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Organisation for Economic Co-operation and Development

The Organisation for Economic Co-operation and Development (OECD) is an international economic organisation of 34 countries founded in 1961 to stimulate economic progress and world trade. It is a forum of countries committed to democracy and the market economy, providing a platform to compare policy experiences, seek answers to common problems, identify good practices and co-ordinate domestic and international policies of its members.

Alle Datensätze:  A B C D E F G H I K L M N O P R S T U V W
  • A
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 03 Dezember, 2015
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    • Juni 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 20 August, 2015
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    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 20 November, 2015
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      A 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.
    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 26 Oktober, 2015
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    • April 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 07 April, 2016
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      This dataset contains bilateral commitment data on aid in support of environment sustainability and aid to biodiversity, climate change mitigation, climate change adaptation and desertification from the Development Assistance Committee (DAC) Creditor Reporting System (CRS) database. In addition to bilateral flows presented in this dataset, an integrated view of climate-related development finance by both bilateral and multilateral providers is available on this website (click on the “Project-level data” to download in Excel or follow link to the “Data visualisation portal” to see the data graphically) In their reporting to the DAC CRS, donors are requested to indicate for each activity whether or not it targets environment and the Rio Conventions (biodiversity, climate change mitigation, climate change adaptation and desertification). A scoring system of three values is used, in which aid activities are "marked" as targeting environment as the "principal objective" or a "significant objective", or as not targeting the objective. The environment marker identifies activities that are "intended to produce an improvement in the physical and/or biological environment of the recipient country, area or target group concerned" or "include specific action to integrate environmental concerns with a range of development objectives through institution building and/or capacity development". A large majority of activities targeting the objectives of the Rio Conventions fall under the DAC definition of "aid to environment". The Rio markers permit their specific identification. Watch out for double-counting! The same activity can be marked for several objectives, e.g. climate change mitigation and biodiversity. These overlaps reflect that the three Rio Conventions are interlinked and mutually reinforcing. However, care needs to be taken not to double-count the amounts when compiling the total for aid in support of more than one Convention: biodiversity-, climate change- and desertification-related aid should not be added up as this can result in double or triple-counting. Activity-level marker data that underlie the aggregate figures presented in this dataset are available for consultation and download: see "Export", "Related files".
    • Dezember 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 01 März, 2016
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      This dataset contains commitment data (since 2002) and disbursement data (since 2009) on aid in support of gender equality from the CRS database. In their reporting to the Development Assistance Committee (DAC) Creditor Reporting System (CRS), donors are requested to indicate for each activity whether or not it targets gender equality as one of its policy objectives. To qualify as “gender equality focussed,” an activity must explicitly promote gender equality and women’s empowerment. An activity can either target gender equality as its “principal objective” or as a “significant objective”. A “principal” score (2) is assigned if gender equality was an explicit objective of the activity and fundamental to its design - i.e. the activity would not have been undertaken without this objective. A “significant” score (1) is assigned if gender equality was an important, but secondary, objective of the activity - i.e. it was not the principal reason for undertaking the activity. A “not targeted” score (0) is assigned if, after being screened against the gender equality policy marker, an activity is not found to target gender equality. Activities assigned a “principal objective” score should not be considered better than activities assigned a “significant objective” score, as donors that mainstream gender equality - and thus integrate it into their projects across a range of sectors - are more likely to allocate the marker score “significant” to their aid activities. The gender equality marker allows an approximate quantification of aid flows that target gender equality as a policy objective. In marker data presentations the figures for principal and significant objectives should be shown separately and the sum referred to as the “estimate” or “upper bound” of gender equality-focussed aid. An activity can have more than one principal or significant objective. Therefore, total amounts targeting the different objectives should not be added-up to avoid double-counting. Policy markers seek information on the donor’s policy objectives which can be best assessed at the design stage of projects. This is why policy markers are applied to commitments. Policy marker data on a disbursement basis can also be compiled, but it is important to note that this does not mean the policy objectives of projects under implementation would have been re-assessed. Rather, the disbursements are linked to the qualitative information on the original commitment through project identifiers. Consequently, a project marked as gender equality focussed at the commitment stage will be flagged as gender equality focussed throughout its lifetime, unless the qualitative information was changed. Activity-level gender equality marker data that underlie the aggregate figures presented in this dataset are available for consultation and download: see “Export”, “Related files”.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 September, 2015
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      The “ALFS Summary tables” dataset is a subset of the Annual Labour Force Statistics database which presents annual labour force statistics and broad population series for 34 OECD member countries plus Brazil, Columbia and Russian Federation and 4 geographical areas (Major Seven, Euro area, European Union and OECD-Total). Data are presented in thousands of persons, in percentage or as indices with base year 2010=100.This dataset contains estimates from the OECD Secretariat for the latest years when countries did not provide data. These estimates are necessary to compile aggregated statistics for the geographical areas for a complete span of time. Since 2003, employment data by sector for the United States are compiled following the North American Industrial Classification System (NAICS); therefore they are not strictly comparable with other countries’ data.Euro area and European Union data were extracted from Eurostat (LFS Series, Detailed annual survey results in New Cronos). Euro area refer to Euro area with 17 countries (geo = ea17). European Union refers to European Union with 27 countries (geo = eu27).
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 22 Juni, 2016
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      OECD Taxing Wages. Taxing Wages provides unique information on income tax paid by workers and social security contributions levied on employees and their employers in OECD countries. In addition, this annual publication specifies family benefits paid as cash transfers. Amounts of taxes and benefits are detailed program by program, for eight household types which differ by income level and household composition. Results reported include the marginal and effective tax burden for one- and two-earner families, and total labour costs of employers.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 Mai, 2016
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      The "ALFS Summary tables" dataset is a subset of the Annual Labor Force Statistics database which presents annual labor force statistics and broad population series for 34 OECD member countries plus Brazil and 4 geographical areas (Major Seven, Euro zone, European Union and OECD-Total). Note that Chile became a member of the OECD on 7 May 2010, Slovenia on 21 July 2010, Israel on 7 September 2010 and Estonia on 9 December 2010. Chile, Estonia, Israel and Slovenia have been included in this dataset. Data are presented in thousands of persons, in percentage or as indices with base year 2010=100.
    • November 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 03 Dezember, 2015
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      The concept used is the total number of hours worked over the year divided by the average number of people in employment. The data are intended for comparisons of trends over time; they are unsuitable for comparisons of the level of average annual hours of work for a given year, because of differences in their sources. Part-time workers are covered as well as full-time workers.The series on annual hours actually worked per person in total employment presented in this table for all 34 OECD countries are consistent with the series retained for the calculation of productivity measures in the OECD Productivity database (www.oecd.org/statistics/productivity/compendium). However, there may be some differences for some countries given that the main purpose of the latter database is to report data series on labour input (i.e. total hours worked) and also because the updating of databases occur at different moments of the year.Hours Hours actually worked per person in employment are according to National Accounts concepts for 18 countries: Austria, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Italy, Korea, the Netherlands, Norway, the Slovak Republic, Spain, Sweden, Switzerland and Turkey. OECD estimates for Belgium, Ireland, Luxembourg and Portugal for annual hours worked are based on the European Labour Force Survey, as are estimates for dependent employment only for Austria, Estonia, Greece, the Slovak Republic and Slovenia. The table includes labour-force-survey-based estimates for the Russian Federation.countries: For further details and country specfic notes see: www.oecd.org/employment/outlook and www.oecd.org/employment/emp/ANNUAL-HOURS-WORKED.pdf
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 31 August, 2015
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      This dataset contains data on average annual wages per full-time and full-year equivalent employee in the total economy. Average annual wages per full-time equivalent dependent employee are obtained by dividing the national-accounts-based total wage bill by the average number of employees in the total economy, which is then multiplied by the ratio of average usual weekly hours per full-time employee to average usually weekly hours for all employees. The data, from 1990 to 2012 are available in : 2012 USD exchange rates and 2012 constant prices Aggregation and consolidation Average wages are converted in USD PPPs using 2012 USD PPPs for private consumption and are deflated by a price deflator for private final consumption expenditures in 2012 prices. in 2012 constant prices and NCU in 2012 USD PPPs and 2012 constant prices in 2012 USD exchange rates and 2012
    • Juni 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 06 Oktober, 2015
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      This table contains data on the average duration of unemployment by sex and standardised age groups (15-19, 15-24, 20-24, 25-54, 55+, total). Data are expressed in months.
  • B
    • April 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 22 April, 2016
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      The balance of payments is a statistical statement that provides a systematic summary of economic transactions of an economy with the rest of the world, for a specific time period. The transactions are for the most part between residents and non-residents of the economy. A transaction is defined as an economic flow that reflects the creation, transformation, exchange, transfer, or extinction of economic value and involves changes in ownership, of goods or assets, the provision of services, labour or capital.For countries compiling Balance of Payments Statistics in accordance with the 6th edition of the Balance of Payments and International Investment Position Manual published by the IMF (BPM6) as indicated in metadata at the country level, transactions include: the goods and services accounts, the primary income account (income account in BPM5), the secondary income account (transfers in BPM5), the capital account, and the financial account. For countries compiling Balance of Payments statistics in accordance with the 5th edition on the Balance of Payments Manual, transactions include: goods, services, and income; those involving financial claims on and liabilities to the rest of the world; and transfers. Changes in BPM6 compared to BPM5 are often a consequence of a stricter application of the change of ownership principle in particular in the goods and services accounts. They relate to transactions on goods and services (merchanting, goods for processing, Insurance), income (investment income), and financial operations (direct investment).Seasonal adjustment - Where the seasonal adjustment has been carried out by the OECD, the X-12 Reg-ARIMA method is used.  
    • Februar 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 18 Februar, 2015
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      Since the collection of 2009 data, the scope of the OECD Global Insurance Statistics questionnaire has been expanded. These changes led to the collection of key balance sheet and income statement items for direct insurance and reinsurance sectors, such as: gross claims paid, outstanding claims provision (changes), gross operating expenses, commissions, total assets, gross technical provisions (of which: unit-linked), shareholder equity, net income.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 15 September, 2015
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    • Juni 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 24 März, 2016
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      The OECD broadband portal provides access to a range of broadband-related statistics gathered by the OECD. Policy makers must examine a range of indicators which reflect the status of individual broadband markets. The OECD broadband speed tests by country show the official measurements of actual access network broadband speed. The OECD broadband map shows national broadband statistics in OECD countries. Mobile broadband penetration has risen to 85.4% in the OECD area, meaning more than four wireless subscriptions for every five inhabitants, according to data for June 2015 released by the OECD .
    • Juni 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 23 März, 2016
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      The OECD broadband portal provides access to a range of broadband-related statistics gathered by the OECD. Policy makers must examine a range of indicators which reflect the status of individual broadband markets. The OECD broadband speed tests by country show the official measurements of actual access network broadband speed. The OECD broadband map shows national broadband statistics in OECD countries. Mobile broadband penetration has risen to 85.4% in the OECD area, meaning more than four wireless subscriptions for every five inhabitants, according to data for June 2015 released by the OECD .
    • Juni 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 24 März, 2016
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      The OECD broadband portal provides access to a range of broadband-related statistics gathered by the OECD. Policy makers must examine a range of indicators which reflect the status of individual broadband markets. The OECD broadband speed tests by country show the official measurements of actual access network broadband speed. The OECD broadband map shows national broadband statistics in OECD countries. Mobile broadband penetration has risen to 85.4% in the OECD area, meaning more than four wireless subscriptions for every five inhabitants, according to data for June 2015 released by the OECD .
    • Juni 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 24 März, 2016
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      The OECD broadband portal provides access to a range of broadband-related statistics gathered by the OECD. Policy makers must examine a range of indicators which reflect the status of individual broadband markets. The OECD broadband speed tests by country show the official measurements of actual access network broadband speed. The OECD broadband map shows national broadband statistics in OECD countries. Mobile broadband penetration has risen to 85.4% in the OECD area, meaning more than four wireless subscriptions for every five inhabitants, according to data for June 2015 released by the OECD .
    • Juni 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 23 März, 2016
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      The OECD broadband portal provides access to a range of broadband-related statistics gathered by the OECD. Policy makers must examine a range of indicators which reflect the status of individual broadband markets. The OECD broadband speed tests by country show the official measurements of actual access network broadband speed. The OECD broadband map shows national broadband statistics in OECD countries. Mobile broadband penetration has risen to 85.4% in the OECD area, meaning more than four wireless subscriptions for every five inhabitants, according to data for June 2015 released by the OECD . Note: unit of measure of indicators related to Internet selling and purchasing by industry is percentage of businesses with 10 or more employees in each industry group.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 06 Mai, 2016
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    • April 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 21 August, 2015
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      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2005 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics performed in the business enterprise sector by industry according to the International Standard Industrial Classification (ISIC) revision 3.1. Data at the industry level are presented beginning 1987, year when most of the countries converted from ISIC rev.2 to the current ISIC rev. 3 classification. This breakdown between industries is, in principle, made at the enterprise level, although some countries are able to break down R&D data for multi product enterprises between their main lines of business. National statistical regulations prevent publication of results where there are very few firms in the given category, hence the many gaps in the tables. Depending on the country, R&D institutes serving enterprises are either classified with the industry concerned, or grouped under “Research and Development” (ISIC rev.3.1, Division 73). When these R&D institutes are classified with the industry served, the evaluation of R&D in these industries is more complete and more comparable between countries for the industries concerned. This results, however, in an underestimation of the percentage of BERD performed by the service sector as compared with other countries. The Frascati Manual recommendation concerning data on R&D by industry is to report BERD on an enterprise basis (see FM section 3.4). When this is interpreted strictly, all the BERD of a diversified enterprise will be allocated to the industrial class of its principal activity. In circumstances where a few large firms dominate R&D spending in several areas, this can and does lead to underestimates of R&D associated with the secondary activities of the firms. Overall, R&D is therefore overestimated for some industries and underestimated for others. However, not all countries follow a strict enterprise basis for allocating R&D expenditures to industrial classes. Some countries make a disaggregation of the R&D of their largest, diversified firms into a number of different activities. In other countries, the enterprise approach has been abandoned and data are reported on a product field basis. This is why two classification criteria for BERD by industry are included in this view of “BERD by industry” (see the variable CLASSIFICATION CRITERIA: Main activity or Product field) depending on which approach is more closely followed by each country (only a few countries currently collect these data both ways and are therefore included according to both criteria)). The two tables that follow, “BERD by industry and source of funds” and “BERD by industry and type of costs” present data for only one of the criteria, depending on the country.
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 April, 2016
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      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2005 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics performed in the business enterprise sector by industry according to the International Standard Industrial Classification (ISIC) revision 3.1. and by source of funds (business enterprise, government, other national funds, and funds from abroad). Data at the industry level are presented beginning 1987, year when most of the countries converted from ISIC rev.2 to the current ISIC rev. 3 classification. This breakdown between industries is, in principle, made at the enterprise level, although some countries are able to break down R&D data for multi product enterprises between their main lines of business. National statistical regulations prevent publication of results where there are very few firms in the given category, hence the many gaps in the tables. Depending on the country, R&D institutes serving enterprises are either classified with the industry concerned, or grouped under “Research and Development” (ISIC rev.3.1, Division 73). When these R&D institutes are classified with the industry served, the evaluation of R&D in these industries is more complete and more comparable between countries for the industries concerned. This results, however, in an underestimation of the percentage of BERD performed by the service sector as compared with other countries. The Frascati Manual recommendation concerning data on R&D by industry is to report BERD on an enterprise basis (see FM section 3.4). When this is interpreted strictly, all the BERD of a diversified enterprise will be allocated to the industrial class of its principal activity. In circumstances where a few large firms dominate R&D spending in several areas, this can and does lead to underestimates of R&D associated with the secondary activities of the firms. Overall, R&D is therefore overestimated for some industries and underestimated for others. However, not all countries follow a strict enterprise basis for allocating R&D expenditures to industrial classes. Some countries make a disaggregation of the R&D of their largest, diversified firms into a number of different activities. In other countries, the enterprise approach has been abandoned and data are reported on a product field basis. This is why two classification criteria for BERD by industry are included in the table “BERD by industry” (see the variable CLASSIFICATION CRITERIA: Main activity or Product field) depending on which approach is more closely followed by each country (only a few countries currently collect these data both ways and are therefore included according to both criteria). However, this table “BERD by industry and source of funds” and the one that follows, “BERD by industry and type of costs” present data for only one of the criteria, depending on the country.
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 April, 2016
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      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2000 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics performed in the business enterprise sector by industry according to the International Standard Industrial Classification (ISIC) revision 3.1. and by type of costs (current expenditure, capital expenditure). Data at the industry level are presented beginning 1987, year when most of the countries converted from ISIC rev.2 to the current ISIC rev. 3 classification. This breakdown between industries is, in principle, made at the enterprise level, although some countries are able to break down R&D data for multi product enterprises between their main lines of business. National statistical regulations prevent publication of results where there are very few firms in the given category, hence the many gaps in the tables. Depending on the country, R&D institutes serving enterprises are either classified with the industry concerned, or grouped under “Research and Development” (ISIC rev.3.1, Division 73). When these R&D institutes are classified with the industry served, the evaluation of R&D in these industries is more complete and more comparable between countries for the industries concerned. This results, however, in an underestimation of the percentage of BERD performed by the service sector as compared with other countries. The Frascati Manual recommendation concerning data on R&D by industry is to report BERD on an enterprise basis (see FM section 3.4). When this is interpreted strictly, all the BERD of a diversified enterprise will be allocated to the industrial class of its principal activity. In circumstances where a few large firms dominate R&D spending in several areas, this can and does lead to underestimates of R&D associated with the secondary activities of the firms. Overall, R&D is therefore overestimated for some industries and underestimated for others. However, not all countries follow a strict enterprise basis for allocating R&D expenditures to industrial classes. Some countries make a disaggregation of the R&D of their largest, diversified firms into a number of different activities. In other countries, the enterprise approach has been abandoned and data are reported on a product field basis. This is why two classification criteria for BERD by industry are included in the table “BERD by industry” (see the variable CLASSIFICATION CRITERIA: Main activity or Product field) depending on which approach is more closely followed by each country (only a few countries currently collect these data both ways and are therefore included according to both criteria). However, this table “BERD by industry and type of costs” and the preceding one “BERD by industry and source of funds” present data for only one of the criteria, depending on the country.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 11 September, 2015
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      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2005 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics performed in the business enterprise sector. Data include total business enterprise intramural expenditure on R&D by size class and source of funds.
    • April 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 18 Mai, 2016
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      This table presents research and development (R&D) statistics on personnel in the business enterprise sector. Measured in full-time equivalent are the number of total R&D personnel and researchers in the business enterprise sector by industry according to the International Standard Industrial Classification (ISIC) revision 3.1. Data at the industry level are presented beginning 1987, year when most of the countries converted from ISIC rev.2 to the current ISIC rev. 3 classification.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 03 Mai, 2016
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      The business tendency survey indicators cover a standard set of indicators for four economic sectors: manufacturing, construction, retail trade and other services. This includes an indicator of overall business conditions or business confidence in each sector. The consumer opinion survey indicators cover a restricted set of indicators on consumer confidence, expected economic situation and price expectations.Business and consumer opinion (tendency) surveys provide qualitative information that has proved useful for monitoring the current economic situation. Typically they are based on a sample of enterprises or households and respondents are asked about their assessments of the current situation and expectations for the immediate future. For enterprise surveys this concerns topics such as production, orders, stocks etc. and in the case of consumer surveys their intentions concerning major purposes, economic situation now compared with the recent past and expectations for the immediate future. Many survey series provide advance warning of turning points in aggregate economic activity as measured by GDP or industrial production. Such series are known as leading indicators in cyclical analysis. These types of survey series are widely used as component series in composite leading indicators. The main characteristic of these types of surveys is that instead of asking for exact figures, they usually ask for the direction of change e.g. a question on tendency by reference to a “normal” state, e.g. of production level. Possible answers are generally of the three point scale type e.g. up/same/down or above normal/normal/below normal for enterprise surveys and of the five point scale type e.g. increase sharply/increase slightly/remain the same/fall slightly/fall sharply for consumer surveys. In presenting the results as a time series, only the balance is shown. That is “same” or “normal” answers are ignored and the balance is obtained by taking the difference between percentages of respondents giving favourable and unfavourable answers.Virtually all business tendency and consumer opinion survey data are presented as time series of balances in this dataset, either in raw or seasonally adjusted form. Very few series are presented as indices, and where these exist they have generally been converted from underlying balances by countries before submitting the data to the OECD.  
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 26 August, 2015
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      Institutional coverage As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Item coverage Business written in the reporting country on a gross and net premium basis. It contains a breakdown between domestic companies, foreign-controlled companies and branches and agencies or foreign companies.
  • C
    • August 2013
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 24 September, 2014
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      Transactions within the international production network and imports and exports of final goods and services can be estimated by using an inter-country economic model based on multi-regional input-output (MRIO) modelling techniques. In order to achieve this, national Input-Output tables are first converted to a common currency (nominal USD) and the import matrices are disaggregated to separate bilateral flows of goods and services. A range of adjustments to deal with measurement issues such as re-exports; unspecified partners and commodities; and missing data, particularly for trade in services, are necessary before the analysis.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 August, 2014
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      Statistical population The focus of this dataset is to provide comprehensive quantitative information on marketable and non-marketable central government debt instruments in all OECD member countries. The coverage of the data is limited to central government debt issuance and excludes therefore state and local government debt and social security funds.
    • April 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 November, 2015
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      This table reports statutory central government personal income tax rates for wage income plus the taxable income thresholds at which these statutory rates apply. The table also reports basic/standard tax allowances, tax credits and surtax rates. The information is applicable to a single person without dependents. The threshold, tax allowance and tax credit amounts are expressed in national currencies Tapered means that the tax relief basic amount is reduced with increasing income Further explanatory notes may be found in the Explanatory Annex This data represents part of the data presented within the Excel file “Personal income tax rates and thresholds for central governments - Table I.1”. The Data for 1981 to 1999 is not included here within as not all the data for these years is either available, or can be verified. The OECD tax database provides comparative information on a range of tax statistics - tax revenues, personal income taxes, non-tax compulsory payments, corporate and capital income taxes and taxes on consumption - that are levied in the 34 OECD member countries.” Tax policy Analysis homepage OECD Tax Database Taxing Wages Dissemination format(s) This data is also presented through the OECD Tax database webpage. OECD Tax Database
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 August, 2014
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      Institutional coverage As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Item coverage Commissions in the reporting country, containing a breakdown between domestic companies, foreign-controlled companies and branches and agences of foreign companies.
    • Juni 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 11 September, 2014
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      The OECD Science, Technology and Industry Outlook 2012 presents, in a series of country profiles, the main features, strengths and weaknesses of national STI systems and major recent changes in national STI policy. The statistical dimension of the country profiles has drawn on the work and empirical research conducted by the OECD on the measurement of innovation and the development of internationally comparable STI indicators for policy analysis.   
    • April 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 20 April, 2016
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      CLIs are calculated for 33 OECD countries (Iceland is not included), 6 non-member economies and 8 zone aggregates. A country CLI comprises a set of component series selected from a wide range of key short-term economic indicators. CLIs, reference series data (see below) and standardised business and consumer confidence indicators are presented in various forms. For further information on interpretation and comparability of various form please refer to the presentation section of the OECD CLI methodology document: http://www.oecd.org/std/leading-indicators/41629509.pdf. The composite leading indicator is a times series, formed by aggregating a variety of component indicators which show a reasonably consistent relationship with a reference series (e.g. industrial production IIP up to March 2012 and since then the reference series is GDP) at turning points. The OECD CLI is designed to provide qualitative information on short-term economic movements, especially at the turning points, rather than quantitative measures. Therefore, the main message of CLI movements over time is the increase or decrease, rather than the amplitude of the changes. The OECD’s headline indicator is the amplitude adjusted CLI. In practice, turning points in the de-trended reference series have been found about 4 to 8 months (on average) after the signals of turning points had been detected in the headline CLI. The full list of component series used in the calculation of each country's CLI is available on the OECD website at: http://www.oecd.org/std/leading-indicators/oecdcompositeleadingindicatorsreferenceturningpointsandcomponentseries.htm . Detailed information on the OECD methodology for CLIs can be found on the OECD website at http://stats.oecd.org/mei/default.asp?rev=2 .
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 10 September, 2015
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    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 14 September, 2015
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      As a general rule in national accounts, the financial flows have to be recorded on a non-consolidated basis. However, consolidation data can be more significant for certain kind of analysis.In Subject 610Q, data are reported on a consolidated basis, which means that counterparts’ transactions of financial assets or liabilities of sub-sectors of the same sector and of institutional units of the same sub-sector are eliminated.As a general principal, the valuation of the financial assets and liabilities are at market value, which is the basic reference for valuation in the SNA.Definitions and concepts are currently in line with the 1993 System of national Accounts (SNA 1993) (see 1993sna.pdf link). For the new 2008 SNA, which will be implemented as from 2014, see SNA2008.pdf link. French version, forthcoming (see sna2008.asp link).Unit of measure used - Statistics are reported at current prices in millions of national currency.
    • Juni 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 21 Juni, 2016
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      The 'Consumer Prices (MEI)' dataset contains predominantly monthly statistics, and associated statistical methodological information, for the 34 OECD member countries and for some non-member countries. The ‘Consumer Prices (MEI)’ dataset itself contains statistics on Consumer Price Indices. The data series presented have been chosen as the most relevant prices statistics in the MEI database for which comparable data across countries is available. In all cases a lot of effort has been made to ensure that the data are internationally comparable across all countries presented and that all the subjects have good historical time-series’ data to aid with analysis. Data are available monthly for all the countries except for Australia and New Zealand (quarterly data), and are presented as an index where the year 2010 is the base year.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 07 September, 2015
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      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
    • Mai 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 28 Mai, 2015
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      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
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      The objective of the CRS Aid Activity database is to provide a set of readily available basic data that enables analysis on where aid goes, what purposes it serves and what policies it aims to implement, on a comparable basis for all DAC members. Data are collected on individual projects and programmes. Focus is on financial data but some descriptive information is also made available.
  • D
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 12 September, 2015
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      This dataset contains three earnings-dispersion measures - ratio of 9th-to-1st, 9th-to-5th and 5th-to-1st - where ninth, fifth (or median) and first deciles are upper-earnings decile limits, unless otherwise indicated, of gross earnings of full-time dependent employees. The dataset also includes series on:the incidence of low-paid workers defined as the share of full-time workers earning less than two-thirds of gross median earnings of all full-time workers;the incidence of high of high-paid workers defined as the share of full-time workers earning more than one-and-half time gross median earnings of all full-time workers;gender wage gap unadjusted and defined as the difference between median wages of men and women relative to the median wages of men.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      National values have been computed based on regional estimates. For this reason, it is possible that in some cases these values differ from national statistics
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 01 April, 2016
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      The objective of this dataset is to trace net changes in terms of volume in the growing stock of standing wood on forest land. It shows data underlying the indicator on the intensity of use of forest resources. This indicator relates actual fellings to annual productive capacity (i.e. gross increment). Forest depletion and growth describe balances or imbalances in different types of forests. The intensity of use of forest resources reflects various forest management methods and their sustainability. These data should be read in connection with other indicators of the OECD Core Set, in particular with indicators on land use changes and forest quality (species diversity, forest degradation), and be complemented with data on forest management practices and protection measures. In interpreting these data, it should be borne in mind that definitions and estimation methods vary among countries.
    • Februar 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 19 Februar, 2015
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      As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business datawhere composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Click to collapse Item coverage Outstanding investment by direct insurance companies, classified by investment category, by the companies' nationality and by its destination (domestic or foreign). As of 2009, investment data exclude assets linked to unit-linked products sold to policyholders.
    • Dezember 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 25 August, 2015
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      The data are on cash basis. The figures exclude local government revenues as the data are not available. Heading 5212: In ECLAC data, property tax on motor vehicles is classified in category 4000. Source: Subsecretaría de Ingresos Públicos, Ministry of Economy and Production.
    • Dezember 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 30 August, 2015
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      Data are on a fiscal year basis beginning 1st April. From 1990, data are on accrual basis. The figures for different groups of taxes are reported on different reporting bases, namely: * Social security contributions (heading 2000) : in principle accrual basis, * Central government taxes : accrual basis (revenues accrued during the fiscal year plus cash receipts collected before the end of May (the end of April until 1977), * Local government taxes : accrual basis (due to be paid during the fiscal year and cash receipts collected before the end of May). The Japanese authorities take the view that the Enterprise tax (classified in 1100 and 1200) and the Mineral product tax (classified in 5121) should be classified in heading 6000 since under articles 72 and 519 of the Local Tax Law these taxes are regarded as levies on the business or mining activity itself. Heading 2000 includes some unidentifiable voluntary contributions. Heading 2300: Includes contibutions to the National pension, National Health Insurance and the Farmer's pension fund. Contributions to the Farmer's pension fund are not available for the years before 1999. Heading 4100: Municipal property tax, includes Prefectural property tax from 1990 to 1994 because data is not available to provide a breakdown. Heading 5121: Municipal tobacco tax, includes Prefectural tobacco tax from 1990 to 1994 because data is not available to provide a breakdown. Heading 5121: In sub-item Petroleum and coal tax, the data before 2003 refer to petroleum tax.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 24 August, 2015
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      From 1981 the figures take into account the classification procedures set out in the OECD Interpretative Guide. Consequently they are not completely comparable with the figures for earlier years though the amounts involved are quite small. Heading 1000: Includes a tax on property 'Contribucion Rustica' which would be more appropriately classified in 4110, and the 'Licencia fiscal industrial and professionales' which, because it is a tax levied by reference to the size of the firm, energy input, etc, would be more appropriately classified in 6000. The data necessary to provide a breakdown is not available. All subdivisions are estimated. Heading 2300: Contributions paid by self-employed were shown under heading 2100 until 1982. Heading 4100: Most of these receipts fall under 4110. Heading 4400: In 1988 revenues from taxes on legal Acts issued by Autonomous Communities (Local) are included in 4400. Heading 5121 comprises certain local levies which may include non-tax revenues. Source: Informacion Estatistica del Ministerio de Hacienda (for national taxes). Cuentas de las Administraciones Publicas (for local taxes and social security) both published by Secretaria General Tecnica del Ministerio de Hacienda.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 Oktober, 2015
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      This table contains data on discouraged workers who are persons not in the labour force who believe that there is no work available due to various reasons and who desire to work. Data are broken down by sex and standardised age groups (15-24, 15-64, 25-54, 55-64, 65+, total).
    • November 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 03 Dezember, 2015
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    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 20 April, 2016
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      1. ccTLDs stands for country code Top Level Domains.2. gTLDs - stands for generic top-level domains.
    • Januar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 18 März, 2016
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  • E
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      Tables show earmarked grants classified into the 10 functions (or policy areas) for which they are disbursed. Functions are the same as used in the Classification of Functions of Government (COFOG) by the System of National Accounts. A 'miscellaneous' category has been added to these 10 functions to allow for situations where a precise breakdown by function is not available.
    • Mai 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 22 Mai, 2014
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      The OECD Long Term Baseline analyzes the major economic trends beyond the OECD short-term projections. For all OECD economies, and the major non-OECD economies, it provides coverage of components of potential growth, fiscal balances and debt accumulation, domestic saving and investment balances, and external balances (through the current account). It also includes interest rates consistent with those projections. The database contains annual data to 2060. Variables are defined in such a way that they are as homogenous as possible for the countries covered. Breaks in underlying series are corrected as far as possible. Sources for the historical data are publications of national statistical agencies and OECD statistical publications such as the Annual National Accounts, the International Monetary Fund, the United Nations, and Eurostat.
    • November 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 23 November, 2015
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      The OECD Economic Outlook analyses the major economic trends over the coming 2 to 3 years. It provides in-depth coverage of the main economic issues and the policy measures required to foster growth in each member country. Forthcoming developments in major non-OECD economies are also evaluated in detail. Each edition of the Outlook provides a unique resource to keep abreast of world economic developments. The OECD Economic Outlook database is a comprehensive and consistent macroeconomic database of the OECD economies, covering expenditures, foreign trade, output, labour markets, interest and exchange rates, balance of payments, and government debt. For the non-OECD regions, foreign trade and current account series are available. The database contains annual and quarterly data (subset) for the projection period. Variables are defined in such a way that they are as homogenous as possible for the countries covered. Breaks in underlying series are corrected as far as possible. Sources for the historical data are publications of national statistical agencies and OECD statistical publications such as the Quarterly National Accounts, the Annual National Accounts, the Labour Force Statistics and the Main Economic Indicators. The cut-off date for information used in the compilation of the projections was the 30 October 2015. Concerning the aggregation of world trade, a new composition has been introduced, since projections are now made for the major non-OECD economies. Thus, besides OECD and the OECD euro area, the following new regions are available: Dynamic Asian Economies (Chinese Taipei, Hong Kong, Malaysia, the Philippines, Singapore, Thailand, Vietnam); Oil Producers (Azerbaijan, Kazakhstan, Turkmenistan, Brunei, Timor-Leste, Bahrain, Iran, Iraq, Kuwait, Libya, Oman, Qatar, Saudi Arabia, United Arab Emirates, Yemen, Ecuador, Trinidad and Tobago, Venezuela, Algeria, Angola, Chad, Rep. of Congo, Equatorial Guinea, Gabon, Nigeria, Sudan); with the remaining countries in a residual 'Rest of the World' group.
    • September 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 21 Oktober, 2015
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      This table contains data on economic short-time workers by professional status (employees or total employment). Economic short-time workers comprise workers who are working less than usual due to business slack, plant stoppage, or technical reasons. However, the definitions are not harmonised which hampers the comparison across countries. Data are broken down professional status - employees, total employment - by sex and by standardised age groups (15-24, 25-54, 55+, total).
    • September 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 23 November, 2015
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      Countries report expenditures by public institutions, government-dependent private institutions, and independent private institutions. These expenditure figures are intended to represent the total cost of services provided by each type of institution, without regard to sources of funds (whether they are public or private). Expenditure is classified into current and capital expenditure. Current expenditure is then broken down, into expenditure on compensation of personnel, and expenditure on other (non-personnel) resources.
    • Juni 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 Juni, 2016
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      The classification of personnel is based on functions and organises staff into four main functional categories: 1) Instructional Personnel; including two sub-groups: A. Classroom Teachers (ISCED 0-4) and Academic Staff (ISCED 5-6); and B. Teacher Aides (ISCED 0-4) and Teaching / Research Assistants (ISCED 5-6); 2) Professional Support for Students; including two sub-groups: A. Pedagogical Support (ISCED 0-4) and Academic Support (ISCED 5-6); B. Health and Social Support (ISCED 0-6); 3) Management/Quality Control/Administration; including four subgroups: A. School Level Management (ISCED 0-6); B. Higher Level Management (ISCED 0-6); C. School Level Administrative Personnel (ISCED 0-6); and D. Higher Level Administrative Personnel (ISCED 0-6); 4) Maintenance and Operations Personnel.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 August, 2014
      Datensatz auswählen
      The Pensions at a Glance indicators, covering all 34 OECD countries, are designed to show future entitlements for workers who entered the labour market in 2008 and spend their entire working lives under the same set of rules. The results presented here include all mandatory pension schemes for private-sector workers, regardless of whether they are public or private.
    • August 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 21 August, 2014
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      These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2012 : OECD COUNTRIES. They comprise the summary of agricultural support estimates for OECD countries.
    • Oktober 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 13 Oktober, 2014
      Datensatz auswählen
      These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2012 : OECD COUNTRIES. They comprise the summary of agricultural support estimates for OECD countries.
    • August 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 26 August, 2014
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      This dataset provides selected information on emissions of traditional air pollutants: emission data are based upon the best available engineering estimates for a given period; they concern man-made emissions of sulphur oxides (SOx), nitrogen oxides (NOx), particulate matter, carbon monoxide (CO) and volatile organic compounds (VOC). The share of human activities as a source in total emissions of traditional air pollutants varies depending on the type of pollutant; most SOx emissions are man-made whereas CO and NOx emissions are mainly of natural origin.
    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 02 November, 2015
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    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 Oktober, 2015
      Datensatz auswählen
      This table contains a distribution of workers by job tenure intervals. Data are broken down by professional status - employees, self-employed, total employment – sex, five-year and broad age groups (15-24, 25-54, 55-64, 15-64, total, etc.).Job tenure is measured by the length of time workers have been in their current or main job or with their current employer. This information is valuable for estimating the degree of fluidity in the labour market and in identifying the areas of economic activity where the turnover of labour is rapid or otherwise. Data are so far reported for a number of European countries and will be expanded to cover a greater number of countries.Unit of measure used - Data are expressed years. Example: 1.5 = 1 year and 6 months.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 Oktober, 2015
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      This table contains the tenure composition (as a percentage of all job tenures). Data are broken down by professional status - employees and total employment - sex, five-year and broad age groups (15-24, 25-54, 55-64, 15-64, total, etc.).Job tenure is measured by the length of time workers have been working with their current employers. This information is valuable for estimating the degree of fluidity in the labour market and in identifying the areas of economic activity where the turnover of labour is rapid or otherwise. Data are reported 32 OECD countries and are missing for Israel and New Zealand as they are collected in their labour force surveys.Unit of measure used - Data are expressed as percentages.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 Dezember, 2015
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      Job tenure is measured by the length of time workers have been in their current or main job or with their current employer. This information is valuable for estimating the degree of fluidity in the labour market and in identifying the areas of economic activity where the turnover of labour is rapid or otherwise. Data are so far reported for a number of European countries and will be expanded to cover a greater number of countries.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 Oktober, 2015
      Datensatz auswählen
      This table contains data on permanent and temporary workers based on the type of work contract of their main job. Data are further broken down by professional status - employees, total employment - by sex and by standardised age groups (15-19, 15-24, 20-24, 25-54, 55-64, 65+, total). Unit of measure used - Data are expressed in thousands of persons.
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 31 März, 2016
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      The Fisheries Committee (COFI) from the Trade and Agriculture Directorate (TAD) collects, on an annual basis from all its participating countries, data on landings, aquaculture production, fleet, employment in the fisheries sector, and government financial transfers. Data are collected from Fisheries Ministries, National Statistics Offices and other institution designated as an official data source. Concepts Classifications Data are collected by the OECD using the methodologies established by the Coordinating Working Party on Fishery Statistics (CWP) (www.fao.org/fishery/cwp/search/en). This inter-agency body, created in 1960 to develop common procedures and standards for the collation of fisheries statistics, provides technical advice on fishery statistical matters. Its handbook of Fishery Statistical Standards comprises definitions of the various concepts used in fishery statistics, with the exception of Government Financial Transfers which is unique to the OECD. All other statistics are based on the CWP definitions. The OECD, a partner with the CWP, additionally collects information on values for its landings and records the breakdown between the types of landings (i.e. landings in domestic ports, landings in foreign ports) data series which are not collected by the FAO. While a number of countries cover landings in a similar fashion, the same does not hold true for capacity (feet/meters, GRT/engine powers), or for employment for which both Full-time equivalents or numbers of people are used. The OECD therefore does not duplicate FAO statistics but requests complementary information to feed its analytical work.
    • August 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 September, 2014
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    • August 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 September, 2014
      Datensatz auswählen
    • Oktober 2013
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      National values have been computed based on regional estimates. For this reason, it is possible that in some cases these values differ from national statistics.
    • September 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 21 Oktober, 2015
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      Agriculture can have significant impacts on the environment as it uses on average over 40% of water and land resources in OECD countries. The impacts occur on and off farm, including both pollution and degradation of soil, water and air, as well as the provision of ecological goods and services, such as biodiversity and providing a sink for greenhouse gases. Most OECD countries are tracking the environmental performance of agriculture, which is informing policy makers and society on the state and trends in agri-environmental conditions, and can provide a valuable aid to policy analysis (Chapter 4). As countries are increasingly using a wide range of policy measures to address agri-environmental issues, indicators provide crucial information to monitor and analyse the effects of those policies on the environment. They are also enriching the understanding and analysis of the environmental effects of possible future policy scenarios and agricultural projections. This report provides the latest and most comprehensive data across OECD countries on the environmental performance of agriculture since 1990. A set of agri-environmental indicators (Annex 1, Section II) has been developed through several specific theme-focused workshops involving OECD country analysts and scientific experts, complemented with thorough reviews of the literature. The OECD’s Driving Force-State-Response model (DSR) is the organising framework for developing the indicators.
    • Juni 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 07 Juni, 2016
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      Unit of measure used Environmental protection (EP) includes all purposeful activities directly aimed at the prevention, reduction and elimination of pollution or any other degradation of the environment resulting from production or consumption processes. The scope of Environmental Protection is defined according to the Classification of Environmental Protection Activities (CEPA), which distinguishes nine different environmental domains. Activities such as energy and material saving are only included to the extent that they mainly aim at environmental protection. An important example is recycling which is included only to the extent that it constitutes a substitute for waste management. Excluded are: (i) activities that, while beneficial to the environment, primarily satisfy technical needs or health and safety requirements for the protection of the workplace. (ii) expenditure linked to mobilisation of natural resources (e.g., water supply). (iii) calculated cost items such as depreciation (consumption of fixed capital) or the cost of capital as this questionnaire only records actual outlays. (iv) payments of interest, fines and penalties for non-compliance with environmental regulations or compensations to third parties etc., as they are not directly linked with an environmental protection activity. Environmental Protection Expenditure can be evaluated both according to the abater principle and the financing principle. This distinction makes it possible to aggregate different sectors and industries without double counting. Expenditure according to the abater principle (EXP I), includes all expenditure that the sector has for measures they themselves execute. Any economic benefits directly linked with the environmental protection activities (Receipts from by-products) are deducted in order to calculate the net amount of money spent by the sector for their own activities. The financing principle (EXP II) measures how much money a particular sector (directly) contributes to overall environmental protection activities, wherever they are executed. This means that the part of EXP I that was directly financed by others (through subsidies or revenues received) should be deducted, while the part of EXP I in other sectors that this sector finances directly (through subsidies or fees paid) should be added. The framework is based on double entry bookkeeping, where each activity and expenditure item has an abater (producer) and a financing side. This means that much expenditure by specialised producers is financed by the users of their services, mainly business sector and households. This will be recorded as Revenues for the Specialised producers (Table 4), and fees/purchases in Business and Households (Tables 2 and 3). Specialised producers include the production of environmental protection services by public and private corporations or quasi-corporations for the use of other units, mainly financed by the users of these services. These are mainly activities within ISIC Rev. 4/NACE Rev. 2 division and classes 37, 38.1, 38.2 and 39 such as: 37 Sewerage, 38.1 Waste collection, 38.2 Waste treatment and disposal, 39  Remediation activities and other waste management services. This sector is the sum of two components: a) Public specialised producers: All corporations and quasi-corporations that are subject to control by government units. Control is defined as the ability to determine general corporate policy by choosing appropriate directors, if necessary (Table 4A). b) Private specialised producers: All corporations and quasi-corporations that are not subject to control by government units (Table 4B). Specialised producers could also include for example the activities of e.g. volunteer environmental organisations or secondary environmental activities. These should be entered along with a footnote describing the coverage. CEPA domains: a column "pollution abatement and control" (PAC) has been kept in the questionnaire to ensure continuity with earlier data series.
    • September 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 Oktober, 2014
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      Countries report expenditures by sources of funds: Governement (central, regional, local); International agencies and other foreign sources; Households and Other private entities (including firms and religious institutions and other non-profit organisations). Three types of financial transactions can be distinguished: -direct expenditure/payments on educational institutions -Intergovernmental transfers for education -Transfers to students or households and to other private entities.
  • F
    • Juni 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 24 Juni, 2016
      Datensatz auswählen
      OECD Factbook provides a global overview of today's major economic, social and environmental indicators which cover a wide range of areas: agriculture, economic production, education, energy, environment, foreign aid, health, industry, information and communications, international trade, labor force, population, taxation, public expenditure and R&D. More countries than ever are covered in greater detail, enabling direct comparisons for many indicators between OECD Members and Brazil, China, India, Indonesia, Russian Federation and South Africa.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 12 Mai, 2016
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    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 12 Mai, 2016
      Datensatz auswählen
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 17 Mai, 2016
      Datensatz auswählen
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 12 Mai, 2016
      Datensatz auswählen
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 12 Mai, 2016
      Datensatz auswählen
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 11 Mai, 2016
      Datensatz auswählen
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 11 Mai, 2016
      Datensatz auswählen
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 12 Mai, 2016
      Datensatz auswählen
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 11 Mai, 2016
      Datensatz auswählen
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 Oktober, 2015
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      It presents the final consumption expenditure of households broken down by the COICOP (Classification of Individual Consumption According to Purpose) classification and by durability.  It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA. In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2010). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      National Accounts - Volume IIIa - Financial Accounts - Flows, which record, by type of financial instruments, the financial transactions between institutional sectors, and are presented in two tables: Financial accounts, consolidated and Financial accounts, non-consolidated.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      National Accounts - Volume IIIa - Financial Accounts - Flows, which record, by type of financial instruments, the financial transactions between institutional sectors, and are presented in two tables: Financial accounts, consolidated and Financial accounts, non-consolidated.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 Oktober, 2015
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      National Accounts - Volume IIIb - Financial Balance Sheets - Stocks, which record the stocks of financial assets and liabilities by institutional sectors, at the end of the accounting period, and are presented in two tables: Balance sheets for financial assets and liabilities, consolidated and Balance sheets for financial assets and liabilities, non consolidated.Statistics are reported at current prices in millions of national currency and in millions of Euros for OECD countries which are members of the Euro zone: Austria, Belgium, Estonia, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Slovak Republic, Slovenia and Spain.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 25 August, 2015
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      The financial indicators in this dataset are derived from OECD countries’ financial accounts (transactions): they give a picture of the short-term behaviour of institutional sectors. They comprise for instance: Net financial transactions of the general government, as a percentage of Gross Domestic Product (GDP), which corresponds to the general government deficit; Transactions in financial assets of Households and NPISHs, as a percentage of Households Gross Disposable Income (GDI); Transactions in liabilities of Households and NPISHs, as a percentage of GDI.
    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 Februar, 2016
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      The financial indicators in this dataset are constructed from OECD countries’ financial balance sheets (stocks): these ratios are considered as relevant to analyse the position and performance of the various institutional sectors. They comprise for instance: Financial net worth of Households and NPISHs, as a percentage of GDI; Non-financial corporations debt to equity ratio; Private sector debt; Leverage of the banking sector; General government debt, as a percentage of GDP.
    • November 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 25 Februar, 2016
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    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 27 Juni, 2016
      Datensatz auswählen
      Fisheries fleet: The FAO has a two dimensional definition, of which the OECD only uses the concept of fishing vessel. Fishery Fleet: The term "fishery fleet" or "fishery vessels" refers to mobile floating objects of any kind and size, operating in freshwater, brackishwater and marine waters which are used for catching, harvesting, searching, transporting, landing, preserving and/or processing fish, shellfish and other aquatic organisms, residues and plants.Fishing vessel: The term "fishing vessel" is used instead when the vessel is engaged only in catching operations. Gross Register Tonnage: The Gross Register Tonnage represents the total measured cubic content of the permanently enclosed spaces of a vessel, with some allowances or deductions for exempt spaces such as living quarters (1 gross register ton = 100 cubic feet = 2.83 cubic metres).
    • November 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 29 Dezember, 2015
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      It presents the whole set of non financial accounts, from the production account to the acquisitions of non-financial assets accounts. For general government sector, property income, other current transfers and capital transfers are consolidated.. It has been prepared from statistics reported to the OECD by Member countries in their answers to the new version of the annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA.
    • September 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 Oktober, 2014
      Datensatz auswählen
      The number of students enrolled refers to the count of students studying in the reference period. Each student enrolled in the education programmes covered by the corresponding category is counted once and only once. National data collection systems permitting, the statistics reflect the number of students enrolled at the beginning of the school / academic year. Preferably, the end (or near-end) of the first month of the school / academic year is chosen (special arrangements are made for part-year students who may not start studies at the beginning of the school year). Students are classified as foreign students (non-citizens) if they are not citizens of the country in which the data are collected. While pragmatic and operational, this classification is inappropriate for capturing student mobility because of differing national policies regarding the naturalisation of immigrants. Countries that have lower propensity to grant permanent residence to its immigrant populations are likely to report second generation immigrants as foreign students. Therefore, for student mobility and bilateral comparisons, interpretations of data based on the concept of foreign students should be made with caution. Students are classified as international students if they left their country of origin and moved to another country for the purpose of study. Depending on country-specific immigration legislation, mobility arrangements, and data availability, international students may be defined as students who are not permanent or usual residents of their country of study or alternatively as students who obtained their prior education in a different country, including another EU country.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 15 September, 2015
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    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 September, 2015
      Datensatz auswählen
      This dataset shows the state and changes over time in the abstractions of freshwater resources in OECD countries. Water abstractions are a major pressure on freshwater resources, particularly from public water supplies, irrigation, industrial processes and cooling of electric power plants. It has significant implications for issues of quantity and quality of water resources. This dataset shows water abstractions by source (surface and ground water) and by major uses. Water abstractions refer to water taken from ground or surface water sources and conveyed to the place of use. If the water is returned to a surface water source, abstraction of the same water by the downstream user is counted again in compiling total withdrawal. When interpreting those data, it should be borne in mind that the definitions and estimation methods employed by Member countries may vary considerably among countries.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 Oktober, 2015
      Datensatz auswählen
      This table contains data on full-time and part-time employment based on a common definition of 30-usual weekly hours of work in the main job. Data are broken down by professional status - employees, total employment - sex and standardised age groups (15-24, 25-54, 55+, total). Unit of measure used - Data are expressed in thousands of persons.
    • September 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 27 November, 2015
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      This table contains data on full-time and part-time employment based on national definition. Data are broken down by professional status - employees, total employment - sex and standardised age groups (15-24, 25-54, 55+, total). Unit of measure used - Data are expressed in thousands of persons
    • November 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 22 Februar, 2016
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      Data include pension funds per the OECD classification by type of pension plans and by type of pension funds. All types of plans are included (occupational and personal, mandatory and voluntary). The OECD classification considers both funded and book reserved pension plans that are workplace-based (occupational pension plans) or accessed directly in retail markets (personal pension plans). Both mandatory and voluntary arrangements are included. The data include plans where benefits are paid by a private sector entity (classified as private pension plans by the OECD) as well as those paid by a funded public sector entity. A full description of the OECD classification can be found at:http://www.oecd.org/dataoecd/0/49/38356329.pdf. Pension funds include also some personal pension arrangements like the Individual Retirement Accounts (IRAs) in the United States as well as funds for government workers. The coverage of the statistics follows the regulatory and supervisory framework. All authorised pension funds are therefore normally covered by the Global Pension Statistics exercise. Assets pertaining to reserve funds in social security systems are excluded.
    • Februar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 29 Februar, 2016
      Datensatz auswählen
      Data include pension funds per the OECD classification by type of pension plans and by type of pension funds. All types of plans are included (occupational and personal, mandatory and voluntary). The OECD classification considers both funded and book reserved pension plans that are workplace-based (occupational pension plans) or accessed directly in retail markets (personal pension plans). Both mandatory and voluntary arrangements are included. The data include plans where benefits are paid by a private sector entity (classified as private pension plans by the OECD) as well as those paid by a funded public sector entity. A full description of the OECD classification can be found at: http://www.oecd.org/dataoecd/0/49/38356329.pdf. Pension funds include also some personal pension arrangements like the Individual Retirement Accounts (IRAs) in the United States as well as funds for government workers. The coverage of the statistics follows the regulatory and supervisory framework. All authorised pension funds are therefore normally covered by the Global Pension Statistics exercise. Assets pertaining to reserve funds in social security systems are excluded.
  • G
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 02 Juni, 2016
      Datensatz auswählen
      The G20 CPI has been calculated for the headline indicators only (CPI All items / HICP Total). It is an annual chain-linked Laspeyres-type index. The weights for each country in each link are based on the previous year's relative share of individual final consumption expenditure of households and non-profit institutions serving households expressed in Purchasing Power Parities (PPPs). Other Aspects Recommended uses and limitations The G20 consists of the following economies: Argentina, Australia, Brazil, Canada, China, France, Germany, India, Indonesia, Italy, Japan, Korea, Mexico, the Russian Federation, Saudi Arabia, South Africa, Turkey, the United Kingdom, the United States, and the European Union. The G20 aggregate is calculated taking the fifteen individual country members of the G20 (other than France, Germany, Italy and the United Kingdom) plus the European Union as an aggregate. In calculating the monthly percentage change of the CPI G20 aggregate, the officially reported data for Argentina have been used. Data from January 2014 onwards exclude Argentina during 2014 for annual inflation rates and index series (2010=100).
    • Februar 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 17 Februar, 2015
      Datensatz auswählen
      The GID-DB is a database providing researchers and policymakers with key data on gender-based discrimination in social institutions. This data helps analyse women’s economic empowerment and understand gender gaps in other key areas of development. Covering 160 countries, the GID-DB contains comprehensive information on legal, cultural and traditional practices that discriminate against women and girls.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 23 September, 2014
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      It provides a faithful image, to the greatest extent possible, of the aggregates and balances of the general government sector in the SNA 1993 conceptual framework. In addition, it brings to light two relevant aggregates that do not belong to this conceptual frame work: the Total Revenue and the Total Expenditure of the general government sector.Unit of measure used - National currency; current prices. Expressed in millions.
    • Februar 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 19 Februar, 2015
      Datensatz auswählen
      This part contains general information on number of insurance companies and employees within the sector.
    • Dezember 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 25 Februar, 2016
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      This table contains deflators for resource flows for individual DAC Members from 1966 as well as the TOTAL DAC deflator, and the deflator for the EURO (EC).The deflators include the effect of exchange rate changes and are therefore only applicable to US dollar figures.The OECD uses the latest deflator to convert current prices to constant prices. The latest available base year used is the base year equal to 100.The OECD applies the total DAC deflator to individual recipient countries and multilateral donors to calculate their receipts or flows in constant prices.
    • Dezember 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 26 Februar, 2016
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      This table provides information on the main relevant indicators. The data have mainly been supplied by the World Bank, and cover, where available: -Current Gross National Income (GNI) in US $ millions; -GNI per capita (US $); -Population; -Energy use as kilogram of oil per capita; -Average Life Expectancy of Adults; and -Adult Literacy Rate as a percentage of the country population. Data for Sudan include South Sudan, with the exception of total population, which is reported separately.
    • Dezember 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 September, 2015
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      Bilateral ODA commitments by purpose. Data cover the years 2005 to 2009. Amounts are expressed in USD million. The sectoral distribution of bilateral ODA commitments refers to the economic sector of destination (i.e. the specific area of the recipient's economic or social structure whose development is, or is intended to be fostered by the aid), rather than to the type of goods or services provided. These are aggregates of individual projects notified under the Creditor Reporting System, supplemented by reporting on the sectoral distribution of technical co-operation, and on actual disbursements of food and emergency aid.
    • Dezember 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 22 Oktober, 2015
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    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 30 März, 2016
      Datensatz auswählen
      Key statistical concept Although there are clear definitions for all the terms used in this survey, countries might have different methodologies to calculate tonne-kilometer and passenger-kilometers. Methods could be based on traffic or mobility surveys, use very different sampling methods and estimating techniques which could affect the comparability of their statistics. Also, if the definition on road fatalities is very clear and well applied by most coutries, this is not the case for road injuies. Indeed, not only countries might have different definitions but the important underreporting of road injuries in most countries can distort analysis based on these data.
    • April 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 12 August, 2015
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      This table presents data on Government appropriations or outlays for RD (GBAORD) by socio-economic objective (SEO), using the NABS 2007 classification i.e.: Exploration and exploitation of the Earth, Environment, Exploration and exploitation of space, Transport, telecommunication and other infrastructures, Energy, Industrial production and technology, Health, Agriculture, Education, Culture, recreation, religion and mass media, Political and social systems, structures and processes, General advancement of knowledge: RD financed from General University Funds (GUF), General advancement of knowledge: RD financed from sources other than GUF, Defence. Please note that in this new NABS 2007 classification, the three socio-economic objectives -- Education, Culture, recreation, religion and mass media, and Political and social systems, structures and processes -- were previously grouped under a single objective: Social structures and relationships. At the time of this publication there is no breakdown of historical data into the three new SEOs. Another issue relating to the transition from NABS 1993 to NABS 2007 is that what was formerly Other civil research is now to be distributed among the other chapters. This distribution has not yet been done in this database. Therefore, until the countries are in a position to provide breakdown according to the NABS 2007 classification, in some cases GBAORD by SEO is greater than the sum of its chapters.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 August, 2014
      Datensatz auswählen
      It provides a breakdown of government expenditure according to their function. To meet this end, economic flows of expenditure must be aggregated according to the Classification of the Functions of Government (COFOG).
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 September, 2015
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    • Februar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 18 März, 2016
      Datensatz auswählen
      Graduates are those who successfully complete an educational programme during the reference year of the data collection. One condition of a successful completion is that students should have enrolled in, and successfully completed, the final year of the corresponding educational programme, although not necessarily in the year of reference. Students who do not complete the final year of an educational programme, but later successfully complete a recognised "equivalency" examination based on knowledge learned outside of the education system, should not be counted as graduates. Successful completion is defined according to the graduation requirements established by each country: in some countries, completion occurs as a result of passing a final, curriculum-based examination or series of examinations. In other countries, completion occurs after a specific number of teaching hours has been accumulated (although completion of some or all of the course hours may also involve examinations).
    • September 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 Oktober, 2014
      Datensatz auswählen
      Graduates are those who successfully complete an educational programme during the reference year of the data collection. One condition of a successful completion is that students should have enrolled in, and successfully completed, the final year of the corresponding educational programme, although not necessarily in the year of reference. Students who do not complete the final year of an educational programme, but later successfully complete a recognised "equivalency" examination based on knowledge learned outside of the education system, should not be counted as graduates. Successful completion is defined according to the graduation requirements established by each country: in some countries, completion occurs as a result of passing a final, curriculum-based examination or series of examinations. In other countries, completion occurs after a specific number of teaching hours has been accumulated (although completion of some or all of the course hours may also involve examinations).
    • März 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 21 August, 2015
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      This dataset contains selected indicators for monitoring progress towards green growth to support policy making and inform the public at large. The indicator bring together the OECD's statistics, indicators and measures of progress. The dataset covers OECD countries as well as BRIICS economies (Brazil, Russian Federation, India, Indonesia, China and South Africa), and selected countries when possible. The indicators are selected according to well specified criteria and embedded in a conceptual framework, which is structured around four groups to capture the main features of green growth: Environmental and resource productivity, to indicate whether economic growth is becoming greener with more efficient use of natural capital and to capture aspects of production which are rarely quantified in economic models and accounting frameworks; The natural asset base, to indicate the risks to growth from a declining natural asset base; Environmental quality of life, to indicate how environmental conditions affect the quality of life and wellbeing of people; Economic opportunities and policy responses, to indicate the effectiveness ofpolicies in delivering green growth and describe the societal responses needed to secure business and employment opportunities.
    • August 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 27 August, 2014
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      This dataset presents trends in man-made emissions of major greenhouse gases and emissions by gas. Data refer to total emissions of CO2 (emissions from energy use and industrial processes, e.g. cement production), CH4 (methane emissions from solid waste, livestock, mining of hard coal and lignite, rice paddies, agriculture and leaks from natural gas pipelines), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs) and sulphur hexafluoride (SF6). When interpreting these data it should be kept in mind that they refer to gross direct emissions excluding emissions or removals from land-use change and forestry (LULUCF). This dataset presents trends in man-made emissions of major greenhouse gases and emissions by gas. Data refer to total emissions of CO2 (emissions from energy use and industrial processes, e.g. cement production), CH4 (methane emissions from solid waste, livestock, mining of hard coal and lignite, rice paddies, agriculture and leaks from natural gas pipelines), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs) and sulphur hexafluoride (SF6). When interpreting these data it should be kept in mind that they refer to gross direct emissions excluding emissions or removals from land-use change and forestry (LULUCF).
    • Juni 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 07 Juni, 2016
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      As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Gross claims payments in the reporting country, containing a breakdown between domestic companies, foreign-controlled companies and branches and agencies of foreign companies.
    • April 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 06 Oktober, 2015
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      This table contains research and development (R&D) expenditure statistics on gross domestic R&D expenditure by sector of performance (business enterprise, government, higher education, private non-profit, and total intramural) and by field of science (natural sciences, engineering, medical sciences, agricultural sciences, social sciences, and humanities). Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2005 prices and PPPs).
    • April 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 21 April, 2016
      Datensatz auswählen
      Unit of measure used Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2005 prices and PPPs). Variables collected This table presents data on Gross domestic expenditure on R&D (GERD) by socio-economic objective (SEO), using the NABS 2007 classification i.e.: Exploration and exploitation of the Earth, Environment, Exploration and exploitation of space, Transport, telecommunication and other infrastructures, Energy, Industrial production and technology, Health, Agriculture, Education, Culture, recreation, religion and mass media, Political and social systems, structures and processes, General advancement of knowledge, and Defence. Please note that in this new NABS 2007 classification, the three socio-economic objectives -- Education, Culture, recreation, religion and mass media, and Political and social systems, structures and processes -- were previously grouped under a single objective: Social structures and relationships. At the time of this publication there is no breakdown of historical data into the three new SEOs. Another issue relating to the transition from NABS 1993 to NABS 2007 is that what was formerly Other civil research is now to be distributed among the other chapters. This distribution has not yet been done in this database. Therefore, until the countries are in a position to provide breakdown according to the NABS 2007 classification, in some cases GERD by SEO is greater than the sum of its chapters.
    • April 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 27 Juni, 2016
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      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2005 prices and PPPs). Variables collected This table contains research and development (R&D) expenditure statistics. Data include gross domestic R&D expenditure by sector of performance (business enterprise, government, higher education, private non-profit, and total intramural) and by source of funds (business enterprise, government - including public general university funds -, higher education, private non-profit and funds from abroad - including funds from enterprises and other funds from abroad).
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 April, 2016
      Datensatz auswählen
      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2005 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics. Data include gross domestic R&D expenditure by sector of performance (business enterprise, government, higher education, private non-profit, and total intramural) and by type of costs (current expenditures: labour costs, other current costs; and capital expenditures: land and buildings, and instruments and equipment).
    • September 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 27 Oktober, 2015
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      It presents the three approaches of the GDP: expenditure based, output based and income based. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA.
    • Juni 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 07 Juni, 2016
      Datensatz auswählen
      As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. This part contains gross operating expenses in the reporting country, with a breakdown between domestic companies, foreign-controlled companies and branches and agencies of foreign companies.
    • November 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 29 Dezember, 2015
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      The OECD Productivity Database aims at providing users with the most comprehensive and the latest productivity estimates. The update cycle is on a rolling basis, i.e. each variable in the dataset is made publicly available as soon as it is updated in the sources databases. However, some time lag may arise which affects individual series and/or individual countries for two reasons: First, hours worked data from the OECD Employment Outlook are typically updated less frequently than the OECD Annual National Accounts Database. Second, source data for capital services are typically available in annual national accounts with a lag. Labour productivity is a key driver of economic growth and changes in living standards, as measured notably by growth in GDP per capita. Labour productivity growth means a higher level of output for every hour worked. This can be achieved if more capital is used in production or through improved overall efficiency with which labour and capital are used together, i.e., higher multifactor productivity growth (MFP). Labour productivity is also a key driver of international competitiveness, e.g. as measured by Unit Labour Costs (ULC).
  • H
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 20 August, 2015
      Datensatz auswählen
      OECD Health Data 2014 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 29 Juli, 2015
      Datensatz auswählen
      OECD Health Data 2014 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.
    • November 2013
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 10 Dezember, 2013
      Datensatz auswählen
      OECD Health Data 2013 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 26 August, 2015
      Datensatz auswählen
      OECD Health Data 2014 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.B1:B4
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 29 Juli, 2015
      Datensatz auswählen
      OECD Health Data 2014 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 29 August, 2015
      Datensatz auswählen
      OECD Health Data 2014 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.
    • Juni 2010
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Datensatz auswählen
      OECD Health Data 2010 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 14 August, 2015
      Datensatz auswählen
    • November 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 26 Februar, 2016
      Datensatz auswählen
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 06 Juni, 2016
      Datensatz auswählen
      The Hourly Earnings (MEI) dataset contains predominantly monthly statistics, and associated statistical methodological information, for the 34 OECD member countries and for selected non-member economies. The MEI Earnings dataset provides monthly and quarterly data on employees' earnings series. It includes earnings series in manufacturing and for the private economic sector. Mostly the sources of the data are business surveys covering different economic sectors, but in some cases administrative data are also used. The target series for hourly earnings correspond to seasonally adjusted average total earnings paid per employed person per hour, including overtime pay and regularly recurring cash supplements. Where hourly earnings series are not available, a series could refer to weekly or monthly earnings. In this case, a series for full-time or full-time equivalent employees is preferred to an all employees series.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      Product coverage The dataset includes a detailed breakdown of Investment funds shares (AF.52), Net equity of households in life insurance reserves (AF.611) and Net equity of households in pension funds reserves (AF.612) as well as some non-financial assets. The finer breakdown of households' financial assets is consistent with the financial classification of the System of National Accounts (SNA).
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 27 Juni, 2016
      Datensatz auswählen
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 19 September, 2014
      Datensatz auswählen
      Human Resource Costs
  • I
    • Januar 2008
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 22 September, 2014
      Datensatz auswählen
      ICT goods are those that are either intended to fulfil the function of information processing and communication by electronic means, including transmission and display, OR which use electronic processing to detect, measure and/or record physical phenomena, or to control a physical process. ICT goods are defined by the OECD in terms of the Harmonised System.The guiding principle for the delineation of ICT goods is that such goods must either be intended to fulfil the function of information processing and communication by electronic means, including transmission and display, OR use electronic processing to detect, measure and/or record physical phenomena, or to control a physical process.Another guiding principle was to use existing classification systems in order to take advantage of existing data sets and therefore ensure the immediate use of the proposed standard. In this case, the underlying system is the Harmonized System (HS). The HS is the only commodity classification system used on a sufficiently wide basis to support international data comparison. A large number of countries use it to classify export and import of goods, and many countries use it (or a classification derived from or linked to it) to categorise domestic outputs.The application of the ICT product definition to selection of in-scope HS categories is a somewhat subjective exercise. The fact that the HS is not built on the basis of the functionality of products makes it much more difficult. The distinction between products which fulfil those functions and products that simply embody electronics but fundamentally fulfil other functions is not always obvious.It is possible to adopt a narrow or broad interpretation of the guideline, though the OECD chose a broader interpretation, an approach which is consistent with that adopted to develop the ICT sector definition.
    • August 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 27 August, 2014
      Datensatz auswählen
      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.
    • August 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 26 August, 2014
      Datensatz auswählen
      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.
    • August 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 26 August, 2014
      Datensatz auswählen
      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older with a tertiary education.
    • August 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 25 August, 2014
      Datensatz auswählen
      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.
    • August 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 25 August, 2014
      Datensatz auswählen
      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      The allocation of bilateral intermediate imports across using industries assumes that import coefficients are the same for all trade partners, i.e. SHAREipkt is identical across exporter countries. Hence, the bilateral pattern of imported intermediates from industry p is the same across all using industries k. However, it is different from the bilateral pattern of total imports from industry p because trade data (measured by VALUEijpt) allows distinguishing bilateral imports of intermediates from final good imports in industry p. While the BEC classification enables the identification of intermediate goods, no similar classification is available for trade in services, due to the high level of aggregation in services trade data. While goods trade data are based on customs declarations allowing the identification of goods at a highly disaggregated level, services trade data are based on a variety of information such as business accounts, administrative sources, surveys, and estimation techniques (Manual on Statistics of International Trade in Services, 2002). Hence, in the case of trade in services, VALUEijpt is the total value of imports of service p, i.e. both final and intermediate (and not only services that are used in the production of other goods and services, as in the case of goods data). By making an additional assumption and adjusting SHAREipkt, it is however possible to calculate trade in intermediate services. In the case of services imports, SHAREipkt is the share of imported service inputs p used by industry k in total imports of p of country i. In the case of services, besides the assumption that all trading partners have the same distribution of intermediate imports p across using industries k, it is furthermore required that the share of intermediate services in overall bilateral services imports of country i is the same across all partner countries j. Finally, it should be mentioned that trade data reported in the trade statistics do not fully match imports as reported in I-O tables. One main reason is that while trade data is recorded at consumer prices, I-O tables are evaluated at producer prices. There are also other differences such as the treatment of re-exports, scrap metal, waste products and second hand goods or unallocated trade data.
    • August 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 September, 2014
      Datensatz auswählen
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 Oktober, 2015
      Datensatz auswählen
      This table contains data on discouraged jobseekers as a percentage of the labour force and as a percentage of the population by sex and standardised age groups (15-24, 15-64, 25-54, 55-64, 65+, total). Unit of measure used - Data are expressed as percentages.
    • September 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 21 Oktober, 2015
      Datensatz auswählen
      This table contains the shares of economic short-time workers among total employment, the ratio of economic short-time workers and labour force, and the gender composition of economic short-time workers. Data re broken down by professional status - employees, total employment – by sex and standardised age groups (15-24, 25-54, 55+, total). Unit of measure used - Data are expressed as percentages.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      This table contains data on the cross-country distribution of employment by hour bands for declared hour bands, broken down by professional status - employees, total employment - sex and detailed age groups.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 Oktober, 2015
      Datensatz auswählen
      This table contains incidences and gender composition of part-time employment with standardised (15-24, 25-54, 55-64, 65+, total) and detailed age groups. Data are further broken down by professional status - employees, total employment. Part-time employment is based on a common 30-usual-hour cut-off in the main job. Unit of measure used - Data are expressed in percentages.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 Oktober, 2015
      Datensatz auswählen
      This table contains incidences and gender composition of part-time employment with standardised (15-24, 25-54, 55-64, 65+, total) and detailed age groups. Data are further broken down by professional status - employees, total employment. Part-time employment is based on national definitions.The definition of part-time work varies considerably across OECD countries Essentially three main approaches can be distinguished: i) a classification based on the worker's perception of his/her employment situation; ii) a cut-off (generally 30 or 35 hours per week) based on usual working hours, with persons usually working fewer hours being considered part-timers; iii) a comparable cut-off based on actual hours worked during the reference week. A criterion based on actual hours will generally yield a part-time rate higher than one based on usual hours, particularly if there are temporary reductions in working time as a result of holidays, illness, short-timing, etc. On the other hand, it is not entirely clear whether a classification based on the worker's perception will necessarily yield estimates of part-time work that are higher or lower than one based on a fixed cut-off. In one country (France) which changed from 1981 to 1982 from a definition based on an actual hours cut-off (30 hours) to one based on the respondent's perception, the latter criterion appeared to produce slightly higher estimates. Other data characteristics
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 10 September, 2015
      Datensatz auswählen
      This table contains the shares of involuntary part-time work among part-time workers and ratio of involuntary part-time work and labour force and the gender composition of involuntary part-time workers. Data are broken down by professional status - employees, total employment - sex and standardised age groups (15-24, 25-54, 55+, total). Unit of measure used - Data are expressed as percentages.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 14 September, 2015
      Datensatz auswählen
      This table contains incidences and gender composition of temporary employment with standardised age groups (15-24, 25-54, 55-64, 65+, total). Data are further broken down by professional status - employees, total employment. Unit of measure used - Data are expressed in percentages.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 Oktober, 2015
      Datensatz auswählen
      This table contains data on the share of the five durations - less than 1 month,>1 month and < 3 months,>3 months and <6 months,>6 months and <1 year, 1 year and over - of unemployment among total unemployment by sex and by standardised age groups (15-19, 15-24, 20-24, 25-54, 55+, total). Unit of measure used - Data expressed in percentages.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 02 September, 2015
      Datensatz auswählen
    • Februar 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 23 März, 2015
      Datensatz auswählen
      Bank profitability statistics are based on financial statements of banks in each Member country and are presented in the standard OECD framework. Although the objective is to include all institutions which conduct ordinary banking business, namely institutions which primarily take deposits from the public and provide finance for a wide range of purposes, the institutional coverage of banks in the statistics available in this database is not the same in each country. Ratios based on various items of the income statements and balance sheets of banks in percentage of some aggregates are also provided to facilitate the analysis of trends in bank profitability of OECD countries.
    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 30 Oktober, 2015
      Datensatz auswählen
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 07 September, 2015
      Datensatz auswählen
      The new database on Institutional investors' assets replaces the former database on Institutional Investors. It constitutes an attempt to better integrate these data in the framework of the System of National Accounts (SNA). Institutional Investors' assets are mainly compiled on the basis of the System of National Accounts (SNA93).
    • Juni 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 07 Juni, 2016
      Datensatz auswählen
      Institutional Investors' Assets and Liabilities data are reported by Central Banks, National Statistical Institutes or Supervisory Authorities. The indicators reported here are compiled on the basis of those statistics.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      These data are part of a larger database, hosted on a different website, which includes both quantitative and qualitative data, as well as graphs.
    • April 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 27 Juni, 2016
      Datensatz auswählen
      These data are part of a larger database, hosted on a different website, which includes both quantitative and qualitative data, as well as graphs.
    • Juni 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 07 Juni, 2016
      Datensatz auswählen
      As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Breakdown of net premiums written in the reporting country in terms of domestic risks and foreign risks, thus providing an indicator of direct cross-border operations of insurance business.
    • Februar 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 19 Februar, 2015
      Datensatz auswählen
      As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Item coverage Covers business written abroad by branches, agencies and subsidiaries established abroad of domestic undertakings and includes all business written outside the country by these entities (in both OECD and non-OECD countries).
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 28 August, 2015
      Datensatz auswählen
      This part deals with premiums written by classes of non-life insurance for the business written in the reporting country.
    • Juni 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 07 Juni, 2016
      Datensatz auswählen
      Geographic coverage OECD countries, Selected African and Asian countries, Selected Latin American countries Institutional coverage The insurance industry is a key component of the economy by virtue of the amount of premiums it collects, the scale of its investment and, more fundamentally, the essential social and economic role it plays in covering personal and business risks. The "OECD Insurance Statistics" publication provides major official insurance statistics for all OECD countries. The reader will find information on the diverse activities of this industry and on international insurance market trends. The data, which are standardised as far as possible, are broken down under numerous sub-headings, and a series of indicators makes the characteristics of the national markets more readily comprehensible. This publication is an essential tool for civil servants, businessmen and academics working in the insurance field. Item coverage This part consists of tables by indicators, which reflect the most significant characteristics of the OECD insurance market. In most cases, the tables contain data of all OECD countries as well as aggregated "OECD", "EU15" (the 15 member countries of the European Union in 1995) and "NAFTA" data from 1983 to 2012, for the following categories: - life insurance, - non-life insurance - and total. The premiums amounts are converted from national currencies into US dollar. Exchange rates used are end-of-period exchanges rates for all variables valued at the end of the year, and period-average for variables representig a flow during the year.
    • Juli 2011
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 September, 2014
      Datensatz auswählen
      Data on grants by type is not available for all OECD countries.A partial dataset is available for one or more years in the following countries: Austria, Belgium, Canada, Estonia, France, Greece, Iceland, Ireland, Italy, Netherlands, Poland, Portugal.No data on grants by type is available for Germany, Israel, New Zealand, Slovak Republic, United Kingdom, United States.The different types of grants are defined as follows:Earmarked grantsAn earmarked grant is a grant that is given under the condition that it can only be used for a specific purpose.Non-earmarked grantsNon-earmarked grants can be spent as if they were the receiving sub-national government's own (non-earmarked) tax revenues.Mandatory grantsMandatory grants (entitlements) are legal, rules-based obligations for the government that issues the grant. This requires that both the size of the grant and the conditions under which it is given be laid down in a statute or executive decree and that these conditions be both necessary and sufficient.Discretionary grantsDiscretionary grants, and the conditions under which they are given, are not determined by rules but decided on an ad hoc, discretionary basis. Discretionary grants are often temporary in nature and include, for example, grants for specific infrastructural projects or emergency aid to a disaster area.Matching grantsMatching grants are grants designed to complement sub-national contributions. Matching grants are dependent on normative or actual spending for services for which the grants are earmarked or on local revenue collection related to these services.Non-matching grantsNon-matching grants are grants not directly linked to any sub-national contribution.Current grantsCurrent grants are grants assumed to be spent on either current or capital expenditures.Capital grantsCapital grants are grants assumed to be spent only on capital expenditures.
    • Januar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 06 Juni, 2016
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    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 01 März, 2016
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      Patents are a key measure of innovation output, as patent indicators reflect the inventive performance of countries, regions, technologies, firms, etc. They are also used to track the level of diffusion of knowledge across technology areas, countries, sectors, firms, etc., and the level of internationalisation of innovative activities. Patent indicators can serve to measure the output of R&D, its productivity, structure and the development of a specific technology/industry. Among the few available indicators of technology output, patent indicators are probably the most frequently used. The relationship between patents as an intermediate output resulting from R&D inputs has been investigated extensively. Patents are often interpreted as an output indicator; however, they could also be viewed as an input indicator, as patents are used as a source of information by subsequent inventors. Like any other indicator, patent indicators have many advantages and disadvantages. The advantages of patent indicators are : patents have a close link to invention; patents cover a broad range of technologies on which there are sometimes few other sources of data; the contents of patent documents are a rich source of information (on the applicant, inventor, technology category, claims, etc.); and patent data are readily available from patent offices. However, patents are subject to certain drawbacks: the value distribution of patents is skewed as many patents have no industrial application (and hence are of little value to society) whereas a few are of substantial value; many inventions are not patented because they are not patentable or inventors may protect the inventions using other methods, such as secrecy, lead time, etc.; the propensity to patent differs across countries and industries; differences in patent regulations make it difficult to compare counts across countries; and changes in patent law over the years make it difficult to analyse trends over time.
    • Juni 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 Juni, 2016
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      The International Trade (MEI) dataset contains predominantly monthly merchandise trade statistics, and associated statistical methodological information, for the 34 OECD member countries and for all non-OECD G20 economies and the EU. The dataset itself contains international trade statistics measured in billions of United States dollars (USD) for: Exports, Imports, Balance. In all cases a lot of effort has been made to ensure that the data are internationally comparable across all countries presented and that all the subjects have good historical time-series’ data to aid with analysis.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 13 Mai, 2016
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      1 paragraph of text from section "Data source(s) used" and 1 paragraph from section"Variables collected" of the source web page
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 14 September, 2015
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      This table contains data on involuntary part-time workers by professional status. Data are broken down by professional status - employees, total employment - by sex and standardised age groups (15-24, 25-54, 55+, total).Involuntary part-time workers are part-timers (working less than 30-usual hours per week) because they could not find a full-time job. However, the definitions are not harmonised which hampers the comparison across countries.Unit of measure used - Data are expressed in thousands of persons
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      This table contains figures on the shares of industrial sectors that are "controlled" by affiliates under foreign control in each country (inward investment as a percentage of national total).
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      This table contains figures on the activity of affiliates under foreign control and all firms by industry according to the International Standard Industrial Classification (ISIC Revision 4).
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      This table contains figures on the activity of affiliates under foreign control by industry according to the International Standard Industrial Classification (ISIC Revision 3).
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      This table contains figures on affiliates under foreign control by investing country in the total manufacturing, total services and total business enterprise sectors.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      This table contains figures on affiliates under foreign control by investing country in the total manufacturing, total services and total business enterprise sectors.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      The IPP.Stat is the statistics portal of the Innovation Policy Platform containing the main available indicators relevant to a country’s innovation performance. In addition to the traditional indicators used to monitor innovation, the range of the coverage to be found in the IPP.Stat calls for the inclusion of indicators from other domains that describe the broader national and international context in which innovation occurs. Indicators are sourced primarily from the OECD and the World Bank, as well as from other sources of comparable quality. The statistics portal is still under development.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      Exchange rates Numbers that are presented in this dataset are those used by the OECD to convert national data: For countries sending data in national currency, the factor used to convert data is an annual exchange rate, built on an average of IMF monthly exchange rates weighted by the monthly trade value of imports and exports. Therefore exchange rates can differ between members of the Eurozone. For countries sending data in USD, the conversion factor is 1. They must be used as an indication and not as an exchange rates.The annual rates are also available (by clicking on the red i) but are not calculated using a trade weight. European Union Currency: The national exchange rates for the euro area countries have been converted into Euro. The option chosen by OECD is to convert exchange rates for periods prior ton entry into European Monetary Union. It means: Prior to 1999 for Austria, Belgium, Finland, France, Germany, Ireland, Italy, Luxembourg, Netherland, Portugal, Spain Prior to 2001 for Greece Prior to 2007 for Slovenia Prior to 2009 for Slovakia Prior to 2011 for Estonia
  • K
  • L
    • November 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 Februar, 2016
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    • Juni 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      National values have been computed based on regional estimates. For this reason, it is possible that in some cases these values differ from national statistics.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 September, 2015
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      Rivers Data show water quality of selected rivers. Water quality is measured in terms of annual mean concentrations of dissolved oxygen and BOD; of nitrates, phosphorus and ammonium; and of lead, cadmuim, chromium and copper. The rivers selected are main rivers draining large watersheds in the countries chosen; the measurement locations are at the mouths or downstream frontiers of the rivers. These parameters provide information concerning the state and trends of pollution by organic matter and nutrients, heavy metals and other metals. In reading the data, one should compare trends rather than absolute values, since measurement methods vary by country. Lakes Data show trends in annual mean concentrations of phosphorus and nitrogen in selected lakes. These parameters concern nutrient concentrations and related degrees of eutrophication of lakes and reservoirs. The interpretation of these tables should take into account variations in the methods of sampling (e.g. sampling location and number of measurements at different sampling locations and in different years).
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 01 April, 2016
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      Land resources are one of the four components of the natural environment: water, air, land and living resources. In this context land is both: a physical "milieu" necessary for the development of natural vegetation as well as cultivated vegetation; a resource for human activities. The data presented here give information concerning land use state and changes (e.g. agricultural land, forest land). Land area excludes area under inland water bodies (i.e. major rivers and lakes). Arable refers to all lan generally under rotation, whether for temporary crops (double-cropped areas are counted only once) or meadows, or left fallow (less than five years). These data are not meant to indicate the amount of land that is potentially cultivable. Permanent crops are those that occupy land for a long period and do not have to be planted for several years after each harvest (e.g. cocoa, coffee, rubber). Land under vines and trees and shrubs producing fruits, nuts and flowers, such as roses and jasmine, is so classified, as are nurseries (except those for forest trees, which should be classified under "forests and other wooded land"). Arable and permanent crop land is defined as the sum of arable area and land under permanent crops. Permanent meadows and pastures refer to land used for five years or more to grow herbaceous forage crops, either cultivated or growing wild (wild prairie or grazing land). Forest refers to land spanning more than 0.5 hectare (0.005 km2) and a canopy cover of more than 10 percent, or trees able to reach these thresholds in situ. This includes land from which forests have been cleared but that will be reforested in the foreseeable future. This excludes woodland or forest predominantly under agricultural or urban land use and used only for recreation purposes. Other areas include built-up and related land, wet open land, and dry open land, with or without vegetation cover. Areas under inland water bodies (rivers and lakes) are excluded. The definitions used in different countries may show variations.
    • Juni 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 September, 2015
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      The productivity and income estimates presented in this dataset are mainly based on GDP, population and employment data from the OECD Annual National Accounts. Hours worked are sourced from the OECD Annual National Accounts, the OECD Employment Outlook and national sources. The OECD Productivity Database aims at providing users with the most comprehensive and the latest productivity estimates. The update cycle is on a rolling basis, i.e. each variable in the dataset is made publicly available as soon as it is updated in the sources databases. However, timely data issues may arise and affect individual series and/or individual countries. In particular, annual hours worked estimates from the OECD Employment Outlook are typically updated less frequently (once a year, in the summer) than series of hours worked from the OECD Annual National Accounts.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 14 September, 2015
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      This table contains labour force data on labour market status - population, labour force, unemployment and employment - by sex and by detailed age groups and standard age groups (15-24, 25-54, 55-64, 65+, total). Note: Population figures reported in table LFS by sex are Census-based, while the data for this table are taken from labour force surveys. Population for total age group refers to working age population (15 to 64 years).
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 10 September, 2015
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      This table contains the age composition (as a percentage of all ages) of the population for each labour force status - labour force, employment, unemployment - by sex. Unit of measure used - Data are expressed as percentages.
    • September 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 25 November, 2015
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        This table contains data on labour force participation rates, employment/population ratios and unemployment rates for both the total labour force and civilian labour force by sex. There are data for both the total age group and the working age population (ages 15 to 64). This table also contains data on the share of civilian employment by sex.
  • M
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 20 April, 2016
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    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 August, 2014
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      The Maritime Transport Costs (MTC)database contains data from 1991 to the most recent available year of bilateral maritime transport costs. Transport costs are available for 43 importing countries (including EU15 countries as a custom union) from 218 countries of origin at the detailed commodity (6 digit) level of the Harmonized System 1988. This dataset should only be used in conjunction with the paper Clarifying Trade Costs in Maritime Transport which outlines methodology, data coverage and caveats to its use. Key Statistical Concept Import charges represent the aggregate cost of all freight, insurance and other charges (excluding import duties) incurred in bringing the merchandise from alongside the carrier at the port of export and placing it alongside the carrier at the first port of entry in the importing country. Insurance charges are therefore included in the transport cost variables and are estimated to be approximately 1.5% of the import value of the merchandise.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      The data presented come from the OECD pilot database on material flows, and from other national and international sources. The definitions used are based on the OECD Guide «Measuring material flows and resource productivity» and on ongoing international work on material flow accounting and analysis (MFA). It should be born in mind that the data should be interpreted with caution and that the time series presented here may change in future as work on methodologies for MF accounting progresses. Furthermore, data contain rough estimates for OECD and BRIICS aggregates. These data refer to material resources, i.e. materials originating from natural resources that form the material basis of the economy: metals (ferrous, non-ferrous) non-metallic minerals (construction minerals, industrial minerals), biomass (wood, food) and fossil energy carriers. The use of materials in production and consumption processes has many economic, social and environmental consequences. These consequences often extend beyond the borders of countries or regions, notably when materials are traded internationally, either in the form of raw materials or as products embodying them. They differ among the various materials and among the various stages of the resource life cycle (extraction, processing, use, transport, end-of-life management). From an environmental point of view these consequences depend on:the rate of extraction and depletion of renewable and non-renewable resource stocksthe extent of harvest and the reproductive capacity and natural productivity of renewable resourcesthe associated environmental burden (e.g. pollution, waste, habitat disruption), and its effects on environmental quality (e.g. air, water, soil, biodiversity, landscape) and on related environmental services These data inform about physical flows of material resources at various levels of detail and at various stages of the flow chain. The information shows: a) the material basis of economies and its composition by major material groups, considering:the extraction of raw materials;the trade balance in physical terms;the consumption of materials;the material inputs b) the consumption of selected materials that are of environmental and economic significance. c) in-use stocks of selected products that are of environmental and economic significance. Domestic extraction used (DEU) refers to the flows of raw materials extracted or harvested from the environment and that physically enter the economic system for further processing or direct consumption (they are used by the economy as material factor inputs). Unused domestic extraction (UDE) exclude excavated soil for construction purposes and soil erosion from agricultural land. The main reason is that excavated soil is commonly not reported in statistics, and estimation methods are not well developed. Imports (IMP) and exports (EXP) are major components of the direct material flow indicators DMI (domestic material input) and DMC (domestic material consumption). They cannot be taken as indication of domestic resource requirements. Indirect flows of imports and exports (IFIMP and IFEXP) indicate the magnitude of global primary materials resource requirements associated with these flows. They thus indicate a generic environmental pressure caused by foreign resource requirements The physical trade balance (PTB) refers to the trade surplus or deficit of an economy, which is defined as imports minus exports of raw materials and manufactured products. Domestic material consumption (DMC) refers to the amount of materials directly used in an economy, which refers to the apparent consumption of materials. DMC is computed as DEU minus exports plus imports. Domestic material input (DMI) is computed as DEU plus imports. Total material requirements (TMR) is computed as DMI plus indirect flows of imports (IFIMP) plus UDE Total material consumption (TMC) is computed as DMC plus UDE plus physical trade balance of indirect flows (IFPTB) Total Material Requirement (TMR) and Total Material Consumption (TMC) exclude the components of (domestic) earth/soil excavation and dredging, and the (domestic) soil erosion from agricultural land. The material groups are: Food: food crops (e.g. cereals, roots, sugar and oil bearing crops, fruits, vegetables), fodder crops (including grazing), wild animals (essentially marine catches), small amounts of non-edible biomass (e.g. fibres, rubber), and related products including livestock. Wood: harvested wood and traded products essentially made of wood (paper, furniture, etc.). Construction minerals: non-metallic construction minerals whether primary (e.g. sand, gravel, stones, limestone, excavated soil if used) or processed (e.g. glass, cement, concrete). Industrial minerals: non-metallic industrial minerals whether primary or processed (e.g. salts, arsenic, potash, phosphate rocks, sulphates, asbestos). Metals: metal ores, metals and products mainly made of metals. Fossil fuel: coal, crude oil, natural gas a,d peat, as well as manufactured products predominantly made of fossil fuels (e.g. plastics, synthetic rubber).
    • April 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 Juni, 2016
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      This dataset presents members' total use of the multilateral system i.e. both their multilateral aid ("Core contributions to") and bilateral aid channelled through ("Contributions through") multilateral organisations. These data originate from members' reporting at item-level in the CRS and are published here starting with 2011 data (item-level data for multilateral aid is not complete in CRS for earlier years). Note that the Secretariat has in the context of the Multilateral Aid Report published excel files with data on core contributions and non-core bilateral aid channelled through multilateral organisations covering the period 2007-2011. These files are available on our website (see link below).
    • Oktober 2013
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 November, 2014
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      The Metropolitan database contains data for 275 metro areas with a population of 500,000 or more over 29 OECD countries. These metro areas follow a harmonized functional definition developed by the OECD, in cooperation with the European Commission.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 September, 2015
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      For cross-country comparisons, data on minimum wage levels are further supplemented with another measure of minimum wages relative to average wages, that is, the ratio of minimum wages to median earnings of full-time employees. Median rather than mean earnings provide a better basis for international comparisons as it accounts for differences in earnings dispersion across countries. However, while median of basic earnings of full-time workers - i.e. excluding overtime and bonus payments - are, ideally, the preferred measure of average wages for international comparisons of minimum-to-median earnings, they are not available for a large number of countries. Minimum relative to mean earnings of full-time workers are also provided.
    • September 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 12 Oktober, 2015
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      This dataset contains statutory and national minimum wages in place in 25 OECD Member countries, Latvia, Lithuania, Malta and Romania. Data are reported in national currency units, at current prices and for different pay periods - hourly, daily, weekly, monthly -- reflecting differences across countries.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 27 November, 2015
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    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 April, 2016
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      This dataset contains monthly Comparative Price Levels (CPL) for OECD countries. CPLs are defined as the ratios of PPPs for private final consumption expenditure to exchange rates. They provide measures of differences in price levels between countries. The monthly PPPs used to derive the table are OECD estimates. The table is to be read vertically. Each column shows the number of specified monetary units needed in each of the countries listed to buy the same representative basket of consumer goods and services. In each case the representative basket costs a hundred units in the country whose currency is specified. Let’s take an example. If you are a Canadian citizen and you want to know the price level in Canada when compared to other countries, you have to look at the column Canada, where the price level is set at 100 for the whole column. If you have 120 for Finland, it means that the price level in Finland is 20% higher than in Canada. It means that you would spend 120 dollars in Finland to buy the same basket of goods and services when you spend 100 in Canada.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 01 September, 2015
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      This dataset presents trends in amounts of municipal (including household waste), and the treatment and disposal method used. The amount of waste generated in each country is related to the rate of urbanisation, the types and pattern of consumption, household revenue and lifestyles.
  • N
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 07 Oktober, 2015
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      It presents gross capital formation, gross fixed capital formation, changes in inventories and acquisition less disposals of valuables broken down by detailed industries. Gross fixed capital formation is also available broken down by type of assets. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA. Unit of measure used - In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2010). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • Februar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 24 Februar, 2016
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      It presents gross capital formation, gross fixed capital formation, changes in inventories and acquisition less disposals of valuables broken down by detailed industries according to the classification ISIC rev.4. Gross fixed capital formation is also available broken down by type of assets. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA. Unit of measure used - In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2005). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 07 Oktober, 2015
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      It presents fixed assets by activity according to the classification ISIC rev.3 and by type of product and by type of assets.  It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA. Unit of measure used - In national currency, in current prices and constant prices (national base year and OECD base year i.e. 2010). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 07 Oktober, 2015
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      It presents the balance sheets for non financial assets by institutional sectors, for both produced assets (fixed assets, inventories, valuables) and non-produced assets (tangible and intangible).  It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA. Unit of measure used - In national currency expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • Oktober 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 Oktober, 2014
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    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 November, 2015
      Datensatz auswählen
      Weights of the national Consumer Price Indices (CPI)
    • April 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 November, 2015
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      National landings in domestic ports
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 10 September, 2015
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      National landings in foreign ports
    • September 2006
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 24 September, 2014
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      New entrants to a level of education are students who are entering any programme leading to a recognised qualification at this level of education for the first time, irrespective of whether the students enter the programme at the beginning or at an advanced stage of the programme. Individuals who are returning to study at a level following a period of absence from studying at that same level are not considered to be new entrants. Foreign students who are enrolling for the first time in the country for which the data are reported are counted as new entrants, regardless of their previous education in other countries.
    • Februar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 18 Februar, 2016
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    • Juni 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 06 Juni, 2016
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      The Financial account, which is the second accumulation account, records financial flows: it indicates the types of financial instruments utilised by the different institutional sectors to acquire financial assets or incur liabilities.
    • Februar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 26 Februar, 2016
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      The following institutional sectors are covered: - Total economy (S1) - Non-financial corporations (S11) - Financial corporations (S12) - General government (S13) - Households and Non-profit institutions serving households (S14_S15) - Rest of the world (S2) The dataset on Quarterly Sector Accounts data presents the whole set of non financial accounts for the institutional sectors. It includes the following accounts: - Production account / External account of goods and services - Generation of income account - Allocation of primary income account - Secondary distribution of income account - Use of disposable income account - Change in net worth due to saving and capital transfers accounts - Acquisitions of non-financial assets account These accounts are designed to produce accounting balances that are of particular interest for economic analysis such as value added, operating surplus, saving or net lending/net borrowing. Quarterly Sector Accounts data have been reported to the OECD by Member countries using a standard questionnaire (simplified table T0119 or detailed table T0801). These questionnaires are designed to collect internationally comparable data according to definitions and concepts presented in the 1993 System of National Accounts (SNA 1993)/1995 European System of Accounts (ESA 1995): Unit of measure used - Statistics are reported at current prices, in millions of national currency. Annual data are derived as the sum of the quarters for the calendar year.
    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 02 November, 2015
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  • O
    • Februar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 22 März, 2016
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      The OECD's quarterly national accounts (QNA) dataset presents data collected from all the OECD member countries and some other major economies on the basis of a standardised questionnaire as well as countries' own definitions and classifications. It contains a wide selection of generally seasonally adjusted quarterly series most widely used for economic analysis from 1960 or whenever available.
    • August 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 20 August, 2014
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       These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2012 : OECD COUNTRIES. They comprise the summary of agricultural support estimates for OECD countries.  
    • September 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 03 November, 2015
      Datensatz auswählen
      These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2012 : OECD COUNTRIES AND EMERGING ECONOMIES.
    • September 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 03 November, 2015
      Datensatz auswählen
      These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2012 : OECD COUNTRIES AND EMERGING ECONOMIES.
    • März 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 13 März, 2014
      Datensatz auswählen
      In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2005) - and for comparative purposes in US $ current prices and constant prices (using exchange rate and PPPs). Expressed in millions and in indices. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 20 April, 2016
      Datensatz auswählen
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 27 April, 2016
      Datensatz auswählen
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 27 April, 2016
      Datensatz auswählen
    • September 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 19 August, 2014
      Datensatz auswählen
      These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2012 : OECD COUNTRIES. They comprise the summary of agricultural support estimates for OECD countries. More detailed data by country and documentation can be found in the full dataset (Excel Format) available at : http://www.oecd.org/agriculture/pse
    • September 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 19 August, 2014
      Datensatz auswählen
      These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2012 : OECD COUNTRIES. They comprise the summary of agricultural support estimates for OECD countries.
    • September 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 20 August, 2014
      Datensatz auswählen
      These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2012 : OECD COUNTRIES. They comprise the summary of agricultural support estimates for OECD countries.
    • Februar 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Datensatz auswählen
      The data presented here refer to the latest year available, which corresponds to the late 2000s for most countries. The data on the state of threatened species build on country replies to the Annual Quality Assurance (AQA) of OECD environmental reference series. These data are harmonised through the work of the OECD Working Party on Environmental Information (WPEI). Some where updated or revised on the basis of comments from national Delegates and in the framework of the OECD Environmental Performance Reviews. When interpreting these data, it should be borne in mind that the number of species known does not always accurately reflect the number of species in extistence and that varying definitions can limit comparability accross countries. The data presented here show numbers of known species and threatened species with the aim of indicating the state of mammals, birds, freshwater fish, reptiles, amphibians and vascular plants.
    • Februar 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Datensatz auswählen
      This dataset covers the uses of wildlife resources and related pressures from human activities: fish production; catches of fish and other aquatic animals and products and the management of wildlife resources: biosphere reserves and wetlands of international importance; major protected areas.
    • November 2008
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Datensatz auswählen
      Dataset provides information on selected economic aspects of environmental management. It includes tables on expenditure, which help to identify the financial consequences of environmental policies: public and private pollution abatement and control expenditure; public research and development financing for environmental protection; official development assistance, including aid in support of environment. Dataset also includes data concerning revenues from environmentally-related taxes.
    • August 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 07 August, 2014
      Datensatz auswählen
      As countries are increasingly using a wide range of policy measures to address agri-environmental issues, indicators provide crucial information to monitor and analyse the effects of those policies on the environment. They can also help the understanding and analysis of the environmental effects of future policy scenarios and agricultural projections. To help improve measurement of the environmental performance of agriculture, OECD has established a set of agri-environmental indicators, with development of the indicators in cooperation with Eurostat and FAO. These indicators inform policy makers and society on the state and trends in agri-environmental conditions, and can provide a valuable aid to policy analysis.
    • Juni 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 06 Juni, 2014
      Datensatz auswählen
      OECD Factbook provides a global overview of today’s major economic, social and environmental indicators which cover a wide range of areas: agriculture, economic production, education, energy, environment, foreign aid, health, industry, information and communications, international trade, labour force, population, taxation, public expenditure and R&D. More countries than ever are covered in greater detail, enabling direct comparisons for many indicators between OECD Members and Brazil, China, India, Indonesia, Russian Federation and South Africa.
    • April 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 07 Mai, 2014
      Datensatz auswählen
      Foreign direct investment reflects the objective of obtaining a lasting interest by a resident entity in one economy (‘‘direct investor'') in anentity resident in an economy other than that of the investor (‘‘direct investment enterprise''). The lasting interest implies the existence of a long-term relationship between the direct investor and the enterprise and a significant degree of influence on the management of the enterprise. Direct investment involves both the initial transaction between the two entities and all subsequent capital transactions between them and among affiliated enterprises, both incorporated and unincorporated.
    • April 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 25 Juni, 2015
      Datensatz auswählen
      Foreign Direct Investment (FDI) is a category of investment that reflects the objective of establishing a lasting interest by a resident enterprise in one economy (direct investor) in an enterprise (direct investment enterprise) that is resident in an economy other than that of the direct investor. The lasting interest implies the existence of a long-term relationship between the direct investor and the direct investment enterprise and a significant degree of influence (not necessarily control) on the management of the enterprise. The direct or indirect ownership of 10% or more of the voting power of an enterprise resident in one economy by an investor resident in another economy is the statistical evidence of such a relationship. FDI statistics are on a directional basis (inward or outward) and relate to FDI flows, FDI positions (stocks) and FDI income. Outward investments are cross-border investments by direct investors resident in the reporting country while inward investments are investments by non-resident investors in the reporting country. FDI flows are cross-border financial transactions within a given period (e.g. year, quarter) between affiliated enterprises that are in a direct investment relationship. FDI positions relate to the stock of investments at a given point in time (e.g. end of year, end of quarter). FDI flows and positions include equity (10% or more voting shares), reinvestment of earnings and inter-company debt. FDI income is the return on direct investment positions of equity (dividends and reinvested earnings) and debt (interest).
    • November 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 07 Dezember, 2015
      Datensatz auswählen
      Pension fund assets in OECD countries hit a record USD 20.1 trillion in 2011 but return on investment fell below zero, with an average negative return of -1.7%, according to the OECD’s latest Pension Markets in Focus. The report says that weak equity markets and low interest rates drove the poor performance.
    • Mai 2013
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 15 September, 2014
      Datensatz auswählen
      In this version, seven GVCs indicators are presented for 59 economies (34 OECD and 23 non-OECD economies, plus the "rest of the world" and the European Union) for 18 industries in the years 1995, 2000, 2005, 2008 and 2009. The indicators are calculated based on the five global input-output matrices of the TiVA database. More details on the aggregation and specific country notes can be downloaded at http://www.oecd.org/sti/ind/input-outputtables.htm and http://oe.cd/gvc/.
    • September 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 20 März, 2015
      Datensatz auswählen
      OECD Health Data 2013 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.
    • Februar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 23 Februar, 2016
      Datensatz auswählen
      OECD Health Data 2014 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      National values have been computed based on regional estimates. For this reason, it is possible that in some cases these values differ from national statistics. Status:  Discontinued 
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      National values have been computed based on regional estimates. For this reason, it is possible that in some cases these values differ from national statistics. Status:  Discontinued 
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 15 Januar, 2015
      Datensatz auswählen
      Most of the data published in this database are taken from the individual contributions of national correspondents appointed by the OECD Secretariat with the approval of the authorities of Member countries. Consequently, these data have not necessarily been harmonised at international level. This network of correspondents, constituting the Continuous Reporting System on Migration (SOPEMI), covers most OECD Member countries as well as the Baltic States, Bulgaria and Romania. SOPEMI has no authority to impose changes in data collection procedures. It is an observatory which, by its very nature, has to use existing statistics. However, it does play an active role in suggesting what it considers to be essential improvements in data collection and makes every effort to present consistent and well-documented statistics.
    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 27 Oktober, 2015
      Datensatz auswählen
    • Januar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 21 März, 2016
      Datensatz auswählen
      This database, published twice a year, provides a set of indicators that reflect the level and structure of the efforts undertaken by OECD Member countries and selected non-member economies in the field of Science and Technology as available from 1981 onwards. It includes final or provisional results as well as forecasts established by government authorities. Indicators cover resources devoted to research and development, patent families, technology balance of payments and international trade in highly R&D-intensive industries. Also presented are the underlying economic series used to calculate these indicators. Indicators on R&D expenditures, budgets and personnel are derived from the OECD's Research and Development Statistics (RDS) database, which is based on the data reported to OECD and Eurostat in the framework of the joint OECD/Eurostat international data collection on resources devoted to R&D. The sources for the other indicators include the OECD databases on Activities of Foreign Affiliates (AFA), on Bilateral Trade in Goods by Industry and End-use Category database (BTDIxE), on Patents and on Technological Balance of Payments (TBP). YEARS COVERED: 1981 onward. COUNTRIES COVERED: Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, and United States. NON-MEMBER ECONOMIES: Argentina, China, Romania, Russian Federation, Singapore, South Africa and Chinese Taipei.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 21 Juni, 2016
      Datensatz auswählen
      The [Monthly Monetary and Financial Statistics (MEI)] dataset is a subset of the [Main Economic Indicators] (MEI) database which contains predominantly monthly statistics, and associated statistical methodological information, for the 34 OECD member countries and the non-member countries: Brazil, China, India, Indonesia, Russian Federation, and South Africa. The MEI database contains a wide variety statistics that can be classified as Short-Term Economic Statistics. The [Financial Indicators (MEI)] dataset itself contains financial statistics on five separate subjects: Monetary Aggregates, Interest Rates, Exchange Rates, Reserve Assets, and Share Prices. The data series presented within these subjects have been chosen as the most relevant financial statistics in the MEI database for which comparable data across countries is available. In all cases a lot of effort has been made to ensure that the data are internationally comparable across all countries presented and that all the subjects have good historical time-series’ data to aid with analysis. All data are available monthly, and are presented as either an index (where the year 2005 is the base year) or as a level depending on which measure is seen as the most appropriate and/or useful in the economic analysis context.
    • Mai 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 Juni, 2015
      Datensatz auswählen
      This Dataset contains information using an "indicator" approach, focusing on cross-country comparisons; the aim being to make the accounts more accessible and informative, whilst, at the same time, taking the opportunity to present the conceptual underpinning of, and comparability issues inherent in, each of the indicators presented.
    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 18 März, 2016
      Datensatz auswählen
      Patents are a key measure of innovation output, as patent indicators reflect the inventive performance of countries, regions, technologies, firms, etc. They are also used to track the level of diffusion of knowledge across technology areas, countries, sectors, firms, etc., and the level of internationalisation of innovative activities. Patent indicators can serve to measure the output of R&D, its productivity, structure and the development of a specific technology/industry. The relationship between patents as an intermediate output resulting from R&D inputs has been investigated extensively. Patents are often interpreted as an output indicator; however, they could also be viewed as an input indicator, as patents are used as a source of information by subsequent inventors. Like any other indicator, patent indicators have many advantages and disadvantages. The advantages of patent indicators are : patents have a close link to invention; patents cover a broad range of technologies on which there are sometimes few other sources of data; the contents of patent documents are a rich source of information (on the applicant, inventor, technology category, claims, etc.); and patent data are readily available from patent offices. However, patents are subject to certain drawbacks: the value distribution of patents is skewed as many patents have no industrial application (and hence are of little value to society) whereas a few are of substantial value; many inventions are not patented because they are not patentable or inventors may protect the inventions using other methods, such as secrecy, lead time, etc.; the propensity to patent differs across countries and industries; differences in patent regulations make it difficult to compare counts across countries; and changes in patent law over the years make it difficult to analyse trends over time.
    • Juni 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      The OECD Science, Technology and Industry Outlook 2012 presents, in a series of country profiles, the main features, strengths and weaknesses of national STI systems and major recent changes in national STI policy. The statistical dimension of the country profiles has drawn on the work and empirical research conducted by the OECD on the measurement of innovation and the development of internationally comparable STI indicators for policy analysis.
    • Juni 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      The OECD Science, Technology and Industry Outlook 2012 presents, in a series of country profiles, the main features, strengths and weaknesses of national STI systems and major recent changes in national STI policy. The statistical dimension of the country profiles has drawn on the work and empirical research conducted by the OECD on the measurement of innovation and the development of internationally comparable STI indicators for policy analysis.
    • Juni 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      The OECD Science, Technology and Industry Outlook 2012 presents, in a series of country profiles, the main features, strengths and weaknesses of national STI systems and major recent changes in national STI policy. The statistical dimension of the country profiles has drawn on the work and empirical research conducted by the OECD on the measurement of innovation and the development of internationally comparable STI indicators for policy analysis.
    • Juni 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 25 September, 2014
      Datensatz auswählen
      The OECD Science, Technology and Industry Outlook 2012 presents, in a series of country profiles, the main features, strengths and weaknesses of national STI systems and major recent changes in national STI policy. The statistical dimension of the country profiles has drawn on the work and empirical research conducted by the OECD on the measurement of innovation and the development of internationally comparable STI indicators for policy analysis.
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 22 März, 2016
      Datensatz auswählen
      The OECD Science, Technology and Industry Outlook reviews key trends in STI policies and performance in OECD countries and major emerging economies. It is published every two years and draws on a unique international policy survey conducted by the OECD - with more than 45 countries involved in 2014 - and the latest OECD work on STI policy analysis and measurement. Following an overview of the recent STI global landscape, key current policy issues are discussed across a series of thematic policy profiles. Country profiles report the STI performance of individual countries and the most recent national policy developments.
    • September 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 20 August, 2014
      Datensatz auswählen
      These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2012 : OECD COUNTRIES. They comprise the summary of agricultural support estimates for OECD countries.  
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 26 Oktober, 2015
      Datensatz auswählen
      The Agricultural Outlook has been prepared as a joint report by the Organisation for Economic Co-operation and Development (OECD) and the Food and Agriculture Organization (FAO) of the United Nations- The report provides a ten year forward looking, assessment of trends and prospects in the major temperate-zone agricultural commodity markets of cereals, oilseeds, sugar, meat, fish and dairy products- It is published annually, in the middle of the second quarter, as part of a continuing effort to promote informed discussion of emerging market and policy issues- The data used to develop the projections underlying the assessment are those available as of January 2012
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 24 Juni, 2016
      Datensatz auswählen
    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 Juni, 2016
      Datensatz auswählen
    • Juni 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 12 September, 2015
      Datensatz auswählen
      The Trade in Value Added (TiVA) database is a joint OECD-WTO initiative. It is derived from OECD Input Output Tables linked together using Bilateral Trade Database in goods by industry and end-use category BTDIxE and estimates of bilateral trade flows in services. TiVA database aims at better tracking global production networks and supply chains. In this new version, 39 indicators are provided for: - 34 OECD countries - 23 non member economies including the BRIICS (Brazil, the Russian Federation, India, Indonesia, China and South Africa) - the Rest of the World - and several economic zones such as the EU27, EU15, ASEAN, etc. - 18 economic activities - the time coverage has been expanded so that now it includes the years 1995, 2000 2005, 2008, 2009, 2010, 2011
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 11 September, 2015
      Datensatz auswählen
      This table contains statistics on research and development (R&D) expenditure performed in the higher education and private non-profit sectors by field of science (natural sciences, engineering, medical sciences, agricultural sciences, social sciences, and humanities) and type of costs (current expenditures, capital expenditures).
    • April 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 19 April, 2016
      Datensatz auswählen
      This table contains statistics on research and development ( R&D) expenditure performed in the higher education and private non-profit sectors by field of science (natural sciences, engineering, medical sciences, agricultural sciences, social sciences, and humanities) and source of funds (direct government, public general university funds, higher education, private non-profit, business enterprise, and funds from abroad). Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2005 prices and PPPs).
    • Februar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 24 Februar, 2016
      Datensatz auswählen
    • Februar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 15 März, 2016
      Datensatz auswählen
      The Benefits and Wages series addresses the complicated interactions of tax and benefit systems for different family types and labour market situations. The series is a valuable tool used to compare the different benefits made available to those without work and those with different levels of in-work income for OECD countries and EU countries. The main social policy areas are as follows: taxes and social security contributions due on earnings and benefits, unemployment benefits, social assistance, family benefits, housing benefits, and in-work benefits. OECD Work Incentive and Income adequacy indicators, country specific files, the tax-benefit models and the tax benefit calculator, including detailed descriptions of all cash benefits available to those in and out of work as well as the taxes they were liable to pay are available on Benefits and Wages: OECD Indicators
    • August 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 07 September, 2014
      Datensatz auswählen
    • August 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      This table contains figures on the shares of industrial sectors that are "controlled" by affiliates located abroad in each country (outward investment as a percentage of national total).
    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 Oktober, 2015
      Datensatz auswählen
      This table contains figures on the activity of affiliates located abroad by host country in the total manufacturing, total services and total business enterprise sectors. The units used to present data in AMNE are millions of national currency for monetary variables and units for the other variables. Monetary variables are in current prices. Euro-area countries: national currency data is expressed in euro beginning with the year of entry into the Economic and Monetary Union (EMU). For years prior to the year of entry into EMU, data have been converted from the former national currency using the appropriate irrevocable conversion rate. This presentation facilitates comparisons within a country over time and ensures that the historical evolution is preserved. Please note, however, that pre-EMU euro are a notional unit and should not be used to form area aggregates or to carry out cross-country comparisons.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 12 September, 2015
      Datensatz auswählen
      This table contains figures on the activity of affiliates located abroad by host country in the total manufacturing sector or in the total business sector.The units used to present data in AFA are millions of national currency for monetary variables and units for the other variables. Monetary variables are in current prices. Euro-area countries: national currency data is expressed in euro beginning with the year of entry into the Economic and Monetary Union (EMU). For years prior to the year of entry into EMU, data have been converted from the former national currency using the appropriate irrevocable conversion rate. This presentation facilitates comparisons within a country over time and ensures that the historical evolution is preserved. Please note, however, that pre-EMU euro are a notional unit and should not be used to form area aggregates or to carry out cross-country comparisons.
    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 Oktober, 2015
      Datensatz auswählen
      This table contains figures on the activity affiliates located abroad by industry according to the International Standard Industrial Classification (ISIC Revision 4). The units used to present data in AMNE are millions of national currency for monetary variables and units for the other variables. Monetary variables are in current prices. Euro-area countries: national currency data is expressed in euro beginning with the year of entry into the Economic and Monetary Union (EMU). For years prior to the year of entry into EMU, data have been converted from the former national currency using the appropriate irrevocable conversion rate. This presentation facilitates comparisons within a country over time and ensures that the historical evolution is preserved. Please note, however, that pre-EMU euro are a notional unit and should not be used to form area aggregates or to carry out cross-country comparisons.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      The units used to present data in AFA are millions of national currency for monetary variables and units for the other variables. Monetary variables are in current prices. Euro-area countries: national currency data is expressed in euro beginning with the year of entry into the Economic and Monetary Union (EMU). For years prior to the year of entry into EMU, data have been converted from the former national currency using the appropriate irrevocable conversion rate. This presentation facilitates comparisons within a country over time and ensures that the historical evolution is preserved. Please note, however, that pre-EMU euro are a notional unit and should not be used to form area aggregates or to carry out cross-country comparisons.
  • P
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 28 August, 2015
      Datensatz auswählen
      Although there are clear definitions for all the terms used in this survey, countries might have different methodologies to calculate tonne-kilometer and passenger-kilometers. Methods could be based on traffic or mobility surveys, use very different sampling methods and estimating techniques which could affect the comparability of their statistics. Also, if the definition on road fatalities is very clear and well applied by most coutries, this is not the case for road injuies. Indeed, not only countries might have different definitions but the important underreporting of road injuries in most countries can distort analysis based on these data. Click to collapse Aggregation and consolidation OECD: Excludes non-ITF states Israel and Chile. Western European Countries (WECs): Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland and the United Kingdom. Central and Eastern European Countries (CEECs): Albania, Bulgaria, Croatia, Czech Republic, Estonia, FYROM, Hungary, Latvia, Lithuania, Montenegro, Poland, Romania, Serbia, Slovakia and Slovenia. North America: Canada, Mexico and the United States. Australasia: Australia and New Zealand. Click to collapse Transformations In case of missing data for a country, ITF can calculate estimates based generaly on the growth rates of the relevant region. These estimates are used solely to calculate aggregated trends in graphic representations and are not shown at the individual country level.
    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 03 Dezember, 2015
      Datensatz auswählen
    • November 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 26 Februar, 2016
      Datensatz auswählen
    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 03 Dezember, 2015
      Datensatz auswählen
    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 02 November, 2015
      Datensatz auswählen
    • Januar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 Februar, 2016
      Datensatz auswählen
      This dataset presents annual population data from 1950 when available by sex and five year age groups. The data is available for the 34 member countries and also for Colombia, Brazil, South Africa and Russian Federation. Data are presented in thousands of persons. The population data is presented in 18 five year age groups which refer to the population from 0-4 to 85 and more.
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 01 April, 2016
      Datensatz auswählen
    • Juli 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 November, 2015
      Datensatz auswählen
      Country weights used for calculation of Consumer Prices and Producer Prices OECD zones
    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 November, 2015
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      Private transactions are those undertaken by firms and individuals resident in the reporting country.
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 01 April, 2016
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      The 'Producer Prices (MEI)' dataset predominantly monthly statistics, and associated statistical methodological information, for the 34 OECD member countries and for some six non-member countries: Brazil, China, India, Indonesia, Russian Federation and South Africa. The ‘Producer Prices (MEI)’ dataset itself contains statistics on Producer Price Indices. The data series presented have been chosen as the most relevant prices statistics for which comparable data across countries is available. In all cases a lot of effort has been made to ensure that the data are internationally comparable across all countries presented and that all the subjects have good historical time-series’ data to aid with analysis. Data are available monthly for all the countries except for Australia and New Zealand (quarterly data), and are presented as an index where the year 2010 is the base year.
    • September 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 10 September, 2014
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      The OECD Indicators of Product Market Regulation (PMR) are a comprehensive and internationally-comparable set of indicators that measure the degree to which policies promote or inhibit competition in areas of the product market where competition is viable. They measure the economy-wide regulatory and market environments in 34 OECD countries in (or around) 1998, 2003, 2008 and 2013, and in another set of non-OECD countries in 2013. They are consistent across time and countries. Users of the data must be aware that they may no longer fully reflect the current situation in fast reforming countries. The indicators cover formal regulations in the following areas: state control of business enterprises; legal and administrative barriers to entrepreneurship; barriers to international trade and investment. Not all data are available for all countries for all years.
    • September 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 September, 2015
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      The 'Production and Sales (MEI)' dataset is a dataset containing predominantly monthly statistics, and associated statistical methodological information, for the 34 OECD member countries and for selected other economies. The Production and Sales dataset contains industrial statistics on four separate subjects: Production; Sales; Orders; and Work started. The data series presented within these subjects have been chosen as the most relevant industrial statistics for which comparable data across countries is available. For Production, data comprise Indices of industrial production (IIP) for total industry, manufacturing, energy and crude petroleum; and further disaggregation of manufacturing production for intermediate goods and for investment goods and crude steel. For others, they comprise retail trade and registration of passenger cars; and permits issued and work started for dwellings. Considerable effort has been made to ensure that the data are internationally comparable across all countries presented, coverage for as many countries as possible, and that all the subjects have reasonable length of time-series to assist analysis. Most data are available monthly and are presented as an index (where the year 2010 is the base year) or as a level depending on which measure is seen as the most appropriate and/or useful in the economic analysis context. Due to differences in statistical or economic environment at country level, however, availability of data varies from one country to another.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 15 September, 2015
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    • Januar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 24 Februar, 2016
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      The OECD Productivity Database aims at providing users with the most comprehensive and the latest productivity estimates. The update cycle is on a rolling basis, i.e. each variable in the dataset is made publicly available as soon as it is updated in the OECD Annual National Accounts (ANA) Database. However, timely data issues may arise and affect individual series and/or individual countries. Productivity and ULC data by main economic activity uses gross value added (in basic prices) as output measure and not GDP (gross value added at market prices). The presented estimates are hence not fully equivalent to the estimates in the database on annual growth in GDP per capita, productivity and ULC for the total economy presented above, although differences are typically relatively small.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 September, 2014
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      The OECD cross-section sectoral indicators measure regulatory conditions in the professional services and retail distribution sectors. The professional services indicators cover entry and conduct regulation in the legal, accounting, engineering, and architectural professions. They are now estimated for the years 1996, 2003, around 2008 and 2013 for 34 OECD countries and for another set of non-OECD countries for 2013. Users of the data must be aware that they may no longer fully reflect the current situation in fast reforming countries. Not all data are available for all countries for all years.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 Dezember, 2015
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      The OECD has collected data for public expenditure on labour market programmes (LMPs) continuously since the mid-1980s. For most longstanding Member countries, data according to a consistent classification system and definition of scope are available for reference years 1985 to 2002. Starting with reference year 1998, Eurostat started collecting and publishing data according to a somewhat different classification system and definition of scope. In line with agreements for bilateral coordination of data collection, the OECD after some time adopted - for non-Eurostat OECD Member countries as well as Eurostat countries – most of the features of the Eurostat system. This allows the OECD to use data collected by Eurostat rather than making a separate data request to the 20 Eurostat countries that are members of the OECD. OECD data according to the "new" classification and definition of scope are generally available for reference year 2002 onwards, or 1998 onwards for Eurostat countries. These data are often used in time-series applications, e.g. for documenting long-term trends in total social expenditure (ìn which labour market programmes are one component), or in time-series regressions that attempt to estimate the impact of training programmes vs. job-creation programmes on unemployment. It is no longer practicable to do such work using only the "old" data which stop in 2002 or the "new" data which start in 2002 or 1998. If the two data sets are combined using crude extrapolation and splicing techniques, time-series movements will result primarily from statistical breaks (i.e. changes in definition and coverage of the statistics) rather than real changes in spending patterns.The unit of measure used depends on the members in dimension 'Country', 'Measure'
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      These splits make it possible to characterize the structure of public finances in OECD countries according to the different types of welfare state. This, in turn, makes it possible for countries to compare themselves with other relevant member countries and may stimulate the national policy debate about questions such as decentralization, redistribution, privatization, the role of the non?profit sector and the application of user fees. Recommended uses and limitations The methodology applied to make the required splits has been developed since 2004 and has gradually become more accurate. The most recent methodology, used in the PFED of 2009, makes use of second level COFOG data and has been applied in a test procedure on five European countries (of which three are OECD countries) that have provided second level COFOG data to Eurostat. In the course of 2007 and 2008, more countries made available second level COFOG data to Eurostat.
    • Juli 2011
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 September, 2014
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      OECD National Account Statistics are based on the System of National of Accounts (SNA), a set of internationally agreed concepts, definitions, classifications and rules for national accounting. Using SNA terminology, general government revenue consists of central, state and local governments, and social security funds. State government is only applicable to the nine OECD member countries that are federal states: Australia, Austria, Belgium, Canada, Germany, Mexico, Spain (considered a de facto federal state in the National Accounts data), Switzerland and the United States.Revenues encompass social contributions (e.g. contributions for pensions, health and social security), taxes other than social contributions (e.g. taxes on consumption, income, wealth, property and capital), and grants and other revenues. Grants can be from foreign governments, international organizations or other general government units. Other revenues include sales, fees, property income and subsidies. The aggregates presented (taxes other than social contributions, social contributions, and grants and other revenues) are not directly available in the OECD National Accounts, and were constructed using sub-account line items.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      Data cover both social security reserve funds and sovereign pension reserve funds, the two main categories of public pension reserve funds. Social security reserve funds are set up as part of the overall social security system. They are funded chiefly by surpluses from employee and/or employer contributions over current payouts and, in some cases, by top-up contributions from the government through fiscal transfers and other sources. They may be managed either as part of a national social security scheme or by an independent - often public sector - fund management entity. Sovereign pension reserve funds are funds established by governments (independently of social security systems), who finance them directly through fiscal transfers. They are usually mandated to finance public pension expenditures at a specific future date. Some are not allowed to make any payouts for decades.
    • September 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 03 Oktober, 2012
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      Data cover both social security reserve funds and sovereign pension reserve funds, the two main categories of public pension reserve funds. Social security reserve funds are set up as part of the overall social security system. They are funded chiefly by surpluses from employee and/or employer contributions over current payouts and, in some cases, by top-up contributions from the government through fiscal transfers and other sources. They may be managed either as part of a national social security scheme or by an independent - often public sector - fund management entity. Sovereign pension reserve funds are funds established by governments (independently of social security systems), who finance them directly through fiscal transfers. They are usually mandated to finance public pension expenditures at a specific future date. Some are not allowed to make any payouts for decades.
    • März 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 September, 2014
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      This dataset contains the main results of the 2011 Eurostat-OECD PPP comparison for the 47 countries that participated in the 2011 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:
    • September 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 September, 2015
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  • R
    • April 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 20 April, 2016
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      This table contains research and development (R&D) expenditure statistics on current domestic R&D and gross domestic R&D expenditures by sector of performance (business enterprise, government, higher education, private non-profit, and total intramural) and by type of R&D within each sector (basic research, applied research, experimental development, non-specified, and total activity).Unit of measure used - Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2005 prices and PPPs).
    • April 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 21 April, 2016
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      These tables contain research and development (RD) personnel statistics. Number of RD personnel is provided in both headcounts and full-time equivalent on RD by sex, sector of employment (business enterprise, government, higher education, and private non-profit) and by occupation (researchers, technicians and other support staff).
    • April 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 21 April, 2016
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      This table presents research and development (R&D) personnel statistics. Number of R&D personnel is provided in headcounts and/or full-time equivalent on R&D by sex, sector of employment (business enterprise, government, higher education, and private non-profit) and by formal qualification (university and other diplomas by ISCED classification). Unit of measure used - Headcounts and/or Full-time equivalent on R&D (FTE)
    • Juli 2013
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 September, 2014
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    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 15 September, 2015
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    • Juni 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 August, 2014
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      The Regional Database contains annual data from 1990 to the most recent available year (generally 2013 for demographic and labour market data, 2011 for regional accounts, innovation and social statistics).
    • Oktober 2013
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 18 September, 2014
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      For each OECD country, data are collected at two sub-national levels:Territorial level 2 (TL2), which refers to the 337 large regions of the OECD area.Territorial Level 3 (TL3), which refers to the 1709 small regions of the OECD area.In any analytical study conducted at sub-national levels, the choice of the territorial unit is of prime importance. The territorial grids used in this database are officially established and relatively stable in all member countries, and are used by many as a framework for implementing regional policies. Regions in OECD Member Countries have been classified according to two territorial levels (TL). The higher level (Territorial Level 2) consists of about 362 macro-regions while the lower level (Territorial Level 3) is composed of 1794 micro-regions.This classification - which, for European countries, is largely consistent with the Eurostat classification - facilitates greater comparability of regions at the same territorial level. The differences with the Eurostat NUTS classification concern Belgium, Greece and the Netherlands where the NUTS 2 level correspond to the OECD TL3 and Germany where the NUTS1 corresponds to the OECD TL2 and the OECD TL3 corresponds to 97 spatial planning regions (Groups of Kreise). For the United Kingdom the Eurostat NUTS1 corresponds to the OECD TL2.Due to limited data availability, labour market indicators in Canada and Australia are presented for a different grid (groups of TL3 regions in the case of Canada). Since these breakdowns are not part of the OECD official territorial grids, for the sake of simplicity they are labelled as Non Official Grids (NOG).National values have been computed based on regional estimates. For this reason, it is possible that in some cases these values differ from national statistics.
    • Mai 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 29 Februar, 2016
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      OECD countries: Large regions ; Small regions (Predominantly urban, rural and intermediate regions) ; Non-OECD member countries: Large regionsThe OECD has classified two levels of geographic units within each member country: large regions (Territorial level 2 or TL2) composed by 362 regions, and small regions (Territorial Level 3 or TL3) composed by 1802 small regions. TL3 regions are further classified as predominantly urban (PU), predominantly rural (PR) and intermediate (IN). All the territorial units are defined within national borders, and each TL3 region is contained in one TL2 region, with the exception of the United States and one region in Germany (Ost-Friesland DE12). National values have been computed based on regional estimates. For this reason, it is possible that in some cases these values differ from national statistics. Key Statistical Concept In any analytical study conducted at sub-national levels, the choice of the territorial unit is of prime importance. The territorial grids (TL2 and TL3) used in this database are officially established and relatively stable in all member countries, and are used by many as a framework for implementing regional policies. This classification - which, for European countries, is largely consistent with the Eurostat classification - facilitates greater comparability of regions at the same territorial level. The differences with the Eurostat NUTS classification concern Belgium, Greece and the Netherlands where the NUTS 2 level correspond to the OECD TL3 and Germany where the NUTS1 corresponds to the OECD TL2 and the OECD TL3 corresponds to 97 spatial planning regions (Groups of Kreise). For the United Kingdom the Eurostat NUTS1 corresponds to the OECD TL2. Due to limited data availability, labour market indicators in Canada are presented for a different grid (groups of TL3 regions). Since these breakdowns are not part of the OECD official territorial grids, for the sake of simplicity they are labelled as Non Official Grids (NOG).
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 21 Juni, 2016
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    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 17 Juni, 2016
      Datensatz auswählen
      The Regional Database contains annual data from 1995 to the most recent available year (generally 2014 for demographic and labour market data, 2013 for regional accounts, innovation and social statistics).The data collection is undertaken by the Directorate of Public Governance and Territorial Development (GOV). Statistics are collected through an annual questionnaire sent to the delegates of the Working Party on Territorial Indicators (WPTI), and through access to the web-sites of National Statistical Offices and Eurostat.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 24 Juni, 2016
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      The Regional Database contains annual data from 1995 to the most recent available year. The data collection is undertaken by the Directorate of Public Governance and Territorial Development, within the Regional Development Policy division (GOV/RDP). Statistics are collected through an annual questionnaire sent to the delegates of the Working Party on Territorial Indicators (WPTI), and through access to the web-sites of National Statistical Offices and Eurostat.The WPTI is responsible for developing regional (subnational) and urban statistics and providing analysis to support policy evaluations. The Regional Database includes statistics on the regional distribution of resources, regional disparities, and how regions contribute to national growth and the well-being of society.Under this framework, the Regional Database is one of the pillars for providing indicators to the publication OECD Regions at a Glance (link).
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 21 Juni, 2016
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    • Juni 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 18 November, 2015
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    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 23 Juni, 2016
      Datensatz auswählen
    • September 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 Oktober, 2014
      Datensatz auswählen
      The Regional well-being dataset presents nine dimensions central for well-being at local level and for 362 OECD regions, covering material conditions (jobs and housing) and quality of life (education, health, environment, safety and access to services). The set of indicators selected to measure these dimensions is a combination of people's individual attributes and their local conditions, and in most cases, are available over two different years (2000 and 2013). Regions can be easily visualised and compared to other regions through the interactive website [www.oecdregionalwellbeing.org]. The dataset, the website and the publication "How’s life in your region?" (available from October 2014) are outputs designed from the framework for regional and local well-being, which starts with the consideration that making better policies for better lives means understanding what matters to people. The Regional income distribution dataset presents comparable data on sub-national differences in income inequality and poverty for OECD countries. The data by region provide information on income distribution within regions (Gini coefficients and income quintiles), and relative income poverty (with poverty thresholds set in respect of the national population), for 2010 and in 28 OECD countries. These new data complement international assessments of differences across regions in living conditions by documenting how household income is distributed within regions and how many people are poor relatively to the typical citizen of their country. Key Statistical Concept For analytical purposes, the OECD classifies regions as the first administrative tier of sub-national government, so called Territorial Level 2 or TL2 in the OECD classification. This classification is used by National Statistical Offices to collect information and it represents in many countries the framework for implementing regional policies. Well-being indicators are shown for the 362 TL2 OECD regions, equivalent of the NUTS2 for European countries, with the exception for Estonian where well-being data are presented at a smaller (TL3) level and for the Regional Income dataset, where Hungary, Poland and Turkey data are presented at a more aggregated (NUTS1) level.
    • Juni 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 Juni, 2016
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      The Registered Unemployment and Job Vacancies dataset is a subset of the Short-Term Labour Situation database, which contains predominantly monthly statistics, and associated statistical methodological information, for the 34 OECD member countries and for selected other economies. There are basically two sources for unemployment statistics: labour force surveys and administrative data. Surveys are based on standard methodology and procedures used all over the world while administrative data are subject to national legislations which evolve through time. Consequently registered unemployment data are not comparable across countries. The relationship between survey and registered unemployment is not the same for all countries. Number of registered unemployed persons and registered unemployment rates are presented here because they are monthly and quickly available after their reference period. The job vacancies data provides estimates of the number of unfilled job vacancies across national economies. Series give an indication of the labour demand while the unemployment is linked with the labour supply.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      The OECD indicators of regulation in energy, transport and communications (ETCR) summarise regulatory provisions in seven sectors: telecoms, electricity, gas, post, rail, air passenger transport, and road freight. The ETCR indicators have been estimated in a long-time series and are therefore well suited for time-series analysis. The ETCR time series was updated, revised and now cover 34 OECD countries and a set of non-OECD countries for 2013. Users of the data must be aware that they may no longer fully reflect the current situation in fast reforming countries. Not all data are available for all countries for all years.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      The OECD cross-section sectoral indicators measure regulatory conditions in the professional services and retail distribution sectors. The retail indicators cover barriers to entry, operational restrictions, and price controls. These indicators were updated and revised; they are now estimated for 34 OECD countries for the years 1998, 2003, around 2008 and 2013 and for another set of non-OECD countries for 2013. Users of the data must be aware that they may no longer fully reflect the current situation in fast reforming countries. Not all data are available for all countries for all years.
    • Dezember 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 18 März, 2016
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      Data on government sector receipts, and on taxes in particular, are basic inputs to most structural economic descriptions and economic analyses and are increasingly used in international comparisons. This annual database presents a unique set of detailed and internationally comparable tax data in a common format for all OECD countries.
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 31 August, 2015
      Datensatz auswählen
      Data on government sector receipts, and on taxes in particular, are basic inputs to most structural economic descriptions and economic analyses and are increasingly used in international comparisons. This annual database presents a unique set of detailed and internationally comparable tax data in a common format for all Latin American countries.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      International comparisons of taxes and charges on road haulage require a framework that can relate all the various taxes and charges levied on transport activities to marginal costs, if they are to provide satisfactory answers to the following types of question: -Do hauliers in one country pay more than in the other, and what impact does this have on the profitability of haulage in each country? -Is the impact of an increase in tax on diesel the same in each country or are differences in the taxation of labour more significant? -Do these differences distort the international haulage market? The 2003 ECMT Report 'Reforming Transport Taxes' developed a methodology for making such comparisons. The database presents information on vehicle taxes, fuel excise duties and user charges and takes also into account any possible refunds, rebates and exemptions. These data allow for comparison of road freight transport fiscal regimes in different countries in quantitative terms. In order to allow for comparisons of road freight taxation regimes in different countries, net taxation levels are calculated for a standard domestic haul (400-km domestic hauls with 40 tonne trucks). These results are then assessed per vehicle-km and per tonne-kilometre.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 03 September, 2015
      Datensatz auswählen
      Although there are clear definitions for all the terms used in this survey, countries might have different methodologies to calculate tonne-kilometer and passenger-kilometers. Methods could be based on traffic or mobility surveys, use very different sampling methods and estimating techniques which could affect the comparability of their statistics. Also, if the definition on road fatalities is very clear and well applied by most coutries, this is not the case for road injuies. Indeed, not only countries might have different definitions but the important underreporting of road injuries in most countries can distort analysis based on these data. Aggregation and consolidationOECD: Excludes non-ITF states Israel and Chile. Western European Countries (WECs): Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland and the United Kingdom. Central and Eastern European Countries (CEECs): Albania, Bulgaria, Croatia, Czech Republic, Estonia, FYROM, Hungary, Latvia, Lithuania, Montenegro, Poland, Romania, Serbia, Slovakia and Slovenia. North America: Canada, Mexico and the United States. Australasia: Australia and New Zealand. TransformationsIn case of missing data for a country, ITF can calculate estimates based generaly on the growth rates of the relevant region. These estimates are used solely to calculate aggregated trends in graphic representations and are not shown at the individual country level. 
  • S
    • Februar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 14 März, 2016
      Datensatz auswählen
      Demand for statistics on business demography has grown and developed considerably in recent years. Data on births and deaths of enterprises, their life expectancy and the important role they play in economic growth and productivity, as well as the information they provide for tackling social demographic issues, are increasingly requested by policy makers and analysts alike. Business demography is a core element of the OECD’s Entrepreneurship Indicators Project, where the OECD and Eurostat are collaborating to develop a framework for the regular and harmonised measurement of entrepreneurial activity and the factors that enhance or impede it. The data in this database is presented in International Standard of Industrial Classification (ISIC Revision 4).
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      The OECD's Business Demography database contains information on variables such as birth rates (business entries), death rates (business exits) survival rates, or High-Growth enterprises rate for most OECD countries. Indicators are broken down by industry using the International Standard of Industrial Classification (ISIC Revision 3) and, for some of them, by employment size-class. 'Employer' indicators (i.e. covering only businesses with at least one employee) are found to be more relevant in the context of international comparisons than the indicators covering all enterprises which are sensitive to the coverage of business registers and it is expected that progressively more and more data will be provided on the 'employer' definition basis. The Eurostat-OECD Manual on Business Demography Statistics (www.oecd.org/std/industry-services/businessdemographymanual) provides guidelines for the compilation of Business Demography indicators.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 August, 2014
      Datensatz auswählen
      The OECD Secretariat collects a wide range of statistics on businesses and business activity. This database features the data collection of the Statistics Directorate relating to a number of key variables, such as value added, operating surplus, employment, and the number of business units, for example, broken down by 4-digit International Standard of Industrial Classification (ISIC Revision 4) industry groups (including the service sector)), referred to as the Structural Statistics on Industry and Services (SSIS) database; and by size class; referred to as the Business Statistics by Size Class (BSC) database.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      The SSIS (Structural Statistics for Industry and Services) database, provides comparable information by detailed industrial sector (up to 4-digit level) where industries are defined according to the International Standard of Industrial Classification (ISIC) Revision 3 for the following economic variables: Turnover; Production at producers' prices; Value added at basic prices and/or factor costs; Gross operating surplus; Total purchases of goods and services;Change in stocks of goods and services; Purchases of energy products;Gross investment in tangible goods; Gross investment in land;Gross investment in existing buildings and structures; Gross investment in machinery and equipment; Number of persons engaged; Number of employees; Number of females' employees; Number of employees in full time equivalent units;Hours worked by employees; Compensation of labour, all persons engaged; Compensation of labour; Wages and salaries, all persons engaged; Wages and salaries, employees; Other employers' social contributions, employees; Number of enterprises and/or establishments. All OECD countries are covered, although the coverage of variables varies, with data typically available for the period 1995 to 2007, whereas for some countries more recent and more historical data are available. The BSC (Business Statistics by Size Class) database, provides comparable information by detailed industrial sector (up to 4-digit level) where industries are defined according to the International Standard of Industrial Classification (ISIC) Revision 3, broken down by business size for the following economic variables: Turnover; Production at producers' prices; Value added at basic prices and/or factor costs; Gross operating surplus; Total purchases of goods and services; Change in stocks of goods and services; Purchases of energy products; Gross investment in tangible goods; Gross investment in land;Gross investment in existing buildings and structures; Gross investment in machinery and equipment; Number of persons engaged; Number of employees; Number of females' employees; Number of employees in full time equivalent units;Hours worked by employees; Compensation of labour, all persons engaged; Compensation of labour; Wages and salaries, all persons engaged; Wages and salaries, employees; Other employers' social contributions, employees; Number of enterprises and/or establishments. Businesses are allocated to size classes on the basis of the number of persons engaged. The size class breakdowns used by national statistics institutes vary widely and so to improve comparability the OECD has defined five standardised size classes that are shown in this database. For most countries they conform to the following size classes: 1-9; 10-19; 20-49; 50-249 and 250+, however it is not always possible to present country data in this way; as shown in the accompanying metadata. All OECD countries are covered, although the coverage of variables varies, with data typically available for the period 1995 to 2007, whereas for some countries more recent and more historical data are available.
    • Mai 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 24 Juni, 2016
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      Trade in services drives the exchange of ideas, know-how and technology. It helps firms cut costs, increase productivity, participate in global value chains and boost competitiveness. Consumers benefit from lower prices and greater choice.However, international trade in services is often impeded by trade and investment barriers and domestic regulations. The Service Trade Restrictions Index (STRI) helps identify which policy measures restrict trade. It provides policy makers and negotiators with information and measurement tools to open up international trade in services and negotiate international trade agreements. It can also help governments identify best practice and then focus their domestic reform efforts on priority sectors and measures.The STRI indices take the value from 0 to 1, where 0 is completely open and 1 is completely closed. They are calculated on the basis of information in the STRI database which reports regulation currently in force.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 22 Juni, 2016
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      The Short-Term Labor Market Statistics dataset contains predominantly quarterly labor statistics, and associated statistical methodological information, for the 34 OECD member countries and selected other economies. The Short-Term Labor Market Statistics dataset covers countries that compile labor statistics from sample household surveys on a monthly or quarterly basis. It is widely accepted that household surveys are the best source for labor market key statistics. In such surveys, information is collected from people living in households through a representative sample and the surveys are based on standard methodology and procedures used internationally. The subjects available cover: working age population by age; active and inactive labor force by age; employment by economic activity, by working time and by status; and, unemployment (including monthly harmonized unemployment) by age and by duration. Data is expressed in levels (thousands of persons) or rates (e.g. employment rate) where applicable.
    • Februar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 26 Februar, 2016
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      It presents simplified non-financial accounts, from the gross value added to the net lending/net borrowing. In this table, the total economy is broken down in three main institutional sectors: corporations, general government, households and non-profit institutions serving households. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA. Unit of measure used - In national currency, in current prices. Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 17 September, 2015
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      The OECD Social Expenditure Database (SOCX) has been developed in order to serve a growing need for indicators of social policy. It includes reliable and internationally comparable statistics on public and mandatory and voluntary private social expenditure at programme level. SOCX provides a unique tool for monitoring trends in aggregate social expenditure and analysing changes in its composition. It covers 34 OECD countries for the period 1980-2009 and estimates for aggregates for 2010-12; this version also includes estimates of net total social spending for 2009 for 30 OECD countries. The main social policy areas are as follows: Old age, Survivors, Incapacity-related benefits, Health, Family, Active labor market programmes, Unemployment, Housing, and Other social policy areas. SOCX 2010 aggregated data are described in Adema and Ladaique (2009) (see particularly sections 2 and 3, and Annex 1 and 4). For SOCX 2012, see definitions, methodological notes and sources in sections 2 and 3, and Annex 1 and 4 from the following document. Sources and methodology for the estimations 2010-2012 are also described here
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 27 November, 2015
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      The OECD Social Expenditure Database (SOCX) has been developed in order to serve a growing need for indicators of social policy. It includes reliable and internationally comparable statistics on public and mandatory and voluntary private social expenditure at programme level. SOCX provides a unique tool for monitoring trends in aggregate social expenditure and analysing changes in its composition. It covers 34 OECD countries for the period 1980-2009 and estimates for aggregates for 2010-13; this version also includes estimates of net total social spending for 2009 for 30 OECD countries. The main social policy areas are as follows: Old age, Survivors, Incapacity-related benefits, Health, Family, Active labor market programmes, Unemployment, Housing, and Other social policy areas. SOCX 2010 aggregated data are described in Adema and Ladaique (2009) (see particularly sections 2 and 3, and Annex 1 and 4). For SOCX 2012, see definitions, methodological notes and sources in sections 2 and 3, and Annex 1 and 4 from the following document. Sources and methodology for the estimations 2010-2013 are also described here
    • Juni 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      National values have been computed based on regional estimates. For this reason, it is possible that in some cases these values differ from national statistics.
    • September 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 06 Oktober, 2015
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      The STAN Bilateral Trade Database for industrial analysis (BTD) belongs to the STAN Family datasets and is designed to provide analysts and researchers with information on trade in goods broken down by reporter, partner country (or geographical/economic area) and economic activity. STAN (Structural Analysis Databases) Bilateral Trade Database by Industry and End-use category (BTDIxE) provides values of imports and exports of goods broken down by industrial sectors and by end-use categories. BTDIxE was designed to extend the BTD database which provided bilateral trade in goods by industry only. BTDIxE allows, for example, insights into the patterns of trade in intermediate goods between countries to track global production networks and supply chains, and it helps to address policy issues such as trade in value added and trade in tasks. The list of reporters covers all OECD Member Countries and 30 non member economies, including the BRIICS (Brazil, the Russian Federation, India, Indonesia, China and South Africa). It should be noted that underlying series for OECD countries are from OECD International Trade by Commodity Statistics., while data for non OECD economies are from UNSD database COMTRADE. The list of partners covers all 34 OECD countries, 30 non member economies, the Rest of the World, the partner Unspecified, and Total World. Trade flows are divided into 46 economic activities and 9 categories including capital goods, intermediate goods and household consumption.
    • November 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 August, 2014
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      The STAN database for industrial analysis provides analysts and researchers with a comprehensive tool for analysing industrial performance at a relatively detailed level of activity across countries. It includes annual measures of output, labour input, investment and international trade which allow users to construct a wide range of indicators to focus on areas such as productivity growth, competitiveness and general structural change.Through the use of a standard industry list, comparisons can be made across countries. The industry list provides sufficient detail to enable users to highlight high-technology sectors and is compatible with those used in related OECD databases. STAN is primarily based on Member countries' annual national accounts by activity tables and uses data from other sources, such as national industrial surveys/censuses, to estimate any missing detail. Since many of the data points in STAN are estimated, they do not represent official Member country submissions. The current version of STAN is based on the International Standard Industrial Classification of all economic activities, Revision 4 (ISIC Rev. 4) and covers all activities (including services). Earlier versions of STAN (pre-2000) were based on ISIC Rev.2 and covered the manufacturing sector only. To optimize timeliness, STAN is updated on a "rolling basis"- new tables are made available as soon as they are ready.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
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      Recommended uses and limitations of STANIt is recommended that STAN is primarily used for broad analyses, particularly at the detailed level where many of the data points are estimated. For example, looking at trends or average growth rates and shares over a few years or general modelling. This also applies to any indicators that may be calculated (see Annex. 2 in the full documentation for examples). Where the data points are official National Accounts (often at more aggregate industry levels) there is more scope for precise analyses such as looking at year-on-year growth rates. STAN is based on data that Member countries provide. Detailed data collections independent of national statistical offices are not performed. In other words, we do not have the scope to build up National Accounts compatible tables from detailed data using consistent methodologies across countries. Therefore, when comparing variables or indicators across countries, users should refer to the STAN country notes to check for industry inclusions and variable definitions. Some comprises may be necessary in terms of the level of detail analysed.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 11 November, 2014
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    • Januar 2010
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 August, 2014
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      TAN Indicators are compiled to respond to the needs of analysts and researchers interested in measuring economic performance and structural changes. They also complement the OECD publications, Science Technology and Industry Scoreboard and Economic Globalisation Indicators.In this edition, STAN Indicators consist of 35 measures related to the production and employment structure, the labour productivity and labour costs, the investment, the business research and development expenditures and the international trade performance.The underlying measures used for calculations are:- Values of exports and imports of goods, at current prices from STAN Bilateral Trade Database- Production, intermediate consumption, value added, labour compensation, gross fixed capital formation, at current prices from STAN Database for Structural Analysis- Value added volumes and employment from STAN Database for Structural Analysis- Research & Development expenditures, at current prices from STAN R&D Expenditure in IndustryMost of STAN Indicators are presented for all OECD countries and a certain number of zones (i.e. country groups) such as the G7, the EUs, etc.The composition of these groups varies according to the indicators in order to optimise the industry and period coverage.Country groups are not based on weighted averages.STAN Indicators cover the period 1970-2008, although the time-coverage may vary considerably across countries /zones and indicators. Indicators are provided for a wide range of economic activities (according to an ISIC Rev.3 based hierarchy) compatible with the list in the underlying STAN Database.
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 August, 2014
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    • März 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 September, 2014
      Datensatz auswählen
      Input-Output tables describe the sale and purchase relationships between producers and consumers within an economy. They can be produced by illustrating flows between the sales and purchases (final and intermediate) of industry outputs or by illustrating the sales and purchases (final and intermediate) of product outputs. The OECD Input-Output database is presented on the former basis, reflecting in part the collection mechanisms for many other data sources such as research and development Research and Development expenditure data, employment statistics, pollution data, energy consumption, which are in the main collected by enterprise or by establishment, and thus according to industry classifications.
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 April, 2016
      Datensatz auswählen
      Input-Output tables describe the sale and purchase relationships between producers and consumers within an economy. They can be produced by illustrating flows between the sales and purchases (final and intermediate) of industry outputs or by illustrating the sales and purchases (final and intermediate) of product outputs. The OECD Input-Output database is presented on the former basis, reflecting in part the collection mechanisms for many other data sources such as research and development Research and Development expenditure data, employment statistics, pollution data, energy consumption, which are in the main collected by enterprise or by establishment, and thus according to industry classifications.
    • März 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      Input-Output tables describe the sale and purchase relationships between producers and consumers within an economy. They can be produced by illustrating flows between the sales and purchases (final and intermediate) of industry outputs or by illustrating the sales and purchases (final and intermediate) of product outputs. The OECD Input-Output database is presented on the former basis, reflecting in part the collection mechanisms for many other data sources such as Research and Development expenditure data, employment statistics, pollution data, energy consumption, which are in the main collected by enterprise or by establishment, and thus according to industry classifications.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 06 Juni, 2016
      Datensatz auswählen
      Input-Output tables describe the sale and purchase relationships between producers and consumers within an economy. They can be produced by illustrating flows between the sales and purchases (final and intermediate) of industry outputs or by illustrating the sales and purchases (final and intermediate) of product outputs. The OECD Input-Output database is presented on the former basis, reflecting in part the collection mechanisms for many other data sources such as research and development Research and Development expenditure data, employment statistics, pollution data, energy consumption, which are in the main collected by enterprise or by establishment, and thus according to industry classifications.
    • März 2012
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      Input-Output tables describe the sale and purchase relationships between producers and consumers within an economy. They can be produced by illustrating flows between the sales and purchases (final and intermediate) of industry outputs or by illustrating the sales and purchases (final and intermediate) of product outputs. The OECD Input-Output database is presented on the former basis, reflecting in part the collection mechanisms for many other data sources such as research and development Research and Development expenditure data, employment statistics, pollution data, energy consumption, which are in the main collected by enterprise or by establishment, and thus according to industry classifications.
    • Februar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 Mai, 2016
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      The OECD’s ANalytical Business Enterprise Research and Development (ANBERD) database presents annual data on R&D expenditures by industry and was developed to provide analysts with comprehensive data on industrial R&D expenditures that address the problems of international comparability and breaks in the time series of official business enterprise R&D data. The ANBERD database includes a number of estimations and is published under the responsibility of the Secretary General of the OECD as it does not represent Member countries’ official submissions of business enterprise R&D data. The current version of the ANBERD database presents industrial R&D expenditure data broken down in up to 100 manufacturing and services sectors for OECD countries and selected non-member economies from 1987 onwards. For the first time, the reported data are in ISIC Revision 4 and are expressed in national currencies as well as in PPP US dollars, both at current and constant prices. The ANBERD data are updated continuously on a rolling basis and additional countries will be included in the coming months as they become available.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 24 Juni, 2016
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      The OECD indicators of employment protection are synthetic indicators of the strictness of regulation on dismissals and the use of temporary contracts. For each year, indicators refer to regulation in force on the 1st of January. The indicator of strictness of employment protection - collective dismissals (additional provisions) - measures additional costs and procedures involved in dismissing more than one worker at a time (compared with the cost of individual dismissal). It incorporates 4 data items. For more information and full methodology, see www.oecd.org/employment/protection. Other Aspects Recommended uses and limitations The indicator for collective dismissal measures additional costs and procedures involved in dismissing more than one worker compared with the costs of individual dismissal. As such, it should not be used in isolation from the indicator of strictness of employment protection - individual dismissals (regular contracts).
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 August, 2014
      Datensatz auswählen
      The OECD indicators of employment protection are synthetic indicators of the strictness of regulation on dismissals and the use of temporary contracts. For each year, indicators refer to regulation in force on the 1st of January. For more information and full methodology, see www.oecd.org/employment/protection.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 27 Juni, 2016
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      The OECD indicators of employment protection are synthetic indicators of the strictness of regulation on dismissals and the use of temporary contracts. For each year, indicators refer to regulation in force on the 1st of January. For more information and full methodology, see www.oecd.org/employment/protection.
    • September 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 Oktober, 2014
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      For data aligned to Finance, the year shown is the calendar year. For data aligned to personnel, the year shown is the year in which the end of the school year falls (e.g. 2002 refers to the school year 2001/2002), with the exceptions of Korea where the year refers to the year in which the school year begins and Australia and New Zealand where the school academic year corresponds to the calendar year.
    • September 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 Oktober, 2014
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      The number of students enrolled refers to the count of students studying in the reference period. Each student enrolled in the education programmes covered by the corresponding category is counted once and only once. National data collection systems permitting, the statistics reflect the number of students enrolled at the beginning of the school / academic year. Preferably, the end (or near-end) of the first month of the school / academic year is chosen (special arrangements are made for part-year students who may not start studies at the beginning of the school year). Exceptions to this may be required: at the pre-primary level of education a gradual inflow may exist and, therefore, an average over several counting dates may be preferable. At the tertiary level the enrolment of students may not be stable enough at the beginning of the academic year and therefore a count at a later point may be preferable. Adult education programmes cover the learning activity of those returning to education after having left initial (or "regular") education. Only programmes (of at least one semester) that are similar to regular education (in subject content or potential qualifications) are included. In some countries, there are, in addition, adult education that are not similar to regular education; these programmes are not included.
    • September 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 Oktober, 2014
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      The number of students enrolled refers to the count of students studying in the reference period. Each student enrolled in the education programmes covered by the corresponding category is counted once and only once. National data collection systems permitting, the statistics reflect the number of students enrolled at the beginning of the school / academic year. Preferably, the end (or near-end) of the first month of the school / academic year is chosen (special arrangements are made for part-year students who may not start studies at the beginning of the school year). Exceptions to this may be required: at the pre-primary level of education a gradual inflow may exist and, therefore, an average over several counting dates may be preferable. At the tertiary level the enrolment of students may not be stable enough at the beginning of the academic year and therefore a count at a later point may be preferable. Adult education programmes cover the learning activity of those returning to education after having left initial (or "regular") education. Only programmes (of at least one semester) that are similar to regular education (in subject content or potential qualifications) are included. In some countries, there are, in addition, adult education that are not similar to regular education; these programmes are not included.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 September, 2015
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      This table shows the representative sub-central personal income tax rates, tax allowances and credits used.Applies to the wage income of a single person no dependants.Can be based on a representative city or an average of sub-central ratesMinimum and maximum sub-central rates across states and municipalities.Amounts of tax allowances are expressed in national currencies.Additional details on sub-central tax systems based on a progressive income tax rate structure are provided in Table I.7.Further explanatory notes may be found in the Explanatory Annex. 
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 April, 2016
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      This table provides detailed information on sub-central income tax systems with progressive rate structures, based on the representative case. - The data (e.g., allowance, tax credit) apply to wage income of a single person without dependants. - The rates are expressed as a percentage of taxable income. Further explanatory notes may be found in the Explanatory Annex. The information shown in the columns 'Level of government' and 'Tax base' corresponds to the same columns in Table I.2.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 10 Mai, 2016
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    • August 2011
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 18 September, 2014
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      Survey on Monitoring the Paris Declaration. The dataset contains data as reported by donors and national co-ordinators in participating partner countries. The dataset includes all quantitative data collected through the 2006, 2008 and 2011 Surveys.
  • T
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 25 September, 2014
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      TALIS averages are based on all countries participating in the TALIS survey, including partner countries and economies. This explains the difference between the OECD average and the TALIS average. Data from the TALIS survey and Education at a Glance (EAG) may differ. See Annex E of the TALIS technical report and Annex 3 of EAG for more details about the data collections.
    • April 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 Oktober, 2015
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      This data is updated after the finalisation of the Taxing Wages publication for the corresponding year.This table reports marginal personal income tax and social security contribution rates for a single person without dependent, at various multiples (67%, 100%, 133%, 167%) of the AW/APW.The average wage (AW) by country and year can be found within the Taxing Wages comparative tables dataset, under the indicator heading: Total gross earnings before taxes (national currency). The AW is based on a single person at 100% of average earnings, no child.The results, derived from the OECD Taxing Wages framework (elaborated in the annual publication Taxing Wages), use tax rates applicable to the tax year. The results take into account basic/standard income tax allowances and tax credits and include family cash transfers (see Taxing Wages).The marginal rates are expressed as a percentage of gross wage earnings, with the exception of the Total tax wedge which is expressed as a percentage of gross labour costs (gross wages + employer SSC).The sub-central personal tax rates used in this table correspond to those used in Taxing Wages. The figures may differ from those published in Taxing Wages where updated information is available, such as revised AW/APW data.Further explanatory notes may be found in the Explanatory Annex.
    • April 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 Oktober, 2015
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      This data is updated after the finalisation of the Taxing Wages publication for the corresponding year.This table reports average personal income tax and social security contribution rates for a single person without dependent, at various multiples (67%, 100%, 133%, 167%) of the AW/APW.The average wage (AW) by country and year can be found within the Taxing Wages comparative tables dataset, under the indicator heading: Total gross earnings before taxes (national currency). The AW is based on a single person at 100% of average earnings, no child.The results, derived from the OECD Taxing Wages framework (elaborated in the annual publication Taxing Wages), use tax rates applicable to the tax year. The results take into account basic/standard income tax allowances and tax credits and include family cash transfers (see Taxing Wages).The marginal rates are expressed as a percentage of gross wage earnings, with the exception of the Total tax wedge which is expressed as a percentage of gross labour costs (gross wages + employer SSC). The sub-central personal tax rates used in this table correspond to those used in Taxing Wages.The figures may differ from those published in Taxing Wages where updated information is available, such as revised AW/APW data.Further explanatory notes may be found in the Explanatory Annex.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 September, 2015
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      The simple approach of comparing the tax/benefit position of example households avoids many of the conceptual and definitional problems involved in more complex international comparisons of tax burdens and transfer programmes. However, a drawback of this methodology is that the earnings of an average worker will usually occupy a different position in the overall income distribution in different economies, although the earnings relate to workers in similar jobs in various OECD Member countries. Because of the limitations on the taxes and benefits covered in the Report, the data cannot be taken as an indication of the overall impact of the government sector on the welfare of taxpayers and their families. Complete coverage would require studies of the impact of indirect taxes, the treatment of non-wage labour income and other income components under personal income taxes and the effect of other tax allowances and cash benefits. Complete coverage would also require that consideration be given to the effect on welfare of services provided by the state, either free or below cost, and the incidence of corporate and other direct taxes on earnings and prices. Such a broad coverage is not possible in an international comparison of all OECD countries. The differences between the results shown here and those of a full study of the overall impact on employees of government interventions in the economy would vary from one country to another. They would depend on the relative shares of different kinds of taxes in government revenues and on the scope and nature of government social expenditures. The Report shows only the formal incidence of taxes on employees and employers. The final, economic incidence of taxes may be quite different, because the tax burden may be shifted from employers onto employees and vice versa by market adjustments to gross wages. The income left at the disposal of a taxpayer may represent different standards of living in various countries because the range of goods and services on which the income is spent and their relative prices differ as between countries. In those countries where the general government sector provides a wide range of goods and services (generous basic old age pension, free health services, public housing, university education, etcetera), the taxpayer may be left with less cash income but may enjoy the same living standards as a taxpayer receiving a higher cash income but living in a country where there are fewer publicly provided goods and services.
    • November 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 02 Dezember, 2015
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    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 Oktober, 2015
      Datensatz auswählen
      This current Taxing Wages model has evolved from 2 earlier versions. The latest version is based on calculations for the Average Worker (AW) in the private sector (see glossary term), and the results are shown for 8 household types covering one- and two-earner families of varying size and different fractions of average gross wage earnings. There are 14 separate tax burden measures that describe the tax and benefit position of these families.This approach was first followed in the 2005-2006 Taxing Wages publication, which also applied these assumptions to calculate tax burden measures as of 2000. These assumptions have been applied since then in the more recent Taxing Wages publications and website databases.The first version of the Taxing Wages model (historical model A) was based on a more narrow definition of the average worker: the Average Production Worker (APW) solely from the manufacturing sector (see glossary term). It included only two of the current 8 family types, and the results are shown for only 3 of the existing 14 tax burden measures. This model was applied to data for years 1979-2004.The second version (historical model B) continued to use the Average Production Worker (APW) basis for its calculations, but was expanded to cover the full 8 family types that are currently used, and increased the number of tax burden measures to 12 of the 14 currently used. This model was applied to data for years 1997-2004.
    • April 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 April, 2016
      Datensatz auswählen
      The data presented here refer to the latest year available, which corresponds to the late 2000s for most countries. The data on the state of threatened species build on country replies to the Annual Quality Assurance (AQA) of OECD environmental reference series. These data are harmonized through the work of the OECD Working Party on Environmental Information (WPEI). Some where updated or revised on the basis of comments from national Delegates and in the framework of the OECD Environmental Performance Reviews. When interpreting these data, it should be borne in mind that the number of species known does not always accurately reflect the number of species in extistence and that varying definitions can limit comparability across countries. Species assessed as Critically Endangered (CR), Endangered (EN), or Vulnerable (VU) are referred to as "threatened" species. Reporting the proportion of threatened species on The IUCN Red List is complicated by the fact that not all species groups have been fully evaluated, and also by the fact that some species have so little information available that they can only be assessed as Data Deficient (DD). For many of the incompletely evaluated groups, assessment efforts have focused on species that are likely to be threatened; therefore any percentage of threatened species reported for these groups would be heavily biased (i.e., the % threatened species would likely be an overestimate).
    • September 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 09 Februar, 2016
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      Since new and young firms contribute critically to job creation, innovation and growth, observing recent trends of firm formation provides valuable information to policy makers
    • Februar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 März, 2016
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      The types of services are presented according to the services classification of the 1993 Fifth edition of the Balance of Payments Manual of the International Monetary Fund (BPM5) and its detailed extension, the Extended Balance of Payments Services (EBOPS) Classification.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 10 Mai, 2016
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      This table shows the top statutory personal income tax rate and top marginal tax rates for employees at the earnings threshold where the top statutory PIT rate first applies.
    • Juni 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 03 September, 2015
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      Official and Private Flows - Disbursements and Commitments. Aggregate data (no breakdown by recipient) on ODA, OOF, private and NGO data by donor, type of aid and flow. The data cover flows from all bilateral and multilateral donors except for Tables DAC1, DAC4, DAC5 and DAC7b which focus on flows from DAC member countries and the EU Institutions.
    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 02 November, 2015
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      Official Development Financing (ODF), measured for recipient countries only, is defined as the sum of their receipts of bilateral ODA, concessional and non-concessional resources from multilateral sources, and bilateral other official flows made available for reasons unrelated to trade, in particular loans to refinance debt.
    • April 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 18 Mai, 2016
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      Total Official Flows: the sum of Official Development Assistance (ODA) and Other Official Flows (OOF) represents the total (gross or net) disbursements by the official sector at large to the recipient country shown.
    • August 2006
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 18 September, 2014
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      For non-EU countries, UNESCO-OECD-Eurostat (UOE) data collection on education statistics, compiled on the basis of national administrative sources, reported by Ministries of Education or National Statistical Offices. For EU countries, Eurostat data.
    • Januar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 10 Februar, 2016
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    • September 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 September, 2014
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      These tables are a complement to the report Agricultural Policies in OECD Countries: Monitoring and Evaluation 2009. They comprise the summary of agricultural support estimates for OECD countries.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 17 Mai, 2016
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      This table presents export/import information by detailed activity sectors (ISIC Rev.4)
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 11 November, 2014
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      The central issue of trade by enterprise characteristics is to try to classify trade operators according to enterprise characteristics and the feasibility of doing so largely depends on the possibility of using or developing common identifiers between the trade register and the business register. Countries are different in their ability to perform such a linking, and matching ratios (between business and trade registers) vary between countries, thus the degree of representativeness of the results varies between countries.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 11 Februar, 2016
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      This dataset shows import and export values (in millions of UDS) using product classification at 2-digit level of CPA classification.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 17 Mai, 2016
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      This dataset presents data by export intensity, that is the share of exports on total turnover.
    • September 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 02 November, 2015
      Datensatz auswählen
      The central issue of trade by enterprise characteristics is to try to classify trade operators according to enterprise characteristics and the feasibility of doing so largely depends on the possibility of using or developing common identifiers between the trade register and the business register. Countries are different in their ability to perform such a linking, and matching ratios (between business and trade registers) vary between countries, thus the degree of representativeness of the results varies between countries.
    • März 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 03 März, 2016
      Datensatz auswählen
      The central issue of trade by enterprise characteristics is to disaggregate trade flows according the characteristics of the enterprises engaged in cross-border transactions. The feasibility of doing so largely depends on the possibility of using or developing common identifiers between the trade register and the business register. Countries differ in their ability to perform such a linking, and matching ratios (between business and trade registers) vary across countries, and as a consequence the degree of representativeness of the results also varies across countries.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 Mai, 2016
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      This dataset presents data by type of ownership, that is foreign or domestically controlled enterprise (with or without own affiliates abroad).
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 17 Mai, 2016
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      This table presents export/import information by enterprise size class and partner country.
    • Juli 2009
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 24 September, 2014
      Datensatz auswählen
      The central issue of trade by enterprise characteristics is to try to classify trade operators according to enterprise characteristics and the feasibility of doing so largely depends on the possibility of using or developing common identifiers between the trade register and the business register. Countries are different in their ability to perform such a linking, and matching ratios (between business and trade registers) vary between countries, thus the degree of representativeness of the results varies between countries.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 15 September, 2015
      Datensatz auswählen
      This dataset shows the number of exporters and importers and their associated trade values for a selected set of partner countries and zones, broken down by three economic sectors: industry, trade and repair and other sectors. Total values for the wide economy are also displayed.Recommended uses and limitations EU countries break down trade data into Intra- and extra- EU zones, whereas non EU countries report their Total trade. Trade values have been aggregated for EU countries and Total (Intra-EU plus Extra-EU) trade flows are displayed, whereas Intra and Extra-EU data expressed in term of number of enterprises cannot be summed up, because of possible double-counting (same enterprise can be trader in both intra- and extra- EU trade). Data have been collected in ISIC revision 3 from 2003 up to 2007 and in ISIC revision 4 as from reference year 2008. Time series are affected by this change in classification, and thus data are displayed into two separate databases.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 12 September, 2015
      Datensatz auswählen
      This dataset presents number of importing/exporting enterprises and their trade value (in millions of USD) by size class, and economic activity expressed in ISIC Rev. 4 TEC data are collected in co-operation with Eurostat, directly from the National Statistical Offices, through a linkage exercise between trade and business registers.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 04 September, 2015
      Datensatz auswählen
      The Trade by Enterprise Characteristics (TEC) database contains international annual trade data broken down in different categories of enterprises. Its aim is to provide a solid basis for analysts who explore, in the context of globalisation, the characteristics of trade actors. The TEC data are collected in co-operation with Eurostat, directly from the NSOs, through a linkage exercise of trade and business registers made. Data in export/import values and in number of exporting/importing enterprises are available for 19 EU member states (Czech Republic, Denmark, Germany, Estonia, France, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Hungary, Austria, Poland, Portugal, Romania, Slovenia, Slovakia, Finland and Sweden), plus Canada, Norway, Israel and the Unites States. Key Statistical Concept The central issue of trade by enterprise characteristics is to try to classify trade operators according to enterprise characteristics and the feasibility of doing so largely depends on the possibility of using or developing common identifiers between the trade register and the business register. Countries are different in their ability to perform such a linking, and matching ratios (between business and trade registers) vary between countries, thus the degree of representativeness of the results varies between countries.
    • September 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 02 November, 2015
      Datensatz auswählen
      The Trade by Enterprise Characteristics (TEC) database contains international annual trade data broken down in different categories of enterprises. Its aim is to provide a solid basis for analysts who explore, in the context of globalisation, the characteristics of trade actors. The international trade data are displayed into the following enterprises characteristics:the economic sector in International Standard Industrial Classification (ISIC),the employment size-classes of enterprises,the concentration of international trade among the domestic firms,the concentration of trade towards the number of partner countriesthe product traded
    • Februar 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 29 Februar, 2016
      Datensatz auswählen
      The central issue of trade by enterprise characteristics is to disaggregate trade flows according the characteristics of the enterprises engaged in cross-border transactions. The feasibility of doing so largely depends on the possibility of using or developing common identifiers between the trade register and the business register. Countries differ in their ability to perform such a linking, and matching ratios (between business and trade registers) vary across countries, and as a consequence the degree of representativeness of the results also varies across countries.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 Mai, 2016
      Datensatz auswählen
      This dataset shows imports/exports by type of trader that is exporter only, importer only or both importer and exporter (Two-way trader).
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 10 September, 2015
      Datensatz auswählen
      The database on statistics of international trade in services broken down by partner country provides statistics on international trade in services by partner country for 29 OECD countries plus EU, Euro Area, European Union Institutions, Hong Kong (SAR China) and the Russian Federation as well as definitions and methodological notes. The data concern trade between residents and non-residents of countries and are reported within the framework of the Manual on Statistics of International Trade in Services.  Sector coverage The aim of the publication is to assemble and disseminate balance of payments data on trade in services at the most detailed partner-country level available. To the extent that countries report them, data are also broken down by type of service according to the EBOPS classification.  
    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 18 November, 2015
      Datensatz auswählen
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 August, 2014
      Datensatz auswählen
      In general, data comply with the UN recommandations defined in International Merchandise Trade Statistics: Concepts and Definitions, Revision 2 (IMTS, Rev.2). For exceptions and for definitions of statistical territories, please refer to country notes. Following the UN recommendations, the international merchandise trade statistics record all goods which add to or subtract from the stock of material resources of a country by entering (imports) or leaving (exports) its economic territory. Goods simply being transported through a country (goods in transit) or temporarily admitted or withdrawn (except for goods for inward or outward processing) do not add to or subtract from the stock of material resources of a country and are not included in the international merchandise trade statistics. Customs records should be the main source of the data; and the additional sources could be used where customs sources are not available. Goods should be included in statistics at the time when they enter or leave the economic territory of a country. In the case of customs-based data collection systems, the time of recording should be the date of lodgement of the customs declaration. Lists of goods to be included, to be recorded separately and to be excluded should be provided. Specific goods are to be excluded from detailed international merchandise trade statistics but recorded separately in order to derive totals of international merchandise trade for national accounts and balance of payments purposes. Trade system There are two trade systems in common use by which international merchandise trade statistics are compiled: general trade system and special trade system. The United Nations recommendations advise using the general trade system that provides a more comprehensive recording of external trade flows than does the special system. It also provides a better approximation of the change of ownership criterion used in the 1993 SNA and BPM5. General trade includes all goods that cross the national frontier including goods that are imported into and exported from custom-bonded warehouses and free zones. The general trade system is in use when the statistical territory of a country coincides with its economic territory so that imports include all goods entering the economic territory of a compiling country and exports include all goods leaving the economic territory of a compiling country. Special trade covers goods that cross the customs frontier plus goods that are imported into and exported from custom-bonded areas. The special trade system is in use when the statistical territory comprises only a particular part of the economic territory.
    • Mai 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 Mai, 2016
      Datensatz auswählen
      Trade union density corresponds to the ratio of  wage and salary earners that are trade union members, divided by the total number of wage and salary earners (OECD Labour Force Statistics). Density is calculated using survey data, wherever possible, and administrative data adjusted for non-active and self-employed members  otherwise.
    • August 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 17 September, 2015
      Datensatz auswählen
      The lack of common definitions and practices to measure transport infrastructure spending hinders comparisons between countries and spending options. Data for road and rail infrastructure are the most comprehensive while data on sea port and airport spending are less detailed in coverage and definition. While our survey covers all sources of financing a number of countries exclude private spending, including Japan and India. Around 65% of countries report data on urban spending while for the remaining countries data on spending in this area are missing. Indicators such as the share of GDP needed for investment in transport infrastructure, depend on a number of factors, such as the quality and age of existing infrastructure, maturity of the transport system, geography of the country and transport-intensity of its productive sector. Caution is therefore required when comparing investment data between countries. However, data for individual countries and country groups are consistent over time and useful for identifying underlying trends and changes in levels of spending, especially for inland transport infrastructure. These issues of definitions and methods are addressed in a companion report Understanding the Value of Transport Infrastructure – Guidelines for macro-level measurement of spending and assets (ITF/OECD2013) that aims to improve the international collection of related statistics.
    • Oktober 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 19 November, 2015
      Datensatz auswählen
  • U
    • Juni 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 06 Oktober, 2015
      Datensatz auswählen
      This table contains data on the share of the five durations - less than 1 month, >1 month and < 3 months, >3 months and <6 months, >6 months and <1 year, 1 year and over - of unemployment among total unemployment by sex and by standardised age groups (15-19, 15-24, 20-24, 25-54, 55+, total).
    • Juli 2014
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 22 September, 2014
      Datensatz auswählen
      This table contains the number of active trade union members and the number of wage and salary earners. Data on union membership are broken down by source of data (administrative or survey data).Membership corresponds to the number of wage and salary earners that are members of a trade union. Total number of wage and salary earners are taken from OECD Labour Force Statistics.Data are expressed in thousands.
    • Dezember 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 05 Dezember, 2015
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    • Juli 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 25 November, 2015
      Datensatz auswählen
      This table contains data on employment by hour bands for usual weekly hours worked in the main job. Standard hour bands are reported for most countries. Actual hours of work instead of usual hours of work are only available in some countries (Japan and Korea). Data are broken down by professional status - employees, total employment - by sex and standardised age groups (15-24, 25-54, 55+, total). Unit of measure used - Data are expressed in thousands of persons.
  • V
    • November 2015
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 08 Dezember, 2015
      Datensatz auswählen
      Its presents output, intermediate consumption and the gross value added and its components, in particular compensation of employees and gross operating surplus and mixed income, broken down by detailed industries. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA. Data presented in this table will not be updated after summer 2010. Data reported to the OECD by countries in their answers to the annual national accounts questionnaire are now available on theme Industry and Services, Structural Analysis (STAN) Databases. In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2005). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
  • W