Switzerland

Ecuador: Arrival and Departure Statistics

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

This dataset is updated with data obtained from Statistics Canada and the U.S. Census Bureau. 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

OECD Indicators on Carbon dioxide (CO2) emissions embodied in international trade (TeCO2) are derived by combining the 2021 editions of OECD Inter-Country Input-Output (ICIO) Database and of International Energy Agency (IEA) statistics on CO2 emissions from fuel combustion. In this release of TeCO2, emissions from fuels used for international aviation and maritime transport (i.e. aviation and marine bunkers) are also considered.Production-based CO2 emissions are estimated by allocating the CO2 emissions to the 45 target industries in OECD ICIO and, to household final consumption of fuels, by both residents and non-residents.Demand-based CO2 emissions are calculated by multiplying the intensities of the production-based emissions (c) with the global Leontief inverse (I-A)(-1) and global final demand matrix (Y) from OECD ICIO, taking the column sums of the resulting matrix and adding residential and private road emissions (FNLC), i.e. direct emissions from final demand: colsum [ diag(c) (I-A)(-1) Y ] + FNLC.For more information, see TeCO2 web page: http://oe.cd/io-co2.

Merchandise Trade by Commodity, HS-As Reported, Chapter-17   Note: United Nations COMTRADE reports trade in 'net weight in Kg' at the 4-digit level. Knoema aggregated 4-digit reported values from the data source to create 2-digit totals for trade in net weight in Kg. These are not official figures.    

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).

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

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

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

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.

Private transactions are those undertaken by firms and individuals resident in the reporting country. To assist with the transition between systems, we provide a mapping of codes between OECD.Stat (legacy) and the OECD Data Explorer. For more information on these flows, please see the OECD’s main page on development finance statistics, including Frequently Asked Questions (FAQs) on ODA. See the Converged Statistical Reporting Directives governing these data.

The OECD Digital STRI heterogeneity indices complement the recently published Digital STRI's and presents indices of regulatory heterogeneity based on the rich information in the Digital STRI regulatory database. The indices are built from assessing – for each country pair and each measure – whether or not the countries have the same regulation. For each country pair and each sector, the indices reflect the (weighted) share of measures for which the two countries have different regulation.

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

For more information, refer to the International Labour Migration Statistics (ILMS) database description.

For more information, refer to the International Labour Migration Statistics (ILMS) database description.

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.

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

This dataset FDI by counterpart area and by economic activity, BMD4 includes inward and outward Foreign Direct Investment (FDI) flows, positions and income by partner country and by economic activity for OECD reporting economies. It is a simplified dataset with fewer breakdowns compared to the other separate datasets specifically dedicated to FDI flows, FDI positions or FDI income by counterpart area, or by economic activity. In this dataset, FDI exclude resident SPEs, when they exist (unless otherwise stated, see metadata attached at the reporting country level); and inward FDI positions are allocated to the ultimate counterpart country when available (see metadata attached at the reporting country level). Inward and outward FDI statistics in this dataset are presented on a directional basis (unless otherwise stated, see metadata attached at the reporting country level); they are measured in USD millions, in millions of national currency and as a share of total (for FDI positions only). This dataset supports FDI indicators by counterpart area and by economic activity available from the OECD Data Portal. In 2014, many countries implemented the latest international standards for Foreign Direct Investment (FDI) statistics:the OECD’s Benchmark Definition of FDI, 4th edition (BMD4); andthe IMF’s Balance of Payments and International Investment Position Manual, 6th edition (BPM6) This OECD database was launched in March 2015 which includes the data series reported by national experts according to BMD4. The data are for the most part based on balance of payments statistics published by Central Banks and Statistical Offices following the recommendations of the IMF’s BPM6 and the OECD’s BMD4. However, some of the data relate to other sources such as notifications or approvals.

This dataset FDI by counterpart area and by economic activity, BMD4 and historical BMD3 includes long time series of FDI statistics by partner country and by industry. It uses available BMD4 series and combines them with BMD3 historical series (from the unrevised OECD FDI datasets according to BMD3) as far back as 2005 and identifies breaks in series. For selected countries, breaks in series were removed as there was no significant impact of BMD4 implementation. In this dataset, inward and outward FDI flows, positions and income include resident SPEs when they exist (unless otherwise stated, see metadata attached at the reporting country level); and they are allocated to the immediate counterpart country (unless otherwise specified, see metadata attached at the reporting country level). Inward and outward FDI statistics in this datset are presented on a directional basis (unless otherwise stated, see metadata attached at the reporting country level); they are measured in USD millions, in millions of national currency and as a share of total (for FDI positions only). In 2014, many countries implemented the latest international standards for Foreign Direct Investment (FDI) statistics:the OECD’s Benchmark Definition of FDI, 4th edition (BMD4); andthe IMF’s Balance of Payments and International Investment Position Manual, 6th edition (BPM6) This OECD database was launched in March 2015 which includes the data series reported by national experts according to BMD4. The data are for the most part based on balance of payments statistics published by Central Banks and Statistical Offices following the recommendations of the IMF’s BPM6 and the OECD’s BMD4. However, some of the data relate to other sources such as notifications or approvals.

This dataset FDI flows by counterpart area, BMD4 includes inward and outward Foreign Direct Investment (FDI) flows by partner country for OECD reporting economies: Inward FDI flows by partner country measure the value of cross-border direct investment transactions received by the reporting economy during a year, by source country, enabling, for example, the identification of the major sources of FDI for a specific OECD economy in that year. Inward FDI flows are allocated to the immediate investing country. Outward FDI flows by partner country measure the value of cross-border direct investment transactions from the reporting economy during a year, by destination country or region, enabling, for example, the identification of the major destinations of FDI for a specific OECD economy in that year. Outward FDI flows are allocated to the immediate counterpart country for all OECD countries. Inward and outward FDI flows by partner country are presented according to the directional principle (unless otherwise specified in the country level metadata); they are measured in USD millions and in millions of national currency.

This dataset FDI income by counterpart area, BMD4 includes Foreign Direct Investment (FDI) payments and receipts by partner country for OECD reporting economies:FDI income payments (or income on inward FDI) by partner country measure the total returns within a year on direct investment stocks paid by enterprises in the reporting economy to their foreign investors, by destination countries or regions, enabling, for example, the identification of the major destinations of FDI income payments for a specific OECD economy in that year. FDI income payments are allocated to the immediate counterpart country.FDi income receipts (or income on outward FDI) by partner country measure the total returns within a year on direct investment stocks received by investors in the reporting economy from their direct investment enterprises abroad, by source countries or region, enabling, for example, the identification of the major sources of FDI income receipts for a specific OECD economy in that year.. FDI income receipts are allocated to the immediate counterpart country or region for all OECD countries. Income payments and receipts (or income on inward and outward FDI respectively) by partner country are presented according to the directional principle (unless otherwise specified in the country level metadata); they are measured in USD millions and in millions of national currency.

This dataset FDI positions by counterpart area, BMD4 includes inward and outward Foreign Direct Investment (FDI) positions by partner country for OECD reporting economies:Inward FDI positions by partner country measure the total level of direct investment in the reporting economy at the end of the year, by source countries, enabling, for example, the identification of the major sources of FDI for a specific OECD economy. Inward FDI positions are allocated to the immediate investing country but inward FDI positions allocated to the ultimate investing country are also available for some OECD economies.Outward FDI positions by partner country measure the total level of direct investment from the reporting economy at the end of the year, by destination countries, enabling, for example, the identification of the major destinations of FDI for a specific OECD economy. Outward FDI positions are allocated to the immediate counterpart country for all OECD countries. Inward and outward FDI positions by partner country are presented according to the directional principle (unless otherwise specified in the country level metadata); they are measured in USD millions, in millions of national currency and as a share of total FDI positions. In 2014, many countries implemented the latest international standards for Foreign Direct Investment (FDI) statistics:the OECD’s Benchmark Definition of FDI, 4th edition (BMD4); andthe IMF’s Balance of Payments and International Investment Position Manual, 6th edition (BPM6) This OECD database was launched in March 2015 which includes the data series reported by national experts according to BMD4. The data are for the most part based on balance of payments statistics published by Central Banks and Statistical Offices following the recommendations of the IMF’s BPM6 and the OECD’s BMD4. However, some of the data relate to other sources such as notifications or approvals. Historical and unrevised series of FDI positions by counterpart area under the previous BMD3 methodology can be accessed in the archived dataset FDI positions by partner country.

This dataset FDI positions by economic activity, BMD4 includes inward and outward Foreign Direct Investment (FDI) positions by economic activity according to ISIC4 for OECD reporting economies:Inward FDI positions by economic activity measure the total level of direct investment in a specific industry of the reporting economy at the end of the year, enabling, for example, the identification of the most attractive industry sectors for FDI in each OECD economy.Outward FDI positions by economic activity measure the total level of direct investment from the reporting economy at the end of the year, by industry sector. The industry sector corresponds to the activity of the direct investment enterprise or to the activity of the direct investor (more details on the activity allocation method for outward FDI positions are indicated in the metadata information attached at the country level). Inward and outward FDI positions by economic activity are presented according to the directional principle (unless otherwise specified in the country level metadata); they are measured in USD millions, in millions of national currency and as a share of total FDI positions. A cross-classification of inward and outward FDI positions by major ISIC4 sections and by main geographic aggregates are also available for some OECD reporting economies. In 2014, many countries implemented the latest international standards for Foreign Direct Investment (FDI) statistics:the OECD’s Benchmark Definition of FDI, 4th edition (BMD4); andthe IMF’s Balance of Payments and International Investment Position Manual, 6th edition (BPM6) This OECD database was launched in March 2015 which includes the data series reported by national experts according to BMD4. The data are for the most part based on balance of payments statistics published by Central Banks and Statistical Offices following the recommendations of the IMF’s BPM6 and the OECD’s BMD4. However, some of the data relate to other sources such as notifications or approvals. Historical and unrevised series of FDI positions by economic activity under the previous BMD3 methodology can be accessed in the archived dataset FDI positions by industry.

The dataset Fisheries International collaboration in technology development (bilateral) provides the number of co-inventions (simple patent families) developed jointly by at least two inventors. This indicator is disaggregated by: Country - country of residence of the inventor(s), integral counted; in cases when inventors from more than two countries collaborate, this is translated into distinct bilateral relationships between country pairs. For example, if inventors from 3 countries collaborate (e.g. USA, DEU, JPN) then a unit count is assigned to 6 country pairs (USA-DEU, USA-JPN, DEU-JPN, DEU-USA, JPN-USA, JPN-DEU); in this case a country generally coordinate the project and the others are partners. Partner – country of residence of the inventor(s) who collaborate to the patent. Technology domain – the three main areas of innovation in fisheries and aquaculture, related to technology development. In detail: 1. Harvesting technology such as more effective ways to find or harvest fish and which are typically associated with improvements in catch per unit of effort (e.g. type/size of vessels and their methods of propulsion, search technologies, method of catching or harvesting fish and bringing them on board); 2.Aquaculture technology such as methods to more effectively grow fish in captivity (innovation in feeds, improving the health of aquaculture animals, etc.); 3. New products and markets such as the development of new fish products and markets (food technologies/processing such as the development of surimi as a crabmeat substitute) and the improvement of market access (secure or enlarge markets for fish products) that provides important incentives for green growth (e.g. eco-certification with fishers adopting by-catch saving technologies or modifying fishing practices and/or territorial user rights in fisheries).

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.

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.

Direct investment arises when an investor resident in one economy makes an investment that gives control or a significant degree of influence on the management of an enterprise that is resident in another economy. Portfolio investment is defined as cross border transactions and positions involving debt or equity securities, other than those included in direct investment or reserve assets.

Direct investment arises when an investor resident in one economy makes an investment that gives control or a significant degree of influence on the management of an enterprise that is resident in another economy. FDI net inflows are the value of inward direct investment made by non-resident investors in the reporting economy

WTO-UNCTAD-ITC Annual trade in services dataset

Oil and Gas of Mexico

Foreign Trade of Djibouti

International Trade in Commodities in UAE

For more information, refer to the International Labour Migration Statistics (ILMS) database description.

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.

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.

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.

Number of people who graduated from an education programme by age and sex.

ICT goods are those that are either intended to fulfil the function of information processing and communication by electronic means, including transmission and display, OR which use electronic processing to detect, measure and/or record physical phenomena, or to control a physical process. ICT goods are defined by the OECD in terms of the Harmonised System. The guiding principle for the delineation of ICT goods is that such goods must either be intended to fulfil the function of information processing and communication by electronic means, including transmission and display, OR use electronic processing to detect, measure and/or record physical phenomena, or to control a physical process.Another guiding principle was to use existing classification systems in order to take advantage of existing data sets and therefore ensure the immediate use of the proposed standard. In this case, the underlying system is the Harmonized System (HS). The HS is the only commodity classification system used on a sufficiently wide basis to support international data comparison. A large number of countries use it to classify export and import of goods, and many countries use it (or a classification derived from or linked to it) to categorise domestic outputs.The application of the ICT product definition to selection of in-scope HS categories is a somewhat subjective exercise. The fact that the HS is not built on the basis of the functionality of products makes it much more difficult. The distinction between products which fulfil those functions and products that simply embody electronics but fundamentally fulfil other functions is not always obvious.It is possible to adopt a narrow or broad interpretation of the guideline, though the OECD chose a broader interpretation, an approach which is consistent with that adopted to develop the ICT sector definition.

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.

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.

Inbound tourism comprises the activities of a non-resident visitor within the country of reference.

For more information, refer to the International Labour Migration Statistics (ILMS) database description.

Inflow of migrants refer to the number of immigrants who changed their country of usual residence during the reference period. A person's country of usual residence is the country in which the person has a place to live where he or she normally spends the daily period of rest. Temporary travel abroad for purposes of recreation, holiday, business, medical treatment or religious pilgrimage does not entail a change in the country of usual residence. Data are disaggregated by sex and 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).

Inflow of return migrants refers to the number of migrants who returned from a period of residence abroad to live again in their country of citizenship (or country of birth, depending on the context). For more information, refer to the International Labour Migration Statistics (ILMS) database description.

For more information, refer to the International Labour Migration Statistics (ILMS) database description.

As a consequence of the implementation of the new OECD Global Insurance Statistics' framework, there is a break in series between 2008 and 2009 regarding life and non-life business data where composite insurance undertakings exist. Up until 2008, the insurance business is broken down between life and non-life business. As of 2009, the insurance business is broken down between the business of pure life, pure non-life and composite undertakings and composite undertakings' business is further broken down between life and non-life business. Some countries do not allow for insurance undertakings to be active in both life and non-life insurance business and therefore composite insurance undertakings do not exist in these countries. In other countries (e.g., Austria, Belgium, Hungary, Italy, Mexico, Portugal, Spain) however, the share of employment in composite insurance undertakings accounts for more than half of the whole domestic insurance sector. Therefore, to have comparable data across years for life business data (resp. non-life), one has to sum up the life (resp. non-life) business of pure life (resp. non-life) undertakings and the life (resp. non-life) business of composite undertakings as of 2009. Item coverage Covers business written abroad by branches, agencies and subsidiaries established abroad of domestic undertakings and includes all business written outside the country by these entities (in both OECD and non-OECD countries).

This dataset presents patent statistics and indicators that are suitable for tracking innovation in environment-related technologies. They allow the assessment of countries and firms' innovation performance as well as the design of governments' environmental and innovation policies.

FIFA is the international governing body of association football, futsal and beach soccer. Its membership comprises 209 national associations. Its headquarters are in Zurich, Switzerland, and its president is Sepp Blatter. FIFA is responsible for the organisation of football's major international tournaments, notably the World Cup.

This dataset contains the number of people who graduated from an education programme by country of origin and sex.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: ESCAP-World Bank: International Trade Costs Publication: https://datacatalog.worldbank.org/dataset/escap-world-bank-international-trade-costs License: http://creativecommons.org/licenses/by/4.0/   The Trade Costs Dataset provides estimates of bilateral trade costs in agriculture and manufactured goods for the 1995-2015 period. It is built on trade and production data collected in 178 countries. Symmetric bilateral trade costs are computed using the Inverse Gravity Framework (Nov. 2009), which estimates trade costs for each country pair using bilateral trade and gross national output. Trade costs are available for two sectors: trade in manufactured goods, and agriculture. Energy is excluded.

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

The dataset provides a consolidated and reconciled version of multiple sources of bilateral trade data. Its advantages over the original source data are that it provides broader coverage based on mirror flows, reconciliation of aggregate with underlying flows, and consolidation (allowing for broader coverage than offered by source data). One weakness, inherent in all available data of this type, is that even with mirror flows, a substantial share of South-South trade is unreported. As such, while we can recover North-South exports from mirror flows, we cannot recover all unreported bilateral flows. The scale of the problem can be gauged by comparing trade with the world with bilateral flows in the database. Notes: • values are in millions of current US dollars • Because of the apparent mixing of zero and missing by source agencies, we have opted to use missing, or “.”, for reported zero and missing flows. • total with world is the greater of reported total with world, or aggregate of bilateral flows • region XWD holds difference between all bilateral flows and global (trade with world) total. It is the sum of flows with missing partners. This means XWD holds identified flows without a partner. It does not hold flows that are totally unreported. • all unreported REP:PAR:BOP:YEAR combinations, meaning that do not even appear in the dataset, can be safely assumed to be missing. By this, we mean there is no reported source for these flows, and the countries-product-year combination does not even occur in any of the underlying source data.

International Travel and Tourism of Mauritius, by Age Group

This table contains figures on affiliates under foreign control by investing country in the total manufacturing, total services and total business enterprise sectors.

The units used to present data in AFA are millions of national currency for monetary variables and units for the other variables. Monetary variables are in current prices. Euro-area countries: national currency data is expressed in euro beginning with the year of entry into the Economic and Monetary Union (EMU). For years prior to the year of entry into EMU, data have been converted from the former national currency using the appropriate irrevocable conversion rate. This presentation facilitates comparisons within a country over time and ensures that the historical evolution is preserved. Please note, however, that pre-EMU euro are a notional unit and should not be used to form area aggregates or to carry out cross-country comparisons.

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

Merchandise Trade values & Merchandise trade - indices and prices

This table presents merchandise trade complementarity index which assesses the suitability of preferential trade agreement between two economies given the structure of one potential partners’ exports match the imports of the other potential partner. Changes over time may indicate whether the trade profiles are becoming more or less compatible.

International merchandise trade data grouped by Principal Trading Partners (PTP). Users have the option of selecting Imports, Exports, or Trade Balance. Data are unadjusted and seasonally adjusted, and are on a Customs and Balance of Payments basis.   Canada: International merchandise trade for all countries and by Principal Trading Partners, monthly

The dataset provides information on the ownership of the merchant fleet for all countries. "Ownership” refers to “Beneficial Ownership Location”: it indicates the economy in which the company that has the main commercial responsibility for the vessel is located. The economy of beneficial ownership may be different from the country in which the vessel is registered.

Migrants comprise individuals who changed their country of usual residence. A person's country of usual residence is the country in which the person has a place to live where he or she normally spends the daily period of rest. Temporary travel abroad for purposes of recreation, holiday, business, medical treatment or religious pilgrimage does not entail a change in the country of usual residence. 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).

Data source(s) used: Persons registered in and cancelled from the population register due to change of residence:The English description of the source is not available at this time, for methodological details go to the Siqual system

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

This dataset contains monthly Comparative Price Levels (CPL) for OECD countries. CPLs are defined as the ratios of PPPs for private final consumption expenditure to exchange rates. They provide measures of differences in price levels between countries. The monthly PPPs used to derive the table are OECD estimates. The table is to be read vertically. Each column shows the number of specified monetary units needed in each of the countries listed to buy the same representative basket of consumer goods and services. In each case the representative basket costs a hundred units in the country whose currency is specified. Let’s take an example. If you are a Canadian citizen and you want to know the price level in Canada when compared to other countries, you have to look at the column Canada, where the price level is set at 100 for the whole column. If you have 120 for Finland, it means that the price level in Finland is 20% higher than in Canada. It means that you would spend 120 dollars in Finland to buy the same basket of goods and services when you spend 100 in Canada. The monthly PPPs used to derive the table are obtained by extrapolating 2022 PPPs for household final consumption expenditure using the relative rates of inflation between the countries as measured by their consumer price indices. Unless a country is a high inflation country, its PPP will tend to change slowly over time. Month-to-month changes in comparative price levels are more likely to be the result of exchange rate fluctuations. Updated data are available at the beginning of each month. Click here for release dates OECD statistics contact: [email protected]

Nights spent. All hotels, holiday villages, hostels, camping sites, commercially arranged private cottages and apartments by region/county Year 2008 - 2017Please state The Swedish Agency for Economic and Regional Growth and Statistics Sweden as source when publishing information.region0010 Greater StockholmCommercially arranged private cottages and apartments are not included in regions and Sweden excluding metropolitan areas.0020 Greater GothenburgCommercially arranged private cottages and apartments are not included in regions and Sweden excluding metropolitan areas.0030 Greater MalmöCommercially arranged private cottages and apartments are not included in regions and Sweden excluding metropolitan areas.0060 Sweden excluding metropolitan areasCommercially arranged private cottages and apartments are not included in regions and Sweden excluding metropolitan areas.

Nights spend on camping sites by region, nationality of the guest, unit, period and time

Nights spent at hotels and holiday resorts by region, nationality of the guest, type, unit, period and time

Nights spent of all hotels, holiday villages, youth hostels, camping sites and commercially arranged private cottages and apartments by region/county and by country of residence. Month 2008M01 - 2018M12Please state The Swedish Agency for Economic and Regional Growth and Statistics Sweden as source when publishing information.The monthly tables include preliminary statistics and are updated upon each publishing date up until the final statistics for the current year are published. The monthly tables for 2008-2017 refer to final statistics. The final statistics for 2018 will be published in the spring of 2019.As of January 2011 camping grounds are presented as the same country of residence as other types of establishments.regionCommercially arranged private cottages and apartments are not included in regions and other Sweden excluding metropolitan areas.country of residenceCountry of residence refers to the country where the guest, regardless of citizenship, resides permanently (more than 12 months). A Swedish citizen residing abroad is thus presented as a guest from the country of residence.

For more information, refer to the International Labour Migration Statistics (ILMS) database description.

Major change in coverage in 2011. Consult About the statisticsOnly vessels at or above 1,000 gross tonnage. No fishing vessels.

Methodological explanationsSymbols used Source: State Statistical Office

Outbound tourism comprises the activities of residents of a given country travelling to and staying in places outside their country of residence.

The outflows of nationals for any given country refer to the number of its legal citizens who changed their country of usual residence to outside of that country during the reference period. A person's country of usual residence is the country in which the person has a place to live where he or she normally spends the daily period of rest. Temporary travel abroad for purposes of recreation, holiday, business, medical treatment or religious pilgrimage does not entail a change in the country of usual residence. For more information, refer to the International Labour Migration Statistics (ILMS) database description.

The outflows of nationals for employment for any given country refer to the number of its citizens who changed their country of usual residence to outside of that country during the reference period for the purpose of employment. For more information, refer to the International Labour Migration Statistics (ILMS) database description.

This table contains figures on the activity of affiliates located abroad by host country in the total manufacturing, total services and total business enterprise sectors. The units used to present data in AMNE are millions of national currency for monetary variables and units for the other variables. Monetary variables are in current prices. Euro-area countries: national currency data is expressed in euro beginning with the year of entry into the Economic and Monetary Union (EMU). For years prior to the year of entry into EMU, data have been converted from the former national currency using the appropriate irrevocable conversion rate. This presentation facilitates comparisons within a country over time and ensures that the historical evolution is preserved. Please note, however, that pre-EMU euro are a notional unit and should not be used to form area aggregates or to carry out cross-country comparisons.

This table contains figures on the activity of affiliates located abroad by host country in the total manufacturing sector or in the total business sector. The units used to present data in AFA are millions of national currency for monetary variables and units for the other variables. Monetary variables are in current prices. Euro-area countries: national currency data is expressed in euro beginning with the year of entry into the Economic and Monetary Union (EMU). For years prior to the year of entry into EMU, data have been converted from the former national currency using the appropriate irrevocable conversion rate. This presentation facilitates comparisons within a country over time and ensures that the historical evolution is preserved. Please note, however, that pre-EMU euro are a notional unit and should not be used to form area aggregates or to carry out cross-country comparisons.

Zaire, officially the Republic of Zaire, was the name of the Democratic Republic of the Congo between 1971 and 1997.

This dataset covers only Cross-Country-Concepts - Portfolio Investment related indicators. Please visit  Principal Global Indicators - Data by Indicator  for other set of Principal Global Indicators. 

Quantity Reporting: Measure food aid deliveries in metric tons

OECD has extracted monthly trade data from the UN Monthly Comtrade database, and aggregates the quarterly and annual frequencies by summing up the months. This may create discrepancies with annual trade figures as presented in International Trade by Commodity Statistics (ITCS). UN Monthly Comtrade (beta version) contains detailed merchandise trade data provided by countries (or areas) to the United Nations Statistics Division, Department of Economic and Social Affairs (UNSD/DESA). Values are expressed in United States dollars (USD) and refer to declared transaction values. All exports are valued f.o.b. (free on board) and imports are valued c.i.f. (including cost, insurance, freight), except the imports of Canada and Mexico which are valued f.o.b. Detailed country metadata (currency conversion rates, information in HS classifications and data publication dates) can be found from the metadata file at the UN Monthly Comtrade website under the heading Metadata.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Remittance Prices Worldwide Publication: https://datacatalog.worldbank.org/dataset/remittance-prices-worldwide License: http://creativecommons.org/licenses/by/4.0/   Provides data on the cost of sending and receiving relatively small amounts of money from one country to another. Data cover 365 "country corridors" worldwide, from 48 remittance sending countries to 105 receiving countries.

Courtesy: National Science Foundation

The SIGI is built on 27 innovative variables measuring discriminatory social institutions, which are grouped into 4 dimensions: discrimination in the family, restricted physical integrity, restricted access to productive and financial resources, and restricted civil liberties.Lower values indicate lower levels of discrimination in social institutions: the SIGI ranges from 0% for no discrimination to 100% for very high discrimination.

Data source(s) used: Marriages: The survey on marriages, was established in 1926. It's an individual and exhaustive survey, which collects the data of all the marriages celebrated in Italy and the socio-demographic characteristics of the spouses.The survey uses the Istat D.3 model, compiled by the officer of the municipality where the marriage was celebrated. The model is divided into two parts: the first one collects the information about the marriage: the date, the rite of celebration (religious or civil), and the common property regime chosen by the couple (joint or separated ownership of property); the second one collects information about the spouses: date of birth, place of birth, place of residence at the time of marriage, future place of residence of the spouses, marital status, level of education, occupational status, position in the profession, branch of economic activity, citizenship. Other data characteristics: The indicators that do not involve the use of the population (civil weddings - percentage values, joint ownership of property - percentages, marriages with at least one foreign spouse - percentages, second or later marriages - percentages) were calculated according to three different territorial classification:- According to the classification in force in 2017 (107 provinces);- According to the classification in force at the time of the Census of 2011 (110 provinces);- According to the classification in force in the year in which the marriage was celebrated, in the event that was different from that of 2017 and of the Census of 2011 (103 provinces for 2004 and 2005, 107 provinces for the years ranging from 2006 to 2009).

NAM stands for The National Association of Manufacturers Note Annual reports are released twice per year.Initial report in the month of March.Revised report in the month of October.

Note: The data has been discontinued since BP Statistical Review Report has a new custodian: Energy Institute (EI) The BP Statistical Review of World Energy has provided high-quality, objective and globally consistent data on world energy markets. The Review is one of the most widely respected and authoritative publications in the field of energy economics, used for reference by the media, academia, world governments and energy companies. A new edition is published every June. Historical data from 1965 for many sections.

Stock of nationals abroad comprise the persons whose country of usual residence is not the same as their country of origin for any given country of origin. A person's country of residence is the country in which the person has a place to live where he or she normally spends the daily period of rest. 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). For more information, refer to the International Labour Migration Statistics (ILMS) database description.

The OECD STRI heterogeneity indices complement the existing STRI's and presents indices of regulatory heterogeneity based on the rich information in the STRI regulatory database. The indices are built from assessing – for each country pair and each measure – whether or not the countries have the same regulation. For each country pair and each sector, the indices reflect the (weighted) share of measures for which the two countries have different regulation.

Location:-Visitors are coming from mentioned location.(World is total of all visitors) Nationality:-Nationality of visitors, whether the nationality of the visitors is same as the location or they belong to different nationality.(Under this dimension "Total" represents total number of visitors by their nationality) Ports:-Tourist arrival via ports.

Survey on Monitoring the Paris Declaration. The dataset contains data as reported by donors and national co-ordinators in participating partner countries. The dataset includes all quantitative data collected through the 2006, 2008 and 2011 Surveys.

UNECE Clearing House on Migration Statistics is a platform for data exchange on migration statistics for countries of Eastern Europe, Caucasus and Central Asia (EECCA) established with the purpose of improving the understanding migration processes and the systems of measuring migration in the region. The data are presented as submitted by national statistical offices. For more information about the methodology of producing statistics on international migration in EECCA region, please refer to the UNECE Handbook on the Use of Administrative Sources and Sample Surveys to Measure International Migration in CIS Countries and the documentation of UNECE Workshops on Migration Statistics. Country: Armenia Data source: 2001, 2011 - population and housing census; 2015 and onwards - administrative source. Country: Azerbaijan Data source: population and housing census. Country: Belarus The sum of the age groups does not correspond to the ''Total'' since age was unknown for a number of persons. Data source: population and housing census. Country: Georgia Data source: 2002 - population and housing census; 2011 and onwards - administrative source. Country: Kyrgyzstan Data source: population and housing census. Country: Moldova, Republic of ''Other'' includes a number of migrants for which the country is unknown. Data source: population register. Country: Russian Federation In 2010, the sum of the age groups does not correspond to the ''Total'' since the age was unknown for a number of persons. Data source: 2010 - population and housing census. Country: Ukraine In 2001, the sum of the age groups does not correspond to the ''Total'' since age was unknown for a number of persons. The population count does not include the territory of the Autonomous Republic of Crimea and the city of Sevastopol. The General Assembly has addressed the status of the Autonomous Republic of Crimea and the city of Sevastopol in resolution 68/262 of 27 March 2014. Data source: 2001 - population and housing census; 2011 and onwards - the annual estimate of the number of permanent residents as of January 1 carried out by the State Statistics Committee.

UNECE Clearing House on Migration Statistics is a platform for data exchange on migration statistics for countries of Eastern Europe, Caucasus and Central Asia (EECCA) established with the purpose of improving the understanding migration processes and the systems of measuring migration in the region. The data are presented as submitted by national statistical offices. For more information about the methodology of producing statistics on international migration in EECCA region, please refer to the UNECE Handbook on the Use of Administrative Sources and Sample Surveys to Measure International Migration in CIS Countries and the documentation of UNECE Workshops on Migration Statistics. Country: Armenia Data source: 2001, 2011 - population and housing census; 2015 and onwards - administrative source. Country: Azerbaijan Data source: population and housing census. Country: Belarus The sum of the age groups does not correspond to the ''Total'' since age was unknown for a number of persons. Data source: population and housing census. Country: Georgia Data source: 2002 - population and housing census; 2011 and onwards - administrative source. Country: Kyrgyzstan Data source: population and housing census. Country: Moldova, Republic of ''Other'' includes a number of migrants for which the country is unknown. Data source: population register. Country: Russian Federation In 2010, the sum of the age groups does not correspond to the ''Total'' since the age was unknown for a number of persons. Data source: 2010 - population and housing census. Country: Tajikistan Data source: 2000, 2010 - population and housing census; 2011-2014 - source unspecified. Country: Ukraine In 2001, the sum of the age groups does not correspond to the ''Total'' since age was unknown for a number of persons. The population count does not include the territory of the Autonomous Republic of Crimea and the city of Sevastopol. The General Assembly has addressed the status of the Autonomous Republic of Crimea and the city of Sevastopol in resolution 68/262 of 27 March 2014. Data source: 2001 - population and housing census; 2011 and onwards - the annual estimate of the number of permanent residents as of January 1 carried out by the State Statistics Committee.

The total for ''All countries'' includes persons for whom the country of previous residence is unknown.UNECE Clearing House on Migration Statistics is a platform for data exchange on migration statistics for countries of Eastern Europe, Caucasus and Central Asia (EECCA) established with the purpose of improving the understanding migration processes and the systems of measuring migration in the region. The data are presented as submitted by national statistical offices. For more information about the methodology of producing statistics on international migration in EECCA region, please refer to the UNECE Handbook on the Use of Administrative Sources and Sample Surveys to Measure International Migration in CIS Countries and the documentation of UNECE Workshops on Migration Statistics. Definition: Unless noted otherwise, an international migrant is defined as any person who changes his or her country of usual residence. A long-term migrant is a person who moves to a country other than that of his or her usual residence for a period of at least a year. A short-term migrant is a person who moves to a country other than that of his or her usual residence for a period of at least 3 months but less than a year. Country: Armenia In 2001 and 2011 the registered data refer to the date of conducting the Population Census and the number exceeds the total foreign population living in Armenia. Data from 2014 onwards are based on administrative sources. Data source: 2001, 2011 - population and housing census; 2014 and onwards - population register. Country: Azerbaijan Data source: residence permits. Country: Belarus Data source: residence permits. Country: Georgia From 2013, long-term migration refers to those who have left or moved to Georgia for at least 6 months. Data source: 2002 - population and housing census; 2012 and onwards - administrative source. Country: Kazakhstan Data source: 2009 - population and housing census; 2010 and onwards - residence permits. Country: Kyrgyzstan Data source: administrative source. Country: Russian Federation 2011 break in series: the Russian Federation introduced a new methodology for estimating immigration. From 2011 onwards, the source of data on international migration (long-term immigration) is registration at the place of residence and at the place of stay for a period of 9 months or more in the bodies of the Ministry of Internal Affairs of Russia. In 2011 and 2012, the full break down by age and sex is not available for some countries of previous residence. The total flow from each country of previous residence is available. Data source: administrative source. Country: Tajikistan The sum of the age groups does not correspond to the ''Total'' since age was unknown for a number of persons. Data source: administrative source. Country: Ukraine 2001 data include all those who have ever moved. Data source: 2001 - population and housing census; 2011, 2012 - residence permits. Country: Uzbekistan Data from 2011 to 2014 include internal migrants within Uzbekistan. Data source: administrative source.

UNECE Clearing House on Migration Statistics is a platform for data exchange on migration statistics for countries of Eastern Europe, Caucasus and Central Asia (EECCA) established with the purpose of improving the understanding migration processes and the systems of measuring migration in the region. The data are presented as submitted by national statistical offices. For more information about the methodology of producing statistics on international migration in EECCA region, please refer to the UNECE Handbook on the Use of Administrative Sources and Sample Surveys to Measure International Migration in CIS Countries and the documentation of UNECE Workshops on Migration Statistics. The total for ''All countries'' includes persons for whom the country of next residence is unknown. Definition: Unless noted otherwise, an international migrant is defined as any person who changes his or her country of usual residence. A long-term migrant is a person who moves to a country other than that of his or her usual residence for a period of at least a year. A short-term migrant is a person who moves to a country other than that of his or her usual residence for a period of at least 3 months but less than a year. Country: Armenia Data source: 2001, 2011 - population and housing census; 2014 and onwards - population register. Country: Azerbaijan Data source: exit permits. Country: Belarus Data source: residence permits. Country: Georgia From 2013, long-term migration refers to those who have left or moved to Georgia for at least 6 months. Data source: 2002 - population and housing census; 2012 and onwards - administrative source. Country: Kazakhstan Data source: exit permits. Country: Kyrgyzstan For a number of persons the information on the country of next residence is missing in the source. Data source: administrative source. Country: Moldova, Republic of Data source: population register. Country: Russian Federation 2012 break in series: the Russian Federation introduced a new methodology for estimating emigration. From 2012 onwards, the source of data on international migration (long-term emigration) is registration at the place of residence and at the place of stay for a period of 9 months or more. In 2011 and 2012, the full break down by age and sex is not available for some countries of next residence. The total flow from each country of next residence is available. Data source: administrative source. Country: Tajikistan The sum of the age groups does not correspond to the ''Total'' since age was unknown for a number of persons. Data source: administrative source. Country: Ukraine Data source: administrative source. Country: Uzbekistan Data from 2011 to 2014 include internal migrants within Uzbekistan. Data source: administrative source.

UNECE Clearing House on Migration Statistics is a platform for data exchange on migration statistics for countries of Eastern Europe, Caucasus and Central Asia (EECCA) established with the purpose of improving the understanding migration processes and the systems of measuring migration in the region. The data are presented as submitted by national statistical offices. For more information about the methodology of producing statistics on international migration in EECCA region, please refer to the UNECE Handbook on the Use of Administrative Sources and Sample Surveys to Measure International Migration in CIS Countries and the documentation of UNECE Workshops on Migration Statistics. Definition: Unless noted otherwise, an international migrant is defined as any person who changes his or her country of usual residence. A long-term migrant is a person who moves to a country other than that of his or her usual residence for a period of at least a year. A short-term migrant is a person who moves to a country other than that of his or her usual residence for a period of at least 3 months but less than a year. Country: Armenia Data source: 2001, 2011 - population and housing census; 2015 and onwards - population register. Country: Azerbaijan Data indicate the number of persons who obtained a permanent residence permit in Azerbaijan. Azer citizens returning from abroad are not included in the total number. Data source: residence permits. Country: Belarus Data source: residence permits. Country: Georgia From 2013, long-term migration refers to those who have left or moved to Georgia for at least 6 months. Data source: 2002 - population and housing census; 2012 and onwards - border cards. Country: Kyrgyzstan Data source: administrative source. Country: Russian Federation 2011 break in series: the Russian Federation introduced a new methodology for estimating immigration. From 2011 onwards, the source of data on international migration (long-term immigration) is registration at the place of residence and at the place of stay for a period of 9 months or more in the bodies of the Ministry of Internal Affairs of Russia. Data source: administrative source. Country: Ukraine Data source: 2001 - population and housing census; 2011, 2012 - residence permits.

UNECE Clearing House on Migration Statistics is a platform for data exchange on migration statistics for countries of Eastern Europe, Caucasus and Central Asia (EECCA) established with the purpose of improving the understanding migration processes and the systems of measuring migration in the region. The data are presented as submitted by national statistical offices. For more information about the methodology of producing statistics on international migration in EECCA region, please refer to the UNECE Handbook on the Use of Administrative Sources and Sample Surveys to Measure International Migration in CIS Countries and the documentation of UNECE Workshops on Migration Statistics. Definition: Unless noted otherwise, an international migrant is defined as any person who changes his or her country of usual residence. A long-term migrant is a person who moves to a country other than that of his or her usual residence for a period of at least a year. A short-term migrant is a person who moves to a country other than that of his or her usual residence for a period of at least 3 months but less than a year. Country: Armenia Data source: 2011 - population and housing census; 2015 and onwards - population register. Country: Azerbaijan Data indicate the number of persons who obtained an exit permit in Azerbaijan. Azer citizens are not included in the total number. Data source: exit permits. Country: Belarus Data source: residence permits. Country: Georgia From 2013, long-term migration refers to those who have left or moved to Georgia for at least 6 months. Data source: 2002 - population and housing census; 2012 and onwards - border cards. Country: Kyrgyzstan Data source: administrative source. Country: Moldova, Republic of Data source: population register. Country: Russian Federation 2012 break in series: the Russian Federation introduced a new methodology for estimating emigration. From 2012 onwards, the source of data on international migration (long-term emigration) is registration at the place of residence and at the place of stay for a period of 9 months or more. Data source: administrative source. Country: Ukraine Data source: administrative source.

UNECE Clearing House on Migration Statistics is a platform for data exchange on migration statistics for countries of Eastern Europe, Caucasus and Central Asia (EECCA) established with the purpose of improving the understanding migration processes and the systems of measuring migration in the region. The data are presented as submitted by national statistical offices. For more information about the methodology of producing statistics on international migration in EECCA region, please refer to the UNECE Handbook on the Use of Administrative Sources and Sample Surveys to Measure International Migration in CIS Countries and the documentation of UNECE Workshops on Migration Statistics. Country: Azerbaijan Data source: residence permits. Country: Belarus Data source: administrative source. Country: Georgia Data source: civil register. Country: Kyrgyzstan Data source: administrative source. Country: Moldova, Republic of Data source: population register. Country: Russian Federation Data source: administrative source. Country: Ukraine Data source: administrative source.

The UNECE Clearing House on Migration Statistics is a platform for data exchange on migration statistics for countries of Eastern Europe, Caucasus and Central Asia (EECCA), established with the purpose of improving the understanding of migration processes and the systems of measuring migration in the region. The data are presented as submitted by national statistical offices. For more information about the methodology of producing statistics on international migration in EECCA region, please refer to the UNECE Handbook on the Use of Administrative Sources and Sample Surveys to Measure International Migration in CIS Countries and the documentation of UNECE Workshops on Migration Statistics. Country: Azerbaijan Data source: residence permits. Country: Belarus Data source: residence permits. Country: Moldova, Republic of Data source: population register. Country: Tajikistan Disaggregation by sex is only available for people who immigrated for work purposes. Data source: work permits.

Because of the limited availability of official statistics on national supply-use and input-output tables in recent years – reflecting the fact that these are only typically available at best two or three years after the reference period to which they refer – TiVA indicators for the most recent years, as displayed in this dataset, are estimated using now-casting techniques. The approach (described in more detail in the accompanying methodological note) in essence estimates national input-output tables by projecting relationships observed in the latest TiVA benchmark year (currently 2011) into nowcast years (currently 2012-2014) but constrained to official estimates of gross output and value-added by industry and national accounts main aggregates of demand and trade, and supplemented by bilateral trade statistics, all of which are available throughout the nowcast period. Importantly, the projections of relationships in 2011 into 2012 are determined using a volume approach, to account for possible distortions that might be introduced – by for example differential price movements in imports and domestic production – if projections were made using nominal relationships. These estimates are then reflated into current prices, and simultaneously balanced – consistent with official volume and current price estimates of trade, demand and activity – to arrive at a balanced national input-output table in 2012, in nominal terms as well as in prices of 2011. Estimates for 2013 and 2014 are calculated in the same manner but using, respectively, the 2012 and 2013 relationships as the starting point.

The data of the sector includes the number of visitors to by tourist location and category of visitors, and hotel services whose data reflect indicators of the number of guests distributed by hotel, governorate, room type, hotel type, nationality of guests, and hotel revenues by type of service.

This table presents export/import information by enterprise size class and partner country.

This dataset shows the number of exporters and importers and their associated trade values for a selected set of partner countries and zones, broken down by three economic sectors: industry, trade and repair and other sectors. Total values for the wide economy are also displayed.Recommended uses and limitations EU countries break down trade data into Intra- and extra- EU zones, whereas non EU countries report their Total trade. Trade values have been aggregated for EU countries and Total (Intra-EU plus Extra-EU) trade flows are displayed, whereas Intra and Extra-EU data expressed in term of number of enterprises cannot be summed up, because of possible double-counting (same enterprise can be trader in both intra- and extra- EU trade). Data have been collected in ISIC revision 3 from 2003 up to 2007 and in ISIC revision 4 as from reference year 2008. Time series are affected by this change in classification, and thus data are displayed into two separate databases.

Note:  In the 2017 data, figures between 1 and 4 represent situations where the figures are being kept confidential to protect the anonymity of individuals. Such figures are not included in any totals. The UNHCR Population Statistics Database currently contains data about UNHCR's populations of concern from the year 1959 up to 2017. UNHCR identifies seven population categories, collectively referred to as ‘persons of concern’: refugees, asylum-seekers, internally displaced persons (IDPs), refugees who have returned home (returnees), IDPs who have returned home, persons under UNHCR’s statelessness mandate, and others who do not fall under these categories but to whom the agency extends protection. Since 2007, two additional sub-categories have been added: individuals in refugee-like situations (included under refugees) and those in IDP-like situations (included under IDPs). Refugees include individuals recognised under the 1951 Convention relating to the Status of Refugees; its 1967 Protocol; the 1969 OAU Convention Governing the Specific Aspects of Refugee Problems in Africa; those recognised in accordance with the UNHCR Statute; individuals granted complementary forms of protection; or those enjoying temporary protection. Since 2007, the refugee population also includes people in a refugee-like situation. Asylum-seekers are individuals who have sought international protection and whose claims for refugee status have not yet been determined, irrespective of when they may have been lodged. Internally displaced persons (IDPs) are people or groups of individuals who have been forced to leave their homes or places of habitual residence, in particular as a result of, or in order to avoid the effects of armed conflict, situations of generalised violence, violations of human rights, or natural or man-made disasters, and who have not crossed an international border. For the purposes of UNHCR's statistics, this population only includes conflict-generated IDPs to whom the Office extends protection and/or assistance. Since 2007, the IDP population also includes people in an IDP-like situation. Returned refugees are former refugees who have returned to their country of origin spontaneously or in an organised fashion but are yet to be fully integrated. Such return would normally only take place in conditions of safety and dignity. Returned IDPs refer to those IDPs who were beneficiaries of UNHCR's protection and assistance activities and who returned to their areas of origin or habitual residence during the year. Stateless persons are defined under international law as persons who are not considered as nationals by any State under the operation of its law. In other words, they do not possess the nationality of any State. UNHCR statistics refer to persons who fall under the agency’s statelessness mandate because they are stateless according to this international definition, but data from some countries may also include persons with undetermined nationality. Others of concern refers to individuals who do not necessarily fall directly into any of the groups above, but to whom UNHCR extends its protection and/or assistance services, based on humanitarian or other special grounds.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: World Integrated Trade Solution Trade Stats Publication: https://datacatalog.worldbank.org/dataset/world-integrated-trade-solution-trade-stats License: http://creativecommons.org/licenses/by/4.0/   WITS Trade Stats is a database created by aggregating data from UN COMTRADE and UNCTAD TRAINS database. It provides information on bilateral trade exports, imports and tariffs for over 180 countries and regions.