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According to the definitions of the International Labour Organisation (ILO) for the purposes of the labour market statistics people are classified as employed, unemployed and economically inactive. The economically active population is the sum of employed and unemployed persons. Inactive persons are those who, during the reference week, were neither employed nor unemployed. The data source from the quarterly EU Labour Force Survey (EU LFS).

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.

The aggregated regional government finance database (Aggregated REGOFI) provides a selection of indicators on expenditure, revenue, and debt for the entire regional government sector in OECD and EU countries. The time coverage ranges from 2010 to 2022 (based on data availability). This database has been produced in the context of the OECD/EU joint project Strengthening analytical frameworks and data on subnational government finance and public employment with the goal of collecting, standardising, and disseminating high-quality comparable data for local government finance and employment. This data provides information to assess the capacities and decision-making power of municipalities and regions, whose role is essential in developing place-based policy. It also allows for within and cross-country comparisons, which sheds light on the disparities between subnational governments in terms of fulfilling their mandates and their ability to raise own-source revenue. You will find more information on subnational government responsibilities in the World Observatory on Subnational Government Finance and Investment.

The data describe the average use of chemical and mineral fertilizers per area of cropland (arable land and permanent crops) at national, regional, and global level in a time series from 2002 to 2014The data describe the average use of chemical and mineral fertilizers per area of cropland (arable land and permanent crops) at national, regional, and global level in a time series from 2002 to 2015

The OECD’s ANalytical Business Enterprise Research and Development (ANBERD) database presents annual data on Research and Development (R&D) expenditures by industry and was developed to provide analysts with comprehensive data on business R&D expenditures. The ANBERD database incorporates a number of estimations that build upon and extend national submissions of business enterprise R&D data by industry (main activity/industry orientation).

Residential Property Prices Indices (RPPIs) – also named House price indices (HPIs), are index numbers that measure the prices of residential properties over time. RPPIs are key statistics not only for citizens and households across the world, but also for economic and monetary policy makers. They can help, for example, to monitor potential macroeconomic imbalances and the risk exposure of the household and financial sectors. This dataset covers the OECD member countries and some non-member countries. In addition to the nominal RPPIs it contains information on real house prices, rental prices, and the ratios of nominal prices to rents and to disposable household income per capita. This dataset contains quarterly and annual statistics for each country. Annual figures refer to the average of the year.

This table presents the balance sheets for non-financial assets for both produced assets (fixed assets such as dwellings as well as inventories and valuables) and non-produced assets (tangibles such as mineral and energy reserves and intangibles). Assets are shown on a net basis, the net value of an asset is calculated as its gross value decreased by the value of consumption of fixed capital (depreciation). These are presented for the whole economy and by institutional sector: Non-financial Corporations, Financial Corporations, General Government, Households and Non-profit institutions serving households (NPISH). These indicators were presented in the previous dissemination system in the SNA_TABLE9B dataset. See ANA Changes for information on changes in methodology: ANA Changes Explore also the GDP and non-financial accounts webpage: GDP and non-financial accounts webpage OECD statistics contact:[email protected]

This table presents gross capital formation, gross fixed capital formation (GFCF, or investment), changes in inventories and acquisition less disposals of valuables broken down by detailed industries based on detailed breakdowns of Revision 4 of the International Standard Industrial Classification of All Economic Activities (ISIC). GFCF is also available broken down by type of non-financial asset, which can be selected using the ‘Financial instruments and non-financial assets’ filter. The presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. Data is presented for each country in national currency as well as in euros for the European Union and the euro area. Data is presented in current prices (default view), but it is also possible to select chain linked volume and other price measures using the ‘Price base’ filter. These indicators were presented in the previous dissemination system in the SNA_TABLE8A dataset. See ANA Changes for information on changes in methodology: ANA Changes Explore also the GDP and non-financial accounts webpage: GDP and non-financial accounts webpage OECD statistics contact: [email protected]

This table presents employment data by economic activity based on detailed breakdowns of Revision 4 of the International Standard Industrial Classification of All Economic Activities (ISIC), according to the domestic concept. The domestic concept is defined by the location of the producer unit: employees are residents and non-residents employed by resident producer units; and self-employed people are resident and non-resident self-employed people in resident producer units. The presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. The default view of the table is for persons, but users can select alternative views for jobs and hours using the ‘Unit of measure’ filter. These indicators were presented in the previous dissemination system in the SNA_TABLE7A dataset. See ANA Changes for information on changes in methodology: ANA Changes Explore also the GDP and non-financial accounts webpage: GDP and non-financial accounts webpage OECD statistics contact: [email protected]

This table presents employment data by main economic activity based on Revision 4 of the International Standard Industrial Classification of All Economic Activities (ISIC), according to the domestic concept. The domestic concept is defined by the location of the producer unit: employees are residents and non-residents employed by resident producer units; and self-employed people are resident and non-resident self-employed people in resident producer units. The presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. The default view of the table is for persons, but users can select alternative views for jobs and hours using the ‘Unit of measure’ filter. .These indicators were presented in the previous dissemination system in the SNA_TABLE3 dataset. See ANA Changes for information on changes in methodology: ANA Changes Explore also the GDP and non-financial accounts webpage: GDP and non-financial accounts webpage OECD statistics contact: [email protected]

The Financial Accounts show net acquisition of financial assets (or changes in assets) during the period, net incurrence of financial liabilities (or changes in liabilities) during the period, and net financial transactions (or changes in the net position: financial assets minus financial liabilities) during the period. This table shows the Financial Accounts on a consolidated basis, which means that flows between units within the same sector or subsector (or the economy as a whole) have been removed, so that the accounts only reflect flows vis-à-vis other (sub)sectors or between the economy and the rest of the world. In this table, the presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. The default view of the table is for the economy as a whole, but you can use the ‘Institutional sector’ filter to select specific sectors such as Non-financial Corporations, Financial Corporations, General Government and Households, as well as the Rest of the world account. For each sector, the table presents breakdowns by financial instrument, for example currency and deposits, debt securities, loans, equity and investment fund shares, insurance and pensions. Users can also choose to compare a single financial instrument, such as listed shares, for several countries. Users should note that some countries do not produce consolidated accounts for all sectors. These indicators were presented in the previous dissemination system in the SNA_TABLE610R dataset. Explore also the OECD Financial Accounts and Balance Sheets webpage: Financial Accounts and Balance Sheets webpage OECD statistics contact: [email protected]

The Financial Accounts show net acquisition of financial assets (or changes in assets) during the period, net incurrence of financial liabilities (or changes in liabilities) during the period, and net financial transactions (or changes in the net position: financial assets minus financial liabilities) during the period. This table shows the Financial Accounts on a non-consolidated basis, meaning that is shows all flows in the economy, both between units belonging to different (sub)sectors and between units belonging to the same (sub)sector, in contrast with consolidated accounts in which flows between units within the same (sub)sector would be removed. In this table, the presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. The default view of the table is for the economy as a whole, but you can use the ‘Institutional sector’ filter to select specific sectors such as Non-financial Corporations, Financial Corporations, General Government and Households, as well as the Rest of the world account. For each sector, the table presents breakdowns by financial instrument, for example currency and deposits, debt securities, loans, equity and investment fund shares, insurance and pensions. Users can also choose to compare a single financial instrument, such as listed shares, for several countries. Users should note that Australia does not produce non-consolidated accounts. These indicators were presented in the previous dissemination system in the SNA_TABLE620R dataset. Explore also the OECD Financial Accounts and Balance Sheets webpage: Financial Accounts and Balance Sheets webpage OECD statistics contact: [email protected]

The Financial Balance Sheets show financial assets, liabilities and net financial worth (assets minus liabilities) at the end of the period. This table is on a non-consolidated basis, meaning that it shows all assets and liabilities of units in a sector or subsector (or the economy as a whole), in contrast with consolidated balance sheets in which counterpart assets and liabilities of units within the same sector or subsector (or the economy as a whole) would be removed. In this table, the presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. The default view of the table is for the economy as a whole, but you can use the ‘Institutional sector’ filter to select specific sectors such as Non-financial Corporations, Financial Corporations, General Government and Households, as well as the Rest of the world account. For each sector, the table presents breakdowns by financial instrument, for example currency and deposits, debt securities, loans, equity and investment fund shares, insurance and pensions. Users can also choose to compare a single financial instrument, such as listed shares, for several countries. Users should note that Australia does not produce non-consolidated accounts. These indicators were presented in the previous dissemination system in the SNA_TABLE720R dataset. Explore also the OECD National Accounts webpage: National Accounts webpage OECD statistics contact: [email protected]

This table presents fixed assets (such as dwellings and other buildings, machinery and equipment, computer software and databases) by detailed breakdowns of Revision 4 of the International Standard Industrial Classification of All Economic Activities (ISIC). Assets are shown on both gross and net bases, the net value of an asset is calculated as its gross value decreased by the value of consumption of fixed capital (depreciation). The presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. Data is presented for each country in national currency as well as in euros for the European Union and the euro area. Results are in current prices, but it is also possible to select chain linked volume and previous year price measures using the ‘Price base’ filter. These indicators were presented in the previous dissemination system in the SNA_TABLE9A dataset. See ANA Changes for information on changes in methodology: ANA Changes Explore also the GDP and non-financial accounts webpage: GDP and non-financial accounts webpage OECD statistics contact: [email protected]

This table presents Gross Domestic Product (GDP) and its components according to the expenditure approach. In the expenditure approach, the main components of GDP are: final consumption expenditure of households and non-profit institutions serving households (NPISH) plus final consumption expenditure of General Government plus gross fixed capital formation (or investment) plus net trade (exports minus imports). Data is presented for each country in national currency as well as in euros for the European Union and the euro area. Data is also presented converted to US dollars using both purchasing power parities and exchange rates. In this table, the presentation of GDP and its components is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. The default view shows all transactions (GDP and components) for the selected area, but it is possible to select specific components and sub-components of GDP using the ‘Transaction’ filter. The sector to which the selected transactions relate will be shown in the 'Institutional sector' filter, and further options (if applicable) will be shown under the ‘Financial instruments and non-financial assets’ filter. It is also possible to select current prices, chain linked volumes etc using the ‘Price base’ filter (the default view is current prices). The table shows OECD countries and selected economies, as well as the OECD total, OECD Europe, European Union and euro area. These can be selected using the ‘Reference area’ filter. We are working on an issue with rows that appear empty but are in fact not applicable. These indicators were presented in the previous dissemination system in the SNA_TABLE1 dataset. See ANA Changes for information on changes in methodology: ANA Changes Explore also the GDP and non-financial accounts webpage: GDP and non-financial accounts webpage OECD statistics contact: [email protected]

This table presents Gross Domestic Product (GDP) and its components according to the income approach. In the income approach, GDP is measured as the sum of compensation of employees (wages and salaries paid to employees and their employers’ social contributions), plus gross operating surplus (business profits) and gross mixed income (profits of the self-employed), plus taxes on production and imports less subsidies. The presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. Data is presented for each country in national currency as well as in euros for the European Union and the euro area. It is also presented converted to US dollars using exchange rates. The table shows OECD countries and selected economies, as well as the OECD total, OECD Europe, European Union and euro area. These indicators were presented in the previous dissemination system in the SNA_TABLE1 dataset. See ANA Changes for information on changes in methodology: ANA Changes Explore also the GDP and non-financial accounts webpage: GDP and non-financial accounts webpage OECD statistics contact: [email protected]

This table presents Gross Domestic Product (GDP) and its components according to the output approach. In the output approach, GDP is measured as the sum of gross value added (GVA) of all economic activities plus taxes less subsidies on products. This table includes breakdowns of GVA by type of economic activity according to Revision 4 of the International Standard Industrial Classification of All Economic Activities (ISIC). The presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. Data is presented for each country in national currency as well as in euros for the European Union and the euro area. Data is also presented converted to US dollars using exchange rates. It is also possible to select current prices, chain linked volumes etc using the ‘Price base’ filter (the default view is current prices). The table shows OECD countries and selected economies, as well as the OECD total, OECD Europe, European Union and euro area. These can be selected using the ‘Reference area’ filter. These indicators were presented in the previous dissemination system in the SNA_TABLE1 dataset. See ANA Changes for information on changes in methodology: ANA Changes Explore also the GDP and non-financial accounts webpage: GDP and non-financial accounts webpage OECD statistics contact: [email protected]

This table provides a breakdown of government expenditure according to the Classification of the Functions of Government (COFOG), which shows how much governments spend in areas such as health, education, environmental protection, defence and servicing public debt. The presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. Data is presented for each country in national currency as well as in euros for the European Union and the euro area. Data are also available, for most countries, for the sub-sectors of general government. Specific categories of expenditure (such as health and education) can be selected using the ‘Expenditure’ filter, while details of the type of expenditure such as compensation of employees (payment of wages and salaries and employers’ social contributions) can be selected using the ‘Transaction’ filter. For government final consumption expenditure a breakdown is also provided, in the ‘Transaction’ filter, between individual and collective consumption expenditure. Data is for General Government. For most countries, results are also available for the General Government sub-sectors: central, local and state (regional) government and social security. These sub-sectors can be selected using the ‘Institutional sector’ filter. These indicators were presented in the previous dissemination system in the SNA_TABLE11 dataset. See ANA Changes for information on changes in methodology: ANA Changes Explore also the Government Finances and Public Sector Debt webpage: Government Finances and Public Sector Debt webpage OECD statistics contact: [email protected]

This table presents taxes and social contribution receipts for General Government and its sub-sectors: central, local and state (regional) government and social security, as well as for institutions of the European Union. Total tax receipts comprise taxes on production and imports, current taxes on income wealth etc. and capital taxes. Social contribution receipts comprise actual and imputed social contributions. The presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. Data is presented for each country in national currency as well as in euros for the European Union and the euro area. These indicators were presented in the previous dissemination system in the SNA_TABLE10 dataset. See ANA Changes for information on changes in methodology: ANA Changes Explore also the Government Finances and Public Sector Debt webpage: Government Finances and Public Sector Debt webpage OECD statistics contact: [email protected]

This dataset provides the whole set of OECD annual households final consumption expenditure data and is recommended for users who wish to query a large amount of data. It is not designed for visualising results using the Table and Chart buttons. To access the ‘Developer API query builder’, click on the ‘Developer API’ button above. The application programming interface (API), based on the SDMX standard, allows a developer to access the data using simple RESTful URL and HTTP header options for various choices of response formats including JSON. The query filter is generated according to the current data selection. To change the data selection, use the filters on the left.

The “ALFS Summary tables” dataset is a subset of the Annual Labour Force Statistics database which presents annual labour force statistics for OECD member countries, Brazil and 4 geographical areas (Major Seven, Euro zone, European Union and OECD-Total). Data are presented in thousands of persons, in percentage or as indices with base year 2015=100. Annual data in this dataset are typically calculated as averages of infra-annual estimates. This can lead to differences with annual data published by National Statistics Institutes. This dataset contains estimates from the OECD for the latest years when countries did not provide data. These estimates are necessary to compile aggregated statistics for the geographical areas for a complete span of time. Since 2003, employment data by sector for the United States are compiled following the North American Industrial Classification System (NAICS); therefore they are not strictly comparable with other countries’ data.

This table presents the different transactions and balances to get from Gross Domestic Product (GDP) to net lending/net borrowing. It includes national disposable income (gross and net), consumption of fixed capital and net saving. The presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. Data is presented for each country in national currency as well as in euros for the European Union and the euro area, but you can also ask for it to be presented in US dollars converted with Purchasing Power Parities (PPPs) and exchange rates using the ‘Unit of measure’ filter. It is also possible to select chain linked volume and previous year price measures using the ‘Price base’ filter (the default view is current prices ). The indicators were presented in the previous dissemination system in the SNA_TABLE2 dataset. See ANA Changes for information on changes in methodology: ANA Changes Explore also the GDP and non-financial accounts webpage: GDP and non-financial accounts webpage OECD statistics contact: [email protected]

This table shows annual Purchasing Power Parities (PPPs) for Gross Domestic Product (GDP), household final consumption expenditure and actual individual consumption. It also shows exchange rates (annual averages and end of period), sourced from the International Monetary Fund's database on International Financial Statistics. Final consumption expenditure is the expenditure of resident households on consumption goods or services, while individual consumption is the sum of household consumption plus the individual (not collective) consumption of the non-profit institutions serving households (NPISH) and General Government sectors. These indicators were presented in the previous dissemination system in the SNA_TABLE4 dataset. For further information on (PPPs) please check the following link: Purchasing Power Parities and more precisely FAQ 5: Purchasing power parities OECD statistics contact: [email protected]

This dataset provides the whole set of OECD annual simplified non-financial accounts by institutional sector data and is recommended for users who wish to query a large amount of data. It is not designed for visualising results using the Table and Chart buttons. To access the ‘Developer API query builder’, click on the ‘Developer API’ button above. The application programming interface (API), based on the SDMX standard, allows a developer to access the data using simple RESTful URL and HTTP header options for various choices of response formats including JSON. The query filter is generated according to the current data selection. To change the data selection, use the filters on the left. To get started check the API documentation .For any question contact us

Data are collected from Ministries of Transport, national statistical offices and other institutions designated as the official data source. The survey used for this exercise is the "Trends in the Transport Sector". Variables collected include inland transport of goods and passengers, as well as road injury crashes. Additional information is also gathered on containers transported by rail and sea as well as short sea shipping. Data are published annually on 31 October. Data series start in 1970 and continue until the current year-1, or the most recent available data.

This table presents gross value added by economic activity based on detailed breakdowns of Revision 4 of the International Standard Industrial Classification of All Economic Activities (ISIC). The table also presents detailed ISIC data for output, intermediate consumption and consumption of fixed capital (depreciation), as well as for components of gross value added (GVA) such as wages and salaries and net operating surplus (business profits) and mixed income (profits of the self-employed). These can be selected using the ‘Transaction filter’. The presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. Data is presented for each country in national currency as well as in euros for the European Union and the euro area. Data is presented in current prices (default view), but for some items it is possible to select chain linked volume and other price measures using the ‘Price base’ filter. These indicators were presented in the previous dissemination system in the SNA_TABLE6A dataset. See ANA Changes for information on changes in methodology: ANA Changes Explore also the GDP and non-financial accounts webpage: GDP and non-financial accounts webpage OECD statistics contact: [email protected]

This dataset contains data on average annual wages per employee in full-time equivalent unit in the total economy. Average annual wages per full-time equivalent dependent employee are obtained by dividing the national-accounts-based total wage bill by the average number of employees in the total economy, which is then converted in full-time equivalent unit by applying the ratio of average usual weekly hours per full-time employee to that of all employees.

Data cited at: Balance of Payments, The International Monetary Fund. The Balance of Payments provides a framework that is applicable for a range of economies, from the smallest and least developed economies to the more advanced and complex economies. As a result, it is recognized that some items may not be relevant in all cases. The balance of payments is a statistical statement that summarizes transactions between residents and nonresidents during a period. It consists of the goods and services account, the primary income account, the secondary income account, the capital account, and the financial account. Contains balance of payments and international investment position (IIP) data of individual countries, jurisdictions, and other reporting entities, and regional and world totals for major components of the balance of payments. Both balance of payments and IIP data are presented in accordance with the standard components of the sixth edition of the Balance of Payments and International Investment Position Manual, BPM6. Balance of payments data are available for approximately 192 economies and international investment position data are available for approximately 152 economies.

Since the collection of 2009 data, the scope of the OECD Global Insurance Statistics questionnaire has been expanded. These changes led to the collection of key balance sheet and income statement items for direct insurance and reinsurance sectors, such as: gross claims paid, outstanding claims provision (changes), gross operating expenses, commissions, total assets, gross technical provisions (of which: unit-linked), shareholder equity, net income.

National accounts are a coherent and consistent 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. Eurostat publishes annual and quarterly national accounts, annual and quarterly sector accounts as well as supply, use and input-output tables, which are each presented with associated metadata. Annual national accounts are compiled in accordance with the European System of Accounts - ESA 2010 as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013.   The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. Further information on the transition from ESA 95 to ESA 2010 is presented on the Eurostat website. The domain consists of the following collections:   1. Main GDP aggregates: main components from the output, expenditure and income side, expenditure breakdowns by durability and exports and imports by origin. <

The OECD-WTO Balanced Trade in Services (BaTIS) dataset is a complete, consistent, and balanced matrix of international trade in services statistics (ITSS). It contains annual bilateral data covering 202 reporters and partners, broken down by the 12 main EBOPS2010 (BPM6) categories from 2005 to 2021. BaTIS is the result of joint efforts by the OECD and WTO. Two main features enable BaTIS to stand out as the international benchmark for any analysis on international trade in services:BaTIS is complete and consistent. At present, only about 63% of world trade in services is bilaterally specified, and the percentage is even lower for the individual service categories. The OECD-WTO methodology leverages all available official statistics and combines them with estimations and adjustments to provide users with a complete matrix covering virtually all economies in the world.BaTIS is balanced. To resolve the asymmetries between reported and mirror flows, exports and imports are reconciled by calculating a symmetry-index weighted average between the two, following a similar approach to that developed for international merchandise trade statistics. BaTIS provides 3 adjustments for each trade flow:Reported. Reflects the value officially reported by the country (where available), some values are rescaled to fit world totals.Adjusted and/or imputed. Reflects, in addition to the reported values, any adjustments made to ensure internal consistency as well as the estimations made by the OECD-WTO to fill in the gaps in the reported information.Balanced. Reflects the reconciled bilateral trade flow, where exports equal mirror imports. Official information on bilateral trade flows was collected from OECD, Eurostat, national sources as well as UNSD. The WTO-UNCTAD trade in services dataset, based on a number of primary sources complemented with estimations, was the main source for data with partner world. The BaTIS dataset can be used as a stand-alone input for economic analysis and policy-making. In addition, balanced trade in services data form an essential input to the OECD Trade in Value Added (TiVA) initiative, for which a balanced view of international trade is crucial. BaTIS is intended to be regularly updated and constantly improved as new data become available. For more information on the methodology, please refer to the working paper accompanying this dataset The OECD-WTO Balanced Trade in Services (BaTIS) For more information on balanced trade statistics, please go to the topic related OECD page Balanced trade statistics Users are encouraged to send their questions, or to signal any apparent errors, regarding this database to [email protected]://www.oecd.org/sdd

This data set provides a snapshot of migration and remittances for all countries, regions and income groups of the world, compiled from available data from various sources

The residential property price statistics collect data from different countries. The BIS has obtained permission from various national data providers, with the assistance of its member central banks, to disseminate these statistics. The topic ‘Property prices: Selected series,’ contains nominal and real quarterly values for 58 countries, both in levels and in growth rates (ie four series per country). Real series are the nominal price series deflated by the consumer price index. The BIS has made the selection based on the Handbook on Residential Property Prices and the experience and metadata of central banks.   Data cited at : https://www.bis.org/statistics/index.htm

Business Tendency Surveys (BTS) – also called business opinion or business climate surveys – are economic surveys used to monitor and forecast business cycles. Covering 4 different economic sectors (manufacturing, construction, retail trade and services), they are designed to collect qualitative information useful in monitoring the current business situation and forecasting short-term developments by directly asking company managers about the pulse of their businesses. They are well known for providing advance warning of turning points in aggregate economic activity as measured by GDP or industrial production. As respondents provide answers on a 3 scale options (up, same, down, or above normal, normal, below normal), data are summarised in net balances corresponsing to the difference in % of positive over negative replies. Because of their collection mode, timeliness and immediate availability, they have proved to be a cost‑effective mean of generating timely information especially during crises. In the late '90, in collaboration with the European Commission, the OECD has developed a system of harmonised business tendency surveys in order to collect and compare data across countries. The EC Directorate General for Economic and Financial Affairs is since then in charge of running the program and collecting data across EU members, while the OECD helped the adoption and implementation of the same harmonised framework in non-EU OECD countries and BRIICS. By construction, BTS questions are formulated in order to exclude seasonal factors. Nevertheless all series are tested for seasonality by both the OECD (using x12) and by the EC for the EU member data (using DAINTIES). This dataset comprises a set of harmonised target indicators available across OECD and BRIICS countries, any departure from target definitions are documented in the metadata.

The data are central government bond yields which are no longer updated.

The data are central government bond yields which are no longer updated.

Climate Change Knowledge Portal, Temperature and Rainfall: Historical Data (CRU Observed)

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. Detailed information on the OECD methodology for CLIs can be found on the OECD website at: OECD CLIs   CLIs are calculated for G20 countries plus Spain and 5 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.   OECD CLI methodology document   OECD statistics contact  

Business surveys provide a rapid means of compiling simple statistics with the results available before those of traditional statistical methods, and provide also information on areas not covered by quantitative statistics. Details provided by respondents are generally of very high quality since the questions related to subjects with which they are familiar, thus the past and future performance of their business is highly reliable. Similarly, consumers provide a very high quality information on their purchasing information and price trend. Source: DG ECFIN

Below Parameters are common for all combinations : Frequency - Quarterly Measure -Amounts Outstanding / Stocks CBS Bank Type - Domestic Banks CBS Reporting Basis - Immediate Counterparty Basis Balance Sheet Position - Total Claims Type of Instruments - All Instruments Remaining Maturity - All Maturities Currency Type of Booking Location - All Currencies Counterparty Sector - All Sectors Data cited at : https://www.bis.org/statistics/index.htm

Eurostat Dataset Id:ei_bsbu_m_r2 Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published:as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)

Industry, Trade and Services statistics are part of Short-term statistics (STS), they give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification(Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are presented in the following forms: UnadjustedCalendar adjustedSeasonally-adjusted Depending on the STS regulation, data are accessible monthly and quarterly. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction Index*Turnover IndexProducer Prices (Domestic Output Prices index)*Import Prices Index*: Total, Euro area market, Non euro area market (euro area countries only)Labour Input Indicators: Number of Persons Employed, Hours Worked, Gross Wages and SalariesCONSTRUCTIONProduction Index*: Total of the construction sector, Building construction, Civil EngineeringLabour input indicators: Number of Persons Employed, Hours Worked, Gross Wages and SalariesConstruction costs IndexBuilding permits indicators*: Number of dwellingsWHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (in value)Labour input indicators: Number of Persons EmployedSERVICES  Turnover Index* Producer prices (Ouput prices)*

The objective of the construction cost index is to show the development of costs incurred by the contractor/producer to carry out the construction process, in others words the cost of labour, materials and plant and overheads. The construction sector corresponds to the NACE Rev. 2 section F but the split between building construction and civil engineering (CC1, CC2) is based on the Classification of types of Construction. Building construction (CC1) is further subdivided in residential building (CC11) and non-residential building (CC12). The data provided in this table concerns residential building excluding the subgroup of residencies for communities (CC11 excluding CC113). Data are not seasonally adjusted.

Data cited at: Consumer price indexes, The International Monetary Fund Consumer price indexes (CPIs) are index numbers that measure changes in the prices of goods and services purchased or otherwise acquired by households, which households use directly, or indirectly, to satisfy their own needs and wants. In practice, most CPIs are calculated as weighted averages of the percentage price changes for a specified set, or ‘‘basket’’, of consumer products, the weights reflecting their relative importance in household consumption in some period. CPIs are widely used to index pensions and social security benefits. CPIs are also used to index other payments, such as interest payments or rents, or the prices of bonds. CPIs are also commonly used as a proxy for the general rate of inflation, even though they measure only consumer inflation. They are used by some governments or central banks to set inflation targets for purposes of monetary policy. The price data collected for CPI purposes can also be used to compile other indices, such as the price indices used to deflate household consumption expenditures in national accounts, or the purchasing power parities used to compare real levels of consumption in different countries.

The FAOSTAT monthly CPI Food CPI database was based on the ILO CPI data until December 2014. In 2014, IMF-ILO-FAO agreed to transfer global CPI data compilation from ILO to IMF. Upon agreement, CPIs for all items and its sub components originates from the International Monetary Fund (IMF), and the UN Statistics Division(UNSD) for countries not covered by the IMF. However, due to a limited time coverage from IMF and UNSD for a number of countries, the Organisation for Economic Co-operation and Development (OECD), the Latin America and the Caribbean statistics (CEPALSTAT), Central Bank of Western African States (BCEAO), Eastern Caribbean Central Bank (ECCB) and national statistical office website data are used for missing historical data from IMF and UNSD food CPI. The FAO CPI dataset for all items(or general CPI) and the Food CPI, consists of a complete and consistent set of time series from January 2000 onwards. These indices measure the price change between the current and reference periods of the average basket of goods and services purchased by households. The CPI,all items is typically used to measure and monitor inflation, set monetary policy targets, index social benefits such as pensions and unemployment benefits, and to escalate thresholds and credits in the income tax systems and wages in public and private wage contracts.

This dataset contains statistics on Consumer Price Indices by COICOP 1999 divisions, including national CPIs, Harmonised Indices of Consumer Prices (HICPs) and their associated weights and contributions to national year-on-year inflation. For countries for which data are already available according to the COICOP 2018 classification statistics on Consumer Price Indices can be found in dataset Consumer price indices (CPIs, HICPs), COICOP 2018. The data series presented have been chosen as the most relevant prices statistics for which comparable data across countries is available. Data are available monthly for all the countries except for Australia and New Zealand (quarterly data).

Eurostat Dataset Id:ei_bsco_m Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published:as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)

Data cited at: Coordinated Direct Investment Survey, The International Monetary Fund. The CDIS database presents detailed data on "inward" direct investment positions (i.e., direct investment into the reporting economy) cross-classified by economy of immediate investor, and data on "outward" direct investment positions (i.e., direct investment abroad by the reporting economy) cross-classified by economy of immediate investment. The CDIS database contains breakdowns of direct investment position data, including, in most instances, separate data on net equity and net debt positions, as well as tables that present "mirror" data (i.e., tables in which data from the reporting economy are shown side-by-side with the data obtained from all other counterpart reporting economies).

The Tax Foundation’s publication Corporate Tax Rates around the World shows how statutory corporate income tax rates have developed since 1980, with data for over 200 jurisdictions for the year 2023. The dataset we compiled for the years 1980 to 2023 is made available as a resource for research.  

Data cited at https://www.transparency.org/en/cpi/2020/index/nzl by Transparency International is licensed under CC-BY-ND 4.0. Global Corruption Barometer is the largest world-wide public opinion survey on corruption. see more at https://www.transparency.org/en/cpi/2020/index/nzl Transparency International(TI) defines corruption as the abuse of entrusted power for private gain. This definition encompasses corrupt practices in both the public and private sectors. The Corruption Perceptions Index (CPI) ranks countries according to the perception of corruption in the public sector. The CPI is an aggregate indicator that combines different sources of information about corruption, making it possible to compare countries. The CPI ranks almost 200 countries by their perceived levels of corruption, as determined by expert assessments and opinion surveys.

Data cited at NUMBEO Numbeo is the world’s largest database of user-contributed data about cities and countries worldwide. Numbeo provides current and timely information on world living conditions including cost of living, housing indicators, health care, traffic, crime and pollution. For more information please check http://www.numbeo.com/cost-of-living/rankings_by_country.jsp   About dataset: These indices are relative to New York City (NYC). Which means that for New York City, each index should be 100(%). If another city has, for example, rent index of 120, it means rents in average in that city are 20% more expensive than in New York City. If a city has rent index of 70, that means in the average in that city rents are 30% less expensive than in New York City. Cost of Living Index (Excl. Rent) is a relative indicator of consumer goods price, including groceries, restaurants, transportation and utilities. Cost of Living Index doesn't include accommodation expenses such as rent or mortgage. If a city has a Cost of Living Index of 120, it means Numbeo estimates it is 20% more expensive than New York (excluding rent). Rent Index is estimation of prices of renting apartments in the city compared to New York City. If Rent index is 80, Numbeo estimates that price for renting in that city is 80% of price in New York. Groceries Index is an estimation of grocery prices in the city compared to New York City. To calculate this section, Numbeo uses "Markets"section of each city. Restaurants Index is a comparison of prices of meals and drinks in restaurants and bars compared to NYC. Cost of Living Plus Rent Index is an estimation of consumer goods prices including rent in the city comparing to New York City. Local Purchasing Power shows relative purchasing power in buying goods and services in a given city for the average wage in that city. If domestic purchasing power is 40, this means that the inhabitants of that city with the average salary can afford to buy 60% less typical goods and services than New York City residents with an average salary.

Citation: Damodaran, Aswath, Equity Risk Premiums (ERP): Determinants, Estimation and Implications – The 2016 Edition (March 5, 2016). Available at SSRN: https://ssrn.com/abstract=2742186 or http://dx.doi.org/10.2139/ssrn.2742186   This dataset summarizes the latest bond ratings and appropriate default spreads for different countries. While you can use these numbers as rough estimates of country risk premiums, you may want to modify the premia to reflect the additional risk of equity markets. To estimate the long term country equity risk premium, I start with a default spread, which I obtain in one of two ways: (1) I use the local currency sovereign rating (from Moody's: www.moodys.com) and estimate the default spread for that rating (based upon traded country bonds) over a default free government bond rate. For countries without a Moody's rating but with an S&P rating, I use the Moody's equivalent of the S&P rating. To get the default spreads by sovereign rating, I use the CDS spreads and compute the average CDS spread by rating. Using that number as a basis, I extrapolate for those ratings for which I have no CDS spreads. (2) I start with the CDS spread for the country, if one is available and subtract out the US CDS spread, since my mature market premium is derived from the US market. That difference becomes the country spread. For the few countries that have CDS spreads that are lower than the US, I will get a negative number. You can add just this default spread to the mature market premium to arrive at the total equity risk premium. I add an additional step. In the short term especially, the equity country risk premium is likely to be greater than the country's default spread. You can estimate an adjusted country risk premium by multiplying the default spread by the relative equity market volatility for that market (Std dev in country equity market/Std dev in country bond). I have used the emerging market average of 1.12 (estimated by comparing a emerging market equity index to an emerging market government/public bond index) to estimate country risk premium.I have added this to my estimated risk premium of 5.08% for mature markets (obtained by looking at the implied premium for the S&P 500) to get the total risk premium. Notes:  The year of publication has been considered as per publication date. For example, data published on 2018-Jan considered as 2018, similarly 2019-Jan as 2019    

The country statistical profiles provide a broad selection of indicators, illustrating the demographic, economic, environmental and social developments, for all OECD members. The dataset also covers the five key partner economies with which the OECD has developed an enhanced engagement program with (Brazil, China, India, Indonesia and South Africa) ,accession countries (Colombia, Costa Rica and Lithuania) , Peru and the Russian Federation. The user can easily compare indicators across all countries. Total fertility rates - Unit of measure used: Number of children born to women aged 15 to 49

Data cited at: Our World in data-https://ourworldindata.org/coronavirus-source-data 

These Community Mobility Reports aim to provide insights into what has changed in response to policies aimed at combating COVID-19. The reports chart movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential.

The data set on credit to the non-financial sector captures borrowing activity by the government sector and the private non-financial sector in more than 40 economies. Quarterly data on credit to the government sector cover on average 20 years, while those on credit to the private non-financial sector on average more than 45 years. The statistics follow the framework of the System of National Accounts.   Data cited at: Bank for International Settlements (2024), Credit to the non-financial sector, BIS WS_TC 2.0 (data set), https://data.bis.org/topics/TOTAL_CREDIT/data.

The objective of the CRS Aid Activity database is to provide a set of readily available basic data that enables analysis on where aid goes, what purposes it serves and what policies it aims to implement, on a comparable basis for all DAC members. Data are collected on individual projects and programmes. Focus is on financial data but some descriptive information is also made available.

Data cited at: Numbeo Methodology: The Index has been calculated twice per year by considering the latest 36 months. A). Beginning of the Year and B). Mid Year Crime Index is an estimation of the overall level of crime in a given city or a country. We consider crime levels lower than 20 as very low, crime levels between 20 and 40 as being low, crime levels between 40 and 60 as being moderate, crime levels between 60 and 80 as being high and finally crime levels higher than 80 as being very high. Safety index is, on the other way, quite the opposite of crime index. If the city has a high safety index, it is considered very safe.

Eurostat Dataset Id:med_ag2 The focus of this domain is on the following countries:Algeria, Egypt, Israel, Jordan, Lebanon, Morocco, Palestinian Authority, Syria, Tunisia. Data are provided for over 1000 indicators depending on the country.   The data for the Mediterranean partner countries are supplied by and under the responsibility of the national statistical authorities  of each of the countries or territories. The data and their denomination in no way constitute the  expression of an opinion by the European Commission on the  legal status of a country or territory or on the delimitation of its frontiers. Â

This table shows exchange rates for currencies used in over 190 world economies presented in a cross rates layout where countries are presented in both rows and columns. National currency per US dollars exchange rates are used to derive explicit exchange rates for each of the countries presented with regard to any other country. Country series are consistent over time: for example, a conversion was made from national currency to Euro for the Euro Zone economies for all years prior to the adoption of Euro.

How’s Life? Well-being is the one-stop shop for the 80+ indicators of the OECD Well-being Dashboard, providing information on current well-being outcomes, well-being inequalities and the resources and risks that underpin future well-being. The 11 dimensions of current well-being relate to material conditions that shape people’s economic options (Income and Wealth, Housing, Work and Job Quality) and quality-of-life factors that encompass how well people are (and how well they feel they are), what they know and can do, and how healthy and safe their places of living are (Health, Knowledge and Skills, Environmental Quality, Subjective Well-being, Safety). Quality of life also encompasses how connected and engaged people are, and how and with whom they spend their time (Work-Life Balance, Social Connections, Civic Engagement). The distribution of current well-being is taken into account by looking at three types of inequality: gaps between population groups (horizontal inequalities); gaps between those at the top and those at the bottom of the achievement scale in each dimension (vertical inequalities); and deprivations (i.e. the share of the population falling below a given threshold of achievement). The systemic resources that underpin future well-being over time are expressed in terms of four types of capital: Economic, Natural, Human and Social.

This database provides aggregates on official development assistance (ODA), other official flows (OOF) and flows from non-governmental organisations (NGOs) or philanthropic foundations. These statistics are shown by provider over time. To assist with the transition between systems, we provide a mapping of codes between OECD.Stat (legacy) and the OECD Data Explorer. For more information on these flows, please see the OECD’s main page on development finance statistics, including Frequently Asked Questions (FAQs) on ODA. See the Converged Statistical Reporting Directives governing these data.

Private transactions are those undertaken by firms and individuals resident in the reporting country. To assist with the transition between systems, we provide a mapping of codes between OECD.Stat (legacy) and the OECD Data Explorer. For more information on these flows, please see the OECD’s main page on development finance statistics, including Frequently Asked Questions (FAQs) on ODA. See the Converged Statistical Reporting Directives governing these data.

Days not worked as a result of strikes and lockouts represent the total number of working days not worked as a result of strikes and lockouts in progress during the year. It is measured in terms of the sum of the actual working days during which work would normally have been carried out by each worker involved had there been no stoppage. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Industrial Relations data (IRdata) database description.

Notes: Figures 019 are estimates. The NATO Europe and NATO Total aggregates from 2017 include Montenegro, which became an Ally on 5 June 2017

Data cited at: Direction of Trade Statistics, The International Monetary Fund. The Direction of Trade Statistics (DOTS) presents current figures on the value of merchandise exports and imports dis-aggregated according to a country's primary trading partners. Area and world aggregates are included in the display of trade flows between major areas of the world. Reported data is supplemented by estimates whenever such data is not available or current. Imports are reported on a cost, insurance and freight (CIF) basis and exports are reported on a free on board (FOB) basis, with the exception of a few countries for which imports are also available FOB. Time series data includes estimates derived from reports of partner countries for non-reporting and slow-reporting countries.

The domain "Income and living conditions" covers four topics: people at risk of poverty or social exclusion, income distribution and monetary poverty, living conditions and material deprivation, which are again structured into collections of indicators on specific topics. The collection "People at risk of poverty or social exclusion" houses main indicator on risk of poverty or social inclusion included in the Europe 2020 strategy as well as the intersections between sub-populations of all Europe 2020 indicators on poverty and social exclusion. The collection "Income distribution and monetary poverty" houses collections of indicators relating to poverty risk, poverty risk of working individuals as well as the distribution of income. The collection "Living conditions" hosts indicators relating to characteristics and living conditions of households, characteristics of the population according to different breakdowns, health and labour conditions, housing conditions as well as childcare related indicators. The collection "Material deprivation" covers indicators relating to economic strain, durables, housing deprivation and environment of the dwelling.

Data cited at:  Retrieved from-https://atlas.cid.harvard.edu/rankings/product

Data cited at:  Retrieved from-https://oec.world/en/rankings/eci/hs6/hs96

The OECD Economic Outlook presents the OECD’s analysis of the major global economic trends and prospects for the next two years. The Outlook puts forward a consistent set of projections for output, employment, government spending, prices and current balances based on a review of each member country and of the induced effect on each of them on international developments. OECD (2024), OECD Economic Outlook No 115 (Edition 2024/1)EO115 Database documentationEO115 Last historical pointsOECD Economic Outlook website: https://www.oecd.org/economic-outlook/ Contact: [email protected]

The Economic Sentiment Indicator (ESI) is a composite indicator made up of five sectoral confidence indicators with different weights: Industrial confidence indicator, Services confidence indicator, Consumer confidence indicator, Construction confidence indicator Retail trade confidence indicator. Confidence indicators are arithmetic means of seasonally adjusted balances of answers to a selection of questions closely related to the reference variable they are supposed to track (e.g. industrial production for the industrial confidence indicator). Surveys are defined within the Joint Harmonised EU Programme of Business and Consumer Surveys. The economic sentiment indicator (ESI) is calculated as an index with mean value of 100 and standard deviation of 10 over a fixed standardised sample period. Data are compiled according to the Statistical classification of economic activities in the European Community, (NACE Rev. 2). Source: DG ECFIN

The OECD, in cooperation with the EU, has developed a harmonised definition of urban areas which overcomes previous limitations linked to administrative definitions (OECD, 2012). According to this definition an urban area is a functional economic unit characterised by densely inhabited “city core” and “commuting zone” whose labour market is highly integrated with the core. The Metropolitan database provides indicators of 649 OECD metropolitan areas identified in 33 OECD countries and the functional urban areas of Colombia. Comparable values of population, GDP, employment, and other indicators are presented.

This dataset presents internationally comparable data on education and earnings, by educational attainment, age and gender as published in OECD Education at a Glance 2022. For trend data, Education at a Glance 2022 includes data for 2005 and 2010-2020 (or years with available data).

This indicator presents internationally comparable data regarding the labour force status and the educational attainment level by the National Educational Attainment Categories (NEAC) as reported by the labour force survey (LFS) and published in OECD Education at a Glance 2017. For trend data, the Education at a Glance Database includes data from 1981 to 2016 (or years with available data).

The nature of expenditure distinguishes between current and capital expenditure. The resource category refers to service provider (public institutions, government-dependent private institutions, and independent private institutions, i.e. both educational and other institutions). These expenditure figures are intended to represent the total cost of services provided by each type of institution, without regard to sources of funds (whether they are public or private).

All entities that provide funds for education, either initially or as final payers, are classified as either governmental (public) sources or non-governmental (private) sources, the sole exception being "international agencies and other foreign sources", which are treated as a separate category. There are three types of financial transactions: Direct expenditure on educational institutions; Transfers to students or households and to other private entities; and Households' expenditure on education outside educational institutions.

These indicators on expenditure on education are published in chapter C of Education at a Glance, which covers financial and human resources invested in education.They are either policy levers or provide context information on education systems, or sometimes both. For example, expenditure per student is a key policy measure that most directly affects the individual learner, as it acts as a constraint on the learning environment in schools and learning conditions in the classroom.The data set “educational finance indicators” provides the main indicators computed for three levels of education : primary, secondary and post-secondary non-tertiary levels combined; tertiary level; and primary to tertiary levels combined. Other datasets provide more breakdowns for each specific indicator.

Average number of teachers by sex and age.

Average number of teachers by sex and type of institution. Educational Personnel by Type of Institution, Management Personnel and Teacher Aides (archived)

This indicator presents electricity prices charged to final consumers. Electricity prices for non-household consumers are defined as follows: Average national price in Euro per kWh without taxes applicable for the first semester of each year for medium size industrial consumers (Consumption Band Ic with annual consumption between 500 and 2000 MWh). Electricity prices for household consumers are defined as follows: Average national price in Euro per kWh including taxes and levies applicable for the first semester of each year for medium size household consumers (Consumption Band Dc with annual consumption between 2500 and 5000 kWh).

As of Jun 2021, estimates of greenhouse gas (GHG) emissions from agriculture and land use are disseminated under the FAOSTAT heading Climate Change/Emissions. This heading consolidates and replaces two previous distinct headings: Emissions-Agriculture and Emissions-Land Use, which no longer exist. Several other domains were consolidated to facilitate data access. https://fenixservices.fao.org/faostat/static/documents/GT/README_Changes_in_2021.pdf   The domain Emissions Totals consolidatesin one single dataset the information previously presented in two separate datasets: Agriculture total (previously: http://www.fao.org/faostat/en/#data/GT; containing data on non-CO2 emissions from agriculture); and Land Use total (previously: http://www.fao.org/faostat/en/#data/GL; containing CO2 and non-CO2 emissions from land use, land use change and forestry. This link no longer works).

Eurostat Dataset Id:cens_01reisco The tables presented in the topic of educational level cover the total population for 31 countries (for more information on received tables and geographic coverage, see "2001 Census Round - Tables Received" in the Annex at the bottom of the page). The level of completeness of the tables depends largely on the availability of data at the respective national statistical institutes. There are four ways of collecting census data, namely: - the traditional method of using census questionnaires (exhaustive census); - the method of using registers and/or other administrative sources; - a combination of registers and/or other administrative sources and - surveys (complete enumerations or sample surveys). Other methods (other mixed census or micro-census) can be used as well. Details for the method employed by each country are provided in "2001 Census Method"in the Annex at the bottom of the page. In the same table you can find the dates on which the census was carried out in each country.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. Data disaggregated by occupation are provided according to the latest version of the International Standard Classification of Occupations (ISCO). Data may have been regrouped from the national classifications, which may not be strictly compatible with ISCO. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are disaggregated by level of education, which refers to the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). For more information, refer to our resources on methods.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.

Regional accounts are a regional specification of the national accounts and therefore based on the same concepts and definitions as national accounts (see domain nama10). The main specific regional issues are addressed in chapter 13 of ESA2010, but not practically specified. For practical rules and recommendations on sources and methods see the publication "Manual on regional accounts methods": http://ec.europa.eu/eurostat/en/web/products-manuals-and-guidelines/-/KS-GQ-13-001 . Gross domestic product (GDP) at market prices is the final result of the production activity of resident producer units. It can be defined in three ways: 1. Output approach GDP is the sum of gross value added of the various institutional sectors or the various industries plus taxes and less subsidies on products (which are not allocated to sectors and industries). It is also the balancing item in the total economy production account. 2. Expenditure approach GDP is the sum of final uses of goods and services by resident institutional units (final consumption expenditure and gross capital formation), plus exports and minus imports of goods and services. At regional level the expenditure approach cannot be used in the EU, because there is no data on regional exports and imports.  3. Income approach GDP is the sum of uses in the total economy generation of income account: compensation of employees plus gross operating surplus and mixed income plus taxes on products less subsidies plus consumption of fixed capital. The different measures for the regional GDP are absolute figures in € and Purchasing Power Standards (PPS), figures per inhabitant and relative data compared to the EU28 average.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. Data disaggregated by occupation are provided according to the latest version of the International Standard Classification of Occupations (ISCO). Data may have been regrouped from the national classifications, which may not be strictly compatible with ISCO. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The employed comprise all persons of working age who, during a specified brief period, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by economic activity, which refers to the main activity of the establishment in which a person worked during the reference period. The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The employed comprise all persons of working age who, during a specified brief period, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by occupation according to the latest version of the International Standard Classification of Occupations (ISCO). The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data disaggregated by occupation are provided according to the latest version of the International Standard Classification of Occupations (ISCO). Data may have been regrouped from the national classifications, which may not be strictly compatible with ISCO. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by status in employment according to the latest version of the International Standard Classification of Status in Employment (ICSE-93). Status in employment refers to the type of explicit or implicit contract of employment the person has with other persons or organizations. The basic criteria used to define the groups of the classification are the type of economic risk and the type of authority over establishments and other workers which the job incumbents have or will have. The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED. For more information, refer to the Education and Mismatch Indicators (EMI) database description.

The employed comprise all persons of working age who, during a specified brief period, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by economic activity, which refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. Data for 1991-2016 are estimates while 2017-2021 data are projections. The dataset was updated as of November 2017. For more information, refer to the indicator description and the ILO estimates and projections methodological note.  

The employed comprise all persons of working age who, during a specified brief period, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by occupation according to the latest version of the International Standard Classification of Occupations (ISCO). Information on occupation provides a description of the set of tasks and duties which are carried out by, or can be assigned to, one person. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. Data for 1991-2016 are estimates while 2017-2021 data are projections. The dataset was updated as of November 2017. For more information, refer to the indicator description and the labour force estimates and projections methodological paper.   

The employed comprise all persons of working age who, during a specified brief period, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by occupation according to the latest version of the International Standard Classification of Occupations (ISCO). For more information, refer to the concepts and definitions page.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The employment-to-population ratio expresses the number of persons who are employed as a percent of the total working age population. The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

Eurostat Dataset Id:ei_isen_m Industry, Trade and Services statistics are part of Short-term statistics (STS), they give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification(Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are presented in the following forms: :Unadjusted :Working-day adjusted (Production, Turnover in wholesale and retail trade and other services, Hours worked) :Seasonally-adjusted Data are accessible as monthly and quarterly data. This heading covers the indicators listed below in four different sectors. INDUSTRY Production IndexTurnover Index Producer Prices (Domestic Output Prices index) Import Prices Index: Total, Euro area market, Non euro area market (euro area countries only) Labour Input Indicators: Number of Persons Employed, Hours Worked, Gross Wages and Salaries CONSTRUCTION Production Index: Total of the construction sector, Building construction, Civil Engineering Labour input indicators: Number of Persons Employed, Hours Worked, Gross Wages and Salaries Construction costs Index Building permits indicators: Number of dwellings WHOLESALE AND RETAIL TRADE Volume of sales (deflated turnover) Turnover (in value) Labour input indicators: Number of Persons Employed SERVICES Turnover Index

1: Most surveys were administered using the Enterprise Surveys Global Methodology as outlined in the Methodology page, while some others did not strictly adhere to the Enterprise Surveys Global Methodology. For example, for surveys which do not follow the Global Methodology, the Universe under consideration may have consisted of only manufacturing firms or the questionnaire used may have been different from the standard global questionnaire. Data users should exercise caution when comparing raw data and point estimates between surveys that did and did not adhere to the Enterprise Surveys Global Methodology. For surveys which did not adhere to the Global Methodology plus Afghanistan 2008, any inference from one of these surveys is representative only for the data sample itself. 2: Regional and "all countries" averages of indicators are computed by taking a simple average of country-level point estimates. For each economy, only the latest available year of survey data is used in this computation. Only surveys, posted during the years 2009-2017, and adhering to the Enterprise Surveys Global Methodology are used to compute these regional and "all countries" averages. 3: Descriptions of firm subgroup levels, e.g. how the ex post groupings are constructed, are provided in the Indicator Descriptions (PDF, 710KB) document. 4: Statistics derived from less than or equal to five firms are displayed with an "n.a." to maintain confidentiality and should be distinguished from ".." which indicates missing values. Also note for three growth-related indicators under the "Performance" topic, these indicators are not computed when they are derived from less than 30 firms. 5: Standard errors are labeled "n.c.", meaning not computed, for the following:    1) indicators for all surveys that were not conducted using the Enterprise Surveys Global Methodology and    2) for indicator breakdowns by ex post groupings: exporter or ownership type, and gender of the top manager.

The yearly “EU energy in figures - statistical pocketbook” provides an annual overview of energy-related structural statistics in the EU and in individual EU countries. Data cited at: European Commission, Directorate-General for Energy, EU energy in figures – Statistical pocketbook 2023, Publications Office of the European Union, 2023, https://data.europa.eu/doi/10.2833/502436

International trade in goods statistics (ITGS) published by Eurostat measure the value and quantity of goods traded between the EU Member States (intra-EU trade) and goods traded by the EU Member States with non-EU countries (extra-EU trade). ‘Goods’ means all movable property including electricity. ‘European’ means that the statistics are compiled on the basis of the concepts and definitions set out in EU legislation. ‘National’ statistics, i.e. statistics published at national level by the Member States, are compiled on the basis of national rules which may differ from EU rules. European ITGS are the official harmonised source of information about exports, imports and the trade balances of the EU, its Member States and the euro area.   Type of users and requirements As international trade forms a major part of the world economy, statistics on trade in goods are an instrument of primary importance for numerous public and private sector decision makers. For example, international trade statistics • enable EU authorities to prepare multilateral and bilateral negotiations under the common commercial policy; • enable EU authorities to evaluate the progress of the Single Market and the integration of EU economies; • enable EU authorities to define and implement anti-dumping policies; • constitute an essential source of information for balance of payments statistics, national accounts and economic studies; and • help EU businesses conduct market research and define their commercial strategy. Statistics satisfy these needs in a variety of ways. Users may need either annual aggregated or detailed monthly data on products or partner countries. They may be interested in trade values in current prices or at constant prices. Alternatively, their interest may be in quantities rather than in values. These examples, which are far from exhaustive, show the diversity of users and their requirements. Eurostat tries to meet these various needs and to adapt to a changing environment, such as changes due to globalisation.   Extrastat and Intrastat: two data collection systems Traditionally ITGS are based on the data collected by customs authorities on trade transactions between countries. Customs declarations are used for statistical purposes as the basic data source which provides detailed information on exports and imports of goods with a geographical breakdown. The first piece of EU legislation on ITGS was adopted in 1975; it provided general guidelines on data collection and obliged Member States to send their data to Eurostat. The advent of the Single Market on 1 January 1993, with its removal of customs formalities between Member States and subsequent loss of trade statistics data sources, required the establishment of a new data collection system: Intrastat.. Since then ITGS are based on two data collection systems: Extrastat and Intrastat. Extrastat data on trade in goods with non-EU countries are collected by customs authorities and are based on the records of trade transactions in customs declarations, whereas Intrastat data are directly collected from intra-EU trade operators once a month. Alternative data sources may be used for some specific goods and movements like for among with ships, aircraft, gas and electricity.   Aggregated versus detailed data International trade in goods statistics are published through different datasets grouped into two categories:Aggregated data which refer to macroeconomic indicators for the EU and euro area. Data are aggregated by broad product categories, both monthly (short-term indicators) and annually (long-term indicators). Broad product categories are defined as one-digit codes of the Standard International Trade Classification (SITC) or aggregates of the Broad Economic Categories (BEC); andDetailed data which refer to the most detailed level of the following product nomenclatures: the Combined Nomenclature (CN), the SITC, the BEC, the Classification of Products by Activity (CPA) and the Standard Goods Classification for Transport Statistics/Revised (NSTR). Detailed data also contain aggregations at higher levels.   Statistical dimensions The frequency at which the data are compiled (data periodicity) and the product nomenclature differ depending on the dataset, but the following statistical fields are always available:reporting country: country or geo-economic area such as EU or euro area;reference period: month and/or year;trade flows: import and export;product according to the relevant classification; andpartner country: EU Member State, non-EU country or geo-economic area. Besides the dimensions listed above, specific datasets contain information on the mode of transport (e.g. by sea, by air or by road) or the statistical procedure (normal trade versus trade for processing activities).

International trade in goods statistics (ITGS) published by Eurostat measure the value and quantity of goods traded between the EU Member States (intra-EU trade) and goods traded by the EU Member States with non-EU countries (extra-EU trade). ‘Goods’ means all movable property including electricity. ‘European’ means that the statistics are compiled on the basis of the concepts and definitions set out in EU legislation. ‘National’ statistics, i.e. statistics published at national level by the Member States, are compiled on the basis of national rules which may differ from EU rules. European ITGS are the official harmonised source of information about exports, imports and the trade balances of the EU, its Member States and the euro area.   Aggregated versus detailed data International trade in goods statistics are published through different datasets grouped into two categories:Aggregated data refer to macroeconomic indicators for the EU and euro area. Monthly (short-term indicators) and annual (long-term indicators) data are aggregated by broad product categories. Broad product categories are defined as one-digit codes of the Standard International Trade Classification (SITC) or aggregates of the Broad Economic Categories (BEC).Detailed data refer to the most detailed level of the following product nomenclatures: the Combined Nomenclature (CN), the SITC, the BEC, the Classification of Products by Activity (CPA) and the Standard Goods Classification for Transport Statistics/Revised (NSTR). Detailed data also contain product aggregations at higher levels.   Statistical dimensions Data periodicity (monthly or yearly) and product nomenclature (CN, SITC, BEC or CPA) differ depending on the dataset, but the following statistical fields are always available:reporting country: country or geo-economic area such as EU or euro area;partner country: EU Member State, non-EU country or geo-economic area.reference period: month and/or year;trade flows: import and export; andproduct according to the relevant classification. Besides the dimensions listed above, specific datasets contain information on the mode of transport (e.g. by sea, by air or by road) or the statistical procedure (normal trade versus trade for processing activities).

A yield curve (which is known as the term structure of interest rates) represents the relationship between market remuneration (interest) rates and the remaining time to maturity of debt securities. The zero coupon yield curves and their corresponding time series are calculated using "AAA-rated" euro area central government bonds, i.e. debt securities with the most favourable credit risk assessment. They represent the yields to maturity of hypothetical zero coupon bonds. Source: European Central Bank.

Dataset includes European Economic economic forecast releases from Autumn 2017 through Winter 2023.

Imports are recorded by country of origin, exports by country of destination; quantities are regarded as imported or exported when they have crossed the political boundaries of the country, whether customs clearance has taken place or not.  The concept of the physical movement of flows applies. The monthly imports and exports data collections cover following energy commodities:solid  fuels (hard coal only)oil and petroleum productsgaselectricity      For solid fuels, crude oil and NGLs, imports and exports are reported by country of ultimate origin, respectively destination, while natural gas, refinery products and feedstocks as well as electricity are reported as coming from the country of last consignment. Quantities of crude oil and petroleum products imported or exported under processing agreements (i.e. refining on account) should be included. However, transit trade, international marine and aviation bunkers are excluded from this data set. Please note that this is different from the definition of natural gas trade in the annual gas questionnaire and from the definition in the previous monthly oil and gas questionnaire (before January 2013). For further information, please consult the Energy Statistics Regulation (Regulation (EC) 1099/2008 on energy statistics) and the reporting instructions. Monthly imports and exports of energy commodities cover the full spectrum of the 28 Member States of the European Union, EFTA States, candidate countries and potential candidates. Â

This table presents annual statistics on international trade in services of individual economies by some 100 service categories for trade-partner “World total”. It further contains aggregated figures for various groups of economies for selected principal service categories. The data presented are the result of the common work of UNCTAD and the World Trade Organization (WTO).

Exports by Country for Senegal

In view of the strong demand for cross-national indicators on the situation of families and children, the OECD Family Database was developed to provide cross-national indicators on family outcomes and family policies across the OECD countries, its enhanced engagement partners and EU member states. The database brings together information from various national and international databases, both from within the OECD and from external organisations. The database classifies indicators into four main dimensions: (i) structure of families, (ii) labour market position of families, (iii) public policies for families and children and (iv) child outcomes. Detailed information on the definitions, sources and methods used in the construction of the database can be found on the OECD Family Database webpage.

Note: Ex: <0.1,<0.2,<0.3 considered as 0.1,0.2,0.3 values  

The Price domain of FAOSTAT contains data on prices received by farmers (called Producer prices) for primary crops, live animals, livestock primary products as collected at the point of initial sale (prices paid at the farm-gate). Data are provided for over 160 countries and for some 200 commodities. The Price domain provides price data in three units: i) Local Currency Units (LCU) ii) Standard Local Currency (SLC) iii) US Dollars.

The Fertilizers by Product dataset contains information on product amounts for the Production, Trade, Agriculture Use and Other Uses of chemical and mineral fertilizers products, over the time series 2002-present. The fertilizer statistics data are validated separately for a set of over thirty individual products. Both straight and compound fertilizers are included.

This dataset FDI by counterpart area and by economic activity, BMD4 includes inward and outward Foreign Direct Investment (FDI) flows, positions and income by partner country and by economic activity for OECD reporting economies. It is a simplified dataset with fewer breakdowns compared to the other separate datasets specifically dedicated to FDI flows, FDI positions or FDI income by counterpart area, or by economic activity. In this dataset, FDI exclude resident SPEs, when they exist (unless otherwise stated, see metadata attached at the reporting country level); and inward FDI positions are allocated to the ultimate counterpart country when available (see metadata attached at the reporting country level). Inward and outward FDI statistics in this dataset are presented on a directional basis (unless otherwise stated, see metadata attached at the reporting country level); they are measured in USD millions, in millions of national currency and as a share of total (for FDI positions only). This dataset supports FDI indicators by counterpart area and by economic activity available from the OECD Data Portal. In 2014, many countries implemented the latest international standards for Foreign Direct Investment (FDI) statistics:the OECD’s Benchmark Definition of FDI, 4th edition (BMD4); andthe IMF’s Balance of Payments and International Investment Position Manual, 6th edition (BPM6) This OECD database was launched in March 2015 which includes the data series reported by national experts according to BMD4. The data are for the most part based on balance of payments statistics published by Central Banks and Statistical Offices following the recommendations of the IMF’s BPM6 and the OECD’s BMD4. However, some of the data relate to other sources such as notifications or approvals.

This dataset FDI by counterpart area and by economic activity, BMD4 and historical BMD3 includes long time series of FDI statistics by partner country and by industry. It uses available BMD4 series and combines them with BMD3 historical series (from the unrevised OECD FDI datasets according to BMD3) as far back as 2005 and identifies breaks in series. For selected countries, breaks in series were removed as there was no significant impact of BMD4 implementation. In this dataset, inward and outward FDI flows, positions and income include resident SPEs when they exist (unless otherwise stated, see metadata attached at the reporting country level); and they are allocated to the immediate counterpart country (unless otherwise specified, see metadata attached at the reporting country level). Inward and outward FDI statistics in this datset are presented on a directional basis (unless otherwise stated, see metadata attached at the reporting country level); they are measured in USD millions, in millions of national currency and as a share of total (for FDI positions only). In 2014, many countries implemented the latest international standards for Foreign Direct Investment (FDI) statistics:the OECD’s Benchmark Definition of FDI, 4th edition (BMD4); andthe IMF’s Balance of Payments and International Investment Position Manual, 6th edition (BPM6) This OECD database was launched in March 2015 which includes the data series reported by national experts according to BMD4. The data are for the most part based on balance of payments statistics published by Central Banks and Statistical Offices following the recommendations of the IMF’s BPM6 and the OECD’s BMD4. However, some of the data relate to other sources such as notifications or approvals.

This dataset FDI flows by counterpart area, BMD4 includes inward and outward Foreign Direct Investment (FDI) flows by partner country for OECD reporting economies: Inward FDI flows by partner country measure the value of cross-border direct investment transactions received by the reporting economy during a year, by source country, enabling, for example, the identification of the major sources of FDI for a specific OECD economy in that year. Inward FDI flows are allocated to the immediate investing country. Outward FDI flows by partner country measure the value of cross-border direct investment transactions from the reporting economy during a year, by destination country or region, enabling, for example, the identification of the major destinations of FDI for a specific OECD economy in that year. Outward FDI flows are allocated to the immediate counterpart country for all OECD countries. Inward and outward FDI flows by partner country are presented according to the directional principle (unless otherwise specified in the country level metadata); they are measured in USD millions and in millions of national currency.

This dataset FDI flows by economic activity, BMD4 includes inward and outward Foreign Direct Investment (FDI) flows by economic activity for OECD reporting economies:Inward FDI flows by economic activity measure the value of cross-border direct investment transactions received by the reporting economy in a specific industry during a year, enabling, for example, the identification of the most attractive industries for FDI in each OECD economy in that year.Outward FDI flows by economic activity measure the value of cross-border direct investment transactions from the reporting economy during a year, by industry. The industry sector corresponds to the activity of the direct investment enterprise or to the activity of the direct investor (more details on the activity allocation method for outward FDI flows are indicated in the metadata information attached at the country level). Inward and outward FDI flows by economic activity are presented according to the directional principle (unless otherwise specified in the country level metadata); they are measured in USD millions and in millions of national currency. A cross-classification of inward and outward FDI flows by major ISIC4 sections and by main geographic aggregates are also available for some OECD reporting economies. In 2014, many countries implemented the latest international standards for Foreign Direct Investment (FDI) statistics:the OECD’s Benchmark Definition of FDI, 4th edition (BMD4); andthe IMF’s Balance of Payments and International Investment Position Manual, 6th edition (BPM6) An OECD database was launched in March 2015 which includes the data series reported by national experts according to BMD4. The data are for the most part based on balance of payments statistics published by Central Banks and Statistical Offices following the recommendations of the IMF’s BPM6 and the OECD’s BMD4. However, some of the data relate to other sources such as notifications or approvals. Historical and unrevised series of FDI flows by economic activity under the previous BMD3 methodology can be accessed in the archived dataset FDI flows by industry.

This dataset FDI income by economic activity, BMD4 includes Foreign Direct Investment (FDI) payments and receipts by economic activity for OECD reporting economies:FDI income payments (or income on inward FDI) by economic activity measure the total returns within a year on direct investment stocks paid by enterprises in the reporting economy, in a specific industry, to their foreign investors.FDi income receipts (or income on outward FDI) by economic activity measure the total returns within a year on direct investment stocks received by investors in the reporting economy from their direct investment enterprises abroad, by industry. The industry sector corresponds to the activity of the direct investment enterprise or to the activity of the direct investor (more details on the activity allocation method for FDI income receipts are indicated in the metadata information attached at the country level). Income payments and receipts (or income on inward and outward FDI respectively) by economic activity are presented according to the directional principle (unless otherwise specified in the country level metadata); they are measured in USD millions and in millions of national currency. In 2014, many countries implemented the latest international standards for Foreign Direct Investment (FDI) statistics:the OECD’s Benchmark Definition of FDI, 4th edition (BMD4); andthe IMF’s Balance of Payments and International Investment Position Manual, 6th edition (BPM6) This OECD database was launched in March 2015 which includes the data series reported by national experts according to BMD4. The data are for the most part based on balance of payments statistics published by Central Banks and Statistical Offices following the recommendations of the IMF’s BPM6 and the OECD’s BMD4. However, some of the data relate to other sources such as notifications or approvals.

This dataset FDI income main aggregates, BMD4 is updated every quarter and includes annual and quarterly aggregate Foreign Direct Investment (FDI) income for OECD member countries and for non-OECD G20 countries (Argentina, Brazil, China, India, Indonesia, Saudi Arabia and South Africa), which are included in Balance of Payments (BOP) accounts.

This dataset FDI main aggregates, BMD4 is updated every quarter and includes quarterly and annual aggregate inward and outward Foreign Direct Investment (FDI) flows, positions and income for OECD reporting economies and for non-OECD G20 countries (Argentina, Brazil, China, India, Indonesia, Saudi Arabia and South Africa). It is a simplified dataset with fewer breakdowns compared to the other separate datasets specifically dedicated to FDI flows, FDI positions or FDI income aggregates. In this dataset, FDI statistics are presented on directional basis only (unless otherwise specified, see metadata attached at the reporting country level) and resident Special Purpose Entities (SPEs), when they exist, are excluded (unless otherwise stated, see metadata attached at the reporting country level). FDI aggregates are measured in USD millions, in millions of national currency and as a share of GDP.

This dataset FDI positions by counterpart area, BMD4 includes inward and outward Foreign Direct Investment (FDI) positions by partner country for OECD reporting economies:Inward FDI positions by partner country measure the total level of direct investment in the reporting economy at the end of the year, by source countries, enabling, for example, the identification of the major sources of FDI for a specific OECD economy. Inward FDI positions are allocated to the immediate investing country but inward FDI positions allocated to the ultimate investing country are also available for some OECD economies.Outward FDI positions by partner country measure the total level of direct investment from the reporting economy at the end of the year, by destination countries, enabling, for example, the identification of the major destinations of FDI for a specific OECD economy. Outward FDI positions are allocated to the immediate counterpart country for all OECD countries. Inward and outward FDI positions by partner country are presented according to the directional principle (unless otherwise specified in the country level metadata); they are measured in USD millions, in millions of national currency and as a share of total FDI positions. In 2014, many countries implemented the latest international standards for Foreign Direct Investment (FDI) statistics:the OECD’s Benchmark Definition of FDI, 4th edition (BMD4); andthe IMF’s Balance of Payments and International Investment Position Manual, 6th edition (BPM6) This OECD database was launched in March 2015 which includes the data series reported by national experts according to BMD4. The data are for the most part based on balance of payments statistics published by Central Banks and Statistical Offices following the recommendations of the IMF’s BPM6 and the OECD’s BMD4. However, some of the data relate to other sources such as notifications or approvals. Historical and unrevised series of FDI positions by counterpart area under the previous BMD3 methodology can be accessed in the archived dataset FDI positions by partner country.

This dataset FDI positions by economic activity, BMD4 includes inward and outward Foreign Direct Investment (FDI) positions by economic activity according to ISIC4 for OECD reporting economies:Inward FDI positions by economic activity measure the total level of direct investment in a specific industry of the reporting economy at the end of the year, enabling, for example, the identification of the most attractive industry sectors for FDI in each OECD economy.Outward FDI positions by economic activity measure the total level of direct investment from the reporting economy at the end of the year, by industry sector. The industry sector corresponds to the activity of the direct investment enterprise or to the activity of the direct investor (more details on the activity allocation method for outward FDI positions are indicated in the metadata information attached at the country level). Inward and outward FDI positions by economic activity are presented according to the directional principle (unless otherwise specified in the country level metadata); they are measured in USD millions, in millions of national currency and as a share of total FDI positions. A cross-classification of inward and outward FDI positions by major ISIC4 sections and by main geographic aggregates are also available for some OECD reporting economies. In 2014, many countries implemented the latest international standards for Foreign Direct Investment (FDI) statistics:the OECD’s Benchmark Definition of FDI, 4th edition (BMD4); andthe IMF’s Balance of Payments and International Investment Position Manual, 6th edition (BPM6) This OECD database was launched in March 2015 which includes the data series reported by national experts according to BMD4. The data are for the most part based on balance of payments statistics published by Central Banks and Statistical Offices following the recommendations of the IMF’s BPM6 and the OECD’s BMD4. However, some of the data relate to other sources such as notifications or approvals. Historical and unrevised series of FDI positions by economic activity under the previous BMD3 methodology can be accessed in the archived dataset FDI positions by industry.

This dataset FDI positions main aggregates, BMD4 is updated every quarter and includes annual aggregate Foreign Direct Investment (FDI) positions for OECD member countries and for non-OECD G20 countries (Argentina, Brazil, China, India, Indonesia, Saudi Arabia and South Africa), which are included in International Investment Position (IIP) accounts. FDI positions record the total level of direct investment at a given point in time, usually the end of a quarter or of a year.

The FDI Regulatory Restrictiveness Index (FDI Index) measures statutory restrictions on foreign direct investment across 22 economic sectors. It gauges the restrictiveness of a country’s FDI rules by looking at the four main types of restrictions on FDI: 1) Foreign equity limitations; 2) Discriminatory screening or approval mechanisms; 3) Restrictions on the employment of foreigners as key personnel and 4) Other operational restrictions, e.g. restrictions on branching and on capital repatriation or on land ownership by foreign-owend enterprises. Restrictions are evaluated on a 0 (open) to 1 (closed) scale. The overall restrictiveness index is the average of sectoral scores. The discriminatory nature of measures, i.e. when they apply to foreign investors only, is the central criterion for scoring a measure. State ownership and state monopolies, to the extent they are not discriminatory towards foreigners, are not scored. The FDI Index is not a full measure of a country’s investment climate. A range of other factors come into play, including how FDI rules are implemented. Entry barriers can also arise for other reasons, including state ownership in key sectors. A country’s ability to attract FDI will be affected by others factors such as the size of its market, the extent of its integration with neighbours and even geography among other. Nonetheless, FDI rules can be a critical determinant of a country’s attractiveness to foreign investors.

Financial flows and stocks data are often referred to collectively in the national accounts framework as 'financial accounts'. Financial flows consist of transactions and other flows, and represent the difference between the opening financial balance sheet at the start of the year and the closing balance sheet at the end of the year. The data are compiled in accordance with the European System of Accounts (ESA 2010), which came into force in September 2014, and are presented here in the following tables: 'Financial transactions', 'Other changes in volume', 'Revaluation account', and 'Financial balance sheets'. 

Financial Indicators aim to capture in quantitative terms an important but heterogeneous and fast evolving area. Key factors driving this change are: globalisation of the financial markets; maturing of national financial markets and therefore the structure of these markets required to service their needs; increased sophistication of the actors in these markets; rapid technological change; and evolving regulatory frameworks. Financial institutions react and adapt to these conditions by changing their strategies; by specialising, by diversifying or concentrating their activities, and by extending through mergers and acquisitions. As a consequence, there is almost constant evolution in the institutional structures in which financial markets operate.   OECD statistics contact   Statistics and Data Directorate

The Financial Soundness Indicators (FSIs) were developed by the IMF, together with the international community, with aim of supporting analysis and assessing strengths and vulnerabilities of financial systems. The Statistics Department of the IMF, disseminates data and metadata on selected FSIs provided by participating countries. For a description of the various FSIs, as well as the consolidation basis, consolidation adjustments, and accounting rules followed, please refer to the concepts and definitions document in the document tab. Reporting countries compile FSI data using different methodologies, which may also vary for different points in time for the same country. Users are advised to consult the accompanying metadata to conduct more meaning cross-country comparisons or to assess the evolution of a given FSI for any of the countries.

National Accounts - Volume IIIa - Financial Accounts - Flows, which record, by type of financial instruments, the financial transactions between institutional sectors, and are presented in two tables: Financial accounts, consolidated and Financial accounts, non-consolidated.

Food Balance Sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply and its utilization. The total quantity of foodstuffs produced in a country added to the total quantity imported and adjusted to any change in stocks that may have occurred since the beginning of the reference period gives the supply available during that period. On the utilization side a distinction is made between the quantities exported, fed to livestock, used for seed, put to manufacture for food use and non-food uses, losses during storage and transportation, and food supplies available for human consumption. The per caput supply of each such food item available for human consumption is then obtained by dividing the respective quantity by the related data on the population actually partaking of it. Data on per caput food supplies are expressed in terms of quantity and - by applying appropriate food composition factors for all primary and processed products - also in terms of caloric value and protein and fat content.

The Food Price Monitoring Tool intends to analyse the available data on price developments through the supply chain. The supply chain is a series of economic activities that are performed by different economic actors that contribute to the production and distribution of one consumer product or a group of consumer products. The Food Price Monitoring Tool monitors 15 supply chains. It compares the price indices of four stages of the supply chain:Retail sector: the harmonised index of consumer prices (HICP)Domestic food industry: the domestic producer price index (PPId)Imported products: the import price index based on unit values from international trade in goods statisticsAgricultural commodities: the agricultural commodity prices index (ACP)

This dataset contains information on foreign direct investment (FDI) inward and outward flows and stock, expressed in millions of dollars. Foreign direct investment (FDI) is an investment made by a resident enterprise in one economy (direct investor or parent enterprise) with the objective of establishing a lasting interest in an enterprise that is resident in another economy (direct investment enterprise or foreign affiliate). The lasting interest implies the existence of a long-term relationship between the direct investor and the direct investment enterprise and a significant degree of influence on the management of the enterprise. The ownership of 10% or more of the voting power of a direct investment enterprise by a direct investor is evidence of such a relationship. FDI flows comprise mainly three components:acquisition or disposal of equity capital. FDI includes the initial equity transaction that meets the 10% threshold and all subsequent financial transactions and positions between the direct investor and the direct investment enterprise;reinvestment of earnings which are not distributed as dividends;inter-company debt.   FDI flows are transactions recorded during the reference period (typically year or quarter). FDI stocks are the accumulated value held at the end of the reference period (typically year or quarter). In 2014, many countries implemented the new guidelines for the compilation of FDI data based on the Sixth edition of the Balance of Payments and International Investment Position Manual (BPM6) and the Fourth edition of OECD Benchmark Definition of Foreign Direct Investment (BD4). One of the major changes introduced in BPM6 and BD4 is the presentation of FDI statistics on an asset/liability basis instead of the directional principle (as recommended by the previous editions of these guidelines). On an asset/liability basis, direct investment statistics are organized according to whether the investment relates to an asset or a liability for the reporting country. Under the directional principle, the direct investment statistics are organized according to the direction of the investment for the reporting country - either inward or outward. The two presentations differ in their treatment of reverse investment (reverse investment is when an affiliate provides loans to its parent). Under the directional presentation, reverse investment is subtracted to derive the total outward or inward investment of the reporting economy. Therefore, FDI statistics on an asset/liability basis tends to be higher than those under the directional principle, but such is not always the case. While the presentation on an asset/liability basis is appropriate for macroeconomic analysis (i.e. the impact on the balance of payments), the presentation on directional principle is more appropriate to assist policymakers and government officials to formulate investment policies. This is because the presentation of the FDI data on directional basis reflects the direction of influence by the foreign direct investor underlying the direct investment: inward or outward direct investment. FDI data in this table are on directional principle, unless otherwise indicated.

Note: " Degree of openness (in%) value for 2019 has been modified from 13 to 0.13 as it looks printing mistake at the source. There is no evidence to shoot up in 2019.

Foreign Trade of Djibouti

Direction of Trade of Ethiopia. Note: Date 2018/19 took as 2019 while considering quarterly dates. 

International Merchandise Trade Statistics

Foreign Trade Statistics of Lesotho

   

Foreign Trade Statistics of Namibia

Monthly summary on foreign trade statistics  

Qatar: Foreign Merchandise Trade The foreign trade data reflects a clear image of the stages of economical growth in the State of Qatar, as it shows the commodities flow in the shape of national exports, re-exports, and imports to / from different countries of the world. The foreign trade tables contains detailed data for visible imports by country of origin and Exports and Re-Exports by country of destination. The commodity tables are classified by sections and items of the Harmonized System (H.S.) issued by World Customs Organization, which was adapted according to GCC’s needs to meet the actual movement of foreign trade in the region, in addition to other statistical tables. The customs declaration entry issued by Customs Department is the main source of statistical information according to the Special Trade System adopted by the State of Qatar.

International Trade in Commodities in UAE

The database contains data on the production and trade in roundwood and primary wood and paper products for all countries and territories in the world. The main types of primary forest products included in are: roundwood, sawnwood, wood-based panels, pulp, and paper and paperboard. These products are detailed further. The definitions are available. The database contains details of the following topics: - Roundwood removals (production) by type of wood and assortment - Production and trade in roundwood, woodfuel and other basic products - Industrial roundwood by assortment and species - Sawnwood, panels and other primary products - Pulp and paper & paperboard. More detailed information on wood products, including definitions, can be found at http://www.fao.org/forestry/statistics/80572/en/

Freedom Status obtained by Combined Average of the Political Rights and Civil Liberties Ratings (Freedom Rating) Range 1-7; 1-2.5 Free; 3-5: Partly Free and 5.5-7: Not Free The score for the A. Electoral Process subcategory The score for the B. Political Pluralism and Participation subcategory The score for the C. Functioning of Government subcategory The score for the Political Rights category The score for the D. Freedom of Expression and Belief subcategory The score for the E. Associational and Organizational Rights subcategory The score for the F. Rule of Law subcategory The score for the G. Personal Autonomy and Individual Rights subcategory The score for the Civil Liberties category Total aggregate Score for all categories  

Date is taken as per country metadata, and which is not having any metadata date is considered as 2023

Data in this domain constitute only a small part of the entire National Accounts data range available from Eurostat. Annual and quarterly national accounts are compiled in accordance with the European System of Accounts - ESA 2010 as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013. The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. Further information on the transition from ESA 95 to ESA 2010 is presented on the Eurostat website. The annual data of this domain consists of the following collections: 1. Main GDP aggregates: main components from the output, expenditure and income side.nama_10_gdp: GDP and main components (output, expenditure and income) The quarterly data of this domain consists of the following collections 1. Main GDP aggregates, main components from the output, expenditure and income side, expenditure breakdowns by industry and assets. namq_10_ma: Main GDP aggregatesnamq_10_gdp: GDP and main components (output, expenditure and income)namq_10_fcs: Final consumption aggregates by durabilitynamq_10_exi: Exports and imports by Member States of the EU/third countries 2. Breakdowns of GDP aggregates and employment data by main industries and asset classes. namq_10_bbr: Basic breakdowns main GDP aggregates and employment (by industry and assets)namq_10_a10: Gross value added and income by A*10 industrynamq_10_an6: Gross fixed capital formation by AN_F6 asset typenamq_10_a10_e: Employment by A*10 industry breakdowns Geographical entities covered are the European Union, the euro area, EU Member States, Candidate Countries, EFTA countries, US, Japan and possibly other countries on an ad-hoc basis. Data sources: National Statistical Institutes.

This dataset provides information on gross domestic product (GDP), total and per capita at current and constant (2010) prices also it contains annual average growth rates of gross domestic product (GDP), total and per capita, in per cent. The total GDP is expressed in millions of dollars, while GDP per capita is expressed in dollars.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Gender Statistics Publication: https://datacatalog.worldbank.org/dataset/gender-statistics License: http://creativecommons.org/licenses/by/4.0/

The general government deficit/surplus is defined in the Maastricht Treaty as general government net lending (+)/net borrowing (-) according to the European System of Accounts. The general government sector comprises central government, state government, local government, and social security funds. The relevant definitions are provided in Council Regulation 479/2009, as amended.

'The TRACE Matrix measures business bribery risk in all countries. Developed in collaboration with RAND Corporation, the TRACE Matrix provides the business community with a powerful new tool for anti-bribery risk assessment. It assesses countries across four domains - Business Interactions with Government, Anti-bribery Laws and Enforcement, Government and Civil Service Transparency, and the Capacity for Civil Society Oversight, including the role of the media - as well as nine sub-domains. Business interactions with government includes the sub-domains of “contact with government,” “expectation of paying bribes” and “regulatory burden.” These indicators capture aspects of the “keys with government” that TRACE identified as very important for business bribery through regulatory and business interviews they conducted. Anti-corruption laws enacted by a country and information about enforcement of those laws. Government and civil service transparency, which includes indicators concerning whether government budgets are publicly available and whether there are regulations addressing conflicts of interest for civil servants. Information concerning the extent of press freedom and social development, both of which serve as indicators of a robust civil society that can provide government oversight. The overall country risk score is a combined and weighted score of four domains . For each of these four "domains" (and related sub-domains), the TRACE Matrix aggregates relevant data obtained from leading public interest and international organizations, including the United Nations, the World Bank and the World Economic Forum. Based on statistical analysis of this information, each country is assigned not only an overall score between 1 and 100 — with 100 representing the greatest risk — but also scores for each of the four domains and nine sub-domains. '  TRANSLATE with xEnglishArabicHebrewPolishBulgarianHindiPortugueseCatalanHmong DawRomanianChinese SimplifiedHungarianRussianChinese TraditionalIndonesianSlovakCzechItalianSlovenianDanishJapaneseSpanishDutchKlingonSwedishEnglishKoreanThaiEstonianLatvianTurkishFinnishLithuanianUkrainianFrenchMalayUrduGermanMalteseVietnameseGreekNorwegianWelshHaitian CreolePersian  TRANSLATE with COPY THE URL BELOW BackEMBED THE SNIPPET BELOW IN YOUR SITEEnable collaborative features and customize widget: Bing Webmaster PortalBack

Data cited at: Germanwatch-https://www.germanwatch.org/en/cri 

Knoema's Global Commodities Summary dataset covers select major commodities traded globally with summary information on pricing and trade from major international data sources. The dataset is available exclusively to subscribers to the Knoema Commodities Data Pack collection.

Data cited at: The World Economic Forum https://www.weforum.org/ Topic: The Global Competitiveness Report Publication URL: https://www.weforum.org/reports/the-global-competitiveness-report-2020 License: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode

DHL Global Connectedness Report, released in partnership with New York University’s Stern School of Business, unveils a remarkable finding: Globalization reached a record high in 2022 and has remained near that level in 2023

The Global Debt Database (GDD) is the result of a multiyear investigative process that started with the October 2016 Fiscal Monitor. The dataset includes total gross debt of the (private and public) non financial sector for an unbalanced panel of 190 advanced economies, emerging market economies and low-income countries, dating back to 1950. For more details on the methodology and definitions, please refer to Mbaye, Moreno Badia and Chae (2018). 

Global Entrepreneurship Index provides information about global entrepreneurship sub Index ranks and scoring of all countries. It also provides information about certain indicators like attitudes, abilities and aspirations with their ranks and scores

Research by the Global Burden of Disease Health Financing Collaborator Network produced projected health spending estimates for 2019-2050 for 204 countries and territories. The estimates cover total health spending, health spending disaggregated by source into three domestic financing source categories (government, out-of-pocket, and Prepaid Private), and development assistance for health (DAH). Retrospective health spending estimates for 1995-2018 and key covariates (including GDP per capita, total government spending, total fertility rate, and fraction of the population older than 65 years) were used to forecast GDP and health spending through 2050. Estimates are reported in constant 2020 US dollars, constant 2020 purchasing-power parity-adjusted (PPP) dollars, and as a percent of gross domestic product.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Global Financial Development Publication: https://datacatalog.worldbank.org/dataset/global-financial-development License: http://creativecommons.org/licenses/by/4.0/   The Global Financial Development Database is an extensive dataset of financial system characteristics for 206 economies. The database includes measures of (1) size of financial institutions and markets (financial depth), (2) degree to which individuals can and do use financial services (access), (3) efficiency of financial intermediaries and markets in intermediating resources and facilitating financial transactions (efficiency), and (4) stability of financial institutions and markets (stability).For a complete description of the dataset and a discussion of the underlying literature, see: Martin Cihak; Asli Demirguc-Kunt; Erik Feyen; and Ross Levine, 2012. "Benchmarking Financial Systems Around the World." World Bank Policy Research Working Paper 6175, World Bank, Washington, D.C.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Global Financial Inclusion (Global Findex) Database Publication: https://datacatalog.worldbank.org/dataset/global-financial-inclusion-global-findex-database License: http://creativecommons.org/licenses/by/4.0/   The Global Financial Inclusion Database provides 850+ country-level indicators of financial inclusion summarized for all adults and disaggregated by key demographic characteristics-gender, age, education, income, employment status and rural residence. Covering more than 140 economies, the indicators of financial inclusion measure how people save, borrow, make payments and manage risk. The reference citation for the data is: Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar, and Jake Hess. 2018. The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution. World Bank: Washington, DC.

Global Financial Stability Report, October 2023: Financial and Climate Policies for a High-Interest-Rate Era

Data cited at: The World Economic Forum https://www.weforum.org/ Topic: Global Gender Gap Report 2023 Publication URL: https://www.weforum.org/reports/global-gender-gap-report-2023 License: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode   The Global Gender Gap Index annually benchmarks the current state and evolution of gender parity across four key dimensions (Economic Participation and Opportunity, Educational Attainment, Health and Survival, and Political Empowerment). It is the longest-standing index tracking the progress of numerous countries’ efforts towards closing these gaps over time since its inception in 2006. This year, the 17th edition of the Global Gender Gap Index benchmarks gender parity across 146 countries, providing a basis for robust cross country analysis.

Data cited at: The World Economic Forum https://www.weforum.org/ Topic: The Global Gender Gap Report Publication URL: https://www.weforum.org/reports License: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode   This dataset provides education and skills related indicators that present in Global Gender Gap Report

Direct greenhouse gases: Carbon Dioxide (CO2), Methane (CH4), Nitrous Oxide (N2O), Hydrofluorocarbons (HFC-23, 32, 125, 134a, 143a, 152a, 227ea, 236fa, 245fa, 365mfc, 43-10-mee), Perfluorocarbons (PFCs: CF4, C2F6, C3F8, c-C4F8, C4F10, C5F12, C6F14, C7F16), Sulfur Hexafluoride (SF6), Nitrogen Trifluoride (NF3) and Sulfuryl Fluoride (SO2F2). Emissions are calculated by individual countries using country-specific information. The countries are organized in different world regions for illustration purposes. Emissions of some small countries are presented together with other countries depending on country definition and availability of activity statistics. Source: European Commission, Joint Research Centre (JRC)/PBL Netherlands Environmental Assessment Agency.

Global Hunger Index, 2023 The 2023 Global Hunger Index shows that since 2015 little progress has been made in reducing hunger. The 2023 GHI score for the world is 18.3, considered moderate. This is less than one point below the world’s 2015 GHI score of 19.1, indicating that progress on reducing hunger has largely stalled. In contrast, between 2000, 2008, and 2015, the world made significant headway against hunger. There has been an increase in the prevalence of undernourishment, one of the indicators used in the calculation of GHI scores, rising from a low of 7.5 percent in 2017 to 9.2 percent in 2022.

The Global Innovation Index 2023 captures the innovation ecosystem performance of 132 economies and tracks the most recent global innovation trends.  The GII 2023 tracks global innovation trends against a background of uncertainty caused by slow economic recovery from the COVID-19 pandemic, high-interest rates, and geopolitical conflict, but with the promise of the Digital Age and Deep Science innovation waves and technological progress.  

Data cited at:  Knowledge4All, United Nations Development Program & Mohammed Bin Rashid Al Maktoum Knowledge Foundation.

Note: It has been observed that LMC Automotive has been acquired by GlobalData, and no relevant/latest data is available publically. Refer https://www.globaldata.com/industries-we-cover/automotive/  for further information.

The Global Opportunity Index (GOI) answers a pressing need for information that's vital to a thriving global economy like what policies can governments pursue to attract foreign direct investment (FDI), expand their economies, and accelerate job creation, everything multinational companies, other investors, and development agencies need to know before making large-scale, long-term capital commitments.   Methodology The GOI considers economic and financial factors that influence investment activities as well as key business, legal and regulatory policies that governments can modify to support and often drive investments. Overall, it tracks countries’ performance on more than 50 variables aggregated in five categories, each measuring an aspect of a country’s attractiveness for investors: (1) its economic performance; (2) the ability for investors to access financial services; (3) the cost of doing business; (4) the level of support its institutions provide to businesses; and (5) the extent to which its institutions, policies, and legal system facilitate international integration.

Data cited at: Institute for Economics and Peace retrieved from Vision of Humanity  The Global Peace Index 2022

Data cited at: Global Petrol Prices web site - https://www.globalpetrolprices.com/ License: https://creativecommons.org/licenses/by-nc/4.0/ Data is getting collected Every Tuesday evening from the Global Petrol Prices website. Weekly Average data is available from 28-Dec-2015 onward. Monthly average price is available for the period of January, 2013 - July, 2013    

Highlights of the  Global Sustainable Competiveness Report 2023:Scandinavia continues to top the Sustainable Competitiveness Index: of the top 6 spots, 5 are Scandinavian. Sweden keeps topping the Index.Only one country in the Top 20 is not European: Japan on 12 (South Korea 21).For the first time, China (ranked 30) overtakes the US on rank 32.Germany ranks 15, The UK 16, and France 18.Brazil ranks 65, India 121, and Nigeria – Africa’s most populous nation – 156.Some of the least developed nations have a considerable higher GSCI ranking than their GDP would suggest (e.g. Colombia, Peu, Nepal, Bhutan, Bolivia.

Data cited at:  Institute for Economics & Peace and available from http://visionofhumanity.org/reports Note: The Year of data has been considered as year of publication, for example 2020 report is considered as year 2020.   The Global Terrorism Index (GTI) is a comprehensive study which accounts for the direct and indirect impact of terrorism in 163 countries in terms of its effect on lives lost, injuries, property damage and the psychological aftereffects of terrorism. This study covers 99.6 per cent of the world's population. It aggregates the most authoritative data source on terrorism today, the Global Terrorism Database (GTD) collated by the National Consortium for the Study of Terrorism and Responses to Terrorism (START) into a composite score in order to provide an ordinal ranking of nations on the negative impact of terrorism. The GTD is unique in that it consists of systematically and comprehensively coded data on domestic as well as international terrorist incidents and now includes more than 140,000 cases.  

This table shows exports, imports and sum/average of exports and imports as percentage of nominal gross domestic product (GDP). The indicators are calculated for trade in goods, trade in services and total trade in goods and services.

This dataset provides a comprehensive view of government expense, including detailed classifications of compensation of employees, use of goods and services, consumption of fixed capital, interest payable, subsidies payable, grants payable, social benefits, and other expense.

This dataset provides a comprehensive view of government revenue, including detailed classifications of taxes, social contributions, grants receivable, and other revenue.

This dataset provides a comprehensive view of the integrated balance sheet. In other words, changes between the opening and closing stock positions in assets and liabilities are explained through transactions, holding gains/losses, and other changes in the volume of assets and liabilities. Data on net investment in non-financial assets – a component of total expenditure – on its components and related stock positions are provided.

This dataset provides an overview of government operations and stock positions, as well as several derived balances. The Statement of Government Operations shows revenue and expense, with their main components, the operating balance and net lending/net borrowing, as well as financing. The Balance sheet shows stock positions in assets and liabilities, with their main components, as well as net worth and net financial worth. In addition, data on gross debt and net debt are included.

This dataset provides the whole set of OECD Annual government non-financial accounts and key indicators data and is recommended for users who wish to query a large amount of data. It is not designed for visualising results using the Table and Chart buttons.

Number of people who graduated from an education programme by field and sex.

The OECD Green Growth database contains selected indicators for monitoring progress towards green growth to support policy making and inform the public at large. The database synthesises data and indicators across a wide range of domains including a range of OECD databases as well as external data sources. The database covers OECD member and accession countries, key partners (including Brazil, China, India, Indonesia and South Africa) and other selected non-OECD countries.

In accordance with Articles 4 and 12 of the Climate Change Convention, and the relevant decisions of the Conference of the Parties, countries that are Parties to the Convention submit national greenhouse gas (GHG) inventories to the Climate Change secretariat. These submissions are made in accordance with the reporting requirements adopted under the Convention, such as The UNFCCC Reporting Guidelines on Annex I Inventories (document FCCC/SBSTA/2004/8) for Annex I Parties and Guidelines for the preparation of national communications for non-Annex I Parites (decision 17/CP.8). The inventory data are provided in the annual GHG inventory submissions by Annex I Parties and in the national communications under the Convention by non-Annex I Parties. The GHG data reported by Parties contain estimates for direct greenhouse gases, such as: CO2 - Carbon dioxide CH4 - Methane N2O - Nitrous oxide PFCs - Perfluorocarbons HFCs - Hydrofluorocarbons SF6 - Sulphur hexafluoride as well as for the indirect greenhouse gases such as SO2, NOx, CO and NMVOC.

Data cited at: CAIT, retrieved from Climate Watch Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2019, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report.

This dataset includes data on greenhouse gas emissions inventory, as reported to the European Environment Agency (EEA). Note that Eurostat is not the producer of these data, only re-publishes them. The European Union (EU) as a party to the United Nations Framework Convention on Climate Change (UNFCCC) reports annually its greenhouse gas inventory for the year t-2 and within the area covered by its Member States. The inventory contains data on carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), perfluorocarbons (PFCs), hydrofluorocarbons (HFCs), sulphur hexafluoride (SF6) and nitrogen trifluoride (NF3). The EU inventory is fully consistent with national greenhouse gas inventories compiled by the EU Member States. Values flagged with 'd' have the notation key 'IE' (included elsewhere) in the original dataset published by the EEA. Notation key combinations that include NE (not estimated), as well as values reported with the additional notation key used by EEA ' – ', are reported as missing values in the air_env_gge dataset. All notation keys combinations that include a C (confidential) are flagged as confidential. The notation keys NA and NO are not associated with a flag. EEA notation keys: NO – not occurring. NE – not estimated. NA – not applicable. IE – included elsewhere. C – confidential.

Regional accounts are a regional specification of the national accounts and therefore based on the same concepts and definitions as national accounts (see domain nama10). The main specific regional issues are addressed in chapter 13 of ESA2010, but not practically specified. For practical rules and recommendations on sources and methods see the publication "Manual on regional accounts methods": http://ec.europa.eu/eurostat/en/web/products-manuals-and-guidelines/-/KS-GQ-13-001 . Gross domestic product (GDP) at market prices is the final result of the production activity of resident producer units. It can be defined in three ways: 1. Output approach GDP is the sum of gross value added of the various institutional sectors or the various industries plus taxes and less subsidies on products (which are not allocated to sectors and industries). It is also the balancing item in the total economy production account. 2. Expenditure approach GDP is the sum of final uses of goods and services by resident institutional units (final consumption expenditure and gross capital formation), plus exports and minus imports of goods and services. At regional level the expenditure approach cannot be used in the EU, because there is no data on regional exports and imports.  3. Income approach GDP is the sum of uses in the total economy generation of income account: compensation of employees plus gross operating surplus and mixed income plus taxes on products less subsidies plus consumption of fixed capital. The different measures for the regional GDP are absolute figures in € and Purchasing Power Standards (PPS), figures per inhabitant and relative data compared to the EU Member States average.

Data in this domain constitute only a small part of the entire National Accounts data range available from Eurostat. Annual and quarterly national accounts are compiled in accordance with the European System of Accounts - ESA 2010 as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013. The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. Further information on the transition from ESA 95 to ESA 2010 is presented on the Eurostat website. The annual data of this domain consists of the following collections: 1. Main GDP aggregates: main components from the output, expenditure and income side.nama_10_gdp: GDP and main components (output, expenditure and income) The quarterly data of this domain consists of the following collections 1. Main GDP aggregates, main components from the output, expenditure and income side, expenditure breakdowns by industry and assets. namq_10_ma: Main GDP aggregatesnamq_10_gdp: GDP and main components (output, expenditure and income)namq_10_fcs: Final consumption aggregates by durabilitynamq_10_exi: Exports and imports by Member States of the EU/third countries 2. Breakdowns of GDP aggregates and employment data by main industries and asset classes. namq_10_bbr: Basic breakdowns main GDP aggregates and employment (by industry and assets)namq_10_a10: Gross value added and income by A*10 industrynamq_10_an6: Gross fixed capital formation by AN_F6 asset typenamq_10_a10_e: Employment by A*10 industry breakdowns Geographical entities covered are the European Union, the euro area, EU Member States, Candidate Countries, EFTA countries, US, Japan and possibly other countries on an ad-hoc basis. Data sources: National Statistical Institutes.

Harmonised Indices of Consumer Prices (HICP) give comparable measures of inflation for the countries and country groups for which they are produced. They are economic indicators that measure the change over time of the prices of consumer goods and services acquired by households. In other words, they are a set of consumer price indices (CPI) calculated according to a harmonised approach and a single set of definitions. In particular, HICP provide the official measure of consumer price inflation in the euro area for the purposes of monetary policy and the assessment of inflation convergence as required under the Maastricht criteria for accession to the euro. HICP are available for all EU Member States, Iceland, Norway and Switzerland. In addition to the individual country series there are three key country-group aggregate indices: the Monetary Union Index of Consumer Prices (MUICP or EA) covering the euro area countries, the European index of consumer prices (EICP or EU) including all Member States, and the European Economic Area index of consumer prices (EEAICP), which in addition to the EU also covers Iceland and Norway. The official country-group aggregates reflect the evolution of Economic and monetary union (EA), the EU and the EEA. The HICP for new Member States is chained into the aggregate indices at the time of accession. In addition to these official aggregates, Eurostat also computes, for analytical purposes, country aggregates with stable composition over time. For example, the aggregate 'EU-28' shows price indices covering all current 28 Member States since 1997. HICP for Turkey (candidate country) is also published. For the USA, a proxy-HICP for the all-items and main headings is available. The national HICP is produced by National Statistical Institutes, while the country-group aggregates are produced by Eurostat. The data released monthly on Eurostat's free dissemination database includes price indices and rates (monthly, annual and 12-month moving average changes). In addition to the headline figure 'all-items HICP', around one hundred sub-indices for different goods and services and over thirty special aggregates are made available. The relative weights for the indices, including the special aggregates, are published for the individual countries and for the country groups, once a year, with the January data. An early estimate of the overall inflation rate for the euro area, as well as for selected components, are published monthly, usually on the last working day of the reference month, both as a News Release and in the database. They are called 'HICP flash estimates'. HICP at constant tax rates (HICP-CT) follows the same computation principles as the HICP, but is based on prices at constant tax rates. The comparison with the standard HICP can show the potential impact of changes in indirect taxes (e.g. VAT and excise duties) on the overall inflation (more information).

Health care expenditure quantifies the economic resources dedicated to health functions, excluding capital investment. Healthcare expenditure concerns itself primarily with healthcare goods and services that are consumed by resident units, irrespective of where that consumption takes place (it may be in the rest of the world) or who is paying for it. As such, exports of healthcare goods and services (to non-resident units) are excluded, whereas imports of healthcare goods and services for final use are included. Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing scheme (e.g. social security, private insurance company, household).

Cancer follow up has been given for the range of 5 years. The highest range has been considered as for this period, for example 1995-2000 is considered as 2000.

OECD Health Data 2016 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.

OECD Health Data 2017 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.B1:B4

A System of Health Accounts 2011 provides an updated and systematic description of the financial flows related to the consumption of health care goods and services. As demands for information increase and more countries implement and institutionalise health accounts according to the system, the data produced are expected to be more comparable, more detailed and more policy relevant. It builds on the original OECD Manual, published in 2000 to create a single global framework for producing health expenditure accounts that can help track resource flows from sources to uses. It is the result of a collaborative effort between the OECD, WHO and the European Commission, and sets out in more detail the boundaries, the definitions and the concepts – responding to health care systems around the globe – from the simplest to the more complicated. The accounting framework is organised around a tri-axial system for the recording of health care expenditure, namely classifications of the functions of health care (ICHA-HC), health care provision (ICHA-HP), and financing schemes (ICHA-HF).

Health Nutrition and Population Statistics database provides key health, nutrition and population statistics gathered from a variety of international and national sources. Themes include global surgery, health financing, HIV/AIDS, immunization, infectious diseases, medical resources and usage, noncommunicable diseases, nutrition, population dynamics, reproductive health, universal health coverage, and water and sanitation.

This dataset presents core population health indicators, covering life expectancy; mortality indicators such as causes of mortality (by ICD codes), maternal and infant mortality, avoidable (preventable+treatable) mortality; potential years of life lost; perceived health status (also disaggregated by socio-economic status and education level); low birthweight; incidence of key communicable diseases; cancer incidence; injuries in road traffic accidents; and absence from work due to illness.

This dataset reports data on key aspects of the utilisation of healthcare, such as consultations with doctors and dentists, immunisation of children and the population aged 65+, cancer screening, hospital indicators such as discharges or average length of stay, diagnostic exams, surgical procedures and waiting times.

The Harmonised Index of Consumer Prices (HICP) gives comparable measures of inflation for the countries and country groups for which it is produced. It is an economic indicator that measures the change over time of the prices of consumer goods and services acquired by households. In other words, it is a set of consumer price indices (CPI) calculated according to a harmonised approach and a set of definitions as laid down in Regulations and recommendations. In addition, the HICP provides the official measure of consumer price inflation in the euro area for the purposes of monetary policy and the assessment of inflation convergence as required under the Maastricht criteria for accession to the euro. The HICP is available for all EU Member States, Iceland, Norway and Switzerland. In addition to the individual country series there are three key country-group aggregate indices: the euro area, the European Union (EU), and the European Economic Area (EEA), which, in addition to the EU, also covers Iceland and Norway, but not Liechtenstein. The official country-group aggregates reflect the changing country composition of the EA, the EU and the EEA. The HICP for new Member States is chained into the aggregate indices at the time of accession. For analytical purposes Eurostat also computes country-group aggregates with stable country composition over time. For example, the EU28 aggregate shows price indices covering all current 28 Member States since 1997. The HICP for Serbia and Turkey (candidate countries) are also published. That data are flagged 'd' ('definition differs'). A proxy-HICP for the all-items and main aggregates is available for the USA. National HICPs are produced by National Statistical Institutes (NSIs), while the country-group aggregates are produced by Eurostat. The data released monthly on Eurostat's free dissemination database include price indices and rates of change (monthly, annual and 12-month moving average changes). In addition to the headline figure 'all-items HICP', around four hundred sub-indices for different goods and services and over thirty special aggregates are available, including the HICP at administered prices (HICP-AP). Once a year, with the release of the January data, the relative weights for the indices and the special aggregates, are published for the individual countries and for the European aggregates. The composition of the HICP-AP aggregates, i.e. which sub-indices are classified as mainly or fully administered by each Member State, is also updated at the same time. Eurostat publishes early estimates, called 'HICP flash estimates', of the euro area overall inflation rate and selected components. They are published monthly, usually on the last working day of the reference month, and disseminated in a news release, in the database and in a Statistics Explained article. The HICP at constant tax rates (HICP-CT) follows the same computation principles as the HICP, but is based on prices at constant tax rates. The comparison with the standard HICP can show the potential impact of changes in indirect taxes, such as VAT and excise duties, on the overall inflation (more information). Flags Flags provide information about the 'status' of the data or a specific data value. The following flags are used for the HICP data in the Eurostat online database: p = provisional data: Data is flagged as provisional by the National Statistical Institutes to signal that data are still being treated or validated. The 'p' flag remains attached to the HICP data values in question for one month only. r = revised data. In the case when the most recent figures published differ from previously disseminated data, they are flagged with 'r'. Countries are allowed to revise their HICP figures at any point and, therefore, revised figures may appear in historic data. The 'r' flag remains attached to the HICP data values in question for one month only. e = estimated data. All the figures of the HICP flash estimate are marked with the 'e' flag. d = definition differs, meaning that the national definition of a series differs from the ECOICOP (European Classification of Individual Consumption according to Purpose) definition. It is also used for data values from countries for which conformity with the requirements of the HICP methodology has not yet been evaluated by Eurostat, including candidate countries, pre-candidate countries, new EU Member States and the United States of America. u = unreliable data. Data is flagged as unreliable by the National Statistical Institutes. The p, e, d and u flags described here do not affect the higher level of aggregation when assigned to a figure.

Data cited at: https://mauritius.opendataforafrica.org/HDIM2016

Data Cited at: UNITED NATIONS DEVELOPMENT PROGRAMME, Human Development Data Center The Human Development Index (HDI) is a summary measure of achievements in three key dimensions of human development: a long and healthy life, access to knowledge and a decent standard of living. The HDI is the geometric mean of normalized indices for each of the the three dimensions.

Data cited at: International Telecommunication Union-https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx 

The Fiscal Monitor surveys and analyzes the latest public finance developments, it updates fiscal implications of the crisis and medium-term fiscal projections and assesses policies to put public finances on a sustainable footing. 

The FAS is the key source of global supply-side data on financial inclusion, encompassing data on access to and usage of financial services by firms and households that can be compared across countries and over time. Contains 180 time series and 65 indicators that are expressed as ratios to GDP, land area, or adult population to facilitate cross-economy comparisons. Provision of FAS data is voluntary.

The baseline forecast is for the world economy to continue growing at 3.2 percent during 2024 and 2025, at the same pace as in 2023. A slight acceleration for advanced economies—where growth is expected to rise from 1.6 percent in 2023 to 1.7 percent in 2024 and 1.8 percent in 2025—will be offset by a modest slowdown in emerging market and developing economies from 4.3 percent in 2023 to 4.2 percent in both 2024 and 2025. The forecast for global growth five years from now—at 3.1 percent—is at its lowest in decades. Global inflation is forecast to decline steadily, from 6.8 percent in 2023 to 5.9 percent in 2024 and 4.5 percent in 2025, with advanced economies returning to their inflation targets sooner than emerging market and developing economies. Core inflation is generally projected to decline more gradually.

The annual Eurostat's collections on statistics on international migration flows are structured as follows:   Data Collection Info & Legislation NOWCAST Annual data collection on provisional monthly data on live births and deaths covering at least six months of the reference year (Article 4.3 of the Commission implementing regulation (EU) No 205/2014) and provisional monthly data on migrants covering at least six months of the reference year on voluntary basis DEMOBAL Demographic balance Annual data collection on provisional data on population, total live births and total deaths at national level (Article 4.1 of the Commission implementing regulation (EU) No 205/2014) and provisional data on total migrants at national level on voluntary basis UNIDEMO Unified Demographic The most extended annual collection on demography and migration, collecting data at national and regional level for population, births, deaths, immigrants,  emigrants, marriages and divorces by a large number of breakdowns. (Art. 3 of the Regulation (EU) No 1260/2013 and Art. 3 of the Regulation (EC) No 862/2007)   The annual demography data collections aim at collecting from the National Statistical Institutes both mandatory data and voluntary data. The mandatory data are those defined by the legislation listed on "6.1. Institutional Mandate - legal acts and other agreements".   The migration data collected on voluntary basis depend on the availability and on the quality of information available in the National Statistical Institutes.   For more specific information on mandatory/voluntary data collection see 6.1. Institutional Mandate - legal acts and other agreements.   The following data on migrants are collected under Unified Demographic data collection:   Immigrants by age, sex and by:                  a.   country of citizenship                  b.   country of birth                  c.   country of previous residenceImmigrants by country of citizenship and country of birthEmigrants by age, sex and by:                   a.   country of citizenship                   b.   country of birth                   c.   country of next residence 

Imports are recorded by country of origin, exports by country of destination; quantities are regarded as imported or exported when they have crossed the political boundaries of the country, whether customs clearance has taken place or not.  The concept of the physical movement of flows applies. The monthly imports and exports data collections cover following energy commodities:solid  fuels (hard coal only)oil and petroleum productsgaselectricity      For solid fuels, crude oil and NGLs, imports and exports are reported by country of ultimate origin, respectively destination, while natural gas, refinery products and feedstocks as well as electricity are reported as coming from the country of last consignment. Quantities of crude oil and petroleum products imported or exported under processing agreements (i.e. refining on account) should be included. However, transit trade, international marine and aviation bunkers are excluded from this data set. Please note that this is different from the definition of natural gas trade in the annual gas questionnaire and from the definition in the previous monthly oil and gas questionnaire (before January 2013). For further information, please consult the Energy Statistics Regulation (Regulation (EC) 1099/2008 on energy statistics) and the reporting instructions. Monthly imports and exports of energy commodities cover the full spectrum of the 28 Member States of the European Union, EFTA States, candidate countries and potential candidates. Â

Inbound tourism comprises the activities of a non-resident visitor within the country of reference.

The OECD Income Distribution Database (IDD) offers data on levels and trends in income inequality and poverty and is updated on a rolling basis, two to three times a year.

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

Please refer the latest version here : https://knoema.com/UNIDOISR2022/industrial-statistics-database-indstat-4-2022-isic-revision-4 Data cited at- https://stat.unido.org/database/INDSTAT%204%202022,%20ISIC%20Revision%204

The UNIDO Industrial Statistics Database at the 4-digit level of ISIC (INDSTAT4) contains highly disaggregated data on the manufacturing sector. Comparability of data over time and across the countries has been the main priority of developing and updating this database. INDSTAT4 offers a unique possibility of in-depth analysis of the structural transformation of economies over time.The database contains seven principle indicators of industrial statistics. The data are arranged at the 3- and 4-digit level of the International Standard Industrial Classification of All Economic Activities (ISIC) Revision 3  and 4 pertaining to the manufacturing, which comprises more than 150 manufacturing sectors and sub-sectors.The database contains following indicators of industrial statistics:Number of establishments.Number of employees.Wages and salaries.Output.Value added.Gross fixed capital formation.Number of female employees Note: Knoema calculated the indicator Productivity Data cited at- https://stat.unido.org/database/INDSTAT%204%202022,%20ISIC%20Revision%204

Eurostat Dataset Id:ei_bsin_m_r2 Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published:as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)

Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the International Labour Migration Statistics (ILMS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. This harmonized series for informal employment is derived using the same set of criteria across countries to improve comparability. The criteria used are based on employment status, institutional sector, destination of production, bookkeeping, registration, social security contribution, places of work and size. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. This harmonized series for informal employment is derived using the same set of criteria across countries to improve comparability. The criteria used are based on employment status, institutional sector, destination of production, bookkeeping, registration, social security contribution, places of work and size. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. This harmonized series for informal employment is derived using the same set of criteria across countries to improve comparability. The criteria used are based on employment status, institutional sector, destination of production, bookkeeping, registration, social security contribution, places of work and size. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

The infra-annual labour statistics dataset contains predominantly monthly and quarterly labour statistics, and associated statistical methodological information, for the OECD member countries and selected other economies. It covers countries that compile labour statistics from sample household surveys on a monthly or quarterly basis. It is widely accepted that household surveys are the best source for labour market key statistics. In such surveys, information is collected from people living in households through a representative sample and the surveys are based on standard methodology and procedures used internationally. The subjects available cover: working age population by age; active and inactive labour force by age; employment by economic activity, by working time and by status; and, unemployment (including monthly unemployment) by age and by duration. Data is expressed in levels (thousands of persons) or rates (e.g. employment rate) where applicable. The relationship between these several measures are as follow: • Working age population = Labour force population + Inactive population • Labour force population = Employed population + Unemployed population • Employment rate = Employed population / Working age population • Unemployment rate = Unemployed population / Labour force population • Labour force participation rate = Labour force population / Working age population The infra-annual labour statistics compiled for all OECD member countries, are drawn from Labour Force Surveys based on definition provided by the 19th Conference of Labour Statisticians in 2013. The uniform application of these definitions across all OECD member countries results in estimates that are internationally comparable.

The Registered Unemployment and Job Vacancies statistics is a subset of the Infra-annual Labour Force Statistics database, which contains predominantly quarterly and monthly statistics, and associated statistical methodological information, for the OECD member countries and selected other economies. There are basically two sources for unemployment statistics: labour force surveys and administrative data. Surveys are based on standard methodology and procedures used all over the world while administrative data are subject to national legislations which evolve through time. Consequently registered unemployment data are not comparable across countries. The relationship between survey and registered unemployment is not the same for all countries. Number of registered unemployed persons and registered unemployment rates are presented here because they are monthly and quickly available after their reference period. The job vacancies data provides estimates of the number of unfilled job vacancies across national economies. Series give an indication of the labour demand while the unemployment is linked with the labour supply.

Geographic coverage OECD countries, Selected African and Asian countries, Selected Latin American countries Institutional coverage The insurance industry is a key component of the economy by virtue of the amount of premiums it collects, the scale of its investment and, more fundamentally, the essential social and economic role it plays in covering personal and business risks. The "OECD Insurance Statistics" publication provides major official insurance statistics for all OECD countries. The reader will find information on the diverse activities of this industry and on international insurance market trends. The data, which are standardised as far as possible, are broken down under numerous sub-headings, and a series of indicators makes the characteristics of the national markets more readily comprehensible. This publication is an essential tool for civil servants, businessmen and academics working in the insurance field. Item coverage This part consists of tables by indicators, which reflect the most significant characteristics of the OECD insurance market. In most cases, the tables contain data of all OECD countries as well as aggregated "OECD", "EU15" (the 15 member countries of the European Union in 1995) and "NAFTA" data from 1983 to 2015, for the following categories: - life insurance, - non-life insurance - and total. The premiums amounts are converted from national currencies into US dollar. Exchange rates used are end-of-period exchanges rates for all variables valued at the end of the year, and period-average for variables representig a flow during the year.

The present data collection consists of the following indicators:Interest rates : Day-to-day money market interest rates, 3-month interest rates, Euro yields and Long term government bond yields - Maastricht definitionEuro/Ecu exchange rates: Exchange rates against the ECU/euroEffective exchange rates indices : Nominal Effective Exchange Rate, Real Effective Exchange Rate Â

Data retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/   FRED Economic Research Division "International Data" dataset contains series for the following categories: money, banking & finance; national accounts; population, employment & labor markets; production & business activity; prices; work started; consumer opinion surveys; business tendency surveys (construction); business tendency surveys (services); business tendency surveys (manufacturing); business tendency surveys (non-manufacturing); leading indicators OECD; business tendency surveys (retail trade).

Data cited at: International Financial Statistics (IFS), The International Monetary Fund. The International Financial Statistics database covers about 200 countries and areas, with some aggregates calculated for selected regions, plus some world totals. Topics covered include balance of payments, commodity prices, exchange rates, fund position, government finance, industrial production, interest rates, international investment position, international liquidity, international transactions, labor statistics, money and banking, national accounts, population, prices, and real effective exchange rates. The International Financial Statistics is based on various IMF data collections. It includes exchange rates series for all Fund member countries plus Anguilla, Aruba, China, PR: Hong Kong, China, PR: Macao, Montserrat, and the Netherlands Antilles. It also includes major Fund accounts series, real effective exchange rates, and other world, area, and country series. Data are available for most IMF member countries with some aggregates calculated for select regions, plus some world totals. National Accounts, Indicators of Economic Activity, Labor Markets, Prices, Government and Public Sector Finance, Financial Indicators, Balance of Payments, International Investment Position, International Reserves, Fund Accounts, External Trade, Exchange Rates, and Population.

The estimates are based on official statistics on the foreign-born or the foreign population, classified by sex, and age. Most of the statistics utilised to estimate the international migrant stock were obtained from population censuses. Additionally, population registers and nationally representative surveys provided information on the number and composition of international migrants. The designations employed and the material in this publication do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory or area or its authorities, or concerning the delimitation of its frontiers or boundaries. The term “country” as used in this publication also refers, as appropriate, to territories or areas. The names and composition of geographical areas follow those presented in “Standard country or area codes for statistical use” (ST/ESA/STAT/SER.M/49/Rev.3), available at http://unstats.un.org/unsd/methods/m49/m49.htm.

International Migration Flows To And From Selected Countries

The 2022 IPRI classifies 129 countries, representing 93.91% of the world population and 97.73% of the global GDP. The selection of countries was determined solely by the availability of sufficient data. The results continue to suggest that countries with high scores on the IPRI and its components also show high levels of income and development, indicating the positive relationship between a property rights regime and quality of life. The average score of the IPRI for 2022 is  5.19, where the Legal and Political Environment (LP) was the weakest component with a score of 5.06, followed by the Intellectual Property Rights (IPR) component with a score of 5.24; and quite close, the Physical Property Rights (PPR) was the strongest component with a score of 5.27  For the fourth consecutive year, we found a decrease in the overall score of the IPRI and this year, also for all of its components. Finland leads the IPRI (8.17) as well as its PPR component (8.53), while New Zealand leads the LP (8.76) and the USA the IPR component (8.73). Singapore ranks 2nd in its IPRI score (7.97) followed by Switzerland (7.94) and New Zealand (7.93).  

This indicator reports the percentage of students of each country of origin over the total of international students.

The international goods and services deficit was $74.6 billion in April, up $14.0 billion from $60.6 billion in March. April exports were $249.0 billion, $9.2 billion less than March exports. April imports were $323.6 billion, $4.8 billion more than March imports. 

Metadata by country are available in English and French. Please click on the link below: https://www.oecd.org/sdd/its/OECD-Trade-In-Services-EBOPS2010-metadata-all-countries.pdf. The aim of this dataflow International Trade in Services EBOPS 2010 (by partner country) is to collect and disseminate balance of payments data on international trade in services at the most detailed partner country level available. To the extent that countries report them, data are also broken down by type of service according to the EBOPS 2010 classification. There has been a growing interest in monitoring patterns of trade in services around the world, which is partly associated with ongoing trade negotiations and partly due to the increasing importance of services in OECD economies. It has been developed to supplement other OECD publications on trade in services to address the data needs of trade analysts. It is also an important part of OECD's programme to facilitate the implementation of the recommendations of the revised Manual on Statistics of International Trade in Services 2010. The currency unit used for all series is: Millions of US dollars or Millions of National Currency or Millions of Euros. OECD statistics contact: [email protected] http://www.oecd.org/sdd

Note: Please visit https://www.oecd-ilibrary.org/transport/road-safety-annual-report_23124571 to access latest data.   Road Safety Annual Report - 2017 The International Traffic Safety Data and Analysis Group (IRTAD) is a permanent working group of the International Transport Forum at the OECD. It is composed of road safety experts and statisticians from renowned safety research institutes, national road and transport administrations, international organisations, universities, automobile associations, the automobile industry, and others from OECD and non-OECD countries. IRTAD’s Road Safety Annual Report series provides a yearly overview of road safety performance in member and observer countries. It presents a synthesis of the latest trends in member countries as well as detailed reports for each country, outlining the crash data collection process, the road safety strategies and targets in place. It also provides detailed safety data by road user, location and age together with information on recent trends in speeding, drink-driving and other aspects of road user behaviour.

International Travel and Tourism of Mauritius, by Age Group

The FAO Statistics Division has compiled an updated dataset series of capital stock in Agriculture from 1975-2007 using 2005 constant prices as the base year. The dataset on capital stock in agriculture are important for analyzing a number of policy issues related to sustainable growth of agriculture and achieving food security.

The JODI-Gas World Database is a platform that provides access to all data reported through monthly submissions of the JODI-Gas Questionnaire by all participating countries and economies. The database is updated on a monthly basis around the 20th of each month, though there are possibilities for additional updates. Registered users are notified by e-mail alert each time the database is updated. Modelled after JODI-Oil, which features monthly oil production, consumption, stocks and trade data from over 90 countries, JODI-Gas embodies the same objective of enhancing energy data transparency, with the ultimate goal of ensuring global energy security for producers and consumers alike. JODI-Gas World Database covers: Three product categories: Natural gas in million m3 Natural gas in TJ LNG in 1000 tons Twelve flows: Production Receipts from Other Sources Total Imports LNG Total Exports LNG Total Imports through Pipeline Total Exports through Pipeline Stock Change Gross Inland Deliveries (Calculated) Statistical Difference (Calculated) Gross Inland Deliveries (Observed) Of which: Electricity and Heat Generation Closing Stocks; Data for around 80 participating countries. Historical data from January 2009: target is to release one month old data (M-1) every month for all participating countries.

The Joint Organisations Data Initiative is a concrete outcome of the producer-consumer energy dialogue. The initiative relies on the combined efforts of producing and consuming countries and the seven JODI partner organisations to build the timely, comprehensive, and sustainable energy data provision architecture which is a prerequisite for stable energy commodity markets. More than 90 countries/economies, Members of the six pioneer organisations (APEC, EUROSTAT, IEA, OLADE, OPEC and UNSD) participate in JODI Oil, representing around 90% of global oil supply and demand. When the Joint Organisations Data Initiative Oil (JODI Oil) was first launched in 2001, the primary goal was not to build a database but to raise the awareness of all oil market players to the need for more transparency in oil market data. The database consists of: seven product categories: crude oil, LPG, gasoline, kerosene, diesel oil, fuel oil and total oil products; eight flows: production, demand, refinery intake and output, imports, exports, closing stock levels and stock change; data in three different units: barrels, tons and litres; data for more than 90 participating countries; data from January 2002 to one month-old.

Data cited at: Prof.Prof. Lauren Gardner; Center for Systems Science and Engineering at John Hopkins University, blog Post -  https://systems.jhu.edu/research/public-health/ncov/   On December 31, 2019, the World Health Organization (WHO) was informed of an outbreak of “pneumonia of unknown cause” detected in Wuhan City, Hubei Province, China – the seventh-largest city in China with 11 million residents. As of February 04, 2020, there are over 24,502 cases confirmed globally, including cases in at least 30 regions in China and 30 countries.  Interests: In-Market Segments Knoema All Users   Knoema modified the original dataset to include calculations per million.   https://knoema.com/WBPEP2018Oct https://knoema.com/USICUBDS2020 https://knoema.com/NBSCN_P_A_A0301 https://knoema.com/IMFIFSS2017Nov https://knoema.com/AUDSS2019 https://knoema.com/UNAIDSS2017 https://knoema.com/UNCTADPOPOCT2019Nov https://knoema.com/WHOWSS2018 https://knoema.com/KPMGDHC2019

The Joint External Debt Hub (JEDH) -jointly developed by the Bank for International Settlements (BIS), the International Monetary Fund (IMF), the Organization for Economic Cooperation and Development (OECD) and the World Bank (WB) -brings together external debt data and selected foreign assets from international creditor / market and national debtor sources. The JEDH replaces the Joint BIS-IMF-OECD-WB Statistics on External Debt, a website that was launched in 1999 to provide international data, mainly from creditor sources, on the external debt of developing and transition countries and territories.

Tourism GDP corresponds to the part of GDP generated by all industries in response to internal tourism consumption. A further distinction must be made between direct tourism GDP and indirect tourism GDP. Put simply, tourism direct GDP is generated by industries directly in contact with visitors, while indirect tourism GDP is generated by industries supplying inputs to industries directly in contact with the visitors. The Tourism Staellite Account (TSA) Framework limits its recommendations to the evaluation of direct tourism GDP.

The World Bank’s Knowledge Assessment Methodology (KAM: www.worldbank.org/kam) is an online interactive tool that produces the Knowledge Economy Index (KEI)–an aggregate index representing a country’s or region’s overall preparedness to compete in the Knowledge Economy (KE). The KEI is based on a simple average of four subindexes, which represent the four pillars of the knowledge economy:  Economic Incentive and Institutional Regime (EIR)  Innovation and Technological Adoption  Education and Training  Information and Communications Technologies (ICT) Infrastructure The EIR comprises incentives that promote the efficient use of existing and new knowledge and the flourishing of entrepreneurship. An efficient innovation system made up of firms, research centers, universities, think tanks, consultants, and other organizations can tap into the growing stock of global knowledge, adapt it to local needs, and create new technological solutions. An educated and appropriately trained population is capable of creating, sharing, and using knowledge. A modern and accessible ICT infrastructure serves to facilitate the effective communication, dissemination, and processing of information.

Abridged Labor Force Survey Under Covid-19 

Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. The quarterly Labour Cost Index (LCI) is a Euro Indicator which measures the cost pressure arising from the production factor "labour". The data covered in the LCI collection relate to total average hourly labour costs and to the labour cost categories "wages and salaries" and "employers' social security contributions plus taxes paid minus subsidies received by the employer". Data - also broken down by economic activity, are available for the EU aggregates and EU Member States (NACE Rev 1.1 Sections C to K (1996Q1-2008Q4) and NACE Rev 2 Sections B to S), in working day and seasonally adjusted form. The data on the Labour Cost Index are given in the form of index numbers (current base year: 2016) and of annual and quarterly growth rates (comparison with the previous quarter, or the same quarter of the previous year). On annual basis the labour cost levels (in Euro and national currency) are also published, based on the latest Labour Cost Survey inflated by the LCI. In contrast to the information collected for the other Labour Cost domains, the labour costs covered in the LCI do not include vocational training costs and other expenditure such as recruitment costs and working clothes expenditure. The data are estimated by the National Statistical Institutes on the basis of available structural and short-term information from samples and administrative records for enterprises of all sizes. The labour cost index (LCI) shows the short-term development of the labour cost, the total cost on an hourly basis of employing labour. In other words, the LCI measures the cost pressure arising from the production factor “labour”.  In addition, Eurostat estimates of the annual labour cost per hour in euros are provided for EU Member States as well as the whole EU; they were obtained by combining the four-yearly Labour cost survey (LCS) with the quarterly labour cost index. 

Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs. The quarterly Labour Cost Index (LCI) is a Euro Indicator which measures the cost pressure arising from the production factor "labour". The data covered in the LCI collection relate to total average hourly labour costs and to the labour cost categories "wages and salaries" and "employers' social security contributions plus taxes paid minus subsidies received by the employer". Data - also broken down by economic activity, are available for the EU aggregates and EU Member States (NACE Rev 1.1 Sections C to K (1996Q1-2008Q4) and NACE Rev 2 Sections B to S), in working day and seasonally adjusted form. The data on the Labour Cost Index are given in the form of index numbers (current reference year: 2012) and of annual and quarterly growth rates (comparison with the previous quarter, or the same quarter of the previous year). On annual basis the labour cost levels (in Euro and national currency) are also published, based on the latest Labour Cost Survey inflated by the LCI. In contrast to the information collected for the other Labour Cost domains, the labour costs covered in the LCI do not include vocational training costs and other expenditure such as recruitment costs and working clothes expenditure. The data are estimated by the National Statistical Institutes on the basis of available structural and short-term information from samples and administrative records for enterprises of all sizes.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The labour force comprises all persons of working age who furnish the supply of labour for the production of goods and services during a specified time-reference period. It refers to the sum of all persons of working age who are employed and those who are unemployed. The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. The labour force comprises all persons of working age who furnish the supply of labour for the production of goods and services during a specified time-reference period. It refers to the sum of all persons of working age who are employed and those who are unemployed. The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The labour force participation rate is the labour force as a percent of the working-age population. The labour force is the sum of all persons of working age who are employed and those who are unemployed. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The labour force participation rate is the labour force as a percent of the working-age population. The labour force is the sum of all persons of working age who are employed and those who are unemployed. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The labour force participation rate is the labour force as a percent of the working-age population. The labour force is the sum of all persons of working age who are employed and those who are unemployed. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED. For more information, refer to the Education and Mismatch Indicators (EMI) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The labour force participation rate is the labour force as a percent of the working-age population. The labour force is the sum of all persons of working age who are employed and those who are unemployed. Data disaggregated by level of education are provided on the highest level of education completed, classified according to the International Standard Classification of Education (ISCED). Data may have been regrouped from national classifications, which may not be strictly compatible with ISCED. For more information, refer to the Education and Mismatch Indicators (EMI) database description.

Short-term statistics (STS) give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification (Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are generally presented in the following forms:UnadjustedCalendar adjustedSeasonally adjusted Depending on the STS regulation data are accessible as monthly, quarterly and annual data. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction (volume)*Turnover: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic turnover into euro area and non euro area is available for the euro area countriesProducer prices (output prices)*: Total, Domestic market and Non-domestic market==> A further breakdown of the non-domestic producer prices into euro area and non euro area is available for the euro area countriesImport prices*: Total, Euro area market, Non euro area market (euro area countries only)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries CONSTRUCTIONProduction (volume)*: Total of the construction sector, Building construction, Civil EngineeringBuilding permits indicators*: Number of dwellings, Square meters of useful floor (or alternative size measure)Construction costs or prices: Construction costs, Material costs, Labour costs (if not available, they may be approximated by the Output prices variable)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries WHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (value)Labour input indicators: Number of persons employed, Hours worked, Gross wages and salaries SERVICESTurnover (in value)*Labour input indicators: Number of persons employed, Hours worked, Gross wages and salariesProducer prices (Output prices )* National reference metadata of the reporting countries can be found in the Annexes of this metadata file.

Gross domestic product (GDP) is a measure for the economic activity. It is defined as the value of all goods and services produced less the value of any goods or services used in their creation. GDP per person employed is intended to give an overall impression of the productivity of national economies expressed in relation to the European Union average. If the index of a country is higher than 100, this country's level of GDP per person employed is higher than the EU average and vice versa. Basic figures are expressed in PPS, i.e. a common currency that eliminates the differences in price levels between countries allowing meaningful volume comparisons of GDP between countries. Please note that 'persons employed' does not distinguish between full-time and part-time employment. Labour productivity per hour worked is calculated as real output per unit of labour input (measured by the total number of hours worked). Measuring labour productivity per hour worked provides a better picture of productivity developments in the economy than labour productivity per person employed, as it eliminates differences in the full time/part time composition of the workforce across countries and years.

The land cover dataset provides a global assessment of land cover and land cover change to monitor pressures on ecosystems and biodiversity. By using geospatial data with high spatio-temporal resolution, it develops a set of internationally comparable indicators with a long time series from 2000 to 2020 with a five-year interval. Please see the working paper for a more complete description of the methods. The dataset has a global coverage on the national level, while on the sub-national TL2 level (i.e. large subnational regions) results are reported for all OECD countries as well as for Argentina, Brazil, China, India, Indonesia and South Africa. The following country aggregates are included: Euro area, European Union, Advanced economies, Emerging market economies, G7, G20, OECD, OECD Europe, OECD Asia Oceania, OECD Americas, the LAC region and the World. Data source(s): Copernicus Climate Change Initiative land cover data and Global Human Settlement Layer built-up area data. Contact: [email protected] Database documentation

Land resources are one of the four components of the natural environment: water, air, land and living resources. In this context land is both: a physical "milieu" necessary for the development of natural vegetation as well as cultivated vegetation;a resource for human activities.  The data presented here give information concerning land use state and changes (e.g. agricultural land, forest land).  Land area excludes area under inland water bodies (i.e. major rivers and lakes).   Arable refers to all land generally under rotation, whether for temporary crops (double-cropped areas are counted only once) or meadows, or left fallow (less than five years). These data are not meant to indicate the amount of land that is potentially cultivable.  Permanent crops are those that occupy land for a long period and do not have to be planted for several years after each harvest (e.g. cocoa, coffee, rubber). Land under vines and trees and shrubs producing fruits, nuts and flowers, such as roses and jasmine, is so classified, as are nurseries (except those for forest trees, which should be classified under "forests and other wooded land").  Arable and permanent crop land is defined as the sum of arable area and land under permanent crops.  Permanent meadows and pastures refer to land used for five years or more to grow herbaceous forage crops, either cultivated or growing wild (wild prairie or grazing land).  Forest refers to land spanning more than 0.5 hectare (0.005 km2) and a canopy cover of more than 10 percent, or trees able to reach these thresholds in situ. This includes land from which forests have been cleared but that will be reforested in the foreseeable future. This excludes woodland or forest predominantly under agricultural or urban land use and used only for recreation purposes.

The Logistics Performance Index overall score reflects assessments of a country's logistics based on efficiency of the customs clearance process, quality of trade- and transport-related infrastructure, ease of arranging competitively priced shipments, quality of logistics services, ability to track and trace consignments, and frequency with which shipments reach the consignee within the scheduled time. The index ranges from 1 to 5, with a higher score representing better performance. Data are from Logistics Performance Index surveys conducted by the World Bank in partnership with academic and international institutions and private companies and individuals engaged in international logistics. 2011 round of surveys covered more than 6,000 country assessments by nearly 1,000 international freight forwarders. Respondents evaluated eight markets on six core dimensions using a scale from 1 (worst) to 5 (best). The markets are chosen based on the most important export and import markets of the respondent's country, random selection, and, for landlocked countries, neighboring countries that connect them with international markets. Scores for the six areas are averaged across all respondents and aggregated to a single score using principal components analysis. Details of the survey methodology and index construction methodology are in Connecting to Compete 2012: Trade Logistics in the Global Economy (2012).

Long term government bond yields are calculated as monthly averages (non seasonally adjusted data). They refer to central government bond yields on the secondary market, gross of tax, with a residual maturity of around 10 years. The bond or the bonds of the basket have to be replaced regularly to avoid any maturity drift. This definition is used in the convergence criteria of the Economic and Monetary Union for long-term interest rates, as required under Article 121 of the Treaty of Amsterdam and the Protocol on the convergence criteria. Data are presented in raw form. Source: European Central Bank (ECB)

The OECD Long-Term Baseline is a projection of some major economic variables beyond the short-term horizon of the OECD Economic Outlook. It covers all OECD economies, non-OECD G20 economies and selected key partners. The projection horizon is currently 2060. For the historical period and the short-run projection horizon, the series are consistent with those of the OECD Economic Outlook number 114. The definitions, sources and methods are also generally the same. For more details on the methodology, please see boxes and Annex in Guillemette, Y. and J. Château (2023), 'Long-Term Scenarios: Incorporating the Energy Transition', OECD Economic Policy Papers, No. 33, OECD Publishing, Paris, and references therein. The baseline scenario is a projection conditional on a number of assumptions, notably that countries do not carry out institutional and policy reforms (see section 2 of the reference cited above). It is used as a reference point to illustrate the potential impact of structural reforms in alternative scenarios. The energy transition scenario is an alternative scenario with accelerated energy transition broadly consistent with net zero GHG emissions by 2050 (see section 3 of the reference cited above).

Main Economic Indicators (MEI) provides a wide range of indicators on recent economic developments in the 35 OECD member countries and 15 non-member countries. The indicators published in MEI have been prepared by national statistical agencies primarily to meet the requirements of users within their own country. In most instances, the indicators are compiled in accordance with international statistical guidelines and recommendations. However, national practices may depart from these guidelines, and these departures may impact on comparability between countries.

Europop2013, the latest population projections released by Eurostat, provide a set of different scenarios for possible population developments at national and at regional levels across 31 European countries: for each EU-28 Member State as well as for Iceland, Norway and Switzerland. These population projections were produced using data for 1 January 2013 as a starting point and therefore include any modifications made to demographic statistics resulting from the 2011 population census exercise. They were developed based on application of a main input dataset of assumptions on future developments for fertility, mortality and net migration (including statistical adjustment) covering the time period 2013 to 2080. Europop2013 at national level includes detailed statistical information related to the main scenario and its four variants with reference to:projected population on 1 January by age and sex;assumptions datasets: age-specific fertility rates, age-specific mortality rates and international net migration figures (including statistical adjustment);approximated values of the life expectancy by age and sex for the main scenario and the higher life expectancy variant;total numbers of the projected live births and deaths;projected population structure indicators: shares of broad age groups in total population, old-age dependency ratios and median age of population;the time horizon covered is from 2013 until 2080 for the main scenario and no migration variant, and from 2013 until 2060 for the higher life expectancy, reduced migration and lower fertility variants. Europop2013 at regional level covers all the regions classified as NUTS level 2 and NUTS level 3 corresponding to the NUTS-2010 classification (the Nomenclature of Territorial Units for Statistics) and to the Statistical Regions (SR) agreed between European Commission and Iceland, Norway and Switzerland. The statistical information included for each NUTS level relates to the main scenario and is summarised below: Europop2013 for NUTS level 2 regions:projected population on 1 January by age and sex;assumptions datasets: age-specific fertility rates, age-specific mortality rates and net migration figures (including statistical adjustment); the assumptions datasets on age-specific fertility rates and age-specific mortality rates for each region at NUTS level 2 were further on used as such for producing the population projections for its component regions at NUTS level 3;approximated values of the life expectancy by age and sex;total numbers of projected live births and deaths;projected population structure indicators: shares of broad age groups in total population, old-age dependency ratios and median age of population;the time horizon covered is from 2013 until 2080;data available are rounded therefore the sum of regional figures for populations and for net migrations will differ from the national ones by few units;287 regions classified as NUTS and SR level 2. Due to the relative small population the following countries have one NUTS level 2 region: Estonia, Cyprus, Latvia, Lithuania, Luxembourg, Malta and Iceland. Thus, for these countries the projected population data for NUTS level 2 region are identical to national data. Europop2013 for NUTS level 3 regions:projected population on 1 January by age and sex;the time horizon covered is from 2014 until 2050;projected population structure indicators: shares of broad age groups in total population, old-age dependency ratios and median age of population;assumptions dataset on international net migration figures (including statistical adjustment);data available are rounded therefore the sum of regional figures for populations will differ from the upper NUTS level 2 ones by few units;1362 regions classified as NUTS and SR level 3. Due to the relative small population Cyprus and Luxembourg have only one NUTS level 3 region. Thus, for these two countries the projected population data at NUTS level 3 are identical to the ones at NUTS level 2 and at national level.

The OECD Main Science and Technology Indicators (MSTI) provide a set of indicators that compare the Science and Technology (S&T) performance of OECD member countries and selected non-member economies. The MSTI database focuses principally on tracking financial and human resources devoted to research and experimental development (R&D), as defined in the OECD Frascati Manual, complemented by additional indicators of outputs and potential outcomes of S&T activities, namely patent data and international trade in R&D-intensive industries. MSTI also comprises several OECD economic and demographic statistical series which are used to calculate relevant benchmarks that account for differences in the relative size of economies, purchasing power and the effect of inflation.

The domain "Income and living conditions" covers four topics: people at risk of poverty or social exclusion, income distribution and monetary poverty, living conditions and material deprivation, which are again structured into collections of indicators on specific topics. The collection "People at risk of poverty or social exclusion" houses main indicator on risk of poverty or social inclusion included in the Europe 2020 strategy as well as the intersections between sub-populations of all Europe 2020 indicators on poverty and social exclusion. The collection "Income distribution and monetary poverty" houses collections of indicators relating to poverty risk, poverty risk of working individuals as well as the distribution of income. The collection "Living conditions" hosts indicators relating to characteristics and living conditions of households, characteristics of the population according to different breakdowns, health and labour conditions, housing conditions as well as childcare related indicators. The collection "Material deprivation" covers indicators relating to economic strain, durables, housing deprivation and environment of the dwelling.

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings. The objective of this legislation is so that National Statistical Institutes (NSIs) provide accurate and harmonised data on earnings in EU Member States and other countries for policy-making and research purposes. The SES 2010 provides detailed and comparable information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise). Regional data is also available for some countries and regional metadata is identical to that provided for national data.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The earnings of employees relate to the gross remuneration in cash and in kind paid to employees, as a rule at regular intervals, for time worked or work done together with remuneration for time not worked, such as annual vacation, other type of paid leave or holidays. Earnings exclude employers' contributions in respect of their employees paid to social security and pension schemes and also the benefits received by employees under these schemes. Earnings also exclude severance and termination pay. This is a harmonized series: (1) data reported as weekly, monthly and yearly are converted to hourly using data on average weekly hours if available; and (2) data are converted to U.S. dollars as the common currency, using exchange rates or using purchasing power parity (PPP) rates for private consumption expenditures. The latter series allows for international comparisons by taking account of the differences in relative prices between countries. Data disaggregated by occupation are provided according to the latest version of the International Standard Classification of Occupations (ISCO). Data may have been regrouped from the national classifications, which may not be strictly compatible with ISCO. For more information, refer to the Wages and Working Time Statistics (COND) database description.

Labour cost is the cost incurred by the employer in the employment of labour in a specified reference period. It comprises remuneration for work performed, payments in respect of time paid for but not worked, bonuses and gratuities, the cost of food, drink and other payments in kind, cost of workers' housing borne by employers, employers' social security expenditures, cost to the employer for vocational training, welfare services and miscellaneous items, such as transport of workers, work clothes and recruitment, together with taxes regarded as labour cost. This is a harmonized series: (1) data reported as weekly, monthly and yearly are converted to hourly in the local currency series, using data on average weekly hours if available; and (2) data are converted to U.S. dollars as the common currency, using exchange rates or using purchasing power parity (PPP) rates for private consumption expenditures. The latter series allows for international comparisons by taking account of the differences in relative prices between countries. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Competitiveness Indicators (COMP) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The earnings of employees relate to the gross remuneration in cash and in kind paid to employees, as a rule at regular intervals, for time worked or work done together with remuneration for time not worked, such as annual vacation, other type of paid leave or holidays. Earnings exclude employers' contributions in respect of their employees paid to social security and pension schemes and also the benefits received by employees under these schemes. Earnings also exclude severance and termination pay. This is a harmonized series: (1) data reported as weekly, monthly and yearly are converted to hourly using data on average weekly hours if available; and (2) data are converted to U.S. dollars as the common currency, using exchange rates or using purchasing power parity (PPP) rates for private consumption expenditures. The latter series allows for international comparisons by taking account of the differences in relative prices between countries. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Wages and Working Time Statistics (COND) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The earnings of employees relate to the gross remuneration in cash and in kind paid to employees, as a rule at regular intervals, for time worked or work done together with remuneration for time not worked, such as annual vacation, other type of paid leave or holidays. Earnings exclude employers' contributions in respect of their employees paid to social security and pension schemes and also the benefits received by employees under these schemes. Earnings also exclude severance and termination pay. This is a harmonized series: (1) data reported as weekly, monthly and yearly are converted to hourly using data on average weekly hours if available; and (2) data are converted to U.S. dollars as the common currency, using exchange rates or using purchasing power parity (PPP) rates for private consumption expenditures. The latter series allows for international comparisons by taking account of the differences in relative prices between countries. Data disaggregated by occupation are provided according to the latest version of the International Standard Classification of Occupations (ISCO). Data may have been regrouped from the national classifications, which may not be strictly compatible with ISCO. For more information, refer to the Wages and Working Time Statistics (COND) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. Data on hours of work are presented, whenever possible, on the basis of the average number of hours of work per week, and with reference to hours worked in the main (paid) job regardless of working time arrangements (e.g. full-time and part-time). Data disaggregated by occupation are provided according to the latest version of the International Standard Classification of Occupations (ISCO). Data may have been regrouped from the national classifications, which may not be strictly compatible with ISCO. For more information, refer to the Gender Equality and Non-Discrimination Indicators (GEND) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. Data on hours of work are presented, whenever possible, on the basis of the average number of hours of work per week, and with reference to hours worked in the main (paid) job regardless of working time arrangements (e.g. full-time and part-time). Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

This Dataset contains Indicators related to IC Development Index and Tables from "Measuring the Information Society Report 2018, Volume 1" For Indicators for other ICT Development data please refer: https://knoema.com/ITUKIICT2019/global-ict-developments

Merchandise: Trade value, volume, unit value, terms of trade indices and purchasing power index of exportsThis dataset contains export and import volume indices, rounding out trade value. Export and import unit value indices, derived terms of trade and purchasing power of exports indices are also provided in various base and reference years (2000, 2010 and 2015).The value index is the current value of exports (FOB) or imports (CIF) converted to United States dollars and expressed in percentage. The volume index is derived as the percentage ratio of the export or import value index to the corresponding unit value index (value index / unit value index *100) unless otherwise noted at country level.The weights used for the calculation of the indices correspond to base year 2000. For convenience, and to facilitate international comparisons, the series have been rescaled to new references 2010=100 and 2015=100.

This Dataset presents merchandise trade by trading partner and product based on the SITC commodity classification, Revision 3, at the one- and two-digit level, expressed in thousands of United States dollars. The data are also summarized by group of economies, for both reporting economy and trading partner, and by broader product groups.

This Dataset presents product concentration and diversification indices.  The diversification index indicates whether the structure of exports or imports by product of a given country or country group differs from the world pattern. The product concentration index shows how exports and imports of individual countries or country groups are concentrated on a few products or otherwise distributed in a more homogeneous manner among a series of products.

This dataset shows statistics on the international maritime transport. It contains data on the size of the world merchant fleet by flag of registration and by type of ship. Data are presented in thousands of dead-weight tons (DWT).The dataset presents also, for each region or country 1) its share in the world fleet, and 2) the share of a ship-type in its fleet. From 2011 onwards, the figures on numbers of ships are also available, as well as the data in gross tonnage (GT).   This table contains consolidated time series from various issues of the UNCTAD Review of Maritime Transport. The Review reports on the worldwide evolution of shipping, ports and multimodal transport related to the major traffics of liquid bulk, dry bulk and containers. Please see http://unctad.org/rmt.   The data refer to the beginning of an indicated year.   The figures cover seagoing propelled merchant ships of 100 gross tons and above, excluding inland waterway vessels, fishing vessels (from 2011 onwards only), military vessels, yachts, and offshore fixed and mobile platforms and barges (with the exception of FPSO - floating production, storage and offloading vessels - and drillships). Break in series: from 2011 onwards - (a) data also include the United States and Canada Great Lakes fleets; and (b) figures no longer cover the fishing vessels.

Migration and Remittances Fact book provides a snapshot of migration and remittances for all countries, regions and income groups of the world, compiled from available data from various sources.

Animal production statistics cover three main sub-domains based on three pieces of relevant legislation and related gentlemen’s agreements.Livestock and meat statistics are collected under Regulation (EC) No 1165/2008. They cover meat production, as activity of slaughterhouses (monthly) and as other slaughtering (annual), meat production (gross indigenous production) forecast (semi-annual or quarterly), livestock statistics, including regional statistics. A quality report is also collected every third year.Milk and milk product statistics are collected under Decision 97/80/EC implementing Directive 96/16/EC. They cover farm production and utilisation of milk (annual), collection (monthly for cows’ milk) and production activity by dairies (annual) and statistics on the structure of dairies (every third year). An annual methodological report is also collected.Statistics on eggs for hatching and farmyard poultry chicks are collected under Regulation (EC) No 617/2008, implementing Regulation (EC) No 1234/2007 (Single CMO Regulation). They cover statistics on the structure (annual) and the activity (monthly) of hatcheries as well as reports on the external trade of chicks. European Economic Area countries (EEA, Iceland, Liechtenstein and Norway) are requested to provide milk statistics, with the exception of those related to home consumption, as stated in Annex XXI of the EEA Agreement. As Iceland is now a candidate country and Liechtenstein is exempted in the Agreement, only Norway is concerned. The Agreement between the European Community and the Swiss Confederation on cooperation in the field of statistics states that Switzerland must provide Eurostat with national milk statistics. It has been amended in 2013 for covering also some livestock and meat statistics. The same statistics are requested from the candidate countries as acquis communautaire. Further data about the same topics refer to repealed legal acts or agreements. The tables on animal product supply balance sheets (apro_mk_bal, apro_mt_bal and apro_ec_bal), statistics on the structure of rearing (apro_mt_str) and the number of laying hens (apro_ec_lshen) are therefore no longer updated. The same applies to some variables (external trade of animals and meat), periods (surveys in April or August) or items (number of horses) included in other tables. The statistical tables disseminated by Eurostat are organised into three groups of tables on Agricultural products (apro), i.e. Milk and milk products (apro_mk), Livestock and meat (apro_mt) and Poultry farming (apro_ec). This last label covers statistics on hatcheries and on trade in chicks. The regional animal production statistics collected on livestock (agr_r_animal) and on cows’ milk production on farms (agr_r_milk_pr) are disseminated separately. Due to the change in the legal basis or in the methodology, the time series may be broken. This is indicated by a flag in the tables. The detailed content of each table and the reference to its legal definition is provided in the table below. Table 3.1: Data tables disseminated regarding animal production statistics

This dataset contains environmental asset accounts for mineral and energy resources, describing the quantities of stocks in physical units (barrels in case of oil, cubic meters in case of gas, and tonnes in case of minerals) of these resources and the changes in stocks (flows) over accounting periods due to additions (discoveries, upward reappraisals, reclassifications) and reductions (extraction, downward reappraisals, reclassifications).

Minimum wage statistics published by Eurostat refer to monthly national minimum wages. The data shown here apply to the situation on 1st of January each year. In some countries the basic national minimum wage is not fixed at a monthly rate but at an hourly or weekly rate. For these countries the hourly or weekly rates are converted into monthly rates. The national minimum wage is enforced by law, often after consultation with the social partners, or directly by national intersectoral agreement (this is the case in Belgium and Greece). The national minimum wage usually applies to all employees, or at least to a large majority of employees in the country. Minimum wages are gross amounts, that is, before deduction of income tax and social security contributions. Such deductions vary from country to country.

We define our day as midnight-to-midnight, Pacific time. Cities represent usage in greater metropolitan areas and are stably defined during this period. In many countries/regions and cities, relative volume has increased since January 13th, consistent with normal, seasonal usage of Apple Maps. Day of week effects are important to normalize as you use this data. Data that is sent from users’ devices to the Maps service is associated with random, rotating identifiers so Apple doesn’t have a profile of your movements and searches. Apple Maps has no demographic information about our users, so we can’t make any statements about the representativeness of our usage against the overall population. This information will be available for a limited time during the COVID‑19 pandemic.

The Monetary and Financial Statistics (MFS) database contains the aggregated surveys covering: i) Central Bank ii) Depository Corporations and iii) Other Financial Corporations. The key macroeconomic aggregates in this dataset include: i) Monetary base and broad money; ii) Credit aggregates (including credit to the private sector); and iii) Foreign assets and liabilities.   Beginning in 2009, there are two presentations of Monetary Statistics in IFS. The new presentation data follows the Monetary and Financial Statistics Manual (MFSM) and the Monetary and Financial Statistics Compilation Guide (MFSCG), a companion to the MFSM that contains more detailed coverage of the classification, economic sectorization, valuation, and recording of financial assets and liabilities in an economy. The MFSCG gives prominence to the source data for monetary and financial statistics.   The majority of countries use the standardized report forms (SRFs) to report monetary data to the IMF and are presented under SRF Countries.   The old presentation is used for those countries that do not use the SRFs for reporting Monetary data and presented under Non-SRF Countries. The presentation of these countries will be changed to the new presentation when the countries implement the reporting of SRF-based data.   The Monetary and Financial Statistics Manual and Compilation Guide (Manual) updates and merges into one volume methodological and practical aspects of the compilation process for monetary and financial statistics (MFS). Aimed at compilers and users of MFS, it offers a conceptual framework for the collection, compilation, and analytical presentation of monetary data, which provide a critical input for monetary policy formulation and monitoring.   Detailed monetary statistics based on the standardized report forms reflecting the conceptual framework of the above Manual and its predecessors.

Day-to-day money market interest rates: averages for the euro area (EONIA= Euro OverNight Index Average), EU27 (theoretical aggregate), and national series (TR, US, JP). 1-month, 3-month, 6-month and 12-month interest rates: averages for the euro area (EURIBOR) and EU27 (theoretical aggregate). 3-month interest rates are also available for the US and Japan.

This dataset contains monthly Comparative Price Levels (CPL) for OECD countries. CPLs are defined as the ratios of PPPs for private final consumption expenditure to exchange rates. They provide measures of differences in price levels between countries. The monthly PPPs used to derive the table are OECD estimates. The table is to be read vertically. Each column shows the number of specified monetary units needed in each of the countries listed to buy the same representative basket of consumer goods and services. In each case the representative basket costs a hundred units in the country whose currency is specified. Let’s take an example. If you are a Canadian citizen and you want to know the price level in Canada when compared to other countries, you have to look at the column Canada, where the price level is set at 100 for the whole column. If you have 120 for Finland, it means that the price level in Finland is 20% higher than in Canada. It means that you would spend 120 dollars in Finland to buy the same basket of goods and services when you spend 100 in Canada. The monthly PPPs used to derive the table are obtained by extrapolating 2022 PPPs for household final consumption expenditure using the relative rates of inflation between the countries as measured by their consumer price indices. Unless a country is a high inflation country, its PPP will tend to change slowly over time. Month-to-month changes in comparative price levels are more likely to be the result of exchange rate fluctuations. Updated data are available at the beginning of each month. Click here for release dates OECD statistics contact: [email protected]

Data cited at: EuroMOMO - https://euromomo.eu/graphs-and-maps/ During the current COVID-19 pandemic, information on its mortality impact is of major concern. The EuroMOMO network hub receives many questions about the weekly mortality data we present, as well as requests to share the underlying national data.

This dataset presents trends in amounts of municipal waste generated (including household waste), and the treatment and disposal method used. The amount of waste generated in each country is related to the rate of urbanisation, the types and pattern of consumption, household revenue and lifestyles.

The National Accounts at a Glance (NAAG) is based on the original publication and has nine chapters: The first chapter focuses on indicators of Gross Domestic Product (GDP). The second is about income and related indicators and presents measures of net national income, savings and net lending/net borrowing. The third chapter looks at the expenditure approach to GDP, with information on the key components of demand and imports. The fourth chapter presents indicators from a production perspective. The fifth chapter looks at household sector indicators such as household disposable income, saving and net worth. The sixth chapter focuses on general government, presenting indicators such as general government revenue, expenditure and gross debt. The seventh chapter looks at financial and non-financial corporations. The eighth chapter presents indicators of capital stock and depreciation. Finally, chapter 9 provides reference indicators, important in their own right but also because they are used in the construction of many of the indicators presented elsewhere in NAAG.

The National Accounts at a Glance (NAAG) is based on the original publication and has nine chapters: The first chapter focuses on indicators of Gross Domestic Product (GDP). The second is about income and related indicators and presents measures of net national income, savings and net lending/net borrowing. The third chapter looks at the expenditure approach to GDP, with information on the key components of demand and imports. The fourth chapter presents indicators from a production perspective. The fifth chapter looks at household sector indicators such as household disposable income, saving and net worth. The sixth chapter focuses on general government, presenting indicators such as general government revenue, expenditure and gross debt. The seventh chapter looks at financial and non-financial corporations. The eighth chapter presents indicators of capital stock and depreciation. Finally, chapter 9 provides reference indicators, important in their own right but also because they are used in the construction of many of the indicators presented elsewhere in NAAG.

The National Accounts at a Glance (NAAG) is based on the original publication and has nine chapters: The first chapter focuses on indicators of Gross Domestic Product (GDP). The second is about income and related indicators and presents measures of net national income, savings and net lending/net borrowing. The third chapter looks at the expenditure approach to GDP, with information on the key components of demand and imports. The fourth chapter presents indicators from a production perspective. The fifth chapter looks at household sector indicators such as household disposable income, saving and net worth. The sixth chapter focuses on general government, presenting indicators such as general government revenue, expenditure and gross debt. The seventh chapter looks at financial and non-financial corporations. The eighth chapter presents indicators of capital stock and depreciation. Finally, chapter 9 provides reference indicators, important in their own right but also because they are used in the construction of many of the indicators presented elsewhere in NAAG.

The National Accounts at a Glance (NAAG) is based on the original publication and has nine chapters: The first chapter focuses on indicators of Gross Domestic Product (GDP). The second is about income and related indicators and presents measures of net national income, savings and net lending/net borrowing. The third chapter looks at the expenditure approach to GDP, with information on the key components of demand and imports. The fourth chapter presents indicators from a production perspective. The fifth chapter looks at household sector indicators such as household disposable income, saving and net worth. The sixth chapter focuses on general government, presenting indicators such as general government revenue, expenditure and gross debt. The seventh chapter looks at financial and non-financial corporations. The eighth chapter presents indicators of capital stock and depreciation. Finally, chapter 9 provides reference indicators, important in their own right but also because they are used in the construction of many of the indicators presented elsewhere in NAAG.

The National Accounts at a Glance (NAAG) is based on the original publication and has nine chapters: The first chapter focuses on indicators of Gross Domestic Product (GDP). The second is about income and related indicators and presents measures of net national income, savings and net lending/net borrowing. The third chapter looks at the expenditure approach to GDP, with information on the key components of demand and imports. The fourth chapter presents indicators from a production perspective. The fifth chapter looks at household sector indicators such as household disposable income, saving and net worth. The sixth chapter focuses on general government, presenting indicators such as general government revenue, expenditure and gross debt. The seventh chapter looks at financial and non-financial corporations. The eighth chapter presents indicators of capital stock and depreciation. Finally, chapter 9 provides reference indicators, important in their own right but also because they are used in the construction of many of the indicators presented elsewhere in NAAG.

The National Accounts at a Glance (NAAG) is based on the original publication and has nine chapters: The first chapter focuses on indicators of Gross Domestic Product (GDP). The second is about income and related indicators and presents measures of net national income, savings and net lending/net borrowing. The third chapter looks at the expenditure approach to GDP, with information on the key components of demand and imports. The fourth chapter presents indicators from a production perspective. The fifth chapter looks at household sector indicators such as household disposable income, saving and net worth. The sixth chapter focuses on general government, presenting indicators such as general government revenue, expenditure and gross debt. The seventh chapter looks at financial and non-financial corporations. The eighth chapter presents indicators of capital stock and depreciation. Finally, chapter 9 provides reference indicators, important in their own right but also because they are used in the construction of many of the indicators presented elsewhere in NAAG.

The National Accounts at a Glance (NAAG) is based on the original publication and has nine chapters: The first chapter focuses on indicators of Gross Domestic Product (GDP). The second is about income and related indicators and presents measures of net national income, savings and net lending/net borrowing. The third chapter looks at the expenditure approach to GDP, with information on the key components of demand and imports. The fourth chapter presents indicators from a production perspective. The fifth chapter looks at household sector indicators such as household disposable income, saving and net worth. The sixth chapter focuses on general government, presenting indicators such as general government revenue, expenditure and gross debt. The seventh chapter looks at financial and non-financial corporations. The eighth chapter presents indicators of capital stock and depreciation. Finally, chapter 9 provides reference indicators, important in their own right but also because they are used in the construction of many of the indicators presented elsewhere in NAAG.

The National Accounts at a Glance (NAAG) is based on the original publication and has nine chapters: The first chapter focuses on indicators of Gross Domestic Product (GDP). The second is about income and related indicators and presents measures of net national income, savings and net lending/net borrowing. The third chapter looks at the expenditure approach to GDP, with information on the key components of demand and imports. The fourth chapter presents indicators from a production perspective. The fifth chapter looks at household sector indicators such as household disposable income, saving and net worth. The sixth chapter focuses on general government, presenting indicators such as general government revenue, expenditure and gross debt. The seventh chapter looks at financial and non-financial corporations. The eighth chapter presents indicators of capital stock and depreciation. Finally, chapter 9 provides reference indicators, important in their own right but also because they are used in the construction of many of the indicators presented elsewhere in NAAG.

The National Accounts at a Glance (NAAG) is based on the original publication and has nine chapters: The first chapter focuses on indicators of Gross Domestic Product (GDP). The second is about income and related indicators and presents measures of net national income, savings and net lending/net borrowing. The third chapter looks at the expenditure approach to GDP, with information on the key components of demand and imports. The fourth chapter presents indicators from a production perspective. The fifth chapter looks at household sector indicators such as household disposable income, saving and net worth. The sixth chapter focuses on general government, presenting indicators such as general government revenue, expenditure and gross debt. The seventh chapter looks at financial and non-financial corporations. The eighth chapter presents indicators of capital stock and depreciation. Finally, chapter 9 provides reference indicators, important in their own right but also because they are used in the construction of many of the indicators presented elsewhere in NAAG.

The National Accounts at a Glance (NAAG) is based on the original publication and has nine chapters: The first chapter focuses on indicators of Gross Domestic Product (GDP). The second is about income and related indicators and presents measures of net national income, savings and net lending/net borrowing. The third chapter looks at the expenditure approach to GDP, with information on the key components of demand and imports. The fourth chapter presents indicators from a production perspective. The fifth chapter looks at household sector indicators such as household disposable income, saving and net worth. The sixth chapter focuses on general government, presenting indicators such as general government revenue, expenditure and gross debt. The seventh chapter looks at financial and non-financial corporations. The eighth chapter presents indicators of capital stock and depreciation. Finally, chapter 9 provides reference indicators, important in their own right but also because they are used in the construction of many of the indicators presented elsewhere in NAAG.

It presents fixed assets by activity according to the classification ISIC rev.3 and by type of product and by type of assets.  It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. In national currency, in current prices and constant prices (national base year and OECD base year i.e. 2010). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.

The National Accounts at a Glance (NAAG) is based on the original publication and has nine chapters: The first chapter focuses on indicators of Gross Domestic Product (GDP). The second is about income and related indicators and presents measures of net national income, savings and net lending/net borrowing. The third chapter looks at the expenditure approach to GDP, with information on the key components of demand and imports. The fourth chapter presents indicators from a production perspective. The fifth chapter looks at household sector indicators such as household disposable income, saving and net worth. The sixth chapter focuses on general government, presenting indicators such as general government revenue, expenditure and gross debt. The seventh chapter looks at financial and non-financial corporations. The eighth chapter presents indicators of capital stock and depreciation. Finally, chapter 9 provides reference indicators, important in their own right but also because they are used in the construction of many of the indicators presented elsewhere in NAAG.

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.

Different series numbers (column “Series”) are used to store different time-series versions of national accounts statistics. Series numbers with two digits (10,20) refer to data compiled following the SNA 1968 national accounts methodology, while series numbers with three digits (100, 200, etc) refer to data compiled using the SNA 1993 national accounts methodology whereas series number with four digits (1000, 1100) refer to data compiled using the SNA 2008 national accounts methodology. In addition to different methodologies, different series numbers are used when data are reported in different currencies, fiscal years, or by different sources. Furthermore, data are stored under a new series number whenever there are significant changes in compilation practices which make the time series no longer comparable. Note: Ethiopia [upto 1993] and Ethiopia [from 1993] merged to get Ethiopia, Similarly Sudan (upto 2011) is combined with Sudan.

It presents gross capital formation, gross fixed capital formation, changes in inventories and acquisition less disposals of valuables broken down by detailed industries. Gross fixed capital formation is also available broken down by type of assets. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA. Unit of measure used - In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2010). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.

National Accounts - Volume IIIa - Financial Accounts - Flows, which record, by type of financial instruments, the financial transactions between institutional sectors, and are presented in two tables: Financial accounts, consolidated and Financial accounts, non-consolidated.

Annual National Accounts>General Government Accounts>750. General Government Debt-Maastricht   Unit of measure used: National currency; current prices. Expressed in millions   Statistical population: Government debt as defined in the Maastricht Treaty (Source : Eurostat). Available for Europeans countries only. In the Protocol on the excessive deficit procedure annexed to the Maastricht Treaty, government debt is defined as the debt of the whole general government sector: gross, consolidated and nominal value (face value). It excludes the other accounts payable (AF.7), as well as, if they exist, insurance technical reserve (AF.6).

Annual National Accounts

Statistical population: Its presents output, intermediate consumption and the gross value added and its components, in particular compensation of employees and gross operating surplus and mixed income, broken down by detailed industries. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. Data presented in this table will not be updated after summer 2010. Data reported to the OECD by countries in their answers to the annual national accounts questionnaire are now available on theme Industry and Services, Structural Analysis (STAN) Databases. Unit of measure used: In national currency, in current prices and constant prices (national base year, previous year prices and OECD base year i.e. 2010). Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.

National Health Accounts (NHA) provides evidence to monitor trends in health spending for all sectors- public and private, different health care activities, providers, diseases, population groups and regions in a country. It helps in developing nationals

Data cited at: Global Fund