pp. 84-164. All series derived from this database need to be referred to as: "Timmer, Marcel P. and Gaaitzen J. de Vries (2009), "Structural Change and Growth Accelerations in Asia and Latin America: A New Sectoral Data Set" Cliometrica, vol 3 (issue 2) pp. 165-190."
    • Сентябрь 2016
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 01 октября, 2016
      Выбрать
      Eurostat Dataset Id:nama_pi64_c 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
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июля, 2019
      Выбрать
      This table contains research and development (R&D) expenditure statistics on gross domestic R&D expenditure by sector of performance (business enterprise, government, higher education, private non-profit, and total intramural) and by field of science (natural sciences, engineering, medical sciences, agricultural sciences, social sciences, and humanities). 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).
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 05 июля, 2019
      Выбрать
      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. Data include gross domestic R&D expenditure by sector of performance (business enterprise, government, higher education, private non-profit, and total intramural) and by type of costs (current expenditures: labour costs, other current costs; and capital expenditures: land and buildings, and instruments and equipment).
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 14 апреля, 2014
      Выбрать
      Eurostat Dataset Id:nama_r_e2gdp Gross domestic product - GDP at market prices - is the final result of the production activity of resident producer units (ESA 1995, 8.89). It can be defined in three ways: 1. Output approach GDP is the sum of gross value added of the various institutional sectors or the various industries plus taxes and less subsidies on products (which are not allocated to sectors and industries). It is also the balancing item in the total economy production account. 2. Expenditure approach GDP is the sum of final uses of goods and services by resident institutional units (final consumption expenditure and gross capital formation), plus exports and minus imports of goods and services. At regional level the expediture approach is not used in the EU, because there is no data on regional exports and imports.  3. Income approach GDP is the sum of uses in the total economy generation of income account: compensation of employees, taxes on production, less subsidies, gross operating surplus and mixed income of the total economy. The different measures for the regional GDP are absolute figures in € and Purchasing Power Standards (PPS), figures per inhabitant and relative data compared to the EU27 average.
    • Февраль 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 14 апреля, 2014
      Выбрать
      Eurostat Dataset Id:nama_r_e3gdp 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
    • Октябрь 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 21 октября, 2015
      Выбрать
      Eurostat Dataset Id:urt_e3gdp
    • Июнь 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 14 апреля, 2014
      Выбрать
      Eurostat Dataset Id:nama_r_e2gfcfr2 Branch accounts include data on gross value added, compensation of employees, gross fixed capital formation, total employment and number of employees. The legal base for the collection of branch accounts data is the European System of Accounts ESA95. The ESA95 data are sent to Eurostat by the National Statistical Institutes. The units for these variables are: Millions of national currency and millions of Euro for gross value added, compensation of employees and gross fixed capital formation. 1000 persons for total employment and number of employees at NUTS level 3 1000 hours worked for total employment and number of employees at NUTS level 2 Geographical coverage comprises all EU Member States and some Candidate countries down to Nuts 3 level (Nuts = "Nomenclature of territorial units for statistics" - see Eurostat's classification server "RAMON") for the variables gross value added, total employment and number of employees. Compensation of employees, employment in hours worked and gross fixed capital formation are only collected down to Nuts 2 level. For further information about sources and collection methods in the Member States, please refer to National Statistical Institutes (select Services - Links).
    • Декабрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 мая, 2014
      Выбрать
      Eurostat Dataset Id:educ_bo_ou_gren 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. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes, personnel in education and the cost and type of resources dedicated to education. The main source of data is the joint UIS (UNESCO Institute of Statistics)/OECD/Eurostat (UOE) questionnaires on education statistics, which constitute the core database on education. Data on regional enrolments and foreign language learning are collected additionally by Eurostat. Countries provide data, coming from administrative records, on the basis of commonly agreed definitions. From the UOE data collection, the following datasets on the Bologna Process are available: A. Widening access educ_bo_ac_ent2: Net entry rate (ISCED 5A) by age and sexeduc_bo_ac_ent3: Female entrants by field of education (ISCED 5A)educ_bo_ac_gent: Entrants at ISCED 5A and qualifying graduates of secondary schooling (ISCED 3A - 4A)educ_bo_ac_el1t: Students (ISCED 5A) studying part-time, by age B. Study framework educ_bo_fi_fgdp: Public expenditure on tertiary education (ISCED 5-6), as % of GDP or total public expenditureeduc_bo_fi_ftot: Annual total expenditure on educational institutions (ISCED 5-6) per full-time equivalent student with and without expenditure on research and ancillary serviceseduc_bo_fi_ffun: Tertiary education institutions' income from private sources (households and other private entities) as % of all public and private sourceseduc_bo_fi_fiaid: Public financial aid to tertiary students (ISCED 5-6), by type of aid, as % of public expenditure on tertiary education C. Student and staff mobility educ_bo_mo_el8o: Students (ISCED 5A and 6) who are nationals of a given country, studying in another country (EU-27, EFTA and CC) as % of the total enrolment in that countryeduc_bo_mo_el8i: Number of foreign students (world and Bologna Area) studying in a given country, as % of the total enrolment in that country, ISCED 5A and 6educ_bo_mo_gr4: Graduates (ISCED 5A and 6) from abroad (non-citizens, permanent residence and prior education outside the country) D. Effective outcomes and employability educ_bo_ou_gren: Gross graduation rate and net entry rate, ISCED 5A   The data for some countries which do not participate in the UOE data collection were provided to Eurostat specifically for the monitoring of the Bologna Process. Not being fully integrated in the UOE, the data sometimes might not be as comparable as the data for the remaining countries, due to differences in the underlying data sources and definitions. These data were provided by the following entities: Andorra (AD): data provided by the University of Andorra (indicators educ_bo_ac_ent3, educ_bo_fi_ffun, educ_bo_mo_el8i, educ_bo_mo_gr4)Armenia (AM): data provided by the Ministry of Education and Science (educ_bo_ac_gent, educ_bo_ac_el1t, educ_bo_mo_gr4, educ_bo_ou_gren)Georgia (GE): data provided by the NSI, Statistics Georgia (educ_bo_ac_ent3, educ_bo_ac_el1t, educ_bo_fi_fgdp, educ_bo_mo_gr4)Serbia (RS): data provided by the NSI, Statistical Office of the Republic of Serbia (educ_bo_mo_el8i)Ukraine (UA): data provided by the NSI, State Statistics Committee for Ukraine (educ_bo_ou_gren, educ_bo_ac_el1t, educ_bo_mo_el8i, educ_bo_mo_gr4, educ_bo_ou_gren)
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 14 апреля, 2014
      Выбрать
      Eurostat Dataset Id:nama_r_e3vab95r2 Branch accounts include data on gross value added, compensation of employees, gross fixed capital formation, total employment and number of employees. The legal base for the collection of branch accounts data is the European System of Accounts ESA95. The ESA95 data are sent to Eurostat by the National Statistical Institutes. The units for these variables are: Millions of national currency and millions of Euro for gross value added, compensation of employees and gross fixed capital formation. 1000 persons for total employment and number of employees at NUTS level 3 1000 hours worked for total employment and number of employees at NUTS level 2 Geographical coverage comprises all EU Member States and some Candidate countries down to Nuts 3 level (Nuts = "Nomenclature of territorial units for statistics" - see Eurostat's classification server "RAMON") for the variables gross value added, total employment and number of employees. Compensation of employees, employment in hours worked and gross fixed capital formation are only collected down to Nuts 2 level. For further information about sources and collection methods in the Member States, please refer to National Statistical Institutes (select Services - Links).
  • H
    • Июнь 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 14 июня, 2012
      Выбрать
      HICP are part of a series of Euro-indicators that are designed to give a general overview of the euro area, European Union and Member State's economic situation. The tables include, for the latest 12 months: Indices Growth rates with respect to the previous month (M/M-1) Growth rates with respect to the corresponding month of the previous year Data are automatically updated on release dates (see release calendar) and are neither calendar nor seasonally adjusted.
    • Ноябрь 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 02 декабря, 2017
      Выбрать
      Eurostat Dataset Id:ei_nasa_q Data in this domain constitute only a small part of the entire National Accounts data range available from Eurostat. The size of the data collection is reduced by selecting only the most frequently used variables, breakdowns and presentations. Annual and Quarterly 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 (new ESA95 transmission programme). 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 a selection for variables from the following collections: Aggregates by branch of gross value added, compensation of employees, wages and salaries, operating surplus and employment (domestic scope) by industry. Main aggregates, in particular GDP and its breakdown from the expenditure side and gross value added. Income aggregates, in particular income, saving and net lending / net borrowing. Price and cost indices, in particular the implicit price indices corresponding to Main aggregates.
    • Май 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 июля, 2015
      Выбрать
      Eurostat Dataset Id:hlth_sha_hf Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. 3.2. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003.
    • Май 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 июля, 2015
      Выбрать
      Eurostat Dataset Id:hlth_sha_ltc Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. 3.2. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003.
    • Июнь 2010
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Выбрать
      OECD Health Data 2010 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.
    • Февраль 2010
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 апреля, 2014
      Выбрать
      Eurostat Dataset Id:nrg_esdgr_a Consumption of energy depends strongly on weather conditions. If the temperature decreases below a certain value, "heating threshold", more energy is consumed due to increased need for space heating. Taking this into account, Eurostat launched a project aiming at the development and implementation of a common method for the climatic correction of final energy consumption for space heating purposes in the 27 Member States of the European Union. Temperature corrected energy consumption data help interpretating energy consumption trends.
    • Ноябрь 2010
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 30 декабря, 2013
      Выбрать
      Eurostat Dataset Id:inn_cis6_mkobj The Community Innovation Survey (CIS) is a survey of innovation activity in enterprises. The harmonised 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, type 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, in close cooperation with the countries, has developed a standard core questionnaire starting with the CIS3 data collection, along with an accompanying set of definitions and methodological recommendations. The concepts and underlying methodology of the CIS are also based on the Oslo Manual — second edition of 1997 and third edition of 2005 . Up to CIS 2010, CIS results were collected under Commission Regulation (EC) No 1450/2004. A new Regulation will apply from CIS 2012 (EC No 995/2012). The data presented in these tables refer to enterprises with ‘10 employees or more’ active in the sectors to be covered under the Regulation (cf. NACE CORE). Further activities may be covered on a voluntary basis. Most statistics are based on a reference period of three years, but some use one calendar year. Since CIS 2008, the survey has included an ad-hoc module. It consists of a set of questions focusing on a special theme. The themes are different in each survey wave, allowing data to be obtained on specific issues beyond the data usually collected. Overview over time: Initially, the CIS data collection was carried out every four years. The first collection (CIS Light) was launched in 1993 as a pilot exercise and the second (CIS2) was carried out in 1997/1998 for most countries except Greece and Ireland, where it was launched in 1999. The third survey (CIS3) was conducted in 2000/2001 for most participating countries with the exception of Norway, Iceland, Luxembourg and Greece, where it was launched in 2002. As from 2004, the survey has been carried out every two years. CIS4 was conducted in the 25 EU Member States (as for 2004), Iceland, Norway, Bulgaria and Romania. The survey was launched in 2005 with a three-year reference period 2002 to 2004 for most indicators. The fifth survey CIS 2006 was carried out in all 25 EU Member States (as for 2006), Norway, Bulgaria, Romania, Croatia and Turkey. It was launched in 2007, mostly for the reference period 2004 to 2006. As regards CIS 2008, 26 Member States (all except Greece), Iceland, Norway, Croatia and Turkey took part in the survey. CIS 2008 was launched in 2009 with a three-year reference period 2006 to 2008 for most indicators. Changes were made to the CIS 2008 questionnaire to bring it into line with the third revision of the Oslo Manual, 2005 edition, by giving greater weight to organisational and marketing innovation. CIS 2008 was complemented by an ad-hoc module on innovation with environmental benefits. The seventh Community Innovation Survey, CIS 2010, had 31 participating countries (all the EU 27 Member States (except Greece), Iceland, Norway, Croatia, Serbia and Turkey) and reported most results for the reference period 2008-2010. CIS 2010 also follows the recommendations of the Oslo Manual and reports indicators on four types of innovation: product, process, organisational and marketing. However, despite implementation of the recommendations of the third edition of the Oslo Manual, the question on innovation expenditures is still limited to product and process innovation in order to maintain continuity with earlier versions of the CIS. Furthermore, generally fewer questions are asked about organisational and marketing innovation than about product and process innovation. 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 the microdata on CD-ROM releases in more anonymised form; some countries also provide access to their micro-data at similar safe centres.
    • Ноябрь 2010
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 29 декабря, 2013
      Выбрать
      Eurostat Dataset Id:inn_cis6_orobj The Community Innovation Survey (CIS) is a survey of innovation activity in enterprises. The harmonised 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, type 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, in close cooperation with the countries, has developed a standard core questionnaire starting with the CIS3 data collection, along with an accompanying set of definitions and methodological recommendations. The concepts and underlying methodology of the CIS are also based on the Oslo Manual — second edition of 1997 and third edition of 2005 . Up to CIS 2010, CIS results were collected under Commission Regulation (EC) No 1450/2004. A new Regulation will apply from CIS 2012 (EC No 995/2012). The data presented in these tables refer to enterprises with ‘10 employees or more’ active in the sectors to be covered under the Regulation (cf. NACE CORE). Further activities may be covered on a voluntary basis. Most statistics are based on a reference period of three years, but some use one calendar year. Since CIS 2008, the survey has included an ad-hoc module. It consists of a set of questions focusing on a special theme. The themes are different in each survey wave, allowing data to be obtained on specific issues beyond the data usually collected. Overview over time: Initially, the CIS data collection was carried out every four years. The first collection (CIS Light) was launched in 1993 as a pilot exercise and the second (CIS2) was carried out in 1997/1998 for most countries except Greece and Ireland, where it was launched in 1999. The third survey (CIS3) was conducted in 2000/2001 for most participating countries with the exception of Norway, Iceland, Luxembourg and Greece, where it was launched in 2002. As from 2004, the survey has been carried out every two years. CIS4 was conducted in the 25 EU Member States (as for 2004), Iceland, Norway, Bulgaria and Romania. The survey was launched in 2005 with a three-year reference period 2002 to 2004 for most indicators. The fifth survey CIS 2006 was carried out in all 25 EU Member States (as for 2006), Norway, Bulgaria, Romania, Croatia and Turkey. It was launched in 2007, mostly for the reference period 2004 to 2006. As regards CIS 2008, 26 Member States (all except Greece), Iceland, Norway, Croatia and Turkey took part in the survey. CIS 2008 was launched in 2009 with a three-year reference period 2006 to 2008 for most indicators. Changes were made to the CIS 2008 questionnaire to bring it into line with the third revision of the Oslo Manual, 2005 edition, by giving greater weight to organisational and marketing innovation. CIS 2008 was complemented by an ad-hoc module on innovation with environmental benefits. The seventh Community Innovation Survey, CIS 2010, had 31 participating countries (all the EU 27 Member States (except Greece), Iceland, Norway, Croatia, Serbia and Turkey) and reported most results for the reference period 2008-2010. CIS 2010 also follows the recommendations of the Oslo Manual and reports indicators on four types of innovation: product, process, organisational and marketing. However, despite implementation of the recommendations of the third edition of the Oslo Manual, the question on innovation expenditures is still limited to product and process innovation in order to maintain continuity with earlier versions of the CIS. Furthermore, generally fewer questions are asked about organisational and marketing innovation than about product and process innovation. 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 the microdata on CD-ROM releases in more anonymised form; some countries also provide access to their micro-data at similar safe centres.
    • Март 2010
      Источник: Maddison Project
      Загружен: Knoema
      Выбрать
      Historical Statistics on Population, GDP and Per Capita GDP for 1-2008 AD period. Copyright Angus Maddison.
    • Ноябрь 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 апреля, 2014
      Выбрать
      Eurostat Dataset Id:vit_bs3 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.
    • Декабрь 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 апреля, 2014
      Выбрать
      Eurostat Dataset Id:vit_bs1 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.
    • Ноябрь 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 12 декабря, 2015
      Выбрать
      Eurostat Dataset Id:vit_bs2 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.
    • Март 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 июня, 2014
      Выбрать
      Eurostat Dataset Id:lc_n08hour_r2 Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Structural information on labour costs is collected through four-yearly Labour Cost Surveys (LCSs), which provides details on level and structure of labour cost data, hours worked and hours paid. LCS results are available for the reference years 2000, 2004 and 2008. All EU Member States together with Norway, Iceland and Croatia (2004, 2008), Turkey and Macedonia (2008) participated in the LCS. As far as available data and confidentiality rules permit, all variables and proportions are further broken down by enterprise size category, economic activity and region (larger countries only). The data are collected by the National Statistical Institutes in most cases on the basis of stratified random samples of enterprises or local units, restricted in most countries to units with at least 10 employees. The stratification is based on economic activity, size category and region (where appropriate). Regional metadata is identical to the metadata provided for national data. Some countries also complement the survey results with administrative data. Monetary variables are expressed in EUR, national currencies (if different) and Purchasing Power Standards (PPS). Labour costs are quoted in total and per year, per month and per hour, as well as per capita and per full-time equivalents (FTE). Information on staff, hours worked and hours paid is quoted in aggregate and separately for full- and part-time employees. Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_hour06s There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Январь 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_cvts76 CVTS2, CVTS3 and CVTS4 data were collected with reference year 1999, 2005 and 2010 in order to provide harmonised, reliable and relevant statistical information on continuing vocational training in enterprises. CVT stands for continuing vocational training i.e. education and training occurring during paid working time or paid at least partially by employers (if training activities are organised outside paid working time). CVTS 2, 3 and 4 provide statistics on incidence of training in enterprises, participation of employees and volume of CVT courses, CVT costs as well as CVT strategies of enterprises including on Initial vocational training (IVT, i.e. apprenticeship). The section "past series on lifelong learning" presents tables which are no longer available in the same format or at the same level of precision as CVTS 4. The CVTS1 was the first survey on continuing vocational training in enterprises carried out on the EU level in a co-ordinated form (outline questionnaire, common definitions, and common recommendations with the respect to the fieldwork). The survey was of pioneering nature, and is not any longer disseminated due to lack of comparability with the following waves.
    • Январь 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_cvts78 CVTS2, CVTS3 and CVTS4 data were collected with reference year 1999, 2005 and 2010 in order to provide harmonised, reliable and relevant statistical information on continuing vocational training in enterprises.CVT stands for continuing vocational training i.e. education and training occurring during paid working time or paid at least partially by employers (if training activities are organised outside paid working time). CVTS 2, 3 and 4 provide statistics on incidence of training in enterprises, participation of employees and volume of CVT courses, CVT costs as well as CVT strategies of enterprises including on Initial vocational training (IVT, i.e. apprenticeship). The section "past series on lifelong learning" presents tables which are no longer available in the same format or at the same level of precision as CVTS 4. The CVTS1 was the first survey on continuing vocational training in enterprises carried out on the EU level in a co-ordinated form (outline questionnaire, common definitions, and common recommendations with the respect to the fieldwork). The survey was of pioneering nature, and is not any longer disseminated due to lack of comparability with the following waves.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_hour05s There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Январь 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_cvts72 CVTS2, CVTS3 and CVTS4 data were collected with reference year 1999, 2005 and 2010 in order to provide harmonised, reliable and relevant statistical information on continuing vocational training in enterprises.CVT stands for continuing vocational training i.e. education and training occurring during paid working time or paid at least partially by employers (if training activities are organised outside paid working time). CVTS 2, 3 and 4 provide statistics on incidence of training in enterprises, participation of employees and volume of CVT courses, CVT costs as well as CVT strategies of enterprises including on Initial vocational training (IVT, i.e. apprenticeship). The section "past series on lifelong learning" presents tables which are no longer available in the same format or at the same level of precision as CVTS 4. The CVTS1 was the first survey on continuing vocational training in enterprises carried out on the EU level in a co-ordinated form (outline questionnaire, common definitions, and common recommendations with the respect to the fieldwork). The survey was of pioneering nature, and is not any longer disseminated due to lack of comparability with the following waves.
    • Декабрь 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_cvts27 CVTS2, CVTS3 and CVTS4 data were collected with reference year 1999, 2005 and 2010 in order to provide harmonised, reliable and relevant statistical information on continuing vocational training in enterprises.CVT stands for continuing vocational training i.e. education and training occurring during paid working time or paid at least partially by employers (if training activities are organised outside paid working time). CVTS 2, 3 and 4 provide statistics on incidence of training in enterprises, participation of employees and volume of CVT courses, CVT costs as well as CVT strategies of enterprises including on Initial vocational training (IVT, i.e. apprenticeship). The section "past series on lifelong learning" presents tables which are no longer available in the same format or at the same level of precision as CVTS 4. The CVTS1 was the first survey on continuing vocational training in enterprises carried out on the EU level in a co-ordinated form (outline questionnaire, common definitions, and common recommendations with the respect to the fieldwork). The survey was of pioneering nature, and is not any longer disseminated due to lack of comparability with the following waves.
    • Декабрь 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_cvts74 CVTS2, CVTS3 and CVTS4 data were collected with reference year 1999, 2005 and 2010 in order to provide harmonised, reliable and relevant statistical information on continuing vocational training in enterprises.CVT stands for continuing vocational training i.e. education and training occurring during paid working time or paid at least partially by employers (if training activities are organised outside paid working time). CVTS 2, 3 and 4 provide statistics on incidence of training in enterprises, participation of employees and volume of CVT courses, CVT costs as well as CVT strategies of enterprises including on Initial vocational training (IVT, i.e. apprenticeship). The section "past series on lifelong learning" presents tables which are no longer available in the same format or at the same level of precision as CVTS 4. The CVTS1 was the first survey on continuing vocational training in enterprises carried out on the EU level in a co-ordinated form (outline questionnaire, common definitions, and common recommendations with the respect to the fieldwork). The survey was of pioneering nature, and is not any longer disseminated due to lack of comparability with the following waves.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_hour09s There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_hour10s There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Январь 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_cvts22 CVTS2, CVTS3 and CVTS4 data were collected with reference year 1999, 2005 and 2010 in order to provide harmonised, reliable and relevant statistical information on continuing vocational training in enterprises.CVT stands for continuing vocational training i.e. education and training occurring during paid working time or paid at least partially by employers (if training activities are organised outside paid working time). CVTS 2, 3 and 4 provide statistics on incidence of training in enterprises, participation of employees and volume of CVT courses, CVT costs as well as CVT strategies of enterprises including on Initial vocational training (IVT, i.e. apprenticeship). The section "past series on lifelong learning" presents tables which are no longer available in the same format or at the same level of precision as CVTS 4. The CVTS1 was the first survey on continuing vocational training in enterprises carried out on the EU level in a co-ordinated form (outline questionnaire, common definitions, and common recommendations with the respect to the fieldwork). The survey was of pioneering nature, and is not any longer disseminated due to lack of comparability with the following waves.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_hour01s There are three main sources providing results on participation in education and training. - The Adult Education Survey (AES) is carried out every 5 years starting from 2011 and is designed to give detailed information on the participation of individuals in education and training activities. A pilot survey took place in 2007. The reference period for the participation in education and training activities is the twelve months prior to the interview. - The Labour Force Survey (LFS) provides annual evolutions for a limited set of indicators. The reference period for the participation in education and training activities is the four weeks prior to the interview. - The Continuing Vocational Training Survey (CVTS) completes the AES results each 5 years focussing on enterprise strategies for employee skill developments. The reference period for the participation in education and training activities is the four weeks prior to the interview. The time series for the indicator 'lifelong learning' (participation of adults aged 25-64 in education and training) is based on the EU-LFS (four-week reference period) which 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 Labour Force Survey data with reference to the available quarter(s)) In addition to these series, an ad-hoc module to the LFS was conducted in 2003 on lifelong leaninng with similar characteristics to the AES (12-month reference period). Life-long learning is also part of the Sustainable Development Indicators.
    • Январь 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_cvts66 CVTS2, CVTS3 and CVTS4 data were collected with reference year 1999, 2005 and 2010 in order to provide harmonised, reliable and relevant statistical information on continuing vocational training in enterprises.CVT stands for continuing vocational training i.e. education and training occurring during paid working time or paid at least partially by employers (if training activities are organised outside paid working time). CVTS 2, 3 and 4 provide statistics on incidence of training in enterprises, participation of employees and volume of CVT courses, CVT costs as well as CVT strategies of enterprises including on Initial vocational training (IVT, i.e. apprenticeship). The section "past series on lifelong learning" presents tables which are no longer available in the same format or at the same level of precision as CVTS 4. The CVTS1 was the first survey on continuing vocational training in enterprises carried out on the EU level in a co-ordinated form (outline questionnaire, common definitions, and common recommendations with the respect to the fieldwork). The survey was of pioneering nature, and is not any longer disseminated due to lack of comparability with the following waves.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 01 июля, 2014
      Выбрать
      Eurostat Dataset Id:lc_n00hour Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Structural information on labour costs is collected through four-yearly Labour Cost Surveys (LCSs), which provides details on level and structure of labour cost data, hours worked and hours paid. LCS results are available for the reference years 2000, 2004 and 2008. All EU Member States together with Norway, Iceland and Croatia (2004, 2008), Turkey and Macedonia (2008) participated in the LCS. As far as available data and confidentiality rules permit, all variables and proportions are further broken down by enterprise size category, economic activity and region (larger countries only). The data are collected by the National Statistical Institutes in most cases on the basis of stratified random samples of enterprises or local units, restricted in most countries to units with at least 10 employees. The stratification is based on economic activity, size category and region (where appropriate). Regional metadata is identical to the metadata provided for national data. Some countries also complement the survey results with administrative data. Monetary variables are expressed in EUR, national currencies (if different) and Purchasing Power Standards (PPS). Labour costs are quoted in total and per year, per month and per hour, as well as per capita and per full-time equivalents (FTE). Information on staff, hours worked and hours paid is quoted in aggregate and separately for full- and part-time employees. Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs.
    • Март 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 01 декабря, 2015
      Выбрать
      Eurostat Dataset Id:yth_incl_160 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.
  • I
    • Январь 2008
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 22 сентября, 2014
      Выбрать
      ICT goods are those that are either intended to fulfil the function of information processing and communication by electronic means, including transmission and display, OR which use electronic processing to detect, measure and/or record physical phenomena, or to control a physical process. ICT goods are defined by the OECD in terms of the Harmonised System. The guiding principle for the delineation of ICT goods is that such goods must either be intended to fulfil the function of information processing and communication by electronic means, including transmission and display, OR use electronic processing to detect, measure and/or record physical phenomena, or to control a physical process.Another guiding principle was to use existing classification systems in order to take advantage of existing data sets and therefore ensure the immediate use of the proposed standard. In this case, the underlying system is the Harmonized System (HS). The HS is the only commodity classification system used on a sufficiently wide basis to support international data comparison. A large number of countries use it to classify export and import of goods, and many countries use it (or a classification derived from or linked to it) to categorise domestic outputs.The application of the ICT product definition to selection of in-scope HS categories is a somewhat subjective exercise. The fact that the HS is not built on the basis of the functionality of products makes it much more difficult. The distinction between products which fulfil those functions and products that simply embody electronics but fundamentally fulfil other functions is not always obvious.It is possible to adopt a narrow or broad interpretation of the guideline, though the OECD chose a broader interpretation, an approach which is consistent with that adopted to develop the ICT sector definition.
    • Февраль 2011
      Источник: Institute for Health Metrics and Evaluation
      Загружен: Knoema
      Выбрать
      IHME results from paper, Worldwide mortality in men and women aged 15–59 years from 1970 to 2010: a systematic analysis, published online in The Lancet on April 30 2010. This dataset provides global estimates of adult mortality risk, 45q15 (probability of death between the ages of 15 years and 60 years), between 1970 and 2010.
    • Февраль 2011
      Источник: Institute for Health Metrics and Evaluation
      Загружен: Knoema
      Выбрать
      IHME results from paper, Neonatal, post neonatal, childhood, and under-5 mortality for 187 countries, 1970-2010: a systematic analysis of progress towards Millennium Development Goal 4, published online in The Lancet on May 24 2010. This dataset provides estimates of neonatal, post neonatal, childhood, and under-5 mortality for 187 countries between 1970 and 2010.
    • Декабрь 2010
      Источник: Institute for Health Metrics and Evaluation
      Загружен: Knoema
      Дата обращения к источнику: 31 июля, 2013
      Выбрать
      IHME research, published online in The Lancet in April 2010, with data from a global assessment of levels and trends in maternal mortality for the years 1980-2008. The study, Maternal mortality for 181 countries, 1980-2008: a systematic analysis of progress towards Millennium Development Goal 5, provides global, regional, and national level estimates of the maternal mortality ratio (MMR - the number of maternal deaths per 100,000 live births) as well as the number of maternal deaths.
    • Сентябрь 2011
      Источник: Institute for Health Metrics and Evaluation
      Загружен: Knoema
      Выбрать
      IHME results data from global analysis of maternal mortality for years 1990-2011 published online in The Lancet in September 2011. The study, Progress towards Millennium Development Goals 4 and 5 on maternal and child mortality: an updated systematic analysis, provides global and country level estimates of the maternal mortality ratio (MMR - the number of maternal deaths per 100,000 live births) and the number of maternal deaths.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 03 декабря, 2018
      Выбрать
      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 03 декабря, 2018
      Выбрать
      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 03 декабря, 2018
      Выбрать
      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older with a tertiary education.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 03 декабря, 2018
      Выбрать
      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 03 декабря, 2018
      Выбрать
      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.
    • Ноябрь 2010
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 30 декабря, 2013
      Выбрать
      Eurostat Dataset Id:inn_cis6_mktype The Community Innovation Survey (CIS) is a survey of innovation activity in enterprises. The harmonised 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, type 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, in close cooperation with the countries, has developed a standard core questionnaire starting with the CIS3 data collection, along with an accompanying set of definitions and methodological recommendations. The concepts and underlying methodology of the CIS are also based on the Oslo Manual — second edition of 1997 and third edition of 2005 . Up to CIS 2010, CIS results were collected under Commission Regulation (EC) No 1450/2004. A new Regulation will apply from CIS 2012 (EC No 995/2012). The data presented in these tables refer to enterprises with ‘10 employees or more’ active in the sectors to be covered under the Regulation (cf. NACE CORE). Further activities may be covered on a voluntary basis. Most statistics are based on a reference period of three years, but some use one calendar year. Since CIS 2008, the survey has included an ad-hoc module. It consists of a set of questions focusing on a special theme. The themes are different in each survey wave, allowing data to be obtained on specific issues beyond the data usually collected. Overview over time: Initially, the CIS data collection was carried out every four years. The first collection (CIS Light) was launched in 1993 as a pilot exercise and the second (CIS2) was carried out in 1997/1998 for most countries except Greece and Ireland, where it was launched in 1999. The third survey (CIS3) was conducted in 2000/2001 for most participating countries with the exception of Norway, Iceland, Luxembourg and Greece, where it was launched in 2002. As from 2004, the survey has been carried out every two years. CIS4 was conducted in the 25 EU Member States (as for 2004), Iceland, Norway, Bulgaria and Romania. The survey was launched in 2005 with a three-year reference period 2002 to 2004 for most indicators. The fifth survey CIS 2006 was carried out in all 25 EU Member States (as for 2006), Norway, Bulgaria, Romania, Croatia and Turkey. It was launched in 2007, mostly for the reference period 2004 to 2006. As regards CIS 2008, 26 Member States (all except Greece), Iceland, Norway, Croatia and Turkey took part in the survey. CIS 2008 was launched in 2009 with a three-year reference period 2006 to 2008 for most indicators. Changes were made to the CIS 2008 questionnaire to bring it into line with the third revision of the Oslo Manual, 2005 edition, by giving greater weight to organisational and marketing innovation. CIS 2008 was complemented by an ad-hoc module on innovation with environmental benefits. The seventh Community Innovation Survey, CIS 2010, had 31 participating countries (all the EU 27 Member States (except Greece), Iceland, Norway, Croatia, Serbia and Turkey) and reported most results for the reference period 2008-2010. CIS 2010 also follows the recommendations of the Oslo Manual and reports indicators on four types of innovation: product, process, organisational and marketing. However, despite implementation of the recommendations of the third edition of the Oslo Manual, the question on innovation expenditures is still limited to product and process innovation in order to maintain continuity with earlier versions of the CIS. Furthermore, generally fewer questions are asked about organisational and marketing innovation than about product and process innovation. 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 the microdata on CD-ROM releases in more anonymised form; some countries also provide access to their micro-data at similar safe centres.
    • Ноябрь 2010
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 30 декабря, 2013
      Выбрать
      Eurostat Dataset Id:inn_cis6_ortype The Community Innovation Survey (CIS) is a survey of innovation activity in enterprises. The harmonised 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, type 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, in close cooperation with the countries, has developed a standard core questionnaire starting with the CIS3 data collection, along with an accompanying set of definitions and methodological recommendations. The concepts and underlying methodology of the CIS are also based on the Oslo Manual — second edition of 1997 and third edition of 2005 . Up to CIS 2010, CIS results were collected under Commission Regulation (EC) No 1450/2004. A new Regulation will apply from CIS 2012 (EC No 995/2012). The data presented in these tables refer to enterprises with ‘10 employees or more’ active in the sectors to be covered under the Regulation (cf. NACE CORE). Further activities may be covered on a voluntary basis. Most statistics are based on a reference period of three years, but some use one calendar year. Since CIS 2008, the survey has included an ad-hoc module. It consists of a set of questions focusing on a special theme. The themes are different in each survey wave, allowing data to be obtained on specific issues beyond the data usually collected. Overview over time: Initially, the CIS data collection was carried out every four years. The first collection (CIS Light) was launched in 1993 as a pilot exercise and the second (CIS2) was carried out in 1997/1998 for most countries except Greece and Ireland, where it was launched in 1999. The third survey (CIS3) was conducted in 2000/2001 for most participating countries with the exception of Norway, Iceland, Luxembourg and Greece, where it was launched in 2002. As from 2004, the survey has been carried out every two years. CIS4 was conducted in the 25 EU Member States (as for 2004), Iceland, Norway, Bulgaria and Romania. The survey was launched in 2005 with a three-year reference period 2002 to 2004 for most indicators. The fifth survey CIS 2006 was carried out in all 25 EU Member States (as for 2006), Norway, Bulgaria, Romania, Croatia and Turkey. It was launched in 2007, mostly for the reference period 2004 to 2006. As regards CIS 2008, 26 Member States (all except Greece), Iceland, Norway, Croatia and Turkey took part in the survey. CIS 2008 was launched in 2009 with a three-year reference period 2006 to 2008 for most indicators. Changes were made to the CIS 2008 questionnaire to bring it into line with the third revision of the Oslo Manual, 2005 edition, by giving greater weight to organisational and marketing innovation. CIS 2008 was complemented by an ad-hoc module on innovation with environmental benefits. The seventh Community Innovation Survey, CIS 2010, had 31 participating countries (all the EU 27 Member States (except Greece), Iceland, Norway, Croatia, Serbia and Turkey) and reported most results for the reference period 2008-2010. CIS 2010 also follows the recommendations of the Oslo Manual and reports indicators on four types of innovation: product, process, organisational and marketing. However, despite implementation of the recommendations of the third edition of the Oslo Manual, the question on innovation expenditures is still limited to product and process innovation in order to maintain continuity with earlier versions of the CIS. Furthermore, generally fewer questions are asked about organisational and marketing innovation than about product and process innovation. 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 the microdata on CD-ROM releases in more anonymised form; some countries also provide access to their micro-data at similar safe centres.
    • Февраль 2004
      Источник: National Institute of Statistics of Equatorial Guinea
      Загружен: Knoema
      Дата обращения к источнику: 02 июня, 2013
      Выбрать
    • Июль 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 04 августа, 2014
      Выбрать
      The allocation of bilateral intermediate imports across using industries assumes that import coefficients are the same for all trade partners, i.e. SHAREipkt is identical across exporter countries. Hence, the bilateral pattern of imported intermediates from industry p is the same across all using industries k. However, it is different from the bilateral pattern of total imports from industry p because trade data (measured by VALUEijpt) allows distinguishing bilateral imports of intermediates from final good imports in industry p. While the BEC classification enables the identification of intermediate goods, no similar classification is available for trade in services, due to the high level of aggregation in services trade data. While goods trade data are based on customs declarations allowing the identification of goods at a highly disaggregated level, services trade data are based on a variety of information such as business accounts, administrative sources, surveys, and estimation techniques (Manual on Statistics of International Trade in Services, 2002). Hence, in the case of trade in services, VALUEijpt is the total value of imports of service p, i.e. both final and intermediate (and not only services that are used in the production of other goods and services, as in the case of goods data). By making an additional assumption and adjusting SHAREipkt, it is however possible to calculate trade in intermediate services. In the case of services imports, SHAREipkt is the share of imported service inputs p used by industry k in total imports of p of country i. In the case of services, besides the assumption that all trading partners have the same distribution of intermediate imports p across using industries k, it is furthermore required that the share of intermediate services in overall bilateral services imports of country i is the same across all partner countries j. Finally, it should be mentioned that trade data reported in the trade statistics do not fully match imports as reported in I-O tables. One main reason is that while trade data is recorded at consumer prices, I-O tables are evaluated at producer prices. There are also other differences such as the treatment of re-exports, scrap metal, waste products and second hand goods or unallocated trade data.
    • Июль 2015
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 08 октября, 2015
      Выбрать
      This table contains data on discouraged jobseekers as a percentage of the labour force and as a percentage of the population by sex and standardised age groups (15-24, 15-64, 25-54, 55-64, 65+, total). Unit of measure used - Data are expressed as percentages.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
      Выбрать
      This table contains the shares of economic short-time workers among total employment, the ratio of economic short-time workers and labour force, and the gender composition of economic short-time workers. Data re broken down by professional status - employees, total employment – by sex and standardised age groups (15-24, 25-54, 55+, total). Unit of measure used - Data are expressed as percentages.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июля, 2019
      Выбрать
      This table contains incidences and gender composition of part-time employment with standardised (15-24, 25-54, 55-64, 65+, total) and detailed age groups. Data are further broken down by professional status - employees, total employment. Part-time employment is based on a common 30-usual-hour cut-off in the main job. Unit of measure used - Data are expressed in percentages.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 21 июня, 2019
      Выбрать
      This table contains incidences and gender composition of part-time employment with standardised (15-24, 25-54, 55-64, 65+, total) and detailed age groups. Data are further broken down by professional status - employees, total employment. Part-time employment is based on national definitions. The definition of part-time work varies considerably across OECD countries Essentially three main approaches can be distinguished: i) a classification based on the worker's perception of his/her employment situation; ii) a cut-off (generally 30 or 35 hours per week) based on usual working hours, with persons usually working fewer hours being considered part-timers; iii) a comparable cut-off based on actual hours worked during the reference week. A criterion based on actual hours will generally yield a part-time rate higher than one based on usual hours, particularly if there are temporary reductions in working time as a result of holidays, illness, short-timing, etc. On the other hand, it is not entirely clear whether a classification based on the worker's perception will necessarily yield estimates of part-time work that are higher or lower than one based on a fixed cut-off. In one country (France) which changed from 1981 to 1982 from a definition based on an actual hours cut-off (30 hours) to one based on the respondent's perception, the latter criterion appeared to produce slightly higher estimates. Other data characteristics
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 21 июня, 2019
      Выбрать
      This table contains incidences and gender composition of temporary employment with standardized age groups (15-24, 25-54, 55-64, 65+, total). Data are further broken down by professional status - employees, total employment. Unit of measure used - Data are expressed in percentages.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июля, 2019
      Выбрать
      This table contains data on the share of the five durations - less than 1 month,>1 month and < 3 months,>3 months and <6 months,>6 months and <1 year, 1 year and over - of unemployment among total unemployment by sex and by standardised age groups (15-19, 15-24, 20-24, 25-54, 55+, total). Unit of measure used - Data expressed in percentages.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 15 апреля, 2014
      Выбрать
      Eurostat Dataset Id:nama_r_ehh2inc 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").
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 05 июля, 2019
      Выбрать
      Bank profitability statistics are based on financial statements of banks in each Member country and are presented in the standard OECD framework. Although the objective is to include all institutions which conduct ordinary banking business, namely institutions which primarily take deposits from the public and provide finance for a wide range of purposes, the institutional coverage of banks in the statistics available in this database is not the same in each country. Ratios based on various items of the income statements and balance sheets of banks in percentage of some aggregates are also provided to facilitate the analysis of trends in bank profitability of OECD countries.
    • Сентябрь 2015
      Источник: Pearson
      Загружен: Knoema
      Дата обращения к источнику: 15 октября, 2015
      Выбрать
      The Global Index of Cognitive Skills and Educational Attainment compares the performance of 39 countries and one region (Hong Kong) on two categories of education: Cognitive Skills and Educational Attainment. The Index provides a snapshot of the relative performance of countries based on their education outputs.List of indicators   Main sourceMain year1. Cognitive Skills  1.1  Grade 8  1.1.1  Reading Literacy - PISAOECD - PISA report20091.1.2  Mathematics Literacy - PISA and TIMSSEIU based on IEA and OECD data 1.1.2.1  PISA - Mathematics LiteracyOECD - PISA report20091.1.2.2  TIMSS - Mathematics AchievementIEA - TIMSS and PIRLS International Study Center20071.1.3  Science Literacy - PISA and TIMSSEIU based on IEA and OECD data 1.1.3.1  PISA - Science LiteracyOECD - PISA report20091.1.3.2  TIMSS - Science  AchievementIEA - TIMSS and PIRLS International Study Center20071.2  Grade 4  1.2.1  PIRLS - Reading Literacy AchievementIEA - TIMSS and PIRLS International Study Center20061.2.2  TIMSS - Mathematics  AchievementIEA - TIMSS and PIRLS International Study Center20071.2.3  TIMSS - Science  AchievementIEA - TIMSS and PIRLS International Study Center20072. Educational Attainment  2.1  Literacy rate  2.1.1  Literacy rate (15 and over), %UNESCO Institute for Statistics (UIS)20102.2  Graduation rate  2.2.1  Graduation rate at upper secondary level OECD 20102.2.2  Graduation rate at tertiary level OECD 2010
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 июля, 2012
      Выбрать
      This Dataset contains 4 Tables. Index of purchasing power of the euro/ECU - Annual data (mny_ppe_a) Index of purchasing power of the euro/ECU - Quarterly data (mny_ppe_q) Index of purchasing power of the euro/ECU - Monthly data (mny_ppe_m). Capital raised on stock markets (mny_h_caprais) Note: Eurostat Hierarchy: Economy and finance > Monetary and other financial statistics (mny) > Monetary and other financial statistics: historical data (mny_h) > Index of purchasing power of the euro/ECU (mny_h_ppe).
    • Июнь 2017
      Источник: Ministry of Statistics and Programme Implementation, India
      Загружен: Knoema
      Дата обращения к источнику: 06 марта, 2018
      Выбрать
      This Dataset describe balance of payments of External Assistance Authorization & Utilization. Notes: i) authorisation of assistance include agreements signed on Government and non-Government accounts (ii) Utilisation figures are exclusive of suppliers' credit and commercial borrowings.(iii) Utilization of assistance is on Government and non-Government accounts. (iv) FY2000-2001 represent as 2001 here.
    • Январь 2014
      Источник: Ministry of Commerce and Industry, Saudi Arabia
      Загружен: Knoema
      Дата обращения к источнику: 16 января, 2014
      Выбрать
      Industry and Trade Statistics of Saudi Arabia, 2011
    • Июнь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 19 июня, 2019
      Выбрать
      Eurostat Dataset Id:sbs_sc_ind_r2 SBS covers the Nace Rev.2 Section B to N and division S95 which are organized in four annexes, covering Industry (sections B-E), Construction (F), Trade (G) and Services (H, I, J, L, M, N and S95). Financial services are covered in three specific annexes and separate metadata files have been compiled. Up to reference year 2007 data was presented using the NACE Rev.1.1 classification. The SBS coverage was limited to NACE Rev.1.1 Sections C to K. Starting from the reference year 2008 data is available in NACE Rev.2. Double reported data in NACE Rev.1.1 for the reference year 2008 will be available in the first and second quarter of 2011. Main characteristics (variables) of the SBS data category:Business Demographic variables (e.g. number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables               - labour input (e.g. Employment, Hours worked)               - goods and services input (e.g. Total of purchases)               - capital input (e.g. Material investments) Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4 digits). Some classes or groups in 'services' in NACE Rev 1.1 sections H, I, K have been aggregated. Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available. Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year is defined in Commission Regulation N° 251/2009.  For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by N°1614/2002 and N°1669/2003. SBS data are collected primarily by National Statistical Institutes (NSI). Regulatory or controlling national offices for financial institutions or central banks often provides the information required for the financial sector (NACE Rev 2 Section K / NACE  Rev 1.1 Section J). 
    • Июнь 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 17 июня, 2012
      Выбрать
    • Январь 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 30 декабря, 2013
      Выбрать
      Eurostat Dataset Id:inn_cis7_exp The Community Innovation Survey (CIS) is a survey of innovation activity in enterprises. The harmonised 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, type 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, in close cooperation with the countries, has developed a standard core questionnaire starting with the CIS3 data collection, along with an accompanying set of definitions and methodological recommendations. The concepts and underlying methodology of the CIS are also based on the Oslo Manual — second edition of 1997 and third edition of 2005 . Up to CIS 2010, CIS results were collected under Commission Regulation (EC) No 1450/2004. A new Regulation will apply from CIS 2012 (EC No 995/2012). The data presented in these tables refer to enterprises with ‘10 employees or more’ active in the sectors to be covered under the Regulation (cf. NACE CORE). Further activities may be covered on a voluntary basis. Most statistics are based on a reference period of three years, but some use one calendar year. Since CIS 2008, the survey has included an ad-hoc module. It consists of a set of questions focusing on a special theme. The themes are different in each survey wave, allowing data to be obtained on specific issues beyond the data usually collected. Overview over time: Initially, the CIS data collection was carried out every four years. The first collection (CIS Light) was launched in 1993 as a pilot exercise and the second (CIS2) was carried out in 1997/1998 for most countries except Greece and Ireland, where it was launched in 1999. The third survey (CIS3) was conducted in 2000/2001 for most participating countries with the exception of Norway, Iceland, Luxembourg and Greece, where it was launched in 2002. As from 2004, the survey has been carried out every two years. CIS4 was conducted in the 25 EU Member States (as for 2004), Iceland, Norway, Bulgaria and Romania. The survey was launched in 2005 with a three-year reference period 2002 to 2004 for most indicators. The fifth survey CIS 2006 was carried out in all 25 EU Member States (as for 2006), Norway, Bulgaria, Romania, Croatia and Turkey. It was launched in 2007, mostly for the reference period 2004 to 2006. As regards CIS 2008, 26 Member States (all except Greece), Iceland, Norway, Croatia and Turkey took part in the survey. CIS 2008 was launched in 2009 with a three-year reference period 2006 to 2008 for most indicators. Changes were made to the CIS 2008 questionnaire to bring it into line with the third revision of the Oslo Manual, 2005 edition, by giving greater weight to organisational and marketing innovation. CIS 2008 was complemented by an ad-hoc module on innovation with environmental benefits. The seventh Community Innovation Survey, CIS 2010, had 31 participating countries (all the EU 27 Member States (except Greece), Iceland, Norway, Croatia, Serbia and Turkey) and reported most results for the reference period 2008-2010. CIS 2010 also follows the recommendations of the Oslo Manual and reports indicators on four types of innovation: product, process, organisational and marketing. However, despite implementation of the recommendations of the third edition of the Oslo Manual, the question on innovation expenditures is still limited to product and process innovation in order to maintain continuity with earlier versions of the CIS. Furthermore, generally fewer questions are asked about organisational and marketing innovation than about product and process innovation. 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 the microdata on CD-ROM releases in more anonymised form; some countries also provide access to their micro-data at similar safe centres.
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 марта, 2019
      Выбрать
      Eurostat Dataset Id:htec_cis6 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.
    • Июль 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 июля, 2012
      Выбрать
    • Декабрь 2018
      Источник: International Federation of Association Football
      Загружен: Knoema
      Дата обращения к источнику: 20 февраля, 2019
      Выбрать
      FIFA is the international governing body of association football, futsal and beach soccer. Its membership comprises 209 national associations. Its headquarters are in Zurich, Switzerland, and its president is Sepp Blatter. FIFA is responsible for the organisation of football's major international tournaments, notably the World Cup.
    • Декабрь 2017
      Источник: United Nations Development Programme
      Загружен: Knoema
      Дата обращения к источнику: 06 февраля, 2018
      Выбрать
      The estimates are based on official statistics on the foreign-born or the foreign population, classified by sex, and age. Most of the statistics utilised to estimate the international migrant stock were obtained from population censuses. Additionally, population registers and nationally representative surveys provided information on the number and composition of international migrants.
    • Июнь 2013
      Источник: United Nations Conference on Trade and Development
      Загружен: Knoema
      Дата обращения к источнику: 22 июля, 2013
      Выбрать
      Time series on international reserves (including gold), by individual country, expressed in millions of dollars. It further presents the number of months of merchandise imports that these reserves could finance at current imports level, as well as annual changes in total reserves.
    • Январь 2011
      Источник: International Comparisons
      Загружен: International Comparisons
      Дата обращения к источнику: 01 октября, 2013
      Выбрать
      Compared to the other 11 countries, United States has averaged more pregnancies, births, and abortions per 1,000 girls while having the lowest ratio of births to abortions.
    • Май 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 15 декабря, 2015
      Выбрать
      Eurostat Dataset Id:bop_its_det 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, to monitor the external commercial performance of different economies. Out of BoP data, some indicators of EU market integration are also derived. Data are in millions of Euro/ECU. 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.
    • Декабрь 2012
      Источник: Internet World Stats
      Загружен: Knoema
      Дата обращения к источнику: 11 сентября, 2013
      Выбрать
      Internet World Stats is an International website that features up to date world Internet Usage, Population Statistics, Travel Stats and Internet Market Research Data, for over 233 individual countries and world regions.
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 марта, 2019
      Выбрать
      Eurostat Dataset Id:educ_thexp The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes by pupils and students, personnel in education and the cost and type of resources dedicated to education. The standards on international statistics on education and training systems are set by the three international organisations jointly administering the UOE data collection:the United Nations Educational, Scientific, and Cultural Organisation Institute for Statistics (UNESCO-UIS),the Organisation for Economic Co-operation and Development (OECD) and,the Statistical Office of the European Union (EUROSTAT). The following topics are covered:Context - School-aged population, overall participation rates in educationDistribution of pupils/students by levelParticipation/enrolment in education (ISCED 0-4)Tertiary education participationTertiary education graduatesTeaching staff (ISCED 1-3)Pupil/students-teacher ratio and average class size (ISCED 1-3)Language learning (ISCED 1-3)Regional enrolmentsExpenditure on education in current pricesExpenditure on education in constant pricesExpenditure on education as % of GDP or public expenditureExpenditure on public and private educational institutionsFinancial aid to studentsFunding of education Other tables, used to measure progress towards the Lisbon objectives in education and training, are gathered in the Thematic indicators tables. They contain the following indicators: - Teachers and trainers - Mathematics, science and technology enrolments and graduates - Investments in education and training - Participation rates in education by age and sex - Foreign language learning - Student mobility
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 05 июля, 2019
      Выбрать
      This table contains figures on the shares of industrial sectors that are "controlled" by affiliates under foreign control in each country (inward investment as a percentage of national total).
    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 28 мая, 2019
      Выбрать
      This table contains figures on the activity of affiliates under foreign control by industry according to the International Standard Industrial Classification (ISIC Revision 3).
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 02 июля, 2019
      Выбрать
      This table contains figures on affiliates under foreign control by investing country in the total manufacturing, total services and total business enterprise sectors.
    • Август 2015
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 18 июля, 2016
      Выбрать
      The units used to present data in AFA are millions of national currency for monetary variables and units for the other variables. Monetary variables are in current prices. Euro-area countries: national currency data is expressed in euro beginning with the year of entry into the Economic and Monetary Union (EMU). For years prior to the year of entry into EMU, data have been converted from the former national currency using the appropriate irrevocable conversion rate. This presentation facilitates comparisons within a country over time and ensures that the historical evolution is preserved. Please note, however, that pre-EMU euro are a notional unit and should not be used to form area aggregates or to carry out cross-country comparisons.
    • Март 2015
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 01 декабря, 2015
      Выбрать
      Eurostat Dataset Id:yth_incl_130 The domain "Income and living conditions" covers four topics: people at risk of poverty or social exclusion, income distribution and monetary poverty, living conditions and material deprivation, which are again structured into collections of indicators on specific topics. The collection "People at risk of poverty or social exclusion" houses main indicator on risk of poverty or social inclusion included in the Europe 2020 strategy as well as the intersections between sub-populations of all Europe 2020 indicators on poverty and social exclusion. The collection "Income distribution and monetary poverty" houses collections of indicators relating to poverty risk, poverty risk of working individuals as well as the distribution of income. The collection "Living conditions" hosts indicators relating to characteristics and living conditions of households, characteristics of the population according to different breakdowns, health and labour conditions, housing conditions as well as childcare related indicators. The collection "Material deprivation" covers indicators relating to economic strain, durables, housing deprivation and environment of the dwelling.
    • Июль 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 04 августа, 2014
      Выбрать
      The IPP.Stat is the statistics portal of the Innovation Policy Platform containing the main available indicators relevant to a country’s innovation performance. In addition to the traditional indicators used to monitor innovation, the range of the coverage to be found in the IPP.Stat calls for the inclusion of indicators from other domains that describe the broader national and international context in which innovation occurs. Indicators are sourced primarily from the OECD and the World Bank, as well as from other sources of comparable quality. The statistics portal is still under development.
    • Март 2013
      Источник: International Transport Forum
      Загружен: Knoema
      Дата обращения к источнику: 01 октября, 2013
      Выбрать
      International comparisons of taxes and charges on road haulage require a framework that can relate all the various taxes and charges levied on transport activities to marginal costs, if they are to provide satisfactory answers to the following types of question. -- Do hauliers in one country pay more than in the other, and what impact does this have on the profitability of haulage in each country? -- Is the impact of an increase in tax on diesel the same in each country or are differences in the taxation of labour more significant? -- Do these differences distort the international haulage market?
    • Январь 2010
      Источник: International Transport Forum
      Загружен: Knoema
      Выбрать
      These tables contain detailed data on Greenhouse Gas (GHG) emissions and carbon dioxide (CO2) emissions from fossil fuel combustion in member countries of the International Transport Forum and member countries of OECD. Data on greenhouse gas emissions (and CO2 emissions in particular) come from national reports to the United Nations Framework Convention on Climate Change (UNFCCC) and from the International Energy Agency (IEA). UNFCCC and IEA emissions data are based on the default methods and emissions factors from the Revised 1996 IPCC (Intergovernmental Panel on Climate Change) Guidelines for National Greenhouse Gas Inventories. CO2 emissions from international aviation and international maritime transport are included in national totals allocated on the basis of fuel sales. There is, however, no internationally agreed allocation methodology for these sectors as of yet.
  • K
    • Январь 2012
      Источник: World Bank
      Загружен: Knoema
      Дата обращения к источнику: 26 августа, 2013
      Выбрать
      The World Bank’s Knowledge Assessment Methodology (KAM: www.worldbank.org/kam) is an online interactive tool that produces the Knowledge Economy Index (KEI)–an aggregate index representing a country’s or region’s overall preparedness to compete in the Knowledge Economy (KE). The KEI is based on a simple average of four subindexes, which represent the four pillars of the knowledge economy:  Economic Incentive and Institutional Regime (EIR)  Innovation and Technological Adoption  Education and Training  Information and Communications Technologies (ICT) Infrastructure The EIR comprises incentives that promote the efficient use of existing and new knowledge and the flourishing of entrepreneurship. An efficient innovation system made up of firms, research centers, universities, think tanks, consultants, and other organizations can tap into the growing stock of global knowledge, adapt it to local needs, and create new technological solutions. An educated and appropriately trained population is capable of creating, sharing, and using knowledge. A modern and accessible ICT infrastructure serves to facilitate the effective communication, dissemination, and processing of information.
  • L
    • Июнь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 12 декабря, 2015
      Выбрать
      Eurostat Dataset Id:lc_lci_r1_cow Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. The quarterly Labour Cost Index (LCI) is a Euro Indicator which measures the cost pressure arising from the production factor "labour". The data covered in the LCI collection relate to total average hourly labour costs and to the labour cost categories "wages and salaries" and "employers' social security contributions plus taxes paid minus subsidies received by the employer". Data - also broken down by economic activity, are available for the EU aggregates and EU Member States (NACE Rev 1.1 Sections C to K or NACE Rev 2 Sections B to S), in working day and seasonally adjusted form. The data on the Labour Cost Index are given in the form of index numbers (current reference year: 2008) and of annual and quarterly growth rates (comparison with the previous quarter, or the same quarter of the previous year). On annual basis the labour cost levels (in Euro and national currency) are also published, based on the latest Labour Cost Survey inflated by the LCI. In contrast to the information collected for the other Labour Cost domains, the labour costs covered in the LCI do not include vocational training costs and other expenditure such as recruitment costs and working clothes expenditure. The data are estimated by the National Statistical Institutes on the basis of available structural and short-term information from samples and administrative records for enterprises of all sizes.
    • Август 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 10 июня, 2014
      Выбрать
      Eurostat Dataset Id:lc_n08costot_r2 Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Structural information on labour costs is collected through four-yearly Labour Cost Surveys (LCSs), which provides details on level and structure of labour cost data, hours worked and hours paid. LCS results are available for the reference years 2000, 2004 and 2008. All EU Member States together with Norway, Iceland and Croatia (2004, 2008), Turkey and Macedonia (2008) participated in the LCS. As far as available data and confidentiality rules permit, all variables and proportions are further broken down by enterprise size category, economic activity and region (larger countries only). The data are collected by the National Statistical Institutes in most cases on the basis of stratified random samples of enterprises or local units, restricted in most countries to units with at least 10 employees. The stratification is based on economic activity, size category and region (where appropriate). Regional metadata is identical to the metadata provided for national data. Some countries also complement the survey results with administrative data. Monetary variables are expressed in EUR, national currencies (if different) and Purchasing Power Standards (PPS). Labour costs are quoted in total and per year, per month and per hour, as well as per capita and per full-time equivalents (FTE). Information on staff, hours worked and hours paid is quoted in aggregate and separately for full- and part-time employees. Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs.
    • Март 2011
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 апреля, 2014
      Выбрать
      Eurostat Dataset Id:lc_r04cost Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Structural information on labour costs is collected through four-yearly Labour Cost Surveys (LCSs), which provides details on level and structure of labour cost data, hours worked and hours paid. LCS results are available for the reference years 2000, 2004 and 2008. All EU Member States together with Norway, Iceland and Croatia (2004, 2008), Turkey and Macedonia (2008) participated in the LCS. As far as available data and confidentiality rules permit, all variables and proportions are further broken down by enterprise size category, economic activity and region (larger countries only). The data are collected by the National Statistical Institutes in most cases on the basis of stratified random samples of enterprises or local units, restricted in most countries to units with at least 10 employees. The stratification is based on economic activity, size category and region (where appropriate). Regional metadata is identical to the metadata provided for national data. Some countries also complement the survey results with administrative data. Monetary variables are expressed in EUR, national currencies (if different) and Purchasing Power Standards (PPS). Labour costs are quoted in total and per year, per month and per hour, as well as per capita and per full-time equivalents (FTE). Information on staff, hours worked and hours paid is quoted in aggregate and separately for full- and part-time employees. Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs.
    • Март 2011
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 22 апреля, 2014
      Выбрать
      Eurostat Dataset Id:lc_r08cost_r2 Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Structural information on labour costs is collected through four-yearly Labour Cost Surveys (LCSs), which provides details on level and structure of labour cost data, hours worked and hours paid. LCS results are available for the reference years 2000, 2004 and 2008. All EU Member States together with Norway, Iceland and Croatia (2004, 2008), Turkey and Macedonia (2008) participated in the LCS. As far as available data and confidentiality rules permit, all variables and proportions are further broken down by enterprise size category, economic activity and region (larger countries only). The data are collected by the National Statistical Institutes in most cases on the basis of stratified random samples of enterprises or local units, restricted in most countries to units with at least 10 employees. The stratification is based on economic activity, size category and region (where appropriate). Regional metadata is identical to the metadata provided for national data. Some countries also complement the survey results with administrative data. Monetary variables are expressed in EUR, national currencies (if different) and Purchasing Power Standards (PPS). Labour costs are quoted in total and per year, per month and per hour, as well as per capita and per full-time equivalents (FTE). Information on staff, hours worked and hours paid is quoted in aggregate and separately for full- and part-time employees. Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 11 июня, 2014
      Выбрать
      Eurostat Dataset Id:lc_n00cost Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Structural information on labour costs is collected through four-yearly Labour Cost Surveys (LCSs), which provides details on level and structure of labour cost data, hours worked and hours paid. LCS results are available for the reference years 2000, 2004 and 2008. All EU Member States together with Norway, Iceland and Croatia (2004, 2008), Turkey and Macedonia (2008) participated in the LCS. As far as available data and confidentiality rules permit, all variables and proportions are further broken down by enterprise size category, economic activity and region (larger countries only). The data are collected by the National Statistical Institutes in most cases on the basis of stratified random samples of enterprises or local units, restricted in most countries to units with at least 10 employees. The stratification is based on economic activity, size category and region (where appropriate). Regional metadata is identical to the metadata provided for national data. Some countries also complement the survey results with administrative data. Monetary variables are expressed in EUR, national currencies (if different) and Purchasing Power Standards (PPS). Labour costs are quoted in total and per year, per month and per hour, as well as per capita and per full-time equivalents (FTE). Information on staff, hours worked and hours paid is quoted in aggregate and separately for full- and part-time employees. Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs.
    • Ноябрь 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 01 июля, 2014
      Выбрать
      Eurostat Dataset Id:lc_an_cost_r2 Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Annual labour cost data published here cover the core labour cost variables "average hourly labour costs" and "average monthly labour costs" as well as the breakdown of labour costs by main categories (wages and salaries; other labour costs). Average hourly and monthly labour costs as well as the structure of total annual labour costs per employee by economic activity are provided for enterprises with 1+ and for enterprises with 10+ employees.Data  are available for the EU Member States and partly for Iceland and Switzerland. The data are either collected by the National Statistical Institutes or, more frequently, estimated by them on the basis of their four-yearly Labour Cost Surveys (LCS), the Labour Cost Index (LCI) and additional up-to-date - though sometimes partial - information. Coverage of statistical units, thresholds and other methodological aspects are identical to that of the four yearly LCS.
    • Апрель 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 26 мая, 2014
      Выбрать
      Eurostat Dataset Id:ef_so_lfesu 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 (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.
    • Апрель 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 26 мая, 2014
      Выбрать
      Eurostat Dataset Id:ef_so_lfaa 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 (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.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 13 апреля, 2014
      Выбрать
      Eurostat Dataset Id:agr_r_landuse
    • Январь 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 января, 2017
      Выбрать
      Eurostat Dataset Id:ef_oluaareg 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 Standard 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 on land use livestock special 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 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.
    • Январь 2017
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 января, 2017
      Выбрать
      Eurostat Dataset Id:ef_oluecsreg 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 Standard 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 on land use livestock special 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 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.
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 марта, 2019
      Выбрать
      Eurostat Dataset Id:educ_ilang The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes by pupils and students, personnel in education and the cost and type of resources dedicated to education. The standards on international statistics on education and training systems are set by the three international organisations jointly administering the UOE data collection:the United Nations Educational, Scientific, and Cultural Organisation Institute for Statistics (UNESCO-UIS),the Organisation for Economic Co-operation and Development (OECD) and,the Statistical Office of the European Union (EUROSTAT). The following topics are covered:Context - School-aged population, overall participation rates in educationDistribution of pupils/students by levelParticipation/enrolment in education (ISCED 0-4)Tertiary education participationTertiary education graduatesTeaching staff (ISCED 1-3)Pupil/students-teacher ratio and average class size (ISCED 1-3)Language learning (ISCED 1-3)Regional enrolmentsExpenditure on education in current pricesExpenditure on education in constant pricesExpenditure on education as % of GDP or public expenditureExpenditure on public and private educational institutionsFinancial aid to studentsFunding of education Other tables, used to measure progress towards the Lisbon objectives in education and training, are gathered in the Thematic indicators tables. They contain the following indicators: - Teachers and trainers - Mathematics, science and technology enrolments and graduates - Investments in education and training - Participation rates in education by age and sex - Foreign language learning - Student mobility
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 апреля, 2014
      Выбрать
      Eurostat Dataset Id:orch_lemon Orchard survey domain (orch) contains the results of the surveys of areas under certain species of fruit trees (apple, pear, peach, apricot, orange, lemon, small citrus fruit). The statistical surveys on orchards are carried out every five years by the Member States in order to determine the production potential of plantations of certain species of fruit trees. These surveys have been carried out since 1977. The results presented in this database provide areas (in hectares) by variety and age and density classes by country and by production region.Data are grouped in tables by fruit tree species. The following species are surveyed: a) apple trees for dessert apples (in the 27 EU member states, except Malta), b) pear trees for dessert pears (in the 27 EU member states, except Estonia, Ireland, Malta and Finland), c) peache trees (in Bulgaria, Czech republic, Greece, Spain, France, Italy, Cyprus, Hungary, Malta, Austria, Poland, Portugal, Romania, Slovenia and Slovakia only), d) apricot trees (in Bulgaria, Czech republic, Greece, Spain, France, Italy, Cyprus, Hungary, Austria, Poland, Portugal, Romania, Slovenia and Slovakia only), e) orange trees (in Greece, Spain, France, Italy, Cyprus and Portugal only), f) lemon trees (in Greece, Spain, France, Italy, Cyprus and Portugal only), g) small-citrus fruit trees (in Greece, Spain, France, Italy, Cyprus and Portugal only). The latter group (small-citrus fruit trees, including tangerines and satsumas; clementines, wilkings and other similar citrus hybrids) is considered as a single species. Data on plantations producing apples and pears for uses other than dessert fruit were sent optionally by some countries from 1987 onwards. The species of fruit and the varieties are listed in Annex III to Commission Decision (EC) No 38/2002.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 06 июля, 2019
      Выбрать
      This table contains data on labour force participation rates, employment/population ratios and unemployment rates for both the total labour force and civilian labour force by sex. There are data for both the total age group and the working age population (ages 15 to 64). This table also contains data on the share of civilian employment by sex.
    • Июнь 2013
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 06 августа, 2013
      Выбрать
      This Dataset presents 8 Tables: Age specific death rate (Mx) by NUTS 2 regions (demo_r_mdthrt), Probability of dying between exact ages (qx) by NUTS 2 regions (demo_r_mpbdth), Probability of surviving between exact ages (px) by NUTS 2 regions (demo_r_mpbsurv), Number left alive at given exact age (lx) by NUTS 2 regions (demo_r_msurv), Number dying between exact ages (dx) by NUTS 2 regions (demo_r_mdie), Person-years lived between exact age (Lx) (demo_r_mpyliv), Total person-years lived above given exact age (Tx) by NUTS 2 regions (demo_r_mtotpyliv), Life expectancy at given exact age (ex) by NUTS 2 regions (demo_r_mlifexp). Note: Eurostat Hierarchy: General and regional statistics > Population and social conditions > Population (populat) > Demography (pop) > Demography - Regional data (demoreg) > Life table - NUTS level 2 regions (demo_rmlifetable).
    • Март 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 30 июля, 2012
      Выбрать
      General and regional statistics > Regional statistics > Regional agriculture statistics > Agri-Environmental Indicators > Livestock density by NUTS 3 regions
    • Август 2018
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 августа, 2018
      Выбрать
      Eurostat Dataset Id:lmp_ind_exp 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
    • Август 2018
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 августа, 2018
      Выбрать
      Eurostat Dataset Id:lmp_partsumm 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
    • Май 2018
      Источник: World Bank
      Загружен: Knoema
      Дата обращения к источнику: 03 августа, 2018
      Выбрать
      The Logistics Performance Index overall score reflects assessments of a country's logistics based on efficiency of the customs clearance process, quality of trade- and transport-related infrastructure, ease of arranging competitively priced shipments, quality of logistics services, ability to track and trace consignments, and frequency with which shipments reach the consignee within the scheduled time. The index ranges from 1 to 5, with a higher score representing better performance. Data are from Logistics Performance Index surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. 2011 round of surveys covered more than 6,000 country assessments by nearly 1,000 international freight forwarders. Respondents evaluated eight markets on six core dimensions using a scale from 1 (worst) to 5 (best). The markets are chosen based on the most important export and import markets of the respondent's country, random selection, and, for landlocked countries, neighboring countries that connect them with international markets. Scores for the six areas are averaged across all respondents and aggregated to a single score using principal components analysis. Details of the survey methodology and index construction methodology are in Connecting to Compete 2012: Trade Logistics in the Global Economy (2012).
    • Июль 2019
      Источник: European Central Bank
      Загружен: Knoema
      Дата обращения к источнику: 18 июля, 2019
      Выбрать
      The statistics for EU Member States published here relate to interest rates for long-term government bonds denominated in national currencies. Where no harmonised long-term government bond yields are available, proxies derived from private sector bond yields or interest rate indicators are presented. The harmonised statistics are used for convergence assessment purposes, as stated in Article 121 of the Treaty establishing the European Community (the Treaty). Specific details are set out in Article 4 of the Protocol on the convergence criteria.
  • M
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_05nowree Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_05nowrep Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_06finiisco Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_05nowre2 Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_05nowre1 Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_06reasstaf Results from the 2006 LFS (Labour Force Survey) ad hoc module on 'transition form work into retirement'.
    • Март 2014
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 05 июня, 2014
      Выбрать
      Eurostat Dataset Id:lfso_05typece Results from the 2005 LFS (Labour Force Survey) ad hoc module on 'reconciliation between work and family life'.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
      Выбрать
      IPAW = Income as a percentage of the average wage   This data is updated after the finalisation of the Taxing Wages publication for the corresponding year. This table reports marginal personal income tax and social security contribution rates for a single person without dependent, at various multiples (67%, 100%, 133%, 167%) of the AW/APW. The average wage (AW) by country and year can be found within the Taxing Wages comparative tables dataset, under the indicator heading: Total gross earnings before taxes (national currency). The AW is based on a single person at 100% of average earnings, no child. The results, derived from the OECD Taxing Wages framework (elaborated in the annual publication Taxing Wages), use tax rates applicable to the tax year. The results take into account basic/standard income tax allowances and tax credits and include family cash transfers (see Taxing Wages). The marginal rates are expressed as a percentage of gross wage earnings, with the exception of the Total tax wedge which is expressed as a percentage of gross labour costs (gross wages + employer SSC). The sub-central personal tax rates used in this table correspond to those used in Taxing Wages. The figures may differ from those published in Taxing Wages where updated information is available, such as revised AW/APW data. Further explanatory notes may be found in the Explanatory Annex.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 21 апреля, 2014
      Выбрать
      Eurostat Dataset Id:tran_r_mago_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.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 21 апреля, 2014
      Выбрать
      Eurostat Dataset Id:tran_r_mapa_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.
    • Июнь 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 июля, 2012
      Выбрать
      This Dataset contains 6 Tables. Market capitalisation - Annual data (mny_stk_mcp_a); Market capitalisation - Quarterly data (mny_stk_mcp_q); Market capitalisation - Monthly data (mny_stk_mcp_m); Turnover - Annual data (mny_stk_tov_a); Turnover - Quarterly data (mny_stk_tov_q); Turnover - Monthly data (mny_stk_tov_m). Note: Eurostat Hierarchy: Economy and finance > Monetary and other financial statistics (mny) > Stock market (mny_stk) > Market capitalisation (mny_stk_mcp) and Stock market turnover (mny_stk_tov)
    • Ноябрь 2011
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 14 июня, 2013
      Выбрать
      Eurostat Dataset Id:isoc_tc_msht The collection of 'Telecommunication Services' statistics covers the following indicators: (1) Employment in telecommunication The indicator gives the total number of people employed in telecommunication services and the number of people employed in fixed and mobile telecommunication and Internet service provision. Employment is converted into full time equivalent units, average of the year. (2) Investment The indicator gives the total gross investment (in Mio euro) in tangible goods i.e. investment for acquiring property (land and buildings) and plant (e.g. switching equipment, transmission equipment, office machinery, and motor vehicles), and investment in fixed telecommunication networks (excluding cable TV services), mobile telecommunications: GSM and GPRS, mobile telecommunications: UMTS (excluding licenses), and in other telecommunication networks (Internet, satellite and cable telecommunication equipment and infrastructure other than for broadcasting). (3) Turnover The indicator gives the total turnover (in Mio euro) from all telecommunication services and turnover from leased lines, fixed network services, cellular mobile telecommunication services, interconnection services and Internet service provision. (4) International receipts and payments The indicator gives the total revenue (receipts, payments) from international incoming and outgoing telecommunication traffic, in Mio euro. Incoming telecommunication traffic: income received from foreign telephone operators for completing calls originating in foreign country. Outgoing telecommunication traffic: charges received from subscribers for placing outgoing calls after deduction of the share of this income to be paid to other organisation for outgoing telecommunication traffic (operators of the incoming and possibly transit countries). (5) International calls The indicator gives the amount (in 1000 minutes) of international incoming (originating outside the country with a destination inside the country) and outgoing (originating inside the country to destinations outside the country) calls in fixed and cellular networks. (6) Traffic The indicator gives the total amount of national calls and the amount of local calls, national long distance calls, cellular mobile calls, minutes of internet connection, calls from fixed to mobile and mobile to fixed networks, calls within mobile networks and calls from mobile to mobile networks (in 1000 minutes). (7) SMS (short message service) The indicator gives the total number of SMS (text messages) sent (in thousands). (8) Access to networks (in thousands) The indicator gives the number of main telephone lines and subscriptions to the services of the operators offering mobile telecommunication services and the number of leased lines, ISDN subscriptions, DSL subscriptions, Internet subscriptions and subscriptions to cable networks enabling internet use, number of connections to telecommunication networks through electricity networks (Power Line Communication - PLC), subscriptions to mobile telecommunication systems enabling use of UMTS and the number of users of Voice over Internet Protocol telephony, in thousands. (9) Access to networks (per 100 inhabitants) The indicator gives the number of main telephone lines and subscriptions to the services of the operators offering mobile telecommunication services per 100 inhabitants. (10) Household share of main telephone lines The indicator gives the share of main telephone lines for residential use (i.e. lines which are not used for business, government or other professional purposes or as public telephone stations) as a percentage of total main telephone lines. (11) Operators and service providers The indicator gives the number of fixed network operators offering local and long distance national telecommunications (facilities based or resale) and international telecommunications, and the number of cellular mobile operators (digital or analogous, facilities based or resale), cable and satellite service providers (excluding pure programme distribution) and internet service providers (access and backbone services). (12) Broadband penetration rate  This indicator shows how widely broadband access to the internet has spread in the countries on the general level, not specifying by user group. (13) Prices of telecommunication The indicator gives the price in Euro of a 10 minute call at 11 am on a weekday (including VAT) for a local call (3km), national long distance call (200km) and an international call (to USA). The prices refer to the month of August for the period 1998-2005, and to the month of September from 2006 onwards. Tariffs without special rates are used. (14) Market shares in telecommunication This covers two structural indicators: market share of the incumbent in fixed telecommunications by type of call (local, long distance and international calls) and market share of the leading operator in mobile telecommunications. (15) Information technology expenditure in millions of euro and as a percentage of GDP Data refer to the expenditure for information and communication technology in millions of euro and as a percentage of GDP, with breakdown by expenditure for telecommunications and IT expenditure. Data in millions of euro are coming from the annual report of the European Information Technology Observatory (EITO).
    • Март 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 18 марта, 2019
      Выбрать
      Eurostat Dataset Id:educ_thflds The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes by pupils and students, personnel in education and the cost and type of resources dedicated to education. The standards on international statistics on education and training systems are set by the three international organisations jointly administering the UOE data collection:the United Nations Educational, Scientific, and Cultural Organisation Institute for Statistics (UNESCO-UIS),the Organisation for Economic Co-operation and Development (OECD) and,the Statistical Office of the European Union (EUROSTAT). The following topics are covered:Context - School-aged population, overall participation rates in educationDistribution of pupils/students by levelParticipation/enrolment in education (ISCED 0-4)Tertiary education participationTertiary education graduatesTeaching staff (ISCED 1-3)Pupil/students-teacher ratio and average class size (ISCED 1-3)Language learning (ISCED 1-3)Regional enrolmentsExpenditure on education in current pricesExpenditure on education in constant pricesExpenditure on education as % of GDP or public expenditureExpenditure on public and private educational institutionsFinancial aid to studentsFunding of education Other tables, used to measure progress towards the Lisbon objectives in education and training, are gathered in the Thematic indicators tables. They contain the following indicators: - Teachers and trainers - Mathematics, science and technology enrolments and graduates - Investments in education and training - Participation rates in education by age and sex - Foreign language learning - Student mobility
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 23 июня, 2014
      Выбрать
      Eurostat Dataset Id:ilc_di06 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.
    • Март 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 01 июля, 2014
      Выбрать
      Eurostat Dataset Id:ilc_di07h 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.
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_nfe18 General description of the ad hoc modules supplementing the Labour Force Survey (LFS)
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_nfe14 General description of the ad hoc modules supplementing the Labour Force Survey (LFS)
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 08 июня, 2014
      Выбрать
      Eurostat Dataset Id:trng_nfe15 General description of the ad hoc modules supplementing the Labour Force Survey (LFS)
    • Январь 2015
      Источник: United Nations Conference on Trade and Development
      Загружен: Knoema
      Дата обращения к источнику: 23 апреля, 2015
      Выбрать
      This table presents merchandise trade complementarity index which assesses the suitability of preferential trade agreement between two economies given the structure of one potential partners’ exports match the imports of the other potential partner. Changes over time may indicate whether the trade profiles are becoming more or less compatible.
    • Апрель 2019
      Источник: World Bank
      Загружен: Knoema
      Дата обращения к источнику: 06 мая, 2019
      Выбрать
      Migration and Remittances Fact book provides a snapshot of migration and remittances for all countries, regions and income groups of the world, compiled from available data from various sources. 
    • Июль 2012
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 25 июля, 2012
      Выбрать
      Note:i) All the Data Present in this dataset are "Value at the end of the period, Not applicable". ii)Eurostat Hierarchy: General and regional statistics > European and national short term indicators (euroind) > Monetary and financial indicators (ei_mf).
    • Март 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 16 июля, 2012
      Выбрать
      This Dataset contains 3 Tables. Former series for euro area countries on monetary aggregates and credit - Annual data (mny_h_agg_a) Former series for euro area countries on monetary aggregates and credit - Quarterly data (mny_h_agg_q) Former series for euro area countries on monetary aggregates and credit - Monthly data(mny_h_agg_m). Note: Eurostat Hierarchy: Economy and finance > Monetary and other financial statistics (mny) > Monetary and other financial statistics: historical data (mny_h) > Monetary aggregates, counterparts, and other banks' balance sheet items: historical data (mny_h_agg).
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
      Выбрать
      This dataset contains monthly Comparative Price Levels (CPL) for OECD countries. CPLs are defined as the ratios of PPPs for private final consumption expenditure to exchange rates. They provide measures of differences in price levels between countries. The monthly PPPs used to derive the table are OECD estimates. The table is to be read vertically. Each column shows the number of specified monetary units needed in each of the countries listed to buy the same representative basket of consumer goods and services. In each case the representative basket costs a hundred units in the country whose currency is specified. Let’s take an example. If you are a Canadian citizen and you want to know the price level in Canada when compared to other countries, you have to look at the column Canada, where the price level is set at 100 for the whole column. If you have 120 for Finland, it means that the price level in Finland is 20% higher than in Canada. It means that you would spend 120 dollars in Finland to buy the same basket of goods and services when you spend 100 in Canada.
    • Январь 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 19 февраля, 2019
      Выбрать
      Eurostat Dataset Id:earn_mw_avgr2 The basic national minimum wage is fixed at an hourly, weekly or monthly rate, and this minimum wage is enforced by law (the government), often after consultation with the social partners, or directly by national intersectoral agreement. The national minimum wage usually applies to all employees, or at least to a large majority of employees in the country. Gross wages are reported. Information is available on:Monthly minimum wages in euro, Purchasing Power Standards (PPS) and, for non euro area countries, national currencies.Monthly minimum wage as a proportion of average monthly earnings in the business economy and in industry, construction and services (except activities of households as employers and extra-territorial organisations and bodies) (Nace Rev. 2, data from 2008 onwards).Monthly minimum wage as a proportion of average monthly earnings in industry and services (NACE Rev. 1.1, data 1999-2009). Minimum wage statistics published by Eurostat refer to monthly national minimum wages. For countries where the national minimum wage is not set monthly (e.g. hourly or weekly) the rates are converted into monthly rates (see also 20.6). The data collection excludes countries which do not have a national minimum wage (see 3.7 for details).
    • Февраль 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 февраля, 2019
      Выбрать
      Eurostat Dataset Id:earn_mw_cur   The basic national minimum wage is fixed at an hourly, weekly or monthly rate, and this minimum wage is enforced by law (the government), often after consultation with the social partners, or directly by national intersectoral agreement. The national minimum wage usually applies to all employees, or at least to a large majority of employees in the country. Gross wages are reported. Information is available on:Monthly minimum wages in euro, Purchasing Power Standards (PPS) and, for non euro area countries, national currencies.Monthly minimum wage as a proportion of average monthly earnings in the business economy and in industry, construction and services (except activities of households as employers and extra-territorial organisations and bodies) (Nace Rev. 2, data from 2008 onwards).Monthly minimum wage as a proportion of average monthly earnings in industry and services (NACE Rev. 1.1, data 1999-2009). Minimum wage statistics published by Eurostat refer to monthly national minimum wages. For countries where the national minimum wage is not set monthly (e.g. hourly or weekly) the rates are converted into monthly rates (see also 20.6). The data collection excludes countries which do not have a national minimum wage (see 3.7 for details).
    • Май 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 июня, 2019
      Выбрать
      Eurostat Dataset Id:dt_turn_n45_r2 SBS covers the Nace Rev.2 Section B to N and division S95 which are organized in four annexes, covering Industry (sections B-E), Construction (F), Trade (G) and Services (H, I, J, L, M, N and S95). Financial services are covered in three specific annexes and separate metadata files have been compiled. Up to reference year 2007 data was presented using the NACE Rev.1.1 classification. The SBS coverage was limited to NACE Rev.1.1 Sections C to K. Starting from the reference year 2008 data is available in NACE Rev.2. Double reported data in NACE Rev.1.1 for the reference year 2008 will be available in the first and second quarter of 2011. Main characteristics (variables) of the SBS data category: Business Demographic variables (e.g. number of enterprises) "Output related" variables (e.g. Turnover, Value added) "Input related" variables - labour input (e.g. Employment, Hours worked) - goods and services input (e.g. Total of purchases) - capital input (e.g. Material investments) Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4 digits). Some classes or groups in 'services' in NACE Rev 1.1 sections H, I, K have been aggregated. Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available. Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by N°1614/2002 and N°1669/2003. SBS data are collected primarily by National Statistical Institutes (NSI). Regulatory or controlling national offices for financial institutions or central banks often provides the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J).
    • Февраль 2016
      Источник: Pew Research Center
      Загружен: Knoema
      Дата обращения к источнику: 05 февраля, 2016
      Выбрать
      Notes : 2010 is Estimated Population, 2030 is Projected Population.
  • N
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 05 июня, 2019
      Выбрать
      National Accounts - Volume IIIa - Financial Accounts - Flows, which record, by type of financial instruments, the financial transactions between institutional sectors, and are presented in two tables: Financial accounts, consolidated and Financial accounts, non-consolidated.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
      Выбрать
    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 17 мая, 2019
      Выбрать
      National Accounts - Volume IIIb - Financial Balance Sheets - Stocks, which record the stocks of financial assets and liabilities by institutional sectors, at the end of the accounting period, and are presented in two tables: Balance sheets for financial assets and liabilities, consolidated and Balance sheets for financial assets and liabilities, non consolidated. Statistics are reported at current prices in millions of national currency and in millions of Euros for OECD countries which are members of the Euro zone: Austria, Belgium, Estonia, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Slovak Republic, Slovenia and Spain.
    • Декабрь 2009
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 27 мая, 2014
      Выбрать
      Eurostat Dataset Id:educ_bo_ac_ent2 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. Many indicators on social dimension and mobility in the Bologna process come from the UOE data collection in the education statistics domain. The aim of the education statistics domain is to provide comparable statistics and indicators on key aspects of the education systems across Europe. The data cover participation and completion of education programmes, personnel in education and the cost and type of resources dedicated to education. The main source of data is the joint UIS (UNESCO Institute of Statistics)/OECD/Eurostat (UOE) questionnaires on education statistics, which constitute the core database on education. Data on regional enrolments and foreign language learning are collected additionally by Eurostat. Countries provide data, coming from administrative records, on the basis of commonly agreed definitions. From the UOE data collection, the following datasets on the Bologna Process are available: A. Widening access educ_bo_ac_ent2: Net entry rate (ISCED 5A) by age and sexeduc_bo_ac_ent3: Female entrants by field of education (ISCED 5A)educ_bo_ac_gent: Entrants at ISCED 5A and qualifying graduates of secondary schooling (ISCED 3A - 4A)educ_bo_ac_el1t: Students (ISCED 5A) studying part-time, by age B. Study framework educ_bo_fi_fgdp: Public expenditure on tertiary education (ISCED 5-6), as % of GDP or total public expenditureeduc_bo_fi_ftot: Annual total expenditure on educational institutions (ISCED 5-6) per full-time equivalent student with and without expenditure on research and ancillary serviceseduc_bo_fi_ffun: Tertiary education institutions' income from private sources (households and other private entities) as % of all public and private sourceseduc_bo_fi_fiaid: Public financial aid to tertiary students (ISCED 5-6), by type of aid, as % of public expenditure on tertiary education C. Student and staff mobility educ_bo_mo_el8o: Students (ISCED 5A and 6) who are nationals of a given country, studying in another country (EU-27, EFTA and CC) as % of the total enrolment in that countryeduc_bo_mo_el8i: Number of foreign students (world and Bologna Area) studying in a given country, as % of the total enrolment in that country, ISCED 5A and 6educ_bo_mo_gr4: Graduates (ISCED 5A and 6) from abroad (non-citizens, permanent residence and prior education outside the country) D. Effective outcomes and employability educ_bo_ou_gren: Gross graduation rate and net entry rate, ISCED 5A   The data for some countries which do not participate in the UOE data collection were provided to Eurostat specifically for the monitoring of the Bologna Process. Not being fully integrated in the UOE, the data sometimes might not be as comparable as the data for the remaining countries, due to differences in the underlying data sources and definitions. These data were provided by the following entities: Andorra (AD): data provided by the University of Andorra (indicators educ_bo_ac_ent3, educ_bo_fi_ffun, educ_bo_mo_el8i, educ_bo_mo_gr4)Armenia (AM): data provided by the Ministry of Education and Science (educ_bo_ac_gent, educ_bo_ac_el1t, educ_bo_mo_gr4, educ_bo_ou_gren)Georgia (GE): data provided by the NSI, Statistics Georgia (educ_bo_ac_ent3, educ_bo_ac_el1t, educ_bo_fi_fgdp, educ_bo_mo_gr4)Serbia (RS): data provided by the NSI, Statistical Office of the Republic of Serbia (educ_bo_mo_el8i)Ukraine (UA): data provided by the NSI, State Statistics Committee for Ukraine (educ_bo_ou_gren, educ_bo_ac_el1t, educ_bo_mo_el8i, educ_bo_mo_gr4, educ_bo_ou_gren)
    • Июль 2019
      Источник: Eurostat
      Загружен: Knoema
      Дата обращения к источнику: 07 июля, 2019
      Выбрать
      Eurostat Dataset Id:spr_net_ben Data on expenditure and receipts of social protection, on net social protection benefits as well as on pension beneficiaries contained in the ESSPROS domain are drawn up according to the ESSPROS (European System of integrated Social Protection Statistics) domain. Detailed information on the ESSPROS 'Concepts and Definitions' is available in Section 3.4 below. The ESSPROS domain  In Eurostat database, ESSPROS domain, ESSPROS data on expenditure and receipts, data on net social protection benefits as well as data on Pension beneficiaries for the total of schemes are currently disseminated. The qualitative information is available in the dedicated section "Social protection" of the Eurostat website.   Data on expenditure and receipts correspond to two collections "EXPEND" (Social protection expenditure) and "RECEIPTS" (Social protection receipts). The collection "EXPEND" is composed by three groups: 1. expsum (Expenditure - Summary tables); it contains two summary tables:e sum Expenditure: main results. The data include the expenditure broken down in social benefits, administration cost and other expenditure. In addition, social benefits are classified by functions of social protection (see ESSPROS Manual-The European System of integrated Social PROtection Statistics (ESSPROS), Part I - § 110).e pens Pensions. The data include the social benefits relating to pensions (old age, disability, survivors and unemployment pensions). In addition the data are split between means-tested and non means-tested benefits. 2. expcur (Expenditure - Tables by functions and aggregated benefits); it contains five tables corresponding to different "currencies": national currencies (e nac), euros (e eur), Purchasing Power Standards (e pps), Purchasing Power Standards per head (e ppsh) and % of the GDP (e gdp). For each table data (social protection benefits) are published:according to the classification by function of social protection: eight functions (Sickness /Health care; Disability; Old age; Survivors; Family/children; Unemployment; Housing; Social exclusion not elsewhere classified) and the total of social benefits;according to the detailed classification of benefits by type - cash benefits and benefits in kind- and by characteristic -split between means-tested and non means-tested benefits-(see ESSPROS Manual - The European System of integrated Social PROtection Statistics (ESSPROS), Part I - §111 and following). 3. expfunc (Expenditure - Tables by benefits and currency); it contains nine tables corresponding to the eight different functions of social protection and one for the total of social benefits. In each table data are published according to the detailed classification of benefits by function,type and characteristic(see ESSPROS Manual - The European System of integrated Social PROtection Statistics (ESSPROS), Part II). The collection "RECEIPTS"is composed by two groups: 1. recsum (Receipts - Summary tables); it contains two tables:r sumt Receipts by type. The data include the receipts of social protection broken down in the different types of receipts - social contributions, general government contributions and other receipts- (see ESSPROS Manual - The European System of integrated Social PROtection Statistics (ESSPROS), Part I - § 70 and following).r sums Receipts by sector