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アルバニア

  • 大統領:Ilir Meta
  • 首相:Edi Rama
  • 首都:Tirana (Tirane)
  • 言語:Albanian 98.8% (official - derived from Tosk dialect), Greek 0.5%, other 0.6% (including Macedonian, Roma, Vlach, Turkish, Italian, and Serbo-Croatian), unspecified 0.1% (2011 est.)
  • 政府
  • 統計局
  • 人口、人:2,866,376 (2018)
  • 面積、平方キロメートル:27,400
  • 1人当たりGDP、US $:5,254 (2018)
  • GDP、現在の10億米ドル:15.1 (2018)
  • GINI指数:No data
  • ビジネスのしやすさランク:63
すべてのデータセット:  1 2 3 A B C D E F G H I J K L M N O P Q R S T U V W Y В И Н П Р С Ч
  • 1
    • 10月 2018
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 03 11月, 2018
      データセットを選択
      This indicator gives the percentage of all 18-year-olds who are still in any kind of school (all ISCED levels). It gives an indication of the number of young people who have not abandoned their efforts to improve their skills through initial education and it includes both those who had a regular education career without any delays as well as those who are continuing even if they had to repeat some steps in the past.
  • 2
    • 8月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Sandeep Reddy
      以下でアクセス: 12 8月, 2019
      データセットを選択
      This dataset contains the main results of the 2014 Eurostat-OECD PPP comparison for the 47 countries that participated in the 2014 round of the Eurostat-OECD Purchasing Power Parity (PPP) Programme. The dataset is organised in 23 tables which show results both in US dollars and OECD as reference (Table 1.1 to Table 1.12) and in euros and European Union as reference (Table 2.1 to Table 2.11) calculated with the EKS method. The tables contain the following information: Table 1.1 to 1.12 The dollar serves as numeraire and the OECD as reference country (except for Table 1.12 where the United States are the reference country). Table 1.1 and Table 1.2 present the data on which the following ten tables are based. • Table 1.1 gives nominal expenditure in national currency of the participating countries. • Table 1.2 presents PPPs (OECD=1.00) that have been calculated for the participating countries using the price and expenditure data collected during the 2014 round. The PPPs were obtained by the EKS method of calculation and aggregation. • Table 1.3 shows nominal expenditure of Table 1.1 converted to US dollars. Exchange rates do not reflect the relative purchasing power of different currencies and the converted expenditure is still expressed at national prices. As such, it remains nominal measures, the spatial equivalent of a time series of GDP for a single country at current prices. Hence, they are called “nominal expenditure”. The nominal expenditure in the table reflects both differences in the quantities of goods and services purchased in the countries and differences in the price levels of the countries. • Table 1.4 gives nominal expenditure of Table 1.3 expressed on a per capita basis using the midyear population data. • Table 1.5 and Table 1.6 present the nominal expenditure from Table 1.3 and the nominal expenditure per head from Table 1.4 as indices with OECD=100. • Table 1.7 shows real expenditure converted to US dollar using the PPPs from Table 1.2. PPPs equalise the purchasing power of different currencies during the process of conversion and the converted expenditures are expressed at international prices (that is at the same price level). As such, they are real measures, the spatial equivalent of a time series of GDP for a single country at constant prices. Hence, they are called “real expenditures”. The real final expenditures in the table reflect only differences in the volumes of goods and services purchased in the countries. • Table 1.8 gives the real expenditure of Table 1.7 expressed on a per capita basis using the midyear population data. Again, the real expenditures per head in this table are not additive nor are they subject to the Gerschenkron effect. • Table 1.9 and Table 1.10 present the real expenditure on GDP from Table 1.7 and the real final expenditure per head on GDP from Table 1.8 as indices with OECD=100. • Table 1.11 gives the price levels which are computed as ratios of the PPPs in Table 1.2 to the exchange rates and are expressed as indices with OECD=100. For a given aggregate, they indicate the number of units of the common currency needed to buy the same volume of the  aggregate in each country. Price levels that exceed 100 indicate that the level of prices in that country and for that analytical category is higher than the average price level for the OECD. • Table 1.12 present PPPs as in Table 1.2 (see description above) but with the United States as reference country (US=1.00). Table 2.1 to 2.11 The euro serves as numeraire and the European Union as reference country. Table 2.1 and Table 2.2 present the data on which the following nine tables are based. Table 2.1 to 2.11 contain the same information as Table 1.1 to 1.11 with a different basis. For explanation on the contents, please see description above.
  • 3
    • 10月 2016
      ソース: Philipps-University of Marburg, Empirical Institutional Economics
      アップロード者: Knoema
      以下でアクセス: 07 12月, 2016
      データセットを選択
      The 3P Anti-trafficking Policy Index evaluates governmental anti-trafficking efforts in the three main policy dimensions (3Ps), based on the requirements prescribed by the United Nations Protocol to Prevent, Suppress and Punish Trafficking in Persons, especially Women and Children (2000).   The three main policy dimensions (3Ps) are:Prosecution of perpetrators of human traffickingPrevention of human traffickingProtection of the victims of human trafficking Each of the 3P areas is evaluated on a 5-point scale and each index is aggregated to the overall 3P Anti-trafficking Index as the  sum (score 3-15).Prosecution Index Score: 1 (no compliance) - 5 (full compliance)Prevention Index Score: 1 (no compliance) - 5 (full compliance)Protection Index Score: 1 (no compliance) - 5 (full compliance)3P Anti-trafficking Policy Index Score: 3 (no compliance for any of the three areas) - 15 (full compliance for all of the three areas) The 3P Anti-trafficking Policy Index is available for each country and each year and currently includes up to 189 countries for the preiod from 2000 to 2015.
  • A
    • 4月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 05 5月, 2019
      データセットを選択
      Not applicable
    • 3月 2016
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 11 12月, 2018
      データセットを選択
      To view the original national data please open the questionnaires. Source: Joint Forest Europe / UNECE / FAO Questionnaire on Pan-European Indicators for Sustainable Forest Management. Country: Russian Federation The source of the data of Russian Federation is the National Report for the Joint Forest Europe / UNECE / FAO reporting on quantitative pan-European indicators 2011.
    • 7月 2016
      ソース: Knoema
      アップロード者: Knoema
      データセットを選択
      Accuracy of annual economic forecasts of international organisations - European Commission, IMF, OECD, World Bank, UN LINK
    • 10月 2019
      ソース: National Institute of Statistics, Italy
      アップロード者: Knoema
      以下でアクセス: 21 10月, 2019
      データセットを選択
      Data source(s) used: Migration and calculation of foreign resident population and structure by citizenship : Istat since 2011 has been producing estimates on characteristics (citizenship of origin, gender and age) of the new Italian citizens and on the different ways of access to citizenship (marriage, residence, etc.). The data are also provided to Eurostat for Regulation (EC) 862/2007. The estimates are produced using different data sources. Istat: municipal registry lists Ministry of Interior: datasets on acquisitions of citizenship.
    • 11月 2018
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 21 11月, 2018
      データセットを選択
      The unemployed comprise all persons of working age who are without work, available for work, and looking for work, unless otherwise stated. This indicator presents the number of persons who have been unemployed for a year or longer as a percent of the unemployed population.
    • 7月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 01 8月, 2019
      データセットを選択
      This indicator aims to capture the share of persons in the labour force protected through a contributory pension scheme (with benefits guaranteed but not currently being received). It provides information about the proportion of the labour force that will receive an old age pension once reaching pensionable age. This right to income security in old age is guaranteed by the prior payment of premiums or contributions, i.e. before the occurrence of the insured contingency.
    • 9月 2014
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 31 8月, 2018
      データセットを選択
      This indicator aims to capture the share of persons in the labour force protected through a contributory pension scheme (with benefits guaranteed but not currently being received). It provides information about the proportion of the labour force that will receive an old age pension once reaching pensionable age. This right to income security in old age is guaranteed by the prior payment of premiums or contributions, i.e. before the occurrence of the insured contingency.
    • 9月 2014
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 31 8月, 2018
      データセットを選択
      This indicator aims to capture the share of persons of working age protected through a contributory pension scheme (with benefits guaranteed but not currently being received). It provides information about the proportion of the working-age population that will receive an old age pension once reaching pensionable age. This right to income security in old age is guaranteed by the prior payment of premiums or contributions, i.e. before the occurrence of the insured contingency.
    • 7月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 01 8月, 2019
      データセットを選択
      This indicator aims to capture the share of persons of working age protected through a contributory pension scheme (with benefits guaranteed but not currently being received). It provides information about the proportion of the working-age population that will receive an old age pension once reaching pensionable age. This right to income security in old age is guaranteed by the prior payment of premiums or contributions, i.e. before the occurrence of the insured contingency.
    • 6月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 11 6月, 2019
      データセットを選択
      Source: UNECE Statistical Database, compiled from national and international (Eurostat, UN Statistics Division Demographic Yearbook, WHO European health for all database and UNICEF TransMONEE) official sources. Definition: Adolescent fertility covers live births to women aged 15-19. A live birth is the complete expulsion or extraction from its mother of a product of conception, irrespective of the duration of pregnancy, which after such separation breathes or shows any other evidence of life such as beating of the heart, pulsation of the umbilical cord or definite movement of voluntary muscles, whether or not the umbilical cord has been cut or the placenta is attached. The adolescent fertility rate is the number of live births to women aged 15-19 per 1000 women aged 15-19. General note: Data on live births come from registers, unless otherwise specified. The adolescent fertility rate is computed by UNECE secretariat. .. - data not available Country: Albania Data refer to age group 0-19. Country: Armenia Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Data refer to age group 0-19. Country: Azerbaijan Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Data refer to age group 0-19. Country: Belarus Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Data refer to age group 0-19. Country: Bosnia and Herzegovina 1995 : data refer to 1996. Country: Canada Data include Canadian residents temporarily in the United States, but exclude United States residents temporarily in Canada. Country: Cyprus Data cover only the area controlled by the Republic of Cyprus. Country: Estonia Data refer to age group 0-19. Country: Finland Data include nationals temporarily outside the country. Country: Georgia Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. From 1995 : data do not cover Abkhazia and South Ossetia (Tshinvali). 1980-2003 : data refer to age group 15-20. Country: Germany 1980-1990 : data cover only West Germany (Federal Republic of Germany). From 1995 : data refer to reunified Germany, i.e. include the ex-German Democratic Republic (East Germany). Country: Ireland Data are tabulated by date of registration (rather than occurrence) and refer to births registered within one year of occurrence. 2005-2006 : provisional data. Country: Israel Data cover East Jerusalem and Israeli residents in certain other territories under occupation by Israeli military forces since June 1967. 1980 : data refer to age group 0-19. Country: Kazakhstan Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Data refer to age group 0-19. Country: Kyrgyzstan 1980-2003 : data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Country: Latvia Data refer to age group 0-19. Country: Malta Data refer to age group 0-19. Country: Netherlands Data refer to age group 0-19. Country: Norway Age classification is based on year of birth of mother rather than the exact age of mother at birth of child. Country: Poland 1980 : data refer to age group 0-19. Country: Portugal Data refer to resident mothers. Country: Russian Federation Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Data refer to age group 0-19. Country: Serbia Data do not cover Kosovo and Metohija. Data are tabulated by date of registration (rather than occurrence). Country: Turkey 1980-2000: data source is population censuses. From 2001: data are from administrative source. Country: Turkmenistan Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Data refer to age group 0-19. Country: Ukraine Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. 2000 : data refer to 1998. 1990 : data refer to age group 0-19. Country: United Kingdom Data are tabulated by date of occurrence for England and Wales and by date of registration for Northern Ireland and Scotland. Country: United States 2000 : data refer to 1999. Country: Uzbekistan Data refer to age group 18-19.
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 16 4月, 2019
      データセットを選択
    • 2月 2016
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 22 11月, 2018
      データセットを選択
      To view the original national data please open the questionnaires. Source: Joint Forest Europe / UNECE / FAO Questionnaire on Pan-European Indicators for Sustainable Forest Management. Country: Russian Federation The source of the data of Russian Federation is the National Report for the Joint Forest Europe / UNECE / FAO reporting on quantitative pan-European indicators 2011.
    • 2月 2016
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 22 11月, 2018
      データセットを選択
      To view the original national data please open the questionnaires. Source: Joint Forest Europe / UNECE / FAO Questionnaire on Pan-European Indicators for Sustainable Forest Management. Country: Russian Federation The source of the data of Russian Federation is the National Report for the Joint Forest Europe / UNECE / FAO reporting on quantitative pan-European indicators 2011.
    • 3月 2019
      ソース: Chief Executives Board for Coordination, UN
      アップロード者: Knoema
      以下でアクセス: 10 10月, 2019
      データセットを選択
      Agency Revenue By Government Donor for assessed revenue type
    • 7月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 01 8月, 2019
      データセットを選択
      Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.
    • 5月 2013
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
    • 5月 2013
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
    • 11月 2018
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      The data describe the average use of chemical and mineral fertilizers per area of cropland (arable land and permanent crops) at national, regional, and global level in a time series from 2002 to 2014The data describe the average use of chemical and mineral fertilizers per area of cropland (arable land and permanent crops) at national, regional, and global level in a time series from 2002 to 2015
    • 9月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 16 10月, 2019
      データセットを選択
      The Agri-environmental Indicators—Land domain provides information on the annual evolution of the distribution of agricultural and forest areas, and their sub-components, including irrigated areas, at national, regional and global levels.
    • 4月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 26 8月, 2019
      データセットを選択
      The Livestock Patterns domain of the FAOSTAT Agri-Environmental Indicators contains data on livestock numbers, shares of major livestock species and livestock densities in the agricultural area. Values are calculated using Livestock Units (LSU), which facilitate aggregating information for different livestock types. Data are available by country, with global coverage, for the period 1961–2014. This methodology applies the LSU coefficients reported in the "Guidelines for the preparation of livestock sector reviews" (FAO, 2011). From this publication, LSU coefficients are computed by livestock type and by country. The reference unit used for the calculation of livestock units (=1 LSU) is the grazing equivalent of one adult dairy cow producing 3000 kg of milk annually, fed without additional concentrated foodstuffs. FAOSTAT agri-environmental indicators on livestock patterns closely follow the structure of the indicators in EUROSTAT.
    • 12月 2018
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 26 8月, 2019
      データセットを選択
      The data describe the average use of pesticides per area of cropland (arable land and permanent crops) at national level in a time series from 1990 to 2014. 
    • 5月 2013
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
    • 5月 2013
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 09 4月, 2019
      データセットを選択
      commitment is a firm written obligation by a government or official agency, backed by the appropriation or availability of the necessary funds, to provide resources of a specified amount under specified financial terms and conditions and for specified purposes for the benefit of a recipient country or a multilateral agency. Members unable to comply with this definition should explain the definition that they use. -- Commitments are considered to be made at the date a loan or grant agreement is signed or the obligation is otherwise made known to the recipient (e.g. in the case of budgetary allocations to overseas territories, the final vote of the budget should be taken as the date of commitment). For certain special expenditures, e.g. emergency aid, the date of disbursement may be taken as the date of commitment. -- Bilateral commitments comprise new commitments and additions to earlier commitments, excluding any commitments cancelled during the same year. Cancellations and reductions in the year reported on of commitments made in earlier years are reported in the CRS, but not in the DAC questionnaire. -- In contrast to bilateral commitments, commitments of capital subscriptions, grants and loans to multilateral agencies should show the sum of amounts which are expected to be disbursed before the end of the next year and amounts disbursed in the year reported on but not previously reported as a commitment. For capital subscriptions in the form of notes payable at sight, enter the expected amount of deposits of such notes as the amount committed.
    • 7月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 02 7月, 2019
      データセットを選択
      Destination of Official Development Assistance Disbursements. Geographical breakdown by donor, recipient and for some types of aid (e.g. grant, loan, technical co-operation) on a disbursement basis (i.e. actual expenditures). The data cover flows from bilateral and multilateral donors which focus on flows from DAC member countries and the EU Institutions.
    • 12月 2017
      ソース: The General Aviation Manufacturers Association
      アップロード者: Sandeep Reddy
      以下でアクセス: 28 5月, 2018
      データセットを選択
      General aviation operations are defined by the FAA based Source: FAA Operations Network (OPSNET) on the traffic operations counted in the OPSNET. Air Traffic Control data shows federal, non-federal, and military through 2005, while 2006 through 2011 are FAA and contract.
    • 6月 2013
      ソース: World Bank
      アップロード者: Knoema
      以下でアクセス: 21 11月, 2014
      データセットを選択
      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).
    • 10月 2019
      ソース: National Institute of Statistics, Italy
      アップロード者: Knoema
      以下でアクセス: 04 10月, 2019
      データセットを選択
      Data source(s) used: Crimes reported to the Judicial authorities by the State Police, Carabinieri and Guardia di Finanza: Are processed the data on felonies and people who were reported by police to the court Other data characteristics: Data referring to social demographic characteristics of alleged offenders could not coincide with data on reports because of the different timing of extraction from police forces database.The sum of the crimes by province could not coincide with the total of the region, and that of the regions with the total Italy, because of the missed precise statement, for some crimes, of the place where they have been committed (or of the region of the committed crime but not of the province).
    • 4月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 16 4月, 2019
      データセットを選択
      Source: UNECE Statistical Database, compiled from national official sources Definition: An ambassador is a diplomatic official accredited to a foreign sovereign or government, or to an international organisation, to serve as the official representative of his or her own country. In everyday usage it applies to the top ranking government representative stationed in a foreign country. .. - data not available Country: Belarus Including consuls genaral Country: Cyprus Reference period (2008): data refer to 2009 Country: Cyprus Territorial change (2006 onward): Government controlled area only. Country: Finland Reference period (2013): situation in March 3, 2014 Country: Georgia Territorial change (1995 onward): Data do not cover Abkhazia AR and Tskhinvali Region. Country: Iceland Data refers to number at end of year. Country: Kazakhstan 1990: data refer to 1992-1994; 1995: data refer to 1999. Country: Latvia Change in definition (1995 - 2012): Data refer to Ambassadors, Ambassadors-at-large, Consuls General, Vice Consuls. Country: Montenegro 2008: data refer to 2009. Country: Slovakia Reference period (2015): Data refer to October 20, 2015. Data refer to heads of Diplomatic missions of the Slovak Republic (Ambassadors, Charge d?affaires, Consul General etc.) Country: Spain 2013 data correspond to 24 January 2014. 2015 data correspond to 15 July 2015. Country: Switzerland Change in definition (1980 - onwards): Data include only heads of missions, i.e. exclude collaborators with ambassador title.
    • 9月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 06 10月, 2016
      データセットを選択
      Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category:Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below:Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 29 10月, 2016
      データセットを選択
      Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category:Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below:Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 29 10月, 2016
      データセットを選択
      Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category:Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below:Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 29 10月, 2016
      データセットを選択
      Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category:Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below:Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 29 10月, 2016
      データセットを選択
      Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards. SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category:Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat's website by tables and an example of the existent tables is presented below:Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N2701/98 and amended by Commission Regulation N1614/2002 and Commission Regulation N1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values.
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 10 10月, 2016
      データセットを選択
      Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category:Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below:Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.
    • 2月 2016
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 22 11月, 2018
      データセットを選択
      To view the original national data please open the questionnaires. Source: Joint Forest Europe / UNECE / FAO Questionnaire on Pan-European Indicators for Sustainable Forest Management. Country: Russian Federation The source of the data of Russian Federation is the National Report for the Joint Forest Europe / UNECE / FAO reporting on quantitative pan-European indicators 2011.
    • 8月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 07 8月, 2019
      データセットを選択
      Yearly data on freshwater resources, water abstraction and use, wastewater treatment (connection rates of resident population to wastewater treatment and treatment capacities of wastewater treatment plants), sewage sludge production and disposal, generation and discharge of wastewater collected biennially by means of the OECD/Eurostat Joint Questionnaire - Inland Waters. Data aggregation: national territories.
    • 12月 2009
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 27 5月, 2014
      データセットを選択
      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
    • 5月 2019
      ソース: European Commission
      アップロード者: Knoema
      以下でアクセス: 11 5月, 2019
      データセットを選択
      AMECO is the annual macro-economic database of the European Commission's Directorate General for Economic and Financial Affairs. The database is indispensable for the analyses and reports of the Directorate General and contains data for EU-28, the euro area, EU Member States, candidate countries and other OECD countries. The database contains data for EU-28, the euro area, EU Member States, candidate countries and other OECD countries (United States, Japan, Canada, Switzerland, Norway, Iceland, Mexico, Korea, Australia and New Zealand). Data for Member States and candidate countries are based on the ESA 2010 system for the last period and on ESA 95 and ESA 79 for the earlier years. Data for other OECD countries are based on the SNA 2008. Discontinuities of the levels of all series have been removed by applying the growth rates of the old series to the levels of the new series.
    • 6月 2017
      ソース: International Tropical Timber Organization
      アップロード者: Knoema
      以下でアクセス: 24 7月, 2017
      データセットを選択
      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. Data cited at: ITTO Biennial review statistics: https://www.itto.int/biennal_review/
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Eurostat's database covers 1) Production and trade in roundwood and wood products, including primary and secondary products 2) Economic data on forestry and logging, including employment data 3) Sustainable forest management, comprising forest resources (assets) and environmental data. The main types of primary forest products included in (1) are: roundwood, sawnwood, wood-based panels, pulp, and paper and paperboard. Secondary products include further processed wood and paper products. These products are presented in greater detail; definitions are available. All of the data are compiled from the Joint Forest Sector Questionnaire (JFSQ), except for table (e), which is directly extracted from Eurostat's international trade database COMEXT (HS/CN Chapter 44). The tables in (1) cover details of the following topics: - Roundwood removals and production by type of wood and assortment (a) - Roundwood production by type of ownership (b) - Production and trade in roundwood, fuelwood and other basic products (c) - Trade in industrial roundwood by assortment and species (d) - Tropical wood imports to the EU from Chapter 44 of the Harmonised System (e) - Production and trade in sawnwood, panels and other primary products (f) - Sawnwood trade by species (g) - Production and trade in pulp and paper & paperboard (h) - Trade in secondary wood and paper products (i) Data in (2) include the output, intermediate consumption, gross value added, fixed capital consumption, gross fixed capital formation and different measures of income of forestry and logging.  The data are in current basic prices and are compatible with National Accounts. They are collected as part of Intergrated environmental and economic accounting for forests (IEEAF), which also covers labour input in annual work units (AWU).  Under (2), two separate tables cover the number of employees of forestry and logging, the manufacture of wood and products of wood and cork, and the manufacture of paper and paper products, as estimated from the Labour Force Survey results. There are two separate tables because of the change in the EU's classification of economic activities from NACE Rev. 1.1 to NACE Rev. 2 in 2008. More detailed information on wood products and accounting, including definitions and questionnaires, can be found on our open-access communication platform under the interest group 'Forestry statistics and accounts'.  Data in (3) are not collected by Eurostat, but by the FAO, UNECE, Forest Euope, the European Commission's departments for Environment and the Joint Research Centre. They include forest area, wood volume, defoliation on sample plots, fires and areas with protective functions.
    • 4月 2019
      ソース: Islamic Development Bank
      アップロード者: Knoema
      以下でアクセス: 12 8月, 2019
      データセットを選択
    • 10月 2013
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 28 11月, 2015
      データセットを選択
      Aquaculture, also known as aquafarming, refers to the farming of aquatic (freshwater or saltwater) organisms, such as fish, molluscs, crustaceans and plants, for human use or consumption, under controlled conditions. Aquaculture implies some form of intervention in the natural rearing process to enhance production, including regular stocking, feeding and protection from predators. Farming also implies individual or corporate ownership of, or contractual rights to, the stock being cultivated. European data on the quantity of aquaculture production, in tonnes life weight (TLW), have been recorded since 1950 [fish_aq_q]. Since 1984, data on the total value of the production in Thousand Euro are also available [fish_aq_v]. With the entry into force of the new Regulation (EC) No 762/2008 on the submission of aquaculture statistics, since the reference year 2008 aquaculture production data are collected and disseminated annually in 5 tables: Production from aquaculture excluding hatcheries and nurseries [fish_aq2a] by species, by FAO major area, by production method, by aquatic environment in TLW (tonnes live weight) and in Euro.Production of fish eggs for human consumption from aquaculture [fish_aq2b] by species, by FAO major area, by aquatic environment in TLW, Euro and Euro/Tonne.Input to capture-based aquaculture [fish_aq3] by species in Number, TLW, Euro and Euro/Tonne.Production of hatcheries and nurseries at eggs stage in life cycle [fish_aq4a] by species and intended uses in Millions.Production of hatcheries and nurseries at juveniles stage in life cycle [fish_aq4b] by species and intended uses in Millions. Every three years, these data are complemented by Data on the structure of the aquaculture sector [fish_aq5] by species, by FAO major area, by production method, by aquatic environment in Meters, 1000 of M3 and Hectares. In addition, annual methodological reports of the national systems for aquaculture statistics [fish_aq6] are provided by the EEA Member States with details on the organisation of the national systems for aquacuture statistics and the respective methods of collecting, processing and compiling the aquaculture data as well as quality aspects in line with the 'Code of Practice for the European Statistical System'. According to the Regulation (EC) No 762/2008, aquaculture production means the output from aquaculture at first sale (including production from hatcheries and nurseries offered for sale). Non-commercial leisure aquaculture is thus not accounted for. Moreover, aquaculture production of aquarium and ornamental species is excluded. Data are submitted by all Member States of the European Economic Area by the 31st of December for the preceeding year (reporting year -1). They are compiled by the respective competent authorities of the Member States, usually either the National Statistical Institute or the Ministry of Agriculture.
    • 10月 2013
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 28 11月, 2015
      データセットを選択
      Aquaculture, also known as aquafarming, refers to the farming of aquatic (freshwater or saltwater) organisms, such as fish, molluscs, crustaceans and plants, for human use or consumption, under controlled conditions. Aquaculture implies some form of intervention in the natural rearing process to enhance production, including regular stocking, feeding and protection from predators. Farming also implies individual or corporate ownership of, or contractual rights to, the stock being cultivated. European data on the quantity of aquaculture production, in tonnes life weight (TLW), have been recorded since 1950 [fish_aq_q]. Since 1984, data on the total value of the production in Thousand Euro are also available [fish_aq_v]. With the entry into force of the new Regulation (EC) No 762/2008 on the submission of aquaculture statistics, since the reference year 2008 aquaculture production data are collected and disseminated annually in 5 tables: Production from aquaculture excluding hatcheries and nurseries [fish_aq2a] by species, by FAO major area, by production method, by aquatic environment in TLW (tonnes live weight) and in Euro.Production of fish eggs for human consumption from aquaculture [fish_aq2b] by species, by FAO major area, by aquatic environment in TLW, Euro and Euro/Tonne.Input to capture-based aquaculture [fish_aq3] by species in Number, TLW, Euro and Euro/Tonne.Production of hatcheries and nurseries at eggs stage in life cycle [fish_aq4a] by species and intended uses in Millions.Production of hatcheries and nurseries at juveniles stage in life cycle [fish_aq4b] by species and intended uses in Millions. Every three years, these data are complemented by Data on the structure of the aquaculture sector [fish_aq5] by species, by FAO major area, by production method, by aquatic environment in Meters, 1000 of M3 and Hectares. In addition, annual methodological reports of the national systems for aquaculture statistics [fish_aq6] are provided by the EEA Member States with details on the organisation of the national systems for aquacuture statistics and the respective methods of collecting, processing and compiling the aquaculture data as well as quality aspects in line with the 'Code of Practice for the European Statistical System'. According to the Regulation (EC) No 762/2008, aquaculture production means the output from aquaculture at first sale (including production from hatcheries and nurseries offered for sale). Non-commercial leisure aquaculture is thus not accounted for. Moreover, aquaculture production of aquarium and ornamental species is excluded. Data are submitted by all Member States of the European Economic Area by the 31st of December for the preceeding year (reporting year -1). They are compiled by the respective competent authorities of the Member States, usually either the National Statistical Institute or the Ministry of Agriculture.
    • 9月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 04 9月, 2019
      データセットを選択
      AQUASTAT is FAO's global information system on water and agriculture, developed by the Land and Water Division. The main mandate of the program is to collect, analyze and disseminate information on water resources, water uses, and agricultural water management with an emphasis on countries in Africa, Asia, Latin America and the Caribbean. This allows interested users to find comprehensive and regularly updated information at global, regional, and national levels.
    • 1月 2014
      ソース: World Resources Institute
      アップロード者: Knoema
      以下でアクセス: 07 12月, 2015
      データセットを選択
      This dataset shows countries and river basins' average exposure to five of Aqueduct's water risk indicators: baseline water stress, interannual variability, seasonal variability, flood occurrence, and drought severity. Risk exposure scores are available for every country (except Greenland and Antarctica), the 100 most populous river basins, and the 100 largest river basins by area. Scores are also available for all industrial, agricultural, and domestic users' average exposure to each indicator in each country and river basin. Citation: Gassert, F., P. Reig, T. Luo, and A. Maddocks. 2013. “Aqueduct country and river basin rankings: a weighted aggregation of spatially distinct hydrological indicators.” Working paper. Washington, DC: World Resources Institute, November 2013. Available online at http://wri.org/publication/aqueduct-country-river-basin-rankings.
    • 8月 2015
      ソース: World Resources Institute
      アップロード者: Knoema
      以下でアクセス: 25 3月, 2019
      データセットを選択
      Suggested citation: Luo, T., R. Young, and P. Reig. 2015. "Aqueduct projected water stress rankings." Technical note. Washington, DC: World Resources Institute, August 215. Available online at http://www.wri.org/publication/aqueduct-projected-water-stress-country-rankings.    Supplemental Materials: Country Scores                         WRI projected future country-level water stress for 2020, 2030, and 2040 under business-as-usual (BAU), optimistic, and pessimistic scenarios. Each tab lists country projected water stress scores for each scenario and year, weighted by overall water withdrawals. Scores weighted by individual sectors (agricultural, domestic, and industrial) are provided as well.   These global projections are best suited to making comparisons among countries for the same year and among scenarios and decades for the same region. More detailed and localized data or scenarios can better estimate potential outcomes for specific regions and expose large sub-national variations that are subsumed under countrywide water-stress values. The country indicators face persistent limitations in attempting to simplify complex information, such as spatial and temporal variations, into a single number. They also do not account for the governance and investment structure of the water sector in different countries.    It is important to note the inherent uncertainty in estimating any future conditions, particularly those associated with climate change, future population and economic trends, and water demand. Additionally, care should be taken when examining the change rates of a country’s projected stress levels between one year and another, because the risk-score thresholds are not linear. For more information on these limitations, see the technical note.   Projections are described in further detail in: Luck, M., M. Landis, and F. Gassert, “Aqueduct Water Stress Projections: Decadal Projections of Water Supply and Demand Using CMIP5 GCMs,” Technical note (Washington, DC: World Resources Institute, April 2015), http://www.wri.org/publication/aqueduct-water-stress-projections.   Water Stress withdrawals / available flow Water stress measures total annual water withdrawals (municipal, industrial, and agricultural) expressed as a percentage of the total annual available blue water. Higher values indicate more competition among users. Score Value [0-1) Low (<10%) [1-2) Low to medium (10-20%) [2-3) Medium to high (20-40%) [3-4) High (40-80%) [4-5] Extremely high (>80%)    
    • 11月 2019
      ソース: Knoema
      アップロード者: Knoema
      以下でアクセス: 11 11月, 2019
      データセットを選択
      Source Dataset: Production, Supply and Distribution of Agricultural Commodities by Market Year Resource Statistics - Land
    • 4月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 30 4月, 2019
      データセットを選択
      To view the original national data please open the questionnaires. The published data contain editions to the values available in national reports. Source: Joint COST Action FACESMAP/UNECE/FAO Enquiry on Forest Ownership in the ECE Region. Country: France The values of the “Owned by local government” category represent the aggregated data of the two categories: “Owned by the state at sub-national government scale” and “Owned by local government”. Please refer to the national report to see the reported values.
    • 4月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 30 4月, 2019
      データセットを選択
      To view the original national data please open the questionnaires. The published data contain editions to the values available in national reports. Source: Joint COST Action FACESMAP/UNECE/FAO Enquiry on Forest Ownership in the ECE Region. Country: Slovakia The values of the “11-50 ha” size represent the aggregated data of the two sizes: “11-50 ha” and “51-500 ha”. Please refer to the national report to see the reported values.
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 26 10月, 2019
      データセットを選択
    • 4月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 30 4月, 2019
      データセットを選択
      To view the original national data please open the questionnaires. The published data contain editions to the values available in national reports. Source: Joint COST Action FACESMAP/UNECE/FAO Enquiry on Forest Ownership in the ECE Region.
    • 4月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 30 4月, 2019
      データセットを選択
      To view the original national data please open the questionnaires. The published data contain editions to the values available in national reports. Source: Joint COST Action FACESMAP/UNECE/FAO Enquiry on Forest Ownership in the ECE Region.
    • 2月 2016
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 21 11月, 2018
      データセットを選択
      To view the original national data please open the questionnaires. Source: Joint Forest Europe / UNECE / FAO Questionnaire on Pan-European Indicators for Sustainable Forest Management. Country: Russian Federation The source of the data of Russian Federation is the National Report for the Joint Forest Europe / UNECE / FAO reporting on quantitative pan-European indicators 2011.
    • 3月 2016
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 21 11月, 2018
      データセットを選択
      To view the original national data please open the questionnaires. Source: Joint Forest Europe / UNECE / FAO Questionnaire on Pan-European Indicators for Sustainable Forest Management. Country: Russian Federation The source of the data of Russian Federation is the National Report for the Joint Forest Europe / UNECE / FAO reporting on quantitative pan-European indicators 2011.
    • 3月 2019
      ソース: Stockholm International Peace Research Institute
      アップロード者: Knoema
      以下でアクセス: 19 3月, 2019
      データセットを選択
      Data cited at: Stockholm International Peace Research Institute (SIPRI)   The SIPRI Arms Transfers Database contains information on all transfers of major conventional weapons from 1950 to the most recent full calendar year. It is a unique resource for researchers, policy-makers and analysts, the media and civil society interested in monitoring and measuring the international flow of major conventional arms. For more information, see http://www.sipri.org/databases/armstransfers/sources-and-methods/
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 12 11月, 2019
      データセットを選択
      Accommodation statistics are a key part of the system of tourism statistics in the EU and have a long history of data collection. Annex I of the Regulation (EU) 692/2011 of the European Parliament and of the Council deals with accommodation statistics and includes 4 sections focusing on accommodation statistics of which sections 1 and 2 include the requirements concerning rented accommodation (capacity and occupancy respectively). Data are collected by the competent national authorities of the Member States and are compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Most of the time, data are collected via sample or census surveys. However, in a few cases data are compiled from a demand-side perspective (i.e. via visitor surveys or border surveys). Surveys on the occupancy of accommodation establishments are generally conducted on a monthly basis. The concepts and definitions used in the collection of data shall conform to the specifications described in the Methodological manual for tourism statistics. Accommodation statistics comprise the following information: Monthly data on tourism industries (NACE 55.1, 55.2 and 55.3) Monthly occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Net occupancy rate of bed-places and bedrooms in hotels and similar accommodation Annual data on tourism industries(NACE 55.1, 55.2 and 55.3) Occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Capacity of tourist accommodation establishments: number of establishments, bedrooms and bed places Regional data  Annual occupancy (arrivals and nights spent by residents and non-residents) of tourist accommodation establishments at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Annual data on number of establishments, bedrooms and bed places at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Data on number of establishments, bedrooms and bed places are available by activity at NUTS 3 level until 2011. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.
    • 10月 2016
      ソース: Hellenic Statistical Authority
      アップロード者: Knoema
      以下でアクセス: 13 6月, 2019
      データセットを選択
    • 10月 2013
      ソース: International Organization of Motor Vehicle Manufacturers
      アップロード者: Carpe Facto
      データセットを選択
      The International Organization of Motor Vehicle Manufacturers was founded in Paris in 1919. It is known as the “Organisation Internationale des Constructeurs d’Automobiles” (OICA). This dataset contains figures related to auto production, sales and usage.
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 07 9月, 2019
      データセットを選択
      Regional accounts are a regional specification of the national accounts and therefore based on the same concepts and definitions as national accounts (see domain nama10). The main specific regional issues are addressed in chapter 13 of ESA2010, but not practically specified. For practical rules and recommendations on sources and methods see the publication "Manual on regional accounts methods": http://ec.europa.eu/eurostat/en/web/products-manuals-and-guidelines/-/KS-GQ-13-001 . Gross domestic product (GDP) at market prices is the final result of the production activity of resident producer units. 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 expenditure approach cannot be 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 plus gross operating surplus and mixed income plus taxes on products less subsidies plus consumption of fixed capital. 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 EU28 average.
    • 6月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 19 6月, 2019
      データセットを選択
      The source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 02 10月, 2019
      データセットを選択
      Labour cost statistics provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. Structural information on labour costs is collected through four-yearly Labour Cost Surveys (LCS), which provides details on the level and structure of labour cost data, hours worked and hours paid. LCS results are available for the reference years 2000, 2004, 2008 and 2012. All EU Member States together with Norway and Iceland (2004 onwards), Turkey and Macedonia (2008), as well as Serbia (2012) participated in the LCS. As far as available data and confidentiality rules permit, all variables and proportions are further broken down by enterprise size category, economic activity and region (for larger countries only). The data are collected by the National Statistical Institutes in most cases on the basis of stratified random samples of enterprises or local units, restricted in most countries to units with at least 10 employees. The stratification is based on economic activity, size category and region (where appropriate). Regional metadata is identical to the metadata provided for national data. Some countries also complement the survey results with administrative data. Monetary variables are expressed in EUR, national currencies (for non-euro-area countries) and Purchasing Power Standards (PPS). Labour costs are quoted in total per year, per month and per hour, as well as per capita and per full-time equivalents (FTE). Information on staff, hours worked and hours paid is quoted in aggregate and separately for full- and part-time employees.
    • 7月 2018
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 17 7月, 2018
      データセットを選択
      This table presents data on average monthly earnings converted to a common currency. Data in U.S. dollars are converted from local currency using exchange rates, while data in constant 2011 U.S. dollars are converted using 2011 purchasing power parities (PPPs)   Dataset splitted into below datasets:-   Local Currency (Total) - https://knoema.com/EAR_TEAR_NOC_NB   Local Currency (Men) - https://knoema.com/EAR_MEAR_NOC_NB   Local Currency (Women) - https://knoema.com/EAR_FEAR_NOC_NB   Constant 2011 PPP $ (Total) - https://knoema.com/EAR_4MPT_NOC_NB   Constant 2011 PPP $ (Men) - https://knoema.com/EAR_4MPM_NOC_NB   Constant 2011 PPP $ (Women) - https://knoema.com/EAR_4MPW_NOC_NB
    • 7月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 01 8月, 2019
      データセットを選択
    • 7月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 01 8月, 2019
      データセットを選択
      The concept of earnings, as applied in wages statistics, relates to gross remuneration in cash and in kind paid to employees, as a rule at regular intervals, for time worked or work done together with remuneration for time not worked, such as annual vacation, other type of paid leave or holidays. This indicator is presented in terms of the average monthly earnings per employee, in local currency.
    • 7月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 01 8月, 2019
      データセットを選択
    • 7月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 01 8月, 2019
      データセットを選択
      The concept of earnings, as applied in wages statistics, relates to gross remuneration in cash and in kind paid to employees, as a rule at regular intervals, for time worked or work done together with remuneration for time not worked, such as annual vacation, other type of paid leave or holidays. This indicator is presented in terms of the average monthly earnings per employee, in local currency, for men.
    • 7月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 01 8月, 2019
      データセットを選択
    • 7月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 01 8月, 2019
      データセットを選択
      The concept of earnings, as applied in wages statistics, relates to gross remuneration in cash and in kind paid to employees, as a rule at regular intervals, for time worked or work done together with remuneration for time not worked, such as annual vacation, other type of paid leave or holidays. This indicator is presented in terms of the average monthly earnings per employee, in local currency, for women.
  • B
    • 10月 2019
      ソース: Statistics Denmark
      アップロード者: Knoema
      以下でアクセス: 11 10月, 2019
      データセットを選択
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 10 11月, 2019
      データセットを選択
      The Balance of Payments (BOP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of an economic area during a given period. The Balance of payments provides harmonized information on international transactions which are part of the current account (goods, services, primary and secondary income), as well as on transactions which fall in the capital and the financial account. International investment position presents value of financial assets owned outside the economy and indebtedness of the economy to the rest of the world. BOP is an important macro-economic indicator used to assess the position of an economy (of credit or debit for current and capital acount, net acquisition of financial assets or net incurrence of liabilities for BOP financial account and international investment position) towards the external world. Out of BOP data, some indicators on international position of the EU and Member States are derived. Indicators on Main Balance of Payments and International Investment Position items as share of GDP are presented as percentage of GDP for given year or quarter and moving average for 3 consecutive years for: Balance, credit and debit flows of current and capital accounts and of main current account  items: goods, services, primary and secondary income,Net flows, net acquisition of financial assets and net incurrence of liabilities for total financial account and foreign direct investment,International investment position and net external debt at the end of reference quarter or year. Indicators on export market shares present shares of each EU Member State in total world exports of goods and services for given year, and 1-year and 5-year percentage changes of these shares, as well as shares in OECD exports and 5-year percentage changes of these shares.
    • 5月 2019
      ソース: International Monetary Fund
      アップロード者: Knoema
      以下でアクセス: 28 5月, 2019
      データセットを選択
      BOPSY Global Tables aggregate country data by major balance of payments components and by international investment position (IIP) data for (i) Net IIP and (ii) Total Assets and Total Liabilities. Data for countries, country groups, and the world are provided. In addition to data reported by countries as shown in BOPSY, balance of payments data are provided for international organizations in BOPSY Global Tables. The BOPSY Global Tables include, in addition to reported data, data derived in a few instances indirectly from published sources.
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 08 11月, 2019
      データセットを選択
      The Balance of Payments (BoP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of a geographical region during a given period. The Balance of payments provides harmonized information on international transactions which are part of the current account (goods, services, income, current transfers), but also on transactions which fall in the capital and the financial account. BoP is an important macro-economic indicator used to assess the position of an economy (of credit or debit) towards the external world. Data on International Trade in Services, a component of BoP current account, and data on Foreign Direct Investment, a component of BoP financial account, are used to monitor the external commercial performance of different economies. Outward Foreign Affiliates Statistics (FATS) measure the commercial presence, as defined by the General Agreement on Trade in Services (GATS), through affiliates in foreign markets. Balance of Payments data are used for calculation of indicators needed for monitoring of macroenomic imbalances such as share of main BoP and International Investment Position (IIP) items in GDP and export market shares calculated as the EU Member States' shares in total world exports.  Out of BoP data, some indicators of EU market integration are also derived. Data are in millions of Euro/ECU or in millions of national currency. Balance of Payments data coverage varies according to the collection. Some collections refer only to Euro area or EU countries, while some others' coverage includes also EU partner countries.   Several statistical adjustments are applied to the original data provided by the Member States. The International Monetary Fund Balance of Payments Manual (BPM5) classification is used for the compilation of the BoP. The BoP data are collected through national surveys and administrative sources.    More information on BoP is available for each specific collection: Quarterly BoP, ITS, FDI, Outward FATS, BoP of EU Institutions.
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 08 11月, 2019
      データセットを選択
      The Balance of Payments is the statistical statement that systematically summarises transactions between residents and non-residents. It consists of the goods and services account, the primary income account, the secondary income account, the capital account and the financial account (BPM6 – 2.12) The current account is an important grouping of accounts within the Balance of Payments. The current account balance shows the difference between the sum of exports and income receivable and the sum of imports and income payable (exports and imports refer to both goods and services, while income refers to both primary and secondary income). The value of current account balance equals the saving-investment gap for the economy. The balance of current account is thus related to understanding domestic transactions (BPM6 – 2.15). Data are expressed in million euros. Data are presented in raw form. Source of euro area data: European Central Bank (ECB).
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 08 11月, 2019
      データセットを選択
      The Balance of Payments (BOP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of an economic area during a given period. The Balance of payments provides harmonized information on international transactions which are part of the current account (goods, services, primary and secondary income), as well as on transactions which fall in the capital and the financial account. International investment position presents value of financial assets owned outside the economy and indebtedness of the economy to the rest of the world. BOP is an important macro-economic indicator used to assess the position of an economy (of credit or debit for current and capital acount, net acquisition of financial assets or net incurrence of liabilities for BOP financial account and international investment position) towards the external world. Out of BOP data, some indicators on international position of the EU and Member States are derived. Indicators on Main Balance of Payments and International Investment Position items are presented for given quarter for:balance, credit and debit flows of current and capital accounts and of main current account  items: goods, services, primary and secondary income,net flows, net acquisition of financial assets and net incurrence of liabilities for total financial account and foreign direct investment, international investment position and net external debt at the end of reference quarter.
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 08 11月, 2019
      データセットを選択
      The Balance of Payments (BoP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of a geographical region during a given period. The Balance of payments provides harmonized information on international transactions which are part of the current account (goods, services, income, current transfers), but also on transactions which fall in the capital and the financial account. BoP is an important macro-economic indicator used to assess the position of an economy (of credit or debit) towards the external world. Data on International Trade in Services, a component of BoP current account, and data on Foreign Direct Investment, a component of BoP financial account, are used to monitor the external commercial performance of different economies. Outward Foreign Affiliates Statistics (FATS) measure the commercial presence, as defined by the General Agreement on Trade in Services (GATS), through affiliates in foreign markets. Balance of Payments data are used for calculation of indicators needed for monitoring of macroenomic imbalances such as share of main BoP and International Investment Position (IIP) items in GDP and export market shares calculated as the EU Member States' shares in total world exports.  Out of BoP data, some indicators of EU market integration are also derived. Data are in millions of Euro/ECU or in millions of national currency. Balance of Payments data coverage varies according to the collection. Some collections refer only to Euro area or EU countries, while some others' coverage includes also EU partner countries.   Several statistical adjustments are applied to the original data provided by the Member States. The International Monetary Fund Balance of Payments Manual (BPM5) classification is used for the compilation of the BoP. The BoP data are collected through national surveys and administrative sources.    More information on BoP is available for each specific collection: Quarterly BoP, ITS, FDI, Outward FATS, BoP of EU Institutions.
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 08 11月, 2019
      データセットを選択
      The Balance of Payments is the statistical statement that systematically summarises transactions between residents and non-residents. It consists of the goods and services account, the primary income account, the secondary income account, the capital account and the financial account (BPM6 – 2.12) The financial account shows net acquisition and disposal of financial assets and liabilities The financial account indicates the functional categories, sectors, instruments, and maturities used for net international financing transactions. (BPM6 – 8.1). Five functional categories of investment are distinguished in the international accounts: a) direct investment, b) portfolio investment, c) financial derivatives and employee stock options, d) other investment and e) reserve assets. (BPM6 – 6.1). Source of euro area data: European Central Bank (ECB).
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 12 11月, 2019
      データセットを選択
      This table includes the areas, productions and humidity of Winter barley sown before or during winter and Spring barley sown in the spring. Cereal grains harvested just before maturity are also included in this table. Cereals harvested green or yellow as whole plant for fodder or renewable energy use are not included in this table. This indicator uses the concepts of "area under cultivation", "harvested production" and "humidity". 1) The "area under cultivation" corresponds: • before the harvest, to the sown area; • after the harvest, to the sown area excluding the non-harvested area (e.g. area ruined by natural disasters, area not harvested for economic reasons, etc.) 2) The "harvested production" corresponds to the production for which harvesting started in year N, even thought harvesting may finish in year N+1. So N is the reference year for data published by Eurostat. 3) In order to facilitate the comparisons of production between the Members States, the publication of "humidity" for each country is needed. Only the EU-aggregate for the production is published with a standard EU humidity.
    • 6月 2015
      ソース: Barro-Lee
      アップロード者: Knoema
      以下でアクセス: 12 10月, 2015
      データセットを選択
      Data cited at: Barro-Lee  
    • 8月 2015
      ソース: Barro-Lee
      アップロード者: Knoema
      以下でアクセス: 12 10月, 2015
      データセットを選択
      Data cited at: Barro-Lee
    • 7月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 25 7月, 2019
      データセットを選択
      6.1. Reference area
    • 1月 2018
      ソース: Bertelsmann Stiftung
      アップロード者: Knoema
      以下でアクセス: 19 4月, 2018
      データセットを選択
      The Bertelsmann Stiftung’s Transformation Index (BTI) analyzes and evaluates the quality of democracy, a market economy and political management in 128 developing and transition countries. It measures successes and setbacks on the path toward a democracy based on the rule of law and a market economy flanked by sociopolitical safeguards. Within this framework, the BTI publishes two rankings, the Status Index and the Management Index. Countries are further categorized on the basis of these status index and management rankings/scores. For instance, countries are categorized in to 5 groups – viz; 5 or failed, 4 or very limited, 3 or limited, 2 or advanced, and 1 or highly advanced—based on their status index score of 1 to 10. A country with a high score, 8.5 and above, is categorized as highly advanced. A country with a low score, below 4, is categorized as failed. A country is categorized as ‘very limited’ if it has a status index score between 4 and 5.5. A score between 5.5 and 7 means the country is categorized as ‘limited’ and a country is categorized as ‘advanced’ for a score between 7.1 and 8.5. On the basis of the democratic status ranking, countries are further categorized as 5 or ‘hard - line autocracies,’ 4 or ‘moderate autocracies,’ 3 or ‘highly defective democracies,’ 2 or ‘defective democracies,’ and 1 or ‘democracies in consolidation.’ A country with a democratic status ranking below 4 is categorized as a hard line autocracy. A democratic status score between 4 and 5 means that the country is part of the ‘moderate autocracy’ group. A country is grouped as a ‘highly defective democracy’ for a score between 5 and 6. A country is recognized as a ‘defective democracy’ for a score between 6 and 8, and a score of 8 and above earns a country the status of a ‘democracy in consolidation.’ Countries are also categorized in to 5 groups based on their market economy status ranking. The countries are categorized as ‘rudimentary’ or group 5, ‘poorly functioning’ or group 4, ‘functional flaws’ or group 3, ‘functioning’ or group 2, and ‘developed’ or group 1. A country is recognized as a member of the ‘developed’ group with a market economy status ranking/score of 8 and above. A country is grouped as ‘functioning’ if it has a score between 7 and 8. A market economy status ranking between 5 and 7 means the country is categorized to group 3 or the ‘functional flaws’ group. A score between 3 and 5 means that the country is ‘poorly functioning’ and a score below 3 means the country enjoys a ‘rudimentary’ status. Based on the management index ranking, countries are categorized as 5 or failed, 4 or weak, 3 or moderate, 2 or good, and1 or very good. A country is categorized as ‘very good’ for a score of 7 and above. It is categorized as ‘good’ for a score between 5.6 and 7, and as ‘moderate’ for a score between 4.4 and 5.5. A score between 3 and 4.3 means a country is categorized as ‘weak,’ and a score below 3 means the categorization of a country as ‘failed.’ Countries are ranked between 1 and 10 on the basis of the level of difficulty they face. The level of difficulty is further categorized as 5 or negligible, 4 or minor, 3 or moderate, 2 or substantial, and 1 or massive. A score of 8.5 and above means the categorization of the country’s level of difficulty as ‘massive, and a score below 2.5 means the categorization of the level of difficulty faced by the country as ‘negligible.’ The level of difficulty score of 2.5 to 4.4 means a country faces a ‘minor’ level of difficulty and a score between 4.5 and 6.4 means the level of difficulty faced by a country is ‘moderate.’ A country with a score of 6.5 to 8.4 faces a ‘substantial’ level of difficulty.
    • 4月 2014
      ソース: United Nations Conference on Trade and Development
      アップロード者: Sandeep Reddy
      以下でアクセス: 08 2月, 2016
      データセットを選択
      UNCTAD's Bilateral FDI Statistics provides up-to-date and systematic FDI data for 206 economies around the world, covering inflows (table 1), outflows (table 2), inward stock (table 3) and outward stock (table 4) by region and economy. Data are in principle collected from national sources. In order to cover the entire world, where data are not available from national sources, data from partner countries (mirror data) as well as from other international organizations have also been used.
    • 4月 2018
      ソース: World Bank
      アップロード者: Knoema
      以下でアクセス: 14 11月, 2018
      データセットを選択
      This data set provides a snapshot of migration and remittances for all countries, regions and income groups of the world, compiled from available data from various sources
    • 4月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 4月, 2019
      データセットを選択
      This indicator is defined as the mean annual BOD5 in rivers, weighted by the number of measuring stations. BOD5 is a measure of the amount of oxygen required by aerobic microorganisms to decompose organic substances in a water sample over a period of five days in the dark at 20°C. It is presented as mg O2/L and indicates the quality of water: the lower the value of BOD5, the lower the organic pollution of the water.
    • 10月 2019
      ソース: United Nations COMTRADE
      アップロード者: Knoema
      以下でアクセス: 18 10月, 2019
      データセットを選択
      Both ethanol and biodiesel are classified under the HS-6 digit categories that also contain other products. Biodiesel is an industrial product (as it is produced through a chemical process called transesterification) and classified under HS code 382490 - products, preparations and residual products of the chemical or allied industries not elsewhere specified. Ethanol is classified as an agriculture product under HS code 2207, which covers un-denatured (HS 2207 10) and denatured alcohol (HS 2207 20).
    • 9月 2019
      ソース: Havocscope Black Market
      アップロード者: Knoema
      以下でアクセス: 11 10月, 2019
      データセットを選択
      Data cited at: Havocscope
    • 4月 2017
      ソース: Bloom Consulting
      アップロード者: Knoema
      以下でアクセス: 24 5月, 2017
      データセットを選択
      Bloom Consulting was founded in 2003 as a Nation Branding consultancy. Our Headquarters are located in Madrid, with offices in Lisbon and São Paulo. Bloom Consulting has been interviewed by The Economist, Forbes and CNN . According to Country Branding Central www.countrybrandingwiki.org, our CEO José Filipe Torres, a recurrent lecturer in Universities such as Harvard, is considered one of the top 3 international experts in the field of Nation Branding, Region and City Branding, providing advisory for the OECD. In addition, Bloom Consulting publishes the Bloom Consulting Country Brand Ranking © annually for both Trade and Tourism, to extensively analyze the brand performance of 193 countries and territories worldwide and the Digital Country Index - Measuring the Brand appeal of countries and territories in the Digital World.
    • 7月 2019
      ソース: State Statistical Office, Republic of North Macedonia
      アップロード者: Knoema
      以下でアクセス: 31 7月, 2019
      データセットを選択
      Symbols used Titles / circulation Circulation in thousands1) 1)The discrepancy in the data on circulation in the column 'total' is dueto rounding to thousands.
    • 2月 2019
      ソース: BP
      アップロード者: Sandeep Reddy
      以下でアクセス: 03 5月, 2019
      データセットを選択
      BP Energy Outlook Charts Data Pack - 2019 edition The Energy Outlook considers different aspects of the energy transition and the key issues and uncertainties these raise.   In all the scenarios considered, world GDP more than doubles by 2040 driven by increasing prosperity in fast-growing developing economies. In the Evolving transition (ET) scenario this improvement in living standards causes energy demand to increase by around a third over the Outlook, driven by India, China and Other Asia which together account for two-thirds of the increase. Despite this increase in energy demand, around two-thirds of the world’s population in 2040 still live in countries where average energy consumption per head is relatively low, highlighting the need for ‘more energy’. Energy consumed within industry and buildings accounts for around three-quarters of the increase in energy demand. Growth in transport demand slows sharply relative to the past, as gains in vehicle efficiency accelerate. The share of passenger vehicle kilometres powered by electricity increases to around 25% by 2040, supported by the growing importance of fully-autonomous cars and shared-mobility services.
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 07 11月, 2019
      データセットを選択
      Short-term statistics (STS) give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification (Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are generally presented in the following forms:UnadjustedCalendar adjustedSeasonally adjusted Depending on the STS regulation data are accessible as monthly, quarterly and annual data. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction (volume)*Turnover: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic turnover into euro area and non euro area is available for the euro area countriesProducer prices (output prices)*: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic producer prices into euro area and non euro area is available for the euro area countriesImport prices*: Total, Euro area market, Non euro area market (euro area countries only)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries CONSTRUCTIONProduction (volume)*: Total of the construction sector, Building construction, Civil EngineeringBuilding permits indicators*: Number of dwellings, Square meters of useful floor (or alternative size measure)Construction costs or prices: Construction costs, Material costs, Labour costs (if not available, they may be approximated by the Output prices variable)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries WHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (value)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries SERVICESTurnover (in value)*Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesProducer prices (Output prices )* National reference metadata of the reporting countries can be found in the Annexes of this metadata file.
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 07 11月, 2019
      データセットを選択
      Short-term statistics (STS) give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification (Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are generally presented in the following forms:UnadjustedCalendar adjustedSeasonally adjusted Depending on the STS regulation data are accessible as monthly, quarterly and annual data. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction (volume)*Turnover: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic turnover into euro area and non euro area is available for the euro area countriesProducer prices (output prices)*: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic producer prices into euro area and non euro area is available for the euro area countriesImport prices*: Total, Euro area market, Non euro area market (euro area countries only)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries CONSTRUCTIONProduction (volume)*: Total of the construction sector, Building construction, Civil EngineeringBuilding permits indicators*: Number of dwellings, Square meters of useful floor (or alternative size measure)Construction costs or prices: Construction costs, Material costs, Labour costs (if not available, they may be approximated by the Output prices variable)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries WHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (value)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries SERVICESTurnover (in value)*Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesProducer prices (Output prices )* National reference metadata of the reporting countries can be found in the Annexes of this metadata file.
    • 3月 2018
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 01 8月, 2019
      データセットを選択
    • 3月 2019
      ソース: World Bank
      アップロード者: Knoema
      以下でアクセス: 20 3月, 2019
      データセットを選択
      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Jobs Publication: https://datacatalog.worldbank.org/dataset/jobs License: http://creativecommons.org/licenses/by/4.0/   The World Bank Jobs Statistics Over 150 indicators on labor-related topics, covering over 200 economies from 1990 to present.
  • C
    • 10月 2017
      ソース: World Resources Institute
      アップロード者: Knoema
      以下でアクセス: 06 8月, 2018
      データセットを選択
      Data Citation: CAIT Climate Data Explorer. 2017. Washington, DC: World Resources Institute. Available online at: http://cait.wri.org   CAIT data carries a Creative Commons Attribution-NonCommercial 4.0 International license   CAIT Historic allows for easy access, analysis and visualization of the latest available international greenhouse gas emissions data. It includes information for 186 countries, 50 U.S. states, 6 gases, multiple economic sectors, and 160 years - carbon dioxide emissions for 1850-2012 and multi-sector greenhouse gas emission for 1990-2012.
    • 4月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 05 5月, 2019
      データセットを選択
      The energy balance is the most complete statistical accounting of energy products and their flow in the economy. The energy balance allows users to see the total amount of energy extracted from the environment, traded, transformed and used by different types of end-users. It also allows seeing the relative contribution of each energy carrier (fuel, product). The energy balance allows studying the overall domestic energy market and monitoring impacts of energy policies. The energy balance offers a complete view on the energy situation of a country in a compact format, such as on energy consumption of the whole economy and of individual sectors. The energy balance presents all statistically significant energy products (fuels) of a country and their production, transformation and consumption by different type of economic actors (industry, transport, etc.). Therefore, an energy balance is the natural starting point to study the energy sector. Annual data collection cover in principle the EU Member States, EFTA, EU candidate countries, and potential candidate countries. Time series starts mostly in year 1990. All data in energy balances are presented in terajoules, kilotonnes of oil equivalent and gigawatt hours.
    • 11月 2019
      ソース: Government of Canada
      アップロード者: Knoema
      以下でアクセス: 04 11月, 2019
      データセットを選択
      This dataset is updated with data obtained from Statistics Canada and the U.S. Census Bureau. Current data June 2018. Trade Data is updated on a monthly and annual basis, with revisions in March, April, May, August and November to previous year's data. Trade Data is available on both product and industry-based versions. The product Trade Data is classified by Harmonized System (HS) codes while the industry data is based on North American Industry Classification System(NAICS) classification codes. Source: Statistics Canada and the U.S.Census Bureau
    • 11月 2019
      ソース: Statistics Canada
      アップロード者: Knoema
      以下でアクセス: 04 11月, 2019
      データセットを選択
      For the location "Puerto Rico" data is available from 1990.
    • 12月 2018
      ソース: Institute for Health Metrics and Evaluation
      アップロード者: Sandeep Reddy
      以下でアクセス: 02 1月, 2019
      データセットを選択
      Data cited: Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2016 (GBD 2016) Cancer Incidence, Mortality, Years of Life Lost, Years Lived with Disability, and Disability-Adjusted Life Years 1990-2016. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2018.   The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries. Estimates for deaths, disability-adjusted life years (DALYs), years lived with disability (YLDs), years of life lost (YLLs), prevalence, and incidence for 29 cancer groups by age and sex for 1990-2016 are available from the GBD Results Tool. Files available in this record are the web tables published in JAMA Oncology in June 2018 in "Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-years for 29 Cancer Groups, 1990 to 2016."
    • 5月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 05 5月, 2019
      データセットを選択
      Eurostat Dataset Id:cpc_agmain  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 10月, 2016
      データセットを選択
      The focus of this domain is on enlargement countries, in other words the following country groups: candidate countries — Albania (AL), the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)potential candidates — Bosnia and Herzegovina (BA), as well as Kosovo (XK) (*) An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. (*) This designation is without prejudice to positions on status and is in line with UNSCR 1244 and the ICJ Opinion on the Kosovo declaration of independence.
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 10月, 2016
      データセットを選択
      Eurostat Dataset Id:cpc_ecnacoi  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Eurostat Dataset Id:cpc_ecbop  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Eurostat Dataset Id:cpc_insbs  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Eurostat Dataset Id:cpc_enclimwa  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      The focus of this domain is on enlargement countries, in other words the following country groups: candidate countries — Albania (AL), the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)potential candidates — Bosnia and Herzegovina (BA), as well as Kosovo (XK) (*) An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. (*) This designation is without prejudice to positions on status and is in line with UNSCR 1244 and the ICJ Opinion on the Kosovo declaration of independence.
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 10月, 2016
      データセットを選択
      Eurostat Dataset Id:cpc_energy  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Eurostat Dataset Id:cpc_ecexint  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 10月, 2016
      データセットを選択
      Eurostat Dataset Id:cpc_agfish  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 10月, 2016
      データセットを選択
      Eurostat Dataset Id:cpc_agfor  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 10月, 2016
      データセットを選択
      Eurostat Dataset Id:cpc_ecnagdp  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Eurostat Dataset Id:cpc_ecgov  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Eurostat Dataset Id:cpc_inisoc  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 3月 2014
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 05 5月, 2014
      データセットを選択
      Eurostat Dataset Id:cpc_etmain  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      The focus of this domain is on enlargement countries, in other words the following country groups: candidate countries — Albania (AL), the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)potential candidates — Bosnia and Herzegovina (BA), as well as Kosovo (XK) (*) An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. (*) This designation is without prejudice to positions on status and is in line with UNSCR 1244 and the ICJ Opinion on the Kosovo declaration of independence.
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Eurostat Dataset Id:cpc_psilc  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 10月, 2016
      データセットを選択
      Eurostat Dataset Id:cpc_ecmain  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      The focus of this domain is on enlargement countries, in other words the following country groups: candidate countries — Albania (AL), the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)potential candidates — Bosnia and Herzegovina (BA), as well as Kosovo (XK) (*) An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. (*) This designation is without prejudice to positions on status and is in line with UNSCR 1244 and the ICJ Opinion on the Kosovo declaration of independence.
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 10月, 2016
      データセットを選択
      Eurostat Dataset Id:cpc_psdemo  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      The focus of this domain is on enlargement countries, in other words the following country groups: candidate countries — Albania (AL), the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)potential candidates — Bosnia and Herzegovina (BA), as well as Kosovo (XK) (*) An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. (*) This designation is without prejudice to positions on status and is in line with UNSCR 1244 and the ICJ Opinion on the Kosovo declaration of independence.
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      The focus of this domain is on enlargement countries, in other words the following country groups: candidate countries — Albania (AL), the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Serbia (RS) and Turkey (TR)potential candidates — Bosnia and Herzegovina (BA), and Kosovo (XK) (*) An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. (*) This designation is without prejudice to positions on status and is in line with UNSCR 1244/1999 and the ICJ Opinion on the Kosovo declaration of independence.
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      The focus of this domain is on enlargement countries, in other words the following country groups: candidate countries — Albania (AL), the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)potential candidates — Bosnia and Herzegovina (BA), as well as Kosovo (XK) (*) An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. (*) This designation is without prejudice to positions on status and is in line with UNSCR 1244 and the ICJ Opinion on the Kosovo declaration of independence.
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 10月, 2016
      データセットを選択
      Eurostat Dataset Id:cpc_siecr  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 10月, 2016
      データセットを選択
      Eurostat Dataset Id:cpc_siemp  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 10月, 2016
      データセットを選択
      Eurostat Dataset Id:cpc_sienv  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 10月, 2016
      データセットを選択
      Eurostat Dataset Id:cpc_sigeb  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 10月, 2016
      データセットを選択
      Eurostat Dataset Id:cpc_siinr  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 10月, 2016
      データセットを選択
      Eurostat Dataset Id:cpc_sisoc  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Eurostat Dataset Id:cpc_ettot  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Eurostat Dataset Id:cpc_intour  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 3月 2014
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 05 5月, 2014
      データセットを選択
      Eurostat Dataset Id:cpc_etsitc  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 10月, 2016
      データセットを選択
      The focus of this domain is on enlargement countries, in other words the following country groups: candidate countries — Albania (AL), the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)potential candidates — Bosnia and Herzegovina (BA), as well as Kosovo (XK) (*) An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. (*) This designation is without prejudice to positions on status and is in line with UNSCR 1244 and the ICJ Opinion on the Kosovo declaration of independence.
    • 10月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 10月, 2016
      データセットを選択
      The focus of this domain is on enlargement countries, in other words the following country groups: candidate countries — Albania (AL), the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)potential candidates — Bosnia and Herzegovina (BA), as well as Kosovo (XK) (*) An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. (*) This designation is without prejudice to positions on status and is in line with UNSCR 1244 and the ICJ Opinion on the Kosovo declaration of independence.
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      The focus of this domain is on enlargement countries, in other words the following country groups: candidate countries — Albania (AL), the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)potential candidates — Bosnia and Herzegovina (BA), as well as Kosovo (XK) (*) An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. (*) This designation is without prejudice to positions on status and is in line with UNSCR 1244 and the ICJ Opinion on the Kosovo declaration of independence.
    • 4月 2019
      ソース: Global Oil & Gas Network
      アップロード者: Knoema
      以下でアクセス: 19 9月, 2019
      データセットを選択
      data as of April 14, 2019
    • 9月 2019
      ソース: National Bureau of Statistics, Nigeria
      アップロード者: Knoema
      以下でアクセス: 17 9月, 2019
      データセットを選択
      Capital Importation into Nigeria
    • 5月 2018
      ソース: China Association of Automobile Manufacturers
      アップロード者: Shakthi Krishnan
      以下でアクセス: 13 9月, 2018
      データセットを選択
      World: Car Sales by Country 2017
    • 4月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 30 4月, 2019
      データセットを選択
      To view the original national data please open the questionnaires. Source: Joint Forest Europe / UNECE / FAO Questionnaire on Pan-European Indicators for Sustainable Forest Management. Country: Russian Federation The source of the data of Russian Federation is the National Report for the Joint Forest Europe / UNECE / FAO reporting on quantitative pan-European indicators 2011.
    • 9月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 26 9月, 2019
      データセットを選択
      Source: UNECE Transport Division Database. Definitions:National rail transport : Rail transport between two places (a place of loading/embarkment and a place of unloading/disembarkment) located in the same country irrespective of the country in which the railway vehicles were registered. It may involve transit through a second country. International rail transport : Rail transport between two places (a place of loading/embarkment and a place of unloading/disembarkment) in two different countries. It may involve transit through one or more additional countries. Goods carried by rail : Any goods moved by rail vehicles. This includes all packaging and equipment, such as containers, swap-bodies or pallets as well as road goods vehicles carried by rail. Tonne-kilometre by rail : Unit of measure of goods transport which represents the transport of one tonne of goods by rail over a distance of one kilometre. Goods loaded : Goods placed on a rail vehicle and dispatched by rail. Unlike in road and inland waterway transport, transshipments from one rail vehicle to another and change of tractive vehicle are not regarded as loading after unloading. Goods unloaded : Goods taken off a rail vehicle after transport by rail. Unlike in road and inland waterway transport, transshipments from one rail vehicle to another and change of tractive vehicle are not regarded as unloading before reloading. International - loaded Goods having left the country by rail (other than goods in transit by rail throughout) : Goods loaded on a reporting railway network and transported by rail to be unloaded in a foreign country. Wagons loaded on a railway network and carried by ferry to a foreign network are included. International - unloaded Goods having entered the country by rail (other than goods in transit by rail throughout) : Goods loaded on a foreign railway network and transported by rail on the reporting railway network for unloading in the country of this reporting network. Wagons loaded on a foreign railway network and carried by ferry to the reporting network are included. Goods in transit by rail throughout : Goods loaded on a foreign railway network for a destination on a foreign railway network which are transported on the reporting railway network. Wagons entering and/or leaving the reporting network by ferry are included. Please note that country footnotes are not always in alphabetical order. .. - data not available Country: Croatia Until 2012 international transport includes goods partly transported by railway and partly by another mode of transport. Since 2013 this kind of goods have been included in national transport. Country: Estonia ''Goods in transit by rail'' includes transition between rail and maritime transport in ports. Country: Slovenia Prior to 2004 data are based on transport of goods as to origin and destination. From 2004 on data are based on journeys, which means that the transport of goods is observed as to the place of loading and the place of unloading to/from a rail vehicle Country: Spain Refers to Renfe and ADIF only Country: Sweden ''Locomotives'' includes railcars. Country: United States Includes only Class I freight railroads.
    • 9月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 26 9月, 2019
      データセットを選択
      Source: UNECE Transport Division Database. Definitions: Oil pipeline transport : Any movement of crude or refined liquid petroleum products in a given oil pipeline network. National oil pipeline transport : Oil pipeline transport between two places (a pumping-in place and a pumping-out place) located in the same country or in that part of the seabed allocated to it. It may involve transit through a second country. International oil pipeline transport : Oil pipeline transport between two places (a pumping-in place and a pumping-out place) located in two different countries or on those parts of the seabed allocated to them. It may involve transit through one or more additional countries. Goods transported by oil pipeline : Any crude or refined liquid petroleum products moved by oil pipelines. Tonne-kilometre by oil pipeline : Unit of measure of transport which represents transport of one tonne of goods by oil pipeline over one kilometre. International - loaded Goods having left the country by oil pipeline ( other than goods in transit by oil pipeline throughout ) : Goods which, having been pumped into an oil pipeline in the country or that part of the seabed allocated to it, left the country by oil pipeline and were pumped out in another country. International - unloaded Goods having entered the country by oil pipeline (other than goods in transit by oil pipeline throughout) : Goods which, having been pumped into an oil pipeline in another country or that part of the seabed allocated to it, entered the country by oil pipeline and were pumped out there. Goods in transit by oil pipeline throughout : Goods which entered the country by oil pipeline and left the country by oil pipeline at a point different from the point of entry, after having been transported across the country solely by oil pipeline. Goods which entered and/or left the country in question by vessels after pumping into/pumping out of an oil pipeline at the frontier are included. Please note that country footnotes are not always in alphabetical order. .. - data not available Country: Serbia Territorial change (2000 onward): Data do not cover Kosovo and Metohija. Country: Canada Data reported in cubic meters. Country: Turkey Data includes only crude petroleum transport of Petroleum Pipeline Corporation and Turkish Petroleum Corporation (TPAO)
    • 1月 2013
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 23 1月, 2016
      データセットを選択
      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).
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 16 10月, 2019
      データセットを選択
      Animal production statistics cover three main sub-domains based on three pieces of relevant legislation and related gentlemen’s agreements. Livestock and meat statistics are collected under Regulation (EC) No 1165/2008. They cover meat production, as activity of slaughterhouses (monthly) and as other slaughtering (annual), meat production (gross indigenous production) forecast (semi-annual or quarterly), livestock statistics, including regional statistics. A quality report is also collected every third year.Milk and milk product statistics are collected under Decision 97/80/EC implementing Directive 96/16/EC. They cover farm production and utilisation of milk (annual), collection (monthly for cows’ milk) and production activity by dairies (annual) and statistics on the structure of dairies (every third year). An annual methodological report is also collected.Statistics on eggs for hatching and farmyard poultry chicks are collected under Regulation (EC) No 617/2008, implementing Regulation (EC) No 1234/2007 (Single CMO Regulation). They cover statistics on the structure (annual) and the activity (monthly) of hatcheries as well as reports on the external trade of chicks. European Economic Area countries (EEA, Iceland, Liechtenstein and Norway) are requested to provide milk statistics, with the exception of those related to home consumption, as stated in Annex XXI of the EEA Agreement. As Iceland is now a candidate country and Liechtenstein is exempted in the Agreement, only Norway is concerned. The Agreement between the European Community and the Swiss Confederation on cooperation in the field of statistics states that Switzerland must provide Eurostat with national milk statistics. It has been amended in 2013 for covering also some livestock and meat statistics. The same statistics are requested from the candidate countries as acquis communautaire. Further data about the same topics refer to repealed legal acts or agreements. The tables on animal product supply balance sheets (apro_mk_bal, apro_mt_bal and apro_ec_bal), statistics on the structure of rearing (apro_mt_str) and the number of laying hens (apro_ec_lshen) are therefore no longer updated. The same applies to some variables (external trade of animals and meat), periods (surveys in April or August) or items (number of horses) included in other tables. The statistical tables disseminated by Eurostat are organised into three groups of tables on Agricultural products (apro), i.e. Milk and milk products (apro_mk), Livestock and meat (apro_mt) and Poultry farming (apro_ec). This last label covers statistics on hatcheries and on trade in chicks. The regional animal production statistics collected on livestock (agr_r_animal) and on cows’ milk production on farms (agr_r_milk_pr) are disseminated separately. Due to the change in the legal basis or in the methodology, the time series may be broken. This is indicated by a flag in the tables. The detailed content of each table and the reference to its legal definition is provided in the table below. Table 3.1: Data tables disseminated regarding animal production statistics
    • 11月 2018
      ソース: Institute for Health Metrics and Evaluation
      アップロード者: Knoema
      以下でアクセス: 05 12月, 2018
      データセットを選択
      The Global Burden of Disease Study 2017 (GBD 2017), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories, and at the subnational level for a subset of countries.
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 13 4月, 2019
      データセットを選択
      Data on causes of death (COD) provide information on mortality patterns and form a major element of public health information. COD data refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". Causes of death are classified by the 86 causes of the "European shortlist" of causes of death. This shortlist is based on the International Statistical Classification of Diseases and Related Health Problems (ICD). COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. Countries code the information provided in the medical certificate of cause of death into ICD codes according to the rules specified in the ICD. Data are broken down by sex, 5-year age groups, cause of death and by residency and country of occurrence. For stillbirths and neonatal deaths additional breakdows might include age of mother. Data are available for EU-28, Iceland, Norway, Liechtenstein, Switzerland, Serbia and Turkey. 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.
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 09 11月, 2019
      データセットを選択
      Data on causes of death (COD) provide information on mortality patterns and form a major element of public health information. COD data refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". Causes of death are classified by the 86 causes of the "European shortlist" of causes of death. This shortlist is based on the International Statistical Classification of Diseases and Related Health Problems (ICD). COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. Countries code the information provided in the medical certificate of cause of death into ICD codes according to the rules specified in the ICD. Data are broken down by sex, 5-year age groups, cause of death and by residency and country of occurrence. For stillbirths and neonatal deaths additional breakdows might include age of mother. Data are available for EU-28, the former Yugoslav Republic of Macedonia, Albania, Iceland, Norway, Liechtenstein and Switzerland. Regional data (NUTS level 2) are available for most of the countries. Annual national data are provided in absolute number, crude death rates and standardised death rates. At regional level (NUTS level 2) the same is provided in form of 3 years averages. Annual crude death rates are also available at NUTS level 2.
    • 7月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 08 7月, 2019
      データセットを選択
      Data on causes of death (COD) provide information on mortality patterns and form a major element of public health information. COD data refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". Causes of death are classified by the 86 causes of the "European shortlist" of causes of death. This shortlist is based on the International Statistical Classification of Diseases and Related Health Problems (ICD). COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. Countries code the information provided in the medical certificate of cause of death into ICD codes according to the rules specified in the ICD. Data are broken down by sex, 5-year age groups, cause of death and by residency and country of occurrence. For stillbirths and neonatal deaths additional breakdows might include age of mother. Data are available for EU-28, the former Yugoslav Republic of Macedonia, Albania, Iceland, Norway, Liechtenstein and Switzerland. Regional data (NUTS level 2) are available for most of the countries. Annual national data are provided in absolute number, crude death rates and standardised death rates. At regional level (NUTS level 2) the same is provided in form of 3 years averages. Annual crude death rates are also available at NUTS level 2.
    • 7月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 04 7月, 2019
      データセットを選択
      Data on causes of death (COD) provide information on mortality patterns and form a major element of public health information. COD data refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". Causes of death are classified by the 86 causes of the "European shortlist" of causes of death. This shortlist is based on the International Statistical Classification of Diseases and Related Health Problems (ICD). COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. Countries code the information provided in the medical certificate of cause of death into ICD codes according to the rules specified in the ICD. Data are broken down by sex, 5-year age groups, cause of death and by residency and country of occurrence. For stillbirths and neonatal deaths additional breakdows might include age of mother. Data are available for EU-28, the former Yugoslav Republic of Macedonia, Albania, Iceland, Norway, Liechtenstein and Switzerland. Regional data (NUTS level 2) are available for most of the countries. Annual national data are provided in absolute number, crude death rates and standardised death rates. At regional level (NUTS level 2) the same is provided in form of 3 years averages. Annual crude death rates are also available at NUTS level 2.
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 24 9月, 2019
      データセットを選択
      Data on causes of death (COD) provide information on mortality patterns and form a major element of public health information. COD data refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". Causes of death are classified by the 86 causes of the "European shortlist" of causes of death. This shortlist is based on the International Statistical Classification of Diseases and Related Health Problems (ICD). COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. Countries code the information provided in the medical certificate of cause of death into ICD codes according to the rules specified in the ICD. Data are broken down by sex, 5-year age groups, cause of death and by residency and country of occurrence. For stillbirths and neonatal deaths additional breakdows might include age of mother. Data are available for EU-28, the former Yugoslav Republic of Macedonia, Albania, Iceland, Norway, Liechtenstein and Switzerland. Regional data (NUTS level 2) are available for most of the countries. Annual national data are provided in absolute number, crude death rates and standardised death rates. At regional level (NUTS level 2) the same is provided in form of 3 years averages. Annual crude death rates are also available at NUTS level 2.
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 01 10月, 2019
      データセットを選択
      Data on causes of death (COD) provide information on mortality patterns and form a major element of public health information. COD data refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". Causes of death are classified by the 86 causes of the "European shortlist" of causes of death. This shortlist is based on the International Statistical Classification of Diseases and Related Health Problems (ICD). COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. Countries code the information provided in the medical certificate of cause of death into ICD codes according to the rules specified in the ICD. Data are broken down by sex, 5-year age groups, cause of death and by residency and country of occurrence. For stillbirths and neonatal deaths additional breakdows might include age of mother. Data are available for EU-28, Iceland, Norway, Liechtenstein, Switzerland, Serbia and Turkey. 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.
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 05 6月, 2019
      データセットを選択
      Data on causes of death (COD) provide information on mortality patterns and form a major element of public health information. COD data refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". Causes of death are classified by the 86 causes of the "European shortlist" of causes of death. This shortlist is based on the International Statistical Classification of Diseases and Related Health Problems (ICD). COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. Countries code the information provided in the medical certificate of cause of death into ICD codes according to the rules specified in the ICD. Data are broken down by sex, 5-year age groups, cause of death and by residency and country of occurrence. For stillbirths and neonatal deaths additional breakdows might include age of mother. Data are available for EU-28, Iceland, Norway, Liechtenstein, Switzerland, Serbia and Turkey. 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.
    • 1月 2014
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 16 5月, 2014
      データセットを選択
      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.
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 04 6月, 2019
      データセットを選択
      Data on causes of death (COD) provide information on mortality patterns and form a major element of public health information. COD data refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". Causes of death are classified by the 86 causes of the "European shortlist" of causes of death. This shortlist is based on the International Statistical Classification of Diseases and Related Health Problems (ICD). COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. Countries code the information provided in the medical certificate of cause of death into ICD codes according to the rules specified in the ICD. Data are broken down by sex, 5-year age groups, cause of death and by residency and country of occurrence. For stillbirths and neonatal deaths additional breakdows might include age of mother. Data are available for EU-28, Iceland, Norway, Liechtenstein, Switzerland, Serbia and Turkey. 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.
    • 1月 2014
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 16 5月, 2014
      データセットを選択
      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.
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 04 6月, 2019
      データセットを選択
      Data on causes of death (COD) provide information on mortality patterns and form a major element of public health information. COD data refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". Causes of death are classified by the 86 causes of the "European shortlist" of causes of death. This shortlist is based on the International Statistical Classification of Diseases and Related Health Problems (ICD). COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. Countries code the information provided in the medical certificate of cause of death into ICD codes according to the rules specified in the ICD. Data are broken down by sex, 5-year age groups, cause of death and by residency and country of occurrence. For stillbirths and neonatal deaths additional breakdows might include age of mother. Data are available for EU-28, Iceland, Norway, Liechtenstein, Switzerland, Serbia and Turkey. 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.
    • 1月 2014
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 16 5月, 2014
      データセットを選択
      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.
    • 6月 2013
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 21 8月, 2013
      データセットを選択
      Notes: Eurostat Hierarchy: General and regional statistics > Population and social conditions > Health (health) > Public health (hlth) > Causes of death (hlth_cdeath).
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 29 9月, 2019
      データセットを選択
      Data on causes of death (COD) provide information on mortality patterns and form a major element of public health information. COD data refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". Causes of death are classified by the 86 causes of the "European shortlist" of causes of death. This shortlist is based on the International Statistical Classification of Diseases and Related Health Problems (ICD). COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. Countries code the information provided in the medical certificate of cause of death into ICD codes according to the rules specified in the ICD. Data are broken down by sex, 5-year age groups, cause of death and by residency and country of occurrence. For stillbirths and neonatal deaths additional breakdows might include age of mother. Data are available for EU-28, the former Yugoslav Republic of Macedonia, Albania, Iceland, Norway, Liechtenstein and Switzerland. Regional data (NUTS level 2) are available for most of the countries. Annual national data are provided in absolute number, crude death rates and standardised death rates. At regional level (NUTS level 2) the same is provided in form of 3 years averages. Annual crude death rates are also available at NUTS level 2.
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 19 4月, 2019
      データセットを選択
      Data on causes of death (COD) provide information on mortality patterns and form a major element of public health information. COD data refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". Causes of death are classified by the 86 causes of the "European shortlist" of causes of death. This shortlist is based on the International Statistical Classification of Diseases and Related Health Problems (ICD). COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. Countries code the information provided in the medical certificate of cause of death into ICD codes according to the rules specified in the ICD. Data are broken down by sex, 5-year age groups, cause of death and by residency and country of occurrence. For stillbirths and neonatal deaths additional breakdows might include age of mother. Data are available for EU-28, Iceland, Norway, Liechtenstein, Switzerland, Serbia and Turkey. 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.
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 12 4月, 2019
      データセットを選択
      Data on causes of death (COD) provide information on mortality patterns and form a major element of public health information. COD data refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". Causes of death are classified by the 86 causes of the "European shortlist" of causes of death. This shortlist is based on the International Statistical Classification of Diseases and Related Health Problems (ICD). COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. Countries code the information provided in the medical certificate of cause of death into ICD codes according to the rules specified in the ICD. Data are broken down by sex, 5-year age groups, cause of death and by residency and country of occurrence. For stillbirths and neonatal deaths additional breakdows might include age of mother. Data are available for EU-28, Iceland, Norway, Liechtenstein, Switzerland, Serbia and Turkey. 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.
    • 4月 2014
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 16 5月, 2014
      データセットを選択
      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.
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 04 6月, 2019
      データセットを選択
      Data on causes of death (COD) provide information on mortality patterns and form a major element of public health information. COD data refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". Causes of death are classified by the 86 causes of the "European shortlist" of causes of death. This shortlist is based on the International Statistical Classification of Diseases and Related Health Problems (ICD). COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. Countries code the information provided in the medical certificate of cause of death into ICD codes according to the rules specified in the ICD. Data are broken down by sex, 5-year age groups, cause of death and by residency and country of occurrence. For stillbirths and neonatal deaths additional breakdows might include age of mother. Data are available for EU-28, Iceland, Norway, Liechtenstein, Switzerland, Serbia and Turkey. 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.
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 18 4月, 2019
      データセットを選択
      Data on causes of death (COD) provide information on mortality patterns and form a major element of public health information. COD data refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". Causes of death are classified by the 86 causes of the "European shortlist" of causes of death. This shortlist is based on the International Statistical Classification of Diseases and Related Health Problems (ICD). COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. Countries code the information provided in the medical certificate of cause of death into ICD codes according to the rules specified in the ICD. Data are broken down by sex, 5-year age groups, cause of death and by residency and country of occurrence. For stillbirths and neonatal deaths additional breakdows might include age of mother. Data are available for EU-28, Iceland, Norway, Liechtenstein, Switzerland, Serbia and Turkey. 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.
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Death rate of a population adjusted to a standard age distribution. As most causes of death vary significantly with people's age and sex, the use of standardised death rates improves comparability over time and between countries, as they aim at measuring death rates independently of different age structures of populations. The standardised death rates used here are calculated on the basis of a standard European population (defined by the World Health Organization). Detailed data for 65 causes of death are available in the database (under the heading 'Data').
    • 4月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 09 4月, 2019
      データセットを選択
      Source: UNECE Statistical Database, compiled from national official sources. Definition:The Central Bank is the institution which is charged with regulating the amount of the money supply in a country, the availability and cost of credit, and the foreign exchange value of its currency. The boards of Central Banks are the decision making bodies. General note: Data on any fixed date of the year. .. - data not available Country: Bosnia and Herzegovina Data refer to: Governor and members of Governing Board. Country: Croatia Additional information (2013): Since 2013, Central Bank has 8 (instead of previously 14) board members. Country: Cyprus Reference period (2011): data refer to 2012. Country: Cyprus Government controlled area only. Country: Czechia Reference period (2008): Data refer to June - July. Country: Georgia Territorial change (2000 onward): Data do not cover Abkhazia AR and Tskhinvali Region. Country: Germany Additional information (1990): The structure of the Deutsche Bundesbank and the maximum number of members of the decision making body was reorganized in 1992. Country: Germany Additional information (2002): The structure of the Deutsche Bundesbank and the maximum number of members of the decision making body was reorganized in 2002. Country: Hungary Change in definition (1995 onward): Data refer to President and deputy presidents. Country: Iceland Change in definition (1980 onward): Data refer to Board of governors. Country: Kazakhstan 1990: data refer to 1993. Country: Latvia Additional information (1995 - 2013): The Bank of Latvia is administered by the Council of the Bank and the Board of the Bank. Country: Latvia Change in definition (1995 - 2013): Data refer to the Council of the Bank. Country: Portugal Banco de Portugal is included. Country: Slovakia 2015 data refer to 20 November 2015. Country: Sweden Change in nomenclature from ISCO-88 to ISCO-08 between 2013 and 2014. Country: Switzerland Reference period: as of 1st January
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 12 11月, 2019
      データセットを選択
      This table includes the areas, productions and humidity of wheat (common wheat and spelt and durum wheat), rye, maslin, barley, oats, mixed grain other than maslin, grain maize, sorghum, triticale, and other cereal crops such as buckwheat, millet, canary seed and rice. Cereal grains harvested just before maturity are also included in this table. Cereals harvested green or yellow as whole plant for fodder or renewable energy use are not included in this table. This indicator uses the concepts of "area under cultivation", "harvested production" and "humidity". 1) The "area under cultivation" corresponds: • before the harvest, to the sown area; • after the harvest, to the sown area excluding the non-harvested area (e.g. area ruined by natural disasters, area not harvested for economic reasons, etc.) 2) The "harvested production" corresponds to the production for which harvesting started in year N, even thought harvesting may finish in year N+1. So N is the reference year for data published by Eurostat. 3) In order to facilitate the comparisons of production between the Members States, the publication of "humidity" for each country is needed. Only the EU-aggregate for the production is published with a standard EU humidity.
    • 6月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 07 6月, 2019
      データセットを選択
      These metadata refer to the annual population data under Population / Demography domain in Eurostat's Dissemination data tree. Eurostat carries on annual demography data collections with the aim of collecting from the National Statistical Institutes detailed data on population, vital events, marriages and divorces. These data are validated, processed and disseminated. Further on, Eurostat uses the collected detailed data to compute and disseminate demographic indicators at country level, at regional level and at EU level, by applying harmonized methods of calculation. The demography data collections are done on voluntary basis and the completeness of information depends on the availability of data reported by the National Statistical Institutes. The first demography data collection of each year, named Rapid, is carried out in April-May (deadline 15 May). Within this data collection the first results on the main demographic developments in the previous year (T-1) and the population on 1st January of the current year (T) are collected from the National Statistical Institutes. A second annual data collection, Joint Demography data collection, is carried out in cooperation with United Nation Statistical Division (UNSD) in the summer of each year, having the deadline 15 September. Within this data collection Eurostat collects from the National Statistical Institutes detailed data on the demographic events (births, deaths, marriages and divorces) of the previous year (T-1) and the population on 1st January of the current year (T), broken down by sex, age and other characteristics. The Nowcast Demography data collection is carried out in October-November (deadline 15 November). The monthly time series on births, deaths, immigrants and emigrants available from the beginning of current year (T) are collected, with the purpose of producing by the end of the current year (T) a forecast on 1st January population of the following year (T+1). The Regional Demography data collection is carried out in November-December (deadline 15 December). It is based on the regional breakdown of the countries agreed at EU level using the latest version of the Nomenclature of Territorial Units for Statistics (NUTS) and of the Statistical regions for the EFTA and Candidate countries. Within this data collection Eurostat collects from the National Statistical Institutes data by NUTS level 1, 2 and 3 for the vital events taking place in the previous year (T-1) and the population figures on 1st January of the current year (T). Any updates sent by the National Statistical Institutes in-between data collections are validated, processed and disseminated in Eurostat's online database as soon as possible. The European aggregates and the demographic indicators are updated accordingly. Please note:The tables presenting population on 1 January figures by various breakdowns may display variations in the total population for some countries at a given moment in time. This may occur due to one of the following reasons: - The timing of the transmission to Eurostat of the population data for various breakdown may lead to different population on 1 January figures displayed in different population tables at a given moment in time. - The transmission to Eurostat of the post-census population revisions (following the 2011 population Censuses) is expected to be done by the national statistical offices gradually for the population breakdowns. The time series of populations between the previous census taking place in the country and 2011 will be revised by end 2013 by some of the countries, taking into account Eurostat’s recommendation. The following countries have transmitted to Eurostat post-2011 Census population revisions, broken down by age and sex, by autumn of 2013, which are reflected in the tables ‘Demographic balance and crude rates (demo_gind)’, ‘Population on 1 January by age and sex (demo_pjan)’, ‘Population on 1 January by five years age groups and sex (demo_pjangroup)’ and ‘Population on 1 January by broad age group and sex (demo_pjanbroad)’: BG 2007-2011; CZ 2001-2011; EE 2000-2011; IE 2007-2011; EL 2011; ES 2002-2011; HR 2001-2011; CY 2003-2011; LV 2001-2011; LT 2001-2011; MT 2006-2011; AT 2008-2011; PT 1992-2011; RO 2002-2011; SK 2002-2011; UK 2002-2011 (not including post-2011 Census data for Scotland); ME 2010-2011; RS 2011. As regards the the population data for the year 2012 and after, for most of the countries these take into account the results of the latest population census (held in 2011). IT 2012-2013 and DE 2012-2013 reported only the total post-2011 Census populations which are published in the table ‘Demographic balance and crude rates (demo_gind)’. The breakdown by age and sex will follow later on. - The succession of the annual demography data collections described above, which collect and update population breakdowns at different moment during the calendar year. - The calendar of the national statistical offices for producing and releasing population broken down by various topics, respectively the timings when data are transmitted to Eurostat. The most updated data on total population on 1st January and on the total number of live births and deaths may be found in the table 'Demographic balance and crude rates (demo_gind)' of the online 'Database by theme'. This table includes the latest updates (or revised data) on total population, births and deaths reported by the countries, while the detailed breakdowns by various characteristics included in the rest of the tables of the Demography domain (and also for Population by citizenship and by country of birth) may be transmitted to Eurostat at a subsequent date.
    • 10月 2014
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 22 11月, 2018
      データセットを選択
      General note on the UNECE MDG Database: The database aims to show the official national estimates of MDG-indicators used for monitoring progress towards the Millennium Development Goals. Data is shown alongside official international estimates of MDG-indicators (as published on the official United Nations site for the MDG Indicators: http://unstats.un.org/unsd/mdg). Besides the international MDG-indicators, other indicators and disaggregates that are relevant for the UNECE-region are included. At present, the tables include data from the latest official MDG-report of each country. Currently, data from official dedicated MDG-websites and previous official national MDG-reports are being added. Additionally, more detailed metadata is being added to the footnotes. Additional indicators might be added if they are used generally across the region. Please note that some indicators are also available in the Gender Statistics Database of UNECE. Figures might differ due to the use of different sources. Definition of the indicators: Explanations on the indicators are listed below. Deviations from the standard definitions provided here are specified in the country-specific footnotes. Indicator Under five mortality rate per 1,000 live births Definition: The under-five mortality rate (U5MR) is the probability of a child born in a specified year dying before reaching the age of five if subject to current age-specific mortality rates. Infant mortality rate (0-1 year) per 1,000 live births Definition: The infant mortality rate (IMR) is the probability of a child born in a specified year dying before reaching the age of one, if subject to current age-specific mortality rates. Children 1 year old immunized against measles, (%) Definition: The proportion of 1 year-old children immunized against measles is the percentage of children under one year of age who have received at least one dose of measles-containing vaccine. Breast-fed under 6 months (%) Definition: Number of children under the age of 6 months that are breast-fed as a percentage of all children under the age of 6 months. Perinatal mortality rate Definition: Number of stillbirths (or fetal deaths) and deaths in the first week of life (or early neonatal deaths) per 1,000 total births (live and still births). The perinatal period commences at 22 completed weeks (154 days) of gestation and ends seven. This indicator is not monitored in The official United Nations site for the MDG Indicators. Indicator: Under five mortality rate per 1,000 live births , Country: Albania National Series Reference: 1990 to 1993: MDG Report 2002; 1994 to 1999: MDG Report 2004; 2000: MDG Progress Report 2010; 2001: MDG Report 2004; 2002 to 2009: MDG Progress Report 2010; Definition: 1994 to 1999: Per 1,000 children under the age of five; 2001: Per 1,000 children under the age of five; Note: 2000: NSO: 18.1; Source in Reference: 1990 to 1993: IPH; 1994 to 2001: NSO; 2002 to 2008: Min. of Health; 2009: NSO; Primary Source in Reference: 2000: DHS 2000; 2002 to 2008: Administrative data; 2009: DHS 2008-2009; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Albania National Series Reference: 1990 to 1993: MDG Report 2002; 1994 to 1999: MDG Report 2004; 2000: MDG Progress Report 2010; 2001: MDG Report 2004; 2002 to 2009: MDG Progress Report 2010; Note: 2000: NSO: 16.0; Source in Reference: 1990 to 1993: IPH; 1994 to 2001: NSO; 2002 to 2008: Min. of Health; 2009: NSO; Primary Source in Reference: 2000: DHS 2000; 2002 to 2008: Administrative data; 2009: DHS 2008-2009; Indicator: Children 1 year old immunized against measles, (%) , Country: Albania National Series Reference: 1991 to 2000: MDG Report 2002; 2001: MDG Report 2004; 2002 to 2009: MDG Progress Report 2010; Source in Reference: 1991 to 2000: IPH; 2001: NSO; 2002 to 2009: Min. of Health; Primary Source in Reference: 2002 to 2009: Administrative data; Indicator: Under five mortality rate per 1,000 live births , Country: Armenia National Series Reference: 1990: MDG Progress Report 2005-2009; 1996: ArmeniaInfo at: http://www.armdevinfo.am/ (accessed: 15 June 2011); 1998 to 1999: MDG Progress Report 2005-2009; 2000 to 2009: ArmeniaInfo at: http://www.armdevinfo.am/ (accessed: 15 June 2011); 2010: ArmeniaInfo (http://www.armdevinfo.am/) 2012-05-12; 2011 to 2012: Armenia MDGs Indicators (http://www.armstat.am/) 06/02/2014; Definition: 2010: Per 1,000 children under the age of five; Note: 2001 to 2005: DHS 2005: 30 (2001-2005); 2010: DHS 2010: 16; Reference period: 1998: 1996-2000; Source in Reference: 1996: Min. of Justice; 1998: NSO; 2000 to 2010: Min. of Justice; 2011 to 2012: NSO; Primary Source in Reference: 1990: Administrative data; 1998: DHS 2000; 1999: Administrative data; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Armenia National Series Reference: 1988 to 1990: MDG Progress Report 2005-2009; 1996: ArmeniaInfo at: http://www.armdevinfo.am/ (accessed: 15 June 2011); 1998 to 1999: MDG Progress Report 2005-2009; 2000 to 2009: ArmeniaInfo at: http://www.armdevinfo.am/ (accessed: 15 June 2011); 2010: ArmeniaInfo (http://www.armdevinfo.am/) 2012-05-12; 2011 to 2012: Armenia MDGs Indicators (http://www.armstat.am/) 06/02/2014; Note: 2001 to 2005: DHS 2005: 26 (2001-2005); 2010: DHS 2010: 13; Reference period: 1988: 1986-1990; 1998: 1996-2000; Source in Reference: 1988: NSO; 1996: Min. of Justice; 1998: NSO; 2000 to 2010: Min. of Justice; 2011 to 2012: NSO; Primary Source in Reference: 1988: DHS 2000; 1990: Administrative data; 1998: DHS 2000; 1999: Administrative data; 2011 to 2012: Administrative data; Indicator: Children 1 year old immunized against measles, (%) , Country: Armenia National Series Reference: 1990: MDG Progress Report 2005-2009; 1996: ArmeniaInfo at: http://www.armdevinfo.am/ (accessed: 15 June 2011); 1999: MDG Progress Report 2005-2009; 2000 to 2003: ArmeniaInfo at: http://www.armdevinfo.am/ (accessed: 15 June 2011); 2004: MDG Progress Report 2005-2009; 2005 to 2006: ArmeniaInfo at: http://www.armdevinfo.am/ (accessed: 15 June 2011); 2007 to 2008: MDG Progress Report 2005-2009; 2009: ArmeniaInfo at: http://www.armdevinfo.am/ (accessed: 15 June 2011); 2010: ArmeniaInfo (http://www.armdevinfo.am/) 2012-05-12; 2011 to 2012: Armenia MDGs Indicators (http://www.armstat.am/) 06/02/2014; Definition: 1990 to 2009: Under two-years old; Source in Reference: 1990 to 2009: Min. of Health; 2010: NSO / Min. of Health; 2011 to 2012: NSO; Primary Source in Reference: 1990: Administrative data; 1999: Administrative data; 2004: Administrative data; 2007 to 2008: Administrative data; 2011 to 2012: Administrative data; Indicator: Under five mortality rate per 1,000 live births , Country: Azerbaijan National Series Reference: 1990 to 2012: NSO MDG data; Note: 1999: RHS 1996-2000: 88.4; Source in Reference: 1990 to 2012: NSO; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Azerbaijan National Series Reference: 1990 to 2012: NSO MDG data; Note: 1999: RHS 1996-2000: 74.4; Source in Reference: 1990 to 2012: NSO; Indicator: Children 1 year old immunized against measles, (%) , Country: Azerbaijan National Series Reference: 1990 to 2012: NSO MDG data; Note: 2003 to 2012: Combined vaccination against measles, rubella, epidemic parotiditis; 2000: MICS 2000: 9.4 (under 4 months); 2006: DHS 2006: 74.4; Source in Reference: 1990 to 2002: NSO; 2003 to 2012: Min. of Health; Indicator: Under five mortality rate per 1,000 live births , Country: Belarus National Series Reference: 1990 to 1999: MDG Progress 2005; 2000 to 2009: MDG progress 2010; 2010 to 2011: MDG Report 2012; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Belarus National Series Reference: 1990 to 1999: MDG Progress 2005; 2000 to 2009: MDG progress 2010; 2010 to 2011: MDG Report 2012; Indicator: Children 1 year old immunized against measles, (%) , Country: Belarus National Series Reference: 1990 to 1999: MDG Progress 2005; 2000 to 2009: MDG progress 2010; 2010 to 2011: MDG Report 2012; Indicator: Under five mortality rate per 1,000 live births , Country: Bosnia and Herzegovina National Series Reference: 2000 to 2011: MDG Report 2013; Note: 2000: UN Inter-agency Group for Child Mortality Estimation; 2008 to 2011: UN Inter-agency Group for Child Mortality Estimation; Source in Reference: 2000: UN Inter-agency Group for Child Mortality Estimation; 2007: NSO (BHAS); 2008 to 2011: UN Inter-agency Group for Child Mortality Estimation; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Bosnia and Herzegovina National Series Reference: 2000 to 2012: MDG Report 2013; Source in Reference: 2000 to 2012: NSO (BHAS); Indicator: Children 1 year old immunized against measles, (%) , Country: Bosnia and Herzegovina National Series Reference: 2000 to 2009: MDG progress report 2010; 2011: MDG Report 2013; Note: 2007 to 2009: Only for the territory of the Federation of Bosnia and Herzegovina; Reference period: 2011: 2011/12; Source in Reference: 2000 to 2001: FBiH PHI, RS HP Fund, FBiH SI; 2007 to 2009: FBiH Public Health Institute; Primary Source in Reference: 2007 to 2009: Administrative data; 2011: MICS 2011-12; Indicator: Breast-fed under 6 months (%) , Country: Bosnia and Herzegovina National Series Reference: 2000 to 2006: MDG progress report 2010; 2011: MDG Report 2013; Reference period: 2011: 2011/12; Source in Reference: 2000: FBiH PHI, RS HP Fund, FBiH SI; Primary Source in Reference: 2006: MICS 2006; 2011: MICS 2011-12; Indicator: Under five mortality rate per 1,000 live births , Country: Bulgaria National Series Reference: 2001 to 2007: MDG report 2010; Source in Reference: 2001 to 2007: National Health Information Center / NSO; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Bulgaria National Series Reference: 2001 to 2007: MDG report 2010; Source in Reference: 2001 to 2007: National Health Information Center / NSO; Indicator: Perinatal mortality rate , Country: Bulgaria National Series Reference: 2001 to 2007: MDG report 2010; Definition: 2001 to 2007: After 28 weeks of gestation; Source in Reference: 2001 to 2007: National Health Information Center / NSO; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Croatia National Series Reference: 1990 to 2002: MDG Report 2004; 2004: MDG Progress Report 2005; Note: 1998 to 2002: To mothers who had lived in Croatia for longer than the period of one year; Indicator: Perinatal mortality rate , Country: Croatia National Series Reference: 2002 to 2005: MDG Progress Report 2005; Definition: 2002 to 2005: birth weight >500g; Indicator: Under five mortality rate per 1,000 live births , Country: Czechia National Series Reference: 2002: MDG report 2004; Source in Reference: 2002: Health Yearbook of the Czech Republic 2001; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Czechia National Series Reference: 1990 to 2002: MDG report 2004; Source in Reference: 1990 to 2002: Health Yearbook of the Czech Republic 2001; Indicator: Perinatal mortality rate , Country: Czechia National Series Reference: 1990 to 2002: MDG report 2004; Definition: 1990 to 2002: After 28 weeks of gestation; Source in Reference: 2000 to 2002: Health Yearbook of the Czech Republic 2001; Indicator: Under five mortality rate per 1,000 live births , Country: Georgia National Series Reference: 2000 to 2004: MDG Progress Report 2004-2005; Definition: 2000 to 2001: Number of deaths below age five per 1,000 live births in a calendar year.; Note: 2000 to 2004: Official statistics; Source in Reference: 2000 to 2004: National Center for Disease Control and Medical Statistics; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Georgia National Series Reference: 2000 to 2004: MDG Progress Report 2004-2005; Note: 2000 to 2004: Official statistics; Source in Reference: 2000 to 2004: National Center for Disease Control and Medical Statistics; Indicator: Children 1 year old immunized against measles, (%) , Country: Georgia National Series Reference: 2000 to 2004: MDG Progress Report 2004-2005; Definition: 2000 to 2004: Under two-years old; Source in Reference: 2000: National Center for Disease Control and Medical Statistics; Indicator: Under five mortality rate per 1,000 live births , Country: Hungary National Series Reference: 1990 to 2001: MDG report 2004; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Hungary National Series Reference: 1990 to 2002: MDG report 2004; Source in Reference: 1990 to 2002: NSO; Primary Source in Reference: 1990 to 2002: Hungarian Health Database 1985-2001; Indicator: Under five mortality rate per 1,000 live births , Country: Kazakhstan National Series Reference: 1987 to 1999: MDG in Kazakhstan 2005; 2000 to 2005: Poverty assessment in Kazakhstan: current status and prospects for development; 2006 to 2008: MDG Report 2010; 2009 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Definition: 1990 to 1999: Excluding pregnancies that terminate at less than 28 weeks of gestation, and newborns weighing less than 1000 grams at the time of birth, shorter than 35 cm, or alive for less than seven days.; Note: 1990 to 1994: DHS 1995: 56.7; 1995 to 1999: DHS 1999: 71.4; 2006: MICS 2006: 36.3; Reference period: 1990 to 1994: 1989-1994; 1995 to 1999: 1995-1999; Source in Reference: 1990 to 1999: TransMonee; 2000 to 2005: NSO; 2006 to 2008: Min. of Healthcare; 2009 to 2012: NSO; Primary Source in Reference: 2006 to 2008: Administrative data; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Kazakhstan National Series Reference: 1987 to 1999: MDG in Kazakhstan 2005; 2000 to 2001: Poverty assessment in Kazakhstan: current status and prospects for development; 2002: MDG in Kazakhstan 2005; 2003 to 2005: Poverty assessment in Kazakhstan: current status and prospects for development; 2006 to 2007: MDG Report 2010; 2008 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Definition: 1990 to 1999: Excluding pregnancies that terminate at less than 28 weeks of gestation, and newborns weighing less than 1000 grams at the time of birth, shorter than 35 cm, or alive for less than seven days.; 2002: Excluding pregnancies that terminate at less than 28 weeks of gestation, and newborns weighing less than 1000 grams at the time of birth, shorter than 35 cm, or alive for less than seven days.; Note: 1990 to 1994: DHS 1995: 49.7; 1995 to 1999: DHS 1999: 61.9; Reference period: 1990 to 1993: 1989-1994; 1994 to 1999: 1995-1999; Source in Reference: 1990 to 1999: Min. of Healthcare; 2000 to 2001: NSO; 2002: Min. of Healthcare; 2003 to 2005: NSO; 2006 to 2007: Min. of Healthcare; 2008 to 2012: NSO; Primary Source in Reference: 2006 to 2007: Administrative data; Indicator: Children 1 year old immunized against measles, (%) , Country: Kazakhstan National Series Reference: 1995: MDG in Kazakhstan 2002; 2000 to 2012: Poverty assessment in Kazakhstan: current status and prospects for development; Source in Reference: 1995: Min. of Healthcare; 2000: NSO; 2001 to 2012: Min. of Health; Indicator: Breast-fed under 6 months (%) , Country: Kazakhstan National Series Reference: 1995 to 2006: MDG Report 2010; Definition: 1995 to 2006: Under 3 months; Source in Reference: 2002: Tazhibayev Sh., Sharmanov T., Ergalieva A., Dolmatova O., Mukasheva O., Seidakhmetova A., Kushenova R. ‘Promotion of Lactation Amenorrhea Method Intervention Trial, Kazakhstan’. Population Council, Frontiers in Reproductive Health 2004; Primary Source in Reference: 1999: DHS 1999; Indicator: Perinatal mortality rate , Country: Kazakhstan National Series Reference: 2008: MDG Report 2010; Definition: 2008: After 22 weeks of gestation; Indicator: Under five mortality rate per 1,000 live births , Country: Kyrgyzstan National Series Reference: 1990 to 1999: NSO MDG database as on 2014-07-08; 2000 to 2009: MDG Progress Report 2010; 2010 to 2012: NSO MDG database as on 2014-07-08; Definition: 1990 to 1999: Excluding pregnancies that terminates at less than 28 weeks of gestation; Source in Reference: 1990 to 2010: NSO; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Kyrgyzstan National Series Reference: 1990 to 1999: NSO MDG database as on 2014-07-08; 2000 to 2009: MDG Progress Report 2010; 2010 to 2012: NSO MDG database as on 2014-07-08; Definition: 1990 to 1999: Excluding pregnancies that terminates at less than 28 weeks of gestation; Source in Reference: 1990 to 1999: NSO / Min. of Health; 2000 to 2009: NSO; 2010: NSO / Min. of Health; Indicator: Children 1 year old immunized against measles, (%) , Country: Kyrgyzstan National Series Reference: 1990 to 1999: NSO MDG database as on 2014-07-08; 2000 to 2009: MDG Progress Report 2010; 2010 to 2012: NSO MDG database as on 2014-07-08; Source in Reference: 1990 to 1999: NSO / Min. of Health; 2000 to 2009: NSO; 2010: NSO / Min. of Health; Indicator: Under five mortality rate per 1,000 live births , Country: Latvia National Series Reference: 1990 to 2003: MDG Report 2005; Definition: 1990 to 2003: Per 1,000 children under the age of five; Source in Reference: 1990 to 2003: NSO / Min. of Health; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Latvia National Series Reference: 1996 to 2003: MDG Report 2005; Source in Reference: 1996 to 2003: NSO / Min. of Health; Indicator: Perinatal mortality rate , Country: Latvia National Series Reference: 1980 to 2003: MDG Report 2005; Definition: 1980 to 2003: After 28 weeks of gestation; Source in Reference: 1980 to 2003: NSO / Min. of Health; Indicator: Under five mortality rate per 1,000 live births , Country: Lithuania National Series Reference: 1990 to 2001: MDG Assessment 2002; Definition: 1990 to 2001: Including live births at least 500 grams weight and 22 weeks gestation; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Lithuania National Series Reference: 1990 to 2001: MDG Assessment 2002; Definition: 1990 to 1991: Excluding pregnancies that terminate at less than 28 weeks of gestation, and newborns weighing less than 1000 grams at the time of birth, shorter than 35 cm, or alive for less than seven days.; 1992 to 2001: Excluding live births weighting less than 500 grams and less than 22 weeks of gestation; Indicator: Children 1 year old immunized against measles, (%) , Country: Lithuania National Series Reference: 2000: MDG Assessment 2002; Indicator: Under five mortality rate per 1,000 live births , Country: Moldova, Republic of National Series Reference: 2000 to 2010: Statbank of the National Bureau of Statistics of the Republic of Moldova as on 08-08-2012; 2011 to 2012: Moldova Statbank (http://statbank.statistica.md) 11-11-2013; Definition: 2000 to 2007: Number of deaths below age five per 1,000 live births. Excluding live births weighting less than 1,000 grams and less than 30 weeks of gestation; 2008 to 2010: Number of deaths below age five per 1,000 live births. Excluding live births weighting less than 500 grams and less than 22 weeks of gestation; 2011 to 2012: Number of deaths below age five per 1,000 live births. Excluding live births weighting less than 1,000 grams and less than 30 weeks of gestation; Note: 2000 to 2012: Information is presented without the data from the left side of the river Nistru and municipality Bender.; Source in Reference: 2000 to 2012: Central Election Commission; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Moldova, Republic of National Series Reference: 2000 to 2010: Statbank of the National Bureau of Statistics of the Republic of Moldova as on 08-08-2012; 2011 to 2012: Moldova Statbank (http://statbank.statistica.md) 11-11-2013; Definition: 2000 to 2007: Excluding live births weighting less than 1,000 grams and less than 30 weeks of gestation; 2008 to 2010: Excluding live births weighting less than 500 grams and less than 22 weeks of gestation; 2011 to 2012: Excluding live births weighting less than 1,000 grams and less than 30 weeks of gestation; Note: 2000 to 2010: Deaths in a given calendar year divided by the size of their birth cohort.; 2000 to 2012: Information is presented without the data from the left side of the river Nistru and municipality Bender.; Source in Reference: 2000 to 2012: Min. of Health / NSO; Indicator: Children 1 year old immunized against measles, (%) , Country: Moldova, Republic of National Series Reference: 2000 to 2005: Statbank of the National Bureau of Statistics of the Republic of Moldova as on 08-08-2012; 2006 to 2012: Third MDG Report 2013; Definition: 2000 to 2012: Under two-years old; Note: 2000 to 2005: Information is presented without the data from the left side of the river Nistru and municipality Bender.; Source in Reference: 2000 to 2005: Min. of Health / NSO; 2006 to 2012: National Centre for Public Health; Indicator: Breast-fed under 6 months (%) , Country: Moldova, Republic of National Series Reference: 2008: MDG Report 2010; Source in Reference: 2008: National Perinatal Program 2008; Indicator: Perinatal mortality rate , Country: Moldova, Republic of National Series Reference: 1990 to 2009: MDG Report 2010; Definition: 1990 to 2009: After 28 weeks of gestation; Indicator: Under five mortality rate per 1,000 live births , Country: Montenegro National Series Reference: 1990 to 2000: MDG report 2005; 2004 to 2008: MDG Report 2010; 2009 to 2011: MDG Report 2013; Source in Reference: 1990 to 2011: NSO; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Montenegro National Series Reference: 1990 to 2000: MDG report 2005; 2004 to 2008: MDG Report 2010; 2009 to 2011: MDG Report 2013; Source in Reference: 1990 to 2011: NSO; Indicator: Children 1 year old immunized against measles, (%) , Country: Montenegro National Series Reference: 1990 to 2000: MDG report 2005; 2004 to 2008: MDG Report 2010; 2009 to 2011: MDG Report 2013; Source in Reference: 1990 to 2000: Report on immuzation against infectious diseases in Montenegro; 2004 to 2008: NSO; Indicator: Breast-fed under 6 months (%) , Country: Montenegro National Series Reference: 2009: MDG Report 2010; Source in Reference: 2009: NSO; Indicator: Under five mortality rate per 1,000 live births , Country: Poland National Series Reference: 1990 to 1999: MDG Report 2002; Source in Reference: 1990: NSO; 1991 to 1998: Demographic Yearbook 2000, NSO; 1999: NSO; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Poland National Series Reference: 1990 to 1999: MDG Report 2002; Source in Reference: 1990 to 1999: Demographic Yearbook 2000, NSO; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Romania National Series Reference: 1990 to 2000: MDG Report 2003; 2001 to 2009: MDG Report 2010; Source in Reference: 1990 to 2000: Min. of Health; 2001 to 2009: NSO; Indicator: Children 1 year old immunized against measles, (%) , Country: Romania National Series Reference: 2001: MDG Report 2003; Source in Reference: 2001: Min. of Health; Indicator: Under five mortality rate per 1,000 live births , Country: Russian Federation National Series Definition: 2003 to 2008: Excluding pregnancies that terminate at less than 28 weeks of gestation, and newborns weighing less than 1000 grams at the time of birth, shorter than 35 cm, or alive for less than seven days.; Source in Reference: 2003 to 2008: WHO; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Russian Federation National Series Definition: 2003 to 2009: Excluding pregnancies that terminate at less than 28 weeks of gestation, and newborns weighing less than 1000 grams at the time of birth, shorter than 35 cm, or alive for less than seven days.; Source in Reference: 2003 to 2009: WHO; Indicator: Children 1 year old immunized against measles, (%) , Country: Russian Federation National Series Source in Reference: 2008: WHO; Indicator: Breast-fed under 6 months (%) , Country: Russian Federation National Series Source in Reference: 2008: WHO; Indicator: Under five mortality rate per 1,000 live births , Country: Serbia National Series Reference: 1990 to 1999: MDG Report 2001-2004; 2000: MDG progress report 2009; 2001 to 2002: MDG Report 2001-2004; 2005: MDG report 2006; 2008: MDG progress report 2009; Source in Reference: 1990 to 2002: NSO; 2008: NSO; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Serbia National Series Reference: 1990 to 1999: MDG Report 2001-2004; 2000: MDG progress report 2009; 2001 to 2002: MDG Report 2001-2004; 2005: MDG report 2006; 2008: MDG progress report 2009; Source in Reference: 1990 to 2002: NSO; 2008: NSO; Indicator: Children 1 year old immunized against measles, (%) , Country: Serbia National Series Reference: 1990 to 1999: MDG Report 2001-2004; 2000: MDG progress report 2009; 2001 to 2002: MDG Report 2001-2004; 2008: MDG progress report 2009; Definition: 1990 to 2008: Under 18 months; Source in Reference: 1990 to 1999: NSO; 2000: National Institute of Public Health Database; 2001 to 2002: NSO; 2008: National Institute of Public Health Database; Indicator: Breast-fed under 6 months (%) , Country: Serbia National Series Reference: 2000 to 2005: MDG progress report 2009; Definition: 2000: Under 4 months; Source in Reference: 2000 to 2005: UNICEF; Primary Source in Reference: 2005: MICS 2005; Indicator: Perinatal mortality rate , Country: Serbia National Series Reference: 1990 to 1999: MDG Report 2001-2004; 2000: MDG progress report 2009; 2001 to 2002: MDG Report 2001-2004; 2005: MDG report 2006; 2008: MDG progress report 2009; Definition: 1990 to 2002: After 28 weeks of gestation; 2005: Gestation period not specified; 2008: After 28 weeks of gestation; Source in Reference: 2000: NSO; 2008: NSO; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Slovakia National Series Reference: 1990 to 2002: MDG report 2004; Source in Reference: 1990 to 2002: European Health for All Database, WHO; Indicator: Children 1 year old immunized against measles, (%) , Country: Slovakia National Series Reference: 2002: MDG report 2004; Definition: 2002: Under 18 months; Indicator: Under five mortality rate per 1,000 live births , Country: Slovenia National Series Reference: 1990 to 2001: MDG report 2004; Source in Reference: 1990 to 2001: European Health for All Database, WHO - Health Statistics yearbook 2003; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Slovenia National Series Reference: 1990 to 2001: MDG report 2004; Source in Reference: 1990 to 2001: European Health for All Database, WHO - Health Statistics yearbook 2003; Indicator: Under five mortality rate per 1,000 live births , Country: Tajikistan National Series Reference: 2000: MDG Progress Report 2010; 2003: MDG Needs Assessment 2005; 2005 to 2009: MDG Progress Report 2010; Source in Reference: 2003: UNICEF SOWC; 2007: NSO; Primary Source in Reference: 2000: MICS 2000; 2005: MICS 2005; 2007: LSS 2007; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Tajikistan National Series Reference: 1990 to 1999: MDG Progress Report 2003; 2000: MDG Progress Report 2010; 2001: MDG Progress Report 2003; 2005 to 2009: MDG Progress Report 2010; Source in Reference: 2001: Republican Center of Medical Statistics; 2007: NSO; Primary Source in Reference: 2000: MICS 2000; 2005: MICS 2005; 2007: LSS 2007; Indicator: Children 1 year old immunized against measles, (%) , Country: Tajikistan National Series Reference: 2001 to 2003: NSO MDG data; 2005 to 2008: MDG Progress Report 2010; Primary Source in Reference: 2001: MICS 2000; 2005: MICS 2005; Indicator: Under five mortality rate per 1,000 live births , Country: The former Yugoslav Republic of Macedonia National Series Reference: 1990: MDG report 2005; 1991 to 1996: MDG progress report 2009; 1997: MDG report 2005; 1998 to 2007: MDG progress report 2009; Note: 2004 to 2007: New Methodology; Source in Reference: 1991 to 1996: NSO; 1998 to 2007: NSO; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: The former Yugoslav Republic of Macedonia National Series Reference: 1990 to 2007: MDG progress report 2009; Note: 2004 to 2007: New Methodology; Source in Reference: 1990 to 2007: NSO; Indicator: Children 1 year old immunized against measles, (%) , Country: The former Yugoslav Republic of Macedonia National Series Reference: 1990 to 2007: MDG progress report 2009; Source in Reference: 1990 to 2007: Republic Institute for Health Protection; Indicator: Breast-fed under 6 months (%) , Country: The former Yugoslav Republic of Macedonia National Series Reference: 2007: MDG progress report 2009; Source in Reference: 2007: UNICEF 2007; Primary Source in Reference: 2007: MICS; Indicator: Under five mortality rate per 1,000 live births , Country: Turkey National Series Reference: 1993 to 2008: MDG Report 2010; Reference period: 1998: 1993-1998; 2003: 1998-2003; Source in Reference: 1993 to 2008: Hacettepe University; Primary Source in Reference: 1993: DHS 1993; 1998: DHS 1998; 2003: DHS 2003; 2008: DHS 2008; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Turkey National Series Reference: 1993 to 2008: MDG Report 2010; Reference period: 1998: 1993-1998; 2003: 1998-2003; Source in Reference: 1993 to 2008: Hacettepe University; Primary Source in Reference: 1993: DHS 1993; 1998: DHS 1998; 2003: DHS 2003; 2008: DHS 2008; Indicator: Children 1 year old immunized against measles, (%) , Country: Turkey National Series Reference: 1993 to 2009: MDG Report 2010; Source in Reference: 1993 to 2003: Hacettepe University; 2009: Min. of Health; Primary Source in Reference: 1993: DHS 1993; 1998: DHS 1998; 2003: DHS 2003; 2009: Ministry of Health Registry; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Turkmenistan National Series Reference: 1991 to 2002: MDG Report 2003; Source in Reference: 1991 to 2002: Min. of Health and the Medical Industry; Indicator: Under five mortality rate per 1,000 live births , Country: Ukraine National Series Reference: 1990 to 2000: MDG Report 2005; 2001 to 2009: MDG Report 2010; 2010 to 2012: MDG Report 2013; Definition: 1990 to 2000: Per 1,000 children under the age of five; Source in Reference: 2010 to 2012: NSO; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Ukraine National Series Reference: 1990: MDG Report 2005; 2000 to 2009: MDG Report 2010; 2010 to 2012: MDG Report 2013; Definition: 1990: Per 1,000 children under 1 years old; Source in Reference: 2000 to 2008: NSO; 2010 to 2012: NSO; Indicator: Children 1 year old immunized against measles, (%) , Country: Ukraine National Series Reference: 2008: MDG Report 2010; Indicator: Under five mortality rate per 1,000 live births , Country: Uzbekistan National Series Reference: 1995 to 2000: MDG Report 2006; Reference period: 1995: 1992-1997; 1998: 1996-2000; 2000: 1998-2002; Source in Reference: 1995: Min. of Health / Institute of Obstetrics and Gynecology; 1998: UNICEF; 2000: Min. of Health / Institute of Obstetrics and Gynecology; Primary Source in Reference: 1995: DHS 1996; 1998: MICS 2000; 2000: Uzbekistan Health Examination Survey 2002; Indicator: Infant mortality rate (0-1 year) per 1,000 live births , Country: Uzbekistan National Series Reference: 1995 to 2000: MDG Report 2006; Reference period: 1995: 1992-1997; 1998: 1996-2000; 2000: 1998-2002; Source in Reference: 1995: Min. of Health / Institute of Obstetrics and Gynecology; 1998: UNICEF; 2000: Min. of Health / Institute of Obstetrics and Gynecology; Primary Source in Reference: 1995: DHS 1996; 1998: MICS 2000; 2000: Uzbekistan Health Examination Survey 2002; Indicator: Children 1 year old immunized against measles, (%) , Country: Uzbekistan National Series Reference: 1996 to 2004: MDG Report 2006; Source in Reference: 1996 to 2004: TransMonee;
    • 2月 2019
      ソース: United Nations Children's Fund
      アップロード者: Knoema
      以下でアクセス: 08 4月, 2019
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      Global and regional deaths of children under 5 years of age by cause. Estimates generated by the WHO and Maternal and Child Epidemiology Estimation Group (MCEE) 2018.
    • 6月 2018
      ソース: Statistics Finland
      アップロード者: Knoema
      以下でアクセス: 29 11月, 2018
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      Data cited at: Statistics Finland http://www.stat.fi/index_en.html Publication: 030 -- Citizenship by sex, by region and municipality in 1990 to 2017 http://pxnet2.stat.fi/PXWeb/pxweb/en/StatFin/StatFin__vrm__vaerak/statfin_vaerak_pxt_030.px License: http://creativecommons.org/licenses/by/4.0/ Concepts and definitions Description Quality description These statistics apply the regional division of 1 January 2018 to the whole time series. Population statistics from 1750 to 2000 have been digitised into PDF format in the National Library's Doria service. Publications on Population structure and vital statistics in Doria (in Finnish) Publications on Population censuses in Doria (in Finnish) Area For reasons of privacy protection, cells with less than 10 cases of citizenship, country of birth, background country or language by municipality have been marked with two dots. Continent sums have not been hidden in municipality data nor have regional data concerning individual languages or countries. Citizenship If a person has two nationalities and one of them is Finnish, he/she will be included in statistics as a Finnish national. The used classification of continents is the classification of Eurostat, where Cyprus and Turkey belong to Europe. Citizens of non-autonomous states are summed under the mother country. Citizenship Czech Republic Czech Republic + Former Czechoslovakia Sudan Sudan + Former Sudan
    • 8月 2019
      ソース: World Bank
      アップロード者: Knoema
      以下でアクセス: 07 8月, 2019
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    • 7月 2019
      ソース: End Coal
      アップロード者: Knoema
      以下でアクセス: 04 9月, 2019
      データセットを選択
      Data cited at: End Coal https://endcoal.org/ Topic: Coal Plants by country Publication URL: https://endcoal.org/global-coal-plant-tracker/summary-statistics/ License: https://creativecommons.org/licenses/by-nc/4.0/
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 05 11月, 2019
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      Data covers cow's milk collected in farms by approved dairies. A distinction should be made between "milk collected by dairies" and "milk production on the farm". Milk collection is only a part of the total use of milk production on the farm. The other part of the use of milk produced on the farm generally includes domestic consumption, direct sale and cattle feed.
    • 4月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 21 5月, 2019
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      The collective bargaining coverage rate conveys the number of employees whose pay and/or conditions of employment are determined by one or more collective agreement(s) as a percentage of the total number of employees. Collective bargaining coverage includes, to the extent possible, workers covered by collective agreements in virtue of their extension. Collective bargaining coverage rates are adjusted for the possibility that some workers do not have the right to bargain collectively over wages (e.g. workers in the public services who have their wages determined by state regulation or other methods involving consultation), unless otherwise stated in the notes. The statistics presented in this table result from an ILO data compilation effort (including an annual questionnaire and numerous special enquiries), with contributions from J. Visser.
    • 11月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 12 11月, 2019
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    • 11月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 12 11月, 2019
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    • 1月 2018
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 26 6月, 2019
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      Food supply data is some of the most important data in FAOSTAT. In fact, this data is for the basis for estimation of global and national undernourishment assessment, when it is combined with parameters and other data sets. This data has been the foundation of food balance sheets ever since they were first constructed. The data is accessed by both business and governments for economic analysis and policy setting, as well as being used by the academic community.
    • 10月 2018
      ソース: U.S. National Center for Education Statistics
      アップロード者: Knoema
      以下でアクセス: 10 12月, 2018
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      Common Core Data For Universe surveys, School District (LEA) The primary purposes of the Local Education Agency (School District) Universe Survey are:to provide a complete listing of every education agency in the United States responsible for providing free public elementary/secondary instruction or education support services;to provide basic information about all education agencies and the students for whose education the agencies are responsible.  
    • 3月 2016
      ソース: UNESCO Institute for Statistics
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2016
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    • 8月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 02 8月, 2019
      データセットを選択
      Please be aware that this indicator has been rescaled, i.e. data is expressed in relation to EU28 = 100. Thus, they are not comparable with previous releases. Comparative price levels are the ratio between Purchasing power parities (PPPs) and market exchange rate for each country. PPPs are currency conversion rates that convert economic indicators expressed in national currencies to a common currency, called Purchasing Power Standard (PPS), which equalises the purchasing power of different national currencies and thus allows meaningful comparison. The ratio is shown in relation to the EU average (EU28 = 100). If the index of the comparative price levels shown for a country is higher/ lower than 100, the country concerned is relatively expensive/cheap as compared with the EU average.
    • 4月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 05 6月, 2019
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      The energy balance is the most complete statistical accounting of energy products and their flow in the economy. The energy balance allows users to see the total amount of energy extracted from the environment, traded, transformed and used by different types of end-users. It also allows seeing the relative contribution of each energy carrier (fuel, product). The energy balance allows studying the overall domestic energy market and monitoring impacts of energy policies. The energy balance offers a complete view on the energy situation of a country in a compact format, such as on energy consumption of the whole economy and of individual sectors. The energy balance presents all statistically significant energy products (fuels) of a country and their production, transformation and consumption by different type of economic actors (industry, transport, etc.). Therefore, an energy balance is the natural starting point to study the energy sector. Annual data collection cover in principle the EU Member States, EFTA, EU candidate countries, and potential candidate countries. Time series starts mostly in year 1990. All data in energy balances are presented in terajoules, kilotonnes of oil equivalent and gigawatt hours.
    • 5月 2018
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 18 6月, 2018
      データセットを選択
      Annual data on quantities for crude oil, oil products, natural gas and manufactures gases, electricity and derived heat, solid fossil fuels,  renewables and wastes covering the full spectrum of the energy sector from supply through transformation to final energy consumption by sector and fuel type. Also, annual imports and exports data of various energy carriers by country of origin and destination, as well as infrastructure information. Annual data collection cover in principle the EU Member States, EFTA, EU candidate countries, and potential candidate countries. Time series starts mostly in year 1990. All data are presented in the form of energy balances.
    • 3月 2018
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 29 3月, 2018
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      Domestic material consumption (DMC) measures the total amount of materials directly used by an economy and is defined as the annual quantity of raw materials extracted from the domestic territory of the focal economy, plus all physical imports minus all physical exports. The indicator Domestic Material Consumption (DMC) is based on the Economy-wide Material Flow Accounts (EW-MFA). The theory of Economy-wide material flow accounts (EW-MFA) includes compilations of the overall material inputs into national economy, the changes of material stock within the economy and the material outputs to other economies or to the environment. EW-MFA covers all solid, gaseous, and liquid materials, except water and air. Water included in products is included. The three main components of the DMC are:   - the raw materials domestically extracted (domestic extraction);   - the total import;   - the total export. It is important to note that the term "consumption" as used in DMC denotes apparent consumption and not final consumption. DMC does not include upstream hidden flows (materials that are extracted or moved, but do not enter the economy) related to imports and exports of raw materials and products. The indicator provides a basis for policies to decouple the growth of the economy from the use of natural resources so as to achieve a reduction of environment degradation resulting from primary production, material processing, manufacturing and waste disposal. DMC is a useful indicator, as it provides an assessment of the absolute level of use of resources and allows distinguishing consumption driven by domestic demand from consumption driven by the export market. Combined with GDP, it also provides insight into whether decoupling between the use of natural resources and growth of the economy is taking place.   The indicator is a Sustainable Development Indicator (SDI). It has been chosen for the assessment of the progress towards the objectives and targets of the EU Sustainable Development Strategy.   tsdpc220´s table: Eurobase > Tables by themes > Environment and energy > Environment > Environmental accounts > Components of domestic material consumption (tsdpc220) tsdpc220´s table within the SDI set: Eurobase > Tables on EU policy > Sustainable Development Indicators > Sustainable consumption and production > Resource use and waste > Components of domestic material consumption (tsdpc220)
    • 11月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 12 11月, 2019
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    • 4月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 22 4月, 2019
      データセットを選択
      Source: UNECE Statistical Database, compiled from national and international (Eurostat) official sources. Definition: Data provided refer to the proportion of persons who used a computer in the last three months preceding the survey over the total population of corresponding sex and age group. A computer is defined as a multi purpose machine, a personal computer, powered by one of the major operating systems, i.e. Macintosh (Apple), Linux or Microsoft (Windows XP, NT or Vista). PDAs (handheld computers or palmtops) are included. Other equipments with embedded computing technologies, e.g. cell phones, TV sets, washing machines and dish washers are not considered as computers. .. - data not available Country: Armenia Additional information (2004 - 2008): Data refer to percentage of persons using computers in households covered in Integrated household living standards survey. Country: Armenia For 2013-2014 data refer to the proportion of persons who used a computer in the last 12 months. Since 2015, to the proportion of persons who used a computer in the last three months. Country: Belarus Refers to computer use in the past 12 months. Country: Israel Change in definition (2002 - 2006): Data refer to population aged 20 and over. Data refer to the proportion of persons who used a computer in the last month. Country: Israel Change in definition (2007 - 2013): Data refer to population aged 20 and over. Country: Moldova, Republic of Change in definition (2009): Data refer to ge groups: 16-29, 30-59, 60-74. Country: Russian Federation Reference period (2013): Data do not refer to equipment such as mobile cellular phones , PDAs ( personal digital assistants) or TVs etc. Country: Serbia Data exclude territory of Kosovo and Metohija Country: United States Change in definition (1990 - 2013): Data do not refer to last 3 months, i.e. not time specific. Data are collected in October.
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 01 11月, 2019
      データセットを選択
      Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published:as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)
    • 8月 2019
      ソース: Bank for International Settlements
      アップロード者: Sandeep Reddy
      以下でアクセス: 26 8月, 2019
      データセットを選択
      The consolidated banking statistics (CBS) measure international banking activity from a nationality perspective, focusing on the country where the banking group's parent is headquartered. While residence-based data such as the locational banking statistics indicate where positions are booked, they do not always identify where underlying decisions are made. This is because banking offices in one country may operate within a business model decided by the group's controlling parent, which may be headquartered in another country. The CBS capture the worldwide claims of banking groups based in reporting countries and exclude intragroup positions, similar to the consolidation approach followed by banking supervisors. The CBS provide several different measures of banking groups' country risk exposures, on either an immediate counterparty or an ultimate risk basis. The most appropriate exposure measure depends on the issue being analysed. The benchmark measure in the CBS is foreign claims, which capture credit to borrowers outside a banking group's home country.   Measure for all Combinations - Amounts Outstanding / Stocks   Note: Under "Reporting country" they have removed "Euro Area".   Data cited at : https://www.bis.org/statistics/index.htm
    • 10月 2019
      ソース: Bank for International Settlements
      アップロード者: Knoema
      以下でアクセス: 28 10月, 2019
      データセットを選択
      Below Parameters are common for all combinations : Frequency - Quarterly Measure -Amounts Outstanding / Stocks CBS Bank Type - Domestic Banks CBS Reporting Basis - Immediate Counterparty Basis Balance Sheet Position - Total Claims Type of Instruments - All Instruments Remaining Maturity - All Maturities Currency Type of Booking Location - All Currencies Counterparty Sector - All Sectors Data cited at : https://www.bis.org/statistics/index.htm
    • 4月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 09 4月, 2019
      データセットを選択
      Definition: Constitutional court is the high court that deals primarily with constitutional law. Its main authority is to rule on whether or not laws that are challenged are in fact constitutional.In the case that the country does not have a separate constitutional court, data relates to the institution that has been delegated constitutional judicial authority, usually the supreme court. General note: Reference period - any fixed date of the year. .. - data not available Country: Croatia Additional information (2012 - 2013): The Croatian Constitution regulates that the Constitutional Court of the Republic of Croatia consists of 13 judges.Due to retirement, there are 12 judges left. Country: Cyprus Reference period (2011): data refer to 2012. Country: Cyprus Government controlled area only. Country: Estonia 2015: Figures reported are data as of 30.08.2016. Refers to justices of the Supreme court, not the full composition of the constitutional court. Country: Germany Change in definition (2004 - 2012): Data refer to members of constitutional court, without constitutional courts of the Federal States (Laender). Country: Moldova, Republic of Data exclude the territory of the Transnistria and municipality of Bender Country: Montenegro Reference period (2007): Data is valid only up to September 2007. Country: Netherlands Reference period (2011): Data refer to April 2012. Country: Slovakia Data for 2014 refer to 15 March. Data for 2015 refer to 20 November. Country: Switzerland Change in definition (1980 - 2013): Data refer to members of Federal Supreme Court.
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 01 11月, 2019
      データセットを選択
      Eurostat Dataset Id:ei_bsbu_m_r2 Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published:as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 01 11月, 2019
      データセットを選択
      Eurostat Dataset Id:ei_bsbu_q_r2 Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published: as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 12 11月, 2019
      データセットを選択
      Industry, Trade and Services statistics are part of Short-term statistics (STS), they give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification(Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are presented in the following forms: UnadjustedCalendar adjustedSeasonally-adjusted Depending on the STS regulation, data are accessible monthly and quarterly. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction Index*Turnover IndexProducer Prices (Domestic Output Prices index)*Import Prices Index*: Total, Euro area market, Non euro area market (euro area countries only)Labour Input Indicators: Number of Persons Employed, Hours Worked, Gross Wages and SalariesCONSTRUCTIONProduction Index*: Total of the construction sector, Building construction, Civil EngineeringLabour input indicators: Number of Persons Employed, Hours Worked, Gross Wages and SalariesConstruction costs IndexBuilding permits indicators*: Number of dwellingsWHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (in value)Labour input indicators: Number of Persons EmployedSERVICES  Turnover Index* Producer prices (Ouput prices)*
    • 5月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 31 5月, 2016
      データセットを選択
      Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category:Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below:Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.
    • 8月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 23 8月, 2019
      データセットを選択
      Non-expenditure health care data provide information on institutions providing health care in countries, on resources used and on output produced in the framework of health care provision. Data on health care form a major element of public health information as they describe the capacities available for different types of health care provision as well as potential 'bottlenecks' observed. The quantity and quality of health care services provided and the work sharing established between the different institutions are a subject of ongoing debate in all countries. Sustainability - continuously providing the necessary monetary and personal resources needed - and meeting the challenges of ageing societies are the primary perspectives used when analysing and using the data. The output-related data ('activities') refer to contacts between patients and the health care system, and to the treatment thereby received. Data are available for hospital discharges of in-patients and day cases, average length of stay of in-patients and medical procedures performed in hospitals. Annual national and regional data are provided in absolute numbers and in population-standardised rates (per 100 000 inhabitants). Wherever applicable, the definitions and classifications of the System of Health Accounts (SHA) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). For hospital discharges, the International Shortlist for Hospital Morbidity Tabulation (ISHMT) is used. Health care data on activities are largely based on administrative data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable.
    • 11月 2019
      ソース: International Monetary Fund
      アップロード者: Knoema
      以下でアクセス: 11 11月, 2019
      データセットを選択
      Consumer price indexes (CPIs) are index numbers that measure changes in the prices of goods and services purchased or otherwise acquired by households, which households use directly, or indirectly, to satisfy their own needs and wants. In practice, most CPIs are calculated as weighted averages of the percentage price changes for a specified set, or ‘‘basket’’, of consumer products, the weights reflecting their relative importance in household consumption in some period. CPIs are widely used to index pensions and social security benefits. CPIs are also used to index other payments, such as interest payments or rents, or the prices of bonds. CPIs are also commonly used as a proxy for the general rate of inflation, even though they measure only consumer inflation. They are used by some governments or central banks to set inflation targets for purposes of monetary policy. The price data collected for CPI purposes can also be used to compile other indices, such as the price indices used to deflate household consumption expenditures in national accounts, or the purchasing power parities used to compare real levels of consumption in different countries.
    • 9月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 03 10月, 2019
      データセットを選択
      The FAOSTAT monthly CPI Food CPI database was based on the ILO CPI data until December 2014. In 2014, IMF-ILO-FAO agreed to transfer global CPI data compilation from ILO to IMF. Upon agreement, CPIs for all items and its sub components originates from the International Monetary Fund (IMF), and the UN Statistics Division(UNSD) for countries not covered by the IMF. However, due to a limited time coverage from IMF and UNSD for a number of countries, the Organisation for Economic Co-operation and Development (OECD), the Latin America and the Caribbean statistics (CEPALSTAT), Central Bank of Western African States (BCEAO), Eastern Caribbean Central Bank (ECCB) and national statistical office website data are used for missing historical data from IMF and UNSD food CPI. The FAO CPI dataset for all items(or general CPI) and the Food CPI, consists of a complete and consistent set of time series from January 2000 onwards. These indices measure the price change between the current and reference periods of the average basket of goods and services purchased by households. The CPI,all items is typically used to measure and monitor inflation, set monetary policy targets, index social benefits such as pensions and unemployment benefits, and to escalate thresholds and credits in the income tax systems and wages in public and private wage contracts.
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 01 11月, 2019
      データセットを選択
      Eurostat Dataset Id:ei_bsco_m Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published:as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 01 11月, 2019
      データセットを選択
      Eurostat Dataset Id:ei_bsco_q Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published: as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)
    • 4月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 05 5月, 2019
      データセットを選択
      Fertilisers contain important nutrients, such as nitrogen (N) and phosphorus (P), which plants absorb from the soil for their growth. With the harvest of crops for human and livestock consumption and industrial uses, N and P is removed from the soil. Continuing agricultural production without fertilisation could lead to soil degradation and erosion. Fertilisers are therefore essential to sustain agricultural production. Fertilisers are also used to improve crop yields and soils. The use of manufactured fertilizers as a regular farming practice began in most European countries in the mid to late nineteenth century but the greatest increase in consumption in these countries occurred in the three decades following World War II. The manufacturing of fertilisers greatly enhanced crop yields and agricultural production, and aided the large increase in the world population in the 20th Century. However when the amount of fertiliser applied exceeds the plants' nutritional requirements, there is a greater risk of nutrient losses from agricultural soils into ground and surface water. The resulting higher concentration of nutrients (eutrophication) can cause serious degradation of ecosystems. With the storage and application to the land of manufactured fertilisers, Nitrogen can volatilise into the air as ammonia contributing to acidification, eutrophication and atmospheric particulate pollution, and nitrous oxides, a potent greenhouse gas contributing to climate change.  In addition fertilisers may also have adverse environmental effects resulting from their production processes. More specifically, nitrogenous fertilisers require large amounts of energy to be produced leading potentially to higher levels of greenhouse gas emissions. In a different way, phosphorus fertilisers also have an environmental impact, since the raw materials used to produce them are mined, therefore potentially leading to landscape destruction, water contamination, excessive water consumption or air pollution. This table contains data on the total use of manufactured fertilisers expressed in tonnes of N and tonnes of P received from the countries. Manufactured fertilisers are also often referred to as inorganic fertilisers or mineral fertilisers. For a definition see 3.4.
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 18 3月, 2019
      データセットを選択
      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
    • 7月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 01 8月, 2019
      データセットを選択
      Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.
    • 1月 2017
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 20 2月, 2017
      データセットを選択
      Control of corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and pricate interests. The Worldwide Governance Indicators report on six broad dimensions of governance for 215 countries over the period 1996-2014: Voice and Accountability, Political Stability and Absence of Violence, Government Effectiveness, Regulatory Quality, Rule of Law and Control of Corruption.
    • 5月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 03 6月, 2019
      データセットを選択
      Source: UNECE Statistical Database, compiled from national official sources. Definition: Persons convicted are persons found guilty by any legal body duly authorised to do so under national law, whether the conviction was later upheld or not. .. - data not available Country: Austria Break in methodlogy (2000): Significantly reduced number of convictions between 1999 and 2000: the decline is due to diversion which is now applicable to adults in criminal law. Country: Austria Change in definition (1990): Juveniles: data refer to persons aged less than 19. Persons, who were convicted more than once in the indicated year are multiple-counted. Country: Austria Change in definition (1995 - 2001): Juveniles: data refer to persons aged less than 19. Country: Bulgaria Break in methodlogy (2000): Until 1997 data are based on the activity of the regional and district courts on penal trials of general, private and administrative character. Since 1998 the information for the activity of military courts is also included. Country: Bulgaria Break in methodlogy (2012): Since 2012 data include activities of the Special Criminal Court. Country: Canada Found guilty includes guilty of the charged offence, of an included offence, of an attempt of the charged offence, or of an attempt of an included offence. This category also includes cases where an absolute or conditional discharge has been imposed. Data refer to fiscal year (April 1 through March 31 of following year). 1995-2004: data do not cover all provinces and territories. Adult is a person of age 18+ at the time of the offence. Juvenile is a person aged 12 to 17 y.o at the time of the offence. Country: Cyprus Data refer to the Government controlled area only. Country: Cyprus Includes convictions of both serious crimes (in violation of the Penal Code) and minor offences, as well as traffic violations. Country: Czechia Change in definition (2000 - 2012): Data include not only imprisonment but also e.g. fines, ban on activity, etc. Country: Denmark Break in methodlogy (2007): From 1980 to 2006, data refer to all persons with a decision, incl. acquitted and prosecutor dropped. From 2007, data cover only those who are convicted. Country: Estonia Break in methodlogy (1990): Change in laws and methodology. Country: Finland Break in methodlogy (2000): Offences against the Road Traffic Act carrying imprisonment as penalty were transferred to the Penal code on 1 October 1999. Country: France Additional information (1995 - 2002): Amnesties (part of convictions was not registered). Country: France Change in definition (1980 - 2012): Data include DOM-TOM. Country: France Provisional value (2012): Country: Georgia Territorial change (1990 onward): Data do not cover Abkhazia AR and Tskhinvali Region. Country: Germany Territorial change (1980 - 2006): Data refer to former territory of Germany. Country: Greece Change in definition (1990 - 2004): Juveniles: persons aged up to 17 Country: Ireland Change in definition (2000 - 2002): Headline Incidents only being included. Juveniles: 16 years or younger. Country: Israel Change in definition (1980 - 1990): Convicted juvenile offenders are those tried in juvenile courts. Country: Israel Change in definition (2000 - 2012): Convicted juvenile offenders are those tried in juvenile courts. Data on persons charged in criminal trials conducted in courts of first instance, who were sentenced during a given year. Since 2000 classification as adults or as juveniles was based on the following criteria, 1) The offender`age at the time crime was committed. 2)The offender`s age at time of the indictment 3)The type of court in which the trial was held.A juvenile offender is a person who meets two out of the three criteria . All other cases are considered to be adults. Country: Israel Reference period (1980): Data refer to 1981 Country: Israel Reference period (1990): Data refer to 1989 Country: Italy Break in methodlogy (2000): Change in methodology and source Country: Italy Change in definition (1980 - 2011): Data refers to the convicted persons recorded in the Judicial Database Country: Kazakhstan Break in methodlogy (2000): Change of source as of 2000 Country: Moldova, Republic of Data exclude the territory of the Transnistria and municipality of Bender Country: Netherlands Change in definition (1990 - 2012): Data exclude persons with unknown sex and age. Country: Poland Change in definition (1980 - 1990): Juveniles: persons aged up to 16. Country: Poland Change in definition (1995 - 2012): Juveniles: persons aged up to 17. Country: Romania Convictions is equivalent to Persons convicted because there are no data regarding final convictions. Country: Serbia Territorial change (2000 onward): Data exclude territory of Kosovo and Metohija. Country: Slovenia Break in methodology (1995): Change in law. Break in methodology (2013): New amendment to the Criminal Procedure Act enabled the implementation of criminal proceedings and economized trials. This is reflected in the large increase of the number of convicted persons over the previous year. The number of convicted juveniles did not significantly increase during the same period – around 10%. Country: Spain Break in methodlogy (2008): Before 2007: different source and partial coverage. Country: Spain Change in definition (1980 - 2013): Juveniles: persons aged between 14 to 17 years. Country: Spain Change in definition (2000 - 2006): Juveniles: persons aged between 14 to 17 years. Convicted persons are partially reported by sex. Country: Sweden Change in definition (1980 onwards): Data refer to number of convictions. One person can contribute with more than one conviction during a calendar year. Includes attempts, assistance, preparation and conspiracy to commit an offence. Country: Switzerland Additional information (1990 - 1995): Data are not complete (Juvenile convictions are not available) Country: Switzerland Change in definition (1990 - 2012): Only convicted persons for felonies and misdemeanours. Country: Turkey 2005: break in series: introduction of changes in laws. 2009: break in series: change in data compilation method. Data refer to the number of sentence decisions rendered for accused persons at criminal courts in accordance with Turkish Criminal Law and special laws for 2009 and later. Total excludes judicial person, foreign national and unknown sex and age for 2009 and later. Country: Ukraine From 2014 data cover the territories under the government control. Country: United Kingdom Change in definition (2008 - onwards): For total convicted persons, male and female may not add up to total because the sex is not always recorded Country: United Kingdom Territorial change (1980): Data refer to England and Wales only. Country: United States Adults: data represent felony conviction in state and federal courts. 1995: data refer to 1994.
    • 5月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 03 6月, 2019
      データセットを選択
      .. - data not available Source: UNECE Statistical Database, compiled from national official sources. Definition: Conviction is the verdict that results when a court of law finds a defendant guilty of a crime. A serious assault is an injury whereby life could be endangered, including cases of injury involving the use of dangerous instrument. Cases where instruments are used only to threaten are excluded. An assault refers to physical attack against the body of another person, including battery but excluding indecent assault. A homicide is intentional or unintentional killing. Intentional homicide is a death deliberately inflicted on a person by another person, including infanticide.Non-intentional homicide is a death not deliberately inflicted on a person by another person. That includes crime of manslaughter but excludes traffic accidents that result in a death of persons. The distinction between intentional and unintentional homicide differs from country to country, as does the definition of attempted murder. Rape is a sexual intercourse without valid consent. Robbery is a theft of property from a person, overcoming resistance by force or threat of force. Theft is any act of intentionally and unlawfully removing property belonging to another person (or organisation), excluding burglary. Drug crimes are any violation involving the illicit brokerage, cultivation, delivery (on any terms whatsoever), dispatch, dispatch in transit, distribution, extraction, exportation or importation, offering for sale, preparation, production, purchase, manufacture, sale, traffic, transportation, or use of narcotic drugs. General note: Data come from administrative data sources unless otherwise specified. Country: Albania Assault includes article 89, this change includes years 2013-2015. Theft includes all crimes against property and economic sphere, but excludes robbery. Country: Austria Break in methodlogy (2000): Significantly reduced number of convictions between 1999 and 2000: the decline is due to diversion which is now applicable to adults in criminal law. Country: Bulgaria Break in methodlogy (2000): Until 1997 data are based on the activity of the regional and district courts on penal trials of general, private and administrative character. Since 1998 the information for the activity of military courts is also included. Country: Bulgaria Break in methodlogy (2012): Since 2012 data include activities of the Special Criminal Court. Country: Canada Assault includes Level 1 Assault, Criminal Code of Canada, section 266. A common assault has been committed when an individual intentionally applies force or threatens to apply force to another person, without that person's consent. The seriousness of physical injury is what distinguishes this type of assault from other, more serious assaults. Serious assault includes assault with a weapon (Level 2, Criminal Code of Canada, section 267), aggravated assault (Level 3, Criminal Code of Canada, section 268) and other assaults (assaults against police officers, and unlawfully causing bodily harm). Homicide includes first-degree murder, second-degree murder, manslaughter and infanticide. Rape is not a recognized offence in the Criminal Code of Canada. Data reported are sexual assault (level 1), sexual assault with a weapon or bodily harm (level 2) and sexual assault aggravated (level 3). Theft includes theft over and under $5,000 as well as motor vehicle theft. Drug crime includes drug possession, trafficking, production, importing and exporting. Data refer to a fiscal year (April 1 through March 31). Data do not cover all provinces and territories. Data includes persons aged 12 y.o. or older at the time of the offence. Country: Croatia Data refer to adults serving imprisonment sentences. Country: Cyprus Data refer to the Government controlled area only. Country: Cyprus Includes convictions of both serious crimes (in violation of the Penal Code) and minor offences, as well as traffic violations. Country: Denmark Change in definition (1980 - 2012): All persons with a decision, incl. acquitted and prosecutor dropped Assault: Include serious assault and homicide Country: Denmark Only guilty decisions included. Country: Estonia Break in methodlogy (1990 - 1995): Change in laws and methodology. Country: Estonia Change in definition (1990 - 2013): Theft includes burglary. Country: Finland Break in methodology (2000): The Penal Code includes the offences against the Road Traffic Act carrying imprisonment as penalty. Country: Finland Data refer to offences against the Penal Code only. Country: France Additional information (1995 - 2002): Amnesties (part of convictions was not registered). Country: France Change in definition (1990 - 2011): Data are based on different classification of offences. Country: Georgia Territorial change (2000 onward): Data do not cover Abkhazia AR and Tskhinvali Region. Country: Germany Territorial change (1980 - 2006): Data refer to former territory of Germany. Country: Greece Change in definition (1980 - 2010): Number of convictions equals to number of convicted persons (persons found definitively guilty from penal courts). Serious assault excludes fatal body injuries. Country: Iceland Data refer to convictions from the district courts. Country: Ireland 2009: break in series, change in methodology. Country: Israel Reference period (1980): Data refer to 1981 Country: Israel Reference period (1990): Data refer to 1989 Country: Italy Break in methodlogy (2000): Until 2000 data referred to the most serious crime. Series from 2000 to 2011 have been updated according to the new systems and calculating the convinctions instead of the persons convicted. Country: Italy Change in definition (1980 - 2011): Rape: convicted for misdemeanours are not included. Country: Kazakhstan Break in methodlogy (2000): Change of source as of 2000 Country: Kyrgyzstan Change in definition (2000 - onwards): Data are changed concidering the definition of the robbery. Country: Latvia Break in methodlogy (2011): Data include fraud and misappropriation on small scale Country: Latvia Change in definition (2000 - 2012): Data for theft include burglary. Country: Moldova, Republic of Territorial change (2004 onward): Data exclude the territory of the Transnistria and municipality of Bender Country: Montenegro 2001-2006: data refer to convicted adults. From 2007: data refer to convicted adults and juveniles. Assaults include serious assaults. Country: Netherlands Assaults include serious assaults. Data exclude persons with unknown sex. Country: Norway Until 2000: the total does not include convictions for misdemeanours, i.e. ticket fines and prosecutions conditionally dropped are not included. Country: Poland Data refer to adults only. Country: Romania Convictions is equivalent to Persons convicted because there are no data regarding final convictions. Country: Serbia Territorial change (2000 onward): Data exclude territory of Kosovo and Metohija. Country: Slovakia Break in methodlogy (2006): Change in criminal code. Country: Slovenia Break in methodology (1995): Change in law. Break in methodology (2013): New amendment to the Criminal Procedure Act enabled the implementation of criminal proceedings and economized trials. This is reflected in the large increase of the number of convicted persons over the previous year. The number of convicted juveniles did not significantly increase during the same period – around 10%. Country: Spain Break in methodology (2007): change in source, data include only firm convictions. Country: Spain Total could be less than sum of convictions by type as each conviction can include different crimes. Country: Sweden Break in methodlogy (2005): Break in series for convictions of Rape due to changes in legislation for sexual offenses. Country: Sweden Statistics presented refers to conviction decisions laid down by courts (first instance county court convictions) or prosecutors (prosecutor fines or waiver of prosecution). Sub groups for some years do not add up to the main level, due to missing data on gender. Attempt, preparation, being an accomplice, incitement, failure to disclose and failure to prevent offences are included in respective offence category. Drug crime does not include drug trafficking for the years 1995 and 2000. Drug trafficking is included from 2001 onwards. Country: Switzerland Change in definition (1990 - onwards): Only convicted persons for felonies and misdemeanours. Country: Turkey Break in methodlogy (2009): Change in data compilation method. Country: Turkey Change in definition (1990 - 2010): Data includes intentional and non-intentional homicide. Theft includes burglary. Country: Turkey Data refer to the number of sentence decisions rendered for accused persons at criminal courts in accordance with Turkish Criminal Law and special laws for 2009 and later. Total excludes judicial person, foreign national and unknown sex for 2009 and later. Country: Ukraine From 2014 data cover the territories under the government control. Country: United Kingdom Change in definition (2000 - onwards): Serious assault includes attempted murder. Rape includes attempted rape. Country: United Kingdom Change in definition (2008 - onwards): Male and female may not add up to total because sex is not always recorded. Country: United Kingdom Territorial change (2000 - onwards): Data refer to England and Wales. Country: United States Data represent felony convictions in State and Federal Courts. Convictions in juvenile courts are not included. Data do not distinguish between assault and serious assault. 1995: data refers to 1994.
    • 12月 2018
      ソース: International Monetary Fund
      アップロード者: Knoema
      以下でアクセス: 22 2月, 2019
      データセットを選択
      The CDIS database presents detailed data on "inward" direct investment positions (i.e., direct investment into the reporting economy) cross-classified by economy of immediate investor, and data on "outward" direct investment positions (i.e., direct investment abroad by the reporting economy) cross-classified by economy of immediate investment. The CDIS database contains breakdowns of direct investment position data, including, in most instances, separate data on net equity and net debt positions, as well as tables that present "mirror" data (i.e., tables in which data from the reporting economy are shown side-by-side with the data obtained from all other counterpart reporting economies).
    • 3月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 11 3月, 2019
      データセットを選択
      Source: UNECE Statistical Database, compiled from national official sources. Definition: A ministry is a department of a government, led by a minister. A minister (sometimes called secretary) is a politician who holds significant public office in a national cabinet and is entrusted with the management of a division of governmental activities. A cabinet is a body of high-ranking members of government, typically representing the executive branch. Core ministries include: Cabinet of Prime Minister, Ministry of Home Affairs, Ministry for Foreign Affairs, Ministry of Finance, Ministry of Defence, Ministry of Justice. General note: Reference period: any fixed date of the year. .. - data not available Country: Estonia 2015: Data refers to composition after September 14, 2015. 2014: Data refers to composition between November 17, 2014 to April 9, 2015. Country: Georgia Territorial change (2004 onward): Data do not cover Abkhazia AR and Tskhinvali Region. Country: Israel 1990: data refer to average from 1988-1990, 1995: data refer to average from 1992-1995, 2000: data refer to average from 1999-2001. Country: Latvia Reference period (1990): data refer to 1991. Country: Moldova, Republic of Additional information (1980): Data include the territory of the Transnistria and municipality of Bender Country: Moldova, Republic of Additional information (1990): Data include the territory of the Transnistria and municipality of Bender Data exclude the territory of the Transnistria and municipality of Bender Country: Moldova, Republic of Additional information (1995 onward): Data exclude the territory of the Transnistria and municipality of Bender Country: Montenegro Additional information (2006): Ministry for Defense was formed in 2006. Country: Portugal 2008: data refer to 2009. Country: Slovakia Data for 2014 refer to 15 March. Data for 2015 refer to 20 November. Country: Switzerland Change in definition (1980 - onwards): All the 7 ministers in Switzerland are considered as being head of a Core Ministry.
    • 8月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 13 8月, 2019
      データセットを選択
      Indicator is a composite index based on a combination of surveys and assessments of corruption from 13 different sources and scores and ranks countries based on how corrupt a country’s public sector is perceived to be. The sources of information used for the 2016 CPI are based on data gathered in the 24 months preceding the publication of the index. The CPI includes only sources that provide a score for a set of countries/territories and that measure perceptions of corruption in the public sector. For a country/territory to be included in the ranking, it must be included in a minimum of three of the CPI’s data sources. The CPI is published by Transparency International.
    • 1月 2019
      ソース: Transparency International
      アップロード者: Knoema
      以下でアクセス: 01 2月, 2019
      データセットを選択
      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.
    • 2月 2019
      ソース: Numbeo
      アップロード者: Knoema
      以下でアクセス: 05 3月, 2019
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      Data cited at NUMBEO Numbeo is the world’s largest database of user contributed data about cities and countries worldwide. Numbeo provides current and timely information on world living conditions including cost of living, housing indicators, health care, traffic, crime and pollution. For more information please check http://www.numbeo.com/cost-of-living/rankings_by_country.jsp   About dataset: These indices are relative to New York City (NYC). Which means that for New York City, each index should be 100(%). If another city has, for example, rent index of 120, it means rents in average in that city are 20% more expensive than in New York City. If a city has rent index of 70, that means in the average in that city rents are 30% less expensive than in New York City. Cost of Living Index (Excl. Rent) is a relative indicator of consumer goods price, including groceries, restaurants, transportation and utilities. Cost of Living Index doesn't include accommodation expenses such as rent or mortgage. If a city has a Cost of Living Index of 120, it means Numbeo estimates it is 20% more expensive than New York (excluding rent). Rent Index is estimation of prices of renting apartments in the city compared to New York City. If Rent index is 80, Numbeo estimates that price for renting in that city is 80% of price in New York. Groceries Index is an estimation of grocery prices in the city compared to New York City. To calculate this section, Numbeo uses "Markets"section of each city. Restaurants Index is a comparison of prices of meals and drinks in restaurants and bars compared to NYC. Cost of Living Plus Rent Index is an estimation of consumer goods prices including rent in the city comparing to New York City. Local Purchasing Power shows relative purchasing power in buying goods and services in a given city for the average wage in that city. If domestic purchasing power is 40, this means that the inhabitants of that city with the average salary can afford to buy 60% less typical goods and services than New York City residents with an average salary.
    • 3月 2019
      ソース: Chief Executives Board for Coordination, UN
      アップロード者: Knoema
      以下でアクセス: 10 10月, 2019
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      Chinese Taipei is WTO terminology for the territory referred to by the United Nations as Taiwan Province of China. Please also refer to the official announcement by WTO at www.wto.org/english/news_e/pres01_e/pr253_e.htm As of 2017, the data includes an additional six entities (CTBTO, ICC, UNCDF, UNFCCC, UNRISD, UNSSC)
    • 4月 2015
      ソース: International Monetary Fund
      アップロード者: Sandeep Reddy
      以下でアクセス: 20 8月, 2015
      データセットを選択
      Global growth is forecast at 3.5 percent in 2015 and 3.8 percent in 2016, with uneven prospects across the main countries and regions of the world. The distribution of risks to near-term global growth has become more balanced relative to the October World Economic Outlook but is still tilted to the downside. The decline in oil prices could boost activity more than expected. Geopolitical tensions continue to pose threats, and risks of disruptive shifts in asset prices remain relevant. In some advanced economies, protracted low inflation or deflation also pose risks to activity. The chapter takes a region-by-region look at the recent development in the world economy and the outlook for 2015, with particular attention to notable development in countries within each region.
    • 1月 2019
      ソース: NYU Stern
      アップロード者: Knoema
      以下でアクセス: 13 2月, 2019
      データセットを選択
      Citation: Damodaran, Aswath, Equity Risk Premiums (ERP): Determinants, Estimation and Implications – The 2016 Edition (March 5, 2016). Available at SSRN: https://ssrn.com/abstract=2742186 or http://dx.doi.org/10.2139/ssrn.2742186   This dataset summarizes the latest bond ratings and appropriate default spreads for different countries. While you can use these numbers as rough estimates of country risk premiums, you may want to modify the premia to reflect the additional risk of equity markets. To estimate the long term country equity risk premium, I start with a default spread, which I obtain in one of two ways: (1) I use the local currency sovereign rating (from Moody's: www.moodys.com) and estimate the default spread for that rating (based upon traded country bonds) over a default free government bond rate. For countries without a Moody's rating but with an S&P rating, I use the Moody's equivalent of the S&P rating. To get the default spreads by sovereign rating, I use the CDS spreads and compute the average CDS spread by rating. Using that number as a basis, I extrapolate for those ratings for which I have no CDS spreads. (2) I start with the CDS spread for the country, if one is available and subtract out the US CDS spread, since my mature market premium is derived from the US market. That difference becomes the country spread. For the few countries that have CDS spreads that are lower than the US, I will get a negative number. You can add just this default spread to the mature market premium to arrive at the total equity risk premium. I add an additional step. In the short term especially, the equity country risk premium is likely to be greater than the country's default spread. You can estimate an adjusted country risk premium by multiplying the default spread by the relative equity market volatility for that market (Std dev in country equity market/Std dev in country bond). I have used the emerging market average of 1.12 (estimated by comparing a emerging market equity index to an emerging market government/public bond index) to estimate country risk premium.I have added this to my estimated risk premium of 5.08% for mature markets (obtained by looking at the implied premium for the S&P 500) to get the total risk premium. Notes:  The year of publication has been considered as per publication date. For example, data published on 2018-Jan considered as 2018, similarly 2019-Jan as 2019    
    • 3月 2018
      ソース: Statistics Finland
      アップロード者: Knoema
      以下でアクセス: 29 11月, 2018
      データセットを選択
      Data cited at: Statistics Finland http://www.stat.fi/index_en.html Publication: 012 -- Country of birth according to age and sex by region in 1990 to 2017 http://pxnet2.stat.fi/PXWeb/pxweb/en/StatFin/StatFin__vrm__vaerak/statfin_vaerak_pxt_012.px License: http://creativecommons.org/licenses/by/4.0/ Concepts and definitions Description Quality description These statistics apply the regional division of 1 January 2018 to the whole time series. Population statistics from 1750 to 2000 have been digitised into PDF format in the National Library's Doria service. Publications on Population structure in Doria (in Finnish) Publications on Vital statistics in Doria (in Finnish) Publications on Population censuses in Doria (in Finnish) Country of birth The used classification of continents is the classification of Eurostat, where Cyprus and Turkey belong to Europe. Non-autonomous states are summed under their mother country. Country of birth Sudan Sudan + Former Sudan
    • 11月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 07 11月, 2019
      データセットを選択
      Source: UNECE Statistical Database, compiled from national and international official sources. Area data exclude overseas departments and territories. For population footnotes click here. For life expectancy footnotes click here. For fertility rate footnotes click here. For population by marital status footnotes click here. For female members of parliament footnotes click here. For female government ministers footnotes click here. For female central bank board members footnotes click here. For female tertiary students footnotes click here. For economic activity rate footnotes click here. For gender pay gap footnotes click here. For employment growth rate footnotes click here. For unemployment rate footnotes click here. For youth unemployment rate footnotes click here. For employment by economic sector footnotes click here. For economic indicator footnotes click here. For road accident footnotes click here. For total length of motorways footnotes click here. For total length of railway lines footnotes click here. Key indicators in maps .. - data not availableIndicatorGDP in agriculture (ISIC4 A): output approach, index, 2010=100If the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP in industry (incl. construction) (ISIC4 B-F): output approach, index, 2010=100If the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP in services (ISIC4 G-U): output approach, index, 2010=100If the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in agriculture etc. (ISIC4 A), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in industry etc. (ISIC4 B-E), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in construction (ISIC4 F), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in trade, hospitality, transport and communication (ISIC4 G-J), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in finance and business services (ISIC4 K-N), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in public administration, education and health (ISIC4 O-Q), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in other service activities (ISIC4 R-U), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in agriculture, hunting, forestry and fishing (ISIC Rev. 4 A), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in industry and energy (ISIC Rev. 4 B-E), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in construction (ISIC Rev. 4 F), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in trade, hotels, restaurants, transport and communications (ISIC Rev. 4 G-J), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in finance, real estate and business services (ISIC Rev. 4 K-N), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in public administration, education and health (ISIC Rev. 4 O-Q), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in other service activities (ISIC Rev. 4 R-U), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.
    • 4月 2018
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 21 5月, 2018
      データセットを選択
      Note: CPA data for 2018 and 2019 are projections from the 2016 Survey on Forward Spending Plans. 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
    • 7月 2016
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 29 7月, 2016
      データセットを選択
      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
    • 12月 2015
      ソース: International Monetary Fund
      アップロード者: Knoema
      以下でアクセス: 18 4月, 2016
      データセットを選択
      COFR presents data on fiscal transparency. It provides an overview of fiscal reporting, including whether fiscal data are available for all of the general government, whether the government reports a balance sheet, and whether spending and revenue are reported on a cash or accrual basis. It also derives specific indices of the coverage of public institutions, fiscal flows, and fiscal stocks.
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 10月, 2019
      データセットを選択
      Animal production statistics cover three main sub-domains based on three pieces of relevant legislation and related gentlemen’s agreements. Livestock and meat statistics are collected under Regulation (EC) No 1165/2008. They cover meat production, as activity of slaughterhouses (monthly) and as other slaughtering (annual), meat production (gross indigenous production) forecast (semi-annual or quarterly), livestock statistics, including regional statistics. A quality report is also collected every third year.Milk and milk product statistics are collected under Decision 97/80/EC implementing Directive 96/16/EC. They cover farm production and utilisation of milk (annual), collection (monthly for cows’ milk) and production activity by dairies (annual) and statistics on the structure of dairies (every third year). An annual methodological report is also collected.Statistics on eggs for hatching and farmyard poultry chicks are collected under Regulation (EC) No 617/2008, implementing Regulation (EC) No 1234/2007 (Single CMO Regulation). They cover statistics on the structure (annual) and the activity (monthly) of hatcheries as well as reports on the external trade of chicks. European Economic Area countries (EEA, Iceland, Liechtenstein and Norway) are requested to provide milk statistics, with the exception of those related to home consumption, as stated in Annex XXI of the EEA Agreement. As Iceland is now a candidate country and Liechtenstein is exempted in the Agreement, only Norway is concerned. The Agreement between the European Community and the Swiss Confederation on cooperation in the field of statistics states that Switzerland must provide Eurostat with national milk statistics. It has been amended in 2013 for covering also some livestock and meat statistics. The same statistics are requested from the candidate countries as acquis communautaire. Further data about the same topics refer to repealed legal acts or agreements. The tables on animal product supply balance sheets (apro_mk_bal, apro_mt_bal and apro_ec_bal), statistics on the structure of rearing (apro_mt_str) and the number of laying hens (apro_ec_lshen) are therefore no longer updated. The same applies to some variables (external trade of animals and meat), periods (surveys in April or August) or items (number of horses) included in other tables. The statistical tables disseminated by Eurostat are organised into three groups of tables on Agricultural products (apro), i.e. Milk and milk products (apro_mk), Livestock and meat (apro_mt) and Poultry farming (apro_ec). This last label covers statistics on hatcheries and on trade in chicks. The regional animal production statistics collected on livestock (agr_r_animal) and on cows’ milk production on farms (agr_r_milk_pr) are disseminated separately. Due to the change in the legal basis or in the methodology, the time series may be broken. This is indicated by a flag in the tables. The detailed content of each table and the reference to its legal definition is provided in the table below. Table 3.1: Data tables disseminated regarding animal production statistics
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 06 11月, 2019
      データセットを選択
      Animal production statistics cover three main sub-domains based on three pieces of relevant legislation and related gentlemen’s agreements.Livestock and meat statistics are collected under Regulation (EC) No 1165/2008. They cover meat production, as activity of slaughterhouses (monthly) and as other slaughtering (annual), meat production (gross indigenous production) forecast (semi-annual or quarterly), livestock statistics, including regional statistics. A quality report is also collected every third year.Milk and milk product statistics are collected under Decision 97/80/EC implementing Directive 96/16/EC. They cover farm production and utilisation of milk (annual), collection (monthly for cows’ milk) and production activity by dairies (annual) and statistics on the structure of dairies (every third year). An annual methodological report is also collected.Statistics on eggs for hatching and farmyard poultry chicks are collected under Regulation (EC) No 617/2008, implementing Regulation (EC) No 1234/2007 (Single CMO Regulation). They cover statistics on the structure (annual) and the activity (monthly) of hatcheries as well as reports on the external trade of chicks. European Economic Area countries (EEA, Iceland, Liechtenstein and Norway) are requested to provide milk statistics, with the exception of those related to home consumption, as stated in Annex XXI of the EEA Agreement. As Iceland is now a candidate country and Liechtenstein is exempted in the Agreement, only Norway is concerned. The Agreement between the European Community and the Swiss Confederation on cooperation in the field of statistics states that Switzerland must provide Eurostat with national milk statistics. It has been amended in 2013 for covering also some livestock and meat statistics. The same statistics are requested from the candidate countries as acquis communautaire. Further data about the same topics refer to repealed legal acts or agreements. The tables on animal product supply balance sheets (apro_mk_bal, apro_mt_bal and apro_ec_bal), statistics on the structure of rearing (apro_mt_str) and the number of laying hens (apro_ec_lshen) are therefore no longer updated. The same applies to some variables (external trade of animals and meat), periods (surveys in April or August) or items (number of horses) included in other tables. The statistical tables disseminated by Eurostat are organised into three groups of tables on Agricultural products (apro), i.e. Milk and milk products (apro_mk), Livestock and meat (apro_mt) and Poultry farming (apro_ec). This last label covers statistics on hatcheries and on trade in chicks. The regional animal production statistics collected on livestock (agr_r_animal) and on cows’ milk production on farms (agr_r_milk_pr) are disseminated separately. Due to the change in the legal basis or in the methodology, the time series may be broken. This is indicated by a flag in the tables. The detailed content of each table and the reference to its legal definition is provided in the table below. Table 3.1: Data tables disseminated regarding animal production statistics
    • 5月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 26 6月, 2019
      データセットを選択
      The Credit to Agriculture dataset provides national data for over 100 countries on the amount of loans provided by the private/commercial banking sector to producers in agriculture, forestry and fisheries, including household producers, cooperatives, and agro-businesses. For some countries, the three sub sectors of agriculture, forestry, and fishing are completely specified. In other cases, complete dis aggregations are not available. The dataset also provides statistics on the total credit to all industries, indicators on the share of credit to agricultural producers, and an agriculture orientation index (the agriculture share of credit, over the agriculture share of GDP).
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 09 5月, 2019
      データセットを選択
      Crop statistics refer to the following types of annual data: area under cultivation, harvested production, yield,  humidity and main area for cereals and for other main field crops (mainly dried pulses, root crops, fodder and industrial crops);harvested area, harvested production and main area for vegetables ;production area, harvested production and main area for permanent crop.The data are provided at national level. For some products regional figures (NUTS 1 or 2) are available too. The areas  are expressed in 1 000 hectares,  the harvested quantities in 1 000 tonnes and the yields in t/ha. The production and yield data are available in EU standard humidity (apro_cpsh) and in national humidity (apro_cpnh). The information concerns more than 100 crop products. The earliest data are available from 1955 for cereals and from the early 1960's for fruits and vegetables. However, most Member States have started to send in data in the 1970's and 1980's. The statistical system has progressively improved and enlarged. The current Regulation (EC) No 543/2009 entered into force in January 2010. The annex was updated in 2015 through a Commission Delegated Regulation (EU) No 2015/1557. At present Eurostat receives and publishes harmonised statistical data from 28 Member States, form the EFTA countries and from the candidate and potential candidate countries broken down in: 17 categories and subcategories for cereals;29 categories and  subcategories for other main crops (mainly dry pulses and protein crops, root crops industrial crops and plants harvested green from arable land);40 categories and subcategories for vegetables;41 categories and subcategories for permanent crops;18 categories and subcategories for the Utilised Agricultural Area (UAA). For the full list of crops, please consult Annex. Some additional crops and transmission deadlines are covered by an ESS agreement on annual crop statistics. The main data sources are administrative records, surveys and expert estimates. National Statistical Institutes or Ministries of Agriculture are responsible for the national data collection in accordance with the Regulations and agreements in force. Eurostat is responsible for drawing the EU aggregations. Regional metadata Please note that for paragraphs where no metadata for regional data has been specified the regional metadata is identical to the metadata for the national data.
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 05 11月, 2019
      データセットを選択
      Crop statistics refer to the following types of annual data: area under cultivation, harvested production, yield,  humidity and main area for cereals and for other main field crops (mainly dried pulses, root crops, fodder and industrial crops);harvested area, harvested production and main area for vegetables ;production area, harvested production and main area for permanent crop.The data are provided at national level. For some products regional figures (NUTS 1 or 2) are available too. The areas  are expressed in 1 000 hectares,  the harvested quantities in 1 000 tonnes and the yields in t/ha. The production and yield data are available in EU standard humidity (apro_cpsh) and in national humidity (apro_cpnh). The information concerns more than 100 crop products. The earliest data are available from 1955 for cereals and from the early 1960's for fruits and vegetables. However, most Member States have started to send in data in the 1970's and 1980's. The statistical system has progressively improved and enlarged. The current Regulation (EC) No 543/2009 entered into force in January 2010. The annex was updated in 2015 through a Commission Delegated Regulation (EU) No 2015/1557. At present Eurostat receives and publishes harmonised statistical data from 28 Member States, form the EFTA countries and from the candidate and potential candidate countries broken down in: 17 categories and subcategories for cereals;29 categories and  subcategories for other main crops (mainly dry pulses and protein crops, root crops industrial crops and plants harvested green from arable land);40 categories and subcategories for vegetables;41 categories and subcategories for permanent crops;18 categories and subcategories for the Utilised Agricultural Area (UAA). For the full list of crops, please consult Annex. Some additional crops and transmission deadlines are covered by an ESS agreement on annual crop statistics. The main data sources are administrative records, surveys and expert estimates. National Statistical Institutes or Ministries of Agriculture are responsible for the national data collection in accordance with the Regulations and agreements in force. Eurostat is responsible for drawing the EU aggregations. Regional metadata Please note that for paragraphs where no metadata for regional data has been specified the regional metadata is identical to the metadata for the national data.
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 05 11月, 2019
      データセットを選択
      Crop statistics refer to the following types of annual data: area under cultivation, harvested production, yield,  humidity and main area for cereals and for other main field crops (mainly dried pulses, root crops, fodder and industrial crops);harvested area, harvested production and main area for vegetables ;production area, harvested production and main area for permanent crop.The data are provided at national level. For some products regional figures (NUTS 1 or 2) are available too. The areas  are expressed in 1 000 hectares,  the harvested quantities in 1 000 tonnes and the yields in t/ha. The production and yield data are available in EU standard humidity (apro_cpsh) and in national humidity (apro_cpnh). The information concerns more than 100 crop products. The earliest data are available from 1955 for cereals and from the early 1960's for fruits and vegetables. However, most Member States have started to send in data in the 1970's and 1980's. The statistical system has progressively improved and enlarged. The current Regulation (EC) No 543/2009 entered into force in January 2010. The annex was updated in 2015 through a Commission Delegated Regulation (EU) No 2015/1557. At present Eurostat receives and publishes harmonised statistical data from 28 Member States, form the EFTA countries and from the candidate and potential candidate countries broken down in: 17 categories and subcategories for cereals;29 categories and  subcategories for other main crops (mainly dry pulses and protein crops, root crops industrial crops and plants harvested green from arable land);40 categories and subcategories for vegetables;41 categories and subcategories for permanent crops;18 categories and subcategories for the Utilised Agricultural Area (UAA). For the full list of crops, please consult Annex. Some additional crops and transmission deadlines are covered by an ESS agreement on annual crop statistics. The main data sources are administrative records, surveys and expert estimates. National Statistical Institutes or Ministries of Agriculture are responsible for the national data collection in accordance with the Regulations and agreements in force. Eurostat is responsible for drawing the EU aggregations. Regional metadata Please note that for paragraphs where no metadata for regional data has been specified the regional metadata is identical to the metadata for the national data.
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 05 11月, 2019
      データセットを選択
      Crop statistics refer to the following types of annual data: area under cultivation, harvested production, yield,  humidity and main area for cereals and for other main field crops (mainly dried pulses, root crops, fodder and industrial crops);harvested area, harvested production and main area for vegetables ;production area, harvested production and main area for permanent crop.The data are provided at national level. For some products regional figures (NUTS 1 or 2) are available too. The areas  are expressed in 1 000 hectares,  the harvested quantities in 1 000 tonnes and the yields in t/ha. The production and yield data are available in EU standard humidity (apro_cpsh) and in national humidity (apro_cpnh). The information concerns more than 100 crop products. The earliest data are available from 1955 for cereals and from the early 1960's for fruits and vegetables. However, most Member States have started to send in data in the 1970's and 1980's. The statistical system has progressively improved and enlarged. The current Regulation (EC) No 543/2009 entered into force in January 2010. The annex was updated in 2015 through a Commission Delegated Regulation (EU) No 2015/1557. At present Eurostat receives and publishes harmonised statistical data from 28 Member States, form the EFTA countries and from the candidate and potential candidate countries broken down in: 17 categories and subcategories for cereals;29 categories and  subcategories for other main crops (mainly dry pulses and protein crops, root crops industrial crops and plants harvested green from arable land);40 categories and subcategories for vegetables;41 categories and subcategories for permanent crops;18 categories and subcategories for the Utilised Agricultural Area (UAA). For the full list of crops, please consult Annex. Some additional crops and transmission deadlines are covered by an ESS agreement on annual crop statistics. The main data sources are administrative records, surveys and expert estimates. National Statistical Institutes or Ministries of Agriculture are responsible for the national data collection in accordance with the Regulations and agreements in force. Eurostat is responsible for drawing the EU aggregations. Regional metadata Please note that for paragraphs where no metadata for regional data has been specified the regional metadata is identical to the metadata for the national data.
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 05 11月, 2019
      データセットを選択
      Crop statistics refer to the following types of annual data: area under cultivation, harvested production, yield,  humidity and main area for cereals and for other main field crops (mainly dried pulses, root crops, fodder and industrial crops);harvested area, harvested production and main area for vegetables ;production area, harvested production and main area for permanent crop.The data are provided at national level. For some products regional figures (NUTS 1 or 2) are available too. The areas  are expressed in 1 000 hectares,  the harvested quantities in 1 000 tonnes and the yields in t/ha. The production and yield data are available in EU standard humidity (apro_cpsh) and in national humidity (apro_cpnh). The information concerns more than 100 crop products. The earliest data are available from 1955 for cereals and from the early 1960's for fruits and vegetables. However, most Member States have started to send in data in the 1970's and 1980's. The statistical system has progressively improved and enlarged. The current Regulation (EC) No 543/2009 entered into force in January 2010. The annex was updated in 2015 through a Commission Delegated Regulation (EU) No 2015/1557. At present Eurostat receives and publishes harmonised statistical data from 28 Member States, form the EFTA countries and from the candidate and potential candidate countries broken down in: 17 categories and subcategories for cereals;29 categories and  subcategories for other main crops (mainly dry pulses and protein crops, root crops industrial crops and plants harvested green from arable land);40 categories and subcategories for vegetables;41 categories and subcategories for permanent crops;18 categories and subcategories for the Utilised Agricultural Area (UAA). For the full list of crops, please consult Annex. Some additional crops and transmission deadlines are covered by an ESS agreement on annual crop statistics. The main data sources are administrative records, surveys and expert estimates. National Statistical Institutes or Ministries of Agriculture are responsible for the national data collection in accordance with the Regulations and agreements in force. Eurostat is responsible for drawing the EU aggregations. Regional metadata Please note that for paragraphs where no metadata for regional data has been specified the regional metadata is identical to the metadata for the national data.
    • 2月 2018
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 2月, 2018
      データセットを選択
      Crop statistics refer to the following types of annual data:area under cultivation, harvested production, yield,  humidity and main area for cereals and for other main field crops (mainly dried pulses, root crops, fodder and industrial crops);harvested area, harvested production and main area for vegetables ;production area, harvested production and main area for permanent crop. The data are provided at national level. For some products regional figures (NUTS 1 or 2) are available too. The areas  are expressed in 1 000 hectares),  the harvested quantities in 1 000 tonnes and the yields in 100kg/ha. The information concerns more than 100 crop products. The earliest data are available from 1955 for cereals and from the early 1960's for fruits and vegetables. However, most Member States have started to send in data in the 1970's and 1980's. The statistical system has progressively improved and enlarged. The current Regulation (EC) No 543/2009 entered into force in January 2010. The annex was updated in 2015 through a Commission Delegated Regulation (EU) No 2015/1557. At present Eurostat receives and publishes harmonised statistical data from 28 Member States, form the EFTA countries and from the candidate and potential candidate countries broken down in:17 categories and subcategories for cereals;29 categories and  subcategories for other main crops (mainly dry pulses and protein crops, root crops industrial crops and plants harvested green from arable land);40 categories and subcategories for vegetables;41 categories and subcategories for permanent crops;18 categories and subcategories for the Utilised Agricultural Area (UAA). For the full list of crops, please consult Annex 1. Some additional crops and transmission deadlines are covered by an ESS agreement on annual crop statistics. The main data sources are administrative records, surveys and expert estimates. National Statistical Institutes or Ministries of Agriculture are responsible for the national data collection in accordance with the Regulations and agreements in force. Eurostat is responsible for drawing the EU aggregations. Regional metadata Please note that for paragraphs where no metadata for regional data has been specified the regional metadata is identical to the metadata for the national data.
    • 2月 2017
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 06 2月, 2017
      データセットを選択
    • 2月 2018
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 21 2月, 2018
      データセットを選択
    • 10月 2015
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 01 11月, 2015
      データセットを選択
      Crop statistics refer to the following types of annual data: area, production harvested and yield for cereals and for other main field crops (mainly dried pulses, root crops, fodder and industrial crops);area, production harvested and yield for a large number of fruits and vegetableshumidity of the harvested crop (humidity content in %)agricultural land use. The statistics provide, for a given product, the area, the yield and the production harvested during the crop year at national level. For some products regional figures (NUTS 1 or 2) are available too. The data refer to areas under cultivation (expressed in 1 000 hectares), the quantity harvested (expressed in 1 000 tonnes) and the yield (expressed in 100kg/ha). The information concerns more than 100 crop products. The earliest data are available from 1955 for cereals and from the early 1960's for fruits and vegetables. However most Member States have started to send in data in the 1970's and 1980's. The statistical system has progressively improved and enlarged. The current Regulation (EC) No 543/2009 entered into force in January 2010. It simplified the data collection and reduced the number of crop sub-classes. At present Eurostat receives and publishes harmonised statistical data from 28 Member States broken down in: 17 categories and subcategories for cereals;30 categories and  subcategories for other main crops (mainly Dried pulses, Root crops and Industrial crops);40 categories and subcategories for vegetables;41 categories and subcategories for fruits;18 categories and subcategories for UAA (Utilised Agricultural Area).For the full list of crops, please consult Annex 1 . Some data are available also for Iceland, Norway, Switzerland, Albania, Montenegro. Former Yugoslav Republic of Macedonia, Serbia, Kosovo (under United Nations Security Council Resolution 1244/99), Bosnia Herzegovina and Turkey as well. Some additional crops are covered bya Gentlemen's agreement. These data is provided on voluntary basis by the Member States. The list of crops collected under the gentlemen's agreements is included in Annex 1. The main data sources are administrative records, surveys and expert estimates. National Statistical Institutes or Ministries of Agriculture are responsible for the national data collection in accordance with EC Regulations. Eurostat is responsible for drawing the EU aggregations. Regional metadata Please note that for paragraphs where no metadata for regional data has been specified the regional metadata is identical to the metadata for the national data.
    • 11月 2017
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 01 12月, 2017
      データセットを選択
      Not applicable
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
      Data on causes of death (COD) provide information on mortality patterns and form a major element of public health information. COD data refer to the underlying cause which - according to the World Health Organisation (WHO) - is "the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury". Causes of death are classified by the 86 causes of the "European shortlist" of causes of death. This shortlist is based on the International Statistical Classification of Diseases and Related Health Problems (ICD). COD data are derived from death certificates. The medical certification of death is an obligation in all Member States. Countries code the information provided in the medical certificate of cause of death into ICD codes according to the rules specified in the ICD. Data are broken down by sex, 5-year age groups, cause of death and by residency and country of occurrence. For stillbirths and neonatal deaths additional breakdows might include age of mother. Data are available for EU-28, the former Yugoslav Republic of Macedonia, Albania, Iceland, Norway, Liechtenstein and Switzerland. Regional data (NUTS level 2) are available for most of the countries. Annual national data are provided in absolute number, crude death rates and standardised death rates. At regional level (NUTS level 2) the same is provided in form of 3 years averages. Annual crude death rates are also available at NUTS level 2.
    • 3月 2018
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 12 3月, 2018
      データセットを選択
      Data on marriages and divorces at national level are based on the annual demographic data collections in the field of demography carried out by Eurostat. The completeness of information depends on the availability of data reported by the National Statistical Institutes. The Joint demographic data collection is carried out in cooperation with United Nation Statistical Division (UNSD) in the summer of each year, having the deadline 15 September. During this data collection Eurostat collects from the national statistical institutes detailed data by sex, age and other characteristics for the demographic events (births, deaths, marriages and divorces) of the previous year and the population on 1 January of the current and previous years. More specifically, during year T the following data are collected and disseminated on fertility field: - total number of marriages and divorces - persons getting married during the reference year by previous legal marital status, year T-1 Data can be found under the section Marriages and divorces (demo_nup). The information is updated towards the end of each year based on information collected during the Joint data collection. Moreover, any update sent by the countries in-between data collections are validated, processed and uploaded into Eurostat's demographic database and in Eurostat's free dissemination online database as soon as possible. Aggregates are recalculated accordingly. The data transmitted by the National Statistical Institutes are validated by Eurostat, processed and uploaded into Eurostat's Demographic Database and in Eurostat's free dissemination online database. The data are also disseminated in several thematic and horizontal Eurostat's publications. Data are presented by single country and for aggregates of countries. For EU and Euro Area, only the current and the previous version of the aggregates are published. The currently disseminated aggregates are: EU-27, EU-25, EA-16, and EA-15. Moreover, data is disseminated for the European Economic Area (EEA) and the European Free Trade Association (EFTA). International marriages and divorces Statistics on the number of international marriages and divorces (2000-2007) were collected by Eurostat from national statistical institutes in September 2008. The data were further used by the European Commission for preparing  a proposal for a Council Regulation on the law applicable in divorce and legal separation.  These data collected are available upon request.
    • 3月 2018
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 12 3月, 2018
      データセットを選択
      Data on marriages and divorces at national level are based on the annual demographic data collections in the field of demography carried out by Eurostat. The completeness of information depends on the availability of data reported by the National Statistical Institutes. The Joint demographic data collection is carried out in cooperation with United Nation Statistical Division (UNSD) in the summer of each year, having the deadline 15 September. During this data collection Eurostat collects from the national statistical institutes detailed data by sex, age and other characteristics for the demographic events (births, deaths, marriages and divorces) of the previous year and the population on 1 January of the current and previous years. More specifically, during year T the following data are collected and disseminated on fertility field: - total number of marriages and divorces - persons getting married during the reference year by previous legal marital status, year T-1 Data can be found under the section Marriages and divorces (demo_nup). The information is updated towards the end of each year based on information collected during the Joint data collection. Moreover, any update sent by the countries in-between data collections are validated, processed and uploaded into Eurostat's demographic database and in Eurostat's free dissemination online database as soon as possible. Aggregates are recalculated accordingly. The data transmitted by the National Statistical Institutes are validated by Eurostat, processed and uploaded into Eurostat's Demographic Database and in Eurostat's free dissemination online database. The data are also disseminated in several thematic and horizontal Eurostat's publications. Data are presented by single country and for aggregates of countries. For EU and Euro Area, only the current and the previous version of the aggregates are published. The currently disseminated aggregates are: EU-27, EU-25, EA-16, and EA-15. Moreover, data is disseminated for the European Economic Area (EEA) and the European Free Trade Association (EFTA). International marriages and divorces Statistics on the number of international marriages and divorces (2000-2007) were collected by Eurostat from national statistical institutes in September 2008. The data were further used by the European Commission for preparing  a proposal for a Council Regulation on the law applicable in divorce and legal separation.  These data collected are available upon request.
    • 8月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 17 8月, 2019
      データセットを選択
      Data on marriages and divorces at national level are transmitted by the National Statistics Institutes on voluntary basis in the context of the annual demographic data collections in the field of demography carried out by Eurostat as follows:
    • 3月 2017
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 30 3月, 2017
      データセットを選択
      These metadata refer to the annual population data under Population / Demography domain in Eurostat's Dissemination data tree. Eurostat carries on annual demography data collections with the aim of collecting from the National Statistical Institutes detailed data on population, vital events, marriages and divorces. These data are validated, processed and disseminated. Further on, Eurostat uses the collected detailed data to compute and disseminate demographic indicators at country level, at regional level and at EU level, by applying harmonized methods of calculation. The demography data collections are done on voluntary basis and the completeness of information depends on the availability of data reported by the National Statistical Institutes. The first demography data collection of each year, named Rapid, is carried out in April-May (deadline 15 May). Within this data collection the first results on the main demographic developments in the previous year (T-1) and the population on 1st January of the current year (T) are collected from the National Statistical Institutes. A second annual data collection, Joint Demography data collection, is carried out in cooperation with United Nation Statistical Division (UNSD) in the summer of each year, having the deadline 15 September. Within this data collection Eurostat collects from the National Statistical Institutes detailed data on the demographic events (births, deaths, marriages and divorces) of the previous year (T-1) and the population on 1st January of the current year (T), broken down by sex, age and other characteristics. The Nowcast Demography data collection is carried out in October-November (deadline 15 November). The monthly time series on births, deaths, immigrants and emigrants available from the beginning of current year (T) are collected, with the purpose of producing by the end of the current year (T) a forecast on 1st January population of the following year (T+1). The Regional Demography data collection is carried out in November-December (deadline 15 December). It is based on the regional breakdown of the countries agreed at EU level using the latest version of the Nomenclature of Territorial Units for Statistics (NUTS) and of the Statistical regions for the EFTA and Candidate countries. Within this data collection Eurostat collects from the National Statistical Institutes data by NUTS level 1, 2 and 3 for the vital events taking place in the previous year (T-1) and the population figures on 1st January of the current year (T). Any updates sent by the National Statistical Institutes in-between data collections are validated, processed and disseminated in Eurostat's online database as soon as possible. The European aggregates and the demographic indicators are updated accordingly. Please note:The tables presenting population on 1 January figures by various breakdowns may display variations in the total population for some countries at a given moment in time. This may occur due to one of the following reasons: - The timing of the transmission to Eurostat of the population data for various breakdown may lead to different population on 1 January figures displayed in different population tables at a given moment in time. - The transmission to Eurostat of the post-census population revisions (following the 2011 population Censuses) is expected to be done by the national statistical offices gradually for the population breakdowns. The time series of populations between the previous census taking place in the country and 2011 will be revised by end 2013 by some of the countries, taking into account Eurostat’s recommendation. The following countries have transmitted to Eurostat post-2011 Census population revisions, broken down by age and sex, by autumn of 2013, which are reflected in the tables ‘Demographic balance and crude rates (demo_gind)’, ‘Population on 1 January by age and sex (demo_pjan)’, ‘Population on 1 January by five years age groups and sex (demo_pjangroup)’ and ‘Population on 1 January by broad age group and sex (demo_pjanbroad)’: BG 2007-2011; CZ 2001-2011; EE 2000-2011; IE 2007-2011; EL 2011; ES 2002-2011; HR 2001-2011; CY 2003-2011; LV 2001-2011; LT 2001-2011; MT 2006-2011; AT 2008-2011; PT 1992-2011; RO 2002-2011; SK 2002-2011; UK 2002-2011 (not including post-2011 Census data for Scotland); ME 2010-2011; RS 2011. As regards the the population data for the year 2012 and after, for most of the countries these take into account the results of the latest population census (held in 2011). IT 2012-2013 and DE 2012-2013 reported only the total post-2011 Census populations which are published in the table ‘Demographic balance and crude rates (demo_gind)’. The breakdown by age and sex will follow later on. - The succession of the annual demography data collections described above, which collect and update population breakdowns at different moment during the calendar year. - The calendar of the national statistical offices for producing and releasing population broken down by various topics, respectively the timings when data are transmitted to Eurostat. The most updated data on total population on 1st January and on the total number of live births and deaths may be found in the table 'Demographic balance and crude rates (demo_gind)' of the online 'Database by theme'. This table includes the latest updates (or revised data) on total population, births and deaths reported by the countries, while the detailed breakdowns by various characteristics included in the rest of the tables of the Demography domain (and also for Population by citizenship and by country of birth) may be transmitted to Eurostat at a subsequent date.
    • 3月 2018
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 12 3月, 2018
      データセットを選択
      Generally speaking, a crude rate is calculated as the ratio of the number of events to the average population of the respective area in a given year. For easier presentation, it is multiplied by 1 000; the result is therefore expressed per 1 000 persons (of the average population). In this particular case, the crude rate of net migration plus adjustment is defined as the ratio of net migration plus adjustment during the year to the average population in that year, expressed per 1 000 inhabitants. The net migration plus adjustment is the difference between the total change and the natural change of the population.
    • 3月 2017
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 30 3月, 2017
      データセットを選択
      These metadata refer to the annual population data under Population / Demography domain in Eurostat's Dissemination data tree. Eurostat carries on annual demography data collections with the aim of collecting from the National Statistical Institutes detailed data on population, vital events, marriages and divorces. These data are validated, processed and disseminated. Further on, Eurostat uses the collected detailed data to compute and disseminate demographic indicators at country level, at regional level and at EU level, by applying harmonized methods of calculation. The demography data collections are done on voluntary basis and the completeness of information depends on the availability of data reported by the National Statistical Institutes. The first demography data collection of each year, named Rapid, is carried out in April-May (deadline 15 May). Within this data collection the first results on the main demographic developments in the previous year (T-1) and the population on 1st January of the current year (T) are collected from the National Statistical Institutes. A second annual data collection, Joint Demography data collection, is carried out in cooperation with United Nation Statistical Division (UNSD) in the summer of each year, having the deadline 15 September. Within this data collection Eurostat collects from the National Statistical Institutes detailed data on the demographic events (births, deaths, marriages and divorces) of the previous year (T-1) and the population on 1st January of the current year (T), broken down by sex, age and other characteristics. The Nowcast Demography data collection is carried out in October-November (deadline 15 November). The monthly time series on births, deaths, immigrants and emigrants available from the beginning of current year (T) are collected, with the purpose of producing by the end of the current year (T) a forecast on 1st January population of the following year (T+1). The Regional Demography data collection is carried out in November-December (deadline 15 December). It is based on the regional breakdown of the countries agreed at EU level using the latest version of the Nomenclature of Territorial Units for Statistics (NUTS) and of the Statistical regions for the EFTA and Candidate countries. Within this data collection Eurostat collects from the National Statistical Institutes data by NUTS level 1, 2 and 3 for the vital events taking place in the previous year (T-1) and the population figures on 1st January of the current year (T). Any updates sent by the National Statistical Institutes in-between data collections are validated, processed and disseminated in Eurostat's online database as soon as possible. The European aggregates and the demographic indicators are updated accordingly. Please note:The tables presenting population on 1 January figures by various breakdowns may display variations in the total population for some countries at a given moment in time. This may occur due to one of the following reasons: - The timing of the transmission to Eurostat of the population data for various breakdown may lead to different population on 1 January figures displayed in different population tables at a given moment in time. - The transmission to Eurostat of the post-census population revisions (following the 2011 population Censuses) is expected to be done by the national statistical offices gradually for the population breakdowns. The time series of populations between the previous census taking place in the country and 2011 will be revised by end 2013 by some of the countries, taking into account Eurostat’s recommendation. The following countries have transmitted to Eurostat post-2011 Census population revisions, broken down by age and sex, by autumn of 2013, which are reflected in the tables ‘Demographic balance and crude rates (demo_gind)’, ‘Population on 1 January by age and sex (demo_pjan)’, ‘Population on 1 January by five years age groups and sex (demo_pjangroup)’ and ‘Population on 1 January by broad age group and sex (demo_pjanbroad)’: BG 2007-2011; CZ 2001-2011; EE 2000-2011; IE 2007-2011; EL 2011; ES 2002-2011; HR 2001-2011; CY 2003-2011; LV 2001-2011; LT 2001-2011; MT 2006-2011; AT 2008-2011; PT 1992-2011; RO 2002-2011; SK 2002-2011; UK 2002-2011 (not including post-2011 Census data for Scotland); ME 2010-2011; RS 2011. As regards the the population data for the year 2012 and after, for most of the countries these take into account the results of the latest population census (held in 2011). IT 2012-2013 and DE 2012-2013 reported only the total post-2011 Census populations which are published in the table ‘Demographic balance and crude rates (demo_gind)’. The breakdown by age and sex will follow later on. - The succession of the annual demography data collections described above, which collect and update population breakdowns at different moment during the calendar year. - The calendar of the national statistical offices for producing and releasing population broken down by various topics, respectively the timings when data are transmitted to Eurostat. The most updated data on total population on 1st January and on the total number of live births and deaths may be found in the table 'Demographic balance and crude rates (demo_gind)' of the online 'Database by theme'. This table includes the latest updates (or revised data) on total population, births and deaths reported by the countries, while the detailed breakdowns by various characteristics included in the rest of the tables of the Demography domain (and also for Population by citizenship and by country of birth) may be transmitted to Eurostat at a subsequent date.
    • 7月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 16 10月, 2019
      データセットを選択
      GHG emissions data from the cultivation of organic soils are those associated with nitrous oxide gas from organic soils under cropland (item: Cropland organic soils) and grassland (item: Grassland organic soils). The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, region and special groups, with global coverage, relative to the period 1990-present (with annual updates) and with projections for 2030 and 2050, expressed both as Gg N2O and Gg CO2eq, by cropland, grassland and by their aggregation. Implied emission factor for N2O as well activity data (areas) are also provided.
    • 8月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 27 8月, 2019
      データセットを選択
      Hospital beds provide information on health care capacities, i.e. on the maximum number of patients who can be treated by hospitals. Curative care (or acute care) beds in hospitals are beds that are available for curative care. These beds are a subgroup of total hospital beds which are defined as all hospital beds which are regularly maintained and staffed and immediately available for the care of admitted patients; both occupied and unoccupied beds are covered. Hospitals are defined according to the classification of health care providers of the System of Health Accounts (SHA); all public and private hospitals should be covered.
    • 6月 2019
      ソース: United Nations Conference on Trade and Development
      アップロード者: Sandeep Reddy
      以下でアクセス: 11 6月, 2019
      データセットを選択
      This table shows exchange rates for currencies used in over 190 world economies presented in a cross rates layout where countries are presented in both rows and columns. National currency per US dollars exchange rates are used to derive explicit exchange rates for each of the countries presented with regard to any other country. Country series are consistent over time: for example, a conversion was made from national currency to Euro for the Euro Zone economies for all years prior to the adoption of Euro.
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 08 11月, 2019
      データセットを選択
      The Balance of Payments (BoP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of a geographical region during a given period. The Balance of payments provides harmonized information on international transactions which are part of the current account (goods, services, income, current transfers), but also on transactions which fall in the capital and the financial account. BoP is an important macro-economic indicator used to assess the position of an economy (of credit or debit) towards the external world. Data on International Trade in Services, a component of BoP current account, and data on Foreign Direct Investment, a component of BoP financial account, are used to monitor the external commercial performance of different economies. Outward Foreign Affiliates Statistics (FATS) measure the commercial presence, as defined by the General Agreement on Trade in Services (GATS), through affiliates in foreign markets. Balance of Payments data are used for calculation of indicators needed for monitoring of macroenomic imbalances such as share of main BoP and International Investment Position (IIP) items in GDP and export market shares calculated as the EU Member States' shares in total world exports.  Out of BoP data, some indicators of EU market integration are also derived. Data are in millions of Euro/ECU or in millions of national currency. Balance of Payments data coverage varies according to the collection. Some collections refer only to Euro area or EU countries, while some others' coverage includes also EU partner countries.   Several statistical adjustments are applied to the original data provided by the Member States. These are described in the International Trade in Services EU 1992-2001 - Compilation guide 2003. The International Monetary Fund Balance of Payments Manual (BPM5) classification is used for the compilation of the BoP. The BoP data are collected through national surveys and administrative sources.    More information on BoP is available for each specific collection: Quarterly BoP, ITS, FDI, Outward FATS, BoP of EU Institutions.
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 08 11月, 2019
      データセットを選択
      The balance of payments is a record of a country's international transactions with the rest of the world. It is composed of the current account and the capital and financial account. The current account is itself subdivided into goods, services, income and current transfers; it registers the value of exports (credits) and imports (debits). The difference between these two values is the "balance".
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 08 11月, 2019
      データセットを選択
      The balance of payments is a record of a country's international transactions with the rest of the world. The balance of payments is composed of two broad sub-balances: the current account and the capital and financial account. The current account is itself subdivided into four basic components: goods, services, income and current transfers. For each of these items, the current account registers the value of exports (credits) and imports (debits). The difference between these two values is the "balance".
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 08 11月, 2019
      データセットを選択
      The balance of payments is a record of a country's international transactions with the rest of the world. The balance of payments is composed by two broad sub-balances: the current account and the capital and financial account. The current account is itself subdivided into four basic components: goods, services, income and current transfers. For each of these items, the current account registers the value of exports (credits) and imports (debits). The difference between these two values is the balance.
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 08 11月, 2019
      データセットを選択
      The balance of payments is a record of a country's international transactions with the rest of the world. It is composed of the current account and the capital and financial account. The current account is itself subdivided into goods, services, income and current transfers; it registers the value of exports (credits) and imports (debits). The difference between these two values is the "balance".
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 08 11月, 2019
      データセットを選択
      The balance of payments is a record of a country's international transactions with the rest of the world. It is composed of the current account and the capital and financial account. The current account is itself subdivided into goods, services, income and current transfers; it registers the value of exports (credits) and imports (debits). The difference between these two values is the "balance".
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 01 11月, 2019
      データセットを選択
      Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published:as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)
  • D
    • 3月 2019
      ソース: Statistics Denmark
      アップロード者: Knoema
      以下でアクセス: 10 4月, 2019
      データセットを選択
    • 6月 2018
      ソース: Bank of Canada
      アップロード者: Knoema
      以下でアクセス: 18 6月, 2019
      データセットを選択
      The Bank of Canada’s Credit Rating Assessment Group (CRAG) comprehensive database of sovereign defaults draws on previously published data sets compiled by various official and private sector sources. It combines elements of these, together with new information, to develop estimates of stocks of government obligations in default, including bonds and other marketable securities, bank loans, and official loans in default, valued in U.S. dollars, for the years 1960 to 2016 on both a country-by-country and a global basis. This update of CRAG’s database, and subsequent updates, will be useful to researchers analyzing the economic and financial effects of individual sovereign defaults and, importantly, the impact on global financial stability of episodes involving multiple sovereign defaults.
    • 3月 2016
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 21 11月, 2018
      データセットを選択
      To view the original national data please open the questionnaires. Source: Joint Forest Europe / UNECE / FAO Questionnaire on Pan-European Indicators for Sustainable Forest Management. Country: Russian Federation The source of the data of Russian Federation is the National Report for the Joint Forest Europe / UNECE / FAO reporting on quantitative pan-European indicators 2011.
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Death rate of a population adjusted to a standard age distribution. As most causes of death vary significantly with people's age and sex, the use of standardised death rates improves comparability over time and between countries, as they aim at measuring death rates independently of different age structures of populations. The standardised death rates used here are calculated on the basis of a standard European population (defined by the World Health Organization). Detailed data for 65 causes of death are available in the database (under the heading 'Data').
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Death rate of a population adjusted to a standard age distribution. As most causes of death vary significantly with people's age and sex, the use of standardised death rates improves comparability over time and between countries, as they aim at measuring death rates independently of different age structures of populations. The standardised death rates used here are calculated on the basis of a standard European population (defined by the World Health Organization). Detailed data for 65 causes of death are available in the database (under the heading 'Data').
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Death rate of a population adjusted to a standard age distribution. As most causes of death vary significantly with people's age and sex, the use of standardised death rates improves comparability over time and between countries, as they aim at measuring death rates independently of different age structures of populations. The standardised death rates used here are calculated on the basis of a standard European population (defined by the World Health Organization). Detailed data for 65 causes of death are available in the database (under the heading 'Data').
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Death rate of a population adjusted to a standard age distribution. As most causes of death vary significantly with people's age and sex, the use of standardised death rates improves comparability over time and between countries, as they aim at measuring death rates independently of different age structures of populations. The standardised death rates used here are calculated on the basis of a standard European population (defined by the World Health Organization). Detailed data for 65 causes of death are available in the database (under the heading 'Data').
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Death rate of a population adjusted to a standard age distribution. As most causes of death vary significantly with people's age and sex, the use of standardised death rates improves comparability over time and between countries, as they aim at measuring death rates independently of different age structures of populations. The standardised death rates used here are calculated on the basis of a standard European population (defined by the World Health Organization). Detailed data for 65 causes of death are available in the database (under the heading 'Data').
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Death rate of a population adjusted to a standard age distribution. As most causes of death vary significantly with people's age and sex, the use of standardised death rates improves comparability over time and between countries, as they aim at measuring death rates independently of different age structures of populations. The standardised death rates used here are calculated on the basis of a standard European population (defined by the World Health Organization). Detailed data for 65 causes of death are available in the database (under the heading 'Data').
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Death rate of a population adjusted to a standard age distribution. As most causes of death vary significantly with people's age and sex, the use of standardised death rates improves comparability over time and between countries, as they aim at measuring death rates independently of different age structures of populations. The standardised death rates used here are calculated on the basis of a standard European population (defined by the World Health Organization). Detailed data for 65 causes of death are available in the database (under the heading 'Data').
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Death rate of a population adjusted to a standard age distribution. As most causes of death vary significantly with people's age and sex, the use of standardised death rates improves comparability over time and between countries, as they aim at measuring death rates independently of different age structures of populations. The standardised death rates used here are calculated on the basis of a standard European population (defined by the World Health Organization). Detailed data for 65 causes of death are available in the database (under the heading 'Data').
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Death rate of a population adjusted to a standard age distribution. As most causes of death vary significantly with people's age and sex, the use of standardised death rates improves comparability over time and between countries, as they aim at measuring death rates independently of different age structures of populations. The standardised death rates used here are calculated on the basis of a standard European population (defined by the World Health Organization). Detailed data for 65 causes of death are available in the database (under the heading 'Data').
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 21 9月, 2019
      データセットを選択
      Death rate of a population adjusted to a standard age distribution. As most causes of death vary significantly with people's age and sex, the use of standardised death rates improves comparability over time and between countries, as they aim at measuring death rates independently of different age structures of populations. The standardised death rates used here are calculated on the basis of a standard European population (defined by the World Health Organization). Detailed data for 65 causes of death are available in the database (under the heading 'Data').
    • 5月 2018
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 21 11月, 2018
      データセットを選択
      .. - data not available Source: UNECE Statistical Division Database, compiled from national and international (WHO European health for all database) official sources. Definitions: The (age-) standardized death rate (SDR) is a weighted average of age-specific mortality rates per 100 000 population. The weighting factor is the age distribution of a standard reference population. The standard reference population used is the European standard population as defined by the World Health Organisation (WHO). As method for standardisation, the direct method is applied. As most causes of death vary significantly with age and sex, the use of standardised death rates improves comparability over time and between countries. Death refers to the permanent disappearance of all evidence of life at any time after a live birth has taken place (post-natal cessation of vital functions without capability of resuscitation). This definition therefore excludes foetal deaths. Causes of death (CoD) are all diseases, morbid conditions or injuries that either resulted in or contributed to death, and the circumstances of the accident or violence that produced any such injuries. Symptoms or modes of dying, such as heart failure or asthenia, are not considered to be causes of death for vital statistics purposes. General note:: Diseases and external causes of death are coded differently in different versions of the International Classification of Diseases (ICD). For many diseases it is not possible to identify codes in different classification systems that would correspond precisely to the same disease or groups of diseases. Often the change in the trend of a certain cause-specific mortality rate may be the result of a changing ICD version or national death certification and coding practices, rather than an actual change in the mortality. It should be noted that mortality rates for some countries may be biased due to the under-registration of death cases. The basic principle of selection of the 17 CoD for presentation in the UNECE Gender Database is to include one main SDR for each of the ICD chapters and also to focus on some of the leading CoD across the European Region and some specific causes with high gender differences. ICD versionCountries9.3 - ICD-9 3-digit codes Albania, The former Yugoslav Republic of Macedonia 9.4 - ICD-9 4-digit or mixture of 3- and 4-digit codesGreece9.5 - ICD-9 BTL codes (in most countries actually original ICD-9 codes were used but the data later were converted by WHO into BTL codes) Bosnia and Herzegovina10.1 - ICD-10 mortality tabulation condensed list No1 (103 causes) Armenia, Azerbaijan, Belarus, Kazakhstan, Russian Federation, Ukraine10.3 - ICD-10 3-digit codes Belgium, Bulgaria, Estonia, Georgia, Latvia, Montenegro, Serbia, Slovakia, Slovenia, Uzbekistan10.4 - ICD-10 4-digit or mixture of 3- and 4-digit codes Austria, Canada, Croatia, Cyprus, Czech Republic, Denmark, Finland, France, Germany, Hungary, Iceland, Ireland, Israel, Italy, Kyrgyzstan, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Republic of Moldova, Romania, Spain, Sweden, Switzerland, United Kingdom, United States 1.75 - Special tabulation list of 175 causes used in some ex-USSR countries Tajikistan, Turkmenistan Link to International Classification of Diseases 10th Revision Country: Canada Data on accidents include sequelae of transport and other accidents. Data on transport accidents include sequelae of transport accidents. Data on suicide and intentional self-harm include sequelae of intentional self-harm. Country: United States Data on accidents include sequelae of transport and other accidents. Data on transport accidents include sequelae of transport accidents.
    • 3月 2018
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 12 3月, 2018
      データセットを選択
      20.1. Source data
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 26 9月, 2019
      データセットを選択
      This indicator is defined as the standardised death rate of certain chronic diseases for persons aged less than 65 years, by sex. The following diseases have been considered: malignant neoplasms, diabetes mellitus, ischaemic heart diseases, cerebrovascular diseases, chronic lower respiratory diseases, and chronic liver diseases. As the incidence of chronic diseases varies significantly with age and sex, the indicator is expressed using age-standardised rates which improve comparability over time and between countries, as they adjust raw incidence rates according to a standard European age structure.
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 26 9月, 2019
      データセットを選択
      Death rate of a population adjusted to a standard age distribution. As most causes of death vary significantly with people's age and sex, the use of standardised death rates improves comparability over time and between countries, as they aim at measuring death rates independently of different age structures of populations. The standardised death rates used here are calculated on the basis of a standard European population (defined by the World Health Organization). Detailed data for 65 causes of death are available in the database (under the heading 'Data').
    • 9月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 26 9月, 2019
      データセットを選択
      number per 100 000 personsThe indicator measures the standardised death rate of selected communicable diseases. The rate is calculated by dividing the number of people dying due to tuberculosis, HIV and hepatitis by the total population. This value is then weighted with the European Standard Population.The data are presented as standardised death rates, meaning they are adjusted to a standard age distribution in order to measure death rates independently of different age structures of populations. This approach improves comparability over time and between countries. The standardised death rates used here are calculated on the basis of a standard European population.
    • 4月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 06 4月, 2019
      データセットを選択
      Eurostat statistics on mortality are based on the annual demographic data collection in the field of demography carried out by Eurostat. The completeness of information depends on the availability of data reported by the National Statistical Institutes. The first demographic data collection of each year (T), named Rapid, is carried out in April-May (deadline 15 May of year T); during this data collection the first results on the main demographic developments in the previous year (T-1) and the population on 1 January of the current year (T) are collected from the National Statistical Institutes. The Joint demographic data collection is carried out in cooperation with United Nation Statistical Division (UNSD) in the summer of each year, having the deadline 15 September. During this data collection Eurostat collects from the National Statistical Institutes detailed data by sex, age and other characteristics for the demographic events (births, deaths, marriages and divorces) of the previous year and the population on 1 January of the current and previous years. The Nowcast demographic data collection is carried out in October-November (deadline 15 November of year T). The monthly time series on births, deaths, immigrants and emigrants available from the beginning of current year (T) are collected, with the purpose of producing a forecast on 1 January population of the following year (T+1). More specifically, during year T the following data are collected and disseminated on mortality field: - Total number of deaths in year (T-1) - Infant mortality by age and sex (T-1) - Late foetal deaths by mother's age (T-1) - Deaths by age, year of birth and sex (T-1) - Deaths by age, sex and educational attainment (ISCED 1997) - Deaths by month, year (T) and (T-1) Based on these information, Eurostat currently computes and disseminates the following mortality indicators: - Crude death rate - Infant mortality rate - Neonatal mortality rate - Early neonatal mortality rate - Late foetal mortality rate - Perinatal mortality rate - Life table - Life expectancy by age and sex - Life expectancy by age, sex and educational attainment (ISCED 1997)  The most recent (aggregated) data on the number of deaths can be found under the Main demographic indicators. This includes also the most recent Eurostat now casts on the main demographic indicators (population, births, deaths and net migration including statistical adjustment). In principle, the table containing the main demographic indicators is updated three times per year, after each of the national data collections. Detailed information on mortality (by age, sex, etc.) can be found under the section Mortality (demo_mor). These disaggregated information are updated towards the end of each year based on information collected during the Joint data collection. Moreover, any update sent by the countries in-between data collections are validated, processed and uploaded into Eurostat's demographic database and in Eurostat's free dissemination online database as soon as possible. The geographical aggregates are recalculated accordingly. The data transmitted by the National Statistical Institutes are validated by Eurostat, processed and uploaded into Eurostat's Demographic Database and in Eurostat's free dissemination online database. The data are also disseminated in several thematic and horizontal Eurostat's publications. Data are presented at national level and for aggregates of countries. For EU and Euro Area, only the current and the previous geographical status are published. The currently disseminated geographical aggregates are: EU-27, EU-25, EA-16, and EA-15. Moreover, data is disseminated for the European Economic Area (EEA) and the European Free Trade Association (EFTA).
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 18 10月, 2019
      データセットを選択
    • 6月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 19 6月, 2019
      データセットを選択
      The source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 07 11月, 2019
      データセットを選択
      number - per 1 000 personsDeath means the permanent disappearance of all evidence of life at any time after life birth has taken place (postnatal cessation of vital functions without capability of resuscitation).The crude death rate is the ratio of the number of deaths during the year to the average population in that year. The value is expressed per 1 000 persons.
    • 5月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 24 5月, 2019
      データセットを選択
      Eurostat statistics on mortality are based on the annual demographic data collection in the field of demography carried out by Eurostat. The completeness of information depends on the availability of data reported by the National Statistical Institutes. The first demographic data collection of each year (T), named Rapid, is carried out in April-May (deadline 15 May of year T); during this data collection the first results on the main demographic developments in the previous year (T-1) and the population on 1 January of the current year (T) are collected from the National Statistical Institutes. The Joint demographic data collection is carried out in cooperation with United Nation Statistical Division (UNSD) in the summer of each year, having the deadline 15 September. During this data collection Eurostat collects from the National Statistical Institutes detailed data by sex, age and other characteristics for the demographic events (births, deaths, marriages and divorces) of the previous year and the population on 1 January of the current and previous years. The Nowcast demographic data collection is carried out in October-November (deadline 15 November of year T). The monthly time series on births, deaths, immigrants and emigrants available from the beginning of current year (T) are collected, with the purpose of producing a forecast on 1 January population of the following year (T+1). More specifically, during year T the following data are collected and disseminated on mortality field: - Total number of deaths in year (T-1) - Infant mortality by age and sex (T-1) - Late foetal deaths by mother's age (T-1) - Deaths by age, year of birth and sex (T-1) - Deaths by age, sex and educational attainment (ISCED 1997) - Deaths by month, year (T) and (T-1) Based on these information, Eurostat currently computes and disseminates the following mortality indicators: - Crude death rate - Infant mortality rate - Neonatal mortality rate - Early neonatal mortality rate - Late foetal mortality rate - Perinatal mortality rate - Life table - Life expectancy by age and sex - Life expectancy by age, sex and educational attainment (ISCED 1997)  The most recent (aggregated) data on the number of deaths can be found under the Main demographic indicators. This includes also the most recent Eurostat now casts on the main demographic indicators (population, births, deaths and net migration including statistical adjustment). In principle, the table containing the main demographic indicators is updated three times per year, after each of the national data collections. Detailed information on mortality (by age, sex, etc.) can be found under the section Mortality (demo_mor). These disaggregated information are updated towards the end of each year based on information collected during the Joint data collection. Moreover, any update sent by the countries in-between data collections are validated, processed and uploaded into Eurostat's demographic database and in Eurostat's free dissemination online database as soon as possible. The geographical aggregates are recalculated accordingly. The data transmitted by the National Statistical Institutes are validated by Eurostat, processed and uploaded into Eurostat's Demographic Database and in Eurostat's free dissemination online database. The data are also disseminated in several thematic and horizontal Eurostat's publications. Data are presented at national level and for aggregates of countries. For EU and Euro Area, only the current and the previous geographical status are published. The currently disseminated geographical aggregates are: EU-27, EU-25, EA-16, and EA-15. Moreover, data is disseminated for the European Economic Area (EEA) and the European Free Trade Association (EFTA).
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 25 10月, 2019
      データセットを選択
    • 4月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 14 5月, 2019
      データセットを選択
      Eurostat statistics on mortality are based on the annual demographic data collection in the field of demography carried out by Eurostat. The completeness of information depends on the availability of data reported by the National Statistical Institutes. The first demographic data collection of each year (T), named Rapid, is carried out in April-May (deadline 15 May of year T); during this data collection the first results on the main demographic developments in the previous year (T-1) and the population on 1 January of the current year (T) are collected from the National Statistical Institutes. The Joint demographic data collection is carried out in cooperation with United Nation Statistical Division (UNSD) in the summer of each year, having the deadline 15 September. During this data collection Eurostat collects from the National Statistical Institutes detailed data by sex, age and other characteristics for the demographic events (births, deaths, marriages and divorces) of the previous year and the population on 1 January of the current and previous years. The Nowcast demographic data collection is carried out in October-November (deadline 15 November of year T). The monthly time series on births, deaths, immigrants and emigrants available from the beginning of current year (T) are collected, with the purpose of producing a forecast on 1 January population of the following year (T+1). More specifically, during year T the following data are collected and disseminated on mortality field: - Total number of deaths in year (T-1) - Infant mortality by age and sex (T-1) - Late foetal deaths by mother's age (T-1) - Deaths by age, year of birth and sex (T-1) - Deaths by age, sex and educational attainment (ISCED 1997) - Deaths by month, year (T) and (T-1) Based on these information, Eurostat currently computes and disseminates the following mortality indicators: - Crude death rate - Infant mortality rate - Neonatal mortality rate - Early neonatal mortality rate - Late foetal mortality rate - Perinatal mortality rate - Life table - Life expectancy by age and sex - Life expectancy by age, sex and educational attainment (ISCED 1997)  The most recent (aggregated) data on the number of deaths can be found under the Main demographic indicators. This includes also the most recent Eurostat now casts on the main demographic indicators (population, births, deaths and net migration including statistical adjustment). In principle, the table containing the main demographic indicators is updated three times per year, after each of the national data collections. Detailed information on mortality (by age, sex, etc.) can be found under the section Mortality (demo_mor). These disaggregated information are updated towards the end of each year based on information collected during the Joint data collection. Moreover, any update sent by the countries in-between data collections are validated, processed and uploaded into Eurostat's demographic database and in Eurostat's free dissemination online database as soon as possible. The geographical aggregates are recalculated accordingly. The data transmitted by the National Statistical Institutes are validated by Eurostat, processed and uploaded into Eurostat's Demographic Database and in Eurostat's free dissemination online database. The data are also disseminated in several thematic and horizontal Eurostat's publications. Data are presented at national level and for aggregates of countries. For EU and Euro Area, only the current and the previous geographical status are published. The currently disseminated geographical aggregates are: EU-27, EU-25, EA-16, and EA-15. Moreover, data is disseminated for the European Economic Area (EEA) and the European Free Trade Association (EFTA).
    • 4月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 16 4月, 2019
      データセットを選択
      Eurostat statistics on mortality are based on the annual demographic data collection in the field of demography carried out by Eurostat. The completeness of information depends on the availability of data reported by the National Statistical Institutes. The first demographic data collection of each year (T), named Rapid, is carried out in April-May (deadline 15 May of year T); during this data collection the first results on the main demographic developments in the previous year (T-1) and the population on 1 January of the current year (T) are collected from the National Statistical Institutes. The Joint demographic data collection is carried out in cooperation with United Nation Statistical Division (UNSD) in the summer of each year, having the deadline 15 September. During this data collection Eurostat collects from the National Statistical Institutes detailed data by sex, age and other characteristics for the demographic events (births, deaths, marriages and divorces) of the previous year and the population on 1 January of the current and previous years. The Nowcast demographic data collection is carried out in October-November (deadline 15 November of year T). The monthly time series on births, deaths, immigrants and emigrants available from the beginning of current year (T) are collected, with the purpose of producing a forecast on 1 January population of the following year (T+1). More specifically, during year T the following data are collected and disseminated on mortality field: - Total number of deaths in year (T-1) - Infant mortality by age and sex (T-1) - Late foetal deaths by mother's age (T-1) - Deaths by age, year of birth and sex (T-1) - Deaths by age, sex and educational attainment (ISCED 1997) - Deaths by month, year (T) and (T-1) Based on these information, Eurostat currently computes and disseminates the following mortality indicators: - Crude death rate - Infant mortality rate - Neonatal mortality rate - Early neonatal mortality rate - Late foetal mortality rate - Perinatal mortality rate - Life table - Life expectancy by age and sex - Life expectancy by age, sex and educational attainment (ISCED 1997)  The most recent (aggregated) data on the number of deaths can be found under the Main demographic indicators. This includes also the most recent Eurostat now casts on the main demographic indicators (population, births, deaths and net migration including statistical adjustment). In principle, the table containing the main demographic indicators is updated three times per year, after each of the national data collections. Detailed information on mortality (by age, sex, etc.) can be found under the section Mortality (demo_mor). These disaggregated information are updated towards the end of each year based on information collected during the Joint data collection. Moreover, any update sent by the countries in-between data collections are validated, processed and uploaded into Eurostat's demographic database and in Eurostat's free dissemination online database as soon as possible. The geographical aggregates are recalculated accordingly. The data transmitted by the National Statistical Institutes are validated by Eurostat, processed and uploaded into Eurostat's Demographic Database and in Eurostat's free dissemination online database. The data are also disseminated in several thematic and horizontal Eurostat's publications. Data are presented at national level and for aggregates of countries. For EU and Euro Area, only the current and the previous geographical status are published. The currently disseminated geographical aggregates are: EU-27, EU-25, EA-16, and EA-15. Moreover, data is disseminated for the European Economic Area (EEA) and the European Free Trade Association (EFTA).
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 17 5月, 2019
      データセットを選択
    • 5月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 24 5月, 2019
      データセットを選択
      Eurostat statistics on mortality are based on the annual demographic data collection in the field of demography carried out by Eurostat. The completeness of information depends on the availability of data reported by the National Statistical Institutes. The first demographic data collection of each year (T), named Rapid, is carried out in April-May (deadline 15 May of year T); during this data collection the first results on the main demographic developments in the previous year (T-1) and the population on 1 January of the current year (T) are collected from the National Statistical Institutes. The Joint demographic data collection is carried out in cooperation with United Nation Statistical Division (UNSD) in the summer of each year, having the deadline 15 September. During this data collection Eurostat collects from the National Statistical Institutes detailed data by sex, age and other characteristics for the demographic events (births, deaths, marriages and divorces) of the previous year and the population on 1 January of the current and previous years. The Nowcast demographic data collection is carried out in October-November (deadline 15 November of year T). The monthly time series on births, deaths, immigrants and emigrants available from the beginning of current year (T) are collected, with the purpose of producing a forecast on 1 January population of the following year (T+1). More specifically, during year T the following data are collected and disseminated on mortality field: - Total number of deaths in year (T-1) - Infant mortality by age and sex (T-1) - Late foetal deaths by mother's age (T-1) - Deaths by age, year of birth and sex (T-1) - Deaths by age, sex and educational attainment (ISCED 1997) - Deaths by month, year (T) and (T-1) Based on these information, Eurostat currently computes and disseminates the following mortality indicators: - Crude death rate - Infant mortality rate - Neonatal mortality rate - Early neonatal mortality rate - Late foetal mortality rate - Perinatal mortality rate - Life table - Life expectancy by age and sex - Life expectancy by age, sex and educational attainment (ISCED 1997)  The most recent (aggregated) data on the number of deaths can be found under the Main demographic indicators. This includes also the most recent Eurostat now casts on the main demographic indicators (population, births, deaths and net migration including statistical adjustment). In principle, the table containing the main demographic indicators is updated three times per year, after each of the national data collections. Detailed information on mortality (by age, sex, etc.) can be found under the section Mortality (demo_mor). These disaggregated information are updated towards the end of each year based on information collected during the Joint data collection. Moreover, any update sent by the countries in-between data collections are validated, processed and uploaded into Eurostat's demographic database and in Eurostat's free dissemination online database as soon as possible. The geographical aggregates are recalculated accordingly. The data transmitted by the National Statistical Institutes are validated by Eurostat, processed and uploaded into Eurostat's Demographic Database and in Eurostat's free dissemination online database. The data are also disseminated in several thematic and horizontal Eurostat's publications. Data are presented at national level and for aggregates of countries. For EU and Euro Area, only the current and the previous geographical status are published. The currently disseminated geographical aggregates are: EU-27, EU-25, EA-16, and EA-15. Moreover, data is disseminated for the European Economic Area (EEA) and the European Free Trade Association (EFTA).
    • 6月 2019
      ソース: North Atlantic Treaty Organization
      アップロード者: Knoema
      以下でアクセス: 23 9月, 2019
      データセットを選択
      Notes: Figures for 2018 and 2019 are estimates. The NATO Europe and NATO Total aggregates from 2017 include Montenegro, which became an Ally on 5 June 2017
    • 4月 2017
      ソース: Islamic Development Bank
      アップロード者: Knoema
      以下でアクセス: 07 9月, 2017
      データセットを選択
    • 6月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 19 6月, 2019
      データセットを選択
      The source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview
    • 6月 2019
      ソース: United Nations Statistics Division
      アップロード者: Knoema
      以下でアクセス: 02 6月, 2019
      データセットを選択
      The United Nations Statistics Division collects, compiles and disseminates official demographic and social statistics on a wide range of topics. Data have been collected since 1948 through a set of questionnaires dispatched annually to over 230 national statistical offices and have been published in the Demographic Yearbook collection. The Demographic Yearbook disseminates statistics on population size and composition, births, deaths, marriage and divorce, as well as respective rates, on an annual basis. The Demographic Yearbook census datasets cover a wide range of additional topics including economic activity, educational attainment, household characteristics, housing characteristics, ethnicity, language, foreign-born and foreign population. The available Population and Housing Censuses' datasets reported to UNSD for the censuses conducted worldwide since 1995, are now available in UNdata. This latest update includes several datasets on international travel and migration inflows and outflows, and on incoming and departing international migrants by several characteristics, as reported by the national authorities to the UN Statistics Division for the reference years 2010 to the present as available.
    • 3月 2019
      ソース: Institute of Statistics, Albania
      アップロード者: Knoema
      以下でアクセス: 11 4月, 2019
      データセットを選択
      This Dataset contains Indicators related to Population, Births, Deaths and Marriages and other relevant Demographic Indicators. Other related datasets: https://knoema.com/ALEDUCAN2018/albania-education https://knoema.com/ALHEALTH2018/albania-health https://knoema.com/ALENVIRNT2018/albania-environment https://knoema.com/ALLABMKT2018/albania-labour-market https://knoema.com/ALTRNSPORT2018/albania-transport https://knoema.com/ALITCOMMU2018/albania-information-communication-and-postal-services  
    • 11月 2018
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 23 11月, 2018
      データセットを選択
      Yearly data on freshwater resources, water abstraction and use, wastewater treatment (connection rates of resident population to wastewater treatment and treatment capacities of wastewater treatment plants), sewage sludge production and disposal, generation and discharge of wastewater collected biennially by means of the OECD/Eurostat Joint Questionnaire - Inland Waters. Data aggregation: national territories.
    • 4月 2019
      ソース: Institute for Health Metrics and Evaluation
      アップロード者: Knoema
      以下でアクセス: 14 6月, 2019
      データセットを選択
      This 10th edition of the Institute for Health Metrics and Evaluation’s annual Financing Global Health report provides the most up-to-date estimates of development assistance for health, domestic spending on health, health spending on two key infectious diseases – malaria and HIV/AIDS – and future scenarios of health spending. Several transitions in global health financing inform this report: the influence of economic development on the composition of health spending; the emergence of other sources of development assistance funds and initiatives; and the increased availability of disease-specific funding data for the global health community. For funders and policymakers with sights on achieving 2030 global health goals, these estimates are of critical importance. They can be used for identifying funding gaps, evaluating the allocation of scarce resources, and comparing funding across time and countries.
    • 2月 2016
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 21 11月, 2018
      データセットを選択
      To view the original national data please open the questionnaires. Source: Joint Forest Europe / UNECE / FAO Questionnaire on Pan-European Indicators for Sustainable Forest Management. Country: Russian Federation The source of the data of Russian Federation is the National Report for the Joint Forest Europe / UNECE / FAO reporting on quantitative pan-European indicators 2011.
    • 12月 2007
      ソース: International Telecommunication Union
      アップロード者: Knoema
      以下でアクセス: 23 5月, 2019
      データセットを選択
      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.
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 08 11月, 2019
      データセットを選択
      The Balance of Payments (BoP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of an economic area during a given period. The BoP provides harmonized information on international transactions which are part of the current, capital and financial accounts. The Current account provides information about the transactions of a country with the rest of the world. It covers all transactions (other than those in financial items) in goods, services, primary income and secondary income, which occur between resident and non-resident units. The MIP scoreboard indicator is 3 years average of Current account balance as % of GDP. In addition annual and quarterly data on the BoP sub-balances and its components are published under the MIP domain.
    • 8月 2019
      ソース: The Central Bank of the Russian Federation
      アップロード者: Knoema
      以下でアクセス: 16 9月, 2019
      データセットを選択
    • 7月 2018
      ソース: U.S. Department of Commerce, Bureau of Economic Analysis
      アップロード者: Sandeep Reddy
      以下でアクセス: 10 8月, 2018
      データセットを選択
      Direct Investment Position Abroad on a Historical-Cost Basis:  Country Detail by Industry, United States
    • 6月 2019
      ソース: Institute for Health Metrics and Evaluation
      アップロード者: Knoema
      以下でアクセス: 30 8月, 2019
      データセットを選択
      GBD 2017 - Disability-Adjusted Life Years and Healthy Life Expectancy 1990-2017 The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries. Estimates for disability-adjusted life years (DALYs) by cause, age, and sex and healthy life expectancy (HALE) by age and sex are available from the GBD Results Tool for 1990-2016 (quinquennial). Select tables published in The Lancet in September 2017 in "Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016" are also available for download via the “Files” tab above.
    • 11月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 12 11月, 2019
      データセットを選択
      Discouraged job-seekers refer to those persons of working age who during a specified reference period were without work and available for work, but did not look for work in the recent past for specific reasons (for example, believing that there were no jobs available, believing there were none for which they would qualify, or having given up hope of finding employment). The working age population is commonly defined as persons aged 15 years and older, but this varies from country to country. In addition to using a minimum age threshold, certain countries also apply a maximum age limit.
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 18 3月, 2019
      データセットを選択
      The Adult Education Survey (AES) covers adults’ participation in education and training (formal, non-formal and informal learning) and is one of the main data sources for EU lifelong learning statistics. The AES covers the resident population aged 25-64. The reference period for the participation in education and training is the twelve months prior to the interview. The following information is available from the AES: Participation in formal education, non-formal education and training and informal learning (respectively labelled FED, NFE and INF)Volume of instruction hoursCharacteristics of the learning activitiesReasons for participatingObstacles to participationAccess to information on learning possibilitiesEmployer financing and costs of learningSelf-reported language skills Three waves of the survey have been implemented so far (2007 AES, 2011 AES and 2016 AES). The first AES – referred to as 2007 AES – was a pilot exercise and carried out on a voluntary basis in 29 countries in the EU, EFTA (European Free Trade Association) and candidate countries between 2005 and 2008. The 2011 AES was underpinned by a European legal act and thus carried out in all Member States on a mandatory basis. The 2016 AES was carried out in 2016/2017 and the dissemination of results is ongoing with the available countries. Comparable data for the three waves can be found in the following folders: Participation in education and training (last 12 months) (trng_aes_12m0)Participation in informal learning (last 12 months) (trng_aes_12m4)Access to information on education and training (last 12 months) (trng_aes_12m1)Time spent on education and training (last 12 months) (trng_aes_12m2)           Obstacles to participation in education and training (last 12 months) (trng_aes_12m3)Self-reported language skills (educ_lang_00)
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 18 3月, 2019
      データセットを選択
      The Adult Education Survey (AES) covers adults’ participation in education and training (formal, non-formal and informal learning) and is one of the main data sources for EU lifelong learning statistics. The AES covers the resident population aged 25-64. The reference period for the participation in education and training is the twelve months prior to the interview. The following information is available from the AES: Participation in formal education, non-formal education and training and informal learning (respectively labelled FED, NFE and INF)Volume of instruction hoursCharacteristics of the learning activitiesReasons for participatingObstacles to participationAccess to information on learning possibilitiesEmployer financing and costs of learningSelf-reported language skills Three waves of the survey have been implemented so far (2007 AES, 2011 AES and 2016 AES). The first AES – referred to as 2007 AES – was a pilot exercise and carried out on a voluntary basis in 29 countries in the EU, EFTA (European Free Trade Association) and candidate countries between 2005 and 2008. The 2011 AES was underpinned by a European legal act and thus carried out in all Member States on a mandatory basis. The 2016 AES was carried out in 2016/2017 and the dissemination of results is ongoing with the available countries. Comparable data for the three waves can be found in the following folders: Participation in education and training (last 12 months) (trng_aes_12m0)Participation in informal learning (last 12 months) (trng_aes_12m4)Access to information on education and training (last 12 months) (trng_aes_12m1)Time spent on education and training (last 12 months) (trng_aes_12m2)           Obstacles to participation in education and training (last 12 months) (trng_aes_12m3)Self-reported language skills (educ_lang_00)
    • 8月 2019
      ソース: World Health Organization
      アップロード者: Knoema
      以下でアクセス: 22 8月, 2019
      データセットを選択
      Note: All data contained within is provisional. The annual number of cases of measles and rubella officially reported by a member state is only available by July of each following year (through the joint WHO UNICEF annual data collection exercise). “provisional data based on monthly data reported to WHO (Geneva) as of April 2019”. Measles cases are defined as laboratory confirmed, epidemiologically linked, and clinical cases as reported to the World Health Organization. Some countries report cases at irregular intervals, providing multiple months of data in a one month period. Future months are reported as 0 and will be updated as data is available. When data is used in public settings, please acknowledge the data source is the World Health Organization.
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 18 3月, 2019
      データセットを選択
      The Adult Education Survey (AES) covers adults’ participation in education and training (formal, non-formal and informal learning) and is one of the main data sources for EU lifelong learning statistics. The AES covers the resident population aged 25-64. The reference period for the participation in education and training is the twelve months prior to the interview. The following information is available from the AES:Participation in formal education, non-formal education and training and informal learning (respectively labelled FED, NFE and INF)Volume of instruction hoursCharacteristics of the learning activitiesReasons for participatingObstacles to participationAccess to information on learning possibilitiesEmployer financing and costs of learningSelf-reported language skills Three waves of the survey have been implemented so far (2007 AES, 2011 AES and 2016 AES). The first AES – referred to as 2007 AES – was a pilot exercise and carried out on a voluntary basis in 29 countries in the EU, EFTA (European Free Trade Association) and candidate countries between 2005 and 2008. The 2011 AES was underpinned by a European legal act and thus carried out in all Member States on a mandatory basis. The 2016 AES was carried out in 2016/2017 and the dissemination of results is ongoing with the available countries. Comparable data for the three waves can be found in the following folders:Participation in education and training (last 12 months) (trng_aes_12m0)Participation in informal learning (last 12 months) (trng_aes_12m4)Access to information on education and training (last 12 months) (trng_aes_12m1)Time spent on education and training (last 12 months) (trng_aes_12m2)           Obstacles to participation in education and training (last 12 months) (trng_aes_12m3)Self-reported language skills (educ_lang_00)
    • 8月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 15 8月, 2019
      データセットを選択
      The Adult Education Survey (AES) covers adults’ participation in education and training (formal, non-formal and informal learning) and is one of the main data sources for EU lifelong learning statistics. The AES covers the resident population aged 25-64. The reference period for the participation in education and training is the twelve months prior to the interview. The following information is available from the AES:Participation in formal education, non-formal education and training and informal learning (respectively labelled FED, NFE and INF)Volume of instruction hoursCharacteristics of the learning activitiesReasons for participatingObstacles to participationAccess to information on learning possibilitiesEmployer financing and costs of learningSelf-reported language skills Three waves of the survey have been implemented so far (2007 AES, 2011 AES and 2016 AES). The first AES – referred to as 2007 AES – was a pilot exercise and carried out on a voluntary basis in 29 countries in the EU, EFTA (European Free Trade Association) and candidate countries between 2005 and 2008. The 2011 AES was underpinned by a European legal act and thus carried out in all Member States on a mandatory basis. The 2016 AES was carried out in 2016/2017 and the dissemination of results is ongoing with the available countries. Comparable data for the three waves can be found in the following folders:Participation in education and training (last 12 months) (trng_aes_12m0)Participation in informal learning (last 12 months) (trng_aes_12m4)Access to information on education and training (last 12 months) (trng_aes_12m1)Time spent on education and training (last 12 months) (trng_aes_12m2)           Obstacles to participation in education and training (last 12 months) (trng_aes_12m3)Self-reported language skills (educ_lang_00)
    • 8月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 15 8月, 2019
      データセットを選択
      The Adult Education Survey (AES) covers adults’ participation in education and training (formal, non-formal and informal learning) and is one of the main data sources for EU lifelong learning statistics. The AES covers the resident population aged 25-64. The reference period for the participation in education and training is the twelve months prior to the interview. The following information is available from the AES:Participation in formal education, non-formal education and training and informal learning (respectively labelled FED, NFE and INF)Volume of instruction hoursCharacteristics of the learning activitiesReasons for participatingObstacles to participationAccess to information on learning possibilitiesEmployer financing and costs of learningSelf-reported language skills Three waves of the survey have been implemented so far (2007 AES, 2011 AES and 2016 AES). The first AES – referred to as 2007 AES – was a pilot exercise and carried out on a voluntary basis in 29 countries in the EU, EFTA (European Free Trade Association) and candidate countries between 2005 and 2008. The 2011 AES was underpinned by a European legal act and thus carried out in all Member States on a mandatory basis. The 2016 AES was carried out in 2016/2017 and the dissemination of results is ongoing with the available countries. Comparable data for the three waves can be found in the following folders:Participation in education and training (last 12 months) (trng_aes_12m0)Participation in informal learning (last 12 months) (trng_aes_12m4)Access to information on education and training (last 12 months) (trng_aes_12m1)Time spent on education and training (last 12 months) (trng_aes_12m2)           Obstacles to participation in education and training (last 12 months) (trng_aes_12m3)Self-reported language skills (educ_lang_00)
    • 8月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 15 8月, 2019
      データセットを選択
      The Adult Education Survey (AES) covers adults’ participation in education and training (formal, non-formal and informal learning) and is one of the main data sources for EU lifelong learning statistics. The AES covers the resident population aged 25-64. The reference period for the participation in education and training is the twelve months prior to the interview. The following information is available from the AES:Participation in formal education, non-formal education and training and informal learning (respectively labelled FED, NFE and INF)Volume of instruction hoursCharacteristics of the learning activitiesReasons for participatingObstacles to participationAccess to information on learning possibilitiesEmployer financing and costs of learningSelf-reported language skills Three waves of the survey have been implemented so far (2007 AES, 2011 AES and 2016 AES). The first AES – referred to as 2007 AES – was a pilot exercise and carried out on a voluntary basis in 29 countries in the EU, EFTA (European Free Trade Association) and candidate countries between 2005 and 2008. The 2011 AES was underpinned by a European legal act and thus carried out in all Member States on a mandatory basis. The 2016 AES was carried out in 2016/2017 and the dissemination of results is ongoing with the available countries. Comparable data for the three waves can be found in the following folders:Participation in education and training (last 12 months) (trng_aes_12m0)Participation in informal learning (last 12 months) (trng_aes_12m4)Access to information on education and training (last 12 months) (trng_aes_12m1)Time spent on education and training (last 12 months) (trng_aes_12m2)           Obstacles to participation in education and training (last 12 months) (trng_aes_12m3)Self-reported language skills (educ_lang_00)
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 18 3月, 2019
      データセットを選択
      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
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 18 3月, 2019
      データセットを選択
      The Adult Education Survey (AES) covers adults’ participation in education and training (formal, non-formal and informal learning) and is one of the main data sources for EU lifelong learning statistics. The AES focuses on people aged 25-64 living in private households. The reference period for the participation in education and training is the twelve months prior to the interview. The following information is available from the AES: Participation in formal education, non-formal education and training and informal learning (respectively labelled FED, NFE and INF)Volume of instruction hoursCharacteristics of the learning activitiesReasons for participatingObstacles to participationAccess to information on learning possibilitiesEmployer financing and costs of learningSelf-reported language skills Two waves of the survey have been implemented so far (2007 AES and 2011 AES). The first AES – referred to as 2007 AES – was a pilot exercise and carried out on a voluntary basis in 29 countries in the EU, EFTA (European Free Trade Association) and candidate countries between 2005 and 2008. The 2011 AES was underpinned by a European legal act and thus carried out in all Member States on a mandatory basis. The next AES is due in 2016. Comparable data from 2007 and 2011 AES can be found in the following folders: Participation in education and training (last 12 months) (trng_aes_12m0)Access to information on education and training (last 12 months) (trng_aes_12m1)Time spent on education and training (last 12 months) (trng_aes_12m2)           Obstacles to participation in education and training (last 12 months) (trng_aes_12m3)Self-reported language skills (educ_lang_00) The domain “Past series on lifelong learning - reference year 2007 (trng_aes_007h)” presents 2007 AES data on participation and non-participation in education and training which are not comparable with 2011 AES due to methodological changes.
    • 5月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 31 5月, 2016
      データセットを選択
      Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category:Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below:Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.
    • 8月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 17 8月, 2019
      データセットを選択
      Data on marriages and divorces at national level are based on the annual demographic data collections in the field of demography carried out by Eurostat. The completeness of information depends on the availability of data reported by the National Statistical Institutes. The Joint demographic data collection is carried out in cooperation with United Nation Statistical Division (UNSD) in the summer of each year, having the deadline 15 September. During this data collection Eurostat collects from the national statistical institutes detailed data by sex, age and other characteristics for the demographic events (births, deaths, marriages and divorces) of the previous year and the population on 1 January of the current and previous years. More specifically, during year T the following data are collected and disseminated on fertility field: - total number of marriages and divorces - persons getting married during the reference year by previous legal marital status, year T-1 Data can be found under the section Marriages and divorces (demo_nup). The information is updated towards the end of each year based on information collected during the Joint data collection. Moreover, any update sent by the countries in-between data collections are validated, processed and uploaded into Eurostat's demographic database and in Eurostat's free dissemination online database as soon as possible. Aggregates are recalculated accordingly. The data transmitted by the National Statistical Institutes are validated by Eurostat, processed and uploaded into Eurostat's Demographic Database and in Eurostat's free dissemination online database. The data are also disseminated in several thematic and horizontal Eurostat's publications. Data are presented by single country and for aggregates of countries. For EU and Euro Area, only the current and the previous version of the aggregates are published. The currently disseminated aggregates are: EU-27, EU-25, EA-16, and EA-15. Moreover, data is disseminated for the European Economic Area (EEA) and the European Free Trade Association (EFTA). International marriages and divorces Statistics on the number of international marriages and divorces (2000-2007) were collected by Eurostat from national statistical institutes in September 2008. The data were further used by the European Commission for preparing  a proposal for a Council Regulation on the law applicable in divorce and legal separation.  These data collected are available upon request.
    • 9月 2012
      ソース: Americans for Divorce Reform
      アップロード者: Knoema
      データセットを選択
      Divorce Indicators across countries
    • 8月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 17 8月, 2019
      データセットを選択
      Data on marriages and divorces at national level are based on the annual demographic data collections in the field of demography carried out by Eurostat. The completeness of information depends on the availability of data reported by the National Statistical Institutes. The Joint demographic data collection is carried out in cooperation with United Nation Statistical Division (UNSD) in the summer of each year, having the deadline 15 September. During this data collection Eurostat collects from the national statistical institutes detailed data by sex, age and other characteristics for the demographic events (births, deaths, marriages and divorces) of the previous year and the population on 1 January of the current and previous years. More specifically, during year T the following data are collected and disseminated on fertility field: - total number of marriages and divorces - persons getting married during the reference year by previous legal marital status, year T-1 Data can be found under the section Marriages and divorces (demo_nup). The information is updated towards the end of each year based on information collected during the Joint data collection. Moreover, any update sent by the countries in-between data collections are validated, processed and uploaded into Eurostat's demographic database and in Eurostat's free dissemination online database as soon as possible. Aggregates are recalculated accordingly. The data transmitted by the National Statistical Institutes are validated by Eurostat, processed and uploaded into Eurostat's Demographic Database and in Eurostat's free dissemination online database. The data are also disseminated in several thematic and horizontal Eurostat's publications. Data are presented by single country and for aggregates of countries. For EU and Euro Area, only the current and the previous version of the aggregates are published. The currently disseminated aggregates are: EU-27, EU-25, EA-16, and EA-15. Moreover, data is disseminated for the European Economic Area (EEA) and the European Free Trade Association (EFTA). International marriages and divorces Statistics on the number of international marriages and divorces (2000-2007) were collected by Eurostat from national statistical institutes in September 2008. The data were further used by the European Commission for preparing  a proposal for a Council Regulation on the law applicable in divorce and legal separation. These data collected are available upon request.
    • 3月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 27 3月, 2019
      データセットを選択
      Data on marriages and divorces at national level are based on the annual demographic data collections in the field of demography carried out by Eurostat. The completeness of information depends on the availability of data reported by the National Statistical Institutes. The Joint demographic data collection is carried out in cooperation with United Nation Statistical Division (UNSD) in the summer of each year, having the deadline 15 September. During this data collection Eurostat collects from the national statistical institutes detailed data by sex, age and other characteristics for the demographic events (births, deaths, marriages and divorces) of the previous year and the population on 1 January of the current and previous years. More specifically, during year T the following data are collected and disseminated on fertility field: - total number of marriages and divorces - persons getting married during the reference year by previous legal marital status, year T-1 Data can be found under the section Marriages and divorces (demo_nup). The information is updated towards the end of each year based on information collected during the Joint data collection. Moreover, any update sent by the countries in-between data collections are validated, processed and uploaded into Eurostat's demographic database and in Eurostat's free dissemination online database as soon as possible. Aggregates are recalculated accordingly. The data transmitted by the National Statistical Institutes are validated by Eurostat, processed and uploaded into Eurostat's Demographic Database and in Eurostat's free dissemination online database. The data are also disseminated in several thematic and horizontal Eurostat's publications. Data are presented by single country and for aggregates of countries. For EU and Euro Area, only the current and the previous version of the aggregates are published. The currently disseminated aggregates are: EU-27, EU-25, EA-16, and EA-15. Moreover, data is disseminated for the European Economic Area (EEA) and the European Free Trade Association (EFTA). International marriages and divorces Statistics on the number of international marriages and divorces (2000-2007) were collected by Eurostat from national statistical institutes in September 2008. The data were further used by the European Commission for preparing  a proposal for a Council Regulation on the law applicable in divorce and legal separation. These data collected are available upon request.
    • 8月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 17 8月, 2019
      データセットを選択
      Data on marriages and divorces at national level are based on the annual demographic data collections in the field of demography carried out by Eurostat. The completeness of information depends on the availability of data reported by the National Statistical Institutes. The Joint demographic data collection is carried out in cooperation with United Nation Statistical Division (UNSD) in the summer of each year, having the deadline 15 September. During this data collection Eurostat collects from the national statistical institutes detailed data by sex, age and other characteristics for the demographic events (births, deaths, marriages and divorces) of the previous year and the population on 1 January of the current and previous years. More specifically, during year T the following data are collected and disseminated on fertility field: - total number of marriages and divorces - persons getting married during the reference year by previous legal marital status, year T-1 Data can be found under the section Marriages and divorces (demo_nup). The information is updated towards the end of each year based on information collected during the Joint data collection. Moreover, any update sent by the countries in-between data collections are validated, processed and uploaded into Eurostat's demographic database and in Eurostat's free dissemination online database as soon as possible. Aggregates are recalculated accordingly. The data transmitted by the National Statistical Institutes are validated by Eurostat, processed and uploaded into Eurostat's Demographic Database and in Eurostat's free dissemination online database. The data are also disseminated in several thematic and horizontal Eurostat's publications. Data are presented by single country and for aggregates of countries. For EU and Euro Area, only the current and the previous version of the aggregates are published. The currently disseminated aggregates are: EU-27, EU-25, EA-16, and EA-15. Moreover, data is disseminated for the European Economic Area (EEA) and the European Free Trade Association (EFTA). International marriages and divorces Statistics on the number of international marriages and divorces (2000-2007) were collected by Eurostat from national statistical institutes in September 2008. The data were further used by the European Commission for preparing  a proposal for a Council Regulation on the law applicable in divorce and legal separation.  These data collected are available upon request.
    • 7月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 03 7月, 2019
      データセットを選択
      18.1. Source data
    • 3月 2018
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 29 3月, 2018
      データセットを選択
      18.1. Source data
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 12 11月, 2019
      データセットを選択
      Short-term statistics (STS) give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification (Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Constructions (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are generally presented in the following forms: UnadjustedCalendar adjustedSeasonally adjusted Depending on the STS regulation data are accessible as monthly, quarterly and annual data. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction (volume)*Turnover: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic turnover into euro area and non euro area is available for the euro area countriesProducer prices (output prices)*: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic producer prices into euro area and non euro area is available for the euro area countriesImport prices*: Total, Euro area market, Non euro area market (euro area countries only)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesCONSTRUCTIONProduction (volume)*: Total of the construction sector, Building construction, Civil EngineeringBuilding permits indicators*: Number of dwellings, Square meters of useful floor (or alternative size measure)Construction costs or prices: Construction costs, Material costs, Labour costs (if not available, they may be approximated by the Producer (output) prices variable)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesWHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (value)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesSERVICESTurnover (in value)*Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesProducer prices (Output prices )* National reference metadata of the reporting countries can be found in the Annexes of this metadata file.
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 12 11月, 2019
      データセットを選択
      Short-term statistics (STS) give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification (Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Constructions (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are generally presented in the following forms: UnadjustedCalendar adjustedSeasonally adjusted Depending on the STS regulation data are accessible as monthly, quarterly and annual data. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction (volume)*Turnover: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic turnover into euro area and non euro area is available for the euro area countriesProducer prices (output prices)*: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic producer prices into euro area and non euro area is available for the euro area countriesImport prices*: Total, Euro area market, Non euro area market (euro area countries only)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesCONSTRUCTIONProduction (volume)*: Total of the construction sector, Building construction, Civil EngineeringBuilding permits indicators*: Number of dwellings, Square meters of useful floor (or alternative size measure)Construction costs or prices: Construction costs, Material costs, Labour costs (if not available, they may be approximated by the Producer (output) prices variable)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesWHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (value)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesSERVICESTurnover (in value)*Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesProducer prices (Output prices )* National reference metadata of the reporting countries can be found in the Annexes of this metadata file.
    • 11月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 12 11月, 2019
      データセットを選択
      This table includes the areas, productions and humidity of field peas, broad and field beans, sweet lupins, dry beans, other dry peas, lentils, chickling vetch, chick peas, vetches and other protein crops sown in pure crops or as mixtures with cereals harvested dry for grain. This indicator uses the concepts of "area under cultivation", "harvested production" and "humidity". 1) The "area under cultivation" corresponds: • before the harvest, to the sown area; • after the harvest, to the sown area excluding the non-harvested area (e.g. area ruined by natural disasters, area not harvested for economic reasons, etc.) 2) The "harvested production" corresponds to the production for which harvesting started in year N, even thought harvesting may finish in year N+1. So N is the reference year for data published by Eurostat. 3) In order to facilitate the comparisons of production between the Members States, the publication of "humidity" for each country is needed. Only the EU-aggregate for the production is published with a standard EU humidity.
    • 12月 2008
      ソース: Institute for Health Metrics and Evaluation
      アップロード者: Peter Speyer
      データセットを選択
      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
    • 7月 2013
      ソース: Earth Policy Institute
      アップロード者: Knoema
      以下でアクセス: 08 7月, 2013
      データセットを選択
      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.
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 01 11月, 2019
      データセットを選択
      The economic accounts for forestry and logging are based on national accounts, but are collected with greater detail. Current prices means prices of that particular year. Annual inflation must yet be taken into account if one wishes to compare the values of different years. Basic prices means the price received by the producer after deduction of all taxes on products, but including all subsidies on products. Gross value added is the value of the output less the value of intermediate consumption. Fixed capital relates to longer-lived assets (e.g. equipment or buildings) that are either acquired (this is gross fixed capital formation) or consumed (this is fixed capital consumption, the annual reduction in the value of fixed assets). The definition of the activity of forestry and logging is based on Division 02 of NACE Rev. 2.
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 01 11月, 2019
      データセットを選択
      Eurostat's database covers 1) Production and trade in roundwood and wood products, including primary and secondary products 2) Economic data on forestry and logging, including employment data 3) Sustainable forest management, comprising forest resources (assets) and environmental data. The main types of primary forest products included in (1) are: roundwood, sawnwood, wood-based panels, pulp, and paper and paperboard. Secondary products include further processed wood and paper products. These products are presented in greater detail; definitions are available. All of the data are compiled from the Joint Forest Sector Questionnaire (JFSQ), except for table (e), which is directly extracted from Eurostat's international trade database COMEXT (HS/CN Chapter 44). The tables in (1) cover details of the following topics: - Roundwood removals and production by type of wood and assortment (a) - Roundwood production by type of ownership (b) - Production and trade in roundwood, fuelwood and other basic products (c) - Trade in industrial roundwood by assortment and species (d) - Tropical wood imports to the EU from Chapter 44 of the Harmonised System (e) - Production and trade in sawnwood, panels and other primary products (f) - Sawnwood trade by species (g) - Production and trade in pulp and paper & paperboard (h) - Trade in secondary wood and paper products (i) Data in (2) include the output, intermediate consumption, gross value added, fixed capital consumption, gross fixed capital formation and different measures of income of forestry and logging.  The data are in current basic prices and are compatible with National Accounts. They are collected as part of Intergrated environmental and economic accounting for forests (IEEAF), which also covers labour input in annual work units (AWU).  Under (2), two separate tables cover the number of employees of forestry and logging, the manufacture of wood and products of wood and cork, and the manufacture of paper and paper products, as estimated from the Labour Force Survey results. There are two separate tables because of the change in the EU's classification of economic activities from NACE Rev. 1.1 to NACE Rev. 2 in 2008. More detailed information on wood products and accounting, including definitions and questionnaires, can be found on our open-access communication platform under the interest group 'Forestry statistics and accounts'.  Data in (3) are not collected by Eurostat, but by the FAO, UNECE, Forest Euope, the European Commission's departments for Environment and the Joint Research Centre. They include forest area, wood volume, defoliation on sample plots, fires and areas with protective functions.
    • 7月 2015
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 16 12月, 2015
      データセットを選択
    • 9月 2019
      ソース: Fraser Institute
      アップロード者: Knoema
      以下でアクセス: 25 9月, 2019
      データセットを選択
      Data cited at: "Economic Freedom of the World: 2019 Annual Report"@Fraser Institute   The economic freedom index measures the degree of economic freedom present in five major areas: [1] Size of Government; [2] Legal System and Security of Property Rights; [3] Sound Money; [4] Freedom to Trade Internationally; [5] Regulation. Within the five major areas, there are 24 components (area) in economic freedom index. Each component and sub-component is placed on a scale from 0 to 10.
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 01 11月, 2019
      データセットを選択
      Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published:as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)
    • 4月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 22 4月, 2019
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      .. - data not available Source: UNECE Statistical Database, compiled from national official sources. Definition: The economically inactive population includes all the persons who are not part of the labour force, i.e. are neither employed nor unemployed. General note: Data come from the Labour Force Survey (LFS), unless otherwise specified. Data are shown in thousands. Country: Armenia For the period of 1995-2006 data are based on integrated data received from various sources. Break in methodlogy (2007, 2014): from 2007 to 2013 data are based on the Integrated Survey of the Household Living Standards. Since 2014 data are based on the Labour Force Survey. Break in series (2008): 2007 data refer to population aged 16-75. Since 2008, application of ILO methodology, data cover population aged 15-75. Country: Austria Data below the threshold of 3 000 persons are not published, while caution should be taken in interpreting data below the threshold of 6 000 persons. Country: Austria Break in methodology (2004): Break in series due to change in data collection procedure. Country: Bulgaria Change in definition (1990): Data for & 39;Other reasons, including sickness& 39; include persons who are inactive for personal or family reasons. Country: Bulgaria Change in definition (1995 - 2002): Data for & 39;Other reasons, including sickness& 39; include persons who are inactive for personal or family reasons. Data refer to June and include persons on compolsory military service Country: Bulgaria Change in definition (2003 - 2012): Data for & 39;Other reasons, including sickness& 39; include persons who are inactive for personal or family reasons. Data are annual averages and exclude persons on compulsory military service. Country: Bulgaria Reference period (1990): Data refer to 1993 Country: Bulgaria Data below the threshold of 4 000 persons are not reliable due to small sample sizes and are not published. Country: Canada Data for Study, Retirement and Home-making include only persons who have left their jobs within the last 12 months. All other inactive persons are included in the category Other reasons, including sickness. Country: Canada Data do not cover the three northern territories (Yukon, Northwest and Nunavuk ). Country: Croatia Data given for 2013 onwards are calibrated according to the results of the Census 2011 and are not fully comparable with data given for previous years. Country: Cyprus Territorial change (2000 - 2012): Data cover government controlled area. Country: Czechia From 2010 a new variable covers retired persons. This creates differences in sum of reasons to total reasons. Country: Denmark Break in methodlogy (2009): Beark in series due to change in sources Country: Estonia Data for age group 15+ refers to 15-74; age group 65+ refers to 65-74. Country: Finland Change in definition (1990 - 2006): Data for age group 15+ refers to 15-74; age group 65+ refers to 65-74. Data for ?Home-making? include persons who take care of own children or other dependants. Data for ?Other reasons, including sickness? include disability and other reasons. Data for inactive persons aged 65+ were all classified as retired. Country: Finland Change in definition (2007 onward): Data for age group 15+ refers to 15-74; age group 65+ refers to 65-74. Data for ?Home-making? include persons who take care of own children or other dependants. Data for ?Other reasons, including sickness? include disability and other reasons. Country: France Data cover only Metropolitan France. Country: Georgia Change in definition (2008 onward): Inactive persons: homemaker - also includes a man who looks after infants or disabled persons Country: Georgia Territorial change (2000 onward): Data do not cover Abkhazia AR and Tskhinvali Region Country: Germany Break in methodlogy (2005): Until 2004, data refer to one reporting week. From 2005 data are annual average figures. Country: Greece Data refer to annual averages. Country: Hungary Change in definition (2000 - 2013): Data for age group 15+ refers to 15-74; age group 65+ refers to 65-74. Data on ?Home-making? category include persons on parental leave. Data on ?Other reasons, including sickness? include permanently disabled persons. Country: Iceland Break in methodology (2003): Break in series because of change to continuous survey every week of the year. Country: Iceland Change in definition (1990 onward): The survey sample covered population aged 16 to 74. Country: Iceland Reference period (1990): Data refer to 1991. Country: Ireland Inactive according to ILO criteria classified by PES Country: Israel Break in methodlogy (2000): In 1998: 1) Changes in the weighting method; 2) Transition to the 1995 Population Census estimates; See explanations: http://www.cbs.gov.il/www/publications/saka_change/tch_e.pdf Country: Israel Break in methodlogy (2001): Changes in the weighting method. See explanations: http://www.cbs.gov.il/www/saka_y/e_intro_f1_comparison-mimi.f Country: Israel Break in methodlogy (2009): 1) Update of the definition of the civilian labour force characteristics; 2) Transition to the 2008 Population Census estimates. See explanations: http://www.cbs.gov.il/publications11/1460/pdf/intro05_e.pdf Country: Israel Break in methodlogy (2012): 1) Transitiom from a quarterly to a monthly LFS; 2) Changes in the definitions of labour force characteristics (including compulsory and permanent military service into labour force). See explanations: http://www.cbs.gov.il/publications/labour_survey04/labour_f--orce_survey/answer_question_e_2012.pdf Country: Israel Change in definition (1995): From 1995, 1) Update of the definitions of labour force characteristics; 2) Changes in the Standard Industrial Classification of Economic Activities; See explanations: http://www.cbs.gov.il/www/publications/saka_change/tch_e.pdf Country: Israel Change in definition (2000): From 2000, changes in the questionnaire (Highest Diploma Received, Discouraged Workers, Employees hired through employment agencies or employment contractors); See explanations: http://www.cbs.gov.il/www/saka_y/e_intro_e_changes.pdf Country: Italy Break in methodlogy (2004): From 2004, there is a break in series due to change in survey and data collection procedure (continuous survey). Country: Kyrgyzstan 2003: break in series: change in methodology. Country: Latvia Change in definition (2002 - 2012): Age group 15+ refers to 15-74; age group 65+ refers to 65-74. Country: Latvia Reference period (1995): Data refer to 1996. Country: Luxembourg Reference period (1980): Data refers to year 1983 Country: Malta Some data not shown due to lack of reliability. Country: Moldova, Republic of Data exclude the territory of the Transnistria and municipality of Bender Country: Netherlands All inactive persons aged 65+ were categorized as retired through 2013, but are included in other categories from 2014. Country: Norway Data for age group 15-64 refers to 15-66; age group 25-49 refers to 25-54; age group 50-64 refers to 55-66; age group 65+ refers to 55-74 and age group 15+ refers to 15-74. Data for ?Retirement? include early retirement and disabled persons. Country: Poland Data are not fully comparable with the results of the surveys prior to 2010 as persons staying outside households for 12 months or longer are excluded from the survey (previously over 3 months). Country: Portugal Data from 2011 onwards are not directly comparable with data for the previous years due to new data collection methods used in the Portuguese Labour Force Survey series. Estimates below 4 500 individuals are not shown due to high coefficients of variation. Country: Romania Break in methodology (2002): Due to the revision of the definitions and the coverage, the data series of 2002-2012 are not perfectly comparable with data series of previous years. Break in series starting with year 2013. For years 2014 onward data were estimated using the resident population. For year 2013 data were estimated based on revised population figures (resident population) in accordance to the 2011 Census results. Country: Romania Reference period (1995): Data for 1995 refers to March 1995 Country: Russian Federation Change in definition (1990 - 2013): Data present the population aged 15-72 years Country: Russian Federation Reference period (1990): Data refer to 1992 Country: Russian Federation Territorial change (1990 - 2006): Data do not include the Chechen Republic Country: Serbia Data do not cover Kosovo and Metohija. Country: Slovenia Some data not shown due to low reliability. Country: Spain Data for age group 15+ refers to 16+; age group 15-24 refers to 16-24 and age group 15-64 refers to 16-64. Data are annual average of the four quarters of the year. Country: Switzerland Break in methodlogy (2010): Change to continuous survey. As of 2010: annual averages Country: Switzerland Reference period (1990): Data refer to 1991 Country: Switzerland Reference period (1990 - 2009): Data refer to 2nd quarter Country: Switzerland Some data were deleted as unreliable Country: Turkey Break in series (2014): Since 2014 series are not comparable with the previous years due to methodological changes in LFS. Country: Turkey Break in methodlogy (2004): Data are revised according to the 2008 population projections. Country: Ukraine Change in definition (2000 - 2012): Economicaly active population include persons aged 15-70, who can not be classified as "employed" and "unemployed". Country: Ukraine Territorial change (2000 - 2012): Data do not cover the area of radioactive contamination from the Chernobyl disaster. Country: United Kingdom Some data were deleted as unreliable
    • 12月 2018
      ソース: Institute of Statistics, Albania
      アップロード者: Knoema
      以下でアクセス: 07 1月, 2019
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      Economy & Rural Development of Albania
    • 12月 2015
      ソース: United Nations Development Programme
      アップロード者: Misha Gusev
      データセットを選択
      Calculated using Mean Years of Schooling and Expected Years of Schooling.
    • 8月 2019
      ソース: World Bank
      アップロード者: Knoema
      以下でアクセス: 02 8月, 2019
      データセットを選択
      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic:Education Statistics Publication: https://datacatalog.worldbank.org/dataset/education-statistics License: http://creativecommons.org/licenses/by/4.0/   The World Bank EdStats All Indicator Query holds over 4,000 internationally comparable indicators that describe education access, progression, completion, literacy, teachers, population, and expenditures. The indicators cover the education cycle from pre-primary to vocational and tertiary education.
    • 5月 2019
      ソース: United Nations Economic Commission for Europe
      アップロード者: Knoema
      以下でアクセス: 07 5月, 2019
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      Source: UNECE Statistical Database, compiled from national official sources. Definition:Educational attainment is defined as the highest level successfully completed by the person, in the educational system of the country where the education was received. The levels of education are defined according to the International Standard Classification of Education (ISCED): - Primary: ISCED level 1 - Lower secondary: ISCED level 2 - Upper and post secondary non-tertiary: ISCED levels 3-4 - Tertiary: ISCED 1997 levels 5-6 or ISCED 2011 levels 5-8. In this table the upper secondary level includes post-secondary non-tertiary education. For most countries the transition from ISCED 1997 to ISCED 2011 is from the scool year 2013-2014. For more details see Country Footnotes. .. - data not available Country: Armenia Change in definition (1980 - 1990): Level of education ?not stated? includes population without education attainment. Country: Armenia Reference period (1980): Data refer to 1979 Country: Armenia Reference period (1990): Data refer to 1989 Country: Austria Break in methodology (2004): In 2014 a new weighting procedure for the LFS was introduced. Following this change in the weighting procedure, data was revised back to 2004. Country: Austria ISCED-11 (2014 onwards): Break in series due to the reclassification of a programme spanning levels: the qualification acquired upon successful completion of higher technical and vocational colleges is allocated in ISCED 2011 to ISCED level 5; under ISCED 1997 the same qualification was reported on ISCED level 4, but earmarked as equivalent to tertiary education Country: Austria Change in definition (1980 - 2000): Data before 2000 do not comply with ISCED97 as regards distinction between upper secondary and tertiary. ISCED97 5B mainly included in Upper Secondary. Country: Austria Change in definition (2004 - 2015): Data include ISCED Level 3c short in lower secondary level. Country: Azerbaijan Reference period (1980 - 2013): Data refer to end of year. Country: Belarus Additional information (1990 - 2013): Total includes population without education. Country: Belarus Break in methodlogy (1990): Data refer to 1989 census Country: Belarus Break in methodlogy (2000): Data refer to 1999 census Country: Belgium 2010: break in series: change in methodology. Measurement: Persons , Country: Bosnia and Herzegovina Population by educational attainment, educational level not stated refers to the population with no primary schooling and some primary. Country: Bulgaria Break in methodlogy (1980): Data are from 1985 census Country: Bulgaria Break in methodlogy (1990): Data are from 1992 census Country: Bulgaria Break in methodlogy (2001): Data are from 2001 census Country: Bulgaria Reference period (1995 - 2002): Data refer to June of respective year Country: Canada Additional information (1990 - onwards): Data cover non-institutionalized population in the 10 provinces, i.e. excluding the three Territories. Country: Croatia Change in definition (1980 - 1990): Data refer to population with permanent residence irrespective of actual residence and duration. "Education level-not stated" comprises persons with unknown education level as well as persons with no school at all. Country: Croatia Change in definition (2001 - 2013): "Education level-not stated" comprises persons with unknown education level as well as persons with no school at all. Country: Croatia Reference period (1980): Data refer to 1981 Country: Croatia Reference period (1990): Data refer to 1991 Country: Cyprus Change in definition (1990): Lower secondary level is included in upper secondary level Country: Cyprus Reference period (1990): Data refer to 1989 Country: Cyprus Reference period (1995): Data refer to 1992 Country: Cyprus Data cover only government controlled area Country: Cyprus From 2014, data compiled using ISCED 2011 classification. Country: Cyprus From 2000, persons who have not attended or finished primary education also included in primary education level. Country: Estonia Change in definition (1980 - 2000): Data are from censuses and refer to population aged 25+ Data for primary level attainment include persons who have not completed the primary level education. Country: Estonia Change in definition (2001 - 2013): Age group 25+ refers to 25-74, age group 50+ refers to 50-74. Data for primary level attainment include persons who have not completed the primary level education. Country: Estonia Change in definition (2012): Data is from census 2011. Data refer to 31.december 2011 Data for primary level attainment include persons who have not completed the primary level education. Country: Estonia Reference period (1980): Data refer to 1979 Country: Estonia Reference period (1990): Data refer to 1989 Country: Finland Data for lower secondary level include primary level. Country: Georgia Change in definition (1980 - 2013): Level of education ?not stated? includes population without education attainment Country: Georgia Reference period (1980): Data refer to 1979 Country: Georgia Reference period (1990): Data refer to 1989 Country: Germany Data from 1990 to 1998 are classified according to ISCED-76, data from 1999 to 2013 according to ISCED 97, data from 2014 on are classified according to ISCED 2011. Country: Greece Break in methodology (2000): From 2000, data refer to population residing in private households Country: Greece Change in definition (2001 - 2013): "Primary" includes also persons that did not completed ISCED 1 programs Country: Greece Data refer to annual averages. From 2014, estimates use ISCED-2011 classification. Country: Hungary Break in methodlogy (1995): Before 1995, data are from population censuses. From 2000, from Country: Hungary Change in definition (2000 - 2008): Data refer to population aged 25-74. Country: Iceland Break in methodology (2003): Change in data collection procedure. Data classified according to ISCED 2011. Country: Iceland Reference period (1990): 1990 refers to 1991 Country: Ireland From 2000, data refer to age group 25-64. From 2014, data are compiled according to ISCED-2011. As a result data breakdown by education level not fully comparable with previous years. Country: Ireland Reference period (1980): Data refer to1981 Country: Ireland Reference period (1990): Data refer to 1991 Country: Ireland Reference period (1995): Data refer to 1996 Country: Israel Break in methodlogy (2001): Changes in the weighting method. Country: Israel Break in methodlogy (2009): Transition to the 2008 Population Census estimates. Country: Israel Break in methodlogy (2012): Transitiom from a quarterly to a monthly LFS. Country: Israel From 2012, using ISCED-2011. Totals include population by educational attainment, pre-primary. Country: Italy Break in methodology (2004): Change in data collection procedure. From 2014, data classified by ISCED 2011. Country: Italy Change in definition (1980 - 1990): Data for primary level attainment include persons who have not completed the primary level education Country: Kyrgyzstan Break in methodlogy (2000): Data refer to 1999 Census Country: Kyrgyzstan Break in methodlogy (2009): Data refer to 2009 Census Country: Kyrgyzstan Reference period (1990): Data refer to 1989 Census Country: Latvia Change in definition (1995 - 2001): Population aged 15+. Data for primary level refers to level 0 and 1 of ISCED 1997 classification. Country: Latvia Change in definition (2002 onward): Population 15-74 age group. For 2002-2013, data for primary level refers to level 0 and 1 of ISCED 1997 classification. From 2014, data for primary level refers to level 0 and 1 of ISCED 2011 classification. Country: Latvia Reference period (1995): Data refer to 1996 Country: Luxembourg Additional information (1990 - onwards): Data for age group 25+ refer to 25-74. Country: Luxembourg Break in methodlogy (2003): Switch from a face-to-face to a telephone survey Country: Luxembourg Break in methodlogy (2009): Random Digit Dialing has replaced the register-based sampling Country: Luxembourg Change in definition (1990 - 2012): The categroy `Lower secodnary` also includes persons who have at most attained the primary level Country: Luxembourg Reference period (1990): Data refer to 1992 Country: Malta Some data not shown due to lack of reliability. Country: Moldova, Republic of Territorial change (2000 onward): Data exclude the territory of the Transnistria and municipality of Bender Country: Netherlands Since 2003, ''Primary'' includes also ISCED level 0 (persons who have not successfully completed ISCED 1 programs). Country: Norway Break in methodology (2007): As of 2007, the results of a survey on education completed abroad before immigration to Norway is included. As a result , the proportion of & 39;educational level not stated& 39; was reduced. All data compiled according ISCED 2011. Country: Poland Change in definition (1990 - 2002): Upper secondary level includes lower secondary level. Country: Poland Reference period (1990): Data refer to 1988 Country: Portugal Data from 2011 onwards are not directly comparable with data for the previous years due to new data collection methods used in the Portuguese Labour Force Survey series. Data from 2014 onward are compiled according to ISCED-2011. Data for ''educational level not stated'' refer to individuals who have not successfully completed ISCED level 1. Country: Romania Break in methodology (2002): Data series of 2002-2012 are not perfectly comparable with data series of previous years. For years 2014 onward data were estimated using the resident population. For year 2013 data were estimated based on revised population figures (resident population) in accordance to the 2011 Census results. Starting with year 2014 educational attainment collected according to ISCED 2011. Educational level not stated includes persons without any formal education graduated. Country: Serbia Data for education level not stated include population without education attainment. Country: Slovakia Change in definition (1995): data for total of education levels include only secondary and tertiary levels. Country: Slovakia Change in definition (2001 - 2011): data on primary education according to ISCED 97, level 1 is not available Country: Slovenia From 2014 data are compiled according to ISCED-2011 and persons with ISCED level 0 are excluded. Country: Spain Data are annual averages of the four quarters of the year. From 2014 data are compiled according to ISCED-2011 Country: Sweden Break in methodlogy (2002): Quality improvement and change in classification from ISCED 1976 to ISCED 1997. Country: Sweden Change in definition (1990 - 2013): Data refer to population aged 25-74 Country: Switzerland Break in methodlogy (2010): Major changes in data collection procedures (quaterly data instead of annual data). Country: Switzerland Change in definition (1990 - 2001): Lower sedondary education includes primary education Country: Switzerland Change in definition (2002): Change in definition of educational attainment levels Country: Switzerland Reference period (1990): Data refer to 1991 Country: Switzerland Since 2014, data are compiled according to ISCED-2011 Country: United States Change in definition (1980): Primary refers to grades 5-8, Lower Secondary refers to grade 9 in High School, no diploma, Upper Secondary refers to High School, college graduate, Tertiary refers to people who have completed Associate& 39;s degree through Doctorate degree, Not stated refers to people who didn& 39;t complete any schooling through 4th grade. Data based on completed schooling years. Country: United States Change in definition (1990 - 2015): Primary refers to grades 5-8, Lower Secondary refers to grade 9 in High School, no diploma, Upper Secondary refers to High School, college graduate, Tertiary refers to people who have completed Associate`s degree through Doctorate degree, Not stated refers to people who did not complete any schooling through 4th grade. Data based on degrees.
    • 4月 2019
      ソース: Organisation for Economic Co-operation and Development
      アップロード者: Knoema
      以下でアクセス: 12 4月, 2019
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    • 3月 2018
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 17 3月, 2018
      データセットを選択
      The indicator is defined as the quantity of electricity consumed by households. Household consumption covers all use of electricity for space and water heating and all electrical appliances.   The indicator is a Sustainable Development Indicator (SDI). It has been chosen for the assessment of the EU progress towards the targets of the Sustainable Development Strategy.   tsdpc310´s table: Eurobase>Tables by themes > Environment and energy > Energy > Energy statistics - quantities > Electricity consumption of households (tsdpc310) tsdpc310´s table within the SDI set: Eurobase > Tables on EU policy > Sustainable Development Indicators > Sustainable consumption and production > Consumption patterns > Electricity consumption of households (tsdpc310)
    • 10月 2018
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 03 11月, 2018
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      This consumption stands for final energy consumption. This means that the consumption in industry covers all industrial sectors with the exception of the energy sector, like power stations, oil refineries, coke ovens and all other installations transforming energy products into another form. Final energy consumption in transport covers mainly the consumption by railways and electrified urban transport systems. Final energy consumption in households/services covers quantities consumed by private households, small-scale industry, crafts, commerce, administrative bodies, services with the exception of transportation, agriculture and fishing.
    • 3月 2018
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 17 3月, 2018
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      20.1. Source data
    • 11月 2018
      ソース: Climatescope
      アップロード者: Sandeep Reddy
      以下でアクセス: 27 2月, 2019
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      World: Electricity Prices
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 01 11月, 2019
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      NEW METHODOLOGY (from 2007 onwards) Average half-yearly electricity prices for households and industrial end-users. The end-users are characterised by predefined annual consumption bands. The prices are collected and published considering three levels of taxationprices excluding taxes and levies;prices excluding VAT and other recoverable taxes;prices including all taxes, levies and VAT.  For the disaggregated electricity prices, separate price components are available for households and industrial consumers forproduction costs of electricitynetwork coststaxes and levies OLD METHODOLOGY (until 2007) Electricity prices for households and industrial standard consumers, valid on 1st January and on 1st July of each calendar year. Standard consumers are characterised by predefined annual consumption. The prices include electricity/basic price, transmission, system services, meter rental, distribution and other services. The prices are collected and published considering three levels of taxation (see above). For structural indicators tables, where only annual data is displayed both for new and old methodology in the same table, the prices refer to the price on 1st January of each year (until 2007) and to the first semester of each year (2008 and later). Data on electricity prices for industrial consumers are collected according to Directive 2008/92/EC of the European Parliament and of the Council of 22 October 2008 concerning a Community procedure to improve the transparency of gas and electricity prices charged to industrial end-users (recast) (Text with EEA relevance). Data for electricity prices for household end-users are collected on a voluntary basis The data collection covers the full spectrum of the 28 Member States of the European Union, Candidate Countries, Potential candidate countries and EFTA countries (except Switzerland).
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 23 10月, 2019
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      NEW METHODOLOGY (from 2007 onwards) Average half-yearly electricity prices for households and industrial end-users. The end-users are characterised by predefined annual consumption bands. The prices are collected and published considering three levels of taxation prices excluding taxes and levies;prices excluding VAT and other recoverable taxes;prices including all taxes, levies and VAT.  For the disaggregated electricity prices, separate price components are available for households and industrial consumers for production costs of electricitynetwork coststaxes and leviesOLD METHODOLOGY (until 2007) Electricity prices for households and industrial standard consumers, valid on 1st January and on 1st July of each calendar year. Standard consumers are characterised by predefined annual consumption. The prices include electricity/basic price, transmission, system services, meter rental, distribution and other services. The prices are collected and published considering three levels of taxation (see above). For structural indicators tables, where only annual data is displayed both for new and old methodology in the same table, the prices refer to the price on 1st January of each year (until 2007) and to the first semester of each year (2008 and later). Data on electricity prices for industrial consumers are collected according to Directive 2008/92/EC of the European Parliament and of the Council of 22 October 2008 concerning a Community procedure to improve the transparency of gas and electricity prices charged to industrial end-users (recast) (Text with EEA relevance). Data for electricity prices for household end-users are collected on a voluntary basis The data collection covers the full spectrum of the 28 Member States of the European Union, Candidate Countries, Potential candidate countries and EFTA countries (except Switzerland).
    • 10月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 16 10月, 2019
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      NEW METHODOLOGY (from 2007 onwards) Average half-yearly electricity prices for households and industrial end-users. The end-users are characterised by predefined annual consumption bands. The prices are collected and published considering three levels of taxation prices excluding taxes and levies;prices excluding VAT and other recoverable taxes;prices including all taxes, levies and VAT.  For the disaggregated electricity prices, separate price components are available for households and industrial consumers for production costs of electricitynetwork coststaxes and leviesOLD METHODOLOGY (until 2007) Electricity prices for households and industrial standard consumers, valid on 1st January and on 1st July of each calendar year. Standard consumers are characterised by predefined annual consumption. The prices include electricity/basic price, transmission, system services, meter rental, distribution and other services. The prices are collected and published considering three levels of taxation (see above). For structural indicators tables, where only annual data is displayed both for new and old methodology in the same table, the prices refer to the price on 1st January of each year (until 2007) and to the first semester of each year (2008 and later). Data on electricity prices for industrial consumers are collected according to Directive 2008/92/EC of the European Parliament and of the Council of 22 October 2008 concerning a Community procedure to improve the transparency of gas and electricity prices charged to industrial end-users (recast) (Text with EEA relevance). Data for electricity prices for household end-users are collected on a voluntary basis The data collection covers the full spectrum of the 28 Member States of the European Union, Candidate Countries, Potential candidate countries and EFTA countries (except Switzerland).
    • 7月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 04 7月, 2019
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      These are data collected via the annual electricity and heat questionnaire and the annual renewables questionnaire, according to Annex B of the Regulation (EC) No 1099/2008 of the European Parliament and of the Council of 22 October 2008 on energy statistics. The variables are: Total capacity (MWe)Capacity by source of electricity production (MWe)Capacity by type of generation in power plants using combustible fuels (MWe)Capacity by type of firing and by type of fuel used in power plants using combustible fuels (MWe) All reported capacities are broken down by type of supplier (main activity producer or auto-producer) in nrg_inf_epc. For plants based on combustion of fuels the capacity is further divided by type of technology of the generating plant (steam, internal combustion….) in nrg_inf_epct, by type of firing and by type of fuels.  The dataset nrg_inf_epcrw offers more detailed renewable fuels. Total capacity calculated from the aggregation of individual categories coming from each of the datasets could yield slightly different values. indeed, the data come from different sources (different questionnaires) and different use of decimal places and rounding could result in these differences.
    • 7月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 04 7月, 2019
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      These are data collected via the annual electricity and heat questionnaire and the annual renewables questionnaire, according to Annex B of the Regulation (EC) No 1099/2008 of the European Parliament and of the Council of 22 October 2008 on energy statistics. The variables are: Total capacity (MWe)Capacity by source of electricity production (MWe)Capacity by type of generation in power plants using combustible fuels (MWe)Capacity by type of firing and by type of fuel used in power plants using combustible fuels (MWe) All reported capacities are broken down by type of supplier (main activity producer or auto-producer) in nrg_inf_epc. For plants based on combustion of fuels the capacity is further divided by type of technology of the generating plant (steam, internal combustion….) in nrg_inf_epct, by type of firing and by type of fuels.  The dataset nrg_inf_epcrw offers more detailed renewable fuels. Total capacity calculated from the aggregation of individual categories coming from each of the datasets could yield slightly different values. indeed, the data come from different sources (different questionnaires) and different use of decimal places and rounding could result in these differences.
    • 7月 2019
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 04 7月, 2019
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      ANNUAL Annual data on quantities for crude oil, petroleum products, natural gas and manufactures gases, electricity and derived heat, solid fossil fuels, renewables and wastes covering the full spectrum of the energy sector from supply through transformation to final consumption oby sector and fuel type. Also, annual imports and exports data of various energy carriers by country of origin and destination, as well as infrastructure information. Data on annual statistics are collected by standard questionnaires according to Annex B of the Regulation (EC) No 1099/2008 of the European Parliament and of the Council of 22 October 2008 on energy statistics   MONTHLY The monthly energy data collections cover the most important energy commodities: Crude oil & Petroleum productsNatural gasSolid fuelsElectricity For each of the above mentioned commodities the inflowing data are delivered by the reporting countries to Eurostat via separate dedicated questionnaires. Data on monthly statistics are collected by standard questionnaires according to Annex C of the Regulation (EC) No 1099/2008 of the European Parliament and of the Council of 22 October 2008 on energy statistics   SHORT-TERM MONTHLY Short-term monthly energy data collections cover the most important energy commodities: Oil & petroleum productsNatural gasElectricity Short-term monthly data provides information on main flows (quantities) on the supply side. Data on monthly short term statistics are collected by standard questionnaires according to Annex D of the Regulation (EC) No 1099/2008 of the European Parliament and of the Council of 22 October 2008 on energy statistics
    • 5月 2016
      ソース: Eurostat
      アップロード者: Knoema
      以下でアクセス: 09 7月, 2016
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      Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category: Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below: Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.
    • 12月 2016
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 22 3月, 2019
      データセットを選択
    • 7月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 16 10月, 2019
      データセットを選択
      Greenhouse Gas (GHG) emissions from burning of savanna consist of methane (CH4) and nitrous oxide (N2O) gases produced from the burning of vegetation biomass in the following five land cover types: Savanna, Woody Savanna, Open Shrublands, Closed Shrublands, and Grasslands. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, regions and special groups, with global coverage, relative to the period 1990-present (with annual updates), expressed as Gg CH4, Gg N2O, Gg CO2eq and Gg CO2eq from both CH4 and N2O, by land cover class (savanna, woody savanna, closed shrubland, open shrubland, grassland) and by aggregates (all categories, savanna and woody savanna, closed and open shrubland). Implied emission factors for N2O and CH4 as well activity data (burned area and biomass burned) are also provided.
    • 9月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 16 10月, 2019
      データセットを選択
      Agriculture Total contains all the emissions produced in the different agricultural emissions sub-domains (enteric fermentation, manure management, rice cultivation, synthetic fertilizers, manure applied to soils, manure left on pastures, crop residues, cultivation of organic soils, burning of crop residues, burning of savanna, energy use), providing a picture of the contribution to the total amount of GHG emissions from agriculture. GHG emissions from agriculture consist of non-CO2 gases, namely methane (CH4) and nitrous oxide (N2O), produced by crop and livestock production and management activities. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/index.html). GHG emissions are provided by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed as Gg CO2 and CO2eq (from CH4 and N2O), by underlying agricultural emission sub-domain and by aggregate (agriculture total, agriculture total plus energy, agricultural soils).
    • 6月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 26 6月, 2019
      データセットを選択
      Greenhouse Gas (GHG) emissions from burning crop residues consist of methane (CH4) and nitrous oxide (N2O) gases produced by the combustion of a percentage of crop residues burnt on-site. The mass of fuel available for burning should be estimated taking into account the fractions removed before burning due to animal consumption, decay in the field, and use in other sectors (e.g., biofuel, domestic livestock feed, building materials, etc.). FAOSTAT emission estimates are computed at Tier 1 following the IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, reguions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed both as Gg CH4, Gg N2O, Gg CO2eq and CO2eq from CH4 and N2O, by crop (maize, rice, sugarcane and wheat) and by aggregates. Implied emission factors for N2O and CH4 as well activity data (biomass burned) are also provided.
    • 6月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 16 10月, 2019
      データセットを選択
      Greenhouse gas (GHG) emissions from crop residues consist of direct and indirect nitrous oxide (N2O) emissions from nitrogen (N) in crop residues and forage/pasture renewal left on agricultural fields by farmers. Specifically, N2O is produced by microbial processes of nitrification and de-nitrification taking place on the deposition site (direct emissions), and after volatilization/re-deposition and leaching processes (indirect emissions). The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories, Vol. 4, Ch. 2 and 11(http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided as direct, indirect and total by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed as Gg N2O and Gg CO2eq, by crop and N content in residues.
    • 6月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 26 6月, 2019
      データセットを選択
      Greenhouse gas (GHG) emissions from enteric fermentation consist of methane gas produced in digestive systems of ruminants and to a lesser extent of non-ruminants. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories vol. 4, ch. 10 and 11 (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed both as Gg CH4 and Gg CO2eq, by livestock species (asses, buffaloes, camels, cattle (dairy and non-dairy), goats, horses, llamas, mules, sheep, swine (breeding and market)) and by species aggregates (all animals, camels and llamas, cattle, mules and asses, sheep and goats, swine). Implied emission factor for CH4 and activity data are also provided
    • 6月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 26 6月, 2019
      データセットを選択
      GHG emissions from manure applied to soils consist of direct and indirect nitrous oxide (N2O) emissions from manure nitrogen (N) added to agricultural soils by farmers. Specifically, N2O is produced by microbial processes of nitrification and de-nitrification taking place on the application site (direct emissions), and after volatilization/re-deposition and leaching processes (indirect emissions). The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories vol. 4, ch. 10 and 11 (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided as direct, indirect and total by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed as Gg N2O and Gg CO2eq, by livestock species (asses, buffaloes, camels, cattle (dairy and non-dairy), chickens (broilers and layers), ducks, goats, horses, llamas, mules, sheep, swine (breeding and market) and turkeys) and by species aggregates (all animals, camels and llamas, cattle, chickens, mules and asses, poultry birds, sheep and goats, swine). Implied emission factor for N2O and activity data (N content in manure) are also provided.
    • 6月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 26 6月, 2019
      データセットを選択
      GHG emissions from manure left on pastures consist of direct and indirect nitrous oxide (N2O) emissions from manure nitrogen (N) left on pastures by grazing livestock. Specifically, N2O is produced by microbial processes of nitrification and de-nitrification taking place on the deposition site (direct emissions), and after volatilization/re-deposition and leaching processes (indirect emissions). The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories vol. 4, ch. 10 and 11 (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed as direct, indirect and total Gg N2O and Gg CO2eq, by livestock species (asses, buffaloes, camels, cattle (dairy and non-dairy), chickens (broilers and layers), ducks, goats, horses, llamas, mules, sheep, swine (breeding, market), turkeys) and by species aggregates (all animals, camels and llamas, cattle, chickens, mules and asses, poultry birds, sheep and goats, swine). Implied emission factor for N2O and N content in manure are also provided.
    • 6月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 26 6月, 2019
      データセットを選択
    • 9月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 16 10月, 2019
      データセットを選択
      Greenhouse gas (GHG) emissions from synthetic fertilizers consist of nitrous oxide gas from synthetic nitrogen additions to managed soils. Specifically, N2O is produced by microbial processes of nitrification and de-nitrification taking place on the addition site (direct emissions), and after volatilization/re-deposition and leaching processes (indirect emissions). The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories vol. 4, ch. 11 (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided as direct, indirect and total by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed as Gg N2O and Gg CO2eq. Implied emission factor for N2O and activity data (consumption) are also provided.
    • 5月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 26 6月, 2019
      データセットを選択
      Greenhouse Gas (GHG) emissions from burning of biomass consist of methane and nitrous oxide gases from biomass combustion of forest land cover classes ‘Humid and Tropical Forest’ and ‘Other Forests’, and of methane, nitrous oxide, and carbon dioxide gases from combustion of organic soils. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, with global coverage, relative to the period 1990-present (with annual updates), expressed as Gg CH4, Gg N2O, Gg CO2, Gg CO2eq and Gg CO2eq from both CH4 and N2O, by land cover class (humid tropical forest, other forest, organic soils) and by aggregate (burning - all categories). Implied emission factors for N2O, CH4 and CO2 as well activity data (burned area and biomass burned) are also provided.
    • 12月 2018
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 26 6月, 2019
      データセットを選択
      Greenhouse gas (GHG) emissions data from cropland are currently limited to emissions from cropland organic soils. They are those associated with carbon losses from drained histosols under cropland. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol5.html). GHG emissions are provided by country, region and special groups, with global coverage, relative to the period 1990-present (with annual updates), expressed as net emissions/removal Gg CO2 and Gg CO2eq. Implied emission factor for C, net stock change Gg C and activity data (area) are also provided.
    • 12月 2018
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 26 6月, 2019
      データセットを選択
      Annual net CO2 emission/removal from Forest Land consist of net carbon stock gain/loss in the living biomass pool (aboveground and belowground biomass) associated with Forest and Net Forest Conversion. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/index.html) and using area and carbon stocks data compiled by countries in the FAO Global Forest Resource Assessments (http://www.fao.org/forestry/fra/en/). GHG emissions are provided by country, regions and special groups, with global coverage, relative to the period 1990-present (with annual updates), expressed as net stock change Gg C, net emissions/removals Gg CO2 and CO2eq, by forest or net forest conversion and by aggregate (forest land). Implied emission factor for CO2 as well as activity data (area, net area difference, total forest area and carbon stock in living biomass) are also given.
    • 12月 2018
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 26 6月, 2019
      データセットを選択
      Greenhouse gas (GHG) emissions data from grassland are currently limited to emissions from grassland organic soils. They are those associated with carbon losses from drained histosols under grassland. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol6.html). GHG emissions are provided by country, region and special groups, with global coverage, relative to the period 1990-present (with annual updates), expressed as net emissions/removal Gg CO2 and Gg CO2eq. Implied emission factor for C, net stock change Gg C and activity data (area) are also provided.
    • 5月 2019
      ソース: Food and Agriculture Organization
      アップロード者: Knoema
      以下でアクセス: 26 6月, 2019
      データセットを選択
      Land Use Total contains all GHG emissions and removals produced in the different Land Use sub-domains, representing the three IPCC Land Use categories: cropland, forest land, and grassland, collectively called emissions/removals from the Forestry and Other Land Use (FOLU) sector. FOLU emissions consist of CO2 (carbon dioxide), CH4 (methane) and N2O (nitrous oxide) associated with land management activities. CO2 emissions/removals are derived from estimated net carbon stock changes in above and below-ground biomass pools of forest land, including forest land converted to other land uses. CH4 and N2O, and additional CO2 emissions are estimated for fires and drainage of organic soils. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/index.html). GHG emissions are provided as by country, regions and special groups, with global coverage, relative to the period 1990-present (with annual updates), expressed as Gg CO2eq from CH4 and N2O, net emissions/removals as GG CO2 and Gg CO2eq, by underlying land use emission sub-domain and by aggregate (land use total).
    • 10月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 24 10月, 2019
      データセットを選択
    • 10月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 24 10月, 2019
      データセットを選択
    • 7月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 01 8月, 2019
      データセットを選択
      Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.
    • 11月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 12 11月, 2019
      データセットを選択
      Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are disaggregated by economic activity and occupation, according to the latest versions of the International Standard Industrial Classification of All Economic Activities (ISIC) and International Standard Classification of Occupations (ISCO), respectively. Economic activity refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works. Information on occupation provides a description of the set of tasks and duties which are carried out by, or can be assigned to, one person.
    • 11月 2019
      ソース: International Labour Organization
      アップロード者: Knoema
      以下でアクセス: 12 11月, 2019
      データセットを選択
      Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts wh