كرواتيا

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.

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

STAN Bilateral Trade Database by Industry and End-use category (BTDIxE) provides values of imports and exports (as well as re-imports and re-exports) of goods broken down by industrial sectors and by end-use categories. BTDIxE was designed to extend the old BTD database which provided bilateral trade in goods by industry only.  BTDIxE allows, for example, insights into the patterns of trade in intermediate goods between countries to track global production networks and supply chains, and it helps to address policy issues such as trade in value added and trade in tasks.  The database presents estimates of bilateral flows of goods from 1990 to the latest available year, i.e. 2018; the latest year shown is subject to the availability of underlying product-based annual trade statistics.  Reporters are the OECD member countries and a large number of non-OECD economies, including the BRIICS: Brazil, the Russian Federation, India, Indonesia, People's Republic of China and South Africa; other selected G20 and Asian economies; and major African and Latin American nations.  It should be noted that starting from mid-2012, the OECD and the United Nations agreed to centralise the data collection and processing procedures within UNSD Comtrade.  The list of partners covers the OECD countries, more than a hundred of non-member economies as well as the partners "World", "Rest of the World" and "Unspecified". The partner "Total foreign trade" corresponds to the flows with partner "World" excluding intra-country flows. Trade flows are divided into economic activities based on the Revision 4 of ISIC and nine end-use categories including capital goods, intermediate goods and household consumption.

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

This dataset provides detailed trade statistics on iron and steel commodities using the Harmonized System (HS) classification of goods (based on the 6-digit commodity level).

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.

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

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).

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

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).

SA1 based data for by Sex, Basic Community Profile Table B09, for 2011 Census ABS Census Homepage

Australia/State/SA4/SA3/SA2 based data for Country Of Birth Of Person by Sex, Time Series Profiles Table t08, for 2011 Census ABS Census Homepage

Australia/State/SA4/SA3/SA2 based data for Year of Arrival in Australia, Basic Community Profile Table B10, for 2011 Census ABS Census Homepage

LGA2011 based data for Year of Arrival in Australia, Basic Community Profile Table B10, for 2011 Census ABS Census Homepage

SA1 based data for Year of Arrival in Australia, Basic Community Profile Table B10, for 2011 Census ABS Census Homepage

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.

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.

Number of students enrolled in different education programmes by country of origin and sex.

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.

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

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

This dataset FDI positions by counterpart area, BMD4 includes inward and outward Foreign Direct Investment (FDI) positions by partner country for OECD reporting economies.  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.

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

Foreign Trade of Djibouti

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.

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.

Tourism can be regarded as a social, cultural and economic phenomenon related to the movement of people outside their usual place of residence.

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.

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

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 dataset presents the liner shipping bilateral connectivity index (LSBCI), which indicates a country pair's integration level into global liner shipping networks. The LSBCI is an extension of UNCTAD’s country-level Liner Shipping Connectivity Index (LSCI) and based on a proper bilateralization transformation.  

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.

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

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.

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.

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

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

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

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.

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.

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

Quantity Reporting: Measure food aid deliveries in metric tons

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.

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

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).

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.

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.

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.

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

Total Receipts, Net: in addition to Official Development Assistance, this heading includes in particular: other official bilateral transactions which are not concessional or which, even though they have concessional elements, are primarily trade facilitating in character (i.e., "Other Official Flows''); changes in bilateral long-term assets of the private non-monetary and monetary sectors, in particular guaranteed export credits, private direct investment, portfolio investment and, to the extent they are not covered in the preceding headings, loans by private banks. Flows from the multilateral sector which are not classified as concessional are also included here.

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.

The European Commission provides statistics on EU crude oil imports and crude oil supply costs.

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.  

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