Organisation for Economic Co-operation and Development

The gross nutrient balances (N and P) are calculated as the difference between the total quantity of nutrient inputs entering an agricultural system (mainly fertilisers, livestock manure), and the quantity of nutrient outputs leaving the system (mainly uptake of nutrients by crops and grassland). Gross nutrient balances are expressed in tonnes of nutrient surplus (when positive) or deficit (when negative). This calculation can be used as a proxy to reveal the status of environmental pressures, such as declining soil fertility in the case of a nutrient deficit, or for a nutrient surplus the risk of polluting soil, water and air. The nutrient balance indicator is also expressed in terms of kilogrammes of nutrient surplus per hectare of agricultural land to facilitate the comparison of the relative intensity of nutrients in agricultural systems between countries.

The gross nutrient balances (N and P) are calculated as the difference between the total quantity of nutrient inputs entering an agricultural system (mainly fertilizers, livestock manure), and the quantity of nutrient outputs leaving the system (mainly uptake of nutrients by crops and grassland). Gross nutrient balances are expressed in tonnes of nutrient surplus (when positive) or deficit (when negative). This calculation can be used as a proxy to reveal the status of environmental pressures, such as declining soil fertility in the case of a nutrient deficit, or for a nutrient surplus the risk of polluting soil, water and air. The nutrient balance indicator is also expressed in terms of kilogrammes of nutrient surplus per hectare of agricultural land to facilitate the comparison of the relative intensity of nutrients in agricultural systems between countries.

This database includes annual, quarterly and monthly information on carbon dioxide (CO2) emissions related to commercial passenger, freight, and general aviation flights, on both a territory and a residence basis, for 186 countries. These CO2 emissions are estimated by the OECD, based on a consistent methodology across countries. The main source used for the estimation of these CO2 emissions is a database compiled by the International Civil Aviation Organisation (ICAO) with all commercial passenger and freight flights around the world.

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 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]

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.

Data source used: The aquaculture production data collection is part of the more comprehensive data gathering carried out on an annual basis by the Fisheries Committee (COFI) of the Trade and Agriculture Directorate (TAD) from OECD members and participating non-OECD economies. Data on marine landings, aquaculture production, inland fisheries catch, fleet, employment, total allowable catch (TAC) and fisheries support estimate (FSE) are collected from Fisheries Ministries, National Statistics Offices and other institutions designated as an official data source. The surveys used for this exercise are the OECD Fisheries questionnaires.

The balance of payments is a statistical statement that provides a systematic summary of economic transactions of an economy with the rest of the world, for a specific time period. The transactions are for the most part between residents and non-residents of the economy. A transaction is defined as an economic flow that reflects the creation, transformation, exchange, transfer, or extinction of economic value and involves changes in ownership, of goods or assets, the provision of services, labour or capital. This dataset presents economies compiling balance of payments statistics in accordance with the 6th edition of the Balance of Payments and International Investment Position Manual published by the IMF (BPM6). Transactions include: the goods and services accounts, the primary income account (income account in BPM5), the secondary income account (transfers in BPM5), the capital account, and the financial account. All economies disseminated here produce balance of payments according to BPM6; providing strong cross-country comparability. As such the main purpose of this dataset is to provide relevant, reliable, consistent, comparable and timely aggregate quarterly balance of payments statistics for analytical purposes. Nevertheless there are some deviations from standard definitions that are indicated in notes (see « i » attached to series). In the financial account, for net value, a positive sign indicates a net flow from the domestic economy to the rest of the world (a lending to the rest of the world) and a negative sign, a net flow from the rest of the world to the domestic economy (i.e. a net borrowing from the rest of the world). At the level of the sub items (investment abroad investment in the reporting economy etc.), a positive sign indicates an increase of the sub item under consideration and a negative sign a decrease. These conventions are imposed by the BPM6. The dataflow covers : all OECD member countries, G20 economies and a selection of non-member economies. The currency unit used for all series is: Millions of US dollars or Millions of National Currency. OECD statistics contact: [email protected] http://www.oecd.org/sdd

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.

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.

Institutional coverage As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Item coverage Business written in the reporting country on a gross and net premium basis. It contains a breakdown between domestic companies, foreign-controlled companies and branches and agencies or foreign companies.

OECD Indicators on Carbon dioxide (CO2) emissions embodied in international trade (TeCO2) are derived by combining the 2021 editions of OECD Inter-Country Input-Output (ICIO) Database and of International Energy Agency (IEA) statistics on CO2 emissions from fuel combustion. In this release of TeCO2, emissions from fuels used for international aviation and maritime transport (i.e. aviation and marine bunkers) are also considered.Production-based CO2 emissions are estimated by allocating the CO2 emissions to the 45 target industries in OECD ICIO and, to household final consumption of fuels, by both residents and non-residents.Demand-based CO2 emissions are calculated by multiplying the intensities of the production-based emissions (c) with the global Leontief inverse (I-A)(-1) and global final demand matrix (Y) from OECD ICIO, taking the column sums of the resulting matrix and adding residential and private road emissions (FNLC), i.e. direct emissions from final demand: colsum [ diag(c) (I-A)(-1) Y ] + FNLC.For more information, see TeCO2 web page: http://oe.cd/io-co2.

Institutional coverage As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Item coverage Commissions in the reporting country, containing a breakdown between domestic companies, foreign-controlled companies and branches and agencies of foreign companies.

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 provides information on the level of public equipment installed by countries to managed and abate water pollution. It shows the percentage of national population connected to "public" sewerage networks and related treatment facilities, and the percentage of national population connected to "public" wastewater treatment plants, and the degree of treatment. Connected here means actually connected to a wastewater plants through a public sewage network. When analysing these data, it should be kept in mind that the optimal connection rate is not necessarily 100%. It may vary among countries and depends on geographical features and on the spatial distribution of habitats. The interpretation of those data should take into account some variations in countries' definitions, as reflected in metadata. Data source(s): Joint OECD/Eurostat questionnaire on Inland Waters. Data for non-OECD countries is sourced from UNSD (https://unstats.un.org/unsd/envstats/country_files)

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).

Note: CPA data for 2018 and 2019 are projections from the 2016 Survey on Forward Spending Plans. Country Programmable Aid (CPA), outlined in our Development Brief  and also known as “core” aid, is the portion of aid donors programme for individual countries, and over which partner countries could have a significant say. CPA is much closer than ODA to capturing the flows of aid that goes to the partner country, and has been proven in several studies to be a good proxy of aid recorded at country level. CPA was developed in 2007 in close collaboration with DAC members. It is derived on the basis of DAC statistics and was retroactively calculated from 2000 onwards

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.

As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business datawhere composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Click to collapse Item coverage Outstanding investment by direct insurance companies, classified by investment category, by the companies' nationality and by its destination (domestic or foreign). As of 2009, investment data exclude assets linked to unit-linked products sold to policyholders.

Graduates/new entrants in each educational field as a percentage of the sum of graduates/new entrants in all fields.

Tourism can be regarded as a social, cultural and economic phenomenon related to the movement of people outside their usual place of residence.

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 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).

Enrolment rate per age is the percentage of students enrolled in each type of institution over the total of students

This indicator examines the share of students by gender, programme orientation, mode of study and type of institution over the total number of students.

Number of students enrolled in different education programmes by country of origin and sex.

Data on enterprises and employment in tourism industry.

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 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 counterpart area, BMD4 includes Foreign Direct Investment (FDI) payments and receipts by partner country for OECD reporting economies:FDI income payments (or income on inward FDI) by partner country measure the total returns within a year on direct investment stocks paid by enterprises in the reporting economy to their foreign investors, by destination countries or regions, enabling, for example, the identification of the major destinations of FDI income payments for a specific OECD economy in that year. FDI income payments are allocated to the immediate counterpart country.FDi income receipts (or income on outward FDI) by partner country 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 source countries or region, enabling, for example, the identification of the major sources of FDI income receipts for a specific OECD economy in that year.. FDI income receipts are allocated to the immediate counterpart country or region for all OECD countries. Income payments and receipts (or income on inward and outward FDI respectively) 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 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 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.

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

The dataset Fisheries International collaboration in technology development (bilateral) provides the number of co-inventions (simple patent families) developed jointly by at least two inventors. This indicator is disaggregated by: Country - country of residence of the inventor(s), integral counted; in cases when inventors from more than two countries collaborate, this is translated into distinct bilateral relationships between country pairs. For example, if inventors from 3 countries collaborate (e.g. USA, DEU, JPN) then a unit count is assigned to 6 country pairs (USA-DEU, USA-JPN, DEU-JPN, DEU-USA, JPN-USA, JPN-DEU); in this case a country generally coordinate the project and the others are partners. Partner – country of residence of the inventor(s) who collaborate to the patent. Technology domain – the three main areas of innovation in fisheries and aquaculture, related to technology development. In detail: 1. Harvesting technology such as more effective ways to find or harvest fish and which are typically associated with improvements in catch per unit of effort (e.g. type/size of vessels and their methods of propulsion, search technologies, method of catching or harvesting fish and bringing them on board); 2.Aquaculture technology such as methods to more effectively grow fish in captivity (innovation in feeds, improving the health of aquaculture animals, etc.); 3. New products and markets such as the development of new fish products and markets (food technologies/processing such as the development of surimi as a crabmeat substitute) and the improvement of market access (secure or enlarge markets for fish products) that provides important incentives for green growth (e.g. eco-certification with fishers adopting by-catch saving technologies or modifying fishing practices and/or territorial user rights in fisheries).

The OECD FISH Unit, in collaboration with the Environment Directorate and the Directorate for Science, Technology and Innovation, has developed patent-based innovation indicators that are suitable for tracking developments in fisheries-related technologies. The search strategy for fisheries and aquaculture related technologies adopts a mixed solution with a definition of the technical field of interest in fisheries and aquaculture innovation complemented by keywords, e.g. by looking for keywords in the International Patent Classification (IPC) codes and checking manually the relevance of the results in the text of patents (in the title, the abstract, etc). Technology domains are detailed in the ANNEX attached below. The indicators allow the assessment of countries' and firms' innovative performance as well as the design of governments' fisheries, aquaculture and innovation policies.

The OECD Fisheries Support Estimates (FSE) database is intended to be the best source of information on fisheries policies in OECD members and participating non-OECD economies.   It is designed to monitor and quantify developments in fisheries policy, to establish a common basis for policy dialogue among countries, and to provide economic data to assess the effectiveness and efficiency of policies.   These tables report country programmes data aggregated according to the main categories presented in the FSE Manual.   More detailed documentation on country programmes can be found in country-level metadata; more data on country programmes can be found in the full dataset (Excel Format - link provided below). Statistics are organized in pivot tables to make possible cross-country comparisons and to filter disaggregated policy-level data by policy implementation criteria and country.   The FSE data collection is part of the more comprehensive data gathering carried out on an annual basis by the Fisheries Committee (COFI) of the Trade and Agriculture Directorate (TAD) from OECD members and participating non-OECD economies.   Data on landings, aquaculture production, inland fisheries catch, fleet, employment, total allowable catch (TAC) and fisheries support estimate (FSE) are collected from Fisheries Ministries, National Statistics Offices and other institutions designated as an official data source. The surveys used for this exercise are the OECD Fisheries questionnaires.

Freshwater abstractions:   This dataset shows water abstractions by source (surface and ground water) and by major uses. Water abstractions refer to water taken from ground or surface water sources and conveyed to the place of use. If the water is returned to a surface water source, abstraction of the same water by the downstream user is counted again in compiling total abstractions.   When interpreting those data, it should be borne in mind that the definitions and estimation methods employed by member countries may vary considerably.   Data source(s): Joint OECD/Eurostat questionnaire on Inland Waters. Data for non-OECD countries is sourced from UNSD (https://unstats.un.org/unsd/envstats/country_files)  

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

Data include pension funds per the OECD classification by type of pension plans and by type of pension funds. All types of plans are included (occupational and personal, mandatory and voluntary). The OECD classification considers both funded and book reserved pension plans that are workplace-based (occupational pension plans) or accessed directly in retail markets (personal pension plans). Both mandatory and voluntary arrangements are included. The data include plans where benefits are paid by a private sector entity (classified as private pension plans by the OECD) as well as those paid by a funded public sector entity. A full description of the OECD classification can be found at:http://www.oecd.org/dataoecd/0/49/38356329.pdf. Pension funds include also some personal pension arrangements like the Individual Retirement Accounts (IRAs) in the United States as well as funds for government workers. The coverage of the statistics follows the regulatory and supervisory framework. All authorised pension funds are therefore normally covered by the Global Pension Statistics exercise. Assets pertaining to reserve funds in social security systems are excluded.

Data include pension funds per the OECD classification by type of pension plans and by type of pension funds. All types of plans are included (occupational and personal, mandatory and voluntary). The OECD classification considers both funded and book reserved pension plans that are workplace-based (occupational pension plans) or accessed directly in retail markets (personal pension plans). Both mandatory and voluntary arrangements are included. The data include plans where benefits are paid by a private sector entity (classified as private pension plans by the OECD) as well as those paid by a funded public sector entity. A full description of the OECD classification can be found at: http://www.oecd.org/dataoecd/0/49/38356329.pdf.  Pension funds include also some personal pension arrangements like the Individual Retirement Accounts (IRAs) in the United States as well as funds for government workers. The coverage of the statistics follows the regulatory and supervisory framework. All authorised pension funds are therefore normally covered by the Global Pension Statistics exercise. Assets pertaining to reserve funds in social security systems are excluded.

This dataset contains statistics on Consumer Price Indices - all items, for G20 countries and for the G20 as a whole.  The G20 area consists of the following economies: Argentina, Australia, Brazil, Canada, China, France, Germany, India, Indonesia, Italy, Japan, Korea, Mexico, the Russian Federation, Saudi Arabia, South Africa, Türkiye, the United Kingdom, the United States, the African Union and the European Union. 

The GID-DB is a database providing researchers and policymakers with key data on gender-based discrimination in social institutions. This data helps analyse women’s empowerment and understand gender gaps in other key areas of development.Covering 180 countries and territories, the GID-DB contains comprehensive information on legal, cultural and traditional practices that discriminate against women and girls.

This part contains general information on number of insurance companies and employees within the sector.

This table provides information on the main relevant indicators. The data have mainly been supplied by the World Bank, and cover, where available: -Current Gross National Income (GNI) in US $ millions; -GNI per capita (US $); -Population; -Energy use as kilogram of oil per capita; -Average Life Expectancy of Adults; and -Adult Literacy Rate as a percentage of the country population. Data for Sudan include South Sudan, with the exception of total population, which is reported separately.

Bilateral ODA commitments by purpose. Data cover the years 2005 to 2009. Amounts are expressed in USD million. The sectoral distribution of bilateral ODA commitments refers to the economic sector of destination (i.e. the specific area of the recipient's economic or social structure whose development is, or is intended to be fostered by the aid), rather than to the type of goods or services provided. These are aggregates of individual projects notified under the Creditor Reporting System, supplemented by reporting on the sectoral distribution of technical co-operation, and on actual disbursements of food and emergency aid.

Graduation/entry rates represent an estimated percentage of an age group expected to graduate/enter a certain level of education at least once in their lifetime.

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.

As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Gross claims payments in the reporting country, containing a breakdown between domestic companies, foreign-controlled companies and branches and agencies of foreign companies.

As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. This part contains gross operating expenses in the reporting country, with a breakdown between domestic companies, foreign-controlled companies and branches and agencies of foreign companies.

Productivity is a key driver of economic growth and changes in living standards. Labour productivity growth implies a higher level of output for unit of labour input (hours worked or persons employed). This can be achieved if more capital is used in production or through improved overall efficiency with which labour and capital are used together, i.e., higher multifactor productivity growth (MFP). Productivity is also a key driver of international competitiveness, e.g. as measured by Unit Labour Costs (ULC).   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, i.e. each variable in the dataset is made publicly available as soon as it is updated in the sources databases. However, some time lag may arise which affects individual series and/or countries for two reasons: first, hours worked data from the OECD Employment Outlook are typically updated less frequently than the OECD Annual National Accounts Database; second, source data for capital services are typically available in annual national accounts later than source data for labour productivity and ULCs.   Note to users: The OECD Productivity Database accounts for the methodological changes in national accounts' statistics, such as the implementation of the System of National Accounts 2008 (2008 SNA) and the implementation of the international industrial classification ISIC Rev.4. These changes had an impact on output, labour and capital measurement. For Chile, China, Colombia, India, Japan, Turkey and the Russian Federation the indicators are in line with the System of National Accounts 1993 (1993 SNA); for all other countries, the indicators presented are based on the 2008 SNA

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.

Data source(s) used The inland fisheries data collection is part of the more comprehensive data gathering carried out on an annual basis by the Fisheries Committee (COFI) of the Trade and Agriculture Directorate (TAD) from OECD members and participating non-OECD economies. Data on marine landings, aquaculture production, inland fisheries catch, fleet, employment, total allowable catch (TAC) and fisheries support estimate (FSE) are collected from Fisheries Ministries, National Statistics Offices and other institutions designated as an official data source. The surveys used for this exercise are the OECD Fisheries questionnaires.   Data are collected in tonnes and national currency at current values. For analytical purposes and data comparisons, value data are converted and published also in US dollars. Exchange rates are average yearly spot rates, taken from the dataset OECD Economic Outlook: Statistics and Projections. Data reported in this dataset are expressed in tonnes, in units of national currency and in US dollars. Data are recorded on a landed weight basis, i.e. the mass (or weight) of a product at the time of landing, regardless of the state in which is landed (i.e. whole, gutted, filleted, meal, etc.). For exceptions, please see the individual notes. Statistical population The statistical population is the set of countries participating in the work of the COFI, i.e. OECD members, excluding landlocked countries, with some exceptions (Czech Republic and Slovakia are included, Israel is not). The group includes also the following partner countries: Argentina, China, Colombia, Costa Rica, Indonesia, Lithuania, Peru, Philippines, Thailand and Chinese Taipei. In order to facilitate analysis and comparisons over time, historical data for OECD members have been provided over as long a period as possible, often even before a country became a member of the Organisation. Information on the membership dates of all OECD countries can be found at OECD Ratification Dates. Key statistical concept Inland fisheries include catches of fish, crustaceans, molluscs and other aquatic invertebrates (and animals), residues and seaweeds in lakes, rivers, ponds, inland canals and other land-locked water bodies. For the purpose of this questionnaire the boundary between inland and marine areas at the river mouth is left to the discretion of the national authority. Production from aquaculture installations should not be reported on this form. However, catches from fisheries that are managed by stocking should be included. The methodological reference document for fisheries and aquaculture statistics is the CWP Handbook of Fishery Statistics.

These data are part of a larger database, hosted on a different website, which includes both quantitative and qualitative data, as well as graphs.

As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Breakdown of net premiums written in the reporting country in terms of domestic risks and foreign risks, thus providing an indicator of direct cross-border operations of insurance business.

As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Item coverage Covers business written abroad by branches, agencies and subsidiaries established abroad of domestic undertakings and includes all business written outside the country by these entities (in both OECD and non-OECD countries).

This data deals with premiums written by classes of non-life insurance for the business written in the reporting country.

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.

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 productivity and income estimates presented in this dataset are mainly based on GDP, population and employment data from the OECD Annual National Accounts. Hours worked are sourced from the OECD Annual National Accounts, the OECD Employment Outlook and national sources. 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, i.e. each variable in the dataset is made publicly available as soon as it is updated in the sources databases. However, timely data issues may arise and affect individual series and/or individual countries. In particular, annual hours worked estimates from the OECD Employment Outlook are typically updated less frequently (once a year, in the summer) than series of hours worked from the OECD Annual National Accounts.

This table contains labour force data on labour market status - population, labour force, unemployment and employment - by sex and by detailed age groups and standard age groups (15-24, 25-54, 55-64, 65+, total). Note: Population figures reported in table LFS by sex are Census-based, while the data for this table are taken from labour force surveys. Population for total age group refers to working age population (15 to 64 years).

This dataset contains the age composition (as a percentage of all ages) of the population for each labour force status - labour force, employment, unemployment - by sex.

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).

This dataset presents members' total use of the multilateral system i.e. both their multilateral aid ("Core contributions to") and bilateral aid channelled through ("Contributions through") multilateral organisations. These data originate from members' reporting at item-level in the CRS and are published here starting with 2011 data (item-level data for multilateral aid is not complete in CRS for earlier years).

Database published : June 2020 

Database published : June 2020 

The International Trade (MEI) dataset contains predominantly monthly merchandise trade statistics, and associated statistical methodological information, for all OECD member countries and for all non-OECD G20 economies and the EU.   The dataset itself contains international trade statistics measured in billions of United States dollars (USD) for: Exports, Imports, Balance. In all cases a lot of effort has been made to ensure that the data are internationally comparable across all countries presented and that all the subjects have good historical time-series’ data to aid with analysis.

Air pollution is considered one of the most pressing environmental and health issues across OECD countries and beyond. According to the World Health Organisation (WHO), exposure to fine particulate matter (PM2.5) and ground-level ozone (O3) have potentially the most significant adverse effects on health compared to other pollutants. PM2.5 can be inhaled and cause serious health problems including both respiratory and cardiovascular disease, having its most severe effects on children and elderly people. Exposure to PM2.5 has been shown to considerably increase the risk of heart disease and stroke in particular. For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator. Exposure to ground-level ozone (O3) has serious consequences for human health, contributing to, or triggering, respiratory diseases. These include breathing problems, asthma and reduced lung function (WHO, 2016; Brauer et al., 2016). Ozone exposure is highest in emission-dense countries with warm and sunny summers. The most important determinants are background atmospheric chemistry, climate, anthropogenic and biogenic emissions of ozone precursors such as volatile organic compounds, and the ratios between different emitted chemicals.

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.

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.

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.

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 Agricultural Outlook has been prepared as a joint report by the Organisation for Economic Co-operation and Development (OECD) and the Food and Agriculture Organization (FAO) of the United Nations. The report provides a ten year forward looking, assessment of trends and prospects in the major temperate-zone agricultural commodity markets of biofuels, cereals, oilseeds and oilseed products, sugar, meat, fish and sea food, dairy products, cotton, roots and tubers and pulses. It is published annually, in the middle of the second quarter, as part of a continuing effort to promote informed discussion of emerging market and policy issues. The data used to develop the projections underlying the assessment are those available as of January 2023. The projections and assessments provided in the report are the result of close co-operation between the OECD and FAO Secretariats and national experts with a jointly developed modelling system, based on the AGLINK-COSIMO model, used to facilitate consistency in the projections. The data series for the projections are drawn from OECD and FAO databases. For the most part information in these databases has been taken from national statistical sources. For further details on particular series, enquiries should be directed to the OECD and FAO Secretariats.

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

This table contains figures on the activity of affiliates located abroad by host country in the total manufacturing, total services and total business enterprise sectors. The units used to present data in AMNE are millions of national currency for monetary variables and units for the other variables. Monetary variables are in current prices. Euro-area countries: national currency data is expressed in euro beginning with the year of entry into the Economic and Monetary Union (EMU). For years prior to the year of entry into EMU, data have been converted from the former national currency using the appropriate irrevocable conversion rate. This presentation facilitates comparisons within a country over time and ensures that the historical evolution is preserved. Please note, however, that pre-EMU euro are a notional unit and should not be used to form area aggregates or to carry out cross-country comparisons.

The International Transport Forum collects data on transport statistics on annual basis from all its Member countries. Data are collected from Transport Ministries, statistical offices and other institution designated as official data source. Variables collected are inland transport of goods (T-km), of passengers (P-km) and road injury accidents. Additional information is also gathered on containers transported by rail and sea (Tons and TEU) as well as short sea shipping data (T-km).

Patent counts (including total patents, estimated total patents for latest years): EPO, USPTO, PCT and Patent Families indicators are presented for technology domains defined by the OECD or by WIPO

The Population and Vital Statistics dataset presents components of change in the population during one year and mid-year population data for the 34 OECD member countries. Data are presented in thousands of persons and as rates in per 1000. The components of change in the population during one year are presented as follow: the first statistics refer to the population on January 1st for each year, the natural increase of the population is the difference between the number of births and deaths over the calendar year, the addition of net migration and statistical adjustments to the natural increase gives the total increase of the population over the calendar year. The addition of the total population increase to the population on January 1st gives the population on December 31st. Note: No longer this dataset be collected by OECD. Population and demographic events are available from the United Nation database at "https://esa.un.org/unpd/wpp/Download/Standard/Population/."    

This dataset contains the number of people by sex and age group per country.

The 'Production and Sales (MEI)' dataset is a dataset containing predominantly monthly statistics, and associated statistical methodological information, for the 34 OECD member countries and for selected other economies. The Production and Sales dataset contains industrial statistics on four separate subjects: Production; Sales; Orders; and Work started. The data series presented within these subjects have been chosen as the most relevant industrial statistics for which comparable data across countries is available. For Production, data comprise Indices of industrial production (IIP) for total industry, manufacturing, energy and crude petroleum; and further disaggregation of manufacturing production for intermediate goods and for investment goods and crude steel. For others, they comprise retail trade and registration of passenger cars; and permits issued and work started for dwellings. Considerable effort has been made to ensure that the data are internationally comparable across all countries presented, coverage for as many countries as possible, and that all the subjects have reasonable length of time-series to assist analysis. Most data are available monthly and are presented as an index (where the year 2010 is the base year) or as a level depending on which measure is seen as the most appropriate and/or useful in the economic analysis context. Due to differences in statistical or economic environment at country level, however, availability of data varies from one country to another.

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

Distribution of graduates/new entrants by gender, country of origin and age as well as the proportion of each tertiary educational level over the total of first-time graduates and new entrants at tertiary level.

This dataset contains Purchasing Power Parities (PPPs) for all OECD countries. PPPs are the rates of currency conversion that eliminate the differences in price levels between countries. Per capita volume indices based on PPP converted data reflect only differences in the volume of goods and services produced. Comparative price levels are defined as the ratios of PPPs to exchange rates. They provide measures of the differences in price levels between countries. The PPPs are given in national currency units per US dollar. The price levels and volume indices derived using these PPPs have been rebased on the OECD average. Per capita volume indices should not be used to rank countries as PPPs are statistical constructs rather than precise measures. Minor differences between countries should be interpreted with caution.

The Regional Database contains annual data from 1995 to the most recent available year. The data collection is undertaken by the Directorate of Public Governance and Territorial Development, within the Regional Development Policy division (GOV/RDP). Statistics are collected through an annual questionnaire sent to the delegates of the Working Party on Territorial Indicators (WPTI), and through access to the web-sites of National Statistical Offices and Eurostat. The WPTI is responsible for developing regional (subnational) and urban statistics and providing analysis to support policy evaluations. The Regional Database includes statistics on the regional distribution of resources, regional disparities, and how regions contribute to national growth and the well-being of society. Under this framework, the Regional Database is one of the pillars for providing indicators to the publication OECD Regions at a Glance (link).

The Regional Database contains annual data from 1995 to the most recent available year (generally 2014 for demographic and labour market data, 2013 for regional accounts, innovation and social statistics).   In any analytical study conducted at sub-national levels, the choice of the territorial unit is of prime importance. The territorial grids (TL2 and TL3) used in this database are officially established and relatively stable in all member countries, and are used by many as a framework for implementing regional policies. This classification - which, for European countries, is largely consistent with the Eurostat classification - facilitates greater comparability of regions at the same territorial level. The differences with the Eurostat NUTS classification concern Belgium, Greece and the Netherlands where the NUTS 2 level correspond to the OECD TL3 and Germany where the NUTS1 corresponds to the OECD TL2 and the OECD TL3 corresponds to 97 spatial planning regions (Groups of Kreise). For the United Kingdom the Eurostat NUTS1 corresponds to the OECD TL2. Due to limited data availability, labour market indicators in Canada are presented for a different grid (groups of TL3 regions). Since these breakdowns are not part of the OECD official territorial grids, for the sake of simplicity they are labelled as Non Official Grids (NOG).

Residential Property Prices Indices (RPPIs) – also named House price indices (HPIs), are index numbers that measure the price 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. Among their professional uses, they serve, for example, to monitor macroeconomic imbalances and risk exposure of the financial sector. This dataset covers the 34 OECD member countries and some non-member countries. Please note that not all RPPIs are available for all countries. For instance, the RPPI at the most aggregate level for the United States only covers single-family dwellings, not all types of dwellings as it is the case for most other OECD countries. This dataset presents, for each country, the RPPI that is available at the most aggregate level. It mainly contains quarterly statistics. The dataset called “Residential Property Price Indices (RPPIs) – Complete dataset” contains the full list of available RPPIs. The dataset called “Analytical house price indicators” contains, in addition to nominal RPPIs, information on real house prices, rental prices and the ratios of nominal prices to rents and to disposable household income per capita. The datasets “Analytical house price indicators” and “Residential Property Price Indices (RPPIs) – Headline Indicators” do not refer to the same price indices for Brazil, Canada, China, Germany, the United States and the Euro area. These differences are further documented in country-specific metadata. For the United States, the series used in “Analytical house price indicators” is included in the dataset called “Residential Property Price Indices (RPPIs) – Complete database”, but is not the headline indicator. For all other countries, non-seasonally adjusted price indices in both datasets are identical in the period in which they overlap.For all other countries, non-seasonally adjusted price indices in both datasets are identical on the overlapping period.

A key set of information for policy analysis is i) how much revenue is collected; ii) in what ways is it collected; iii) from which institutional units of the economy are revenues raised for each particular financing scheme; and iv) which financing schemes receive those revenues. This dataset provides information about the contribution mechanisms the particular financing schemes use to raise their revenues. Understanding the nature of the flows is of importance from the perspective of both health and public finance policy. For example, the classification of revenues make it possible to distinguish between public and private funding of health care finance. Understanding how resources are raised by financing schemes is important for many countries, as many health systems are struggling with the issue of funding. The classification of revenues of financing schemes is suitable for tracking the collection mechanisms of a financing framework. Furthermore, the new classification makes it possible to analyse the contribution of the institutional units to health financing.

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.

This indicator shows the percentage of international students in each field of education.

Input-Output tables describe the sale and purchase relationships between producers and consumers within an economy. They can be produced by illustrating flows between the sales and purchases (final and intermediate) of industry outputs or by illustrating the sales and purchases (final and intermediate) of product outputs. The OECD Input-Output database is presented on the former basis, reflecting in part the collection mechanisms for many other data sources such as research and development Research and Development expenditure data, employment statistics, pollution data, energy consumption, which are in the main collected by enterprise or by establishment, and thus according to industry classifications.

Input-Output tables describe the sale and purchase relationships between producers and consumers within an economy. They can be produced by illustrating flows between the sales and purchases (final and intermediate) of industry outputs or by illustrating the sales and purchases (final and intermediate) of product outputs. The OECD Input-Output database is presented on the former basis, reflecting in part the collection mechanisms for many other data sources such as research and development Research and Development expenditure data, employment statistics, pollution data, energy consumption, which are in the main collected by enterprise or by establishment, and thus according to industry classifications.

The OECD indicators of employment protection legislation evaluate the regulations on the dismissal of workers on regular contracts and the hiring of workers on temporary contracts. They cover both individual and collective dismissals.The indicators have been compiled using the Secretariat’s own reading of statutory laws, collective bargaining agreements and case law as well as contributions from officials from OECD member countries and advice from country experts

This dataset presents internationally comparable data on (full-time) salaries of teachers and school heads in public institutions at pre-primary, primary and general (lower and upper) secondary education. Actual salaries are displayed by level of education and are also available by age and gender. Data also include other statistics related to salaries of teachers.

This dataset presents internationally comparable data on (full-time) salaries of teachers and school heads in public institutions at pre-primary, primary and general (lower and upper) secondary education. Statutory salaries are displayed by level of education, Data also include other statistics related to salaries of teachers.

Official Development Financing (ODF), measured for recipient countries only, is defined as the sum of their receipts of bilateral ODA, concessional and non-concessional resources from multilateral sources, and bilateral other official flows made available for reasons unrelated to trade, in particular loans to refinance debt.

This table presents export/import information by enterprise size class and partner country.

This dataset shows the number of exporters and importers and their associated trade values for a selected set of partner countries and zones, broken down by three economic sectors: industry, trade and repair and other sectors. Total values for the wide economy are also displayed.Recommended uses and limitations EU countries break down trade data into Intra- and extra- EU zones, whereas non EU countries report their Total trade. Trade values have been aggregated for EU countries and Total (Intra-EU plus Extra-EU) trade flows are displayed, whereas Intra and Extra-EU data expressed in term of number of enterprises cannot be summed up, because of possible double-counting (same enterprise can be trader in both intra- and extra- EU trade). Data have been collected in ISIC revision 3 from 2003 up to 2007 and in ISIC revision 4 as from reference year 2008. Time series are affected by this change in classification, and thus data are displayed into two separate databases.

The TiVA database contains a range of indicators measuring the value added content of international trade flows and final demand. The indicators are derived from the 2016 version of OECD's Inter-Country Input-Output (ICIO) Database.  The ICIO has been constructed from various national and international data sources all drawn together and balanced under constraints based on official (SNA93) National Accounts by economic activity and National Accounts main aggregates.  Underlying sources used are notably:  • National supply and use tables (SUTs)  • National and harmonised Input-Output Tables • Bilateral trade in goods by industry and end-use category (BTDIxE) and  • Bilateral trade in services.  Compared to the old versions of the TiVA database, this current version includes two more countries, Morocco and Peru. The data are presented for all years from 1995 to 2011. The industry breakdown remains the same. 

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.