Афганистан

The 3P Anti-trafficking Policy Index evaluates governmental anti-trafficking efforts in the three main policy dimensions (3Ps), based on the requirements prescribed by the United Nations Protocol to Prevent, Suppress and Punish Trafficking in Persons, especially Women and Children (2000).   The three main policy dimensions (3Ps) are:Prosecution of perpetrators of human traffickingPrevention of human traffickingProtection of the victims of human trafficking Each of the 3P areas is evaluated on a 5-point scale and each index is aggregated to the overall 3P Anti-trafficking Index as the  sum (score 3-15).Prosecution Index Score: 1 (no compliance) - 5 (full compliance)Prevention Index Score: 1 (no compliance) - 5 (full compliance)Protection Index Score: 1 (no compliance) - 5 (full compliance)3P Anti-trafficking Policy Index Score: 3 (no compliance for any of the three areas) - 15 (full compliance for all of the three areas) The 3P Anti-trafficking Policy Index is available for each country and each year and currently includes up to 189 countries for the preiod from 2000 to 2015.

Accuracy of annual economic forecasts of international organisations - European Commission, IMF, OECD, World Bank, UN LINK

This indicator aims to capture the share of persons in the labour force protected through a contributory pension scheme (with benefits guaranteed but not currently being received). It provides information about the proportion of the labour force that will receive an old age pension once reaching pensionable age. This right to income security in old age is guaranteed by the prior payment of premiums or contributions, i.e. before the occurrence of the insured contingency.

This indicator aims to capture the share of persons in the labour force protected through a contributory pension scheme (with benefits guaranteed but not currently being received). It provides information about the proportion of the labour force that will receive an old age pension once reaching pensionable age. This right to income security in old age is guaranteed by the prior payment of premiums or contributions, i.e. before the occurrence of the insured contingency.

This indicator aims to capture the share of persons of working age protected through a contributory pension scheme (with benefits guaranteed but not currently being received). It provides information about the proportion of the working-age population that will receive an old age pension once reaching pensionable age. This right to income security in old age is guaranteed by the prior payment of premiums or contributions, i.e. before the occurrence of the insured contingency.

This indicator aims to capture the share of persons of working age protected through a contributory pension scheme (with benefits guaranteed but not currently being received). It provides information about the proportion of the working-age population that will receive an old age pension once reaching pensionable age. This right to income security in old age is guaranteed by the prior payment of premiums or contributions, i.e. before the occurrence of the insured contingency.

This dataset provides data for foreign tourist arrivals distributed by age  group.

The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.

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

The Agri-environmental Indicators—Land domain provides information on the annual evolution of the distribution of agricultural and forest areas, and their sub-components, including irrigated areas, at national, regional and global levels.

The Livestock Patterns domain of the FAOSTAT Agri-Environmental Indicators contains data on livestock numbers, shares of major livestock species and livestock densities in the agricultural area. Values are calculated using Livestock Units (LSU), which facilitate aggregating information for different livestock types. Data are available by country, with global coverage, for the period 1961–2014. This methodology applies the LSU coefficients reported in the "Guidelines for the preparation of livestock sector reviews" (FAO, 2011). From this publication, LSU coefficients are computed by livestock type and by country. The reference unit used for the calculation of livestock units (=1 LSU) is the grazing equivalent of one adult dairy cow producing 3000 kg of milk annually, fed without additional concentrated foodstuffs. FAOSTAT agri-environmental indicators on livestock patterns closely follow the structure of the indicators in EUROSTAT.

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

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

Data source(s) used: Crimes reported to the Judicial authorities by the State Police, Carabinieri and Guardia di Finanza: Are processed the data on felonies and people who were reported by police to the court Other data characteristics: Data referring to social demographic characteristics of alleged offenders could not coincide with data on reports because of the different timing of extraction from police forces database.The sum of the crimes by province could not coincide with the total of the region, and that of the regions with the total Italy, because of the missed precise statement, for some crimes, of the place where they have been committed (or of the region of the committed crime but not of the province).

This indicator conveys the annual growth rates of labour productivity. Labour productivity represents the total volume of output (measured in terms of Gross Domestic Product, GDP) produced per unit of labour (measured in terms of the number of employed persons) during a given time reference period. The indicator allows data users to assess GDP-to-labour input levels and growth rates over time, thus providing general information about the efficiency and quality of human capital in the production process for a given economic and social context, including other complementary inputs and innovations used in production. For further information, see the SDG Indicators Metadata Repository or ILOSTAT's indicator description.

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.

This dataset shows countries and river basins' average exposure to five of Aqueduct's water risk indicators: baseline water stress, interannual variability, seasonal variability, flood occurrence, and drought severity. Risk exposure scores are available for every country (except Greenland and Antarctica), the 100 most populous river basins, and the 100 largest river basins by area. Scores are also available for all industrial, agricultural, and domestic users' average exposure to each indicator in each country and river basin. Citation: Gassert, F., P. Reig, T. Luo, and A. Maddocks. 2013. “Aqueduct country and river basin rankings: a weighted aggregation of spatially distinct hydrological indicators.” Working paper. Washington, DC: World Resources Institute, November 2013. Available online at http://wri.org/publication/aqueduct-country-river-basin-rankings.

Suggested citation: Luo, T., R. Young, and P. Reig. 2015. "Aqueduct projected water stress rankings." Technical note. Washington, DC: World Resources Institute, August 215. Available online at http://www.wri.org/publication/aqueduct-projected-water-stress-country-rankings.    Supplemental Materials: Country Scores                         WRI projected future country-level water stress for 2020, 2030, and 2040 under business-as-usual (BAU), optimistic, and pessimistic scenarios. Each tab lists country projected water stress scores for each scenario and year, weighted by overall water withdrawals. Scores weighted by individual sectors (agricultural, domestic, and industrial) are provided as well.   These global projections are best suited to making comparisons among countries for the same year and among scenarios and decades for the same region. More detailed and localized data or scenarios can better estimate potential outcomes for specific regions and expose large sub-national variations that are subsumed under countrywide water-stress values. The country indicators face persistent limitations in attempting to simplify complex information, such as spatial and temporal variations, into a single number. They also do not account for the governance and investment structure of the water sector in different countries.    It is important to note the inherent uncertainty in estimating any future conditions, particularly those associated with climate change, future population and economic trends, and water demand. Additionally, care should be taken when examining the change rates of a country’s projected stress levels between one year and another, because the risk-score thresholds are not linear. For more information on these limitations, see the technical note.   Projections are described in further detail in: Luck, M., M. Landis, and F. Gassert, “Aqueduct Water Stress Projections: Decadal Projections of Water Supply and Demand Using CMIP5 GCMs,” Technical note (Washington, DC: World Resources Institute, April 2015), http://www.wri.org/publication/aqueduct-water-stress-projections.   Water Stress withdrawals / available flow Water stress measures total annual water withdrawals (municipal, industrial, and agricultural) expressed as a percentage of the total annual available blue water. Higher values indicate more competition among users. Score Value [0-1) Low (<10%) [1-2) Low to medium (10-20%) [2-3) Medium to high (20-40%) [3-4) High (40-80%) [4-5] Extremely high (>80%)    

Data cited at: Stockholm International Peace Research Institute (SIPRI)   The SIPRI Arms Transfers Database contains information on all transfers of major conventional weapons from 1950 to the most recent full calendar year. It is a unique resource for researchers, policy-makers and analysts, the media and civil society interested in monitoring and measuring the international flow of major conventional arms. For more information, see http://www.sipri.org/databases/armstransfers/sources-and-methods/

U.S. Direct Investment Abroad: Balance of Payments and Direct Investment Position 

BOPSY Global Tables aggregate country data by major balance of payments components and by international investment position (IIP) data for (i) Net IIP and (ii) Total Assets and Total Liabilities. Data for countries, country groups, and the world are provided. In addition to data reported by countries as shown in BOPSY, balance of payments data are provided for international organizations in BOPSY Global Tables. The BOPSY Global Tables include, in addition to reported data, data derived in a few instances indirectly from published sources.

Data cited at: Barro-Lee  

UNCTAD's Bilateral FDI Statistics provides up-to-date and systematic FDI data for 206 economies around the world, covering inflows (table 1), outflows (table 2), inward stock (table 3) and outward stock (table 4) by region and economy. Data are in principle collected from national sources. In order to cover the entire world, where data are not available from national sources, data from partner countries (mirror data) as well as from other international organizations have also been used.

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

Both ethanol and biodiesel are classified under the HS-6 digit categories that also contain other products. Biodiesel is an industrial product (as it is produced through a chemical process called transesterification) and classified under HS code 382490 - products, preparations and residual products of the chemical or allied industries not elsewhere specified. Ethanol is classified as an agriculture product under HS code 2207, which covers un-denatured (HS 2207 10) and denatured alcohol (HS 2207 20).

Bloom Consulting was founded in 2003 as a Nation Branding consultancy. Our Headquarters are located in Madrid, with offices in Lisbon and São Paulo. Bloom Consulting has been interviewed by The Economist, Forbes and CNN . According to Country Branding Central www.countrybrandingwiki.org, our CEO José Filipe Torres, a recurrent lecturer in Universities such as Harvard, is considered one of the top 3 international experts in the field of Nation Branding, Region and City Branding, providing advisory for the OECD. In addition, Bloom Consulting publishes the Bloom Consulting Country Brand Ranking © annually for both Trade and Tourism, to extensively analyze the brand performance of 193 countries and territories worldwide and the Digital Country Index - Measuring the Brand appeal of countries and territories in the Digital World.

BP Energy Outlook Charts Data Pack - 2019 edition The Energy Outlook considers different aspects of the energy transition and the key issues and uncertainties these raise.   In all the scenarios considered, world GDP more than doubles by 2040 driven by increasing prosperity in fast-growing developing economies. In the Evolving transition (ET) scenario this improvement in living standards causes energy demand to increase by around a third over the Outlook, driven by India, China and Other Asia which together account for two-thirds of the increase. Despite this increase in energy demand, around two-thirds of the world’s population in 2040 still live in countries where average energy consumption per head is relatively low, highlighting the need for ‘more energy’. Energy consumed within industry and buildings accounts for around three-quarters of the increase in energy demand. Growth in transport demand slows sharply relative to the past, as gains in vehicle efficiency accelerate. The share of passenger vehicle kilometres powered by electricity increases to around 25% by 2040, supported by the growing importance of fully-autonomous cars and shared-mobility services.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Jobs Publication: https://datacatalog.worldbank.org/dataset/jobs License: http://creativecommons.org/licenses/by/4.0/   The World Bank Jobs Statistics Over 150 indicators on labor-related topics, covering over 200 economies from 1990 to present.

Внешняя торговля товарами Российской Федерации по странам партнерам, 1995-2011

Data Citation: CAIT Climate Data Explorer. 2017. Washington, DC: World Resources Institute. Available online at: http://cait.wri.org   CAIT data carries a Creative Commons Attribution-NonCommercial 4.0 International license   CAIT Historic allows for easy access, analysis and visualization of the latest available international greenhouse gas emissions data. It includes information for 186 countries, 50 U.S. states, 6 gases, multiple economic sectors, and 160 years - carbon dioxide emissions for 1850-2012 and multi-sector greenhouse gas emission for 1990-2012.

This dataset is updated with data obtained from Statistics Canada and the U.S. Census Bureau. Current data June 2018. Trade Data is updated on a monthly and annual basis, with revisions in March, April, May, August and November to previous year's data. Trade Data is available on both product and industry-based versions. The product Trade Data is classified by Harmonized System (HS) codes while the industry data is based on North American Industry Classification System(NAICS) classification codes. Source: Statistics Canada and the U.S.Census Bureau

For the location "Puerto Rico" data is available from 1990.

Data cited: Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2016 (GBD 2016) Cancer Incidence, Mortality, Years of Life Lost, Years Lived with Disability, and Disability-Adjusted Life Years 1990-2016. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2018.   The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries. Estimates for deaths, disability-adjusted life years (DALYs), years lived with disability (YLDs), years of life lost (YLLs), prevalence, and incidence for 29 cancer groups by age and sex for 1990-2016 are available from the GBD Results Tool. Files available in this record are the web tables published in JAMA Oncology in June 2018 in "Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-years for 29 Cancer Groups, 1990 to 2016."

The Global Burden of Disease Study 2017 (GBD 2017), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories, and at the subnational level for a subset of countries.

Global and regional deaths of children under 5 years of age by cause. Estimates generated by the WHO and Maternal and Child Epidemiology Estimation Group (MCEE) 2018.

Data cited at: Statistics Finland http://www.stat.fi/index_en.html Publication: 030 -- Citizenship by sex, by region and municipality in 1990 to 2017 http://pxnet2.stat.fi/PXWeb/pxweb/en/StatFin/StatFin__vrm__vaerak/statfin_vaerak_pxt_030.px License: http://creativecommons.org/licenses/by/4.0/ Concepts and definitions Description Quality description These statistics apply the regional division of 1 January 2018 to the whole time series. Population statistics from 1750 to 2000 have been digitised into PDF format in the National Library's Doria service. Publications on Population structure and vital statistics in Doria (in Finnish) Publications on Population censuses in Doria (in Finnish) Area For reasons of privacy protection, cells with less than 10 cases of citizenship, country of birth, background country or language by municipality have been marked with two dots. Continent sums have not been hidden in municipality data nor have regional data concerning individual languages or countries. Citizenship If a person has two nationalities and one of them is Finnish, he/she will be included in statistics as a Finnish national. The used classification of continents is the classification of Eurostat, where Cyprus and Turkey belong to Europe. Citizens of non-autonomous states are summed under the mother country. Citizenship Czech Republic Czech Republic + Former Czechoslovakia Sudan Sudan + Former Sudan

Population as of 1 Juli. Our Populationregister holds information on all persons, who have had address in Greenland after Januar 1st 1977. Purpose of the register Registrets formål er at danne grundlag for befolkningsstatistikken, samt supplere andre personhenførbare oplysninger med basisoplysninger om personen, samt dennes adresse og familierelationer. Befolkningsstatistikregistret opdateres med oplysninger fra CPR (Folkeregistrene) hvor følgende oplysninger hentes: navn, køn, alder, fødested, statsborgerskab, civilstand, henvisning til mor, far samt ægtefælle, bopælsadresse og tilflytningsdato. Jfr §13 i Lov om Grønlands Statistik, videregives ingen personhenførbare oplysninger fra registret, bortset fra personnumre, som efter Datatilsynets godkendelse er udtrukket til interviewundersøgelser

Food supply data is some of the most important data in FAOSTAT. In fact, this data is for the basis for estimation of global and national undernourishment assessment, when it is combined with parameters and other data sets. This data has been the foundation of food balance sheets ever since they were first constructed. The data is accessed by both business and governments for economic analysis and policy setting, as well as being used by the academic community.

The consolidated banking statistics (CBS) measure international banking activity from a nationality perspective, focusing on the country where the banking group's parent is headquartered. While residence-based data such as the locational banking statistics indicate where positions are booked, they do not always identify where underlying decisions are made. This is because banking offices in one country may operate within a business model decided by the group's controlling parent, which may be headquartered in another country. The CBS capture the worldwide claims of banking groups based in reporting countries and exclude intragroup positions, similar to the consolidation approach followed by banking supervisors. The CBS provide several different measures of banking groups' country risk exposures, on either an immediate counterparty or an ultimate risk basis. The most appropriate exposure measure depends on the issue being analysed. The benchmark measure in the CBS is foreign claims, which capture credit to borrowers outside a banking group's home country.   Measure for all Combinations - Amounts Outstanding / Stocks   Note: Under "Reporting country" they have removed "Euro Area".  

Below Parameters are common for all combinations : Frequency - Quarterly Measure -Amounts Outstanding / Stocks CBS Bank Type - Domestic Banks CBS Reporting Basis - Immediate Counterparty Basis Balance Sheet Position - Total Claims Type of Instruments - All Instruments Remaining Maturity - All Maturities Currency Type of Booking Location - All Currencies Counterparty Sector - All Sectors

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

The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.

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 CORRUPTION PERCEPTIONS INDEX 2018 by Transparency International is licensed under CC-BY-ND 4.0. Global Corruption Barometer is the largest world-wide public opinion survey on corruption. see more at https://www.transparency.org/cpi2018 Transparency International(TI) defines corruption as the abuse of entrusted power for private gain. This definition encompasses corrupt practices in both the public and private sectors. The Corruption Perceptions Index (CPI) ranks countries according to the perception of corruption in the public sector. The CPI is an aggregate indicator that combines different sources of information about corruption, making it possible to compare countries. The CPI ranks almost 200 countries by their perceived levels of corruption, as determined by expert assessments and opinion surveys.

Countries at the Crossroads is an annual analysis of government performance in 70 strategically important countries worldwide that are at a critical crossroads in determining their political future. The in-depth comparative assessments and quantitative ratings – examining government accountability, civil liberties, rule of law, and anticorruption and transparency efforts – are intended to help international policymakers identify areas of progress, as well as to highlight areas of concern that could be addressed in diplomatic efforts and reform assistance.The Crossroads project has generated far-reaching interest since its inception in 2004. Increased attention to the relationship between competent governance and respect for civil and political rights means that scholars and policymakers require sophisticated tools to help place the performance of various governments in perspective. Crossroads helps ground this analysis by providing indispensable quantitative assessment that allows for comparison over time, as well as detailed narrative reports that provide real-world context.A new edition of Crossroads is published each year, with half the set of countries analyzed in odd years and the other half in even years. Crossroads reports are written and evaluated by some of the most prominent independent experts available for each country.

Global growth is forecast at 3.5 percent in 2015 and 3.8 percent in 2016, with uneven prospects across the main countries and regions of the world. The distribution of risks to near-term global growth has become more balanced relative to the October World Economic Outlook but is still tilted to the downside. The decline in oil prices could boost activity more than expected. Geopolitical tensions continue to pose threats, and risks of disruptive shifts in asset prices remain relevant. In some advanced economies, protracted low inflation or deflation also pose risks to activity. The chapter takes a region-by-region look at the recent development in the world economy and the outlook for 2015, with particular attention to notable development in countries within each region.

Data cited at: Statistics Finland http://www.stat.fi/index_en.html Publication: 012 -- Country of birth according to age and sex by region in 1990 to 2017 http://pxnet2.stat.fi/PXWeb/pxweb/en/StatFin/StatFin__vrm__vaerak/statfin_vaerak_pxt_012.px License: http://creativecommons.org/licenses/by/4.0/ Concepts and definitions Description Quality description These statistics apply the regional division of 1 January 2018 to the whole time series. Population statistics from 1750 to 2000 have been digitised into PDF format in the National Library's Doria service. Publications on Population structure in Doria (in Finnish) Publications on Vital statistics in Doria (in Finnish) Publications on Population censuses in Doria (in Finnish) Country of birth The used classification of continents is the classification of Eurostat, where Cyprus and Turkey belong to Europe. Non-autonomous states are summed under their mother country. Country of birth Sudan Sudan + Former Sudan

The World Bank's Country Policy and Institutional Assessment is done annually for all its borrowing countries. It has evolved into a set of criteria, which are grouped in four clusters: (a) economic management; (b) structural policies; (c) policies for social inclusion and equity; and (d) public sector management and institutions. The number of criteria, currently sixteen, reflect a balance between ensuring that all key factors that foster pro-poor growth and poverty alleviation are captured, without overly burdening the evaluation process. Ratings for each of the criteria reflect a variety of indicators, observations, and judgments. They focus on the quality of each country's current policies and institutions - which are the main determinant of present aid effectiveness prospects. To fully underscore the importance of the CPIA in the IDA Performance Based Allocations, the overall country score is referred to as the IDA Resource Allocation Index (IRAI)

Note: CPA data for 2018 and 2019 are projections from the 2016 Survey on Forward Spending Plans. Country Programmable Aid (CPA), outlined in our Development Brief  and also known as “core” aid, is the portion of aid donors programme for individual countries, and over which partner countries could have a significant say. CPA is much closer than ODA to capturing the flows of aid that goes to the partner country, and has been proven in several studies to be a good proxy of aid recorded at country level. CPA was developed in 2007 in close collaboration with DAC members. It is derived on the basis of DAC statistics and was retroactively calculated from 2000 onwards

Country Programmable Aid (CPA), outlined in our Development Brief  and also known as “core” aid, is the portion of aid donors programme for individual countries, and over which partner countries could have a significant say. CPA is much closer than ODA to capturing the flows of aid that goes to the partner country, and has been proven in several studies to be a good proxy of aid recorded at country level. CPA was developed in 2007 in close collaboration with DAC members. It is derived on the basis of DAC statistics and was retroactively calculated from 2000 onwards

COFR presents data on fiscal transparency. It provides an overview of fiscal reporting, including whether fiscal data are available for all of the general government, whether the government reports a balance sheet, and whether spending and revenue are reported on a cash or accrual basis. It also derives specific indices of the coverage of public institutions, fiscal flows, and fiscal stocks.

The Credit to Agriculture dataset provides national data for over 100 countries on the amount of loans provided by the private/commercial banking sector to producers in agriculture, forestry and fisheries, including household producers, cooperatives, and agro-businesses. For some countries, the three sub sectors of agriculture, forestry, and fishing are completely specified. In other cases, complete dis aggregations are not available. The dataset also provides statistics on the total credit to all industries, indicators on the share of credit to agricultural producers, and an agriculture orientation index (the agriculture share of credit, over the agriculture share of GDP).

Cricket Player Statistics, 1971 - 2017 This dataset covers cricket players statistics on batting, bowling, fielding, all rounders across Test, ODI, T20 matches.

Data cited at: Numbeo Crime Index is an estimation of overall level of crime in a given city or a country. We consider crime levels lower than 20 as very low, crime levels between 20 and 40 as being low, crime levels between 40 and 60 as being moderate, crime levels between 60 and 80 as being high and finally crime levels higher than 80 as being very high. Safety index is, on the other way, quite opposite of crime index. If the city has a high safety index, it is considered very safe.  

GHG emissions data from the cultivation of organic soils are those associated with nitrous oxide gas from organic soils under cropland (item: Cropland organic soils) and grassland (item: Grassland organic soils). The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, region and special groups, with global coverage, relative to the period 1990-present (with annual updates) and with projections for 2030 and 2050, expressed both as Gg N2O and Gg CO2eq, by cropland, grassland and by their aggregation. Implied emission factor for N2O as well activity data (areas) are also provided.

This table shows exchange rates for currencies used in over 190 world economies presented in a cross rates layout where countries are presented in both rows and columns. National currency per US dollars exchange rates are used to derive explicit exchange rates for each of the countries presented with regard to any other country. Country series are consistent over time: for example, a conversion was made from national currency to Euro for the Euro Zone economies for all years prior to the adoption of Euro.

The Bank of Canada’s Credit Rating Assessment Group (CRAG) comprehensive database of sovereign defaults draws on previously published data sets compiled by various official and private sector sources. It combines elements of these, together with new information, to develop estimates of stocks of government obligations in default, including bonds and other marketable securities, bank loans, and official loans in default, valued in U.S. dollars, for the years 1960 to 2016 on both a country-by-country and a global basis. This update of CRAG’s database, and subsequent updates, will be useful to researchers analyzing the economic and financial effects of individual sovereign defaults and, importantly, the impact on global financial stability of episodes involving multiple sovereign defaults.

Defense Aircraft Summary

Financing Global Health 2016 is the eighth edition of IHME’s annual series on global health spending and health financing. In addition to describing the trends in development assistance for health (DAH), this year’s report features an expanded discussion of domestic spending across low-, middle-, and high-income countries to describe the context in which DAH operates, identify health financing gaps, and support the pursuit of universal health coverage. Also new in Financing Global Health this year are detailed data for the funding of specific program areas within DAH for malaria and more thorough analysis of DAH for health system strengthening. This adds to the existing detailed tracking of DAH by program area for HIV/AIDS, maternal, newborn, and child health, and non-communicable diseases (NCDs). The coverage of domestic health spending builds on data and analyses presented in two papers published this year: “Global Burden of Disease Financing Global Health Collaborator Network. Evolution and patterns of global health financing 1995–2014: development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries,” and “Global Burden of Disease Financing Global Health Collaborator Network. Future and potential spending on health 2015–2040 by government, prepaid private, out-of-pocket, and donor financing for 184 countries.” Both analyses were published in The Lancet in April 2017. More information about these data and methods are found in the online methods annex.

Direct Investment Position Abroad on a Historical-Cost Basis:  Country Detail by Industry, United States

GBD 2017 - Disability-Adjusted Life Years and Healthy Life Expectancy 1990-2017 The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries. Estimates for disability-adjusted life years (DALYs) by cause, age, and sex and healthy life expectancy (HALE) by age and sex are available from the GBD Results Tool for 1990-2016 (quinquennial). Select tables published in The Lancet in September 2017 in "Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016" are also available for download via the “Files” tab above.

Discouraged job-seekers refer to those persons of working age who during a specified reference period were without work and available for work, but did not look for work in the recent past for specific reasons (for example, believing that there were no jobs available, believing there were none for which they would qualify, or having given up hope of finding employment). The working age population is commonly defined as persons aged 15 years and older, but this varies from country to country. In addition to using a minimum age threshold, certain countries also apply a maximum age limit.

Note: All data contained within is provisional. The annual number of cases of measles and rubella officially reported by a member state is only available by July of each following year (through the joint WHO UNICEF annual data collection exercise). “provisional data based on monthly data reported to WHO (Geneva) as of April 2019”. Measles cases are defined as laboratory confirmed, epidemiologically linked, and clinical cases as reported to the World Health Organization. Some countries report cases at irregular intervals, providing multiple months of data in a one month period. Future months are reported as 0 and will be updated as data is available. When data is used in public settings, please acknowledge the data source is the World Health Organization.

IHME research, published in the Lancet in 2008. The study, Tracking progress towards universal childhood immunizations and the impact of global initiatives, provides estimates with confidence intervals of the coverage of three-dose diphtheria, tetanus, and pertussis (DTP3) vaccination. The estimates take into account all publicly available data, including data from routine reporting systems and nationally representative surveys.

Contains annual data series on water consumption, irrigated area, solar water and space heating area, countries overpumping aquifers and water deficits for the countries and regions through the time period from 1961 to 2013.

Calculated using Mean Years of Schooling and Expected Years of Schooling.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic:Education Statistics Publication: https://datacatalog.worldbank.org/dataset/education-statistics License: http://creativecommons.org/licenses/by/4.0/   The World Bank EdStats All Indicator Query holds over 4,000 internationally comparable indicators that describe education access, progression, completion, literacy, teachers, population, and expenditures. The indicators cover the education cycle from pre-primary to vocational and tertiary education.

World: Electricity Prices

Greenhouse Gas (GHG) emissions from burning of savanna consist of methane (CH4) and nitrous oxide (N2O) gases produced from the burning of vegetation biomass in the following five land cover types: Savanna, Woody Savanna, Open Shrublands, Closed Shrublands, and Grasslands. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, regions and special groups, with global coverage, relative to the period 1990-present (with annual updates), expressed as Gg CH4, Gg N2O, Gg CO2eq and Gg CO2eq from both CH4 and N2O, by land cover class (savanna, woody savanna, closed shrubland, open shrubland, grassland) and by aggregates (all categories, savanna and woody savanna, closed and open shrubland). Implied emission factors for N2O and CH4 as well activity data (burned area and biomass burned) are also provided.

Agriculture Total contains all the emissions produced in the different agricultural emissions sub-domains (enteric fermentation, manure management, rice cultivation, synthetic fertilizers, manure applied to soils, manure left on pastures, crop residues, cultivation of organic soils, burning of crop residues, burning of savanna, energy use), providing a picture of the contribution to the total amount of GHG emissions from agriculture. GHG emissions from agriculture consist of non-CO2 gases, namely methane (CH4) and nitrous oxide (N2O), produced by crop and livestock production and management activities. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/index.html). GHG emissions are provided by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed as Gg CO2 and CO2eq (from CH4 and N2O), by underlying agricultural emission sub-domain and by aggregate (agriculture total, agriculture total plus energy, agricultural soils).

Greenhouse Gas (GHG) emissions from burning crop residues consist of methane (CH4) and nitrous oxide (N2O) gases produced by the combustion of a percentage of crop residues burnt on-site. The mass of fuel available for burning should be estimated taking into account the fractions removed before burning due to animal consumption, decay in the field, and use in other sectors (e.g., biofuel, domestic livestock feed, building materials, etc.). FAOSTAT emission estimates are computed at Tier 1 following the IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, reguions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed both as Gg CH4, Gg N2O, Gg CO2eq and CO2eq from CH4 and N2O, by crop (maize, rice, sugarcane and wheat) and by aggregates. Implied emission factors for N2O and CH4 as well activity data (biomass burned) are also provided.

Greenhouse gas (GHG) emissions from crop residues consist of direct and indirect nitrous oxide (N2O) emissions from nitrogen (N) in crop residues and forage/pasture renewal left on agricultural fields by farmers. Specifically, N2O is produced by microbial processes of nitrification and de-nitrification taking place on the deposition site (direct emissions), and after volatilization/re-deposition and leaching processes (indirect emissions). The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories, Vol. 4, Ch. 2 and 11(http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided as direct, indirect and total by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed as Gg N2O and Gg CO2eq, by crop and N content in residues.

Greenhouse gas (GHG) emissions from enteric fermentation consist of methane gas produced in digestive systems of ruminants and to a lesser extent of non-ruminants. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories vol. 4, ch. 10 and 11 (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed both as Gg CH4 and Gg CO2eq, by livestock species (asses, buffaloes, camels, cattle (dairy and non-dairy), goats, horses, llamas, mules, sheep, swine (breeding and market)) and by species aggregates (all animals, camels and llamas, cattle, mules and asses, sheep and goats, swine). Implied emission factor for CH4 and activity data are also provided

GHG emissions from manure applied to soils consist of direct and indirect nitrous oxide (N2O) emissions from manure nitrogen (N) added to agricultural soils by farmers. Specifically, N2O is produced by microbial processes of nitrification and de-nitrification taking place on the application site (direct emissions), and after volatilization/re-deposition and leaching processes (indirect emissions). The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories vol. 4, ch. 10 and 11 (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided as direct, indirect and total by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed as Gg N2O and Gg CO2eq, by livestock species (asses, buffaloes, camels, cattle (dairy and non-dairy), chickens (broilers and layers), ducks, goats, horses, llamas, mules, sheep, swine (breeding and market) and turkeys) and by species aggregates (all animals, camels and llamas, cattle, chickens, mules and asses, poultry birds, sheep and goats, swine). Implied emission factor for N2O and activity data (N content in manure) are also provided.

GHG emissions from manure left on pastures consist of direct and indirect nitrous oxide (N2O) emissions from manure nitrogen (N) left on pastures by grazing livestock. Specifically, N2O is produced by microbial processes of nitrification and de-nitrification taking place on the deposition site (direct emissions), and after volatilization/re-deposition and leaching processes (indirect emissions). The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories vol. 4, ch. 10 and 11 (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed as direct, indirect and total Gg N2O and Gg CO2eq, by livestock species (asses, buffaloes, camels, cattle (dairy and non-dairy), chickens (broilers and layers), ducks, goats, horses, llamas, mules, sheep, swine (breeding, market), turkeys) and by species aggregates (all animals, camels and llamas, cattle, chickens, mules and asses, poultry birds, sheep and goats, swine). Implied emission factor for N2O and N content in manure are also provided.

Greenhouse gas (GHG) emissions from synthetic fertilizers consist of nitrous oxide gas from synthetic nitrogen additions to managed soils. Specifically, N2O is produced by microbial processes of nitrification and de-nitrification taking place on the addition site (direct emissions), and after volatilization/re-deposition and leaching processes (indirect emissions). The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories vol. 4, ch. 11 (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided as direct, indirect and total by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed as Gg N2O and Gg CO2eq. Implied emission factor for N2O and activity data (consumption) are also provided.

Greenhouse Gas (GHG) emissions from burning of biomass consist of methane and nitrous oxide gases from biomass combustion of forest land cover classes ‘Humid and Tropical Forest’ and ‘Other Forests’, and of methane, nitrous oxide, and carbon dioxide gases from combustion of organic soils. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, with global coverage, relative to the period 1990-present (with annual updates), expressed as Gg CH4, Gg N2O, Gg CO2, Gg CO2eq and Gg CO2eq from both CH4 and N2O, by land cover class (humid tropical forest, other forest, organic soils) and by aggregate (burning - all categories). Implied emission factors for N2O, CH4 and CO2 as well activity data (burned area and biomass burned) are also provided.

Greenhouse gas (GHG) emissions data from cropland are currently limited to emissions from cropland organic soils. They are those associated with carbon losses from drained histosols under cropland. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol5.html). GHG emissions are provided by country, region and special groups, with global coverage, relative to the period 1990-present (with annual updates), expressed as net emissions/removal Gg CO2 and Gg CO2eq. Implied emission factor for C, net stock change Gg C and activity data (area) are also provided.

Annual net CO2 emission/removal from Forest Land consist of net carbon stock gain/loss in the living biomass pool (aboveground and belowground biomass) associated with Forest and Net Forest Conversion. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/index.html) and using area and carbon stocks data compiled by countries in the FAO Global Forest Resource Assessments (http://www.fao.org/forestry/fra/en/). GHG emissions are provided by country, regions and special groups, with global coverage, relative to the period 1990-present (with annual updates), expressed as net stock change Gg C, net emissions/removals Gg CO2 and CO2eq, by forest or net forest conversion and by aggregate (forest land). Implied emission factor for CO2 as well as activity data (area, net area difference, total forest area and carbon stock in living biomass) are also given.

Greenhouse gas (GHG) emissions data from grassland are currently limited to emissions from grassland organic soils. They are those associated with carbon losses from drained histosols under grassland. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol6.html). GHG emissions are provided by country, region and special groups, with global coverage, relative to the period 1990-present (with annual updates), expressed as net emissions/removal Gg CO2 and Gg CO2eq. Implied emission factor for C, net stock change Gg C and activity data (area) are also provided.

Land Use Total contains all GHG emissions and removals produced in the different Land Use sub-domains, representing the three IPCC Land Use categories: cropland, forest land, and grassland, collectively called emissions/removals from the Forestry and Other Land Use (FOLU) sector. FOLU emissions consist of CO2 (carbon dioxide), CH4 (methane) and N2O (nitrous oxide) associated with land management activities. CO2 emissions/removals are derived from estimated net carbon stock changes in above and below-ground biomass pools of forest land, including forest land converted to other land uses. CH4 and N2O, and additional CO2 emissions are estimated for fires and drainage of organic soils. The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/index.html). GHG emissions are provided as by country, regions and special groups, with global coverage, relative to the period 1990-present (with annual updates), expressed as Gg CO2eq from CH4 and N2O, net emissions/removals as GG CO2 and Gg CO2eq, by underlying land use emission sub-domain and by aggregate (land use total).

Employed migrants refer to the number of persons who changed their country of usual residence and were also employed during a specified brief period. Data are disaggregated by country of origin. A person's country of origin is that from which the person originates, i.e. the country of his or her citizenship (or, in the case of stateless persons, the country of usual residence).

The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.

Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are disaggregated by economic activity and occupation, according to the latest versions of the International Standard Industrial Classification of All Economic Activities (ISIC) and International Standard Classification of Occupations (ISCO), respectively. Economic activity refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works. Information on occupation provides a description of the set of tasks and duties which are carried out by, or can be assigned to, one person.

Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are disaggregated by economic activity according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Economic activity refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works.

Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are provided by institutional sector, which refers to disaggregations by public and private sector employment. Public sector employment covers employment in the government sector plus employment in publicly-owned resident enterprises and companies, operating at central, state (or regional) and local levels of government. It covers all persons employed directly by those institutions, regardless of the particular type of employment contract. Private sector employment comprises employment in all resident units operated by private enterprises, that is, it excludes enterprises controlled or operated by the government sector.

Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are disaggregated by occupation according to the latest version of the International Standard Classification of Occupations (ISCO) available for that year and presented for categories at the 2-digit level of the classification. Information on occupation provides a description of the set of tasks and duties which are carried out by, or can be assigned to, one person.

Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are disaggregated by occupation according to the latest version of the International Standard Classification of Occupations (ISCO) available for that year. Information on occupation provides a description of the set of tasks and duties which are carried out by, or can be assigned to, one person.

Employees are all those workers who hold paid employment jobs, which are those where the incumbents hold employment contracts which give them a basic remuneration not directly dependent upon the revenue of the unit for which they work. Data are disaggregated by weekly hours actually worked, on the basis of the mean number of hours of work per week, and with reference to hours worked in all jobs of employed persons and in all types of working time arrangements (e.g. full-time and part-time). Hours actually worked include (a) direct hours or the time spent carrying out the tasks and duties of a job, (b) related hours, or the time spent maintaining, facilitating or enhancing productive activities (c) down time, or time when a person in a job cannot work due to machinery or process breakdown, accident, lack of supplies or power or Internet access and (d) resting time, or time spent in short periods of rest, relief or refreshment, including tea, coffee or prayer breaks, generally practised by custom or contract according to established norms and/or national circumstances. Hours actually worked excludes time not worked during activities such as: (a) Annual leave, public holidays, sick leave, parental leave or maternity/paternity leave, other leave for personal or family reasons or civic duty, (b) Commuting time between work and home when no productive activity for the job is performed; for paid employment, even when paid by the employer; (c) Time spent in certain educational activities; for paid employment, even when authorized, paid or provided by the employer; (d) Longer breaks distinguished from short resting time when no productive activity is performed (such as meal breaks or natural repose during long trips); for paid employment, even when paid by the employer.

The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.

National accounts are a coherent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. The data presented in this collection are the results of a pilot exercise on the sharing selected main GDP aggregates, population and employment data collected by different international organisations. It wasconducted by the Task Force in International Data Collection (TFIDC) which was established by the  Inter-Agency Group on Economic and Financial Statistics (IAG).  The goal of this pilot is to develop a set of commonly shared principles and working arrangements for data cooperation that could be implemented by the international agencies. The data sets are an experimental exercise to present national accounts data form various countries across the globe in one coherent folder, but users should be aware that these data are collected and validated by different organisations and not fully harmonised from a methodological point of view.  The domain consists of the following collections:

The employed comprise all persons of working age who, during a specified brief period, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by economic activity and occupation, according to the latest versions of the International Standard Industrial Classification of All Economic Activities (ISIC) and International Standard Classification of Occupations (ISCO), respectively. Economic activity refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works. Information on occupation provides a description of the set of tasks and duties which are carried out by, or can be assigned to, one person.

Data cited at: Statistics Finland http://www.stat.fi/index_en.html Publication: 018 -- Employed persons by occupational group (Classification of Occupations 2010, levels 1 to 2), background country, sex and year 2010-2016 http://pxnet2.stat.fi/PXWeb/pxweb/en/StatFin/StatFin__vrm__tyokay/statfin_tyokay_pxt_018.px License: http://creativecommons.org/licenses/by/4.0/ Hint: Occupational data can be filtered to different hierarchy levels of the classification (Level 1, Level 2) by entering in the Search field, e.g. Level 2. The figures in the tables are final. Description of statistics Concepts and definitions Classifications .. = Data not available or too uncertain for presentation, or subject to secrecy. From 2005, the employment pension insurance includes those aged 18 to 68, while previously the obligation to take out pension insurance for employees already started from the age of 14. This is visible in the employment statistics from 2005 onwards as a fall in employment by young people and a rise in the number of students. Statistics cannot be compiled reliably on employment by under-age people on the basis of register data. Background countries are specified in the table if the number of employed persons in the background country exceeds 99. © Tilastokeskus - Statistics Finland

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. Data for 1991-2016 are estimates while 2017-2021 data are projections. The dataset was updated as of November 2017. For more information, refer to the ILO estimates and projections methodological note.

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work).

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

The employed comprise all persons of working age who, during a specified brief period, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by economic activity according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Economic activity refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works.

The employed comprise all persons of working age who, during a specified brief period, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are provided by institutional sector, which refers to disaggregations by public and private sector employment. Public sector employment covers employment in the government sector plus employment in publicly-owned resident enterprises and companies, operating at central, state (or regional) and local levels of government. It covers all persons employed directly by those institutions, regardless of the particular type of employment contract. Private sector employment comprises employment in all resident units operated by private enterprises, that is, it excludes enterprises controlled or operated by the government sector.

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

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by occupation according to the latest version of the International Standard Classification of Occupations (ISCO) available for that year and presented for a selection of categories at the 2-digit level of the classification. Information on occupation provides a description of the set of tasks and duties which are carried out by, or can be assigned to, one person.

The employed comprise all persons of working age who, during a specified brief period, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by occupation according to the latest version of the International Standard Classification of Occupations (ISCO) available for that year. Information on occupation provides a description of the set of tasks and duties which are carried out by, or can be assigned to, one person.

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by status in employment according to the latest version of the International Standard Classification of Status in Employment (ICSE-93). Status in employment refers to the type of explicit or implicit contract of employment the person has with other persons or organizations. The basic criteria used to define the groups of the classification are the type of economic risk and the type of authority over establishments and other workers which the job incumbents have or will have. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. Data for 1991-2016 are estimates while 2017-2021 data are projections. The dataset was updated as of November 2017. For more information, refer to the ILO estimates and projections methodological note.

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by status in employment according to the latest version of the International Standard Classification of Status in Employment (ICSE-93). Status in employment refers to the type of explicit or implicit contract of employment the person has with other persons or organizations. The basic criteria used to define the groups of the classification are the type of economic risk and the type of authority over establishments and other workers which the job incumbents have or will have.

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by weekly hours actually worked, on the basis of the mean number of hours of work per week, and with reference to hours worked in all jobs of employed persons and in all types of working time arrangements (e.g. full-time and part-time). Hours actually worked include (a) direct hours or the time spent carrying out the tasks and duties of a job, (b) related hours, or the time spent maintaining, facilitating or enhancing productive activities (c) down time, or time when a person in a job cannot work due to machinery or process breakdown, accident, lack of supplies or power or Internet access and (d) resting time, or time spent in short periods of rest, relief or refreshment, including tea, coffee or prayer breaks, generally practised by custom or contract according to established norms and/or national circumstances. Hours actually worked excludes time not worked during activities such as: (a) Annual leave, public holidays, sick leave, parental leave or maternity/paternity leave, other leave for personal or family reasons or civic duty, (b) Commuting time between work and home when no productive activity for the job is performed; for paid employment, even when paid by the employer; (c) Time spent in certain educational activities; for paid employment, even when authorized, paid or provided by the employer; (d) Longer breaks distinguished from short resting time when no productive activity is performed (such as meal breaks or natural repose during long trips); for paid employment, even when paid by the employer.

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by level of education, which refers to the highest levelof education completed, classified according to the International Standard Classification of Education (ISCE).

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are provided by age and geographical coverage, which entails a disaggregation by rural and urban areas.

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by status in employment according to the latest version of the International Standard Classification of Status in Employment (ICSE-93). Status in employment refers to the type of explicit or implicit contract of employment the person has with other persons or organizations. The basic criteria used to define the groups of the classification are the type of economic risk and the type of authority over establishments and other workers which the job incumbents have or will have. Data are also disaggregated by economic activity according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Economic activity refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works.

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by status in employment according to the latest version of the International Standard Classification of Status in Employment (ICSE-93). Status in employment refers to the type of explicit or implicit contract of employment the person has with other persons or organizations. The basic criteria used to define the groups of the classification are the type of economic risk and the type of authority over establishments and other workers which the job incumbents have or will have. Data are also disaggregated by occupation according to the latest version of the International Standard Classification of Occupations (ISCO) available for that year. Information on occupation provides a description of the set of tasks and duties which are carried out by, or can be assigned to, one person.

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

The employed comprise all persons of working age who, during a specified brief period, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by economic activity, which refers to the main activity of the establishment in which a person worked during the reference period and does not depend on the specific duties or functions of the person's job, but on the characteristics of the economic unit in which this person works.

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by level of education, which refers to the highest levelof education completed, classified according to the International Standard Classification of Education (ISCE).

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by weekly hours actually worked, on the basis of the mean number of hours of work per week, and with reference to hours worked in all jobs of employed persons and in all types of working time arrangements (e.g. full-time and part-time). Hours actually worked include (a) direct hours or the time spent carrying out the tasks and duties of a job, (b) related hours, or the time spent maintaining, facilitating or enhancing productive activities (c) down time, or time when a person in a job cannot work due to machinery or process breakdown, accident, lack of supplies or power or Internet access and (d) resting time, or time spent in short periods of rest, relief or refreshment, including tea, coffee or prayer breaks, generally practised by custom or contract according to established norms and/or national circumstances. Hours actually worked excludes time not worked during activities such as: (a) Annual leave, public holidays, sick leave, parental leave or maternity/paternity leave, other leave for personal or family reasons or civic duty, (b) Commuting time between work and home when no productive activity for the job is performed; for paid employment, even when paid by the employer; (c) Time spent in certain educational activities; for paid employment, even when authorized, paid or provided by the employer; (d) Longer breaks distinguished from short resting time when no productive activity is performed (such as meal breaks or natural repose during long trips); for paid employment, even when paid by the employer.

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

The employed comprise all persons of working age who, during a specified brief period, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by occupation according to the latest version of the International Standard Classification of Occupations (ISCO). Information on occupation provides a description of the set of tasks and duties which are carried out by, or can be assigned to, one person.

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by status in employment according to the latest version of the International Standard Classification of Status in Employment (ICSE-93). Status in employment refers to the type of explicit or implicit contract of employment the person has with other persons or organizations. The basic criteria used to define the groups of the classification are the type of economic risk and the type of authority over establishments and other workers which the job incumbents have or will have. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. Data for 1991-2016 are estimates while 2017-2021 data are projections. The dataset was updated as of November 2017. For more information, refer to the ILO estimates and projections methodological note.

The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data are disaggregated by status in employment according to the latest version of the International Standard Classification of Status in Employment (ICSE-93). Status in employment refers to the type of explicit or implicit contract of employment the person has with other persons or organizations. The basic criteria used to define the groups of the classification are the type of economic risk and the type of authority over establishments and other workers which the job incumbents have or will have.

The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.

The employment-to-population ratio expresses the number of persons who are employed as a percent of the total working age population.

The employment-to-population ratio expresses the number of persons who are employed as a percent of the total working age population. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. Data for 1991-2016 are estimates while 2017-2021 data are projections. The dataset was updated as of November 2017. For more information, refer to the indicator description and the ILO estimates and projections methodological note.

The employment-to-population ratio is the number of persons who are employed as a percent of the total of working age population.

The employment-to-population ratio is the number of persons who are employed as a percent of the total of working age populion. Data by level of education are provided on the highest level of education completed.

The employment-to-population ratio is the number of persons who are employed as a percent of the total of working age population.

The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.

The employment-to-population ratio expresses the number of persons who are employed as a percent of the total working age population. Data provided only refers to males.

The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.

The employment-to-population ratio expresses the number of persons who are employed as a percent of the total working age population. Data provided only refers to females.

The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. For more information, refer to the ILO estimates and projections methodological note.

Data cited at: Statistics Finland http://www.stat.fi/index_en.html Publication: 005 -- Energy import and export by country, % http://pxnet2.stat.fi/PXWeb/pxweb/en/StatFin/StatFin__ene__ehk/statfin_ehk_pxt_005_en.px License: http://creativecommons.org/licenses/by/4.0/ Revisions in these statistics Description kuvaus Consepts and definitions *Year preliminary

Data cited at: Statistics Finland http://www.stat.fi/index_en.html Publication: 006 -- Energy import and export by country, proportion % http://pxnet2.stat.fi/PXWeb/pxweb/en/StatFin/StatFin__ene__ehk/statfin_ehk_pxt_006_en.px License: http://creativecommons.org/licenses/by/4.0/ Revisions in these statistics Description kuvaus Consepts and definitions *Year preliminary

Data cited at: Statistics Finland http://www.stat.fi/index_en.html Publication: 004 -- Energy import and export by country http://pxnet2.stat.fi/PXWeb/pxweb/en/StatFin/StatFin__ene__ehk/statfin_ehk_pxt_004_en.px License: http://creativecommons.org/licenses/by/4.0/ Revisions in these statistics Description Consepts and definitions *Year preliminary

This dataset presents the number of students enrolled in different education programmes by country of origin and sex.

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

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.

The estimated resident population (ERP) is the official measure of the Australian population. This dataset contains annual ERP by country of birth, age and sex at the Australia level. At the state/territory level it is available for Census years only. Population_Estimates:_Concepts,_Sources_and_Methods_2009

The estimated resident population (ERP) is the official measure of the Australian population. This dataset contains annual ERP by country of birth, age and sex at the Australia level. At the state/territory level it is available for Census years only.

Recent exchange rate movements have been unusually large, triggering a debate regarding their likely effects on trade. Historical experience in advanced and emerging market and developing economies suggests that exchange rate movements typically have sizable effects on export and import volumes. A 10 percent real effective depreciation in an economy’s currency is associated with a rise in real net exports of, on average, 1.5 percent of GDP, with substantial cross-country variation around this average. Although these effects fully materialize over a number of years, much of the adjustment occurs in the first year. The boost to exports associated with currency depreciation is found to be largest in countries with initial economic slack and with domestic financial systems that are operating normally. Some evidence suggests that the rise of global value chains has weakened the relationship between exchange rates and trade in intermediate products used as inputs into other economies’ exports. However, the bulk of global trade still consists of conventional trade, and there is little evidence of a general trend toward disconnect between exchange rates and total exports and imports.

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

If a search in the StatBank does not return any result, this does not necessarily mean that there is no trade in this particular period. A zero (0) could also imply that the value is less than half of the unit used. A colon (:) in the Statbank implies that the figures can not be published separately, due to confidentiality.A colon (:) in the Statbank implies that the figures can not be published separately, due to confidentiality. Within the SITC classification group 03 'Fish, crustaceans, molluscs and other aquatic invertebrates', Statistics Norway has grouped everything by species based on the product groups in the HS nomenclature. Some discrepancies may occur since not all product groups are specified by species. The group 'Other fish' is the sum of the remaining product groups under SITC 03. From 2006 on the following countries had their belonging to continent changed - Cyprus from Asia to Europe, and Armenia, Georgia, Kyrgyzstan, Kazakhstan, Tajikistan, Turkmenistan and Uzbekistan from Europe to Asia. The total for Trade are/continent includes this change - while in the selections of countries in the pull-down menu for European/Asian countries it is the present classification that will be shown for the whole time period (Cypros belonging to Europe and the other countries to Asia). Statistics Norway do not publish figures for the trade region previously Comecon after 2011. For more information, see About the statistics For the years 2007 and 2008 the commodity numbers 03.03.5200 and 03.05.5107 has erroneously been placed in the group 'Other fish'. This has been corrected from 21.01.2013. Monthly figures are released on the 15th of the month after the observation period (the previous month), or the first subsequent working day. These figures are preliminary. Corresponding yearly figures are published together with the monthly figures for December. With regard to the current year, all the monthly figures are updated in every publication. Final figures for the preceding year are released twice. For the first time in May the following year, while the corrected final figures are published in May one year later. commodity group Shrimps Due to confidentiality in group 'Shrimps' from 2013 on, exports in this group can not be published separately. This group is therefore included in commodity group 'Other crustaceous animals except shrimps and mollusk'. The suppression is visualized by a colon (:) in the Statbank. Other crustacean/mollusc Due to confidentiality in group 'Shrimps' from 2013 on, exports in this group can not be published separately. This group is therefore included in commodity group 'Other crustaceous animals except shrimps and mollusk'. The suppression is visualized by a colon (:) in the Statbank. country All countries Figures for 'Total fish, crustaceous animals and mollusc', 'Torsk' and 'Other fish' for 2013 were corrected at 19:00 17 January 2014. EU Croatia is included in the trade with the EU from 2014 on. Palestine (2013-) Previously: West Bank/Gaza Stripe (2001-2012) year 2017 The figures were corrected 25 January 2018.

Air pollution is considered one of the most pressing environmental and health issues across OECD countries and beyond. According to the World Health Organisation (WHO), exposure to fine particulate matter (PM2.5) has potentially the most significant adverse effects on health compared to other pollutants. PM2.5 can be inhaled and cause serious health problems including both respiratory and cardiovascular disease, having its most severe effects on children and elderly people. Exposure to PM2.5 has been shown to considerably increase the risk of heart disease and stroke in particular. For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator. The underlying PM2.5 concentrations estimates are taken from van Donkelaar et al. (2016). They have been derived using satellite observations and a chemical transport model, calibrated to global ground-based measurements using Geographically Weighted Regression at 0.01° resolution. The underlying population data, Gridded Population of the World, version 4 (GPWv4) are taken from the Socioeconomic Data and Applications Center (SEDAC) at the NASA. The underlying boundary geometries are taken from the Global Administrative Unit Layers (GAUL) developed by the FAO, and the OECD Territorial Classification, when available. The current version of the database presents much more variation with respect to the previous one. The reason is that the underlying concentration estimates previously included smoothed multi-year averages and interpolations; while in the current version annual concentration estimates are used. Establishing trends of pollution exposure should be done with care, especially at smaller output areas, as their inputs (e.g. underlying data and models) can change from year to year. We recommend using a 3-year moving average for visualisation.

Debt figures for countries significantly or highly vulnerable to debt distress. All GDP and debt statistics reflect 2016 or end-2016 values, with the exception of the lending pipeline, which reflects estimated values post-2016. Data citation: John Hurley, Scott Morris, and Gailyn Portelance. 2018. “Examining the Debt Implications of the Belt and Road Initiative from a Policy Perspective.” CGD Policy Paper. Washington, DC: Center for Global Development. https://www.cgdev.org/publication/examining-debt-implications-belt-and-roadinitiative-policy-perspective

This table presents information on the external long-term indebtedness of developing economies (as debtors), expressed in millions of dollars, expressed as percentage of total long-term debt, as percentage of debt source and as percentage of region. The table also provides breakdown of public and publicly guaranteed debt by source of lending (as creditors).

If a search in the StatBank does not return any result, this does not necessarily mean that there is no trade or that the country code is not valid in the particular period. A zero (0) could also imply that the figures are confidential or that the value is less than half of the unit used. From 2006 on the following countries had their belonging to continent changed - Cyprus from Asia to Europe, and Armenia, Georgia, Kyrgyzstan, Kazakhstan, Tajikistan, Turkmenistan and Uzbekistan from Europe to Asia. The total for Trade are/continent includes this change - while in the selections of countries in the pull-down menu for European/Asian countries it is the present classification that will be shown for the whole time period (Cypros belonging to Europe and the other countries to Asia). Statistics Norway do not publish figures for the trade region previously Comecon after 2011. For more information, see About the statistics Monthly figures are released on the 15th of the month after the observation period (the previous month), or the first subsequent working day. These figures are preliminary. Corresponding yearly figures are published together with the monthly figures for December. With regard to the current year, all the monthly figures are updated in every publication. Final figures for the preceding year are released twice. For the first time in May the following year, while the corrected final figures are published in May one year later. country EU Croatia is included in the trade with the EU from 2014 on. Palestine (2013-) Previously: West Bank/Gaza Stripe (2001-2012)

If a search in the StatBank does not return any result, this does not necessarily mean that there is no trade or that the country code is not valid in the particular period. A zero (0) could also imply that the figures are confidential or that the value is less than half of the unit used. From 2006 on the following countries had their belonging to continent changed - Cyprus from Asia to Europe, and Armenia, Georgia, Kyrgyzstan, Kazakhstan, Tajikistan, Turkmenistan and Uzbekistan from Europe to Asia. The total for Trade are/continent includes this change - while in the selections of countries in the pull-down menu for European/Asian countries it is the present classification that will be shown for the whole time period (Cypros belonging to Europe and the other countries to Asia). Statistics Norway do not publish figures for the trade region previously Comecon after 2011. For more information, see About the statistics Monthly figures are released on the 15th of the month after the observation period (the previous month), or the first subsequent working day. These figures are preliminary. Corresponding yearly figures are published together with the monthly figures for December. With regard to the current year, all the monthly figures are updated in every publication. Final figures for the preceding year are released twice. For the first time in May the following year, while the corrected final figures are published in May one year later. country EU Croatia is included in the trade with the EU from 2014 on. Palestine (2013-) Previously: West Bank/Gaza Stripe (2001-2012)

Methodological explanationsSymbols used Source: State Statistical Office Year 2018M12 preliminary data

Methodological explanationsSymbols used Source: State Statistical Office Year 2018 preliminary data

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

1.Following the recommendation of experts gathered in the Committee on World Food Security (CFS) Round Table on hunger measurement, hosted at FAO headquarters in September 2011, an initial set of indicators aiming to capture various aspects of food insecurity is presented here. 2.The choice of the indicators has been informed by expert judgment and the availability of data with sufficient coverage to enable comparisons across regions and over time. Many of these indicators are produced and published elsewhere by FAO and other international organizations. They are reported here in a single database with the aim of building a wide food security information system. More indicators will be added to this set as more data will become available. Note: Data represent values for time periods (1999-2001,2000-02,2005-07) and is shown as data for the last year of time period 2001, 2002,2007

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

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

Producer Price Indices - AnnualIndices of agricultural producer prices measure the average annual change over time in the selling prices received by farmers (prices at the farm-gate or at the first point of sale). Annual data are provided for over 80 countries. The three categories of producer price indices available in FAOSTAT comprise: Single-item price indices, Commodity group indices and the Agriculture producer price index.

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

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

The labour force comprises all persons of working age who furnish the supply of labour for the production of goods and services during a specified time-reference period. It refers to the sum of all persons of working age who are employed and those who are unemployed. The working-age population is commonly defined as persons aged 15 years and older, but this varies from country to country. The series is part of the ILO estimates and is harmonized to account for differences in national data and scope of coverage, collection and tabulation methodologies as well as for other country-specific factors. Data for 1990-2015 are estimates while 2016-2030 data are projections. The dataset was updated as of July 2017. For more information, refer to the ILO estimates and projections methodological note.

Data refers to the number of women employed in the agricultural sector as a percent of total employment in agriculture

Data refers to the number of women employed in the industry sector as a percent of total employment in industry.

The female share of employment in managerial positions conveys the number of women in management as a percentage of employment in management. Employment in management is defined based on the International Standard Classification of Occupations. Two different measures are presented: one referring to total management (category 1 of ISCO-08 or ISCO-88), and another one referring to senior and middle management only, thus excluding junior management (category 1 in both ISCO-08 and ISCO-88 minus category 14 in ISCO-08 and minus category 13 in ISCO-88). This indicator is calculated based on data on employment by sex and occupation. For further information, see the SDG Indicators Metadata Repository or ILOSTAT's indicator description.

This indicator refers to the proportion of females in total employment in senior and middle management corresponding to major group 1 in both ISCO-08 and ISCO-88 minus category 14 in ISCO-08 (hospitality, retail and other services managers) and minus category 13 in ISCO-88 (general managers), since these comprise mainly managers of small enterprises. The indicator provides information on the proportion of women who are employed in decision-making and management roles in government, large enterprises and institutions.

Data provided refers to the number of women employed in the services sector as a percent of total employment in services.

The 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.

Monthly updates of FIFA World Football Men's Ranking 

This indicator is a proxy for the quality of health care. It represents the percentage of the population without access to health care due to financial resource deficit. The threshold for having sufficient financial resources is US$239 per person per year. A higher figure indicates worse levels of coverage. To estimate the quality of health care, this indicator uses as a proxy the relative difference between per capita health expenditure in a given country and its median value in countries with a low level of vulnerability.To establish whether a country is spending 'enough' or has 'enough' key health workers, it is necessary first to define what constitutes 'enough', i.e. set a threshold against which a country's performance can be compared. Opinions differ on what constitutes 'enough' in these contexts, not least because it is likely to be a moving target, influenced by prevailing health issues, demography etc. The ILO's approach for measuring financial deficit is to: (i) calculate the median expenditure on health (excluding OOP) in low-vulnerability countries, then (ii) for each country, compare spending against this median. In 2014, the median in low-vulnerability countries was US$239. For example, a country spending 50% less than the median in low-vulnerability countries has a financial deficit of 50%. This is one of five indicators measuring key dimensions of deficits in health care access and coverage. For analytical purposes the full set of indicators should be considered together.

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

The Reporting entities dataset provides information on the structure, size, and coverage of the financial institutions that are used for compiling financial soundness indicators. It provides a better understanding of the structure of the reporting entities in terms of the type of institution, number of entities, size of assets, and type of control. Reporting entities are domestically incorporated entities but are divided into two: domestically controlled and foreign controlled. The concepts of residency criterion and control are determined based on FSI Guide methodology which is in line with international best practices such as Systems of National Accounts. Data on reporting entities cover the branches, subsidiaries and the value of asset for both domestically and foreign controlled entities resident in the reporting country together their resident and non-resident subsidiaries.

Data cited at: Statistics Finland http://www.stat.fi/index_en.html Publication: 004 -- International trade in services by region, 1 000 000 euros http://pxnet2.stat.fi/PXWeb/pxweb/en/StatFin/StatFin__kan__tpulk/statfin_tpulk_pxt_004.px License: http://creativecommons.org/licenses/by/4.0/ The statistics on international trade in goods and services cover international trade in balance of payments terms on the quarterly level. The statistics form a link for goods trade in customs and balance of payments terms, describe the breakdown of quarterly trade in services, and indicate the total exports of goods and services by area. . = Category not applicable. .. = Data not available or too uncertain for presentation, or subject to secrecy. Description of statistics Concepts and definitionsRegion Region and statesYear Year.Data Import The value of imports, 1 000 000 euros.Export The value of exports, 1 000 000 euros.

Data cited at: Statistics Finland http://www.stat.fi/index_en.html Publication: 004 -- Population by main type of activity, nationality, occupational status, sex, age and year 2000-2017* http://pxnet2.stat.fi/PXWeb/pxweb/en/StatFin/StatFin__vrm__tyokay/statfin_tyokay_pxt_004.px License: http://creativecommons.org/licenses/by/4.0/ The figures in the tables are final. Description of statistics Concepts and definitions Classifications .. = Data not available or too uncertain for presentation, or subject to secrecy. From 2005, the employment pension insurance includes those aged 18 to 68, while previously the obligation to take out pension insurance for employees already started from the age of 14. This is visible in the employment statistics from 2005 onwards as a fall in employment by young people and a rise in the number of students. Statistics cannot be compiled reliably on employment by under-age people on the basis of register data. Citizenships are specified in the table if the number of people in the citizenship group exceeds 99. © Tilastokeskus - Statistics Finland

Data cited at: Statistics Finland http://www.stat.fi/index_en.html Publication: 008 -- Nationality according to age and sex by region in 1990 to 2017 http://pxnet2.stat.fi/PXWeb/pxweb/en/StatFin/StatFin__vrm__vaerak/statfin_vaerak_pxt_008.px License: http://creativecommons.org/licenses/by/4.0/ Concepts and definitions Description Quality description These statistics apply the regional division of 1 January 2018 to the whole time series. Population statistics from 1750 to 2000 have been digitised into PDF format in the National Library's Doria service. Publications on Population structure in Doria (in Finnish) Publications on Vital statistics in Doria (in Finnish) Publications on Population censuses in Doria (in Finnish)Nationality If a person has two nationalities and one of them is Finnish, he/she will be included in statistics as a Finnish national. The used classification of continents is the classification of Eurostat, where Cyprus and Turkey belong to Europe. Citizens of non-autonomous states are summed under the mother country.Nationality Czech Republic Czech Republic + Former CzechoslovakiaSudan Sudan + Former Sudan

Data cited at: Statistics Finland http://www.stat.fi/index_en.html Publication: 009 -- Finnish citizens with dual nationality by age and second nationality in 2000 to 2017 http://pxnet2.stat.fi/PXWeb/pxweb/en/StatFin/StatFin__vrm__vaerak/statfin_vaerak_pxt_009.px License: http://creativecommons.org/licenses/by/4.0/ Concepts and definitions Description Quality description Population statistics from 1750 to 2000 have been digitised into PDF format in the National Library's Doria service. Publications on Population structure in Doria (in Finnish) Publications on Vital statistics in Doria (in Finnish) Publications on Population censuses in Doria (in Finnish) Second nationality If a person has two nationalities and one of them is Finnish, he/she will be included in statistics as a Finnish national. Second nationality Czech Republic Czech Republic + Former Czechoslovakia Sudan Sudan + Former Sudan

The IMF’s Fiscal Decentralization Dataset compiles indicators widely used by academics and policymakers to assess recent trends, conduct benchmark analysis, and identify the causes, and consequences of fiscal decentralization for a global sample of IMF members.   Fiscal decentralization indicators are computed using fiscal data on flows and stocks of the general government sector disaggregated between central and subnational government subsectors (state/provincial/regional, and local) measured within the framework of the Government Finance Statistics Manual, 2014.

IRMA is computed on one representative ton of the food aid basket the user has selected. The "representativity" of the ton comes from the fact that the shares of the commodities are the same as those in the total selected food basket. Therefore it can be used for comparisons among food aid baskets of different size and in understanding how much of their difference in nutritional content is due to the absolute value in metric tons of the donations and how much is due to the nutritional qualities of food delivered.   IRMA, IRMAs and IRMAt provide only information on their 'nutritional potential' of meeting average requirements.

The energy intake of a human being is the only one among the nutrients that cannot in the short run be renounced without putting at immediate risk the possibility of survival itself. A lack of other nutrients increases susceptibility to infections and slows cognitive development and growth, contributing to poorer school performance and reduced work productivity. These effects are largely irreversible and long term, particularly when they occur at a young age. For these reasons, the IRMAs computation takes the content of Energy as a benchmark to compare with the other nutrients' content. For the calculation of IRMAs, we start with the IRMA values for each nutrient. IRMA of a nutrient counts the number of average individuals that could potentially be satisfied by the nutrient contained in a ton of food aid.   IRMA, IRMAs and IRMAt provide only information on their 'nutritional potential' of meeting average requirements.

IRMAt (Individual Requirements Met on Average, Total) can be considered an alternative measure for food aid deliveries. By knowing how many tons of which commodity are contained in the food aid basket, it is easy to compute how many micrograms of nutrients there are in the overall basket. But, a measure like that would not be easy to interpret. Furthermore, each nutrient is measured in a different unit (for example, vitamin C is measured in micrograms and fat is measured in grams). IRMAt 'standardizes' the nutritional content of food aid by taking it as a percentage of human nutritional requirements. IRMAt of a nutrient is nothing but the number of individual requirements that could potentially be met on an annual basis by the total food aid deliveries selected. IRMAt values are descriptive of a food aid basket and are dependent on the absolute value in tonnage. They give information that reflects both nutritional content and the size of the food aid deliveries. From this point of view IRMAt can be considered a unit of measurement for food aid flows: it measures food aid basket by the number of average individuals that its nutritional content could potentially satisfy.   IRMA, IRMAs and IRMAt provide only information on their 'nutritional potential' of meeting average requirements.

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

Commodity balances show balances of food and agricultural commodities in a standardized form. The scope of standardization is to present these data in a less detailed form for a selected number of commodities without causing any significant loss of the basic variables monitoring the agricultural sector. The selected commodities include the equivalents of their derived products falling in the same commodity group, but exclude the equivalents of by-products and derived commodities, which through processing, change their nature and become part of different commodity groups. A number of commodity/item aggregates have been included to offer synthetic information. Some of these are included with the aim of simplifying the extraction of all component commodities. Data shown in the item aggregates represent the sum of the component commodities as presented in this domain (standardized form). Commodity coverage: The commodity list in this domain has been generally confined to primary commodities - except for sugar, oils and fats and beverages. Whenever possible trade in processed commodities is expressed in the originating primary commodity equivalent. Rice is expressed in milled equivalent.

Food supply data is some of the most important data in FAOSTAT. In fact, this data is for the basis for estimation of global and national undernourishment assessment, when it is combined with parameters and other data sets. This data has been the foundation of food balance sheets ever since they were first constructed. The data is accessed by both business and governments for economic analysis and policy setting, as well as being used by the academic community.

Food supply data is some of the most important data in FAOSTAT. In fact, this data is for the basis for estimation of global and national undernourishment assessment, when it is combined with parameters and other data sets. This data has been the foundation of food balance sheets ever since they were first constructed. The data is accessed by both business and governments for economic analysis and policy setting, as well as being used by the academic community.

The number of students enrolled refers to the count of students studying in the reference period. Each student enrolled in the education programmes covered by the corresponding category is counted once and only once. National data collection systems permitting, the statistics reflect the number of students enrolled at the beginning of the school / academic year. Preferably, the end (or near-end) of the first month of the school / academic year is chosen (special arrangements are made for part-year students who may not start studies at the beginning of the school year). Students are classified as foreign students (non-citizens) if they are not citizens of the country in which the data are collected. While pragmatic and operational, this classification is inappropriate for capturing student mobility because of differing national policies regarding the naturalisation of immigrants. Countries that have lower propensity to grant permanent residence to its immigrant populations are likely to report second generation immigrants as foreign students. Therefore, for student mobility and bilateral comparisons, interpretations of data based on the concept of foreign students should be made with caution. Students are classified as international students if they left their country of origin and moved to another country for the purpose of study. Depending on country-specific immigration legislation, mobility arrangements, and data availability, international students may be defined as students who are not permanent or usual residents of their country of study or alternatively as students who obtained their prior education in a different country, including another EU country.

This dataset contains information on foreign direct investment (FDI) inward and outward flows and stock, expressed in millions of dollars. These figures correspond to the Statistical Annexes of the UNCTAD World Investment Report. The World Investment Report, which is released in June each year (t), contains annual data up to the year before (t-1). However, at the time of publication, the data for the most recent year are still preliminary and are subject to revision by the national authorities. When they revise data, UNCTAD updates its database accordingly. The dataset also presents the following indicators: the percentage share of each economy/group in the world, and percentage ratios of FDI to GDP. Foreign direct investment (FDI) is an investment made by a resident enterprise in one economy (direct investor or parent enterprise) with the objective of establishing a lasting interest in an enterprise that is resident in an another economy (direct investment enterprise or foreign affiliate). The lasting interest implies the existence of a long-term relationship between the direct investor and the direct investment enterprise and a significant degree of influence on the management of the enterprise. The ownership of 10% or more of the voting power of a direct investment enterprise by a direct investor is evidence of such a relationship. FDI flows comprise mainly three components:acquisition or disposal of equity capital. FDI includes the initial equity transaction that meets the 10% threshold and all subsequent financial transactions and positions between the direct investor and the direct investment enterprise;reinvestment of earnings which are not distributed as dividends;inter-company debt. FDI flows are transactions recorded during the reference period (typically year or quarter). FDI stocks are the accumulated value held at the end of the reference period (typically year or quarter). In 2014, many countries implemented the new guidelines for the compilation of FDI data based on the Sixth edition of the Balance of Payments and International Investment Position Manual (BPM6) and the Fourth edition of OECD Benchmark Definition of Foreign Direct Investment (BD4). One of the major changes introduced in BPM6 and BD4 is the presentation of FDI statistics on an asset/liability basis instead of the directional principle (as recommended by the previous editions of these guidelines). On an asset/liability basis, direct investment statistics are organized according to whether the investment relates to an asset or a liability for the reporting country. Under the directional principle, the direct investment statistics are organized according to the direction of the investment for the reporting country - either inward or outward. The two presentations differ in their treatment of reverse investment (reverse investment is when an affiliate provides loans to its parent). Under the directional presentation, reverse investment is subtracted to derive the total outward or inward investment of the reporting economy. Therefore, FDI statistics on an asset/liability basis tends to be higher than those under the directional principle, but such is not always the case. While the presentation on an asset/liability basis is appropriate for macroeconomic analysis (i.e. the impact on the balance of payments), the presentation on directional principle is more appropriate to assist policymakers and government officials to formulate investment policies. This is because the presentation of the FDI data on directional basis reflects the direction of influence by the foreign direct investor underlying the direct investment: inward or outward direct investment. FDI data in this table are on directional principle, unless otherwise indicated

The statistics cover only goods exported to and imported from the economic territory of the Republic of China (Taiwan, Penghu, Kinmen and Matsu). Fish caught and sold overseas by national fishing vessels are also included in exports.Total Exports = Exports + Re-exports, Total Imports = Imports + Re-imports.Exports/re-exports is based on F.O.B. value. Imports/re-imports is based on C.I.F value.The same currency exchange rate from NT dollar to US dollar is applied to either imports/re-imports or exports/re-exports, which is the midpoint between selling and buying rates announced by Customs every 10 days in a month for filling Customs declaration purpose.Notes:  1. Prior to 2015, the value of exports includes bunker oil for the use of national vessels, aircrafts and other means of conveyance engaged in international trade. 2. Prior to 1998, the value of exports and imports by Continent/Country excludes re-exports and re-imports.   2019 values are year to date

World Bank/WTO/UNCTAD - Annual Trade in Services Dataset

Data cited at: https://senegal.opendataforafrica.org/SNFT2015

This dataset covers the following public data available at RBI website. 1. Direction of Foreign Trade (in USD $ RS.) Notes: Financial Year 2015-2016 and 2016-2017 is taken as 2016, 2017

Foreign Trade, Iran

Data cited at: https://uaenumbers.fcsa.gov.ae/UAEITSS2018U3

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

World and National CO2 Emissions from Fossil-Fuel Burning, Cement Manufacture, and Gas Flaring. Source: Tom Boden, Gregg Marland and Bob Andres (Oak Ridge National Laboratory)

The FSI focuses on the indicators of risk and is based on thousands of articles and reports that are processed by our CAST Software from electronically available sources. Measures of fragility, like Demographic Pressures,Refugees and IDPs and etc., have been scaled on 0 to 10 where 10 is highest fragility and 0 no fragility.

Freedom in the World is Freedom House’s flagship annual report, assessing the condition of political rights and civil liberties around the world. It is composed of numerical ratings and supporting descriptive texts for many countries. Freedom in the World has been published since 1973, allowing Freedom House to track global trends in freedom over more than 40 years. It has become the most widely read and cited report of its kind, used on a regular basis by policymakers, journalists, academics, activists, and many others.

Variables converted from character to numeric as follow:Variables under consideration are top 3 vars i.e. Status, print and Broadcast 1 = Free (F) 2 = Partly Free (PF) 3 = Not Free (NF) Under source it values are present like: "F" , "PF" and "NF"  Note:- Date range has been considered as follow: Jan.1981-Aug.1982 is considered as 1982 Aug.1982-Nov.1983 is considered as 1983 Nov.1983-Nov.1984 is considered as 1984 Nov.1984-Nov.1985 is considered as 1985 Nov.1985-Nov.1986 is considered as 1986 Nov.1986-Nov.1987 is considered as 1987   About Freedom of the press: Freedom of the Press, an annual report on media independence around the world which assesses the degree of print, broadcast, and digital media freedom in 199 countries and territories. Published since 1980, it provides numerical scores and country narratives evaluating the legal environment for the media, political pressures that influence reporting, and economic factors that affect access to news and information. Freedom of the Press is the most comprehensive data set available on global media freedom and serves as a key resource for policymakers, international institutions, journalists, activists, and scholars worldwide.

The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level. As part of this study, estimates for obesity and overweight prevalence and the disease burden attributable to high body mass index (BMI) were produced by sex, age group, and year for 195 countries and territories. Estimates for high BMI-attributable deaths, DALYs, and other measures (1990-2015) are available from the GBD Results Tool. Files available in this record include obesity and overweight prevalence estimates for 1980-2015. Study results were published in The New England Journal of Medicine in June 2017 in "Health Effects of Overweight and Obesity in 195 Countries over 25 Years."

The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level. As part of this study, estimates for daily smoking prevalence and smoking-attributable mortality and disease burden, as measured by disability-adjusted life years (DALYs), were produced by sex, age group, and year for 195 countries and territories. Estimates for deaths and DALYs (1990-2015) are available from the GBD Results Tool. Files available in this record include daily smoking prevalence (1980-2015) and annualized rate of change estimates. Study results were published in The Lancet in April 2017 in "Smoking prevalence and attributable disease burden in 195 countries and territories, 1990–2015: a systematic analysis from the Global Burden of Disease Study 2015." Date ranges have been considered as follows: 1990-2015 as 1990 1990-2005 as 2005 2005-2015 as 2015

The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level. This dataset measures progress towards the Millennium Development Goal 5 (MDG 5) target of a 75% reduction in the maternal mortality ratio between 1990 and 2015. Maternal mortality ratio estimates for 21 regions, 195 countries and territories and 4 United Kingdom subnational units for 1990-2015 (quinquennial) are available by age and cause from the GBD Results Tool. Files available in this record include tables published in The Lancet in October 2016 in "Global, regional, and national levels of maternal mortality, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015.

The Global Burden of Disease Study 2017 (GBD 2017), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries. Developed by GBD researchers and used to help produce these estimates, the Socio-demographic Index (SDI) is a composite indicator of development status strongly correlated with health outcomes. It is the geometric mean of 0 to 1 indices of total fertility rate under the age of 25 (TFU25), mean education for those ages 15 and older (EDU15+), and lag distributed income (LDI) per capita. As a composite, a location with an SDI of 0 would have a theoretical minimum level of development relevant to health, while a location with an SDI of 1 would have a theoretical maximum level. This dataset provides tables with SDI values for all estimated GBD 2017 locations for 1950–2017 and groupings by location based on their 2017 values.

Data cited at: Global Database of Events, Language, and Tone   The GDELT Event Database records over 300 categories of physical activities around the world, from riots and protests to peace appeals and diplomatic exchanges, georeferenced to the city or mountain top, across the entire planet dating back to January 1, 1979 and updated every 15 minutes. Essentially it takes a sentence like "The United States criticized Russia yesterday for deploying its troops in Crimea, in which a recent clash with its soldiers left 10 civilians injured" and transforms this blurb of unstructured text into three structured database entries, recording US CRITICIZES RUSSIA, RUSSIA TROOP-DEPLOY UKRAINE (CRIMEA), and RUSSIA MATERIAL-CONFLICT CIVILIANS (CRIMEA). Nearly 60 attributes are captured for each event, including the approximate location of the action and those involved. This translates the textual descriptions of world events captured in the news media into codified entries in a grand "global spreadsheet."

National accounts are a coherent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. The data presented in this collection are the results of a pilot exercise on the sharing selected main GDP aggregates, population and employment data collected by different international organisations. It wasconducted by the Task Force in International Data Collection (TFIDC) which was established by the  Inter-Agency Group on Economic and Financial Statistics (IAG).  The goal of this pilot is to develop a set of commonly shared principles and working arrangements for data cooperation that could be implemented by the international agencies. The data sets are an experimental exercise to present national accounts data form various countries across the globe in one coherent folder, but users should be aware that these data are collected and validated by different organisations and not fully harmonised from a methodological point of view.  The domain consists of the following collections:

This dataset includes gender inequality and development indices.

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 GID-DB is a database providing researchers and policymakers with key data on gender-based discrimination in social institutions. This data helps analyse women’s empowerment and understand gender gaps in other key areas of development.Covering 180 countries and territories, the GID-DB contains comprehensive information on legal, cultural and traditional practices that discriminate against women and girls.

This table provides information on the main relevant indicators. The data have mainly been supplied by the World Bank, and cover, where available: -Current Gross National Income (GNI) in US $ millions; -GNI per capita (US $); -Population; -Energy use as kilogram of oil per capita; -Average Life Expectancy of Adults; and -Adult Literacy Rate as a percentage of the country population. Data for Sudan include South Sudan, with the exception of total population, which is reported separately.

Bilateral ODA commitments by purpose. Data cover the years 2005 to 2009. Amounts are expressed in USD million. The sectoral distribution of bilateral ODA commitments refers to the economic sector of destination (i.e. the specific area of the recipient's economic or social structure whose development is, or is intended to be fostered by the aid), rather than to the type of goods or services provided. These are aggregates of individual projects notified under the Creditor Reporting System, supplemented by reporting on the sectoral distribution of technical co-operation, and on actual disbursements of food and emergency aid.

The aim of the Index is both to capture the multidimensional nature of the quality of life and wellbeing of older people, and to provide a means by which to measure performance and promote improvements. We have chosen 13 different indicators for the four key domains of Income security, Health status, Capability, and Enabling environment. Domain 1: Income security The income security domain assesses people's access to a sufficient amount of income, and the capacity to use it independently, in order to meet basic needs in older age. Domain 2: Health status The three indicators used for the health domain provide information about physical and psychological wellbeing. Domain 3: Capability The employment and education indicators in this domain look at different aspects of the empowerment of older people. Domain 4: Enabling environment This domain uses data from Gallup World View to assess older people's perception of social connectedness, safety, civic freedom and access to public transport - issues older people have singled out as particularly important.

This database contains statistics on production volume and value by species, country or area, fishing area and culture environment

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Global Bilateral Migration Database Publication: https://datacatalog.worldbank.org/dataset/global-bilateral-migration-database License: http://creativecommons.org/licenses/by/4.0/   Global Bilateral Migration Database: Global matrices of bilateral migrant stocks spanning the period 1960-2000, disaggregated by gender and based primarily on the foreign-born concept are presented. Over one thousand census and population register records are combined to construct decennial matrices corresponding to the last five completed census rounds. For the first time, a comprehensive picture of bilateral global migration over the last half of the twentieth century emerges. The data reveal that the global migrant stock increased from 92 to 165 million between 1960 and 2000. South-North migration is the fastest growing component of international migration in both absolute and relative terms. The United States remains the most important migrant destination in the world, home to one fifth of the world’s migrants and the top destination for migrants from no less than sixty sending countries. Migration to Western Europe remains largely from elsewhere in Europe. The oil-rich Persian Gulf countries emerge as important destinations for migrants from the Middle East, North Africa and South and South-East Asia. Finally, although the global migrant stock is still predominantly male, the proportion of women increased noticeably between 1960 and 2000.

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

Contains the volume of fish catches landed by country or territory of capture, by species or a higher taxonomic level, by FAO major fishing areas, and year for all commercial, industrial, recreational and subsistence purpose

Data cited at: Boden et al. (2017), UNFCCC (2018), BP (2018) 

This database contains statistics on the annual production of fishery commodities and imports and exports of fishery commodities by country and commodities in terms of volume and value from 1976.

DHL released the fifth edition of the DHL Global Connectedness Index (GCI) – a detailed analysis of globalization, measured by international flows of trade, capital, information and people. The new GCI report represents the first comprehensive assessment of developments in globalization across 169 countries and territories since the Brexit referendum in the United Kingdom and the 2016 presidential election in the United States. In spite of growing anti-globalization tensions in many countries, connectedness reached an all-time high in 2017, as the flows of trade, capital, information and people across national borders all intensified significantly for the first time since 2007. Strong economic growth boosted international flows while key policy changes such as US tariff increases had not yet been implemented.

Data cited at: Global Corruption Barometer (2013) by Transparency International is licensed under CC-BY-ND 4.0 Global Corruption Barometer is the largest world-wide public opinion survey on corruption - See more at: http://www.transparency.org/gcb2013/in_detail#sthash.hey9okGH.dpuf

  The Global Cybersecurity Index (GCI) is a survey that measures the commitment of Member States to cybersecurity in order to raise awareness. The GCI revolves around the ITU Global Cybersecurity Agenda (GCA) and its five pillars (legal, technical, organizational, capacity building and cooperation). For each of these pillars, questions were developed to assess commitment. Through consultation with a group of experts, these questions were weighted in order to arrive at an overall GCI score. The survey was administered through an online platform through which supporting evidence was also collected. One-hundred and thirty-four Member States responded to the survey throughout 2016. Member States who did not respond were invited to validate responses determined from open-source research. As such, the GCI results reported herein cover all 193 ITU Member States. The 2017 publication of the GCI continues to show the commitment to cybersecurity of countries around the world. The overall picture shows improvement and strengthening of all five elements of the cybersecurity agenda in various countries in all regions. However, there is space for further improvement in cooperation at all levels, capacity building and organizational measures. As well, the gap in the level of cybersecurity engagement between different regions is still present and visible. The level of development of the different pillars varies from country to country in the regions, and while commitment in Europe remains very high in the legal and technical fields in particular, the challenging situation in the Africa and Americas regions shows the need for continued engagement and support. In addition to providing the GCI score, this report also provides a set of illustrative practices that give insight into the achievements of certain countries.

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

Research by the Global Burden of Disease Health Financing Collaborator Network produced retrospective national health spending estimates for 1995-2016 for 184 countries. The estimates cover total health spending, and health spending disaggregated by source into government spending, out-of-pocket, prepaid private, and development assistance for health. National health spending by source, including development assistance for health, was estimated based on a diverse set of data, including program reports, budget data, national estimates, and 964 National Health Accounts. The resulting estimates were used to help produce forecasted health spending estimates for. Results of the study were published in The Lancet in April 2017 in "Evolution and patterns of global health financing 1995–2016: development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries."

Project LINK is an international collaborative research group for econometric modelling, coordinated jointly by the Development Policy and Analysis Division of UN/DESA and the University of Toronto. Each year, a UN/DESA Expert Group Meeting on the World Economy, also known as the Project LINK Meeting, is held in October to discuss the world economic outlook. The meeting is participated in by a wide range of experts from academia, economic research institutions and international economic organizations as well as colleagues from the five regional commissions: Economic Commission for Africa (ECA), Economic Commission for Europe (ECE), Economic Commission for Latin America and the Caribbean (ECLAC), Economic and Social Commission for Asia and the Pacific (ESCAP) and Economic and Social Commission for Western Asia (ESCWA).

The energy subsidy estimates reported here are based on the broad notion of post-tax subsidies, which arise when consumer prices are below supply costs plus a tax to reflect environmental damage and an additional tax applied to all consumption goods to raise government revenues. Pre-tax subsidies, which arise when consumer prices are below supply costs, are also reported as a component of post-tax subsidies. These subsidies will not necessarily coincide with definitions used by governments or with their reported subsidy numbers. The energy subsidy estimates are not available for the following countries in 2013: Bhutan, Central African Republic, Chad, Comoros, Eritrea, Fiji, Gambia, Guinea, Guinea-Bissau, Kiribati, Kosovo, Lao P.D.R., Liberia, Maldives, Marshall Islands, Mauritius, Micronesia, Niger, Palau, Samoa, San Marino, São Tomé and Príncipe, Seychelles, Sierra Leone, Solomon Islands, South Sudan, St. Lucia, St. Vincent and the Grenadines, Swaziland, Timor-Leste, Tonga, Tuvalu, and Vanuatu. In 2015, estimates are not available for two addtional countries: Burundi and Togo.

Environmental Indicators disseminate global environment statistics on ten indicator themes compiled from a wide range of data sources. The themes and indicator tables were selected based on the current demands for international environmental statistics and the availability of internationally comparable data. Indicator tables, charts and maps with relatively good quality and coverage across countries, as well as links to other international sources, are provided under each theme. Statistics on Water and Waste are based on official statistics supplied by national statistical offices and/or ministries of environment (or equivalent institutions) in response to the biennial UNSD/UNEP Questionnaire on Environment Statistics, complemented with comparable statistics from OECD and Eurostat, and water resources data from FAO Aqua stat. Statistics on other themes were compiled by UNSD from other international sources. In a few cases, UNSD has made some calculations in order to derive the indicators. However, generally no adjustments have been made to the values received from the source. UNSD is not responsible for the quality, completeness/availability, and validity of the data. Environment statistics is still in an early stage of development in many countries, and data are often sparse. The indicators selected here are those of relatively good quality and geographic coverage. Information on data quality and comparability is given at the end of each table together with other important metadata.

Research by the Global Burden of Disease Health Financing Collaborator Network produced projected health spending estimates for 2016-2040 for 188 countries. The estimates cover total health spending, and health spending disaggregated by source into government spending, out-of-pocket, prepaid private, and development assistance for health. GDP and all-sector government spending were extracted for 1980–2015 and used with retrospective health spending estimates for 1995-2015 to forecast GDP, all-sector government spending, and health spending through 2040. Results of the study were published in The Lancet in April 2018 in "Trends in future health financing and coverage: future health spending and universal health coverage in 188 countries,."

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

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

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.  The dataset help us to know about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Contains global production statistics (capture and aquaculture). This database contains the volume of aquatic species caught by country or area, by species items, by FAO major fishing areas, and year, for all commercial, industrial, recreational and subsistence purposes. The harvest from mariculture, aquaculture and other kinds of fish farming is also included

DescriptionThe Global Forest Resources Assessment 2015 (FRA 2015) is the most comprehensive assessment of forests and forestry to date - not only in terms of the number of countries and people involved - but also in terms of scope. It examines the current status and recent trends for about 90 variables covering the extent, condition, uses and values of forests and other wooded land, with the aim of assessing all benefits from forest resources. Information has been collated from 233 countries and territories for four points in time: 1990, 2000, 2005 and 2010. The results are presented according to the seven thematic elements of sustainable forest management. FAO worked closely with countries and specialists in the design and implementation of FRA 2010 - through regular contact, expert consultations, training for national correspondents and ten regional and subregional workshops. More than 900 contributors were involved, including 178 officially nominated national correspondents and their teams. The outcome is better data, a transparent reporting process and enhanced national capacity in developing countries for data analysis and reporting. The final report of FRA 2010 was published at the start of the latest biennial meeting of the FAO' Committee on Forestry and World Forest Week, in Rome.

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

Emissions are calculated for the following substances: 1) Direct greenhouse gases: Carbon Dioxide (CO2), Methane (CH4), Nitrous Oxide (N2O), Hydrofluorocarbons (HFC-23, 32, 125, 134a, 143a, 152a, 227ea, 236fa, 245fa, 365mfc, 43-10-mee), Perfluorocarbons (PFCs: CF4, C2F6, C3F8, c-C4F8, C4F10, C5F12, C6F14, C7F16), Sulfur Hexafluoride (SF6), Nitrogen Trifluoride (NF3) and Sulfuryl Fluoride (SO2F2); 2) Ozone precursor gases: Carbon Monoxide (CO), Nitrogen Oxides (NOx), Non-Methane Volatile Organic Compounds (NMVOC) and Methane (CH4). 3) Acidifying gases: Ammonia (NH3), Nitrogen oxides (NOx) and Sulfur Dioxide (SO2). 4) Primary particulates: Fine Particulate Matter (PM10) - Carbonaceous speciation (BC , OC) is under progress. 5) Stratospheric Ozone Depleting Substances: Chlorofluorocarbons (CFC-11, 12, 113, 114, 115), Halons (1211, 1301, 2402), Hydrochlorofluorocarbons (HCFC-22, 124, 141b, 142b), Carbon Tetrachloride (CCl4), Methyl Bromide (CH3Br) and Methyl Chloroform (CH3CCl2). Emissions (EM) for a country C are calculated for each compound x on an annual basis (y) and sector wise (for i sectors, multiplying on the one hand the country-specific activity data (AD), quantifying the human activity for each of the i sectors, with the mix of j technologies (TECH) for each sector i, and with their abatement percentage by one of the k end-of-pipe (EOP) measures for each technology j, and on the other hand the country-specific emission factor (EF) for each sector i and technology j with relative reduction (RED) of the uncontrolled emission by installed abatement measure k. Emissions in are calculated by individual countries using country-specific information. The countries are organized in different world regions for illustration purposes. Emissions of some small countries are presented together with other countries depending on country definition and availability of activity statistics.

The GHO data provides access to indicators on priority health topics including mortality and burden of diseases, the Millennium Development Goals (child nutrition, child health, maternal and reproductive health, immunization, HIV/AIDS, tuberculosis, malaria, neglected diseases, water and sanitation), non communicable diseases and risk factors, epidemic-prone diseases, health systems, environmental health, violence and injuries, equity among others.

Global Hunger Index, 2018   The Global Hunger Index (GHI) is a tool designed to comprehensively measure and track hunger globally, regionally, and by country. Each year, the International Food Policy Research Institute (IFPRI) calculates GHI scores in order to assess progress, or the lack thereof, in decreasing hunger. The GHI is designed to raise awareness and understanding of regional and country differences in the struggle against hunger. Since 2015, GHI scores have been calculated using a revised and improved formula. The revision replaces child underweight, previously the sole indicator of child under-nutrition, with two indicators of child under-nutrition—child wasting and child stunting—which are equally weighted in the GHI calculation. The revised formula also standardizes each of the component indicators to balance their contribution to the overall index and to changes in the GHI scores over time. GHI scores are calculated using a three-step process that draws on available data from various sources to capture the multidimensional nature of hunger: 1. Undernourishment: The share of the population that is undernourished (that is, whose caloric intake is insufficient). 2. Child wasting and stunting: The share of children under the age of five who are wasted (that is, who have low weight for their height, reflecting acute under-nutrition). 3.Child Stunting: The share of children under the age of five who are stunted (that is, who have low height for their age, reflecting chronic under-nutrition). 4. Child Mortality: The mortality rate of children under the age of five (in part, a reflection of the fatal mix of inadequate nutrition and unhealthy environments).   Note: Values for the years are taken as per below table.1Global Hunger Index Scores2Proportion of Undernourished in the Population (%)3Prevalence of Wasting in Children Under Five Years(%)4Prevalence of Stunting in Children Under Five Years (%)5Prevalence of underweight in children under five years (%)   Date for above indicators are taken as per below year ranges. 1   2   3   4   5   Date Range Date Range Date Range Date Range Date Range 2018 2013-2017 2018 2015-2017 2018 2013-2017 2018 2013-2017 2012 2009-2013 2017 2012-2016 2017 2014-2016 2017 2012-2016 2017 2012-2016 2011 2008-2012 2015 2010-2016 2015 2014-2016 2015 2012-2016 2015 2012-2016 2010 2005-2010 2014 2009-2013 2013 2014-2016 2013 2010-2014 2013 2010-2014 2009 2004-2009 2013 2008-2012 2012 2011-2013 2010 2008-2012 2010 2008-2012 2008 2003-2008 2012 2005-2010 2011 2010-2012 2008 2006-2010 2008 2006-2010 2007 2002-2007 2011 2004-2009 2010 2009-2011 2005 2003-2007 2005 2003-2007 2006 2001-2006 2010 2008-2012 2009 2005-2007 2000 1998-2002 2000 1998-2002 2005 2003-2007 2009 2002-2007 2008 2007-2009 1995 1993-1997 1995 1993-1997 2004 2000-2005 2008 2006-2010 2007 2003-2005 1992 1990-1994 1992 1990-1994 2003 1999-2003 2005 2003-2007 2006 2002-2004 1990 1988-1992 1990 1988-1992 2000 1998-2002 2001 1994-1998 2005 2004-2006         1997 1993-1998 2000 1998-2002 2004 2001-2003         1995 1993-1997 1996 1988-1992 2003 2000-2002         1990 1988-1992 1995 1993-1997 2000 1999-2001         1980 1977-1982 1992 1990-1994 1997 1995-1997             1990 1988-1992 1995 1994-1996                 1992 1991-1993                 1990 1990-1992                 1980 1979-1981               6. "Under-five Mortality  Rate(%)" year range has not been specified in source. GHI Severity Scale ≤ 9.9 low 10.0–19.9 moderate 20.0–34.9 serious 35.0–49.9 alarming 50.0 ≤ extremely alarming

The Global Innovation Index (GII) provides detailed metrics about the innovation performance of 126 countries which represent 90.8% of the world’s population and 96.3% of global GDP. Its 80 indicators explore a broad vision of innovation, including political environment, education, infrastructure and business sophistication.   The GII 2018 marks the 11th edition of the GII, and the beginning of its second decade providing data and insights gathered from tracking innovation across the globe. This year’s edition, is dedicated to the theme of Energizing the World with Innovation. It analyses the energy innovation landscape of the next decade and identifies possible breakthroughs in fields such as energy production, storage, distribution, and consumption. It also looks at how breakthrough innovation occurs at the grassroots level and describes how small-scale renewable systems are on the rise.

Global Internal Displacement Database (GIDD) aims to provide comprehensive information on internal displacement worldwide. It covers all countries and territories for which IDMC has obtained data on situations of internal displacement, and provides data on situations of internal displacement associated with conflict and generalized violence (2014-2015), displacement associated with sudden-onset natural hazard-related disasters (2008-2015).

The global Multidimensional Poverty Index (MPI) is an international measure of acute poverty covering over 100 developing countries. It complements traditional income-based poverty measures by capturing the severe deprivations that each person faces at the same time with respect to education, health and living standards. The MPI assesses poverty at the individual level. If someone is deprived in a third or more of ten (weighted) indicators (see left), the global index identifies them as ‘MPI poor’, and the extent – or intensity – of their poverty is measured by the number of deprivations they are experiencing. The MPI can be used to create a comprehensive picture of people living in poverty, and permits comparisons both across countries, regions and the world and within countries by ethnic group, urban/rural location, as well as other key household and community characteristics. This makes it invaluable as an analytical tool to identify the most vulnerable people – the poorest among the poor, revealing poverty patterns within countries and over time, enabling policy makers to target resources and design policies more effectively. The global MPI was developed by OPHI with the UN Development Programme (UNDP) for inclusion in UNDP’s flagship Human Development Report in 2010. It has been published in the HDR ever since.    

GPSS data (Accounts & Access, retail payment transactions and RTGS transactions – volumes and values). The World Bank’s Global Payment Systems Survey (GPSS) surveys national and regional central banks and monetary authorities on the status of payment systems. The GPSS is the only global survey that combines quantitative and qualitative measures of payment system development and covers all aspects of national payment systems – from infrastructure and the legal and regulatory environment to technological and business model innovations, international remittances, and oversight framework. The GPSS aims to take an accurate snapshot of payment systems worldwide to obtain information on payment system reforms and the factors which hinder and/or facilitate them in order to help guide policy-dialogue at the international and national levels, and World Bank Group technical assistance. In April 2007, the World Bank launched the first Global Payment Systems Survey among national central banks to collect information on the situation of national payment and securities settlement systems worldwide and provide a payment systems snapshot of both advanced and emerging economies in order to identify main issues that should guide the agenda of authorities, multilateral and market players in the field over the next few years.

Data cited at: Institute for Economics and Peace The Global Peace Index 2018 report finds that the global level of peace has deteriorated by 0.27% over the last year. This is the fourth successive year of deterioration, finding that 92 countries have deteriorated, while 71 countries have improved. The report reveals a world in which tensions, conflicts and crises that have emerged over the past decade remain unresolved, causing a gradual, sustained decline in global levels of peacefulness.

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

Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013. Comparable estimates based on systematically identified surveys, reports, and published studies (n=1769) that included data for height and weight, both through physical measurements and self-reports, using mixed effects linear regression to correct for bias in self-reports. Data for prevalence of obesity and overweight by age, sex, country, and year (n=19 244) obtained with a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs). Research by the staff of the Institute for Health Metrics and Evalutaion with co-authors. Published online 28 May 2014, "The Lancet" Volume 384, No. 9945, p766–781. DOI: http://dx.doi.org/10.1016/S0140-6736(14)60460-8

Note: The dataset has been collected from "Global status report on road safety 2018".  For this report, 2018 data were used for the review of vehicle standards; 2017 data were used for the review of legislation, road standards and post-crash care; fatality estimates were based on data from 2016. The Global status report on road safety 2018, launched by WHO in December 2018, highlights that the number of annual road traffic deaths has reached 1.35 million. Road traffic injuries are now the leading killer of people aged 5-29 years. The burden is disproportionately borne by pedestrians, cyclists and motorcyclists, in particular those living in developing countries. The report suggests that the price paid for mobility is too high, especially because proven measures exist. These include strategies to address speed and drinking and driving, among other behaviors; safer infrastructure like dedicated lanes for cyclists and motorcyclists; improved vehicle standards such as those that mandate electronic stability control; and enhanced post-crash care. Drastic action is needed to put these measures in place to meet any future global target that might be set and save lives.

The Global status report on violence prevention 2014, which reflects data from 133 countries, is the first report of its kind to assess national efforts to address interpersonal violence, namely child maltreatment, youth violence, intimate partner and sexual violence, and elder abuse. Jointly published by WHO, the United Nations Development Programme, and the United Nations Office on Drugs and Crime, the report reviews the current status of violence prevention efforts in countries, and calls for a scaling up of violence prevention programmes; stronger legislation and enforcement of laws relevant for violence prevention; and enhanced services for victims of violence.

Intentional homicide is defined as unlawful death purposefully inflicted on a person by another person

Covers data on corporate, indirect and individual income tax rates throughout 163 countries across the world during the period from 2006 to 2018. Provided by KPMG.

Data cited at: Institute for Economics and Peace   The Global Terrorism Index (GTI) is a comprehensive study which accounts for the direct and indirect impact of terrorism in 163 countries in terms of its effect on lives lost, injuries, property damage and the psychological aftereffects of terrorism. This study covers 99.6 per cent of the world’s population. It aggregates the most authoritative data source on terrorism today, the Global Terrorism Database (GTD) collated by the National Consortium for the Study of Terrorism and Responses to Terrorism (START) into a composite score in order to provide an ordinal ranking of nations on the negative impact of terrorism. The GTD is unique in that it consists of systematically and comprehensively coded data on domestic as well as international terrorist incidents and now includes more than 140,000 cases. Note: "Change in score values" have been calculated for 2015 by score in 2015 minus score in 2014 (Score_2015-Score_2014). For rest of the years according to source.

This dataset shows indicators of trade balances as the following: - Normalized trade balance, - Trade balance as percentage of imports and, - Trade balance as percentage of nominal gross domestic product (GDP). Normalized trade balance (NTB) of goods and services is defined as the trade balance (total exports less total imports) divided by the total trade (exports plus imports).   NTB=(EX-IM)/EX+IM)

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

National Accounts of Costa Rica

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

This dataset provides an overview of government’s cash flows, as summarized in the Statement of Sources and Uses of Cash, for those countries compiling GFS on a noncash basis (for example, an accrual basis) and are also including a cash flow statement.

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

This dataset provides an overview of total financial assets and liabilities classified by the sector to which the counterpart claim belongs. The counterpart sectors include non-financial corporations, the central bank, deposit taking corporations, other financial corporation sectors, government sectors, international organizations, external financial corporations, external general government, and other external sectors.

This dataset provides a comprehensive view of the integrated balance sheet. In other words, changes between the opening and closing stock positions in assets and liabilities are explained through transactions, holding gains/losses, and other changes in the volume of assets and liabilities. Data on net investment in non-financial assets – a component of total expenditure – on its components and related stock positions are provided.

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

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: GPE Results Forms Database Publication: https://datacatalog.worldbank.org/dataset/gpe-results-forms-database License: http://creativecommons.org/licenses/by/4.0/   The data originate from the education goals of developing-country partners of the Global Partnership for Education (GPE). Indicators compare actual values observed against targets, as set in education sector plans, joint sector reviews, and GPE grant applications. Indicators present key education outcomes and service delivery data; domestic, external, and GPE financing; learning outcomes; the composition of the Local Education Groups; and aid effectiveness in the education sector.

This dataset contains selected indicators for monitoring progress towards green growth to support policy making and inform the public at large. The indicator bring together the OECD's statistics, indicators and measures of progress. The dataset covers OECD countries as well as BRIICS economies (Brazil, Russian Federation, India, Indonesia, China and South Africa), and selected countries when possible. The indicators are selected according to well specified criteria and embedded in a conceptual framework, which is structured around four groups to capture the main features of green growth: Environmental and resource productivity, to indicate whether economic growth is becoming greener with more efficient use of natural capital and to capture aspects of production which are rarely quantified in economic models and accounting frameworks; The natural asset base, to indicate the risks to growth from a declining natural asset base; Environmental quality of life, to indicate how environmental conditions affect the quality of life and wellbeing of people; Economic opportunities and policy responses, to indicate the effectiveness ofpolicies in delivering green growth and describe the societal responses needed to secure business and employment opportunities.

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

National accounts are a coherent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. The data presented in this collection are the results of a pilot exercise on the sharing selected main GDP aggregates, population and employment data collected by different international organisations. It wasconducted by the Task Force in International Data Collection (TFIDC) which was established by the  Inter-Agency Group on Economic and Financial Statistics (IAG).  The goal of this pilot is to develop a set of commonly shared principles and working arrangements for data cooperation that could be implemented by the international agencies. The data sets are an experimental exercise to present national accounts data form various countries across the globe in one coherent folder, but users should be aware that these data are collected and validated by different organisations and not fully harmonised from a methodological point of view.  The domain consists of the following collections:

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 20.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 20.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 18.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

Global Trade Alert - Trade Coverage Estimates

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.

This dataset presents HNP data by wealth quintile since 1990s to present. It covers more than 70 indicators, including childhood diseases and interventions, nutrition, sexual and reproductive health, mortality, and other determinants of health, for more than 90 low- and middle-income countries. The data sources are Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS).

Global Burden of Disease Study 2016 (GBD 2016) Healthcare Access and Quality Index Based on Amenable Mortality 1990–2016. Global Burden of Disease Study 2016 (GBD 2016) estimates were used in an analysis of personal healthcare access and quality for 195 countries and territories, as well as selected subnational locations, over time. This dataset includes the following global, regional, national, and selected subnational estimates for 1990-2016: age-standardized risk-standardized death rates from 24 non-cancer causes considered amenable to healthcare; age-standardized mortality-to-incidence ratios for 8 cancers considered amenable to healthcare; and the Healthcare Access and Quality (HAQ) Index and individual scores for each of the 32 causes on a scale of 0 to 100. Code used to produce the estimates is also included. Results were published in The Lancet in May 2018 in "Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016

The World Organisation for Animal Health (OIE) data on Highly Pathogenic Avian Influenza in Animals (HPAI, informally known as bird flu). Number of outbreaks, total susceptible animals & animals destroyed and other stats by country.

The Historical Public Debt Database contains unbalanced panel data on Gross Domestic Product, Gross Government Debt, and Gross Government Debt-to-GDP Ratio for 187 countries. The series spans the years 1800 through 2015 although each country’s data depends on its date of independence and data availability. The database was constructed by bringing together a number of other datasets and information from original sources. For the most recent years, the data are linked to the IMF World Economic Outlook (WEO) database to facilitate regular updates.

Historical Statistics on Population, GDP and Per Capita GDP for 1-2008 AD period. Copyright Angus Maddison.

Data cited at: https://mauritius.opendataforafrica.org/HDIM2016

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.

Data cited at: Financial Tracking Service

ICTD Government Revenue Dataset, 2018 A major obstacle to cross-country research on the role of revenue and taxation in development has been the weakness of available data. Government Revenue Dataset (GRD), developed through the International Centre for Tax and Development (ICTD), is aimed at overcoming this obstacle. It meticulously combines data from several major international databases, as well as drawing on data compiled from all available International Monetary Fund (IMF) Article IV reports. It achieves marked improvements in data coverage and accuracy, including a standardized approach to revenue from natural resources, and holds the promise of significant improvement in the credibility and robustness of research in this area. Dataset contains Central, General and merged government revenue data reported as % of GDP.

The World Bank’s IDA Resource Allocation Index (IRAI) is based on the results of the annual CPIA exercise that covers the IDA eligible countries.The CPIA rates countries against a set of 16 criteria grouped in four clusters: (a) economic management; (b) structural policies; (c) policies for social inclusion and equity; and (d) public sector management and institutions. The criteria (pdf) are focused on balancing the capture of the key factors that foster growth and poverty reduction, with the need to avoid undue burden on the assessment process. To fully underscore the importance of the CPIA in the IDA Performance Based Allocations, the overall country score is referred to as the IRAI. 

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: IDA Results Measurement System Publication: https://datacatalog.worldbank.org/dataset/ida-results-measurement-system License: http://creativecommons.org/licenses/by/4.0/   The IDA Results Measurement System dataset measures progress on aggregate outcomes for IDA countries for selected indicators. It includes key country outcome indicators covering areas that are consistent with the Millennium Development Goals, are priorities in many national development plans and/or poverty reduction strategies, and reflect IDA's activities in IDA countries. The indicators capture both the economic growth and the human development priorities of ongoing IDA programs.

Member countries are allocated votes at the time of membership and subsequently for additional subscriptions to capital. Votes are allocated differently in each organization. Each member receives the votes it is allocated under IDA replenishments according to the rules established in each IDA replenishment resolution. Votes consist of subscription votes and membership votes.

IHME results from paper, Worldwide mortality in men and women aged 15–59 years from 1970 to 2010: a systematic analysis, published online in The Lancet on April 30 2010. This dataset provides global estimates of adult mortality risk, 45q15 (probability of death between the ages of 15 years and 60 years), between 1970 and 2010.

IHME results from paper, Neonatal, post neonatal, childhood, and under-5 mortality for 187 countries, 1970-2010: a systematic analysis of progress towards Millennium Development Goal 4, published online in The Lancet on May 24 2010. This dataset provides estimates of neonatal, post neonatal, childhood, and under-5 mortality for 187 countries between 1970 and 2010.

IHME research, published online in The Lancet in April 2010, with data from a global assessment of levels and trends in maternal mortality for the years 1980-2008. The study, Maternal mortality for 181 countries, 1980-2008: a systematic analysis of progress towards Millennium Development Goal 5, provides global, regional, and national level estimates of the maternal mortality ratio (MMR - the number of maternal deaths per 100,000 live births) as well as the number of maternal deaths.

IHME results data from global analysis of maternal mortality for years 1990-2011 published online in The Lancet in September 2011. The study, Progress towards Millennium Development Goals 4 and 5 on maternal and child mortality: an updated systematic analysis, provides global and country level estimates of the maternal mortality ratio (MMR - the number of maternal deaths per 100,000 live births) and the number of maternal deaths.

Covering 187 countries including most low-income countries, the toolkit provides indicators on export product diversification and export product quality from 1962-2010. The measures in this toolkit are based on an updated version of the UN–NBER dataset, which harmonizes COMTRADE bilateral trade flow data at the 4-digit SITC (Rev. 1) level. The export diversification and quality database was developed by IMF staff under an IMF-DFID research collaboration. The Export Diversification Database has three main indicators: the Export Diversification Index, the Extensive Margin, and the Intensive Margin. Higher values for the all three indices indicate lower diversification. The Export Quality Database contains export quality measures across different aggregation levels of export products. Higher values for the quality indices indicate higher quality levels.

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

The World Economic Outlook (WEO) database contains selected macroeconomic data series from the statistical appendix of the World Economic Outlook report, which presents the IMF staff's analysis and projections of economic developments at the global level, in major country groups and in many individual countries. The WEO is released in April and September/October each year. Use this database to find data on national accounts, inflation, unemployment rates, balance of payments, fiscal indicators, trade for countries and country groups (aggregates), and commodity prices whose data are reported by the IMF. Data are available from 1980 to the present, and projections are given for the next two years. Additionally, medium-term projections are available for selected indicators. For some countries, data are incomplete or unavailable for certain years. Changes to the April 2019 Database:  FYR Macedonia is now called North Macedonia. In February 2019, Zimbabwe adopted a new local currency unit, the RTGS dollar, which has become the official unit of account. Efforts are underway to revise and update all national accounts series to the new RTGS dollar. Current data are based on IMF staff estimates of price and exchange rate developments in US (and RTGS) dollars. Staff estimates of US dollar values may differ from authorities’ estimates.    

This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.

The sources for this database are mainly census data, from the 2000 round of censuses. Census data were used for 22 countries. Countries not taking periodic censuses but keeping population registers have provided data extracted from these registers; this is the case for four countries: Denmark, Finland, Norway and Sweden. For some countries, not all themes covered in the database are present in the national census or register. Labour force surveys, provided by Eurostat and averaged over the period 1998-2002, have been used to fill the gaps where possible.

This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.

This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older with a tertiary education.

This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.

The sources for this database are mainly census data, from the 2000 round of censuses. Census data were used for 22 countries. Countries not taking periodic censuses but keeping population registers have provided data extracted from these registers; this is the case for four countries: Denmark, Finland, Norway and Sweden. For some countries, not all themes covered in the database are present in the national census or register. Labour force surveys, provided by Eurostat and averaged over the period 1998-2002, have been used to fill the gaps where possible.

The sources for this database are mainly census data, from the 2000 round of censuses. Census data were used for 22 countries. Countries not taking periodic censuses but keeping population registers have provided data extracted from these registers; this is the case for four countries: Denmark, Finland, Norway and Sweden. For some countries, not all themes covered in the database are present in the national census or register. Labour force surveys, provided by Eurostat and averaged over the period 1998-2002, have been used to fill the gaps where possible. The exact national source and reference period for each file is given in Table A.1 (see the methodological document).

This database contains information on several demographic and labour market characteristics of the population of 28 OECD countries around the year 2000, by country of birth. The OECD countries included are Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. Most of the thematic files of the database include three core variables: the country of residence, the country of birth and educational attainment. Other variables available in the database include age, gender, citizenship, duration of stay, labour force status, occupation, sector of activity and field of study. In general, the database covers all individuals aged 15 and older.

region See list over changes in regional classifications (in Norwegian).

The allocation of bilateral intermediate imports across using industries assumes that import coefficients are the same for all trade partners, i.e. SHAREipkt is identical across exporter countries. Hence, the bilateral pattern of imported intermediates from industry p is the same across all using industries k. However, it is different from the bilateral pattern of total imports from industry p because trade data (measured by VALUEijpt) allows distinguishing bilateral imports of intermediates from final good imports in industry p. While the BEC classification enables the identification of intermediate goods, no similar classification is available for trade in services, due to the high level of aggregation in services trade data. While goods trade data are based on customs declarations allowing the identification of goods at a highly disaggregated level, services trade data are based on a variety of information such as business accounts, administrative sources, surveys, and estimation techniques (Manual on Statistics of International Trade in Services, 2002). Hence, in the case of trade in services, VALUEijpt is the total value of imports of service p, i.e. both final and intermediate (and not only services that are used in the production of other goods and services, as in the case of goods data). By making an additional assumption and adjusting SHAREipkt, it is however possible to calculate trade in intermediate services. In the case of services imports, SHAREipkt is the share of imported service inputs p used by industry k in total imports of p of country i. In the case of services, besides the assumption that all trading partners have the same distribution of intermediate imports p across using industries k, it is furthermore required that the share of intermediate services in overall bilateral services imports of country i is the same across all partner countries j. Finally, it should be mentioned that trade data reported in the trade statistics do not fully match imports as reported in I-O tables. One main reason is that while trade data is recorded at consumer prices, I-O tables are evaluated at producer prices. There are also other differences such as the treatment of re-exports, scrap metal, waste products and second hand goods or unallocated trade data.