سان مارينو

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

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).

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.

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.

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.

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.

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.

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.

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).

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

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.

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.

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.

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

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

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).

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).

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.

U.S Census Bureau Attribution: "This product uses the Census Bureau Data API but is not endorsed or certified by the Census Bureau." Note: Knoema modified the original dataset to include geo coordinates for each port

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.  

التجارة الدولية في السلع في دولة الإمارات العربية المتحدة