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AQUASTAT is FAO's global information system on water and agriculture, developed by the Land and Water Division. The main mandate of the program is to collect, analyze and disseminate information on water resources, water uses, and agricultural water management with an emphasis on countries in Africa, Asia, Latin America and the Caribbean. This allows interested users to find comprehensive and regularly updated information at global, regional, and national levels.

Accommodation statistics are a key part of the system of tourism statistics in the EU and have a long history of data collection. Annex I of the Regulation (EU) 692/2011 of the European Parliament and of the Council deals with accommodation statistics and includes 4 sections focusing on accommodation statistics of which sections 1 and 2 include the requirements concerning rented accommodation (capacity and occupancy respectively). Data are collected by the competent national authorities of the Member States and are compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Most of the time, data are collected via sample or census surveys. However, in a few cases data are compiled from a demand-side perspective (i.e. via visitor surveys or border surveys). Surveys on the occupancy of accommodation establishments are generally conducted on a monthly basis. The concepts and definitions used in the collection of data shall conform to the specifications described in the Methodological manual for tourism statistics. Accommodation statistics comprise the following information: Monthly data on tourism industries (NACE 55.1, 55.2 and 55.3) Monthly occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Net occupancy rate of bed-places and bedrooms in hotels and similar accommodation Annual data on tourism industries(NACE 55.1, 55.2 and 55.3) Occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Capacity of tourist accommodation establishments: number of establishments, bedrooms and bed places Regional data  Annual occupancy (arrivals and nights spent by residents and non-residents) of tourist accommodation establishments at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Annual data on number of establishments, bedrooms and bed places at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Data on number of establishments, bedrooms and bed places are available by activity at NUTS 3 level until 2011. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

20.1. Source data

NetIndex provides you with a few great ways to visualize our comprehensive global broadband and mobile performance data, our licensable data product, NetMetrics, gives your organization the ability to dive even deeper. Powered by millions of verified Ookla Speedtest results from around the globe, each record contains over 20 individual data points such as GPS or GeoIP location, ISP, throughput, latency, OS, browser, device and more. Gain unparalleled insight into cable, DSL, and fiber performance, as well as cellular 3G/4G and LTE connectivity around the world.

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.

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 2024. The dataset we compiled for the years 1980 to 2024 is made available as a resource for research.  

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).

The section 'LFS series - detailed quarterly survey results' reports detailed quarterly results going beyond the EU-LFS main aggregates, which have a separate data domain and some methodological differences. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

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.

Definition of an environmental tax (Regulation (EU) N° 691/2011) An environmental tax is a tax whose tax base is a physical unit (or a proxy of a physical unit) of something that has a proven, specific negative impact on the environment, and which is identified in ESA2010 as a tax. Eurostat collects data on environmental tax revenue (by tax category - energy, transport, pollution and resource taxes) broken down by economic activities (tax payers) using the NACE classification for production activities plus households and non-residents. Eurostat with the European Commission's Directorate General for Taxation and Customs Union also produces annually an analysis of each tax listed in the national accounts of European countries including: - assigning an economic function to each tax; - attributing an environmental code to the environmental taxes (E for Energy, T for Transport, P for Pollution, RS for Resource). These function and environmental codes are reported by countries in their national tax list (NTL) and are validated by Eurostat. Efforts are made to ensure full consistency of the data on environmental taxes by economic activities and revenue data based on the national tax lists even if some discrepancies remain for some countries.

A yield curve, also known as term structure of interest rates, represents the relationship between market remuneration (interest) rates and the remaining time to maturity of debt securities. The information content of a yield curve reflects the asset pricing process on financial markets. When buying and selling bonds, investors include their expectations of  future inflation, real interest rates and their assessment of risks. An investor calculates the price of a bond by discounting the expected future cash flows (coupon payments and/or redemption). ECB estimates zero-coupon yield curves for the euro area and also derives forward and par yield curves. A zero coupon bond is a bond that pays no cupon and is sold at a discount from its face value. The zero coupon curve represents the yield to maturity of hypothetical zero coupon bonds, since they are not directly observable in the market for a wide range of maturities. They must therfore be estimatedfrom existing zero coupon bonds and fixed coupon bond prices or yields.  The forward curve shows the short-term (instantaneous) interest rate for future periods implied in the yield curve. The par yield reflects hypothetical yields, namely the interest rates the bonds would have yielded had they been priced at par (i.e. at 100).

The dataset includes data on gross and net production indices for various food and agriculture aggregates expressed in both totals and per capita.

Value of gross production has been compiled by multiplying gross production in physical terms by output prices at farm gate. Thus, value of production measures production in monetary terms at the farm gate level. Since intermediate uses within the agricultural sector (seed and feed) have not been subtracted from production data, this value of production aggregate refers to the notion of "gross production". Value of gross production is provided in both current and constant terms and is expressed in US dollars and Standard Local Currency (SLC). The current value of production measures value in the prices relating to the period being measured. Thus, it represents the market value of food and agricultural products at the time they were produced. Knowing this figure is helpful in understanding exactly what was happening within a given economy at that point in time. Often, this information can help explain economic trends that emerged in later periods and why they took place. Value of production in constant terms is derived using the average prices of a selected year or years, known as the base period. Constant price series can be used to show how the quantity or volume of products has changed, and are often referred to as volume measures. The ratio of the current and constant price series gives a measure of price movements. US dollar figures for value of gross production are converted from local currencies using official exchange rates as prevailing in the respective years. The SLC of a country is the local currency prevailing in the latest year. Expressing data series in one uniform currency is useful because it avoids the influence of revaluation in local currency, if any, on value of production

cThe dataset contains data on Import and Export Value (expressed in 1000 USD) for a selected list of fertilizers, from 1961 on wards. Country and country aggregate data are available. The fertilizers covered are: Nitrogenous fertilizers; Phosphate fertilizers; Potash fertilizers; Fertilizers Manufactured, nes; Fertilizers, Organic; Natural Phosphates; Natural Potassic Salts; Natural Sodium Nitrate.

 

US: Exports and Imports of New Passenger Vehicles and Light Trucks 2019.

The Global Innovation Index 2024 captures the innovation ecosystem performance of 133 economies and tracks the most recent global innovation trends. The Global Innovation Tracker 2024 provides a comprehensive analysis of the current state of global innovation. Findings highlight progress as well as challenges across four key stages of the innovation cycle: science and innovation investment, technological progress, technology adoption, and the socioeconomic impact of innovation.

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.

The House Price Index (HPI) measures inflation in the residential property market. The HPI captures price changes of all kinds of residential property purchased by households (flats, detached houses, terraced houses, etc.), both new and existing. Only market prices are considered, self-build dwellings are therefore excluded. The land component of the residential property is included. These indices are the result of the work that National Statistical Institutes (NSIs) have been doing mostly within the framework of the Owner-Occupied Housing (OOH) pilot project coordinated by Eurostat. HPI is available for EU Member States, Iceland and Norway. In addition to the individual country series Eurostat produces indices for the euro area and for the EU. The national HPIs are produced by NSIs, while the European aggregates are computed by Eurostat, by aggregating the national indices. The data released quarterly on Eurostat's website include price indices themselves as well as their rates of change compared to the same quarter of the previous year. House Sales cover the total value of dwellings transactions at national level (both houses and flats) where the purchaser is a household. House Sales indicators complement the data on the HPI in order to offer a more comprehensive picture of the housing market. At this moment Eurostat is publishing the annual index for the value of housing transactions and the annual rate of change.

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

FAOSTAT database on Agriculture Machinery is no longer active. The latest online version of the database has as reference year 2009 (with data collected in year 2011). UN FAO Resource Statistics - Machinery. The Agricultural Resources domain covers: Investment, Land and irrigation, Labor, Machinery, Fertilizers, Pesticides, Population. The Resources domain considers factors of production for the agricultural sector. Broadly speaking, this section details how countries differ in endowments of the three classic inputs: labor, land and capital. Qualitative differences are important for each but are particularly difficult to summarize in a single indicator for land, the productivity of which depends heavily on water and soil conditions.

The Global Cybersecurity Index (GCI) is a trusted reference that measures the commitment of countries to cybersecurity at a global level – to raise awareness of the importance and different dimensions of the issue. As cybersecurity has a broad field of application, cutting across many industries and various sectors, each country’s level of development or engagement is assessed along five pillars – (i) Legal Measures, (ii) Technical Measures, (iii) Organizational Measures, (iv) Capacity Development, and (v) Cooperation – and then aggregated into an overall score.​ Based on a multi‐stakeholder approach and initiative, the GCI leverages the capacity and expertise of different organizations (see key partners below), with the objectives of improving the quality of the survey, fostering international cooperation, and promoting knowledge exchange on this topic. The ITU Global Cybersecurity Agenda (GCA)​ ​provides the general foundation and framework for the initiative.​

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

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. 

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.

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)

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

Accommodation statistics are a key part of the system of tourism statistics in the EU and have a long history of data collection. Annex I of the Regulation (EU) 692/2011 of the European Parliament and of the Council deals with accommodation statistics and includes 4 sections focusing on accommodation statistics of which sections 1 and 2 include the requirements concerning rented accommodation (capacity and occupancy respectively). Data are collected by the competent national authorities of the Member States and are compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Most of the time, data are collected via sample or census surveys. However, in a few cases data are compiled from a demand-side perspective (i.e. via visitor surveys or border surveys). Surveys on the occupancy of accommodation establishments are generally conducted on a monthly basis. The concepts and definitions used in the collection of data shall conform to the specifications described in the Methodological manual for tourism statistics. Accommodation statistics comprise the following information: Monthly data on tourism industries (NACE 55.1, 55.2 and 55.3) Monthly occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Net occupancy rate of bed-places and bedrooms in hotels and similar accommodation Annual data on tourism industries(NACE 55.1, 55.2 and 55.3) Occupancy of tourist accommodation establishments: arrivals and nights spent by residents and non-residents Capacity of tourist accommodation establishments: number of establishments, bedrooms and bed places Regional data  Annual occupancy (arrivals and nights spent by residents and non-residents) of tourist accommodation establishments at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Annual data on number of establishments, bedrooms and bed places at NUTS 2 level, by degree of urbanisation and by coastal/non-coastal area Data on number of establishments, bedrooms and bed places are available by activity at NUTS 3 level until 2011. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

The indicator measures the share of obese people based on their body mass index (BMI). BMI is defined as the weight in kilos divided by the square of the height in meters. People aged 18 years or over are considered obese with a BMI equal or greater than 30. Other categories are: underweight (BMI less than 18.5), normal weight (BMI between 18.5 and less than 25), and pre-obese (BMI between 25 and less than 30). The category overweight (BMI equal or greater than 25) combines the two categories pre-obese and obese.

Owners occupiers are those households that live in a dwelling (flat, house) that they own. Owner occupier's housing expenditures represent those expenditures incurred by owners occupiers when purchasing, maintaining and living in their own home. The Owner-Occupied Housing Price Index (OOHPI) measures the change over time in the transaction prices of dwellings that were purchased for own-use and the cost of all goods and services that households purchase in their role as owners occupiers of dwellings (see classification below). As the index is based on the net acquisitions approach, only purchased dwellings that are new to the household sector are covered, while transactions between households are excluded (see section 3.4 Statistical concepts and definitions) . These indices are the result of the work that National Statistical Institutes (NSIs) have been doing since 2001 within the framework of the Owner-Occupied Housing (OOH) pilot project coordinated by Eurostat. OOHPIs are available for 26 EU Member States, plus Iceland and Norway (published for 27 countries). The data that is released quarterly on Eurostat's website include price indices themselves as well as their rates of change compared to the previous quarter (Qt-1) and the same quarter of the previous year (Qt-4).

The data in this dataset comes from the Common Questionnaire for Transport Statistics, developed and surveyed in co-operation between the United Nations Economic Commission for Europe (UNECE), the International Transport Forum (ITF) and Eurostat. The Common Questionnaire is not supported by a legal act, but is based on a gentlemen's agreement with the participating countries; the completeness varies from country to country. Eurostat’s datasets based on the Common Questionnaire cover annual data for the EU Member States, EFTA states and Candidate countries to the EU. Data for other participating countries are available through the ITF and the UNECE. In total, comparable transport data collected through the Common Questionnaire is available for close to 60 countries worldwide. The Common Questionnaire collects aggregated annual data on: Railway transportRoad transportInland waterways transportOil pipelines transportGas pipelines transport For each mode of transport, the Common Questionnaire cover some or all of the following sub-modules (the number of questions/variables within each sub-module varies between the different modes of transport): Infrastructure (All modes)Transport equipment (RAIL, ROAD and INLAND WATERWAYS)Enterprises, economic performance and employment (All modes)Traffic (RAIL, ROAD and INLAND WATERWAYS)Transport measurement (All modes) Accidents (ROAD only) The Common Questionnaire is completed by the competent national authorities. The responsibility for completing specific modules (e.g. Transport by Rail) or part of modules (e.g. Road Infrastructure) may be delegated to other national authorities in charge of specific fields.

The data in this dataset comes from the Common Questionnaire for Transport Statistics, developed and surveyed in co-operation between the United Nations Economic Commission for Europe (UNECE), the International Transport Forum (ITF) and Eurostat. The Common Questionnaire is not supported by a legal act, but is based on a gentlemen's agreement with the participating countries; the completeness varies from country to country. Eurostat’s datasets based on the Common Questionnaire cover annual data for the EU Member States, EFTA states and Candidate countries to the EU. Data for other participating countries are available through the ITF and the UNECE. In total, comparable transport data collected through the Common Questionnaire is available for close to 60 countries worldwide. The Common Questionnaire collects aggregated annual data on: Railway transportRoad transportInland waterways transportOil pipelines transportGas pipelines transport For each mode of transport, the Common Questionnaire cover some or all of the following sub-modules (the number of questions/variables within each sub-module varies between the different modes of transport): Infrastructure (All modes)Transport equipment (RAIL, ROAD and INLAND WATERWAYS)Enterprises, economic performance and employment (All modes)Traffic (RAIL, ROAD and INLAND WATERWAYS)Transport measurement (All modes) Accidents (ROAD only) The Common Questionnaire is completed by the competent national authorities. The responsibility for completing specific modules (e.g. Transport by Rail) or part of modules (e.g. Road Infrastructure) may be delegated to other national authorities in charge of specific fields.

Passport Index is an interactive tool, which collects, displays and ranks the passports of the world. You can discover the world’s passports on a map, by country name, by Passport Power Rank and even by the color of their cover. Visa Free Score Passports accumulate points for each visa free country that their holders can visit without a visa, or they can obtain a visa on arrival. Passport Power Rank Passports are ranked based on their Visa Free Score. The higher the Visa Free Score, the better the Passport Power Rank. Methodology The country list is based on the 193 UN member countries and 6 territories (Macao, Kosovo, etc.) for a total of 199. Territories annexed to other countries such as Norfolk Island, French Polynesia, etc. are excluded. Data is based on research from publicly available sources, as well as information shared by government agencies.

Non-expenditure health care data provide information on institutions providing health care in countries, on resources used and on output produced in the framework of health care provision. Data on health care form a major element of public health information as they describe the capacities available for different types of health care provision as well as potential 'bottlenecks' observed. The quantity and quality of health care services provided and the work sharing established between the different institutions are a subject of ongoing debate in all countries. Sustainability - continuously providing the necessary monetary and personal resources needed - and meeting the challenges of ageing societies are the primary perspectives used when analysing and using the data. The resource-related data refer to both human and technical resources, i.e. they relate to: - 'Health care staff': 'manpower' active in the health care sector (doctors, dentists, nurses, etc.); - 'Health care facilities': technical capacity dimensions (hospital beds, beds in nursing and residential care facilities, etc.). Annual national and regional data are provided in absolute numbers and in population-standardised rates (per 100 000 inhabitants). Wherever applicable, the definitions and classifications of the System of Health Accounts (SHA) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). For hospital discharges, the International Shortlist for Hospital Morbidity Tabulation (ISHMT) is used. Health care data on resources are largely based on administrative data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable.

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 agricultural production domain covers: Quantity produced Producer price Value at farmgate (forthcoming) Area harvested Yield per hectare  

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

World : Renewable Electricity Capacity and Generation Statistics

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.

This dataset contains indicators related to Tourism for provincial level.

  

The Energy Statistics Database contains comprehensive energy statistics on the production, trade, conversion and final consumption of primary and secondary; conventional and unconventional; and new and renewable sources of energy. The Energy Statistics dataset, covering the period from 1990 onwards, is available at UNdata

This database contains country-reported GAM data. For HIV epidemiological estimates, as well as ART and PMTCT indicators

This Dataset contains Regional and National level Data.

The primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates