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Canada

  • Governor General:Julie Payette
  • Prime Minister:Justin Pierre James Trudeau
  • Capital city:Ottawa
  • Languages:English (official) 58.7%, French (official) 22%, Punjabi 1.4%, Italian 1.3%, Spanish 1.3%, German 1.3%, Cantonese 1.2%, Tagalog 1.2%, Arabic 1.1%, other 10.5% (2011 est.)
  • Government
  • National statistics office
  • Population, persons:3,70,58,856 (2018)
  • Area, sq km:90,93,510
  • GDP per capita, US$:46,125 (2018)
  • GDP, billion current US$:1,709.3 (2018)
  • GINI index:No data
  • Ease of Doing Business rank:22
All datasets:  A B C D E F G H I K L M N O P R S T W И П Р С
  • A
    • सितम्बर 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2019
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    • मई 2019
      Source: European Commission
      Uploaded by: Knoema
      Accessed On: 11 मई, 2019
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      AMECO is the annual macro-economic database of the European Commission's Directorate General for Economic and Financial Affairs. The database is indispensable for the analyses and reports of the Directorate General and contains data for EU-28, the euro area, EU Member States, candidate countries and other OECD countries. The database contains data for EU-28, the euro area, EU Member States, candidate countries and other OECD countries (United States, Japan, Canada, Switzerland, Norway, Iceland, Mexico, Korea, Australia and New Zealand). Data for Member States and candidate countries are based on the ESA 2010 system for the last period and on ESA 95 and ESA 79 for the earlier years. Data for other OECD countries are based on the SNA 2008. Discontinuities of the levels of all series have been removed by applying the growth rates of the old series to the levels of the new series.
  • B
    • मार्च 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 20 मार्च, 2019
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      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Jobs Publication: https://datacatalog.worldbank.org/dataset/jobs License: http://creativecommons.org/licenses/by/4.0/   The World Bank Jobs Statistics Over 150 indicators on labor-related topics, covering over 200 economies from 1990 to present.
  • C
    • मार्च 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 12 मार्च, 2019
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    • मार्च 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 12 मार्च, 2019
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    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 04 नवम्बर, 2019
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      Statistical population: CLIs are calculated for 33 OECD countries (Iceland is not included), 6 non-member economies and 8 zone aggregates. A country CLI comprises a set of component series selected from a wide range of key short-term economic indicators.   CLIs, reference series data (see below) and standardised business and consumer confidence indicators are presented in various forms.   Recommended uses and limitations: The composite leading indicator is a times series, formed by aggregating a variety of component indicators which show a reasonably consistent relationship with a reference series (e.g. industrial production IIP up to March 2012 and since then the reference series is GDP) at turning points. The OECD CLI is designed to provide qualitative information on short-term economic movements, especially at the turning points, rather than quantitative measures. Therefore, the main message of CLI movements over time is the increase or decrease, rather than the amplitude of the changes. The OECD’s headline indicator is the amplitude adjusted CLI. In practice, turning points in the de-trended reference series have been found about 4 to 8 months (on average) after the signals of turning points had been detected in the headline CLI.
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 नवम्बर, 2019
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      The 'Consumer Price Indices (CPIs)' contains all data that was previously contained in three different datasets: 'Consumer Prices', 'National Consumer Price Indices (CPIs) by COICOP divisions' and 'Harmonised Indices of Consumer Prices (HICPs) by COICOP divisions'. The 'Consumer Price Indices (CPIs)' dataset contains predominantly monthly statistics, and associated statistical methodological information, for the 36 OECD member countries and for some non-member countries. The ‘Consumer Price Indices (CPIs)' dataset contains statistics on Consumer Price Indices including national CPIs, Harmonised Indices of Consumer Prices (HICPs) and their associated weights and contributions to national annual inflation. The data series presented have been chosen as the most relevant prices statistics for which comparable data across countries is available. In all cases, a lot of effort has been made to ensure that the data are internationally comparable across all countries presented and that all the subjects have good historical time-series’ data to aid with analysis. Data are available monthly for all the countries except for Australia and New Zealand (quarterly data).
    • अगस्त 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 02 सितम्बर, 2019
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    • अप्रैल 2015
      Source: International Monetary Fund
      Uploaded by: Sandeep Reddy
      Accessed On: 20 अगस्त, 2015
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      Global growth is forecast at 3.5 percent in 2015 and 3.8 percent in 2016, with uneven prospects across the main countries and regions of the world. The distribution of risks to near-term global growth has become more balanced relative to the October World Economic Outlook but is still tilted to the downside. The decline in oil prices could boost activity more than expected. Geopolitical tensions continue to pose threats, and risks of disruptive shifts in asset prices remain relevant. In some advanced economies, protracted low inflation or deflation also pose risks to activity. The chapter takes a region-by-region look at the recent development in the world economy and the outlook for 2015, with particular attention to notable development in countries within each region.
    • नवम्बर 2019
      Source: United Nations Economic Commission for Europe
      Uploaded by: Knoema
      Accessed On: 07 नवम्बर, 2019
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      Source: UNECE Statistical Database, compiled from national and international official sources. Area data exclude overseas departments and territories. For population footnotes click here. For life expectancy footnotes click here. For fertility rate footnotes click here. For population by marital status footnotes click here. For female members of parliament footnotes click here. For female government ministers footnotes click here. For female central bank board members footnotes click here. For female tertiary students footnotes click here. For economic activity rate footnotes click here. For gender pay gap footnotes click here. For employment growth rate footnotes click here. For unemployment rate footnotes click here. For youth unemployment rate footnotes click here. For employment by economic sector footnotes click here. For economic indicator footnotes click here. For road accident footnotes click here. For total length of motorways footnotes click here. For total length of railway lines footnotes click here. Key indicators in maps .. - data not availableIndicatorGDP in agriculture (ISIC4 A): output approach, index, 2010=100If the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP in industry (incl. construction) (ISIC4 B-F): output approach, index, 2010=100If the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP in services (ISIC4 G-U): output approach, index, 2010=100If the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in agriculture etc. (ISIC4 A), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in industry etc. (ISIC4 B-E), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in construction (ISIC4 F), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in trade, hospitality, transport and communication (ISIC4 G-J), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in finance and business services (ISIC4 K-N), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in public administration, education and health (ISIC4 O-Q), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in other service activities (ISIC4 R-U), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in agriculture, hunting, forestry and fishing (ISIC Rev. 4 A), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in industry and energy (ISIC Rev. 4 B-E), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in construction (ISIC Rev. 4 F), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in trade, hotels, restaurants, transport and communications (ISIC Rev. 4 G-J), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in finance, real estate and business services (ISIC Rev. 4 K-N), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in public administration, education and health (ISIC Rev. 4 O-Q), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in other service activities (ISIC Rev. 4 R-U), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.
    • मार्च 2012
      Source: Knoema
      Uploaded by: Knoema
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      Country Risk Assessment Database, 2012. Source: Multiple Sources - EuroStat, WB, IMF, OECD, UNCTAD
    • अप्रैल 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 08 मई, 2019
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  • D
    • जनवरी 2018
      Source: The Fletcher School,Tufts University
      Uploaded by: Knoema
      Accessed On: 30 अगस्त, 2018
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      The DEI 2017 is a data-driven holistic evaluation of the progress of the digital economy across 60 countries, combining more than 100 different indicators across four key drivers: Supply Conditions, Demand Conditions, Institutional Environment, and Innovation and Change. The resulting framework captures both the state and rate of digital evolution and identifies implications for investment, innovation, and policy priorities. DEI 2017 also highlights the evolving nature of the risks being created by our continuing reliance on digital technology. Towards this end, the study covers a key question of “digital trust.“ The DEI 2017 incorporates a newly devised analysis of digital trust that takes into account the trustworthiness of the digital environment for each country; the quality of users’ experience; attitudes towards key institutions and organizations; and users’ behavior when they interact with the digital world. This subject is of great interest to all participants in the digital economy, given the concerns about security of essential information, cyber-attacks, and consumers’ apprehensions—about the digital systems and their reliability, the digital companies and their growing dominance, and about the leaders of digital companies. The DEI framework segments the 60 countries into Stand Outs, Stall Outs, Break Outs and Watch Outs. Three countries are notable as standouts even within the Stand Out segment: Singapore, New Zealand, and the UAE. Each has a unique policy-led digital strategy and a narrative that may be considered by other nations as worthy of emulation or adoption. The Nordic countries and Switzerland are at the top of the DEI 2017 rankings. China, once again, tops the list of countries in terms of the pace of change in its digital evolution, or momentum.
    • मार्च 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 29 अप्रैल, 2019
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    • मार्च 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 29 अप्रैल, 2019
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  • E
    • सितम्बर 2019
      Source: Fraser Institute
      Uploaded by: Knoema
      Accessed On: 25 सितम्बर, 2019
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      Data cited at: "Economic Freedom of the World: 2019 Annual Report"@Fraser Institute   The economic freedom index measures the degree of economic freedom present in five major areas: [1] Size of Government; [2] Legal System and Security of Property Rights; [3] Sound Money; [4] Freedom to Trade Internationally; [5] Regulation. Within the five major areas, there are 24 components (area) in economic freedom index. Each component and sub-component is placed on a scale from 0 to 10.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 30 अक्तूबर, 2019
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      The OECD Long-Term Baseline Scenario is a projection of some major economic variables beyond the short-term horizon of the OECD Economic Outlook. It covers all OECD economies, non-OECD G20 economies and key partners. The projection horizon is currently 2060. For the historical period and the short-run projection horizon, the series are consistent with those of the OECD Economic Outlook number in the dataset title. The definitions, sources and methods are also the same, except where noted explicitly (such as coverage of the non-OECD and world aggregates). For more details on the methodology, please see Boxes 1 to 3 in The Long View: Scenarios for the World Economy to 2060 and the references therein.The baseline scenario is a projection conditional on a number of assumptions, notably that countries do not carry out institutional and policy reforms. It is used as a reference point to illustrate the potential impact of structural reforms in alternative scenarios, such as those discussed in The Long View: Scenarios for the World Economy to 2060. The data for these alternative scenarios are not available here but can be obtained on request by writing to EcoOutlook@oecd.org.
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 नवम्बर, 2019
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      The OECD Economic Outlook analyses the major economic trends over the coming 2 years. It provides in-depth coverage of the main economic issues and the policy measures required to foster growth in each member country. Forthcoming developments in major non-OECD economies are also evaluated in detail. Each edition of the Outlook provides a unique resource to keep abreast of world economic developments. The OECD Economic Outlook database is a comprehensive and consistent macroeconomic database of the OECD economies, covering expenditures, foreign trade, output, labour markets, interest and exchange rates, balance of payments, and government debt. For the non-OECD regions, foreign trade and current account series are available.   The database contains annual data (for all variables) and quarterly figures (for a subset of variables). Variables are defined in such a way that they are as homogenous as possible for the countries covered. Breaks in underlying series are corrected as far as possible. Sources for the historical data are publications of national statistical agencies and OECD data bases such as Quarterly National Accounts, Annual National Accounts, Labour Force Statistics and Main Economic Indicators. The cut-off date for information used in the compilation of the projections was the 15 May 2019.   Concerning the aggregation of world trade, a new composition has been introduced, since projections are now made for the major non-OECD economies. Thus, besides OECD and the OECD euro area, the following new regions are available: Dynamic Asian Economies (Chinese Taipei, Hong Kong, Malaysia, the Philippines, Singapore, Thailand, Vietnam); Oil Producers (Azerbaijan, Kazakhstan, Turkmenistan, Brunei, Timor-Leste, Bahrain, Iran, Iraq, Kuwait, Libya, Oman, Qatar, Saudi Arabia, United Arab Emirates, Yemen, Ecuador, Trinidad and Tobago, Venezuela, Algeria, Angola, Chad, Rep. of Congo, Equatorial Guinea, Gabon, Nigeria, Sudan); with the remaining countries in a residual 'Rest of the World' group.
    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 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.
    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 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 the Outlook provides a unique resource to keep abreast of world economic developments. The OECD Economic Outlook database is a comprehensive and consistent macroeconomic database of the OECD economies, covering expenditures, foreign trade, output, labour markets, interest and exchange rates, balance of payments, and government debt. For the non-OECD regions, foreign trade and current account series are available. The database contains annual for the projection period. Variables are defined in such a way that they are as homogenous as possible for the countries covered. Breaks in underlying series are corrected as far as possible. Sources for the historical data are publications of national statistical agencies and OECD statistical publications such as the Quarterly National Accounts, the Annual National Accounts, the Annual Labour Force Statistics and the Main Economic Indicators. The cut-off date for information used in the compilation of the projections was the 15 May 2013. With the OECD Economic Outlook 87, new aggregation techniques have been applied to construct the OECD area (34 countries) and the OECD euro area (15 OECD countries that are also members of Euro area). The new approach aims to better handle issues arising from evolving composition of these areas and different data availability across countries. The main changes are a switch from a fixed weighting scheme to moving weighting schemes for OECD and the direct aggregation of ratios, rather than computing them as ratios of aggregated components. Consequently, a number of series expressed in levels differ from the series previously published, while others are no longer available, particularly government and labour market data. Concerning the aggregation of world trade, a new composition has been introduced, since projections are now made for the major non-OECD economies. Thus, besides OECD and the OECD euro area, the following new regions are available: Dynamic Asian Economies (Chinese Taipei, Hong Kong, Malaysia, the Philippines, Singapore, Thailand, Vietnam); Oil Producers (Azerbaijan, Kazakhstan, Turkmenistan, Brunei, Timor-Leste, Bahrain, Iran, Iraq, Kuwait, Libya, Oman, Qatar, Saudi Arabia, United Arab Emirates, Yemen, Ecuador, Trinidad and Tobago, Venezuela, Algeria, Angola, Chad, Rep. of Congo, Equatorial Guinea, Gabon, Nigeria, Sudan); with the remaining countries in a residual 'Rest of the World' group.
    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 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 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 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 जुलाई, 2019
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      The OECD Economic Outlook analyses the major economic trends over the coming 2 to 3 years. It provides in-depth coverage of the main economic issues and the policy measures required to foster growth in each member country. Forthcoming developments in major non-OECD economies are also evaluated in detail. Each edition of the Outlook provides a unique resource to keep abreast of world economic developments. The OECD Economic Outlook database is a comprehensive and consistent macroeconomic database of the OECD economies, covering expenditures, foreign trade, output, labour markets, interest and exchange rates, balance of payments, and government debt. For the non-OECD regions, foreign trade and current account series are available. The database contains annual for the projection period. Variables are defined in such a way that they are as homogenous as possible for the countries covered. Breaks in underlying series are corrected as far as possible. Sources for the historical data are publications of national statistical agencies and OECD statistical publications such as the Quarterly National Accounts, the Annual National Accounts, the Labour Force Statistics and the Main Economic Indicators. The cut-off date for information used in the compilation of the projections was the 29 May 2015. Concerning the aggregation of world trade, a new composition has been introduced, since projections are now made for the major non-OECD economies. Thus, besides OECD and the OECD euro area, the following new regions are available: Dynamic Asian Economies (Chinese Taipei, Hong Kong, Malaysia, the Philippines, Singapore, Thailand, Vietnam); Oil Producers (Azerbaijan, Kazakhstan, Turkmenistan, Brunei, Timor-Leste, Bahrain, Iran, Iraq, Kuwait, Libya, Oman, Qatar, Saudi Arabia, United Arab Emirates, Yemen, Ecuador, Trinidad and Tobago, Venezuela, Algeria, Angola, Chad, Rep. of Congo, Equatorial Guinea, Gabon, Nigeria, Sudan); with the remaining countries in a residual 'Rest of the World' group.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2019
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    • फरवरी 2019
      Source: National Institute of Statistics, Italy
      Uploaded by: Knoema
      Accessed On: 25 फरवरी, 2019
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      Data source(s) used: Data source: OECD Education at a glance (annually published) containing detailed analysis of several internationally comparable indicators of human capital.For further details please see the volume on the site: www.oecd.org
    • मार्च 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 12 मार्च, 2019
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    • अगस्त 2011
      Source: Knoema
      Uploaded by: Knoema
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      A compilation of monthly closing stock indices for major stock exchanges across the World. This dataset is updated on a monthly basis.
    • जुलाई 2019
      Source: European Commission
      Uploaded by: Knoema
      Accessed On: 13 सितम्बर, 2019
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      Dataset includes European Economic economic forecast releases from Winter 2018 through Summer 2019(Interim).
    • अक्तूबर 2015
      Source: International Monetary Fund
      Uploaded by: Knoema
      Accessed On: 22 अक्तूबर, 2015
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      Recent exchange rate movements have been unusually large, triggering a debate regarding their likely effects on trade. Historical experience in advanced and emerging market and developing economies suggests that exchange rate movements typically have sizable effects on export and import volumes. A 10 percent real effective depreciation in an economy’s currency is associated with a rise in real net exports of, on average, 1.5 percent of GDP, with substantial cross-country variation around this average. Although these effects fully materialize over a number of years, much of the adjustment occurs in the first year. The boost to exports associated with currency depreciation is found to be largest in countries with initial economic slack and with domestic financial systems that are operating normally. Some evidence suggests that the rise of global value chains has weakened the relationship between exchange rates and trade in intermediate products used as inputs into other economies’ exports. However, the bulk of global trade still consists of conventional trade, and there is little evidence of a general trend toward disconnect between exchange rates and total exports and imports.
  • F
  • G
    • नवम्बर 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 नवम्बर, 2019
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      National accounts are a coherent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. The data presented in this collection are the results of a pilot exercise on the sharing selected main GDP aggregates, population and employment data collected by different international organisations. It wasconducted by the Task Force in International Data Collection (TFIDC) which was established by the  Inter-Agency Group on Economic and Financial Statistics (IAG).  The goal of this pilot is to develop a set of commonly shared principles and working arrangements for data cooperation that could be implemented by the international agencies. The data sets are an experimental exercise to present national accounts data form various countries across the globe in one coherent folder, but users should be aware that these data are collected and validated by different organisations and not fully harmonised from a methodological point of view.  The domain consists of the following collections:
    • नवम्बर 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 12 नवम्बर, 2019
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      National accounts are a coherent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. The data presented in this collection are the results of a pilot exercise on the sharing selected main GDP aggregates, population and employment data collected by different international organisations. It wasconducted by the Task Force in International Data Collection (TFIDC) which was established by the  Inter-Agency Group on Economic and Financial Statistics (IAG).  The goal of this pilot is to develop a set of commonly shared principles and working arrangements for data cooperation that could be implemented by the international agencies. The data sets are an experimental exercise to present national accounts data form various countries across the globe in one coherent folder, but users should be aware that these data are collected and validated by different organisations and not fully harmonised from a methodological point of view.  The domain consists of the following collections:
    • जुलाई 2019
      Source: United Nations Economic Commission for Europe
      Uploaded by: Sandeep Reddy
      Accessed On: 26 जुलाई, 2019
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      GDP: Expenditure Approach, in National Currency, by Country and Expenditure
    • अगस्त 2019
      Source: United Nations Department of Economic and Social Affairs
      Uploaded by: Knoema
      Accessed On: 23 अक्तूबर, 2019
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    • अक्तूबर 2019
      Source: Economic Policy Uncertainty
      Uploaded by: Knoema
      Accessed On: 16 अक्तूबर, 2019
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      Data cited at: Economic Policy Uncertainty The Global Economic Policy Uncertainty (GEPU) Index is a GDP-weighted average of national EPU indices for 20 countries: Australia, Brazil, Canada, Chile, China, France, Germany, Greece, India, Ireland, Italy, Japan, Mexico, the Netherlands, Russia, South Korea, Spain, Sweden, the United Kingdom, and the United States.
    • अक्तूबर 2019
      Source: International Monetary Fund
      Uploaded by: Knoema
      Accessed On: 18 अक्तूबर, 2019
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      Vulnerabilities in a Maturing Credit Cycle The October 2019 Global Financial Stability Report (GFSR) finds that despite significant variability over the past two quarters, financial conditions remain accommodative. As a result, financial vulnerabilities have continued to build in the sovereign, corporate, and non bank financial sectors in several systemically important countries, leading to elevated medium-term risks. The report attempts to provide a comprehensive assessment of these vulnerabilities while focusing specifically on corporate sector debt in advanced economies, the sovereign–financial sector nexus in the euro area, China’s financial imbalances, volatile portfolio flows to emerging markets, and downside risks to the housing market. These vulnerabilities require action by policymakers, including through the clear communication of any changes in their monetary policy outlook, the deployment and expansion of macroprudential tools, the stepping up of measures to repair public and private sector balance sheets, and the strengthening of emerging market resilience to foreign portfolio out flows. Downside Risks to House Prices The study and quantifies house prices at risk, a measure of downside risks to future house price growth—using theory, insights from past analyses, and new statistical techniques applied to 32 advanced and emerging market economies and major cities. The chapter finds that lower house price momentum, overvaluation, excessive credit growth, and tighter financial conditions predict heightened downside risks to house prices up to three years ahead. The measure of house prices at risk helps forecast downside risks to GDP growth and adds to early-warning models for financial crises. Policymakers can use estimates of house prices at risk to complement other surveillance indicators of housing market vulnerabilities and guide macroprudential policy actions aimed at building buffers and reducing vulnerabilities. Downside risks to house prices could also be relevant for monetary policymakers when forming their views on the downside risks to the economic and inflation outlook. Authorities considering measures to manage capital flows might also find such information useful when a surge in capital inflows increases downside risks to house prices and when other policy options are limited.
    • सितम्बर 2018
      Source: Dual Citizen LLC
      Uploaded by: Knoema
      Accessed On: 21 सितम्बर, 2018
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      The performance index of the 2018 GGEI is defined by 20 underlying indicators, each contained within one of the four main dimensions of leadership & climate change, efficiency sectors, markets & investment and the environment.   For more detail on our approach to aggregating these diverse data sources to define the composite indicators in the GGEI and its four main dimensions, as well as our approach to data selection, weighting and other issues associated with creating an index, please visit the Methodology section.
    • दिसम्बर 2018
      Source: Knowledge4All
      Uploaded by: Sandeep Reddy
      Accessed On: 18 मार्च, 2019
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      Data cited at: Knowledge4All,United Nations Development Programme & Mohammed Bin Rashid Al Maktoum Knowledge Foundation.   Note-Full Version can be checked here: https://knoema.com/WLDKALLGKI2018Dec/global-knowledge-index The GKI is a partnership initiative between the United Nations Development Programme (UNDP) and Mohammed Bin Rashid Al Maktoum Knowledge Foundation (MBRF), it was first announced during the Knowledge Summit in 2016. The Global Knowledge Index (GKI) is the index that measures knowledge on the global level, it highlights the strategic role of knowledge and the importance of developing objective and scientific tools to measure and evaluate it. The GKI aims at measuring knowledge as a broad concept that is intricately related to all aspects of modern human life, in a systematic approach that builds on solid conceptual and methodological principles. The Global Knowledge Index (GKI) is the only index that measures knowledge on the global level, it highlights the strategic role of knowledge and the importance of developing objective and scientific tools to measure and evaluate it. The GKI aims at measuring knowledge as a broad concept that is intricately related to all aspects of modern human life, in a systematic approach that builds on solid conceptual and methodological principles. The GKI is composed of six sectoral indices: 1) Pre - university education 2) Technical vocational education and training(TVET) 3) Higher education 4) Research, development and innovation(RDI) 5) Information and communications technology (ICT) 6) Economy in addition to a seventh supporting index on the General Enabling Environment. All values are normalized to a scale from 0 (worst) to 100 (best).
    • दिसम्बर 2018
      Source: Knowledge4All
      Uploaded by: Sandeep Reddy
      Accessed On: 18 मार्च, 2019
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      Data cited at: Knowledge4All,United Nations Development Programme & Mohammed Bin Rashid Al Maktoum Knowledge Foundation. The GKI is a partnership initiative between the United Nations Development Programme (UNDP) and Mohammed Bin Rashid Al Maktoum Knowledge Foundation (MBRF), it was first announced during the Knowledge Summit in 2016. The Global Knowledge Index (GKI) is the index that measures knowledge on the global level, it highlights the strategic role of knowledge and the importance of developing objective and scientific tools to measure and evaluate it. The GKI aims at measuring knowledge as a broad concept that is intricately related to all aspects of modern human life, in a systematic approach that builds on solid conceptual and methodological principles. The Global Knowledge Index (GKI) is the only index that measures knowledge on the global level, it highlights the strategic role of knowledge and the importance of developing objective and scientific tools to measure and evaluate it. The GKI aims at measuring knowledge as a broad concept that is intricately related to all aspects of modern human life, in a systematic approach that builds on solid conceptual and methodological principles. The GKI is composed of six sectoral indices: 1) Pre - university education 2) Technical vocational education and training(TVET) 3) Higher education 4) Research, development and innovation(RDI) 5) Information and communications technology (ICT) 6) Economy in addition to a seventh supporting index on the General Enabling Environment. All values are normalized to a scale from 0 (worst) to 100 (best).   The Pre-University Education sector plays a central role in building the knowledge capital that represents the first input in preparing young people to acquire and produce knowledge. Pre-university education equips youth with scientific knowledge, as well as creative skills and capacities, to access lifelong learning opportunities. This sector is therefore key, as it constitutes the first basis for other sectors to build upon. It is composed of two pillars: knowledge capital and educational enabling environment. The Technical Vocational Education and Training (TVET) sector represents the main connection between education and the labour market and provides educated young people with opportunities for professional integration. It contributes to the provision of high-skilled labour and the development of conducive working environments. It is composed of two pillars: formation and professional training and features of the labour market. The Higher Education sector is of high importance, as it is an active component in educating youth, developing their qualifications, and expanding their knowledge and skills, which results in the improvement of a country’s productivity and competitiveness in global markets. It is also considered among the most important factors that directly contribute to the advancement of scientific research and technological development. It is composed of two pillars: higher education inputs and higher education outputs and quality. Research, Development, and Innovation (RDI) contribute to increasing knowledge at the national and regional levels. RDI, which serves as a driver for economic growth and sustainable development in both developed and developing countries, is mainly based on the production of new or improved goods, services, production processes, and organizational models. RDI is closely linked to other sectors as it provides essential inputs to the entire system. It is composed of three pillars: research and development, innovation in production, and social innovation. Information and Communications Technology (ICT) plays an essential role in supporting the advancement of knowledge across all sectors. Advancements in knowledge-intensive production have become closely linked to the provision of advanced technology, especially as the Internet has increased the opportunities available to acquire knowledge. Therefore, it is essential for countries to employ indicators that quantify their levels of ICT development for the benefit of stakeholders in their societies. It is composed of two pillars: ICT inputs and ICT outputs. Information and Communications Technology (ICT) plays an essential role in supporting the advancement of knowledge across all sectors. Advancements in knowledge-intensive production have become closely linked to the provision of advanced technology, especially as the Internet has increased the opportunities available to acquire knowledge. Therefore, it is essential for countries to employ indicators that quantify their levels of ICT development for the benefit of stakeholders in their societies. It is composed of two pillars: ICT inputs and ICT outputs. The Knowledge Economy is the main driver of sustainable development, wealth creation, and job creation in various economic fields, across the industrial, agricultural, and service sectors. Unlike the traditional concept of economic resource analysis and availability, a knowledge economy is primarily based on providing economic resources, particularly human resources, with knowledge tools, including digital and technological knowledge assets, as well as innovative and creative skills. It is composed of three pillars: knowledge competitiveness, economic openness, and financing and value added. The General Enabling Environment was added to support the 6 sectoral indices, as these sectors do not operate in isolation from their surroundings, but rather in a space governed by a range of contextual factors – political, socioeconomic, health-related, and environmental. It is composed of three pillars: political and institutional, socio-economic, and health and environment.
    • मई 2019
      Source: KPMG
      Uploaded by: Knoema
      Accessed On: 28 जून, 2019
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      Covers data on corporate, indirect and individual income tax rates throughout 163 countries across the world during the period from 2006 to 2019. Provided by KPMG.
    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 अप्रैल, 2019
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      Going for Growth helps to promote sustainable economic growth and improve the well-being of OECD citizens. The surveillance is based on a systematic and in-depth analysis of structural policies and their outcomes across OECD members, relying on a set of internationally comparable and regularly updated policy indicators with a well-established link to performance. From one issue to the next, Going for Growth follows up on these recommendations and priorities evolve, not least as a result of governments taking action, http://www.oecd.org/eco/going-for-growth/. This dataset contains time series of a comprehensive set of quantitative indicators that allow for a comparison of policy settings across OECD countries and selected non-member economies: Argentina, Brazil, China, Colombia, Costa Rica, India, Indonesia, Lithuania, the Russian Federation and South Africa. The dataset covers several areas: Product market regulation (economy-wide and sector-specific regulation), Education, Public investment and subsidies, Taxation, Labour market, Transfers. Data are consistent with those published in the Structural Policy Indicators chapter of Going for Growth 2018. The cut-off date is December 2017.
    • सितम्बर 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2019
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    • सितम्बर 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2019
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    • सितम्बर 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2019
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    • सितम्बर 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2019
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    • सितम्बर 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2019
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    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 15 अक्तूबर, 2019
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    • अक्तूबर 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2019
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    • नवम्बर 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 15 नवम्बर, 2019
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      National accounts are a coherent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. The data presented in this collection are the results of a pilot exercise on the sharing selected main GDP aggregates, population and employment data collected by different international organisations. It wasconducted by the Task Force in International Data Collection (TFIDC) which was established by the  Inter-Agency Group on Economic and Financial Statistics (IAG).  The goal of this pilot is to develop a set of commonly shared principles and working arrangements for data cooperation that could be implemented by the international agencies. The data sets are an experimental exercise to present national accounts data form various countries across the globe in one coherent folder, but users should be aware that these data are collected and validated by different organisations and not fully harmonised from a methodological point of view.  The domain consists of the following collections:
    • नवम्बर 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 15 नवम्बर, 2019
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      National accounts are a coherent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. The data presented in this collection are the results of a pilot exercise on the sharing selected main GDP aggregates, population and employment data collected by different international organisations. It wasconducted by the Task Force in International Data Collection (TFIDC) which was established by the  Inter-Agency Group on Economic and Financial Statistics (IAG).  The goal of this pilot is to develop a set of commonly shared principles and working arrangements for data cooperation that could be implemented by the international agencies. The data sets are an experimental exercise to present national accounts data form various countries across the globe in one coherent folder, but users should be aware that these data are collected and validated by different organisations and not fully harmonised from a methodological point of view.  The domain consists of the following collections:
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    • जुलाई 2018
      Source: International Centre for Tax and Development
      Uploaded by: Knoema
      Accessed On: 23 मई, 2019
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      Data cited at: ICTD/UNU-WIDER, ‘Government Revenue Dataset’, 2018, https://www.wider.unu.edu/project/government-revenue-dataset' ICTD Government Revenue Dataset, 2018 A major obstacle to cross-country research on the role of revenue and taxation in development has been the weakness of available data. Government Revenue Dataset (GRD), developed through the International Centre for Tax and Development (ICTD), is aimed at overcoming this obstacle. It meticulously combines data from several major international databases, as well as drawing on data compiled from all available International Monetary Fund (IMF) Article IV reports. It achieves marked improvements in data coverage and accuracy, including a standardized approach to revenue from natural resources, and holds the promise of significant improvement in the credibility and robustness of research in this area. Dataset contains Central, General and merged government revenue data reported as % of GDP.
    • अक्तूबर 2019
      Source: International Monetary Fund
      Uploaded by: Knoema
      Accessed On: 23 अक्तूबर, 2019
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      The World Economic Outlook (WEO) database contains selected macroeconomic data series from the statistical appendix of the World Economic Outlook report, which presents the IMF staff's analysis and projections of economic developments at the global level, in major country groups and in many individual countries. The WEO is released in April and September/October each year.
    • फरवरी 2019
      Source: Heritage Foundation
      Uploaded by: Knoema
      Accessed On: 04 फरवरी, 2019
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      Data cited at: Heritage Foundation   Economic freedom is the fundamental right of every human to control his or her own labor and property. In an economically free society, individuals are free to work, produce, consume, and invest in any way they please, with that freedom both protected by the state and unconstrained by the state. In economically free societies, governments allow labor, capital and goods to move freely, and refrain from coercion or constraint of liberty beyond the extent necessary to protect and maintain liberty itself. Economic Freedom Scores: Range and level of freedom 80–100:- Free 70–79.9:- Mostly Free 60–69.9:- Moderately Free 50–59.9:- Mostly Unfree 0–49.9:- Repressed
    • दिसम्बर 2018
      Source: U.S. Department of Agriculture
      Uploaded by: Knoema
      Accessed On: 26 दिसम्बर, 2018
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      The International Macroeconomic Data Set provides historical and projected data for 189 countries that account for more than 99 percent of the world economy. These macroeconomic data and projections are assembled explicitly to serve as underlying assumptions for the annually updated USDA agricultural supply and demand projections, which provide a 10-year outlook on U.S. and global agriculture. The macroeconomic projections describe the long-term scenario that is used as a benchmark for analyzing the impacts of alternative scenarios and macroeconomic shocks.  The projections assume there are no changes in policy and abstract from business cycle effects.  Historical data are available for real (inflation-adjusted) gross domestic product (GDP), inflation, population, and real exchange rates from 1969 to the most recent available year, and each variable is projected forward to 2030.
    • जून 2013
      Source: United Nations Conference on Trade and Development
      Uploaded by: Knoema
      Accessed On: 22 जुलाई, 2013
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      Time series on international reserves (including gold), by individual country, expressed in millions of dollars. It further presents the number of months of merchandise imports that these reserves could finance at current imports level, as well as annual changes in total reserves.
    • अक्तूबर 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2019
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  • K
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 अक्तूबर, 2019
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      The Key Economic Indicators (KEI) database contains monthly and quarterly statistics (and associated statistical methodological information) for all OECD member countries and for a selection of non-member countries on a wide variety of economic indicators, namely: quarterly national accounts, industrial production, composite leading indicators, business tendency and consumer opinion surveys, retail trade, consumer and producer prices, hourly earnings, employment/unemployment, interest rates, monetary aggregates, exchange rates, international trade and balance of payments.
    • मार्च 2019
      Source: European Bank for Reconstruction and Development
      Uploaded by: Sandeep Reddy
      Accessed On: 17 मई, 2019
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      The “knowledge economy” (KE) is a concept of economic development, in which innovation and access to information drive productivity growth. New trends, such as the Internet of Things or digitalisation, are examples of the transition towards to the knowledge economy. Building the key pillars required to stimulate knowledge-economy development is therefore central to achieving long-term competitiveness. To measure KE development, the European Bank for Reconstruction and Development (EBRD) has constructed the EBRD Knowledge Economy Index, spanning 46 economies – 38 where the EBRD invests and eight comparators.
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    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 अक्तूबर, 2019
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      This dataset 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.
    • दिसम्बर 2018
      Source: United Nations Statistics Division
      Uploaded by: Knoema
      Accessed On: 04 मार्च, 2019
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      The National Accounts Main Aggregates Database presents a series of analytical national accounts tables from 1970 onwards for more than 200 countries and areas of the world. It is the product of a global cooperation effort between the Economic Statistics Branch of the United Nations Statistics Division, international statistical agencies and the national statistical services of these countries and is developed in accordance with the recommendation of the Statistical Commission at its first session in 1947 that the Statistics Division should publish regularly the most recent available data on national accounts for as many countries and areas as possible. The database is updated in December of each year with newly available national accounts data for all countries and areas.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 23 जुलाई, 2019
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      It presents the three approaches of the GDP: expenditure based, output based and income based. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA.
    • नवम्बर 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 13 नवम्बर, 2019
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      The non-financial Quarterly Sector Accounts (QSA) are compiled in accordance with the European System of Accounts (ESA 2010) and are transmitted by the EU Member States and EEA Members (Norway, Iceland) following ESA2010 transmission programme (Table 801) established by the Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013 on the European system of national and regional accounts in the European Union, annexes A and B respectively). The QSA encompass non-financial accounts that provide a description of the different stages of the economic process: production, generation of income, distribution of income, redistribution of income, use of income and non-financial accumulation. The ASA record the economic flows of institutional sectors in order to illustrate their economic behaviour and interactions between them. They also provide a list of balancing items that have high analytical value in their own right: value added, operating surplus and mixed income, balance of primary incomes, disposable income, saving, net lending / net borrowing. All of them but net lending / net borrowing, can be expressed in gross or net terms, i.e. with and without consumption of fixed capital that accounts for the use and obsolescence of fixed assets. In terms of institutional sectors, a broad distinction is made between the domestic economy (ESA 2010 classification code S.1) and the rest of the world (S.2). Within S.1 and S.2, in turn, more detailed subsectors are distinguished as explained in more detail in section "3.2 Classification system". Data are presented in the table "Non-financial transactions" (nasq_10_nf_tr). The table contains data, as far as they are available, expressed in national currency and millions of euro in current prices. In line with ESA2010 Transmission programme requirements data series start from 1999 Q1 (unless subject to voluntary transmission option and/or country specific derogations). Available level of detail by sectors and transactions may also vary by country due to voluntary transmission of some items (as defined in ESA2010 transmission programme) and country specific derogations. QSA collected according ESA2010 Transmission programme include selected data on employment (in persons and hours worked) and seasonally adjusted variables by institutional sectors. However, as transmission of these variables is voluntary (except for the selected seasonally adjusted variables of Total economy and the Rest of the world), data availability may vary significantly across countries. A set of key indicators, deemed meaningful for economic analysis, is available in the table "Key indicators" (nasq_10_ki) for most of the members of the European Economic Area (EEA), of the Euro area and EU. Key ratios are derived from non-financial transactions as follows:Gross household saving rate (S.14_S.15): B8G/(B6G+D8rec-D8pay)*100Gross investment rate of households (S.14_S.15): P51G/(B6G+D8rec-D8pay)*100Gross investment rate of non-financial corporations (S.11): P51G/B1G*100Gross profit share of non-financial corporations (S.11): B2G_B3G/B1G*100 With the following transaction codes:B6G - Gross disposable incomeB8G -  Gross savingD8rec / D8pay - the adjustment for the change in pension entitlements (receivable / payable)P51G - Gross fixed capital formationB1G - Gross value addedB2G_B3G - Gross operating surplus/ mixed income. The following key indicators are calculated in real terms for European aggregates only: Gross disposable income of households in real terms (B6G, percentage change on previous period, S.14_S.15)Real growth of household adjusted disposable income per capita (percentage change on previous period, S.14_S.15): B7G/(POP_NC*Price Deflator)Real growth of household actual consumption per capita (percentage change on previous period, S.14_S.15): P4/(POP_NC*Price Deflator) With the following codes (the codes already described above have not been listed): B7G - Gross adjusted gross disposable income (adjusted for social transfers in kind)P4 - Actual final consumption (adjusted for social transfers in kind)POP_NC - Total population national concept (source:Quarterly national accounts, Eurobase domain namq_10_pe)Price deflator - Price index/implicit deflator calculated as CP_MEUR/CLV05_MEUR – both indicators refer to households and NPISH final consumption expenditure (P31_S14_S15) (source: Quarterly national accounts, Eurobase domain namq_10_gdp) In the above, all ratios are expressed in gross terms, i.e. before deduction of consumption of fixed capital. The following key indicators combine non-financial with financial accounts:Household net financial assets ratio (BF90/(B6G+D8net)) With the following codes (the codes already described above have not been listed):BF90 – Financial net worth "rec" means resources, that is transactions that add to the economic value of a given sector. "pay" means "uses", that is transactions that reduce the economic value of a given sector. "liab" refers to the stock of liabilities incurred by a given sector and recorded in the financial balance sheets. See also the sector accounts dedicated website for more information.
    • अक्तूबर 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 03 नवम्बर, 2019
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      The non-financial Annual Sector Accounts (ASA) are compiled in accordance with the European System of Accounts (ESA 2010) and are transmitted by the EU Member States, EEA Members (Norway, Iceland) and Switzerland following ESA2010 transmission programme (Table 8) established by the Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013 on the European system of national and regional accounts in the European Union, annexes A and B respectively). The ASA encompass non-financial accounts that provide a description of the different stages of the economic process: production, generation of income, distribution of income, redistribution of income, use of income and non-financial accumulation. The ASA record the economic flows of institutional sectors in order to illustrate their economic behaviour and interactions between them. They also provide a list of balancing items that have high analytical value in their own right: value added, operating surplus and mixed income, balance of primary incomes, disposable income, saving, net lending / net borrowing. All of them but net lending / net borrowing, can be expressed in gross or net terms, i.e. with and without consumption of fixed capital that accounts for the use and obsolescence of fixed assets. In terms of institutional sectors, a broad distinction is made between the domestic economy (ESA 2010 classification code S.1) and the rest of the world (S.2). Within S.1 and S.2, in turn, more detailed subsectors are distinguished as explained in more detail in section "3.2 Classification system". Data are presented in the table "Non-financial transactions" (nasa_10_nf_tr). The table contains data, as far as they are available, expressed in national currency and millions of euro in current prices. In line with ESA2010 Transmission programme requirements data series start from 1995 (unless subject to voluntary transmission option and/or country specific derogations). Countries may transmit longer series on voluntary basis. Available level of detail by sectors and transactions may also vary by country due to voluntary transmission of some items (as defined in ESA2010 transmission programme) and country specific derogations. ASA collected according ESA2010 Transmission programme include selected data on employment (in persons and hours worked) by institutional sectors. However, as transmission of these variables is voluntary (except for the sector of General government), data availability may vary significantly across countries. A set of key indicators, deemed meaningful for economic analysis, is available in the table "Key indicators" (nasa_10_ki) for most of the members of the European Economic Area (EEA), of the Euro area and EU. Key ratios are derived from non-financial transactions as follows: Gross household saving rate (S.14_S.15): B8G/(B6G+D8rec-D8pay)*100Gross investment rate of households (S.14_S.15): P51G/(B6G+D8rec-D8pay)*100Gross investment rate of non-financial corporations (S.11): P51G/B1G*100Gross profit share of non-financial corporations (S.11): B2G_B3G/B1G*100Total investment to GDP ratio (S.1): P51G/B1GQ*100Business investment to GDP ratio: (S.11_P51G+S.12_P51G)/B1GQ*100Government investment to GDP ratio: S.13_P51G/B1GQ*100Households investment to GDP ratio: (S.14_S.15_P51G)/B1GQ*100 With the following transaction codes: B8G -  Gross savingB6G - Gross disposable incomeD8rec / D8pay - the adjustment for the change in pension entitlements (receivable / payable)P51G - Gross fixed capital formationB1G - Gross value addedB1GQ – Gross domestic productB2G_B3G - Gross operating surplus/ mixed income. In the above, all ratios are expressed in gross terms, i.e. before deduction of consumption of fixed capital. The following key indicators are calculated in real or nominal terms: Real growth of household adjusted disposable income per capita (percentage change on previous period, S.14_S.15): B7G/(POP_NC*Price Deflator)Nominal growth of household adjusted disposable income per capita (percentage change on previous period, S.14_S.15): B7G/(POP_NC)Real growth of household actual consumption per capita (percentage change on previous period, S.14_S.15): P4/(POP_NC*Price Deflator) With the following codes (the codes already described above have not been listed): B7G - Gross adjusted gross disposable income (adjusted for social transfers in kind)P4 - Actual final consumption (adjusted for social transfers in kind)POP_NC - Total population national concept (source:Quarterly national accounts, Eurobase domain namq_10_pe)Price deflator - Price index/implicit deflator calculated as CP_MEUR/CLV10_MEUR – both indicators refer to households and NPISH final consumption expenditure (P31_S14_S15) (source: Quarterly national accounts, Eurobase domain namq_10_gdp) The following key indicators combine non-financial with financial accounts: Gross return on capital employed, before taxes, of non-financial corporations (S.11): [B2G_B3G/(AF2+AF3+AF4+AF5, liab)]*100Net debt-to-income ratio, after taxes, of non-financial corporations (S.11): ([(AF2+AF3+AF4, liab)/(B4N-D5pay)]*100)Net return on equity, after taxes, of non-financial corporations (S.11): [(B4N-D5pay)/(AF5, liab)]*100Gross debt-to-income ratio of households (S.14_15): [(AF4, liab)/(B6G+D8net)]*100Household net financial assets ratio (BF90/(B6G+D8net)) With the following codes (the codes already described above have not been listed): B4N - Net entrepreneurial incomeD5pay - Current taxes on income and wealthAF2 - Currency and depositsAF3 - Debt securities (excluding financial derivatives)AF4 - LoansAF5 - Equity and investment fund sharesBF90 – Financial net worth "rec" means resources, that is transactions that add to the economic value of a given sector. "pay" means "uses", that is transactions that reduce the economic value of a given sector. "liab" refers to the stock of liabilities incurred by a given sector and recorded in the financial balance sheets. See also the sector accounts dedicated website for more information.
    • फरवरी 2019
      Source: The National Committee on North Korea
      Uploaded by: Knoema
      Accessed On: 12 अगस्त, 2019
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  • O
    • अक्तूबर 2015
      Source: International Monetary Fund
      Uploaded by: Sandeep Reddy
      Accessed On: 27 अक्तूबर, 2015
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      Commodity prices have declined sharply over the past three years, and output growth has slowed considerably among those emerging market and developing economies that are net exporters of commodities. A critical question for policymakers in these countries is whether commodity windfall gains and losses influence potential output or merely trigger transient fluctuations of actual output around an unchanged trend for potential output. The analysis in this chapter suggests that both actual and potential output move together with the commodity terms of trade but that actual output commoves twice as strongly as potential output. The weak commodity price outlook is estimated to subtract almost 1 percentage point annually from the average rate of economic growth in commodity exporters over 2015–17 as compared with 2012–14. In exporters of energy commodities, the drag is estimated to be larger: about 2¼ percentage points on average over the same period. The projected drag on the growth of potential output is about one-third of that for actual output.
    • नवम्बर 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 12 नवम्बर, 2019
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  • P
    • फरवरी 2012
      Source: Center for International Comparisons at the University of Pennsylvania
      Uploaded by: Knoema
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      Benchmark data used in the component price level estimates for past PWTs. The published record of benchmark comparisons includes regional and world comparisons. These are described through 1985 in publications of the World Bank, including the published comparisons of the Penn group. The Penn World Table provides purchasing power parity and national income accounts converted to international prices for 189 countries/territories for some or all of the years 1950-2010.  Its expenditure entries are denominated in a common set of prices in a common currency so that real quantity comparisons can be made, both between countries and over time. It also provides information about relative prices within and between countries, as well as demographic data and capital stock estimates. The Penn World Table grew out of the United Nations International Comparison Programme (ICP) that was jointly directed by Irving Kravis at Penn through the first three phases ending with 1975 comparison (Kravis, Heston and Summers, 1982). PWT 7.1 Alan Heston, Robert Summers and Bettina Aten, Penn World Table Version 7.1, Center for International Comparisons of Production, Income and Prices at the University of Pennsylvania, Nov 2012.
    • अप्रैल 2019
      Source: University of Groningen, Netherlands
      Uploaded by: Knoema
      Accessed On: 23 मई, 2019
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      PWT version 9.1 is a database with information on relative levels of income, output, input and productivity, covering 182 countries between 1950 and 2017.
    • मई 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 31 मई, 2019
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    • नवम्बर 2019
      Source: International Monetary Fund
      Uploaded by: Knoema
      Accessed On: 08 नवम्बर, 2019
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      The Principal Global Indicators (PGI) dataset provides internationally comparable data for the Group of 20 economies (G-20) and economies with systemically important financial sectors that are not members of the G-20. The PGI facilitates the monitoring of economic and financial developments for these jurisdictions. Launched in 2009, the PGI website is hosted by the IMF and is a joint undertaking of the Inter-Agency Group of Economic and Financial Statistics (IAG).
    • अप्रैल 2015
      Source: International Monetary Fund
      Uploaded by: Shakthi Krishnan
      Accessed On: 13 अगस्त, 2015
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      Private fixed investment in advanced economies contracted sharply during the global financial crisis, and there has been little recovery since. Investment has generally slowed more gradually in the rest of the world. Although housing investment fell especially sharply during the crisis, business investment accounts for the bulk of the slump, and the overriding factor holding it back has been the overall weakness of economic activity. In some countries, other contributing factors include financial constraints and policy uncertainty. These findings suggest that addressing the general weakness in economic activity is crucial for restoring growth in private investment.
    • जून 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 जून, 2019
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      The OECD Indicators of Product Market Regulation (PMR) are a comprehensive and internationally-comparable set of indicators that measure the degree to which policies promote or inhibit competition in areas of the product market where competition is viable. They measure the economy-wide regulatory and market environments in 34 OECD countries in (or around) 1998, 2003, 2008 and 2013, and in another set of non-OECD countries in 2013. They are consistent across time and countries. Users of the data must be aware that they may no longer fully reflect the current situation in fast reforming countries. The indicators cover formal regulations in the following areas: state control of business enterprises; legal and administrative barriers to entrepreneurship; barriers to international trade and investment. Not all data are available for all countries for all years.
    • अप्रैल 2019
      Source: Inter-American Development Bank
      Uploaded by: Knoema
      Accessed On: 26 जून, 2019
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      Public Debt around the World
  • R
    • मार्च 2018
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 29 मार्च, 2018
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      The REER (or Relative price and cost indicators) aim to assess a country's (or currency area's) price or cost competitiveness relative to its principal competitors in international markets. Changes in cost and price competitiveness depend not only on exchange rate movements but also on cost and price trends. The specific REER for the Sustainable Development Indicators is deflated by nominal unit labour costs (total economy) against a panel of 37 countries (= EU28 + 9 other industrial countries: Australia, Canada, United States, Japan, Norway, New Zealand, Mexico, Switzerland, and Turkey). Double export weights are used to calculate REERs, reflecting not only competition in the home markets of the various competitors, but also competition in export markets elsewhere. A rise in the index means a loss of competitiveness.
    • अक्तूबर 2015
      Source: International Monetary Fund
      Uploaded by: Knoema
      Accessed On: 27 अक्तूबर, 2015
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      Global growth declined in the first half of 2015, reflecting a further slowdown in emerging markets and a weaker recovery in advanced economies. It is now projected at 3.1 percent for 2015 as a whole, slightly lower than in 2014, and 0.2 percentage point below the forecasts in the July 2015 World Economic Outlook (WEO) Update. Prospects across the main countries and regions remain uneven. Relative to last year, growth in advanced economies is expected to pick up slightly, while it is projected to decline in emerging market and developing economies. With declining commodity prices, depreciating emerging market currencies, and increasing financial market volatility, downside risks to the outlook have risen, particularly for emerging market and developing economies. Global activity is projected to gather some pace in 2016. In advanced economies, the modest recovery that started in 2014 is projected to strengthen further. In emerging market and developing economies, the outlook is projected to improve: in particular, growth in countries in economic distress in 2015 (including Brazil, Russia, and some countries in Latin America and in the Middle East), while remaining weak or negative, is projected to be higher next year, more than offsetting the expected gradual slowdown in China.
    • जून 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 जून, 2019
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      The OECD cross-section sectoral indicators measure regulatory conditions in the professional services and retail distribution sectors. The retail indicators cover barriers to entry, operational restrictions, and price controls. These indicators were updated and revised; they are now estimated for 34 OECD countries for the years 1998, 2003, around 2008 and 2013 and for another set of non-OECD countries for 2013. Users of the data must be aware that they may no longer fully reflect the current situation in fast reforming countries. Not all data are available for all countries for all years.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 जुलाई, 2019
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  • S
    • जुलाई 2017
      Source: Johannes Kepler University
      Uploaded by: Knoema
      Accessed On: 12 मार्च, 2019
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      Data cited at: Shadow Economies around the World: New Results for 158 Countries over 1991-2015 by Friedrisch SCHNEIDER. Working Paper No. 1710 July 2017   Abstract: This paper is a first attempt to estimate the size and development of the shadow economy of 158 countries over the period 1991 up to 2015. Using the Multiple Indicators, Multiple Causes (MIMIC) method we apply for the first time (i) the light intensity approach instead of GDP avoiding the problem that quite often GDP is used as a cause and indicator variable, (ii) the Predictive Mean Matching (PMM) method, and (iii) a variety of robustness tests. Results suggest that the average size of the shadow economy of these 158 countries over 1991-2015 is 32.5% of official GDP, which was 34.82% in 1991 and decreased to 30.66% in 2015. The lowest size of the shadow economy East Asian countries with 16.77% averaged over the period 1991- 2015, then follows OECD countries with 18.7% and the highest value have Latin American and sub-Saharan African countries with values above 35%.
    • जनवरी 2015
      Source: Johannes Kepler University
      Uploaded by: Knoema
      Accessed On: 18 अक्तूबर, 2016
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      Data citation: Schneider, Friedrich & Schneider, Friedrich. (2013). Size and Development of the Shadow Economy of 31 European and 5 other OECD Countries from 2003 to 2012: Some New Facts.  The calculation of the size and development of the shadow economy is done with the MIMIC (Multiple Indicators and Multiple Courses) estimation procedure. Using the MIMIC estimation procedure one gets only relative values and one needs other methods like the currency demand approach or the income discrepancy method, to calibrate the MIMIC values into absolute ones. The calculated values for 2014 are projections for some countries, for 2015 they are projections for all countries, based on the forecasts of the official figures (GDP, unemployment, etc.) of these countries.
    • दिसम्बर 2015
      Source: Office of National Statistics, Mauritania
      Uploaded by: Knoema
      Accessed On: 11 जनवरी, 2019
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      Data cited at: https://mauritania.opendataforafrica.org/MRSCD2015
    • जून 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 04 जून, 2019
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      Recommended uses and limitations of STAN It is recommended that STAN is primarily used for broad analyses, particularly at the detailed level where many of the data points are estimated. For example, looking at trends or average growth rates and shares over a few years or general modelling. This also applies to any indicators that may be calculated (see Annex. 2 in the full documentation for examples). Where the data points are official National Accounts (often at more aggregate industry levels) there is more scope for precise analyses such as looking at year-on-year growth rates. STAN is based on data that Member countries provide. Detailed data collections independent of national statistical offices are not performed. In other words, we do not have the scope to build up National Accounts compatible tables from detailed data using consistent methodologies across countries. Therefore, when comparing variables or indicators across countries, users should refer to the STAN country notes to check for industry inclusions and variable definitions. Some comprises may be necessary in terms of the level of detail analysed.
    • जून 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 05 जून, 2019
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      The subnational government finance dataset presents data on the institutional organisation at local and regional levels as well as on public finance. Financial data cover the general government sector and subnational government subsector (state and local government levels) in the 35 OECD member countries and in the EU. Four main dimensions are presented: expenditure (including investment), revenue, budget balance and debt. The dataset is released as a beta version. Data at country level are derived mainly from the OECD National Accounts harmonised according to the new standards of the System of National Accounts (SNA) 2008, implemented by most OECD countries since December 2014. They are complemented by data from Eurostat, IMF (Australia, Chile), and national statistical institutes for some countries or indicators (in particular, territorial organisation). Data were extracted in February 2017 and are from 2015, unless otherwise specified
  • T
    • जनवरी 2018
      Source: RAND Corporation
      Uploaded by: Knoema
      Accessed On: 24 जनवरी, 2018
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      Given the potential adverse effects of insufficient sleep on health, well-being and productivity, the consequences of sleep-deprivation have far-reaching economic consequences. Hence, in order to raise awareness of the scale of insufficient sleep as a public-health issue, comparative quantitative figures need to be provided for policy- and decision-makers, as well as recommendations and potential solutions that can help tackling the problem.
    • अप्रैल 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 12 अप्रैल, 2019
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      Because of the limited availability of official statistics on national supply-use and input-output tables in recent years – reflecting the fact that these are only typically available at best two or three years after the reference period to which they refer – TiVA indicators for the most recent years, as displayed in this dataset, are estimated using now-casting techniques. The approach (described in more detail in the accompanying methodological note) in essence estimates national input-output tables by projecting relationships observed in the latest TiVA benchmark year (currently 2011) into nowcast years (currently 2012-2014) but constrained to official estimates of gross output and value-added by industry and national accounts main aggregates of demand and trade, and supplemented by bilateral trade statistics, all of which are available throughout the nowcast period. Importantly, the projections of relationships in 2011 into 2012 are determined using a volume approach, to account for possible distortions that might be introduced – by for example differential price movements in imports and domestic production – if projections were made using nominal relationships. These estimates are then reflated into current prices, and simultaneously balanced – consistent with official volume and current price estimates of trade, demand and activity – to arrive at a balanced national input-output table in 2012, in nominal terms as well as in prices of 2011. Estimates for 2013 and 2014 are calculated in the same manner but using, respectively, the 2012 and 2013 relationships as the starting point.
    • सितम्बर 2019
      Source: Statistics Canada
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2019
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  • W
    • जून 2018
      Source: World Economics and Politics (WEP) Dataverse
      Uploaded by: Knoema
      Accessed On: 25 सितम्बर, 2018
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      Data cited at: World Economics and Politics (WEP) Dataverse   World Economic and Politics dataverse- 1800 to 2017
    • अप्रैल 2019
      Source: International Monetary Fund
      Uploaded by: Sandeep Reddy
      Accessed On: 26 अप्रैल, 2019
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      The WHD Regional Economic Outlook (REO) provides information on recent economic developments and prospects for countries in the Western Hemisphere. Data for the Western Hemisphere REO are prepared in conjunction and are consistent with the semi-annual World Economic Outlook (WEO) exercises. REO aggregate data may differ from WEO aggregates due to differences in group membership. Composite data for country groups are weighted averages of data for individual countries. Arithmetic weighted averages are used for all concepts except for inflation and broad money, for which geometric averages are used. PPP GDP weights from the WEO database are used for the aggregation of real GDP growth, real non-oil GDP growth, real per capita GDP growth, investment, national savings, broad money, claims on the nonfinancial private sector, and real and nominal effective exchange rates. Aggregates for other concepts are weighted by GDP in U.S. dollars at market exchange rates.
    • फरवरी 2018
      Source: World Input-Output Database
      Uploaded by: Knoema
      Accessed On: 16 फरवरी, 2018
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      Data cited at: World Input-Output Database http://www.wiod.org/home Topic: Socio - Economic Accounts Publication: http://www.wiod.org/database/seas16 License: https://creativecommons.org/licenses/by/4.0/   Basic data on output and employment, World Input-Output Database (WIOD) database, February 2018 released. The Socio-economic accounts contain industry-level data on employment, capital stocks, gross output and value added at current and constant prices. The industry classification is the same as for the world input-output tables. Reference: Timmer, M. P., Dietzenbacher, E., Los, B., Stehrer, R. and de Vries, G. J. (2015),  "An Illustrated User Guide to the World Input–Output Database: the Case of Global Automotive Production",  Review of International Economics., 23: 575–605
    • नवम्बर 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 12 नवम्बर, 2019
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      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Global Economic Monitor Publication: https://datacatalog.worldbank.org/dataset/global-economic-monitor License: http://creativecommons.org/licenses/by/4.0/   The dataset Provides daily updates of global economic developments, with coverage of high income- as well as developing countries. Average period data updates are provided for exchange rates, equity markets, interest rates, stripped bond spreads, and emerging market bond indices. Monthly data coverage (updated daily and populated upon availability) is provided for consumer prices, high-tech market indicators, industrial production and merchandise trade.
    • दिसम्बर 2016
      Source: International Monetary Fund
      Uploaded by: Knoema
      Accessed On: 20 मार्च, 2017
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      The World Commodity Exporters Database is a collection of key macro-fiscal  indicators covering 52 countries that are exporters of oil, gas, and metals (such as copper, gold, iron, and silver), where these commodities represent a large share of exports (20 percent or more of total exports) or fiscal revenues. The dataset was compiled from the following sources:  International Financial Statistics (IFS), Balance of Payments Statistics, Direction of Trade Statistics, World Economic Outlook, and FAD’s fiscal rules. Data for all variables of interest are collected on an annual basis from 1970 to 2014, where available.
    • अक्तूबर 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2019
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      The primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates
    • मार्च 2019
      Source: United Nations Department of Economic and Social Affairs
      Uploaded by: Knoema
      Accessed On: 22 मार्च, 2019
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      Note: World Economic Situation and Prospects (WESP) mid-year update available here: https://knoema.com/WESP2019JUN/world-economic-situation-and-prospects-mid-2019 Economic growth accelerated in more than half the world’s economies in both 2017 and 2018. Developed economies expanded at a steady pace of 2.2 per cent in both years, and growth rates in many countries have risen close to their potential, while unemployment rates in several developed economies have dropped to historical lows. Among the developing economies, the regions of East and South Asia remain on relatively strong growth trajectory, expanding by 5.8 per cent and 5.6 per cent, respectively in 2018. Many commodityexporting countries, notably fuel exporters, are continuing a gradual recovery, although they remain exposed to volatile prices. The impact of the sharp drop in commodity markets in 2014/15 also continues to weigh on fiscal and external balances and has left a legacy of higher levels of debt. Global economic growth remained steady at 3.1 per cent in 2018, as a fiscally induced acceleration in the United States of America offset slower growth in some other large economies. Economic activity at the global level is expected to expand at a solid pace of 3 per cent in 2019, but there are increasing signs that growth may have peaked. The growth in global industrial production and merchandise trade volumes has been tapering since the beginning of 2018, especially in trade-intensive capital and intermediate goods sectors. Leading indicators point to some softening in economic momentum in many countries in 2019, amid escalating trade disputes, risks of financial stress and volatility, and an undercurrent of geopolitical tensions. At the same time, several developed economies are facing capacity constraints, which may weigh on growth in the short term.
    • अक्तूबर 2019
      Source: Economic Policy Uncertainty
      Uploaded by: Knoema
      Accessed On: 03 अक्तूबर, 2019
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      Data cited at: World Uncertainty Index (WUI), developed by Hites Ahir (International Monetary Fund), Nicholas Bloom (Stanford University) and Davide Furceri (International Monetary Fund).
  • И
    • सितम्बर 2018
      Source: Federal State Statistics Service, Russia
      Uploaded by: Knoema
      Accessed On: 14 दिसम्बर, 2018
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      Методологические пояснения: Валовой внутренний продукт (ВВП) по паритету покупательной способности (ППС) - Объем ВВП стран, выраженный в национальной валюте, пересчитан в единую валюту, используя паритет покупательной способности (ППС). Также применяется выражение ВВП в реальном выражении по аналогии с похожей практикой выражения стоимостных показателей в ценах другого года. (последняя версия - Международные сопоставления валового внутреннего продукта за 2005 год: Стат. сб./ Росстат. – M., 2008. стр.15, расчетный показатель) Комментарий: Данные предоставляются на 5-й рабочий день после публикации результатов сопоставлений ОЭСР Ведомство (субъект статистического учета): Федеральная служба государственной статистики Размещение: Информация о результатах международных сопоставлений валового внутреннего продукта, координируемых Организаций экономического сотрудничества и развития (ОЭСР) и Евростатом (за год, принятый за базу сопоставлений) Источники и способ формирования показателя: Расчет
    • सितम्बर 2018
      Source: Federal State Statistics Service, Russia
      Uploaded by: Knoema
      Accessed On: 14 दिसम्बर, 2018
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      Методологические пояснения: Для проведения международных сопоставлений ВВП необходимо иметь данные о стоимостных объемах на уровне первичных групп товаров и услуг. Разбивка национальных расходов ВВП на первичные товарные группы основывается на двух критериях. Во-первых, первичные группы должны быть как можно более однородными, чтобы свести к минимуму разброс отдельных значений цен по странам внутри каждой первичной группы. Во-вторых, необходимо получить достаточно надежные данные о расходах по каждой первичной группе. Проведение сопоставлений осуществляется по международному графику, в котором отмечены последние сроки представления и согласования данных. Все результаты сопоставлений ВВП основываются на информации, представленной странами. Все изменения в национальных данных после окончательных сроков представления в соответствии с графиком работ не использовались в расчетах. (Последняя версия - Международные сопоставления валового внутреннего продукта за 2005 год: Стат. сб./ Росстат. – M., 2008. стр.17, 26, расчетный показатель). Комментарий: Данные предоставляются на 5-й рабочий день после публикации результатов сопоставлений ОЭСР Ведомство (субъект статистического учета): Федеральная служба государственной статистики Размещение: Информация о результатах международных сопоставлений валового внутреннего продукта, координируемых Организаций экономического сотрудничества и развития (ОЭСР) и Евростатом (за год, принятый за базу сопоставлений) Источники и способ формирования показателя: Расчет
  • П
    • सितम्बर 2018
      Source: Federal State Statistics Service, Russia
      Uploaded by: Knoema
      Accessed On: 14 दिसम्बर, 2018
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      Методологические пояснения: Паритет покупательной способности (ППС) представляет собой количество единиц валюты, необходимое для покупки стандартного набора товаров и услуг, который можно купить за одну денежную единицу базовой страны (или одну единицу общей валюты группы стран). ППС представляют собой переводные коэффициенты, которые элиминируют различия в уровне цен между странами в процессе пересчета, т. е. ППС являются одновременно и дефляторами, и инструментами пересчета денежных единиц в сопоставимую валюту. (последняя версия - Международные сопоставления валового внутреннего продукта за 2005 год: Стат. сб./ Росстат. – M., 2008. стр.13-14 , расчетный показатель) Комментарий: Данные предоставляются на 5-й рабочий день после публикации результатов сопоставлений ОЭСР Ведомство (субъект статистического учета): Федеральная служба государственной статистики Размещение: Информация о результатах международных сопоставлений валового внутреннего продукта, координируемых Организаций экономического сотрудничества и развития (ОЭСР) и Евростатом (за год, принятый за базу сопоставлений) Источники и способ формирования показателя: Расчет
  • Р
    • अक्तूबर 2018
      Source: Federal State Statistics Service, Russia
      Uploaded by: Knoema
      Accessed On: 14 दिसम्बर, 2018
      Select Dataset
      Методологические пояснения: Валовой внутренний продукт  (ВВП) на душу населения по паритету покупательной способности (ППС) - ВВП по ППС или в реальном выражении, рассчитанный на душу населения.  (последняя версия - Международные сопоставления валового внутреннего продукта за 2005 год: Стат. сб./ Росстат. – M., 2008. стр.15, расчетный показатель) Комментарий: Данные предоставляются на 5-й рабочий день после публикации результатов сопоставлений ОЭСР Ведомство (субъект статистического учета): Федеральная служба государственной статистики Размещение: Информация о результатах международных сопоставлений валового внутреннего продукта, координируемых Организаций экономического сотрудничества и развития (ОЭСР) и Евростатом (за год, принятый за базу сопоставлений) Источники и способ формирования показателя: Расчет
  • С
    • सितम्बर 2018
      Source: Federal State Statistics Service, Russia
      Uploaded by: Knoema
      Accessed On: 14 दिसम्बर, 2018
      Select Dataset
      Методологические пояснения: Сопоставимый уровень цен - отношение паритета покупательной способности (ППС ) к валютному курсу. Различие между ППС и валютным курсом используется в качестве критерия выявления «более дешевых» или «более дорогих» стран по сравнению с другой страной.(последняя версия - Международные сопоставления валового внутреннего продукта за 2005 год: Стат. сб./ Росстат. – M., 2008. стр.15, расчетный показатель. Комментарий: Данные предоставляются на 5-й рабочий день после публикации результатов сопоставлений ОЭСР Ведомство (субъект статистического учета): Федеральная служба государственной статистики Размещение: Информация о результатах международных сопоставлений валового внутреннего продукта, координируемых Организаций экономического сотрудничества и развития (ОЭСР) и Евростатом (за год, принятый за базу сопоставлений) Источники и способ формирования показателя: Расчет
    • सितम्बर 2018
      Source: Federal State Statistics Service, Russia
      Uploaded by: Knoema
      Accessed On: 14 दिसम्बर, 2018
      Select Dataset
      Методологические пояснения: Результаты сопоставлений и их точность зависят от от структуры ВВП. Влияние структуры обусловлено национальной структурой ВВП стран-участниц. Резкие изменения в национальной структуре ВВП приводят к изменению результатов сопоставлений в ту или иную сторону. Например, как было отмечено в сопоставлениях ВВП, большое положительное сальдо чистого экспорта увеличивает показатель ВВП на душу наседления, а отрицательное - существенно уменьшает. (Последняя версия - Международные сопоставления валового внутреннего продукта за 2005 год: Стат. сб./ Росстат. – M., 2008. стр.27,  расчетный показатель). Комментарий: Данные предоставляются на 5-й рабочий день после публикации результатов сопоставлений ОЭСР Ведомство (субъект статистического учета): Федеральная служба государственной статистики Размещение: Информация о результатах международных сопоставлений валового внутреннего продукта, координируемых Организаций экономического сотрудничества и развития (ОЭСР) и Евростатом (за год, принятый за базу сопоставлений) Источники и способ формирования показателя: Расчет

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

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