एक त्रुटि हुई. विवरण छिपाओ
आप के पेज सहेजे नहीं गए है. नवीकरण करें रद्द करें

Costa Rica

  • President:Carlos Alvarado Quesada
  • First Vice President:Epsy Campbell Barr
  • Capital city:San José
  • Languages:Spanish (official), English
  • Government:No data
  • National statistics office
  • Population, persons:49,99,441 (2018)
  • Area, sq km:51,060
  • GDP per capita, US$:12,027 (2018)
  • GDP, billion current US$:60.1 (2018)
  • GINI index:No data
  • Ease of Doing Business rank:67
All datasets:  B C E F G H I K N O P R S T W
  • B
    • मार्च 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 20 मार्च, 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
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 नवम्बर, 2019
      Select Dataset
      The 'Consumer Price Indices (CPIs)' contains all data that was previously contained in three different datasets: 'Consumer Prices', 'National Consumer Price Indices (CPIs) by COICOP divisions' and 'Harmonised Indices of Consumer Prices (HICPs) by COICOP divisions'. The 'Consumer Price Indices (CPIs)' dataset contains predominantly monthly statistics, and associated statistical methodological information, for the 36 OECD member countries and for some non-member countries. The ‘Consumer Price Indices (CPIs)' dataset contains statistics on Consumer Price Indices including national CPIs, Harmonised Indices of Consumer Prices (HICPs) and their associated weights and contributions to national annual inflation. The data series presented have been chosen as the most relevant prices statistics for which comparable data across countries is available. In all cases, a lot of effort has been made to ensure that the data are internationally comparable across all countries presented and that all the subjects have good historical time-series’ data to aid with analysis. Data are available monthly for all the countries except for Australia and New Zealand (quarterly data).
    • अप्रैल 2015
      Source: International Monetary Fund
      Uploaded by: Sandeep Reddy
      Accessed On: 20 अगस्त, 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.
  • E
    • सितम्बर 2019
      Source: Fraser Institute
      Uploaded by: Knoema
      Accessed On: 25 सितम्बर, 2019
      Select Dataset
      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
      Select Dataset
      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: 22 नवम्बर, 2019
      Select Dataset
      The OECD Economic Outlook analyses the major economic trends over the coming 2 years. It provides in-depth coverage of the main economic issues and the policy measures required to foster growth in each member country. Forthcoming developments in selected non-OECD economies are also evaluated in detail. Each edition of the Outlook provides a unique resource to keep abreast of world economic developments. The OECD Economic Outlook database is a comprehensive and consistent macroeconomic database of the OECD economies, covering expenditures, foreign trade, output, labour markets, interest and exchange rates, balance of payments, and government debt. For the non-OECD regions, foreign trade and current account series are available.    The database contains annual data (for all variables) and quarterly figures (for a subset of variables). Variables are defined in such a way that they are as homogenous as possible for the countries covered. Breaks in underlying series are corrected as far as possible. Sources for the historical data are publications of national statistical agencies and OECD data bases such as Quarterly National Accounts, Annual National Accounts, Labour Force Statistics and Main Economic Indicators. The cut-off date for information used in the compilation of the projections was the 14 November 2019.   Concerning the aggregation of world trade, a new composition has been introduced, since projections are now made for selected non-OECD economies. Thus, besides OECD and the OECD euro area, the following new regions are available: Dynamic Asian Economies (Chinese Taipei, Hong Kong, Malaysia, the Philippines, Singapore, Thailand, Vietnam); Oil Producers (Azerbaijan, Kazakhstan, Turkmenistan, Brunei, Timor-Leste, Bahrain, Iran, Iraq, Kuwait, Libya, Oman, Qatar, Saudi Arabia, United Arab Emirates, Yemen, Ecuador, Trinidad and Tobago, Venezuela, Algeria, Angola, Chad, Rep. of Congo, Equatorial Guinea, Gabon, Nigeria, Sudan); with the remaining countries in a residual 'Rest of the World' group.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2019
      Select Dataset
    • अक्तूबर 2015
      Source: International Monetary Fund
      Uploaded by: Knoema
      Accessed On: 22 अक्तूबर, 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.
    • सितम्बर 2013
      Source: United Nations Conference on Trade and Development
      Uploaded by: Knoema
      Accessed On: 10 अक्तूबर, 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
  • G
    • नवम्बर 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 05 दिसम्बर, 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:
    • नवम्बर 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 02 दिसम्बर, 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:
    • अगस्त 2019
      Source: United Nations Department of Economic and Social Affairs
      Uploaded by: Knoema
      Accessed On: 23 अक्तूबर, 2019
      Select Dataset
    • सितम्बर 2018
      Source: Dual Citizen LLC
      Uploaded by: Knoema
      Accessed On: 21 सितम्बर, 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.
    • नवम्बर 2019
      Source: Knowledge4All
      Uploaded by: Sandeep Reddy
      Accessed On: 28 नवम्बर, 2019
      Select Dataset
      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
      Select Dataset
      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
      Select Dataset
      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.
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 नवम्बर, 2019
      Select Dataset
      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.
    • जनवरी 2015
      Source: University of Groningen, Netherlands
      Uploaded by: Knoema
      Accessed On: 25 फरवरी, 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."
  • H
  • I
    • जुलाई 2018
      Source: International Centre for Tax and Development
      Uploaded by: Knoema
      Accessed On: 23 मई, 2019
      Select Dataset
      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
      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.
    • फरवरी 2019
      Source: Heritage Foundation
      Uploaded by: Knoema
      Accessed On: 04 फरवरी, 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
    • दिसम्बर 2018
      Source: U.S. Department of Agriculture
      Uploaded by: Knoema
      Accessed On: 26 दिसम्बर, 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.
    • जून 2013
      Source: United Nations Conference on Trade and Development
      Uploaded by: Knoema
      Accessed On: 22 जुलाई, 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
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 19 नवम्बर, 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
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 10 अक्तूबर, 2019
      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.
    • दिसम्बर 2018
      Source: United Nations Statistics Division
      Uploaded by: Knoema
      Accessed On: 04 मार्च, 2019
      Select Dataset
      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
      Select Dataset
      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: 02 दिसम्बर, 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.
    • फरवरी 2019
      Source: The National Committee on North Korea
      Uploaded by: Knoema
      Accessed On: 12 अगस्त, 2019
      Select Dataset
  • O
    • अक्तूबर 2015
      Source: International Monetary Fund
      Uploaded by: Sandeep Reddy
      Accessed On: 27 अक्तूबर, 2015
      Select Dataset
      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.
  • P
    • अप्रैल 2019
      Source: University of Groningen, Netherlands
      Uploaded by: Knoema
      Accessed On: 23 मई, 2019
      Select Dataset
      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.
    • अप्रैल 2019
      Source: Inter-American Development Bank
      Uploaded by: Knoema
      Accessed On: 26 जून, 2019
      Select Dataset
      Public Debt around the World
  • R
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 14 जुलाई, 2019
      Select Dataset
  • S
    • जुलाई 2017
      Source: Johannes Kepler University
      Uploaded by: Knoema
      Accessed On: 12 मार्च, 2019
      Select Dataset
      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%.
  • T
    • नवम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 25 नवम्बर, 2019
      Select Dataset
      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.
  • W
    • जून 2018
      Source: World Economics and Politics (WEP) Dataverse
      Uploaded by: Knoema
      Accessed On: 25 सितम्बर, 2018
      Select Dataset
      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
      Select Dataset
      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.
    • नवम्बर 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 12 नवम्बर, 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.
    • जून 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 12 जून, 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.
    • अक्तूबर 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 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
    • मार्च 2019
      Source: United Nations Department of Economic and Social Affairs
      Uploaded by: Knoema
      Accessed On: 22 मार्च, 2019
      Select Dataset
      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
      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).

हमारी गोपनीयता कथन और कुकी नीति

"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।"

गोपनीयता नीति