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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.

All datasets:  2 A B C D E F G H I K L M N O P Q R S T U W
  • 2
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 12 अगस्त, 2019
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      This dataset contains the main results of the 2014 Eurostat-OECD PPP comparison for the 47 countries that participated in the 2014 round of the Eurostat-OECD Purchasing Power Parity (PPP) Programme. The dataset is organised in 23 tables which show results both in US dollars and OECD as reference (Table 1.1 to Table 1.12) and in euros and European Union as reference (Table 2.1 to Table 2.11) calculated with the EKS method. The tables contain the following information: Table 1.1 to 1.12 The dollar serves as numeraire and the OECD as reference country (except for Table 1.12 where the United States are the reference country). Table 1.1 and Table 1.2 present the data on which the following ten tables are based. • Table 1.1 gives nominal expenditure in national currency of the participating countries. • Table 1.2 presents PPPs (OECD=1.00) that have been calculated for the participating countries using the price and expenditure data collected during the 2014 round. The PPPs were obtained by the EKS method of calculation and aggregation. • Table 1.3 shows nominal expenditure of Table 1.1 converted to US dollars. Exchange rates do not reflect the relative purchasing power of different currencies and the converted expenditure is still expressed at national prices. As such, it remains nominal measures, the spatial equivalent of a time series of GDP for a single country at current prices. Hence, they are called “nominal expenditure”. The nominal expenditure in the table reflects both differences in the quantities of goods and services purchased in the countries and differences in the price levels of the countries. • Table 1.4 gives nominal expenditure of Table 1.3 expressed on a per capita basis using the midyear population data. • Table 1.5 and Table 1.6 present the nominal expenditure from Table 1.3 and the nominal expenditure per head from Table 1.4 as indices with OECD=100. • Table 1.7 shows real expenditure converted to US dollar using the PPPs from Table 1.2. PPPs equalise the purchasing power of different currencies during the process of conversion and the converted expenditures are expressed at international prices (that is at the same price level). As such, they are real measures, the spatial equivalent of a time series of GDP for a single country at constant prices. Hence, they are called “real expenditures”. The real final expenditures in the table reflect only differences in the volumes of goods and services purchased in the countries. • Table 1.8 gives the real expenditure of Table 1.7 expressed on a per capita basis using the midyear population data. Again, the real expenditures per head in this table are not additive nor are they subject to the Gerschenkron effect. • Table 1.9 and Table 1.10 present the real expenditure on GDP from Table 1.7 and the real final expenditure per head on GDP from Table 1.8 as indices with OECD=100. • Table 1.11 gives the price levels which are computed as ratios of the PPPs in Table 1.2 to the exchange rates and are expressed as indices with OECD=100. For a given aggregate, they indicate the number of units of the common currency needed to buy the same volume of the  aggregate in each country. Price levels that exceed 100 indicate that the level of prices in that country and for that analytical category is higher than the average price level for the OECD. • Table 1.12 present PPPs as in Table 1.2 (see description above) but with the United States as reference country (US=1.00). Table 2.1 to 2.11 The euro serves as numeraire and the European Union as reference country. Table 2.1 and Table 2.2 present the data on which the following nine tables are based. Table 2.1 to 2.11 contain the same information as Table 1.1 to 1.11 with a different basis. For explanation on the contents, please see description above.
  • A
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 05 जुलाई, 2019
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      The gross nutrient balances (N and P) are calculated as the difference between the total quantity of nutrient inputs entering an agricultural system (mainly fertilisers, livestock manure), and the quantity of nutrient outputs leaving the system (mainly uptake of nutrients by crops and grassland). Gross nutrient balances are expressed in tonnes of nutrient surplus (when positive) or deficit (when negative). This calculation can be used as a proxy to reveal the status of environmental pressures, such as declining soil fertility in the case of a nutrient deficit, or for a nutrient surplus the risk of polluting soil, water and air. The nutrient balance indicator is also expressed in terms of kilogrammes of nutrient surplus per hectare of agricultural land to facilitate the comparison of the relative intensity of nutrients in agricultural systems between countries.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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.
    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 अप्रैल, 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.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 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.
    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 16 अप्रैल, 2019
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      AITRAW = All in average income tax rates at average wage   OECD Taxing Wages. Taxing Wages provides unique information on income tax paid by workers and social security contributions levied on employees and their employers in OECD countries. In addition, this annual publication specifies family benefits paid as cash transfers. Amounts of taxes and benefits are detailed program by program, for eight household types which differ by income level and household composition. Results reported include the marginal and effective tax burden for one- and two-earner families, and total labour costs of employers.
    • जून 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 18 जून, 2019
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      The OECD's ANalytical Business Enterprise Research and Development (ANBERD) database presents annual data on Research and Development (R&D) expenditures by industry and was developed to provide analysts with comprehensive data on business R&D expenditures. The ANBERD database incorporates a number of estimations that build upon and extend national submissions of business enterprise R&D data by industry (main activity/industry orientation). The current version of the ANBERD database presents OECD countries' and selected non-member economies' business expenditure on R&D since 1987, broken down across 100 manufacturing and service industry groups. The reported data follow the International Standard Industrial Classification, Revision 4 (ISIC Rev. 4) and are expressed in national currencies as well as in US dollars at Purchasing Power Parity (PPP), both at current and constant prices.   Main activity and industry orientation: The 2015 Frascati Manual practice is to report BERD on an enterprise basis. The main economic activity of an enterprise is usually defined as that which accounts for most of its economic outputs; this may be identified directly from sales or indirectly proxied (such as by numbers of personnel devoted to different activities). This determines the industry in which the enterprise, and any BERD it carries out, is classified. As such, all BERD of a diversified enterprise (i.e. one with multiple lines of business) is allocated to the same industry, that of its main activity. This enables, as far as possible, the alignment and compatability of BERD data with other economic statistics (e.g. value added broken down by industry). In addition, the Frascati Manual also recommends reporting BERD by industry orientation, whereby the statistical unit’s R&D is distributed across the various lines of business to which it relates. In a few countries, hybrid approaches are followed and reported as main activity data. As an example, some countries primarily follow the main activity approach but redistribute the R&D of large diversified firms across the economic activities to which it relates. This can affect interpretation of the data and resulting statistics. There are also important differences between countries in the treatment of R&D undertaken by firms in the service sector but closely associated (though not necessarily contractually) with manufacturing firms. Industrial research institutes, largely funded by the manufacturing industries they serve, are the most frequent examples. With the implementation of the 2015 Frascati Manual, such hybrid data will be phased out in favour of a strict main activity approach. Countries still reporting hybrid data are flagged in the ANBERD country notes.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 जुलाई, 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).
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 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.
  • B
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 नवम्बर, 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) .
    • फरवरी 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 01 मार्च, 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.
    • दिसम्बर 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 18 दिसम्बर, 2017
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      Better Life Index aims to involve citizens in the debate on measuring the well-being of societies, and to empower them to become more informed and engaged in the policy-making process that shapes all our lives. Each of the 11 topics of the Index is currently based on one to three indicators. Within each topic, the indicators are averaged with equal weights. The indicators have been chosen on the basis of a number of statistical criteria such as relevance (face-validity, depth, policy relevance) and data quality (predictive validity, coverage, timeliness, cross-country comparability etc.) and in consultation with OECD member countries. These indicators are good measures of the concepts of well-being, in particular in the context of a country comparative exercise. Other indicators will gradually be added to each topic.
    • जून 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 28 अगस्त, 2018
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    • दिसम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 दिसम्बर, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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
    • मई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 मई, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 15 अक्तूबर, 2019
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      CGPITRT: Central government personal income tax rates and threshold   This table reports statutory central government personal income tax rates for wage income plus the taxable income thresholds at which these statutory rates apply. The table also reports basic/standard tax allowances, tax credits and surtax rates. The information is applicable to a single person without dependents. The threshold, tax allowance and tax credit amounts are expressed in national currencies Tapered means that the tax relief basic amount is reduced with increasing income Further explanatory notes may be found in the Explanatory Annex This data represents part of the data presented within the Excel file “Personal income tax rates and thresholds for central governments - Table I.1”. The Data for 1981 to 1999 is not included here within as not all the data for these years is either available, or can be verified. The OECD tax database provides comparative information on a range of tax statistics - tax revenues, personal income taxes, non-tax compulsory payments, corporate and capital income taxes and taxes on consumption - that are levied in the 34 OECD member countries.” Tax policy Analysis homepage OECD Tax Database Taxing Wages Dissemination format(s) This data is also presented through the OECD Tax database webpage. OECD Tax Database
    • फरवरी 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 28 फरवरी, 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.
    • दिसम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 2019
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      Statistical population: CLIs are calculated for 33 OECD countries (Iceland is not included), 6 non-member economies and 8 zone aggregates. A country CLI comprises a set of component series selected from a wide range of key short-term economic indicators.   CLIs, reference series data (see below) and standardised business and consumer confidence indicators are presented in various forms.   Recommended uses and limitations: The composite leading indicator is a times series, formed by aggregating a variety of component indicators which show a reasonably consistent relationship with a reference series (e.g. industrial production IIP up to March 2012 and since then the reference series is GDP) at turning points. The OECD CLI is designed to provide qualitative information on short-term economic movements, especially at the turning points, rather than quantitative measures. Therefore, the main message of CLI movements over time is the increase or decrease, rather than the amplitude of the changes. The OECD’s headline indicator is the amplitude adjusted CLI. In practice, turning points in the de-trended reference series have been found about 4 to 8 months (on average) after the signals of turning points had been detected in the headline CLI.
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 नवम्बर, 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).
    • अप्रैल 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 21 मई, 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
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 अगस्त, 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
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 अक्तूबर, 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.
    • फरवरी 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 01 मार्च, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 14 अक्तूबर, 2019
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      The OECD FSE database is intended to be the best source of information on fisheries policies in OECD members and participating non-OECD economies. It is designed to monitor and quantify developments in fisheries policy, to establish a common basis for policy dialogue among countries, and to provide economic data to assess the effectiveness and efficiency of policies. These tables report country programmes data aggregated according to the main categories presented in the FSE Manual. More detailed documentation on country programmes can be found in country-level metadata; more data on country programmes can be found in the full dataset (Excel Format - link provided below). Statistics are organized in pivot tables to make possible cross-country comparisons and to filter disaggregated policy-level data by policy implementation criteria and country.
  • E
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 नवम्बर, 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 selected non-OECD economies are also evaluated in detail. Each edition of the Outlook provides a unique resource to keep abreast of world economic developments. The OECD Economic Outlook database is a comprehensive and consistent macroeconomic database of the OECD economies, covering expenditures, foreign trade, output, labour markets, interest and exchange rates, balance of payments, and government debt. For the non-OECD regions, foreign trade and current account series are available.    The database contains annual data (for all variables) and quarterly figures (for a subset of variables). Variables are defined in such a way that they are as homogenous as possible for the countries covered. Breaks in underlying series are corrected as far as possible. Sources for the historical data are publications of national statistical agencies and OECD data bases such as Quarterly National Accounts, Annual National Accounts, Labour Force Statistics and Main Economic Indicators. The cut-off date for information used in the compilation of the projections was the 14 November 2019.   Concerning the aggregation of world trade, a new composition has been introduced, since projections are now made for selected 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.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2019
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    • सितम्बर 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 16 अक्तूबर, 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).
    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 अप्रैल, 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).
    • सितम्बर 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 मार्च, 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.  
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 23 जुलाई, 2019
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      Employment, participation rates: population aged 15-64; Unemployment rate: active population aged 15-64.   Rates as defined by the International Labour Organization.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 15 अक्तूबर, 2019
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    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 18 जुलाई, 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.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 जुलाई, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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.
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 सितम्बर, 2019
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      Number of students enrolled in different education programmes by age and sex.
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 अगस्त, 2019
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      Number of students enrolled in different education programmes by type of institution and sex.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 2019
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    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 जुलाई, 2019
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      Unit of measure used Environmental protection (EP) includes all purposeful activities directly aimed at the prevention, reduction and elimination of pollution or any other degradation of the environment resulting from production or consumption processes. The scope of Environmental Protection is defined according to the Classification of Environmental Protection Activities (CEPA), which distinguishes nine different environmental domains. Activities such as energy and material saving are only included to the extent that they mainly aim at environmental protection. An important example is recycling which is included only to the extent that it constitutes a substitute for waste management. Excluded are: (i) activities that, while beneficial to the environment, primarily satisfy technical needs or health and safety requirements for the protection of the workplace. (ii) expenditure linked to mobilisation of natural resources (e.g., water supply). (iii) calculated cost items such as depreciation (consumption of fixed capital) or the cost of capital as this questionnaire only records actual outlays. (iv) payments of interest, fines and penalties for non-compliance with environmental regulations or compensations to third parties etc., as they are not directly linked with an environmental protection activity. Environmental Protection Expenditure can be evaluated both according to the abater principle and the financing principle. This distinction makes it possible to aggregate different sectors and industries without double counting. Expenditure according to the abater principle (EXP I), includes all expenditure that the sector has for measures they themselves execute. Any economic benefits directly linked with the environmental protection activities (Receipts from by-products) are deducted in order to calculate the net amount of money spent by the sector for their own activities. The financing principle (EXP II) measures how much money a particular sector (directly) contributes to overall environmental protection activities, wherever they are executed. This means that the part of EXP I that was directly financed by others (through subsidies or revenues received) should be deducted, while the part of EXP I in other sectors that this sector finances directly (through subsidies or fees paid) should be added. The framework is based on double entry bookkeeping, where each activity and expenditure item has an abater (producer) and a financing side. This means that much expenditure by specialised producers is financed by the users of their services, mainly business sector and households. This will be recorded as Revenues for the Specialised producers (Table 4), and fees/purchases in Business and Households (Tables 2 and 3). Specialised producers include the production of environmental protection services by public and private corporations or quasi-corporations for the use of other units, mainly financed by the users of these services. These are mainly activities within ISIC Rev. 4/NACE Rev. 2 division and classes 37, 38.1, 38.2 and 39 such as: 37 Sewerage, 38.1 Waste collection, 38.2 Waste treatment and disposal, 39  Remediation activities and other waste management services. This sector is the sum of two components: a) Public specialised producers: All corporations and quasi-corporations that are subject to control by government units. Control is defined as the ability to determine general corporate policy by choosing appropriate directors, if necessary (Table 4A). b) Private specialised producers: All corporations and quasi-corporations that are not subject to control by government units (Table 4B). Specialised producers could also include for example the activities of e.g. volunteer environmental organisations or secondary environmental activities. These should be entered along with a footnote describing the coverage. CEPA domains: a column "pollution abatement and control" (PAC) has been kept in the questionnaire to ensure continuity with earlier data series.
  • F
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 अगस्त, 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.
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 अगस्त, 2019
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      FDI statistics cover all entities in an FDI relationship. An FDI relationship is established when an investor in one country acquires 10% or more of the voting power in a business enterprise in another country. The investor is also called a direct investor or a parent and the business enterprise is called a direct investment enterprise or an affiliate. The 10 percent criteria is used to establish that the direct investor has a significant degree of influence over the operations of the direct investment enterprise. The FDI population includes affiliates that are directly and indirectly owned by the parent. In direct ownership, the parent owns the 10% or more voting power itself. In indirect ownership, the parent controls an affiliate that in turn owns 10 percent or more of the voting power in another enterprise. The FDI population also includes enterprises that are not in a direct investment relationship themselves but have a direct investor in common. Called fellow enterprises, they are included because, even though there is no direct investment relationship between the two, any transactions between them likely resulted from the influence that their common direct investor has on both of their operations.
    • मार्च 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 मार्च, 2019
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    • फरवरी 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जून, 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
    • जून 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2018
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    • मार्च 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 मार्च, 2019
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    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 अगस्त, 2019
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      FDI statistics cover all entities in an FDI relationship. An FDI relationship is established when an investor in one country acquires 10% or more of the voting power in a business enterprise in another country. The investor is also called a direct investor or a parent and the business enterprise is called a direct investment enterprise or an affiliate. The 10 percent criteria is used to establish that the direct investor has a significant degree of influence over the operations of the direct investment enterprise. The FDI population includes affiliates that are directly and indirectly owned by the parent. In direct ownership, the parent owns the 10% or more voting power itself. In indirect ownership, the parent controls an affiliate that in turn owns 10 percent or more of the voting power in another enterprise. The FDI population also includes enterprises that are not in a direct investment relationship themselves but have a direct investor in common. Called fellow enterprises, they are included because, even though there is no direct investment relationship between the two, any transactions between them likely resulted from the influence that their common direct investor has on both of their operations.
    • मार्च 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 मार्च, 2019
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    • जून 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2018
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    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 अप्रैल, 2019
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    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 अक्तूबर, 2019
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      Source: OECD International direct investment database, IMF Reference:Benchmark Definition of Foreign Direct Investment, 3rd edition   Foreign direct investment reflects the objective of obtaining a lasting interest by a resident entity in one economy (‘‘direct investor'') in anentity resident in an economy other than that of the investor (‘‘direct investment enterprise''). The lasting interest implies the existence of a long-term relationship between the direct investor and the enterprise and a significant degree of influence on the management of the enterprise. Direct investment involves both the initial transaction between the two entities and all subsequent capital transactions between them and among affiliated enterprises, both incorporated and unincorporated.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 23 अक्तूबर, 2019
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      The financial indicators in this dataset are constructed from OECD countries’ financial balance sheets (stocks): these ratios are considered as relevant to analyse the position and performance of the various institutional sectors. They comprise for instance: Financial net worth of Households and NPISHs, as a percentage of GDI; Non-financial corporations debt to equity ratio; Private sector debt; Leverage of the banking sector; General government debt, as a percentage of GDP.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 अक्तूबर, 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).
    • मार्च 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 मार्च, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 अक्तूबर, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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).
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 2019
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      FDI statistics cover all entities in an FDI relationship. An FDI relationship is established when an investor in one country acquires 10% or more of the voting power in a business enterprise in another country. The investor is also called a direct investor or a parent and the business enterprise is called a direct investment enterprise or an affiliate. The 10 percent criteria is used to establish that the direct investor has a significant degree of influence over the operations of the direct investment enterprise.   The FDI population includes affiliates that are directly and indirectly owned by the parent. In direct ownership, the parent owns the 10% or more voting power itself. In indirect ownership, the parent controls an affiliate that in turn owns 10 percent or more of the voting power in another enterprise.   The FDI population also includes enterprises that are not in a direct investment relationship themselves but have a direct investor in common. Called fellow enterprises, they are included because, even though there is no direct investment relationship between the two, any transactions between them likely resulted from the influence that their common direct investor has on both of their operations.
    • दिसम्बर 2014
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 11 नवम्बर, 2016
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    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 अगस्त, 2019
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      Key statistical concept Although there are clear definitions for all the terms used in this survey, countries might have different methodologies to calculate tonne-kilometer and passenger-kilometers. Methods could be based on traffic or mobility surveys, use very different sampling methods and estimating techniques which could affect the comparability of their statistics. Also, if the definition on road fatalities is very clear and well applied by most countries, this is not the case for road injuries. Indeed, not only countries might have different definitions but the important underreporting of road injuries in most countries can distort analysis based on these data.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 15 अक्तूबर, 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.
    • मार्च 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 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
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 13 अगस्त, 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.
    • मई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 मई, 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.
    • मार्च 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 21 मई, 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
    • दिसम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 2019
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      Consumer price indices (CPIs) measure inflation as price changes of a representative basket of goods and services typically purchased by households. The G20 CPI aggregate reflects national CPIs for all G20 countries that are not part of the European Union (EU) while it reflects the Harmonised Indices of Consumer Prices (HICP) for the EU, its Member States and for Turkey.   The G20 CPI has been calculated for the headline indicators only (CPI All items / HICP Total). It is an annual chain-linked Laspeyres-type index. The weights for each country in each link are based on the previous year's relative share of individual final consumption expenditure of households and non-profit institutions serving households expressed in Purchasing Power Parities (PPPs).
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 15 अक्तूबर, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 2019
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      This part contains general information on number of insurance companies and employees within the sector.
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 2019
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    • मार्च 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 मार्च, 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.
    • फरवरी 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 फरवरी, 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.
    • मई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 28 जून, 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
    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 अप्रैल, 2019
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    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 अक्तूबर, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 15 अक्तूबर, 2019
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    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 अक्तूबर, 2019
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    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 सितम्बर, 2019
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      As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. This part contains gross operating expenses in the reporting country, with a breakdown between domestic companies, foreign-controlled companies and branches and agencies of foreign companies.
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 अगस्त, 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
    • नवम्बर 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 नवम्बर, 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.
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 अगस्त, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 जुलाई, 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.
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 अगस्त, 2019
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      OECD Health Data 2015 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse healthcare systems.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2019
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    • दिसम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 03 दिसम्बर, 2019
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      Unit of measure usedIndex: Year 2015 = 100 The Hourly Earnings (MEI) dataset contains predominantly monthly statistics, and associated statistical methodological information, for the 35 OECD member countries and for selected non-member economies.  The MEI Earnings dataset provides monthly and quarterly data on employees' earnings series. It includes earnings series in manufacturing and for the private economic sector. Mostly the sources of the data are business surveys covering different economic sectors, but in some cases administrative data are also used. The target series for hourly earnings correspond to seasonally adjusted average total earnings paid per employed person per hour, including overtime pay and regularly recurring cash supplements. Where hourly earnings series are not available, a series could refer to weekly or monthly earnings. In this case, a series for full-time or full-time equivalent employees is preferred to an all employees series.
    • दिसम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 दिसम्बर, 2019
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      The elaboration of a more precise nomenclature of households' financial assets and liabilities and the collection of more detailed information constitute an attempt to better identify and analyse households' wealth in OECD countries. The objective of the sub-classification of assets and liabilities is to identify the relative importance of the various types of assets, classified according to the increasing risk
  • I
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 अगस्त, 2019
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      This dataset presents number of importing/exporting enterprises and their trade value (in millions of USD) by size class, and economic activity expressed in ISIC Rev.4.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 15 अक्तूबर, 2019
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    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 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.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2019
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      http://www.oecd.org/els/soc/IDD-Metadata.pdf
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 अक्तूबर, 2019
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      Data source(s) used The inland fisheries data collection is part of the more comprehensive data gathering carried out on an annual basis by the Fisheries Committee (COFI) of the Trade and Agriculture Directorate (TAD) from OECD members and participating non-OECD economies. Data on marine landings, aquaculture production, inland fisheries catch, fleet, employment, total allowable catch (TAC) and fisheries support estimate (FSE) are collected from Fisheries Ministries, National Statistics Offices and other institutions designated as an official data source. The surveys used for this exercise are the OECD Fisheries questionnaires.   Data are collected in tonnes and national currency at current values. For analytical purposes and data comparisons, value data are converted and published also in US dollars. Exchange rates are average yearly spot rates, taken from the dataset OECD Economic Outlook: Statistics and Projections. Data reported in this dataset are expressed in tonnes, in units of national currency and in US dollars. Data are recorded on a landed weight basis, i.e. the mass (or weight) of a product at the time of landing, regardless of the state in which is landed (i.e. whole, gutted, filleted, meal, etc.). For exceptions, please see the individual notes. Statistical population The statistical population is the set of countries participating in the work of the COFI, i.e. OECD members, excluding landlocked countries, with some exceptions (Czech Republic and Slovakia are included, Israel is not). The group includes also the following partner countries: Argentina, China, Colombia, Costa Rica, Indonesia, Lithuania, Peru, Philippines, Thailand and Chinese Taipei. In order to facilitate analysis and comparisons over time, historical data for OECD members have been provided over as long a period as possible, often even before a country became a member of the Organisation. Information on the membership dates of all OECD countries can be found at OECD Ratification Dates. Key statistical concept Inland fisheries include catches of fish, crustaceans, molluscs and other aquatic invertebrates (and animals), residues and seaweeds in lakes, rivers, ponds, inland canals and other land-locked water bodies. For the purpose of this questionnaire the boundary between inland and marine areas at the river mouth is left to the discretion of the national authority. Production from aquaculture installations should not be reported on this form. However, catches from fisheries that are managed by stocking should be included. The methodological reference document for fisheries and aquaculture statistics is the CWP Handbook of Fishery Statistics.
    • मई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 28 मई, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 अक्तूबर, 2019
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      As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Item coverage Covers business written abroad by branches, agencies and subsidiaries established abroad of domestic undertakings and includes all business written outside the country by these entities (in both OECD and non-OECD countries).
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 सितम्बर, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 अक्तूबर, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 अक्तूबर, 2019
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    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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.
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 नवम्बर, 2019
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      The International Transport Forum collects, on a quarterly basis, monthly data from all its Member countries. When monthly information is not available then quarterly data is provided. The survey contains a dozen variables selected for their quarterly availability among reporting countries. Data are collected from Transport Ministries, statistical offices and other institution designated as official data source. The survey used for this exercise is the ITF "Quarterly Transport Statistics". Variables collected are rail, road and inland waterways goods transport (T-km), rail passengers (P-km), road traffic (V-km), first registration of brand new vehicles, petrol deliveries to the road transport sector and road fatalities. Although there are clear definitions for all the terms used in this survey, countries might have different methodologies to gather or estimate quarterly data. The information provided in short-term surveys does not necessarily have the same coverage as annual data exercises and therefore remains provisional. Depending on countries, data is not always revised so totals might not correspond to the sum of the elements. The main purpose of this data collection is to identify in advance changes in transport data trends. In case of missing data for a country, ITF can calculate estimates based generally on growth rates from previous years or from data available from other sources. These estimates are used solely to calculate aggregated trends in graphic representations and are not shown at the individual country level.  
  • K
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 19 नवम्बर, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 2019
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  • L
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 02 जुलाई, 2019
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      This dataset contains data on employment by hour bands for usual weekly hours worked in the main job.  Standard hour bands are reported for most countries.  Actual hours of work instead of usual hours of work are only available in some countries (Japan and Korea).  Data are broken down by professional status - employees, total employment - by sex and standardised age groups (15-24, 25-54, 55+, total). Unit of measure used - Data are expressed in thousands of persons. For detailed information on labour force surveys for all countries please see the attached file : www.oecd.org/els/employmentpoliciesanddata/LFSNOTE
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 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.
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 अगस्त, 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.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 जुलाई, 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).
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 13 अगस्त, 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.
  • M
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 अक्तूबर, 2019
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      This biannual publication provides a set of indicators that reflect the level and structure of the efforts undertaken by OECD member countries and seven non-member economies (Argentina, People's Republic of China, Romania, Russian Federation, Singapore, South Africa, Chinese Taipei) in the field of science and technology. These data include final or provisional results as well as forecasts established by government authorities. The indicators cover the resources devoted to research and development, patent families, technology balance of payments and international trade in R&D-intensive industries. Also presented are the underlying economic series used to calculate these indicators. Indicators on R&D expenditures, budgets and personnel are derived from the OECD's Research and Development Statistics (RDS) database, which is based on the data reported to OECD and Eurostat in the framework of a co-ordinated collection. The sources for the other indicators include the OECD databases on Activities of Multinational Enterprises (AMNE), on Bilateral Trade in Goods by Industry and End-use Category database (BTDIxE), on Patents and on Technological Balance of Payments (TBP). The R&D data used in this publication have been collected and presented in line with the standard OECD methodology for R&D statistics as laid out in the OECD "Frascati Manual". The 2002 edition of the manual has now been superseded by the 2015 edition. The revised guidelines and definitions are in the course of being implemented and are not expected to change the main indicators significantly although some terminology changes will occur. This edition of MSTI has been compiled in accordance with the 2002 Frascati Manual; these changes will be made in a coming edition as R&D surveys move to the new standard.   2018 values are estimated value.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 जुलाई, 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).
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 08 अक्तूबर, 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.
    • जून 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 नवम्बर, 2019
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      This dataset and predefined summary tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2019, which monitors agricultural policy developments in 36 OECD member countries, 5 non-OECD EU member states and 12 emerging economies: Argentina, Brazil, China, Colombia, Costa Rica, India, Kazakhstan, the Russian Federation, 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.
    • जून 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 नवम्बर, 2019
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      Database published : June 2019
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 अक्तूबर, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 अक्तूबर, 2019
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      The Financial Statistics dataset contains predominantly monthly statistics, and associated statistical methodological information, for the 36 OECD member countries and some selected other countries. The dataset itself contains financial statistics on 4 separate subjects: Monetary Aggregates, Interest Rates, Exchange Rates, and Share Prices. The data series presented within these subjects have been chosen as the most relevant financial statistics for which comparable data across countries is available. In all cases a lot of effort has been made to ensure that the data are internationally comparable across all countries presented and that all the subjects have good historical time-series’ data to aid with analysis. All data are available monthly, and are presented as either an index (where the year 2015 is the base year) or as a level depending on which measure is seen as the most appropriate and/or useful in the economic analysis context.
    • दिसम्बर 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 11 दिसम्बर, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 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.
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 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.
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 2019
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      It presents the balance sheets for non financial assets by institutional sectors, for both produced assets (fixed assets, inventories, valuables) and non-produced assets (tangible and intangible).  It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA. Unit of measure used - In national currency expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 अक्तूबर, 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.
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 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..
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 2019
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      It presents the whole set of non financial accounts, from the production account to the acquisitions of non-financial assets accounts. For general government sector, property income, other current transfers and capital transfers are consolidated.. It has been prepared from statistics reported to the OECD by Member countries in their answers to the new version of the annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA.
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 2019
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      It presents gross capital formation, gross fixed capital formation, changes in inventories and acquisition less disposals of valuables broken down by detailed industries. Gross fixed capital formation is also available broken down by type of assets. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA. Unit of measure used - In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2010). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 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.
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 24 सितम्बर, 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.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2019
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      National Accounts - Volume IIIa - Financial Accounts - Flows, which record, by type of financial instruments, the financial transactions between institutional sectors, and are presented in two tables: Financial accounts, consolidated and Financial accounts, non-consolidated.
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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).
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 23 जुलाई, 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.
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 2019
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    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 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.
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 2019
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    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 2019
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      It presents simplified non-financial accounts, from the gross value added to the net lending/net borrowing. In this table, the total economy is broken down in three main institutional sectors: corporations, general government, households and non-profit institutions serving households. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA. Unit of measure used - In national currency, in current prices. Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 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.
    • जून 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जून, 2019
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      Statistical population: Its presents output, intermediate consumption and the gross value added and its components, in particular compensation of employees and gross operating surplus and mixed income, broken down by detailed industries. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. Data presented in this table will not be updated after summer 2010. Data reported to the OECD by countries in their answers to the annual national accounts questionnaire are now available on theme Industry and Services, Structural Analysis (STAN) Databases. Unit of measure used: In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2010). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • जून 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2018
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      The "National CPI Weights" dataset contains the annual expenditure weights for the national CPI for the OECD Member countries at a detailed level of the COICOP classification (except Australia and Korea). The weight of a product in a CPI is the proportion of total household expenditure which is spent on that product during the weight reference period.
    • मई 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 जून, 2016
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      National landings in domestic ports
    • दिसम्बर 2014
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 नवम्बर, 2016
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      The Fisheries Committee (COFI) from the Trade and Agriculture Directorate (TAD) collects, on an annual basis from all its participating countries, data on landings, aquaculture production, fleet, employment in the fisheries sector, and government financial transfers. Data are collected from Fisheries Ministries, National Statistics Offices and other institution designated as an official data source. The OECD, a partner with the CWP, additionaly collects information on values for its landings and records the breakdown between the types of landings (i.e. landings in domestic ports, landings in foreign ports) data series which are not collected by the FAO. While a number of countries cover landings in a similar fashion, the same does not hold true for capacity (feet/meters, GRT/engine powers), or for employment for which both Full-time equivalents or numbers of people are used. The OECD therefore does not duplicate FAO statistics but requests complementary information to feed its analytical work.  
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 2019
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      This dataset presents the number of new entrants in a given programme by age and sex.
  • O
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 अक्तूबर, 2019
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       These tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2011 : OECD COUNTRIES AND EMERGING ECONOMIES. They comprise the summary of agricultural support estimates for OECD countries.
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 नवम्बर, 2019
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    • अक्तूबर 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 अगस्त, 2018
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      The biennial OECD Digital Economy Outlook examines and documents evolutions and emerging opportunities and challenges in the digital economy. It highlights how OECD countries and partner economies are taking advantage of information and communication technologies (ICTs) and the Internet to meet their public policy objectives. Through comparative evidence, it informs policy makers of regulatory practices and policy options to help maximise the potential of the digital economy as a driver for innovation and inclusive growth.   This dataset provides data underlying Chapter 3 on Access and Connectivity in the OECD Digital Economy Outlook 2017.     Table 3.2. Access trends in the OECD area Table 3.3. Fixed telephone access paths in the OECD area Table 3.4. Total communication access paths in the OECD area Table 3.5. Total communication access paths in the OECD area per 100 inhabitants Table 3.6. Cellular mobile subscriptions in the OECD area Table 3.7. Cellular mobile subscriptions in the OECD area per 100 inhabitants Table 3.8. Telecommunication revenue in the OECD area Table 3.9. Telecommunication revenue in the OECD area per GDP Table 3.10. Telecommunication investment in the OECD area Table 3.11. Telecommunication investment as a percentage of telecommunications revenue
    • जून 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 04 जून, 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.
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 नवम्बर, 2019
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      The Agricultural Outlook has been prepared as a joint report by the Organisation for Economic Co-operation and Development (OECD) and the Food and Agriculture Organization (FAO) of the United Nations. The report provides a ten year forward looking, assessment of trends and prospects in the major temperate-zone agricultural commodity markets of biofuels, cereals, oilseeds and oilseed products, sugar, meat, fish and sea food, dairy products, cotton. It is published annually, in the middle of the second quarter, as part of a continuing effort to promote informed discussion of emerging market and policy issues. The data used to develop the projections underlying the assessment are those available as of January 2018.   The projections and assessments provided in the report are the result of close co-operation between the OECD and FAO Secretariats and national experts with a jointly developed modelling system, based on the AGLINK-COSIMO model, used to facilitate consistency in the projections. The data series for the projections are drawn from OECD and FAO databases. For the most part information in these databases has been taken from national statistical sources.
    • मई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 मई, 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.
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 2019
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    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2019
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      This table contains figures on the activity of affiliates located abroad by host country in the total manufacturing, total services and total business enterprise sectors. The units used to present data in AMNE are millions of national currency for monetary variables and units for the other variables. Monetary variables are in current prices. Euro-area countries: national currency data is expressed in euro beginning with the year of entry into the Economic and Monetary Union (EMU). For years prior to the year of entry into EMU, data have been converted from the former national currency using the appropriate irrevocable conversion rate. This presentation facilitates comparisons within a country over time and ensures that the historical evolution is preserved. Please note, however, that pre-EMU euro are a notional unit and should not be used to form area aggregates or to carry out cross-country comparisons.
  • P
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 19 नवम्बर, 2019
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      The International Transport Forum collects data on transport statistics on annual basis from all its Member countries. Data are collected from Transport Ministries, statistical offices and other institution designated as official data source. Variables collected are inland transport of goods (T-km), of passengers (P-km) and road injury accidents. Additional information is also gathered on containers transported by rail and sea (Tons and TEU) as well as short sea shipping data (T-km).
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 अगस्त, 2019
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    • मार्च 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 28 नवम्बर, 2016
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      The Population and Vital Statistics dataset presents components of change in the population during one year and mid-year population data for the 34 OECD member countries. Data are presented in thousands of persons and as rates in per 1000. The components of change in the population during one year are presented as follow: the first statistics refer to the population on January 1st for each year, the natural increase of the population is the difference between the number of births and deaths over the calendar year, the addition of net migration and statistical adjustments to the natural increase gives the total increase of the population over the calendar year. The addition of the total population increase to the population on January 1st gives the population on December 31st. Note: No longer this dataset be collected by OECD. Population and demographic events are available from the United Nation database at "https://esa.un.org/unpd/wpp/Download/Standard/Population/."    
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 2019
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      This dataset contains the number of people by sex and age group per country.
    • जनवरी 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 2018
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      This dataset presents annual population data from 1950 when available by sex and five year age groups. The data is available for the 34 member countries and also for Colombia, Brazil, South Africa and Russian Federation. Data are presented in thousands of persons. The population data is presented in 18 five year age groups which refer to the population from 0-4 to 85 and more.
    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 01 अगस्त, 2019
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      Private transactions are those undertaken by firms and individuals resident in the reporting country.
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 नवम्बर, 2019
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    • दिसम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 जुलाई, 2019
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      Data cover both social security reserve funds and sovereign pension reserve funds, the two main categories of public pension reserve funds. Social security reserve funds are set up as part of the overall social security system. They are funded chiefly by surpluses from employee and/or employer contributions over current payouts and, in some cases, by top-up contributions from the government through fiscal transfers and other sources. They may be managed either as part of a national social security scheme or by an independent - often public sector - fund management entity. Sovereign pension reserve funds are funds established by governments (independently of social security systems), who finance them directly through fiscal transfers. They are usually mandated to finance public pension expenditures at a specific future date. Some are not allowed to make any payouts for decades.
    • मार्च 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 मार्च, 2019
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      This dataset contains Purchasing Power Parities (PPPs) for all OECD countries. PPPs are the rates of currency conversion that eliminate the differences in price levels between countries. Per capita volume indices based on PPP converted data reflect only differences in the volume of goods and services produced. Comparative price levels are defined as the ratios of PPPs to exchange rates. They provide measures of the differences in price levels between countries. The PPPs are given in national currency units per US dollar. The price levels and volume indices derived using these PPPs have been rebased on the OECD average. Per capita volume indices should not be used to rank countries as PPPs are statistical constructs rather than precise measures. Minor differences between countries should be interpreted with caution.
  • Q
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 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
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2019
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      This table contains research and development (R&D) expenditure statistics on current domestic R&D and gross domestic R&D expenditures by sector of performance (business enterprise, government, higher education, private non-profit, and total intramural) and by type of R&D within each sector (basic research, applied research, experimental development, non-specified, and total activity). Unit of measure used - Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2005 prices and PPPs).
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2019
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      These tables contain research and development (RD) personnel statistics. Number of RD personnel is provided in both headcounts and full-time equivalent on RD by sex, sector of employment (business enterprise, government, higher education, and private non-profit) and by occupation (researchers, technicians and other support staff).
    • जून 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 21 जून, 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.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 जुलाई, 2019
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    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 07 नवम्बर, 2019
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      The Regional Database contains annual data from 1995 to the most recent available year. The data collection is undertaken by the Directorate of Public Governance and Territorial Development, within the Regional Development Policy division (GOV/RDP). Statistics are collected through an annual questionnaire sent to the delegates of the Working Party on Territorial Indicators (WPTI), and through access to the web-sites of National Statistical Offices and Eurostat. The WPTI is responsible for developing regional (subnational) and urban statistics and providing analysis to support policy evaluations. The Regional Database includes statistics on the regional distribution of resources, regional disparities, and how regions contribute to national growth and the well-being of society. Under this framework, the Regional Database is one of the pillars for providing indicators to the publication OECD Regions at a Glance (link).
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 2019
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      The Regional Database contains annual data from 1995 to the most recent available year (generally 2014 for demographic and labour market data, 2013 for regional accounts, innovation and social statistics).   In any analytical study conducted at sub-national levels, the choice of the territorial unit is of prime importance. The territorial grids (TL2 and TL3) used in this database are officially established and relatively stable in all member countries, and are used by many as a framework for implementing regional policies. This classification - which, for European countries, is largely consistent with the Eurostat classification - facilitates greater comparability of regions at the same territorial level. The differences with the Eurostat NUTS classification concern Belgium, Greece and the Netherlands where the NUTS 2 level correspond to the OECD TL3 and Germany where the NUTS1 corresponds to the OECD TL2 and the OECD TL3 corresponds to 97 spatial planning regions (Groups of Kreise). For the United Kingdom the Eurostat NUTS1 corresponds to the OECD TL2. Due to limited data availability, labour market indicators in Canada are presented for a different grid (groups of TL3 regions). Since these breakdowns are not part of the OECD official territorial grids, for the sake of simplicity they are labelled as Non Official Grids (NOG).
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2019
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      The Regional well-being dataset presents eleven dimensions central for well-being at local level and for 395 OECD regions, covering material conditions (income, jobs and housing), quality of life (education, health, environment, safety and access to services) and subjective well-being (social network support and life satisfaction). The set of indicators selected to measure these dimensions is a combination of people's individual attributes and their local conditions, and in most cases, are available over two different years (2000 and 2014). Regions can be easily visualised and compared to other regions through the interactive website [www.oecdregionalwellbeing.org]. The dataset, the website and the publications "Regions at a Glance" and "How’s life in your region?" are outputs designed from the framework for regional and local well-being. The Regional income distribution dataset presents comparable data on sub-national differences in income inequality and poverty for OECD countries. The data by region provide information on income distribution within regions (Gini coefficients and income quintiles), and relative income poverty (with poverty thresholds set in respect of the national population) for 2013. These new data complement international assessments of differences across regions in living conditions by documenting how household income is distributed within regions and how many people are poor relatively to the typical citizen of their country. For analytical purposes, the OECD classifies regions as the first administrative tier of sub-national government, so called Territorial Level 2 or TL2 in the OECD classification. This classification is used by National Statistical Offices to collect information and it represents in many countries the framework for implementing regional policies. Well-being indicators are shown for the 395 TL2 OECD regions, equivalent of the NUTS2 for European countries, with the exception for Estonian where well-being data are presented at a smaller (TL3) level and for the Regional Income dataset, where Greece, Hungary and Poland data are presented at a more aggregated (NUTS1) level.
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 04 नवम्बर, 2019
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      Residential Property Prices Indices (RPPIs) – also named House price indices (HPIs), are index numbers that measure the price of residential properties over time. RPPIs are key statistics not only for citizens and households across the world, but also for economic and monetary policy makers. Among their professional uses, they serve, for example, to monitor macroeconomic imbalances and risk exposure of the financial sector. This dataset covers the 34 OECD member countries and some non-member countries. Please note that not all RPPIs are available for all countries. For instance, the RPPI at the most aggregate level for the United States only covers single-family dwellings, not all types of dwellings as it is the case for most other OECD countries. This dataset presents, for each country, the RPPI that is available at the most aggregate level. It mainly contains quarterly statistics. The dataset called “Residential Property Price Indices (RPPIs) – Complete dataset” contains the full list of available RPPIs. The dataset called “Analytical house price indicators” contains, in addition to nominal RPPIs, information on real house prices, rental prices and the ratios of nominal prices to rents and to disposable household income per capita. The datasets “Analytical house price indicators” and “Residential Property Price Indices (RPPIs) – Headline Indicators” do not refer to the same price indices for Brazil, Canada, China, Germany, the United States and the Euro area. These differences are further documented in country-specific metadata. For the United States, the series used in “Analytical house price indicators” is included in the dataset called “Residential Property Price Indices (RPPIs) – Complete database”, but is not the headline indicator. For all other countries, non-seasonally adjusted price indices in both datasets are identical in the period in which they overlap.For all other countries, non-seasonally adjusted price indices in both datasets are identical on the overlapping period.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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
    • दिसम्बर 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 2018
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      Data on government sector receipts, and on taxes in particular, are basic inputs to most structural economic descriptions and economic analyses and are increasingly used in international comparisons. This annual database presents a unique set of detailed and internationally comparable tax data in a common format for all OECD countries.
    • मार्च 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 मार्च, 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
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 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
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 अक्तूबर, 2019
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      Demand for statistics on business demography has grown and developed considerably in recent years. Data on births and deaths of enterprises, their life expectancy and the important role they play in economic growth and productivity, as well as the information they provide for tackling social demographic issues, are increasingly requested by policy makers and analysts alike. Business demography is a core element of the OECD’s Entrepreneurship Indicators Project, where the OECD and Eurostat are collaborating to develop a framework for the regular and harmonised measurement of entrepreneurial activity and the factors that enhance or impede it. The data in this database is presented in International Standard of Industrial Classification (ISIC Revision 4).
    • मार्च 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 मार्च, 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.
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 नवम्बर, 2019
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      The Short-Term Labour Market Statistics dataset contains predominantly quarterly labour statistics, and associated statistical methodological information, for the 35 OECD member countries and selected other economies. The Short-Term Labour Market Statistics dataset covers countries that compile labour statistics from sample household surveys on a monthly or quarterly basis. It is widely accepted that household surveys are the best source for labour market key statistics. In such surveys, information is collected from people living in households through a representative sample and the surveys are based on standard methodology and procedures used internationally. The subjects available cover: working age population by age; active and inactive labour force by age; employment by economic activity, by working time and by status; and, unemployment (including monthly harmonised unemployment) by age and by duration. Data is expressed in levels (thousands of persons) or rates (e.g. employment rate) where applicable.   Data are based on Labour Force Surveys and national information in this dataset is directly collected from the following sources:   ABS - Australian Bureau of Statistics (Australia) Statistics Canada (Canada) INE - Instituto Nacional de Estadísticas (Chile) CBS – Central Bureau of Statistics (Israel) Statistics Bureau (Japan) Statistics Korea (Korea) INEGI - Instituto Nacional de Estadísticas y Geografía (Mexico) Statistics New Zealand (New Zealand) BLS - Bureau of Labor Statistics (the United States) Eurostat (Austria, Belgium, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Luxembourg, the Netherlands, Norway, Poland, Portugal, the Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey and the United Kingdom).
    • सितम्बर 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 नवम्बर, 2017
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      The OECD Social Expenditure Database (SOCX) has been developed in order to serve a growing need for indicators of social policy. It includes reliable and internationally comparable statistics on public and mandatory and voluntary private social expenditure at programme level. SOCX provides a unique tool for monitoring trends in aggregate social expenditure and analysing changes in its composition. It covers 35 OECD countries for the period 1980-2013/14 and estimates for aggregates for 2014-16. A Social Expenditure Update - 8-page report- can be found under www.oecd.org/social/expenditure.htm The main social policy areas are as follows: Old age, Survivors, Incapacity-related benefits, Health, Family, Active labor market programmes, Unemployment, Housing, and Other social policy areas. This version also includes estimates of net total social spending for 2013 for 34 OECD countries. SOCX aggregated data are described in Adema, W., P. Fron and M. Ladaique (2011) (see Methodology Part II). Sources and methodology for the estimations 2014-2016 are also described here
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 अगस्त, 2019
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      The OECD Social Expenditure Database (SOCX) has been developed in order to serve a growing need for indicators of social policy. It includes reliable and internationally comparable statistics on public and mandatory and voluntary private social expenditure at programme level. SOCX provides a unique tool for monitoring trends in aggregate social expenditure and analysing changes in its composition. It covers 35 OECD countries for the period 1980-2013/14 and estimates for aggregates for 2014-16. The main social policy areas are as follows: Old age, Survivors, Incapacity-related benefits, Health, Family, Active labor market programmes, Unemployment, Housing, and Other social policy areas. This version also includes estimates of net total social spending for 2013 for 34 OECD countries.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 जुलाई, 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.
    • दिसम्बर 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 2018
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      Input-Output tables describe the sale and purchase relationships between producers and consumers within an economy. They can be produced by illustrating flows between the sales and purchases (final and intermediate) of industry outputs or by illustrating the sales and purchases (final and intermediate) of product outputs. The OECD Input-Output database is presented on the former basis, reflecting in part the collection mechanisms for many other data sources such as research and development Research and Development expenditure data, employment statistics, pollution data, energy consumption, which are in the main collected by enterprise or by establishment, and thus according to industry classifications.
    • दिसम्बर 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 2018
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      Input-Output tables describe the sale and purchase relationships between producers and consumers within an economy. They can be produced by illustrating flows between the sales and purchases (final and intermediate) of industry outputs or by illustrating the sales and purchases (final and intermediate) of product outputs. The OECD Input-Output database is presented on the former basis, reflecting in part the collection mechanisms for many other data sources such as research and development Research and Development expenditure data, employment statistics, pollution data, energy consumption, which are in the main collected by enterprise or by establishment, and thus according to industry classifications.
    • जून 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 जुलाई, 2019
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  • T
    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 16 अप्रैल, 2019
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      This table reports self-employed social security contribution rates and related provisions. A representative case is used for those countries where social security provisions vary by locality. Threshold and maximum contribution amounts are shown in national currencies.
    • मार्च 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 15 मई, 2019
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      The data presented here refer to the latest year available. The data on the state of threatened species build on country replies to the Annual Quality Assurance (AQA) of OECD environmental reference series. These data are harmonised through the work of the OECD Working Party on Environmental Information (WPEI). Some where updated or revised on the basis of comments from national Delegates and in the framework of the OECD Environmental Performance Reviews. When interpreting these data, it should be borne in mind that the number of species known does not always accurately reflect the number of species in extistence and that varying definitions can limit comparability accross countries. Species assessed as Critically Endangered (CR), Endangered (EN), or Vulnerable (VU) are referred to as "threatened" species. Reporting the proportion of threatened species on The IUCN Red List is complicated by the fact that not all species groups have been fully evaluated, and also by the fact that some species have so little information available that they can only be assessed as Data Deficient (DD). For many of the incompletely evaluated groups, assessment efforts have focused on species that are likely to be threatened; therefore any percentage of threatened species reported for these groups would be heavily biased (i.e., the % threatened species would likely be an overestimate). The data presented here show numbers of known species (or assessed) and threatened species with the aim of indicating the state of mammals, birds, freshwater fish, reptiles, amphibians, vascular plants, mosses, lichens and invertebrates.
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 24 सितम्बर, 2019
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      Official Development Financing (ODF), measured for recipient countries only, is defined as the sum of their receipts of bilateral ODA, concessional and non-concessional resources from multilateral sources, and bilateral other official flows made available for reasons unrelated to trade, in particular loans to refinance debt.
    • मई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 28 मई, 2019
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      Total Official Flows: the sum of Official Development Assistance (ODA) and Other Official Flows (OOF) represents the total (gross or net) disbursements by the official sector at large to the recipient country shown.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 15 अक्तूबर, 2019
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      Total Receipts, Net: in addition to Official Development Assistance, this heading includes in particular: other official bilateral transactions which are not concessional or which, even though they have concessional elements, are primarily trade facilitating in character (i.e., "Other Official Flows''); changes in bilateral long-term assets of the private non-monetary and monetary sectors, in particular guaranteed export credits, private direct investment, portfolio investment and, to the extent they are not covered in the preceding headings, loans by private banks. Flows from the multilateral sector which are not classified as concessional are also included here.
    • मार्च 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 मार्च, 2019
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      The central issue of trade by enterprise characteristics is to disaggregate trade flows according the characteristics of the enterprises engaged in cross-border transactions. The feasibility of doing so largely depends on the possibility of using or developing common identifiers between the trade register and the business register. Countries differ in their ability to perform such a linking, and matching ratios (between business and trade registers) vary across countries, and as a consequence the degree of representativeness of the results also varies across countries.
    • मार्च 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 मार्च, 2019
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      This table presents export/import information by enterprise size class and partner country.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2019
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      This dataset shows the number of exporters and importers and their associated trade values for a selected set of partner countries and zones, broken down by three economic sectors: industry, trade and repair and other sectors. Total values for the wide economy are also displayed.Recommended uses and limitations EU countries break down trade data into Intra- and extra- EU zones, whereas non EU countries report their Total trade. Trade values have been aggregated for EU countries and Total (Intra-EU plus Extra-EU) trade flows are displayed, whereas Intra and Extra-EU data expressed in term of number of enterprises cannot be summed up, because of possible double-counting (same enterprise can be trader in both intra- and extra- EU trade). Data have been collected in ISIC revision 3 from 2003 up to 2007 and in ISIC revision 4 as from reference year 2008. Time series are affected by this change in classification, and thus data are displayed into two separate databases.
    • जून 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 जून, 2019
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      The central issue of trade by enterprise characteristics is to disaggregate trade flows according the characteristics of the enterprises engaged in cross-border transactions. The feasibility of doing so largely depends on the possibility of using or developing common identifiers between the trade register and the business register. Countries differ in their ability to perform such a linking, and matching ratios (between business and trade registers) vary across countries, and as a consequence the degree of representativeness of the results also varies across countries.
    • दिसम्बर 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 2018
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      This dataset shows imports/exports by type of trader that is exporter only, importer only or both importer and exporter (Two-way trader).
    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 अप्रैल, 2019
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      This table contains the number of active trade union members and the number of wage and salary earners. Data on union membership are broken down by source of data (administrative or survey data). Membership corresponds to the number of wage and salary earners that are members of a trade union. Total number of wage and salary earners are taken from OECD Labour Force Statistics.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 23 जुलाई, 2019
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      The lack of common definitions and practices to measure transport infrastructure spending hinders comparisons between countries and spending options. Data for road and rail infrastructure are the most comprehensive while data on sea port and airport spending are less detailed in coverage and definition. While our survey covers all sources of financing a number of countries exclude private spending, including Japan and India. Around 65% of countries report data on urban spending while for the remaining countries data on spending in this area are missing. Indicators such as the share of GDP needed for investment in transport infrastructure, depend on a number of factors, such as the quality and age of existing infrastructure, maturity of the transport system, geography of the country and transport-intensity of its productive sector. Caution is therefore required when comparing investment data between countries. However, data for individual countries and country groups are consistent over time and useful for identifying underlying trends and changes in levels of spending, especially for inland transport infrastructure. These issues of definitions and methods are addressed in a companion report Understanding the Value of Transport Infrastructure – Guidelines for macro-level measurement of spending and assets (ITF/OECD2013) that aims to improve the international collection of related statistics.
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 नवम्बर, 2019
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      This data set is a combination of three tables, 1. Good Transport- Inland freight 2. Passenger transport 3. Transport Safety- Road injury accidents- Road CausalitiesThe geographical area covered is the ITF member countries.The International Transport Forum collects data on transport statistics on annual basis from all its Member countries. Data are collected from Transport Ministries, statistical offices and other institution designated as official data source.TEU (Twenty-foot Equivalent Unit): a statistical unit based on an ISO container of 20 foot length (6.10 m) to provide a standardised measure of containers of various capacities and for describing the capacity of container ships or terminals. one 20 Foot ISO container equals 1 TEU.  
  • U
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 13 अगस्त, 2019
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      This dataset contains data on the share of the five durations - less than 1 month, >1 month and < 3 months, >3 months and <6 months, >6 months and <1 year, 1 year and over - of unemployment among total unemployment by sex and by standardised age groups (15-19, 15-24, 20-24, 25-54, 55+, total).
  • W
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 08 अक्तूबर, 2019
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      This dataset provides information on the level of public equipment installed by countries to managed and abate water pollution. It shows the percentage of national population connected to "public" sewerage networks and related treatment facilities, and the percentage of national population connected to "public" wastewater treatment plants, and the degree of treatment. Connected here means actually connected to a wastewater plants through a public sewage network. Individual private treatment facilities such as septic tanks are not covered here. When analysing these data, it should be kept in mind that the optimal connection rate is not necessarily 100 per cent; it may vary among countries and depends on geographical features and on the spatial distribution of habitats. The interpretation of those data should take into account some variations in countries' definitions, as reflected in metadata.

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"हमारी वेबसाइट आपके ऑनलाइन अनुभव को बेहतर बनाने के लिए कुकीज़ का उपयोग करती है। जब आपने यह वेबसाइट लॉन्च की, तो उन्हें आपके कंप्यूटर पर रखा गया था। आप अपने इंटरनेट ब्राउज़र सेटिंग्स के माध्यम से अपनी व्यक्तिगत कुकी सेटिंग्स बदल सकते हैं।"

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