Organisation for Economic Co-operation and Development

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.

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.

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

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 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  

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).

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

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.

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.

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 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)

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.

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 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

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

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.

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).

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.

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.

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.

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.

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

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

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 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 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.

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 Maritime Transport Costs (MTC)database contains data from 1991 to the most recent available year of bilateral maritime transport costs. Transport costs are available for 43 importing countries (including EU15 countries as a custom union) from 218 countries of origin at the detailed commodity (6 digit) level of the Harmonized System 1988. This dataset should only be used in conjunction with the paper Clarifying Trade Costs in Maritime Transport which outlines methodology, data coverage and caveats to its use. Key Statistical Concept Import charges represent the aggregate cost of all freight, insurance and other charges (excluding import duties) incurred in bringing the merchandise from alongside the carrier at the port of export and placing it alongside the carrier at the first port of entry in the importing country. Insurance charges are therefore included in the transport cost variables and are estimated to be approximately 1.5% of the import value of the merchandise.

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]

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.

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.

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).

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.

Net Replacement Rates in unemployment measure the proportion of income that is maintained after 1, 2, …, T months of unemployment.   Calculations for families with children assume 2 children aged 4 and 6 who do not use formal childcare.

This dataset provides the whole set of OECD annual 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

This table presents the full sequence of non-financial accounts in the national accounts from the production account to the capital account. The sequence of non-financial accounts is presented for the economy of each country (or area) as a whole and also for its sectors: Non-financial Corporations, Financial Corporations, General Government, Households and Non-profit institutions serving households (NPISHs) and for the Rest of the world account. This table presents the Revenue (or Resources) side of the accounts, including the balancing items. It is designed to be used in conjunction with the table entitled 'Quarterly non-financial accounts by institutional sector (Expenditure)'. 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 in order to view the full sequence of non-financial accounts. Alternatively, specific lines within the sequence can be selected using the ‘Transaction’ filter to compare this item for combinations of sectors, countries and time periods. These indicators were presented in the previous dissemination system in the QASA_TABLE801 dataset. Explore also the GDP and non-financial accounts webpage: GDP and non-financial accounts webpage OECD statistics contact: [email protected]

Non-medical determinants of health: Unhealthy lifestyles and poor environments cause millions of people to die prematurely. Smoking, harmful alcohol use, physical inactivity and obesity are the root cause of many chronic conditions. This dataset presents the latest data for tobacco consumption (including daily smokers by age and sex), vaping (by age and sex), alcohol consumption, fruits and vegetables consumption, as well as measured and self-reported data on overweight and obesity.

The OECD Digital Economy Outlook 2020 examines trends and analyses emerging opportunities and challenges in the digital economy. It highlights how OECD countries and partner economies are taking advantage of information and communication technologies (ICTs) and the Internet to meet their public policy objectives. Through comparative evidence, it informs policy makers of regulatory practices and policy options to help maximise the potential of the digital economy as a driver for innovation and inclusive growth.   This third edition of the OECD Digital Economy Outlook provides a holistic overview of converging trends, policy developments and data on both the supply and demand sides of the digital economy. It illustrates how the digital transformation is affecting economies and societies. Finally, it provides a special focus on how the COVID-19 pandemic is amplifying opportunities and challenges from the digital transformation.

The OECD Science, Technology and Industry Outlook reviews key trends in STI policies and performance in OECD countries and major emerging economies. It is published every two years and draws on a unique international policy survey conducted by the OECD - with more than 45 countries involved in 2014 - and the latest OECD work on STI policy analysis and measurement. Following an overview of the recent STI global landscape, key current policy issues are discussed across a series of thematic policy profiles. Country profiles report the STI performance of individual countries and the most recent national policy developments.

  The OECD Weekly Tracker of GDP growth provides a real-time high-frequency indicator of economic activity using machine learning and Google Trends data. It has a wide country coverage of OECD and G20 countries. The Tracker is thus particularly well suited to assessing activity during the turbulent period of the current global pandemic. It applies a machine learning model to a panel of Google Trends data for 46 countries, and aggregates together information about search behaviour related to consumption, labour markets, housing, trade, industrial activity and economic uncertainty.   The Weekly Tracker proxies the percent change in weekly GDP levels from the pre-crisis trend. The pre-crisis trend is taken from OECD forecasts made prior to the crisis (in the November 2019 Economic Outlook). Two other flavours of the Tracker are also available in the datafiles: a Tracker of weekly GDP growth year-on-year (that is, the percent change in weekly GDP from the same week in the past year), and a Tracker of weekly GDP growth year-on-two-year (the percent change in weekly GDP from the same week two years earlier). 

Outbound tourism comprises the activities of residents of a given country travelling to and staying in places outside their country of residence.

The OECD Pensions at a Glance Database has been developed in order to serve a growing need for pensions indicators. It includes reliable and internationally comparable statistics on public and mandatory and voluntary pensions. It covers OECD countries and aims to cover all G20 countries. Pensions at a Glance reviews and analyses the pension measures enacted or legislated in OECD countries for workers entering the labour market at age 22 in the specified year. It provides an in-depth review of the first layer of protection of the elderly, first-tier pensions across countries and provideds a comprehensive selection of pension policy indicators for all OECD and G20 countries. OECD Pensions at a Glance - OECD and G20 indicators

The OECD Productivity Database aims at providing users with the most comprehensive and the latest productivity estimates. The update cycle is on a rolling basis: each variable in the dataset is made publicly available as soon as it is updated in the sources databases. The productivity database contains data on labour productivity both measured using employment or hours worked and the compenents of capital and labour inputs. The productivity database in levels, in growth rates and by industry contains annual data, while the database on productivity and unit labour costs are quarterly estimates. Further information for all datasets and the methodology may be found in the attached file OECD-Productivity-Statistics-Database-metadata

Data on Public Sector Debt is for the whole of the public sector which includes financial and non-financial public corporations as well as General Government. The table presents estimates of gross debt broken down by financial instrument (such as debt securities, loans and insurance, pensions and standardized guarantees), by whether the debt is denominated in domestic or foreign currency and by the residence of the creditor. You can also choose breakdowns by maturity using the ‘Original and residual maturity’ filter. Unless otherwise specified, data is consolidated within sectors and across sectors (meaning that all reciprocal stock positions and flows between units belonging to the same sector and between subsectors of the public sector are eliminated); and results are in nominal values, by contrast with the General Government financial balance sheets which are in market values. These indicators were presented in the previous dissemination system in the QASA_TABLE7PSD dataset. Explore also the OECD Government Finances and Public Sector Debt webpage: Government Finances and Public Sector Debt 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 it 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 QASA_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 QASA_TABLE720R dataset. Explore also the OECD Financial Accounts and Balance Sheets webpage: Financial Accounts and Balance Sheets webpage OECD statistics contact: [email protected]

This dataset presents reference statistics (GDP, Total Government Expenditure, deflators, etc.) that are used to calculate some of the indicators on educational expenditure included in the indicators dataset.

The OECD STRI is a unique, evidence-based tool that collects information on services trade restrictions across 22 services sectors. The project has two distinct but complementary instruments: a services trade regulatory database and a services trade restrictiveness index. Based on the qualitative information in the database, composite indices quantify the identified restrictions across five standard policy categories, with values between zero and one. Complete openness to trade and investment gives a score of zero, while being completely closed to foreign services providers yields a score of one.

The share of a population covered for a core set of health services offers an initial measure of access to care and financial protection. Most OECD countries have achieved universal or near-universal coverage for a core set of health services, which usually include consultations with doctors, tests and examinations, and hospital care.

STAN database for structural analysis provides analysts and researchers with a comprehensive tool for analysing industrial performance at a relatively detailed level of activity across countries. It includes annual measures of output, value added and its components, labour input, investment and capital stock thus allowing to construct indicators which focus on productivity growth, competitiveness and general structural change. STAN is primarily based on Member countries' Annual National Accounts by economic activity tables compiled according to the recommendations of System of National Accounts 2008 (SNA 2008). Previous versions of STAN (from 2000) were based on SNA93 statistics. Missing data are estimated using other sources such as national industrial surveys/censuses. Time series are extended back to the 1970's where possible. This is done using vintage SNA93 or STAN estimates. In STAN, many data points are Secretariat's estimates and are flagged to the attention of users; as such, they do not represent official Member countries' submissions. The current version of STAN is using an industry list based on the International Standard Industrial Classification of all economic activities, Revision 4 (ISIC Rev. 4). Earlier versions of STAN were based on ISIC Rev. 3 and, prior to 2000, ISIC Rev. 2 (the latter covering the manufacturing industries only).The industries covered in STAN provide sufficient detail to highlight technology and digital-intensive sectors. • Structure • Documentation • Coverage Note that STAN updates resume progressively starting from the 1st quarter of 2024. Users are encouraged to send comments or questions to [email protected]

OECD statistics contact: [email protected] The OECD Secretariat collects a wide range of statistics on businesses and business activity. The Structural Business Statistics by size class dataset is part of the Structural and Demographic Business Statistics (SDBS) database featuring the harmonised data collection of the OECD Statistics and Data Directorate relating to a number of key variables, such as value added, operating surplus, employment, and the number of business units. Data are broken down to class (4-digit) level of International Standard of Industrial Classification (ISIC Revision 4), and by enterprise size class based on the number of persons employed. Data cover OECD member and partner countries, non-OECD countries that are members of the European Statistical System who provide data to Eurostat, as well as countries participating in OECD Regional initiatives.

Student-teacher ratio refers to the average number of students per teacher, while average class size is the average number of students in a classroom.

Total supply refers to the sum of output produced in the territory and imports of all goods and services in the economy, which is broken down by type of product. Purchasers’ prices refer to the prices paid by the buyer. For each product, the indicator is calculated as: Imports of the product / Total supply at purchasers’ prices of the same product. This indicator is calculated by the OECD from the Supply table reported to the OECD by countries in their answers to the Supply and Use questionnaire. The dataset corresponds to SNA_TABLE45 dataset in the previous dissemination system. A mapping between the new codes and previous codes is available in SUT_INDICATOR_Codes_mapping Explore the OECD SUT webpage SUT webpage

This dataset describes the supply of goods and services in the economy by product and by type of supply, distinguishing between whether the products supplied are produced domestically or imported. It presents the Supply table at basic prices (the price received by the producer or, for imports, the value at the border) and purchasers’ prices (the price paid by the buyer). The Supply table is organized in a matrix format: The columns provide information about the suppliers. They consist of: output by economic activity (at the 2-digit level of the International Standard Industrial Classification of All Economic Activities (ISIC) Rev 4, containing 89 industries); imports of goods and services valued on a cif basis; cost insurance freight (cif) basis; cif/fob (free on board) adjustment; direct purchases abroad by residents; trade and transport margins (broken down between trade margins and transports margins); taxes less subsidies on products (broken down between taxes on products and subsidies on products). The rows provide a breakdown by product (using the comparable European Classification of Products by Activities (CPA) breakdown). The dataset has been prepared from statistics reported to the OECD by countries in their answers to the annual Supply and Use questionnaire. Information about data availability is available in SUT updates The dataset corresponds to SNA_TABLE30 dataset in the previous dissemination system. A mapping between the new codes and previous codes is available in SUT_SUPPLY_Codes_mapping The file SUT_Tips contains further suggestions on how to navigate and use the various Supply and Use tables (SUTs) in the new dissemination system. Explore the OECD SUT webpage SUT webpage

This dataset describes the breakdown of output of the economy at basic prices (the price received by the producer) into market output, output for own final use (goods or services produced and kept for its own final consumption or investment) and non-market output (goods or services provided free of charge or at prices that are economically insignificant), by activity at the 2-digit level of the International Standard Industrial Classification of All Economic Activities ISIC Rev 4 level (containing 89 industries). The dataset has been prepared from statistics reported to the OECD by countries in their answers to the annual Supply and Use questionnaire. Information about data availability is available in SUT updates The dataset corresponds to SNA_TABLE31 dataset in the previous dissemination system. A mapping between the new codes and previous codes is available in SUT_SUPPLYP1_Codes_mapping The file SUT_Tips contains further suggestions on how to navigate and use the various Supply and Use tables (SUTs) in the new dissemination system. Explore the OECD SUT webpage SUT webpage

This dataset describes the matrix of trade and transport margins (trade margins are the difference in price realised by a wholesaler or retailer when reselling a good compared with the price to replace the good ; transport margins are transportation charges explicitly invoiced for the delivery). This dataset is one of the valuation matrices that are used to transform the Use table at purchasers’ prices (the price paid by the buyer) into the Use table at basic prices (the price received by the producer or for imports, the value at the border). The columns provide information about trade and transport margins related to intermediate consumption by economic activities (at the 2-digit level of the International Standard Industrial Classification of All Economic Activities (ISIC) Rev 4, containing 89 industries); final consumption expenditure of households, general government and non-profit institutions serving households (NPISHs); gross capital formation (broken down between gross fixed capital formation, changes in inventories, and acquisitions less disposals of valuables); and exports. The rows provide a breakdown by product (using the comparable European Classification of Products by Activities (CPA) breakdown). The dataset has been prepared from statistics reported to the OECD by countries in their answers to the annual Supply and Use questionnaire. Information about data availability is available in SUT updates The dataset corresponds to SNA_TABLE44 dataset in the previous dissemination system. A mapping between the new codes and previous codes is available in SUT_VALUATION_Codes_mapping The file SUT_Tips contains further suggestions on how to navigate and use the various Supply and Use tables (SUTs) in the new dissemination system. Explore the OECD SUT webpage SUT webpage

This dataset describes the use of goods and services in the economy by product and by type of use, distinguishing between intermediate consumption (use of a product as input into a production process) and various categories of final demand such as consumption, investment and exports. It presents the Use table at basic prices (the price received by the producer or for imports, the value at the border). The Use table is organized in a matrix format: The columns provide information about the type of use and consist of intermediate consumption by economic activity (at the 2-digit level of the International Standard Industrial Classification of All Economic Activities (ISIC) Rev 4, containing 89 industries); final consumption expenditure of households, general government and non-profit institutions serving households; investment or gross capital formation (broken down between gross fixed capital formation, changes in inventories, acquisitions less disposals of valuables); and exports, of which re-exports. The rows provide a breakdown by product (using the comparable European breakdown Classification of Products by Activities (CPA) breakdown). This dataset does not contain the value added block. This is presented separately in the dataset “SUT Use, Value added and its components by activity”. The dataset has been prepared from statistics reported to the OECD by countries in their answers to the annual Supply and Use questionnaire. Information about data availability is available in SUT updates The dataset corresponds to SNA_TABLE43 dataset in the previous dissemination system. A mapping between the new codes and previous codes is available in SUT_USEBP_Codes_mapping The file SUT_Tips contains further suggestions on how to navigate and use the various Supply and Use tables (SUTs) in the new dissemination system. Explore the OECD SUT webpage SUT webpage

This dataset describes the use of goods and services in the economy by product and by type of use, distinguishing between intermediate consumption (products and services bought and consumed into a production process) and various categories of final demand such as consumption, investment and exports. It presents the Use table at purchasers’ prices (the price paid by the buyer). The Use table is organized in a matrix format: The columns provide information about the type of use and consist of intermediate consumption by economic activity (at the 2-digit level of the International Standard Industrial Classification of All Economic Activities (ISIC) Rev 4, containing 89 industries); final consumption expenditure of households, general government and non-profit institutions serving households (NPISHs); ‘gross capital formation’ or investment (broken down between gross fixed capital formation, changes in inventories, acquisitions less disposals of valuables); and exports, of which re-exports. The rows provide a breakdown by product (using the comparable European Classification of Products by Activities (CPA) breakdown). This dataset does not contain the value added block. This is presented separately in the dataset “SUT Use, Value added and its components by activity”. The dataset has been prepared from statistics reported to the OECD by countries in their answers to the annual Supply and Use questionnaire. Information about data availability is available in SUT updates The dataset corresponds to SNA_TABLE40 dataset in the previous dissemination system. A mapping between the new codes and previous codes is available in SUT_USEPP_Codes_mapping The file SUT_Tips contains further suggestions on how to navigate and use the various Supply and Use tables (SUTs) in the new dissemination system. Explore the OECD SUT webpage SUT webpage

The dataset contains the value added block of the Use table and complements the dataset “SUT Use at purchasers' prices”. It describes output, intermediate consumption (use of a product as input into a production process) and value added disaggregated to show the elements of the generation of income account: compensation of employees (wages and salaries paid to employees and their employers’ social contributions),other taxes less subsidies on production, gross operating surplus (business profits), and gross mixed income (profits of the self-employed), broken down by activity at the 2-digit level of the International Standard Industrial Classification of All Economic Activities (ISIC) Rev 4 (containing 89 industries). The dataset has been prepared from statistics reported to the OECD by countries in their answers to the annual Supply and Use questionnaire. Information about data availability is available in SUT updates The dataset corresponds to SNA_TABLE41 dataset in the previous dissemination system. A mapping between the new codes and previous codes is available in SUT_USEVA_Codes_mapping The file SUT_Tips contains further suggestions on how to navigate and use the various Supply and Use tables (SUTs) in the new dissemination system. Explore the OECD SUT webpage SUT webpage

This dataset (TEC 01) presents a breakdown by economic activity according to International Standard Industrial Classification, Revision 4 (ISIC Rev. 4) and by employment size class. International trade statistics are among the most widely available and consulted data, and offer a picture of trade flows between countries, broken down by types of goods and services. However, such conventional international trade statistics do not offer insights into the actors who are actually engaged in cross-border trade. The Trade by Enterprise Characteristics (TEC) database aims to fill this gap, and contains international annual trade in goods data broken down by different categories of enterprises. The data provide a solid basis for policy analyses that explore which types of firms are responsible for international trade in goods. It answers questions like who are the firms that are engaged in foreign markets, and what are their characteristics. Both the export and import values and the number of exporting and importing enterprises are available for 26 OECD and 8 non-OECD countries: including 27 EU member states plus Canada, Costa Rica, Norway, Israel, Turkey, the United Kingdom and the United States. Data for the United Kingdom haven't been updated since reference year 2018, for Korea and Mexico since reference year 2015. The database consists of ten datasets presenting various combinations of breakdowns by economic activity, employment size class, concentration of trade, partner countries, commodity, type of traders, type of ownership (foreign vs. domestic), exports intensity. TEC data are collected in co-operation with Eurostat and directly from National Statistical Authorities (NSOs). To create TEC data, NSOs have to attribute trade flows to enterprises with different characteristics by merging data on international trade (usually customs data) with statistical business register information on enterprises at the individual enterprise level. Related datasets: Employer Business Demography Statistics, Business Demography Statistics, Regional Business Demography, Structural Business Statistics by Size Class, Timely Indicators of Entrepreneurship by Enterprise Characteristics.

The Trade in Value Added (TiVA) database consists of a set of measures that aim to provide better insights into global production networks and supply chains than is possible with conventional trade statistics.   The Origin of value added in final demand presented here, is derived from the latest version of OECD’s Inter-Country Input-Output (ICIO) database and provides estimates of final demand in country c for industry i final goods and services, broken down by the value added originating from source industry j in source country s.   In other words, it reveals how the value of final demand goods and services consumed within a country is an accumulation of value generated by many industries in many countries.   For a description of the method used for calculating these estimates using the ICIO   Domestic value added origin is shown where source country s = c and, for convenience, also represented by source country = “DXD: Domestic”.   From this data cube, a range of final demand-based measures can be derived including those in TiVA principal indicators cube such as: • Domestic value added embodied in foreign final demand, FFD_DVA and related partner shares FFD_DVApSH. • Foreign value added embodied in domestic final demand, DFD_FVA and related partner shares DFD_FVApSH.

The Trade-in Value Added (TiVA) database consists of a set of measures that aim to provide better insights into global production networks and supply chains than is possible with conventional trade statistics.   The Origin of value-added in gross imports presented here is derived from the latest version of OECD’s Inter-Country Input-Output (ICIO) database. It provides estimates of gross imports by country c of goods and services from industry in partner country/region p broken down by value-added originating from source country/region s.   In other words, the four dimensions link the imports of country c to the value-added from source country s embodied in the exports of industry in the exporting country p - thus revealing how the value of a country’s gross imports of intermediate and final products from a particular partner is an accumulation of value generated by many countries.   For a description of the method used for calculating these estimates, using the ICIO   From this data cube, a range of gross imports-based measures can be derived including the following found in the main TiVA indicators database: • Total gross imports by industry, IMGR (c, i): set exporting country p = World and source country s = World. • Domestic value-added content of gross imports by partner and industry, IMGR_DVA (c, i, p): set source country s = importing country c. • Share of IMGR_DVA in relation to IMGR: IMGR_DVAsh (c, i, p).   Note that the same value-added originating from source country s can be present in the gross imports of more than one importing country c (as embodied value-added, from upstream production, may cross national borders many times). In general, therefore, these estimates should be viewed from the perspective of an importing country c.

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 "Investment Spending in Transport Infrastructure". The original data is collected in national currency, current values. Data are converted and published in euros, both current and constant (2015 prices). The variables collected include investment, maintenance spending and capital value of road, rail, inland waterways, maritime ports and airports. Data are published annually on 31 March. Data series start in 1995 and continue until the current year-2, or the most recent available data.

While much of the comparative evidence on inequalities that is currently available refers to household income, wealth is a critical dimension of households’ economic well-being. How wealth is distributed is important for equity and inter-generational mobility, but also for the stability of the economic system and for its resilience to shocks. While the lack of comparative evidence in this field reflects the absence of an agreed standard that statistical offices could use when collecting this information, this gap has been addressed by the OECD with the release in 2013 of a set of statistical guidelines in this field. In 2013, the OECD issued a set of ‘Guidelines’ for micro statistics on household wealth (OECD, 2013) and an increasing number of countries have engaged in the collection of micro statistics in this field (European Central Bank, 2013). Building on these initiatives as well as others, such as the Luxembourg Wealth Study (Sierminska et al, 2006) which have informed previous OECD analysis (Jantii et al., 2008), the OECD has updated the data on the distribution of household wealth for OECD countries, based on the set of conventions and classifications proposed in the 2013 OECD Guidelines.