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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.

Все наборы данных:  2 A B C D E F G H I J K L M N O P Q R S T U V W
  • 2
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      Databasepublished June 2010These tables are a complement to the report Agricultural Policies in OECD Countries: At a Glance 2010. 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 :
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Databasepublished June 2010These tables are a complement to the report Agricultural Policies in OECD Countries: At a Glance 2010. 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 :
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Databasepublished June 2010These tables are a complement to the report Agricultural Policies in OECD Countries: At a Glance 2010. 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 :
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Databasepublished June 2010These tables are a complement to the report Agricultural Policies in OECD Countries: At a Glance 2010. 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 :
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Databasepublished June 2010These tables are a complement to the report Agricultural Policies in OECD Countries: At a Glance 2010. 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 :
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Databasepublished September 2011These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. 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 :
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Databasepublished September 2011These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. 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 :
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Databasepublished September 2011These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. 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 :
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Databasepublished September 2011These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. 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 :
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Databasepublished September 2011These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. 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 :
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Databasepublished September 2011These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. 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 :
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Databasepublished September 2011These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. 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 :
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Databasepublished September 2011These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. 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 :
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Databasepublished : September 2012These 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 :
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 29 апреля, 2019
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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.More detailed data by country and documentation can be found in the full dataset (Excel Format) available at :
    • Февраль 2017
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 01 августа, 2017
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      This dataset contains the main results of the 2014 Eurostat-OECD PPP comparison for the 47 countries that participated in the 2014 round of the Eurostat-OECD Purchasing Power Parity (PPP) Programme. The dataset is organised in 23 tables which show results both in US dollars and OECD as reference (Table 1.1 to Table 1.12) and in euros and European Union as reference (Table 2.1 to Table 2.11) calculated with the EKS method. The tables contain the following information: Table 1.1 to 1.12 The dollar serves as numeraire and the OECD as reference country (except for Table 1.12 where the United States are the reference country). Table 1.1 and Table 1.2 present the data on which the following ten tables are based. • Table 1.1 gives nominal expenditure in national currency of the participating countries. • Table 1.2 presents PPPs (OECD=1.00) that have been calculated for the participating countries using the price and expenditure data collected during the 2014 round. The PPPs were obtained by the EKS method of calculation and aggregation. • Table 1.3 shows nominal expenditure of Table 1.1 converted to US dollars. Exchange rates do not reflect the relative purchasing power of different currencies and the converted expenditure is still expressed at national prices. As such, it remains nominal measures, the spatial equivalent of a time series of GDP for a single country at current prices. Hence, they are called “nominal expenditure”. The nominal expenditure in the table reflects both differences in the quantities of goods and services purchased in the countries and differences in the price levels of the countries. • Table 1.4 gives nominal expenditure of Table 1.3 expressed on a per capita basis using the midyear population data. • Table 1.5 and Table 1.6 present the nominal expenditure from Table 1.3 and the nominal expenditure per head from Table 1.4 as indices with OECD=100. • Table 1.7 shows real expenditure converted to US dollar using the PPPs from Table 1.2. PPPs equalise the purchasing power of different currencies during the process of conversion and the converted expenditures are expressed at international prices (that is at the same price level). As such, they are real measures, the spatial equivalent of a time series of GDP for a single country at constant prices. Hence, they are called “real expenditures”. The real final expenditures in the table reflect only differences in the volumes of goods and services purchased in the countries. • Table 1.8 gives the real expenditure of Table 1.7 expressed on a per capita basis using the midyear population data. Again, the real expenditures per head in this table are not additive nor are they subject to the Gerschenkron effect. • Table 1.9 and Table 1.10 present the real expenditure on GDP from Table 1.7 and the real final expenditure per head on GDP from Table 1.8 as indices with OECD=100. • Table 1.11 gives the price levels which are computed as ratios of the PPPs in Table 1.2 to the exchange rates and are expressed as indices with OECD=100. For a given aggregate, they indicate the number of units of the common currency needed to buy the same volume of the  aggregate in each country. Price levels that exceed 100 indicate that the level of prices in that country and for that analytical category is higher than the average price level for the OECD. • Table 1.12 present PPPs as in Table 1.2 (see description above) but with the United States as reference country (US=1.00). Table 2.1 to 2.11 The euro serves as numeraire and the European Union as reference country. Table 2.1 and Table 2.2 present the data on which the following nine tables are based. Table 2.1 to 2.11 contain the same information as Table 1.1 to 1.11 with a different basis. For explanation on the contents, please see description above.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Databasepublished : June 2018This dataset and predefined summary tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2018, which monitors agricultural policy developments in 35 OECD member countries, 6 non-OECD EU member states and 10 emerging economies: Brazil, China, Colombia, Costa Rica, Kazakhstan, Russia, the Philippines, South Africa, Ukraine and Viet Nam.The OECD uses a comprehensive system for measuring and classifying support to agriculture - the Producer and Consumer Support Estimates (PSEs and CSEs) and related indicators. They provide insight into the increasingly complex nature of agricultural policy and serve as a basis for OECD’s work on agricultural policies. More detailed data by country and documentation can be found in the full dataset (Excel Format) available at :
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      Databasepublished : June 2018This dataset and predefined summary tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2018, which monitors agricultural policy developments in 35 OECD member countries, 6 non-OECD EU member states and 10 emerging economies: Brazil, China, Colombia, Costa Rica, Kazakhstan, Russia, the Philippines, South Africa, Ukraine and Viet Nam.The OECD uses a comprehensive system for measuring and classifying support to agriculture - the Producer and Consumer Support Estimates (PSEs and CSEs) and related indicators. They provide insight into the increasingly complex nature of agricultural policy and serve as a basis for OECD’s work on agricultural policies. More detailed data by country and documentation can be found in the full dataset (Excel Format) available at :
  • A
    • Сентябрь 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 15 декабря, 2017
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      Chapter C includes indicators that are a mixture of outcome indicators, policy levers and context indicators. Internationalisation of education and progression rates are, for instance, outcome measures to the extent that they indicate the results of policies and practices at the classroom, school and system levels. But they can also provide contexts for establishing policy by identifying areas where policy intervention is necessary, for example, to address issues of inequity.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      This indicator measures the income of jobless families relying on minimum-income safety-net benefits as a percentage of the median disposable income in the population. This can be compared with a poverty line defined as a fixed percentage of median income. For instance, if the poverty threshold is 50% of median income, a value of 30% means that benefit entitlements alleviate poverty risks of 60%
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      Produced by the OECD Sahel and West Africa Club, Africapolis.org is the only comprehensive and standardised geospatial database on cities and urbanisation dynamics in Africa. Combining demographic sources, satellite and aerial imagery and other cartographic sources, it is designed to enable comparative and long-term analyses of urban dynamics - covering 7 500 agglomerations in 50 countries. Bulk download is available from below link
    • Март 2015
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 10 августа, 2017
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      Data is available for the 17 countries covered by the SWAC/OECD (Benin, Burkina Faso, Cabo Verde, Chad, Cote d'Ivoire, The Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Mauritania, Niger, Nigeria, Senegal, Sierra Leone and Togo).   Agglomerated population: Population of urban agglomerations above 10 000 inhabitants.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Июль 2015
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Denis Chernyshev
      Дата обращения к источнику: 03 декабря, 2015
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    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июля, 2019
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      The gross nutrient balances (N and P) are calculated as the difference between the total quantity of nutrient inputs entering an agricultural system (mainly fertilisers, livestock manure), and the quantity of nutrient outputs leaving the system (mainly uptake of nutrients by crops and grassland). Gross nutrient balances are expressed in tonnes of nutrient surplus (when positive) or deficit (when negative). This calculation can be used as a proxy to reveal the status of environmental pressures, such as declining soil fertility in the case of a nutrient deficit, or for a nutrient surplus the risk of polluting soil, water and air. The nutrient balance indicator is also expressed in terms of kilogrammes of nutrient surplus per hectare of agricultural land to facilitate the comparison of the relative intensity of nutrients in agricultural systems between countries.
    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 мая, 2019
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      The gross nutrient balances (N and P) are calculated as the difference between the total quantity of nutrient inputs entering an agricultural system (mainly fertilizers, livestock manure), and the quantity of nutrient outputs leaving the system (mainly uptake of nutrients by crops and grassland). Gross nutrient balances are expressed in tonnes of nutrient surplus (when positive) or deficit (when negative). This calculation can be used as a proxy to reveal the status of environmental pressures, such as declining soil fertility in the case of a nutrient deficit, or for a nutrient surplus the risk of polluting soil, water and air. The nutrient balance indicator is also expressed in terms of kilogrammes of nutrient surplus per hectare of agricultural land to facilitate the comparison of the relative intensity of nutrients in agricultural systems between countries.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 09 апреля, 2019
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      commitment is a firm written obligation by a government or official agency, backed by the appropriation or availability of the necessary funds, to provide resources of a specified amount under specified financial terms and conditions and for specified purposes for the benefit of a recipient country or a multilateral agency. Members unable to comply with this definition should explain the definition that they use. -- Commitments are considered to be made at the date a loan or grant agreement is signed or the obligation is otherwise made known to the recipient (e.g. in the case of budgetary allocations to overseas territories, the final vote of the budget should be taken as the date of commitment). For certain special expenditures, e.g. emergency aid, the date of disbursement may be taken as the date of commitment. -- Bilateral commitments comprise new commitments and additions to earlier commitments, excluding any commitments cancelled during the same year. Cancellations and reductions in the year reported on of commitments made in earlier years are reported in the CRS, but not in the DAC questionnaire. -- In contrast to bilateral commitments, commitments of capital subscriptions, grants and loans to multilateral agencies should show the sum of amounts which are expected to be disbursed before the end of the next year and amounts disbursed in the year reported on but not previously reported as a commitment. For capital subscriptions in the form of notes payable at sight, enter the expected amount of deposits of such notes as the amount committed.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      Destination of Official Development Assistance Disbursements. Geographical breakdown by donor, recipient and for some types of aid (e.g. grant, loan, technical co-operation) on a disbursement basis (i.e. actual expenditures). The data cover flows from bilateral and multilateral donors which focus on flows from DAC member countries and the EU Institutions.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 04 июня, 2019
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      This dataset is used to report the tying status of bilateral ODA commitments. Members have agreed that administrative costs and technical co-operation expenditure should be disregarded in assessing the percentages of tied, partially untied and untied aid. These items have not been included in the data reported in this data set.
    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 февраля, 2019
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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 visualization 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". Constant Price is at 2016  
    • Июль 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 сентября, 2018
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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”.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 марта, 2019
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      Air Emission Accounts are available for European countries and a few non-European countries. The System of Environmental-Economic Accounting (SEEA) Central Framework is an accounting system developed around two objectives: "understanding the interactions between the economy and the environment" and describing "stocks and changes in stocks of environmental assets". The SEEA combines national accounts and environmental statistics in a statistical framework with consistent definitions, classifications and concepts allowing policy makers to evaluate environmental pressures from economic activities at macro- and meso-levels. Data refer to total emissions of CO2 (CO2 emissions from energy use and industrial processes, e.g. cement production), CH4 (methane emissions from solid waste, livestock, mining of hard coal and lignite, rice paddies, agriculture and leaks from natural gas pipelines), N2O (nitrous oxide), HFCs (hydrofluorocarbons), PFCs (perfluorocarbons), (SF6 +NF3) (sulphur hexafluoride and nitrogen trifluoride), SOx (sulphur oxides, NOx (nitrogen oxides), CO (carbon monoxide), NMVOC (non-methane volatile organic compounds), PM2.5 (particulates less that 2.5 µm), PM10 (particulates less that 10 µm) and NH3 (ammonia). The OECD Air Emission Accounts present data based on ISIC rev. 4.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      AITRAW = All in average income tax rates at average wage   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.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
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      Residential Property Prices Indices (RPPIs) – also named House price indices (HPIs), are index numbers that measure the prices of residential properties over time. RPPIs are key statistics not only for citizens and households across the world, but also for economic and monetary policy makers. They can help, for example, to monitor potential macroeconomic imbalances and the risk exposure of the household and financial sectors. This dataset covers the 34 OECD member countries and some non-member countries. In addition to the nominal RPPIs it contains information on real house prices, rental prices and the ratios of nominal prices to rents and to disposable household income per capita. This dataset contains quarterly statistics for each country. House prices differ widely across OECD countries, both with respect to recent changes and to valuation levels. The OECD has identified one main nominal index for each country that covers the prices for the sale of newly-built and existing dwellings. The datasets “Analytical house price indicators” and “Residential Property Price Indices (RPPIs) – Headline Indicators” refer to the same price indices for all countries apart from Brazil, Canada, China, the United States and the Euro area. These differences are further documented in country-specific metadata. For the United States, the series used in “Analytical house price indicators” is included in the dataset called “Residential Property Price Indices (RPPIs) – Complete database”, but is not the headline indicator. For all other countries, non-seasonally adjusted price indices in both datasets are identical in the period in which they overlap. This research dataset provides extended time series coverage for many countries. The objective is to provide information on the long term trend of house prices and develop indicators which can be used to help track and analyse macroeconomic developments and risks. The extended data supplement the OECD RPPI data with historical data from a variety of sources, including other international organisations, central banks and national statistical offices. The methodological basis on the historical data and the types of geographical areas and dwellings they cover can differ from those used in the OECD RPPI data. The database contains a number of additional series. Real house prices are given by the ratio of seasonally adjusted nominal house prices to the seasonally adjusted consumers’ expenditure deflator in each country, from the OECD national accounts database. This provides information on how nominal house prices have changed over time relative to prices in the general economy. The rental prices come from the OECD Main Economic Indicators database and refer to Consumer Price Indices (CPIs) for Actual rentals for housing (COICOP 04.1). If this indicator is missing for a country, another indicator is chosen. The chosen indicator are usually those corresponding to the CPI aggregate for Housing including Actual rentals for housing (COICOP 04.1), imputed rentals for housing (COICOP 04.2) and Maintenance and repair of the dwelling (COICOP 04.3). The disposable income indicators come from the OECD national accounts database. Net household disposable income is used. The population data come from the OECD national accounts database. The price-to-rent ratio is given by the ratio of nominal house prices to rental prices. This is a measure of the profitability of owning a house. The price-to-income ratio is given by the ratio of nominal house prices to nominal household disposable income per capita. This is a measure of the affordability of purchasing a house. An indication that house prices may be overvalued is provided if either of these ratios is above their long-term averages. The standardised price-rent and price-income ratios show the current price-rent and price-income ratios relative to their respective long-term averages. The long-term average, which is used as a reference value, is calculated over the whole period available when the indicator begins after 1980 or 1980 if the indicator is available over a longer time period. The standardised ratio is indexed to a reference value equal to 100 over the full sample period. Values over 100 indicate that the present price-rent ratio, or price-income ratio, is above its long-run norms. This provides an indication of possible housing market pressures.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
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      The OECD's ANalytical Business Enterprise Research and Development (ANBERD) database presents annual data on Research and Development (R&D) expenditures by industry and was developed to provide analysts with comprehensive data on business R&D expenditures. The ANBERD database incorporates a number of estimations that build upon and extend national submissions of business enterprise R&D data by industry (main activity/industry orientation). The current version of the ANBERD database presents OECD countries' and selected non-member economies' business expenditure on R&D since 1987, broken down across 100 manufacturing and service industry groups. The reported data follow the International Standard Industrial Classification, Revision 4 (ISIC Rev. 4) and are expressed in national currencies as well as in US dollars at Purchasing Power Parity (PPP), both at current and constant prices.   Main activity and industry orientation: The 2015 Frascati Manual practice is to report BERD on an enterprise basis. The main economic activity of an enterprise is usually defined as that which accounts for most of its economic outputs; this may be identified directly from sales or indirectly proxied (such as by numbers of personnel devoted to different activities). This determines the industry in which the enterprise, and any BERD it carries out, is classified. As such, all BERD of a diversified enterprise (i.e. one with multiple lines of business) is allocated to the same industry, that of its main activity. This enables, as far as possible, the alignment and compatability of BERD data with other economic statistics (e.g. value added broken down by industry). In addition, the Frascati Manual also recommends reporting BERD by industry orientation, whereby the statistical unit’s R&D is distributed across the various lines of business to which it relates. In a few countries, hybrid approaches are followed and reported as main activity data. As an example, some countries primarily follow the main activity approach but redistribute the R&D of large diversified firms across the economic activities to which it relates. This can affect interpretation of the data and resulting statistics. There are also important differences between countries in the treatment of R&D undertaken by firms in the service sector but closely associated (though not necessarily contractually) with manufacturing firms. Industrial research institutes, largely funded by the manufacturing industries they serve, are the most frequent examples. With the implementation of the 2015 Frascati Manual, such hybrid data will be phased out in favour of a strict main activity approach. Countries still reporting hybrid data are flagged in the ANBERD country notes.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      The dataset includes a detailed breakdown of Investment funds, Insurance companies and Pension funds, and Other forms of institutional savings, as institutional sectors. This finer breakdown by type of investors has been established with reference to the System of National Accounts (SNA), when possible. Within Investment funds, one distinguishes Open-end companies, further broken down into Money market funds and Other mutual funds, and Closed-end companies, of which Real estate funds. Within Insurance companies and pension funds one distinguishes Insurance companies, further broken down into Life insurance companies and Non-life insurance companies, and Autonomous pension funds. Financial assets included correspond to the assets requested in the previous database on Institutional Investors, i.e. Currency and deposits, Securities other than shares, Loans, Shares and other equities and Other financial assets. Moreover, Total non-financial assets are also included. While the sub-classification of the above financial assets corresponds to SNA93, a further breakdown between assets issued by residents and assets issued by non-residents is reported.
    • Январь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 29 января, 2019
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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).
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      Data source used: The aquaculture production data collection is part of the more comprehensive data gathering carried out on an annual basis by the Fisheries Committee (COFI) of the Trade and Agriculture Directorate (TAD) from OECD members and participating non-OECD economies. Data on marine landings, aquaculture production, inland fisheries catch, fleet, employment, total allowable catch (TAC) and fisheries support estimate (FSE) are collected from Fisheries Ministries, National Statistics Offices and other institutions designated as an official data source. The surveys used for this exercise are the OECD Fisheries questionnaires.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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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
    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 18 мая, 2019
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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.   Average wages are converted in USD PPPs using 2017 USD PPPs for private consumption and are deflated by a price deflator for private final consumption expenditures in 2017 prices.   Real compensation per employee (instead of real wages) are considered for Chile, Iceland, Mexico and New Zealand.
    • Сентябрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 22 марта, 2019
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      This dataset presents the average number of students in a class by type of institution.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июня, 2019
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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.
    • Октябрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 21 июня, 2019
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      The average effective age of retirement is calculated as a weighted average of (net) withdrawals from the labour market at different ages over a 5-year period for workers initially aged 40 and over. In order to abstract from compositional effects in the age structure of the population, labour force withdrawals are estimated based on changes in labour force participation rates rather than labour force levels. These changes are calculated for each (synthetic) cohort divided into 5-year age groups. The estimates shown in red are less reliable as they have been derived from interpolations of census data rather than from annual labour force surveys. The estimates for women in Turkey are based on 3-yearly moving averages of participation rates for each 5-year age group. OECD estimates based on the results of national labour force surveys, the European Union Labour Force Survey and, for earlier years in some countries, national censuses.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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  • B
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 09 июля, 2019
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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.  This dataset presents countries compiling balance of payments statistics in accordance with the 6th edition of the Balance of Payments and International Investment Position Manual published by the IMF (BPM6). Transactions include: the goods and services accounts, the primary income account (income account in BPM5), the secondary income account (transfers in BPM5), the capital account, and the financial account. Changes in BPM6 compared to BPM5 are often a consequence of a stricter application of the change of ownership principle in particular in the goods and services accounts. They relate to transactions on goods and services (merchanting, goods for processing, Insurance), income (investment income), and financial operations (direct investment) .
    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 01 марта, 2019
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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.
    • Май 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 31 мая, 2018
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      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   Unit of measure used: Estonia: 2011 - EUR; 2010; 2009; 2008; 2007; 2006; 2005 -EEK Slovak Republic: 2010; 2009 - EUR; 2008; 2007; 2006; 2005 -SKK
    • Декабрь 2017
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 декабря, 2017
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      Better Life Index aims to involve citizens in the debate on measuring the well-being of societies, and to empower them to become more informed and engaged in the policy-making process that shapes all our lives. Each of the 11 topics of the Index is currently based on one to three indicators. Within each topic, the indicators are averaged with equal weights. The indicators have been chosen on the basis of a number of statistical criteria such as relevance (face-validity, depth, policy relevance) and data quality (predictive validity, coverage, timeliness, cross-country comparability etc.) and in consultation with OECD member countries. These indicators are good measures of the concepts of well-being, in particular in the context of a country comparative exercise. Other indicators will gradually be added to each topic.
    • Сентябрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 октября, 2018
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      STAN 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 database presents estimates of bilateral flows (imports and exports) of goods from 1990 to the latest available year; 2015 is included when available (the latest year shown is subject to the availability of underlying product-based annual trade statistics).  Reporters are the OECD member countries and a large number of Non-OECD economies, including the BRIICS: Brazil, the Russian Federation, India, Indonesia, People's Republic of China and South Africa; other selected G20 and Asian economies; as well as major African nations. A snapshot of the database's coverage is available in BTDIxE major reporters.  It should be noted that starting from mid-2012, the OECD and the United Nations agreed to centralise the data collection and processing procedures within UNSD Comtrade.  The list of partners covers the OECD countries, more than a hundred of Non-member economies as well as the partners World, Rest of the World and Unspecified.  Trade flows are divided into economic activities based on the Revision 4 of ISIC, and 9 end-use categories including capital goods, intermediate goods and household consumption.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      The OECD broadband database provides access to a range of broadband-related statistics gathered by the OECD. Policymakers must examine a range of indicators which reflect the status of individual broadband markets in the OECD.
    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 мая, 2019
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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 .
    • Июнь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 августа, 2018
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    • Июнь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 августа, 2018
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 15 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      The Burkina Faso Gender, Institutions and Development Database (Burkina Faso-GID) provides researchers and policymakers with key data at the national and subnational levels on gender-based discrimination in social institutions. This data helps analyse women’s empowerment and understand gender gaps in other key areas of development. Covering the 13 regions of the country, the Burkina Faso-GID contains comprehensive information on social norms, attitudes and both perceived and actual practices that discriminate against women and girls.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      The Burkina Faso-SIGI is a composite indicator measuring discriminatory social institutions. It is built on 46 innovative variables which are grouped into 5 sub-indices: discrimination in the family, restricted physical and moral integrity, son preference, restricted access to resources and assets and restricted civil liberties. The Burkina Faso-SIGI and its sub-indices range from 0, for no discrimination, to 1, for very high discrimination.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Май 2017
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 12 июня, 2017
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      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Май 2017
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 20 июня, 2017
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    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 05 марта, 2019
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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.
    • Май 2017
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 09 июня, 2017
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      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Май 2017
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 июня, 2017
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      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2010 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics performed in the business enterprise sector. Data include total business enterprise intramural expenditure on R&D by size class and source of funds.
    • Май 2017
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 21 июня, 2017
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      This table presents research and development (R&D) statistics on personnel in the business enterprise sector. Measured in full-time equivalent are the number of total R&D personnel and researchers in the business enterprise sector by industry according to the International Standard Industrial Classification (ISIC) revision 3.1. Data at the industry level are presented beginning 1987, year when most of the countries converted from ISIC rev.2 to the current ISIC rev. 3 classification.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 29 апреля, 2019
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    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 19 июня, 2019
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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.
    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 февраля, 2019
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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
    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 06 мая, 2019
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      Indicators in the OECD database on Carbon dioxide (CO2) emissions embodied in international trade are derived by combining the 2015 version of OECD's Inter-Country Input-Output (ICIO) Database with International Energy Agency (IEA) statistics on CO2 emissions from fuel combustion. Production-based CO2 emissions are estimated by allocating the IEA CO2 emissions to the 34 target industries in OECD ICIO and, to final demand for fuels, by both residents and non-residents. Consumption-based CO2 emissions are calculated by multiplying the intensities of the production-based emissions (c) with the global Leontief inverse (I-A)(-1) and global final demand matrix (Y) from OECD ICIO, taking the column sums of the resulting matrix and adding residential and private road emissions (FNLC), i.e. direct emissions from final demand: colsum [ diag(c) (I-A)(-1) Y ] + FNLC. The ICIO system includes discrepancies in the trade data (referred to as DISC). Emissions allocated to DISC are made explicit (e.g. in indicator FD_CO2). This ensures that global CO2 production equals global CO2 consumption.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 03 декабря, 2018
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      Note:  The updates and revisions for the OECD Central Government Debt Database have been suspended. This dataset is no longer updated. For more info, please read http://stats.oecd.org/Index.aspx?DataSetCode=GOV_DEBT   Statistical population The focus of this dataset is to provide comprehensive quantitative information on marketable and non-marketable central government debt instruments in all OECD member countries. The coverage of the data is limited to central government debt issuance and excludes therefore state and local government debt and social security funds.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      CGPITRT: Central government personal income tax rates and threshold   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
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 28 февраля, 2019
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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 agencies of foreign companies.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 03 декабря, 2018
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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.   
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
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      Statistical population: 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.   Recommended uses and limitations: 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.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
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      This dataset presents the Consolidated financial balance sheets by economic sector (Quarterly table 0710), according to SNA 2008 methodology. It comprises all flows, which record, by type of financial instruments, the financial transactions between institutional sectors.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 21 июня, 2019
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      This dataset presents the Consolidated financial transactions by economic sector (Quarterly table 0610), according to SNA 2008 methodology. It comprises all flows, which record, by type of financial instruments, the financial transactions between institutional sectors.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
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      The 'Consumer Price Indices (CPIs)' contains all data that was previously contained in three different datasets: 'Consumer Prices', 'National Consumer Price Indices (CPIs) by COICOP divisions' and 'Harmonised Indices of Consumer Prices (HICPs) by COICOP divisions'. The 'Consumer Price Indices (CPIs)' dataset contains predominantly monthly statistics, and associated statistical methodological information, for the 36 OECD member countries and for some non-member countries. The ‘Consumer Price Indices (CPIs)' dataset contains statistics on Consumer Price Indices including national CPIs, Harmonised Indices of Consumer Prices (HICPs) and their associated weights and contributions to national annual inflation. 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).
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 21 мая, 2018
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      Note: CPA data for 2018 and 2019 are projections from the 2016 Survey on Forward Spending Plans. Country Programmable Aid (CPA), outlined in our Development Brief  and also known as “core” aid, is the portion of aid donors programme for individual countries, and over which partner countries could have a significant say. CPA is much closer than ODA to capturing the flows of aid that goes to the partner country, and has been proven in several studies to be a good proxy of aid recorded at country level. CPA was developed in 2007 in close collaboration with DAC members. It is derived on the basis of DAC statistics and was retroactively calculated from 2000 onwards
    • Июль 2016
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 29 июля, 2016
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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
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июня, 2019
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      The country statistical profiles provide a broad selection of indicators, illustrating the demographic, economic, environmental and social developments, for all OECD members. The dataset also covers the five key partner economies with which the OECD has developed an enhanced engagement program with (Brazil, China, India, Indonesia and South Africa) ,accession countries (Colombia, Costa Rica and Lithuania) , Peru and the Russian Federation. The user can easily compare indicators across all countries. Total fertility rates - Unit of measure used: Number of children born to women aged 15 to 49
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Октябрь 2017
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 30 ноября, 2017
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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
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 09 июля, 2019
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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.
    • Июль 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 04 августа, 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
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 марта, 2019
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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.
    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 01 марта, 2019
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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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 04 мая, 2019
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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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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    • Апрель 2019
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    • Август 2018
      Источник: Organisation for Economic Co-operation and Development
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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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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    • Август 2018
      Источник: Organisation for Economic Co-operation and Development
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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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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    • Апрель 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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      Дата обращения к источнику: 16 апреля, 2019
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      The OECD Digital STRI identifies, catalogues and quantifies barriers that affect trade in digitally enabled services across 46 countries. It provides policy makers with an evidence-based tool that helps to identify regulatory bottlenecks, design policies that foster more competitive and diversified markets for digital trade, and analyze the impact of policy reforms. The OECD Digital STRI captures cross-cutting impediments that affect all types of services traded digitally. As a stand-alone instrument, it complements the OECD Services Trade Restrictiveness Index (STRI).
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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      The OECD Digital STRI heterogeneity indices complement the recently published Digital STRI's and presents indices of regulatory heterogeneity based on the rich information in the Digital STRI regulatory database. The indices are built from assessing – for each country pair and each measure – whether or not the countries have the same regulation. For each country pair and each sector, the indices reflect the (weighted) share of measures for which the two countries have different regulation.
    • Июль 2015
      Источник: Organisation for Economic Co-operation and Development
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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).
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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      Graduates/new entrants in each educational field as a percentage of the sum of graduates/new entrants in all fields.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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      Distribution of teachers by gender and different age groups.
    • Март 2016
      Источник: Organisation for Economic Co-operation and Development
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      Дата обращения к источнику: 20 апреля, 2016
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      1. ccTLDs stands for country code Top Level Domains. 2. gTLDs - stands for generic top-level domains.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 марта, 2019
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      The OECD FSE database is intended to be the best source of information on fisheries policies in OECD members and participating non-OECD economies. It is designed to monitor and quantify developments in fisheries policy, to establish a common basis for policy dialogue among countries, and to provide economic data to assess the effectiveness and efficiency of policies. These tables report country programmes data aggregated according to the main categories presented in the FSE Manual. More detailed documentation on country programmes can be found in country-level metadata; more data on country programmes can be found in the full dataset (Excel Format - link provided below). Statistics are organized in pivot tables to make possible cross-country comparisons and to filter disaggregated policy-level data by policy implementation criteria and country.
  • E
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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      Дата обращения к источнику: 12 апреля, 2019
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    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 05 июля, 2019
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      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.
    • Июль 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 08 августа, 2018
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      There has been a growing interest in monitoring patterns of trade in services around the world, which is partly associated with ongoing trade negotiations and partly due to the increasing importance of services in OECD economies. It has been developed to supplement other OECD publications on trade in services to address the data needs of trade analysts. It is also an important part of OECD's programme to facilitate the implementation of the recommendations of the revised Manual on Statistics of International Trade in Services 2010.Other commentsThe Task Force on Statistics of International Trade in Services maintains a matrix summarising the status of the trade in services data collection performed by International Organisations. The table displays links to the databases as well as update timetables, availability of metadata, availability of bilateral data, and other important characteristics.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
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      Дата обращения к источнику: 29 апреля, 2019
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      The OECD Long-Term Baseline Scenario is a projection of some major economic variables beyond the short-term horizon of the OECD Economic Outlook. It covers all OECD economies, non-OECD G20 economies and key partners. The projection horizon is currently 2060. For the historical period and the short-run projection horizon, the series are consistent with those of the OECD Economic Outlook number in the dataset title. The definitions, sources and methods are also the same, except where noted explicitly (such as coverage of the non-OECD and world aggregates). For more details on the methodology, please see Boxes 1 to 3 in The Long View: Scenarios for the World Economy to 2060 and the references therein.The baseline scenario is a projection conditional on a number of assumptions, notably that countries do not carry out institutional and policy reforms. It is used as a reference point to illustrate the potential impact of structural reforms in alternative scenarios, such as those discussed in The Long View: Scenarios for the World Economy to 2060. The data for these alternative scenarios are not available here but can be obtained on request by writing to [email protected].
    • Ноябрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 04 марта, 2019
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      The OECD Economic Outlook analyses the major economic trends over the coming 2 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 data (for all variables) and quarterly figures (for a subset of variables). 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 data bases such as Quarterly National Accounts, Annual National Accounts, Labour Force Statistics and Main Economic Indicators. The cut-off date for information used in the compilation of the projections was the 14 November 2018.   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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 29 апреля, 2019
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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 this Outlook provides a unique tool 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 rates and exchange rates, the balance of payments, government and of households, and government debt. For the non-OECD regions, foreign trade and current account series are available. The database contains annual and quarterly data for the historical period and for the projection period. For this latter period, quarterly data are available for the G7 countries, and the OECD regions, while annual data are available for all OECD countries and for non-OECD regions. Quarterly series are seasonally adjusted. Variables are defined in such a way that they are as homogenous as possible over the countries. 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 Annual Labour Force Statistics and the Main Economic Indicators.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 29 апреля, 2019
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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 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 Annual Labour Force Statistics and the Main Economic Indicators. The cut-off date for information used in the compilation of the projections was the 15 May 2013. With the OECD Economic Outlook 87, new aggregation techniques have been applied to construct the OECD area (34 countries) and the OECD euro area (15 OECD countries that are also members of Euro area). The new approach aims to better handle issues arising from evolving composition of these areas and different data availability across countries. The main changes are a switch from a fixed weighting scheme to moving weighting schemes for OECD and the direct aggregation of ratios, rather than computing them as ratios of aggregated components. Consequently, a number of series expressed in levels differ from the series previously published, while others are no longer available, particularly government and labour market data. 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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 29 апреля, 2019
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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 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 29 May 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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 29 апреля, 2019
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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 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 29 May 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.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 03 декабря, 2018
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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).
    • Январь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 20 февраля, 2019
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      The OECD, in cooperation with the EU, has developed a harmonised definition of urban areas which overcomes previous limitations linked to administrative definitions (OECD, 2012). According to this definition an urban area is a functional economic unit characterised by densely inhabited “city core” and “commuting zone” whose labour market is highly integrated with the core. The Metropolitan database provides indicators of 649 OECD metropolitan areas identified in 33 OECD countries and the functional urban areas of Colombia. Comparable values of population, GDP, employment, and other indicators are presented.
    • Сентябрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 октября, 2018
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      This indicator presents internationally comparable data on education and earnings, by educational attainment, age and gender as published in OECD Education at a Glance 2018. For trend data, Education at a Glance 2018 includes data for 2005 and 2010-2016 (or years available).
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 марта, 2019
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      This indicator presents internationally comparable data regarding the labour force status and the educational attainment level by the National Educational Attainment Categories (NEAC) as reported by the labour force survey (LFS) and published in OECD Education at a Glance 2017. For trend data, the Education at a Glance Database includes data from 1981 to 2016 (or years with available data).
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 29 апреля, 2019
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      The nature of expenditure distinguishes between current and capital expenditure. The resource category refers to service provider (public institutions, government-dependent private institutions, and independent private institutions, i.e. both educational and other 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).
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      All entities that provide funds for education, either initially or as final payers, are classified as either governmental (public) sources or non-governmental (private) sources, the sole exception being "international agencies and other foreign sources", which are treated as a separate category. There are three types of financial transactions: Direct expenditure on educational institutions; Transfers to students or households and to other private entities; and Households' expenditure on education outside educational institutions.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      These indicators on expenditure on education are published in chapter C of Education at a Glance, which covers financial and human resources invested in education.They are either policy levers or provide context information on education systems, or sometimes both. For example, expenditure per student is a key policy measure that most directly affects the individual learner, as it acts as a constraint on the learning environment in schools and learning conditions in the classroom.The data set “educational finance indicators” provides the main indicators computed for three levels of education : primary, secondary and post-secondary non-tertiary levels combined; tertiary level; and primary to tertiary levels combined. Other datasets provide more breakdowns for each specific indicator.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 02 июля, 2019
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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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      This dataset presents the average number of teachers by sex and age.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      This dataset presents the average number of teachers by sex and type of institution.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      This indicator measures the proportion of earnings that are lost to either higher taxes or lower benefit entitlements when a jobless person takes up employment. It is commonly referred to as "Participation Tax Rate (PTR)" as it measures financial disincentives to participate in the labour market.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      This indicator measures the proportion of earnings that are lost to either higher taxes, lower benefits or childcare costs when a parent with young children takes up full-time employment and requires use of centre-based childcare services.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      This indicator measures the fraction of any additional earnings that is lost to either higher taxes or lower benefits when an employed person increases their working hours.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Июль 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 05 августа, 2014
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      The Pensions at a Glance indicators, covering all 34 OECD countries, are designed to show future entitlements for workers who entered the labour market in 2008 and spend their entire working lives under the same set of rules. The results presented here include all mandatory pension schemes for private-sector workers, regardless of whether they are public or private.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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      These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. They comprise the summary of agricultural support estimates for OECD countries.
    • Сентябрь 2012
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 22 марта, 2019
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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.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 марта, 2019
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      These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. They comprise the summary of agricultural support estimates for OECD countries.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 06 июля, 2019
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      2011 G) Emerging Economies: Consumer Support Estimate by Country These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. They comprise the summary of agricultural support estimates for OECD countries. NPC: Nominal Protection Coefficient. NAC: Nominal Assistance Coefficient.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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      These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. They comprise the summary of agricultural support estimates for OECD countries. TSE : Total support estimate.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июня, 2019
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      2011 E) Emerging Economies: Producer Support Estimate by Country These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. They comprise the summary of agricultural support estimates for OECD countries. NPC: Nominal Protection Coefficient. NAC: Nominal Assistance Coefficient.  
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 марта, 2019
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      These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. They comprise the summary of agricultural support estimates for OECD countries.
    • Сентябрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 22 марта, 2019
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      This dataset provides selected information on national 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 (PM), carbon monoxide (CO) and volatile organic compounds (VOC). Categories presented are based on the NFR 2014 classification. Data exclude non man-made emissions and international aviation and maritime transports emissions. For some countries residential mobile emissions (e.g. mowers) are included into Other combustion instead of Other mobile. The GDP used to calculate intensities is expressed in USD at 2010 prices and PPPs.  
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 17 апреля, 2019
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      Compared to men, women are less likely to work full-time, more likely to be employed in lower-paid occupations, and less likely to progress in their careers. As a result gender pay gaps persist and women are more likely to end their lives in poverty. This data looks at how many men and women are in paid work, who works full-time, and how having children and growing older affect women’s work patterns and earnings differently to men’s. It looks at how women bear the brunt of domestic and family responsibilities, even when working full-time. It also considers the benefits for businesses of keeping skilled women in the workplace, and encouraging them to sit on company boards. It looks at women’s representation in parliaments, judicial systems, and the senior civil service. It examines male and female employment in the wake of the crisis, and how women tend to be confined to the most vulnerable categories within the informal sector in developing countries.
    • Июль 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 23 июля, 2018
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      Employment, participation rates: population aged 15-64; Unemployment rate: active population aged 15-64.   Rates as defined by the International Labour Organization.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      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.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 марта, 2019
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      This dataset 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.). Geographic coverageIn order to facilitate analysis and comparisons over time, historical data for OECD members have been provided over as long a period as possible, often even before a country became a member of the Organisation. Information on the membership dates of all OECD countries can be found at OECD Ratification Dates.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 03 декабря, 2018
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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.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      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.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 марта, 2019
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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.
    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 21 мая, 2019
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    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 15 марта, 2019
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      This dataset presents the number of students enrolled in different education programmes by country of origin and sex.
    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 мая, 2019
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      Number of students enrolled in different education programmes by age and sex.
    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 21 мая, 2019
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      This dataset presents the number of students enrolled in different education programmes by field and sex.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      This indicator examines the share of students by gender, programme orientation and mode of study over the total number of students.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
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      Number of students enrolled in different education programmes by type of institution and sex.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Number of students by level of education, adjusted to the financial year. When financial year, school year and calendar year differs, adjustments are made to ease comparison.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июля, 2019
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      Enrolment rate per age is the percentage of students enrolled in each type of institution over the total of students
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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    • Август 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 08 сентября, 2014
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Entrepreneurship is crucial to economic development, promoting social integration and reducing inequalities. The Gender-entrepreneurship dataset presents an original collection of indicators that measure gender equality in entrepreneurship, providing an important reference for policy insights and policy making. Data refer mainly to the self-employed, their profile, age, education and sector of activity.
    • Октябрь 2013
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 04 августа, 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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      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.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      The OECD Environmental Policy Stringency Index (EPS) is a country-specific and internationally-comparable measure of the stringency of environmental policy. Stringency is defined as the degree to which environmental policies put an explicit or implicit price on polluting or environmentally harmful behaviour. The index ranges from 0 (not stringent) to 6 (highest degree of stringency). The index covers 28 OECD and 6 BRIICS countries for the period 1990-2012. The index is based on the degree of stringency of 14 environmental policy instruments, primarily related to climate and air pollution.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июля, 2019
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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.
    • Июль 2016
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 29 августа, 2017
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      EAMFP growth measures the residual growth in the joint production of both the desirable and the undesirable outputs that cannot be explained by changes in the consumption of factor inputs (including labour, produced capital and natural capital). Therefore, for a given growth of input use, EAMFP increases when GDP increases or when pollution decreases. As part of the growth accounting framework underlying the EAMFP indicator, the growth contribution of natural capital and growth adjustment for pollution abatement indicators are derived: Growth contribution of natural capital - measures to what extent a country's growth in output is attributable to natural resource use; Growth adjustment for pollution abatement - measures to what extent a country's GDP growth should be corrected for pollution abatement efforts - adding what has been undervalued due to resources being diverted to pollution abatement, or deducing the ‘excess' growth which is generated at the expense of environmental quality.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 26 декабря, 2018
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      National currencies are converted in United States dollars (USD) using IMF monthly average conversion rates.
    • Сентябрь 2017
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 ноября, 2017
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    • Сентябрь 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 04 октября, 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.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      Air pollution is considered one of the most pressing environmental and health issues across OECD countries and beyond. According to the World Health Organisation (WHO), exposure to fine particulate matter (PM2.5) has potentially the most significant adverse effects on health compared to other pollutants. PM2.5 can be inhaled and cause serious health problems including both respiratory and cardiovascular disease, having its most severe effects on children and elderly people. Exposure to PM2.5 has been shown to considerably increase the risk of heart disease and stroke in particular. For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator. The underlying PM2.5 concentrations estimates are taken from van Donkelaar et al. (2016). They have been derived using satellite observations and a chemical transport model, calibrated to global ground-based measurements using Geographically Weighted Regression at 0.01° resolution. The underlying population data, Gridded Population of the World, version 4 (GPWv4) are taken from the Socioeconomic Data and Applications Center (SEDAC) at the NASA. The underlying boundary geometries are taken from the Global Administrative Unit Layers (GAUL) developed by the FAO, and the OECD Territorial Classification, when available. The current version of the database presents much more variation with respect to the previous one. The reason is that the underlying concentration estimates previously included smoothed multi-year averages and interpolations; while in the current version annual concentration estimates are used. Establishing trends of pollution exposure should be done with care, especially at smaller output areas, as their inputs (e.g. underlying data and models) can change from year to year. We recommend using a 3-year moving average for visualisation.
    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 мая, 2019
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      Air pollution is considered one of the most pressing environmental and health issues across OECD countries and beyond. According to the World Health Organisation (WHO), exposure to fine particulate matter (PM2.5) has potentially the most significant adverse effects on health compared to other pollutants. PM2.5 can be inhaled and cause serious health problems including both respiratory and cardiovascular disease, having its most severe effects on children and elderly people. Exposure to PM2.5 has been shown to considerably increase the risk of heart disease and stroke in particular. For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator. The underlying PM2.5 concentrations estimates are taken from van Donkelaar et al. (2016). They have been derived using satellite observations and a chemical transport model, calibrated to global ground-based measurements using Geographically Weighted Regression at 0.01° resolution. The underlying population data, Gridded Population of the World, version 4 (GPWv4) are taken from the Socioeconomic Data and Applications Center (SEDAC) at the NASA. The underlying boundary geometries are taken from the Global Administrative Unit Layers (GAUL) developed by the FAO, and the OECD Territorial Classification, when available. The current version of the database presents much more variation with respect to the previous one. The reason is that the underlying concentration estimates previously included smoothed multi-year averages and interpolations; while in the current version annual concentration estimates are used. Establishing trends of pollution exposure should be done with care, especially at smaller output areas, as their inputs (e.g. underlying data and models) can change from year to year. We recommend using a 3-year moving average for visualization.
  • F
    • Август 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 07 августа, 2018
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      In view of the strong demand for cross-national indicators on the situation of families and children, the OECD Family Database was developed to provide cross-national indicators on family outcomes and family policies across the OECD countries, its enhanced engagement partners and EU member states. The database brings together information from various national and international databases, both from within the OECD and from external organisations. The database classifies indicators into four main dimensions: (i) structure of families, (ii) labour market position of families, (iii) public policies for families and children and (iv) child outcomes. Detailed information on the definitions, sources and methods used in the construction of the database can be found on the OECD Family Database webpage.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 17 апреля, 2019
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    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 11 июня, 2019
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      FDI statistics cover all entities in an FDI relationship. An FDI relationship is established when an investor in one country acquires 10% or more of the voting power in a business enterprise in another country. The investor is also called a direct investor or a parent and the business enterprise is called a direct investment enterprise or an affiliate. The 10 percent criteria is used to establish that the direct investor has a significant degree of influence over the operations of the direct investment enterprise. The FDI population includes affiliates that are directly and indirectly owned by the parent. In direct ownership, the parent owns the 10% or more voting power itself. In indirect ownership, the parent controls an affiliate that in turn owns 10 percent or more of the voting power in another enterprise. The FDI population also includes enterprises that are not in a direct investment relationship themselves but have a direct investor in common. Called fellow enterprises, they are included because, even though there is no direct investment relationship between the two, any transactions between them likely resulted from the influence that their common direct investor has on both of their operations.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 марта, 2019
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    • Февраль 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 26 июня, 2018
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      FDI data are based on statistics provided by 35 OECD member countries and by Lithuania. BMD4: OECD Benchmark Definition of Foreign Direct Investment - 4th Edition
    • Июнь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 25 июля, 2018
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    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 марта, 2019
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    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 19 июня, 2019
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      FDI statistics cover all entities in an FDI relationship. An FDI relationship is established when an investor in one country acquires 10% or more of the voting power in a business enterprise in another country. The investor is also called a direct investor or a parent and the business enterprise is called a direct investment enterprise or an affiliate. The 10 percent criteria is used to establish that the direct investor has a significant degree of influence over the operations of the direct investment enterprise. The FDI population includes affiliates that are directly and indirectly owned by the parent. In direct ownership, the parent owns the 10% or more voting power itself. In indirect ownership, the parent controls an affiliate that in turn owns 10 percent or more of the voting power in another enterprise. The FDI population also includes enterprises that are not in a direct investment relationship themselves but have a direct investor in common. Called fellow enterprises, they are included because, even though there is no direct investment relationship between the two, any transactions between them likely resulted from the influence that their common direct investor has on both of their operations.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 марта, 2019
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    • Июнь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2018
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 30 апреля, 2019
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    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 22 мая, 2019
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      The FDI Regulatory Restrictiveness Index (FDI Index) measures statutory restrictions on foreign direct investment across 22 economic sectors. It gauges the restrictiveness of a country’s FDI rules by looking at the four main types of restrictions on FDI: 1) Foreign equity limitations; 2) Discriminatory screening or approval mechanisms; 3) Restrictions on the employment of foreigners as key personnel and 4) Other operational restrictions, e.g. restrictions on branching and on capital repatriation or on land ownership by foreign-owend enterprises. Restrictions are evaluated on a 0 (open) to 1 (closed) scale. The overall restrictiveness index is the average of sectoral scores. The discriminatory nature of measures, i.e. when they apply to foreign investors only, is the central criterion for scoring a measure. State ownership and state monopolies, to the extent they are not discriminatory towards foreigners, are not scored. The FDI Index is not a full measure of a country’s investment climate. A range of other factors come into play, including how FDI rules are implemented. Entry barriers can also arise for other reasons, including state ownership in key sectors. A country’s ability to attract FDI will be affected by others factors such as the size of its market, the extent of its integration with neighbours and even geography among other. Nonetheless, FDI rules can be a critical determinant of a country’s attractiveness to foreign investors.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 18 июня, 2019
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      Source: OECD International direct investment database, IMF Reference:Benchmark Definition of Foreign Direct Investment, 3rd edition   Foreign direct investment reflects the objective of obtaining a lasting interest by a resident entity in one economy (‘‘direct investor'') in anentity resident in an economy other than that of the investor (‘‘direct investment enterprise''). The lasting interest implies the existence of a long-term relationship between the direct investor and the enterprise and a significant degree of influence on the management of the enterprise. Direct investment involves both the initial transaction between the two entities and all subsequent capital transactions between them and among affiliated enterprises, both incorporated and unincorporated.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июля, 2019
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      Chapter B includes indicators that are either policy levers or antecedents to policy, or sometimes both. For example, expenditure per student is a key policy measure that most directly affects the individual learner, as it acts as a constraint on the learning environment in schools and learning conditions in the classroom.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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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.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
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      Data are compiled either by Central banks, or Statistical National Institutes. EU data are validated and provided by the European Central Bank whereas non-EU data are provided by national institutions. The sectors for which information is presented are: Total economy (S1) - Non-financial corporations (S11) - Financial corporations (S12) and its sub-sectors (S121 to S125) - General government (S13) and its sub-sectors (1311 to S1314) - Households (S14) - Non-profit institutions serving households (S15) Rest of the world (S2)
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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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 behavior 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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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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.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 04 июня, 2019
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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.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
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      The Financial account, which is the second accumulation account, records financial flows: it indicates the types of financial instruments utilized by the different institutional sectors to acquire financial assets or incur liabilities. Data are compiled either by Central banks, or Statistical National Institutes. EU data are validated and provided by the European Central Bank whereas non-EU data are provided by national institutions.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 11 июня, 2019
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      The dataset Fisheries International collaboration in technology development (bilateral) provides the number of co-inventions (simple patent families) developed jointly by at least two inventors. This indicator is disaggregated by: Country - country of residence of the inventor(s), integral counted; in cases when inventors from more than two countries collaborate, this is translated into distinct bilateral relationships between country pairs. For example, if inventors from 3 countries collaborate (e.g. USA, DEU, JPN) then a unit count is assigned to 6 country pairs (USA-DEU, USA-JPN, DEU-JPN, DEU-USA, JPN-USA, JPN-DEU); in this case a country generally coordinate the project and the others are partners. Partner – country of residence of the inventor(s) who collaborate to the patent. Technology domain – the three main areas of innovation in fisheries and aquaculture, related to technology development. In detail: 1. Harvesting technology such as more effective ways to find or harvest fish and which are typically associated with improvements in catch per unit of effort (e.g. type/size of vessels and their methods of propulsion, search technologies, method of catching or harvesting fish and bringing them on board); 2.Aquaculture technology such as methods to more effectively grow fish in captivity (innovation in feeds, improving the health of aquaculture animals, etc.); 3. New products and markets such as the development of new fish products and markets (food technologies/processing such as the development of surimi as a crabmeat substitute) and the improvement of market access (secure or enlarge markets for fish products) that provides important incentives for green growth (e.g. eco-certification with fishers adopting by-catch saving technologies or modifying fishing practices and/or territorial user rights in fisheries).
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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      The OECD FISH Unit, in collaboration with the Environment Directorate and the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in fisheries-related technologies. The search strategy for fisheries and aquaculture related technologies adopts a mixed solution with a definition of the technical field of interest in fisheries and aquaculture innovation complemented by keywords, e.g. by looking for keywords in the International Patent Classification (IPC) codes and checking manually the relevance of the results in the text of patents (in the title, the abstract, etc). Technology domains are detailed in the ANNEX attached below. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' fisheries, aquaculture and innovation policies.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 26 марта, 2019
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      The Fisheries R&D expenditures dataset contains the budgetary expenditures in research and development on total budgetary FSE. Three variables are presented in this dataset:  • R&D expenditures - they are budgetary expenditures that finance research and development activities related to fisheries, irrespective of the institution (private or public, ministry, university, research centre or fisher group) or where they take place, the nature of research (scientific, institutional, etc.), or its purpose. The focus is on research and development expenditures on applied research related to the fisheries sector. Social-sciences research related to fisheries is included. It is also included data dissemination when associated primarily with research and development (knowledge generation), e.g. reports from research and databases developed as an adjunct to research. •FISHERIES SUPPORT ESTIMATE - Budgetary - it is the annual monetary value of gross transfers from taxpayers to fishers arising from policy measures that support fisheries, regardless of their nature, objectives or impacts. Data on FSE are collected by the Fisheries Committee (COFI) from the Trade and Agriculture Directorate (TAD) on an annual basis from all its participating countries. Data are provided by Fisheries Ministries, National Statistics Offices and other institution designated as an official data source. The original financial data is collected in national currency at current values; they are converted and published also in US dollars, for analytical purposes and to allow data comparisons. • Share of R&D expenditures on FSE - it is the share of budgetary research and development expenditures on total budgetary FSE. Please notice that total budgetary FSE is defined ‘net’, i.e. it is adjusted for costs incurred by fishers in order to receive the support. Whenever these costs are of significant amount, total budgetary FSE becomes remarkably low or negative. The corresponding share of research and development expenditures turns into a percentage exceptionally high or negative.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 19 марта, 2019
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      The OECD Fisheries Support Estimates (FSE) database is intended to be the best source of information on fisheries policies in OECD members and participating non-OECD economies.   It is designed to monitor and quantify developments in fisheries policy, to establish a common basis for policy dialogue among countries, and to provide economic data to assess the effectiveness and efficiency of policies.   These tables report country programmes data aggregated according to the main categories presented in the FSE Manual.   More detailed documentation on country programmes can be found in country-level metadata; more data on country programmes can be found in the full dataset (Excel Format - link provided below). Statistics are organized in pivot tables to make possible cross-country comparisons and to filter disaggregated policy-level data by policy implementation criteria and country.   The FSE data collection is part of the more comprehensive data gathering carried out on an annual basis by the Fisheries Committee (COFI) of the Trade and Agriculture Directorate (TAD) from OECD members and participating non-OECD economies.   Data on landings, aquaculture production, inland fisheries catch, fleet, employment, total allowable catch (TAC) and fisheries support estimate (FSE) are collected from Fisheries Ministries, National Statistics Offices and other institutions designated as an official data source. The surveys used for this exercise are the OECD Fisheries questionnaires.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 марта, 2019
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      The OECD FISH Unit, in collaboration with the Environment Directorate and the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in fisheries-related technologies. The search strategy for fisheries and aquaculture related technologies adopts a mixed solution with a definition of the technical field of interest in fisheries and aquaculture innovation complemented by keywords, e.g. by looking for keywords in the International Patent Classification (IPC) codes and checking manually the relevance of the results in the text of patents (in the title, the abstract, etc). Technology domains are detailed in the ANNEX attached below. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' fisheries, aquaculture and innovation policies.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 марта, 2019
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      The OECD FISH Unit, in collaboration with the Environment Directorate and the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in fisheries-related technologies. The search strategy for fisheries and aquaculture related technologies adopts a mixed solution with a definition of the technical field of interest in fisheries and aquaculture innovation complemented by keywords, e.g. by looking for keywords in the International Patent Classification (IPC) codes and checking manually the relevance of the results in the text of patents (in the title, the abstract, etc). Technology domains are detailed in the ANNEX attached below. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' fisheries, aquaculture and innovation policies.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 марта, 2019
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      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).
    • Июль 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 30 августа, 2017
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      The OECD food waste dataset is a compilation of available data related to food loss and food waste for 32 countries. The period covered may vary across different countries depending on data availability (globally ranging from 1993 to 2013). Several types of sources have been used: international organisations, government and national statistic institutes, OECD delegations, academic studies and private sector or>>/governmental analytical reports. When available, detailed information on sources is provided in the "variable def. and sources" (eg. references to an academic article or a government website).
    • Сентябрь 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 04 октября, 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). 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.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
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      FDI statistics cover all entities in an FDI relationship. An FDI relationship is established when an investor in one country acquires 10% or more of the voting power in a business enterprise in another country. The investor is also called a direct investor or a parent and the business enterprise is called a direct investment enterprise or an affiliate. The 10 percent criteria is used to establish that the direct investor has a significant degree of influence over the operations of the direct investment enterprise.   The FDI population includes affiliates that are directly and indirectly owned by the parent. In direct ownership, the parent owns the 10% or more voting power itself. In indirect ownership, the parent controls an affiliate that in turn owns 10 percent or more of the voting power in another enterprise.   The FDI population also includes enterprises that are not in a direct investment relationship themselves but have a direct investor in common. Called fellow enterprises, they are included because, even though there is no direct investment relationship between the two, any transactions between them likely resulted from the influence that their common direct investor has on both of their operations.
    • Декабрь 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 11 ноября, 2016
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      ARGENTINA: GENERAL METADATA Data documentation General notes The fiscal year in Argentina coincides with the calendar year. The Republic of Argentina is a federal country comprising twenty-three provinces and one autonomous city (Autonomous City of Buenos Aires - CABA), which is the capital city of the country. Methodological notes This inventory includes monetary transfers made by the National Administration to finance the current expenditures of different stakeholders related to the energy sector, including state-owned companies, private companies and trust funds. It also includes tax expenditures related to taxes on fuels (motor gasoline, diesel fuel and compressed natural gas). These are calculated by the government as revenue foregone when a tax treatment other than the one established in more general terms in the tax laws, or a different tax treatment to substitute goods, is provided (Ministerio de Hacienda y Finanzas Públicas, 2016).
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
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      AUSTRALIA: GENERAL METADATA Data documentation General notes The fiscal year in Australia runs from 1July to 30June. Following OECD convention, data are allocated to the starting calendar year so that data covering the period July2005 to June2006 are allocated to 2005. Australia being a federal country, the data also cover the following states and territories: the Australian Capital Territory (ACT), New South Wales (NSW), the Northern Territory (NT), Queensland (QLD), South Australia (SA), Tasmania (TAS), Victoria (VIC), and Western Australia (WA). Certain features of Australia’s tax system that indirectly support the production of fossil fuels apply to the mining sector as a whole. While the OECD’s approach to support for fossil fuels stresses the importance of specificity [1], the present inventory considers those measures that apply to mining in general to be specific enough to warrant their inclusion in the database. In the absence of data on the actual sector distribution of the usage of these measures, as in other countries, the OECD has estimated based on relative levels of output or exploration expenditure the share of the usage that relates to fossil-fuel extraction, as opposed to the share relating to the extraction of other minerals (e.g. gold or zinc). This estimation should not be interpreted, however, as reflecting the views of the responsible governments. [2] Because 90% of Australia’s power generation uses fossil fuels (and coal in particular), and taking into account the fact that the country does not trade electricity with other economies, measures directly supporting the use of electricity in Australia are here treated as indirect support for fossil fuels. Since Victoria is the only state where recoverable brown coal reserves are available, all state-level measures in place in other states and benefitting coal have been allocated to hard coal only. [ABS Mineral Account (1996) and Minerals Council of Australia (2015) Coal Hard Facts] Notes relating to Producer Support Estimates The offshore extraction of oil and natural gas in Australia is subject to a particular tax regime combining a resource tax and the regular corporate income tax. The former, the Petroleum Resource Rent Tax (PRRT), was introduced with the Petroleum Resource Rent Tax Assessment Act of 1987. It is project-based and applies to taxable profits at the rate of 40%. [3] Rules under the PRRT allow for the full deduction of exploration, development, and decommissioning expenditures in the year in which they are incurred. Financing costs are, however, not deductible for PRRT purposes. Unclaimed deductions can be carried forward and compounded every year at varying rates. Some of these deductions can also be transferred to other projects within the same company or group. The general corporate income-tax rate in Australia is 30% and deductions are allowed for PRRT and royalty payments, business expenses, and exploration costs incurred for mining (including coal) and oil and gas extraction. Some expenses related to mine rehabilitation and the decommissioning of offshore platforms are also deductible for income-tax purposes. Because the tax is not ring-fenced, losses from one project can be deducted against the profits of another. The immediate write-off of expenditures of a capital nature (including exploration and development expenditures) is normally considered under the tax systems of many countries to amount to a preferential tax treatment. The reason is that in calculating taxable profits in most income-tax systems, capital expenses are amortised over the period to which they contribute to earnings. Allowing these types of expenditure to be written-off in full in the year in which they are incurred therefore provides companies with a benefit akin to a zero-interest loan from the government since it delays the collection of taxes. A present-value calculation would thus show a positive transfer from the government to the companies benefitting from such provisions. However, when combined with a provision preventing companies from deducting interest costs and other financing charges, the immediate write-off of expenditures of a capital nature may not be considered preferential tax treatment. This is because this particular combination of tax provisions may approximate what is known as "cash-flow" taxation. Cash-flow tax systems can be theoretically equivalent to the more common imputed-income tax systems where the objective is to levy a neutral business tax. For that reason, measures such as the expensing of exploration and development costs may not be preferential tax provisions in the particular case of Australia’s PRRT. [4] In recent years, the Australian Government has enacted legislation that modified the country’s resource-taxation regime considerably. Changes include the extension of the PRRT regime to most onshore and offshore oil and natural-gas projects, and the introduction and subsequent repeal of the short-lived Mineral Resource Rent Tax (MRRT), which only applied from 2012 through 2013 and sought to tax the profits from the extraction of coal and iron ore at a 30% rate. Footnotes [1] Article2 of the WTO’s Agreement on Subsidies and Countervailing Measures (SCM) also stresses the importance of "specificity" in determining whether a particular measure falls under the scope of the agreement. [2] An estimated allocation based on gross-output shares or exploration expenditure by mineral is used here to provide readers with a sense of the magnitudes involved. Since these allocations are not from government sources and are based on general volume and value ratios, they might not always correlate well with actual distributions, if such information were available. These assumptions have been made by the OECD and should not be interpreted as reflecting the views of the responsible government. [3] Some offshore areas like the North West Shelf were, until recently, still subject to the previous royalty and crude-oil excise regime, or to production-sharing contracts. However, legislation enacted by the Australian Government now provides for the extension of the PRRT regime to all onshore and offshore oil and gas projects by 1July2012, with the exception of the Joint Petroleum Development Area in the Timor Sea which remains subject to production-sharing contracts with Timor-Leste under the Timor Sea Treaty. [4] See Box5 in OECD (2015).
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      AUSTRIA: GENERAL METADATA Data documentation General notes The fiscal year in Austria coincides with the calendar year. Amounts prior to 1999 are expressed as "euro-fixed series", meaning that this inventory applies the fixed EMU conversion rate (EUR 1 = ATS 13.7603) to data initially expressed in Austrian Schilling (ATS). In the case of the support measure AUT_te_04 ("Energy-Tax Refund to Energy-Intensive Industries"), the conversion into EUR was already made by the Federal Ministry of Finance. Annual estimates were found on the website of the Federal Ministry of Finance or provided directly by the Federal Ministry of Finance (for years prior to 2004).
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      BELGIUM: GENERAL METADATA Data documentation General notes The fiscal year in Belgium coincides with the calendar year. Following OECD convention, amounts prior to 1999 are expressed as "euro-fixed series", meaning that this inventory applies the fixed EMU conversion rate (EUR 1 = BEF 40.339) to data initially expressed in the Belgian Franc (BEF). Producer Support Estimate Belgium supported the production of hard coal until 1992, at which time the last mine still in operation was closed. Since then, it has not supported the production of any fossil fuel.
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      BRAZIL: GENERAL METADATA Data documentation General notes Brazil is a federation comprising 27sub-national jurisdictions [1] that possess a certain degree of freedom in setting prices for energy generation, transmission, and distribution. For this reason, there may be variations between federal and regional authorities in the adoption and implementation of energy-related policies. A few regional spending programmes provide reductions in the ICMS tax for transactions involving diesel fuel used in public transport. A cursory review of these regional policies suggests that the overall value of sub-national support for fossil fuels is much less significant than that of federal support. Brazil’s fiscal year coincides with the calendar year. Methodological note A large part of support to fossil fuels in non-OECD economies takes the form of price controls or regulations benefitting final consumers. In many cases, this occurs through the government mandating state-owned oil and gas companies to charge lower retail prices, which lowers the revenues these companies collect through their sales of fuel. This sometimes results in the government subsequently intervening to compensate state-owned oil and gas companies for the losses they incurred in the downstream sector due to the regulated prices, with this compensation taking many forms. Some governments choose, for example, to compensate national oil and gas companies through targeted tax concessions (e.g., VAT exemptions) or equity injections. This inventory focusses on the direct budgetary transfers and tax expenditures that encourage the production or consumption of fossil fuels, including those benefitting national oil and gas companies. For this reason, some of the measures classified here under "Producer Support Estimate" may have been introduced by governments with a view to compensating domestic, vertically integrated oil and gas companies for the lower prices they are required to charge at the retail level, resulting in these measures being connected to some extent to consumer support. Producer Support Estimate Upstream operators of oil and natural-gas concession blocks in Brazil are subject to additional specific government levies - notably royalties, a signature bonus, a special participation tax, and an area-retention tax. Royalties take the form of a monthly tax applied on sales revenue at a rate of 10%, which can be reduced in exceptional cases to 5%. Special participation is a quarterly tax applied on sales revenue at a rate that varies from 10% to 40%, which is adjusted for certain high-volume or high-profit-margin fields. The signature bonus is an amount included by oil and gas producers in their concession bids, and which is payable to the ANP upon signature of the concession agreement. Lastly, the area-retention tax is an annual tax set by the ANP during the bidding round, the rate of which depends on the size and the geological characteristics of the field. Under this latter tax, upstream operators of concession blocks located onshore must pay the owners of the land where they operate an amount determined by the ANP, usually in the range of 0.5% to 1% of the value of production. Under concession agreements, upstream operators are also required to carry out domestic R&D investments equal to at least 1% of their gross revenues. Readers are advised that some fiscal measures related to oil and natural-gas production may not constitute tax expenditures under an alternative baseline where resource taxes (or production taxes) vary with market conditions and production costs. This inventory uses the annual amounts of tax expenditures as reported by the Federal Revenue Secretariat of Brazil. Footnotes [1] The Federative Republic ofBrazil currently consists of 26 states and one federal district.
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      CANADA: GENERAL METADATA Data documentation General notes The fiscal year in Canada runs from 1 April to 31 March. Following OECD convention, data are allocated to the starting calendar year so that data covering the period April 2005 to March 2006 are allocated to 2005. Canada being a federal country, the data also cover the following provinces and territories: Alberta (AB), British Columbia (BC), Manitoba (MB), New Brunswick (NB), Newfoundland and Labrador (NL), Nova Scotia (NS), Ontario (ON), Prince Edward Island (PE), Quebec (QC), Saskatchewan (SK), and Yukon Territory (YT). [1] The inventory includes a number of provincial tax expenditures within resource royalty systems. These are included because they are explicitly defined as quantified departures from the general royalty rules. As noted in Chapter 2 of OECD (2015), however, it is important that such measures, including their objectives and impacts, be considered (in a parallel way with income-tax and consumption-tax measures) within the context of the broader royalty system of which they form a part. Certain features of Canada’s tax system that indirectly support the production of fossil fuels - including coal and oil sands - apply to the mining sector as a whole. While the OECD definition of support to fossil fuels stresses specificity as a requisite [2], the present inventory considers those measures that apply to mining in general to be specific enough to warrant their inclusion in the database. In the absence of data on the actual sector distribution of the usage of these measures, as in other countries, the OECD has estimated based on relative output levels the share of the usage that relates to fossil-fuel extraction, as opposed to the share relating to the extraction of other minerals (e.g. uranium). This should not be interpreted, however, as reflecting the views of the responsible governments. [3] Notes relating to Producer Support Estimates in the Province of Quebec The province of Quebec does not currently produce fossil fuels on a significant scale, though some companies are actively exploring for oil in the Gaspe Peninsula and around the Anticosti Island. Exploration efforts are also concentrating on the province’s potential for shale gas, mostly in the south (e.g. Basses-Terres du Saint-Laurent). The refundable tax credit for resources (Crédit d’impôt remboursable relatif aux ressources) was introduced in March 2001 by the government of Quebec and provides eligible mining companies operating in the province with a refundable tax credit for up to 38.75% of qualifying exploration expenditure. [4] Qualifying exploration expenditure includes those expenses made with respect to oil and natural-gas, and which attract an additional 50% deduction for tax purposes. While this measure benefits some companies engaged in the exploration for fossil fuels in Quebec, exploration expenditure in the province remains heavily oriented towards non-energy minerals. This measure is therefore not deemed specific enough to warrant inclusion in the present inventory, which would not preclude its inclusion at a later stage should fossil-fuel exploration further increase in scale. Footnotes [1] The inventory does not include at this stage Nunavut and the Northwest Territories. [2] Article 2 of the WTO’s Agreement on Subsidies and Countervailing Measures (SCM) also stresses the importance of "specificity" in determining whether a particular measure falls under the scope of the agreement. [3] An estimated allocation based on gross-output shares is used here to provide readers with a sense of the magnitudes involved. Since these allocations are not from government sources and are based on general volume and value ratios, they might not always correlate well with actual distributions, if such information were available. These assumptions have been made by the OECD and should not be interpreted as reflecting the views of the responsible government. [4] The amount of credit that can be claimed depends on whether taxpayers are also engaged in the extraction of minerals or hydrocarbons, and on the region in which they operate (e.g. the Great North). This measure is not compatible with flow-through shares.
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      SWITZERLAND: GENERAL METADATA Data documentation General notes The fiscal year in Switzerland coincides with the calendar year.
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      CHILE: GENERAL METADATA Data documentation General notes The Chilean tax system relies on the use of the UTM (Unidad Tributaria Mensual). The UTM is a unit of account used exclusively for tax purposes. Its exchange rate vis-à-vis the Chilean peso is adjusted monthly on the basis of the consumer price index, thereby keeping its real value more or less constant.
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      CHINA: GENERAL METADATA Data documentation General notes China’s publically available budget data lack the specificity of many OECD countries. Where available, figures provided as part of the official budget cycle typically group expenses at the highest level for overall categories, while estimates of the revenue foregone due to tax expenditures are rarely provided. Official announcements, especially those related to overall programme budgets, are often made via reports issued by official news agencies of the People’s Central Government (Xinhua, CCTV) or the Chinese Communist Party (People’s Daily). Media sources (Caixin, Caijing and other financial websites) also occasionally reveal budget support levels or estimates of tax expenditures. The sources are typically the Central Government or relevant ministries, firms themselves, or top company officials. News sources will also occasionally compare these statements with other official documents they were able to obtain in order to arrive at broader estimates. These documents are often featured on official government websites of the Central People’s Government or the Ministry of Finance (MOF). Sources are clearly stated in this database, including whether the amounts have been initially provided or subsequently cited by government websites or by official media sources. The same caveats apply to amounts listed as "government grants" (in English-language reports) or either "government support" or "subsidies" (in Chinese-language reports), notably in the annual reports that state energy firms provide to major stock markets (Shanghai; Hong-Kong, China; and New York) as part of their disclosure requirements for listed subsidiaries. Sometimes these numbers specify the source and use of funds, but they are rarely as specific as would be preferred in order to fully allocate the amounts of stated subsidies to the measures listed below or other relevant programmes. Estimates for budgetary support and tax expenditures are allocated to the various support categories and programmes to the best extent possible given available information. In view of the limited availability of the data, assumptions are sometimes necessary to assess the allocation and, in some cases, the amount of support. Those assumptions are clearly stated where applicable. Methodological note A large part of support to fossil fuels in non-OECD countries (and in a few member countries such as Mexico) takes the form of price controls or regulations benefitting final consumers. In many cases, this occurs through the government mandating state-owned oil and gas companies to charge lower retail prices, thereby lowering the revenues these companies collect through sales of fuel. This often results in the government subsequently intervening to compensate state-owned oil and gas companies for the losses they incurred in the downstream sector due to the regulated prices, with this compensation taking many forms. Some governments choose, for example, to compensate national oil and gas companies through targeted tax concessions (e.g., VAT exemptions) or equity injections. This inventory focusses on the direct budgetary transfers and tax expenditures that encourage the production or consumption of fossil fuels, including those benefitting national oil and gas companies. For this reason, some of the measures classified here under "Producer Support Estimate" may have been introduced by governments with a view to compensating domestic, vertically integrated oil and gas companies for the lower prices they are required to charge at the retail level, resulting in these measures being connected to some extent to consumer support. Estimates of the support directly conferred to final consumers by regulated prices are available from the International Energy Agency (IEA), which estimates these induced transfers as part of its annual World Energy Outlook publication. Readers are therefore advised not to add together the OECD and IEA estimates given the significant risk of overlap and double-counting this involves.
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      COLOMBIA: GENERAL METADATA Data documentation General notes Colombia’s fiscal year matches the calendar year.
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      CZECH REPUBLIC: GENERAL METADATA Data documentation General notes The fiscal year in the Czech Republic coincides with the calendar year. Consumer support estimates were provided directly by the Ministry of Environment, the Ministry of Finance, and the Ministry of Industry and Trade. Measures pertaining to the restructuring of the country’s coal-mining industry and associated environmental liabilities are taken from a study included in the Mineral Commodity Summaries of the Czech Republic (Czech Geological Survey - Geofond, 2010) that was published by the Ministry of Industry and Trade: "Eliminating negative consequences of mining in the Czech Republic" - main methods and financial resources" (Kaštovský and Platzek, 2010). Notes relating to the General Services Support Estimate Since 1991, the Czech Republic has not supported the production or consumption of coal. The state retains, however, an obligation to deal with the social, health, and environmental liabilities associated with past mining activity. The government transferred these obligations to two state-owned enterprises, DIAMO, s.p. and Palivový kombinát Ústí, s.p., which acquired the assets of the closed mining companies. These state-owned enterprises receive government subsidies for the activities they carry out. Since measures financed through these subsidy payments do not act to increase current production or consumption of coal, they are all allocated to the GSSE. Restructuring the coal-mining industry and remediating the negative environmental consequences of mining are conducted in several different ways and using several different financial resources (Kaštovský and Platzek, 2010). Besides the measures reported in this inventory, mining companies have since 1994 been required to set up two reserve funds: a financial reserve for remediation and reclamation of all plots of land affected by mining, and a financial reserve for alleviating material damage caused by mining (e.g. land subsidence).
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      GERMANY: GENERAL METADATA Data documentation The fiscal year in Germany coincides with the calendar year. Following OECD convention, amounts prior to 1999 are expressed as "euro-fixed series", in which the fixed EMU conversion rate (EUR 1 EUR = DEM 1.956) was applied to data initially expressed in the Deutsche Mark (DEM). In a few cases [1], the conversion into EUR was already made in official government documents. Germany being a federal country, the data also cover the states (Länder) that are still producing hard coal (North Rhine Westphalia, NW) and those that were producing hard coal until recently (Saarland, SR). Also included are payments for the rehabilitation of lignite-mining sites in eastern Germany (see DEU_dt_13) made by the Federal Government and the states of Saxony (SN), Brandenburg (BR), Saxony Anhalt (ST), and Thüringen (TH). Producer Support Estimate Hard-coal mining in Germany has traditionally attracted support for geological, historical, and political reasons. Since production of hard coal remains largely uneconomic, most mines are due to close by 2018 when government support to the industry is planned to be removed. Over the years, production of hard coal has been scaled back through numerous government initiatives. In the 1990s, the industry underwent various capacity-adjustment plans. Funding for these programmes was usually provided jointly by the coal-mining Land and the Federal Government, with the former accounting for about two-thirds of total payments. Hard-coal production has generally been supported through a combination of debt-relief schemes, mining-royalty concessions, reduced pension contributions for miners and provisions guaranteeing demand for the hard coal produced (see Combined Aids in North Rhine-Westphalia). In accordance with the EU’s state-aid rules, the Federal Government does not provide any more assistance to coal-mining under article 5-3 (current production aid). In preparation for the closure of mines, most of the support is now provided in the form of early-retirement funding for coal miners. Footnotes [1] This applies to the support measures for which the source is Landtag des Saarlandes (2005).
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      DENMARK: GENERAL METADATA Data documentation General notes Denmark’s fiscal year coincides with the calendar year. Producer Support Estimate Income derived from oil and natural-gas production is subject to various taxes and fees: the regular corporate income tax; the hydrocarbon tax (a specific tax on income derived from oil and gas production); royalties and compensatory payments; and profit sharing. Payments under the corporate tax are deductible from the hydrocarbon tax base. In addition, the oil pipeline tariff and compensatory fee can be offset against the hydrocarbon tax, but not against the corporate tax base. As of 2014, the corporate income tax amounts to 24.5%. However, in 2013 the Danish parliament passed two bills that will reduce the corporate income tax rate to 22% by 2016. Until January2014, the hydrocarbon tax regime differentiated between "old" licences granted before January2004 and "new" licences granted since 1 January 2004. For old licences, hydrocarbon income was subject to a 70% tax rate, but licensees were allowed to offset 25% of their capital expenditure (CAPEX) against their hydrocarbon tax bill over a period of ten years. For new licences, the hydrocarbon income tax was set at 52% and the allowance was granted for 5% of CAPEX over six years. From January2014 on, this differentiation is now abolished and old licences are treated under the same tax terms as new ones.
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      SPAIN: GENERAL METADATA Data documentation General notes The fiscal year in Spain coincides with the calendar year. Following OECD convention, amounts prior to 1999 appear as "euro-fixed series" where fixed EMU conversion rate (EUR 1EUR = ESP 166.386) were applied to data initially expressed in Spanish Peseta (ESP).
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      ESTONIA: GENERAL METADATA Data documentation General notes The fiscal year in Estonia coincides with the calendar year. Following OECD convention, amounts prior to 2011 are expressed as ‘euro-fixed series’, meaning that the fixed EMU conversion rate (EUR 1 = EEK 15.647) was applied to data initially expressed in the Estonian kroon (EEK).
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      FINLAND: GENERAL METADATA Data documentation General notes The fiscal year in Finland coincides with the calendar year. The Ministry of Finance reviewed the collected estimates and provided calculations of missing estimates where necessary.
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      FRANCE: GENERAL METADATA Data documentation General notes The fiscal year in France coincides with the calendar year. Following OECD convention, amounts prior to 1999 are expressed as ‘euro-fixed series’, meaning that this inventory applies the fixed EMU conversion rate (EUR1= FRF 6.559) to data initially expressed in the French Franc (FRF). Producer Support Estimate France used to support the production of hard coal through Charbonnages de France (CdF), a state-owned mining enterprise. Support was at the time deemed necessary owing to the low competitiveness of the French coal industry. By 1990, production had already ceased in the North of the country. An agreement between trade unions and CdF, the Pacte Charbonnier, was therefore concluded in October1994 to organise the progressive dismantling of the remaining production sites. The agreement provided for the end of all production by 2005. This was to be achieved through a series of measures meant to address the social costs associated with mine closures. One such measure, the congé charbonnier de fin de carrière, allowed coal miners to stop working at the age of 45 while remaining entitled to payments worth 80% of their previous wages. The last remaining mine was closed in 2004, ahead of schedule. CdF was liquidated in 2007 and its debt transferred to the French state, along with the responsibility for all inherited social and environmental liabilities. France does not produce coal any more.
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      UNITED KINGDOM: GENERAL METADATA Data documentation General notes The fiscal year in the United Kingdom runs from 1April to 31March. Following OECD convention, data are allocated to the starting calendar year so that data covering the period April 2016 to March 2017 are allocated to 2016. Producer Support Estimate Taxation of the oil and gas sector in the United Kingdom occurs through a variety of taxes. Notably, fields approved for development prior to 16March1993 were subject to the old Petroleum Revenue Tax (PRT) - a project-based tax levied on the profits from a given field - instituted in 1975. In the last several years the PRT rate was amended twice, being reduced from 50% to 35% in January 2015 and then being cut to nil in January 2016. . The PRT allowed for the full deduction of both operating and capital expenditures. It did not, however, allow the deduction of interest costs and other financing charges from taxable profits. Meanwhile, oil and gas corporations that have invested in approved fields after 16 March 1993 are also subject to a modified version of the regular corporation tax, namely the Ring-Fence Corporation Tax (RFCT). The imposition of a "ring fence" around upstream oil and gas activities means that these particular activities are to be treated separately for tax purposes from any other trade in which oil and gas companies may be engaged. This therefore allows upstream oil and gas activities to be taxed differently at the company-level. Differences in taxation include, for instance, the impossibility for companies to use losses in other activities as deductions against the income arising from oil and natural gas extraction. While all fields are subject to the RFCT, those that were approved for development prior to 16March1993 could deduct the amount of PRT taxes paid from their RFCT tax base. This ensured that the fields that were still subject to the old PRT regime were not taxed twice on the same profits. In addition, all types of fields are liable to the so-called Supplementary Charge (SC), which was introduced in the Finance Act of 2002. The SC is currently a 10% tax on profits from oil and natural gas production that is levied on top of the RFCT. The immediate write-off of both capital and exploration-and-development expenditures is normally considered under the systems in many countries to amount to a preferential tax treatment. The reason is that in calculating taxable profits in most income-tax systems, capital expenses are allocated over the period to which they contribute to earnings. Allowing the immediate writing-off of these types of expenditure therefore provides companies with something akin to a zero-interest loan from the government since it delays the collection of taxes. A present-value calculation would indeed show a positive transfer from the government to the companies benefiting from such provisions. However, when combined with impossibility for companies to deduct interest costs and other financing charges, the immediate write-off of both capital and exploration-and-development expenditures may not be considered a preferential tax treatment. Instead, this particular combination of tax provisions may approximate what is known as a "cash-flow" tax system. Cash-flow tax systems can be theoretically equivalent to the more common imputed-income tax systems where the objective is to levy a neutral business tax (Boadway and Bruce, 1984). For that reason, provisions such as the expensing of exploration and development costs may not be preferential tax provisions in the particular case of the United Kingdom.
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      GREECE: GENERAL METADATA Data documentation General notes The fiscal year in Greece coincides with the calendar year. Following OECD convention, amounts prior to 1999 are expressed as "euro-fixed series", so that this inventory applies the fixed EMU conversion rate (1EUR = GRD 340.750) to data initially expressed in Greek drachma (GRD).
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      HUNGARY: GENERAL METADATA Data documentation General notes The fiscal year in Hungary coincides with the calendar year.
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      INDONESIA: GENERAL METADATA Data documentation General notes Until 2010, the Indonesian fiscal year ran from 1April till 31March of the following year. Following OECD conventions, for the years prior to 2011, data are allocated to the starting calendar year so that data covering the period April2005 to March2006 are allocated to 2005. After 2010, the Indonesian fiscal year coincides with the calendar year. Most of the data were obtained from publications by the Global Subsidies Initiative, the Indonesian Ministry of Finance, the Ministry of Energy and Mineral Resources (MEMR), and SKK Migas (the energy regulator). Methodological note A large part of support to fossil fuels in non-OECD countries (and in a few member countries such as Mexico) takes the form of price controls or regulations benefitting final consumers. In many cases, this occurs through the government mandating state-owned oil and gas companies to charge lower retail prices, thereby lowering the revenues these companies collect through sales of fuel. This often results in the government subsequently intervening to compensate state-owned oil and gas companies for the losses they incurred in the downstream sector due to the regulated prices, with this compensation taking many forms. Some governments choose, for example, to compensate national oil and gas companies through targeted tax concessions (e.g., VAT exemptions) or equity injections. This inventory focusses on the direct budgetary transfers and tax expenditures that encourage the production or consumption of fossil fuels, including those benefitting national oil and gas companies. For this reason, some of the measures classified here under "Producer Support Estimate" may have been introduced by governments with a view to compensating domestic, vertically integrated oil and gas companies for the lower prices they are required to charge at the retail level, resulting in these measures being connected to some extent to consumer support. Estimates of the support directly conferred to final consumers by regulated prices are available from the International Energy Agency (IEA), which estimates these induced transfers as part of its annual "World Energy Outlook" publication. Readers are therefore advised not to add together the OECD and IEA estimates given the significant risk of overlap and double-counting this involves. Producer Support Estimate Since 1966, International Oil Companies (IOCs) seeking to explore and develop oil or natural-gas resources in Indonesia have to enter into Production Sharing Contracts (PSCs) with the MEMR. The terms and conditions of the PSC system have varied with each "generation" of PSCs that has been issued since. The first generation applied from 1965 to 1975, the second generation from 1976 to 1987, and the third from 1988 until now. The main characteristics of the PSC system have, however, remained the same, namely that the government and IOCs share the production of the oil and natural gas rather than the resulting profits, and that the effective income for each side amounts to a share of the "First Tranche Petroleum" and an equity share of the profit oil after cost recovery. Since 2001, Pertamina is required to enter into a Work Agreement (WA) with SKK Migas (previously BP Migas, the energy regulator) for each of its operations, the terms and conditions for which are more or less the same than that for the PSCs. PSCs currently in force in Indonesia usually provide for the state to receive 70% of the produced natural gas, with contractors being allocated the remaining 30%. In the case of coal-bed methane (CBM), however, PSCs signed since 2007 have often featured a lower government share (45%). Historically, the applicable income tax for companies operating in the upstream oil and natural-gas sector has been the prevailing income tax at the time that the PSC got signed, i.e. 25% as of 2013. The income tax applicable to the downstream sector normally also follows the prevailing tax law. However, as other industries in "high priority economic sectors", a number of downstream businesses can benefit from a number of income-tax concessions subject to approval by the Ministry of Finance. These businesses include: oil and natural-gas refineries, LNG and LPG producers, lubricant manufacturers, and the organic chemical industry using oil and natural gas as inputs. The list of income-tax concessions eligible taxpayers can receive includes additional net-income deductions (up to 30% of the amount invested), accelerated depreciation, the extension to ten years of the period for carrying losses forward, and a cap on withholding tax. Footnotes: [1] Instead of a royalty, the Indonesian government charges a so-called "First Tranche Petroleum". This requires that the first 20% of production be shared in favour of the government and before cost recovery according to the equity split set in the contract (Johnston, 1994). In more recent PSCs, the government has taken the entire FTP, although in this case the FTP has usually been lowered to 10% of the first production.
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      INDIA: GENERAL METADATA Data documentation General notes India is a federation comprising 35sub-national jurisdictions that possess a certain degree of freedom in setting prices for energy generation, transmission, and distribution. For this reason, there may be variations between central and regional authorities in the adoption and implementation of energy-related policies. The fiscal year in India runs from 1April to 31March of the following year. Following OECD convention, data are allocated to the starting calendar year, so that data covering the period April2005 to March2006 are allocated to 2005. Methodological note A large part of support to fossil fuels in non-OECD countries (and in a few member countries such as Mexico) takes the form of price controls or regulations benefitting final consumers. In many cases, this occurs through the government mandating state-owned oil and gas companies to charge lower retail prices, thereby lowering the revenues these companies collect through sales of fuel. This often results in the government subsequently intervening to compensate state-owned oil and gas companies for the losses they incurred in the downstream sector due to the regulated prices, with this compensation taking many forms. Some governments choose, for example, to compensate national oil and gas companies through targeted tax concessions (e.g., VAT exemptions) or equity injections. This inventory focusses on the direct budgetary transfers and tax expenditures that encourage the production or consumption of fossil fuels, including those benefitting national oil and gas companies. For this reason, some of the measures classified here under "Producer Support Estimate" may have been introduced by governments with a view to compensating domestic, vertically integrated oil and gas companies for the lower prices they are required to charge at the retail level, resulting in these measures being connected to some extent to consumer support. Estimates of the support directly conferred to final consumers by regulated prices are available from the International Energy Agency (IEA), which estimates these induced transfers as part of its annual "World Energy Outlook" publication. Readers are therefore advised not to add together the OECD and IEA estimates given the significant risk of overlap and double-counting this involves. Producer Support Estimate Upstream operators of oil and natural-gas exploration blocks in India are subject to a hybrid tax regime under production sharing contracts (PSCs), which comprises fixed and ad valorem royalty payments, production sharing, and the recovery of contract costs (exploration, development, and production costs). In December2012, the Central Government announced plans to reform the current PSC fiscal regime. Readers are advised that some fiscal measures related to oil and natural-gas production may not constitute tax expenditures under an alternative baseline where resource taxes (or production taxes) vary with market conditions and production costs. This inventory uses the annual amounts of tax expenditures as reported in India’s Union Budget. Footnotes [1] The Republic of India currently consists of 28 states and seven Union Territories.
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      IRELAND: GENERAL METADATA Data documentation General notes The fiscal year in Ireland coincides with the calendar year. Following OECD convention, amounts prior to 1999 are expressed as "euro-fixed series", meaning that we applied the fixed EMU conversion rate (EUR 1 = IEP 0.788) to data initially expressed in the Irish Pound (IEP).
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      ISRAEL: GENERAL METADATA Data documentation General notes Israel’s fiscal year coincides with the calendar year. Producer Support Estimate The oil and gas industry in Israel is regulated by a system of fees, royalty payments and tax deductions developed in the 1950s. The fiscal provisions that are unique to the oil and gas industry are the Oil Law (1952), Oil Regulations (1953), Income Tax Ordinance (1961) and some parts of the income tax legislation, especially the Deductions from the Income of Holders of Oil Rights (1956) and the Rules for Calculating Tax for the Holding and Sale of Participation Units in an Oil Exploration Partnership (1988). Israel started producing natural gas in 2004. As this is a relatively recent development, the issues of producer taxation and royalty payments are currently under review by the government (Knesset), the Ministry of Finance and participants representing the civil society. In April 2010, the Minister of Finance appointed a committee to examine the fiscal framework for the oil and gas resources in Israel, headed by Professor Eytan Sheshinski. The Sheshinski Committee submitted its final conclusions in January 2011. It recommended that the 12.5% rate of royalty payments should remain unchanged since increasing it could have a negative impact on the development of relatively less profitable gas fields. The depletion deduction, however, should be cancelled as it leads to a considerable reduction of the amount of taxable income which has no economic justification, the Committee concluded. The Committee also instituted a progressive oil and gas levy on profits. The initial rate of the levy is 20%, but it will not be collected before quotient of net cumulative revenues divided by the exploration and development expenses reaches or bypasses 1.5. When this quotient exceeds 2.3, the levy will gradually increase to 50%. Since production from the Tamar field began in 2013, it is projected that the government will only begin collecting revenue from the designated levy in 2018. In addition, as per income tax calculations, costs that accumulated during the lease stage of the oil-and-gas-asset development will be awarded accelerated depreciation at a rate of 10%. Investments made by the end of 2013 were given a maximum of amount of accelerated depreciation rate of 15%.
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      ITALY: GENERAL METADATA Data documentation General notes Following OECD convention, amounts prior to 1999 are expressed as "euro-fixed series", meaning that we applied the fixed EMU conversion rate (EUR 1 = ITL 1936.27) to data initially expressed in the Italian Lira (ITL). The fiscal year in Italy runs from 1July to 30June. Following OECD convention, data are allocated to the starting calendar year so that, for example, data covering the period July 2005 to June 2006 are allocated to 2005.
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      JAPAN: GENERAL METADATA Data documentation General notes The Japanese fiscal year runs from 1April through 31March of the following year. Following OECD convention, fiscal-year data are assigned to the closest calendar year; hence data covering the period April 2009 through March 2010 are reported as "2009" in the database.
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      KOREA: GENERAL METADATA Data documentation General notes The fiscal year in Korea coincides with the calendar year.
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      LUXEMBOURG: GENERAL METADATA Data documentation General notes The fiscal year in Luxembourg coincides with the calendar year. Following OECD convention, amounts prior to 1999 are expressed as "euro-fixed series", meaning that we apply the fixed EMU conversion rate (EUR 1 = LUF 40.339) to data initially expressed in the Luxembourg franc (LUF).
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      LATVIA GENERAL METADATA Data documentation General notes The fiscal year in Latvia coincides with the calendar year, except for excise tax relief mechanism of diesel used in agriculture transport where fiscal year is from July 1 till June 30. The Ministry of Finance of Latvia annually publish official tax-expenditure data on the website of the Ministry of Finance.
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      MEXICO: GENERAL METADATA Data documentation General notes The fiscal year in Mexico coincides with the calendar year. Producer Support Estimate Following the constitutional reform of the energy sector, the Mexican government signed a new fiscal regime for the oil and gas sector into law that will take effect on January 2015. The new regime is two-fold collecting a corporate income tax of 30% plus a set of taxes and fees varying depending on whether extraction and exploration is conducted as: (a) assignments (asignaciones) which are only granted to Pemex or a "state productive company" or (b) contracts signed with Pemex, either in association with private entities or with private entities entirely on their own. Under the assignment regime, state-owned companies pay three different types of federal fees: (i) a shared profit fee, (ii) a hydrocarbons extraction fee and (iii) a hydrocarbon exploration fee. The shared profit fee applies to the value of extracted hydrocarbons during the corresponding fiscal year (including consumption of these by the assignment holder, spillage and flaring) minus deductions. The fee will initially amount to 70% in FY2015 and will be lowered to 65% by FY2019. Next, the hydrocarbons extraction fee is determined in a similar way to the royalty payments charged under the contractual regime with fees varying on a sliding scale depending on the type of hydrocarbon extracted and the prevailing international price. Finally, the hydrocarbon exploration fee, also known as surface rental fee, will be charged on a monthly basis depending on the surface area being explored. The fee is aimed at incentivising companies to fulfil their exploration plans within a specified time frame. With respect to the contractual regime, there will be four different contract types: licence, production sharing, profit sharing and service contracts. Similar to taxes, fees and royalties will apply to different contract types, except in the case of service contracts where contracted companies do not receive any profits from the hydrocarbon extraction project: Licence contracts: contract signing bonus, royalties, exploration phase tax, and a compensation on the value of hydrocarbons Profit sharing and production sharing contracts: royalties, exploration phase tax and a compensation on net operation profit Royalty rates are determined on a sliding scale basis varying according to the type of field, its production level and the prevailing international price of oil and gas (similar to the hydrocarbon extraction fee under the assignment regime). Under this approach, royalties will go up if production or prices move above a certain threshold; the exact amount will only be published in the signed contract. Additionally, companies will also have to pay an exploration phase tax whose value is determined similar to the hydrocarbon exploration fee under the assignment regime. Profit sharing and product sharing contract will pay a compensation based on their net operational profits (the value of hydrocarbons extracted minus royalties and cost deductions) as defined in the signed contract. Licensors, on the other hand, will make payments based on the value of hydrocarbons they produce. In order to encourage oil and gas production, the new regime will provide a royalty discount for shale gas. Under this regime, coast deductions will usually be capped at USD 6.50 for each barrel of oil produced at 12.5% of oil revenues for onshore and shallow water assignments. Furthermore, a cap of 60% will be observed on oil revenues from deep water production and the Chicontepe field, currently operated by Pemex. There will also be a cost deduction cap of 80% for revenues in the production of gas. Compared with the previous fiscal regime, foreign firms were only allowed to operate under service contracts monopolized by Pemex and in addition pay a corporate income tax plus 10 additional taxes. Among the changes, the new system will be much simpler allowing profits to be shared with foreign oil and gas companies. Under this regime, the Mexican government estimates that Pemex can save 36% in tax and royalty payments annually, totalling to about MXP 90 billion. Furthermore, the government has proposed to assume one-third of Pemex’s social security contribution liabilities for its 15 000 employees, worth around USD 127 billion. However, before the government assumes this cost, the following conditions must be negotiated by Pemex with the Union of Petroleum workers: (i) raise the retirement age from 55 to 65 years; (ii) agree that the pension fund will be audited and; (iii) transfer the currently defined benefit plan to a defined contribution type on an individual basis.
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      NETHERLANDS: GENERAL METADATA Data documentation General notes The fiscal year in the Netherlands coincides with the calendar year. Tax-expenditure estimates for the years 2001-09 were provided by the Ministry of Finance. All other data estimates come from publicly available government sources as indicated below. Producer Support Estimate The taxes and fees that apply to exploration and production of oil and natural gas in the Netherlands are described in the 2003 Mining Act. Income from the production of hydrocarbons is subject to the standard statutory rate of corporate income tax (25%) and a State Profit Share (SPS) levy at a 50% rate, which is itself deductible for income-tax purposes. Royalties are also levied on the onshore extraction of oil and gas at rates that vary between 0% and 7% (or more when the price of imported crude oil exceeds EUR25 per barrel). Oil and gas companies operating upstream in the Netherlands have the ability to deduct an extra 10% of their costs from their taxable income, a provision known as the "cost uplift" or "capital uplift". Exploration expenditures, whether successful or not, can be written-off in full in the year in which they are incurred.
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      NORWAY: GENERAL METADATA Data documentation General notes The fiscal year in Norway coincides with the calendar year. Tax expenditures in Norway have been reported in the national budget (St. meld. nr.1 (Nasjonalbudsjettet)) since 1999. Since FY2010-2011, estimates of the tax expenditures listed below can be found in the following table in the budgetary reports: "Tax expenditures and sanctions[1] by sector" (Skatteutgifter og -sanksjoner for næringslivet). Producer Support Estimate The taxation of upstream activities on the Norwegian Continental Shelf is directed by the Petroleum Tax Act of 1975; where there are no specific rules given in the PTA, the General Tax Act (GTA) applies. For taxation purposes, income is calculated on the basis of a norm price set by the petroleum price board, giving rise to a difference in revenue figures for taxation and accounting purposes, Income derived from oil and gas production is subject to a special resource tax of 53%, in addition to the ordinary corporate income tax of 25% (in total a marginal tax rate of 78%). A range of expenses are allowable against both the special resource tax and the ordinary corporate income tax; most notably exploration costs are deductible, and a company may claim an annual refund of the tax value of direct and indirect exploration expenses (excluding financial expenses) for each tax year loss. Alternatively, these losses can be carried forward. In practice, this means reimbursement by the government of up to the full value of all the direct and indirect exploration expenses. In this respect, the government shares symmetrically in both profits and losses from exploration and production of petroleum products. Where taxable income is subject to a marginal rate of 78%, investments in offshore production facilities, pipelines and installations are depreciated over 6 years at a rate of 16.66% per annum. Additional allowances are permitted at a rate of 22% (5.5% each year over a four year period) when calculating the special tax basis for the 53% tax rate, such that 89.66% of offshore investments are nominally borne by the government.[2] Other capital investments are depreciated on a declining balance basis at rates between 0 and 30% per annum; for example, exploration rigs are depreciated on a declining balance basis at a maximum rate of 14% per annum. In addition to the regular corporate income tax and special resource tax, petroleum producers must also pay taxes on emissions of carbon dioxide and nitrogen oxide. As of 1 Jan 2016, the CO2 tax is charged at a rate of NOK 1.02 per standard cubic meter on gas consumed or flared on offshore production installations and at a rate of NOK 0.84 per m3 for natural gas and NOK 1.26 per litre for LPG imported from offshore production facilities or withdrawal from a warehouse. The tax on NOx emissions was NOK 21.17 per kilogram in 2016; however rather than pay this fee companies can choose to pay a fee into a fund (tax deductible at a rate of 78%) and commit to emissions reductions targets. Footnotes: [1] Tax expenditures (tax sanctions) are defined as exceptions from the general rules in the tax system that are applied to certain groups or certain activities and imply lower (higher) government tax revenue. Norway uses revenue forgone method for calculating tax expenditures. There are different benchmarks for calculating tax expenditures related to excise duties and environmental taxes. Excise duties are treated individually which means that each excise tax expenditure calculation relies on a different benchmark. [2] Expenditure incurred prior to May 2013 are subject to an annual uplift of 7.5% (30% in total over four years)
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      NEW ZEALAND: GENERAL METADATA Data documentation General notes The fiscal year in New Zealand runs from 1July to 30June. Following OECD convention, data are allocated to the starting calendar year so that data covering the period July 2005 to June 2006 are allocated to 2005. Producer Support Estimate New Zealand’s fiscal regime applicable to the oil and natural-gas industry combines a corporate income tax and royalty-based taxation. The corporate income tax amounts to 28% of taxable income, where taxable income is defined as any assessable income less deductions and net losses, the latter of which can be carried forward indefinitely. Generally, companies cannot deduct expenditures of a capital nature when incurred. However, deductions for certain exploration and development expenditures of a capital nature are available for oil and natural-gas companies (see Tax Deductions for Petroleum-Mining Expenditures). Depending on the year of the discovery, different royalty regimes apply. For discoveries made on or after 1995, royalties are set out in detail in the 2005 Minerals Programme for Petroleum and comprise of the following: an ad valorem royalty (AVR) component of 5% payable on the basis of either a sales price received or, where there has been no sale or no arm’s length sale, the deemed sales price; and an accounting profits royalty (APR) component of 20% payable on the difference between revenue received from the sale of products and the costs of extracting, processing and selling those products up to the point of sale. In case of an exploration permit, the permit holder is liable to pay only the AVR. For all mining permits with net sales above NZD1 million, the permit holder is required to calculate for each period for which a royalty return must be provided to both the AVR and the APR, and pay whichever is higher. Typically, AVR is paid in the early years of production as prior costs are netted against revenue and at the end of the field’s life, as production falls. APR is typically paid during the peak years of production of non-marginal fields. In order to encourage exploration for new natural-gas reserves, the government reduced royalty rates from June 2004 through 31December 2009 (see Reduction in Royalty Payments for Petroleum). For discoveries after 31 December 2009, the same royalty rates that are in operation before 30 June 2004 are applicable. More generally, royalties are payable for petroleum that is (1) discovered and sold, (2) used in the production process as fuel, (3) exchanged or transferred out of permit boundaries without sale or (3) left unsold at the expiry of the permit (Ernst and Young, 2013). No royalties are payable on petroleum that is flared or returned to natural reservoirs within the permit boundaries (e.g. the re-injection of gas). In 2008, the government introduced an emissions trading scheme (ETS) for greenhouse gases. Legislation for the scheme has been subsequently amended with the latest enacted in 2012. There are no special exceptions for the oil and gas sector under the current ETS regime.
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      POLAND: GENERAL METADATA Data documentation General notes The fiscal year in Poland normally coincides with the calendar year. Corporations, however, may choose a different starting point of the fiscal year. Producer Support Estimate Most of Polish state aid to the energy sector is apportioned to the coal industry. Poland’s heavy reliance on coal stems from both a large domestic endowment of this fuel and the fact that it used to have a limited access to foreign-exchange earnings with which it could have imported other fuels during the communist period. Because coal-mining was considered a strategic sector, the state subsidised the production of coal, providing various social benefits to coal miners and regulating coal prices to keep them low. With the economic transition of the early 1990s, the state envisioned to transform coal mines into self-reliant commercial companies that would adapt to the conditions of a free-market economy. The continued policy of price controls, however, meant that the industry had a very limited potential for economic growth and hence, needed further state assistance. All subsequent plans for restructuring the coal sector throughout the 1990s supported capacity adjustment, shutting down unprofitable mines and reducing employment to levels that would improve productivity. The overarching objective of those programmes was thus to make the coal-mining sector profitable. These programmes proved ineffective due to the lack of consensus between the government and the trade unions. This changed in 1998 as the new government, supported by Solidarno?? (the biggest Polish trade union), devised a coal-mining restructuring plan, the Reforma górnictwa w?gla kamiennego w Polsce w latach 1998 - 2002. The plan provided additional funding for social schemes and expressed a commitment to write-off the debt which the mines have accumulated over the years. Another plan adopted in 2003 - the Program restrukturyzacji górnictwa w?gla kamiennego w Polsce w latach 2003-2006 - pursued similar objectives. When Poland joined the European Union in 2004, state aid became subject to the Community rules. In practice, this development meant that coal-mining restructuring plans would have to be compatible with the common market, and that the European Commission would need to approve any state-aid scheme before it reached recipients. The Council of Ministers has so far adopted two documents regarding the restructuring of the sector: the Restrukturyzacja górnictwa w?gla kamiennego w latach 2004-2006 oraz strategia na lata 2007-2010, which was then replaced by Strategia dzia?alno?ci górnictwa w?gla kamiennego w Polsce w latach. Poland does not provide subsidies to coal-mining under article 5-3 (current production aid). All current subsidies therefore result from article 7 (aid to cover exceptional costs) and are associated either with mine decommissioning or investment aid to operating mines (for up to 30% of the total investments made). The former measures are mainly allocated to the GSSE as most of them do not increase current production or consumption of coal. The latter are allocated to the PSE since they directly support coal producers. The coal-mining sector underwent major restructuring through a series of management mergers and mine closures. At the beginning of the transition, the industry comprised of 71 independent mines. In 1993, the management of hard-coal production was taken over by seven joint-stock holding companies that held the assets of 60 mines. Four mines remained stand-alone enterprises, while the rest was shut down on unprofitability grounds. The Polish coal-mining sector now comprises 31 mines grouped into seven joint-stock holding companies and is dominated by three state-owned firms: Europe’s largest hard-coal company, Kompania W?glowa S.A. (KW), Katowicki Holding W?glowy S.A. (KHW) and Jastrz?bska Spó?ka W?glowa S.A. In 2000, two state-owned liquidation companies, Spó?ka Restrukturyzacji Kopal? S.A. (SRK) and Bytomska Spó?ka Restrukturyzacji Kopal? Sp. z o.o. (BSRK), were given responsibility to manage mine decommissioning. Since 2006, only two companies in Poland have been benefitting from state aid: KW and KHW. Aid is also being envisaged for the SRK (BSRK was consolidated into SRK in 2009).
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      PORTUGAL: GENERAL METADATA Data documentation General notes Portugal’s fiscal year coincides with the calendar year. Following OECD convention, amounts prior to 1999 are expressed as "euro-fixed series," meaning that the fixed EMU conversion rate (EUR 1 = PRT 200.482) is applied to data initially expressed in Portuguese Escudos (PRT).
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      RUSSIAN FEDERATION: GENERAL METADATA Data documentation General notes Although Russia is a federation comprising 83sub-national jurisdictions [1], a cursory review of regional policies suggests that the overall value of sub-national support for fossil fuels is much less significant than that of federal support. This is partly because Russia possesses a highly centralised budgetary and fiscal system, which acts to limit the amounts of support that can be provided by the country’s provinces, republics, districts, and territories. While there exists a few regional spending programmes that provide targeted support to the local oil and natural-gas industry (e.g., support for exploration and research activities or expenditure in relation to environmental liabilities), beneficiaries tend to be small- or medium-sized companies receiving small amounts of support. Regional government ownership of upstream oil and gas enterprises is very limited. More common is the ownership of electric-power utilities by these governments. However, even though this ownership results in considerable decision-making power over the purchase of natural gas as fuel for electricity generation, transactions are generally market-driven while natural-gas prices remain regulated at the federal level (see the country overview). The measures listed in this inventory are therefore predominantly federal in nature despite the fact that Russia is formed of a large number of sub-national jurisdictions. The fiscal year in Russia coincides with the calendar year. Methodological note A large part of support to fossil fuels in non-OECD countries takes the form of price controls or regulations benefitting final consumers. In many cases, this occurs through the government mandating state-owned oil and gas companies to charge lower retail prices, which lowers the revenues these companies collect through their sales of fuel. This sometimes results in the government subsequently intervening to compensate state-owned oil and gas companies for the losses they incurred in the downstream sector due to the regulated prices, with this compensation taking many forms. Some governments choose, for example, to compensate national oil and gas companies through targeted tax concessions (e.g., VAT exemptions) or equity injections. This inventory focusses on the direct budgetary transfers and tax expenditures that encourage the production or consumption of fossil fuels, including those benefitting national oil and gas companies. For this reason, some of the measures classified here under "Producer Support Estimate" may have been introduced by governments with a view to compensating domestic, vertically integrated oil and gas companies for the lower prices they are required to charge at the retail level, resulting in these measures being connected to some extent to consumer support. Estimates of the support directly conferred to final consumers by regulated prices are available from the International Energy Agency (IEA), which estimates these induced transfers as part of its annual World Energy Outlook publication. Readers are therefore advised not to add together the OECD and IEA estimates given the significant risk of overlap and double-counting this involves. Producer Support Estimate Readers are advised that some fiscal measures related to oil and natural-gas production may not constitute tax expenditures under an alternative baseline where resource taxes (or production taxes) vary with market conditions and production costs. This inventory uses the annual amounts of tax expenditures as reported by the Ministry of Finance of the Russian Federation or other government agencies. Footnotes: [1] The Russian federation currently consists of 46 oblasts (provinces), 21 republics, 9 krais (territories), 4 autonomous okrugs (districts), 2 federal cities (Moscow and Saint Petersburg), and one autonomous oblast, for a total of 83 sub-national jurisdictions.
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      SLOVAK REPUBLIC: GENERAL METADATA Data documentation General notes The fiscal year in the Slovak Republic coincides with the calendar year. Data prior to 2009 were converted to "euro-fixed series" by the Ministry of Finance (unless otherwise specified).
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      SLOVENIA: GENERAL METADATA Data documentation General notes The fiscal year in Slovenia coincides with the calendar year. The conversion into EUR for the estimates in the period prior to 2007 was made by the Ministry of Finance, which kindly provided all estimates and fuel allocations.
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      SWEDEN: GENERAL METADATA Data documentation General notes The fiscal year in Sweden coincides with the calendar year. Producer Support Estimate No producer support estimates were identified.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      TURKEY: GENERAL METADATA Data documentation General notes The fiscal year in Turkey coincides with the calendar year.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      UNITED STATES: GENERAL METADATA Data documentation General notes The fiscal year in the United States runs from 1October to 30September. Following OECD convention, data are allocated to the ending calendar year so that data covering the period October2005 to September2006 are allocated to 2006. States can, however, have a different fiscal year. Since the United States is a federal country, data collection was also conducted for a sample comprising the following states: Alaska (AK), California (CA), Colorado (CO), Kentucky (KY), Louisiana (LA), North Dakota (ND), Oklahoma (OK), Pennsylvania (PA), Texas (TX), West Virginia (WV), and Wyoming (WY).
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      SOUTH AFRICA: GENERAL METADATA Data documentation General notes The fiscal year in South Africa runs from 1April to 31March of the following year. Following OECD conventions, data are allocated to the starting calendar year so that data covering the period April2005 to March2006 are allocated to 2005. The initial data were obtained from the National Treasury and the National Budgets (not the Provincial Budgets). For several estimates, data are taken from annual reports of companies such as Eskom, from other government organisations such as the South Africa Revenue Service SARS), and from other organisations working in the field. Methodological note A large part of support to fossil fuels in non-OECD countries (and in a few member countries such as Mexico) takes the form of price controls or regulations benefitting final consumers. In many cases, this occurs through the government mandating state-owned oil and gas companies to charge lower retail prices, thereby lowering the revenues these companies collect through sales of fuel. This often results in the government subsequently intervening to compensate state-owned oil and gas companies for the losses they incurred in the downstream sector due to the regulated prices, with this compensation taking many forms. Some governments choose, for example, to compensate national oil and gas companies through targeted tax concessions (e.g., VAT exemptions) or equity injections. This inventory focusses on the direct budgetary transfers and tax expenditures that encourage the production or consumption of fossil fuels, including those benefitting national oil and gas companies. Estimates of the support directly conferred to final consumers by regulated prices are available from the International Energy Agency (IEA), which estimates these induced transfers as part of its annual "World Energy Outlook" publication. Readers are therefore advised not to add together the OECD and IEA estimates given the significant risk of overlap and double-counting this involves. Producer Support Estimate The fiscal regime applicable to oil, natural-gas, and mining companies in South Africa consists mostly of a corporate income tax, indirect taxes, and royalties. Additionally, oil, natural-gas, and coal-mining companies pay the indirect taxes paid by other sectors, including the regular VAT and the customs duties and import tariffs that are levied on purchased inputs. Resident and non-resident companies are liable for corporation tax at a rate of 28 %. In addition, the government levies various withholding taxes including: on royalties paid to non-residents (at a rate of 15%), on interest payable to non-residents (at a rate of 15%), on dividends (at a rate of 15%), and on the disposal of immovable property (at a rate of 7.5% for a company). Finally, capital gains tax is payable at a rate of 18.65%, with an expected increase to 22.4% for the 2017 fiscal year. The tenth schedule to the Income Tax Act of 1962 sets out specific provisions relating to the taxation of upstream oil and gas exploration and production. These measures include deductions for all expenditures and losses related to exploration and post exploration losses, as well as 100% of capital spend on exploration activities and 50% on post-exploration activities. Furthermore, dividends paid out of income relating to oil and gas activities are not liable to the 15% withholding tax described above. Prior to 2010, South Africa’s oil, natural-gas, and mining companies did not have to pay royalties. The Mineral and Petroleum Resources Royalty Act (MPRRA) of 2008 imposed royalties related to extractive activities, with the rate calculated as a function of gross sales and profit (specifically, earnings before interest and tax), and varying between 0.5% and 5% (for refined resources) and between 0.5% and 7% for non-refined resources). Exemptions apply for certain small producers, but these are also applicable to operators extracting non-energy minerals. Given the size of South Africa’s total mining sector, royalty concessions such as these lack the specificity required to be characterised as support measures for the purpose of the present inventory.
    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 мая, 2019
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      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 countries, this is not the case for road injuries. 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.
    • Март 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 24 марта, 2019
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      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.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 03 декабря, 2018
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      Austria: Long-term annual average 1961-90 Belgium: Data exclude underground flows and include estimates Canada: Long-term annual average 1971-2004 Chile: Long-term annual average 2000-2014 Colombia: Long-term annual average 1974-2012 Czech Republic: The long-term annual average refers to the latest 20 years Denmark: Long-term annual average 1995-2015 Estonia: Long-term annual average refers to the latest 30 years and includes only data about fresh surface water France: Long-term annual average : 1981-2010. Inflow and outflow: outflow is computed using the throughput of rivers having their source in France but the mouth outside France; measures are taken at the French border using the daily throughputs. Precipitation and real evapotranspiration data are derived from a gridded atmospheric model (grid point of 8 by 8 km2) applied to the territory of metropolitan France. Germany: Long-term annual average 1995-2015 Hungary: Long-term annual average 1971-2000 Ireland: Long-term annual average 1981-2010. Groundwater figures are not available and therefore are not included. Israel: Long-term annual average 2000-2013 Italy: Long-term annual average 1971-2000 Japan: Long-term annual average 1971-2006 Korea: Long-term annual average 1974-2003 Latvia: Long-term annual average 2005-2013 Lithuania: Long-term annual average 2000-2014 Mexico: The long-term annual average covers 30 years Netherlands: Long-term annual average 1981-2010 New Zealand: Long-term annual average 1995-2014 Norway: The data for precipitation and evotranspiration refer to the period LTAA (long-term annual average) 1961-90 whereas the others to the period LTAA 1981-2010, that is why precipitation minus evotranspiration is different from internal resources. Poland: Long-term annual average 1951-2014. Estimates on the base of mean annual flow. For more information, see: http://www.kzgw.gov.pl/ , http://www.pgi.gov.pl/ , http://www.psh.gov.pl/ , http://www.imgw.pl/ Slovak Republic: Long-term annual average is 1961-1990 for internal resources, 1961-2000 for external inflow Slovenia: Long-term annual average is 1971-2000 Sweden: Long-term annual average : 1990-2009. The difference between precipitation and evapotranspiration refers to storage Switzerland: Long-term annual average : 1981-2010 Turkey: Long-term annual average: data for internal flow refers to the period 1980-2011 Costa Rica: The long-term annual average refers to 1990-2014 Russia: The long-term annual average refers to 1936-1980
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июля, 2019
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      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.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июня, 2019
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      This dataset contains incidences and gender composition of part-time employment with standardised age groups (15-24, 25-54, 55-64, 65+, total). 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.
    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 03 мая, 2019
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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.
    • Март 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 21 мая, 2018
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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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 29 апреля, 2019
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      The Future of Business Survey is an original source of information on small and medium-sized enterprises (SMEs). Launched in February 2016, the survey is a partnership between Facebook, OECD, and the World Bank. It provides timely information on business owners’ assessment of the current state and future outlook of their business, job creation perspectives, main business challenges and participation in international trade. Several data breakdowns are available, in particular by size of the enterprise, age, sector, trading status and gender of owners or managers.
  • G
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
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      Consumer price indices (CPIs) measure inflation as price changes of a representative basket of goods and services typically purchased by households. The G20 CPI aggregate reflects national CPIs for all G20 countries that are not part of the European Union (EU) while it reflects the Harmonised Indices of Consumer Prices (HICP) for the EU, its Member States and for Turkey.   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).
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      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 empowerment and understand gender gaps in other key areas of development.Covering 180 countries and territories, the GID-DB contains comprehensive information on legal, cultural and traditional practices that discriminate against women and girls.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 17 июня, 2019
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      General government debt-to-GDP ratio is the amount of a country's total gross government debt as a percentage of its GDP. It is an indicator of an economy's health and a key factor for the sustainability of government finance. "Debt" is commonly defined as a specific subset of liabilities identified according to the types of financial instruments included or excluded. Debt is thus obtained as the sum of the following liability categories (as applicable): currency and deposits; securities other than shares, except financial derivatives; loans; insurance technical reserves; and other accounts payable. Changes in government debt over time reflect the impact of government deficits. This indicator is measured as a percentage of GDP. All OECD countries compile their data according to the 2008 System of National Accounts (SNA).
    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 февраля, 2019
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      This part contains general information on number of insurance companies and employees within the sector.
    • Февраль 2017
      Источник: Organisation for Economic Co-operation and Development
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      Дата обращения к источнику: 17 ноября, 2017
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      Netherlands) Non-point sources include diffuse emissions from: a) road, rail and water transport, b) corrosion processes, c) run-off and drainage from agricultural soils, d) atmospheric deposition (excluding deposition on marine waters), e) urban run-off to sewers systems. Direct discharges from non-point sources: sum of direct discharges from diffuse sources and transfers like drainage and run-off from soils and direct atmospheric deposition at fresh surface waters (only N, Cu and Zn). Total discharges to the sea include atmospheric deposition at marine surface water. In most cases atmospheric deposition is the larger part of the total load to marine waters Sweden) Industrial wastewater, total discharged only includes industrial wastewater treatment plants with a permit in the national register for environmental reports and industries with own treatment and release to water. Excluded are industrial wastewater treatment plants that transfer water to urban wastewater treatment plants
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 19 марта, 2019
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      This dataset shows data provided by Member countries' authorities through the questionnaire on the state of the environment (OECD/Eurostat), and to Eurostat through the Waste Statistics Regulation. They were updated or revised on the basis of data from other national and international sources available to the OECD Secretariat, and on the basis of comments received from national Delegates. Selected updates were also done in the context of the OECD Environmental Performance Reviews. The data are harmonised through the work of the OECD Working Party on Environmental Information (WPEI) and benefit from continued data quality efforts in OECD member countries, the OECD itself and other international organisations. In many countries systematic collection of environmental data has a short history; sources are typically spread across a range of agencies and levels of government, and information is often collected for other purposes. When interpreting these data, one should keep in mind that definitions and measurement methods vary among countries, and that inter-country comparisons require careful interpretation. One should also note that data presented here refer to national level and may conceal major subnational differences.
    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 27 февраля, 2019
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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.
    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 февраля, 2019
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    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 марта, 2019
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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.
    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 27 февраля, 2019
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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.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 03 декабря, 2018
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      Geolocation of urban agglomerations in West Africa.
    • Январь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 08 апреля, 2019
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      This data set contains information of The insurance industry is a major 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 by covering personal and business risks. This annual report monitors global insurance market trends to support a better understanding of the insurance industry's overall performance and health.The OECD has collected and analysed data on insurance such as the number of insurance companies and employees, insurance premiums and investments by insurance companies dating back to the early 1980s. Over time, the framework of this exercise has expanded and now includes key balance sheet and income statement items for the direct insurance and reinsurance sector.
    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 июня, 2019
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      Pension assets continued to rise in 2017, exceeding USD 40 trillion in the OECD area for the first time ever, with almost all countries showing positive investment results. This can be attributed to the strong investment performance of pension assets that benefitted from buoyant stock markets
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Going for Growth helps to promote sustainable economic growth and improve the well-being of OECD citizens. The surveillance is based on a systematic and in-depth analysis of structural policies and their outcomes across OECD members, relying on a set of internationally comparable and regularly updated policy indicators with a well-established link to performance. From one issue to the next, Going for Growth follows up on these recommendations and priorities evolve, not least as a result of governments taking action, http://www.oecd.org/eco/going-for-growth/. This dataset contains time series of a comprehensive set of quantitative indicators that allow for a comparison of policy settings across OECD countries and selected non-member economies: Argentina, Brazil, China, Colombia, Costa Rica, India, Indonesia, Lithuania, the Russian Federation and South Africa. The dataset covers several areas: Product market regulation (economy-wide and sector-specific regulation), Education, Public investment and subsidies, Taxation, Labour market, Transfers. Data are consistent with those published in the Structural Policy Indicators chapter of Going for Growth 2018. The cut-off date is December 2017.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 29 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 22 марта, 2019
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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.
    • Июнь 2016
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 04 июля, 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 marine landings, aquaculture production, fleet, employment, and government financial transfers (GFT).
    • Февраль 2016
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 18 марта, 2016
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      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).
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      This dataset contains the number of people who graduated from an education programme by field and sex.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 02 июля, 2019
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      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).
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Graduation/entry rates represent an estimated percentage of an age group expected to graduate/enter a certain level of education at least once in their lifetime.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 27 марта, 2019
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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.
    • Сентябрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 сентября, 2018
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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), sulphur hexafluoride (SF6) and nitrogen trifluoride (NF3). Data exclude indirect CO2.   Intensities (per unit of GDP and per capita) as well as index are calculated on gross direct emissions excluding emissions or removals from land-use, land-use change and forestry (LULUCF).   The GDP used to calculate intensities is expressed in USD at 2010 prices and PPPs.
    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 февраля, 2019
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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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 29 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июля, 2019
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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 (2010 prices and PPPs).
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 05 июля, 2019
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      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2010 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics. 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).
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 февраля, 2019
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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. 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.
    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 февраля, 2019
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      Productivity is a key driver of economic growth and changes in living standards. Labour productivity growth implies a higher level of output for unit of labour input (hours worked or persons employed). 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). Productivity is also a key driver of international competitiveness, e.g. as measured by Unit Labour Costs (ULC).   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 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 later than source data for labour productivity and ULCs.   Note to users: The OECD Productivity Database accounts for the methodological changes in national accounts' statistics, such as the implementation of the System of National Accounts 2008 (2008 SNA) and the implementation of the international industrial classification ISIC Rev.4. These changes had an impact on output, labour and capital measurement. For Chile, China, Colombia, India, Japan, Turkey and the Russian Federation the indicators are in line with the System of National Accounts 1993 (1993 SNA); for all other countries, the indicators presented are based on the 2008 SNA
  • H
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 03 июля, 2019
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    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 03 июля, 2019
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    • Ноябрь 2017
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 ноября, 2017
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      Cancer follow up has been given for the range of 5 years. The highest range has been considered as for this period, for example 1995-2000 is considered as 2000.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      OECD Health Data 2016 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.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      OECD Health Data 2017 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
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 09 июля, 2019
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      OECD Health Data 2017 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.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      OECD Health Data 2015 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 healthcare systems.
    • Июнь 2010
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
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      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.
    • Ноябрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 09 января, 2019
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      Classification(s) used: ICHA-HC: Classification of health care functions ICHA-HP: Classification of health care providers ICHA-HF: Classification of health care financing schemes
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      OECD Health Data 2016 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.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      This dataset presents annual population data from 1950 to 2050 by sex and five year age groups as well as age-dependency ratios. The data is available for 46 countries. Data from 1950 to 2011 (2012) are historical data while data from 2012 (2013) are projections. In order to estimate the population in coming years, fertility rate, life expectancy and level of immigration have to be estimated. Assumptions underlying the estimations of each of these three elements are usually categorise as low, medium or high within one specific country. Where a range of projections are available, the projection data presented here are based on the "medium variant". Assumptions underlying the projection data shown are described country per country in the metadata table as well as the source of data. There are three sources for the data: national statistical institutes, Eurostat or the United Nations. The population data is presented in 18 five year age groups which refer to the population from 0-4 to 85 and more. The following age groups are also available: less than 15, less than 20, 15 to 64, 20-64, 65 and over. Age-dependency ratios are also presented. Assumptions by country. Data are presented for 46 countries. The 34 OECD member countries, the 6 EU countries not belonging to the OECD, and Brazil, Colombia, India, Indonesia, China, Russia and South Africa.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 22 июня, 2019
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      Unit of measure usedIndex: Year 2015 = 100 The Hourly Earnings (MEI) dataset contains predominantly monthly statistics, and associated statistical methodological information, for the 35 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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      This indicator shows the working hours needed to escape poverty for a jobless family claiming Guaranteed Minimum Income benefits.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 21 июня, 2019
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      The elaboration of a more precise nomenclature of households' financial assets and liabilities and the collection of more detailed information constitute an attempt to better identify and analyse households' wealth in OECD countries. The objective of the sub-classification of assets and liabilities is to identify the relative importance of the various types of assets, classified according to the increasing risk
    • Июль 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 19 сентября, 2014
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      Human Resource Costs
  • I
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 15 апреля, 2019
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    • Август 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 22 августа, 2018
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      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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      The ICT Access and Usage by Businesses database provides a selection of 51 indicators, based on the 2nd revision of the OECD Model Survey on ICT Access and Usage by Businesses. The selected indicators originate from two sources: 1. An OECD data collection on the following OECD and accession countries or key partners: Australia, Brazil, Canada, Colombia, Japan, Korea, Mexico, New Zealand, Switzerland and the United States. Data collection methodology followed by these countries is available in each respective country metadata file.2. Eurostat Statistics on Businesses for the OECD countries that are part of the European Statistical system. For those countries, indicators shown in this database refer to the original indicator as published by EUROSTAT -see the correspondence table-. Please refer to Eurostat methodology to access the methodological information.For all countries, breakdowns used correspond to those of EUROSTAT, unless otherwise stated in the metadata.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      The ICT Access and Usage by Households and Individuals database provides a selection of 92 indicators, based on the of 2nd revision of the OECD Model Survey on ICT Access and Usage by Households and Individuals.The selected indicators originate from two sources:1. An OECD data collection on the following OECD and accession countries or key partners: Australia, Brazil, Canada, Costa Rica, Chile, Colombia, Israel, Japan, Korea, Mexico, New Zealand, Switzerland, and the United States. Data collection methodology followed by these countries is available in each respective country metadata file.2. Eurostat Statistics on Households and Individuals for the OECD countries that are part of the European Statistical system. For those countries, indicators shown in this database refer to the original indicator as published by EUROSTAT -see the correspondence table-. Please refer to Eurostat methodology to access the methodological information.For all countries, breakdowns used correspond to those of EUROSTAT, unless otherwise stated in the metadata.
    • Январь 2008
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 22 сентября, 2014
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      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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      NOTE FOR THIS DATA CUBEFor all indicators provided in this cube, value are expressed as percentage of Internet users.For each country (except for Costa Rica -see below-), the value of the indicators provided in this cube are based on data from the ICT Access and Usage by Households and Individuals database, and metadata and sources are strictly identical.Internet users generally relate to a recall period of 3 months or 12 months as indicated below. For exceptions, see the country metadata in the ICT Access and Usage by Households and Individuals database.For Australia, 12 months before 2014, 3 months from 2014 onwards.For Canada, Colombia and Japan, 12 months.For Israel, Costa Rica and the United States, 3 months.For New Zealand, 12 months in 2006.For Chile, Korea, Mexico, New Zeland (2006 excepted), Switzerland and Brazil: 1. For indicators starting with D1, I3 and I9, Internet users relate to a recall period of 3 months; 2. For indicators starting with F1, Internet users relate to a recall period of 3 months untill 2007 and of 12 months from 2008 onwards; 3. For the remaining indicators, Internet users relate to a recall period of 12 months.For Costa Rica, data are OECD estimates based on data provided by the National Institute of Statistics and Censuses and by the Ministry of Science, Technology and Telecommunications (MICITT), and for all the indicators, Internet users relate to a recall period of 3 months.For the remaining countries (all from Eurostat): 1. For indicators starting with D1, Internet users relate to a recall period of 3 months; 2. For indicators starting with F1, Internet users relate to a recall period of 3 months untill 2007 and of 12 months from 2008 onwards; 3. For the remaining indicators, Internet users relate to a recall period of 12 months.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 03 декабря, 2018
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      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.
    • Март 2016
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 08 ноября, 2017
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      The sources for this database are mainly census data, from the 2000 round of censuses. Census data were used for 22 countries. Countries not taking periodic censuses but keeping population registers have provided data extracted from these registers; this is the case for four countries: Denmark, Finland, Norway and Sweden. For some countries, not all themes covered in the database are present in the national census or register. Labour force surveys, provided by Eurostat and averaged over the period 1998-2002, have been used to fill the gaps where possible.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 03 декабря, 2018
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      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 03 декабря, 2018
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      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older with a tertiary education.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 03 декабря, 2018
      Выбрать
      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.
    • Март 2016
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 08 ноября, 2017
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      The sources for this database are mainly census data, from the 2000 round of censuses. Census data were used for 22 countries. Countries not taking periodic censuses but keeping population registers have provided data extracted from these registers; this is the case for four countries: Denmark, Finland, Norway and Sweden. For some countries, not all themes covered in the database are present in the national census or register. Labour force surveys, provided by Eurostat and averaged over the period 1998-2002, have been used to fill the gaps where possible.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 03 декабря, 2018
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      The sources for this database are mainly census data, from the 2000 round of censuses. Census data were used for 22 countries. Countries not taking periodic censuses but keeping population registers have provided data extracted from these registers; this is the case for four countries: Denmark, Finland, Norway and Sweden. For some countries, not all themes covered in the database are present in the national census or register. Labour force surveys, provided by Eurostat and averaged over the period 1998-2002, have been used to fill the gaps where possible. The exact national source and reference period for each file is given in Table A.1 (see the methodological document).
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 03 декабря, 2018
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      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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      This database presents the 2018 edition of OECD time-series indicators of implied R&D tax subsidy rates for OECD member countries and five non-member economies (Brazil, People's Republic of China, Romania, Russian Federation, and South Africa) over the period 2000-2018, drawing on data collected in the OECD-NESTI R&D tax incentive surveys from 2007 to 2018. The 2018 edition of RDTAXSUB contains time-series estimates that are based on headline tax credit and allowance rates, by firm size and profitability scenario. Due to limited historical data availability, the estimates are not adjusted for provisions that bound the tax benefits received by firms (e.g. ceilings, thresholds). They therefore provide an upper bound for the marginal tax subsidy implied by R&D tax relief measures across countries over time. These estimates should not be confused with separate contemporary cross-sectional OECD estimates of marginal tax subsidy rates (OECD, 2018) that compute adjusted (weighted) tax credit/allowance rates for a number of countries based on available information on the proportion of eligible R&D subject to different marginal levels of relief (see 2017).The tax subsidy rate is defined as 1 minus the B-index, a measure of the before-tax income needed by a “representative” firm to break even on USD 1 of R&D outlays (Warda, 2001). As tax component of the user cost of R&D, the B-Index is is directly linked to measures of effective marginal tax rates. Measures of tax subsidy rates such as those based on the B-index provide a convenient proxy for examining the implications of tax relief provisions. These provide a synthetic representation of the generosity of a tax system from the perspective of a generic or model type of firm for the marginal unit of R&D expenditure. To provide a more accurate representation of different scenarios, B-indices are calculated for “representative” firms according to whether they can claim tax benefits against their tax liability in the reporting period (OECD, 2013). When credits or allowances are fully refundable, the B-index of a firm in such a position is identical to the profit scenario. Carry-forwards are modelled as discounted options to claim incentives in the future, assuming a constant annual probability of returning to profit of 50% and a nominal discount rate of 10%. For general and country-specific notes on the time-series estimates of implied marginal tax subsidy rates on R&D expenditures (based on the B-index), see http://www.oecd.org/sti/rd-tax-stats-bindex-notes.pdf.
    • Июль 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 04 августа, 2014
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      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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 09 апреля, 2019
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    • Июль 2015
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 08 октября, 2015
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      This table contains data on discouraged jobseekers as a percentage of the labour force and as a percentage of the population by sex and standardised age groups (15-24, 15-64, 25-54, 55-64, 65+, total). Unit of measure used - Data are expressed as percentages.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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      This table contains the shares of economic short-time workers among total employment, the ratio of economic short-time workers and labour force, and the gender composition of economic short-time workers. Data re broken down by professional status - employees, total employment – by sex and standardised age groups (15-24, 25-54, 55+, total). Unit of measure used - Data are expressed as percentages.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      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.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июля, 2019
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      This table contains incidences and gender composition of part-time employment with standardised (15-24, 25-54, 55-64, 65+, total) and detailed age groups. Data are further broken down by professional status - employees, total employment. Part-time employment is based on a common 30-usual-hour cut-off in the main job. Unit of measure used - Data are expressed in percentages.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 21 июня, 2019
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      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
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 06 июля, 2019
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      This datasetcontains 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).
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 21 июня, 2019
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      This table contains incidences and gender composition of temporary employment with standardized age groups (15-24, 25-54, 55-64, 65+, total). Data are further broken down by professional status - employees, total employment. Unit of measure used - Data are expressed in percentages.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июля, 2019
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      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.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      http://www.oecd.org/els/soc/IDD-Metadata.pdf
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 05 июля, 2019
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      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.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 марта, 2019
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      Data source(s) used The inland fisheries data collection is part of the more comprehensive data gathering carried out on an annual basis by the Fisheries Committee (COFI) of the Trade and Agriculture Directorate (TAD) from OECD members and participating non-OECD economies. Data on marine landings, aquaculture production, inland fisheries catch, fleet, employment, total allowable catch (TAC) and fisheries support estimate (FSE) are collected from Fisheries Ministries, National Statistics Offices and other institutions designated as an official data source. The surveys used for this exercise are the OECD Fisheries questionnaires.   Data are collected in tonnes and national currency at current values. For analytical purposes and data comparisons, value data are converted and published also in US dollars. Exchange rates are average yearly spot rates, taken from the dataset OECD Economic Outlook: Statistics and Projections. Data reported in this dataset are expressed in tonnes, in units of national currency and in US dollars. Data are recorded on a landed weight basis, i.e. the mass (or weight) of a product at the time of landing, regardless of the state in which is landed (i.e. whole, gutted, filleted, meal, etc.). For exceptions, please see the individual notes. Statistical population The statistical population is the set of countries participating in the work of the COFI, i.e. OECD members, excluding landlocked countries, with some exceptions (Czech Republic and Slovakia are included, Israel is not). The group includes also the following partner countries: Argentina, China, Colombia, Costa Rica, Indonesia, Lithuania, Peru, Philippines, Thailand and Chinese Taipei. In order to facilitate analysis and comparisons over time, historical data for OECD members have been provided over as long a period as possible, often even before a country became a member of the Organisation. Information on the membership dates of all OECD countries can be found at OECD Ratification Dates. Key statistical concept Inland fisheries include catches of fish, crustaceans, molluscs and other aquatic invertebrates (and animals), residues and seaweeds in lakes, rivers, ponds, inland canals and other land-locked water bodies. For the purpose of this questionnaire the boundary between inland and marine areas at the river mouth is left to the discretion of the national authority. Production from aquaculture installations should not be reported on this form. However, catches from fisheries that are managed by stocking should be included. The methodological reference document for fisheries and aquaculture statistics is the CWP Handbook of Fishery Statistics.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
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      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.   The first set of indicators measure total financial assets (liabilities) held by each institutional investor as a percentage of GDP. Total financial assets (liabilities) is defined as the sum of the following asset (liability) categories: currency and deposits (F2), debt securities (F3), loans (F4), equity and investment fund shares (F5), insurance pension and standardized guarantee schemes (F6), financial derivatives and employee stock options (F7), and other accounts receivable (payable) (F8). The second set of indicators shows the share of each asset (liability) category in the total financial assets (liabilities) of each investor. They help to analyse the investment portfolio composition of the investor as well as financial risks borne by the investor. The third set of indicators shows the sub-sector composition of total financial assets (liabilities) by investor category, by showing the share of each sub-sector in the total financial assets (liabilities) of each investor category.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      This dataset presents internationally comparable data on instruction time in full-time compulsory education. It covers primary and (lower and upper) secondary general education, but excludes pre-primary education, even if compulsory. Total number of instruction hours and the distribution of hours per subject is available either by level of education or by age.
    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 мая, 2019
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      These data are part of a larger database, hosted on a different website, which includes both quantitative and qualitative data, as well as graphs.
    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 февраля, 2019
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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. 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.
    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 февраля, 2019
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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. 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).
    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 февраля, 2019
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      This data deals with premiums written by classes of non-life insurance for the business written in the reporting country.
    • Февраль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 27 февраля, 2019
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      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 2015, 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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июля, 2019
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      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 grants An earmarked grant is a grant that is given under the condition that it can only be used for a specific purpose. Non-earmarked grants Non-earmarked grants can be spent as if they were the receiving sub-national government's own (non-earmarked) tax revenues. Mandatory grants Mandatory 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 grants Discretionary 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 grants Matching 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 grants Non-matching grants are grants not directly linked to any sub-national contribution. Current grants Current grants are grants assumed to be spent on either current or capital expenditures. Capital grants Capital grants are grants assumed to be spent only on capital expenditures.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 марта, 2019
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    • Октябрь 2017
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 27 июля, 2018
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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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      This dataset contains the number of people who graduated from an education programme by country of origin and sex.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 21 июня, 2019
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      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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      This indicator reports the percentage of students of each country of origin over the total of international students.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июля, 2019
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      This dataset presents official international trade statistics in fisheries products, directly sourced from the UN Comtrade Database.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 19 июня, 2019
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      The International Transport Forum collects, on a quarterly basis, monthly data from all its Member countries. When monthly information is not available then quarterly data is provided. The survey contains a dozen variables selected for their quarterly availability among reporting countries. Data are collected from Transport Ministries, statistical offices and other institution designated as official data source. The survey used for this exercise is the ITF "Quarterly Transport Statistics". Variables collected are rail, road and inland waterways goods transport (T-km), rail passengers (P-km), road traffic (V-km), first registration of brand new vehicles, petrol deliveries to the road transport sector and road fatalities. Although there are clear definitions for all the terms used in this survey, countries might have different methodologies to gather or estimate quarterly data. The information provided in short-term surveys does not necessarily have the same coverage as annual data exercises and therefore remains provisional. Depending on countries, data is not always revised so totals might not correspond to the sum of the elements. The main purpose of this data collection is to identify in advance changes in transport data trends. In case of missing data for a country, ITF can calculate estimates based generally on growth rates from previous years or from data available from other sources. These estimates are used solely to calculate aggregated trends in graphic representations and are not shown at the individual country level.  
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      The intra-EEA Services Trade Restrictiveness Index identifies and catalogues which policy measures restrict trade within the European Economic Area (EEA) for 25 OECD EU member countries. It complements the existing STRI, which quantifies multilateral services trade restrictiveness, allowing to track the progress of regional services integration across 19 major services sectors.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      The intra-EEA Services Trade Restrictiveness Index identifies and catalogues which policy measures restrict trade within the European Economic Area (EEA) for 25 OECD EU member countries. It complements the existing STRI, which quantifies multilateral services trade restrictiveness, allowing to track the progress of regional services integration across 19 major services sectors.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июня, 2019
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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
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 05 июля, 2019
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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).
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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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).
    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 28 мая, 2019
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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).
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 02 июля, 2019
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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.
    • Август 2015
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 18 июля, 2016
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      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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Июль 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 04 августа, 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.
  • J
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      Job quality refers to multiple aspects of employment that contribute to well-being of workers and represents an inherently multi-dimensional construct. Job quality database focuses on three key dimensions. These are earnings quality, labour market security and quality of the working environment.
  • K
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 03 декабря, 2018
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      Benefit Generosity, Income Adequacy, Work Incentives.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 19 июня, 2019
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      The Key Economic Indicators (KEI) database contains monthly and quarterly statistics (and associated statistical methodological information) for all OECD member countries and for a selection of non-member countries on a wide variety of economic indicators, namely: quarterly national accounts, industrial production, composite leading indicators, business tendency and consumer opinion surveys, retail trade, consumer and producer prices, hourly earnings, employment/unemployment, interest rates, monetary aggregates, exchange rates, international trade and balance of payments.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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  • L
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      This dataset 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. For detailed information on labour force surveys for all countries please see the attached file : www.oecd.org/els/employmentpoliciesanddata/LFSNOTE
    • Июнь 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 04 августа, 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.
    • Август 2017
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 09 января, 2018
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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).
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 15 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 марта, 2019
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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.
    • Январь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 29 января, 2019
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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.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 06 июля, 2019
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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).
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 04 июня, 2019
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      This dataset contains the age composition (as a percentage of all ages) of the population for each labour force status - labour force, employment, unemployment - by sex.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 06 июля, 2019
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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.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 03 декабря, 2018
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      Data is available for the 17 countries covered by the SWAC/OECD (Benin, Burkina Faso, Cabo Verde, Chad, Cote d'Ivoire, The Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Mauritania, Niger, Nigeria, Senegal, Sierra Leone and Togo).
  • M
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 марта, 2019
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      This biannual publication provides a set of indicators that reflect the level and structure of the efforts undertaken by OECD member countries and seven non-member economies (Argentina, People's Republic of China, Romania, Russian Federation, Singapore, South Africa, Chinese Taipei) in the field of science and technology. These data include final or provisional results as well as forecasts established by government authorities. The indicators cover the resources devoted to research and development, patent families, technology balance of payments and international trade in 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 a co-ordinated collection. The sources for the other indicators include the OECD databases on Activities of Multinational Enterprises (AMNE), on Bilateral Trade in Goods by Industry and End-use Category database (BTDIxE), on Patents and on Technological Balance of Payments (TBP). The R&D data used in this publication have been collected and presented in line with the standard OECD methodology for R&D statistics as laid out in the OECD "Frascati Manual". The 2002 edition of the manual has now been superseded by the 2015 edition. The revised guidelines and definitions are in the course of being implemented and are not expected to change the main indicators significantly although some terminology changes will occur. This edition of MSTI has been compiled in accordance with the 2002 Frascati Manual; these changes will be made in a coming edition as R&D surveys move to the new standard.   2018 values are estimated value.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      This dataset contains the number of Management personnel and teacher aides in educational institutions by sex and intensity.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      IPAW = Income as a percentage of the average wage   This data is updated after the finalisation of the Taxing Wages publication for the corresponding year. This table reports marginal personal income tax and social security contribution rates for a single person without dependent, at various multiples (67%, 100%, 133%, 167%) of the AW/APW. The average wage (AW) by country and year can be found within the Taxing Wages comparative tables dataset, under the indicator heading: Total gross earnings before taxes (national currency). The AW is based on a single person at 100% of average earnings, no child. The results, derived from the OECD Taxing Wages framework (elaborated in the annual publication Taxing Wages), use tax rates applicable to the tax year. The results take into account basic/standard income tax allowances and tax credits and include family cash transfers (see Taxing Wages). The marginal rates are expressed as a percentage of gross wage earnings, with the exception of the Total tax wedge which is expressed as a percentage of gross labour costs (gross wages + employer SSC). The sub-central personal tax rates used in this table correspond to those used in Taxing Wages. The figures may differ from those published in Taxing Wages where updated information is available, such as revised AW/APW data. Further explanatory notes may be found in the Explanatory Annex.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Июль 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 05 августа, 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.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 09 июля, 2019
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      The data presented come from two international sources: (1) UN and International Resource Panel "Global Material Flows Database" for non-EU OECD and non-OECD countries, and (2) Eurostat  "Material Flows and Resource Productivity" database for EU OECD countries. 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). 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. 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. Direct material input (DMI) is computed as DEU plus imports. 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 or processed. They comprise marble, granite, sandstone, porphyry, basalt, other ornamental or building stone (excluding slate); chalk and dolomite; sand and gravel; clays and kaolin; limestone and gypsum. 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 energy materials/carriers: coal, crude oil, natural gas and peat, as well as manufactured products predominantly made of fossil fuels (e.g. plastics, synthetic rubber).
    • Январь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 06 марта, 2019
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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).
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 29 мая, 2019
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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.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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      This dataset contains statutory and national minimum wages in place in 27 OECD Member countries, Brazil, Colombia, Costa Rica, Lithuania, Malta, Romania and the Russian Federation.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      The aim of the OECD’s new Skills for Jobs Indicators is to facilitate better adaptation to changing skill needs by making available a database of skill imbalances indicators that is comparable across countries and regularly updated. The Skill Needs Indicators provide an overview of the shortages and surpluses of skills across countries.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      This dataset and predefined summary tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2017, which monitors agricultural policy developments in 35 OECD member countries, 6 non-OECD EU member states and 11 emerging economies: Brazil, China, Colombia, Costa Rica, Indonesia, Kazakhstan, Russia, the Philippines, South Africa, Ukraine and Viet Nam. The OECD uses a comprehensive system for measuring and classifying support to agriculture - the Producer and Consumer Support Estimates (PSEs and CSEs) and related indicators. They provide insight into the increasingly complex nature of agricultural policy and serve as a basis for OECD’s work on agricultural policies. 
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
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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.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 19 июня, 2019
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      The International Trade (MEI) dataset contains predominantly monthly merchandise trade statistics, and associated statistical methodological information, for all 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.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
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      The Financial Statistics dataset contains predominantly monthly statistics, and associated statistical methodological information, for the 36 OECD member countries and some selected other countries. The dataset itself contains financial statistics on 4 separate subjects: Monetary Aggregates, Interest Rates, Exchange Rates, and Share Prices. The data series presented within these subjects have been chosen as the most relevant financial 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. All data are available monthly, and are presented as either an index (where the year 2015 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.
    • Декабрь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 11 декабря, 2018
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      Air pollution is considered one of the most pressing environmental and health issues across OECD countries and beyond. According to the World Health Organisation (WHO), exposure to fine particulate matter (PM2.5) and ground-level ozone (O3) have potentially the most significant adverse effects on health compared to other pollutants. PM2.5 can be inhaled and cause serious health problems including both respiratory and cardiovascular disease, having its most severe effects on children and elderly people. Exposure to PM2.5 has been shown to considerably increase the risk of heart disease and stroke in particular. For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator. Exposure to ground-level ozone (O3) has serious consequences for human health, contributing to, or triggering, respiratory diseases. These include breathing problems, asthma and reduced lung function (WHO, 2016; Brauer et al., 2016). Ozone exposure is highest in emission-dense countries with warm and sunny summers. The most important determinants are background atmospheric chemistry, climate, anthropogenic and biogenic emissions of ozone precursors such as volatile organic compounds, and the ratios between different emitted chemicals.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 19 марта, 2019
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      This dataset shows data provided by Member countries' authorities through the questionnaire on the state of the environment (OECD/Eurostat). They were updated or revised on the basis of data from other national and international sources available to the OECD Secretariat, and on the basis of comments received from national Delegates. Selected updates were also done in the context of the OECD Environmental Performance Reviews. The data are harmonised through the work of the OECD Working Party on Environmental Information (WPEI) and benefit from continued data quality efforts in OECD member countries, the OECD itself and other international organisations. In many countries systematic collection of environmental data has a short history; sources are typically spread across a range of agencies and levels of government, and information is often collected for other purposes. When interpreting these data, one should keep in mind that definitions and measurement methods vary among countries, and that inter-country comparisons require careful interpretation. One should also note that data presented here refer to national level and may conceal major subnational differences. 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
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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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.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 марта, 2019
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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. 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.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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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.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 марта, 2019
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      This dataset presents information using an "indicator" approach, focusing on cross-country comparisons. The aim is to make the accounts more accessible and informative, whilst taking the opportunity to present the conceptual underpinning  and comparability issues of each of the indicators presented. The range of indicators is set deliberately wide to reflect the richness of the national accounts dataset and to encourage users of economic statistics to refocus some of the spotlight that is often placed on GDP to other important economic indicators, which may better respond to their needs. Indeed many users themselves have been instrumental in this regard. The report of the Commission on the Measurement of Economic Performance and Social Progress (Stiglitz-Sen-Fitoussi Commission) is but one notable example. That is not to undermine the importance of GDP, which arguably remains the most important measure of total economic activity, but other measures may better reflect other aspects of the economy. For example, net national income may be a more appropriate measure of income available to citizens in countries with large outflows of property income, and household adjusted disposable income per capita may be a better indicator of the material well-being of citizens. But certainly from a data perspective more can and remains to be done. The Stiglitz-Sen-Fitoussi Commission for example highlights the pressing need for the provision, by official statistics institutes, of more detailed information that better describes the distributional aspects of activity, especially income, and the need to build on the national accounts framework to address issues such as non-market services produced by households or leisure. It is hoped that by producing a publication such as this and thereby raising awareness, the momentum from this and other initiatives will be accelerated. The publication itself will pick up new indicators in the future as they become available at the OECD.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 15 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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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..
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 15 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 15 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 марта, 2019
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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.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 марта, 2019
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      It presents the different transactions and balances to get from the GDP to the net lending/net borrowing. Therefore, it includes, in particular, national disposable income (gross and net), consumption of fixed capital as well as net saving.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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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.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 05 июня, 2019
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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.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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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.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 15 апреля, 2019
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    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 15 апреля, 2019
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    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 17 мая, 2019
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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.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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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.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 28 марта, 2019
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      Annual National Accounts>General Government Accounts>750. General Government Debt-Maastricht   Unit of measure used: National currency; current prices. Expressed in millions   Statistical population: Government debt as defined in the Maastricht Treaty (Source : Eurostat). Available for Europeans countries only. In the Protocol on the excessive deficit procedure annexed to the Maastricht Treaty, government debt is defined as the debt of the whole general government sector: gross, consolidated and nominal value (face value). It excludes the other accounts payable (AF.7), as well as, if they exist, insurance technical reserve (AF.6).
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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      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).
    • Январь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 22 января, 2019
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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.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 27 марта, 2019
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      Annual National Accounts>Detailed Tables and Simplified Accounts>7A. Labour input by activity, ISIC rev4   Unit of measure used: In persons, full-time equivalents, jobs and hours.   Statistical population: It presents employment, broken down by detailed industries according to the classification ISIC rev.4. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Pallavi S
      Дата обращения к источнику: 14 марта, 2019
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      It presents population data and employment by main activity. It includes national concept data for economically active population, unemployed persons, total employment, employees and self-employed, as well as domestic concept data for total employment, employees and self-employed. The domestic concept data are available broken down by main activity. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 марта, 2019
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    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 13 марта, 2019
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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.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 09 июля, 2019
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      Annual National Accounts>Supply and Use Tables>30. Supply at basic prices and its transformation into purchasers' prices   Unit of measure used: In national currency, in current prices and previous year 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.   Statistical population: It presents the Supply table at basic prices and its transformation into purchaser's prices. It provides information by industry (at the 2 digit ISIC Rev 4 level, containing 89 industries) with corresponding breakdowns by product (using the comparable CPA product breakdown). It has been prepared from statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 02 июля, 2019
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      Annual National Accounts>Supply and Use Tables>SUT Indicators>SUT Indicators   Statistical population: These indicators are calculated by the OECD from the SUT statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.   Key statistical concept: The supply table describes the supply of goods and services, which are either produced in the domestic industry or imported. The use table shows where and how goods and services are used in the economy. Therefore in addition to their essential role to better estimations of National Accounts, Supply and Use tables are also a very powerful tool to understand the impact of policy decisions and globalisation, as they provide a detailed analysis of the process of production and the use of goods and services. For example, the Supply and Use Tables could be used to measure the the percentage of imports used in the production process or the share of trade and transport margins in the households’ final consumption expenditure.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 09 июля, 2019
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      Annual National Accounts>Supply and Use Tables>31. Supply, Output and its components by industries   Unit of measure used: In national currency, in current prices and previous year 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.   Statistical population: It presents the breakdown of output at basic prices between market output, output for own final use and non-market output, by activty at the 2 digit ISIC Rev 4 level. It has been prepared from statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 марта, 2019
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      It provides a faithful image, to the greatest extent possible, of the aggregates and balances of the general government sector Data are also available, for most countries, for the sub-sectors of general government.
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 27 марта, 2019
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      Annual National Accounts
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 27 марта, 2019
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      Annual National Accounts>Supply and Use Tables>40. Use at purchasers' prices   Unit of measure used: In national currency, in current prices and previous year 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.   Statistical population: It presents the Use table at purchaser's prices. It provides information by industry (at the 2 digit ISIC Rev 4 level, containing 89 industries) with corresponding breakdowns by product (using the comparable CPA product breakdown). It has been prepared from statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.
    • Май 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 29 мая, 2019
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      Annual National Accounts
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 27 марта, 2019
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      Annual National Accounts
    • Март 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 27 марта, 2019
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      Annual National Accounts>Supply and Use Tables>44. Valuation Matrices   Unit of measure used: In national currency, in current prices and previous year 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.   Statistical population: It presents the tables of trade and transport margins, of taxes less subsidies on products. It provides information by industry (at the 2 digit ISIC Rev 4 level, containing 89 industries) with corresponding breakdowns by product (using the comparable CPA product breakdown). It has been prepared from statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 21 июня, 2019
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      Statistical population: 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 according to the classification ISIC rev.4. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. 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.   Note: 6A. Value added and its components by activity, ISIC rev4
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 25 июня, 2019
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      Statistical population: 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. 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. 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.
    • Июнь 2018
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 24 июля, 2018
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      The "National CPI Weights" dataset contains the annual expenditure weights for the national CPI for the OECD Member countries at a detailed level of the COICOP classification (except Australia and Korea). The weight of a product in a CPI is the proportion of total household expenditure which is spent on that product during the weight reference period.
    • Май 2016
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 29 июня, 2016
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      National landings in domestic ports
    • Декабрь 2014
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 14 ноября, 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. The OECD, a partner with the CWP, additionaly 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.  
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      This indicator measures the net costs paid by parents for full-time centre-based childcare, after any benefits designed to reduce the gross childcare fees. Childcare benefits can be received in the form of childcare allowances, tax concessions, fee rebates and increases in other benefit entitlements.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 16 апреля, 2019
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      Net Replacement Rates in unemployment measure the proportion of previous in-work income that is maintained after 1, 2, …, T months of unemployment.
    • Июль 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 05 июля, 2019
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      This dataset presents the number of new entrants in a given programme by age and sex.
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      This dataset presents the number of new entrants in a given programme by field and sex.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
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      This dataset presents the Non-consolidated financial balance sheets by economic sector (Quarterly table 0720), according to SNA 2008 methodology. It comprises all flows, which record, by type of financial instruments, the financial transactions between institutional sectors.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 19 июня, 2019
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      This dataset presents the Non-consolidated financial transactions by economic sector (Quarterly table 0620), according to SNA 2008 methodology. It comprises all flows, which record, by type of financial instruments, the financial transactions between institutional sectors.
    • Июнь 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 18 июня, 2019
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      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 - Balance sheets for non-financial assets - Employment by sector 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 and Key Partner 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 System of National Accounts (SNA 2008 or SNA 1993 for a few countries):
    • Апрель 2019
      Источник: Organisation for Economic Co-operation and Development
      Загружен: Knoema
      Дата обращения к источнику: 12 апреля, 2019
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      This dataset contains the number of people who graduated from an education programme by age and sex.
    • O
      • Март 2014
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 13 марта, 2014
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        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.
      • Март 2016
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 27 апреля, 2016
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      • Март 2016
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 27 апреля, 2016
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      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 марта, 2019
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        These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. They comprise the summary of agricultural support estimates for OECD countries
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 марта, 2019
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        These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. They comprise the summary of agricultural support estimates for OECD countries.
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 13 марта, 2019
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        These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. They comprise the summary of agricultural support estimates for OECD countries
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 14 марта, 2019
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         These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. They comprise the summary of agricultural support estimates for OECD countries.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 05 июня, 2019
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        2011 F) OECD Countries : Consumer Support Estimate by Country These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. They comprise the summary of agricultural support estimates for OECD countries. NPC: Nominal Protection Coefficient. NAC: Nominal Assistance Coefficient.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 04 июня, 2019
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        2011 H) OECD Countries : General Services Support Estimate by Country These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. They comprise the summary of agricultural support estimates for OECD countries. TSE : Total support estimate
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 04 июня, 2019
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        2011 D) OECD Countries : Producer Support Estimate by Country These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. They comprise the summary of agricultural support estimates for OECD countries. NPC: Nominal Protection Coefficient. NAC: Nominal Assistance Coefficient.
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 02 июля, 2019
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      • Октябрь 2017
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 14 августа, 2018
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        The biennial OECD Digital Economy Outlook examines and documents evolutions and emerging opportunities and challenges in the digital economy. It highlights how OECD countries and partner economies are taking advantage of information and communication technologies (ICTs) and the Internet to meet their public policy objectives. Through comparative evidence, it informs policy makers of regulatory practices and policy options to help maximise the potential of the digital economy as a driver for innovation and inclusive growth.   This dataset provides data underlying Chapter 3 on Access and Connectivity in the OECD Digital Economy Outlook 2017.     Table 3.2. Access trends in the OECD area Table 3.3. Fixed telephone access paths in the OECD area Table 3.4. Total communication access paths in the OECD area Table 3.5. Total communication access paths in the OECD area per 100 inhabitants Table 3.6. Cellular mobile subscriptions in the OECD area Table 3.7. Cellular mobile subscriptions in the OECD area per 100 inhabitants Table 3.8. Telecommunication revenue in the OECD area Table 3.9. Telecommunication revenue in the OECD area per GDP Table 3.10. Telecommunication investment in the OECD area Table 3.11. Telecommunication investment as a percentage of telecommunications revenue
      • Февраль 2012
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
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        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.
      • Февраль 2012
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
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        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.
      • Ноябрь 2008
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
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        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.
      • Август 2014
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 07 августа, 2014
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        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.
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 06 июля, 2019
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        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/.
      • Сентябрь 2014
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 20 марта, 2015
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        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.
      • Июль 2014
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 04 августа, 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. Status:  Discontinued 
      • Июль 2014
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 04 августа, 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. Status:  Discontinued 
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        This OECD inventory maps existing cross-country surveys that provide information on the characteristics of people's jobs. The information included in this inventory covers international surveys conducted since the early 1990s that are based on individuals' self-reported assessment of their current job, for 160 countries over 25 years. Survey questions are grouped into 19 indicators. For each indicator, binary codes (1 and 0) show whether indicators are available or not for the various countries and years. The inventory also provides users with detailed documentation on the questions used in the various surveys for measuring these indicators.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 04 июня, 2019
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        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.
      • Июль 2015
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 09 марта, 2018
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        ICT investment is defined as the acquisition of equipment and computer software that is used in production for more than one year. ICT has three components: information technology equipment (computers and related hardware); communications equipment; and software. Software includes acquisition of pre-packaged software, customised software and software developed in-house. This indicator is measured as a percentage of total non-residential gross fixed capital formation.
      • Июль 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 22 августа, 2018
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        This dataset provides an access to a limited version of the database presented in the OECD-FAO Agricultural Outlook.  For most of the commodity markets analysed in the Outlook, detailed supply and use balances are available, as well as domestic and international commodity prices.  For OECD countries, the data is accompanied by detailed meta-data. In most cases the data is going back to 1970 and extended to the latest year in the projections (currently 2027).
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 02 июля, 2019
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        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).
      • Май 2017
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 20 июня, 2017
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        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).
      • Май 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 29 мая, 2019
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        Other official flows are official sector transactions which do not meet the ODA criteria, e.g.:  i.) Grants to developing countries for representational or essentially commercial purposes;  ii.) Official bilateral transactions intended to promote development but having a grant element of less than 25 per cent;  iii.) Official bilateral transactions, whatever their grant element, that are primarily export-facilitating in purpose. This category includes by definition export credits extended directly to an aid recipient by an official agency or institution ("official direct export credits");  iv.) The net acquisition by governments and central monetary institutions of securities issued by multilateral development banks at market terms;  v.) Subsidies (grants) to the private sector to soften its credits to developing countries [see Annex 3, paragraph A3.5.iv)b)];  vi.) Funds in support of private investment.
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 13 марта, 2019
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      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 05 июня, 2019
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        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).
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 02 июля, 2019
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        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.
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 02 июля, 2019
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        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.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 23 апреля, 2019
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        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.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 05 июня, 2019
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        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.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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    • P
      • Май 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 17 мая, 2019
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        The International Transport Forum collects data on transport statistics on annual basis from all its Member countries. Data are collected from Transport Ministries, statistical offices and other institution designated as official data source. Variables collected are inland transport of goods (T-km), of passengers (P-km) and road injury accidents. Additional information is also gathered on containers transported by rail and sea (Tons and TEU) as well as short sea shipping data (T-km).
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 13 марта, 2019
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        The OECD Environment Directorate, in collaboration with the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in environment-related technologies. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' environmental and innovation policies. The patent statistics presented here are constructed using data extracted from the Worldwide Patent Statistical Database (PATSTAT) of the European Patent Office (EPO) using algorithms developed by the OECD. Consistent with other patent statistics provided in OECD.Stat, only published applications for "patents of invention" are considered (i.e. excluding utility models, petty patents, etc.). The relevant patent documents are identified using search strategies for environment-related technologies (ENV-TECH) which were developed specifically for this purpose. They allow identifying technologies relevant to environmental management, water-related adaptation and climate change mitigation. An aggregate category labelled "selected environment-related technologies" includes all of the environmental domains presented here.
      • Ноябрь 2017
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 04 января, 2018
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        The OECD Environment Directorate, in collaboration with the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in environment-related technologies. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' environmental and innovation policies. The patent statistics presented here are constructed using data extracted from the Worldwide Patent Statistical Database (PATSTAT) of the European Patent Office (EPO) using algorithms developed by the OECD. Consistent with other patent statistics provided in OECD.Stat, only published applications for "patents of invention" are considered (i.e. excluding utility models, petty patents, etc.). The relevant patent documents are identified using search strategies for environment-related technologies (ENV-TECH) which were developed specifically for this purpose. They allow identifying technologies relevant to environmental management, water-related adaptation and climate change mitigation. An aggregate category labelled "selected environment-related technologies" includes all of the environmental domains presented here.
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 05 марта, 2019
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        The OECD Environment Directorate, in collaboration with the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in environment-related technologies. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' environmental and innovation policies. The patent statistics presented here are constructed using data extracted from the Worldwide Patent Statistical Database (PATSTAT) of the European Patent Office (EPO) using algorithms developed by the OECD. Consistent with other patent statistics provided in OECD.Stat, only published applications for "patents of invention" are considered (i.e. excluding utility models, petty patents, etc.). The relevant patent documents are identified using search strategies for environment-related technologies (ENV-TECH) which were developed specifically for this purpose. They allow identifying technologies relevant to environmental management, water-related adaptation and climate change mitigation. An aggregate category labelled "selected environment-related technologies" includes all of the environmental domains presented here.
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 05 марта, 2019
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        The OECD Environment Directorate, in collaboration with the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in environment-related technologies. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' environmental and innovation policies. The patent statistics presented here are constructed using data extracted from the Worldwide Patent Statistical Database (PATSTAT) of the European Patent Office (EPO) using algorithms developed by the OECD. Consistent with other patent statistics provided in OECD.Stat, only published applications for "patents of invention" are considered (i.e. excluding utility models, petty patents, etc.). The relevant patent documents are identified using search strategies for environment-related technologies (ENV-TECH) which were developed specifically for this purpose. They allow identifying technologies relevant to environmental management, water-related adaptation and climate change mitigation. An aggregate category labelled "selected environment-related technologies" includes all of the environmental domains presented here.
      • Февраль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 22 февраля, 2019
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        The OECD Environment Directorate, in collaboration with the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in environment-related technologies. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' environmental and innovation policies. The patent statistics presented here are constructed using data extracted from the Worldwide Patent Statistical Database (PATSTAT) of the European Patent Office (EPO) using algorithms developed by the OECD. Consistent with other patent statistics provided in OECD.Stat, only published applications for "patents of invention" are considered (i.e. excluding utility models, petty patents, etc.). The relevant patent documents are identified using search strategies for environment-related technologies (ENV-TECH) which were developed specifically for this purpose. They allow identifying technologies relevant to environmental management, water-related adaptation and climate change mitigation. An aggregate category labelled "selected environment-related technologies" includes all of the environmental domains presented here.
      • Март 2016
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 16 января, 2017
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         Description The OECD's Directorate for Science, Technology and Industry has developed patent data and indicators that are suitable for statistical analysis and that can help addressing S&T policy issues. To date, the OECD Patent Database fully covers:Patent applications to the European Patent Office (EPO) (from 1978 onwards);Patents applications to the US Patent and Trademark Office (USPTO) (granted patents from 1976 onwards, patent filings as of 2001 only);Patents filed under the Patent Co-operation Treaty (PCT), at international phase, that designate the EPO (from 1978 onwards);Patents that belong to Triadic Patent Families (OECD definition): i.e. sub-set of patents all filed together at the EPO, at the Japanese Patent Office (JPO) and at the USPTO, protecting the same set of inventions. EPO and PCT patent counts are based on data received from the EPO (EPO Bibliographic database, patent published until November 2015).  Series on USPTO patents and Triadic patent families are mainly derived from EPO's Worldwide Statistical Patent Database (PATSTAT, Autumn 2015). Regional data are based on OECD, REGPAT database, February 2016. Indicators based on patent families improve the international comparability and the quality of patent's indicators (overcoming the drawbacks of traditional patent-based indicators, such as the "home advantage")
      • Октябрь 2017
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 23 июля, 2018
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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. 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.
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 02 июля, 2019
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        The OECD Pensions at a Glance Database has been developed in order to serve a growing need for pensions indicators. It includes reliable and internationally comparable statistics on public and mandatory and voluntary pensions. It covers 34 OECD countries and aims to cover all G20 countries. Pensions at a Glance reviews and analyses the pension measures enacted or legislated in OECD countries. It provides an in-depth review of the first layer of protection of the elderly, first-tier pensions across countries and provideds a comprehensive selection of pension policy indicators for all OECD and G20 countries.
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 03 июля, 2019
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      • Март 2017
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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      • Март 2016
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 28 ноября, 2016
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        The Population and Vital Statistics dataset presents components of change in the population during one year and mid-year population data for the 34 OECD member countries. Data are presented in thousands of persons and as rates in per 1000. The components of change in the population during one year are presented as follow: the first statistics refer to the population on January 1st for each year, the natural increase of the population is the difference between the number of births and deaths over the calendar year, the addition of net migration and statistical adjustments to the natural increase gives the total increase of the population over the calendar year. The addition of the total population increase to the population on January 1st gives the population on December 31st. Note: No longer this dataset be collected by OECD. Population and demographic events are available from the United Nation database at "https://esa.un.org/unpd/wpp/Download/Standard/Population/."    
      • Сентябрь 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 22 марта, 2019
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        This dataset contains the number of people by sex and age group per country.
      • Январь 2016
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 03 декабря, 2018
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        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.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 28 июня, 2019
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        Country weights used for calculation of Consumer Prices and Producer Prices OECD zones
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 02 июля, 2019
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        Private transactions are those undertaken by firms and individuals resident in the reporting country.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        This dataset presents activities in support of development from philanthropic foundations since 2009, including bilateral activities and core contributions to multilateral organisations. Bilateral activities from this dataset can also be found in the Creditor Reporting System (CRS) database. Collecting data on private philanthropy for development is work in progress, which may explain break in series for some foundations.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 19 июня, 2019
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      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 05 июня, 2019
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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.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 18 июня, 2019
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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.
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 05 марта, 2019
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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 database. However, timely data issues may arise and affect individual series and/or individual countries. Sectors differ from each other with respect to their productivity growth. Understanding the drivers of productivity growth at the total economy level requires an understanding of the contribution of each sector. Data of real gross value added, labour compensation, hours worked and employment are sourced from the OECD Annual National Accounts.
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 02 июля, 2019
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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.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
        Distribution of graduates/new entrants by gender, country of origin and age as well as the proportion of each tertiary educational level over the total of first-time graduates and new entrants at tertiary level.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 06 июля, 2019
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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'
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 05 июня, 2019
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        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.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 05 июня, 2019
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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.
      • Июль 2014
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 04 августа, 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.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        The magnitude of government debt, and public sector debt likewise, depends on the coverage of instruments used and available data. To accommodate a fair international comparison of related indicators, the IMF, the OECD and the World Bank have agreed to define various debt measures depending on the coverage or non-coverage of instruments: D1 to D4. The D1-D4 presentation classifies gross government debt and public sector debt into four separate categories, as defined in the 2012 IMF Staff Discussion Note: “What Lies Beneath: The Statistical Definition of Public Sector Debt”. This coverage of instruments according to this classification ranges from a narrow definition including only debt securities and loans (D1) to a fully comprehensive definition covering all six debt instruments (D4), as defined in the Public Sector Debt Statistics Guide for User and Compilers, and the Government Finance Statistics Manual 2014. For more information, please see the document:
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 22 июня, 2019
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        The Public Sector Debt database includes quarterly detailed information on all liabilities which constitute debt instruments, by initial and residual maturity, which are held by the government, and more broadly the public sector. The debt instruments are those instruments that require the payment of principal and interest or both at some point(s) in the future. All liabilities are considered debt, except liabilities in the form of equity and investment fund shares and, financial derivatives and employee stock options.
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 13 марта, 2019
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        This dataset contains Purchasing Power Parities (PPPs) for all OECD countries. PPPs are the rates of currency conversion that eliminate the differences in price levels between countries. Per capita volume indices based on PPP converted data reflect only differences in the volume of goods and services produced. Comparative price levels are defined as the ratios of PPPs to exchange rates. They provide measures of the differences in price levels between countries. The PPPs are given in national currency units per US dollar. The price levels and volume indices derived using these PPPs have been rebased on the OECD average. Per capita volume indices should not be used to rank countries as PPPs are statistical constructs rather than precise measures. Minor differences between countries should be interpreted with caution.
    • Q
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 18 июня, 2019
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        OECD has extracted monthly trade data from the UN Monthly Comtrade database, and aggregates the quarterly and annual frequencies by summing up the months. This may create discrepancies with annual trade figures as presented in International Trade by Commodity Statistics (ITCS). UN Monthly Comtrade (beta version) contains detailed merchandise trade data provided by countries (or areas) to the United Nations Statistics Division, Department of Economic and Social Affairs (UNSD/DESA). Values are expressed in United States dollars (USD) and refer to declared transaction values. All exports are valued f.o.b. (free on board) and imports are valued c.i.f. (including cost, insurance, freight), except the imports of Canada and Mexico which are valued f.o.b. Detailed country metadata (currency conversion rates, information in HS classifications and data publication dates) can be found from the metadata file at the UN Monthly Comtrade website under the heading Metadata.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 19 июня, 2019
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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: - GDP expenditure and output approaches (current prices and volume estimates); - GDP income approach (current prices); - Gross fixed capital formation (current prices and volume estimates) broken down separately by type of asset or product and by institutional sector; - Disposable income and Real disposable income components; - Saving and net lending (current prices); - Population and Employment (in persons); - Employment by industry (in persons and hours worked); - Compensation of employees (current prices); - Household final consumption expenditure by durability (current prices and volume estimates). The main purpose of this dataset is to provide relevant, reliable, consistent, comparable and timely quarterly national accounts for OECD member countries, some non-member countries and some area totals for analytical purposes. All the OECD member countries compile their accounts according to the 2008 SNA. The non-member countries which are still producing national accounts according to the 1993 SNA will switch to the new 2008 SNA over the coming months/years. This will allow the improvement of cross-countries comparability.
    • R
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 16 апреля, 2019
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      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 16 апреля, 2019
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      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 17 апреля, 2019
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      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 16 апреля, 2019
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      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        This database provides a set of indicators that reflect the level and structure of central government support for business R&D; in form of R&D; tax incentives and direct funding across OECD member countries and ten non-member economies (Argentina, Brazil, Bulgaria, Croatia, Cyprus, People's Republic of China, Romania, Russian Federation, and South Africa). This includes time-series indicators of tax expenditures for R&D;, based on the latest 2017 OECD data collection on tax incentive support for R&D; expenditures that was completed in July 2017. These estimates of the cost of R&D; tax relief have been combined with data on direct R&D; funding, as compiled by National Statistical Offices based on reports from firms, in order to provide a more complete picture of government efforts to promote business R&D.; The latest indicators and information on R&D; tax incentives also feature on the dedicated OECD website Measuring R&D; tax incentives.Tax expenditures are deviations from a benchmark tax system (OECD, 2010) and countries use different national benchmarks. Available estimates typically reflect the sum of foregone tax revenues – on an accruals basis – and refunds where applicable, with no or minimal adjustments for behavior effects. Some countries only report claims realised in a given year (cash basis), while others report losses to government on an accrual basis, excluding claims referring to earlier periods and including claims for current R&D; to be used in the future. For general and country-specific notes on the estimates of government tax relief for R&D; expenditures (GTARD), see http://www.oecd.org/sti/rd-tax-stats-gtard-notes.pdfThe sources for the other indicators (direct funding of BERD, BERD and GDP) include the OECD databases on Main Science and Technology Indicators and Eurostat R&D; statistics.
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 02 июля, 2019
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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).
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 02 июля, 2019
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        These tables present research and development (R&D) personnel statistics for : - Total R&D personnel by sector of employment and field of science, in full-time equivalent on R&D; - Researchers by sex, sector of employment and field of science, in full-time equivant on R&D; - Researchers by sex, sector of employment and field of science, in headcounts. Sectors of employment are business enterprise, government, higher education, private non-profit and total. Breakdown by field of science includes natural sciences, engineering, medical sciences, agricultural sciences, social sciences, and humanities.
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 02 июля, 2019
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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).
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 02 июля, 2019
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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)
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 21 июня, 2019
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        Real hourly and annual minimum wages are statutory minimum wages converted into a common hourly and annual pay period for the 28 OECD countries and 4 non-member countries for which they are available. The resulting estimates are deflated by national Consumer Price Indices (CPI). The data are then converted into a common currency unit using either US $ current exchange rates or US $ Purchasing Power Parities (PPPs) for private consumption expenditures. Real hourly and annual minimum wages are calculated first by deflating the series using the consumer price index taking 2017 as the base year.  The series are then converted into a common currency unit (USD) using Purchasing Power Parities (PPPs) for private consumption expenditures in 2017.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 05 июля, 2019
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      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 13 марта, 2019
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        The reference series used in the publication are: GDP for tax reporting years at market prices, national currency Exchange rates national currency per US dollar Population These data are extracted from various datasets managed by OECD directorates. The figures presented here are those used in creating the latest Revenue Statistics publication. These datasets are updated periodically during the year and therefore the figures in the latest versions may differ from those implied in the publication.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 29 апреля, 2019
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      • Март 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 19 июня, 2018
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        The Regional Database contains annual data from 1995 to the most recent available year (generally 2016 for demographic, 2015 for labour market data and 2014 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), Eurostat, and access of National Statistical Offices websites.
      • Март 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 13 июня, 2018
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        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.
      • Май 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 06 мая, 2019
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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).
      • Апрель 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 июля, 2018
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        The Regional Database contains annual data from 1995 to the most recent available year (generally 2016 for demographic, 2015 for labor market data and 2014 for regional accounts, innovation and social statistics).
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 13 марта, 2019
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        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).   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).
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 02 июля, 2019
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        The Regional well-being dataset presents eleven dimensions central for well-being at local level and for 395 OECD regions, covering material conditions (income, jobs and housing), quality of life (education, health, environment, safety and access to services) and subjective well-being (social network support and life satisfaction). 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 2014). Regions can be easily visualised and compared to other regions through the interactive website [www.oecdregionalwellbeing.org]. The dataset, the website and the publications "Regions at a Glance" and "How’s life in your region?" are outputs designed from the framework for regional and local well-being. 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 2013. 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. 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 395 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 Greece, Hungary and Poland data are presented at a more aggregated (NUTS1) level.
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 09 июля, 2019
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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.
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 05 июля, 2019
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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.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 05 июня, 2019
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        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.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 09 июля, 2019
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        Residential Property Prices Indices (RPPIs) – also named House price indices (HPIs), are index numbers that measure the price of residential properties over time. RPPIs are key statistics not only for citizens and households across the world, but also for economic and monetary policy makers. Among their professional uses, they serve, for example, to monitor macroeconomic imbalances and risk exposure of the financial sector. This dataset covers the 34 OECD member countries and some non-member countries. Please note that not all RPPIs are available for all countries. For instance, the RPPI at the most aggregate level for the United States only covers single-family dwellings, not all types of dwellings as it is the case for most other OECD countries. This dataset presents, for each country, the RPPI that is available at the most aggregate level. It mainly contains quarterly statistics. The dataset called “Residential Property Price Indices (RPPIs) – Complete dataset” contains the full list of available RPPIs. The dataset called “Analytical house price indicators” contains, in addition to nominal RPPIs, information on real house prices, rental prices and the ratios of nominal prices to rents and to disposable household income per capita. The datasets “Analytical house price indicators” and “Residential Property Price Indices (RPPIs) – Headline Indicators” do not refer to the same price indices for Brazil, Canada, China, Germany, the United States and the Euro area. These differences are further documented in country-specific metadata. For the United States, the series used in “Analytical house price indicators” is included in the dataset called “Residential Property Price Indices (RPPIs) – Complete database”, but is not the headline indicator. For all other countries, non-seasonally adjusted price indices in both datasets are identical in the period in which they overlap.For all other countries, non-seasonally adjusted price indices in both datasets are identical on the overlapping period.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 01 июля, 2019
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      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 14 марта, 2019
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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 data on both tax and non-tax revenue in a common format for African countries participating in Revenue Statistics in Africa. Click to collapse Direct source Country representatives authorized to obtain revenue data from the appropriate government departments and responsible for compiling the data and preparing data tables that adhere to the OECD tax classification.
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 14 марта, 2019
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        Revenue Statistics in Asian Countries is a joint publication by the OECD Centre for Tax Policy and Administration and the OECD Development Centre. It presents detailed, internationally comparable data on tax revenues for seven Asian economies, two of which (Korea and Japan) are OECD members. Its approach is based on the well-established methodology of the OECD Revenue Statistics (OECD, 2015), which has become an essential reference source for OECD member countries. Comparisons are also made with the average for OECD economies. Comparable tables show revenue data by type of tax in national currency and US dollars, as a percentage of GDP, and, for the different types of taxes, as a share of total taxation. Detailed country tables show information in national currency values
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 27 марта, 2019
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        Revenue Statistics in LAC Countries is a joint publication by the OECD Centre for Tax Policy and Administration, the OECD Development Centre, the Economic Commission for Latin America and the Caribbean (ECLAC) , the Inter-American Center for Tax Administrations (CIAT) and the Interamerican Development Bank (IDB). It presents detailed, internationally comparable data on tax revenues for 24 Latin American and Caribbean economies, two of which (Chile and Mexico) are OECD members. Its approach is based on the well-established methodology of the OECD Revenue Statistics (OECD, 2016), which has become an essential reference source for OECD member countries. Comparisons are also made with the average for OECD economies. Comparable tables show total tax revenue data and by tax as a percentage of GDP, and, for the different types of taxes, as a share of total taxation. Detailed country tables show information in national currency values
      • Декабрь 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 03 декабря, 2018
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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.
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 13 марта, 2019
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        Reference Series - Latin American Countries Source: OECD National Accounts data for Chile and Mexico and official National Accounts data for the other countries
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 21 июня, 2019
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        Classification(s) used: ICHA-FS: Classification of revenues of health care financing schemes ICHA-HF: Classification of health care financing schemes
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 06 июля, 2019
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        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.
      • Май 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 28 мая, 2019
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        Although there are clear definitions for all the terms used in this survey, countries might have different methodologies to calculate tonne-kilometre and passenger-kilometres. 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 countries, this is not the case for road injuries. 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. 
    • S
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 11 июня, 2019
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        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).
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 02 июля, 2019
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        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.
      • Январь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 27 мая, 2019
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        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.
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 14 марта, 2019
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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.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        The percentage of students enrolled in each type of institution over the total of students.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        This indicator shows the percentage of international students in each field of education.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 18 июня, 2019
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        The Short-Term Labour Market Statistics dataset contains predominantly quarterly labour statistics, and associated statistical methodological information, for the 35 OECD member countries and selected other economies. The Short-Term Labour Market Statistics dataset covers countries that compile labour statistics from sample household surveys on a monthly or quarterly basis. It is widely accepted that household surveys are the best source for labour 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 labour force by age; employment by economic activity, by working time and by status; and, unemployment (including monthly harmonised unemployment) by age and by duration. Data is expressed in levels (thousands of persons) or rates (e.g. employment rate) where applicable.   Data are based on Labour Force Surveys and national information in this dataset is directly collected from the following sources:   ABS - Australian Bureau of Statistics (Australia) Statistics Canada (Canada) INE - Instituto Nacional de Estadísticas (Chile) CBS – Central Bureau of Statistics (Israel) Statistics Bureau (Japan) Statistics Korea (Korea) INEGI - Instituto Nacional de Estadísticas y Geografía (Mexico) Statistics New Zealand (New Zealand) BLS - Bureau of Labor Statistics (the United States) Eurostat (Austria, Belgium, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Luxembourg, the Netherlands, Norway, Poland, Portugal, the Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey and the United Kingdom).
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        The aim of the OECD’s new Skills for Jobs Indicators is to facilitate better adaptation to changing skill needs by making available a database of skill imbalances indicators that is comparable across countries and regularly updated. The Skill Needs Indicators provide an overview of the shortages and surpluses of skills across countries.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        The aim of the OECD’s new Skills for Jobs Indicators is to facilitate better adaptation to changing skill needs by making available a database of skill imbalances indicators that is comparable across countries and regularly updated. The Skill Needs Indicators provide an overview of the shortages and surpluses of skills across countries.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        The aim of the OECD’s new Skills for Jobs Indicators is to facilitate better adaptation to changing skill needs by making available a database of skill imbalances indicators that is comparable across countries and regularly updated. The Skill Needs Indicators provide an overview of the shortages and surpluses of skills across countries.
      • Сентябрь 2017
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 08 ноября, 2017
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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 35 OECD countries for the period 1980-2013/14 and estimates for aggregates for 2014-16. A Social Expenditure Update - 8-page report- can be found under www.oecd.org/social/expenditure.htm 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. This version also includes estimates of net total social spending for 2013 for 34 OECD countries. SOCX aggregated data are described in Adema, W., P. Fron and M. Ladaique (2011) (see Methodology Part II). Sources and methodology for the estimations 2014-2016 are also described here
      • Январь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 23 января, 2019
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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 36 OECD countries for the period 1980-2015/16 and estimates for aggregates for 2017-18. A Social Expenditure Update - 8-page report- can be found under www.oecd.org/social/expenditure.htm 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. This version also includes estimates of net total social spending for 2015 for 35 OECD countries.
      • Январь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 23 января, 2019
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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 35 OECD countries for the period 1980-2013/14 and estimates for aggregates for 2014-16. 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. This version also includes estimates of net total social spending for 2013 for 34 OECD countries.
      • Июнь 2014
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 04 августа, 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.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        The SIGI is built on 21 innovative variables of discriminatory social institutions, which are grouped into 5 sub-indices: Discriminatory Family Code, Restricted Physical Integrity, Son Bias, Restricted Civil Liberties and Restricted Resources and Assets. Each of the SIGI variables is coded between 0, meaning no or very low discrimination, and 1, indicating very high discrimination.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        The SIGI is built on 27 innovative variables measuring discriminatory social institutions, which are grouped into 4 dimensions: discrimination in the family, restricted physical integrity, restricted access to productive and financial resources, and restricted civil liberties.Lower values indicate lower levels of discrimination in social institutions: the SIGI ranges from 0% for no discrimination to 100% for very high discrimination.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 09 апреля, 2019
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        The OECD’s Social Benefit Recipients Database (SOCR) presents, for the first time, comparable information on the number of people receiving cash benefits. SOCR includes data for the main income replacement programmes in the unemployment, social assistance, disability and old-age branches. It currently covers eight years (2007-2014) for most OECD and EU countries
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 09 апреля, 2019
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        A good complement to the number of recipients of social benefits is the number of individuals belonging to population groups that are close to the target of social benefits. The database SOCR includes a number of series providing these reference populations. For example: old-age pensions are mainly targeted on individuals of retirement age, the over 65 population is provided; unemployment benefits go to jobseekers, the number of unemployed (ILO definition) is provided.
      • Июль 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 14 августа, 2018
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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 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 economic activity tables compiled according to the recommendations of System of National Accounts 2008 (SNA 2008). Previous versions of STAN (from 2000) were based on SNA93 statistics. Missing detail is estimated using data from other sources such as results from national industrial surveys/censuses. Time series are extended backwards (to 1970 where possible) using vintage SNA93 or STAN estimates. Many data points in STAN are estimated and are flagged as such; they do not represent official Member countries' submissions.  The current version of STAN is based on the International Standard Industrial Classification of all economic activities, Revision 4 (ISIC Rev. 4). Earlier versions of STAN were based on ISIC Rev.3 and, prior to 2000, ISIC Rev.2 (the latter covering the manufacturing sector only). STAN is updated on a "rolling basis" with new country tables, or updated tables, being made available as soon as they are ready.
      • Ноябрь 2012
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 05 августа, 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.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 04 июня, 2019
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        Recommended uses and limitations of STAN It 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.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        STAN Indicators provides annual indicators related to production and employment structure, labour productivity and labour costs, investment, business research and development expenditures and international trade patterns. Data are presented for OECD countries and cover the time-period 1970-2011, although the time coverage may vary across countries and indicators. Series are provided for a wide range of economic activities (according to an ISIC Rev.4 based hierarchy) compatible with the list in the underlying STAN Database in ISIC Rev. 4. STAN Indicators belong to the STAN family datasets; they are primarily drawn from STAN Database for Structural Analysis (STAN), STAN Bilateral Trade (BTDIxE) and STAN Research & Development Expenditures in Industry (ANBERD). Indicators are compiled to respond to the needs of analysts and researchers interested in measuring economic performance, productivity growth, competitiveness and structural changes. They also complement the OECD publications, Science Technology and Industry Scoreboard and Economic Globalisation Indicators.
      • Декабрь 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 03 декабря, 2018
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        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.
      • Декабрь 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 03 декабря, 2018
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        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.
      • Март 2012
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 04 августа, 2014
        Выбрать
        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.
      • Декабрь 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 03 декабря, 2018
        Выбрать
        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.
      • Декабрь 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 03 декабря, 2018
        Выбрать
        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.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 18 июня, 2019
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        The dataset on Statistical discrepancy (Institutional Investors – Financial Balance Sheets) represents the time series of the dataset on Institutional investors' assets and liabilities (7II) along with those of the dataset on Financial Balance Sheets (720), for the financial instruments and institutional sectors which are in common to these two datasets.  Additionally, for each of the above-mentioned time series, a statistical discrepancy is reported in order to show any possible differences which may exist between the two datasets (7II and 720).  In fact, the dataset on Institutional investors' assets and liabilities (7II) constitutes an attempt to better integrate these data in the framework of the System of National Accounts 2008 (SNA 2008).  However, discrepancies may exist and may, for example, be caused by balancing practices (e.g. when sector and counterpart sector data are reconciled) in the compilation of Financial Balance Sheets at a higher level of aggregation, which may not have been carried through at a lower level of aggregation. Moreover, differences may also be caused by the use of different source data.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 02 июля, 2019
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        Excess capacity is one of the main challenges facing the global steel sector. The OECD Steel making Capacity database contains data on crude steel making capacity by economy and provides researchers and policymakers with an important tool for analyzing steel capacity developments.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        The OECD STRI heterogeneity indices complement the existing STRI's and presents indices of regulatory heterogeneity based on the rich information in the STRI regulatory database. The indices are built from assessing – for each country pair and each measure – whether or not the countries have the same regulation. For each country pair and each sector, the indices reflect the (weighted) share of measures for which the two countries have different regulation.
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 05 июля, 2019
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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).
      • Май 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 13 мая, 2019
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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. Version 1 of the indicator of strictness of employment protection - individual and collective dismissals (regular contracts) - does not incorporate all the data items of version 3 and, in particular, does not incorporate regulation of collective dismissals. You should only use version 1 if you need data for years for which neither version 2 nor 3 are available.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 05 июня, 2019
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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.
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 05 июля, 2019
        Выбрать
        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.
      • Сентябрь 2014
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 04 октября, 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.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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        Student-teacher ratio refers to the average number of students per teacher, while average class size is the average number of students in a classroom.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 16 апреля, 2019
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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.  IndexS - State (state, provincial, regional, cantonal) taxation appliesL - Local (local, municipal) taxation appliesCT - Central government tax net of (central government) tax creditsCTg - Central government tax gross of tax creditsTY - Taxable income for central government tax purposesTYs - Taxable income modified for state government tax purposesTYI - Taxable income modified for local government tax purposes  
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
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        CGTRT = Central govt. tax rates and thresholds   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 dependents. - 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.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
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        Дата обращения к источнику: 05 июня, 2019
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        The subnational government finance dataset presents data on the institutional organisation at local and regional levels as well as on public finance. Financial data cover the general government sector and subnational government subsector (state and local government levels) in the 35 OECD member countries and in the EU. Four main dimensions are presented: expenditure (including investment), revenue, budget balance and debt. The dataset is released as a beta version. Data at country level are derived mainly from the OECD National Accounts harmonised according to the new standards of the System of National Accounts (SNA) 2008, implemented by most OECD countries since December 2014. They are complemented by data from Eurostat, IMF (Australia, Chile), and national statistical institutes for some countries or indicators (in particular, territorial organisation). Data were extracted in February 2017 and are from 2015, unless otherwise specified
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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      • Июнь 2018
        Источник: Organisation for Economic Co-operation and Development
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        Дата обращения к источнику: 04 июня, 2018
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      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
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        Дата обращения к источнику: 02 июля, 2019
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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
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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        Statutory corporate income tax rate - This table shows 'basic' (non-targeted) central, sub-central and combined (statutory) corporate income tax rates. Where a progressive (as opposed to flat) rate structure applies, the top marginal rate is shown.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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        Targeted statutory corporate income tax rate - This table reports central, sub-central and combined corporate income tax rates typically applying for or targeted at 'small (incorporated) business', where such 'targeting' is on the basis of size alone (e.g. number of employees, amount of assets, turnover or taxable income) and not on the basis of expenditures or other targeting criteria. A 'small business corporate tax rate' may be a special statutory corporate tax rate applicable to (all or part of) the taxable income of qualifying 'small' firms (e.g., meeting a turnover, income, or asset test), or an effective corporate tax rate below the basic statutory corporate rate provided through a tax deduction or credit for 'small' firms determined as a percentage of qualifying taxable income (e.g., up to a given threshold). If corporate income is taxed at progressive rates, the rate typically applying for 'small' firms should be reported. Where the central government, or sub-central government, or both, have a lower small business tax rate, the applicable central and sub-central rates are both shown (to enable a combined rate calculation). Thus, for example, where only the sub-central government has a small business rate, the basic central corporate income tax rate is shown in order to compute the combined central and sub-central tax rate on small business (a cross-check with Table II.3 shows whether the central or sub-central rate is basic or not).
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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        SCCIT = Sub-Central Corporate Income Tax   Sub-central corporate income tax rates - This table reports information on sub-central government (statutory) corporate income tax rates in the representative case which is used in Table II.1, which can be based on a representative city or an average of sub-central rates. Countries are grouped according to the determination of the sub-central tax base (the representative rate). Minimum and maximum sub-central rates across states/localities are also reported.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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        Overall statutory tax rates on dividend income- reports effective statutory tax rates on distributions of domestic source income to a resident individual shareholder, taking account of corporate income tax, personal income tax and any type of integration or relief to reduce the effects of double taxation. PIT: Personal Income Tax CIT: Corporate Income Tax CL - Classical system (dividend income is taxed at the shareholder level in the same way as other types of capital income (e.g. interest income) MCL - Modified classical system (dividend income taxed at preferantial rates (e.g. compared to interest income) at the shareholder level. FI - Full imputation (dividend tax credit at shareholder level for underlying corporate profits tax) PI - Partial imputation (dividend tax credit at shareholder level for part of underlying corporate profits tax) PIN - Partial inclusion (a part of received dividends is included as taxable income at the shareholder level) SR - Split rate system (distributed dividends are taxed at higher rates than retained earnings at the corporate level) NST - No shareholder taxation of dividends (no other tax than the tax on corporate profits) CD - Corporate deduction (corporate level deduction, fully or partly, in respect of dividend paid) OTH - Other types of systems
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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        This table reports employee social security contribution rates and related provisions. A representative case is used for those countries where social security provisions vary by locality.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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        This table reports employer social security contribution rates and related provisions (using the representative case for those countries where social security provisions vary by locality). Threshold and maximum contribution amounts are shown in national currencies. Note on aggregation In some social security systems, both flat rate and progressive rate structures apply. Where these apply to the same base (e.g., gross earnings), the elements are aggregated for the purpose of reporting in this table.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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        This table reports self-employed social security contribution rates and related provisions. A representative case is used for those countries where social security provisions vary by locality. Threshold and maximum contribution amounts are shown in national currencies.
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
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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.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
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        Дата обращения к источнику: 21 июня, 2019
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        The term "tax autonomy" captures the freedom sub-central governments (SCG) have over their own taxes.   Tax autonomy data for 2002, 2005 and 2008 is classified into 11 categories and sub-categories and ranges from full taxing power to no taxing power at all. The classification is shown below :   a.1 - The recipient SCG can set the tax rate and any tax reliefs without needing to consult a higher level government. a.2 - The recipient SCG can set the rate and any reliefs after consulting a higher level government. b.1 - The recipient SCG can set the tax rate, and a higher level government does not set upper or lower limits on the rate chosen. b.2 - The recipient SCG can set the tax rate, and a higher level government does set upper and/or lower limits on the rate chosen. c - The recipient SCG can set some tax reliefs (tax allowances and/or tax credits) but not tax rates. d.1 - There is a tax-sharing arrangement in which the SCGs determine the revenue split. d.2 - There is a tax-sharing arrangement in which the revenue split can be changed only with the consent of SCGs. d.3 - There is a tax-sharing arrangement in which the revenue split can be changed unilaterally by a higher level government, but less frequently than once a year. d.4 - There is a tax-sharing arrangement in which the revenue split is determined annually by a higher level government. e - Other cases in which the central government sets the rate and base of the SCG tax. f - None of the above categories a, b, c, d or e applies.   In the data for 1995, there is only one category under each of the headings a and b as follows: a - The recipient SCG can set the tax rate and any tax reliefs. b - The recipient SCG can set the tax rate.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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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.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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      • Май 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 28 мая, 2019
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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.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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        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.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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        This dataset presents internationally comparable data on (full-time) salaries of teachers and school heads in public institutions at pre-primary, primary and general (lower and upper) secondary education. Actual salaries are displayed by level of education, and data on actual salaries of teachers are also available by age and gender. Data also include other statistics related to salaries of teachers.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
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        This dataset presents internationally comparable data on (full-time) salaries of teachers and school heads in public institutions at pre-primary, primary and general (lower and upper) secondary education. Statutory salaries are displayed by level of education, Data also include other statistics related to salaries of teachers.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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        This dataset presents internationally comparable data on teaching and working time of (full-time) teachers in public institutions at pre-primary, primary and general and vocational (lower and upper) secondary education. Data refer to formal statutory requirements and also cover actual teaching time. Teaching and working time are displayed by level of education.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
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        Дата обращения к источнику: 05 июня, 2019
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        Chapter D includes indicators on instruction time, teachers’ working time and teachers’ salaries that not only represent policy levers that can be manipulated, but that also provide context for the quality of instruction and the outcomes of individual learners. It also presents data on the profile of teachers, the levels of government at which decisions concerning education systems are taken, and pathways and gateways to gain access to secondary and tertiary education.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
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        Indicators in Chapter A refer to education and learning outputs and outcomes. They describe educational attainment of different generations, measure the outputs of the education system, and provide context for education policies, including those on lifelong learning.
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
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        Дата обращения к источнику: 15 мая, 2019
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        The data presented here refer to the latest year available. 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. 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). The data presented here show numbers of known species (or assessed) and threatened species with the aim of indicating the state of mammals, birds, freshwater fish, reptiles, amphibians, vascular plants, mosses, lichens and invertebrates.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
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        Дата обращения к источнику: 18 июня, 2019
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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. Seasonal adjustment: For the purpose of presentation of quarterly series, seasonal adjustment is applied using TramoSeats algorithm with 5 regressors: log/level, trading days, Easter, outlier detection, and automatic model identification). Series are log-transformed and decomposed into a trend component. Finally, index is calculated based on a 2007 (2007 = average of 2007 quarters) in order to present movements between the base year and a given quarter.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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        Because of the limited availability of official statistics on national supply-use and input-output tables in recent years – reflecting the fact that these are only typically available at best two or three years after the reference period to which they refer – TiVA indicators for the most recent years, as displayed in this dataset, are estimated using now-casting techniques. The approach (described in more detail in the accompanying methodological note) in essence estimates national input-output tables by projecting relationships observed in the latest TiVA benchmark year (currently 2011) into nowcast years (currently 2012-2014) but constrained to official estimates of gross output and value-added by industry and national accounts main aggregates of demand and trade, and supplemented by bilateral trade statistics, all of which are available throughout the nowcast period. Importantly, the projections of relationships in 2011 into 2012 are determined using a volume approach, to account for possible distortions that might be introduced – by for example differential price movements in imports and domestic production – if projections were made using nominal relationships. These estimates are then reflated into current prices, and simultaneously balanced – consistent with official volume and current price estimates of trade, demand and activity – to arrive at a balanced national input-output table in 2012, in nominal terms as well as in prices of 2011. Estimates for 2013 and 2014 are calculated in the same manner but using, respectively, the 2012 and 2013 relationships as the starting point.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 16 апреля, 2019
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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.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
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        Note: 2017 figures are Preliminary. 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.
      • Сентябрь 2018
        Источник: Organisation for Economic Co-operation and Development
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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.
      • Май 2019
        Источник: Organisation for Economic Co-operation and Development
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        Дата обращения к источнику: 28 мая, 2019
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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.
      • Май 2019
        Источник: Organisation for Economic Co-operation and Development
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        Total Receipts, Net: in addition to Official Development Assistance, this heading includes in particular: other official bilateral transactions which are not concessional or which, even though they have concessional elements, are primarily trade facilitating in character (i.e., "Other Official Flows''); changes in bilateral long-term assets of the private non-monetary and monetary sectors, in particular guaranteed export credits, private direct investment, portfolio investment and, to the extent they are not covered in the preceding headings, loans by private banks. Flows from the multilateral sector which are not classified as concessional are also included here.
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
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        Дата обращения к источнику: 02 июля, 2019
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        These tables are a complement to the report Agricultural Policies in OECD Countries: Monitoring and Evaluation 2010. They comprise the summary of agricultural support estimates for OECD countries.
      • Декабрь 2018
        Источник: Organisation for Economic Co-operation and Development
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        Дата обращения к источнику: 03 декабря, 2018
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        This table presents export/import information by detailed activity sectors (ISIC Rev.4)
      • Декабрь 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 03 декабря, 2018
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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.
      • Май 2017
        Источник: Organisation for Economic Co-operation and Development
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        Дата обращения к источнику: 23 июня, 2017
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        This dataset presents data by export intensity, that is the share of exports on total turnover.
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 14 марта, 2019
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        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.
      • Декабрь 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 03 декабря, 2018
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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).
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 13 марта, 2019
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        This table presents export/import information by enterprise size class and partner country.
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 02 июля, 2019
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        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.
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 02 июля, 2019
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        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.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 05 июня, 2019
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        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.
      • Декабрь 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 03 декабря, 2018
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        This dataset shows imports/exports by type of trader that is exporter only, importer only or both importer and exporter (Two-way trader).
      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 02 июля, 2019
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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.
      • Декабрь 2016
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 07 августа, 2017
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        The TiVA database contains a range of indicators measuring the value added content of international trade flows and final demand. The indicators are derived from the 2016 version of OECD's Inter-Country Input-Output (ICIO) Database.  The ICIO has been constructed from various national and international data sources all drawn together and balanced under constraints based on official (SNA93) National Accounts by economic activity and National Accounts main aggregates.  Underlying sources used are notably:  • National supply and use tables (SUTs)  • National and harmonised Input-Output Tables • Bilateral trade in goods by industry and end-use category (BTDIxE) and  • Bilateral trade in services.  Compared to the old versions of the TiVA database, this current version includes two more countries, Morocco and Peru. The data are presented for all years from 1995 to 2011. The industry breakdown remains the same. 
      • Декабрь 2016
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 21 августа, 2017
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        The Trade in Value Added (TiVA) database consists of a set of measures that aim to provide better insights into global production networks and supply chains than is possible with conventional trade statistics. See TiVA.  The Origin of value added in final demandpresented here, is derived from the latest version of OECD’s Inter-Country Input-Output (ICIO) database and provides estimates of final demand in country c for industry i final goods and services, broken down by the value added originating from source industry j in source country p.  In other words, it reveals how the value of final demand goods and services consumed within a country is an accumulation of value generated by many industries in many countries.  For a description of the method used for calculating these estimates, using the ICIO, see the document TiVA indicators definitions hereafter.  Domestic value added origin is shown where source country p = c and, for convenience, also represented by source country = “DXD: Domestic”. From this data cube, a range of final demand-based measures can be derived including those in the main TiVA indicators database such as:  • Domestic value added embodied in foreign final demand, FFD_DVA and related partner shares FFD_DVApSH.  • Foreign value added embodied in domestic final demand, DFD_FVA and related partner shares DFD_FVApSH.
      • Декабрь 2016
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 08 августа, 2017
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        The Trade in Value Added (TiVA) database consists of a set of measures that aim to provide better insights into global production networks and supply chains than is possible with conventional trade statistics. See TiVA.  The Origin of value added in gross exportspresented here, is derived from the latest version of OECD’s Inter-Country Input-Output (ICIO) database and provides estimates of gross exports of goods and services by exporting industry i in country c, broken down by the value added originating from source industry j in source country/region p.  In other words, it reveals how the value of a country’s gross exports of intermediate and final products is an accumulation of value generated by many industries in many countries.  For a description of the method used for calculating these estimates, using the ICIO, see the document TiVA indicators definitions hereafter. Domestic value added origin is shown where source country p = c and, for convenience, also represented by source country = “DXD: Domestic”. From this data cube, a range of gross exports-based measures can be derived including those in the main TiVA indicators database such as:  • Total gross exports by industry, EXGR (c,i): set source country p = World, source industry j = CTOTAL. • Total domestic and foreign value added content of gross exports by industry, EXGR_DVA (c,i) and EXGR_FVA (c,i). For EXGR_DVA, set source country p = DXD “Domestic”, source industry j = CTOTAL. • Shares of EXGR_DVA and EXGR_FVA in relation to EXGR such as EXGR_DVASH (c,i), EXGR_TDVAIND (c,i), and the “GVC backward linkage” indicators EXGR_FVASH (c,i) and EXGR_TFVAIND (c,i). • “GVC forward linkage” indicators such as EXGR_DVAFXSH. • Service value added contents of gross exports EXGR_SERV_DVASH(c,i) and EXGR_SERV_FVASH(c,i). Set source industry j = “C45T95: Total Services including Construction activities”. For regions, exports exclude intra-regional trade and intra-regional value added flows are considered as domestic value added. For example, for exporting region EU28, exports are to non-EU28 and source country “DXD : domestic” includes value added originating from Member States. Note that the same value added originating from industry j in country p can be present in the gross exports of more than one country c (as embodied value added, from upstream production, may cross national borders many times). In general, therefore, these estimates should be viewed from the perspective of the exporting country c and exporting industry i. However, for indicators of “GVC forward linkages” a source country p, source industry jperspective is required.
      • Март 2017
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 23 августа, 2017
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        The Trade in Value Added (TiVA) database consists of a set of measures that aim to provide better insights into global production networks and supply chains than is possible with conventional trade statistics. See TiVA. The Origin of value added in gross imports presented here, is derived from the latest version of OECD’s Inter-Country Input-Output (ICIO) database and provides estimates of gross imports by country c of goods and services from industry i in partner country/region p broken down by value added originating from source country/region s. In other words, the four dimensions link the imports of country c to the value added from source country s embodied in the exports of industry i in the exporting country p - thus revealing how the value of a country’s gross imports of intermediate and final products from a particular partner is an accumulation of value generated by many countries.
      • Июль 2014
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Pallavi S
        Дата обращения к источнику: 05 августа, 2014
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        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.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 18 июня, 2019
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        Values are expressed in United States dollars (USD) and refer to declared transaction values. Imports are reported c.i.f. and exports are reported f.o.b. with the exception of Australia, Canada, Mexico, Slovak Republic and United States where imports are reported f.o.b. United States exports are reported f.a.s. Data published are expressed as monthly averages. Quarterly and annual data are calculated as averages of monthly figures. The option chosen by OECD is to convert exchange rates for periods prior to entry into European Monetary Union (EMU), i.e. prior to 1999 for all members apart from Greece, which acceded in 2001, from the former national currency exchange rate using the appropriate irrevocable exchange rate. Such a conversion facilitates comparisons over time within a country and also preserves the historical evolution (i.e. growth rates). However, pre-EMU euro rates are notional units and are not always suitable to form area aggregates or for cross country comparisons. For further details, see The Statistics Brief Number 2, February 2002.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 30 апреля, 2019
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        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.
      • Июль 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 08 августа, 2018
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        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.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 16 апреля, 2019
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      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 05 июня, 2019
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        Mexico: "Total urban wastewater treatment" include some plants whose treatment type is not identified Netherlands: Other waste water treatment, design capacity BOD 1000 kg O2/day: the design capacity is expressed in Total Oxygen Demand (1000 kg O2/day, not BOD). This value is based on pollution equivalents of 136 grams O2 per day.
      • Декабрь 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 11 декабря, 2018
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        This data set is a combination of three tables, 1. Good Transport- Inland freight 2. Passenger transport 3. Transport Safety- Road injury accidents- Road CausalitiesThe geographical area covered is the ITF member countries.The International Transport Forum collects data on transport statistics on annual basis from all its Member countries. Data are collected from Transport Ministries, statistical offices and other institution designated as official data source.TEU (Twenty-foot Equivalent Unit): a statistical unit based on an ISO container of 20 foot length (6.10 m) to provide a standardised measure of containers of various capacities and for describing the capacity of container ships or terminals. one 20 Foot ISO container equals 1 TEU.  
    • U
      • Декабрь 2016
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 10 июня, 2019
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      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        The Uganda Gender, Institutions and Development Database (Uganda-GID) provides researchers and policymakers with key data at the national and sub-national levels on gender-based discrimination in social institutions. This data helps analyse women’s empowerment and understand gender gaps in other key areas of development. Covering 5 regions and 10 sub-regions, the Uganda-GID contains comprehensive information on social norms, attitudes and both perceived and actual practices that discriminate against women and girls.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        The Uganda-SIGI is a composite indicator measuring discriminatory social institutions. It is built on 64 innovative variables which are grouped into 5 sub-indices: Discriminatory Family Code, Restricted Physical Integrity, Son Preference, Restricted Resources and Assets and Restricted Civil Liberties. The Uganda-SIGI and its soub-indices range from 0, for no discrimination, to 1, for very high discrimination.
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 19 июня, 2019
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        This dataset 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).
      • Июнь 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 22 июня, 2019
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        Early Estimates of Quarterly Unit Labour Cost (ULC) indicators for the total economy provide current edge data on ULCs and their components labour productivity and labour compensation per employed person.  Recent and more longer terms trends in productivity and competitiveness on the total economy level and by sector or activity can be found in the OECD Compendium of Productivity Indicators.Data of quarterly GDP, labour compensation and employment are sourced from the OECD Quarterly National Accounts and the Main Economic Indicators Databases.  Early Estimates of Quarterly ULCs are available for all OECD member countries (except Chile, Iceland, Mexico), as well as for the zone aggregates Euro area and OECD Total. Unit labour costs (ULCs) measure the average cost of labour per unit of output. They are calculated as the ratio of total labour costs to real output. Different from the estimates of annual ULC above, the Early Estimates of Quarterly ULC use employment and not hours worked as measure of labour input (see below "Other aspects, Recommended uses and limitations"). Quarterly ULCs can be decomposed into the components labour compensation per employee and output per person employed (employment-based labour productivity). The OECD estimates of total labour costs adjust for labour compensation of self-employed persons Every effort has been made to ensure that data are comparable across countries. The adjustment for the self-employed assumes that labour compensation per person is equivalent for the self-employed and employees. This assumption may be more or less valid across different countries and economic activities.  EEQ ULCs are also fully compatible with the ULC series published by the ECB which provides ULC series for 21 EU OECD member countries and Euro area. Those for nine Non-EU member OECD countries are compiled by the OECD following a methodology that is fully consistent with that used by the ECB.
      • Декабрь 2018
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 24 апреля, 2019
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        Uranium is the raw material used to produce fuel for long-lived nuclear power facilities, necessary for the generation of significant amounts of baseload low-carbon electricity for decades to come. Although a valuable commodity, declining market prices for uranium in recent years, driven by uncertainties concerning the evolution in the use of nuclear power, have led to significant production cutbacks and the postponement of mine development plans in a number of countries and to some questions being raised about future uranium supply.
    • V
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        In the OECD Entrepreneurship Financing Database venture capital is made up of the sum of early stage (including pre-seed, seed, start-up and other early stage) and later stage venture capital. As there are no harmonised definitions of venture capital stages across venture capital associations and other data providers, original data have been re-aggregated to fit the OECD classification of venture capital by stages. Korea, New Zealand, the Russian Federation and South Africa do not provide breakdowns of venture capital by stage that would allow meaningful international comparisons.
    • W
      • Март 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 01 апреля, 2019
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        This dataset provides information on the level of public equipment installed by countries to managed and abate water pollution. It shows the percentage of national population connected to "public" sewerage networks and related treatment facilities, and the percentage of national population connected to "public" wastewater treatment plants, and the degree of treatment. Connected here means actually connected to a wastewater plants through a public sewage network. Individual private treatment facilities such as septic tanks are not covered here. When analysing these data, it should be kept in mind that the optimal connection rate is not necessarily 100 per cent; it may vary among countries and depends on geographical features and on the spatial distribution of habitats. The interpretation of those data should take into account some variations in countries' definitions, as reflected in metadata.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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      • Июль 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 02 июля, 2019
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        While much of the comparative evidence on inequalities that is currently available refers to household income, wealth is a critical dimension of households’ economic well-being. How wealth is distributed is important for equity and inter-generational mobility, but also for the stability of the economic system and for its resilience to shocks. While the lack of comparative evidence in this field reflects the absence of an agreed standard that statistical offices could use when collecting this information, this gap has been addressed by the OECD with the release in 2013 of a set of statistical guidelines in this field. In 2013, the OECD issued a set of ‘Guidelines’ for micro statistics on household wealth (OECD, 2013) and an increasing number of countries have engaged in the collection of micro statistics in this field (European Central Bank, 2013). Building on these initiatives as well as others, such as the Luxembourg Wealth Study (Sierminska et al, 2006) which have informed previous OECD analysis (Jantii et al., 2008), the OECD has now collected a new set of data on the distribution of household wealth for 18 OECD countries, based on the set of conventions and classifications proposed in the 2013 OECD Guidelines.
      • Апрель 2019
        Источник: Organisation for Economic Co-operation and Development
        Загружен: Knoema
        Дата обращения к источнику: 12 апреля, 2019
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        World Indicators of Skills for Employment (WISE) provide a comprehensive system of information relating to skills development. WISE presents countries with data upon which they can design skills policies and programs and monitor their impact on key outcomes, including responsiveness to current and emerging patterns of labour market demand, employability, productivity, health status, gender equity and lifelong learning.The database covers the period from 1990 to the present and consists of five inter-related domains of indicators:Contextual factors drive both the supply of and demand for skills.Skill acquisition covers investments in skills, the stock of human capital and its distribution.Skill requirements measure the demand for skills arising in the labour market.The degree of matching captures how well skills obtained through education and training correspond to the skills required in the labour market.Outcomes reflect the impact of skills on economic performance and employment and social outcomes.