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Organisation for Economic Co-operation and Development

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

Todos os conjuntos de dados:  2 A B C D E F G H I K L M N O P Q R S T U W
  • 2
    • junho 2017
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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      This dataset and predefined summary tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2017, which monitors agricultural policy developments in 35 OECD member countries, 6 non-OECD EU member states and 11 emerging economies: Brazil, China, Colombia, Costa Rica, Indonesia, Kazakhstan, Russia, the Philippines, South Africa, Ukraine and Viet Nam. The OECD uses a comprehensive system for measuring and classifying support to agriculture - the Producer and Consumer Support Estimates (PSEs and CSEs) and related indicators. They provide insight into the increasingly complex nature of agricultural policy and serve as a basis for OECD’s work on agricultural policies. 
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      Databasepublished : June 2018This dataset and predefined summary tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2018, which monitors agricultural policy developments in 35 OECD member countries, 6 non-OECD EU member states and 10 emerging economies: Brazil, China, Colombia, Costa Rica, Kazakhstan, Russia, the Philippines, South Africa, Ukraine and Viet Nam.The OECD uses a comprehensive system for measuring and classifying support to agriculture - the Producer and Consumer Support Estimates (PSEs and CSEs) and related indicators. They provide insight into the increasingly complex nature of agricultural policy and serve as a basis for OECD’s work on agricultural policies. More detailed data by country and documentation can be found in the full dataset (Excel Format) available at :
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 16 abril, 2019
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      Databasepublished : June 2018This dataset and predefined summary tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2018, which monitors agricultural policy developments in 35 OECD member countries, 6 non-OECD EU member states and 10 emerging economies: Brazil, China, Colombia, Costa Rica, Kazakhstan, Russia, the Philippines, South Africa, Ukraine and Viet Nam.The OECD uses a comprehensive system for measuring and classifying support to agriculture - the Producer and Consumer Support Estimates (PSEs and CSEs) and related indicators. They provide insight into the increasingly complex nature of agricultural policy and serve as a basis for OECD’s work on agricultural policies. More detailed data by country and documentation can be found in the full dataset (Excel Format) available at :
  • A
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 16 abril, 2019
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    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      The gross nutrient balances (N and P) are calculated as the difference between the total quantity of nutrient inputs entering an agricultural system (mainly fertilizers, livestock manure), and the quantity of nutrient outputs leaving the system (mainly uptake of nutrients by crops and grassland). Gross nutrient balances are expressed in tonnes of nutrient surplus (when positive) or deficit (when negative). This calculation can be used as a proxy to reveal the status of environmental pressures, such as declining soil fertility in the case of a nutrient deficit, or for a nutrient surplus the risk of polluting soil, water and air. The nutrient balance indicator is also expressed in terms of kilogrammes of nutrient surplus per hectare of agricultural land to facilitate the comparison of the relative intensity of nutrients in agricultural systems between countries.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 09 abril, 2019
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      commitment is a firm written obligation by a government or official agency, backed by the appropriation or availability of the necessary funds, to provide resources of a specified amount under specified financial terms and conditions and for specified purposes for the benefit of a recipient country or a multilateral agency. Members unable to comply with this definition should explain the definition that they use. -- Commitments are considered to be made at the date a loan or grant agreement is signed or the obligation is otherwise made known to the recipient (e.g. in the case of budgetary allocations to overseas territories, the final vote of the budget should be taken as the date of commitment). For certain special expenditures, e.g. emergency aid, the date of disbursement may be taken as the date of commitment. -- Bilateral commitments comprise new commitments and additions to earlier commitments, excluding any commitments cancelled during the same year. Cancellations and reductions in the year reported on of commitments made in earlier years are reported in the CRS, but not in the DAC questionnaire. -- In contrast to bilateral commitments, commitments of capital subscriptions, grants and loans to multilateral agencies should show the sum of amounts which are expected to be disbursed before the end of the next year and amounts disbursed in the year reported on but not previously reported as a commitment. For capital subscriptions in the form of notes payable at sight, enter the expected amount of deposits of such notes as the amount committed.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 02 julho, 2019
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      Destination of Official Development Assistance Disbursements. Geographical breakdown by donor, recipient and for some types of aid (e.g. grant, loan, technical co-operation) on a disbursement basis (i.e. actual expenditures). The data cover flows from bilateral and multilateral donors which focus on flows from DAC member countries and the EU Institutions.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      Residential Property Prices Indices (RPPIs) – also named House price indices (HPIs), are index numbers that measure the prices of residential properties over time. RPPIs are key statistics not only for citizens and households across the world, but also for economic and monetary policy makers. They can help, for example, to monitor potential macroeconomic imbalances and the risk exposure of the household and financial sectors. This dataset covers the 34 OECD member countries and some non-member countries. In addition to the nominal RPPIs it contains information on real house prices, rental prices and the ratios of nominal prices to rents and to disposable household income per capita. This dataset contains quarterly statistics for each country. House prices differ widely across OECD countries, both with respect to recent changes and to valuation levels. The OECD has identified one main nominal index for each country that covers the prices for the sale of newly-built and existing dwellings. The datasets “Analytical house price indicators” and “Residential Property Price Indices (RPPIs) – Headline Indicators” refer to the same price indices for all countries apart from Brazil, Canada, China, the United States and the Euro area. These differences are further documented in country-specific metadata. For the United States, the series used in “Analytical house price indicators” is included in the dataset called “Residential Property Price Indices (RPPIs) – Complete database”, but is not the headline indicator. For all other countries, non-seasonally adjusted price indices in both datasets are identical in the period in which they overlap. This research dataset provides extended time series coverage for many countries. The objective is to provide information on the long term trend of house prices and develop indicators which can be used to help track and analyse macroeconomic developments and risks. The extended data supplement the OECD RPPI data with historical data from a variety of sources, including other international organisations, central banks and national statistical offices. The methodological basis on the historical data and the types of geographical areas and dwellings they cover can differ from those used in the OECD RPPI data. The database contains a number of additional series. Real house prices are given by the ratio of seasonally adjusted nominal house prices to the seasonally adjusted consumers’ expenditure deflator in each country, from the OECD national accounts database. This provides information on how nominal house prices have changed over time relative to prices in the general economy. The rental prices come from the OECD Main Economic Indicators database and refer to Consumer Price Indices (CPIs) for Actual rentals for housing (COICOP 04.1). If this indicator is missing for a country, another indicator is chosen. The chosen indicator are usually those corresponding to the CPI aggregate for Housing including Actual rentals for housing (COICOP 04.1), imputed rentals for housing (COICOP 04.2) and Maintenance and repair of the dwelling (COICOP 04.3). The disposable income indicators come from the OECD national accounts database. Net household disposable income is used. The population data come from the OECD national accounts database. The price-to-rent ratio is given by the ratio of nominal house prices to rental prices. This is a measure of the profitability of owning a house. The price-to-income ratio is given by the ratio of nominal house prices to nominal household disposable income per capita. This is a measure of the affordability of purchasing a house. An indication that house prices may be overvalued is provided if either of these ratios is above their long-term averages. The standardised price-rent and price-income ratios show the current price-rent and price-income ratios relative to their respective long-term averages. The long-term average, which is used as a reference value, is calculated over the whole period available when the indicator begins after 1980 or 1980 if the indicator is available over a longer time period. The standardised ratio is indexed to a reference value equal to 100 over the full sample period. Values over 100 indicate that the present price-rent ratio, or price-income ratio, is above its long-run norms. This provides an indication of possible housing market pressures.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 29 julho, 2019
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      The “ALFS Summary tables” dataset is a subset of the Annual Labour Force Statistics database which presents annual labour force statistics and broad population series for 34 OECD member countries plus Brazil, Columbia and Russian Federation and 4 geographical areas (Major Seven, Euro area, European Union and OECD-Total). Data are presented in thousands of persons, in percentage or as indices with base year 2010=100. This dataset contains estimates from the OECD Secretariat for the latest years when countries did not provide data. These estimates are necessary to compile aggregated statistics for the geographical areas for a complete span of time. Since 2003, employment data by sector for the United States are compiled following the North American Industrial Classification System (NAICS); therefore they are not strictly comparable with other countries’ data. Euro area and European Union data were extracted from Eurostat (LFS Series, Detailed annual survey results in New Cronos). Euro area refer to Euro area with 17 countries (geo = ea17). European Union refers to European Union with 27 countries (geo = eu27).
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 02 julho, 2019
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      Data source used: The aquaculture production data collection is part of the more comprehensive data gathering carried out on an annual basis by the Fisheries Committee (COFI) of the Trade and Agriculture Directorate (TAD) from OECD members and participating non-OECD economies. Data on marine landings, aquaculture production, inland fisheries catch, fleet, employment, total allowable catch (TAC) and fisheries support estimate (FSE) are collected from Fisheries Ministries, National Statistics Offices and other institutions designated as an official data source. The surveys used for this exercise are the OECD Fisheries questionnaires.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 outubro, 2019
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      The concept used is the total number of hours worked over the year divided by the average number of people in employment. The data are intended for comparisons of trends over time; they are unsuitable for comparisons of the level of average annual hours of work for a given year, because of differences in their sources. Part-time workers are covered as well as full-time workers. The series on annual hours actually worked per person in total employment presented in this table for all 34 OECD countries are consistent with the series retained for the calculation of productivity measures in the OECD Productivity database (www.oecd.org/statistics/productivity/compendium). However, there may be some differences for some countries given that the main purpose of the latter database is to report data series on labour input (i.e. total hours worked) and also because the updating of databases occur at different moments of the year. Hours Hours actually worked per person in employment are according to National Accounts concepts for 18 countries: Austria, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Italy, Korea, the Netherlands, Norway, the Slovak Republic, Spain, Sweden, Switzerland and Turkey. OECD estimates for Belgium, Ireland, Luxembourg and Portugal for annual hours worked are based on the European Labour Force Survey, as are estimates for dependent employment only for Austria, Estonia, Greece, the Slovak Republic and Slovenia. The table includes labour-force-survey-based estimates for the Russian Federation.countries: For further details and country specfic notes see: www.oecd.org/employment/outlook and www.oecd.org/employment/emp/ANNUAL-HOURS-WORKED.pdf
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 10 outubro, 2019
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      This dataset presents the average number of students in a class by type of institution.
    • junho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 05 junho, 2019
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      This table contains data on the average duration of unemployment by sex and standardised age groups (15-19, 15-24, 20-24, 25-54, 55+, total). Data are expressed in months.
    • outubro 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 21 junho, 2019
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      The average effective age of retirement is calculated as a weighted average of (net) withdrawals from the labour market at different ages over a 5-year period for workers initially aged 40 and over. In order to abstract from compositional effects in the age structure of the population, labour force withdrawals are estimated based on changes in labour force participation rates rather than labour force levels. These changes are calculated for each (synthetic) cohort divided into 5-year age groups. The estimates shown in red are less reliable as they have been derived from interpolations of census data rather than from annual labour force surveys. The estimates for women in Turkey are based on 3-yearly moving averages of participation rates for each 5-year age group. OECD estimates based on the results of national labour force surveys, the European Union Labour Force Survey and, for earlier years in some countries, national censuses.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 14 julho, 2019
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  • B
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 outubro, 2019
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      The balance of payments is a statistical statement that provides a systematic summary of economic transactions of an economy with the rest of the world, for a specific time period. The transactions are for the most part between residents and non-residents of the economy. A transaction is defined as an economic flow that reflects the creation, transformation, exchange, transfer, or extinction of economic value and involves changes in ownership, of goods or assets, the provision of services, labour or capital.  This dataset presents countries compiling balance of payments statistics in accordance with the 6th edition of the Balance of Payments and International Investment Position Manual published by the IMF (BPM6). Transactions include: the goods and services accounts, the primary income account (income account in BPM5), the secondary income account (transfers in BPM5), the capital account, and the financial account. Changes in BPM6 compared to BPM5 are often a consequence of a stricter application of the change of ownership principle in particular in the goods and services accounts. They relate to transactions on goods and services (merchanting, goods for processing, Insurance), income (investment income), and financial operations (direct investment) .
    • fevereiro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 01 março, 2019
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      Since the collection of 2009 data, the scope of the OECD Global Insurance Statistics questionnaire has been expanded. These changes led to the collection of key balance sheet and income statement items for direct insurance and reinsurance sectors, such as: gross claims paid, outstanding claims provision (changes), gross operating expenses, commissions, total assets, gross technical provisions (of which: unit-linked), shareholder equity, net income.
    • março 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 outubro, 2019
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      The business tendency survey indicators cover a standard set of indicators for four economic sectors: manufacturing, construction, retail trade and other services. This includes an indicator of overall business conditions or business confidence in each sector. The consumer opinion survey indicators cover a restricted set of indicators on consumer confidence, expected economic situation and price expectations.   Business and consumer opinion (tendency) surveys provide qualitative information that has proved useful for monitoring the current economic situation. Typically they are based on a sample of enterprises or households and respondents are asked about their assessments of the current situation and expectations for the immediate future. For enterprise surveys this concerns topics such as production, orders, stocks etc. and in the case of consumer surveys their intentions concerning major purposes, economic situation now compared with the recent past and expectations for the immediate future. Many survey series provide advance warning of turning points in aggregate economic activity as measured by GDP or industrial production. Such series are known as leading indicators in cyclical analysis. These types of survey series are widely used as component series in composite leading indicators.   The main characteristic of these types of surveys is that instead of asking for exact figures, they usually ask for the direction of change e.g. a question on tendency by reference to a “normal” state, e.g. of production level. Possible answers are generally of the three point scale type e.g. up/same/down or above normal/normal/below normal for enterprise surveys and of the five point scale type e.g. increase sharply/increase slightly/remain the same/fall slightly/fall sharply for consumer surveys. In presenting the results as a time series, only the balance is shown. That is “same” or “normal” answers are ignored and the balance is obtained by taking the difference between percentages of respondents giving favourable and unfavourable answers.   Virtually all business tendency and consumer opinion survey data are presented as time series of balances in this dataset, either in raw or seasonally adjusted form. Very few series are presented as indices, and where these exist they have generally been converted from underlying balances by countries before submitting the data to the OECD.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      Institutional coverage As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Item coverage Business written in the reporting country on a gross and net premium basis. It contains a breakdown between domestic companies, foreign-controlled companies and branches and agencies or foreign companies.
  • C
    • maio 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 06 maio, 2019
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      Indicators in the OECD database on Carbon dioxide (CO2) emissions embodied in international trade are derived by combining the 2015 version of OECD's Inter-Country Input-Output (ICIO) Database with International Energy Agency (IEA) statistics on CO2 emissions from fuel combustion. Production-based CO2 emissions are estimated by allocating the IEA CO2 emissions to the 34 target industries in OECD ICIO and, to final demand for fuels, by both residents and non-residents. Consumption-based CO2 emissions are calculated by multiplying the intensities of the production-based emissions (c) with the global Leontief inverse (I-A)(-1) and global final demand matrix (Y) from OECD ICIO, taking the column sums of the resulting matrix and adding residential and private road emissions (FNLC), i.e. direct emissions from final demand: colsum [ diag(c) (I-A)(-1) Y ] + FNLC. The ICIO system includes discrepancies in the trade data (referred to as DISC). Emissions allocated to DISC are made explicit (e.g. in indicator FD_CO2). This ensures that global CO2 production equals global CO2 consumption.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 16 abril, 2019
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    • fevereiro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 28 fevereiro, 2019
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      Institutional coverage As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Item coverage Commissions in the reporting country, containing a breakdown between domestic companies, foreign-controlled companies and branches and agencies of foreign companies.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
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      The 'Consumer Price Indices (CPIs)' contains all data that was previously contained in three different datasets: 'Consumer Prices', 'National Consumer Price Indices (CPIs) by COICOP divisions' and 'Harmonised Indices of Consumer Prices (HICPs) by COICOP divisions'. The 'Consumer Price Indices (CPIs)' dataset contains predominantly monthly statistics, and associated statistical methodological information, for the 36 OECD member countries and for some non-member countries. The ‘Consumer Price Indices (CPIs)' dataset contains statistics on Consumer Price Indices including national CPIs, Harmonised Indices of Consumer Prices (HICPs) and their associated weights and contributions to national annual inflation. The data series presented have been chosen as the most relevant prices statistics for which comparable data across countries is available. In all cases, a lot of effort has been made to ensure that the data are internationally comparable across all countries presented and that all the subjects have good historical time-series’ data to aid with analysis. Data are available monthly for all the countries except for Australia and New Zealand (quarterly data).
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 18 outubro, 2019
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    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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    • abril 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 21 maio, 2018
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      Note: CPA data for 2018 and 2019 are projections from the 2016 Survey on Forward Spending Plans. Country Programmable Aid (CPA), outlined in our Development Brief  and also known as “core” aid, is the portion of aid donors programme for individual countries, and over which partner countries could have a significant say. CPA is much closer than ODA to capturing the flows of aid that goes to the partner country, and has been proven in several studies to be a good proxy of aid recorded at country level. CPA was developed in 2007 in close collaboration with DAC members. It is derived on the basis of DAC statistics and was retroactively calculated from 2000 onwards
    • julho 2016
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 29 julho, 2016
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      Country Programmable Aid (CPA), outlined in our Development Brief  and also known as “core” aid, is the portion of aid donors programme for individual countries, and over which partner countries could have a significant say. CPA is much closer than ODA to capturing the flows of aid that goes to the partner country, and has been proven in several studies to be a good proxy of aid recorded at country level. CPA was developed in 2007 in close collaboration with DAC members. It is derived on the basis of DAC statistics and was retroactively calculated from 2000 onwards
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 13 agosto, 2019
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      The country statistical profiles provide a broad selection of indicators, illustrating the demographic, economic, environmental and social developments, for all OECD members. The dataset also covers the five key partner economies with which the OECD has developed an enhanced engagement program with (Brazil, China, India, Indonesia and South Africa) ,accession countries (Colombia, Costa Rica and Lithuania) , Peru and the Russian Federation. The user can easily compare indicators across all countries. Total fertility rates - Unit of measure used: Number of children born to women aged 15 to 49
  • D
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 09 julho, 2019
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      This dataset contains three earnings-dispersion measures - ratio of 9th-to-1st, 9th-to-5th and 5th-to-1st - where ninth, fifth (or median) and first deciles are upper-earnings decile limits, unless otherwise indicated, of gross earnings of full-time dependent employees. The dataset also includes series on: the incidence of low-paid workers defined as the share of full-time workers earning less than two-thirds of gross median earnings of all full-time workers; the incidence of high of high-paid workers defined as the share of full-time workers earning more than one-and-half time gross median earnings of all full-time workers; gender wage gap unadjusted and defined as the difference between median wages of men and women relative to the median wages of men.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 10 outubro, 2019
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      The objective of this dataset is to trace net changes in terms of volume in the growing stock of standing wood on forest land. It shows data underlying the indicator on the intensity of use of forest resources. This indicator relates actual fellings to annual productive capacity (i.e. gross increment). Forest depletion and growth describe balances or imbalances in different types of forests. The intensity of use of forest resources reflects various forest management methods and their sustainability. These data should be read in connection with other indicators of the OECD Core Set, in particular with indicators on land use changes and forest quality (species diversity, forest degradation), and be complemented with data on forest management practices and protection measures. In interpreting these data, it should be borne in mind that definitions and estimation methods vary among countries.
    • fevereiro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 01 março, 2019
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      As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business datawhere composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Click to collapse Item coverage Outstanding investment by direct insurance companies, classified by investment category, by the companies' nationality and by its destination (domestic or foreign). As of 2009, investment data exclude assets linked to unit-linked products sold to policyholders.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 16 abril, 2019
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      The OECD Digital STRI identifies, catalogues and quantifies barriers that affect trade in digitally enabled services across 46 countries. It provides policy makers with an evidence-based tool that helps to identify regulatory bottlenecks, design policies that foster more competitive and diversified markets for digital trade, and analyze the impact of policy reforms. The OECD Digital STRI captures cross-cutting impediments that affect all types of services traded digitally. As a stand-alone instrument, it complements the OECD Services Trade Restrictiveness Index (STRI).
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 16 abril, 2019
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      The OECD Digital STRI heterogeneity indices complement the recently published Digital STRI's and presents indices of regulatory heterogeneity based on the rich information in the Digital STRI regulatory database. The indices are built from assessing – for each country pair and each measure – whether or not the countries have the same regulation. For each country pair and each sector, the indices reflect the (weighted) share of measures for which the two countries have different regulation.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 abril, 2019
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      Graduates/new entrants in each educational field as a percentage of the sum of graduates/new entrants in all fields.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      Distribution of teachers by gender and different age groups.
  • E
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 29 abril, 2019
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      The OECD Long-Term Baseline Scenario is a projection of some major economic variables beyond the short-term horizon of the OECD Economic Outlook. It covers all OECD economies, non-OECD G20 economies and key partners. The projection horizon is currently 2060. For the historical period and the short-run projection horizon, the series are consistent with those of the OECD Economic Outlook number in the dataset title. The definitions, sources and methods are also the same, except where noted explicitly (such as coverage of the non-OECD and world aggregates). For more details on the methodology, please see Boxes 1 to 3 in The Long View: Scenarios for the World Economy to 2060 and the references therein.The baseline scenario is a projection conditional on a number of assumptions, notably that countries do not carry out institutional and policy reforms. It is used as a reference point to illustrate the potential impact of structural reforms in alternative scenarios, such as those discussed in The Long View: Scenarios for the World Economy to 2060. The data for these alternative scenarios are not available here but can be obtained on request by writing to EcoOutlook@oecd.org.
    • maio 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 31 maio, 2019
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      The OECD Economic Outlook analyses the major economic trends over the coming 2 years. It provides in-depth coverage of the main economic issues and the policy measures required to foster growth in each member country. Forthcoming developments in major non-OECD economies are also evaluated in detail. Each edition of the Outlook provides a unique resource to keep abreast of world economic developments. The OECD Economic Outlook database is a comprehensive and consistent macroeconomic database of the OECD economies, covering expenditures, foreign trade, output, labour markets, interest and exchange rates, balance of payments, and government debt. For the non-OECD regions, foreign trade and current account series are available.   The database contains annual data (for all variables) and quarterly figures (for a subset of variables). Variables are defined in such a way that they are as homogenous as possible for the countries covered. Breaks in underlying series are corrected as far as possible. Sources for the historical data are publications of national statistical agencies and OECD data bases such as Quarterly National Accounts, Annual National Accounts, Labour Force Statistics and Main Economic Indicators. The cut-off date for information used in the compilation of the projections was the 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.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 02 julho, 2019
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    • setembro 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 16 outubro, 2018
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      This indicator presents internationally comparable data on education and earnings, by educational attainment, age and gender as published in OECD Education at a Glance 2018. For trend data, Education at a Glance 2018 includes data for 2005 and 2010-2016 (or years available).
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 04 outubro, 2019
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      This indicator presents internationally comparable data regarding the labour force status and the educational attainment level by the National Educational Attainment Categories (NEAC) as reported by the labour force survey (LFS) and published in OECD Education at a Glance 2017. For trend data, the Education at a Glance Database includes data from 1981 to 2016 (or years with available data).
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 29 abril, 2019
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      The nature of expenditure distinguishes between current and capital expenditure. The resource category refers to service provider (public institutions, government-dependent private institutions, and independent private institutions, i.e. both educational and other institutions). These expenditure figures are intended to represent the total cost of services provided by each type of institution, without regard to sources of funds (whether they are public or private).
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      All entities that provide funds for education, either initially or as final payers, are classified as either governmental (public) sources or non-governmental (private) sources, the sole exception being "international agencies and other foreign sources", which are treated as a separate category. There are three types of financial transactions: Direct expenditure on educational institutions; Transfers to students or households and to other private entities; and Households' expenditure on education outside educational institutions.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      These indicators on expenditure on education are published in chapter C of Education at a Glance, which covers financial and human resources invested in education.They are either policy levers or provide context information on education systems, or sometimes both. For example, expenditure per student is a key policy measure that most directly affects the individual learner, as it acts as a constraint on the learning environment in schools and learning conditions in the classroom.The data set “educational finance indicators” provides the main indicators computed for three levels of education : primary, secondary and post-secondary non-tertiary levels combined; tertiary level; and primary to tertiary levels combined. Other datasets provide more breakdowns for each specific indicator.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      This dataset presents the average number of teachers by sex and age.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      This dataset presents the average number of teachers by sex and type of institution.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
      Selecionar Conjunto de dados
    • setembro 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 22 março, 2019
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      This dataset provides selected information on national emissions of traditional air pollutants: emission data are based upon the best available engineering estimates for a given period; they concern man-made emissions of sulphur oxides (SOx), nitrogen oxides (NOx), particulate matter (PM), carbon monoxide (CO) and volatile organic compounds (VOC). Categories presented are based on the NFR 2014 classification. Data exclude non man-made emissions and international aviation and maritime transports emissions. For some countries residential mobile emissions (e.g. mowers) are included into Other combustion instead of Other mobile. The GDP used to calculate intensities is expressed in USD at 2010 prices and PPPs.  
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 22 julho, 2019
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      Compared to men, women are less likely to work full-time, more likely to be employed in lower-paid occupations, and less likely to progress in their careers. As a result gender pay gaps persist and women are more likely to end their lives in poverty. This data looks at how many men and women are in paid work, who works full-time, and how having children and growing older affect women’s work patterns and earnings differently to men’s. It looks at how women bear the brunt of domestic and family responsibilities, even when working full-time. It also considers the benefits for businesses of keeping skilled women in the workplace, and encouraging them to sit on company boards. It looks at women’s representation in parliaments, judicial systems, and the senior civil service. It examines male and female employment in the wake of the crisis, and how women tend to be confined to the most vulnerable categories within the informal sector in developing countries.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 outubro, 2019
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    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 18 julho, 2019
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      This dataset contains the tenure composition (as a percentage of all job tenures). Data are broken down by professional status - employees and total employment - sex, five-year and broad age groups (15-24, 25-54, 55-64, 15-64, total, etc.). Geographic coverageIn order to facilitate analysis and comparisons over time, historical data for OECD members have been provided over as long a period as possible, often even before a country became a member of the Organisation. Information on the membership dates of all OECD countries can be found at OECD Ratification Dates.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 14 julho, 2019
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      Job tenure is measured by the length of time workers have been in their current or main job or with their current employer. This information is valuable for estimating the degree of fluidity in the labour market and in identifying the areas of economic activity where the turnover of labour is rapid or otherwise. Data are so far reported for a number of European countries and will be expanded to cover a greater number of countries.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 02 julho, 2019
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      This table contains data on permanent and temporary workers based on the type of work contract of their main job. Data are further broken down by professional status - employees, total employment - by sex and by standardised age groups (15-19, 15-24, 20-24, 25-54, 55-64, 65+, total). Unit of measure used - Data are expressed in thousands of persons.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      The Fisheries Committee (COFI) from the Trade and Agriculture Directorate (TAD) collects, on an annual basis from all its participating countries, data on landings, aquaculture production, fleet, employment in the fisheries sector, and government financial transfers. Data are collected from Fisheries Ministries, National Statistics Offices and other institution designated as an official data source. Concepts Classifications Data are collected by the OECD using the methodologies established by the Coordinating Working Party on Fishery Statistics (CWP) (www.fao.org/fishery/cwp/search/en). This inter-agency body, created in 1960 to develop common procedures and standards for the collation of fisheries statistics, provides technical advice on fishery statistical matters. Its handbook of Fishery Statistical Standards comprises definitions of the various concepts used in fishery statistics, with the exception of Government Financial Transfers which is unique to the OECD. All other statistics are based on the CWP definitions. The OECD, a partner with the CWP, additionally collects information on values for its landings and records the breakdown between the types of landings (i.e. landings in domestic ports, landings in foreign ports) data series which are not collected by the FAO. While a number of countries cover landings in a similar fashion, the same does not hold true for capacity (feet/meters, GRT/engine powers), or for employment for which both Full-time equivalents or numbers of people are used. The OECD therefore does not duplicate FAO statistics but requests complementary information to feed its analytical work.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 17 setembro, 2019
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      Number of students enrolled in different education programmes by age and sex.
    • maio 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 21 maio, 2019
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      This dataset presents the number of students enrolled in different education programmes by field and sex.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      This indicator examines the share of students by gender, programme orientation and mode of study over the total number of students.
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 06 agosto, 2019
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      Number of students enrolled in different education programmes by type of institution and sex.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      Number of students by level of education, adjusted to the financial year. When financial year, school year and calendar year differs, adjustments are made to ease comparison.
    • março 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 março, 2019
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      This dataset presents the number of students enrolled in different education programmes by country of origin and sex.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      Enrolment rate per age is the percentage of students enrolled in each type of institution over the total of students
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      Entrepreneurship is crucial to economic development, promoting social integration and reducing inequalities. The Gender-entrepreneurship dataset presents an original collection of indicators that measure gender equality in entrepreneurship, providing an important reference for policy insights and policy making. Data refer mainly to the self-employed, their profile, age, education and sector of activity.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 16 abril, 2019
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    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 06 agosto, 2019
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      EAMFP growth measures the residual growth in the joint production of both the desirable and the undesirable outputs that cannot be explained by changes in the consumption of factor inputs (including labour, produced capital and natural capital). Therefore, for a given growth of input use, EAMFP increases when GDP increases or when pollution decreases. As part of the growth accounting framework underlying the EAMFP indicator, the growth contribution of natural capital and growth adjustment for pollution abatement indicators are derived: Growth contribution of natural capital - measures to what extent a country's growth in output is attributable to natural resource use; Growth adjustment for pollution abatement - measures to what extent a country's GDP growth should be corrected for pollution abatement efforts - adding what has been undervalued due to resources being diverted to pollution abatement, or deducing the ‘excess' growth which is generated at the expense of environmental quality.
    • novembro 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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      Air pollution is considered one of the most pressing environmental and health issues across OECD countries and beyond. According to the World Health Organisation (WHO), exposure to fine particulate matter (PM2.5) has potentially the most significant adverse effects on health compared to other pollutants. PM2.5 can be inhaled and cause serious health problems including both respiratory and cardiovascular disease, having its most severe effects on children and elderly people. Exposure to PM2.5 has been shown to considerably increase the risk of heart disease and stroke in particular. For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator. The underlying PM2.5 concentrations estimates are taken from van Donkelaar et al. (2016). They have been derived using satellite observations and a chemical transport model, calibrated to global ground-based measurements using Geographically Weighted Regression at 0.01° resolution. The underlying population data, Gridded Population of the World, version 4 (GPWv4) are taken from the Socioeconomic Data and Applications Center (SEDAC) at the NASA. The underlying boundary geometries are taken from the Global Administrative Unit Layers (GAUL) developed by the FAO, and the OECD Territorial Classification, when available. The current version of the database presents much more variation with respect to the previous one. The reason is that the underlying concentration estimates previously included smoothed multi-year averages and interpolations; while in the current version annual concentration estimates are used. Establishing trends of pollution exposure should be done with care, especially at smaller output areas, as their inputs (e.g. underlying data and models) can change from year to year. We recommend using a 3-year moving average for visualisation.
  • F
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 agosto, 2019
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      In view of the strong demand for cross-national indicators on the situation of families and children, the OECD Family Database was developed to provide cross-national indicators on family outcomes and family policies across the OECD countries, its enhanced engagement partners and EU member states. The database brings together information from various national and international databases, both from within the OECD and from external organisations. The database classifies indicators into four main dimensions: (i) structure of families, (ii) labour market position of families, (iii) public policies for families and children and (iv) child outcomes. Detailed information on the definitions, sources and methods used in the construction of the database can be found on the OECD Family Database webpage.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 17 abril, 2019
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    • fevereiro 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 26 junho, 2018
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      FDI data are based on statistics provided by 35 OECD member countries and by Lithuania. BMD4: OECD Benchmark Definition of Foreign Direct Investment - 4th Edition
    • março 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 05 março, 2019
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    • junho 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 02 julho, 2018
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    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 14 julho, 2019
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      The FDI Regulatory Restrictiveness Index (FDI Index) measures statutory restrictions on foreign direct investment across 22 economic sectors. It gauges the restrictiveness of a country’s FDI rules by looking at the four main types of restrictions on FDI: 1) Foreign equity limitations; 2) Discriminatory screening or approval mechanisms; 3) Restrictions on the employment of foreigners as key personnel and 4) Other operational restrictions, e.g. restrictions on branching and on capital repatriation or on land ownership by foreign-owend enterprises. Restrictions are evaluated on a 0 (open) to 1 (closed) scale. The overall restrictiveness index is the average of sectoral scores. The discriminatory nature of measures, i.e. when they apply to foreign investors only, is the central criterion for scoring a measure. State ownership and state monopolies, to the extent they are not discriminatory towards foreigners, are not scored. The FDI Index is not a full measure of a country’s investment climate. A range of other factors come into play, including how FDI rules are implemented. Entry barriers can also arise for other reasons, including state ownership in key sectors. A country’s ability to attract FDI will be affected by others factors such as the size of its market, the extent of its integration with neighbours and even geography among other. Nonetheless, FDI rules can be a critical determinant of a country’s attractiveness to foreign investors.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 14 julho, 2019
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    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 09 outubro, 2019
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      The dataset Fisheries International collaboration in technology development (bilateral) provides the number of co-inventions (simple patent families) developed jointly by at least two inventors. This indicator is disaggregated by: Country - country of residence of the inventor(s), integral counted; in cases when inventors from more than two countries collaborate, this is translated into distinct bilateral relationships between country pairs. For example, if inventors from 3 countries collaborate (e.g. USA, DEU, JPN) then a unit count is assigned to 6 country pairs (USA-DEU, USA-JPN, DEU-JPN, DEU-USA, JPN-USA, JPN-DEU); in this case a country generally coordinate the project and the others are partners. Partner – country of residence of the inventor(s) who collaborate to the patent. Technology domain – the three main areas of innovation in fisheries and aquaculture, related to technology development. In detail: 1. Harvesting technology such as more effective ways to find or harvest fish and which are typically associated with improvements in catch per unit of effort (e.g. type/size of vessels and their methods of propulsion, search technologies, method of catching or harvesting fish and bringing them on board); 2.Aquaculture technology such as methods to more effectively grow fish in captivity (innovation in feeds, improving the health of aquaculture animals, etc.); 3. New products and markets such as the development of new fish products and markets (food technologies/processing such as the development of surimi as a crabmeat substitute) and the improvement of market access (secure or enlarge markets for fish products) that provides important incentives for green growth (e.g. eco-certification with fishers adopting by-catch saving technologies or modifying fishing practices and/or territorial user rights in fisheries).
    • março 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 13 março, 2019
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      The OECD FISH Unit, in collaboration with the Environment Directorate and the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in fisheries-related technologies. The search strategy for fisheries and aquaculture related technologies adopts a mixed solution with a definition of the technical field of interest in fisheries and aquaculture innovation complemented by keywords, e.g. by looking for keywords in the International Patent Classification (IPC) codes and checking manually the relevance of the results in the text of patents (in the title, the abstract, etc). Technology domains are detailed in the ANNEX attached below. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' fisheries, aquaculture and innovation policies.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 09 outubro, 2019
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      The Fisheries R&D expenditures dataset contains the budgetary expenditures in research and development on total budgetary FSE. Three variables are presented in this dataset:  • R&D expenditures - they are budgetary expenditures that finance research and development activities related to fisheries, irrespective of the institution (private or public, ministry, university, research centre or fisher group) or where they take place, the nature of research (scientific, institutional, etc.), or its purpose. The focus is on research and development expenditures on applied research related to the fisheries sector. Social-sciences research related to fisheries is included. It is also included data dissemination when associated primarily with research and development (knowledge generation), e.g. reports from research and databases developed as an adjunct to research. •FISHERIES SUPPORT ESTIMATE - Budgetary - it is the annual monetary value of gross transfers from taxpayers to fishers arising from policy measures that support fisheries, regardless of their nature, objectives or impacts. Data on FSE are collected by the Fisheries Committee (COFI) from the Trade and Agriculture Directorate (TAD) on an annual basis from all its participating countries. Data are provided by Fisheries Ministries, National Statistics Offices and other institution designated as an official data source. The original financial data is collected in national currency at current values; they are converted and published also in US dollars, for analytical purposes and to allow data comparisons. • Share of R&D expenditures on FSE - it is the share of budgetary research and development expenditures on total budgetary FSE. Please notice that total budgetary FSE is defined ‘net’, i.e. it is adjusted for costs incurred by fishers in order to receive the support. Whenever these costs are of significant amount, total budgetary FSE becomes remarkably low or negative. The corresponding share of research and development expenditures turns into a percentage exceptionally high or negative.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      The OECD Fisheries Support Estimates (FSE) database is intended to be the best source of information on fisheries policies in OECD members and participating non-OECD economies.   It is designed to monitor and quantify developments in fisheries policy, to establish a common basis for policy dialogue among countries, and to provide economic data to assess the effectiveness and efficiency of policies.   These tables report country programmes data aggregated according to the main categories presented in the FSE Manual.   More detailed documentation on country programmes can be found in country-level metadata; more data on country programmes can be found in the full dataset (Excel Format - link provided below). Statistics are organized in pivot tables to make possible cross-country comparisons and to filter disaggregated policy-level data by policy implementation criteria and country.   The FSE data collection is part of the more comprehensive data gathering carried out on an annual basis by the Fisheries Committee (COFI) of the Trade and Agriculture Directorate (TAD) from OECD members and participating non-OECD economies.   Data on landings, aquaculture production, inland fisheries catch, fleet, employment, total allowable catch (TAC) and fisheries support estimate (FSE) are collected from Fisheries Ministries, National Statistics Offices and other institutions designated as an official data source. The surveys used for this exercise are the OECD Fisheries questionnaires.
    • março 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 14 março, 2019
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      The OECD FISH Unit, in collaboration with the Environment Directorate and the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in fisheries-related technologies. The search strategy for fisheries and aquaculture related technologies adopts a mixed solution with a definition of the technical field of interest in fisheries and aquaculture innovation complemented by keywords, e.g. by looking for keywords in the International Patent Classification (IPC) codes and checking manually the relevance of the results in the text of patents (in the title, the abstract, etc). Technology domains are detailed in the ANNEX attached below. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' fisheries, aquaculture and innovation policies.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 10 outubro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      Fisheries fleet: The FAO has a two dimensional definition, of which the OECD only uses the concept of fishing vessel. Fishery Fleet: The term "fishery fleet" or "fishery vessels" refers to mobile floating objects of any kind and size, operating in freshwater, brackishwater and marine waters which are used for catching, harvesting, searching, transporting, landing, preserving and/or processing fish, shellfish and other aquatic organisms, residues and plants. Fishing vessel: The term "fishing vessel" is used instead when the vessel is engaged only in catching operations. Gross Register Tonnage: The Gross Register Tonnage represents the total measured cubic content of the permanently enclosed spaces of a vessel, with some allowances or deductions for exempt spaces such as living quarters (1 gross register ton = 100 cubic feet = 2.83 cubic metres).
    • setembro 2014
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 04 outubro, 2014
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      The number of students enrolled refers to the count of students studying in the reference period. Each student enrolled in the education programmes covered by the corresponding category is counted once and only once. National data collection systems permitting, the statistics reflect the number of students enrolled at the beginning of the school / academic year. Preferably, the end (or near-end) of the first month of the school / academic year is chosen (special arrangements are made for part-year students who may not start studies at the beginning of the school year). Students are classified as foreign students (non-citizens) if they are not citizens of the country in which the data are collected. While pragmatic and operational, this classification is inappropriate for capturing student mobility because of differing national policies regarding the naturalisation of immigrants. Countries that have lower propensity to grant permanent residence to its immigrant populations are likely to report second generation immigrants as foreign students. Therefore, for student mobility and bilateral comparisons, interpretations of data based on the concept of foreign students should be made with caution. Students are classified as international students if they left their country of origin and moved to another country for the purpose of study. Depending on country-specific immigration legislation, mobility arrangements, and data availability, international students may be defined as students who are not permanent or usual residents of their country of study or alternatively as students who obtained their prior education in a different country, including another EU country.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 outubro, 2019
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      This dataset shows the state and changes over time in the abstractions of freshwater resources in OECD countries. Water abstractions are a major pressure on freshwater resources, particularly from public water supplies, irrigation, industrial processes and cooling of electric power plants. It has significant implications for issues of quantity and quality of water resources. This dataset shows water abstractions by source (surface and ground water) and by major uses. Water abstractions refer to water taken from ground or surface water sources and conveyed to the place of use. If the water is returned to a surface water source, abstraction of the same water by the downstream user is counted again in compiling total withdrawal. When interpreting those data, it should be borne in mind that the definitions and estimation methods employed by Member countries may vary considerably among countries.
    • março 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 dezembro, 2018
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      Austria: Long-term annual average 1961-90 Belgium: Data exclude underground flows and include estimates Canada: Long-term annual average 1971-2004 Chile: Long-term annual average 2000-2014 Colombia: Long-term annual average 1974-2012 Czech Republic: The long-term annual average refers to the latest 20 years Denmark: Long-term annual average 1995-2015 Estonia: Long-term annual average refers to the latest 30 years and includes only data about fresh surface water France: Long-term annual average : 1981-2010. Inflow and outflow: outflow is computed using the throughput of rivers having their source in France but the mouth outside France; measures are taken at the French border using the daily throughputs. Precipitation and real evapotranspiration data are derived from a gridded atmospheric model (grid point of 8 by 8 km2) applied to the territory of metropolitan France. Germany: Long-term annual average 1995-2015 Hungary: Long-term annual average 1971-2000 Ireland: Long-term annual average 1981-2010. Groundwater figures are not available and therefore are not included. Israel: Long-term annual average 2000-2013 Italy: Long-term annual average 1971-2000 Japan: Long-term annual average 1971-2006 Korea: Long-term annual average 1974-2003 Latvia: Long-term annual average 2005-2013 Lithuania: Long-term annual average 2000-2014 Mexico: The long-term annual average covers 30 years Netherlands: Long-term annual average 1981-2010 New Zealand: Long-term annual average 1995-2014 Norway: The data for precipitation and evotranspiration refer to the period LTAA (long-term annual average) 1961-90 whereas the others to the period LTAA 1981-2010, that is why precipitation minus evotranspiration is different from internal resources. Poland: Long-term annual average 1951-2014. Estimates on the base of mean annual flow. For more information, see: http://www.kzgw.gov.pl/ , http://www.pgi.gov.pl/ , http://www.psh.gov.pl/ , http://www.imgw.pl/ Slovak Republic: Long-term annual average is 1961-1990 for internal resources, 1961-2000 for external inflow Slovenia: Long-term annual average is 1971-2000 Sweden: Long-term annual average : 1990-2009. The difference between precipitation and evapotranspiration refers to storage Switzerland: Long-term annual average : 1981-2010 Turkey: Long-term annual average: data for internal flow refers to the period 1980-2011 Costa Rica: The long-term annual average refers to 1990-2014 Russia: The long-term annual average refers to 1936-1980
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 05 julho, 2019
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      This table contains data on full-time and part-time employment based on a common definition of 30-usual weekly hours of work in the main job. Data are broken down by professional status - employees, total employment - sex and standardised age groups (15-24, 25-54, 55+, total). Unit of measure used - Data are expressed in thousands of persons.
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 13 agosto, 2019
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      This dataset contains incidences and gender composition of part-time employment with standardised age groups (15-24, 25-54, 55-64, 65+, total). Part-time employment is based on national definitions.  The definition of part-time work varies considerably across OECD countries Essentially three main approaches can be distinguished: i) a classification based on the worker’s perception of his/her employment situation; ii) a cut-off (generally 30 or 35 hours per week) based on usual working hours, with persons usually working fewer hours being considered part-timers; iii) a comparable cut-off based on actual hours worked during the reference week. A criterion based on actual hours will generally yield a part-time rate higher than one based on usual hours, particularly if there are temporary reductions in working time as a result of holidays, illness, short-timing, etc. On the other hand, it is not entirely clear whether a classification based on the worker’s perception will necessarily yield estimates of part-time work that are higher or lower than one based on a fixed cut-off. In one country (France) which changed from 1981 to 1982 from a definition based on an actual hours cut-off (30 hours) to one based on the respondent’s perception, the latter criterion appeared to produce slightly higher estimates.
    • maio 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 maio, 2019
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      Data include pension funds per the OECD classification by type of pension plans and by type of pension funds. All types of plans are included (occupational and personal, mandatory and voluntary). The OECD classification considers both funded and book reserved pension plans that are workplace-based (occupational pension plans) or accessed directly in retail markets (personal pension plans). Both mandatory and voluntary arrangements are included. The data include plans where benefits are paid by a private sector entity (classified as private pension plans by the OECD) as well as those paid by a funded public sector entity. A full description of the OECD classification can be found at:http://www.oecd.org/dataoecd/0/49/38356329.pdf. Pension funds include also some personal pension arrangements like the Individual Retirement Accounts (IRAs) in the United States as well as funds for government workers. The coverage of the statistics follows the regulatory and supervisory framework. All authorised pension funds are therefore normally covered by the Global Pension Statistics exercise. Assets pertaining to reserve funds in social security systems are excluded.
    • março 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 21 maio, 2018
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      Data include pension funds per the OECD classification by type of pension plans and by type of pension funds. All types of plans are included (occupational and personal, mandatory and voluntary). The OECD classification considers both funded and book reserved pension plans that are workplace-based (occupational pension plans) or accessed directly in retail markets (personal pension plans). Both mandatory and voluntary arrangements are included. The data include plans where benefits are paid by a private sector entity (classified as private pension plans by the OECD) as well as those paid by a funded public sector entity. A full description of the OECD classification can be found at: http://www.oecd.org/dataoecd/0/49/38356329.pdf.  Pension funds include also some personal pension arrangements like the Individual Retirement Accounts (IRAs) in the United States as well as funds for government workers. The coverage of the statistics follows the regulatory and supervisory framework. All authorised pension funds are therefore normally covered by the Global Pension Statistics exercise. Assets pertaining to reserve funds in social security systems are excluded.
  • G
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 outubro, 2019
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      The GID-DB is a database providing researchers and policymakers with key data on gender-based discrimination in social institutions. This data helps analyse women’s empowerment and understand gender gaps in other key areas of development.Covering 180 countries and territories, the GID-DB contains comprehensive information on legal, cultural and traditional practices that discriminate against women and girls.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      This part contains general information on number of insurance companies and employees within the sector.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
      Selecionar Conjunto de dados
      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
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
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      This dataset shows data provided by Member countries' authorities through the questionnaire on the state of the environment (OECD/Eurostat), and to Eurostat through the Waste Statistics Regulation. They were updated or revised on the basis of data from other national and international sources available to the OECD Secretariat, and on the basis of comments received from national Delegates. Selected updates were also done in the context of the OECD Environmental Performance Reviews. The data are harmonised through the work of the OECD Working Party on Environmental Information (WPEI) and benefit from continued data quality efforts in OECD member countries, the OECD itself and other international organisations. In many countries systematic collection of environmental data has a short history; sources are typically spread across a range of agencies and levels of government, and information is often collected for other purposes. When interpreting these data, one should keep in mind that definitions and measurement methods vary among countries, and that inter-country comparisons require careful interpretation. One should also note that data presented here refer to national level and may conceal major subnational differences.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
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    • março 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 05 março, 2019
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      This table provides information on the main relevant indicators. The data have mainly been supplied by the World Bank, and cover, where available: -Current Gross National Income (GNI) in US $ millions; -GNI per capita (US $); -Population; -Energy use as kilogram of oil per capita; -Average Life Expectancy of Adults; and -Adult Literacy Rate as a percentage of the country population. Data for Sudan include South Sudan, with the exception of total population, which is reported separately.
    • fevereiro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 27 fevereiro, 2019
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      Bilateral ODA commitments by purpose. Data cover the years 2005 to 2009. Amounts are expressed in USD million. The sectoral distribution of bilateral ODA commitments refers to the economic sector of destination (i.e. the specific area of the recipient's economic or social structure whose development is, or is intended to be fostered by the aid), rather than to the type of goods or services provided. These are aggregates of individual projects notified under the Creditor Reporting System, supplemented by reporting on the sectoral distribution of technical co-operation, and on actual disbursements of food and emergency aid.
    • janeiro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 abril, 2019
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      This data set contains information of The insurance industry is a major component of the economy by virtue of the amount of premiums it collects, the scale of its investment and, more fundamentally, the essential social and economic role it plays by covering personal and business risks. This annual report monitors global insurance market trends to support a better understanding of the insurance industry's overall performance and health.The OECD has collected and analysed data on insurance such as the number of insurance companies and employees, insurance premiums and investments by insurance companies dating back to the early 1980s. Over time, the framework of this exercise has expanded and now includes key balance sheet and income statement items for the direct insurance and reinsurance sector.
    • maio 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 28 junho, 2019
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      Pension assets continued to rise in 2017, exceeding USD 40 trillion in the OECD area for the first time ever, with almost all countries showing positive investment results. This can be attributed to the strong investment performance of pension assets that benefitted from buoyant stock markets
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 16 abril, 2019
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    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      Going for Growth helps to promote sustainable economic growth and improve the well-being of OECD citizens. The surveillance is based on a systematic and in-depth analysis of structural policies and their outcomes across OECD members, relying on a set of internationally comparable and regularly updated policy indicators with a well-established link to performance. From one issue to the next, Going for Growth follows up on these recommendations and priorities evolve, not least as a result of governments taking action, http://www.oecd.org/eco/going-for-growth/. This dataset contains time series of a comprehensive set of quantitative indicators that allow for a comparison of policy settings across OECD countries and selected non-member economies: Argentina, Brazil, China, Colombia, Costa Rica, India, Indonesia, Lithuania, the Russian Federation and South Africa. The dataset covers several areas: Product market regulation (economy-wide and sector-specific regulation), Education, Public investment and subsidies, Taxation, Labour market, Transfers. Data are consistent with those published in the Structural Policy Indicators chapter of Going for Growth 2018. The cut-off date is December 2017.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 29 abril, 2019
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    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
      Selecionar Conjunto de dados
      This dataset contains the number of people who graduated from an education programme by field and sex.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      Graduation/entry rates represent an estimated percentage of an age group expected to graduate/enter a certain level of education at least once in their lifetime.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 10 outubro, 2019
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      This dataset contains selected indicators for monitoring progress towards green growth to support policy making and inform the public at large. The indicator bring together the OECD's statistics, indicators and measures of progress. The dataset covers OECD countries as well as BRIICS economies (Brazil, Russian Federation, India, Indonesia, China and South Africa), and selected countries when possible. The indicators are selected according to well specified criteria and embedded in a conceptual framework, which is structured around four groups to capture the main features of green growth: Environmental and resource productivity, to indicate whether economic growth is becoming greener with more efficient use of natural capital and to capture aspects of production which are rarely quantified in economic models and accounting frameworks; The natural asset base, to indicate the risks to growth from a declining natural asset base; Environmental quality of life, to indicate how environmental conditions affect the quality of life and wellbeing of people; Economic opportunities and policy responses, to indicate the effectiveness ofpolicies in delivering green growth and describe the societal responses needed to secure business and employment opportunities.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      This dataset presents trends in man-made emissions of major greenhouse gases and emissions by gas. Data refer to total emissions of CO2 (emissions from energy use and industrial processes, e.g. cement production), CH4 (methane emissions from solid waste, livestock, mining of hard coal and lignite, rice paddies, agriculture and leaks from natural gas pipelines), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulphur hexafluoride (SF6) and nitrogen trifluoride (NF3). Data exclude indirect CO2.   Intensities (per unit of GDP and per capita) as well as index are calculated on gross direct emissions excluding emissions or removals from land-use, land-use change and forestry (LULUCF).   The GDP used to calculate intensities is expressed in USD at 2010 prices and PPPs.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Gross claims payments in the reporting country, containing a breakdown between domestic companies, foreign-controlled companies and branches and agencies of foreign companies.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 02 julho, 2019
      Selecionar Conjunto de dados
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 17 setembro, 2019
      Selecionar Conjunto de dados
      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.
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 agosto, 2019
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      Productivity is a key driver of economic growth and changes in living standards. Labour productivity growth implies a higher level of output for unit of labour input (hours worked or persons employed). This can be achieved if more capital is used in production or through improved overall efficiency with which labour and capital are used together, i.e., higher multifactor productivity growth (MFP). Productivity is also a key driver of international competitiveness, e.g. as measured by Unit Labour Costs (ULC).   The OECD Productivity Database aims at providing users with the most comprehensive and the latest productivity estimates. The update cycle is on a rolling basis, i.e. each variable in the dataset is made publicly available as soon as it is updated in the sources databases. However, some time lag may arise which affects individual series and/or countries for two reasons: first, hours worked data from the OECD Employment Outlook are typically updated less frequently than the OECD Annual National Accounts Database; second, source data for capital services are typically available in annual national accounts later than source data for labour productivity and ULCs.   Note to users: The OECD Productivity Database accounts for the methodological changes in national accounts' statistics, such as the implementation of the System of National Accounts 2008 (2008 SNA) and the implementation of the international industrial classification ISIC Rev.4. These changes had an impact on output, labour and capital measurement. For Chile, China, Colombia, India, Japan, Turkey and the Russian Federation the indicators are in line with the System of National Accounts 1993 (1993 SNA); for all other countries, the indicators presented are based on the 2008 SNA
  • H
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 13 agosto, 2019
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    • novembro 2017
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 13 novembro, 2017
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      Cancer follow up has been given for the range of 5 years. The highest range has been considered as for this period, for example 1995-2000 is considered as 2000.
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 06 agosto, 2019
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      OECD Health Data 2016 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      OECD Health Data 2017 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.B1:B4
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 09 julho, 2019
      Selecionar Conjunto de dados
      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.
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 06 agosto, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
      Selecionar Conjunto de dados
      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.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 02 julho, 2019
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    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 outubro, 2019
      Selecionar Conjunto de dados
      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.
  • I
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 abril, 2019
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    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 22 agosto, 2019
      Selecionar Conjunto de dados
      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.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 16 abril, 2019
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      The ICT Access and Usage by Households and Individuals database provides a selection of 92 indicators, based on the of 2nd revision of the OECD Model Survey on ICT Access and Usage by Households and Individuals.The selected indicators originate from two sources:1. An OECD data collection on the following OECD and accession countries or key partners: Australia, Brazil, Canada, Costa Rica, Chile, Colombia, Israel, Japan, Korea, Mexico, New Zealand, Switzerland, and the United States. Data collection methodology followed by these countries is available in each respective country metadata file.2. Eurostat Statistics on Households and Individuals for the OECD countries that are part of the European Statistical system. For those countries, indicators shown in this database refer to the original indicator as published by EUROSTAT -see the correspondence table-. Please refer to Eurostat methodology to access the methodological information.For all countries, breakdowns used correspond to those of EUROSTAT, unless otherwise stated in the metadata.
    • janeiro 2008
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 22 setembro, 2014
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      ICT goods are those that are either intended to fulfil the function of information processing and communication by electronic means, including transmission and display, OR which use electronic processing to detect, measure and/or record physical phenomena, or to control a physical process. ICT goods are defined by the OECD in terms of the Harmonised System. The guiding principle for the delineation of ICT goods is that such goods must either be intended to fulfil the function of information processing and communication by electronic means, including transmission and display, OR use electronic processing to detect, measure and/or record physical phenomena, or to control a physical process.Another guiding principle was to use existing classification systems in order to take advantage of existing data sets and therefore ensure the immediate use of the proposed standard. In this case, the underlying system is the Harmonized System (HS). The HS is the only commodity classification system used on a sufficiently wide basis to support international data comparison. A large number of countries use it to classify export and import of goods, and many countries use it (or a classification derived from or linked to it) to categorise domestic outputs.The application of the ICT product definition to selection of in-scope HS categories is a somewhat subjective exercise. The fact that the HS is not built on the basis of the functionality of products makes it much more difficult. The distinction between products which fulfil those functions and products that simply embody electronics but fundamentally fulfil other functions is not always obvious.It is possible to adopt a narrow or broad interpretation of the guideline, though the OECD chose a broader interpretation, an approach which is consistent with that adopted to develop the ICT sector definition.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 16 abril, 2019
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      NOTE FOR THIS DATA CUBEFor all indicators provided in this cube, value are expressed as percentage of Internet users.For each country (except for Costa Rica -see below-), the value of the indicators provided in this cube are based on data from the ICT Access and Usage by Households and Individuals database, and metadata and sources are strictly identical.Internet users generally relate to a recall period of 3 months or 12 months as indicated below. For exceptions, see the country metadata in the ICT Access and Usage by Households and Individuals database.For Australia, 12 months before 2014, 3 months from 2014 onwards.For Canada, Colombia and Japan, 12 months.For Israel, Costa Rica and the United States, 3 months.For New Zealand, 12 months in 2006.For Chile, Korea, Mexico, New Zeland (2006 excepted), Switzerland and Brazil: 1. For indicators starting with D1, I3 and I9, Internet users relate to a recall period of 3 months; 2. For indicators starting with F1, Internet users relate to a recall period of 3 months untill 2007 and of 12 months from 2008 onwards; 3. For the remaining indicators, Internet users relate to a recall period of 12 months.For Costa Rica, data are OECD estimates based on data provided by the National Institute of Statistics and Censuses and by the Ministry of Science, Technology and Telecommunications (MICITT), and for all the indicators, Internet users relate to a recall period of 3 months.For the remaining countries (all from Eurostat): 1. For indicators starting with D1, Internet users relate to a recall period of 3 months; 2. For indicators starting with F1, Internet users relate to a recall period of 3 months untill 2007 and of 12 months from 2008 onwards; 3. For the remaining indicators, Internet users relate to a recall period of 12 months.
    • dezembro 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 dezembro, 2018
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      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.
    • março 2016
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 novembro, 2017
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      The sources for this database are mainly census data, from the 2000 round of censuses. Census data were used for 22 countries. Countries not taking periodic censuses but keeping population registers have provided data extracted from these registers; this is the case for four countries: Denmark, Finland, Norway and Sweden. For some countries, not all themes covered in the database are present in the national census or register. Labour force surveys, provided by Eurostat and averaged over the period 1998-2002, have been used to fill the gaps where possible.
    • dezembro 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 dezembro, 2018
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      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.
    • dezembro 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 dezembro, 2018
      Selecionar Conjunto de dados
      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.
    • dezembro 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 dezembro, 2018
      Selecionar Conjunto de dados
      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.
    • março 2016
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 novembro, 2017
      Selecionar Conjunto de dados
      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.
    • dezembro 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 dezembro, 2018
      Selecionar Conjunto de dados
      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).
    • dezembro 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 dezembro, 2018
      Selecionar Conjunto de dados
      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.
    • julho 2014
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 04 agosto, 2014
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      The allocation of bilateral intermediate imports across using industries assumes that import coefficients are the same for all trade partners, i.e. SHAREipkt is identical across exporter countries. Hence, the bilateral pattern of imported intermediates from industry p is the same across all using industries k. However, it is different from the bilateral pattern of total imports from industry p because trade data (measured by VALUEijpt) allows distinguishing bilateral imports of intermediates from final good imports in industry p. While the BEC classification enables the identification of intermediate goods, no similar classification is available for trade in services, due to the high level of aggregation in services trade data. While goods trade data are based on customs declarations allowing the identification of goods at a highly disaggregated level, services trade data are based on a variety of information such as business accounts, administrative sources, surveys, and estimation techniques (Manual on Statistics of International Trade in Services, 2002). Hence, in the case of trade in services, VALUEijpt is the total value of imports of service p, i.e. both final and intermediate (and not only services that are used in the production of other goods and services, as in the case of goods data). By making an additional assumption and adjusting SHAREipkt, it is however possible to calculate trade in intermediate services. In the case of services imports, SHAREipkt is the share of imported service inputs p used by industry k in total imports of p of country i. In the case of services, besides the assumption that all trading partners have the same distribution of intermediate imports p across using industries k, it is furthermore required that the share of intermediate services in overall bilateral services imports of country i is the same across all partner countries j. Finally, it should be mentioned that trade data reported in the trade statistics do not fully match imports as reported in I-O tables. One main reason is that while trade data is recorded at consumer prices, I-O tables are evaluated at producer prices. There are also other differences such as the treatment of re-exports, scrap metal, waste products and second hand goods or unallocated trade data.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 outubro, 2019
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    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 02 julho, 2019
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      This table contains data on the cross-country distribution of employment by hour bands for declared hour bands, broken down by professional status - employees, total employment - sex and detailed age groups.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 05 julho, 2019
      Selecionar Conjunto de dados
      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.
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 06 agosto, 2019
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      This table contains incidences and gender composition of part-time employment with standardised (15-24, 25-54, 55-64, 65+, total) and detailed age groups. Data are further broken down by professional status - employees, total employment. Part-time employment is based on national definitions. The definition of part-time work varies considerably across OECD countries Essentially three main approaches can be distinguished: i) a classification based on the worker's perception of his/her employment situation; ii) a cut-off (generally 30 or 35 hours per week) based on usual working hours, with persons usually working fewer hours being considered part-timers; iii) a comparable cut-off based on actual hours worked during the reference week. A criterion based on actual hours will generally yield a part-time rate higher than one based on usual hours, particularly if there are temporary reductions in working time as a result of holidays, illness, short-timing, etc. On the other hand, it is not entirely clear whether a classification based on the worker's perception will necessarily yield estimates of part-time work that are higher or lower than one based on a fixed cut-off. In one country (France) which changed from 1981 to 1982 from a definition based on an actual hours cut-off (30 hours) to one based on the respondent's perception, the latter criterion appeared to produce slightly higher estimates. Other data characteristics
    • junho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 21 junho, 2019
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      This table contains incidences and gender composition of temporary employment with standardized age groups (15-24, 25-54, 55-64, 65+, total). Data are further broken down by professional status - employees, total employment. Unit of measure used - Data are expressed in percentages.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 05 julho, 2019
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      This table contains data on the share of the five durations - less than 1 month,>1 month and < 3 months,>3 months and <6 months,>6 months and <1 year, 1 year and over - of unemployment among total unemployment by sex and by standardised age groups (15-19, 15-24, 20-24, 25-54, 55+, total). Unit of measure used - Data expressed in percentages.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 02 julho, 2019
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      http://www.oecd.org/els/soc/IDD-Metadata.pdf
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 02 julho, 2019
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    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      Institutional Investors' Assets and Liabilities data are reported by Central Banks, National Statistical Institutes or Supervisory Authorities. The indicators reported here are compiled on the basis of those statistics.   The first set of indicators measure total financial assets (liabilities) held by each institutional investor as a percentage of GDP. Total financial assets (liabilities) is defined as the sum of the following asset (liability) categories: currency and deposits (F2), debt securities (F3), loans (F4), equity and investment fund shares (F5), insurance pension and standardized guarantee schemes (F6), financial derivatives and employee stock options (F7), and other accounts receivable (payable) (F8). The second set of indicators shows the share of each asset (liability) category in the total financial assets (liabilities) of each investor. They help to analyse the investment portfolio composition of the investor as well as financial risks borne by the investor. The third set of indicators shows the sub-sector composition of total financial assets (liabilities) by investor category, by showing the share of each sub-sector in the total financial assets (liabilities) of each investor category.
    • junho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 18 junho, 2019
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    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 18 outubro, 2019
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      This dataset presents internationally comparable data on instruction time in full-time compulsory education. It covers primary and (lower and upper) secondary general education, but excludes pre-primary education, even if compulsory. Total number of instruction hours and the distribution of hours per subject is available either by level of education or by age.
    • maio 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 28 maio, 2019
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      These data are part of a larger database, hosted on a different website, which includes both quantitative and qualitative data, as well as graphs.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Breakdown of net premiums written in the reporting country in terms of domestic risks and foreign risks, thus providing an indicator of direct cross-border operations of insurance business.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 17 setembro, 2019
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      This data deals with premiums written by classes of non-life insurance for the business written in the reporting country.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 10 outubro, 2019
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      Geographic coverage OECD countries, Selected African and Asian countries, Selected Latin American countries Institutional coverage The insurance industry is a key component of the economy by virtue of the amount of premiums it collects, the scale of its investment and, more fundamentally, the essential social and economic role it plays in covering personal and business risks. The "OECD Insurance Statistics" publication provides major official insurance statistics for all OECD countries. The reader will find information on the diverse activities of this industry and on international insurance market trends. The data, which are standardised as far as possible, are broken down under numerous sub-headings, and a series of indicators makes the characteristics of the national markets more readily comprehensible. This publication is an essential tool for civil servants, businessmen and academics working in the insurance field. Item coverage This part consists of tables by indicators, which reflect the most significant characteristics of the OECD insurance market. In most cases, the tables contain data of all OECD countries as well as aggregated "OECD", "EU15" (the 15 member countries of the European Union in 1995) and "NAFTA" data from 1983 to 2015, for the following categories: - life insurance, - non-life insurance - and total. The premiums amounts are converted from national currencies into US dollar. Exchange rates used are end-of-period exchanges rates for all variables valued at the end of the year, and period-average for variables representig a flow during the year.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 14 julho, 2019
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      This dataset contains the number of people who graduated from an education programme by country of origin and sex.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      Most of the data published in this database are taken from the individual contributions of national correspondents appointed by the OECD Secretariat with the approval of the authorities of Member countries. Consequently, these data have not necessarily been harmonised at international level. This network of correspondents, constituting the Continuous Reporting System on Migration (SOPEMI), covers most OECD Member countries as well as the Baltic States, Bulgaria and Romania. SOPEMI has no authority to impose changes in data collection procedures. It is an observatory which, by its very nature, has to use existing statistics. However, it does play an active role in suggesting what it considers to be essential improvements in data collection and makes every effort to present consistent and well-documented statistics.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 16 abril, 2019
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      This indicator reports the percentage of students of each country of origin over the total of international students.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      This dataset presents official international trade statistics in fisheries products, directly sourced from the UN Comtrade Database.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 02 julho, 2019
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      This table contains figures on affiliates under foreign control by investing country in the total manufacturing, total services and total business enterprise sectors.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 14 julho, 2019
      Selecionar Conjunto de dados
    • julho 2014
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 04 agosto, 2014
      Selecionar Conjunto de dados
      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.
  • K
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 outubro, 2019
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      The Key Economic Indicators (KEI) database contains monthly and quarterly statistics (and associated statistical methodological information) for all OECD member countries and for a selection of non-member countries on a wide variety of economic indicators, namely: quarterly national accounts, industrial production, composite leading indicators, business tendency and consumer opinion surveys, retail trade, consumer and producer prices, hourly earnings, employment/unemployment, interest rates, monetary aggregates, exchange rates, international trade and balance of payments.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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  • L
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 02 julho, 2019
      Selecionar Conjunto de dados
      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
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 abril, 2019
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    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
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      Land resources are one of the four components of the natural environment: water, air, land and living resources. In this context land is both: a physical "milieu" necessary for the development of natural vegetation as well as cultivated vegetation; a resource for human activities. The data presented here give information concerning land use state and changes (e.g. agricultural land, forest land). Land area excludes area under inland water bodies (i.e. major rivers and lakes). Arable refers to all lan generally under rotation, whether for temporary crops (double-cropped areas are counted only once) or meadows, or left fallow (less than five years). These data are not meant to indicate the amount of land that is potentially cultivable. Permanent crops are those that occupy land for a long period and do not have to be planted for several years after each harvest (e.g. cocoa, coffee, rubber). Land under vines and trees and shrubs producing fruits, nuts and flowers, such as roses and jasmine, is so classified, as are nurseries (except those for forest trees, which should be classified under "forests and other wooded land"). Arable and permanent crop land is defined as the sum of arable area and land under permanent crops. Permanent meadows and pastures refer to land used for five years or more to grow herbaceous forage crops, either cultivated or growing wild (wild prairie or grazing land). Forest refers to land spanning more than 0.5 hectare (0.005 km2) and a canopy cover of more than 10 percent, or trees able to reach these thresholds in situ. This includes land from which forests have been cleared but that will be reforested in the foreseeable future. This excludes woodland or forest predominantly under agricultural or urban land use and used only for recreation purposes. Other areas include built-up and related land, wet open land, and dry open land, with or without vegetation cover. Areas under inland water bodies (rivers and lakes) are excluded. The definitions used in different countries may show variations.
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 agosto, 2019
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      The productivity and income estimates presented in this dataset are mainly based on GDP, population and employment data from the OECD Annual National Accounts. Hours worked are sourced from the OECD Annual National Accounts, the OECD Employment Outlook and national sources. The OECD Productivity Database aims at providing users with the most comprehensive and the latest productivity estimates. The update cycle is on a rolling basis, i.e. each variable in the dataset is made publicly available as soon as it is updated in the sources databases. However, timely data issues may arise and affect individual series and/or individual countries. In particular, annual hours worked estimates from the OECD Employment Outlook are typically updated less frequently (once a year, in the summer) than series of hours worked from the OECD Annual National Accounts.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 06 julho, 2019
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      This table contains labour force data on labour market status - population, labour force, unemployment and employment - by sex and by detailed age groups and standard age groups (15-24, 25-54, 55-64, 65+, total). Note: Population figures reported in table LFS by sex are Census-based, while the data for this table are taken from labour force surveys. Population for total age group refers to working age population (15 to 64 years).
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 13 agosto, 2019
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      This dataset contains the age composition (as a percentage of all ages) of the population for each labour force status - labour force, employment, unemployment - by sex.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 06 julho, 2019
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      This table contains data on labour force participation rates, employment/population ratios and unemployment rates for both the total labour force and civilian labour force by sex. There are data for both the total age group and the working age population (ages 15 to 64). This table also contains data on the share of civilian employment by sex.
  • M
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      This dataset contains the number of Management personnel and teacher aides in educational institutions by sex and intensity.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
      Selecionar Conjunto de dados
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 23 julho, 2019
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      The Maritime Transport Costs (MTC)database contains data from 1991 to the most recent available year of bilateral maritime transport costs. Transport costs are available for 43 importing countries (including EU15 countries as a custom union) from 218 countries of origin at the detailed commodity (6 digit) level of the Harmonized System 1988. This dataset should only be used in conjunction with the paper Clarifying Trade Costs in Maritime Transport which outlines methodology, data coverage and caveats to its use. Key Statistical Concept Import charges represent the aggregate cost of all freight, insurance and other charges (excluding import duties) incurred in bringing the merchandise from alongside the carrier at the port of export and placing it alongside the carrier at the first port of entry in the importing country. Insurance charges are therefore included in the transport cost variables and are estimated to be approximately 1.5% of the import value of the merchandise.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 09 julho, 2019
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      The data presented come from two international sources: (1) UN and International Resource Panel "Global Material Flows Database" for non-EU OECD and non-OECD countries, and (2) Eurostat  "Material Flows and Resource Productivity" database for EU OECD countries. It should be born in mind that the data should be interpreted with caution and that the time series presented here may change in future as work on methodologies for MF accounting progresses. Furthermore, data contain rough estimates for OECD and BRIICS aggregates. These data refer to material resources, i.e. materials originating from natural resources that form the material basis of the economy: metals (ferrous, non-ferrous) non-metallic minerals (construction minerals, industrial minerals), biomass (wood, food) and fossil energy carriers. The use of materials in production and consumption processes has many economic, social and environmental consequences. These consequences often extend beyond the borders of countries or regions, notably when materials are traded internationally, either in the form of raw materials or as products embodying them. They differ among the various materials and among the various stages of the resource life cycle (extraction, processing, use, transport, end-of-life management). From an environmental point of view these consequences depend on:the rate of extraction and depletion of renewable and non-renewable resource stocksthe extent of harvest and the reproductive capacity and natural productivity of renewable resourcesthe associated environmental burden (e.g. pollution, waste, habitat disruption), and its effects on environmental quality (e.g. air, water, soil, biodiversity, landscape) and on related environmental services These data inform about physical flows of material resources at various levels of detail and at various stages of the flow chain. The information shows: a) the material basis of economies and its composition by major material groups, considering:the extraction of raw materials;the trade balance in physical terms;the consumption of materials;the material inputs b) the consumption of selected materials that are of environmental and economic significance. c) in-use stocks of selected products that are of environmental and economic significance. Domestic extraction used (DEU) refers to the flows of raw materials extracted or harvested from the environment and that physically enter the economic system for further processing or direct consumption (they are used by the economy as material factor inputs). Imports (IMP) and exports (EXP) are major components of the direct material flow indicators DMI (domestic material input) and DMC (domestic material consumption). They cannot be taken as indication of domestic resource requirements. Domestic material consumption (DMC) refers to the amount of materials directly used in an economy, which refers to the apparent consumption of materials. DMC is computed as DEU minus exports plus imports. Direct material input (DMI) is computed as DEU plus imports. The material groups are: Food: food crops (e.g. cereals, roots, sugar and oil bearing crops, fruits, vegetables), fodder crops (including grazing), wild animals (essentially marine catches), small amounts of non-edible biomass (e.g. fibres, rubber), and related products including livestock. Wood: harvested wood and traded products essentially made of wood (paper, furniture, etc.). Construction minerals: non-metallic construction minerals whether primary or processed. They comprise marble, granite, sandstone, porphyry, basalt, other ornamental or building stone (excluding slate); chalk and dolomite; sand and gravel; clays and kaolin; limestone and gypsum. Industrial minerals: non-metallic industrial minerals whether primary or processed (e.g. salts, arsenic, potash, phosphate rocks, sulphates, asbestos). Metals: metal ores, metals and products mainly made of metals. Fossil energy materials/carriers: coal, crude oil, natural gas and peat, as well as manufactured products predominantly made of fossil fuels (e.g. plastics, synthetic rubber).
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 17 setembro, 2019
      Selecionar Conjunto de dados
      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.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      This dataset contains statutory and national minimum wages in place in 27 OECD Member countries, Brazil, Colombia, Costa Rica, Lithuania, Malta, Romania and the Russian Federation.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 outubro, 2019
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      The International Trade (MEI) dataset contains predominantly monthly merchandise trade statistics, and associated statistical methodological information, for all OECD member countries and for all non-OECD G20 economies and the EU.   The dataset itself contains international trade statistics measured in billions of United States dollars (USD) for: Exports, Imports, Balance. In all cases a lot of effort has been made to ensure that the data are internationally comparable across all countries presented and that all the subjects have good historical time-series’ data to aid with analysis.
    • dezembro 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 11 dezembro, 2018
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      Air pollution is considered one of the most pressing environmental and health issues across OECD countries and beyond. According to the World Health Organisation (WHO), exposure to fine particulate matter (PM2.5) and ground-level ozone (O3) have potentially the most significant adverse effects on health compared to other pollutants. PM2.5 can be inhaled and cause serious health problems including both respiratory and cardiovascular disease, having its most severe effects on children and elderly people. Exposure to PM2.5 has been shown to considerably increase the risk of heart disease and stroke in particular. For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator. Exposure to ground-level ozone (O3) has serious consequences for human health, contributing to, or triggering, respiratory diseases. These include breathing problems, asthma and reduced lung function (WHO, 2016; Brauer et al., 2016). Ozone exposure is highest in emission-dense countries with warm and sunny summers. The most important determinants are background atmospheric chemistry, climate, anthropogenic and biogenic emissions of ozone precursors such as volatile organic compounds, and the ratios between different emitted chemicals.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      This dataset shows data provided by Member countries' authorities through the questionnaire on the state of the environment (OECD/Eurostat). They were updated or revised on the basis of data from other national and international sources available to the OECD Secretariat, and on the basis of comments received from national Delegates. Selected updates were also done in the context of the OECD Environmental Performance Reviews. The data are harmonised through the work of the OECD Working Party on Environmental Information (WPEI) and benefit from continued data quality efforts in OECD member countries, the OECD itself and other international organisations. In many countries systematic collection of environmental data has a short history; sources are typically spread across a range of agencies and levels of government, and information is often collected for other purposes. When interpreting these data, one should keep in mind that definitions and measurement methods vary among countries, and that inter-country comparisons require careful interpretation. One should also note that data presented here refer to national level and may conceal major subnational differences. This dataset presents trends in amounts of municipal (including household waste), and the treatment and disposal method used. The amount of waste generated in each country is related to the rate of urbanisation, the types and pattern of consumption, household revenue and lifestyles.
  • N
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
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      It presents gross capital formation, gross fixed capital formation, changes in inventories and acquisition less disposals of valuables broken down by detailed industries according to the classification ISIC rev.4. Gross fixed capital formation is also available broken down by type of assets. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA. Unit of measure used - In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2005). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
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      It presents fixed assets by activity according to the classification ISIC rev.3 and by type of product and by type of assets.  It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. In national currency, in current prices and constant prices (national base year and OECD base year i.e. 2010). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
      Selecionar Conjunto de dados
      It presents the balance sheets for non financial assets by institutional sectors, for both produced assets (fixed assets, inventories, valuables) and non-produced assets (tangible and intangible).  It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA. Unit of measure used - In national currency expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 10 outubro, 2019
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      This dataset presents information using an "indicator" approach, focusing on cross-country comparisons. The aim is to make the accounts more accessible and informative, whilst taking the opportunity to present the conceptual underpinning  and comparability issues of each of the indicators presented. The range of indicators is set deliberately wide to reflect the richness of the national accounts dataset and to encourage users of economic statistics to refocus some of the spotlight that is often placed on GDP to other important economic indicators, which may better respond to their needs. Indeed many users themselves have been instrumental in this regard. The report of the Commission on the Measurement of Economic Performance and Social Progress (Stiglitz-Sen-Fitoussi Commission) is but one notable example. That is not to undermine the importance of GDP, which arguably remains the most important measure of total economic activity, but other measures may better reflect other aspects of the economy. For example, net national income may be a more appropriate measure of income available to citizens in countries with large outflows of property income, and household adjusted disposable income per capita may be a better indicator of the material well-being of citizens. But certainly from a data perspective more can and remains to be done. The Stiglitz-Sen-Fitoussi Commission for example highlights the pressing need for the provision, by official statistics institutes, of more detailed information that better describes the distributional aspects of activity, especially income, and the need to build on the national accounts framework to address issues such as non-market services produced by households or leisure. It is hoped that by producing a publication such as this and thereby raising awareness, the momentum from this and other initiatives will be accelerated. The publication itself will pick up new indicators in the future as they become available at the OECD.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
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      It presents the whole set of non financial accounts, from the production account to the acquisitions of non-financial assets accounts. For general government sector, property income, other current transfers and capital transfers are consolidated..
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 abril, 2019
      Selecionar Conjunto de dados
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 abril, 2019
      Selecionar Conjunto de dados
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
      Selecionar Conjunto de dados
      It presents the whole set of non financial accounts, from the production account to the acquisitions of non-financial assets accounts. For general government sector, property income, other current transfers and capital transfers are consolidated.. It has been prepared from statistics reported to the OECD by Member countries in their answers to the new version of the annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
      Selecionar Conjunto de dados
      It presents gross capital formation, gross fixed capital formation, changes in inventories and acquisition less disposals of valuables broken down by detailed industries. Gross fixed capital formation is also available broken down by type of assets. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA. Unit of measure used - In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2010). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
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      It presents the different transactions and balances to get from the GDP to the net lending/net borrowing. Therefore, it includes, in particular, national disposable income (gross and net), consumption of fixed capital as well as net saving.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
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      It presents the final consumption expenditure of households broken down by the COICOP (Classification of Individual Consumption According to Purpose) classification and by durability.  It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA. In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2010). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
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      It provides a faithful image, to the greatest extent possible, of the aggregates and balances of the general government sector in the SNA 1993 conceptual framework. In addition, it brings to light two relevant aggregates that do not belong to this conceptual frame work: the Total Revenue and the Total Expenditure of the general government sector. Unit of measure used - National currency; current prices. Expressed in millions.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 04 outubro, 2019
      Selecionar Conjunto de dados
      Annual National Accounts>General Government Accounts>750. General Government Debt-Maastricht   Unit of measure used: National currency; current prices. Expressed in millions   Statistical population: Government debt as defined in the Maastricht Treaty (Source : Eurostat). Available for Europeans countries only. In the Protocol on the excessive deficit procedure annexed to the Maastricht Treaty, government debt is defined as the debt of the whole general government sector: gross, consolidated and nominal value (face value). It excludes the other accounts payable (AF.7), as well as, if they exist, insurance technical reserve (AF.6).
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      It provides a breakdown of government expenditure according to their function. To meet this end, economic flows of expenditure must be aggregated according to the Classification of the Functions of Government (COFOG).
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 23 julho, 2019
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      It presents the three approaches of the GDP: expenditure based, output based and income based. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
      Selecionar Conjunto de dados
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 16 outubro, 2019
      Selecionar Conjunto de dados
      Annual National Accounts>Detailed Tables and Simplified Accounts>7A. Labour input by activity, ISIC rev4   Unit of measure used: In persons, full-time equivalents, jobs and hours.   Statistical population: It presents employment, broken down by detailed industries according to the classification ISIC rev.4. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
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      It presents population data and employment by main activity. It includes national concept data for economically active population, unemployed persons, total employment, employees and self-employed, as well as domestic concept data for total employment, employees and self-employed. The domestic concept data are available broken down by main activity. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
      Selecionar Conjunto de dados
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
      Selecionar Conjunto de dados
      It presents simplified non-financial accounts, from the gross value added to the net lending/net borrowing. In this table, the total economy is broken down in three main institutional sectors: corporations, general government, households and non-profit institutions serving households. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA. Unit of measure used - In national currency, in current prices. Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 09 julho, 2019
      Selecionar Conjunto de dados
      Annual National Accounts>Supply and Use Tables>30. Supply at basic prices and its transformation into purchasers' prices   Unit of measure used: In national currency, in current prices and previous year prices. Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.   Statistical population: It presents the Supply table at basic prices and its transformation into purchaser's prices. It provides information by industry (at the 2 digit ISIC Rev 4 level, containing 89 industries) with corresponding breakdowns by product (using the comparable CPA product breakdown). It has been prepared from statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 02 julho, 2019
      Selecionar Conjunto de dados
      Annual National Accounts>Supply and Use Tables>SUT Indicators>SUT Indicators   Statistical population: These indicators are calculated by the OECD from the SUT statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.   Key statistical concept: The supply table describes the supply of goods and services, which are either produced in the domestic industry or imported. The use table shows where and how goods and services are used in the economy. Therefore in addition to their essential role to better estimations of National Accounts, Supply and Use tables are also a very powerful tool to understand the impact of policy decisions and globalisation, as they provide a detailed analysis of the process of production and the use of goods and services. For example, the Supply and Use Tables could be used to measure the the percentage of imports used in the production process or the share of trade and transport margins in the households’ final consumption expenditure.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 09 julho, 2019
      Selecionar Conjunto de dados
      Annual National Accounts>Supply and Use Tables>31. Supply, Output and its components by industries   Unit of measure used: In national currency, in current prices and previous year prices. Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.   Statistical population: It presents the breakdown of output at basic prices between market output, output for own final use and non-market output, by activty at the 2 digit ISIC Rev 4 level. It has been prepared from statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
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      It provides a faithful image, to the greatest extent possible, of the aggregates and balances of the general government sector Data are also available, for most countries, for the sub-sectors of general government.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 16 outubro, 2019
      Selecionar Conjunto de dados
      Annual National Accounts>Supply and Use Tables>40. Use at purchasers' prices   Unit of measure used: In national currency, in current prices and previous year prices. Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.   Statistical population: It presents the Use table at purchaser's prices. It provides information by industry (at the 2 digit ISIC Rev 4 level, containing 89 industries) with corresponding breakdowns by product (using the comparable CPA product breakdown). It has been prepared from statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.
    • maio 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 29 maio, 2019
      Selecionar Conjunto de dados
      Annual National Accounts
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 06 agosto, 2019
      Selecionar Conjunto de dados
      Annual National Accounts
    • junho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 21 junho, 2019
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      Statistical population: Its presents output, intermediate consumption and the gross value added and its components, in particular compensation of employees and gross operating surplus and mixed income, broken down by detailed industries according to the classification ISIC rev.4. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. Unit of measure used: In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2010). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.   Note: 6A. Value added and its components by activity, ISIC rev4
    • junho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 25 junho, 2019
      Selecionar Conjunto de dados
      Statistical population: Its presents output, intermediate consumption and the gross value added and its components, in particular compensation of employees and gross operating surplus and mixed income, broken down by detailed industries. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. Data presented in this table will not be updated after summer 2010. Data reported to the OECD by countries in their answers to the annual national accounts questionnaire are now available on theme Industry and Services, Structural Analysis (STAN) Databases. Unit of measure used: In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2010). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      This dataset presents the number of new entrants in a given programme by age and sex.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      This dataset presents the number of new entrants in a given programme by field and sex.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
      Selecionar Conjunto de dados
      This dataset contains the number of people who graduated from an education programme by age and sex.
  • O
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 outubro, 2019
      Selecionar Conjunto de dados
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 14 julho, 2019
      Selecionar Conjunto de dados
      This OECD inventory maps existing cross-country surveys that provide information on the characteristics of people's jobs. The information included in this inventory covers international surveys conducted since the early 1990s that are based on individuals' self-reported assessment of their current job, for 160 countries over 25 years. Survey questions are grouped into 19 indicators. For each indicator, binary codes (1 and 0) show whether indicators are available or not for the various countries and years. The inventory also provides users with detailed documentation on the questions used in the various surveys for measuring these indicators.
    • junho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 04 junho, 2019
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      The OECD Science, Technology and Industry Outlook reviews key trends in STI policies and performance in OECD countries and major emerging economies. It is published every two years and draws on a unique international policy survey conducted by the OECD - with more than 45 countries involved in 2014 - and the latest OECD work on STI policy analysis and measurement. Following an overview of the recent STI global landscape, key current policy issues are discussed across a series of thematic policy profiles. Country profiles report the STI performance of individual countries and the most recent national policy developments.
    • maio 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 29 maio, 2019
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      Other official flows are official sector transactions which do not meet the ODA criteria, e.g.:  i.) Grants to developing countries for representational or essentially commercial purposes;  ii.) Official bilateral transactions intended to promote development but having a grant element of less than 25 per cent;  iii.) Official bilateral transactions, whatever their grant element, that are primarily export-facilitating in purpose. This category includes by definition export credits extended directly to an aid recipient by an official agency or institution ("official direct export credits");  iv.) The net acquisition by governments and central monetary institutions of securities issued by multilateral development banks at market terms;  v.) Subsidies (grants) to the private sector to soften its credits to developing countries [see Annex 3, paragraph A3.5.iv)b)];  vi.) Funds in support of private investment.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
      Selecionar Conjunto de dados
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 02 julho, 2019
      Selecionar Conjunto de dados
      This table contains figures on the activity of affiliates located abroad by host country in the total manufacturing, total services and total business enterprise sectors. The units used to present data in AMNE are millions of national currency for monetary variables and units for the other variables. Monetary variables are in current prices. Euro-area countries: national currency data is expressed in euro beginning with the year of entry into the Economic and Monetary Union (EMU). For years prior to the year of entry into EMU, data have been converted from the former national currency using the appropriate irrevocable conversion rate. This presentation facilitates comparisons within a country over time and ensures that the historical evolution is preserved. Please note, however, that pre-EMU euro are a notional unit and should not be used to form area aggregates or to carry out cross-country comparisons.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 23 abril, 2019
      Selecionar Conjunto de dados
      This table contains figures on the activity affiliates located abroad by industry according to the International Standard Industrial Classification (ISIC Revision 4). The units used to present data in AMNE are millions of national currency for monetary variables and units for the other variables. Monetary variables are in current prices. Euro-area countries: national currency data is expressed in euro beginning with the year of entry into the Economic and Monetary Union (EMU). For years prior to the year of entry into EMU, data have been converted from the former national currency using the appropriate irrevocable conversion rate. This presentation facilitates comparisons within a country over time and ensures that the historical evolution is preserved. Please note, however, that pre-EMU euro are a notional unit and should not be used to form area aggregates or to carry out cross-country comparisons.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
      Selecionar Conjunto de dados
  • P
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 06 agosto, 2019
      Selecionar Conjunto de dados
      The OECD Environment Directorate, in collaboration with the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in environment-related technologies. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' environmental and innovation policies. The patent statistics presented here are constructed using data extracted from the Worldwide Patent Statistical Database (PATSTAT) of the European Patent Office (EPO) using algorithms developed by the OECD. Consistent with other patent statistics provided in OECD.Stat, only published applications for "patents of invention" are considered (i.e. excluding utility models, petty patents, etc.). The relevant patent documents are identified using search strategies for environment-related technologies (ENV-TECH) which were developed specifically for this purpose. They allow identifying technologies relevant to environmental management, water-related adaptation and climate change mitigation. An aggregate category labelled "selected environment-related technologies" includes all of the environmental domains presented here.
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 06 agosto, 2019
      Selecionar Conjunto de dados
      The OECD Environment Directorate, in collaboration with the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in environment-related technologies. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' environmental and innovation policies. The patent statistics presented here are constructed using data extracted from the Worldwide Patent Statistical Database (PATSTAT) of the European Patent Office (EPO) using algorithms developed by the OECD. Consistent with other patent statistics provided in OECD.Stat, only published applications for "patents of invention" are considered (i.e. excluding utility models, petty patents, etc.). The relevant patent documents are identified using search strategies for environment-related technologies (ENV-TECH) which were developed specifically for this purpose. They allow identifying technologies relevant to environmental management, water-related adaptation and climate change mitigation. An aggregate category labelled "selected environment-related technologies" includes all of the environmental domains presented here.
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 06 agosto, 2019
      Selecionar Conjunto de dados
      The OECD Environment Directorate, in collaboration with the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in environment-related technologies. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' environmental and innovation policies. The patent statistics presented here are constructed using data extracted from the Worldwide Patent Statistical Database (PATSTAT) of the European Patent Office (EPO) using algorithms developed by the OECD. Consistent with other patent statistics provided in OECD.Stat, only published applications for "patents of invention" are considered (i.e. excluding utility models, petty patents, etc.). The relevant patent documents are identified using search strategies for environment-related technologies (ENV-TECH) which were developed specifically for this purpose. They allow identifying technologies relevant to environmental management, water-related adaptation and climate change mitigation. An aggregate category labelled "selected environment-related technologies" includes all of the environmental domains presented here.
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 21 agosto, 2019
      Selecionar Conjunto de dados
      The OECD Environment Directorate, in collaboration with the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in environment-related technologies. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' environmental and innovation policies. The patent statistics presented here are constructed using data extracted from the Worldwide Patent Statistical Database (PATSTAT) of the European Patent Office (EPO) using algorithms developed by the OECD. Consistent with other patent statistics provided in OECD.Stat, only published applications for "patents of invention" are considered (i.e. excluding utility models, petty patents, etc.). The relevant patent documents are identified using search strategies for environment-related technologies (ENV-TECH) which were developed specifically for this purpose. They allow identifying technologies relevant to environmental management, water-related adaptation and climate change mitigation. An aggregate category labelled "selected environment-related technologies" includes all of the environmental domains presented here.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
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      This dataset contains the number of people by sex and age group per country.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 01 agosto, 2019
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      Private transactions are those undertaken by firms and individuals resident in the reporting country.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 16 outubro, 2019
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      This dataset presents activities in support of development from philanthropic foundations since 2009, including bilateral activities and core contributions to multilateral organisations. Bilateral activities from this dataset can also be found in the Creditor Reporting System (CRS) database. Collecting data on private philanthropy for development is work in progress, which may explain break in series for some foundations.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 outubro, 2019
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      The 'Production and Sales (MEI)' dataset is a dataset containing predominantly monthly statistics, and associated statistical methodological information, for the 34 OECD member countries and for selected other economies. The Production and Sales dataset contains industrial statistics on four separate subjects: Production; Sales; Orders; and Work started. The data series presented within these subjects have been chosen as the most relevant industrial statistics for which comparable data across countries is available. For Production, data comprise Indices of industrial production (IIP) for total industry, manufacturing, energy and crude petroleum; and further disaggregation of manufacturing production for intermediate goods and for investment goods and crude steel. For others, they comprise retail trade and registration of passenger cars; and permits issued and work started for dwellings. Considerable effort has been made to ensure that the data are internationally comparable across all countries presented, coverage for as many countries as possible, and that all the subjects have reasonable length of time-series to assist analysis. Most data are available monthly and are presented as an index (where the year 2010 is the base year) or as a level depending on which measure is seen as the most appropriate and/or useful in the economic analysis context. Due to differences in statistical or economic environment at country level, however, availability of data varies from one country to another.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      The OECD Productivity Database aims at providing users with the most comprehensive and the latest productivity estimates. The update cycle is on a rolling basis, i.e. each variable in the dataset is made publicly available as soon as it is updated in the OECD Annual National Accounts database. However, timely data issues may arise and affect individual series and/or individual countries. Sectors differ from each other with respect to their productivity growth. Understanding the drivers of productivity growth at the total economy level requires an understanding of the contribution of each sector. Data of real gross value added, labour compensation, hours worked and employment are sourced from the OECD Annual National Accounts.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      Distribution of graduates/new entrants by gender, country of origin and age as well as the proportion of each tertiary educational level over the total of first-time graduates and new entrants at tertiary level.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 julho, 2019
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      The magnitude of government debt, and public sector debt likewise, depends on the coverage of instruments used and available data. To accommodate a fair international comparison of related indicators, the IMF, the OECD and the World Bank have agreed to define various debt measures depending on the coverage or non-coverage of instruments: D1 to D4. The D1-D4 presentation classifies gross government debt and public sector debt into four separate categories, as defined in the 2012 IMF Staff Discussion Note: “What Lies Beneath: The Statistical Definition of Public Sector Debt”. This coverage of instruments according to this classification ranges from a narrow definition including only debt securities and loans (D1) to a fully comprehensive definition covering all six debt instruments (D4), as defined in the Public Sector Debt Statistics Guide for User and Compilers, and the Government Finance Statistics Manual 2014. For more information, please see the document:
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 06 agosto, 2019
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      The Public Sector Debt database includes quarterly detailed information on all liabilities which constitute debt instruments, by initial and residual maturity, which are held by the government, and more broadly the public sector. The debt instruments are those instruments that require the payment of principal and interest or both at some point(s) in the future. All liabilities are considered debt, except liabilities in the form of equity and investment fund shares and, financial derivatives and employee stock options.
  • Q
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 06 agosto, 2019
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      OECD has extracted monthly trade data from the UN Monthly Comtrade database, and aggregates the quarterly and annual frequencies by summing up the months. This may create discrepancies with annual trade figures as presented in International Trade by Commodity Statistics (ITCS). UN Monthly Comtrade (beta version) contains detailed merchandise trade data provided by countries (or areas) to the United Nations Statistics Division, Department of Economic and Social Affairs (UNSD/DESA). Values are expressed in United States dollars (USD) and refer to declared transaction values. All exports are valued f.o.b. (free on board) and imports are valued c.i.f. (including cost, insurance, freight), except the imports of Canada and Mexico which are valued f.o.b. Detailed country metadata (currency conversion rates, information in HS classifications and data publication dates) can be found from the metadata file at the UN Monthly Comtrade website under the heading Metadata.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
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      The OECD's quarterly national accounts (QNA) dataset presents data collected from all the OECD member countries and some other major economies on the basis of a standardised questionnaire as well as countries' own definitions and classifications. It contains a wide selection of generally seasonally adjusted quarterly series most widely used for economic analysis from 1960 or whenever available: - GDP expenditure and output approaches (current prices and volume estimates); - GDP income approach (current prices); - Gross fixed capital formation (current prices and volume estimates) broken down separately by type of asset or product and by institutional sector; - Disposable income and Real disposable income components; - Saving and net lending (current prices); - Population and Employment (in persons); - Employment by industry (in persons and hours worked); - Compensation of employees (current prices); - Household final consumption expenditure by durability (current prices and volume estimates). The main purpose of this dataset is to provide relevant, reliable, consistent, comparable and timely quarterly national accounts for OECD member countries, some non-member countries and some area totals for analytical purposes. All the OECD member countries compile their accounts according to the 2008 SNA. The non-member countries which are still producing national accounts according to the 1993 SNA will switch to the new 2008 SNA over the coming months/years. This will allow the improvement of cross-countries comparability.
  • R
    • junho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 21 junho, 2019
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      Real hourly and annual minimum wages are statutory minimum wages converted into a common hourly and annual pay period for the 28 OECD countries and 4 non-member countries for which they are available. The resulting estimates are deflated by national Consumer Price Indices (CPI). The data are then converted into a common currency unit using either US $ current exchange rates or US $ Purchasing Power Parities (PPPs) for private consumption expenditures. Real hourly and annual minimum wages are calculated first by deflating the series using the consumer price index taking 2017 as the base year.  The series are then converted into a common currency unit (USD) using Purchasing Power Parities (PPPs) for private consumption expenditures in 2017.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 outubro, 2019
      Selecionar Conjunto de dados
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 14 julho, 2019
      Selecionar Conjunto de dados
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 outubro, 2019
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    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      Revenue Statistics in LAC Countries is a joint publication by the OECD Centre for Tax Policy and Administration, the OECD Development Centre, the Economic Commission for Latin America and the Caribbean (ECLAC) , the Inter-American Center for Tax Administrations (CIAT) and the Interamerican Development Bank (IDB). It presents detailed, internationally comparable data on tax revenues for 24 Latin American and Caribbean economies, two of which (Chile and Mexico) are OECD members. Its approach is based on the well-established methodology of the OECD Revenue Statistics (OECD, 2016), which has become an essential reference source for OECD member countries. Comparisons are also made with the average for OECD economies. Comparable tables show total tax revenue data and by tax as a percentage of GDP, and, for the different types of taxes, as a share of total taxation. Detailed country tables show information in national currency values
    • março 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 13 março, 2019
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      Reference Series - Latin American Countries Source: OECD National Accounts data for Chile and Mexico and official National Accounts data for the other countries
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
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      Classification(s) used: ICHA-FS: Classification of revenues of health care financing schemes ICHA-HF: Classification of health care financing schemes
  • S
    • março 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 14 março, 2019
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      Trade in services drives the exchange of ideas, know-how and technology. It helps firms cut costs, increase productivity, participate in global value chains and boost competitiveness. Consumers benefit from lower prices and greater choice. However, international trade in services is often impeded by trade and investment barriers and domestic regulations. The Service Trade Restrictions Index (STRI) helps identify which policy measures restrict trade. It provides policy makers and negotiators with information and measurement tools to open up international trade in services and negotiate international trade agreements. It can also help governments identify best practice and then focus their domestic reform efforts on priority sectors and measures. The STRI indices take the value from 0 to 1, where 0 is completely open and 1 is completely closed. They are calculated on the basis of information in the STRI database which reports regulation currently in force.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 16 outubro, 2019
      Selecionar Conjunto de dados
      The percentage of students enrolled in each type of institution over the total of students.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      This indicator shows the percentage of international students in each field of education.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      The SIGI is built on 27 innovative variables measuring discriminatory social institutions, which are grouped into 4 dimensions: discrimination in the family, restricted physical integrity, restricted access to productive and financial resources, and restricted civil liberties.Lower values indicate lower levels of discrimination in social institutions: the SIGI ranges from 0% for no discrimination to 100% for very high discrimination.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 14 julho, 2019
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      The STAN database for industrial analysis provides analysts and researchers with a comprehensive tool for analysing industrial performance at a relatively detailed level of activity across countries. It includes annual measures of output, labour input, investment which allow users to construct a wide range of indicators to focus on areas such as productivity growth, competitiveness and general structural change. Through the use of a standard industry list, comparisons can be made across countries. The industry list provides sufficient detail to enable users to highlight high-technology sectors and is compatible with those used in related OECD databases.  STAN is primarily based on Member countries' annual National Accounts by economic activity tables compiled according to the recommendations of System of National Accounts 2008 (SNA 2008). Previous versions of STAN (from 2000) were based on SNA93 statistics. Missing detail is estimated using data from other sources such as results from national industrial surveys/censuses. Time series are extended backwards (to 1970 where possible) using vintage SNA93 or STAN estimates. Many data points in STAN are estimated and are flagged as such; they do not represent official Member countries' submissions.  The current version of STAN is based on the International Standard Industrial Classification of all economic activities, Revision 4 (ISIC Rev. 4). Earlier versions of STAN were based on ISIC Rev.3 and, prior to 2000, ISIC Rev.2 (the latter covering the manufacturing sector only). STAN is updated on a "rolling basis" with new country tables, or updated tables, being made available as soon as they are ready.
    • junho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 18 junho, 2019
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      The dataset on Statistical discrepancy (Institutional Investors – Financial Balance Sheets) represents the time series of the dataset on Institutional investors' assets and liabilities (7II) along with those of the dataset on Financial Balance Sheets (720), for the financial instruments and institutional sectors which are in common to these two datasets.  Additionally, for each of the above-mentioned time series, a statistical discrepancy is reported in order to show any possible differences which may exist between the two datasets (7II and 720).  In fact, the dataset on Institutional investors' assets and liabilities (7II) constitutes an attempt to better integrate these data in the framework of the System of National Accounts 2008 (SNA 2008).  However, discrepancies may exist and may, for example, be caused by balancing practices (e.g. when sector and counterpart sector data are reconciled) in the compilation of Financial Balance Sheets at a higher level of aggregation, which may not have been carried through at a lower level of aggregation. Moreover, differences may also be caused by the use of different source data.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 18 julho, 2019
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      Excess capacity is one of the main challenges facing the global steel sector. The OECD Steel making Capacity database contains data on crude steel making capacity by economy and provides researchers and policymakers with an important tool for analyzing steel capacity developments.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 18 julho, 2019
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      Excess capacity is one of the main challenges facing the global steel sector. The OECD Steelmaking Capacity database contains data on crude steelmaking capacity by economy and provides researchers and policymakers with an important tool for analysing steel capacity developments.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
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      The OECD STRI heterogeneity indices complement the existing STRI's and presents indices of regulatory heterogeneity based on the rich information in the STRI regulatory database. The indices are built from assessing – for each country pair and each measure – whether or not the countries have the same regulation. For each country pair and each sector, the indices reflect the (weighted) share of measures for which the two countries have different regulation.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 05 julho, 2019
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      The OECD indicators of employment protection are synthetic indicators of the strictness of regulation on dismissals and the use of temporary contracts. For each year, indicators refer to regulation in force on the 1st of January. The indicator of strictness of employment protection - collective dismissals (additional provisions) - measures additional costs and procedures involved in dismissing more than one worker at a time (compared with the cost of individual dismissal). It incorporates 4 data items. For more information and full methodology, see www.oecd.org/employment/protection. Other Aspects Recommended uses and limitations The indicator for collective dismissal measures additional costs and procedures involved in dismissing more than one worker compared with the costs of individual dismissal. As such, it should not be used in isolation from the indicator of strictness of employment protection - individual dismissals (regular contracts).
    • maio 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 13 maio, 2019
      Selecionar Conjunto de dados
      The OECD indicators of employment protection are synthetic indicators of the strictness of regulation on dismissals and the use of temporary contracts. For each year, indicators refer to regulation in force on the 1st of January. Version 1 of the indicator of strictness of employment protection - individual and collective dismissals (regular contracts) - does not incorporate all the data items of version 3 and, in particular, does not incorporate regulation of collective dismissals. You should only use version 1 if you need data for years for which neither version 2 nor 3 are available.
    • junho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 05 junho, 2019
      Selecionar Conjunto de dados
      The OECD indicators of employment protection are synthetic indicators of the strictness of regulation on dismissals and the use of temporary contracts. For each year, indicators refer to regulation in force on the 1st of January. For more information and full methodology, see www.oecd.org/employment/protection.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 05 julho, 2019
      Selecionar Conjunto de dados
      The OECD indicators of employment protection are synthetic indicators of the strictness of regulation on dismissals and the use of temporary contracts. For each year, indicators refer to regulation in force on the 1st of January. For more information and full methodology, see www.oecd.org/employment/protection.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 outubro, 2019
      Selecionar Conjunto de dados
      Student-teacher ratio refers to the average number of students per teacher, while average class size is the average number of students in a classroom.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
      Selecionar Conjunto de dados
    • junho 2016
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 29 julho, 2019
      Selecionar Conjunto de dados
  • T
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 outubro, 2019
      Selecionar Conjunto de dados
      This dataset presents internationally comparable data on (full-time) salaries of teachers and school heads in public institutions at pre-primary, primary and general (lower and upper) secondary education. Actual salaries are displayed by level of education, and data on actual salaries of teachers are also available by age and gender. Data also include other statistics related to salaries of teachers.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
      Selecionar Conjunto de dados
      This dataset presents internationally comparable data on (full-time) salaries of teachers and school heads in public institutions at pre-primary, primary and general (lower and upper) secondary education. Statutory salaries are displayed by level of education, Data also include other statistics related to salaries of teachers.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 outubro, 2019
      Selecionar Conjunto de dados
      This dataset presents internationally comparable data on teaching and working time of (full-time) teachers in public institutions at pre-primary, primary and general and vocational (lower and upper) secondary education. Data refer to formal statutory requirements and also cover actual teaching time. Teaching and working time are displayed by level of education.
    • março 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 maio, 2019
      Selecionar Conjunto de dados
      The data presented here refer to the latest year available. The data on the state of threatened species build on country replies to the Annual Quality Assurance (AQA) of OECD environmental reference series. These data are harmonised through the work of the OECD Working Party on Environmental Information (WPEI). Some where updated or revised on the basis of comments from national Delegates and in the framework of the OECD Environmental Performance Reviews. When interpreting these data, it should be borne in mind that the number of species known does not always accurately reflect the number of species in extistence and that varying definitions can limit comparability accross countries. Species assessed as Critically Endangered (CR), Endangered (EN), or Vulnerable (VU) are referred to as "threatened" species. Reporting the proportion of threatened species on The IUCN Red List is complicated by the fact that not all species groups have been fully evaluated, and also by the fact that some species have so little information available that they can only be assessed as Data Deficient (DD). For many of the incompletely evaluated groups, assessment efforts have focused on species that are likely to be threatened; therefore any percentage of threatened species reported for these groups would be heavily biased (i.e., the % threatened species would likely be an overestimate). The data presented here show numbers of known species (or assessed) and threatened species with the aim of indicating the state of mammals, birds, freshwater fish, reptiles, amphibians, vascular plants, mosses, lichens and invertebrates.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
      Selecionar Conjunto de dados
      Because of the limited availability of official statistics on national supply-use and input-output tables in recent years – reflecting the fact that these are only typically available at best two or three years after the reference period to which they refer – TiVA indicators for the most recent years, as displayed in this dataset, are estimated using now-casting techniques. The approach (described in more detail in the accompanying methodological note) in essence estimates national input-output tables by projecting relationships observed in the latest TiVA benchmark year (currently 2011) into nowcast years (currently 2012-2014) but constrained to official estimates of gross output and value-added by industry and national accounts main aggregates of demand and trade, and supplemented by bilateral trade statistics, all of which are available throughout the nowcast period. Importantly, the projections of relationships in 2011 into 2012 are determined using a volume approach, to account for possible distortions that might be introduced – by for example differential price movements in imports and domestic production – if projections were made using nominal relationships. These estimates are then reflated into current prices, and simultaneously balanced – consistent with official volume and current price estimates of trade, demand and activity – to arrive at a balanced national input-output table in 2012, in nominal terms as well as in prices of 2011. Estimates for 2013 and 2014 are calculated in the same manner but using, respectively, the 2012 and 2013 relationships as the starting point.
    • setembro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 24 setembro, 2019
      Selecionar Conjunto de dados
      Official Development Financing (ODF), measured for recipient countries only, is defined as the sum of their receipts of bilateral ODA, concessional and non-concessional resources from multilateral sources, and bilateral other official flows made available for reasons unrelated to trade, in particular loans to refinance debt.
    • maio 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 28 maio, 2019
      Selecionar Conjunto de dados
      Total Official Flows: the sum of Official Development Assistance (ODA) and Other Official Flows (OOF) represents the total (gross or net) disbursements by the official sector at large to the recipient country shown.
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 15 outubro, 2019
      Selecionar Conjunto de dados
      Total Receipts, Net: in addition to Official Development Assistance, this heading includes in particular: other official bilateral transactions which are not concessional or which, even though they have concessional elements, are primarily trade facilitating in character (i.e., "Other Official Flows''); changes in bilateral long-term assets of the private non-monetary and monetary sectors, in particular guaranteed export credits, private direct investment, portfolio investment and, to the extent they are not covered in the preceding headings, loans by private banks. Flows from the multilateral sector which are not classified as concessional are also included here.
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 17 julho, 2019
      Selecionar Conjunto de dados
      This dataset shows import and export values (in millions of UDS) using product classification at 2-digit level of CPA classification.
    • março 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 14 março, 2019
      Selecionar Conjunto de dados
      The central issue of trade by enterprise characteristics is to disaggregate trade flows according the characteristics of the enterprises engaged in cross-border transactions. The feasibility of doing so largely depends on the possibility of using or developing common identifiers between the trade register and the business register. Countries differ in their ability to perform such a linking, and matching ratios (between business and trade registers) vary across countries, and as a consequence the degree of representativeness of the results also varies across countries.
    • dezembro 2018
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 03 dezembro, 2018
      Selecionar Conjunto de dados
      This dataset presents data by type of ownership, that is foreign or domestically controlled enterprise (with or without own affiliates abroad).
    • julho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 02 julho, 2019
      Selecionar Conjunto de dados
      This dataset shows the number of exporters and importers and their associated trade values for a selected set of partner countries and zones, broken down by three economic sectors: industry, trade and repair and other sectors. Total values for the wide economy are also displayed.Recommended uses and limitations EU countries break down trade data into Intra- and extra- EU zones, whereas non EU countries report their Total trade. Trade values have been aggregated for EU countries and Total (Intra-EU plus Extra-EU) trade flows are displayed, whereas Intra and Extra-EU data expressed in term of number of enterprises cannot be summed up, because of possible double-counting (same enterprise can be trader in both intra- and extra- EU trade). Data have been collected in ISIC revision 3 from 2003 up to 2007 and in ISIC revision 4 as from reference year 2008. Time series are affected by this change in classification, and thus data are displayed into two separate databases.
    • junho 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 05 junho, 2019
      Selecionar Conjunto de dados
      The central issue of trade by enterprise characteristics is to disaggregate trade flows according the characteristics of the enterprises engaged in cross-border transactions. The feasibility of doing so largely depends on the possibility of using or developing common identifiers between the trade register and the business register. Countries differ in their ability to perform such a linking, and matching ratios (between business and trade registers) vary across countries, and as a consequence the degree of representativeness of the results also varies across countries.
  • U
    • agosto 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 13 agosto, 2019
      Selecionar Conjunto de dados
      This dataset contains data on the share of the five durations - less than 1 month, >1 month and < 3 months, >3 months and <6 months, >6 months and <1 year, 1 year and over - of unemployment among total unemployment by sex and by standardised age groups (15-19, 15-24, 20-24, 25-54, 55+, total).
  • W
    • outubro 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 08 outubro, 2019
      Selecionar Conjunto de dados
      This dataset provides information on the level of public equipment installed by countries to managed and abate water pollution. It shows the percentage of national population connected to "public" sewerage networks and related treatment facilities, and the percentage of national population connected to "public" wastewater treatment plants, and the degree of treatment. Connected here means actually connected to a wastewater plants through a public sewage network. Individual private treatment facilities such as septic tanks are not covered here. When analysing these data, it should be kept in mind that the optimal connection rate is not necessarily 100 per cent; it may vary among countries and depends on geographical features and on the spatial distribution of habitats. The interpretation of those data should take into account some variations in countries' definitions, as reflected in metadata.
    • abril 2019
      Fonte: Organisation for Economic Co-operation and Development
      Carregamento por: Knoema
      Acesso em 12 abril, 2019
      Selecionar Conjunto de dados
      World Indicators of Skills for Employment (WISE) provide a comprehensive system of information relating to skills development. WISE presents countries with data upon which they can design skills policies and programs and monitor their impact on key outcomes, including responsiveness to current and emerging patterns of labour market demand, employability, productivity, health status, gender equity and lifelong learning.The database covers the period from 1990 to the present and consists of five inter-related domains of indicators:Contextual factors drive both the supply of and demand for skills.Skill acquisition covers investments in skills, the stock of human capital and its distribution.Skill requirements measure the demand for skills arising in the labour market.The degree of matching captures how well skills obtained through education and training correspond to the skills required in the labour market.Outcomes reflect the impact of skills on economic performance and employment and social outcomes.

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