The OECD regional database is delivered through the viewer OECD eXplorer, an interactive mapping tool designed to let users explore, download and visualize data with maps, histograms, scatterplot and others. The database comprise a set of comparable statistics on about 2000 regions in the 33 OECD countries, on topics such as population, economic output, productivity, labor market, education and innovation themes to highlight differences within countries.

Detailed, internationally comparable data on the level and structure of tax revenues for more than 130 economies are available from 1990 onwards. The dataset combines data from the annual publications Revenue Statistics OECD, Revenue Statistics in Latin America and the Caribbean, Revenue Statistics in Africa and Revenue Statistics in Asia and the Pacific . It also includes data for countries that are not included in any regional publication. The classification approach is based on the well-established methodology of OECD Revenue Statistics, which is set out in the internationally recognised Interpretative Guide for tax revenues. The detailed country tables are also available in the OECD Data.explorer and provide information in national currency and by level of government.

The OECD Family database is an on-line database on family outcomes and family policies with indicators for all OECD countries. Coverage also includes EU Member States that are not OECD members. To date the database brings together 58 indicators on family structure, labor market participation, public policies and child outcomes. When possible, indicators are updated on a regular basis.

The OECD is known as a think tank of the WTO, emphasizing economic cooperation and development among governments through policy dialogue. The current number of OECD members, including original and subsequently approved new members, totals 38 countries. In order to secure support from OECD members for our country's participation in the OECD, it is necessary to grasp the characteristics of OECD members. This dataset provides serial numbers, classifications, and member country information based on the regional economic integration distribution of OECD member countries.

The OECD Employment database is part of the Organisation for Economic Co-operation and Development (OECD) and offers statistics that are comparable between countries and over time on various employment-related topics, such as unemployment, the labour force and working time. Data is available for all 35 OECD countries. Here we focus on the statistical data.

The QoG Institute is an independent research institute within the Department of Political Science at the University of Gothenburg. The main objective of our research is to address the theoretical and empirical problem of how political institutions of high quality can be created and maintained.

To achieve said goal, the QoG Institute makes comparative data on QoG and its correlates publicly available. To accomplish this, we have compiled several datasets that draw on a number of freely available data sources, including aggregated individual-level data.

The QoG OECD Datasets focus exclusively on OECD member countries. They have a high data coverage in terms of geography and time. In the QoG OECD TS dataset, data from 1946 to 2021 is included and the unit of analysis is country-year (e.g., Sweden-1946, Sweden-1947, etc.).

In the QoG OECD Cross-Section dataset, data from and around 2018 is included. Data from 2018 is prioritized, however, if no data are available for a country for 2018, data for 2019 is included. If no data for 2019 exists, data for 2017 is included, and so on up to a maximum of +/- 3 years. In the QoG OECD Time-Series dataset, data from 1946 to 2021 are included and the unit of analysis is country-year (e.g. Sweden-1946, Sweden-1947 and so on).

The QoG OECD Datasets focus exclusively on OECD member countries. They have a high data coverage in terms of geography and time. In the QoG OECD Time-Series dataset, data from 1946 to 2021 are included and the unit of analysis is country-year (e.g. Sweden-1946, Sweden-1947 and so on).

In the literature, the consensus about the importance of the independence of the central banks towards stable economic growth has been proven (e.g. Barro and Gordon 1983). The empirical papers studying this problem follow Cukierman, Webb, and Neyapti (1992) central bank independence index which does not include some important factors such as rule of law in the given country and defines the components of independence too generally. In this project, we aim to build an alternative index that will measure the central bank independence in more detail which will account for the rule of law and other relevant aspects that indirectly affect the true independence of the central bank. Obtaining the index, we will study whether the independence of the central bank has a positive effect on maintaining the given central bank's primary target. Furthermore, in this research, we aim to test whether our results differ from the previous findings in the empirical literature on the central bank independence and its effect on stable prices. Based on the obtained results, an optimal legislature of the central bank's independence shall be suggested. This panel dataset provides an assessment of the independence of central banks in 21 OECD countries (excluding the Eurozone), focusing on their monetary policy autonomy as determined by legislation in 2010, 2015, and 2020. Our data collection adopts a novel approach, building upon theinnovating methodology proposed by Cukierman et al. (1992), while incorporating revised components of the index that place greater emphasis on current standards of central bank independence. Additionally, we introduce new criteria to evaluate budgetary independence, an important aspect of central bank autonomy (Swinburne and Castello-Branco, 1991). The dataset serves as a valuable resource for empirical studies seeking to analyze the impact of monetary policy independence on economic performance. Furthermore, policymakers can draw insights from this index to enhance legislative frameworks and promote stronger performance in central bank independence.

The Better Life Index is an initiative created by the OECD to compare the well-being priorities of people around the world. It consists of 11 social indicators: “housing, income, jobs, community, education, environment, governance, health, life satisfaction, safety, work-life balance” that contribute to well-being in OECD countries. This initiative aims to involve citizens in the debate on measuring the well-being of societies, and to empower them to become more informed and engaged in the policy-making process that shapes all our lives.

The 11 indicators in turn are composed of 20 sub-indicators through averaging and normalization. The visualization tool is available here. By selecting a set of weights to the sub-indicators, a user can rank countries according to their weighted sum.

This dataset provides statistics on labour productivity, for large regions (TL2) and small regions (TL3).

Data source and definition

Labour productivity is measured as gross value added per employment at place of work by main economic activity. Regional gross value added and employment data are collected from Eurostat (reg_eco10) for EU countries and via delegates of the OECD Working Party on Territorial Indicators (WPTI), as well as from national statistical offices' websites. In order to allow comparability over time and across countries, labour productivity data in current prices are transformed into constant prices and PPP measures (link).

Definition of regions

Regions are subnational units below national boundaries. OECD countries have two regional levels: large regions (territorial level 2 or TL2) and small regions (territorial level 3 or TL3). The OECD regions are presented in the OECD Territorial grid (pdf) and in the OECD Territorial correspondence table (xlsx).

Use of economic data on small regions

When economic analyses are carried out at the TL3 level, it is advisable to aggregate data at the metropolitan region level when several TL3 regions are associated to the same metropolitan region. Metropolitan regions combine TL3 regions when 50% or more of the regional population live in a functionnal urban areas above 250 000 inhabitants. This approach corrects the distortions created by commuting, see the list of OECD metropolitan regions (xlsx) and the EU methodology (link).

Small regions (TL3) are categorized based on shared characteristics into regional typologies. See the economic indicators aggregated by territorial typology at country level on the access to City typology (link) and by urban-rural typology (link).

Cite this dataset

OECD Regions and Cities databases http://oe.cd/geostats

Further information

• The interactive web-tool OECD Regions and Cities Statistical Atlas
• The report OECD Regions and Cities at a Glance

Contact: RegionStat@oecd.org

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

FDI flows record the value of cross-border transactions related to direct investment during a given period of time, usually a quarter or a year, and consist of equity transactions, reinvestment of earnings, and intercompany debt transactions.

In this dataset, FDI flows are presented on two different basis:

• the asset/liability presentation: FDI statistics are organised according to whether the investment relates to an asset or a liability for the country compiling the statistics. The asset/liability presentation does not show the direction of influence as the directional presentation does.
• the directional presentation: FDI statistics are organised according to the direction of the investment for the reporting economy—either outward or inward.

For more details on the difference between the two presentations, see the OECD note Implementing latest international standards-Asset liability versus directional presentation

FDI flows aggregates in this dataset are measured in USD millions, in millions of national currency and as a share of GDP.

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); and
• the 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 flows aggregates under the previous BMD3 methodology can be accessed in the archived dataset FDI series of BOP and IIP aggregates

Communication Research in OECD Countries: H-Classics Dataset

This dataset and predefined summary tables are a complement to the report Agricultural Policy Monitoring and Evaluation 2021, which monitors agricultural policy developments in 37 OECD member countries, 5 non-OECD European Union member states and 12 emerging and developing economies: Argentina, Brazil, China, Costa Rica, India, Indonesia, Kazakhstan, the Philippines, the Russian Federation, South Africa, Ukraine and Viet Nam. Costa Rica became the 38th Member of the OECD in May 2021, but in this dataset, it is not included in the OECD total. The OECD uses a comprehensive system for measuring and classifying support to agriculture - the Producer and Consumer Support Estimates (PSEs and CSEs) and related indicators. They provide insight into the increasingly complex nature of agricultural policy and serve as a basis for OECD’s work on agricultural policies.

Abstract copyright UK Data Service and data collection copyright owner. The Organisation for Economic Co-operation and Development (OECD) Health Statistics 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. Within UKDS.Stat the data are presented in the following databases: Health status This datasets presents internationally comparable statistics on morbidity and mortality with variables such as life expectancy, causes of mortality, maternal and infant mortality, potential years of life lost, perceived health status, infant health, dental health, communicable diseases, cancer, injuries, absence from work due to illness. The annual data begins in 2000. Non-medical determinants of health This dataset examines the non-medical determinants of health by comparing food, alcohol, tobacco consumption and body weight amongst countries. The data are expressed in different measures such as calories, grammes, kilo, gender, population. The data begins in 1960. Healthcare resources This dataset includes comparative tables analyzing various health care resources such as total health and social employment, physicians by age, gender, categories, midwives, nurses, caring personnel, personal care workers, dentists, pharmacists, physiotherapists, hospital employment, graduates, remuneration of health professionals, hospitals, hospital beds, medical technology with their respective subsets. The statistics are expressed in different units of measure such as number of persons, salaried, self-employed, per population. The annual data begins in 1960. Healthcare utilisation This dataset includes statistics comparing different countries’ level of health care utilisation in terms of prevention, immunisation, screening, diagnostics exams, consultations, in-patient utilisation, average length of stay, diagnostic categories, acute care, in-patient care, discharge rates, transplants, dialyses, ICD-9-CM. The data is comparable with respect to units of measures such as days, percentages, population, number per capita, procedures, and available beds. Health Care Quality Indicators This dataset includes comparative tables analyzing various health care quality indicators such as cancer care, care for acute exacerbation of chronic conditions, care for chronic conditions and care for mental disorders. The annual data begins in 1995. Pharmaceutical market This dataset focuses on the pharmaceutical market comparing countries in terms of pharmaceutical consumption, drugs, pharmaceutical sales, pharmaceutical market, revenues, statistics. The annual data begins in 1960. Long-term care resources and utilisation This dataset provides statistics comparing long-term care resources and utilisation by country in terms of workers, beds in nursing and residential care facilities and care recipients. In this table data is expressed in different measures such as gender, age and population. The annual data begins in 1960. Health expenditure and financing This dataset compares countries in terms of their current and total expenditures on health by comparing how they allocate their budget with respect to different health care functions while looking at different financing agents and providers. The data covers the years starting from 1960 extending until 2010. The countries covered are Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, and United States. Social protection This dataset introduces the different health care coverage systems such as the government/social health insurance and private health insurance. The statistics are expressed in percentage of the population covered or number of persons. The annual data begins in 1960. Demographic references This dataset provides statistics regarding general demographic references in terms of population, age structure, gender, but also in term of labour force. The annual data begins in 1960. Economic references This dataset presents main economic indicators such as GDP and Purchasing power parities (PPP) and compares countries in terms of those macroeconomic references as well as currency rates, average annual wages. The annual data begins in 1960. These data were first provided by the UK Data Service in November 2014.

Abstract copyright UK Data Service and data collection copyright owner. Updated annually, this database contains an up-to-date array of comparative education statistics and indicators from Organisation for Economic Co-operation and Development (OECD) and non-OECD countries from 1985 onwards. It provides information on the human and financial resources invested in education, on access to, progression and completion of education, on how education and learning systems operate, and on the returns to educational investments. These data were first provided by the UK Data Service in January 2007. Main Topics: Within UKDS.Stat, the OECD Education Statistics are presented in the following datasets (some will include missing data): • Education and skills. • Education at a Glance. • Measuring Innovation in Education. • Teaching and Learning International Survey (TALIS). Data series include: • Educational Personnel • Expenditure by funding source and transaction type • Expenditure by nature and resource category • Foreign / international students enrolled • Graduates by age • Graduates by field of education • New entrants by sex and age • Students aligned to finance and personnel data • Students enrolled by age • Students enrolled by type of institution • Total population by sex and age See documentation for details

This data set is generated based on the data from EU KLEMS and IFR by using STATAThis data contains capital, labor, value added and robots data for 12 OECD countries from 2008 to 2020.Except for the first title, there are 923 rows and 67 columns and the total observation number is 923.

Dataset collected and processed as part of the ODDEA (Overcoming Digital Divide Between Europe and Southeast Asia) EU research project (Project ID: HORIZON MSCA-SE 101086381).The dataset consists of four OECD databases: Broadband and Telecommunication Database (23 indicators), The ICT Access and Usage by Households Database, The ICT Access and Usage by Individuals Database (106 indicators for households and individuals) , The ICT Usage by Business Database (59 indicators). The data are collected in Excel files (3) and csv file (1). They cover a period of 2012 to 2023 (if available) for OECD countries (40).

This table presents Gross Domestic Product (GDP) and its main components according to the expenditure approach. Data is presented as growth rates. In the expenditure approach, the 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).

When using the filters, please note that final consumption expenditure is shown separately for the Households/NPISH and General Government sectors, not for the whole economy. All other components of GDP are shown for the whole economy, not for the sector breakdowns.

The data is presented for OECD countries individually, as well as the OECD total, G20, G7, OECD Europe, United States - Mexico - Canada Agreement (USMCA), European Union and euro area.

These indicators were presented in the previous dissemination system in the QNA dataset.
See User Guide on Quarterly National Accounts (QNA) in OECD Data Explorer: QNA User guide
See QNA Calendar for information on advance release dates: QNA Calendar
See QNA Changes for information on changes in methodology: QNA Changes
See QNA TIPS for a better use of QNA data: QNA TIPS
Explore also the GDP and non-financial accounts webpage: GDP and non-financial accounts webpage
OECD statistics contact: STAT.Contact@oecd.org

Abstract copyright UK Data Service and data collection copyright owner. The International Energy Agency (IEA) datasets published by the Energy Statistics Division (ESD) contain annual and quarterly time series data from 1960 onwards on energy production, trade, stocks, transformation, consumption, prices and taxes as well as on greenhouse gas emissions for over the 30 Organisation for Economic Co-operation and Development (OECD) Member countries and over 100 non-OECD countries worldwide. In OECD Member countries the data are collected by official bodies (most often the national statistics office in each country) from firms, government agencies and industry organisations and are then reported to the IEA using questionnaires to ensure international comparability. In non-OECD countries the data are collected directly from government and industry contacts and from national publications. Energy Balances of OECD Countries: This database contains energy balances for 30 OECD countries and six regions. Detailed energy balances are provided in kJ/kg and toe/t. Definitions of products and flows, explanatory notes on the individual country data, indicators (including GDP, population, industrial production index and ratios calculated with the energy data) and net calorific values are also included. In general, data are available from 1960. This database is updated by the IEA in May each year. This database was first made available by the UK Data Service in June 2005 and is updated annually. The UK Data Service web site includes further information on its IEA Energy Balances of OECD Countries database, including a dataset user guide and details of latest database updates. Citation: The bibliographic citation for the database is: International Energy Agency ({YYYY}): Energy Balances of OECD Countries Database ({Ed. YYYY}). UK Data Service. DOI: {edition specific doi - e.g. http://dx.doi.org/10.5257/iea/ebo/2011}. Alternative DOIs: 10.1787/enestats-data-en (to access via OECD.Stat subscription). Main Topics: Topics covered include:energy balances in kJ/kg and toe/tcoal and coal productspeatcrude, NGL (natural gas liquids) and feedstockspetroleum productsnatural gasnuclearhydrogeothermalsolar/wind/othercombustible renewables and wasteelectricityheat See the <a href="http://ukdataservice.ac.uk//use-data/guides/dataset/iea.aspx" title="IEA dataset u

The OECD Income Distribution database (IDD) has been developed to benchmark and monitor countries' performance in the field of income inequality and poverty. It contains a number of standardised indicators based on the central concept of "equivalised household disposable income", i.e. the total income received by the households less the current taxes and transfers they pay, adjusted for household size with an equivalence scale. While household income is only one of the factors shaping people's economic well-being, it is also the one for which comparable data for all OECD countries are most common. Income distribution has a long-standing tradition among household-level statistics, with regular data collections going back to the 1980s (and sometimes earlier) in many OECD countries. Achieving comparability in this field is a challenge, as national practices differ widely in terms of concepts, measures, and statistical sources. In order to maximise international comparability as well as inter-temporal consistency of data, the IDD data collection and compilation process is based on a common set of statistical conventions (e.g. on income concepts and components). The information obtained by the OECD through a network of national data providers, via a standardized questionnaire, is based on national sources that are deemed to be most representative for each country. Small changes in estimates between years should be treated with caution as they may not be statistically significant. Fore more details, please refer to: https://www.oecd.org/els/soc/IDD-Metadata.pdf and https://www.oecd.org/social/income-distribution-database.htm

This dataset contains the demographic indicators included by OECD in the group of health indicators. The indicators values are for the total population, population structure by gender, the population of 65, 85 and over, fertility, live births, civilian employment population and their values cover periods of time between the years 1960 and 2016.