An error occured. Details Hide
You have unsaved pages. Restore Cancel

China

  • President:Xi Jinping
  • Premier:Li Keqiang
  • Capital city:Beijing
  • Languages:Standard Chinese or Mandarin (official; Putonghua, based on the Beijing dialect), Yue (Cantonese), Wu (Shanghainese), Minbei (Fuzhou), Minnan (Hokkien-Taiwanese), Xiang, Gan, Hakka dialects, minority languages (see Ethnic groups entry) note: Zhuang is official in Guangxi Zhuang, Yue is official in Guangdong, Mongolian is official in Nei Mongol, Uighur is official in Xinjiang Uygur, Kyrgyz is official in Xinjiang Uygur, and Tibetan is official in Xizang (Tibet)
  • Government
  • National statistics office
  • Population, persons:1,386,395,000 (2017)
  • Area, sq km:9,388,211 (2017)
  • GDP per capita, US$:8,827 (2017)
  • GDP, billion current US$:12,237.7 (2017)
  • GINI index:42.2 (2012)
  • Ease of Doing Business rank:78 (2017)
All datasets:  A B C D E F G H I K N O P R S T U W
  • A
    • October 2018
      Source: International Monetary Fund
      Uploaded by: Knoema
      Accessed On: 31 October, 2018
      Select Dataset
      APD Regional Economic Outlook (REO) provides information on recent economic developments and prospects for countries in Asia and Pacific. Data for the REO for Asia and Pacific is prepared in conjunction with the semi-annual World Economic Outlook (WEO) exercises, spring and fall. Data are consistent with the projections underlying the WEO. 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.
  • B
    • February 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 15 February, 2019
      Select Dataset
      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
    • January 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 January, 2019
      Select Dataset
      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.
    • April 2015
      Source: International Monetary Fund
      Uploaded by: Knoema
      Accessed On: 20 August, 2015
      Select Dataset
      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.
    • March 2012
      Source: Knoema
      Uploaded by: Knoema
      Select Dataset
      Country Risk Assessment Database, 2012. Source: Multiple Sources - EuroStat, WB, IMF, OECD, UNCTAD
  • D
    • January 2018
      Source: The Fletcher School,Tufts University
      Uploaded by: Knoema
      Accessed On: 30 August, 2018
      Select Dataset
      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.
  • E
    • September 2018
      Source: Fraser Institute
      Uploaded by: Knoema
      Accessed On: 02 November, 2018
      Select Dataset
      Data cited at: "Economic Freedom of the World: 2018 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.
    • December 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 03 December, 2018
      Select Dataset
      The OECD Long Term Baseline analyzes the major economic trends beyond the OECD short-term projections. For all OECD economies, and the major non-OECD economies, it provides coverage of components of potential growth, fiscal balances and debt accumulation, domestic saving and investment balances, and external balances (through the current account). It also includes interest rates consistent with those projections. The database contains annual data to 2060. 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 Annual National Accounts, the International Monetary Fund, the United Nations, and Eurostat.
    • June 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 26 September, 2018
      Select Dataset
    • August 2011
      Source: Multiple Sources
      Uploaded by: Knoema
      Select Dataset
      A compilation of monthly closing stock indices for major stock exchanges across the World. This dataset is updated on a monthly basis.
    • October 2015
      Source: International Monetary Fund
      Uploaded by: Knoema
      Accessed On: 22 October, 2015
      Select Dataset
      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.
    • September 2013
      Source: United Nations Conference on Trade and Development
      Uploaded by: Knoema
      Accessed On: 10 October, 2013
      Select Dataset
      This table presents information on the external long-term indebtedness of developing economies (as debtors), expressed in millions of dollars, expressed as percentage of total long-term debt, as percentage of debt source and as percentage of region. The table also provides breakdown of public and publicly guaranteed debt by source of lending (as creditors).
  • F
    • November 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 16 November, 2018
      Select Dataset
      OECD Factbook provides a global overview of today's major economic, social and environmental indicators which cover a wide range of areas: agriculture, economic production, education, energy, environment, foreign aid, health, industry, information and communications, international trade, labor force, population, taxation, public expenditure and R&D. More countries than ever are covered in greater detail, enabling direct comparisons for many indicators between OECD Members and Brazil, China, India, Indonesia, Russian Federation and South Africa.
  • G
    • February 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 11 February, 2019
      Select Dataset
      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:
    • February 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 15 February, 2019
      Select Dataset
      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:
    • January 2019
      Source: Economic Policy Uncertainty
      Uploaded by: Knoema
      Accessed On: 31 January, 2019
      Select Dataset
      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.
    • September 2018
      Source: Dual Citizen LLC
      Uploaded by: Knoema
      Accessed On: 21 September, 2018
      Select Dataset
      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.
    • June 2018
      Source: KPMG
      Uploaded by: Knoema
      Accessed On: 03 July, 2018
      Select Dataset
      Covers data on corporate, indirect and individual income tax rates throughout 163 countries across the world during the period from 2006 to 2018. Provided by KPMG.
    • January 2015
      Source: University of Groningen
      Uploaded by: Pallavi S
      Accessed On: 25 February, 2016
      Select Dataset
      The GGDC 10-Sector Database provides a long-run internationally comparable dataset on sectoral productivity performance in Asia, Europe, Latin America and the US. Variables covered in the data set are annual series of value added, output deflators, and persons employed for 10 broad sectors. It gives sectoral detail to the historical macro data in Maddison (2003) from 1950 onwards. It consists of series for 10 countries in Asia, 9 in Latin-America and 9 in Europe and the US. The data for Asia and Latin-America are based on Marcel P. Timmer and Gaaitzen J. de Vries (2007), 'A Cross-Country Database For Sectoral Employment And Productivity In Asia And Latin America, 1950-2005', GGDC Research memorandum GD-98, Groningen Growth and Development Centre, August 2007. Data for Europe and the US is based on an update of Bart van Ark (1996), Sectoral Growth Accounting and Structural Change in Post-War Europe, in B. van Ark and N.F.R. Crafts, eds., Quantitative Aspects of Post-War European Economic Growth, CEPR/Cambridge University Press, pp. 84-164. All series derived from this database need to be referred to as: "Timmer, Marcel P. and Gaaitzen J. de Vries (2009), "Structural Change and Growth Accelerations in Asia and Latin America: A New Sectoral Data Set" Cliometrica, vol 3 (issue 2) pp. 165-190."
    • February 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 11 February, 2019
      Select Dataset
      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:
    • February 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 15 February, 2019
      Select Dataset
      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:
  • H
  • I
    • July 2017
      Source: International Centre for Tax and Development
      Uploaded by: Knoema
      Accessed On: 11 October, 2017
      Select Dataset
      ICTD Government Revenue Dataset, 2017 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.
    • October 2018
      Source: International Monetary Fund
      Uploaded by: Knoema
      Accessed On: 15 October, 2018
      Select Dataset
      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. Use this database to find data on national accounts, inflation, unemployment rates, balance of payments, fiscal indicators, trade for countries and country groups (aggregates), and commodity prices whose data are reported by the IMF. Data are available from 1980 to the present, and projections are given for the next two years. Additionally, medium-term projections are available for selected indicators. For some countries, data are incomplete or unavailable for certain years.   Changes to the October 2018 DatabaseArgentina’s consumer prices, which were previously excluded from the group composites because of data constraints, are now included starting from 2017 onward.Data for Aruba are included in the data aggregated for the emerging market and developing economies. It is classified as a member of the Latin America and Caribbean.Egypt’s forecast data from which the nominal exchange rate assumptions are calculated that were previously excluded because the nominal exchange rate was a market-sensitive issue, are now made public.Swaziland is now called Eswatini.Venezuela redenominated its currency on August 20, 2018, by replacing 100,000 bolívares Fuertes (VEF) with 1 bolívar Soberano (VES). Local currency data, including the historical data, for Venezuela are expressed in the new currency beginning with the October 2018 WEO database.
    • February 2019
      Source: Heritage Foundation
      Uploaded by: Knoema
      Accessed On: 04 February, 2019
      Select Dataset
      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
    • December 2018
      Source: U.S. Department of Agriculture
      Uploaded by: Knoema
      Accessed On: 26 December, 2018
      Select Dataset
      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.
    • June 2013
      Source: United Nations Conference on Trade and Development
      Uploaded by: Knoema
      Accessed On: 22 July, 2013
      Select Dataset
      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.
  • K
    • January 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 January, 2019
      Select Dataset
      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.
  • N
    • August 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 07 August, 2018
      Select Dataset
      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.
    • December 2017
      Source: United Nations Statistics Division
      Uploaded by: Knoema
      Accessed On: 03 January, 2018
      Select Dataset
      The Economic Statistics Branch of the United Nations Statistics Division maintains this National Accounts Statistics database of main national accounts aggregates. It is the product of a global cooperation effort between the United Nations Statistics Division, international statistical agencies and the national statistical services of more than 200 countries and is in accordance with the request of the Statistical Commission that the most recent available data on national accounts of as many countries and areas as possible be published and disseminated regularly. This National Accounts Statistics database contains a complete and consistent set of time series from 1970 onwards of main national accounts aggregates for allUN Members States and all other countries and areas in the world. It is maintained and updated on the basis of annual collections of the official annual national accounts statistics supplemented by estimates of national accounts statistics for those years and countries for which the official statistics has incomplete or inconsistent information. In addition, to the values of national accounts statistics, it contains analytical indicators and ratios derived from the main national accounts aggregates related to economic structure and development.
    • January 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 17 January, 2019
      Select Dataset
      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.
    • August 2018
      Source: The National Committee on North Korea
      Uploaded by: Knoema
      Accessed On: 13 August, 2018
      Select Dataset
  • O
    • March 2014
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 March, 2014
      Select Dataset
      In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2005) - and for comparative purposes in US $ current prices and constant prices (using exchange rate and PPPs). Expressed in millions and in indices. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.
    • December 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Pallavi S
      Accessed On: 03 December, 2018
      Select Dataset
      The OECD Science, Technology and Industry Outlook 2012 presents, in a series of country profiles, the main features, strengths and weaknesses of national STI systems and major recent changes in national STI policy. The statistical dimension of the country profiles has drawn on the work and empirical research conducted by the OECD on the measurement of innovation and the development of internationally comparable STI indicators for policy analysis.
    • January 2019
      Source: International Monetary Fund
      Uploaded by: Knoema
      Accessed On: 22 January, 2019
      Select Dataset
      Real effective exchange rates are assumed to remain constant at the levels prevailing during October 29-November 26, 2018. Economies are listed on the basis of economic size. The aggregated quarterly data are seasonally adjusted. WEO = World Economic Outlook.
  • P
    • October 2017
      Source: University of Groningen
      Uploaded by: Knoema
      Accessed On: 05 October, 2018
      Select Dataset
      PWT version 9.0 is a database with information on relative levels of income, output, inputs and productivity, covering 182 countries between 1950 and 2014.
    • February 2019
      Source: International Monetary Fund
      Uploaded by: Knoema
      Accessed On: 12 February, 2019
      Select Dataset
      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).
    • April 2015
      Source: International Monetary Fund
      Uploaded by: Shakthi Krishnan
      Accessed On: 13 August, 2015
      Select Dataset
      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.
    • April 2015
      Source: International Monetary Fund
      Uploaded by: Shakthi Krishnan
      Accessed On: 12 August, 2015
      Select Dataset
      This chapter finds that potential output growth across advanced and emerging market economies has declined in recent years. In advanced economies, this decline started as far back as the early 2000s and worsened with the global financial crisis. In emerging market economies, in contrast, it began only after the crisis. The chapter’s analysis suggests that potential output growth in advanced economies is likely to increase slightly from current rates as some crisis-related effects wear off, but to remain below precrisis rates in the medium term. The main reasons are aging populations and the gradual increase in capital growth from current rates as output and investment recover from the crisis. In contrast, in emerging market economies, potential output growth is expected to decline further, owing to aging populations, weaker investment, and lower total factor productivity growth as these economies catch up to the technological frontier.
  • R
    • March 2018
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 29 March, 2018
      Select Dataset
      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.
    • October 2015
      Source: International Monetary Fund
      Uploaded by: Knoema
      Accessed On: 27 October, 2015
      Select Dataset
      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.
  • S
    • October 2016
      Source: Friedrich Schneider
      Uploaded by: Knoema
      Accessed On: 24 November, 2017
      Select Dataset
      Size and Development of the Shadow Economies of 157 Countries Worldwide-1999 to 2013.   Source:Mai Hassan CNMS, University of Marburg and Friedrich Schneider Johannes Kepler University of Linz and IZA (Discussion Paper No. 10281 October 2016)    Methodology: The shadow economies have been estimated on the basis of MIMIC models. Different MIMIC models have been constructed and used models which have high significance levels. There are two categories of the models are given below, with reduced samples and without reduced samples, Adjusted and Non-adjusted.                                                                     MIMIC estimation of the size of the shadow economy from 1999 to 2013MIMIC estimation of the size of the shadow economy from 1999 to 2013,yearly data for the reduced sampleVariables/spec MIMIC 1 MIMIC 2MIMIC 3MIMIC 1MIMIC 2MIMIC 35-1-34-1-34-1-26-1-25-1-24-1-2Causes      Tax burden0.15**0.15**0.15*0.08*0.08*0.07*-2.07-2.07-2.06-1.7-1.7-1.7Regulatory burden0.29***0.29***0.29***0.26***0.26***0.24***-2.74-2.74-2.73-3.04-3.04-2.82Unemployment rate0.53***0.53***0.52***0.43***0.43***0.41***(first difference)-2.87-2.87-2.86-3.27-3.27-3.03Self-employment rate   0.12**0.10**0.10**(first difference)   -2.2-2.2-2.14Economic Freedom-0.09*-0.10*-0.09**-0.06*-0.06*_____Index(-1.90)(-1.97)(-1.93)(-1.66)(-1.74) (first difference)      Business freedom-0.007_________-0.01_________Index(-0.19)  (-0.38)  (first difference)      Indicators      GDP growth-1***-1***-1***-1***-1***-1***(-2.62)(-2.97)-2.55(-3.34)(-3.33)(-3.08)Currency0.09**0.09**0.09***0.11***0.11**0.10***(first difference)-2.49-2.49-2.55   Labor force rate-0.02-0.02____   (first difference)(-0.54)(-0.55)    Fit Statistics      Chi^2 (pvalue)12.1211.465.449.939.663.44-0.277-0.1768-0.1423-0.0773-0.0465-0.3282GFI0.940.940.970.960.960.98CFI0.9880.9720.9850.9750.9730.995CD0.4610.460.4380.3250.3240.283RMSEA0.010.0140.0190.0250.0290.01Degrees of freedom352720352720Number of219821982198163816381638observations      Number of countries157157157117117117Notes: Absolute z-statistics are reported in parenthesis. *, **, *** denote significance at 10, 5 and 1% significance levels. Goodnessof fit index (GFI): values closer to 0.90 reflect a perfect fit. CFI: when the comparative fit index is closer to one, it indicates a goodmodel fit. SRMR: The values less than 0.08 indicate a good model fit. Coefficient of Determination (CD): A perfect fit corresponds toa CD=1 (Kline, 2011). Degrees of freedom=0.5(p+q)(p+q+1)-t, where p:number of causes, q=number of indicators, t=number of free parameters.  
    • December 2015
      Source: Office of National Statistics, Mauritania
      Uploaded by: Knoema
      Accessed On: 11 January, 2019
      Select Dataset
      Data cited at: https://mauritania.opendataforafrica.org/MRSCD2015
    • January 2015
      Source: Deutsche Bank Research
      Uploaded by: Kirill Kosenkov
      Accessed On: 06 January, 2015
      Select Dataset
      CDS-implied sovereign default probabilities for various recovery rate assumptions computed by Deutsche Bank Research Team from CDS spreads. For more information about computation consult DB Research notes
  • T
    • November 2018
      Source: Conference Board
      Uploaded by: Knoema
      Accessed On: 26 November, 2018
      Select Dataset
      Data cited at: https://www.conference-board.org This dataset contains time series data on Gross Domestic Product (GDP), Population, Employment, Total Hours Worked, Per Capita Income and Labor Productivity (measured as GDP per Person Employed and GDP per Hour Worked). Data is available for 123 countries, plus a second version of Chinese data based on alternative data, covering the period 1950-2018.
  • U
    • October 2017
      Source: United Nations Department of Economic and Social Affairs
      Uploaded by: Knoema
      Accessed On: 27 June, 2018
      Select Dataset
      This dataset contains short-term prospects for the global economy in 2015-2019   Project LINK is an international collaborative research group for econometric modelling, coordinated jointly by the Development Policy and Analysis Division of UN/DESA and the University of Toronto. Each year, a UN/DESA Expert Group Meeting on the World Economy, also known as the Project LINK Meeting, is held in October to discuss the world economic outlook. The meeting is participated in by a wide range of experts from academia, economic research institutions and international economic organizations as well as United Nations colleagues from the regional commissions of ECA, ECE, ECLAC, ESCAP and ESCWA. Global Economic Outlook presents the short-term prospects for the global economy in 2016 and 2017, including major risks and policy challenges. The report draws on inputs from the experts of Project LINK, as well as analysis of staff in the Global Economic Monitoring Unit of the Development Policy and Analysis Division (DPAD) of UN/DESA.
  • W
    • June 2018
      Source: World Economics and Politics Dataverse
      Uploaded by: Knoema
      Accessed On: 25 September, 2018
      Select Dataset
      Data cited at: World Economics and Politics (WEP) Dataverse   World Economic and Politics dataverse- 1800 to 2017
    • February 2018
      Source: World Input-Output Database
      Uploaded by: Knoema
      Accessed On: 16 February, 2018
      Select Dataset
      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
    • February 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 12 February, 2019
      Select Dataset
      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.
    • February 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 15 February, 2019
      Select Dataset
      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Global Economic Prospects Publication: https://datacatalog.worldbank.org/dataset/global-economic-prospects License: http://creativecommons.org/licenses/by/4.0/   Country-level data on the short-, medium, and long-term outlook for the global economy and the implications for developing countries and poverty reduction. Includes historical trends and growth forecasts.
    • January 2019
      Source: World Council on City Data
      Uploaded by: Knoema
      Accessed On: 22 January, 2019
      Select Dataset
      World Council City Data
    • January 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 30 January, 2019
      Select Dataset
      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
    • January 2019
      Source: United Nations Department of Economic and Social Affairs
      Uploaded by: Knoema
      Accessed On: 07 January, 2019
      Select Dataset
      The world economy has strengthened as lingering fragilities related to the global financial crisis subside. In 2017, global economic growth reached 3 per cent—the highest growth rate since 2011—and growth is expected to remain steady for the coming year.  The improved global economic situation provides an opportunity for countries to focus policy towards longer-term issues such as low carbon economic growth, reducing inequalities, economic diversification and eliminating deep-rooted barriers that hinder development. However, the recent improvements in growth remain unevenly distributed across countries and regions. Economic prospects for many commodity exporters remain particularly challenging. Negligible growth in per capita GDP is anticipated in several parts of Africa, Western Asia, and Latin America and the Caribbean. The impacted regions combined are home to 275 million people living in extreme poverty. Without sustained, economic growth, the chances of bringing that number to zero remain slim. To achieve the goals of eradicating poverty and creating decent jobs for all, it is essential to address the longer‑term structural issues that hold back a faster progress towards sustainable development.
    • January 2019
      Source: Economic Policy Uncertainty
      Uploaded by: Knoema
      Accessed On: 08 February, 2019
      Select Dataset
      Data cited at: World Uncertainty Index (WUI), developed by Hites Ahir (International Monetary Fund), Nicholas Bloom (Stanford University) and Davide Furceri (International Monetary Fund).