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: 1 2 3 6 7 8 9 A B C D E F G H I J K L M N O P Q R S T U V W
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    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 अगस्त, 2023
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      This dataset contains the main results of the 2017 Eurostat-OECD PPP comparison for the 49 countries that participated in the 2017 round of the Eurostat-OECD Purchasing Power Parity (PPP) Programme. Colombia and Costa Rica participated for the first time. Please note that time series for PPPs for GDP, actual individual consumption and household final consumption for these two countries in the National Accounts databases are still based on the 2011 ICP results until April 2020 (release of ICP 2017 results).
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 14 सितम्बर, 2023
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  • A
    • अक्तूबर 2020
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 27 अक्तूबर, 2020
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      Chapter C includes indicators that are a mixture of outcome indicators, policy levers and context indicators. Internationalisation of education and progression rates are, for instance, outcome measures to the extent that they indicate the results of policies and practices at the classroom, school and system levels. But they can also provide contexts for establishing policy by identifying areas where policy intervention is necessary, for example, to address issues of inequity.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 09 नवम्बर, 2023
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      This indicator measures the income of selected jobless families that claim Guaranteed Minimum Income (GMI) benefits. Values are expressed both in national currency and as a percentage of the median disposable income in the country. When the country's poverty line is defined as a fixed percentage of the median disposable income, the normalization of GMI amounts in terms of the median disposable income allows measuring the gap between benefit entitlements and the poverty line. For instance, if the poverty threshold is 50% of the median disposable income, a value of the indicator of 30% means that benefit entitlements are 20 percentage points below the poverty line.
    • अप्रैल 2024
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 25 अप्रैल, 2024
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    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 30 अगस्त, 2023
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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 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 20 अक्तूबर, 2023
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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.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 अक्तूबर, 2023
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    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 09 अक्तूबर, 2023
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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.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 05 अक्तूबर, 2023
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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.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 08 अक्तूबर, 2023
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      This dataset is used to report the tying status of bilateral ODA commitments. Members have agreed that administrative costs and technical co-operation expenditure should be disregarded in assessing the percentages of tied, partially untied and untied aid. These items have not been included in the data reported in this data set.
    • अप्रैल 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 05 मई, 2023
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      This dataset contains bilateral commitment data on aid in support of environment sustainability and aid to biodiversity, climate change mitigation, climate change adaptation and desertification from the Development Assistance Committee (DAC) Creditor Reporting System (CRS) database. In their reporting to the DAC CRS, donors are requested to indicate for each activity whether or not it targets environment and the Rio Conventions (biodiversity, climate change mitigation, climate change adaptation and desertification). A scoring system of three values is used, in which aid activities are "marked" as targeting environment as the "principal objective" or a "significant objective", or as not targeting the objective. The environment marker identifies activities that are "intended to produce an improvement in the physical and/or biological environment of the recipient country, area or target group concerned" or "include specific action to integrate environmental concerns with a range of development objectives through institution building and/or capacity development". A large majority of activities targeting the objectives of the Rio Conventions fall under the DAC definition of "aid to environment". The Rio markers permit their specific identification.
    • जनवरी 2021
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 06 सितम्बर, 2022
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      This dataset contains commitment data (since 2002) and disbursement data (since 2009) on aid in support of gender equality from the CRS database. In their reporting to the Development Assistance Committee (DAC) Creditor Reporting System (CRS), donors are requested to indicate for each activity whether or not it targets gender equality as one of its policy objectives. To qualify as “gender equality focussed,” an activity must explicitly promote gender equality and women’s empowerment. An activity can either target gender equality as its “principal objective” or as a “significant objective”. A “principal” score (2) is assigned if gender equality was an explicit objective of the activity and fundamental to its design - i.e. the activity would not have been undertaken without this objective. A “significant” score (1) is assigned if gender equality was an important, but secondary, objective of the activity - i.e. it was not the principal reason for undertaking the activity. A “not targeted” score (0) is assigned if, after being screened against the gender equality policy marker, an activity is not found to target gender equality. Activities assigned a “principal objective” score should not be considered better than activities assigned a “significant objective” score, as donors that mainstream gender equality - and thus integrate it into their projects across a range of sectors - are more likely to allocate the marker score “significant” to their aid activities. The gender equality marker allows an approximate quantification of aid flows that target gender equality as a policy objective. In marker data presentations the figures for principal and significant objectives should be shown separately and the sum referred to as the “estimate” or “upper bound” of gender equality-focussed aid. An activity can have more than one principal or significant objective. Therefore, total amounts targeting the different objectives should not be added-up to avoid double-counting. Policy markers seek information on the donor’s policy objectives which can be best assessed at the design stage of projects. This is why policy markers are applied to commitments. Policy marker data on a disbursement basis can also be compiled, but it is important to note that this does not mean the policy objectives of projects under implementation would have been re-assessed. Rather, the disbursements are linked to the qualitative information on the original commitment through project identifiers. Consequently, a project marked as gender equality focussed at the commitment stage will be flagged as gender equality focussed throughout its lifetime, unless the qualitative information was changed. Activity-level gender equality marker data that underlie the aggregate figures presented in this dataset are available for consultation and download: see “Export”, “Related files”.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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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.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 08 नवम्बर, 2023
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      Residential Property Prices Indices (RPPIs) – also named House price indices (HPIs), are index numbers that measure the prices of residential properties over time. RPPIs are key statistics not only for citizens and households across the world, but also for economic and monetary policy makers. They can help, for example, to monitor potential macroeconomic imbalances and the risk exposure of the household and financial sectors. This dataset covers the 34 OECD member countries and some non-member countries. In addition to the nominal RPPIs it contains information on real house prices, rental prices and the ratios of nominal prices to rents and to disposable household income per capita. This dataset contains quarterly statistics for each country. House prices differ widely across OECD countries, both with respect to recent changes and to valuation levels. The OECD has identified one main nominal index for each country that covers the prices for the sale of newly-built and existing dwellings. The datasets “Analytical house price indicators” and “Residential Property Price Indices (RPPIs) – Headline Indicators” refer to the same price indices for all countries apart from Brazil, Canada, China, the United States and the Euro area. These differences are further documented in country-specific metadata. For the United States, the series used in “Analytical house price indicators” is included in the dataset called “Residential Property Price Indices (RPPIs) – Complete database”, but is not the headline indicator. For all other countries, non-seasonally adjusted price indices in both datasets are identical in the period in which they overlap. This research dataset provides extended time series coverage for many countries. The objective is to provide information on the long term trend of house prices and develop indicators which can be used to help track and analyse macroeconomic developments and risks. The extended data supplement the OECD RPPI data with historical data from a variety of sources, including other international organisations, central banks and national statistical offices. The methodological basis on the historical data and the types of geographical areas and dwellings they cover can differ from those used in the OECD RPPI data. The database contains a number of additional series. Real house prices are given by the ratio of seasonally adjusted nominal house prices to the seasonally adjusted consumers’ expenditure deflator in each country, from the OECD national accounts database. This provides information on how nominal house prices have changed over time relative to prices in the general economy. The rental prices come from the OECD Main Economic Indicators database and refer to Consumer Price Indices (CPIs) for Actual rentals for housing (COICOP 04.1). If this indicator is missing for a country, another indicator is chosen. The chosen indicator are usually those corresponding to the CPI aggregate for Housing including Actual rentals for housing (COICOP 04.1), imputed rentals for housing (COICOP 04.2) and Maintenance and repair of the dwelling (COICOP 04.3). The disposable income indicators come from the OECD national accounts database. Net household disposable income is used. The population data come from the OECD national accounts database. The price-to-rent ratio is given by the ratio of nominal house prices to rental prices. This is a measure of the profitability of owning a house. The price-to-income ratio is given by the ratio of nominal house prices to nominal household disposable income per capita. This is a measure of the affordability of purchasing a house. An indication that house prices may be overvalued is provided if either of these ratios is above their long-term averages. The standardised price-rent and price-income ratios show the current price-rent and price-income ratios relative to their respective long-term averages. The long-term average, which is used as a reference value, is calculated over the whole period available when the indicator begins after 1980 or 1980 if the indicator is available over a longer time period. The standardised ratio is indexed to a reference value equal to 100 over the full sample period. Values over 100 indicate that the present price-rent ratio, or price-income ratio, is above its long-run norms. This provides an indication of possible housing market pressures.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 25 जुलाई, 2023
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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.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 08 अक्तूबर, 2023
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      The dataset includes a detailed breakdown of Investment funds, Insurance companies and Pension funds, and Other forms of institutional savings, as institutional sectors. This finer breakdown by type of investors has been established with reference to the System of National Accounts (SNA), when possible. Within Investment funds, one distinguishes Open-end companies, further broken down into Money market funds and Other mutual funds, and Closed-end companies, of which Real estate funds. Within Insurance companies and pension funds one distinguishes Insurance companies, further broken down into Life insurance companies and Non-life insurance companies, and Autonomous pension funds. Financial assets included correspond to the assets requested in the previous database on Institutional Investors, i.e. Currency and deposits, Securities other than shares, Loans, Shares and other equities and Other financial assets. Moreover, Total non-financial assets are also included. While the sub-classification of the above financial assets corresponds to SNA93, a further breakdown between assets issued by residents and assets issued by non-residents is reported.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 13 जनवरी, 2024
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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).
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 12 सितम्बर, 2023
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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.
    • जून 2021
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 29 जून, 2021
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      This dataset presents the average number of students in a class by type of institution.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 17 अक्तूबर, 2023
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      This table contains data on the average duration of unemployment by sex and standardised age groups (15-19, 15-24, 20-24, 25-54, 55+, total). Data are expressed in months.
    • दिसम्बर 2019
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 12 अगस्त, 2020
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      The average effective age of retirement is calculated as a weighted average of (net) withdrawals from the labour market at different ages over a 5-year period for workers initially aged 40 and over. In order to abstract from compositional effects in the age structure of the population, labour force withdrawals are estimated based on changes in labour force participation rates rather than labour force levels. These changes are calculated for each (synthetic) cohort divided into 5-year age groups. The estimates shown in red are less reliable as they have been derived from interpolations of census data rather than from annual labour force surveys. The estimates for women in Turkey are based on 3-yearly moving averages of participation rates for each 5-year age group. OECD estimates based on the results of national labour force surveys, the European Union Labour Force Survey and, for earlier years in some countries, national censuses.
  • B
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 26 जनवरी, 2024
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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) .
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 22 दिसम्बर, 2023
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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 2020
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 11 जनवरी, 2021
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    • मई 2018
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 31 मई, 2018
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      The Benefits and Wages series addresses the complicated interactions of tax and benefit systems for different family types and labour market situations. The series is a valuable tool used to compare the different benefits made available to those without work and those with different levels of in-work income for OECD countries and EU countries. The main social policy areas are as follows: taxes and social security contributions due on earnings and benefits, unemployment benefits, social assistance, family benefits, housing benefits, and in-work benefits. OECD Work Incentive and Income adequacy indicators, country specific files, the tax-benefit models and the tax benefit calculator, including detailed descriptions of all cash benefits available to those in and out of work as well as the taxes they were liable to pay are available on Benefits and Wages: OECD Indicators   Unit of measure used: Estonia: 2011 - EUR; 2010; 2009; 2008; 2007; 2006; 2005 -EEK Slovak Republic: 2010; 2009 - EUR; 2008; 2007; 2006; 2005 -SKK
    • मार्च 2024
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 17 जुलाई, 2024
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      The OECD broadband database provides access to a range of broadband-related statistics gathered by the OECD. Policymakers must examine a range of indicators which reflect the status of individual broadband markets in the OECD. Source - https://www.oecd.org/digital/broadband/broadband-statistics/
    • नवम्बर 2021
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 06 सितम्बर, 2022
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      The OECD broadband portal provides access to a range of broadband-related statistics gathered by the OECD. Policy makers must examine a range of indicators which reflect the status of individual broadband markets. The OECD broadband speed tests by country show the official measurements of actual access network broadband speed. The OECD broadband map shows national broadband statistics in OECD countries. Mobile broadband penetration has risen to 85.4% in the OECD area, meaning more than four wireless subscriptions for every five inhabitants, according to data for June 2015 released by the OECD .
    • मार्च 2022
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 मई, 2022
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 24 जुलाई, 2023
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      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2000 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics performed in the business enterprise sector by industry according to the International Standard Industrial Classification (ISIC) revision 3.1. and by type of costs (current expenditure, capital expenditure). Data at the industry level are presented beginning 1987, year when most of the countries converted from ISIC rev.2 to the current ISIC rev. 3 classification. This breakdown between industries is, in principle, made at the enterprise level, although some countries are able to break down R&D data for multi product enterprises between their main lines of business. National statistical regulations prevent publication of results where there are very few firms in the given category, hence the many gaps in the tables. Depending on the country, R&D institutes serving enterprises are either classified with the industry concerned, or grouped under “Research and Development” (ISIC rev.3.1, Division 73). When these R&D institutes are classified with the industry served, the evaluation of R&D in these industries is more complete and more comparable between countries for the industries concerned. This results, however, in an underestimation of the percentage of BERD performed by the service sector as compared with other countries. The Frascati Manual recommendation concerning data on R&D by industry is to report BERD on an enterprise basis (see FM section 3.4). When this is interpreted strictly, all the BERD of a diversified enterprise will be allocated to the industrial class of its principal activity. In circumstances where a few large firms dominate R&D spending in several areas, this can and does lead to underestimates of R&D associated with the secondary activities of the firms. Overall, R&D is therefore overestimated for some industries and underestimated for others. However, not all countries follow a strict enterprise basis for allocating R&D expenditures to industrial classes. Some countries make a disaggregation of the R&D of their largest, diversified firms into a number of different activities. In other countries, the enterprise approach has been abandoned and data are reported on a product field basis. This is why two classification criteria for BERD by industry are included in the table “BERD by industry” (see the variable CLASSIFICATION CRITERIA: Main activity or Product field) depending on which approach is more closely followed by each country (only a few countries currently collect these data both ways and are therefore included according to both criteria). However, this table “BERD by industry and type of costs” and the preceding one “BERD by industry and source of funds” present data for only one of the criteria, depending on the country.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 26 जुलाई, 2023
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    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2005 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics performed in the business enterprise sector by industry according to the International Standard Industrial Classification (ISIC) revision 3.1. and by source of funds (business enterprise, government, other national funds, and funds from abroad). Data at the industry level are presented beginning 1987, year when most of the countries converted from ISIC rev.2 to the current ISIC rev. 3 classification. This breakdown between industries is, in principle, made at the enterprise level, although some countries are able to break down R&D data for multi product enterprises between their main lines of business. National statistical regulations prevent publication of results where there are very few firms in the given category, hence the many gaps in the tables. Depending on the country, R&D institutes serving enterprises are either classified with the industry concerned, or grouped under “Research and Development” (ISIC rev.3.1, Division 73). When these R&D institutes are classified with the industry served, the evaluation of R&D in these industries is more complete and more comparable between countries for the industries concerned. This results, however, in an underestimation of the percentage of BERD performed by the service sector as compared with other countries. The Frascati Manual recommendation concerning data on R&D by industry is to report BERD on an enterprise basis (see FM section 3.4). When this is interpreted strictly, all the BERD of a diversified enterprise will be allocated to the industrial class of its principal activity. In circumstances where a few large firms dominate R&D spending in several areas, this can and does lead to underestimates of R&D associated with the secondary activities of the firms. Overall, R&D is therefore overestimated for some industries and underestimated for others. However, not all countries follow a strict enterprise basis for allocating R&D expenditures to industrial classes. Some countries make a disaggregation of the R&D of their largest, diversified firms into a number of different activities. In other countries, the enterprise approach has been abandoned and data are reported on a product field basis. This is why two classification criteria for BERD by industry are included in the table “BERD by industry” (see the variable CLASSIFICATION CRITERIA: Main activity or Product field) depending on which approach is more closely followed by each country (only a few countries currently collect these data both ways and are therefore included according to both criteria). However, this table “BERD by industry and source of funds” and the one that follows, “BERD by industry and type of costs” present data for only one of the criteria, depending on the country.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2010 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics performed in the business enterprise sector. Data include total business enterprise intramural expenditure on R&D by size class and source of funds.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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      This table presents research and development (R&D) statistics on personnel in the business enterprise sector. Measured in full-time equivalent are the number of total R&D personnel and researchers in the business enterprise sector by industry according to the International Standard Industrial Classification (ISIC) revision 3.1. Data at the industry level are presented beginning 1987, year when most of the countries converted from ISIC rev.2 to the current ISIC rev. 3 classification.
    • जुलाई 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 31 जनवरी, 2024
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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.
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 दिसम्बर, 2023
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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
    • जनवरी 2022
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Darshini Priya Premkumar
      Accessed On: 31 जनवरी, 2022
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      OECD Indicators on Carbon dioxide (CO2) emissions embodied in international trade (TeCO2) are derived by combining the 2021 editions of OECD Inter-Country Input-Output (ICIO) Database and of International Energy Agency (IEA) statistics on CO2 emissions from fuel combustion. In this release of TeCO2, emissions from fuels used for international aviation and maritime transport (i.e. aviation and marine bunkers) are also considered.Production-based CO2 emissions are estimated by allocating the CO2 emissions to the 45 target industries in OECD ICIO and, to household final consumption of fuels, by both residents and non-residents.Demand-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.For more information, see TeCO2 web page: http://oe.cd/io-co2.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 07 सितम्बर, 2023
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      This indicator reports the amount of carbon emissions from fossil fuel combustion embodied in imports and exports in mega tonnes of CO2 (MtCO2) for 63 countries and 34 industries between 1995 and 2011.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 अक्तूबर, 2023
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      The indicator reports the hypothetical amount of carbon emissions from fossil fuel combustion embodied in imports if imported goods were produced with a carbon intensity (i.e. emissions factors) equal to that of the importing country at a given time – the Equal Carbon Intensity (ECI) assumption. It covers 65 countries and 34 industries between 1995 and 2011.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 अक्तूबर, 2023
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    • दिसम्बर 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 2018
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      Note:  The updates and revisions for the OECD Central Government Debt Database have been suspended. This dataset is no longer updated. For more info, please read http://stats.oecd.org/Index.aspx?DataSetCode=GOV_DEBT   Statistical population The focus of this dataset is to provide comprehensive quantitative information on marketable and non-marketable central government debt instruments in all OECD member countries. The coverage of the data is limited to central government debt issuance and excludes therefore state and local government debt and social security funds.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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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
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 दिसम्बर, 2023
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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 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 2018
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      The OECD Science, Technology and Industry Outlook 2012 presents, in a series of country profiles, the main features, strengths and weaknesses of national STI systems and major recent changes in national STI policy. The statistical dimension of the country profiles has drawn on the work and empirical research conducted by the OECD on the measurement of innovation and the development of internationally comparable STI indicators for policy analysis.   
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 जनवरी, 2024
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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.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 अक्तूबर, 2023
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      This dataset presents the Consolidated financial balance sheets by economic sector (Quarterly table 0710), according to SNA 2008 methodology. It comprises all flows, which record, by type of financial instruments, the financial transactions between institutional sectors.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 अक्तूबर, 2023
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      This dataset presents the Consolidated financial transactions by economic sector (Quarterly table 0610), according to SNA 2008 methodology. It comprises all flows, which record, by type of financial instruments, the financial transactions between institutional sectors.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 जनवरी, 2024
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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).
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 अक्तूबर, 2023
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    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 21 नवम्बर, 2023
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    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 23 अगस्त, 2023
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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
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2023
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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
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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    • अप्रैल 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 मई, 2024
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      The objective of the CRS Aid Activity database is to provide a set of readily available basic data that enables analysis on where aid goes, what purposes it serves and what policies it aims to implement, on a comparable basis for all DAC members. Data are collected on individual projects and programmes. Focus is on financial data but some descriptive information is also made available.
  • D
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 2023
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    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 दिसम्बर, 2023
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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.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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      The OECD Digital STRI identifies, catalogues and quantifies barriers that affect trade in digitally enabled services across 46 countries. It provides policy makers with an evidence-based tool that helps to identify regulatory bottlenecks, design policies that foster more competitive and diversified markets for digital trade, and analyze the impact of policy reforms. The OECD Digital STRI captures cross-cutting impediments that affect all types of services traded digitally. As a stand-alone instrument, it complements the OECD Services Trade Restrictiveness Index (STRI).   STRI indices take the value from 0 to 1. Complete openness to trade and investment gives a score of zero, while being completely closed to foreign services providers yields a score of one.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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      The OECD Digital STRI heterogeneity indices complement the recently published Digital STRI's and presents indices of regulatory heterogeneity based on the rich information in the Digital STRI regulatory database. The indices are built from assessing – for each country pair and each measure – whether or not the countries have the same regulation. For each country pair and each sector, the indices reflect the (weighted) share of measures for which the two countries have different regulation.
    • जुलाई 2015
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 2015
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      This table contains data on discouraged workers who are persons not in the labour force who believe that there is no work available due to various reasons and who desire to work. Data are broken down by sex and standardised age groups (15-24, 15-64, 25-54, 55-64, 65+, total).
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Ritesh Kumar
      Accessed On: 27 जुलाई, 2023
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      Graduates/new entrants in each educational field as a percentage of the sum of graduates/new entrants in all fields.
    • फरवरी 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 फरवरी, 2023
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      Distribution of net official development assistance (ODA) is defined as geographical aid allocations. Net ODA may be distributed by income group (least developed countries, other low-income countries, lower middle-income countries, upper middle-income countries, unallocated and more advanced developing countries and territories) or by geography (sub-Saharan Africa, South and Central Asia, other Asia and Oceania, Middle East and North Africa, Latin America and the Caribbean, Europe, and unspecified). The OECD Development Assistance Committee's "List of ODA Recipients" shows developing countries and territories eligible for ODA. The list is revised every three years. It is designed for statistical purposes, not as guidance for aid distribution or for other preferential treatment. In particular, geographical aid allocations are national policy decisions and responsibilities. This indicator is measured in million USD constant prices, using 2018 as the base year.
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 अगस्त, 2023
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      Distribution of teachers by gender and different age groups.
    • मार्च 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 अप्रैल, 2016
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      1. ccTLDs stands for country code top-level domains. 2. gTLDs - stands for generic top-level domains.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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      Tourism can be regarded as a social, cultural and economic phenomenon related to the movement of people outside their usual place of residence.
  • E
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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      Tables show earmarked grants classified into the 10 functions (or policy areas) for which they are disbursed. Functions are the same as used in the Classification of Functions of Government (COFOG) by the System of National Accounts. A 'miscellaneous' category has been added to these 10 functions to allow for situations where a precise breakdown by function is not available.
    • जनवरी 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 21 जुलाई, 2023
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      There has been a growing interest in monitoring patterns of trade in services around the world, which is partly associated with ongoing trade negotiations and partly due to the increasing importance of services in OECD economies. It has been developed to supplement other OECD publications on trade in services to address the data needs of trade analysts. It is also an important part of OECD's programme to facilitate the implementation of the recommendations of the revised Manual on Statistics of International Trade in Services 2010.Other commentsThe Task Force on Statistics of International Trade in Services maintains a matrix summarising the status of the trade in services data collection performed by International Organisations. The table displays links to the databases as well as update timetables, availability of metadata, availability of bilateral data, and other important characteristics.
    • जून 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 अक्तूबर, 2020
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      Latest Version is available here: https://knoema.com/OECDEO2020DEC/economic-outlook-no-108-december-2020   Economic Outlook No 107 (EO107) 2/2   Given the unusual level of uncertainty caused by the Covid-19 pandemic, this Economic Outlook (EO107) presents two scenarios for each country and economy – one scenario in which a second outbreak occurs in most economies towards the end of this year (double-hit scenario) and an alternative scenario where the second outbreak is avoided (single-hit scenario).Furthermore, only a limited number of series is made available compared to past editions.   This data set presents the double-hit scenario.   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 4 June 2020.   Concerning the aggregation of world trade, a new composition has been introduced, since projections are now made for the major non-OECD economies. Thus, besides OECD and the OECD euro area, the following new regions are available: Dynamic Asian Economies (Chinese Taipei, Hong Kong, Malaysia, the Philippines, Singapore, Thailand, Vietnam); Oil Producers (Azerbaijan, Kazakhstan, Turkmenistan, Brunei, Timor-Leste, Bahrain, Iran, Iraq, Kuwait, Libya, Oman, Qatar, Saudi Arabia, United Arab Emirates, Yemen, Ecuador, Trinidad and Tobago, Venezuela, Algeria, Angola, Chad, Rep. of Congo, Equatorial Guinea, Gabon, Nigeria, Sudan); with the remaining countries in a residual 'Rest of the World' group.
    • जून 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 04 जून, 2020
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      Latest version is available here: https://knoema.com/OECDEO2020DEC/economic-outlook-no-108-december-2020   Economic Outlook No 107 (EO107) 1/2   Given the unusual level of uncertainty caused by the Covid-19 pandemic, this Economic Outlook (EO107) presents two scenarios for each country and economy – one scenario in which a second outbreak occurs in most economies towards the end of this year (double-hit scenario) and an alternative scenario where the second outbreak is avoided (single-hit scenario).Furthermore, only a limited number of series is made available compared to past editions.   This data set presents the single-hit scenario.   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 4 June 2020.   Concerning the aggregation of world trade, a new composition has been introduced, since projections are now made for the major non-OECD economies. Thus, besides OECD and the OECD euro area, the following new regions are available: Dynamic Asian Economies (Chinese Taipei, Hong Kong, Malaysia, the Philippines, Singapore, Thailand, Vietnam); Oil Producers (Azerbaijan, Kazakhstan, Turkmenistan, Brunei, Timor-Leste, Bahrain, Iran, Iraq, Kuwait, Libya, Oman, Qatar, Saudi Arabia, United Arab Emirates, Yemen, Ecuador, Trinidad and Tobago, Venezuela, Algeria, Angola, Chad, Rep. of Congo, Equatorial Guinea, Gabon, Nigeria, Sudan); with the remaining countries in a residual 'Rest of the World' group.
    • अप्रैल 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 मई, 2024
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      The OECD Economic Outlook analyzes the major economic trends over the coming 2 years. It provides in-depth coverage of the main economic issues and the policy measures required to foster growth in each member country. Forthcoming developments in major non-OECD economies are also evaluated in detail. Each edition of the Outlook provides a unique resource to keep abreast of world economic developments. The OECD Economic Outlook database is a comprehensive and consistent macroeconomic database of the OECD economies, covering expenditures, foreign trade, output, labor markets, interest and exchange rates, balance of payments and government debt. For the non-OECD regions, foreign trade and current account series are available. 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, Labor Force Statistics and Main Economic Indicators. The cut-off date for information used in the compilation of the projections was June 1, 2023. The aggregation of world trade takes into account the projections made for the main non-OECD economies. Thus, besides OECD and the OECD euro area, the following regions are available: Dynamic Asian Economies (Chinese Taipei, Hong Kong, Malaysia, the Philippines, Singapore, Thailand, Vietnam); Oil Producers (Algeria, Angola, Azerbaijan Bahrain, Brunei, Chad, Rep. of Congo, Ecuador, Equatorial Guinea, Gabon, Iran, Iraq, Kazakhstan, Kuwait, Libya, Nigeria, Oman, Qatar, Saudi Arabia, Sudan, Timor-Leste , Trinidad and Tobago, Turkmenistan, United Arab Emirates, Yemen, Venezuela); with the remaining countries in a residual 'Rest of the World' group.
    • दिसम्बर 2009
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 अप्रैल, 2019
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      The OECD Economic Outlook analyses the major economic trends over the coming 2 to 3 years. It provides in-depth coverage of the main economic issues and the policy measures required to foster growth in each member country. Forthcoming developments in major non-OECD economies are also evaluated in detail. Each edition of this Outlook provides a unique tool to keep abreast of world economic developments. The OECD Economic Outlook database is a comprehensive and consistent macroeconomic database of the OECD economies, covering expenditures, foreign trade, output, labour markets, interest rates and exchange rates, the balance of payments, government and of households, and government debt. For the non-OECD regions, foreign trade and current account series are available. The database contains annual and quarterly data for the historical period and for the projection period. For this latter period, quarterly data are available for the G7 countries, and the OECD regions, while annual data are available for all OECD countries and for non-OECD regions. Quarterly series are seasonally adjusted. Variables are defined in such a way that they are as homogenous as possible over the countries. Breaks in underlying series are corrected as far as possible. Sources for the historical data are publications of national statistical agencies and OECD statistical publications such as the Quarterly National Accounts, the Annual National Accounts, the Annual Labour Force Statistics and the Main Economic Indicators.
    • अक्तूबर 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 अक्तूबर, 2020
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      The OECD Economic Outlook analyses the major economic trends over the coming 2 to 3 years. It provides in-depth coverage of the main economic issues and the policy measures required to foster growth in each member country. Forthcoming developments in major non-OECD economies are also evaluated in detail. Each edition of this Outlook provides a unique tool to keep abreast of world economic developments. The OECD Economic Outlook database is a comprehensive and consistent macroeconomic database of the OECD economies, covering expenditures, foreign trade, output, labour markets, interest rates and exchange rates, the balance of payments, government and of households, and government debt. For the non-OECD regions, foreign trade and current account series are available. The database contains annual and quarterly data for the historical period and for the projection period. For this latter period, quarterly data are available for the G7 countries, and the OECD regions, while annual data are available for all OECD countries and for non-OECD regions. Quarterly series are seasonally adjusted. Variables are defined in such a way that they are as homogenous as possible over the countries. Breaks in underlying series are corrected as far as possible. Sources for the historical data are publications of national statistical agencies and OECD statistical publications such as the Quarterly National Accounts, the Annual National Accounts, the Annual Labour Force Statistics and the Main Economic Indicators.
    • अक्तूबर 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 अक्तूबर, 2020
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      Current data with full Archive version is available here: https://knoema.com/OECDEO2020DEC/economic-outlook-no-108-december-2020  
    • अक्तूबर 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 अक्तूबर, 2020
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      Current data with full Archive version is available here: https://knoema.com/OECDEO2020DEC/economic-outlook-no-108-december-2020
    • अप्रैल 2021
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 अप्रैल, 2021
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       The OECD Economic Outlook analyses the major economic trends over the coming 2 to 3 years. It provides in-depth coverage of the main economic issues and the policy measures required to foster growth in each member country. Forthcoming developments in major non-OECD economies are also evaluated in detail. Each edition of the Outlook provides a unique resource to keep abreast of world economic developments. The OECD Economic Outlook database is a comprehensive and consistent macroeconomic database of the OECD economies, covering expenditures, foreign trade, output, labour markets, interest and exchange rates, balance of payments, and government debt. For the non-OECD regions, foreign trade and current account series are available. The database contains annual for the projection period. Variables are defined in such a way that they are as homogenous as possible for the countries covered. Breaks in underlying series are corrected as far as possible. Sources for the historical data are publications of national statistical agencies and OECD statistical publications such as the Quarterly National Accounts, the Annual National Accounts, the Labour Force Statistics and the Main Economic Indicators. The cut-off date for information used in the compilation of the projections was the 29 May 2015. Concerning the aggregation of world trade, a new composition has been introduced, since projections are now made for the major non-OECD economies. Thus, besides OECD and the OECD euro area, the following new regions are available: Dynamic Asian Economies (Chinese Taipei, Hong Kong, Malaysia, the Philippines, Singapore, Thailand, Vietnam); Oil Producers (Azerbaijan, Kazakhstan, Turkmenistan, Brunei, Timor-Leste, Bahrain, Iran, Iraq, Kuwait, Libya, Oman, Qatar, Saudi Arabia, United Arab Emirates, Yemen, Ecuador, Trinidad and Tobago, Venezuela, Algeria, Angola, Chad, Rep. of Congo, Equatorial Guinea, Gabon, Nigeria, Sudan); with the remaining countries in a residual 'Rest of the World' group.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2023
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    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 अक्तूबर, 2023
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      This table contains data on economic short-time workers by professional status (employees or total employment). Economic short-time workers comprise workers who are working less than usual due to business slack, plant stoppage, or technical reasons. However, the definitions are not harmonised which hampers the comparison across countries. Data are broken down professional status - employees, total employment - by sex and by standardised age groups (15-24, 25-54, 55+, total).
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 27 जुलाई, 2023
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      The OECD, in cooperation with the EU, has developed a harmonised definition of urban areas which overcomes previous limitations linked to administrative definitions (OECD, 2012). According to this definition an urban area is a functional economic unit characterised by densely inhabited “city core” and “commuting zone” whose labour market is highly integrated with the core. The Metropolitan database provides indicators of 649 OECD metropolitan areas identified in 33 OECD countries and the functional urban areas of Colombia. Comparable values of population, GDP, employment, and other indicators are presented.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 24 जुलाई, 2023
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      The data presented in this table are addressing one of the seven quality of life dimensions that have been identified within the framework of Education and Social Outcomes. The seven dimensions are: Health status, Work-life balance, Social connections, Civic engagement and governance, Environment, Personal safety and Subjective well-being.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 अक्तूबर, 2023
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      This dataset presents internationally comparable data on education and earnings, by educational attainment, age and gender as published in OECD Education at a Glance 2022. For trend data, Education at a Glance 2022 includes data for 2005 and 2010-2020 (or years with available data).
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 25 जुलाई, 2023
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      This indicator presents internationally comparable data regarding the labour force status and the educational attainment level by the National Educational Attainment Categories (NEAC) as reported by the labour force survey (LFS) and published in OECD Education at a Glance 2017. For trend data, the Education at a Glance Database includes data from 1981 to 2016 (or years with available data).
    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
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      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).
    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 12 अप्रैल, 2019
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      All entities that provide funds for education, either initially or as final payers, are classified as either governmental (public) sources or non-governmental (private) sources, the sole exception being "international agencies and other foreign sources", which are treated as a separate category. There are three types of financial transactions: Direct expenditure on educational institutions; Transfers to students or households and to other private entities; and Households' expenditure on education outside educational institutions.
    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 अप्रैल, 2019
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      These indicators on expenditure on education are published in chapter C of Education at a Glance, which covers financial and human resources invested in education.They are either policy levers or provide context information on education systems, or sometimes both. For example, expenditure per student is a key policy measure that most directly affects the individual learner, as it acts as a constraint on the learning environment in schools and learning conditions in the classroom.The data set “educational finance indicators” provides the main indicators computed for three levels of education : primary, secondary and post-secondary non-tertiary levels combined; tertiary level; and primary to tertiary levels combined. Other datasets provide more breakdowns for each specific indicator.
    • अक्तूबर 2020
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 28 अक्तूबर, 2020
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      The classification of personnel is based on functions and organises staff into four main functional categories: 1) Instructional Personnel; including two sub-groups: A. Classroom Teachers (ISCED 0-4) and Academic Staff (ISCED 5-6); and B. Teacher Aides (ISCED 0-4) and Teaching / Research Assistants (ISCED 5-6); 2) Professional Support for Students; including two sub-groups: A. Pedagogical Support (ISCED 0-4) and Academic Support (ISCED 5-6); B. Health and Social Support (ISCED 0-6); 3) Management/Quality Control/Administration; including four subgroups: A. School Level Management (ISCED 0-6); B. Higher Level Management (ISCED 0-6); C. School Level Administrative Personnel (ISCED 0-6); and D. Higher Level Administrative Personnel (ISCED 0-6); 4) Maintenance and Operations Personnel.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Ritesh Kumar
      Accessed On: 25 जुलाई, 2023
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      Average number of teachers by sex and age.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Ritesh Kumar
      Accessed On: 25 जुलाई, 2023
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      Average number of teachers by sex and type of institution.
    • अगस्त 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 अगस्त, 2020
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       This indicator measures the proportion of earnings that are lost to either higher taxes or lower benefit entitlements when a jobless person takes up employment. It is commonly referred to as "Participation Tax Rate (PTR)" as it measures financial disincentives to participate in the labour market.
    • अगस्त 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 अगस्त, 2020
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      Related data is available here: https://knoema.com/PTRCCSA/ptrs-for-parents-claiming-guaranteed-minimum-income-gmi-benefits-and-using-childcare-services This indicator measures the proportion of earnings that are lost to either higher taxes, lower benefits or childcare costs when a parent with young children takes up full-time employment and requires use of centre-based childcare services.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 नवम्बर, 2023
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    • जनवरी 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 अप्रैल, 2019
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    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 15 सितम्बर, 2023
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      The Pensions at a Glance indicators, covering all 34 OECD countries, are designed to show future entitlements for workers who entered the labour market in 2008 and spend their entire working lives under the same set of rules. The results presented here include all mandatory pension schemes for private-sector workers, regardless of whether they are public or private.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 01 नवम्बर, 2023
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      Compared to men, women are less likely to work full-time, more likely to be employed in lower-paid occupations, and less likely to progress in their careers. As a result gender pay gaps persist and women are more likely to end their lives in poverty. This data looks at how many men and women are in paid work, who works full-time, and how having children and growing older affect women’s work patterns and earnings differently to men’s. It looks at how women bear the brunt of domestic and family responsibilities, even when working full-time. It also considers the benefits for businesses of keeping skilled women in the workplace, and encouraging them to sit on company boards. It looks at women’s representation in parliaments, judicial systems, and the senior civil service. It examines male and female employment in the wake of the crisis, and how women tend to be confined to the most vulnerable categories within the informal sector in developing countries.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 21 नवम्बर, 2023
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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.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 सितम्बर, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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      This table contains a distribution of workers by job tenure intervals. Data are broken down by professional status - employees, self-employed, total employment – sex, five-year and broad age groups (15-24, 25-54, 55-64, 15-64, total, etc.). Job tenure is measured by the length of time workers have been in their current or main job or with their current employer. This information is valuable for estimating the degree of fluidity in the labour market and in identifying the areas of economic activity where the turnover of labour is rapid or otherwise. Data are so far reported for a number of European countries and will be expanded to cover a greater number of countries. Unit of measure used - Data are expressed years. Example: 1.5 = 1 year and 6 months.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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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 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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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.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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      This table contains data on permanent and temporary workers based on the type of work contract of their main job. Data are further broken down by professional status - employees, total employment - by sex and by standardised age groups (15-19, 15-24, 20-24, 25-54, 55-64, 65+, total). Unit of measure used - Data are expressed in thousands of persons.
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अगस्त, 2023
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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.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 21 नवम्बर, 2023
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    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 अप्रैल, 2019
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      Number of students by level of education, adjusted to the financial year. When financial year, school year and calendar year differs, adjustments are made to ease comparison.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 सितम्बर, 2023
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      Enrolment rate per age is the percentage of students enrolled in each type of institution over the total of students
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Ritesh Kumar
      Accessed On: 24 जुलाई, 2023
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      Number of students enrolled in different education programmes by age and sex.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Ritesh Kumar
      Accessed On: 27 जुलाई, 2023
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      Number of students enrolled in different education programmes by field and sex.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Ritesh Kumar
      Accessed On: 24 जुलाई, 2023
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      This indicator examines the share of students by gender, programme orientation, mode of study and type of institution over the total number of students.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Ritesh Kumar
      Accessed On: 24 जुलाई, 2023
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      Number of students enrolled in different education programmes by type of institution and sex.
    • मार्च 2021
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 15 मार्च, 2021
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      Number of students by level of education, adjusted to the financial year. When financial year, school year and calendar year differs, adjustments are made to ease comparison.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Ritesh Kumar
      Accessed On: 24 जुलाई, 2023
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      Number of students enrolled in different education programmes by country of origin and sex.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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    • अगस्त 2014
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 सितम्बर, 2014
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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      Entrepreneurship is crucial to economic development, promoting social integration and reducing inequalities. The Gender-entrepreneurship dataset presents an original collection of indicators that measure gender equality in entrepreneurship, providing an important reference for policy insights and policy making. Data refer mainly to the self-employed, their profile, age, education and sector of activity.
    • नवम्बर 2008
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
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      Dataset provides information on selected economic aspects of environmental management. It includes tables on expenditure, which help to identify the financial consequences of environmental policies: public and private pollution abatement and control expenditure; public research and development financing for environmental protection; official development assistance, including aid in support of environment. Dataset also includes data concerning revenues from environmentally-related taxes.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 नवम्बर, 2023
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    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 अगस्त, 2023
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      As countries are increasingly using a wide range of policy measures to address agri-environmental issues, indicators provide crucial information to monitor and analyse the effects of those policies on the environment. They can also help the understanding and analysis of the environmental effects of future policy scenarios and agricultural projections. To help improve measurement of the environmental performance of agriculture, OECD has established a set of agri-environmental indicators, with development of the indicators in cooperation with Eurostat and FAO. These indicators inform policy makers and society on the state and trends in agri-environmental conditions, and can provide a valuable aid to policy analysis.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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      The OECD Environmental Policy Stringency Index (EPS) is a country-specific and internationally-comparable measure of the stringency of environmental policy. Stringency is defined as the degree to which environmental policies put an explicit or implicit price on polluting or environmentally harmful behaviour. The index ranges from 0 (not stringent) to 6 (highest degree of stringency). The index covers 28 OECD and 6 BRIICS countries for the period 1990-2012. The index is based on the degree of stringency of 14 environmental policy instruments, primarily related to climate and air pollution.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2023
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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.
    • दिसम्बर 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 दिसम्बर, 2018
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      National currencies are converted in United States dollars (USD) using IMF monthly average conversion rates.
    • सितम्बर 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 नवम्बर, 2017
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    • अक्तूबर 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 अक्तूबर, 2020
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      Countries report expenditures by sources of funds: Governement (central, regional, local); International agencies and other foreign sources; Households and Other private entities (including firms and religious institutions and other non-profit organisations). Three types of financial transactions can be distinguished: -direct expenditure/payments on educational institutions -Intergovernmental transfers for education -Transfers to students or households and to other private entities.
    • मई 2021
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 04 मई, 2021
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      Air pollution is considered one of the most pressing environmental and health issues across OECD countries and beyond. According to the World Health Organisation (WHO), exposure to fine particulate matter (PM2.5) has potentially the most significant adverse effects on health compared to other pollutants. PM2.5 can be inhaled and cause serious health problems including both respiratory and cardiovascular disease, having its most severe effects on children and elderly people. Exposure to PM2.5 has been shown to considerably increase the risk of heart disease and stroke in particular. For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator. The underlying PM2.5 concentrations estimates are taken from van Donkelaar et al. (2016). They have been derived using satellite observations and a chemical transport model, calibrated to global ground-based measurements using Geographically Weighted Regression at 0.01° resolution. The underlying population data, Gridded Population of the World, version 4 (GPWv4) are taken from the Socioeconomic Data and Applications Center (SEDAC) at the NASA. The underlying boundary geometries are taken from the Global Administrative Unit Layers (GAUL) developed by the FAO, and the OECD Territorial Classification, when available. The current version of the database presents much more variation with respect to the previous one. The reason is that the underlying concentration estimates previously included smoothed multi-year averages and interpolations; while in the current version annual concentration estimates are used. Establishing trends of pollution exposure should be done with care, especially at smaller output areas, as their inputs (e.g. underlying data and models) can change from year to year. We recommend using a 3-year moving average for visualisation.
    • अक्तूबर 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 अक्तूबर, 2020
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      Air pollution is considered one of the most pressing environmental and health issues across OECD countries and beyond. According to the World Health Organisation (WHO), exposure to fine particulate matter (PM2.5) has potentially the most significant adverse effects on health compared to other pollutants. PM2.5 can be inhaled and cause serious health problems including both respiratory and cardiovascular disease, having its most severe effects on children and elderly people. Exposure to PM2.5 has been shown to considerably increase the risk of heart disease and stroke in particular. For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator. The underlying PM2.5 concentrations estimates are taken from van Donkelaar et al. (2016). They have been derived using satellite observations and a chemical transport model, calibrated to global ground-based measurements using Geographically Weighted Regression at 0.01° resolution. The underlying population data, Gridded Population of the World, version 4 (GPWv4) are taken from the Socioeconomic Data and Applications Center (SEDAC) at the NASA. The underlying boundary geometries are taken from the Global Administrative Unit Layers (GAUL) developed by the FAO, and the OECD Territorial Classification, when available. The current version of the database presents much more variation with respect to the previous one. The reason is that the underlying concentration estimates previously included smoothed multi-year averages and interpolations; while in the current version annual concentration estimates are used. Establishing trends of pollution exposure should be done with care, especially at smaller output areas, as their inputs (e.g. underlying data and models) can change from year to year. We recommend using a 3-year moving average for visualization.
  • F
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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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.
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 दिसम्बर, 2023
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    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 21 दिसम्बर, 2023
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    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 दिसम्बर, 2023
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    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 दिसम्बर, 2023
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    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 21 दिसम्बर, 2023
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    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 23 अगस्त, 2023
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      The FDI Regulatory Restrictiveness Index (FDI Index) measures statutory restrictions on foreign direct investment across 22 economic sectors. It gauges the restrictiveness of a country’s FDI rules by looking at the four main types of restrictions on FDI: 1) Foreign equity limitations; 2) Discriminatory screening or approval mechanisms; 3) Restrictions on the employment of foreigners as key personnel and 4) Other operational restrictions, e.g. restrictions on branching and on capital repatriation or on land ownership by foreign-owend enterprises. Restrictions are evaluated on a 0 (open) to 1 (closed) scale. The overall restrictiveness index is the average of sectoral scores. The discriminatory nature of measures, i.e. when they apply to foreign investors only, is the central criterion for scoring a measure. State ownership and state monopolies, to the extent they are not discriminatory towards foreigners, are not scored. The FDI Index is not a full measure of a country’s investment climate. A range of other factors come into play, including how FDI rules are implemented. Entry barriers can also arise for other reasons, including state ownership in key sectors. A country’s ability to attract FDI will be affected by others factors such as the size of its market, the extent of its integration with neighbours and even geography among other. Nonetheless, FDI rules can be a critical determinant of a country’s attractiveness to foreign investors.
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 21 दिसम्बर, 2023
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    • अक्तूबर 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 अक्तूबर, 2020
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      Chapter B includes indicators that are either policy levers or antecedents to policy, or sometimes both. For example, expenditure per student is a key policy measure that most directly affects the individual learner, as it acts as a constraint on the learning environment in schools and learning conditions in the classroom.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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      National Accounts - Volume IIIb - Financial Balance Sheets - Stocks, which record the stocks of financial assets and liabilities by institutional sectors, at the end of the accounting period, and are presented in two tables: Balance sheets for financial assets and liabilities, consolidated and Balance sheets for financial assets and liabilities, non consolidated.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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      Data are compiled either by Central banks, or Statistical National Institutes. EU data are validated and provided by the European Central Bank whereas non-EU data are provided by national institutions. The sectors for which information is presented are: Total economy (S1) - Non-financial corporations (S11) - Financial corporations (S12) and its sub-sectors (S121 to S125) - General government (S13) and its sub-sectors (1311 to S1314) - Households (S14) - Non-profit institutions serving households (S15) Rest of the world (S2)
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 28 नवम्बर, 2023
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      The financial indicators in this dataset are derived from OECD countries’ financial accounts (transactions): they give a picture of the short-term behavior of institutional sectors. They comprise for instance: Net financial transactions of the general government, as a percentage of Gross Domestic Product (GDP), which corresponds to the general government deficit; Transactions in financial assets of Households and NPISHs, as a percentage of Households Gross Disposable Income (GDI); Transactions in liabilities of Households and NPISHs, as a percentage of GDI.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 31 अक्तूबर, 2023
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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 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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      The Financial account, which is the second accumulation account, records financial flows: it indicates the types of financial instruments utilized by the different institutional sectors to acquire financial assets or incur liabilities. Data are compiled either by Central banks, or Statistical National Institutes. EU data are validated and provided by the European Central Bank whereas non-EU data are provided by national institutions.
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 दिसम्बर, 2023
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    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 18 अक्तूबर, 2023
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    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 अक्तूबर, 2023
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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).
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 अक्तूबर, 2023
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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 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 अक्तूबर, 2023
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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.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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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.
    • दिसम्बर 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 11 दिसम्बर, 2020
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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.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 नवम्बर, 2023
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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.
    • जुलाई 2014
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 अगस्त, 2017
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      The OECD food waste dataset is a compilation of available data related to food loss and food waste for 32 countries. The period covered may vary across different countries depending on data availability (globally ranging from 1993 to 2013). Several types of sources have been used: international organisations, government and national statistic institutes, OECD delegations, academic studies and private sector or>>/governmental analytical reports. When available, detailed information on sources is provided in the "variable def. and sources" (eg. references to an academic article or a government website).
    • अक्तूबर 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 अक्तूबर, 2020
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      The number of students enrolled refers to the count of students studying in the reference period. Each student enrolled in the education programmes covered by the corresponding category is counted once and only once. National data collection systems permitting, the statistics reflect the number of students enrolled at the beginning of the school / academic year. Preferably, the end (or near-end) of the first month of the school / academic year is chosen (special arrangements are made for part-year students who may not start studies at the beginning of the school year). Students are classified as foreign students (non-citizens) if they are not citizens of the country in which the data are collected. While pragmatic and operational, this classification is inappropriate for capturing student mobility because of differing national policies regarding the naturalisation of immigrants. Countries that have lower propensity to grant permanent residence to its immigrant populations are likely to report second generation immigrants as foreign students. Therefore, for student mobility and bilateral comparisons, interpretations of data based on the concept of foreign students should be made with caution. Students are classified as international students if they left their country of origin and moved to another country for the purpose of study. Depending on country-specific immigration legislation, mobility arrangements, and data availability, international students may be defined as students who are not permanent or usual residents of their country of study or alternatively as students who obtained their prior education in a different country, including another EU country.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 23 जनवरी, 2024
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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.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 01 नवम्बर, 2023
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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.
    • जून 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Raju Sangappa Rampur
      Accessed On: 29 जून, 2023
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      Date is taken as per country metadata, and which is not having any metadata date is considered as 2023
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 23 अगस्त, 2023
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      This table contains data on full-time and part-time employment based on a common definition of 30-usual weekly hours of work in the main job. Data are broken down by professional status - employees, total employment - sex and standardised age groups (15-24, 25-54, 55+, total). Unit of measure used - Data are expressed in thousands of persons.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 अक्तूबर, 2023
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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.
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 19 दिसम्बर, 2023
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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.
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 19 दिसम्बर, 2023
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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.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 अक्तूबर, 2023
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      The Future of Business Survey is an original source of information on small and medium-sized enterprises (SMEs). Launched in February 2016, the survey is a partnership between Facebook, OECD, and the World Bank. It provides timely information on business owners’ assessment of the current state and future outlook of their business, job creation perspectives, main business challenges and participation in international trade. Several data breakdowns are available, in particular by size of the enterprise, age, sector, trading status and gender of owners or managers.
  • G
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 सितम्बर, 2023
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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.
    • फरवरी 2021
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 01 अप्रैल, 2021
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      General government debt-to-GDP ratio is the amount of a country's total gross government debt as a percentage of its GDP. It is an indicator of an economy's health and a key factor for the sustainability of government finance. "Debt" is commonly defined as a specific subset of liabilities identified according to the types of financial instruments included or excluded. Debt is thus obtained as the sum of the following liability categories (as applicable): currency and deposits; securities other than shares, except financial derivatives; loans; insurance technical reserves; and other accounts payable. Changes in government debt over time reflect the impact of government deficits. This indicator is measured as a percentage of GDP. All OECD countries compile their data according to the 2008 System of National Accounts (SNA).
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 दिसम्बर, 2023
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      This part contains general information on number of insurance companies and employees within the sector.
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 18 अगस्त, 2023
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      This table contains deflators for resource flows for individual DAC Members from 1966 as well as the TOTAL DAC deflator, and the deflator for the EURO (EC). The deflators include the effect of exchange rate changes and are therefore only applicable to US dollar figures. The OECD uses the latest deflator to convert current prices to constant prices. The latest available base year used is the base year equal to 100. The OECD applies the total DAC deflator to individual recipient countries and multilateral donors to calculate their receipts or flows in constant prices.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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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.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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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.
    • फरवरी 2022
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 07 मार्च, 2022
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      This data set contains information of The insurance industry is a major component of the economy by virtue of the amount of premiums it collects, the scale of its investment and, more fundamentally, the essential social and economic role it plays by covering personal and business risks. This annual report monitors global insurance market trends to support a better understanding of the insurance industry's overall performance and health.The OECD has collected and analysed data on insurance such as the number of insurance companies and employees, insurance premiums and investments by insurance companies dating back to the early 1980s. Over time, the framework of this exercise has expanded and now includes key balance sheet and income statement items for the direct insurance and reinsurance sector.
    • फरवरी 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 फरवरी, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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      This data set combines the different regional publications of Revenue Statistics:Revenue Statistics 2019OECD/ATAF/AUC (2019), Revenue Statistics in Africa 2019OECD et al (2020), Revenue Statistics in Latin America and the Caribbean 2020 (LAC)Revenue Statistics in Asian and Pacific Economies 2019 Revenue Statistics The annual statistical publications present a unique set of detailed and internationally comparable tax revenue data in a common format. Its approach is based on the well-established methodology of the OECD Revenue Statistics (OECD, 2019), which has become an essential reference. It provides a conceptual framework defining which government receipts should be regarded as taxes and classifies different types of taxes. Comparable tables show revenue data by type of tax in national currency, as a percentage of GDP, and, for the different types of taxes, as a share of total taxation. Comparisons are also made with the averages of the 36 OECD economies, of the 24 LAC countries (two of which are OECD members countries° and of 26 African countries.   The data set does not replace the other publications, and users are advised to consult the regional data sets for country specific information.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 31 अगस्त, 2023
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      Going for Growth helps to promote sustainable economic growth and improve the well-being of OECD citizens. The surveillance is based on a systematic and in-depth analysis of structural policies and their outcomes across OECD members, relying on a set of internationally comparable and regularly updated policy indicators with a well-established link to performance. From one issue to the next, Going for Growth follows up on these recommendations and priorities evolve, not least as a result of governments taking action, http://www.oecd.org/eco/going-for-growth/. This dataset contains time series of a comprehensive set of quantitative indicators that allow for a comparison of policy settings across OECD countries and selected non-member economies: Argentina, Brazil, China, Colombia, Costa Rica, India, Indonesia, Lithuania, the Russian Federation and South Africa. The dataset covers several areas: Product market regulation (economy-wide and sector-specific regulation), Education, Public investment and subsidies, Taxation, Labour market, Transfers. Data are consistent with those published in the Structural Policy Indicators chapter of Going for Growth 2018. The cut-off date is December 2017.
    • जुलाई 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2024
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    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 2023
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    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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      This table presents data on Government appropriations or outlays for RD (GBAORD) by socio-economic objective (SEO), using the NABS 2007 classification i.e.: Exploration and exploitation of the Earth, Environment, Exploration and exploitation of space, Transport, telecommunication and other infrastructures, Energy, Industrial production and technology, Health, Agriculture, Education, Culture, recreation, religion and mass media, Political and social systems, structures and processes, General advancement of knowledge: RD financed from General University Funds (GUF), General advancement of knowledge: RD financed from sources other than GUF, Defence. Please note that in this new NABS 2007 classification, the three socio-economic objectives -- Education, Culture, recreation, religion and mass media, and Political and social systems, structures and processes -- were previously grouped under a single objective: Social structures and relationships. At the time of this publication there is no breakdown of historical data into the three new SEOs. Another issue relating to the transition from NABS 1993 to NABS 2007 is that what was formerly Other civil research is now to be distributed among the other chapters. This distribution has not yet been done in this database. Therefore, until the countries are in a position to provide breakdown according to the NABS 2007 classification, in some cases GBAORD by SEO is greater than the sum of its chapters.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 अक्तूबर, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Ritesh Kumar
      Accessed On: 24 जुलाई, 2023
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      Number of people who graduated from an education programme by age and sex.
    • फरवरी 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 18 मार्च, 2016
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      Graduates are those who successfully complete an educational programme during the reference year of the data collection. One condition of a successful completion is that students should have enrolled in, and successfully completed, the final year of the corresponding educational programme, although not necessarily in the year of reference. Students who do not complete the final year of an educational programme, but later successfully complete a recognised "equivalency" examination based on knowledge learned outside of the education system, should not be counted as graduates. Successful completion is defined according to the graduation requirements established by each country: in some countries, completion occurs as a result of passing a final, curriculum-based examination or series of examinations. In other countries, completion occurs after a specific number of teaching hours has been accumulated (although completion of some or all of the course hours may also involve examinations).
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Dinesh Kumar Gouducheruvu
      Accessed On: 27 जुलाई, 2023
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      Number of people who graduated from an education programme by field and sex.
    • अक्तूबर 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 अक्तूबर, 2020
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      Graduates are those who successfully complete an educational programme during the reference year of the data collection. One condition of a successful completion is that students should have enrolled in, and successfully completed, the final year of the corresponding educational programme, although not necessarily in the year of reference. Students who do not complete the final year of an educational programme, but later successfully complete a recognised "equivalency" examination based on knowledge learned outside of the education system, should not be counted as graduates. Successful completion is defined according to the graduation requirements established by each country: in some countries, completion occurs as a result of passing a final, curriculum-based examination or series of examinations. In other countries, completion occurs after a specific number of teaching hours has been accumulated (although completion of some or all of the course hours may also involve examinations).
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Ritesh Kumar
      Accessed On: 24 जुलाई, 2023
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      Graduation/entry rates represent an estimated percentage of an age group expected to graduate/enter a certain level of education at least once in their lifetime.
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 दिसम्बर, 2023
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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.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 16 अक्तूबर, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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      This table contains research and development (R&D) expenditure statistics on gross domestic R&D expenditure by sector of performance (business enterprise, government, higher education, private non-profit, and total intramural) and by field of science (natural sciences, engineering, medical sciences, agricultural sciences, social sciences, and humanities). Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2010 prices and PPPs).
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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      Data are provided in million national currency (for the euro zone, pre-EMU euro or EUR), million current PPP USD and million constant USD (2010 prices and PPPs). Variables collected This table presents research and development (R&D) expenditure statistics. Data include gross domestic R&D expenditure by sector of performance (business enterprise, government, higher education, private non-profit, and total intramural) and by type of costs (current expenditures: labour costs, other current costs; and capital expenditures: land and buildings, and instruments and equipment).
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 दिसम्बर, 2023
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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.
    • नवम्बर 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 नवम्बर, 2020
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      The Gross Replacement Rate (GRR) of unemployment benefits measure the amount of unemployment benefit received after 1, 2, …, T months of unemployment in proportion to the employment income earned before losing the job. All values are calculated before taxes and social security contribution payments. Calculations exclude family benefits, social assitance, housing benefits as well as in-work benefits. Because of these exclusions, the Net Replacement Rates in unemployment may provide a more complete measure of income maintenance than the GRR, especially when considering longer periods of unemployment and/or families with children.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 अक्तूबर, 2023
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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
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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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.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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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 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2024
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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 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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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.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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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 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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    • जून 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 जून, 2024
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      This dataset presents annual population data from 1950 to 2050 by sex and five year age groups as well as age-dependency ratios. The data is available for 46 countries. Data from 1950 to 2011 (2012) are historical data while data from 2012 (2013) are projections. In order to estimate the population in coming years, fertility rate, life expectancy and level of immigration have to be estimated. Assumptions underlying the estimations of each of these three elements are usually categorise as low, medium or high within one specific country. Where a range of projections are available, the projection data presented here are based on the "medium variant". Assumptions underlying the projection data shown are described country per country in the metadata table as well as the source of data. There are three sources for the data: national statistical institutes, Eurostat or the United Nations. The population data is presented in 18 five year age groups which refer to the population from 0-4 to 85 and more. The following age groups are also available: less than 15, less than 20, 15 to 64, 20-64, 65 and over. Age-dependency ratios are also presented. Assumptions by country. Data are presented for 46 countries. The 34 OECD member countries, the 6 EU countries not belonging to the OECD, and Brazil, Colombia, India, Indonesia, China, Russia and South Africa.
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 दिसम्बर, 2023
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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.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 नवम्बर, 2023
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      This indicator shows the working hours needed to escape poverty for a jobless family claiming Guaranteed Minimum Income benefits.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2023
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      Gross domestic product (GDP) is the standard measure of the value added created through the production of goods and services in a country during a certain period. Equivalently it measures the income earned from that production, or the total amount spent on final goods and services (less imports). While GDP is the single most important indicator to capture these economic activities, it falls short of providing a suitable measure of people's material well-being. There is however a wealth of information available within the System of National Accounts (SNA) to help determine households’ economic well-being in a more appropriate way.The indicators selected for the OECD Household Dashboard represent a macro perspective on households using data produced within the framework of the SNA, supplemented with indicators such as the unemployment rate and consumer confidence. Taken together this set of indicators highlights material well-being from the household perspective, and thus provides more detailed information than simply looking at economic growth.The Household Dashboard indicators are based on data compiled according to the 2008 SNA "System of National Accounts, 2008". For countries who are still in the process of finalising the 2008 SNA, the indicators are based on data compiled according to the 1993 SNA.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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      How’s Life? Well-being is the one-stop shop for the 80+ indicators of the OECD Well-being Dashboard, providing information on current well-being outcomes, well-being inequalities and the resources and risks that underpin future well-being. The 11 dimensions of current well-being relate to material conditions that shape people’s economic options (Income and Wealth, Housing, Work and Job Quality) and quality-of-life factors that encompass how well people are (and how well they feel they are), what they know and can do, and how healthy and safe their places of living are (Health, Knowledge and Skills, Environmental Quality, Subjective Well-being, Safety). Quality of life also encompasses how connected and engaged people are, and how and with whom they spend their time (Work-Life Balance, Social Connections, Civic Engagement). The distribution of current well-being is taken into account by looking at three types of inequality: gaps between population groups (horizontal inequalities); gaps between those at the top and those at the bottom of the achievement scale in each dimension (vertical inequalities); and deprivations (i.e. the share of the population falling below a given threshold of achievement). The systemic resources that underpin future well-being over time are expressed in terms of four types of capital: Economic, Natural, Human and Social.
    • जुलाई 2014
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 19 सितम्बर, 2014
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      Human Resource Costs
  • I
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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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.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 21 सितम्बर, 2023
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    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 15 दिसम्बर, 2023
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      The ICT Access and Usage by Households and Individuals database provides a selection of 92 indicators, based on the of 2nd revision of the OECD Model Survey on ICT Access and Usage by Households and Individuals.The selected indicators originate from two sources:1. An OECD data collection on the following OECD and accession countries or key partners: Australia, Brazil, Canada, Costa Rica, Chile, Colombia, Israel, Japan, Korea, Mexico, New Zealand, Switzerland, and the United States. Data collection methodology followed by these countries is available in each respective country metadata file.2. Eurostat Statistics on Households and Individuals for the OECD countries that are part of the European Statistical system. For those countries, indicators shown in this database refer to the original indicator as published by EUROSTAT -see the correspondence table-. Please refer to Eurostat methodology to access the methodological information.For all countries, breakdowns used correspond to those of EUROSTAT, unless otherwise stated in the metadata.
    • जनवरी 2008
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 सितम्बर, 2014
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      ICT goods are those that are either intended to fulfil the function of information processing and communication by electronic means, including transmission and display, OR which use electronic processing to detect, measure and/or record physical phenomena, or to control a physical process. ICT goods are defined by the OECD in terms of the Harmonised System. The guiding principle for the delineation of ICT goods is that such goods must either be intended to fulfil the function of information processing and communication by electronic means, including transmission and display, OR use electronic processing to detect, measure and/or record physical phenomena, or to control a physical process.Another guiding principle was to use existing classification systems in order to take advantage of existing data sets and therefore ensure the immediate use of the proposed standard. In this case, the underlying system is the Harmonized System (HS). The HS is the only commodity classification system used on a sufficiently wide basis to support international data comparison. A large number of countries use it to classify export and import of goods, and many countries use it (or a classification derived from or linked to it) to categorise domestic outputs.The application of the ICT product definition to selection of in-scope HS categories is a somewhat subjective exercise. The fact that the HS is not built on the basis of the functionality of products makes it much more difficult. The distinction between products which fulfil those functions and products that simply embody electronics but fundamentally fulfil other functions is not always obvious.It is possible to adopt a narrow or broad interpretation of the guideline, though the OECD chose a broader interpretation, an approach which is consistent with that adopted to develop the ICT sector definition.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 26 जुलाई, 2023
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      NOTE FOR THIS DATA CUBEFor all indicators provided in this cube, value are expressed as percentage of Internet users.For each country (except for Costa Rica -see below-), the value of the indicators provided in this cube are based on data from the ICT Access and Usage by Households and Individuals database, and metadata and sources are strictly identical.Internet users generally relate to a recall period of 3 months or 12 months as indicated below. For exceptions, see the country metadata in the ICT Access and Usage by Households and Individuals database.For Australia, 12 months before 2014, 3 months from 2014 onwards.For Canada, Colombia and Japan, 12 months.For Israel, Costa Rica and the United States, 3 months.For New Zealand, 12 months in 2006.For Chile, Korea, Mexico, New Zeland (2006 excepted), Switzerland and Brazil: 1. For indicators starting with D1, I3 and I9, Internet users relate to a recall period of 3 months; 2. For indicators starting with F1, Internet users relate to a recall period of 3 months untill 2007 and of 12 months from 2008 onwards; 3. For the remaining indicators, Internet users relate to a recall period of 12 months.For Costa Rica, data are OECD estimates based on data provided by the National Institute of Statistics and Censuses and by the Ministry of Science, Technology and Telecommunications (MICITT), and for all the indicators, Internet users relate to a recall period of 3 months.For the remaining countries (all from Eurostat): 1. For indicators starting with D1, Internet users relate to a recall period of 3 months; 2. For indicators starting with F1, Internet users relate to a recall period of 3 months untill 2007 and of 12 months from 2008 onwards; 3. For the remaining indicators, Internet users relate to a recall period of 12 months.
    • दिसम्बर 2018
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 03 दिसम्बर, 2018
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      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.
    • मार्च 2016
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 08 नवम्बर, 2017
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      The sources for this database are mainly census data, from the 2000 round of censuses. Census data were used for 22 countries. Countries not taking periodic censuses but keeping population registers have provided data extracted from these registers; this is the case for four countries: Denmark, Finland, Norway and Sweden. For some countries, not all themes covered in the database are present in the national census or register. Labour force surveys, provided by Eurostat and averaged over the period 1998-2002, have been used to fill the gaps where possible.
    • दिसम्बर 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 2018
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      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.
    • दिसम्बर 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 2018
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      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older with a tertiary education.
    • दिसम्बर 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 2018
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      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.
    • मार्च 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 नवम्बर, 2017
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      The sources for this database are mainly census data, from the 2000 round of censuses. Census data were used for 22 countries. Countries not taking periodic censuses but keeping population registers have provided data extracted from these registers; this is the case for four countries: Denmark, Finland, Norway and Sweden. For some countries, not all themes covered in the database are present in the national census or register. Labour force surveys, provided by Eurostat and averaged over the period 1998-2002, have been used to fill the gaps where possible.
    • दिसम्बर 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 2018
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      The sources for this database are mainly census data, from the 2000 round of censuses. Census data were used for 22 countries. Countries not taking periodic censuses but keeping population registers have provided data extracted from these registers; this is the case for four countries: Denmark, Finland, Norway and Sweden. For some countries, not all themes covered in the database are present in the national census or register. Labour force surveys, provided by Eurostat and averaged over the period 1998-2002, have been used to fill the gaps where possible. The exact national source and reference period for each file is given in Table A.1 (see the methodological document).
    • दिसम्बर 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 2018
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      This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 14 सितम्बर, 2023
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      This database presents the 2018 edition of OECD time-series indicators of implied R&D tax subsidy rates for OECD member countries and five non-member economies (Brazil, People's Republic of China, Romania, Russian Federation, and South Africa) over the period 2000-2018, drawing on data collected in the OECD-NESTI R&D tax incentive surveys from 2007 to 2018. The 2018 edition of RDTAXSUB contains time-series estimates that are based on headline tax credit and allowance rates, by firm size and profitability scenario. Due to limited historical data availability, the estimates are not adjusted for provisions that bound the tax benefits received by firms (e.g. ceilings, thresholds). They therefore provide an upper bound for the marginal tax subsidy implied by R&D tax relief measures across countries over time. These estimates should not be confused with separate contemporary cross-sectional OECD estimates of marginal tax subsidy rates (OECD, 2018) that compute adjusted (weighted) tax credit/allowance rates for a number of countries based on available information on the proportion of eligible R&D subject to different marginal levels of relief (see 2017).The tax subsidy rate is defined as 1 minus the B-index, a measure of the before-tax income needed by a “representative” firm to break even on USD 1 of R&D outlays (Warda, 2001). As tax component of the user cost of R&D, the B-Index is is directly linked to measures of effective marginal tax rates. Measures of tax subsidy rates such as those based on the B-index provide a convenient proxy for examining the implications of tax relief provisions. These provide a synthetic representation of the generosity of a tax system from the perspective of a generic or model type of firm for the marginal unit of R&D expenditure. To provide a more accurate representation of different scenarios, B-indices are calculated for “representative” firms according to whether they can claim tax benefits against their tax liability in the reporting period (OECD, 2013). When credits or allowances are fully refundable, the B-index of a firm in such a position is identical to the profit scenario. Carry-forwards are modelled as discounted options to claim incentives in the future, assuming a constant annual probability of returning to profit of 50% and a nominal discount rate of 10%. For general and country-specific notes on the time-series estimates of implied marginal tax subsidy rates on R&D expenditures (based on the B-index), see http://www.oecd.org/sti/rd-tax-stats-bindex-notes.pdf.
    • जुलाई 2014
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 04 अगस्त, 2014
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      The allocation of bilateral intermediate imports across using industries assumes that import coefficients are the same for all trade partners, i.e. SHAREipkt is identical across exporter countries. Hence, the bilateral pattern of imported intermediates from industry p is the same across all using industries k. However, it is different from the bilateral pattern of total imports from industry p because trade data (measured by VALUEijpt) allows distinguishing bilateral imports of intermediates from final good imports in industry p. While the BEC classification enables the identification of intermediate goods, no similar classification is available for trade in services, due to the high level of aggregation in services trade data. While goods trade data are based on customs declarations allowing the identification of goods at a highly disaggregated level, services trade data are based on a variety of information such as business accounts, administrative sources, surveys, and estimation techniques (Manual on Statistics of International Trade in Services, 2002). Hence, in the case of trade in services, VALUEijpt is the total value of imports of service p, i.e. both final and intermediate (and not only services that are used in the production of other goods and services, as in the case of goods data). By making an additional assumption and adjusting SHAREipkt, it is however possible to calculate trade in intermediate services. In the case of services imports, SHAREipkt is the share of imported service inputs p used by industry k in total imports of p of country i. In the case of services, besides the assumption that all trading partners have the same distribution of intermediate imports p across using industries k, it is furthermore required that the share of intermediate services in overall bilateral services imports of country i is the same across all partner countries j. Finally, it should be mentioned that trade data reported in the trade statistics do not fully match imports as reported in I-O tables. One main reason is that while trade data is recorded at consumer prices, I-O tables are evaluated at producer prices. There are also other differences such as the treatment of re-exports, scrap metal, waste products and second hand goods or unallocated trade data.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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      Tourism can be regarded as a social, cultural and economic phenomenon related to the movement of people outside their usual place of residence.
    • जुलाई 2015
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 2015
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      Note: Update to this data are available only to OECD subscribers. Please visit: https://stats.oecd.org/Index.aspx?DataSetCode=DW_I This table contains data on discouraged jobseekers as a percentage of the labour force and as a percentage of the population by sex and standardised age groups (15-24, 15-64, 25-54, 55-64, 65+, total). Unit of measure used - Data are expressed as percentages.
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 11 अगस्त, 2023
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      This table contains the shares of economic short-time workers among total employment, the ratio of economic short-time workers and labour force, and the gender composition of economic short-time workers. Data re broken down by professional status - employees, total employment – by sex and standardised age groups (15-24, 25-54, 55+, total). Unit of measure used - Data are expressed as percentages.
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 19 अगस्त, 2023
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      This table contains incidences and gender composition of part-time employment with standardised (15-24, 25-54, 55-64, 65+, total) and detailed age groups. Data are further broken down by professional status - employees, total employment. Part-time employment is based on a common 30-usual-hour cut-off in the main job. Unit of measure used - Data are expressed in percentages.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 27 जुलाई, 2023
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      This table contains incidences and gender composition of part-time employment with standardised (15-24, 25-54, 55-64, 65+, total) and detailed age groups. Data are further broken down by professional status - employees, total employment. Part-time employment is based on national definitions. The definition of part-time work varies considerably across OECD countries Essentially three main approaches can be distinguished: i) a classification based on the worker's perception of his/her employment situation; ii) a cut-off (generally 30 or 35 hours per week) based on usual working hours, with persons usually working fewer hours being considered part-timers; iii) a comparable cut-off based on actual hours worked during the reference week. A criterion based on actual hours will generally yield a part-time rate higher than one based on usual hours, particularly if there are temporary reductions in working time as a result of holidays, illness, short-timing, etc. On the other hand, it is not entirely clear whether a classification based on the worker's perception will necessarily yield estimates of part-time work that are higher or lower than one based on a fixed cut-off. In one country (France) which changed from 1981 to 1982 from a definition based on an actual hours cut-off (30 hours) to one based on the respondent's perception, the latter criterion appeared to produce slightly higher estimates. Other data characteristics
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 23 अगस्त, 2023
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      This datasetcontains the shares of involuntary part-time work among part-time workers and ratio of involuntary part-time work and labour force and the gender composition of involuntary part-time workers. Data are broken down by professional status - employees, total employment - sex and standardised age groups (15-24, 25-54, 55+, total).
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 2023
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    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 अगस्त, 2023
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      This table contains incidences and gender composition of temporary employment with standardized age groups (15-24, 25-54, 55-64, 65+, total). Data are further broken down by professional status - employees, total employment. Unit of measure used - Data are expressed in percentages.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 अक्तूबर, 2023
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      This table contains data on the share of the five durations - less than 1 month,>1 month and < 3 months,>3 months and <6 months,>6 months and <1 year, 1 year and over - of unemployment among total unemployment by sex and by standardised age groups (15-19, 15-24, 20-24, 25-54, 55+, total). Unit of measure used - Data expressed in percentages.
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 20 दिसम्बर, 2023
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      http://www.oecd.org/els/soc/IDD-Metadata.pdf
    • मई 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 06 मई, 2023
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      Bank profitability statistics are based on financial statements of banks in each Member country and are presented in the standard OECD framework. Although the objective is to include all institutions which conduct ordinary banking business, namely institutions which primarily take deposits from the public and provide finance for a wide range of purposes, the institutional coverage of banks in the statistics available in this database is not the same in each country. Ratios based on various items of the income statements and balance sheets of banks in percentage of some aggregates are also provided to facilitate the analysis of trends in bank profitability of OECD countries.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 17 अक्तूबर, 2023
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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.
    • नवम्बर 2021
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 24 दिसम्बर, 2021
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    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 19 सितम्बर, 2023
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      Institutional Investors' Assets and Liabilities data are reported by Central Banks, National Statistical Institutes or Supervisory Authorities. The indicators reported here are compiled on the basis of those statistics.   The first set of indicators measure total financial assets (liabilities) held by each institutional investor as a percentage of GDP. Total financial assets (liabilities) is defined as the sum of the following asset (liability) categories: currency and deposits (F2), debt securities (F3), loans (F4), equity and investment fund shares (F5), insurance pension and standardized guarantee schemes (F6), financial derivatives and employee stock options (F7), and other accounts receivable (payable) (F8). The second set of indicators shows the share of each asset (liability) category in the total financial assets (liabilities) of each investor. They help to analyse the investment portfolio composition of the investor as well as financial risks borne by the investor. The third set of indicators shows the sub-sector composition of total financial assets (liabilities) by investor category, by showing the share of each sub-sector in the total financial assets (liabilities) of each investor category.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 19 सितम्बर, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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      This dataset presents internationally comparable data on instruction time in full-time compulsory education. It covers primary and (lower and upper) secondary general education, but excludes pre-primary education, even if compulsory. Total number of instruction hours and the distribution of hours per subject is available either by level of education or by age.
    • मई 2019
      Source: Organisation for Economic Co-operation and Development
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      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.
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 दिसम्बर, 2023
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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.
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 दिसम्बर, 2023
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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).
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 22 दिसम्बर, 2023
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      This data deals with premiums written by classes of non-life insurance for the business written in the reporting country.
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 22 दिसम्बर, 2023
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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.
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 17 जनवरी, 2020
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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      Data on grants by type is not available for all OECD countries. A partial dataset is available for one or more years in the following countries: Austria, Belgium, Canada, Estonia, France, Greece, Iceland, Ireland, Italy, Netherlands, Poland, Portugal. No data on grants by type is available for Germany, Israel, New Zealand, Slovak Republic, United Kingdom, United States. The different types of grants are defined as follows: Earmarked grants An earmarked grant is a grant that is given under the condition that it can only be used for a specific purpose. Non-earmarked grants Non-earmarked grants can be spent as if they were the receiving sub-national government's own (non-earmarked) tax revenues. Mandatory grants Mandatory grants (entitlements) are legal, rules-based obligations for the government that issues the grant. This requires that both the size of the grant and the conditions under which it is given be laid down in a statute or executive decree and that these conditions be both necessary and sufficient. Discretionary grants Discretionary grants, and the conditions under which they are given, are not determined by rules but decided on an ad hoc, discretionary basis. Discretionary grants are often temporary in nature and include, for example, grants for specific infrastructural projects or emergency aid to a disaster area. Matching grants Matching grants are grants designed to complement sub-national contributions. Matching grants are dependent on normative or actual spending for services for which the grants are earmarked or on local revenue collection related to these services. Non-matching grants Non-matching grants are grants not directly linked to any sub-national contribution. Current grants Current grants are grants assumed to be spent on either current or capital expenditures. Capital grants Capital grants are grants assumed to be spent only on capital expenditures.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2023
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    • जून 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 सितम्बर, 2022
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      Patents are a key measure of innovation output, as patent indicators reflect the inventive performance of countries, regions, technologies, firms, etc. They are also used to track the level of diffusion of knowledge across technology areas, countries, sectors, firms, etc., and the level of internationalisation of innovative activities. Patent indicators can serve to measure the output of R&D, its productivity, structure and the development of a specific technology/industry. Among the few available indicators of technology output, patent indicators are probably the most frequently used. The relationship between patents as an intermediate output resulting from R&D inputs has been investigated extensively. Patents are often interpreted as an output indicator; however, they could also be viewed as an input indicator, as patents are used as a source of information by subsequent inventors. Like any other indicator, patent indicators have many advantages and disadvantages. The advantages of patent indicators are : patents have a close link to invention; patents cover a broad range of technologies on which there are sometimes few other sources of data; the contents of patent documents are a rich source of information (on the applicant, inventor, technology category, claims, etc.); and patent data are readily available from patent offices. However, patents are subject to certain drawbacks: the value distribution of patents is skewed as many patents have no industrial application (and hence are of little value to society) whereas a few are of substantial value; many inventions are not patented because they are not patentable or inventors may protect the inventions using other methods, such as secrecy, lead time, etc.; the propensity to patent differs across countries and industries; differences in patent regulations make it difficult to compare counts across countries; and changes in patent law over the years make it difficult to analyse trends over time.
    • जुलाई 2021
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 जुलाई, 2021
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      This dataset contains the number of people who graduated from an education programme by country of origin and sex.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 अक्तूबर, 2023
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      Unit of measure used: Thousands   OECD countries seldom have tools specifically designed to measure the inflows and outflows of the foreign population, and national estimates are generally based either on population registers or residence permit data. This note is aimed at describing more systematically what is measured by each of the sources used.   Flows derived from population registers   Population registers can usually produce inflow and outflow data for both nationals and foreigners. To register, foreigners may have to indicate possession of an appropriate residence and/or work permit valid for at least as long as the minimum registration period. Emigrants are usually identified by a stated intention to leave the country, although the period of (intended) absence is not always specified.   When population registers are used, departures tend to be less well recorded than arrivals. Indeed, the emigrant who plans to return to the host country in the future may be reluctant to inform about his departure to avoid losing rights related to the presence on the register. Registration criteria vary considerably across countries (as the minimum duration of stay for individuals to be defined as immigrants ranges from three months to one year), which poses major problems of international comparison. For example, in some countries, register data cover a portion of temporary migrants, in some cases including asylum seekers when they live in private households (as opposed to reception centres or hostels for immigrants) and international students.   Flows derived from residence and/or work permits   Statistics on permits are generally based on the number of permits issued during a given period and depend on the types of permits used. The so-called “settlement countries” (Australia, Canada, New Zealand and the United States) consider as immigrants persons who have been granted the right of permanent residence. Statistics on temporary immigrants are also published in this database for these countries since the legal duration of their residence is often similar to long-term migration (over a year). In the case of France, the permits covered are those valid for at least one year (excluding students). Data for Italy and Portugal include temporary migrants.   Another characteristic of permit data is that flows of nationals are not recorded. Some flows of foreigners may also not be recorded, either because the type of permit they hold is not tabulated in the statistics or because they are not required to have a permit (freedom of movement agreements). In addition, permit data do not necessarily reflect physical flows or actual lengths of stay since: i) permits may be issued overseas but individuals may decide not to use them, or delay their arrival; ii) permits may be issued to persons who have in fact been resident in the country for some time, the permit indicating a change of status, or a renewal of the same permit.   Permit data may be influenced by the processing capacity of government agencies. In some instances a large backlog of applications may build up and therefore the true demand for permits may only emerge once backlogs are cleared.   Flows estimated from specific surveys   Ireland provides estimates based on the results of Quarterly National Household Surveys and other sources such as permit data and asylum applications. These estimates are revised periodically on the basis of census data. Data for the United Kingdom are based on a survey of passengers entering or exiting the country by plane, train or boat (International Passenger Survey). One of the aims of this survey is to estimate the number and characteristics of migrants. The survey is based on a random sample of approximately one out of every 500 passengers. The figures were revised significantly following the latest census in each of these two countries, which seems to indicate that these estimates do not constitute an “ideal” source either. Australia and New Zealand also conduct passenger surveys which enable them to establish the length of stay on the basis of migrants’ stated intentions when they enter or exit the country.
    • जून 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Collins Omwaga
      Accessed On: 02 जून, 2023
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      This indicator reports the percentage of students of each country of origin over the total of international students.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 अक्तूबर, 2023
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      This dataset presents official international trade statistics in fisheries products, directly sourced from the UN Comtrade Database.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 31 जनवरी, 2024
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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.  
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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      The intra-EEA Services Trade Restrictiveness Index identifies and catalogues which policy measures restrict trade within the European Economic Area (EEA) for 25 OECD EU member countries. It complements the existing STRI, which quantifies multilateral services trade restrictiveness, allowing to track the progress of regional services integration across 19 major services sectors.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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      The intra-EEA Services Trade Restrictiveness Index identifies and catalogues which policy measures restrict trade within the European Economic Area (EEA) for 25 OECD EU member countries. It complements the existing STRI, which quantifies multilateral services trade restrictiveness, allowing to track the progress of regional services integration across 19 major services sectors.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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      This table contains data on involuntary part-time workers by professional status. Data are broken down by professional status - employees, total employment - by sex and standardised age groups (15-24, 25-54, 55+, total). Involuntary part-time workers are part-timers (working less than 30-usual hours per week) because they could not find a full-time job. However, the definitions are not harmonised which hampers the comparison across countries. Unit of measure used - Data are expressed in thousands of persons
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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      This table contains figures on the shares of industrial sectors that are "controlled" by affiliates under foreign control in each country (inward investment as a percentage of national total).
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 दिसम्बर, 2023
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      This table contains figures on the activity of affiliates under foreign control and all firms by industry according to the International Standard Industrial Classification (ISIC Revision 4).
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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      This table contains figures on the activity of affiliates under foreign control by industry according to the International Standard Industrial Classification (ISIC Revision 3).
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 दिसम्बर, 2023
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      This table contains figures on affiliates under foreign control by investing country in the total manufacturing, total services and total business enterprise sectors.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 07 सितम्बर, 2023
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      The units used to present data in AFA are millions of national currency for monetary variables and units for the other variables. Monetary variables are in current prices. Euro-area countries: national currency data is expressed in euro beginning with the year of entry into the Economic and Monetary Union (EMU). For years prior to the year of entry into EMU, data have been converted from the former national currency using the appropriate irrevocable conversion rate. This presentation facilitates comparisons within a country over time and ensures that the historical evolution is preserved. Please note, however, that pre-EMU euro are a notional unit and should not be used to form area aggregates or to carry out cross-country comparisons.
    • फरवरी 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 फरवरी, 2020
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    • जुलाई 2014
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 04 अगस्त, 2014
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      The IPP.Stat is the statistics portal of the Innovation Policy Platform containing the main available indicators relevant to a country’s innovation performance. In addition to the traditional indicators used to monitor innovation, the range of the coverage to be found in the IPP.Stat calls for the inclusion of indicators from other domains that describe the broader national and international context in which innovation occurs. Indicators are sourced primarily from the OECD and the World Bank, as well as from other sources of comparable quality. The statistics portal is still under development.
  • J
    • जुलाई 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 01 जुलाई, 2024
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      Job quality refers to multiple aspects of employment that contribute to well-being of workers and represents an inherently multi-dimensional construct. Job quality database focuses on three key dimensions. These are earnings quality, labour market security and quality of the working environment.
    • जुलाई 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 07 दिसम्बर, 2021
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      OECD calculation based on the survey of Adults Skills (PIAAC) (2012).Note : Jobs are at Risk of Automation if the likelihood of their job being automated is at-least 70%. Jobs at Risk of Significant change are those with the likelihood of their job being automated estimated at between 50% to 70%.Data for Belgium correspond to Flanders and data for the United Kingdom to England and North Ireland.
  • K
    • दिसम्बर 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 दिसम्बर, 2018
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      Benefit Generosity, Income Adequacy, Work Incentives.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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  • L
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 अगस्त, 2023
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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
    • अगस्त 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 जनवरी, 2018
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      Rivers Data show water quality of selected rivers. Water quality is measured in terms of annual mean concentrations of dissolved oxygen and BOD; of nitrates, phosphorus and ammonium; and of lead, cadmuim, chromium and copper. The rivers selected are main rivers draining large watersheds in the countries chosen; the measurement locations are at the mouths or downstream frontiers of the rivers. These parameters provide information concerning the state and trends of pollution by organic matter and nutrients, heavy metals and other metals. In reading the data, one should compare trends rather than absolute values, since measurement methods vary by country. Lakes Data show trends in annual mean concentrations of phosphorus and nitrogen in selected lakes. These parameters concern nutrient concentrations and related degrees of eutrophication of lakes and reservoirs. The interpretation of these tables should take into account variations in the methods of sampling (e.g. sampling location and number of measurements at different sampling locations and in different years).
    • मार्च 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 15 अप्रैल, 2019
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    • मार्च 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 अप्रैल, 2019
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    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 नवम्बर, 2023
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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.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 अक्तूबर, 2023
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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 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 अगस्त, 2023
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      This table contains data on labour force participation rates, employment/population ratios and unemployment rates for both the total labour force and civilian labour force by sex. There are data for both the total age group and the working age population (ages 15 to 64). This table also contains data on the share of civilian employment by sex.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2023
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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.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 मई, 2024
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      The OECD Long-Term Baseline is a projection of some major economic variables beyond the short-term horizon of the OECD Economic Outlook. It covers all OECD economies, non-OECD G20 economies and selected key partners. The projection horizon is currently 2060. For the historical period and the short-run projection horizon, the series are consistent with those of the OECD Economic Outlook number 114. The definitions, sources and methods are also generally the same. For more details on the methodology, please see boxes and Annex in Guillemette, Y. and J. Château (2023), 'Long-Term Scenarios: Incorporating the Energy Transition', OECD Economic Policy Papers, No. 33, OECD Publishing, Paris, and references therein. The baseline scenario is a projection conditional on a number of assumptions, notably that countries do not carry out institutional and policy reforms (see section 2 of the reference cited above). It is used as a reference point to illustrate the potential impact of structural reforms in alternative scenarios. The energy transition scenario is an alternative scenario with accelerated energy transition broadly consistent with net zero GHG emissions by 2050 (see section 3 of the reference cited above).
  • M
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 31 जनवरी, 2024
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      Main Economic Indicators (MEI) provides a wide range of indicators on recent economic developments in the 35 OECD member countries and 15 non-member countries. The indicators published in MEI have been prepared by national statistical agencies primarily to meet the requirements of users within their own country. In most instances, the indicators are compiled in accordance with international statistical guidelines and recommendations. However, national practices may depart from these guidelines, and these departures may impact on comparability between countries.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2023
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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.
    • जून 2021
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 28 जून, 2021
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      This dataset contains the number of Management personnel and teacher aides in educational institutions by sex and intensity.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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      IPAW = Income as a percentage of the average wage This data is updated after the finalisation of the Taxing Wages publication for the corresponding year. This table reports marginal personal income tax and social security contribution rates for a single person without dependent, at various multiples (67%, 100%, 133%, 167%) of the AW/APW. The average wage (AW) by country and year can be found within the Taxing Wages comparative tables dataset, under the indicator heading: Total gross earnings before taxes (national currency). The AW is based on a single person at 100% of average earnings, no child. The results, derived from the OECD Taxing Wages framework (elaborated in the annual publication Taxing Wages), use tax rates applicable to the tax year. The results take into account basic/standard income tax allowances and tax credits and include family cash transfers (see Taxing Wages). The marginal rates are expressed as a percentage of gross wage earnings, with the exception of the Total tax wedge which is expressed as a percentage of gross labour costs (gross wages + employer SSC). The sub-central personal tax rates used in this table correspond to those used in Taxing Wages. The figures may differ from those published in Taxing Wages where updated information is available, such as revised AW/APW data. Further explanatory notes may be found in the Explanatory Annex.
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 18 अगस्त, 2023
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    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 अक्तूबर, 2023
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      The Maritime Transport Costs (MTC)database contains data from 1991 to the most recent available year of bilateral maritime transport costs. Transport costs are available for 43 importing countries (including EU15 countries as a custom union) from 218 countries of origin at the detailed commodity (6 digit) level of the Harmonized System 1988. This dataset should only be used in conjunction with the paper Clarifying Trade Costs in Maritime Transport which outlines methodology, data coverage and caveats to its use. Key Statistical Concept Import charges represent the aggregate cost of all freight, insurance and other charges (excluding import duties) incurred in bringing the merchandise from alongside the carrier at the port of export and placing it alongside the carrier at the first port of entry in the importing country. Insurance charges are therefore included in the transport cost variables and are estimated to be approximately 1.5% of the import value of the merchandise.
    • मार्च 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 19 अप्रैल, 2024
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    • जनवरी 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 15 नवम्बर, 2021
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      This dataset presents members' total use of the multilateral system i.e. both their multilateral aid ("Core contributions to") and bilateral aid channelled through ("Contributions through") multilateral organisations. These data originate from members' reporting at item-level in the CRS and are published here starting with 2011 data (item-level data for multilateral aid is not complete in CRS for earlier years).
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 अगस्त, 2023
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      Despite the growing importance of international trade, driven in large part by the rise of globalisation and the accompanying international fragmentation of production, the availability of statistics on price change in international merchandise trade at more graular level is still limited. To fill this data gap, the OECD has developed this new Merchandise Trade Price Index (MTPI) database using UN COMTRADE. The first release covers about 100 countries from 2011 to 2017. Indices by reporting country are available for both exports and imports, broken down by 30 products, aligned with the 2-digit level of the Classification of Products of Activity (CPA, version 2.1). Future releases are planned to expand the country coverage and the level of disaggregation.
    • जुलाई 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 01 जुलाई, 2024
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      The aim of the OECD's new Skills for Jobs Indicators is to facilitate better adaptation to changing skill needs by making available a database of skill imbalances indicators that is comparable across countries and regularly updated. The Skill Needs Indicators provide an overview of the shortages and surpluses of skills across countries.
    • फरवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 फरवरी, 2024
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      This dataset contains monthly Comparative Price Levels (CPL) for OECD countries. CPLs are defined as the ratios of PPPs for private final consumption expenditure to exchange rates. They provide measures of differences in price levels between countries. The monthly PPPs used to derive the table are OECD estimates. The table is to be read vertically. Each column shows the number of specified monetary units needed in each of the countries listed to buy the same representative basket of consumer goods and services. In each case the representative basket costs a hundred units in the country whose currency is specified. Let’s take an example. If you are a Canadian citizen and you want to know the price level in Canada when compared to other countries, you have to look at the column Canada, where the price level is set at 100 for the whole column. If you have 120 for Finland, it means that the price level in Finland is 20% higher than in Canada. It means that you would spend 120 dollars in Finland to buy the same basket of goods and services when you spend 100 in Canada.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 जनवरी, 2024
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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.
    • फरवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 फरवरी, 2024
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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.
  • N
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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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.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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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.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 22 जनवरी, 2024
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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.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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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 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 07 सितम्बर, 2023
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    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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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.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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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.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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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.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 अक्तूबर, 2023
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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.
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 अगस्त, 2023
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    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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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.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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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.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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      Annual National Accounts>General Government Accounts>750. General Government Debt-Maastricht   Unit of measure used: National currency; current prices. Expressed in millions   Statistical population: Government debt as defined in the Maastricht Treaty (Source : Eurostat). Available for Europeans countries only. In the Protocol on the excessive deficit procedure annexed to the Maastricht Treaty, government debt is defined as the debt of the whole general government sector: gross, consolidated and nominal value (face value). It excludes the other accounts payable (AF.7), as well as, if they exist, insurance technical reserve (AF.6).
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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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).
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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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.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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      Annual National Accounts>Detailed Tables and Simplified Accounts>7A. Labour input by activity, ISIC rev4   Unit of measure used: In persons, full-time equivalents, jobs and hours.   Statistical population: It presents employment, broken down by detailed industries according to the classification ISIC rev.4. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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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.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 31 जनवरी, 2024
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2023
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      Annual National Accounts>Supply and Use Tables>30. Supply at basic prices and its transformation into purchasers' prices   Unit of measure used: In national currency, in current prices and previous year prices. Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.   Statistical population: It presents the Supply table at basic prices and its transformation into purchaser's prices. It provides information by industry (at the 2 digit ISIC Rev 4 level, containing 89 industries) with corresponding breakdowns by product (using the comparable CPA product breakdown). It has been prepared from statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 अक्तूबर, 2023
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      Annual National Accounts>Supply and Use Tables>SUT Indicators>SUT Indicators   Statistical population: These indicators are calculated by the OECD from the SUT statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.   Key statistical concept: The supply table describes the supply of goods and services, which are either produced in the domestic industry or imported. The use table shows where and how goods and services are used in the economy. Therefore in addition to their essential role to better estimations of National Accounts, Supply and Use tables are also a very powerful tool to understand the impact of policy decisions and globalisation, as they provide a detailed analysis of the process of production and the use of goods and services. For example, the Supply and Use Tables could be used to measure the the percentage of imports used in the production process or the share of trade and transport margins in the households’ final consumption expenditure.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 अक्तूबर, 2023
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      Annual National Accounts>Supply and Use Tables>31. Supply, Output and its components by industries   Unit of measure used: In national currency, in current prices and previous year prices. Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.   Statistical population: It presents the breakdown of output at basic prices between market output, output for own final use and non-market output, by activty at the 2 digit ISIC Rev 4 level. It has been prepared from statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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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.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 अक्तूबर, 2023
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      Annual National Accounts
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2023
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      Annual National Accounts>Supply and Use Tables>40. Use at purchasers' prices   Unit of measure used: In national currency, in current prices and previous year prices. Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.   Statistical population: It presents the Use table at purchaser's prices. It provides information by industry (at the 2 digit ISIC Rev 4 level, containing 89 industries) with corresponding breakdowns by product (using the comparable CPA product breakdown). It has been prepared from statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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      Annual National Accounts
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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      Annual National Accounts
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 अक्तूबर, 2023
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      Annual National Accounts>Supply and Use Tables>44. Valuation Matrices   Unit of measure used: In national currency, in current prices and previous year prices. Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.   Statistical population: It presents the tables of trade and transport margins, of taxes less subsidies on products. It provides information by industry (at the 2 digit ISIC Rev 4 level, containing 89 industries) with corresponding breakdowns by product (using the comparable CPA product breakdown). It has been prepared from statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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      Statistical population: Its presents output, intermediate consumption and the gross value added and its components, in particular compensation of employees and gross operating surplus and mixed income, broken down by detailed industries according to the classification ISIC rev.4. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. Unit of measure used: In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2010). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.   Note: 6A. Value added and its components by activity, ISIC rev4
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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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.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Ritesh Kumar
      Accessed On: 26 जुलाई, 2023
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      This indicator measures the net costs paid by parents for full-time centre-based childcare, after any benefits designed to reduce the gross childcare fees. Childcare benefits can be received in the form of childcare allowances, tax concessions, fee rebates and increases in other benefit entitlements.
    • फरवरी 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 01 फरवरी, 2023
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      Official development assistance (ODA) is defined as government aid designed to promote the economic development and welfare of developing countries. Loans and credits for military purposes are excluded. Aid may be provided bilaterally, from donor to recipient, or channelled through a multilateral development agency such as the United Nations or the World Bank. Aid includes grants, "soft" loans and the provision of technical assistance. The OECD maintains a list of developing countries and territories; only aid to these countries counts as ODA. The list is periodically updated and currently contains over 150 countries or territories. 
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Saikrishna Valluparambath
      Accessed On: 10 नवम्बर, 2023
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      Net Replacement Rates in unemployment measure the proportion of income that is maintained after 1, 2, …, T months of unemployment.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Ritesh Kumar
      Accessed On: 27 जुलाई, 2023
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      Number of new entrants in a given programme by age and sex.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Ritesh Kumar
      Accessed On: 27 जुलाई, 2023
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      Number of new entrants in a given programme by field and sex.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 अक्तूबर, 2023
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      The breakdown of transactions and positions by counterpart sector enriches the information as included in the financial accounts and balance sheets by providing insight into the relationships between institutional sectors within an economy as well as between residents and non-residents. For a given financial instrument it is possible to trace the creditor-debtor relations between institutional sectors and with the rest of the world.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 अक्तूबर, 2023
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      The breakdown of transactions and positions by counterpart sector enriches the information as included in the financial accounts and balance sheets by providing insight into the relationships between institutional sectors within an economy as well as between residents and non-residents. For a given financial instrument it is possible to trace the creditor-debtor relations between institutional sectors and with the rest of the world.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 अक्तूबर, 2023
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      The dataset on Quarterly Sector Accounts data presents the whole set of non financial accounts for the institutional sectors.It includes the following accounts: - Production account / External account of goods and services - Generation of income account - Allocation of primary income account - Secondary distribution of income account - Use of disposable income account - Change in net worth due to saving and capital transfers accounts - Acquisitions of non-financial assets account - Balance sheets for non-financial assets - Employment by sector These accounts are designed to produce accounting balances that are of particular interest for economic analysis such as value added, operating surplus, saving or net lending/net borrowing. Quarterly Sector Accounts data have been reported to the OECD by Member countries and Key Partner countries using a standard questionnaire (simplified table T0119 or detailed table T0801). These questionnaires are designed to collect internationally comparable data according to definitions and concepts presented in the System of National Accounts (SNA 2008 or SNA 1993 for a few countries):
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 31 अगस्त, 2023
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      The indicator reports the nutrient balance of nitrogen and phosphorus – the difference between the quantity of nutrient inputs entering an agricultural system and the quantity of nutrient outputs leaving this system – for exports of nine cereal and oilseed (hence excluding pasture) as a share of the total nutrient balance for 21 countries in years 2006, 2007, 2010 and 2014. Grains covered by this indicator are wheat, maize, barley, sorghum, oats, rice soybeans, sunflower seed and rapeseed.
  • O
    • मार्च 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 अप्रैल, 2016
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    • जुलाई 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2024
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    • नवम्बर 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Ngendo Ngwiri Christine
      Accessed On: 18 सितम्बर, 2022
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      The OECD Digital Economy Outlook 2020 examines trends and analyses 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 third edition of the OECD Digital Economy Outlook provides a holistic overview of converging trends, policy developments and data on both the supply and demand sides of the digital economy. It illustrates how the digital transformation is affecting economies and societies. Finally, it provides a special focus on how the COVID-19 pandemic is amplifying opportunities and challenges from the digital transformation.
    • फरवरी 2012
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
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      The data presented here refer to the latest year available, which corresponds to the late 2000s for most countries. The data on the state of threatened species build on country replies to the Annual Quality Assurance (AQA) of OECD environmental reference series. These data are harmonised through the work of the OECD Working Party on Environmental Information (WPEI). Some where updated or revised on the basis of comments from national Delegates and in the framework of the OECD Environmental Performance Reviews. When interpreting these data, it should be borne in mind that the number of species known does not always accurately reflect the number of species in extistence and that varying definitions can limit comparability accross countries. The data presented here show numbers of known species and threatened species with the aim of indicating the state of mammals, birds, freshwater fish, reptiles, amphibians and vascular plants.
    • अगस्त 2014
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 07 अगस्त, 2014
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      As countries are increasingly using a wide range of policy measures to address agri-environmental issues, indicators provide crucial information to monitor and analyse the effects of those policies on the environment. They can also help the understanding and analysis of the environmental effects of future policy scenarios and agricultural projections. To help improve measurement of the environmental performance of agriculture, OECD has established a set of agri-environmental indicators, with development of the indicators in cooperation with Eurostat and FAO. These indicators inform policy makers and society on the state and trends in agri-environmental conditions, and can provide a valuable aid to policy analysis.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 अक्तूबर, 2023
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      In this version, seven GVCs indicators are presented for 59 economies (34 OECD and 23 non-OECD economies, plus the "rest of the world" and the European Union) for 18 industries in the years 1995, 2000, 2005, 2008 and 2009. The indicators are calculated based on the five global input-output matrices of the TiVA database. More details on the aggregation and specific country notes can be downloaded at http://www.oecd.org/sti/ind/input-outputtables.htm and http://oe.cd/gvc/.
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 18 अगस्त, 2023
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      This OECD inventory maps existing cross-country surveys that provide information on the characteristics of people's jobs. The information included in this inventory covers international surveys conducted since the early 1990s that are based on individuals' self-reported assessment of their current job, for 160 countries over 25 years. Survey questions are grouped into 19 indicators. For each indicator, binary codes (1 and 0) show whether indicators are available or not for the various countries and years. The inventory also provides users with detailed documentation on the questions used in the various surveys for measuring these indicators.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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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.
    • जुलाई 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जुलाई, 2024
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      The OECD Weekly Tracker of GDP growth provides a real-time high-frequency indicator of economic activity using machine learning and Google Trends data. It has a wide country coverage of OECD and G20 countries. The Tracker is thus particularly well suited to assessing activity during the turbulent period of the current global pandemic. It applies a machine learning model to a panel of Google Trends data for 46 countries, and aggregates together information about search behaviour related to consumption, labour markets, housing, trade, industrial activity and economic uncertainty.   The Weekly Tracker proxies the percent change in weekly GDP levels from the pre-crisis trend. The pre-crisis trend is taken from OECD forecasts made prior to the crisis (in the November 2019 Economic Outlook). Two other flavours of the Tracker are also available in the datafiles: a Tracker of weekly GDP growth year-on-year (that is, the percent change in weekly GDP from the same week in the past year), and a Tracker of weekly GDP growth year-on-two-year (the percent change in weekly GDP from the same week two years earlier). 
    • मई 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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      This table contains statistics on research and development (R&D) expenditure performed in the higher education and private non-profit sectors by field of science (natural sciences, engineering, medical sciences, agricultural sciences, social sciences, and humanities) and type of costs (current expenditures, capital expenditures).
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 अक्तूबर, 2023
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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 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 नवम्बर, 2023
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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.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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      This table contains figures on the activity of affiliates located abroad by host country in the total manufacturing sector or in the total business sector. The units used to present data in AFA are millions of national currency for monetary variables and units for the other variables. Monetary variables are in current prices. Euro-area countries: national currency data is expressed in euro beginning with the year of entry into the Economic and Monetary Union (EMU). For years prior to the year of entry into EMU, data have been converted from the former national currency using the appropriate irrevocable conversion rate. This presentation facilitates comparisons within a country over time and ensures that the historical evolution is preserved. Please note, however, that pre-EMU euro are a notional unit and should not be used to form area aggregates or to carry out cross-country comparisons.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 नवम्बर, 2023
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      This table contains figures on the activity affiliates located abroad by industry according to the International Standard Industrial Classification (ISIC Revision 4). The units used to present data in AMNE are millions of national currency for monetary variables and units for the other variables. Monetary variables are in current prices. Euro-area countries: national currency data is expressed in euro beginning with the year of entry into the Economic and Monetary Union (EMU). For years prior to the year of entry into EMU, data have been converted from the former national currency using the appropriate irrevocable conversion rate. This presentation facilitates comparisons within a country over time and ensures that the historical evolution is preserved. Please note, however, that pre-EMU euro are a notional unit and should not be used to form area aggregates or to carry out cross-country comparisons.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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      The units used to present data in AFA are millions of national currency for monetary variables and units for the other variables. Monetary variables are in current prices. Euro-area countries: national currency data is expressed in euro beginning with the year of entry into the Economic and Monetary Union (EMU). For years prior to the year of entry into EMU, data have been converted from the former national currency using the appropriate irrevocable conversion rate. This presentation facilitates comparisons within a country over time and ensures that the historical evolution is preserved. Please note, however, that pre-EMU euro are a notional unit and should not be used to form area aggregates or to carry out cross-country comparisons.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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  • P
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 01 नवम्बर, 2023
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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).
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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      The OECD Environment Directorate, in collaboration with the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in environment-related technologies. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' environmental and innovation policies. The patent statistics presented here are constructed using data extracted from the Worldwide Patent Statistical Database (PATSTAT) of the European Patent Office (EPO) using algorithms developed by the OECD. Consistent with other patent statistics provided in OECD.Stat, only published applications for "patents of invention" are considered (i.e. excluding utility models, petty patents, etc.). The relevant patent documents are identified using search strategies for environment-related technologies (ENV-TECH) which were developed specifically for this purpose. They allow identifying technologies relevant to environmental management, water-related adaptation and climate change mitigation. An aggregate category labelled "selected environment-related technologies" includes all of the environmental domains presented here.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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      The OECD Environment Directorate, in collaboration with the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in environment-related technologies. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' environmental and innovation policies. The patent statistics presented here are constructed using data extracted from the Worldwide Patent Statistical Database (PATSTAT) of the European Patent Office (EPO) using algorithms developed by the OECD. Consistent with other patent statistics provided in OECD.Stat, only published applications for "patents of invention" are considered (i.e. excluding utility models, petty patents, etc.). The relevant patent documents are identified using search strategies for environment-related technologies (ENV-TECH) which were developed specifically for this purpose. They allow identifying technologies relevant to environmental management, water-related adaptation and climate change mitigation. An aggregate category labelled "selected environment-related technologies" includes all of the environmental domains presented here.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 अक्तूबर, 2023
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      Patents are a key measure of innovation output, as patent indicators reflect the inventive performance of countries, regions, technologies, firms, etc. They are also used to track the level of diffusion of knowledge across technology areas, countries, sectors, firms, etc., and the level of internationalisation of innovative activities. Patent indicators can serve to measure the output of R&D, its productivity, structure and the development of a specific technology/industry. The relationship between patents as an intermediate output resulting from R&D inputs has been investigated extensively. Patents are often interpreted as an output indicator; however, they could also be viewed as an input indicator, as patents are used as a source of information by subsequent inventors. Like any other indicator, patent indicators have many advantages and disadvantages. The advantages of patent indicators are :patents have a close link to invention;patents cover a broad range of technologies on which there are sometimes few other sources of data;the contents of patent documents are a rich source of information (on the applicant, inventor, technology category, claims, etc.); andpatent data are readily available from patent offices. However, patents are subject to certain drawbacks:the value distribution of patents is skewed as many patents have no industrial application (and hence are of little value to society) whereas a few are of substantial value;many inventions are not patented because they are not patentable or inventors may protect the inventions using other methods, such as secrecy, lead time, etc.;the propensity to patent differs across countries and industries;differences in patent regulations make it difficult to compare counts across countries; andchanges in patent law over the years make it difficult to analyse trends over time. 
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Dinesh Kumar Gouducheruvu
      Accessed On: 14 सितम्बर, 2023
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    • अप्रैल 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 अप्रैल, 2024
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      The OECD Pensions at a Glance Database has been developed in order to serve a growing need for pensions indicators. It includes reliable and internationally comparable statistics on public and mandatory and voluntary pensions. It covers 34 OECD countries and aims to cover all G20 countries. Pensions at a Glance reviews and analyses the pension measures enacted or legislated in OECD countries. It provides an in-depth review of the first layer of protection of the elderly, first-tier pensions across countries and provideds a comprehensive selection of pension policy indicators for all OECD and G20 countries.
    • मार्च 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 अप्रैल, 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/."    
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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      This dataset contains the number of people by sex and age group per country.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 07 सितम्बर, 2023
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      Country weights used for calculation of Consumer Prices and Producer Prices OECD zones
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 अक्तूबर, 2023
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      Private transactions are those undertaken by firms and individuals resident in the reporting country.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 सितम्बर, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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      DUE TO CHANGES IN THE METHODOLOGY THE 2018 PMR VALUES CANNOT BE COMPARED WITH PREVIOUS VINTAGES. The 2018 OECD Indicators of Product Market Regulation (PMR) are a comprehensive and internationally-comparable set of indicators that measure the degree to which laws and policies promote or inhibit competition in areas of the product and service market where competition is viable. These indicators measure the de iure regulatory environments in 34 OECD countries and in a set of non-OECD countries in 2018. The economy-wide indicators cover the extent to which the involvement of the state in the economy can generate distortions to competition and the level of the barriers to entry and expansion to domestic and foreign firms in different sectors of the economy. Users of the data must be aware that they may no longer fully reflect the current situation in fast reforming countries.
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 जनवरी, 2024
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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.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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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.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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      The OECD cross-section sectoral indicators measure regulatory conditions in the professional services and retail distribution sectors. The professional services indicators cover entry and conduct regulation in the legal, accounting, engineering, and architectural professions. They are now estimated for the years 1996, 2003, around 2008 and 2013 for 34 OECD countries and for another set of non-OECD countries for 2013. Users of the data must be aware that they may no longer fully reflect the current situation in fast reforming countries. Not all data are available for all countries for all years.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Ritesh Kumar
      Accessed On: 20 जुलाई, 2023
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      Distribution of graduates/new entrants by gender, country of origin and age as well as the proportion of each tertiary educational level over the total of first-time graduates and new entrants at tertiary level.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 नवम्बर, 2023
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      This indicator measures the financial disincentives to participate in the labour market. It shows the proportion of earnings in the new job that are lost to either higher taxes or lower benefit entitlements when a jobless person takes up employment and their family claims social assistance and/or Guaranteed Minimum Income (GMI) benefits. Higher values means higher financial disincentives.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 नवम्बर, 2023
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      This indicator measures the financial disincentives to participate in the labour market. It calculates the proportion of earnings in the new job that are lost to either higher taxes or lower benefit entitlements when a jobless person takes up employment and claims unemployment benefits. Higher values means higher financial disincentives.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 अक्तूबर, 2023
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      This indicator measures the financial disincentives to participate in the labour market for a jobseeker claiming unemployment benefits. It calculates the proportion of earnings that are lost to either higher taxes, lower benefits and net childcare costs when a parent with young children takes up full-time employment and uses full-time centre-based childcare. This indicators is calculated assuming that the jobseeker claims unemployment insurance and/or unemployment assistance benefits when s/he is out of work.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2023
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      This indicator measures the financial disincentives to participate in the labour market. It calculates the proportion of earnings that are lost to either higher taxes, lower benefits and net childcare costs when a parent with young children takes up full-time employment and uses full-time centre-based childcare. This indicators is calculated assuming that the family claims social assitance and/or Guaranteed Minimum Income (GMI) benefits but not unemployment benefits.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 सितम्बर, 2023
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      The OECD has collected data for public expenditure on labour market programmes (LMPs) continuously since the mid-1980s. For most longstanding Member countries, data according to a consistent classification system and definition of scope are available for reference years 1985 to 2002. Starting with reference year 1998, Eurostat started collecting and publishing data according to a somewhat different classification system and definition of scope. In line with agreements for bilateral coordination of data collection, the OECD after some time adopted - for non-Eurostat OECD Member countries as well as Eurostat countries – most of the features of the Eurostat system. This allows the OECD to use data collected by Eurostat rather than making a separate data request to the 20 Eurostat countries that are members of the OECD. OECD data according to the "new" classification and definition of scope are generally available for reference year 2002 onwards, or 1998 onwards for Eurostat countries. These data are often used in time-series applications, e.g. for documenting long-term trends in total social expenditure (ìn which labour market programmes are one component), or in time-series regressions that attempt to estimate the impact of training programmes vs. job-creation programmes on unemployment. It is no longer practicable to do such work using only the "old" data which stop in 2002 or the "new" data which start in 2002 or 1998. If the two data sets are combined using crude extrapolation and splicing techniques, time-series movements will result primarily from statistical breaks (i.e. changes in definition and coverage of the statistics) rather than real changes in spending patterns. The unit of measure used depends on the members in dimension 'Country', 'Measure'
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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      These splits make it possible to characterize the structure of public finances in OECD countries according to the different types of welfare state. This, in turn, makes it possible for countries to compare themselves with other relevant member countries and may stimulate the national policy debate about questions such as decentralization, redistribution, privatization, the role of the non?profit sector and the application of user fees. Recommended uses and limitations The methodology applied to make the required splits has been developed since 2004 and has gradually become more accurate. The most recent methodology, used in the PFED of 2009, makes use of second level COFOG data and has been applied in a test procedure on five European countries (of which three are OECD countries) that have provided second level COFOG data to Eurostat. In the course of 2007 and 2008, more countries made available second level COFOG data to Eurostat.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2023
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      OECD National Account Statistics are based on the System of National of Accounts (SNA), a set of internationally agreed concepts, definitions, classifications and rules for national accounting. Using SNA terminology, general government revenue consists of central, state and local governments, and social security funds. State government is only applicable to the nine OECD member countries that are federal states: Australia, Austria, Belgium, Canada, Germany, Mexico, Spain (considered a de facto federal state in the National Accounts data), Switzerland and the United States. Revenues encompass social contributions (e.g. contributions for pensions, health and social security), taxes other than social contributions (e.g. taxes on consumption, income, wealth, property and capital), and grants and other revenues. Grants can be from foreign governments, international organizations or other general government units. Other revenues include sales, fees, property income and subsidies. The aggregates presented (taxes other than social contributions, social contributions, and grants and other revenues) are not directly available in the OECD National Accounts, and were constructed using sub-account line items.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2023
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      The magnitude of government debt, and public sector debt likewise, depends on the coverage of instruments used and available data. To accommodate a fair international comparison of related indicators, the IMF, the OECD and the World Bank have agreed to define various debt measures depending on the coverage or non-coverage of instruments: D1 to D4. The D1-D4 presentation classifies gross government debt and public sector debt into four separate categories, as defined in the 2012 IMF Staff Discussion Note: “What Lies Beneath: The Statistical Definition of Public Sector Debt”. This coverage of instruments according to this classification ranges from a narrow definition including only debt securities and loans (D1) to a fully comprehensive definition covering all six debt instruments (D4), as defined in the Public Sector Debt Statistics Guide for User and Compilers, and the Government Finance Statistics Manual 2014. For more information, please see the document:
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जनवरी, 2024
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      The Public Sector Debt database includes quarterly detailed information on all liabilities which constitute debt instruments, by initial and residual maturity, which are held by the government, and more broadly the public sector. The debt instruments are those instruments that require the payment of principal and interest or both at some point(s) in the future. All liabilities are considered debt, except liabilities in the form of equity and investment fund shares and, financial derivatives and employee stock options.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 अक्तूबर, 2023
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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
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 19 अगस्त, 2023
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      OECD has extracted monthly trade data from the UN Monthly Comtrade database, and aggregates the quarterly and annual frequencies by summing up the months. This may create discrepancies with annual trade figures as presented in International Trade by Commodity Statistics (ITCS). UN Monthly Comtrade (beta version) contains detailed merchandise trade data provided by countries (or areas) to the United Nations Statistics Division, Department of Economic and Social Affairs (UNSD/DESA). Values are expressed in United States dollars (USD) and refer to declared transaction values. All exports are valued f.o.b. (free on board) and imports are valued c.i.f. (including cost, insurance, freight), except the imports of Canada and Mexico which are valued f.o.b. Detailed country metadata (currency conversion rates, information in HS classifications and data publication dates) can be found from the metadata file at the UN Monthly Comtrade website under the heading Metadata.
  • R
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 11 अक्तूबर, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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      This database provides a set of indicators that reflect the level and structure of central government support for business R&D; in form of R&D; tax incentives and direct funding across OECD member countries and ten non-member economies (Argentina, Brazil, Bulgaria, Croatia, Cyprus, People's Republic of China, Romania, Russian Federation, and South Africa). This includes time-series indicators of tax expenditures for R&D;, based on the latest 2017 OECD data collection on tax incentive support for R&D; expenditures that was completed in July 2017. These estimates of the cost of R&D; tax relief have been combined with data on direct R&D; funding, as compiled by National Statistical Offices based on reports from firms, in order to provide a more complete picture of government efforts to promote business R&D.; The latest indicators and information on R&D; tax incentives also feature on the dedicated OECD website Measuring R&D; tax incentives.Tax expenditures are deviations from a benchmark tax system (OECD, 2010) and countries use different national benchmarks. Available estimates typically reflect the sum of foregone tax revenues – on an accruals basis – and refunds where applicable, with no or minimal adjustments for behavior effects. Some countries only report claims realised in a given year (cash basis), while others report losses to government on an accrual basis, excluding claims referring to earlier periods and including claims for current R&D; to be used in the future. For general and country-specific notes on the estimates of government tax relief for R&D; expenditures (GTARD), see http://www.oecd.org/sti/rd-tax-stats-gtard-notes.pdfThe sources for the other indicators (direct funding of BERD, BERD and GDP) include the OECD databases on Main Science and Technology Indicators and Eurostat R&D; statistics.
    • मई 2017
      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 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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      These tables present research and development (R&D) personnel statistics for : - Total R&D personnel by sector of employment and field of science, in full-time equivalent on R&D; - Researchers by sex, sector of employment and field of science, in full-time equivant on R&D; - Researchers by sex, sector of employment and field of science, in headcounts. Sectors of employment are business enterprise, government, higher education, private non-profit and total. Breakdown by field of science includes natural sciences, engineering, medical sciences, agricultural sciences, social sciences, and humanities.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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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).
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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      This table presents research and development (R&D) personnel statistics. Number of R&D personnel is provided in headcounts and/or full-time equivalent on R&D by sex, sector of employment (business enterprise, government, higher education, and private non-profit) and by formal qualification (university and other diplomas by ISCED classification). Unit of measure used - Headcounts and/or Full-time equivalent on R&D (FTE)
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2023
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    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 दिसम्बर, 2023
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      The reference series used in the publication are: GDP for tax reporting years at market prices, national currency Exchange rates national currency per US dollar Population These data are extracted from various datasets managed by OECD directorates. The figures presented here are those used in creating the latest Revenue Statistics publication. These datasets are updated periodically during the year and therefore the figures in the latest versions may differ from those implied in the publication.
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 अगस्त, 2023
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      This dataset presents reference statistics (GDP, Total Government Expenditure, deflators, etc.) that are used to calculate some of the indicators on educational expenditure included in the indicators dataset.
    • सितम्बर 2022
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 सितम्बर, 2022
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    • मई 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जून, 2024
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      This data set provides demographic indicators aggregated at national level and broken down by territorial typology according to the population's access to cities
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 19 जुलाई, 2023
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      The Regional database contains annual data from 1995 to the most recent available year (generally 2018 for demographic and labor market data, 2017 for regional accounts, innovation and social statistics). The data collection is undertaken by the Center for Entrepreneurship, SMEs, Regions and Cities (CFE). Statistics are collected through an annual questionnaire sent to the delegates of the Working Party on Territorial Indicators (WPTI), and via downloads from the web-sites of National Statistical Offices and Eurostat
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 19 अगस्त, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 सितम्बर, 2023
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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).
    • मई 2021
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 सितम्बर, 2022
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      The Regional Database contains annual data from 1995 to the most recent available year (generally 2016 for demographic, 2015 for labor market data and 2014 for regional accounts, innovation and social statistics).
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2023
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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).
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 अक्तूबर, 2023
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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.
    • फरवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 01 फरवरी, 2024
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      The Registered Unemployment and Job Vacancies dataset is a subset of the Short-Term Labour Situation database, which contains predominantly monthly statistics, and associated statistical methodological information, for the 34 OECD member countries and for selected other economies. There are basically two sources for unemployment statistics: labour force surveys and administrative data. Surveys are based on standard methodology and procedures used all over the world while administrative data are subject to national legislations which evolve through time. Consequently registered unemployment data are not comparable across countries. The relationship between survey and registered unemployment is not the same for all countries. Number of registered unemployed persons and registered unemployment rates are presented here because they are monthly and quickly available after their reference period. The job vacancies data provides estimates of the number of unfilled job vacancies across national economies. Series give an indication of the labour demand while the unemployment is linked with the labour supply.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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      The OECD indicators of regulation in energy, transport and communications (ETCR) summarise regulatory provisions in seven sectors: telecoms, electricity, gas, post, rail, air passenger transport, and road freight. The ETCR indicators have been estimated in a long-time series and are therefore well suited for time-series analysis. The ETCR time series was updated, revised and now cover 34 OECD countries and a set of non-OECD countries for 2013. Users of the data must be aware that they may no longer fully reflect the current situation in fast reforming countries. Not all data are available for all countries for all years.
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 अगस्त, 2023
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      The PMR sector indicators measure the degree to which laws and policies promote or inhibit competition in seven network sectors (electricity, natural gas, air transport, rail transport, road transport, water transport and e-communications) and in eight service sectors (lawyers, notaries, accountants, civil engineers, architects, estate agents, retail trade and retail sales of medicines). The seven indicators for the network sectors are aggregated into a single indicator of regulation in network sectors. For more information:
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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      The OECD cross-section sectoral indicators measure regulatory conditions in the professional services and retail distribution sectors. The retail indicators cover barriers to entry, operational restrictions, and price controls. These indicators were updated and revised; they are now estimated for 34 OECD countries for the years 1998, 2003, around 2008 and 2013 and for another set of non-OECD countries for 2013. Users of the data must be aware that they may no longer fully reflect the current situation in fast reforming countries. Not all data are available for all countries for all years.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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    • जून 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 18 जून, 2020
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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.
    • जून 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 16 जून, 2020
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    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 दिसम्बर, 2023
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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.
    • अक्तूबर 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 अक्तूबर, 2020
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      International comparisons of taxes and charges on road haulage require a framework that can relate all the various taxes and charges levied on transport activities to marginal costs, if they are to provide satisfactory answers to the following types of question: -Do hauliers in one country pay more than in the other, and what impact does this have on the profitability of haulage in each country? -Is the impact of an increase in tax on diesel the same in each country or are differences in the taxation of labour more significant? -Do these differences distort the international haulage market? The 2003 ECMT Report 'Reforming Transport Taxes' developed a methodology for making such comparisons. The database presents information on vehicle taxes, fuel excise duties and user charges and takes also into account any possible refunds, rebates and exemptions. These data allow for comparison of road freight transport fiscal regimes in different countries in quantitative terms. In order to allow for comparisons of road freight taxation regimes in different countries, net taxation levels are calculated for a standard domestic haul (400-km domestic hauls with 40 tonne trucks). These results are then assessed per vehicle-km and per tonne-kilometre.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 01 नवम्बर, 2023
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      Although there are clear definitions for all the terms used in this survey, countries might have different methodologies to calculate tonne-kilometre and passenger-kilometres. Methods could be based on traffic or mobility surveys, use very different sampling methods and estimating techniques which could affect the comparability of their statistics. Also, if the definition on road fatalities is very clear and well applied by most countries, this is not the case for road injuries. Indeed, not only countries might have different definitions but the important underreporting of road injuries in most countries can distort analysis based on these data. 
  • S
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 नवम्बर, 2023
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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).
    • फरवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जनवरी, 2023
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      The OECD Secretariat collects a wide range of statistics on businesses and business activity. This database features the data collection of the Statistics Directorate relating to a number of key variables, such as value added, operating surplus, employment, and the number of business units, for example, broken down by 4-digit International Standard of Industrial Classification (ISIC Revision 4) industry groups (including the service sector)), referred to as the Structural Statistics on Industry and Services (SSIS) database; and by size class; referred to as the Business Statistics by Size Class (BSC) database.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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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.
    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 अप्रैल, 2019
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Ritesh Kumar
      Accessed On: 24 जुलाई, 2023
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      This indicator shows the percentage of international students in each field of education.
    • जून 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
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    • जून 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2018
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    • फरवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 फरवरी, 2024
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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).
    • अक्तूबर 2020
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 अक्तूबर, 2020
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      The aim of the OECD’s new Skills for Jobs Indicators is to facilitate better adaptation to changing skill needs by making available a database of skill imbalances indicators that is comparable across countries and regularly updated. The Skill Needs Indicators provide an overview of the shortages and surpluses of skills across countries.
    • जुलाई 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Collins Omwaga
      Accessed On: 02 जुलाई, 2024
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      The aim of the OECD's new Skills for Jobs Indicators is to facilitate better adaptation to changing skill needs by making available a database of skill imbalances indicators that is comparable across countries and regularly updated. The Skill Needs Indicators provide an overview of the shortages and surpluses of skills across countries.
    • जुलाई 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Collins Omwaga
      Accessed On: 01 जुलाई, 2024
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      The aim of the OECD’s new Skills for Jobs Indicators is to facilitate better adaptation to changing skill needs by making available a database of skill imbalances indicators that is comparable across countries and regularly updated. The Skill Needs Indicators provide an overview of the shortages and surpluses of skills across countries.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Darshini Priya
      Accessed On: 28 जुलाई, 2023
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    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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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.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 अक्तूबर, 2023
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      The SIGI is built on 27 innovative variables measuring discriminatory social institutions, which are grouped into 4 dimensions: discrimination in the family, restricted physical integrity, restricted access to productive and financial resources, and restricted civil liberties.Lower values indicate lower levels of discrimination in social institutions: the SIGI ranges from 0% for no discrimination to 100% for very high discrimination.
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 दिसम्बर, 2023
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    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 अक्तूबर, 2023
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      The OECD’s Social Benefit Recipients Database (SOCR) presents, for the first time, comparable information on the number of people receiving cash benefits. SOCR includes data for the main income replacement programmes in the unemployment, social assistance, disability and old-age branches. It currently covers eight years (2007-2014) for most OECD and EU countries
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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      A good complement to the number of recipients of social benefits is the number of individuals belonging to population groups that are close to the target of social benefits. The database SOCR includes a number of series providing these reference populations. For example: old-age pensions are mainly targeted on individuals of retirement age, the over 65 population is provided; unemployment benefits go to jobseekers, the number of unemployed (ILO definition) is provided.
    • दिसम्बर 2012
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 अप्रैल, 2019
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      STAN Indicators provides annual indicators related to production and employment structure, labour productivity and labour costs, investment, business research and development expenditures and international trade patterns. Data are presented for OECD countries and cover the time-period 1970-2011, although the time coverage may vary across countries and indicators. Series are provided for a wide range of economic activities (according to an ISIC Rev.4 based hierarchy) compatible with the list in the underlying STAN Database in ISIC Rev. 4. STAN Indicators belong to the STAN family datasets; they are primarily drawn from STAN Database for Structural Analysis (STAN), STAN Bilateral Trade (BTDIxE) and STAN Research & Development Expenditures in Industry (ANBERD). Indicators are compiled to respond to the needs of analysts and researchers interested in measuring economic performance, productivity growth, competitiveness and structural changes. They also complement the OECD publications, Science Technology and Industry Scoreboard and Economic Globalisation Indicators.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 17 अक्तूबर, 2023
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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 and to focus on areas such as productivity growth, competitiveness and general structural change.Through the use of a standard industry list, international comparisons can be made. The industry list, compatible with those used in related OECD databases, provides sufficient detail to highlight technology and digital-intensive sectors. 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 other sources of data such as national industrial surveys/censuses. Time series are extended back to the 1970's where possible. This is done using vintage SNA93 or STAN estimates. In STAN, many data points are Secretariat's estimates and are flagged to the attention of users; 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 published on a "rolling basis" with new, or updated, country tables being made available as soon as they are ready.
    • मार्च 2012
      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.
    • मार्च 2012
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 04 अगस्त, 2014
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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 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
      Select Dataset
      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.
    • मार्च 2012
      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.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 अक्तूबर, 2023
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      The dataset on Statistical discrepancy (Institutional Investors – Financial Balance Sheets) represents the time series of the dataset on Institutional investors' assets and liabilities (7II) along with those of the dataset on Financial Balance Sheets (720), for the financial instruments and institutional sectors which are in common to these two datasets.  Additionally, for each of the above-mentioned time series, a statistical discrepancy is reported in order to show any possible differences which may exist between the two datasets (7II and 720).  In fact, the dataset on Institutional investors' assets and liabilities (7II) constitutes an attempt to better integrate these data in the framework of the System of National Accounts 2008 (SNA 2008).  However, discrepancies may exist and may, for example, be caused by balancing practices (e.g. when sector and counterpart sector data are reconciled) in the compilation of Financial Balance Sheets at a higher level of aggregation, which may not have been carried through at a lower level of aggregation. Moreover, differences may also be caused by the use of different source data.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 21 नवम्बर, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2023
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      Excess capacity is one of the main challenges facing the global steel sector. The OECD Steelmaking Capacity database contains data on crude steelmaking capacity by economy and provides researchers and policymakers with an important tool for analysing steel capacity developments.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 14 सितम्बर, 2023
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      The OECD STRI heterogeneity indices complement the existing STRI's and presents indices of regulatory heterogeneity based on the rich information in the STRI regulatory database. The indices are built from assessing – for each country pair and each measure – whether or not the countries have the same regulation. For each country pair and each sector, the indices reflect the (weighted) share of measures for which the two countries have different regulation.
    • अक्तूबर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 अक्तूबर, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 जुलाई, 2023
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      The OECD indicators of employment protection are synthetic indicators of the strictness of regulation on dismissals and the use of temporary contracts. For each year, indicators refer to regulation in force on the 1st of January. Version 1 of the indicator of strictness of employment protection - individual and collective dismissals (regular contracts) - does not incorporate all the data items of version 3 and, in particular, does not incorporate regulation of collective dismissals. You should only use version 1 if you need data for years for which neither version 2 nor 3 are available.
    • अगस्त 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 12 अगस्त, 2023
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      The OECD indicators of employment protection are synthetic indicators of the strictness of regulation on dismissals and the use of temporary contracts. For each year, indicators refer to regulation in force on the 1st of January. For more information and full methodology, see www.oecd.org/employment/protection.
    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 06 नवम्बर, 2023
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      The OECD indicators of employment protection are synthetic indicators of the strictness of regulation on dismissals and the use of temporary contracts. For each year, indicators refer to regulation in force on the 1st of January. For more information and full methodology, see www.oecd.org/employment/protection.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 27 जुलाई, 2023
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      The OECD indicators of employment protection legislation evaluate the regulations on the dismissal of workers on regular contracts and the hiring of workers on temporary contracts. They cover both individual and collective dismissals.The indicators have been compiled using the Secretariat’s own reading of statutory laws, collective bargaining agreements and case law as well as contributions from officials from OECD member countries and advice from country experts
    • अक्तूबर 2020
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 27 अक्तूबर, 2020
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      For data aligned to Finance, the year shown is the calendar year. For data aligned to personnel, the year shown is the year in which the end of the school year falls (e.g. 2002 refers to the school year 2001/2002), with the exceptions of Korea where the year refers to the year in which the school year begins and Australia and New Zealand where the school academic year corresponds to the calendar year.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 25 जुलाई, 2023
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      Student-teacher ratio refers to the average number of students per teacher, while average class size is the average number of students in a classroom.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 14 सितम्बर, 2023
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      The subnational government finance dataset presents data on the institutional organisation at local and regional levels as well as on public finance. Financial data cover the general government sector and subnational government subsector (state and local government levels) in the 35 OECD member countries and in the EU. Four main dimensions are presented: expenditure (including investment), revenue, budget balance and debt. The dataset is released as a beta version. Data at country level are derived mainly from the OECD National Accounts harmonised according to the new standards of the System of National Accounts (SNA) 2008, implemented by most OECD countries since December 2014. They are complemented by data from Eurostat, IMF (Australia, Chile), and national statistical institutes for some countries or indicators (in particular, territorial organisation). Data were extracted in February 2017 and are from 2015, unless otherwise specified
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 04 जुलाई, 2023
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      Data cited at: OECD (2020), Suicide rates (indicator). doi: 10.1787/a82f3459-en (Accessed on 18 August 2020) Suicide rates are defined as the deaths deliberately initiated and performed by a person in the full knowledge or expectation of its fatal outcome. Comparability of data between countries is affected by a number of reporting criteria, including how a person's intention of killing themselves is ascertained, who is responsible for completing the death certificate, whether a forensic investigation is carried out, and the provisions for confidentiality of the cause of death. Caution is required therefore in interpreting variations across countries. The rates have been directly age-standardised to the 2010 OECD population to remove variations arising from differences in age structures across countries and over time. The original source of the data is the WHO Mortality Database. This indicator is presented as a total and per gender and is measured in terms of deaths per 100 000 inhabitants (total), per 100 000 men and per 100 000 women.
    • सितम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 सितम्बर, 2023
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    • जून 2016
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 12 नवम्बर, 2021
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2023
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      Survey on Monitoring the Paris Declaration. The dataset contains data as reported by donors and national co-ordinators in participating partner countries. The dataset includes all quantitative data collected through the 2006, 2008 and 2011 Surveys.
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    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 21 नवम्बर, 2023
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    • नवम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 21 नवम्बर, 2023
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    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 जुलाई, 2023
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      Statutory corporate income tax rate - This table shows 'basic' (non-targeted) central, sub-central and combined (statutory) corporate income tax rates. Where a progressive (as opposed to flat) rate structure applies, the top marginal rate is shown.
    • जुलाई 2023
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 26 जुलाई, 2023
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      Targeted statutory corporate income tax rate - This table reports central, sub-central and combined corporate income tax rates typically applying for or targeted at 'small (incorporated) business', where such 'targeting' is on the basis of size alone (e.g. number of employees, amount of assets, turnover or taxable income) and not on the basis of expen