حدث خطأ. التفاصيل إخفاء
لديك صفحات غير محفوظة. استعادة إلغاء

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.

All datasets:  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
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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 :
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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 :
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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 :
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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 :
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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 :
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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 :
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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 :
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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 :
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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 :
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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 :
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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 :
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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 :
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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 :
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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 :
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 29 نيسان, 2019
      تحديد مجموعة بيانات
      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 :
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 آب, 2019
      تحديد مجموعة بيانات
      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.
    • حزيران 2017
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 01 آب, 2019
      تحديد مجموعة بيانات
      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. 
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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 :
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      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
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 04 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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%
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 تموز, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      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
    • آذار 2015
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 10 آب, 2017
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
    • تموز 2015
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Denis Chernyshev
      تم الوصول في: 03 كانون الأول, 2015
      تحديد مجموعة بيانات
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 09 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 25 تموز, 2019
      تحديد مجموعة بيانات
      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 2017  
    • تموز 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 أيلول, 2018
      تحديد مجموعة بيانات
      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”.
    • آذار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 آذار, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • حزيران 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 18 حزيران, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 29 تموز, 2019
      تحديد مجموعة بيانات
      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).
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 10 تشرين الأول, 2019
      تحديد مجموعة بيانات
      This dataset presents the average number of students in a class by type of institution.
    • حزيران 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 حزيران, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 21 حزيران, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 14 تموز, 2019
      تحديد مجموعة بيانات
  • B
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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) .
    • شباط 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 01 آذار, 2019
      تحديد مجموعة بيانات
      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.
    • أيار 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 31 أيار, 2018
      تحديد مجموعة بيانات
      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
    • كانون الأول 2017
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 18 كانون الأول, 2017
      تحديد مجموعة بيانات
      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.
    • أيار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 17 أيلول, 2019
      تحديد مجموعة بيانات
      STAN Bilateral Trade Database by Industry and End-use category (BTDIxE) provides values of imports and exports (as well as re-imports and re-exports) of goods broken down by industrial sectors and by end-use categories. BTDIxE was designed to extend the old 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 of goods from 1990 to the latest available year, i.e. 2018; 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; and major African and Latin American nations.  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". The partner "Total foreign trade" corresponds to the flows with partner "World" excluding intra-country flows. Trade flows are divided into economic activities based on the Revision 4 of ISIC and nine end-use categories including capital goods, intermediate goods and household consumption.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 22 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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 .
    • حزيران 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 28 آب, 2018
      تحديد مجموعة بيانات
    • حزيران 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 28 آب, 2018
      تحديد مجموعة بيانات
    • آذار 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 01 آب, 2019
      تحديد مجموعة بيانات
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 تشرين الأول, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
    • أيار 2017
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 حزيران, 2017
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 14 تموز, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
    • أيار 2017
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 20 حزيران, 2017
      تحديد مجموعة بيانات
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 04 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • أيار 2017
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 09 حزيران, 2017
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
    • أيار 2017
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 13 حزيران, 2017
      تحديد مجموعة بيانات
      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.
    • أيار 2017
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 21 حزيران, 2017
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 29 نيسان, 2019
      تحديد مجموعة بيانات
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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
    • أيار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 06 أيار, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
    • كانون الأول 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 كانون الأول, 2018
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
    • شباط 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 28 شباط, 2019
      تحديد مجموعة بيانات
      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.
    • كانون الأول 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 كانون الأول, 2018
      تحديد مجموعة بيانات
      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.   
    • أيلول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 24 أيلول, 2019
      تحديد مجموعة بيانات
      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.
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 13 آب, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • أيلول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 24 أيلول, 2019
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
    • نيسان 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 21 أيار, 2018
      تحديد مجموعة بيانات
      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
    • تموز 2016
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 29 تموز, 2016
      تحديد مجموعة بيانات
      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
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 13 آب, 2019
      تحديد مجموعة بيانات
      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
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
    • تشرين الأول 2017
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 30 تشرين الثاني, 2017
      تحديد مجموعة بيانات
      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
  • E
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 26 آب, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 29 نيسان, 2019
      تحديد مجموعة بيانات
      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 EcoOutlook@oecd.org.
    • أيار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 31 أيار, 2019
      تحديد مجموعة بيانات
      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 15 May 2019.   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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 29 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 29 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 29 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 29 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
    • كانون الأول 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 كانون الأول, 2018
      تحديد مجموعة بيانات
      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).
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 06 آب, 2019
      تحديد مجموعة بيانات
      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.
    • أيلول 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 تشرين الأول, 2018
      تحديد مجموعة بيانات
      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).
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 04 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 29 نيسان, 2019
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      This dataset presents the average number of teachers by sex and age.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      This dataset presents the average number of teachers by sex and type of institution.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 26 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 10 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 19 آب, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 06 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • أيلول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 24 أيلول, 2019
      تحديد مجموعة بيانات
      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.
    • حزيران 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 حزيران, 2019
      تحديد مجموعة بيانات
      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.  
    • أيلول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 17 أيلول, 2019
      تحديد مجموعة بيانات
      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.
    • أيلول 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 22 آذار, 2019
      تحديد مجموعة بيانات
      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.  
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 22 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 23 تموز, 2019
      تحديد مجموعة بيانات
      Employment, participation rates: population aged 15-64; Unemployment rate: active population aged 15-64.   Rates as defined by the International Labour Organization.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 18 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 14 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • أيار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 21 أيار, 2019
      تحديد مجموعة بيانات
    • أيلول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 17 أيلول, 2019
      تحديد مجموعة بيانات
      Number of students enrolled in different education programmes by age and sex.
    • أيار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 21 أيار, 2019
      تحديد مجموعة بيانات
      This dataset presents the number of students enrolled in different education programmes by field and sex.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      This indicator examines the share of students by gender, programme orientation and mode of study over the total number of students.
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 06 آب, 2019
      تحديد مجموعة بيانات
      Number of students enrolled in different education programmes by type of institution and sex.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • آذار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 آذار, 2019
      تحديد مجموعة بيانات
      This dataset presents the number of students enrolled in different education programmes by country of origin and sex.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      Enrolment rate per age is the percentage of students enrolled in each type of institution over the total of students
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
    • آب 2014
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 أيلول, 2014
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2013
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 04 آب, 2014
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 06 آب, 2019
      تحديد مجموعة بيانات
      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.
    • كانون الأول 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 26 كانون الأول, 2018
      تحديد مجموعة بيانات
      National currencies are converted in United States dollars (USD) using IMF monthly average conversion rates.
    • أيلول 2017
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 14 تشرين الثاني, 2017
      تحديد مجموعة بيانات
    • أيلول 2014
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 04 تشرين الأول, 2014
      تحديد مجموعة بيانات
      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.
    • تشرين الثاني 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 01 آب, 2019
      تحديد مجموعة بيانات
      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.
    • أيار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 28 أيار, 2019
      تحديد مجموعة بيانات
      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
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 آب, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 17 نيسان, 2019
      تحديد مجموعة بيانات
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 20 آب, 2019
      تحديد مجموعة بيانات
      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.
    • آذار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 آذار, 2019
      تحديد مجموعة بيانات
    • شباط 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 26 حزيران, 2018
      تحديد مجموعة بيانات
      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
    • حزيران 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 25 تموز, 2018
      تحديد مجموعة بيانات
    • آذار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 آذار, 2019
      تحديد مجموعة بيانات
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 06 آب, 2019
      تحديد مجموعة بيانات
      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.
    • آذار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 آذار, 2019
      تحديد مجموعة بيانات
    • حزيران 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2018
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 30 نيسان, 2019
      تحديد مجموعة بيانات
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 14 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 10 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 14 تموز, 2019
      تحديد مجموعة بيانات
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • أيلول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 24 أيلول, 2019
      تحديد مجموعة بيانات
      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)
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 10 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • حزيران 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 04 حزيران, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 10 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 09 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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).
    • آذار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 13 آذار, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 09 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • آذار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 14 آذار, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 10 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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).
    • تموز 2014
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 30 آب, 2017
      تحديد مجموعة بيانات
      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).
    • أيلول 2014
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 04 تشرين الأول, 2014
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • كانون الأول 2014
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 11 تشرين الثاني, 2016
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      SWITZERLAND: GENERAL METADATA Data documentation General notes The fiscal year in Switzerland coincides with the calendar year.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      COLOMBIA: GENERAL METADATA Data documentation General notes Colombia’s fiscal year matches the calendar year.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      HUNGARY: GENERAL METADATA Data documentation General notes The fiscal year in Hungary coincides with the calendar year.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 14 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 14 تموز, 2019
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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%.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      KOREA: GENERAL METADATA Data documentation General notes The fiscal year in Korea coincides with the calendar year.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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)
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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 2007-2015. 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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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).
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 14 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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).
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 14 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      TURKEY: GENERAL METADATA Data documentation General notes The fiscal year in Turkey coincides with the calendar year.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 13 آب, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • آذار 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 كانون الأول, 2018
      تحديد مجموعة بيانات
      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
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 13 آب, 2019
      تحديد مجموعة بيانات
      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.
    • أيار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 أيار, 2019
      تحديد مجموعة بيانات
      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.
    • آذار 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 21 أيار, 2018
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 29 نيسان, 2019
      تحديد مجموعة بيانات
      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
    • أيلول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 24 أيلول, 2019
      تحديد مجموعة بيانات
      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).
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • آذار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 17 حزيران, 2019
      تحديد مجموعة بيانات
      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).
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      This part contains general information on number of insurance companies and employees within the sector.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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
    • أيلول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 24 أيلول, 2019
      تحديد مجموعة بيانات
      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.
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 19 آب, 2019
      تحديد مجموعة بيانات
      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.
    • أيلول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 24 أيلول, 2019
      تحديد مجموعة بيانات
    • آذار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 آذار, 2019
      تحديد مجموعة بيانات
      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.
    • شباط 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 27 شباط, 2019
      تحديد مجموعة بيانات
      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.
    • كانون الأول 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 كانون الأول, 2018
      تحديد مجموعة بيانات
      Geolocation of urban agglomerations in West Africa.
    • كانون الثاني 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • أيار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 28 حزيران, 2019
      تحديد مجموعة بيانات
      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
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 29 نيسان, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • شباط 2016
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 18 آذار, 2016
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      This dataset contains the number of people who graduated from an education programme by field and sex.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 10 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 14 تموز, 2019
      تحديد مجموعة بيانات
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 29 نيسان, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 تموز, 2019
      تحديد مجموعة بيانات
      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).
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 تموز, 2019
      تحديد مجموعة بيانات
      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).
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
    • أيلول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 17 أيلول, 2019
      تحديد مجموعة بيانات
      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.
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 آب, 2019
      تحديد مجموعة بيانات
      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
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 13 آب, 2019
      تحديد مجموعة بيانات
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 13 آب, 2019
      تحديد مجموعة بيانات
    • تشرين الثاني 2017
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 13 تشرين الثاني, 2017
      تحديد مجموعة بيانات
      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.
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 06 آب, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 09 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 06 آب, 2019
      تحديد مجموعة بيانات
      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.
    • حزيران 2010
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تحديد مجموعة بيانات
      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.
    • حزيران 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 آب, 2019
      تحديد مجموعة بيانات
      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
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      This indicator shows the working hours needed to escape poverty for a jobless family claiming Guaranteed Minimum Income benefits.
    • حزيران 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 21 حزيران, 2019
      تحديد مجموعة بيانات
      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
    • تموز 2014
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 19 أيلول, 2014
      تحديد مجموعة بيانات
      Human Resource Costs
  • I
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 نيسان, 2019
      تحديد مجموعة بيانات
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 22 آب, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • كانون الثاني 2008
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 22 أيلول, 2014
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • كانون الأول 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 كانون الأول, 2018
      تحديد مجموعة بيانات
      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.
    • آذار 2016
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الثاني, 2017
      تحديد مجموعة بيانات
      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.
    • كانون الأول 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 كانون الأول, 2018
      تحديد مجموعة بيانات
      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.
    • كانون الأول 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 كانون الأول, 2018
      تحديد مجموعة بيانات
      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.
    • كانون الأول 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 كانون الأول, 2018
      تحديد مجموعة بيانات
      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.
    • آذار 2016
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الثاني, 2017
      تحديد مجموعة بيانات
      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.
    • كانون الأول 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 كانون الأول, 2018
      تحديد مجموعة بيانات
      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).
    • كانون الأول 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 كانون الأول, 2018
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2014
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 04 آب, 2014
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
    • تموز 2015
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2015
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 06 آب, 2019
      تحديد مجموعة بيانات
      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
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 06 تموز, 2019
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
    • حزيران 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 21 حزيران, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
      http://www.oecd.org/els/soc/IDD-Metadata.pdf
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 10 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • حزيران 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 18 حزيران, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • أيار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 28 أيار, 2019
      تحديد مجموعة بيانات
      These data are part of a larger database, hosted on a different website, which includes both quantitative and qualitative data, as well as graphs.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 10 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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).
    • أيلول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 17 أيلول, 2019
      تحديد مجموعة بيانات
      This data deals with premiums written by classes of non-life insurance for the business written in the reporting country.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 10 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 09 تشرين الأول, 2019
      تحديد مجموعة بيانات
    • تشرين الأول 2017
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 27 تموز, 2018
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 14 تموز, 2019
      تحديد مجموعة بيانات
      This dataset contains the number of people who graduated from an education programme by country of origin and sex.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      This indicator reports the percentage of students of each country of origin over the total of international students.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      This dataset presents official international trade statistics in fisheries products, directly sourced from the UN Comtrade Database.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.  
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 18 تموز, 2019
      تحديد مجموعة بيانات
      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
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 05 تموز, 2019
      تحديد مجموعة بيانات
      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).
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
      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).
    • أيار 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 28 أيار, 2019
      تحديد مجموعة بيانات
      This table contains figures on the activity of affiliates under foreign control by industry according to the International Standard Industrial Classification (ISIC Revision 3).
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
      This table contains figures on affiliates under foreign control by investing country in the total manufacturing, total services and total business enterprise sectors.
    • أيلول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 24 أيلول, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 14 تموز, 2019
      تحديد مجموعة بيانات
    • تموز 2014
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 04 آب, 2014
      تحديد مجموعة بيانات
      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
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 أيلول, 2019
      تحديد مجموعة بيانات
      OECD calculation based on the survey of Adults Skills (PIAAC) (2012).Note : Jobs are at Risk of Automation if the likelihood of their job being automated is at-least 70%. Jobs at Risk of Significant change are those with the likelihood of their job being automated estimated at between 50% to 70%.Data for Belgium correspond to Flanders and data for the United Kingdom to England and North Ireland.
  • K
    • كانون الأول 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 كانون الأول, 2018
      تحديد مجموعة بيانات
      Benefit Generosity, Income Adequacy, Work Incentives.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
  • L
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 02 تموز, 2019
      تحديد مجموعة بيانات
      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
    • حزيران 2014
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 04 آب, 2014
      تحديد مجموعة بيانات
      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.
    • آب 2017
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 09 كانون الثاني, 2018
      تحديد مجموعة بيانات
      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).
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 نيسان, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
    • أيلول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 24 أيلول, 2019
      تحديد مجموعة بيانات
      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.
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 آب, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 06 تموز, 2019
      تحديد مجموعة بيانات
      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).
    • آب 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 13 آب, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 06 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • كانون الأول 2018
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 03 كانون الأول, 2018
      تحديد مجموعة بيانات
      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
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 10 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
      This dataset contains the number of Management personnel and teacher aides in educational institutions by sex and intensity.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 15 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 12 نيسان, 2019
      تحديد مجموعة بيانات
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 23 تموز, 2019
      تحديد مجموعة بيانات
      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.
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 09 تموز, 2019
      تحديد مجموعة بيانات
      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).
    • كانون الثاني 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 06 آذار, 2019
      تحديد مجموعة بيانات
      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).
    • تموز 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 14 تموز, 2019
      تحديد مجموعة بيانات
    • أيلول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 17 أيلول, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • نيسان 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 16 نيسان, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema
      تم الوصول في: 08 تشرين الأول, 2019
      تحديد مجموعة بيانات
      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.
    • تشرين الأول 2019
      المصدر: Organisation for Economic Co-operation and Development
      تم التحميل بواسطة: Knoema