Monaco

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

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.

Preliminary Release: China's Total Export & Import Values ​​by Country/Region (in USD)

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.

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.

Financing Global Health 2019: Tracking Health Spending in a Time of Crisis This edition of the Institute for Health Metrics and Evaluation’s annual Financing Global Health report, the 11th in the series, provides up-to-date estimates of domestic spending on health, development assistance for health, spending for HIV/AIDS, tuberculosis, and malaria, as well as projections of future health spending. Our health spending tracking and estimates show patterns between income groups and regions over time, highlight variations in how much each country spends on health, and identify where more resources are needed most. Financing Global Health 2020: Tracking Health Spending in a Time of Crisis This edition of IHME's annual Financing Global Health report, the 12th in the series, provides updated estimates of spending on health, development assistance for health, and projections of future health spending. This year's report specifically highlights changes in health spending during a global pandemic and includes dedicated sections on COVID-19, as well as in-depth analysis of pandemic preparedness spending and seven other health focus areas.

Measles cases are defined as laboratory confirmed, epidemiologically linked, and clinical cases as reported to the World Health Organization.

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.

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).

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.

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 are an important data source for many public and private sector decision-makers at international, European Union and national level. For example, at the European Union level, external trade data are extensively used for multilateral and bilateral negotiations within the framework of the common commercial policy, to define and implement anti-dumping policy, to evaluate the progress of the Single Market and many other policies. Moreover, they constitute an essential source for the compilation of balance of payments statistics and national accounts. International trade in goods statistics cover both extra- and intra-EU trade: Extra-EU trade statistics cover the trading of goods between Member States and a non-member countries. Intra-EU trade statistics cover the trading of goods between Member States. "Goods" means all movable property including electricity. Detailed and aggregated data are published for the Euro area, the European Union and for each Member State separately. Main components: Data record the monthly trade between Member States in terms of arrivals and dispatches of goods as well as the monthly trade in terms of imports and exports between Member States and non-member countries. However, in publications only the term “exports” for all outward flows and “imports” for all inward flows are applied for both intra-EU trade and extra-EU trade. Extra-EU trade imports and exports are recorded in the Member State where the goods are placed under the customs procedures. Extra-EU trade statistics do not record goods in transit, goods placed into customs warehouses or goods for temporary admission. Data sources: The statistical information is mainly provided by the traders on the basis of Customs (extra-EU) and Intrastat (intra-EU) declarations. Data are collected by the competent national authorities of the Member States and compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Classification systems: - Product classification: For detailed data, products are disseminated according to the Combined Nomenclature (CN8), which first six digit codes coincide with the Harmonized Commodity Description and Coding System (HS), products are disseminated as well according to the Standard International Trade Classification (SITC) and the Broad Economic Categories (BEC). - Country classification: The Geonomenclature is used for classifying reporting countries and trading partners. Nomenclatures and correspondence tables are available at the Eurostat’s classification server RAMON. The following basic information is provided by Eurostat: - reporting country, - reference period, - trade flow, - product, - trading partner, - mode of transport. Detailed data are disseminated according to the Combined Nomenclature (HS2, HS4, HS6 and CN8 levels) for the following indicators: - trade value (in Euro), - trade quantity in 100 kg, - trade quantity in supplementary units (published for some goods according to the Combined Nomenclature). Aggregated data cover both short and long term indicators. Short term indicators are disseminated according to major SITC and BEC groups for the following indicators: - gross and seasonally adjusted trade value (in million Euro), - unit-value indices, - gross and seasonally adjusted volume indices, - growth rates of trade values and indices. Adjustments are applied by the Member States to compensate the impact of exemption thresholds, which release the information providers from statistical formalities, as well as, to take into account the late or not response of the providers. In addition, Eurostat applies seasonal adjustments to aggregated time series.

The food and agricultural trade dataset is collected, processed and disseminated by FAO according to the standard International Merchandise Trade Statistics Methodology. The data is mainly provided by UNSD, Eurostat, and other national authorities as needed. This source data is checked for outliers, trade partner data is used for non-reporting countries or missing cells, and data on food aid is added to take into account total cross-border trade flows. The trade database includes the following variables: export quantity, export value, import quantity and import value. The trade database includes all food and agricultural products imported/exported annually by all the countries in the world.   Classification system: HS 2012 converted into FAO Commodity List (also known as FCL, which is a classification based on the item tree approach used for the compilation of SUA/FBS).   Sector coverage: The dataset contains all food and agricultural products imported and exported during the reference year by country. In addition to the individual country data, other item and country aggregates are disseminated. The processed trade data is essential for the compilation of Supply/Utilization Accounts (SUA) and Food Balance Sheets (FBS).   Statistical concepts and definitions:Quantity of food and agricultural exports: Export quantity is defined by the IMTS as the physical quantity of domestic origin or manufactured products shipped out of the country. It includes re-exports. According to the FAO methodology, the quantity of food and agricultural exports included in the FAOSTAT database is expressed in terms of weight (tonnes) for all commodities except for live animals which are expressed in units (heads); poultry, rabbits, pigeons and other birds are expressed in thousand units. As a general rule, trade quantity refers to net weight, excluding any sort of container.  Value of agricultural exports: Value of agricultural exports are expressed in thousand US dollars in the FAOSTAT database. Export values are reported as FOB  (free on board—that is, the value of the goods plus the value of the services performed to deliver the goods to the border of the exporting country). Quantity of food and agricultural imports: Import quantity represents the physical quantity of the products imported for domestic consumption or processing shipped into a country. It includes re-imports. According to the FAO methodology, the quantity of food and agricultural imports included in the FAOSTAT database is expressed in terms of weight (tonnes) for all commodities except for live animals which are expressed in units (heads); poultry, rabbits, pigeons and other birds are expressed in thousand units. As a general rule, trade quantity refers to net weight, excluding any sort of container. It includes also food aid quantities, where relevant.  Value of agricultural imports: Value of agricultural imports are expressed in thousand US dollars in the FAOSTAT database. Import values are reported as CIF (cost insurance and freight—that is, the value of the goods, plus the value of the services performed to deliver goods to the border of the exporting country, plus the value of the services performed to deliver the good from the border of the exporting country to the border of the importing country). Statistical unit:All crops and livestock products registered by the customs office in the country. In case of non-customs trade data, the observation unit is the trade operator. For example, within intra-EU trade statistics, this unit is any taxable person carrying out intra-EU trade. For more information, see the IMTS compiler manual, edition 2012. Statistical population:All trade data on food and agricultural products, including livestock, are compiled by all customs offices in the country. For intra-EU trade, the statistical population is all trade operators recording trade transactions over a certain threshold. Total merchandise import/export value is also included.

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.

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.

Data cited at: tax justice network - https://fsi.taxjustice.net/en/introduction/fsi-results;  License term - https://fsi.taxjustice.net/en/introduction/copyright-license     Jurisdiction Note for Year 2020: Footnote 1: The territories marked in dark color are Overseas Territories (OTs) and Crown Dependencies (CDs) where the Queen is head of state; powers to appoint key government officials rest with the British Crown; laws must be approved in London; and the UK government holds various other powers (see here for more details: www.financialsecrecyindex.com/PDF/UnitedKingdom.pdf). Territories marked in light color are British Commonwealth territories which are not OTs or CDs but whose final court of appeal is the Judicial Committee of the Privy Council in London (see here for more details: http://www.taxjustice.net/cms/upload/pdf/Privy_Council_and_Secrecy_Scores.pdf). Footnote 6: For jurisdictions marked with 2, we provide special narrative reports exploring the history and politics of their offshore sectors. You can read and download these reports by clicking on the country name.

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 Global Cybersecurity Index (GCI) was first launched in 2015 by the International Telecommunication Union (ITU) to measure the commitment of 193 ITU Member States and the State of Palestine1 to cybersecurity to help them identify areas of improvement and encourage countries to take action, through raising awareness on the state of cybersecurity worldwide. As cybersecurity risks, priorities, and resources evolve, the GCI has also adapted to give a more accurate snapshot of cybersecurity measures taken by countries. This report aims to better understand countries’ commitments to cybersecurity, identify gaps, encourage the incorporation of good practices, and provide useful insights for countries to improve their cybersecurity postures.     Update on this version: Unlike previous iterations, which have a scale of 0 to 1, this iteration of the GCI is on a scale of 0 to 100, with each pillar weighted at 20 points. As a composite weighted index, each indicator, sub-indicator, and micro-indicator are assigned a weight given the relative importance to the indicator group. Weightage can have a significant impact on final scores, and different techniques will produce different rankings.

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.

Citation: Global Health Observatory (GHO) Data: https://www.who.int/gho/en/: World Health Organization; 2019. Licence: 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.

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.  

Global Trends in Prevalence of Tobacco Smoking 2000-2025

Source: UNECE Statistical Database, compiled from national and international (CIS, EUROSTAT, IMF, OECD, World Bank) official sources. Indicators that base on OECD Handbook on Economic Globalisation Indicators are indicated (OECD). General note: The UNECE secretariat presents time series ready for immediate analysis. When appropriate, source segments with methodological differences have been linked and rescaled to build long consistent time series. The national accounts estimates are compiled according to 2008 SNA (System of National Accounts 2008) – e.g. EU member countries, United States, Canada, Ukraine - or 1993 SNA (System of National Accounts 1993). Growth rates (per cent) are over the preceding period, unless otherwise specified. .. - data not available Indicator: Domestic final demand met by total imports, % Indicator measures the share of total domestic final demand (the difference between GDP and net exports) met by imports. Sometimes it is referred to as an import penetration rate. It should be noted that small economies or those rich in mineral resources may be specialized in their production, and so import higher proportions of other goods. In addition, the size of service sector is likely to affect this relationship. [ ( imports / ( final consumption expenditure + gross capital formation ) ) * 100 ] Indicator: Export performance, percentage points Export performance measures the difference between the annual growth rate of exports of a country and the growth rate of imports to the country from the rest of the world. A result above zero level indicates a faster growth of exports compared to the growth of imports during the reference period. [ ( exports (t) / exports (t-1) ) – ( imports (t) / imports (t-1) ) * 100 ] Indicator: Export performance, value in millions of US $, in constant prices of comon base year Export performance measures the difference between the annual growth of exports of a country and the growth of imports to the country from the rest of the world. A result indicates a relation of growth of exports compared to the growth of imports during the reference period in millions of US dollars. [ ( ( exports (t) - exports (t-1) ) – ( ( imports (t) - imports (t-1) ) ) ] Indicator: Growth rate of exports, % Growth rate of exports is an indicator of the annual growth or decline of exports from the previous year. [ ( exports (t) / exports (t-1) ) * 100 ] Indicator: Growth rate of imports, % Growth rate of imports is an indicator of the annual growth or decline of imports from the previous year. [ ( imports (t) / imports (t-1) ) * 100 ] Indicator: Growth rate of total trade, % Growth rate of total trade describes either annual growth or decline of the volume of international trade from the previous year. [ ( exports + imports ) (t) / ( exports + imports ) (t-1) ) * 100 ] Indicator: Import coverage by exports, % Indicator shows whether or not a country’s imports are fully covered for by exports. The results describe how many per cent of imports are covered by exports. [ ( exports / imports ) * 100 ] Indicator: Total exports to GDP, % Total exports in GDP show the dependence of domestic producers on foreign markets. It may provide a better indicator of vulnerability to some types of external shocks than total trade in GDP, thus, it is one of the most frequently used globalization indicators. This ratio may indicate the intensity of a country’s trade. In the case of some countries, it may not show significant growth if, during the reference period, services that are not traded internationally and are included in GDP grow more rapidly than exports. Furthermore, larger economies tend to show lower export to GDP ratios because the larger domestic demand. [ ( exports / GDP ) * 100 ] Indicator: Total trade per capita, value in thousands of US $, current prices Total trade per capita measures the relative importance of international trade against the size of the country in terms of population. It is a very concrete measure of the value of international trade per person. [ ( absolute values of imports + exports ) / population ] Indicator: Total trade to GDP, % Total trade (the sum of exports and imports) as a share of GDP measures the dependence on foreign markets and intermediate inputs and, on the other hand, the importance of international trade in the country. It may give indications of the degree to which an economy is open to trade, but should be interpreted with care. This indicator may be called a trade dependence or openness indicator. [ ( (exports + imports ) / GDP ) * 100 ] Indicator: Trade balance to GDP, % Trade balance to GDP highlights the countries with major surplus or deficit in the reference period in relation to the size of their economies. [ ( ( exports - imports ) / GDP ) * 100 ] Indicator: Trade balance to total trade, % Indicator measures international transactions of the country with the rest of the world normalised against its own total trade. This indicator is sometimes also called the normalized trade balance. [ ( ( exports - imports ) / ( exports + imports ) ) * 100 ] Indicator: Trade balance, value in millions of US $, current prices Trade balance shows the difference between exports and imports (surplus / deficit). This conventional measure reflects a country’s performance in international markets in terms of the net value of goods and services transactions between the country and the rest of the world. [ ( exports - imports ) ]

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.

In accordance with Articles 4 and 12 of the Climate Change Convention, and the relevant decisions of the Conference of the Parties, countries that are Parties to the Convention submit national greenhouse gas (GHG) inventories to the Climate Change secretariat. These submissions are made in accordance with the reporting requirements adopted under the Convention, such as The UNFCCC Reporting Guidelines on Annex I Inventories (document FCCC/SBSTA/2004/8) for Annex I Parties and Guidelines for the preparation of national communications for non-Annex I Parites (decision 17/CP.8). The inventory data are provided in the annual GHG inventory submissions by Annex I Parties and in the national communications under the Convention by non-Annex I Parties. The GHG data reported by Parties contain estimates for direct greenhouse gases, such as: CO2 - Carbon dioxide CH4 - Methane N2O - Nitrous oxide PFCs - Perfluorocarbons HFCs - Hydrofluorocarbons SF6 - Sulphur hexafluoride as well as for the indirect greenhouse gases such as SO2, NOx, CO and NMVOC.

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.

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.

La collection primaire d'indicateurs de développement de la Banque mondiale, compilée à partir de sources internationales officiellement reconnues. Il présente les données les plus récentes et les plus précises sur le développement mondial et comprend des estimations nationales, régionales et mondiales.

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 Balance of Payments (BoP) systematically summarizes all economic transactions between the residents and the non-residents of a country or of an  economic area during a given period and provides harmonized information on international transactions which are part of the current account, the capital and the financial account. Data on International Trade in Services (ITS), are an important component of the BoP current account, and are used, alongside with data on Foreign Direct Investment, to monitor the external commercial performance of different economies. ITS data are collected by national enterprise surveys, International Transaction System (ITRS) and administrative records. Guidance for compilers is provided in the Manual on Statistics of International Trade in services 2010 (http://unstats.un.org/unsd/tradeserv/TFSITS/msits2010/docs/MSITS%202010%20M86%20(E)%20web.pdf)

The mission of the Internet Crime Complaint Center (IC3) is to provide the public with a reliable and convenient reporting mechanism to submit information to the FBI concerning suspected Internet-facilitated criminal activity and to develop effective alliances with industry partners. Information is processed for investigative and intelligence purposes for law enforcement and public awareness.

International trade in goods statistics are an important data source for many public and private sector decision-makers at international, European Union and national level. For example, at the European Union level, international trade data are extensively used for multilateral and bilateral negotiations within the framework of the common commercial policy, to define and implement anti-dumping policy, to evaluate the progress of the Single Market and many other policies. Moreover, they constitute an essential source for the compilation of balance of payments statistics and national accounts. International trade in goods statistics cover both extra- and intra-EU trade: Extra-EU trade statistics cover the trading of goods between Member States and a non-member countries. Intra-EU trade statistics cover the trading of goods between Member States. "Goods" means all movable property including electricity. Detailed and aggregated data are published for the Euro area, the European Union and for each Member State separately. Main components: Data record the monthly trade between Member States in terms of arrivals and dispatches of goods as well as the monthly trade in terms of imports and exports between Member States and non-member countries. However, in publications only the term “exports” for all outward flows and “imports” for all inward flows are applied for both intra-EU trade and extra-EU trade. Extra-EU trade imports and exports are recorded in the Member State where the goods are placed under the customs procedures. Extra-EU trade statistics do not record goods in transit, goods placed into customs warehouses or goods for temporary admission. Data sources: The statistical information is mainly provided by the traders on the basis of Customs (extra-EU) and Intrastat (intra-EU) declarations. Data are collected by the competent national authorities of the Member States and compiled according to a harmonised methodology established by EU regulations before transmission to Eurostat. Classification systems: - Product classification: For detailed data, products are disseminated according to the Combined Nomenclature (CN8), which first six digit codes coincide with the Harmonized Commodity Description and Coding System (HS), products are disseminated as well according to the Standard International Trade Classification (SITC) and the Broad Economic Categories (BEC). - Country classification: The Geonomenclature is used for classifying reporting countries and trading partners. Nomenclatures and correspondence tables are available at the Eurostat’s classification server RAMON. The following basic information is provided by Eurostat: - reporting country, - reference period, - trade flow, - product, - trading partner - mode of transport. Detailed data are disseminated according to the Combined Nomenclature (HS2, HS4, HS6 and CN8 levels) for the following indicators: - trade value (in Euro), - trade quantity in 100 kg, - trade quantity in supplementary units (published for some goods according to the Combined Nomenclature). Aggregated data cover both short and long term indicators. Short term indicators are disseminated according to major SITC and BEC groups for the following indicators: - gross and seasonally adjusted trade value (in million Euro), - unit-value indices, - gross and seasonally adjusted volume indices, - growth rates of trade values and indices. Long term indicators are disseminated according to major SITC groups for the following indicators: - trade value (in billion Euro), - shares of Member States in EU and world trade, - shares of main trading partners in EU trade, - volume indices. Adjustments are applied by the Member States to compensate the impact of exemption thresholds, which release the information providers from statistical formalities, as well as, to take into account the late or not response of the providers. In addition, Eurostat applies seasonal adjustments to aggregated time series.

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.

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.

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

World : Renewable Electricity Capacity and Generation Statistics

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.

Restrictions apply: https://www.scimagojr.com/aboutus.php   Citation: SCImago, (n.d.). SJR — SCImago Journal & Country Rank [Portal]. Retrieved Date you Retrieve, from http://www.scimagojr.com   SCImago Journal Rank: It expresses the average number of weighted citations received in the selected year by the documents published in the selected journal in the three previous years, --i.e. weighted citations received in year X to documents published in the journal in years X-1, X-2 and X-3. H Index: The h index expresses the journal's number of articles (h) that have received at least h citations. It quantifies both journal scientific productivity and scientific impact and it is also applicable to scientists, countries, etc. Total Documents: Output of the selected period. All types of documents are considered, including citable and non citable documents. Total Cites (3years): Number of citations received in the seleted year by a journal to the documents published in the three previous years, --i.e. citations received in year X to documents published in years X-1, X-2 and X-3. All types of documents are considered. Self Cites: Number of journal's self-citations in the selected year to its own documents published in the three previous years, --i.e. self-citations in year X to documents published in years X-1, X-2 and X-3. All types of documents are considered. Cited Documents: Number of documents cited at least once in the three previous years, --i.e. years X-1, X-2 and X-3 Cites per Document (2 years): Average citations per document in a 2 year period. It is computed considering the number of citations received by a journal in the current year to the documents published in the two previous years, --i.e. citations received in year X to documents published in years X-1 and X-2.

Data Cited at - Sachs, J., Schmidt-Traub, G., Kroll, C., Lafortune, G., Fuller, G. (2019): Sustainable Development Report 2019. New York: Bertelsmann Stiftung and Sustainable Development Solutions Network (SDSN). The Sustainable Development Report 2020 presents the SDG Index and Dashboards for all UN member states and frames the implementation of the Sustainable Development Goals (SDGs) in terms of six broad transformations. It was prepared by teams of independent experts at the Sustainable Development Solutions Network (SDSN) and the Bertelsmann Stiftung.

Data cited at: UN E-Government Knowledgebase - https://publicadministration.un.org/egovkb/en-us/ 1. The EGDI is based on a comprehensive Survey of the online presence of all 193 United Nations Member States, which assesses national websites and how e-government policies and strategies are applied in general and in specific sectors for delivery of essential services. The assessment rates the e-government performance of countries relative to one another as opposed to being an absolute measurement. The results are tabulated and combined with a set of indicators embodying a country’s capacity to participate in the information society, without which e-government development efforts are of limited immediate use. Although the basic model has remained consistent, the precise meaning of these values varies from one edition of the Survey to the next as understanding of the potential of e-government changes and the underlying technology evolves. This is an important distinction because it also implies that it is a comparative framework that seeks to encompass various approaches that may evolve over time instead of advocating a linear path with an absolute goal. 2. E-Government Development Index-EGDI Very High-EGDI (Greater than 0.75) High-EGDI (Between 0.50 and 0.75) Middle-EGDI (Between 0.25 and 0.50) Low-EGDI (Less than 0.25)

National Monitoring : School life expectancy by level of education

This Dataset contains Regional and National level Data.

Climate change is expected to hit developing countries the hardest. Its effects—higher temperatures, changes in precipitation patterns, rising sea levels, and more frequent weather-related disasters—pose risks for agriculture, food, and water supplies. At stake are recent gains in the fight against poverty, hunger and disease, and the lives and livelihoods of billions of people in developing countries. Addressing climate change requires unprecedented global cooperation across borders. The World Bank Group is helping support developing countries and contributing to a global solution, while tailoring our approach to the differing needs of developing country partners. Data here cover climate systems, exposure to climate impacts, resilience, greenhouse gas emissions, and energy use. Other indicators relevant to climate change are found under other data pages, particularly Environment, Agriculture & Rural Development, Energy & Mining, Health, Infrastructure, Poverty, and Urban Development.

The 2022 Revision of World Population Prospects is the twenty-seventh edition of official United Nations population estimates and projections that have been prepared by the Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat.

The 2018 Revision of World Urbanization Prospects presents the latest United Nations estimates of the size of urban and rural populations for 233 countries or areas from 1950 to 2018, with projections until 2050. It also includes data on population size for close to 1900 urban settlements having 300000 inhabitants or more in 2018. These 1900 cities or urban areas are now home to nearly 60 per cent of the world’s urban population.