إندونيسيا

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

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

commitment is a firm written obligation by a government or official agency, backed by the appropriation or availability of the necessary funds, to provide resources of a specified amount under specified financial terms and conditions and for specified purposes for the benefit of a recipient country or a multilateral agency. Members unable to comply with this definition should explain the definition that they use. -- Commitments are considered to be made at the date a loan or grant agreement is signed or the obligation is otherwise made known to the recipient (e.g. in the case of budgetary allocations to overseas territories, the final vote of the budget should be taken as the date of commitment). For certain special expenditures, e.g. emergency aid, the date of disbursement may be taken as the date of commitment. -- Bilateral commitments comprise new commitments and additions to earlier commitments, excluding any commitments cancelled during the same year. Cancellations and reductions in the year reported on of commitments made in earlier years are reported in the CRS, but not in the DAC questionnaire. -- In contrast to bilateral commitments, commitments of capital subscriptions, grants and loans to multilateral agencies should show the sum of amounts which are expected to be disbursed before the end of the next year and amounts disbursed in the year reported on but not previously reported as a commitment. For capital subscriptions in the form of notes payable at sight, enter the expected amount of deposits of such notes as the amount committed.

Destination of Official Development Assistance Disbursements. Geographical breakdown by donor, recipient and for some types of aid (e.g. grant, loan, technical co-operation) on a disbursement basis (i.e. actual expenditures). The data cover flows from bilateral and multilateral donors which focus on flows from DAC member countries and the EU Institutions.

Residential Property Prices Indices (RPPIs) – also named House price indices (HPIs), are index numbers that measure the prices of residential properties over time. RPPIs are key statistics not only for citizens and households across the world, but also for economic and monetary policy makers. They can help, for example, to monitor potential macroeconomic imbalances and the risk exposure of the household and financial sectors. This dataset covers the 34 OECD member countries and some non-member countries. In addition to the nominal RPPIs it contains information on real house prices, rental prices and the ratios of nominal prices to rents and to disposable household income per capita. This dataset contains quarterly statistics for each country. House prices differ widely across OECD countries, both with respect to recent changes and to valuation levels. The OECD has identified one main nominal index for each country that covers the prices for the sale of newly-built and existing dwellings. The datasets “Analytical house price indicators” and “Residential Property Price Indices (RPPIs) – Headline Indicators” refer to the same price indices for all countries apart from Brazil, Canada, China, 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. This research dataset provides extended time series coverage for many countries. The objective is to provide information on the long term trend of house prices and develop indicators which can be used to help track and analyse macroeconomic developments and risks. The extended data supplement the OECD RPPI data with historical data from a variety of sources, including other international organisations, central banks and national statistical offices. The methodological basis on the historical data and the types of geographical areas and dwellings they cover can differ from those used in the OECD RPPI data. The database contains a number of additional series. Real house prices are given by the ratio of seasonally adjusted nominal house prices to the seasonally adjusted consumers’ expenditure deflator in each country, from the OECD national accounts database. This provides information on how nominal house prices have changed over time relative to prices in the general economy. The rental prices come from the OECD Main Economic Indicators database and refer to Consumer Price Indices (CPIs) for Actual rentals for housing (COICOP 04.1). If this indicator is missing for a country, another indicator is chosen. The chosen indicator are usually those corresponding to the CPI aggregate for Housing including Actual rentals for housing (COICOP 04.1), imputed rentals for housing (COICOP 04.2) and Maintenance and repair of the dwelling (COICOP 04.3). The disposable income indicators come from the OECD national accounts database. Net household disposable income is used. The population data come from the OECD national accounts database. The price-to-rent ratio is given by the ratio of nominal house prices to rental prices. This is a measure of the profitability of owning a house. The price-to-income ratio is given by the ratio of nominal house prices to nominal household disposable income per capita. This is a measure of the affordability of purchasing a house. An indication that house prices may be overvalued is provided if either of these ratios is above their long-term averages. The standardised price-rent and price-income ratios show the current price-rent and price-income ratios relative to their respective long-term averages. The long-term average, which is used as a reference value, is calculated over the whole period available when the indicator begins after 1980 or 1980 if the indicator is available over a longer time period. The standardised ratio is indexed to a reference value equal to 100 over the full sample period. Values over 100 indicate that the present price-rent ratio, or price-income ratio, is above its long-run norms. This provides an indication of possible housing market pressures.

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

This dataset present the Balanced Trade in Services (BaTIS) dataset published by OECD. It is a complete, consistent and balanced matrix of international trade in services statistics (ITSS). It contains annual bilateral data covering 202 reporters and partners, broken down by the 12 main EBOPS2010 (BPM6) categories.

The Bertelsmann Stiftung’s Transformation Index (BTI) analyzes and evaluates the quality of democracy, a market economy and political management in 128 developing and transition countries. It measures successes and setbacks on the path toward a democracy based on the rule of law and a market economy flanked by sociopolitical safeguards. Within this framework, the BTI publishes two rankings, the Status Index and the Management Index. Countries are further categorized on the basis of these status index and management rankings/scores. For instance, countries are categorized in to 5 groups – viz; 5 or failed, 4 or very limited, 3 or limited, 2 or advanced, and 1 or highly advanced—based on their status index score of 1 to 10. A country with a high score, 8.5 and above, is categorized as highly advanced. A country with a low score, below 4, is categorized as failed. A country is categorized as ‘very limited’ if it has a status index score between 4 and 5.5. A score between 5.5 and 7 means the country is categorized as ‘limited’ and a country is categorized as ‘advanced’ for a score between 7.1 and 8.5. On the basis of the democratic status ranking, countries are further categorized as 5 or ‘hard - line autocracies,’ 4 or ‘moderate autocracies,’ 3 or ‘highly defective democracies,’ 2 or ‘defective democracies,’ and 1 or ‘democracies in consolidation.’ A country with a democratic status ranking below 4 is categorized as a hard line autocracy. A democratic status score between 4 and 5 means that the country is part of the ‘moderate autocracy’ group. A country is grouped as a ‘highly defective democracy’ for a score between 5 and 6. A country is recognized as a ‘defective democracy’ for a score between 6 and 8, and a score of 8 and above earns a country the status of a ‘democracy in consolidation.’ Countries are also categorized in to 5 groups based on their market economy status ranking. The countries are categorized as ‘rudimentary’ or group 5, ‘poorly functioning’ or group 4, ‘functional flaws’ or group 3, ‘functioning’ or group 2, and ‘developed’ or group 1. A country is recognized as a member of the ‘developed’ group with a market economy status ranking/score of 8 and above. A country is grouped as ‘functioning’ if it has a score between 7 and 8. A market economy status ranking between 5 and 7 means the country is categorized to group 3 or the ‘functional flaws’ group. A score between 3 and 5 means that the country is ‘poorly functioning’ and a score below 3 means the country enjoys a ‘rudimentary’ status. Based on the management index ranking, countries are categorized as 5 or failed, 4 or weak, 3 or moderate, 2 or good, and1 or very good. A country is categorized as ‘very good’ for a score of 7 and above. It is categorized as ‘good’ for a score between 5.6 and 7, and as ‘moderate’ for a score between 4.4 and 5.5. A score between 3 and 4.3 means a country is categorized as ‘weak,’ and a score below 3 means the categorization of a country as ‘failed.’ Countries are ranked between 1 and 10 on the basis of the level of difficulty they face. The level of difficulty is further categorized as 5 or negligible, 4 or minor, 3 or moderate, 2 or substantial, and 1 or massive. A score of 8.5 and above means the categorization of the country’s level of difficulty as ‘massive, and a score below 2.5 means the categorization of the level of difficulty faced by the country as ‘negligible.’ The level of difficulty score of 2.5 to 4.4 means a country faces a ‘minor’ level of difficulty and a score between 4.5 and 6.4 means the level of difficulty faced by a country is ‘moderate.’ A country with a score of 6.5 to 8.4 faces a ‘substantial’ level of difficulty.

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

Note: No further updates planned by source Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Jobs Publication: https://datacatalog.worldbank.org/dataset/jobs License: http://creativecommons.org/licenses/by/4.0/   The World Bank Jobs Statistics Over 150 indicators on labor-related topics, covering over 200 economies from 1990 to present.

The business tendency survey indicators cover a standard set of indicators for four economic sectors: manufacturing, construction, retail trade and other services. This includes an indicator of overall business conditions or business confidence in each sector. The consumer opinion survey indicators cover a restricted set of indicators on consumer confidence, expected economic situation and price expectations.   Business and consumer opinion (tendency) surveys provide qualitative information that has proved useful for monitoring the current economic situation. Typically they are based on a sample of enterprises or households and respondents are asked about their assessments of the current situation and expectations for the immediate future. For enterprise surveys this concerns topics such as production, orders, stocks etc. and in the case of consumer surveys their intentions concerning major purposes, economic situation now compared with the recent past and expectations for the immediate future. Many survey series provide advance warning of turning points in aggregate economic activity as measured by GDP or industrial production. Such series are known as leading indicators in cyclical analysis. These types of survey series are widely used as component series in composite leading indicators.   The main characteristic of these types of surveys is that instead of asking for exact figures, they usually ask for the direction of change e.g. a question on tendency by reference to a “normal” state, e.g. of production level. Possible answers are generally of the three point scale type e.g. up/same/down or above normal/normal/below normal for enterprise surveys and of the five point scale type e.g. increase sharply/increase slightly/remain the same/fall slightly/fall sharply for consumer surveys. In presenting the results as a time series, only the balance is shown. That is “same” or “normal” answers are ignored and the balance is obtained by taking the difference between percentages of respondents giving favourable and unfavourable answers.   Virtually all business tendency and consumer opinion survey data are presented as time series of balances in this dataset, either in raw or seasonally adjusted form. Very few series are presented as indices, and where these exist they have generally been converted from underlying balances by countries before submitting the data to the OECD.

OICA Car Production Statistics 1999-2021 contains world motor vehicle production statistics, obtained from national trade organisations, OICA members or correspondents. Passenger cars are motor vehicles with at least four wheels, used for the transport of passengers, and comprising no more than eight seats in addition to the driver's seat. Commercial vehicles include light commercial vehicles, heavy trucks, coaches and buses.

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

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

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

Statistical population: CLIs are calculated for 33 OECD countries (Iceland is not included), 6 non-member economies and 8 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.   Recommended uses and limitations: 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.

This dataset provides statistics on international trade in services by service category and partner country. Data are also broken down by type of service according to the Extended Balance of Payments Services classification (EBOPS 2002) 

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

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

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

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

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

This dataset contains indicators related to CPI and Inflation at provincial level.

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

The 'Consumer Price Indices (CPIs)' contains all data that was previously contained in three different datasets: 'Consumer Prices', 'National Consumer Price Indices (CPIs) by COICOP divisions' and 'Harmonised Indices of Consumer Prices (HICPs) by COICOP divisions'. The 'Consumer Price Indices (CPIs)' dataset contains predominantly monthly statistics, and associated statistical methodological information, for the 36 OECD member countries and for some non-member countries. The ‘Consumer Price Indices (CPIs)' dataset contains statistics on Consumer Price Indices including national CPIs, Harmonised Indices of Consumer Prices (HICPs) and their associated weights and contributions to national annual inflation. The data series presented have been chosen as the most relevant prices statistics for which comparable data across countries is available. 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. Data are available monthly for all the countries except for Australia and New Zealand (quarterly data).

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

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

Data cited at: Coordinated Portfolio Investment Survey (CPIS), The International Monetary Fund. The Coordinated Portfolio Investment Survey (CPIS) is a voluntary data collection exercise conducted under the auspices of the IMF. An economy provides data on its holdings of portfolio investment securities (data are separately requested for equity and investment fund shares, long-term debt instruments, and short-term debt instruments).   Worldwide portfolio holdings of equity and investment fund shares (31 USD trillion) at end-2017 surpasses holdings of debt securities (29.7 USD trillion). After the peak of the financial crisis in 2008, the annual growth rate of equity holdings has exceeded substantially that for debt securities holdings. That pattern is similar in all the economies with the largest cross border portfolio assets and liabilities. As per G20 emerging economies, while the holdings of equity and investment fund shares had already been consistently higher than those of debt securities, during the last five years the gap has widened even further.

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

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

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

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

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

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

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

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

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

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

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

Data cited at : https://www.bis.org/statistics/index.htm

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

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.Other commentsThe Task Force on Statistics of International Trade in Services maintains a matrix summarising the status of the trade in services data collection performed by International Organisations. The table displays links to the databases as well as update timetables, availability of metadata, availability of bilateral data, and other important characteristics.

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

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

The OECD Economic Outlook analyzes 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 major 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, labor markets, interest and exchange rates, balance of payments and government debt. For the non-OECD regions, foreign trade and current account series are available. 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, Labor Force Statistics and Main Economic Indicators. The cut-off date for information used in the compilation of the projections was June 1, 2023. The aggregation of world trade takes into account the projections made for the main non-OECD economies. Thus, besides OECD and the OECD euro area, the following regions are available: Dynamic Asian Economies (Chinese Taipei, Hong Kong, Malaysia, the Philippines, Singapore, Thailand, Vietnam); Oil Producers (Algeria, Angola, Azerbaijan Bahrain, Brunei, Chad, Rep. of Congo, Ecuador, Equatorial Guinea, Gabon, Iran, Iraq, Kazakhstan, Kuwait, Libya, Nigeria, Oman, Qatar, Saudi Arabia, Sudan, Timor-Leste , Trinidad and Tobago, Turkmenistan, United Arab Emirates, Yemen, Venezuela); with the remaining countries in a residual 'Rest of the World' group.

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

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

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

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

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

World: Electricity Prices

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Data cited at: Wendling, Z. A., Emerson, J. W., Esty, D. C., Levy, M. A., de Sherbinin, A., et al. (2018). 2018 Environmental Performance Index. New Haven, CT: Yale Center for Environmental Law & Policy. https://epi.yale.edu/   The Environmental Performance Index (EPI) is constructed through the calculation and aggregation of 20 indicators reflecting national-level environmental data. These indicators are combined into nine issue categories, each of which fit under one of two overarching objectives. The two objectives that provide the overarching structure of the EPI are Environmental Health and Ecosystem Vitality. Environmental Health measures the protection of human health from environmental harm. Ecosystem Vitality measures ecosystem protection and resource management. These two objectives are further divided into nine issue categories that span high-priority environmental policy issues, including air quality, forests, fisheries, and climate and energy, among others. The issue categories are extensive but not comprehensive. Underlying the nine issue categories are 20 indicators calculated from country-level data and statistics. After more than 15 years of work on environmental performance measurement and six iterations of the EPI, global data are still lacking on a number of key environmental issues. These include: freshwater quality, toxic chemical exposures, municipal solid waste management, nuclear safety, wetlands loss, agricultural soil quality and degradation, recycling rates, adaptation, vulnerability, and resiliency to climate change, desertification.

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

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

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

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

Historical Data of Export, Import and Prices on Resources and Energy of Australia

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

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

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

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

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

FDI data are based on statistics provided by 35 OECD member countries and by Lithuania. BMD4: OECD Benchmark Definition of Foreign Direct Investment - 4th Edition

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

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

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

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

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

The Resources and Energy Quarterly (REQ) contains the Office of the Chief Economist’s forecasts for the value, volume, and price of Australia’s major resources and energy commodity exports.

FDI statistics cover all entities in an FDI relationship. An FDI relationship is established when an investor in one country acquires 10% or more of the voting power in a business enterprise in another country. The investor is also called a direct investor or a parent and the business enterprise is called a direct investment enterprise or an affiliate. The 10 percent criteria is used to establish that the direct investor has a significant degree of influence over the operations of the direct investment enterprise.   The FDI population includes affiliates that are directly and indirectly owned by the parent. In direct ownership, the parent owns the 10% or more voting power itself. In indirect ownership, the parent controls an affiliate that in turn owns 10 percent or more of the voting power in another enterprise.   The FDI population also includes enterprises that are not in a direct investment relationship themselves but have a direct investor in common. Called fellow enterprises, they are included because, even though there is no direct investment relationship between the two, any transactions between them likely resulted from the influence that their common direct investor has on both of their operations.

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

Monthly summary on foreign trade statistics  

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

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

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

The Future of Business Survey is an original source of information on small and medium-sized enterprises (SMEs). Launched in February 2016, the survey is a partnership between Facebook, OECD, and the World Bank. It provides timely information on business owners’ assessment of the current state and future outlook of their business, job creation perspectives, main business challenges and participation in international trade. Several data breakdowns are available, in particular by size of the enterprise, age, sector, trading status and gender of owners or managers.

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. 

Data citation: Data retrieved from the Area Database of the Global Data Lab, https://globaldatalab.org/areadata/, version v4.2.Smits, J. GDL Area Database. Sub-national development indicators for research and policy making. GDL Working Paper 16-101 (2016).

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

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

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

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

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

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

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

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

The Global Consumption Database is a one-stop source of data on household consumption patterns in developing countries. It is designed to serve a wide range of users—from researchers seeking data for analytical studies to businesses seeking a better understanding of the markets into which they are expanding or those they are already serving.   The data are based on national household surveys, which collect information for a group of households representative of the entire country. For each of the countries covered, the resulting datasets have been used to calculate the share of the population at different levels of consumption.   Four levels of consumption are used to segment the market in each country: lowest, low, middle, and higher. They are based on global income distribution data, which rank the global population by income per capita. The lowest consumption segment corresponds to the bottom half of the global distribution, or the 50th percentile and below; the low consumption segment to the 51th–75th percentiles; the middle consumption segment to the 76th–90th percentiles; and the higher consumption segment to the 91st percentile and above.   The Global Consumption Database is the most comprehensive data source to date on consumer spending patterns in developing countries. It builds on the 2007 report The Next 4 Billion, published by IFC (a member of the World Bank Group) and the World Resources Institute.

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

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

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

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

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

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

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

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

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

Citation: Global Health Observatory (GHO) Data: https://www.who.int/gho/en/: World Health Organization; 2019. License: CC BY-NC-SA 3.0 IGO   The GHO data provides access to indicators on priority health topics including mortality and burden of diseases, the Millennium Development Goals (child nutrition, child health, maternal and reproductive health, immunization, HIV/AIDS, tuberculosis, malaria, neglected diseases, water and sanitation), non communicable diseases and risk factors, epidemic-prone diseases, health systems, environmental health, violence and injuries, equity among others.

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

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

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

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

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

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

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

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

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

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

This dataset provides a comprehensive view of the functions, or socioeconomic objectives, that government aims to achieve through various kinds of expenditure, comprising detailed classifications of general public service, defense, public order and safety, economic affairs, environment protection, housing and community services, health, recreation, culture and religion, education, and social protection services.

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

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

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

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.

This dataset presents trends in man-made emissions of major greenhouse gases and emissions by gas.   Data refer to total emissions of CO2 (emissions from energy use and industrial processes, e.g. cement production), CH4 (methane emissions from solid waste, livestock, mining of hard coal and lignite, rice paddies, agriculture and leaks from natural gas pipelines), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulphur hexafluoride (SF6) and nitrogen trifluoride (NF3). Data exclude indirect CO2.   Intensities (per unit of GDP and per capita) as well as index are calculated on gross direct emissions excluding emissions or removals from land-use, land-use change and forestry (LULUCF).   The GDP used to calculate intensities is expressed in USD at 2010 prices and PPPs.

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

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

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

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

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

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

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

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.

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

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

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.

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

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

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

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

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

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

Data cited at: Heritage Foundation   Economic freedom is the fundamental right of every human to control his or her own labor and property. In an economically free society, individuals are free to work, produce, consume, and invest in any way they please, with that freedom both protected by the state and unconstrained by the state. In economically free societies, governments allow labor, capital and goods to move freely, and refrain from coercion or constraint of liberty beyond the extent necessary to protect and maintain liberty itself. Economic Freedom Scores: Range and level of freedom 80–100:- Free 70–79.9:- Mostly Free 60–69.9:- Moderately Free 50–59.9:- Mostly Unfree 0–49.9:- Repressed

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

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

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

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

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

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

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

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

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

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: International Debt Statistics Publication: https://datacatalog.worldbank.org/dataset/international-debt-statistics License: http://creativecommons.org/licenses/by/4.0/   Focuses on financial flows, trends in external debt, and other major financial indicators for low- and middle-income countries. Includes over 200 time series indicators from 1970 to 2016, for most reporting countries, and pipeline data for scheduled debt service payments on existing commitments to 2024. Note: Total reserves in months of imports=(Total reserves/Total Imports)*12

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

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

Unit of measure used: Thousands   OECD countries seldom have tools specifically designed to measure the inflows and outflows of the foreign population, and national estimates are generally based either on population registers or residence permit data. This note is aimed at describing more systematically what is measured by each of the sources used.   Flows derived from population registers   Population registers can usually produce inflow and outflow data for both nationals and foreigners. To register, foreigners may have to indicate possession of an appropriate residence and/or work permit valid for at least as long as the minimum registration period. Emigrants are usually identified by a stated intention to leave the country, although the period of (intended) absence is not always specified.   When population registers are used, departures tend to be less well recorded than arrivals. Indeed, the emigrant who plans to return to the host country in the future may be reluctant to inform about his departure to avoid losing rights related to the presence on the register. Registration criteria vary considerably across countries (as the minimum duration of stay for individuals to be defined as immigrants ranges from three months to one year), which poses major problems of international comparison. For example, in some countries, register data cover a portion of temporary migrants, in some cases including asylum seekers when they live in private households (as opposed to reception centres or hostels for immigrants) and international students.   Flows derived from residence and/or work permits   Statistics on permits are generally based on the number of permits issued during a given period and depend on the types of permits used. The so-called “settlement countries” (Australia, Canada, New Zealand and the United States) consider as immigrants persons who have been granted the right of permanent residence. Statistics on temporary immigrants are also published in this database for these countries since the legal duration of their residence is often similar to long-term migration (over a year). In the case of France, the permits covered are those valid for at least one year (excluding students). Data for Italy and Portugal include temporary migrants.   Another characteristic of permit data is that flows of nationals are not recorded. Some flows of foreigners may also not be recorded, either because the type of permit they hold is not tabulated in the statistics or because they are not required to have a permit (freedom of movement agreements). In addition, permit data do not necessarily reflect physical flows or actual lengths of stay since: i) permits may be issued overseas but individuals may decide not to use them, or delay their arrival; ii) permits may be issued to persons who have in fact been resident in the country for some time, the permit indicating a change of status, or a renewal of the same permit.   Permit data may be influenced by the processing capacity of government agencies. In some instances a large backlog of applications may build up and therefore the true demand for permits may only emerge once backlogs are cleared.   Flows estimated from specific surveys   Ireland provides estimates based on the results of Quarterly National Household Surveys and other sources such as permit data and asylum applications. These estimates are revised periodically on the basis of census data. Data for the United Kingdom are based on a survey of passengers entering or exiting the country by plane, train or boat (International Passenger Survey). One of the aims of this survey is to estimate the number and characteristics of migrants. The survey is based on a random sample of approximately one out of every 500 passengers. The figures were revised significantly following the latest census in each of these two countries, which seems to indicate that these estimates do not constitute an “ideal” source either. Australia and New Zealand also conduct passenger surveys which enable them to establish the length of stay on the basis of migrants’ stated intentions when they enter or exit the country.

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

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

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

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

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

The Key Economic Indicators (KEI) database contains monthly and quarterly statistics (and associated statistical methodological information) for all OECD member countries and for a selection of non-member countries on a wide variety of economic indicators, namely: quarterly national accounts, industrial production, composite leading indicators, business tendency and consumer opinion surveys, retail trade, consumer and producer prices, hourly earnings, employment/unemployment, interest rates, monetary aggregates, exchange rates, international trade and balance of payments.

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

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

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

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

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

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

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

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

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

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

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

Data cited at : https://www.bis.org/statistics/index.htm

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Australia's international merchandise trade statistics record goods which add to or subtract from the stock of material resources of Australia by entering (imports) or leaving (exports) its territory. Goods simply transported through Australia (goods in transit), or temporarily admitted or withdrawn, do not add to or subtract from Australia's stock of material resources and are not included in Australia's international merchandise trade statistics.

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

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

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

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

The USGS Mineral Resources Program (MRP) provides scientific information for objective resource assessments and unbiased research results on mineral potential, production, consumption, and environmental effects. The MRP is the sole Federal source for this information. Values of 2019 are estimated.

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

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

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

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

The Financial Statistics dataset contains predominantly monthly statistics, and associated statistical methodological information, for the 36 OECD member countries and some selected other countries. The dataset itself contains financial statistics on 4 separate subjects: Monetary Aggregates, Interest Rates, Exchange Rates, and Share Prices. The data series presented within these subjects have been chosen as the most relevant financial statistics for which comparable data across countries is available. 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. All data are available monthly, and are presented as either an index (where the year 2015 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.

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 gross capital formation, gross fixed capital formation, changes in inventories and acquisition less disposals of valuables broken down by detailed industries according to the classification ISIC rev.4. 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. 2005). 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.

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.

It presents the balance sheets for non financial assets by institutional sectors, for both produced assets (fixed assets, inventories, valuables) and non-produced assets (tangible and intangible).  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 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.

This dataset presents information using an "indicator" approach, focusing on cross-country comparisons. The aim is to make the accounts more accessible and informative, whilst taking the opportunity to present the conceptual underpinning  and comparability issues of each of the indicators presented. The range of indicators is set deliberately wide to reflect the richness of the national accounts dataset and to encourage users of economic statistics to refocus some of the spotlight that is often placed on GDP to other important economic indicators, which may better respond to their needs. Indeed many users themselves have been instrumental in this regard. The report of the Commission on the Measurement of Economic Performance and Social Progress (Stiglitz-Sen-Fitoussi Commission) is but one notable example. That is not to undermine the importance of GDP, which arguably remains the most important measure of total economic activity, but other measures may better reflect other aspects of the economy. For example, net national income may be a more appropriate measure of income available to citizens in countries with large outflows of property income, and household adjusted disposable income per capita may be a better indicator of the material well-being of citizens. But certainly from a data perspective more can and remains to be done. The Stiglitz-Sen-Fitoussi Commission for example highlights the pressing need for the provision, by official statistics institutes, of more detailed information that better describes the distributional aspects of activity, especially income, and the need to build on the national accounts framework to address issues such as non-market services produced by households or leisure. It is hoped that by producing a publication such as this and thereby raising awareness, the momentum from this and other initiatives will be accelerated. The publication itself will pick up new indicators in the future as they become available at the OECD.

The National Accounts Main Aggregates Database presents a series of analytical national accounts tables from 1970 onwards for more than 200 countries and areas of the world. It is the product of a global cooperation effort between the Economic Statistics Branch of the United Nations Statistics Division, international statistical agencies and the national statistical services of these countries and is developed in accordance with the recommendation of the Statistical Commission at its first session in 1947 that the Statistics Division should publish regularly the most recent available data on national accounts for as many countries and areas as possible. The database is updated in December of each year with newly available national accounts data for all countries and areas.

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

It presents the whole set of non financial accounts, from the production account to the acquisitions of non-financial assets accounts. For general government sector, property income, other current transfers and capital transfers are consolidated..

It presents the whole set of non financial accounts, from the production account to the acquisitions of non-financial assets accounts. For general government sector, property income, other current transfers and capital transfers are consolidated.. It has been prepared from statistics reported to the OECD by Member countries in their answers to the new version of the annual national accounts questionnaire. This questionnaire is designed to collect internationally comparable data according to the 1993 SNA.

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.

It presents the different transactions and balances to get from the GDP to the net lending/net borrowing. Therefore, it includes, in particular, national disposable income (gross and net), consumption of fixed capital as well as net saving.

It presents the final consumption expenditure of households broken down by the COICOP (Classification of Individual Consumption According to Purpose) classification and by durability.  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. 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.

It provides a faithful image, to the greatest extent possible, of the aggregates and balances of the general government sector in the SNA 1993 conceptual framework. In addition, it brings to light two relevant aggregates that do not belong to this conceptual frame work: the Total Revenue and the Total Expenditure of the general government sector. Unit of measure used - National currency; current prices. Expressed in millions.

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

It provides a breakdown of government expenditure according to their function. To meet this end, economic flows of expenditure must be aggregated according to the Classification of the Functions of Government (COFOG).

It presents the three approaches of the GDP: expenditure based, output based and income based. 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.

Annual National Accounts>Detailed Tables and Simplified Accounts>7A. Labour input by activity, ISIC rev4   Unit of measure used: In persons, full-time equivalents, jobs and hours.   Statistical population: It presents employment, broken down by detailed industries according to the classification ISIC rev.4. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire.

It presents population data and employment by main activity. It includes national concept data for economically active population, unemployed persons, total employment, employees and self-employed, as well as domestic concept data for total employment, employees and self-employed. The domestic concept data are available broken down by main activity. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire.

It presents simplified non-financial accounts, from the gross value added to the net lending/net borrowing. In this table, the total economy is broken down in three main institutional sectors: corporations, general government, households and non-profit institutions serving households. 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. Expressed in millions. For the Euro area countries, the data in national currency for all years are calculated using the fixed conversion rates against the euro.

Annual National Accounts>Supply and Use Tables>30. Supply at basic prices and its transformation into purchasers' prices   Unit of measure used: In national currency, in current prices and previous year prices. 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: It presents the Supply table at basic prices and its transformation into purchaser's prices. It provides information by industry (at the 2 digit ISIC Rev 4 level, containing 89 industries) with corresponding breakdowns by product (using the comparable CPA product breakdown). It has been prepared from statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.

Annual National Accounts>Supply and Use Tables>SUT Indicators>SUT Indicators   Statistical population: These indicators are calculated by the OECD from the SUT statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.   Key statistical concept: The supply table describes the supply of goods and services, which are either produced in the domestic industry or imported. The use table shows where and how goods and services are used in the economy. Therefore in addition to their essential role to better estimations of National Accounts, Supply and Use tables are also a very powerful tool to understand the impact of policy decisions and globalisation, as they provide a detailed analysis of the process of production and the use of goods and services. For example, the Supply and Use Tables could be used to measure the the percentage of imports used in the production process or the share of trade and transport margins in the households’ final consumption expenditure.

Annual National Accounts>Supply and Use Tables>31. Supply, Output and its components by industries   Unit of measure used: In national currency, in current prices and previous year prices. 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: It presents the breakdown of output at basic prices between market output, output for own final use and non-market output, by activty at the 2 digit ISIC Rev 4 level. It has been prepared from statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.

It provides a faithful image, to the greatest extent possible, of the aggregates and balances of the general government sector Data are also available, for most countries, for the sub-sectors of general government.

Annual National Accounts>Supply and Use Tables>40. Use at purchasers' prices   Unit of measure used: In national currency, in current prices and previous year prices. 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: It presents the Use table at purchaser's prices. It provides information by industry (at the 2 digit ISIC Rev 4 level, containing 89 industries) with corresponding breakdowns by product (using the comparable CPA product breakdown). It has been prepared from statistics reported to the OECD by countries in their answers to Supply and Use questionnaire.

Annual National Accounts

Statistical population: Its presents output, intermediate consumption and the gross value added and its components, in particular compensation of employees and gross operating surplus and mixed income, broken down by detailed industries according to the classification ISIC rev.4. It has been prepared from statistics reported to the OECD by Member countries in their answers to annual national accounts questionnaire. 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.   Note: 6A. Value added and its components by activity, ISIC rev4

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

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

Data cited at: Global Fund

Data cited at: Portulans Institute (PI)-http://portulansinstitute.org/   The Network Readiness Index 2023 ranks a total of 134 economies that collectively account for 95 percent of global gross domestic product (GDP). In the latest rankings, the United States and Singapore have retained their top positions as Rank 1 and 2, respectively, from the previous year. A notable advancement is Finland, which has surged by 4 places to secure 3rd place from its 7th position last year. Following closely are the Netherlands and Sweden, now ranking 4th and 5th, respectively. Completing the top 10 are Switzerland (6th, down from 5th in NRI 2022), Republic of Korea (7th, up from 9th), Denmark (8th, down from 6th), Germany (9th, down from 8th), and the United Kingdom (10th, up from 12th). China has ascended to the 20th position, marking the only upper-middle-income country in the top 20. Conversely, Norway has experienced a significant decline, now standing at 16th place, down from 10th in 2022. The top 10 performers in NRI 2023 underscore that advanced economies in Europe, the Americas, Asia, and the Pacific are leading the way in terms of network readiness. Specifically, among the top 25 countries, 16 are from Europe (primarily Northern and Western Europe), five hail from Eastern and Southeastern Asia (including Singapore, the Republic of Korea, China, Hong Kong, and Japan), two come from Oceania (Australia and New Zealand), and two are from North America (Canada and the United States). Of the economies covered in this year's index, 49 are high-income economies, 32 are upper-middle-income countries, 36 are lower-middle-income countries, and 14 are low-income countries. In terms of regional distribution, there are 33 African countries, 12 Arab States, 21 economies from Asia and the Pacific, 7 from the Commonwealth of Independent States (CIS), 41 European countries, and 20 countries from the Americas.

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.

This entry gives the total number of airports or airfields recognizable from the air. The runway(s) may be paved (concrete or asphalt surfaces) or unpaved (grass, earth, sand, or gravel surfaces) and may include closed or abandoned installations. Airports or airfields that are no longer recognizable (overgrown, no facilities, etc.) are not included. Note that not all airports have accommodations for refueling, maintenance, or air traffic control.

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

A strike is a temporary work stoppage carried out by one or more groups of workers with a view to enforcing or resisting demands or expressing grievances, or supporting other workers in their demands or grievances. A lockout is a total or partial temporary closure of one or more places of employment, or the hindering of the normal work activities of employees, by one or more employers with a view to enforcing or resisting demands or expressing grievances, or supporting other employers in their demands or grievances. Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Industrial Relations data (IRdata) database description.

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

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

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

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.

The IEA Oil Market Report (OMR) is one of the world's most authoritative and timely sources of data, forecasts and analysis on the global oil market – including detailed statistics and commentary on oil supply, demand, inventories, prices and refining activity, as well as oil trade for IEA and selected non-IEA countries. IEA (2023),  Oil Market Report - December 2023 , IEA, Paris https://www.iea.org/reports/oil-market-report-december-2023

Other official flows are official sector transactions which do not meet the ODA criteria, e.g.:  i.) Grants to developing countries for representational or essentially commercial purposes;  ii.) Official bilateral transactions intended to promote development but having a grant element of less than 25 per cent;  iii.) Official bilateral transactions, whatever their grant element, that are primarily export-facilitating in purpose. This category includes by definition export credits extended directly to an aid recipient by an official agency or institution ("official direct export credits");  iv.) The net acquisition by governments and central monetary institutions of securities issued by multilateral development banks at market terms;  v.) Subsidies (grants) to the private sector to soften its credits to developing countries [see Annex 3, paragraph A3.5.iv)b)];  vi.) Funds in support of private investment.

University of Oxford baseline measure of variation in governments’ responses is the COVID-19 Government Response Stringency Index. This composite measure is a simple additive score of seven indicators measured on an ordinal scale, rescaled to vary from 0 to 100. Please note that this measure is for comparative purposes only, and should not necessarily be interpreted as rating of the appropriateness or effectiveness of a country's response.   Data cited at: Hale, Thomas and Samuel Webster (2020). Oxford COVID-19 Government Response Tracker. Data use policy: Creative Commons Attribution CC BY standard.

Data refer to applications filed directly under the European Patent Convention or to applications filed under the Patent Co-operation Treaty and designated to the EPO (Euro-PCT). Patent applications are counted according to the year in which they were filed at the EPO and are broken down according to the International Patent Classification (IPC). They are also broken down according to the inventor's place of residence, using fractional counting if multiple inventors or IPC classes are provided to avoid double counting.

The OECD Pensions at a Glance Database has been developed in order to serve a growing need for pensions indicators. It includes reliable and internationally comparable statistics on public and mandatory and voluntary pensions. It covers 34 OECD countries and aims to cover all G20 countries. Pensions at a Glance reviews and analyses the pension measures enacted or legislated in OECD countries. It provides an in-depth review of the first layer of protection of the elderly, first-tier pensions across countries and provideds a comprehensive selection of pension policy indicators for all OECD and G20 countries.

Value added at factor cost in the ICT sector (source: SBS, variable V12150) Since 2008, definition of the ICT sector is based on NACE Rev. 2 classification as follows: ICT Total (261 + 262 + 263 + 264 + 268 + 951 + 465 + 582 + 61 + 62 + 631) ICT Manufacturing (261 + 262 + 263 + 264 + 268) ICT Services (951 + 465 + 582 + 61 + 62 + 631) Until 2007, definition of the ICT sector is based on NACE Rev. 1.1 classification as follows: ICT Total (30 + 313 + 32 + 332 + 333 + 5184 + 5186 + 642 + 72) ICT Manufacturing (30 + 313 + 32 + 332 + 333) ICT Services (5184 + 5186 + 642 + 72) Total value added at factor cost (source: National Accounts, all branches) Value added at factor cost is defined as Gross value added (at basic prices) minus Other taxes less other subsidies on production. Due to change of the ICT sector definition as a consequence of change of the underlying classification, data for 2008 are not comparable with data published for previous years.

Imputed observations are not based on national data, are subject to high uncertainty and should not be used for country comparisons or rankings. Persons outside the labour force comprise all persons of working age who, during the specified reference period, were not in the labour force (that is, were not employed or unemployed). The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILOSTAT pages on concepts and definitions and ILO modelled estimates and projections.

Eurostat Dataset Id:cens_01rews The tables presented in the topic of educational level cover the total population for 31 countries (for more information on received tables and geographic coverage, see "2001 Census Round - Tables Received" in the Annex at the bottom of the page). The level of completeness of the tables depends largely on the availability of data at the respective national statistical institutes. There are four ways of collecting census data, namely: - the traditional method of using census questionnaires (exhaustive census); - the method of using registers and/or other administrative sources; - a combination of registers and/or other administrative sources and - surveys (complete enumerations or sample surveys). Other methods (other mixed census or micro-census) can be used as well. Details for the method employed by each country are provided in "2001 Census Method"in the Annex at the bottom of the page. In the same table you can find the dates on which the census was carried out in each country.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Population Estimates And Projections Publication: https://datacatalog.worldbank.org/dataset/population-estimates-and-projections License: http://creativecommons.org/licenses/by/4.0/   This database presents population and other demographic estimates and projections from 1960 to 2050. They are disaggregated by age-group and sex and covers more than 200 economies.

The FAOSTAT Population module contains time series data on population, by sex and urban/rural. The series consist of both estimates and projections for different periods as available from the original sources, namely: 1. Population data refers to the World Population Prospects: The 2015 Revision from the UN Population Division. 2. Urban/rural population data refers to the World Urbanization Prospects: The 2014 Revision from the UN Population Division. Long term series estimates and projections from 1961 to 2050. http://www.un.org/en/development/desa/population/

This is part of a supporting dataset for Lester R. Brown, Full Planet, Empty Plates: The New Geopolitics of Food Scarcity (New York: W.W. Norton & Company, 2012).

The World Bank updated the global poverty lines in September 2022. The Poverty data are now expressed in 2017 Purchasing Power Parity (PPP) prices, versus 2011 PPP in previous editions. The new global poverty lines of $2.15, $3.65, and $6.85 reflect the typical national poverty lines of low-income, lower-middle-income, and upper-middle-income countries in 2017 prices.

The Principal Global Indicators (PGI) dataset provides internationally comparable data for the Group of 20 economies (G-20) and economies with systemically important financial sectors that are not members of the G-20. The PGI facilitates the monitoring of economic and financial developments for these jurisdictions. Launched in 2009, the PGI website is hosted by the IMF and is a joint undertaking of the Inter-Agency Group of Economic and Financial Statistics (IAG).

Private transactions are those undertaken by firms and individuals resident in the reporting country.

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

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

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

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

The industrial production index shows the output and activity of the industry sector. It measures changes in the volume of output on a monthly basis. Data are compiled according to the Statistical classification of economic activities in the European Community, (NACE Rev. 2, Eurostat). Industrial production is compiled as a "fixed base year Laspeyres type volume-index". The current base year is 2015 (Index 2015 = 100). The index is presented in calendar and seasonally adjusted form. Growth rates with respect to the previous month (M/M-1) are calculated from calendar and seasonally adjusted figures while growth rates with respect to the same month of the previous year (M/M-12) are calculated from calendar adjusted figures.

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

Public Debt around the World

Data cited at:The Global Economy Under licence of Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported    

The main objective of the research is to address the theoretical and empirical problems of how political institutions of high quality can be created and maintained. The second objective is to study the effects of Quality of Government on a number of policy areas, such as health, environment, social policy, and poverty. Data citation: Teorell, Jan, Aksel Sundström, Sören Holmberg, Bo Rothstein, Natalia Alvarado Pachon, Cem Mert Dalli, Rafael Lopez Valverde & Paula Nilsson. 2024. The Quality of Government Standard Dataset, version Jan24. University of Gothenburg: The Quality of Government Institute, https://www.gu.se/en/quality-government doi:10.18157/qogstdjan24

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic:Quarterly External Debt Statistics GDDS Publication: https://datacatalog.worldbank.org/dataset/quarterly-external-debt-statistics-gdds License: http://creativecommons.org/licenses/by/4.0/   The World Bank launched the new Quarterly External Debt Statistics (QEDS) GDDS database. This database is consistent with the classifications and definitions of the 2013 External Debt Statistics: Guide for Compilers and Users (2013 EDS Guide) and Sixth Edition of Balance of Payments and International Investment Position Manual (BPM6). The QEDS GDDS database provides external debt data, starting from 2002Q4, for an extension of countries that participate in the IMF's General Data Dissemination System (GDDS).

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic:Quarterly External Debt Statistics SDDS Publication: https://datacatalog.worldbank.org/dataset/quarterly-external-debt-statistics-sdds License: http://creativecommons.org/licenses/by/4.0/   In October 2014, the World Bank launched the new Quarterly External Debt Statistics (QEDS) SDDS database. This database is consistent with the classifications and definitions of the 2013 External Debt Statistics: Guide for Compilers and Users (2013 EDS Guide) and Sixth Edition of Balance of Payments and International Investment Position Manual (BPM6). The QEDS SDDS database provides detailed external debt data starting from 1998Q1. Data are published individually by countries that subscribe to the IMF’s Special Data Dissemination Standard (SDDS), as well as, GDDS participating countries that are in a position to produce the external debt data prescribed by the SDDS.

The OECD's quarterly national accounts (QNA) dataset presents data collected from all the OECD member countries and some other major economies on the basis of a standardised questionnaire. It contains a wide selection of generally seasonally adjusted quarterly series most widely used for economic analysis from 1960 or whenever available:

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic:Quarterly Public Sector Debt Publication: https://datacatalog.worldbank.org/dataset/quarterly-public-sector-debt License: http://creativecommons.org/licenses/by/4.0/   Quarterly Public Sector Debt (QPSD) database, jointly developed by the World Bank and the International Monetary Fund, brings together detailed public sector debt data of selected countries. The QPSD database includes country and cross-country tables, and specific public debt components. The data represent the following sectors on an as-available basis: General government; otherwise Central government; otherwise Budgetary central government; Non Financial public corporations and Financial public corporations and a table presenting the total public sector debt.

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

The Regional database contains annual data from 1995 to the most recent available year (generally 2022 for demographic and labor market data, 2021 for regional accounts, innovation and social statistics). 

The Regional database contains annual data from 1995 to the most recent available year (generally 2018 for demographic and labor market data, 2017 for regional accounts, innovation and social statistics). The data collection is undertaken by the Center for Entrepreneurship, SMEs, Regions and Cities (CFE). Statistics are collected through an annual questionnaire sent to the delegates of the Working Party on Territorial Indicators (WPTI), and via downloads from the web-sites of National Statistical Offices and Eurostat

World : Renewable Electricity Capacity and Generation Statistics

Research and experimental development (R&D) comprise creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new applications. R&D expenditures include all expenditures for R&D performed within the business enterprise sector (BERD) on the national territory during a given period, regardless of the source of funds. R&D expenditure in BERD are shown as a percentage of GDP (R&D intensity).

Note: The financial years 2015/16, 2016/17, 2017/18 and 2018/2019 have been considered as 2015, 2016, 2017 and 2018. respectively.

Data on agricultural land-use are valuable for conducting studies on a various perspectives concerning agricultural production, food security and for deriving cropping intensity among others uses. Indicators derived from the land-use categories can also elucidate the environmental sustainability of countries’ agricultural practices. FAOSTAT Land-use statistics contain a wide range of information on variables that are significant for: understanding the structure of a country’s agricultural sector; making economic plans and policies for food security; deriving environmental indicators, including those related to investment in agriculture and data on gross crop area and net crop area which are useful for policy formulation and monitoring. Land-use resources sub-domain covers: Country area (including area under inland water bodies), Land area (excluding area under inland water bodies), Agricultural area, Arable land and Permanent crops, Arable land, Permanent crops, Permanent meadows and pastures, Forest area, Other land and Area equipped for irrigation. Detailed information on sub-categories: Temporary crops, Temporary meadows and pastures, Fallow land (temporary: less than 5 years), Permanent meadows and pastures cultivated and naturally grown and Organic land. Data are available from 1961 to 2009 for more than 200 countries and areas. Forest area: Global Forest Resource Assessment 2010 (FRA 2010) is the main source of forest area data in FAOSTAT. Data were provided by countries for years 1990, 2000, 2005 and 2010. Data for intermediate years were estimated for FAO using linear interpolation and tabulation. Some of the most interesting data for economists is found in this domain. The national distribution of land, among arable land, pastures and other lands, as well as the importance of irrigation are just some of the interesting data sets.

The Pesticides Use database includes data on the use of major pesticide groups (Insecticides, Herbicides, Fungicides, Plant growth regulators and Rodenticides) and of relevant chemical families. Data report the quantities (in tonnes of active ingredients) of pesticides used in or sold to the agricultural sector for crops and seeds. Information on quantities applied to single crops is not available.

Eurostat Dataset Id:ei_bsrt_m_r2 Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published:as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)

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

Data cited at:  The World Justice Project (WJP) The World Justice Project (WJP) Rule of Law Index® is a quantitative assessment tool designed by the World Justice Project to offer a detailed and comprehensive picture of the extent to which countries adhere to the rule of law in practice. Factors of the WJP Rule of Law Index include: 1. Constraints on Government Powers 2. Absence of Corruption 3. Open Government 4. Fundamental Rights 5. Order and Security 6. Regulatory Enforcement 7. Civil Justice 8. Criminal Justice (Data is collected for a 9th factor, Informal Justice, but it is not included in aggregated scores and rankings. This is due to the complexities of these systems and the difficulties in measuring their fairness and effectiveness in a matter that is both systematic and comparable across countries.) Every year WJP collects data from representative samples of the general public and legal professionals to compute the index scores. The data, once collected, are carefully processed to arrive at country-level scores. The respondent level data is first edited to exclude partially-completed surveys, suspicious data, and outliers. Individual answers are then mapped on to the 44 sub-factors of the index. Answers are coded so that all values ​​fall between 0 (least rule of law) and 1 (most rule of law), and aggregated at country level using the simple, or unweighted, average of all respondents. Note: 2012-2013 values ​​given for year 2013 and 2017-2018 given for year 2018.

The SCImago Institutions Rankings (SIR) is a classification of academic and research-related institutions ranked by a composite indicator that combines three different sets of indicators based on research performance, innovation outputs and societal impact measured by their web visibility. It provides a friendly interface that allows the visualization of any customized ranking from the combination of these three sets of indicators. Additionally, it is possible to compare the trends for individual indicators of up to six institutions. For each large sector it is also possible to obtain distribution charts of the different indicators.  

The series is part of the ILO modelled estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. This indicator conveys the annual growth rates of labour productivity. Labour productivity represents the total volume of output (measured in terms of Gross Domestic Product, GDP) produced per unit of labour (measured in terms of the number of employed persons) during a given time reference period. The indicator allows data users to assess GDP-to-labour input levels and growth rates over time, thus providing general information about the efficiency and quality of human capital in the production process for a given economic and social context, including other complementary inputs and innovations used in production. For more information, refer to the Labour Market-related SDG Indicators (ILOSDG) database description.

Data may differ from nationally reported figures and the Global SDG Indicators Database due to differences in sources and/or reference years. This indicator presents data by sex on employees' average hourly earnings. The concept of earnings, as applied in wage statistics, relates to gross remuneration in cash and in kind paid to employees, as a rule at regular intervals, for time worked or work done together with remuneration for time not worked, such as annual vacation, other type of paid leave or holidays. Earnings exclude employers' contributions in respect of their employees paid to social security and pension schemes and also the benefits received by employees under these schemes. Earnings also exclude severance and termination pay. Data are also disaggregated by occupation. Statistics on average hourly earnings by sex are the basis for the calculation of the gender pay gap. Data disaggregated by occupation are provided according to the latest version of the International Standard Classification of Occupations (ISCO). Data may have been regrouped from the national classifications, which may not be strictly compatible with ISCO. For more information, refer to the Labour Market-related SDG Indicators (ILOSDG) database description.

Data may differ from nationally reported figures and the Global SDG Indicators Database due to differences in sources and/or reference years. This indicator conveys the share of employment in manufacturing. Employment in manufacturing is defined based on the International Standard Industrial Classification of All Economic Activities (ISIC). Employment refers to all persons of working age who, during a specified brief period, were in paid employment (whether at work or with a job but not at work) or in self-employment (whether at work or with an enterprise but not at work). This indicator is calculated based on data on employment by sex and economic activity. For more information, refer to the Labour Market-related SDG Indicators (ILOSDG) database description.

Eurostat Dataset Id:ei_bssi_m_r2 Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published: as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)

Eurostat Dataset Id:ei_bsse_m_r2 Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published:as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)

This Dataset contains new preliminary annual estimates on international trade in services, based on the most recent quarterly figures. The underlying sources and methodology are different to previously used by UNCTAD and those used in the table containing the longer series of annual trade-in-services statistics. Consequently, the two data sets should not be merged or used interchangeably. The preliminary figures and derived growth rates included in this new series should be given priority as they are more up-to-date. However, users are advised that when the final annual data are published in May, these should be treated as the definitive series. The data in the table entitled "Services (BPM6): Exports and imports by service-category and by trade-partner” are kept on the web for users who require information on detailed services' sub-items or longer time-series.

This table presents annual statistics on international trade in services of individual economies by trading partner and by 78 selected service categories. In addition, the table contains data for services trade of various groups of economies with "world" and for selected principal service categories. The data presented are the result of the common work of UNCTAD and the World Trade Organization (WTO), in cooperation with the International Trade Center (ITC) and the United Nations Statistics Division (UNSD).

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Services Trade Restrictions Database Publication: https://datacatalog.worldbank.org/dataset/services-trade-restrictions-database License: http://creativecommons.org/licenses/by/4.0/ The Services Trade Restrictions Database collects information on applied services trade policies across 103 countries, 18 services sectors (covering telecommunications, finance, transportation, retail and professional services) and key modes of service supply. It contains qualitative policy information as well as a preliminary quantification of applied measures' restrictiveness. Data Coverage 2012-2016

The Short-Term Labour Market Statistics dataset contains predominantly quarterly labour statistics, and associated statistical methodological information, for the 35 OECD member countries and selected other economies. The Short-Term Labour Market Statistics dataset covers countries that compile labour statistics from sample household surveys on a monthly or quarterly basis. It is widely accepted that household surveys are the best source for labour market key statistics. In such surveys, information is collected from people living in households through a representative sample and the surveys are based on standard methodology and procedures used internationally. The subjects available cover: working age population by age; active and inactive labour force by age; employment by economic activity, by working time and by status; and, unemployment (including monthly harmonised unemployment) by age and by duration. Data is expressed in levels (thousands of persons) or rates (e.g. employment rate) where applicable.   Data are based on Labour Force Surveys and national information in this dataset is directly collected from the following sources:   ABS - Australian Bureau of Statistics (Australia) Statistics Canada (Canada) INE - Instituto Nacional de Estadísticas (Chile) CBS – Central Bureau of Statistics (Israel) Statistics Bureau (Japan) Statistics Korea (Korea) INEGI - Instituto Nacional de Estadísticas y Geografía (Mexico) Statistics New Zealand (New Zealand) BLS - Bureau of Labor Statistics (the United States) Eurostat (Austria, Belgium, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Luxembourg, the Netherlands, Norway, Poland, Portugal, the Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey and the United Kingdom).

Note: Worldsteel's Steel Statistical Yearbook for 2019 and 2020 are concise version World steel's Steel Statistical Yearbook presents a cross-section of steel industry statistics. It contains comprehensive statistics from 2008 to 2022 on crude steel production by country and process, steel production by product, steel trade by product, apparent steel use and apparent steel use per capita by country, as well as production and trade of pig iron and directly reduced iron. It also includes data on production and trade of iron ore and trade of scrap.  of steel and true steel use. The statistics were collected from members of world steel and various international organizations.

This domain covers statistics and indicators on key aspects of the education systems across Europe. The data show entrants and enrolments in education levels, education personnel and the cost and type of resources dedicated to education. The standards on international statistics on education and training systems are set by the three international organisations jointly administering the annual UOE data collection: the United Nations Educational, Scientific, and Cultural Organisation Institute for Statistics (UNESCO-UIS),the Organisation for Economic Co-operation and Development (OECD) and,the Statistical Office of the European Union (EUROSTAT). The following topics are covered: Pupils and students – Enrolments and EntrantsLearning mobilityEducation personnelEducation financeGraduatesLanguage learningData and indicators disseminated include e.g. participation rates at different levels of education,  shares of pupils and students by programme orientation (general/academic and vocational/professional) and in combined school and work-based programmes, enrolments in public and private institutions, tertiary education graduates, degree mobile students enrolled and graduates, pupil-teacher ratios, foreign language learning, expenditure on education per student and relative GDP etc.

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

Data cited at: The Economist THE Big Mac index was invented by The Economist in 1986 as a lighthearted guide to whether currencies are at their “correct” level. It is based on the theory of purchasing-power parity (PPP), the notion that in the long run exchange rates should move towards the rate that would equalise the prices of an identical basket of goods and services (in this case, a burger) in any two countries. For example, the average price of a Big Mac in America in January 2018 was $5.28; in China it was only $3.17 at market exchange rates. So the "raw" Big Mac index says that the yuan was undervalued by 40% at that time.

Data cited at: The World Economic Forum https://www.weforum.org/ Topic: The Global Enabling Trade Report 2016 Publication URL: http://reports.weforum.org/global-enabling-trade-report-2016/ License: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode   The Enabling Trade Index (ETI) was developed within the context of the World Economic Forum’s Transportation Industry Partnership program, and was first published in The Global Enabling Trade Report 2008. The ETI measures the extent to which individual economies have developed institutions, policies, and services facilitating the free flow of goods over borders and to destination. The structure of the Index reflects the main enablers of trade, breaking them into four overall issue areas, captured in the subindexes: 1) The market access subindex measures the extent to which the policy framework of the country welcomes foreign goods into the economy and enables access to foreign markets for its exporters. 2) The border administration subindex assesses the extent to which the administration at the border facilitates the entry and exit of goods. 3) Infrastructure subindex takes into account whether the country has in place the transport and communications infrastructure necessary to facilitate the movement of goods within the country and across the border. 4) The business environment subindex looks at the quality of governance as well as at the overarching regulatory and security environment impacting the business of importers and exporters active in the country. Each of these four subindexes is composed in turn of a number of pillars of enabling trade, of which there are seven in all. These are: 1) Domestic market access; 2) Foreign market access; 3) Efficiency and transparency of border administration; 4) Availability and quality of transport infrastructure; 5) Availability and quality of transport services; 6) Availability and use of ICTs; 7) Operating environment. Each indicator and sub-indicator is given a score on a scale of 1 to 7 that corresponds to the worst and best possible outcome, respectively.

This dataset provides trade and tariff data for countries where the reporter is "World".

This collection provides users with data concerning R&D expenditure and R&D personnel broken down by following institutional sectors: business enterprise (BES), government (GOV), higher education (HES), private non-profit (PNP) with the total of sectors. All data are broken down by the above mentioned sectors of performance. The R&D expenditure is further broken down by source of funds, by type of costs, by economic activity (NACE Rev.2), by size class, by type of R&D, by fields of science, by socio-economic objectives and by regions (NUTS 2 level). Besides R&D expenditures in basic unit National currency (MIO_NAC) the following units are available: Euro (MIO_EUR), Euro per inhabitant (EUR_HAB) Purchasing Power Standard (MIO_PPS), Purchasing Power Standard at 2005 prices (MIO_PPS_KP05), Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_KP05_HAB), Percentage of GDP (PC_GDP) and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds). R&D personnel data is available in full-time equivalent (FTE), in head count (HC), as a % of employment and as a % of labour force. The data is further broken down by occupation, by qualification, by gender, by size class, by citizenship, by age groups, by fields of science, by economic activity (NACE Rev.2) and by regions (NUTS 2 level). The periodicity of R&D data is biennial except for the key R&D indicators (R&D expenditure, R&D personnel and Researchers by sectors of performance) which are transmitted annually by the EU Member States on the basis of a legal obligation from 2003 onwards. Some other breakdowns of the data may appear on annual basis based on voluntary data provisions. The data are collected through sample or census surveys, from administrative registers or through a combination of sources. R&D data are available for following countries and country groups: - All EU Member States, plus Candidate Countries, EFTA Countries, the Russian Federation, China, Japan, the United States and South Korea. - Country groups: EU-28, EU-15 and EA-18. R&D data are compiled in accordance to the guidelines laid down in the Proposed standard practice for surveys of research and experimental development - Frascati Manual (FM), OECD, 2002 .

Total Official Flows: the sum of Official Development Assistance (ODA) and Other Official Flows (OOF) represents the total (gross or net) disbursements by the official sector at large to the recipient country shown.