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 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.

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.

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.

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 presents the Consolidated financial transactions by economic sector (Quarterly table 0610), according to SNA 2008 methodology. It comprises all flows, which record, by type of financial instruments, the financial transactions between institutional sectors.

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.

Latest Version is available here: https://knoema.com/OECDEO2020DEC/economic-outlook-no-108-december-2020   Economic Outlook No 107 (EO107) 2/2   Given the unusual level of uncertainty caused by the Covid-19 pandemic, this Economic Outlook (EO107) presents two scenarios for each country and economy – one scenario in which a second outbreak occurs in most economies towards the end of this year (double-hit scenario) and an alternative scenario where the second outbreak is avoided (single-hit scenario).Furthermore, only a limited number of series is made available compared to past editions.   This data set presents the double-hit scenario.   The OECD Economic Outlook analyses the major economic trends over the coming 2 years. It provides in-depth coverage of the main economic issues and the policy measures required to foster growth in each member country. Forthcoming developments in selected non-OECD economies are also evaluated in detail. Each edition of the Outlook provides a unique resource to keep abreast of world economic developments. The OECD Economic Outlook database is a comprehensive and consistent macroeconomic database of the OECD economies, covering expenditures, foreign trade, output, labour markets, interest and exchange rates, balance of payments, and government debt. For the non-OECD regions, foreign trade and current account series are available.   The database contains annual data (for all variables) and quarterly figures (for a subset of variables). Variables are defined in such a way that they are as homogenous as possible for the countries covered. Breaks in underlying series are corrected as far as possible. Sources for the historical data are publications of national statistical agencies and OECD data bases such as Quarterly National Accounts, Annual National Accounts, Labour Force Statistics and Main Economic Indicators. The cut-off date for information used in the compilation of the projections was the 4 June 2020.   Concerning the aggregation of world trade, a new composition has been introduced, since projections are now made for the major non-OECD economies. Thus, besides OECD and the OECD euro area, the following new regions are available: Dynamic Asian Economies (Chinese Taipei, Hong Kong, Malaysia, the Philippines, Singapore, Thailand, Vietnam); Oil Producers (Azerbaijan, Kazakhstan, Turkmenistan, Brunei, Timor-Leste, Bahrain, Iran, Iraq, Kuwait, Libya, Oman, Qatar, Saudi Arabia, United Arab Emirates, Yemen, Ecuador, Trinidad and Tobago, Venezuela, Algeria, Angola, Chad, Rep. of Congo, Equatorial Guinea, Gabon, Nigeria, Sudan); with the remaining countries in a residual 'Rest of the World' group.

Latest version is available here: https://knoema.com/OECDEO2020DEC/economic-outlook-no-108-december-2020   Economic Outlook No 107 (EO107) 1/2   Given the unusual level of uncertainty caused by the Covid-19 pandemic, this Economic Outlook (EO107) presents two scenarios for each country and economy – one scenario in which a second outbreak occurs in most economies towards the end of this year (double-hit scenario) and an alternative scenario where the second outbreak is avoided (single-hit scenario).Furthermore, only a limited number of series is made available compared to past editions.   This data set presents the single-hit scenario.   The OECD Economic Outlook analyses the major economic trends over the coming 2 years. It provides in-depth coverage of the main economic issues and the policy measures required to foster growth in each member country. Forthcoming developments in selected non-OECD economies are also evaluated in detail. Each edition of the Outlook provides a unique resource to keep abreast of world economic developments. The OECD Economic Outlook database is a comprehensive and consistent macroeconomic database of the OECD economies, covering expenditures, foreign trade, output, labour markets, interest and exchange rates, balance of payments, and government debt. For the non-OECD regions, foreign trade and current account series are available.   The database contains annual data (for all variables) and quarterly figures (for a subset of variables). Variables are defined in such a way that they are as homogenous as possible for the countries covered. Breaks in underlying series are corrected as far as possible. Sources for the historical data are publications of national statistical agencies and OECD data bases such as Quarterly National Accounts, Annual National Accounts, Labour Force Statistics and Main Economic Indicators. The cut-off date for information used in the compilation of the projections was the 4 June 2020.   Concerning the aggregation of world trade, a new composition has been introduced, since projections are now made for the major non-OECD economies. Thus, besides OECD and the OECD euro area, the following new regions are available: Dynamic Asian Economies (Chinese Taipei, Hong Kong, Malaysia, the Philippines, Singapore, Thailand, Vietnam); Oil Producers (Azerbaijan, Kazakhstan, Turkmenistan, Brunei, Timor-Leste, Bahrain, Iran, Iraq, Kuwait, Libya, Oman, Qatar, Saudi Arabia, United Arab Emirates, Yemen, Ecuador, Trinidad and Tobago, Venezuela, Algeria, Angola, Chad, Rep. of Congo, Equatorial Guinea, Gabon, Nigeria, Sudan); with the remaining countries in a residual 'Rest of the World' group.

The financial indicators are based on data compiled according to the 2008 SNA "System of National Accounts, 2008". Many indicators are expressed as a percentage of Gross Domestic Product (GDP) or as a percentage of Gross Disposable Income (GDI) when referring to the Households and NPISHs sector. The definition of GDP and GDI are the following: Gross Domestic Product: Gross Domestic Product (GDP) is derived from the concept of value added. Gross value added is the difference of output and intermediate consumption. GDP is the sum of gross value added of all resident producer units plus that part (possibly the total) of taxes on products, less subsidies on products, that is not included in the valuation of output [System of National Accounts, 2008, par. 2.138]. GDP is also equal to the sum of final uses of goods and services (all uses except intermediate consumption) measured at purchasers’ prices, less the value of imports of goods and services [System of National Accounts, 2008, par. 2.139]. GDP is also equal to the sum of primary incomes distributed by producer units [System of National Accounts, 2008, par. 2.140]. Gross Disposable Income: Gross Disposable Income (GDI) is equal to net disposable income which is the balancing item of the secondary distribution income account plus the consumption of fixed capital. The use of the Gross Disposable Income (GDI), rather than net disposable income, is preferable for analytical purposes because there are uncertainty and comparability problems with the calculation of consumption of fixed capital. GDI measures the income available to the total economy for final consumption and gross saving [System of National Accounts, 2008, par. 2.145]. Definition of Debt: Debt is a commonly used concept, defined as a specific subset of liabilities identified according to the types of financial instruments included or excluded. Generally, debt is defined as all liabilities that require payment or payments of interest or principal by the debtor to the creditor at a date or dates in the future. Consequently, all debt instruments are liabilities, but some liabilities such as shares, equity and financial derivatives are not debt [System of National Accounts, 2008, par. 22.104]. According to the SNA, most debt instruments are valued at market prices. However, some countries do not apply this valuation, in particular for securities other than shares, except financial derivatives (AF33). In this dataset, for financial indicators referring to debt, the concept of debt is the one adopted by the SNA 2008 as well as by the International Monetary Fund in “Public Sector Debt Statistics – Guide for compilers and users” (Pre-publication draft, May 2011). Debt is thus obtained as the sum of the following liability categories, whenever available / applicable in the financial balance sheet of the institutional sector:special drawing rights (AF12), currency and deposits (AF2), debt securities (AF3), loans (AF4), insurance, pension, and standardised guarantees (AF6), and other accounts payable (AF8). This definition differs from the definition of debt applied under the Maastricht Treaty for European countries. First, gross debt according to the Maastricht definition excludes not only financial derivatives and employee stock options (AF7) and equity and investment fund shares (AF5) but also insurance pensions and standardised guarantees (AF6) and other accounts payable (AF8). Second, debt according to Maastricht definition is valued at nominal prices and not at market prices. To view other related indicator datasets, please refer to: Institutional Investors Indicators [add link] Household Dashboard [add link]

The financial indicators in this dataset are derived from OECD countries’ financial accounts (transactions): they give a picture of the short-term behavior of institutional sectors. They comprise for instance: Net financial transactions of the general government, as a percentage of Gross Domestic Product (GDP), which corresponds to the general government deficit; Transactions in financial assets of Households and NPISHs, as a percentage of Households Gross Disposable Income (GDI); Transactions in liabilities of Households and NPISHs, as a percentage of GDI.

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

This data set contains information of The insurance industry is a major 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 by covering personal and business risks. This annual report monitors global insurance market trends to support a better understanding of the insurance industry's overall performance and health.The OECD has collected and analysed data on insurance such as the number of insurance companies and employees, insurance premiums and investments by insurance companies dating back to the early 1980s. Over time, the framework of this exercise has expanded and now includes key balance sheet and income statement items for the direct insurance and reinsurance sector.

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.

This dataset presents annual population data from 1950 to 2050 by sex and five year age groups as well as age-dependency ratios. The data is available for 46 countries. Data from 1950 to 2011 (2012) are historical data while data from 2012 (2013) are projections. In order to estimate the population in coming years, fertility rate, life expectancy and level of immigration have to be estimated. Assumptions underlying the estimations of each of these three elements are usually categorise as low, medium or high within one specific country. Where a range of projections are available, the projection data presented here are based on the "medium variant". Assumptions underlying the projection data shown are described country per country in the metadata table as well as the source of data. There are three sources for the data: national statistical institutes, Eurostat or the United Nations. The population data is presented in 18 five year age groups which refer to the population from 0-4 to 85 and more. The following age groups are also available: less than 15, less than 20, 15 to 64, 20-64, 65 and over. Age-dependency ratios are also presented. Assumptions by country. Data are presented for 46 countries. The 34 OECD member countries, the 6 EU countries not belonging to the OECD, and Brazil, Colombia, India, Indonesia, China, Russia and South Africa.

This indicator shows the working hours needed to escape poverty for a jobless family claiming Guaranteed Minimum Income benefits.

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.

Institutional Investors' Assets and Liabilities data are reported by Central Banks, National Statistical Institutes or Supervisory Authorities. The indicators reported here are compiled on the basis of those statistics.   The first set of indicators measure total financial assets (liabilities) held by each institutional investor as a percentage of GDP. Total financial assets (liabilities) is defined as the sum of the following asset (liability) categories: currency and deposits (F2), debt securities (F3), loans (F4), equity and investment fund shares (F5), insurance pension and standardized guarantee schemes (F6), financial derivatives and employee stock options (F7), and other accounts receivable (payable) (F8). The second set of indicators shows the share of each asset (liability) category in the total financial assets (liabilities) of each investor. They help to analyse the investment portfolio composition of the investor as well as financial risks borne by the investor. The third set of indicators shows the sub-sector composition of total financial assets (liabilities) by investor category, by showing the share of each sub-sector in the total financial assets (liabilities) of each investor category.

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.

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

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

This dataset presents annual population projections data up to 2061 by sex and five year age groups as well as the share of children, youth, the elderly, old-age and total dependency ratios. The data is available for all 38 member countries as well as for the EU27 and G20 countries, Singapore and the World total. Population projections are, in most countries, according to medium variant. (See country details for the variants retained for each demographic component of total fertility, life expectancy at birth and net annual migration).

The Financial Accounts show net acquisition of financial assets (or changes in assets) during the period, net incurrence of financial liabilities (or changes in liabilities) during the period, and net financial transactions (or changes in the net position: financial assets minus financial liabilities) during the period. This table shows the Financial Accounts on a non-consolidated basis, meaning that it shows all flows in the economy, both between units belonging to different (sub)sectors and between units belonging to the same (sub)sector, in contrast with consolidated accounts in which flows between units within the same (sub)sector would be removed. In this table, the presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. The default view of the table is for the economy as a whole, but you can use the ‘Institutional sector’ filter to select specific sectors such as Non-financial Corporations, Financial Corporations, General Government and Households, as well as the Rest of the world account. For each sector, the table presents breakdowns by financial instrument, for example currency and deposits, debt securities, loans, equity and investment fund shares, insurance and pensions. Users can also choose to compare a single financial instrument, such as listed shares, for several countries. Users should note that Australia does not produce non-consolidated accounts. These indicators were presented in the previous dissemination system in the QASA_TABLE620R dataset. Explore also the OECD Financial Accounts and Balance Sheets webpage: Financial Accounts and Balance Sheets webpage OECD statistics contact: [email protected]

The Financial Balance Sheets show financial assets, liabilities and net financial worth (assets minus liabilities) at the end of the period. This table is on a consolidated basis, which means that counterpart assets and liabilities of units within the same sector or subsector (or the economy as a whole) have been removed. In this table, the presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. The default view of the table is for the economy as a whole, but you can use the ‘Institutional sector’ filter to select specific sectors such as Non-financial Corporations, Financial Corporations, General Government and Households, as well as the Rest of the world account. For each sector, the table presents breakdowns by financial instrument, for example currency and deposits, debt securities, loans, equity and investment fund shares, insurance and pensions. Users can also choose to compare a single financial instrument, such as listed shares, for several countries. Users should note that some countries do not produce consolidated accounts for all sectors. These indicators were presented in the previous dissemination system in the QASA_TABLE710R dataset. Explore also the OECD Financial Accounts and Balance Sheets webpage: Financial Accounts and Balance Sheets webpage OECD statistics contact: [email protected]

The Financial Balance Sheets show financial assets, liabilities and net financial worth (assets minus liabilities) at the end of the period. This table is on a non-consolidated basis, meaning that it shows all assets and liabilities of units in a sector or subsector (or the economy as a whole), in contrast with consolidated balance sheets in which counterpart assets and liabilities of units within the same sector or subsector (or the economy as a whole) would be removed. In this table, the presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter. The default view of the table is for the economy as a whole, but you can use the ‘Institutional sector’ filter to select specific sectors such as Non-financial Corporations, Financial Corporations, General Government and Households, as well as the Rest of the world account. For each sector, the table presents breakdowns by financial instrument, for example currency and deposits, debt securities, loans, equity and investment fund shares, insurance and pensions. Users can also choose to compare a single financial instrument, such as listed shares, for several countries. Users should note that Australia does not produce non-consolidated accounts. These indicators were presented in the previous dissemination system in the QASA_TABLE720R dataset. Explore also the OECD Financial Accounts and Balance Sheets webpage: Financial Accounts and Balance Sheets webpage OECD statistics contact: [email protected]

Excess capacity is one of the main challenges facing the global steel sector. The OECD Steelmaking Capacity database contains data on crude steelmaking capacity by economy and provides researchers and policymakers with an important tool for analysing steel capacity developments.

In the OECD Entrepreneurship Financing Database venture capital is made up of the sum of early stage (including pre-seed, seed, start-up and other early stage) and later stage venture capital. As there are no harmonised definitions of venture capital stages across venture capital associations and other data providers, original data have been re-aggregated to fit the OECD classification of venture capital by stages. Korea, New Zealand, the Russian Federation and South Africa do not provide breakdowns of venture capital by stage that would allow meaningful international comparisons.

This dataset presents national-level data on water made available for use, by sector. 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)