DDI_MNG_1989_PHC_v01_M_v03_A_IPUMS Minnesota Population Center 2016-04-25 NADA Version 6.4 (April 2016): Documentation of census data and harmonized variables as found in IPUMS-International. The International Household Survey Network (IHSN) contracted IPUMS International for generating DDI and Dublin Core-compliant metadata related to population and housing census datasets from developing countries. The objective was to provide countries with detailed metadata in a format compatible with the DDI standard used by most of these countries, with a view to guarantee the preservation of the data and metadata, and the publishing of metadata. The intellectual rights (including copyright) for the data and metadata in IPUMS are retained by the countries under a Memorandum of Understanding with the contributing countries. IPUMS-International has distribution rights to the metadata and data. The XML documents generated by this process are viewed as a distribution of the metadata. Fields edited by the World Bank are: DDI ID and study ID to match World Bank study naming convention, as well as DDI Document Version and Version Description to reflect changes included in version 6.4. Previous version documented in the World Bank Microdata Library: - v6.3 (August 2014) Population and Housing Census 1989 - IPUMS Subset PHC 1989 (IPUMS Harmonized Subset) MNG_1989_PHC_v01_M_v03_A_IPUMS National Statistical Office of Mongolia Minnesota Population Center (c) Copyright 1989, National Statistical Office of Mongolia and Minnesota Population Center NADA National Statistical Office of Mongolia Population and Housing Census [hh/popcen] Version 6.4. The datasets contain selected variables from the original census microdata plus harmonized variables from the IPUMS-International database. In v6.4, the research team continued to carry out improvements to geography, providing harmonized geographic units for the second administrative level for roughly half the countries. More information about IPUMS geography variables is available <a href='https://international.ipums.org/international/geography_variables.shtml'>here</a>. Also, approximately 100 integrated variables were renamed. Affected variables with their current and previous names are listed <a href='https://international.ipums.org/international/resources/misc_docs/renamed_variables_sept2015.pdf'>here</a>. Geography variable also underwent wholesale renaming. In this update, IPUMS added 19 new samples for Armenia, Austria, Costa Rica, Ethiopia, France, Ghana, Mozambique, Paraguay, Portugal, Puerto Rico, South Africa, and Spain. Ethiopia, Mozambique, and Paraguay were newly added countries to IPUMS. Samples for other countries extend pre-existing series for those countries. Technical Household Variables -- HOUSEHOLD Group Quarters Variables -- HOUSEHOLD Geography: Global Variables -- HOUSEHOLD Utilities Variables -- HOUSEHOLD Dwelling Characteristics Variables -- HOUSEHOLD Constructed Household Variables -- HOUSEHOLD Technical Person Variables -- PERSON Constructed Family Interrelationship Variables -- PERSON Demographic Variables -- PERSON Fertility and Mortality Variables -- PERSON Nativity and Birthplace Variables -- PERSON Education Variables -- PERSON Geography: M-Z Variables -- HOUSEHOLD Household Economic Variables -- HOUSEHOLD Appliances, Mechanicals, Other Amenities Variables -- HOUSEHOLD Other Household Variables -- HOUSEHOLD Other Person Variables -- PERSON Ethnicity and Language Variables -- PERSON Work Variables -- PERSON IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system. The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems. Mongolia National coverage Province (aimag) Households UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: Yes - Special populations: Not specified UNIT DESCRIPTIONS: - Dwellings: Not specified - Households: One or more individuals who live under one roof, have either family or relationship relation, and have one budget. All population inside Mongolia and abroad Census/enumeration data [cen] MICRODATA SOURCE: National Statistical Office of Mongolia SAMPLE DESIGN: Cluster sample of entire districts (soums) or portions of districts. Every province has some districts sampled. NOTE: Because of extreme clustering, the sample weights may not ensure representative results for all types of analyses. SAMPLE UNIT: Households SAMPLE FRACTION: 10% SAMPLE SIZE (person records): 190,631 Face-to-face [f2f] There are three enumeration forms: 1) census questionnaire, 2) household questionnaire, and 3) housing questionnaire. De facto and de jure, CENSUS DAY: January 5, 1989, FIELD WORK PERIOD: January 5-9, 1989 Direct interview Weights designed to yield the proper age structure for each province based on published census results. Household weights are computed as the mean of the person weights in the unit. COVERAGE: 100% IPUMS-International distributes integrated microdata of individuals and households only by agreement of collaborating national statistical offices and under the strictest of confidence. Before data may be distributed to an individual researcher, an electronic license agreement must be signed and approved. To gain access to the data, a researcher must agree to the following: (1) Implement security measures to prevent unauthorized access to census microdata. Under IPUMS-International agreements with collaborating agencies, redistribution of the data to third parties is prohibited. (2) Use the microdata for the exclusive purposes of scholarly research and education. Researchers must explicitly agree to not use microdata acquired for any commercial or income-generating venture. (3) Maintain the confidentiality of persons, households, and other entities. Any attempt to ascertain the identity of persons or households from the microdata is prohibited. Alleging that a person or household has been identified is also prohibited. (4) Report all publications based on these data to IPUMS-International, which will in turn pass the information on to the relevant national statistical agencies. Once a project is approved, a password is issued and data may be acquired through the Internet. Penalties for violating the license include: revocation of the license, recall of all microdata acquired, filing of a motion of censure to the appropriate professional organizations, and civil prosecution under the relevant national or international statutes. These safeguards mirror the principles from the Joint ECE/Eurostat Work Session on Statistical Data Confidentiality. Employees of the Minnesota Population Center who work with the census microdata to produce the harmonized database also sign agreements to respect the confidentiality of the data. IPUMS-International works with each country's statistical office to minimize the risk of disclosure of respondent information. The details of the confidentiality protections vary across countries, but in all cases, names and detailed geographic information are suppressed and top-codes are imposed on variables such as income that might identify specific persons. In addition, IPUMS-International uses a variety of technical procedures to enhance confidentiality protection. These include the following: (1) Swapping an undisclosed fraction of records from one administrative district to another to make positive identification of individuals impossible. (2) Randomizing the placement of households within districts to disguise the order in which individuals were enumerated or the data processed. (3) Aggregating codes of sensitive characteristics (e.g., grouping together very small ethnic categories) (4) Top- and bottom-coding continuous variables to prevent identification of extreme cases. The safety record for public-use census microdata is apparently perfect. In almost four decades of use, there has not been a single verified breach of statistical confidentiality. The measures implemented by the IPUMS-International are designed to extend this record. IPUMS International Minnesota Population Center. Integrated Public Use Microdata Series, International: Version 6.4 [dataset]. Minneapolis: University of Minnesota, 2015. http://doi.org/10.18128/D020.V6.4. Researchers should also acknowledge the statistical agency that originally produced the data: Mongolia, National Statistical Office of Mongolia, Population and Housing Census 1989 The licensing agreement for use of IPUMS-International data requires that users supply IPUMS-International with the title and full citation for any publications, research reports, or educational materials making use of the data or documentation. Copies of such materials are also gratefully received at ipums@umn.edu. Printed matter should be sent to: IPUMS-International Minnesota Population Center University of Minnesota 50 Willey Hall 225 19th Avenue South Minneapolis, MN 55455 An adapted version of the dataset, harmonized for international comparability, is available from IPUMS-International (https://international.ipums.org/international/) under the following conditions: IPUMS-International distributes integrated microdata of individuals and households only by agreement of collaborating national statistical offices and under the strictest of confidence. Before data may be distributed to an individual researcher, an electronic license agreement must be signed and approved. To gain access to the data, a researcher must agree to the following: (1) Implement security measures to prevent unauthorized access to census microdata. Under IPUMS-International agreements with collaborating agencies, redistribution of the data to third parties is prohibited. (2) Use the microdata for the exclusive purposes of scholarly research and education. Researchers must explicitly agree to not use microdata acquired for any commercial or income-generating venture. (3) Maintain the confidentiality of persons, households, and other entities. Any attempt to ascertain the identity of persons or households from the microdata is prohibited. Alleging that a person or household has been identified is also prohibited. (4) Report all publications based on these data to IPUMS-International, which will in turn pass the information on to the relevant national statistical agencies. Once a project is approved, a password is issued and data may be acquired through the Internet. Penalties for violating the license include: revocation of the license, recall of all microdata acquired, filing of a motion of censure to the appropriate professional organizations, and civil prosecution under the relevant national or international statutes. These safeguards mirror the principles from the Joint ECE/Eurostat Work Session on Statistical Data Confidentiality. Employees of the Minnesota Population Center who work with the census microdata to produce the harmonized database also sign agreements to respect the confidentiality of the data. The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses. MNG1989-H-H Household records 0 72 MNG1989-P-H Person records 0 63 Record type Record type Record type Record type Record type RECTYPE identifies the type of record for the case: household or person. NOTE: RECTYPE is an alphabetic (character string) variable with a value of 'H' for household records and 'P' for person records. RECTYPE will not appear as a variable in the default rectangular extracts produced by the data extract system. It is only available in hierarchical extracts, to distinguish between the two record types. RECTYPE is a 1-digit alphabetic (non-numeric) variable. H = Household record P = Person record IPUMS Year Year Year Year Year 1960 1960 1962 1962 1963 1963 1964 1964 1966 1966 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 YEAR gives the year in which the census was taken. IPUMS IPUMS sample identifier IPUMS sample identifier IPUMS sample identifier IPUMS sample identifier IPUMS sample identifier 32197001 Argentina 1970 32199101 Argentina 1991 32200101 Argentina 2001 32201001 Argentina 2010 32219801 Argentina 1980 40197101 Austria 1971 40198101 Austria 1981 40199101 Austria 1991 40200101 Austria 2001 40201101 Austria 2011 50199101 Bangladesh 1991 50200101 Bangladesh 2001 50201101 Bangladesh 2011 51200101 Armenia 2001 51201101 Armenia 2011 68197601 Bolivia 1976 68199201 Bolivia 1992 68200101 Bolivia 2001 76196001 Brazil 1960 76197001 Brazil 1970 76198001 Brazil 1980 76199101 Brazil 1991 76200001 Brazil 2000 76201001 Brazil 2010 112199901 Belarus 1999 116199801 Cambodia 1998 116200801 Cambodia 2008 120197601 Cameroon 1976 120198701 Cameroon 1987 120200501 Cameroon 2005 124197101 Canada 1971 124198101 Canada 1981 124199101 Canada 1991 124200101 Canada 2001 152196001 Chile 1960 152197001 Chile 1970 152198201 Chile 1982 152199201 Chile 1992 152200201 Chile 2002 156198201 China 1982 156199001 China 1990 170196401 Colombia 1964 170197301 Colombia 1973 170198501 Colombia 1985 170199301 Colombia 1993 170200501 Colombia 2005 188196301 Costa Rica 1963 188197301 Costa Rica 1973 188198401 Costa Rica 1984 188200001 Costa Rica 2000 188201101 Costa Rica 2011 192200201 Cuba 2002 214196001 Dominican Republic 1960 214197001 Dominican Republic 1970 214198101 Dominican Republic 1981 214200201 Dominican Republic 2002 214201001 Dominican Republic 2010 218196201 Ecuador 1962 218197401 Ecuador 1974 218198201 Ecuador 1982 218199001 Ecuador 1990 218200101 Ecuador 2001 218201001 Ecuador 2010 222199201 El Salvador 1992 222200701 El Salvador 2007 231198401 Ethiopia 1984 231199401 Ethiopia 1994 231200701 Ethiopia 2007 242196601 Fiji 1966 242197601 Fiji 1976 242198601 Fiji 1986 242199601 Fiji 1996 242200701 Fiji 2007 250196201 France 1962 250196801 France 1968 250197501 France 1975 250198201 France 1982 250199001 France 1990 250199901 France 1999 250200601 France 2006 250201101 France 2011 275199701 Palestine 1997 275200701 Palestine 2007 276197001 Germany 1970 (West) 276197101 Germany 1971 (East) 276198101 Germany 1981 (East) 276198701 Germany 1987 (West) 288198401 Ghana 1984 288200001 Ghana 2000 288201001 Ghana 2010 300197101 Greece 1971 300198101 Greece 1981 300199101 Greece 1991 300200101 Greece 2001 324198301 Guinea 1983 324199601 Guinea 1996 332197101 Haiti 1971 332198201 Haiti 1982 332200301 Haiti 2003 348197001 Hungary 1970 348198001 Hungary 1980 348199001 Hungary 1990 348200101 Hungary 2001 356198341 India 1983 356198741 India 1987 356199341 India 1993 356199941 India 1999 356200441 India 2004 360197101 Indonesia 1971 360197601 Indonesia 1976 360198001 Indonesia 1980 360198501 Indonesia 1985 360199001 Indonesia 1990 360199501 Indonesia 1995 360200001 Indonesia 2000 360200501 Indonesia 2005 360201001 Indonesia 2010 364200601 Iran 2006 368199701 Iraq 1997 372197101 Ireland 1971 372197901 Ireland 1979 372198101 Ireland 1981 372198601 Ireland 1986 372199101 Ireland 1991 372199601 Ireland 1996 372200201 Ireland 2002 372200601 Ireland 2006 372201101 Ireland 2011 376197201 Israel 1972 376198301 Israel 1983 376199501 Israel 1995 380200101 Italy 2001 388198201 Jamaica 1982 388199101 Jamaica 1991 388200101 Jamaica 2001 400200401 Jordan 2004 404196901 Kenya 1969 404197901 Kenya 1979 404198901 Kenya 1989 404199901 Kenya 1999 404200901 Kenya 2009 417199901 Kyrgyz Republic 1999 417200901 Kyrgyz Republic 2009 430197401 Liberia 1974 430200801 Liberia 2008 454198701 Malawi 1987 454199801 Malawi 1998 454200801 Malawi 2008 458197001 Malaysia 1970 458198001 Malaysia 1980 458199101 Malaysia 1991 458200001 Malaysia 2000 466198701 Mali 1987 466199801 Mali 1998 466200901 Mali 2009 484196001 Mexico 1960 484197001 Mexico 1970 484199001 Mexico 1990 484199501 Mexico 1995 484200001 Mexico 2000 484200501 Mexico 2005 484201001 Mexico 2010 496198901 Mongolia 1989 496200001 Mongolia 2000 504198201 Morocco 1982 504199401 Morocco 1994 504200401 Morocco 2004 508199701 Mozambique 1997 508200701 Mozambique 2007 524200101 Nepal 2001 528196001 Netherlands 1960 528197101 Netherlands 1971 528200101 Netherlands 2001 558197101 Nicaragua 1971 558199501 Nicaragua 1995 558200501 Nicaragua 2005 566200621 Nigeria 2006 566200721 Nigeria 2007 566200821 Nigeria 2008 566200921 Nigeria 2009 566201021 Nigeria 2010 586197301 Pakistan 1973 586198101 Pakistan 1981 586199801 Pakistan 1998 591196001 Panama 1960 591197001 Panama 1970 591198001 Panama 1980 591199001 Panama 1990 591200001 Panama 2000 591201001 Panama 2010 600196201 Paraguay 1962 600197201 Paraguay 1972 600198201 Paraguay 1982 600199201 Paraguay 1992 600200201 Paraguay 2002 604199301 Peru 1993 604200701 Peru 2007 608199001 Philippines 1990 608199501 Philippines 1995 608200001 Philippines 2000 620198101 Portugal 1981 620199101 Portugal 1991 620200101 Portugal 2001 620201101 Portugal 2011 630197001 Puerto Rico 1970 630198001 Puerto Rico 1980 630199001 Puerto Rico 1990 630200001 Puerto Rico 2000 630200501 Puerto Rico 2005 630201001 Puerto Rico 2010 642197701 Romania 1977 642199201 Romania 1992 642200201 Romania 2002 646199101 Rwanda 1991 646200201 Rwanda 2002 662198001 Saint Lucia 1980 662199101 Saint Lucia 1991 686198801 Senegal 1988 686200201 Senegal 2002 694200401 Sierra Leone 2004 704198901 Vietnam 1989 704199901 Vietnam 1999 704200901 Vietnam 2009 705200201 Slovenia 2002 710199601 South Africa 1996 710200101 South Africa 2001 710200701 South Africa 2007 710201101 South Africa 2011 724198101 Spain 1981 724199101 Spain 1991 724200101 Spain 2001 724201101 Spain 2011 728200801 South Sudan 2008 729200801 Sudan 2008 756197001 Switzerland 1970 756198001 Switzerland 1980 756199001 Switzerland 1990 756200001 Switzerland 2000 764197001 Thailand 1970 764198001 Thailand 1980 764199001 Thailand 1990 764200001 Thailand 2000 792198501 Turkey 1985 792199001 Turkey 1990 792200001 Turkey 2000 800199101 Uganda 1991 800200201 Uganda 2002 804200101 Ukraine 2001 818199601 Egypt 1996 818200601 Egypt 2006 826199101 United Kingdom 1991 826200101 United Kingdom 2001 834198801 Tanzania 1988 834200201 Tanzania 2002 840196001 United States 1960 840197001 United States 1970 840198001 United States 1980 840199001 United States 1990 840200001 United States 2000 840200501 United States 2005 840201001 United States 2010 854198501 Burkina Faso 1985 854199601 Burkina Faso 1996 854200601 Burkina Faso 2006 858196301 Uruguay 1963 858197501 Uruguay 1975 858198501 Uruguay 1985 858199601 Uruguay 1996 858200621 Uruguay 2006 858201101 Uruguay 2011 862197101 Venezuela 1971 862198101 Venezuela 1981 862199001 Venezuela 1990 862200101 Venezuela 2001 894199001 Zambia 1990 894200001 Zambia 2000 894201001 Zambia 2010 SAMPLE identifies the IPUMS sample from which the case is drawn. Each sample receives a unique 9-digit code. The code is structured as follows: The first 3 digits are the ISO/UN codes used in COUNTRY The next 4 digits are the year of the census/survey The final 2 digits identify the sample within the year. For the last two digits, censuses or large census-like surveys have a value "0" (e.g, 01) in the second-to-last digit, household surveys have a value of "2" (e.g., 21), and employment surveys have a value of "4" (e.g., 41). IPUMS Household serial number Household serial number Household serial number Household serial number Household serial number SERIAL is an identifying number unique to each household in a given sample. All person records are assigned the same serial number as the household record that they follow. (Person records also have their own unique identifiers -- see PERNUM.) The combination of SAMPLE and SERIAL provides a unique identifier for every household in the IPUMS-International database; SAMPLE, SERIAL and PERNUM uniquely identify every person in the database. SERIAL can be used to identify dwellings in some samples. In these samples, the first 7 digits of SERIAL provide the dwelling number common to all households that were sampled from the same structure. The last three digits give the sequence of the household within the dwelling. The following is a list of samples in which dwellings can be inferred: Chile 1970, 1992, 2002 Colombia 1993, 2005 Costa Rica 1984, 2000 Cuba 2002 Dominican Republic 1981, 2002, 2010 Ecuador 1990, 2001 Germany 1971 Hungary 1980, 1990, 2001 Jamaica 1982, 1991, 2001 Malaysia 1970, 1991, 2000 Mexico 1995, 1990, 2000, 2005 Nigeria 2006 Panama 2000 Peru 1993, 2007 Portugal 1981, 1991, 2001 Spain 1991 Uruguay 2011 Venezuela 1990, 2001 Vietnam 1989 In all other samples, the last 3 digits are always zeroes. SERIAL was constructed for IPUMS-International, and has no relation to the serial number in the original datasets. SERIAL is a 10-digit numeric variable. The last 3 digits of SERIAL indicate household number within dwelling for selected samples noted in the variable description. In all other samples, the last 3 digits are always zeroes. IPUMS Number of person records in the household Number of person records in the household Number of person records in the household Number of person records in the household Number of person records in the household PERSONS indicates how many person records are included in the household (i.e., the number of person records associated with the household record in the sample). These person records will all have the same serial number (SERIAL) as the household record. The information contained in the household record will normally apply to all of these persons. PERSONS is a 3-digit numeric variable. IPUMS Subsample number Subsample number Subsample number Subsample number Subsample number 1st 1% subsample 1 2nd 1% subsample 2 3rd 1% subsample 3 4th 1% subsample 4 5th 1% subsample 5 6th 1% subsample 6 7th 1% subsample 7 8th 1% subsample 8 9th 1% subsample 9 10th 1% subsample 10 11th 1% subsample 11 12th 1% subsample 12 13th 1% subsample 13 14th 1% subsample 14 15th 1% subsample 15 16th 1% subsample 16 17th 1% subsample 17 18th 1% subsample 18 19th 1% subsample 19 20th 1% subsample 20 21st 1% subsample 21 22nd 1% subsample 22 23rd 1% subsample 23 24th 1% subsample 24 25th 1% subsample 25 26th 1% subsample 26 27th 1% subsample 27 28th 1% subsample 28 29th 1% subsample 29 30th 1% subsample 30 31st 1% subsample 31 32nd 1% subsample 32 33rd 1% subsample 33 34th 1% subsample 34 35th 1% subsample 35 36th 1% subsample 36 37th 1% subsample 37 38th 1% subsample 38 39th 1% subsample 39 40th 1% subsample 40 41st 1% subsample 41 42nd 1% subsample 42 43rd 1% subsample 43 44th 1% subsample 44 45th 1% subsample 45 46th 1% subsample 46 47th 1% subsample 47 48th 1% subsample 48 49th 1% subsample 49 50th 1% subsample 50 51st 1% subsample 51 52nd 1% subsample 52 53rd 1% subsample 53 54th 1% subsample 54 55th 1% subsample 55 56th 1% subsample 56 57th 1% subsample 57 58th 1% subsample 58 59th 1% subsample 59 60th 1% subsample 60 61st 1% subsample 61 62nd 1% subsample 62 63rd 1% subsample 63 64th 1% subsample 64 65th 1% subsample 65 66th 1% subsample 66 67th 1% subsample 67 68th 1% subsample 68 69th 1% subsample 69 70th 1% subsample 70 71st 1% subsample 71 72nd 1% subsample 72 73rd 1% subsample 73 74th 1% subsample 74 75th 1% subsample 75 76th 1% subsample 76 77th 1% subsample 77 78th 1% subsample 78 79th 1% subsample 79 80th 1% subsample 80 81st 1% subsample 81 82nd 1% subsample 82 83rd 1% subsample 83 84th 1% subsample 84 85th 1% subsample 85 86th 1% subsample 86 87th 1% subsample 87 88th 1% subsample 88 89th 1% subsample 89 90th 1% subsample 90 91st 1% subsample 91 92nd 1% subsample 92 93rd 1% subsample 93 94th 1% subsample 94 95th 1% subsample 95 96th 1% subsample 96 97th 1% subsample 97 98th 1% subsample 98 99th 1% subsample 99 100th 1% subsample SUBSAMP allocates each case to one of 100 subsample replicates, randomly numbered from 0 to 99. Each subsample is nationally representative and preserves any stratification of the sample from which it is drawn. Users who need a representative subset of a sample can use SUBSAMP to select their cases. For example, to randomly extract 10% of the cases from a sample, select any 10 of the 100 subsamples. IPUMS Group quarters (collective dwelling) status Group quarters (collective dwelling) status Group quarters (collective dwelling) status Group quarters (collective dwelling) status Group quarters (collective dwelling) status Vacant 10 Households 20 Group quarters, n.s. 21 Institutions 22 Other group quarters 29 1-person unit created by splitting large household 99 Unknown/group quarters not identified GQ identifies households as vacant dwellings, group quarters, or private households. Group quarters -- collective dwellings -- are generally institutions and other group living arrangements such as rooming houses and boarding schools. Institutions often retain persons under formal supervision or custody, such as correctional institutions, military barracks, asylums, or nursing homes. Educational and religious group dwellings (e.g., boarding schools, convents, monasteries, etc.) are also included in the institutional classification. Group quarter designations are often useful for understanding the universe of households that answered questions about household characteristics. Censuses will often exclude group quarters from such questions. IPUMS Number of unrelated persons Number of unrelated persons Number of unrelated persons Number of unrelated persons Number of unrelated persons 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9+ UNREL indicates the number of persons in the household who are unrelated to the head. IPUMS Continent and region of country Continent and region of country Continent and region of country Continent and region of country Continent and region of country 11 Eastern Africa 12 Middle Africa 13 Northern Africa 14 Southern Africa 15 Western Africa 21 Caribbean 22 Central America 23 North America 24 South America 31 Central Asia 32 Eastern Asia 33 Southern Asia 34 South-Eastern Asia 35 Western Asia 41 Eastern Europe 42 Northern Europe 43 Southern Europe 44 Western Europe 51 Australia and New Zealand 52 Melanesia 53 Micronesia 54 Polynesia REGIONW identifies the continent and region of each country. IPUMS Water supply Water supply Water supply Water supply Water supply NIU (not in universe) 10 Yes, piped water 11 Piped inside dwelling 12 Piped, exclusively to this household 13 Piped, shared with other households 14 Piped outside the dwelling 15 Piped outside dwelling, in building 16 Piped within the building or plot of land 17 Piped outside the building or lot 18 Have access to public piped water 20 No piped water 99 Unknown WATSUP describes the physical means by which the housing unit receives its water. The primary distinction is whether or not the household had piped (running) water. IPUMS Number of rooms Number of rooms Number of rooms Number of rooms Number of rooms Part of a room; no rooms 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) ROOMS indicates the number of rooms occupied by the housing unit. IPUMS Kitchen or cooking facilities Kitchen or cooking facilities Kitchen or cooking facilities Kitchen or cooking facilities Kitchen or cooking facilities NIU (not in universe) 10 No kitchen 11 Food is prepared in a non-kitchen room 13 Does not prepare food in the dwelling 20 Yes, have a kitchen 21 Kitchen located inside the dwelling 22 Indoor kitchen, exclusive use 23 Indoor kitchen, shared use 24 Exclusive use of kitchen (indoor/outdoor status not specified) 25 Kitchen shared with another household (indoor/outdoor status not specified) 26 Kitchen located outside the dwelling 27 Outdoor kitchen, exclusive use 28 Outdoor kitchen, shared use 99 Unknown/missing KITCHEN indicates whether the household had a kitchen, cooking facilities, or room dedicated to food preparation. IPUMS Bathing facilities Bathing facilities Bathing facilities Bathing facilities Bathing facilities NIU (not in universe) 1 No bathing facility 2 Have bathing facility, exclusivity not specified 3 Have bathing facility, exclusive use 4 Have bathing facility, shared use 9 Unknown BATH indicates whether the household had access to bathing facilities and, in most cases, whether it had exclusive access. IPUMS Household classification Household classification Household classification Household classification Household classification Vacant household 1 One-person household 2 Married/cohab couple, no children 3 Married/cohab couple with children 4 Single-parent family 5 Polygamous family 6 Extended family, relatives only 7 Composite household, family and non-relatives 8 Non-family household 9 Unclassified subfamily 10 Other relative or non-relative household 11 Group quarters 99 Unclassifiable HHTYPE is a constructed variable that describes the composition of households. HHTYPE is constructed from information in RELATE (relationship to head), from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father), and from information on group quarters status, GQ. IPUMS Number of families in household Number of families in household Number of families in household Number of families in household Number of families in household Vacant household 1 1 family 2 2 families 3 3 families 4 4 families 5 5 families 6 6 families 7 7 families 8 8 families 9 9 or more families NFAMS is a constructed variable that indicates the number of families within each household. A "family" is any group of persons related by blood, adoption, or marriage. An unrelated individual within the household is considered a separate family. Thus, a household consisting of a widow and her servant contains two families; a household consisting of a large, multiple-generation extended family with no lodgers or servants would count as a single family. NFAMS is constructed from information in RELATE (relationship to head) and from the constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). See those variable descriptions for more detail. IPUMS Head's location in household Head's location in household Head's location in household Head's location in household Head's location in household HEADLOC gives the person number of the head of household in samples in which persons are organized into households. This is a 3-digit numeric variable with 0 implied decimal places IPUMS 1st subnational geographic level, world [consistent boundaries over time] 1st subnational geographic level, world [consistent boundaries over time] 1st subnational geographic level, world [consistent boundaries over time] 1st subnational geographic level, world [consistent boundaries over time] 1st subnational geographic level, world [consistent boundaries over time] 32002 City of Buenos Aires [Province: Argentina] 32006 Buenos Aires province [Province: Argentina] 32010 Catamarca [Province: Argentina] 32014 Córdoba [Province: Argentina] 32018 Corrientes [Province: Argentina] 32022 Chaco [Province: Argentina] 32026 Chubut [Province: Argentina] 32030 Entre Ríos [Province: Argentina] 32034 Formosa [Province: Argentina] 32038 Jujuy [Province: Argentina] 32042 La Pampa [Province: Argentina] 32046 La Rioja [Province: Argentina] 32050 Mendoza [Province: Argentina] 32054 Misiones [Province: Argentina] 32058 Neuquén [Province: Argentina] 32062 Río Negro [Province: Argentina] 32066 Salta [Province: Argentina] 32070 San Juan [Province: Argentina] 32074 San Luis [Province: Argentina] 32078 Santa Cruz [Province: Argentina] 32082 Santa Fe [Province: Argentina] 32086 Santiago del Estero [Province: Argentina] 32090 Tucumán [Province: Argentina] 32094 Tierra del Fuego [Province: Argentina] 32099 Unknown [Province: Argentina] 40011 Burgenland [State: Austria] 40012 Niederösterreich [State: Austria] 40013 Wien [State: Austria] 40021 Kärnten [State: Austria] 40022 Steiermark [State: Austria] 40031 Oberösterreich [State: Austria] 40032 Salzburg [State: Austria] 40033 Tirol [State: Austria] 40034 Vorarlberg [State: Austria] 50010 Barisal [Division, Bangladesh] 50020 Chittagong [Division, Bangladesh] 50030 Dhaka [Division, Bangladesh] 50040 Khulna [Division, Bangladesh] 50050 Rajshahi, Rangpur [Division, Bangladesh] 50060 Sylhet [Division, Bangladesh] 51901 Yerevan [Province: Armenia] 51902 Aragatsotn [Province: Armenia] 51903 Ararat [Province: Armenia] 51904 Armavir [Province: Armenia] 51905 Gegharkunik [Province: Armenia] 51906 Lori [Province: Armenia] 51907 Kotayk [Province: Armenia] 51908 Shirak [Province: Armenia] 51909 Syunik [Province: Armenia] 51910 Vayots Dzor [Province: Armenia] 51911 Tavush [Province: Armenia] 68001 Chuquisaca [Department: Bolivia] 68002 La Paz [Department: Bolivia] 68003 Cochabamba [Department: Bolivia] 68004 Oruro [Department: Bolivia] 68005 Potosí [Department: Bolivia] 68006 Tarija [Department: Bolivia] 68007 Santa Cruz [Department: Bolivia] 68008 Beni [Department: Bolivia] 68009 Pando [Department: Bolivia] 76011 Rondonia [State: Brazil] 76012 Acre [State: Brazil] 76013 Amazonas [State: Brazil] 76014 Roraima [State: Brazil] 76015 Pará [State: Brazil] 76016 Amapa [State: Brazil] 76021 Maranhao [State: Brazil] 76022 Piauí [State: Brazil] 76023 Ceará [State: Brazil] 76024 Rio Grande do Norte [State: Brazil] 76025 Paraiba [State: Brazil] 76026 Pernambuco [State: Brazil] 76027 Alagoas [State: Brazil] 76028 Sergipe [State: Brazil] 76029 Bahia [State: Brazil] 76031 Minas Gerais [State: Brazil] 76032 Espírito Santo [State: Brazil] 76033 Rio de Janeiro [State: Brazil] 76035 São Paulo [State: Brazil] 76041 Parana [State: Brazil] 76042 Santa Catarina [State: Brazil] 76043 Rio Grande do Sul [State: Brazil] 76051 Mato Grosso, Mato Grosso do Sul [State: Brazil] 76052 Goiás and Tocantins [State: Brazil] 76053 Distrito Federal [State: Brazil] 112001 Brest [Region: Belarus] 112002 Vitebsk [Region: Belarus] 112003 Gomel [Region: Belarus] 112004 Grodno [Region: Belarus] 112006 Minsk [Region: Belarus] 112007 Mogilev [Region: Belarus] 116001 Banteay Meanchey [Province: Cambodia] 116002 Battambang [Province: Cambodia] 116003 Kampong Cham [Province: Cambodia] 116004 Kampong Chhnang [Province: Cambodia] 116005 Kampong Speu [Province: Cambodia] 116006 Kampong Thom [Province: Cambodia] 116007 Kampot [Province: Cambodia] 116008 Kandal [Province: Cambodia] 116009 Koh Kong [Province: Cambodia] 116010 Kratie [Province: Cambodia] 116011 Mondul Kiri [Province: Cambodia] 116012 Phnom Penh [Province: Cambodia] 116013 Preah Vihear [Province: Cambodia] 116014 Prey Veng [Province: Cambodia] 116015 Pursat [Province: Cambodia] 116016 Rotanak Kiri [Province: Cambodia] 116017 Siem Reap and Otdar Meanchey [Province: Cambodia] 116018 Preah Sihanouk [Province: Cambodia] 116019 Stung Treng [Province: Cambodia] 116020 Svay Rieng [Province: Cambodia] 116021 Takeo [Province: Cambodia] 116023 Kep [Province: Cambodia] 116024 Pailin [Province: Cambodia] 120002 Centre, Sud [Province: Cameroon] 120003 Est [Province: Cameroon] 120004 Nord, Adamoua , Extrème Nord [Province: Cameroon] 120005 Littoral [Province: Cameroon] 120007 Nord Ouest [Province: Cameroon] 120008 Ouest [Province: Cameroon] 120010 Sud Ouest [Province: Cameroon] 124010 Newfoundland and Labrador [Province: Canada] 124011 Prince Edward Island, Yukon, Northwest Territories, and Nunavut [Province: Canada] 124012 Nova Scotia [Province: Canada] 124013 New Brunswick [Province: Canada] 124024 Quebec [Province: Canada] 124035 Ontario [Province: Canada] 124046 Manitoba [Province: Canada] 124047 Saskatchewan [Province: Canada] 124048 Alberta [Province: Canada] 124059 British Columbia [Province: Canada] 152002 Antofagasta and Tarapacá [Region: Chile] 152004 Atacama and Coquimbo [Region: Chile] 152007 Del Maule [Region: Chile] 152008 Del Biobio [Region: Chile] 152009 La Araucanía [Region: Chile] 152010 Aysen del Gral Carlos Ibáñez del Campo and Los Lagos [Region: Chile] 152012 Magallanes and La Antártica Chilena [Region: Chile] 152013 Libertador General Bernardo O"Higgins, Metropolitana de Santiago, and Valparaiso [Region: Chile] 152099 Unknown [Region: Chile] 156011 Beijing (municipality) [Province: China] 156012 Tianjin (municipality) [Province: China] 156013 Hebei [Province: China] 156014 Shanxi [Province: China] 156015 Inner Mongolia [Province: China] 156021 Liaoning [Province: China] 156022 Jilin [Province: China] 156023 Heilongjiang [Province: China] 156031 Shanghai (municipality) [Province: China] 156032 Jiangsu [Province: China] 156033 Zhejiang [Province: China] 156034 Anhui [Province: China] 156035 Fujian [Province: China] 156036 Jiangxi [Province: China] 156037 Shangdong [Province: China] 156041 Henan [Province: China] 156042 Hubei [Province: China] 156043 Hunan [Province: China] 156044 Guangdong and Hainan [Province: China] 156045 Guangxi [Province: China] 156051 Sichuan [Province: China] 156052 Guizhou [Province: China] 156053 Yunnan [Province: China] 156054 Tibet [Province: China] 156061 Shaanxi [Province: China] 156062 Gansu [Province: China] 156063 Qinghai [Province: China] 156064 Ningxia [Province: China] 156065 Xinjiang [Province: China] 170005 Antioquia [Department: Colombia] 170008 Atlántico [Department: Colombia] 170011 Bogotá [Department: Colombia] 170013 Bolívar and Sucre [Department: Colombia] 170015 Boyacá and Casanare [Department: Colombia] 170018 Caquetá [Department: Colombia] 170019 Cauca [Department: Colombia] 170023 Córdoba [Department: Colombia] 170025 Cundinamarca [Department: Colombia] 170027 Chocó [Department: Colombia] 170041 Huila [Department: Colombia] 170044 La Guajira [Department: Colombia] 170047 Cesar and Magdalena [Department: Colombia] 170050 Meta and Vichada [Department: Colombia] 170052 Nariño [Department: Colombia] 170054 Norte de Santander [Department: Colombia] 170066 Caldas, Quindío, and Risaralda [Department: Colombia] 170068 Santander [Department: Colombia] 170073 Tolima [Department: Colombia] 170076 Valle [Department: Colombia] 170081 Arauca [Department: Colombia] 170086 Putumayo [Department: Colombia] 170088 San Andrés [Department: Colombia] 170091 Amazonas [Department: Colombia] 170095 Guaviare, Vaupés, and Guainía [Department: Colombia] 188001 San José [Province: Costa Rica] 188002 Alajuela [Province: Costa Rica] 188003 Cartago [Province: Costa Rica] 188004 Heredia [Province: Costa Rica] 188005 Guanacaste [Province: Costa Rica] 188006 Puntarenas [Province: Costa Rica] 188007 Limón [Province: Costa Rica] 192001 Pinar del Río [Province: Cuba] 192002 La Habana [Province: Cuba] 192003 Ciudad de la Habana [Province: Cuba] 192004 Matanzas [Province: Cuba] 192005 Villa Clara [Province: Cuba] 192006 Cienfuegos [Province: Cuba] 192007 Sancti Spiritus [Province: Cuba] 192008 Ciego de Avila [Province: Cuba] 192009 Camagüey [Province: Cuba] 192010 Las Tunas [Province: Cuba] 192011 Holguín [Province: Cuba] 192012 Granma [Province: Cuba] 192013 Santiago de Cuba [Province: Cuba] 192014 Guantánamo [Province: Cuba] 192099 Isla de la Juventud [Province: Cuba] 214001 Federal district and Santo Domingo [Province: Dominican Republic] 214002 Azua [Province: Dominican Republic] 214003 Baoruco [Province: Dominican Republic] 214004 Barahona [Province: Dominican Republic] 214005 Dajabón [Province: Dominican Republic] 214006 Duarte [Province: Dominican Republic] 214007 Elías Piña [Province: Dominican Republic] 214008 El Seibo and Hato Mayor [Province: Dominican Republic] 214009 Espaillat [Province: Dominican Republic] 214010 Independencia [Province: Dominican Republic] 214011 La Altagracia and La Romana [Province: Dominican Republic] 214013 La Vega and Monseñor Nouel [Province: Dominican Republic] 214014 María Trinidad Sánchez and Samaná [Province: Dominican Republic] 214015 Monte Cristi [Province: Dominican Republic] 214016 Pedernales [Province: Dominican Republic] 214017 Peravia and San José de Ocoa [Province: Dominican Republic] 214018 Puerto Plata [Province: Dominican Republic] 214019 Hermanas Mirabal [Province: Dominican Republic] 214021 San Cristóbal and Monte Plata [Province: Dominican Republic] 214022 San Juan [Province: Dominican Republic] 214023 San Pedro de Macorís [Province: Dominican Republic] 214024 Sánchez Ramírez [Province: Dominican Republic] 214025 Santiago [Province: Dominican Republic] 214026 Santiago Rodríguez [Province: Dominican Republic] 214027 Valverde [Province: Dominican Republic] 218001 Azuay [Province: Ecuador] 218002 Bolívar [Province: Ecuador] 218004 Carchi [Province: Ecuador] 218005 Cotopaxi [Province: Ecuador] 218006 Chimborazo [Province: Ecuador] 218007 El Oro [Province: Ecuador] 218009 Cañar, Esmeraldas, Guayas, Manabí, Manga del Cura [Disputed canton], Pichincha, El Piedrero [Disputed canton], Los Ríos, Santa Elena, Santo Domingo de las Tsáchilas, Galápagos [Disputed canton], Pichincha, El Piedrero 218010 Imbabura, Las Golondrinas [Disputed canton] [Disputed canton] 218011 Loja [Province: Ecuador] 218014 Morona Santiago [Province: Ecuador] 218016 Pastaza [Province: Ecuador] 218018 Tungurahua [Province: Ecuador] 218019 Zamora Chinchipe [Province: Ecuador] 218021 Napo, Orellana, Sucumbíos [Province: Ecuador] 218099 Unknown [Province: Ecuador] 222001 Ahuachapán [Department: El Salvador] 222002 Santa Ana [Department: El Salvador] 222003 Sonsonate [Department: El Salvador] 222004 Chalatenango [Department: El Salvador] 222005 La Libertad [Department: El Salvador] 222006 San Salvador [Department: El Salvador] 222007 Cuscatlán [Department: El Salvador] 222008 La Paz [Department: El Salvador] 222009 Cabañas [Department: El Salvador] 222010 San Vicente [Department: El Salvador] 222011 Usulután [Department: El Salvador] 222012 San Miguel [Department: El Salvador] 222013 Morazán [Department: El Salvador] 222014 La Unión [Department: El Salvador] 231001 Tigray [Region: Ethiopia] 231002 Affar [Region: Ethiopia] 231003 Amhara [Region: Ethiopia] 231004 Oromiya [Region: Ethiopia] 231005 Somali [Region: Ethiopia] 231006 Benishangul-Gumz [Region: Ethiopia] 231007 Southern Nations, Nationalities, and People (SNPP) [Region: Ethiopia] 231012 Gambela [Region: Ethiopia] 231013 Harari [Region: Ethiopia] 231014 Addis Ababa [Region: Ethiopia] 231015 Dire Dawa [Region: Ethiopia] 231017 Special region [Region: Ethiopia] 238094 Falkland Islands [Province: Argentina] 239094 South Georgia and South Sandwich Islands [Province: Argentina] 242001 Ba [Province: Fiji] 242003 Bua, Cakaudrove [Province: Fiji] 242006 Kadavu, Lau, Lomaiviti, Rotuma [Province: Fiji] 242007 Macuata [Province: Fiji] 242008 Nadroha [Province: Fiji] 242009 Naitasiri, Rewa [Province: Fiji] 242011 Ra [Province: Fiji] 242014 Serua, Namosi [Province: Fiji] 242015 Tailevu [Province: Fiji] 242099 Ships, unknown [Province: Fiji] 250001 Guadeloupe [Oversea Department, France] 250002 Martinique [Oversea Department, France] 250003 French Guyana [Oversea Department, France] 250004 Réunion Island [Oversea Department, France] 250011 Île-de-France [Region: France] 250021 Champagne-Ardenne [Region: France] 250022 Picardy [Region: France] 250023 Upper Normandy [Region: France] 250024 Centre [Region: France] 250025 Lower Normandy [Region: France] 250026 Burgundy [Region: France] 250031 North Pas-de-Calais [Region: France] 250041 Lorraine [Region: France] 250042 Alsace [Region: France] 250043 Franche-Comté [Region: France] 250052 Loire Valley [Region: France] 250053 Brittany [Region: France] 250054 Poitou-Charentes [Region: France] 250072 Aquitaine [Region: France] 250073 Midi-Pyrénées [Region: France] 250074 Limousin [Region: France] 250082 Rhône-Alpes [Region: France] 250083 Auvergne [Region: France] 250091 Languedoc-Roussillon [Region: France] 250093 Provence-Alpes-Riviera [Region: France] 250094 Corsica [Region: France] 250999 Unknown [Region: France] 275001 Jenin [Governorate: Palestine] 275005 Tubas [Governorate: Palestine] 275010 Tulkarm [Governorate: Palestine] 275015 Nablus [Governorate: Palestine] 275020 Qalqiliya [Governorate: Palestine] 275025 Salfit [Governorate: Palestine] 275030 Ramallah and Al-Bireh [Governorate: Palestine] 275035 Jericho [Governorate: Palestine] 275040 Jerusalem [Governorate: Palestine] 275045 Bethlehem [Governorate: Palestine] 275050 Hebron [Governorate: Palestine] 275055 North Gaza [Governorate: Palestine] 275060 Gaza [Governorate: Palestine] 275065 Deir Al-Balah [Governorate: Palestine] 275070 Khan Yunis [Governorate: Palestine] 275075 Rafah [Governorate: Palestine] 276001 Schleswig-Holstein [State: Germany] 276002 Hamburg [State: Germany] 276003 Niedersachsen [State: Germany] 276004 Bremen [State: Germany] 276005 Nordrhein-Westfalen [State: Germany] 276006 Hessen [State: Germany] 276007 Rheinland-Pfalz [State: Germany] 276008 Baden-Württemberg [State: Germany] 276009 Bayern [State: Germany] 276010 Saarland [State: Germany] 276012 Brandenburg [State: Germany] 276013 Mecklenburg-West Pomerania [State: Germany] 276014 Saxony [State: Germany] 276015 Saxony-Anhalt [State: Germany] 276016 Thuringia [State: Germany] 276017 East Berlin [State: Germany] 276018 West Berlin [State: Germany] 276099 NIU (Not in universe) [State: Germany] 288001 Western [Region: Ghana] 288002 Central [Region: Ghana] 288003 Greater Accra [Region: Ghana] 288004 Volta [Region: Ghana] 288005 Eastern [Region: Ghana] 288006 Ashanti [Region: Ghana] 288007 Brong Ahafo [Region: Ghana] 288008 Northern [Region: Ghana] 288009 Upper East [Region: Ghana] 288010 Upper West [Region: Ghana] 300001 Etolia and Akarnania [Department: Greece] 300003 Viotia [Department: Greece] 300004 Evia [Department: Greece] 300005 Evrytania [Department: Greece] 300006 Fthiotida [Department: Greece] 300007 Fokida [Department: Greece] 300011 Argolida [Department: Greece] 300012 Arkadia [Department: Greece] 300013 Achaia [Department: Greece] 300014 Ilia [Department: Greece] 300015 Korinthia [Department: Greece] 300016 Lakonia [Department: Greece] 300017 Messinia [Department: Greece] 300021 Zakynthos [Department: Greece] 300022 Kerkyra [Department: Greece] 300023 Kefallinia [Department: Greece] 300024 Lefkada [Department: Greece] 300031 Arta [Department: Greece] 300032 Thesprotia [Department: Greece] 300033 Ioannina [Department: Greece] 300034 Preveza [Department: Greece] 300041 Karditsa [Department: Greece] 300042 Larissa [Department: Greece] 300043 Magnissia [Department: Greece] 300044 Trikala [Department: Greece] 300051 Grevena [Department: Greece] 300052 Drama [Department: Greece] 300053 Imathia [Department: Greece] 300054 Thessaloniki [Department: Greece] 300055 Kavala [Department: Greece] 300056 Kastoria [Department: Greece] 300057 Kilkis [Department: Greece] 300058 Kozani [Department: Greece] 300059 Pella [Department: Greece] 300061 Pieria [Department: Greece] 300062 Serres [Department: Greece] 300063 Florina [Department: Greece] 300064 Chalkidiki and Aghion Oros [Department: Greece] 300071 Evros [Department: Greece] 300072 Xanthi [Department: Greece] 300073 Rodopi [Department: Greece] 300081 Dodekanissos [Department: Greece] 300082 Kyklades [Department: Greece] 300083 Lesvos [Department: Greece] 300084 Samos [Department: Greece] 300085 Chios [Department: Greece] 300091 Iraklio [Department: Greece] 300092 Lassithi [Department: Greece] 300093 Rethymno [Department: Greece] 300094 Chania [Department: Greece] 300101 Prefecture of Athens [Department: Greece] 300102 Prefecture of East Attiki [Department: Greece] 300103 Prefecture of West Attiki [Department: Greece] 300104 Prefecture of Pireas [Department: Greece] 324001 Boké [Region: Guinea] 324002 Faranah [Region: Guinea] 324003 Kankan [Region: Guinea] 324004 Kindia, Labe, Mamou [Region: Guinea] 324007 N'zerekore [Region: Guinea] 324008 Conakry [Region: Guinea] 332003 Nord (North) and Nord'est (North East) [Department: Haiti] 332006 Centre (Central), L'Artibonite, Ouest (West), Sud'Est (South East) [Department: Haiti] 332007 Grand'Anse, Nippes, Sud (South) [Department: Haiti] 332009 Nord'Ouest (North West) [Department: Haiti] 356001 Jammu and Kashmir [State: India] 356002 Himachal Pradesh [State: India] 356003 Punjab [State: India] 356004 Chandigarh [State: India] 356006 Haryana [State: India] 356007 Delhi [State: India] 356008 Rajasthan [State: India] 356009 Uttar Pradesh and Uttaranchal [State: India] 356010 Bihar and Jharkhand [State: India] 356011 Sikkim [State: India] 356012 Arunachal Pradesh [State: India] 356013 Nagaland [State: India] 356014 Manipur [State: India] 356015 Mizoram [State: India] 356016 Tripura [State: India] 356017 Meghalaya [State: India] 356018 Assam [State: India] 356019 West Bengal [State: India] 356021 Orissa [State: India] 356023 Chhattisgarh and Madhya Pradesh [State: India] 356024 Gujarat [State: India] 356026 Dadra and Nagar Haveli [State: India] 356027 Maharashtra [State: India] 356028 Andhra Pradesh [State: India] 356029 Karnataka [State: India] 356030 Daman and Diu and Goa [State: India] 356031 Lakshadweep [State: India] 356032 Kerala [State: India] 356033 Tamil Nadu [State: India] 356034 Pondicherry [State: India] 356035 Andaman and Nicobar Islands [State: India] 360011 Nanggroe Aceh Darussalam [Province: Indonesia] 360012 Sumatera Utara [Province: Indonesia] 360013 Sumatera Barat [Province: Indonesia] 360014 Riau and Kepulauan Riau [Province: Indonesia] 360015 Jambi [Province: Indonesia] 360016 Sumatera Selatan and Bangka Belitung [Province: Indonesia] 360017 Bengkulu [Province: Indonesia] 360018 Lampung [Province: Indonesia] 360031 DKI Jakarta [Province: Indonesia] 360032 West Java and Banten [Province: Indonesia] 360033 Jawa Tengah [Province: Indonesia] 360034 DI Yogyakarta [Province: Indonesia] 360035 Jawa Timur [Province: Indonesia] 360051 Bali [Province: Indonesia] 360052 Nusa Tenggara Barat [Province: Indonesia] 360053 East Nusa Tenggara [Province: Indonesia] 360061 Kalimantan Barat [Province: Indonesia] 360062 Kalimantan Tengah [Province: Indonesia] 360063 Kalimantan Selatan [Province: Indonesia] 360064 Kalimantan Timur [Province: Indonesia] 360071 Sulawesi Utara and Gorontalo [Province: Indonesia] 360072 Sulawesi Tengah [Province: Indonesia] 360073 Sulawesi Selatan, Sulawesi Tenggara and Sulawesi Barat [Province: Indonesia] 360081 Maluku and Maluku Utara [Province: Indonesia] 360094 Papua and Papua Barat [Province: Indonesia] 364000 Markazi [Province: Iran] 364001 Gilan [Province: Iran] 364002 Mazandaran [Province: Iran] 364003 East Azarbayejan [Province: Iran] 364004 West Azarbayejan [Province: Iran] 364005 Kermanshah [Province: Iran] 364006 Khuzestan [Province: Iran] 364007 Fars [Province: Iran] 364008 Kerman [Province: Iran] 364009 Khorasan-e- Razavi [Province: Iran] 364010 Esfahan [Province: Iran] 364011 Sistan and Baluchestan [Province: Iran] 364012 Kordestan [Province: Iran] 364013 Hamedan [Province: Iran] 364014 Chaharmahal and Bakhtiyari [Province: Iran] 364015 Lorestan [Province: Iran] 364016 Ilam [Province: Iran] 364017 Kohgiluyeh and Boyerahmad [Province: Iran] 364018 Bushehr [Province: Iran] 364019 Zanjan [Province: Iran] 364020 Semnan [Province: Iran] 364021 Yazd [Province: Iran] 364022 Hormozgan [Province: Iran] 364023 Tehran [Province: Iran] 364024 Ardebil [Province: Iran] 364025 Qom [Province: Iran] 364026 Qazvin [Province: Iran] 364027 Golestan [Province: Iran] 364028 North Khorasan [Province: Iran] 364029 South Khorasan [Province: Iran] 368011 Dhok [Governorate: Iraq] 368012 Nineveh [Governorate: Iraq] 368013 Al-Sulaimaniya [Governorate: Iraq] 368014 Al-Tameem [Governorate: Iraq] 368015 Arbil [Governorate: Iraq] 368021 Diala [Governorate: Iraq] 368022 Al-Anbar [Governorate: Iraq] 368023 Baghdad [Governorate: Iraq] 368024 Babylon [Governorate: Iraq] 368025 Kerbela [Governorate: Iraq] 368026 Wasit [Governorate: Iraq] 368027 Salah Al-Deen [Governorate: Iraq] 368028 Al-Najaf [Governorate: Iraq] 368031 Al-Qadisiya [Governorate: Iraq] 368032 Al-Muthanna [Governorate: Iraq] 368033 Thi-Qar [Governorate: Iraq] 368034 Maysan [Governorate: Iraq] 368035 Al-Basrah [Governorate: Iraq] 372001 Border [Region: Ireland] 372002 Dublin [Region: Ireland] 372003 Mid-East [Region: Ireland] 372004 Midlands [Region: Ireland] 372005 Mid-West [Region: Ireland] 372006 South-East [Region: Ireland] 372007 South-West [Region: Ireland] 372008 West [Region: Ireland] 376001 Jerusalem [District: Israel] 376002 Northern [District: Israel] 376003 Haifa [District: Israel] 376004 Central [District: Israel] 376005 Tel-Aviv [District: Israel] 376006 Southern [District: Israel] 376009 Judea, Samaria, and Gaza areas [District: Israel] 380001 Piemonte-Valle d'Aosta [Region: Italy] 380003 Lombardia [Region: Italy] 380004 Trentino-Alto Adige [Region: Italy] 380005 Veneto [Region: Italy] 380006 Friuli-Venezia Giulia [Region: Italy] 380007 Liguria [Region: Italy] 380008 Emilia-Romagna [Region: Italy] 380009 Toscana [Region: Italy] 380010 Umbria [Region: Italy] 380011 Marche [Region: Italy] 380012 Lazio [Region: Italy] 380013 Abruzzo [Region: Italy] 380014 Molise [Region: Italy] 380015 Campania [Region: Italy] 380016 Puglia [Region: Italy] 380017 Basilicata [Region: Italy] 380018 Calabria [Region: Italy] 380019 Sicilia [Region: Italy] 380020 Sardegna [Region: Italy] 388001 Kingston [Parish: Jamaica] 388002 Saint Andrew [Parish: Jamaica] 388003 Saint Thomas [Parish: Jamaica] 388004 Portland [Parish: Jamaica] 388005 Saint Mary [Parish: Jamaica] 388006 Saint Ann [Parish: Jamaica] 388007 Trelawny [Parish: Jamaica] 388008 Saint James [Parish: Jamaica] 388009 Hanover [Parish: Jamaica] 388010 Westmoreland [Parish: Jamaica] 388011 Saint Elizabeth [Parish: Jamaica] 388012 Manchester [Parish: Jamaica] 388013 Clarendon [Parish: Jamaica] 388014 Saint Catherine [Parish: Jamaica] 400011 Amman [Governorate: Jordan] 400012 Balqa [Governorate: Jordan] 400013 Zarqa [Governorate: Jordan] 400014 Madaba [Governorate: Jordan] 400021 Irbid [Governorate: Jordan] 400022 Mafraq [Governorate: Jordan] 400023 Jarash [Governorate: Jordan] 400024 Ajlun [Governorate: Jordan] 400031 Karak [Governorate: Jordan] 400032 Tafilah [Governorate: Jordan] 400033 Ma'an [Governorate: Jordan] 400034 Aqaba [Governorate: Jordan] 404001 Nairobi [Province: Kenya] 404002 Central Province [Province: Kenya] 404003 Coast Province [Province: Kenya] 404004 Eastern Province [Province: Kenya] 404005 North-Eastern Province [Province: Kenya] 404006 Nyanza Province [Province: Kenya] 404007 Rift Valley Province [Province: Kenya] 404008 Western Province [Province: Kenya] 417001 Gorkenesh Bishkek [Region: Kyrgyz Republic] 417002 Issyk-Kul [Region: Kyrgyz Republic] 417003 Dzhalal-Abad [Region: Kyrgyz Republic] 417004 Naryn [Region: Kyrgyz Republic] 417005 Batken [Region: Kyrgyz Republic] 417006 Oshskaya [Region: Kyrgyz Republic] 417007 Talasskaya [Region: Kyrgyz Republic] 417008 Chuya [Region: Kyrgyz Republic] 430006 Bong [County: Liberia] 430009 Grand Bassa and Rivercess [County: Liberia] 430012 Grand Cape Mount [County: Liberia] 430015 Grand Gedeh and River Gee [County: Liberia] 430021 Lofa and Gbarpolu [County: Liberia] 430027 Maryland and Grand Kru [County: Liberia] 430030 Montserrado, Bomi, and Margibi [County: Liberia] 430033 Nimba [County: Liberia] 430039 Sinoe [County: Liberia] 454101 Chitipa [District: Malawi] 454102 Karonga [District: Malawi] 454103 Nkhata Bay, Likoma [District: Malawi] 454104 Rumphi [District: Malawi] 454105 Mzimba, Mzuzu city [District: Malawi] 454201 Kasungu [District: Malawi] 454202 Nkhota Kota [District: Malawi] 454203 Ntchisi [District: Malawi] 454204 Dowa [District: Malawi] 454205 Salima [District: Malawi] 454206 Lilongwe [District: Malawi] 454207 Mchinji [District: Malawi] 454208 Dedza [District: Malawi] 454209 Ntcheu [District: Malawi] 454301 Mangochi [District: Malawi] 454302 Machinga [District: Malawi] 454303 Zomba [District: Malawi] 454304 Chiradzulu [District: Malawi] 454305 Blantyre [District: Malawi] 454307 Thyolo [District: Malawi] 454308 Mulanje [District: Malawi] 454310 Chikwawa [District: Malawi] 454311 Nsanje [District: Malawi] 454313 Mwanza, Neno [District: Malawi] 458001 Johor [State: Malaysia] 458002 Kedah [State: Malaysia] 458003 Kelantan [State: Malaysia] 458004 Melaka [State: Malaysia] 458005 Negeri Sembilan [State: Malaysia] 458006 Pahang [State: Malaysia] 458007 Pulau Pinang [State: Malaysia] 458008 Perak [State: Malaysia] 458009 Perlis [State: Malaysia] 458010 Selangor and Kuala Lumpur Federal Territory [State: Malaysia] 458011 Terengganu [State: Malaysia] 458012 Sabah and Labuan Federal Territory [State: Malaysia] 458013 Sarawak [State: Malaysia] 466001 Kayes [Region: Mali] 466002 Koulikoro [Region: Mali] 466003 Sikasso [Region: Mali] 466004 Ségou [Region: Mali] 466005 Mopti [Region: Mali] 466006 Tombouctou [Region: Mali] 466007 Gao and Kidal [Region: Mali] 466009 Bamako [Region: Mali] 466099 Unknown [Region: Mali] 484001 Aguascalientes [State: Meico] 484002 Baja California [State: Meico] 484003 Baja California Sur [State: Meico] 484004 Campeche [State: Meico] 484005 Coahuila [State: Meico] 484006 Colima [State: Meico] 484007 Chiapas [State: Meico] 484008 Chihuahua [State: Meico] 484009 Distrito Federal [State: Meico] 484010 Durango [State: Meico] 484011 Guanajuato [State: Meico] 484012 Guerrero [State: Meico] 484013 Hidalgo [State: Meico] 484014 Jalisco [State: Meico] 484015 México [State: Meico] 484016 Michoacán [State: Meico] 484017 Morelos [State: Meico] 484018 Nayarit [State: Meico] 484019 Nuevo León [State: Meico] 484020 Oaxaca [State: Meico] 484021 Puebla [State: Meico] 484022 Querétaro [State: Meico] 484023 Quintana Roo [State: Meico] 484024 San Luis Potosí [State: Meico] 484025 Sinaloa [State: Meico] 484026 Sonora [State: Meico] 484027 Tabasco [State: Meico] 484028 Tamaulipas [State: Meico] 484029 Tlaxcala [State: Meico] 484030 Veracruz [State: Meico] 484031 Yucatán [State: Meico] 484032 Zacatecas [State: Meico] 496001 Arkhangai [Province: Mongolia] 496002 Bayan-Ölgii [Province: Mongolia] 496003 Bayankhongor [Province: Mongolia] 496004 Bulgan [Province: Mongolia] 496005 Govi-Altai [Province: Mongolia] 496006 Dornogovi [Province: Mongolia] 496007 Dornod [Province: Mongolia] 496008 Dundgovi and Govisumber [Province: Mongolia] 496009 Zavkhan [Province: Mongolia] 496010 Övörkhangai [Province: Mongolia] 496011 Ömnögovi [Province: Mongolia] 496012 Sükhbaatar [Province: Mongolia] 496013 Selenge [Province: Mongolia] 496014 Töv [Province: Mongolia] 496015 Uvs [Province: Mongolia] 496016 Khovd [Province: Mongolia] 496017 Khövsgöl [Province: Mongolia] 496018 Khentii [Province: Mongolia] 496019 Darkhan-Uul [Province: Mongolia] 496020 Ulaanbaatar [Province: Mongolia] 496021 Orkhon [Province: Mongolia] 504001 Oued-Ed-Dahab-Lagouira [Region: Morocco] 504002 Laâyoune-Boujdour-Sakia El Hamra [Region: Morocco] 504003 Guelmin-Es-Samara [Region: Morocco] 504004 Souss-Massa-Draâ [Region: Morocco] 504005 Charb-Chrarda-Béni Hssen [Region: Morocco] 504006 Chaouia-Ouardigha [Region: Morocco] 504007 Marrakech-Tensift-Al Haouz [Region: Morocco] 504008 Oriental [Region: Morocco] 504009 Grand-Casablanca [Region: Morocco] 504010 Rabat-Salé-Zemmour-Zaer [Region: Morocco] 504011 Doukala Abda [Region: Morocco] 504012 Tadla Azilal [Region: Morocco] 504013 Meknès-Tafilalet [Region: Morocco] 504014 Fès-Boulemane [Region: Morocco] 504015 Taza-Al Heiceima-Taounate [Region: Morocco] 504016 Tanger-Tétouan [Region: Morocco] 508001 Niassa [Province: Mozambique] 508002 Cabo Delgado [Province: Mozambique] 508003 Nampula [Province: Mozambique] 508004 Zambézia [Province: Mozambique] 508005 Tete [Province: Mozambique] 508006 Manica [Province: Mozambique] 508007 Sofala [Province: Mozambique] 508008 Inhambane [Province: Mozambique] 508009 Gaza [Province: Mozambique] 508010 Maputo province [Province: Mozambique] 508011 Maputo city [Province: Mozambique] 524001 Mechi [Administrative zone: Nepal] 524002 Koshi [Administrative zone: Nepal] 524003 Sagarmatha [Administrative zone: Nepal] 524004 Janakpur [Administrative zone: Nepal] 524005 Bagmati [Administrative zone: Nepal] 524006 Narayani [Administrative zone: Nepal] 524007 Gandaki [Administrative zone: Nepal] 524008 Dhawalagiri [Administrative zone: Nepal] 524009 Lumbini [Administrative zone: Nepal] 524010 Rapti [Administrative zone: Nepal] 524011 Bheri [Administrative zone: Nepal] 524012 Karnali [Administrative zone: Nepal] 524013 Seti [Administrative zone: Nepal] 524014 Mahakali [Administrative zone: Nepal] 558005 Nueva Segovia [Department: Nicaragua] 558010 Jinotega [Department: Nicaragua] 558020 Madríz [Department: Nicaragua] 558030 Chinandega [Department: Nicaragua] 558035 Leon and Esteli [Department: Nicaragua] 558040 Matagalpa [Department: Nicaragua] 558050 Boaco [Department: Nicaragua] 558055 Managua [Department: Nicaragua] 558060 Masaya [Department: Nicaragua] 558065 Chontales [Department: Nicaragua] 558070 Granada [Department: Nicaragua] 558075 Carazo [Department: Nicaragua] 558080 Rivas [Department: Nicaragua] 558085 Río San Juan [Department: Nicaragua] 558093 Atlántico Norte and Atlántico Sur [Department: Nicaragua] 558099 Unknown [Department: Nicaragua] 566001 Abia [State: Nigeria] 566002 Adamawa [State: Nigeria] 566003 Akwa Ibom [State: Nigeria] 566004 Anambra [State: Nigeria] 566005 Bauchi [State: Nigeria] 566006 Bayelsa [State: Nigeria] 566007 Benue [State: Nigeria] 566008 Borno [State: Nigeria] 566009 Cross River [State: Nigeria] 566010 Delta [State: Nigeria] 566011 Ebonyi [State: Nigeria] 566012 Edo [State: Nigeria] 566013 Ekiti [State: Nigeria] 566014 Enugu [State: Nigeria] 566015 Gombe [State: Nigeria] 566016 Imo [State: Nigeria] 566017 Jigawa [State: Nigeria] 566018 Kaduna [State: Nigeria] 566019 Kano [State: Nigeria] 566020 Katsina [State: Nigeria] 566021 Kebbi [State: Nigeria] 566022 Kogi [State: Nigeria] 566023 Kwara [State: Nigeria] 566024 Lagos [State: Nigeria] 566025 Nasarawa [State: Nigeria] 566026 Niger [State: Nigeria] 566027 Ogun [State: Nigeria] 566028 Ondo [State: Nigeria] 566029 Osun [State: Nigeria] 566030 Oyo [State: Nigeria] 566031 Plateau [State: Nigeria] 566032 Rivers [State: Nigeria] 566033 Sokoto [State: Nigeria] 566034 Taraba [State: Nigeria] 566035 Yobe [State: Nigeria] 566036 Zamfara [State: Nigeria] 566037 Federal Capital Territory Abuja [State: Nigeria] 566099 Unknown [State: Nigeria] 586001 North-West Frontier Province [Province: Pakistan] 586002 Fata [Province: Pakistan] 586003 Punjab, Islamabad [Province: Pakistan] 586004 Sind [Province: Pakistan] 586005 Baluchistan [Province: Pakistan] 586007 Northern areas [Province: Pakistan] 586008 Kashmir [Province: Pakistan] 591002 Coclé [Province: Panama] 591003 Colón, Comarca Kuna Yala (San Blas) [Province: Panama] 591004 Bocas de Toro, Chiriquí, Comarca Ngäbe Buglé, Veraguas [Province: Panama] 591005 Comarca Emberá, Darién [Province: Panama] 591006 Herrera [Province: Panama] 591007 Los Santos [Province: Panama] 591008 Panamá [Province: Panama] 600000 Asunción [Department: Paraguay] 600001 Concepción [Department: Paraguay] 600002 San Pedro [Department: Paraguay] 600007 Itapúa [Department: Paraguay] 600008 Misiones and Ñeembucú [Department: Paraguay] 600009 Guairá, Caazapá, and Paraguarí [Department: Paraguay] 600010 Cordillera, Caaguazú, Alto Paraná, and Canindeyú [Department: Paraguay] 600011 Central [Department: Paraguay] 600013 Amambay [Department: Paraguay] 600015 Presidente Hayes, Boqueron, and Alto Paraguay [Department: Paraguay] 600099 Unknown [Department: Paraguay] 604001 Amazonas [Region: Peru] 604002 Ancash [Region: Peru] 604003 Apurímac [Region: Peru] 604004 Arequipa [Region: Peru] 604005 Ayacucho [Region: Peru] 604006 Cajamarca [Region: Peru] 604007 Callao [Region: Peru] 604008 Cusco [Region: Peru] 604009 Huancavelica [Region: Peru] 604010 Huánuco [Region: Peru] 604011 Ica [Region: Peru] 604012 Junín [Region: Peru] 604013 La Libertad [Region: Peru] 604014 Lambayeque [Region: Peru] 604015 Lima [Region: Peru] 604016 Loreto [Region: Peru] 604017 Madre de Dios [Region: Peru] 604018 Moquegua [Region: Peru] 604019 Pasco [Region: Peru] 604020 Piura [Region: Peru] 604021 Puno [Region: Peru] 604022 San Martín [Region: Peru] 604023 Tacna [Region: Peru] 604024 Tumbes [Region: Peru] 604025 Ucayali [Region: Peru] 608001 Ilocos [Region: Philippines] 608002 Cagayan Valley [Region: Philippines] 608003 Central Luzon [Region: Philippines] 608004 Southern Tagalog [Region: Philippines] 608005 Bicol [Region: Philippines] 608006 Western Visayas [Region: Philippines] 608007 Central Visayas [Region: Philippines] 608008 Eastern Visayas [Region: Philippines] 608009 Western Mindanao [Region: Philippines] 608011 Northern Mindanao, Southern Mindanao, and Caraga [Region: Philippines] 608012 Central Mindanao and Autonomous Region of Muslim Mindanao [Region: Philippines] 608013 National Capital Region [Region: Philippines] 608014 Cordillera Administrative Region [Region: Philippines] 620111 Minho-Lima [Subregion: Portugal] 620112 Cávado [Subregion: Portugal] 620113 Ave [Subregion: Portugal] 620114 Grande Porto [Subregion: Portugal] 620115 Tâmega [Subregion: Portugal] 620116 Entre Douro e Vouga [Subregion: Portugal] 620117 Douro [Subregion: Portugal] 620118 Alto Trás-os-Montes [Subregion: Portugal] 620150 Algarve [Subregion: Portugal] 620161 Baixo Vouga [Subregion: Portugal] 620162 Baixo Mondego [Subregion: Portugal] 620163 Pinhal Litoral [Subregion: Portugal] 620165 Dão-Lafões [Subregion: Portugal] 620166 Oeste [Subregion: Portugal] 620167 Médio Tejo [Subregion: Portugal] 620169 Other Center [Subregion: Portugal] 620171 Grande Lisboa [Subregion: Portugal] 620172 Península de Setúbal [Subregion: Portugal] 620185 Lezíria do Tejo [Subregion: Portugal] 620189 Other Alentejo [Subregion: Portugal] 620200 Região Autónoma dos Açores [Subregion: Portugal] 620300 Região Autónoma da Madeira [Subregion: Portugal] 630101 G7201001 [PUMA: Puerto Rico] 630104 G7201002, G7201003, G7201004 [PUMA: Puerto Rico] 630110 G7201100 [PUMA: Puerto Rico] 630180 G7201800 [PUMA: Puerto Rico] 630200 G7200100, G7200200, G7200300, G7200400, G7200500, G72000700, G7201200, G7201300, G7201400, G7201500, G7201600, G7201700, G7201900, G7202000, G7202100, G7202200, G7202300, G7202400, G7202600, G7200600, G7200801, G7200802, G7200900 [PUMA: Puerto Rico] 630250 G7202500 [PUMA: Puerto Rico] 642001 Alba [County: Romania] 642002 Arad [County: Romania] 642003 Arges [County: Romania] 642004 Bacau [County: Romania] 642005 Bihor [County: Romania] 642006 Bistrita Nasaud [County: Romania] 642007 Botosani [County: Romania] 642008 Brasov [County: Romania] 642009 Braila [County: Romania] 642010 Buzau [County: Romania] 642011 Caras Severin [County: Romania] 642012 Cluj [County: Romania] 642013 Constanta [County: Romania] 642014 Covasna [County: Romania] 642015 Dimbovita [County: Romania] 642016 Dolj [County: Romania] 642017 Galati [County: Romania] 642018 Gorj [County: Romania] 642019 Harghita [County: Romania] 642020 Hunedoara [County: Romania] 642022 Iasi [County: Romania] 642024 Maramures [County: Romania] 642025 Mehedinti [County: Romania] 642026 Mures [County: Romania] 642027 Neamt [County: Romania] 642028 Olt [County: Romania] 642029 Prahova [County: Romania] 642030 Satu Mare [County: Romania] 642031 Salaj [County: Romania] 642032 Sibiu [County: Romania] 642033 Suceava [County: Romania] 642034 Teleorman [County: Romania] 642035 Timis [County: Romania] 642036 Tulcea [County: Romania] 642037 Vaslui [County: Romania] 642038 Valcea [County: Romania] 642039 Vrancea [County: Romania] 642043 Bucharest Sector 1 to 6 [County: Romania] 642051 Calarasi, Giurgiu, Ialomita, Ilfov [County: Romania] 646001 Kigali City [Province: Rwanda] 646002 Kigali Ngali [Province: Rwanda] 646004 Gitarama [Province: Rwanda] 646005 Butare [Province: Rwanda] 646006 Gikongoro [Province: Rwanda] 646007 Cyangugu [Province: Rwanda] 646008 Kibuye [Province: Rwanda] 646009 Gisenyi [Province: Rwanda] 646010 Ruhengeri [Province: Rwanda] 646012 Byumba, Kibungo and Umutara [Province: Rwanda] 686001 Dakar [Region: Senegal] 686002 Diourbel [Region: Senegal] 686003 Fatick [Region: Senegal] 686004 Kaolack [Region: Senegal] 686005 Kolda [Region: Senegal] 686008 Louga, Saint Louis, Matam [Region: Senegal] 686009 Tambacounda [Region: Senegal] 686010 Thiès [Region: Senegal] 686011 Ziguinchor [Region: Senegal] 694011 Kailahun [District: Sierra Leone] 694012 Kenema [District: Sierra Leone] 694013 Kono [District: Sierra Leone] 694021 Bombali [District: Sierra Leone] 694022 Kambia [District: Sierra Leone] 694023 Koinadugu [District: Sierra Leone] 694024 Port Loko [District: Sierra Leone] 694025 Tonkolili [District: Sierra Leone] 694031 Bo [District: Sierra Leone] 694032 Bonthe [District: Sierra Leone] 694033 Moyamba [District: Sierra Leone] 694034 Pujehun [District: Sierra Leone] 694041 Western - rural [District: Sierra Leone] 694042 Western - urban [District: Sierra Leone] 704001 Ninh Binh, Hoa Binh, Ha Noi, Phu Tho, Vinh Phuc, Ha Nam, and Nam Dinh [Province: Vietnam] 704002 Ha Giang and Tuyen Quang [Province: Vietnam] 704004 Cao Bang [Province: Vietnam] 704014 Son La [Province: Vietnam] 704015 Lai Chau, Dien Bien, Lao Cai, and Yen Bai [Province: Vietnam] 704019 Bac Kan and Thai Nguyen [Province: Vietnam] 704020 Lang Son [Province: Vietnam] 704022 Quang Ninh [Province: Vietnam] 704024 Bac Giang, and Bac Ninh [Province: Vietnam] 704030 Hai Duong and Hung Yen [Province: Vietnam] 704031 Hai Phong [Province: Vietnam] 704034 Thai Binh [Province: Vietnam] 704038 Thanh Hoa [Province: Vietnam] 704040 Nghe An and Ha Tinh [Province: Vietnam] 704046 Quang Binh, Quang Tri, and Thua Thien - Hue [Province: Vietnam] 704049 Da Nang and Quang Nam [Province: Vietnam] 704051 Binh Dinh and Quang Ngai [Province: Vietnam] 704054 Phu Yen and Khanh Hoa [Province: Vietnam] 704060 Thuan Hai, Ninh Thuan, and Binh Thuan [Province: Vietnam] 704062 Gia Lai and Kon Tum [Province: Vietnam] 704066 Dak Lak and Dak Nong [Province: Vietnam] 704068 Lam Dong [Province: Vietnam] 704072 Tay Ninh [Province: Vietnam] 704074 Binh Duong and Binh Phuoc [Province: Vietnam] 704075 Dong Nai and Ba Ria - Vung Tau [Province: Vietnam] 704079 Ho Chi Minh City [Province: Vietnam] 704080 Long An [Province: Vietnam] 704082 Tien Giang [Province: Vietnam] 704083 Ben Tre [Province: Vietnam] 704086 Vinh Long and Tra Vinh [Province: Vietnam] 704087 Dong Thap [Province: Vietnam] 704089 An Giang [Province: Vietnam] 704091 Kien Giang [Province: Vietnam] 704094 Hau Giang, Can Tho City, and Soc Trang [Province: Vietnam] 704096 Bac Lieu and Ca Mau [Province: Vietnam] 705001 Pomurska [Region: Slovenia] 705002 Podravska [Region: Slovenia] 705003 Koroška [Region: Slovenia] 705004 Savinjska [Region: Slovenia] 705005 Zasavska [Region: Slovenia] 705006 Spodnjeposavska [Region: Slovenia] 705007 Jugovzhodna Slovenija [Region: Slovenia] 705008 Osrednjeslovenska [Region: Slovenia] 705009 Gorenjska [Region: Slovenia] 705010 Notranjsko-kraška [Region: Slovenia] 705011 Goriška [Region: Slovenia] 705012 Obalno-kraška [Region: Slovenia] 705099 Unknown [Region: Slovenia] 710001 Western Cape [Province: South Africa] 710004 Free State [Province: South Africa] 710005 Eastern Cape, KwaZulu-Natal [Province: South Africa] 710007 Gauteng, Limpopo, Mpumalanga, North West, Northern Cape [Province: South Africa] 710999 Unknown [Province: South Africa] 724011 Galicia [Communities and Autonomous Cities: Spain] 724012 Principado de Asturias [Communities and Autonomous Cities: Spain] 724013 Cantabria [Communities and Autonomous Cities: Spain] 724021 País Vasco [Communities and Autonomous Cities: Spain] 724022 Comunidad Foral de Navarra [Communities and Autonomous Cities: Spain] 724023 La Rioja [Communities and Autonomous Cities: Spain] 724024 Aragón [Communities and Autonomous Cities: Spain] 724030 Comunidad de Madrid [Communities and Autonomous Cities: Spain] 724041 Castilla y León [Communities and Autonomous Cities: Spain] 724042 Castilla-La Mancha [Communities and Autonomous Cities: Spain] 724043 Extremadura [Communities and Autonomous Cities: Spain] 724051 Cataluña [Communities and Autonomous Cities: Spain] 724052 Comunidad Valenciana [Communities and Autonomous Cities: Spain] 724053 Illes Balears [Communities and Autonomous Cities: Spain] 724061 Andalucía [Communities and Autonomous Cities: Spain] 724062 Región de Murcia [Communities and Autonomous Cities: Spain] 724063 Ciudad Autónoma de Ceuta [Communities and Autonomous Cities: Spain] 724064 Ciudad Autónoma de Melilla [Communities and Autonomous Cities: Spain] 724070 Canarias [Communities and Autonomous Cities: Spain] 724099 Unknown [Communities and Autonomous Cities: Spain] 728071 Upper Nile [State: South Sudan] 728072 Jonglei [State: South Sudan] 728073 Unity [State: South Sudan] 728081 Warrap [State: South Sudan] 728082 Northern Bahr El Ghazal [State: South Sudan] 728083 Western Bahr El Ghazal [State: South Sudan] 728084 Lakes [State: South Sudan] 728091 Western Equatoria [State: South Sudan] 728092 Central Equatoria [State: South Sudan] 728093 Eastern Equatoria [State: South Sudan] 729011 Northern [State: Sudan] 729012 Nahr El Nil [State: Sudan] 729021 Red Sea [State: Sudan] 729022 Kassala [State: Sudan] 729023 Al Gedarif [State: Sudan] 729031 Khartoum [State: Sudan] 729041 Al Gezira [State: Sudan] 729042 White Nile [State: Sudan] 729043 Sinnar [State: Sudan] 729044 Blue Nile [State: Sudan] 729051 North Kordofan [State: Sudan] 729052 South Kordofan [State: Sudan] 729061 North Darfur [State: Sudan] 729062 West Darfur [State: Sudan] 729063 South Darfur [State: Sudan] 756001 Zurich [Canton: Switzerland] 756002 Bern [Canton: Switzerland] 756003 Luzern (Lucerne) [Canton: Switzerland] 756004 Uri [Canton: Switzerland] 756005 Schwyz [Canton: Switzerland] 756006 Obwalden (Obwald) [Canton: Switzerland] 756007 Nidwalden (Nidwald) [Canton: Switzerland] 756008 Glarus [Canton: Switzerland] 756009 Zug [Canton: Switzerland] 756010 Fribourg [Canton: Switzerland] 756011 Solothurn [Canton: Switzerland] 756012 Basel-Stadt (Basel-City) [Canton: Switzerland] 756013 Basel-Landschaft (Basel-Country) [Canton: Switzerland] 756014 Schaffhausen [Canton: Switzerland] 756015 Outer and Inner Rhodes [Canton: Switzerland] 756017 St. Gallen (St. Gall) [Canton: Switzerland] 756018 Graubundun (Grisons) [Canton: Switzerland] 756019 Aargau (Argovia) [Canton: Switzerland] 756020 Thurgau (Thurgovia) [Canton: Switzerland] 756021 Ticino [Canton: Switzerland] 756022 Vaud [Canton: Switzerland] 756023 Valais [Canton: Switzerland] 756024 Neuchatel [Canton: Switzerland] 756025 Geneva [Canton: Switzerland] 756026 Jura [Canton: Switzerland] 764010 Bangkok [Province: Thailand] 764011 Samut Prakan [Province: Thailand] 764012 Nonthaburi [Province: Thailand] 764013 Pathum Thani [Province: Thailand] 764014 Phra Nakhon si Ayutthaya [Province: Thailand] 764015 Ang Thong [Province: Thailand] 764016 Lop Buri [Province: Thailand] 764017 Sing Buri [Province: Thailand] 764018 Chai Nat [Province: Thailand] 764019 Prachin Buri and Sa Kaeo [Province: Thailand] 764020 Chon Buri [Province: Thailand] 764021 Rayong [Province: Thailand] 764022 Chanthaburi [Province: Thailand] 764023 Trat [Province: Thailand] 764024 Chachoengsao [Province: Thailand] 764026 Nakhon Nayok [Province: Thailand] 764027 Saraburi [Province: Thailand] 764030 Nakhon Ratchasima [Province: Thailand] 764031 Buri Ram [Province: Thailand] 764032 Surin [Province: Thailand] 764033 Si Sa Ket [Province: Thailand] 764034 Ubon Ratchathani, Yasothon and Amnat Charoen [Province: Thailand] 764036 Chaiyaphum [Province: Thailand] 764040 Khon Kaen [Province: Thailand] 764041 Udon Thani and Nong Bua Lam Phu [Province: Thailand] 764042 Loei [Province: Thailand] 764043 Nong Khai [Province: Thailand] 764044 Maha Sarakham [Province: Thailand] 764045 Roi Et [Province: Thailand] 764046 Kalasin [Province: Thailand] 764047 Sakon Nakhon [Province: Thailand] 764048 Nakhon Phanom and Mukdahan [Province: Thailand] 764050 Chiang Mai [Province: Thailand] 764051 Lamphun [Province: Thailand] 764052 Lampang [Province: Thailand] 764053 Uttaradit [Province: Thailand] 764054 Phrae [Province: Thailand] 764055 Nan [Province: Thailand] 764057 Chiang Rai and Phayao [Province: Thailand] 764058 Mae Hong Son [Province: Thailand] 764060 Nakhon Sawan [Province: Thailand] 764061 Uthai Thani [Province: Thailand] 764062 Kamphaeng Phet [Province: Thailand] 764063 Tak [Province: Thailand] 764064 Sukhothai [Province: Thailand] 764065 Phitsanulok [Province: Thailand] 764066 Phichit [Province: Thailand] 764067 Phetchabun [Province: Thailand] 764070 Ratchaburi [Province: Thailand] 764071 Kanchanaburi [Province: Thailand] 764072 Suphanburi [Province: Thailand] 764073 Nakhon Pathom [Province: Thailand] 764074 Samut Sakhon [Province: Thailand] 764075 Samut Songkhram [Province: Thailand] 764076 Phetchaburi [Province: Thailand] 764077 Prachuap Khiri Khan [Province: Thailand] 764080 Nakhon Si Thammarat [Province: Thailand] 764081 Krabi [Province: Thailand] 764082 Phangnga [Province: Thailand] 764083 Phuket [Province: Thailand] 764084 Surat Thani [Province: Thailand] 764085 Ranong [Province: Thailand] 764086 Chumphon [Province: Thailand] 764090 Songkhla [Province: Thailand] 764091 Satun [Province: Thailand] 764092 Trang [Province: Thailand] 764093 Phatthalung [Province: Thailand] 764094 Pattani [Province: Thailand] 764095 Yala [Province: Thailand] 764096 Narathiwat [Province: Thailand] 792001 Adana, Gaziantep, Osmaniye and Kilis [Province: Turkey] 792002 Adiyaman [Province: Turkey] 792003 Afyon [Province: Turkey] 792004 Agri [Province: Turkey] 792005 Amasya [Province: Turkey] 792006 Ankara and Kirikkale [Province: Turkey] 792007 Antalya [Province: Turkey] 792008 Artvin [Province: Turkey] 792009 Aydin [Province: Turkey] 792010 Balikesir [Province: Turkey] 792011 Bilecik [Province: Turkey] 792012 Bingöl [Province: Turkey] 792013 Bitlis [Province: Turkey] 792014 Bolu and Düzce [Province: Turkey] 792015 Burdur [Province: Turkey] 792017 Çanakkale [Province: Turkey] 792019 Çorum [Province: Turkey] 792020 Denizli [Province: Turkey] 792021 Diyarbakir [Province: Turkey] 792022 Edirne [Province: Turkey] 792023 Elazig [Province: Turkey] 792024 Erzincan [Province: Turkey] 792025 Erzurum [Province: Turkey] 792026 Eskisehir [Province: Turkey] 792028 Giresun [Province: Turkey] 792029 Gümüshane and Bayburt [Province: Turkey] 792031 Hatay [Province: Turkey] 792032 Isparta [Province: Turkey] 792033 Mersin (içel) [Province: Turkey] 792034 Istanbul, Bursa, Kocaeli and Yalova [Province: Turkey] 792035 Izmir [Province: Turkey] 792036 Kars, Ardahan and Igdir [Province: Turkey] 792037 Kastamonu [Province: Turkey] 792038 Kayseri [Province: Turkey] 792039 Kirklareli [Province: Turkey] 792040 Kirsehir [Province: Turkey] 792042 Konya and Karaman [Province: Turkey] 792043 Kütahya [Province: Turkey] 792044 Malatya [Province: Turkey] 792045 Manisa [Province: Turkey] 792046 Kahramanmaras [Province: Turkey] 792047 Mardin, Hakkari, Siirt, Batman and Sirnak [Province: Turkey] 792048 Mugla [Province: Turkey] 792049 Mus [Province: Turkey] 792050 Nevsehir [Province: Turkey] 792051 Nigde and Aksaray [Province: Turkey] 792052 Ordu [Province: Turkey] 792053 Rize [Province: Turkey] 792054 Sakarya [Province: Turkey] 792055 Samsun [Province: Turkey] 792057 Sinop [Province: Turkey] 792058 Sivas [Province: Turkey] 792059 Tekirdag [Province: Turkey] 792060 Tokat [Province: Turkey] 792061 Trabzon [Province: Turkey] 792062 Tunceli [Province: Turkey] 792063 Sanliurfa [Province: Turkey] 792064 Usak [Province: Turkey] 792065 Van [Province: Turkey] 792066 Yozgat [Province: Turkey] 792067 Zonguldak, Çankiri, Karabuk and Bartin [Province: Turkey] 800101 Kalangala [District: Uganda] 800102 Kampala [District: Uganda] 800103 Kiboga [District: Uganda] 800104 Luwero and Nakasongola [District: Uganda] 800105 Masaka and Sembabule [District: Uganda] 800107 Mubende [District: Uganda] 800108 Mukono and Kayunga [District: Uganda] 800110 Rakai [District: Uganda] 800113 Mpigi and Wakiso [District: Uganda] 800203 Iganga, Buguri, and Mayuge [District: Uganda] 800204 Jinja [District: Uganda] 800205 Kamuli [District: Uganda] 800206 Kapchorwa [District: Uganda] 800208 Kumi [District: Uganda] 800209 Mbale and Sironko [District: Uganda] 800210 Pallisa [District: Uganda] 800211 Soroti, Katakwi, and Kaberamaido [District: Uganda] 800212 Busia and Tororo [District: Uganda] 800301 Moyo and Adjumani [District: Uganda] 800302 Apac [District: Uganda] 800303 Arua and Yumbe [District: Uganda] 800304 Gulu [District: Uganda] 800306 Kotido [District: Uganda] 800307 Lira [District: Uganda] 800308 Moroto and Nakapiripirit [District: Uganda] 800310 Nebbi [District: Uganda] 800312 Kitgum and Pader [District: Uganda] 800401 Bundibugyo [District: Uganda] 800403 Hoima [District: Uganda] 800404 Kabale [District: Uganda] 800405 Kabarole, Kamwenge, and Kyenjojo [District: Uganda] 800406 Kasese [District: Uganda] 800407 Kibaale [District: Uganda] 800408 Kisoro [District: Uganda] 800409 Masindi [District: Uganda] 800410 Bushenyi, Mbarara, and Ntungamo [District: Uganda] 800412 Rukungiri and Kanungu [District: Uganda] 800999 Unknown [District: Uganda] 804001 The Autonomous Republic of Crimea [Region: Ukraine] 804005 Vinnytska oblast [Region: Ukraine] 804007 Volynska oblast [Region: Ukraine] 804012 Dnipropetrovska oblast [Region: Ukraine] 804014 Donetska oblast [Region: Ukraine] 804018 Zhytomyrska oblast [Region: Ukraine] 804021 Zakarpatska oblast [Region: Ukraine] 804023 Zaporizka oblast [Region: Ukraine] 804026 Ivano-Frankivska oblast [Region: Ukraine] 804032 Kyivska oblast [Region: Ukraine] 804035 Kirovohradska oblast [Region: Ukraine] 804044 Luhanska oblast [Region: Ukraine] 804046 Lvivska oblast [Region: Ukraine] 804048 Mykolaivska oblast [Region: Ukraine] 804051 Odeska oblast [Region: Ukraine] 804053 Poltavska oblast [Region: Ukraine] 804056 Rivnenska oblast [Region: Ukraine] 804059 Sumska oblast [Region: Ukraine] 804061 Ternopilska oblast [Region: Ukraine] 804063 Kharkivska oblast [Region: Ukraine] 804065 Khersonska oblast [Region: Ukraine] 804068 Khmelnytska oblast [Region: Ukraine] 804071 Cherkaska oblast [Region: Ukraine] 804073 Chernivetska oblast [Region: Ukraine] 804074 Chernihivska oblast [Region: Ukraine] 804080 Kyiv [Region: Ukraine] 804085 Sevastopol [Region: Ukraine] 818001 Cairo [Governorate: Egypt] 818002 Alexandria [Governorate: Egypt] 818003 Port Said [Governorate: Egypt] 818004 Suez [Governorate: Egypt] 818011 Damietta [Governorate: Egypt] 818012 Dakahlia [Governorate: Egypt] 818013 Sharkia [Governorate: Egypt] 818014 Kaliobia [Governorate: Egypt] 818015 Kafr Sheikh [Governorate: Egypt] 818016 Gharbia [Governorate: Egypt] 818017 Menoufia [Governorate: Egypt] 818018 Behera [Governorate: Egypt] 818019 Ismailia [Governorate: Egypt] 818021 Giza [Governorate: Egypt] 818022 Bani Swif [Governorate: Egypt] 818023 Fayoum [Governorate: Egypt] 818024 Menia [Governorate: Egypt] 818025 Asiut [Governorate: Egypt] 818026 Sohag [Governorate: Egypt] 818027 Qena [Governorate: Egypt] 818028 Aswan [Governorate: Egypt] 818029 Luxor [Governorate: Egypt] 818031 Red Sea [Governorate: Egypt] 818032 New Valley [Governorate: Egypt] 818033 Marsa Matroh [Governorate: Egypt] 818034 North Sinai [Governorate: Egypt] 818035 South Sinai [Governorate: Egypt] 826011 North East [Region: United Kingdom] 826013 North West [Region: United Kingdom] 826014 Yorkshire and the Humber [Region: United Kingdom] 826021 East Midlands [Region: United Kingdom] 826022 West Midlands [Region: United Kingdom] 826031 East of England [Region: United Kingdom] 826032 South East and London [Region: United Kingdom] 826040 South West [Region: United Kingdom] 826060 Scotland [Region: United Kingdom] 826070 Wales [Region: United Kingdom] 826080 Northern Ireland [Region: United Kingdom] 834001 Dodoma [Region: Tanzania] 834003 Kilimanjaro [Region: Tanzania] 834004 Tanga [Region: Tanzania] 834005 Morogoro [Region: Tanzania] 834006 Pwani [Region: Tanzania] 834007 Dar es Salaam [Region: Tanzania] 834008 Lindi [Region: Tanzania] 834009 Mtwara [Region: Tanzania] 834010 Ruvumba [Region: Tanzania] 834011 Iringa [Region: Tanzania] 834012 Mbeya [Region: Tanzania] 834013 Singida [Region: Tanzania] 834014 Tabora [Region: Tanzania] 834015 Rukwa [Region: Tanzania] 834016 Kigoma [Region: Tanzania] 834017 Shinyanga [Region: Tanzania] 834018 Kagera [Region: Tanzania] 834019 Mwanza [Region: Tanzania] 834020 Mara [Region: Tanzania] 834021 Arusha and Manyara [Region: Tanzania] 834051 Zanzibar North [Region: Tanzania] 834052 Zanzibar South [Region: Tanzania] 834053 Zanzibar Town/West [Region: Tanzania] 834054 Pemba North [Region: Tanzania] 834055 Pemba South [Region: Tanzania] 840001 Alabama [State: U.S.] 840002 Alaska [State: U.S.] 840004 Arizona [State: U.S.] 840005 Arkansas [State: U.S.] 840006 California [State: U.S.] 840008 Colorado [State: U.S.] 840009 Connecticut [State: U.S.] 840010 Delaware [State: U.S.] 840011 District of Columbia [State: U.S.] 840012 Florida [State: U.S.] 840013 Georgia [State: U.S.] 840015 Hawaii [State: U.S.] 840016 Idaho [State: U.S.] 840017 Illinois [State: U.S.] 840018 Indiana [State: U.S.] 840019 Iowa [State: U.S.] 840020 Kansas [State: U.S.] 840021 Kentucky [State: U.S.] 840022 Louisiana [State: U.S.] 840023 Maine [State: U.S.] 840024 Maryland [State: U.S.] 840025 Massachusetts [State: U.S.] 840026 Michigan [State: U.S.] 840027 Minnesota [State: U.S.] 840028 Mississippi [State: U.S.] 840029 Missouri [State: U.S.] 840030 Montana [State: U.S.] 840031 Nebraska [State: U.S.] 840032 Nevada [State: U.S.] 840033 New Hampshire [State: U.S.] 840034 New Jersey [State: U.S.] 840035 New Mexico [State: U.S.] 840036 New York [State: U.S.] 840037 North Carolina [State: U.S.] 840038 North Dakota [State: U.S.] 840039 Ohio [State: U.S.] 840040 Oklahoma [State: U.S.] 840041 Oregon [State: U.S.] 840042 Pennsylvania [State: U.S.] 840044 Rhode Island [State: U.S.] 840045 South Carolina [State: U.S.] 840046 South Dakota [State: U.S.] 840047 Tennessee [State: U.S.] 840048 Texas [State: U.S.] 840049 Utah [State: U.S.] 840050 Vermont [State: U.S.] 840051 Virginia [State: U.S.] 840053 Washington [State: U.S.] 840054 West Virginia [State: U.S.] 840055 Wisconsin [State: U.S.] 840056 Wyoming [State: U.S.] 840099 State not identified [State: U.S.] 854001 Boucle du Mouhoun [Region: Burkina Faso] 854002 Cascades [Region: Burkina Faso] 854003 Centre [Region: Burkina Faso] 854004 Centre-Est [Region: Burkina Faso] 854005 Centre-Nord [Region: Burkina Faso] 854006 Centre-Ouest [Region: Burkina Faso] 854007 Centre-Sud [Region: Burkina Faso] 854008 Est [Region: Burkina Faso] 854009 Hauts-Bassins [Region: Burkina Faso] 854010 Nord [Region: Burkina Faso] 854011 Plateau Central [Region: Burkina Faso] 854012 Sahel [Region: Burkina Faso] 854013 Sud-Ouest [Region: Burkina Faso] 858001 Montevideo [Department: Uruguay] 858002 Artigas [Department: Uruguay] 858003 Canelones [Department: Uruguay] 858004 Cerro Largo [Department: Uruguay] 858005 Colonia [Department: Uruguay] 858006 Durazno [Department: Uruguay] 858007 Flores [Department: Uruguay] 858008 Florida [Department: Uruguay] 858009 Lavalleja [Department: Uruguay] 858010 Maldonado [Department: Uruguay] 858011 Paysandú [Department: Uruguay] 858012 Río Negro [Department: Uruguay] 858013 Rivera [Department: Uruguay] 858014 Rocha [Department: Uruguay] 858015 Salto [Department: Uruguay] 858016 San Jose [Department: Uruguay] 858017 Soriano [Department: Uruguay] 858018 Tacuarembó [Department: Uruguay] 858019 Treinta Y Tres [Department: Uruguay] 862001 Federal District, Vargas [State: Venezuela] 862002 Amazonas Federal Territory [State: Venezuela] 862003 Anzoátegui [State: Venezuela] 862004 Apure [State: Venezuela] 862005 Aragua [State: Venezuela] 862007 Bolívar [State: Venezuela] 862008 Carabobo [State: Venezuela] 862009 Cojedes [State: Venezuela] 862010 Amacuros Delta Federal Territory [State: Venezuela] 862011 Falcón [State: Venezuela] 862012 Guárico [State: Venezuela] 862013 Lara [State: Venezuela] 862014 Barinas, Mérida [State: Venezuela] 862015 Miranda [State: Venezuela] 862016 Monagas [State: Venezuela] 862017 Nueva Esparta, Federal Dependencies [State: Venezuela] 862018 Portuguesa [State: Venezuela] 862019 Sucre [State: Venezuela] 862020 Táchira [State: Venezuela] 862021 Trujillo [State: Venezuela] 862022 Yaracuy [State: Venezuela] 862023 Zulia [State: Venezuela] 894001 Central [Province: Zambia] 894002 Copperbelt [Province: Zambia] 894003 Eastern, Muchinga, Northern [Province: Zambia] 894004 Luapula [Province: Zambia] 894005 Lusaka [Province: Zambia] 894008 North Western [Province: Zambia] 894009 Southern [Province: Zambia] 894010 Western [Province: Zambia] GEOLEV1 indicates the major administrative unit in which the household was enumerated. The variable incorporates the geographies for every country, to enable cross-national geographic analysis over time. First administrative units in GEOLEV1 have been spatiotemporally harmonized to provide spatially consistent boundaries across samples in each country. IPUMS Dwelling number Dwelling number Dwelling number Dwelling number Dwelling number Dwelling number All households This variable indicates the dwelling number. This is a 5-digit numeric variable with 0 implied decimal places IPUMS Number of persons in household Number of persons in household Number of persons in household Number of persons in household Number of persons in household Number of persons in household All households 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 This variable indicates the number of persons in the household. IPUMS Province (aimag) Province (aimag) Province (aimag) Province (aimag) Province (aimag) Aimag (province) _____ All households 1 Arkhangai 2 Bayan-Ulgii 3 Bayankhongor 4 Bulgan 5 Gobi-Altai 6 Dornogobi 7 Dornod 8 Dundgobi 9 Zavkhan 10 Uvurkhangai 11 Umnugobi 12 Sukhbaatar 13 Selenge 14 Tuv 15 Uvs 16 Khovd 17 Khuvsgul 18 Khentii 19 Darkhan 20 Ulaanbaatar 21 Erdenet This variable indicates the province (aimag) in which the household resides. IPUMS Household size Household size Household size Household size Household size Household size _ _ Of which: number of people working _ _ Of which: number of children age 0 to16 _ _ All households 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 This variable indicates the number of persons in the household. IPUMS Number of people working Number of people working Number of people working Number of people working Number of people working Household size _ _ Of which: number of people working _ _ Of which: number of children age 0 to16 _ _ All households 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 16 16 This variable indicates the number of household members who work. IPUMS Number of children aged 0 to16 Number of children aged 0 to16 Number of children aged 0 to16 Number of children aged 0 to16 Number of children aged 0 to16 Household size _ _ Of which: number of people working _ _ Of which: number of children age 0 to16 _ _ All households 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 14 14 This variable indicates the number of children in the household who are 16 years old or younger. IPUMS Location Location Location Location Location Aimag (province) _____ Soum (khoroo)(district) _____ Census: Commission _____ EA _____ [] 1 Capital city [] 2 Village [] 3 Soum (bag) center [] 4 Brigade, farm center [] 5 Countryside All households 1 Capital city 2 Village 3 Soum (bag) center 4 Brigade, farm center 5 Countryside This variable indicates the household's location (broadly urban or rural area). IPUMS House Type House Type House Type House Type House Type House Type All households 1 House 2 Ger This variable indicates the type of house in which the household resides. IPUMS Type of living quarters Type of living quarters Type of living quarters Type of living quarters Type of living quarters 1. Type of living quarters: [] 1 House, apartment [] 2 Some part of house, apartment [] 3 Public dormitory [] 4 Students dormitory Households living in houses 1 House, apartment 2 Some part of house, apartment 3 Public dormitory 4 Students dormitory 9 NIU (not in universe) This variable indicates the type of living quarters in which the household resides. IPUMS Ownership type of living quarters Ownership type of living quarters Ownership type of living quarters Ownership type of living quarters Ownership type of living quarters 2. Type of property: [] 1 Government [] 2 Agricultural cooperative [] 3 Joint venture [] 4 Cooperative [] 5 Private, had built with own money [] 6 Private, had built with a loan Households living in houses 1 Government 2 Agricultural cooperative 3 Joint venture 4 Cooperative 5 Private, had built by own money 6 Private, had built by loan 9 NIU (not in universe) This variable indicates the type of ownership of the living quarters in which the household resides. IPUMS Numbering of households in same house Numbering of households in same house Numbering of households in same house Numbering of households in same house Numbering of households in same house Number of households in same house _ _ Households living in houses 1 1 2 2 3 3 4 4 5 5 8 Unknown 9 NIU (not in universe) This variable indicates the numbering of households in the same house. The number of households could be different from the number written here. IPUMS Number of rooms Number of rooms Number of rooms Number of rooms Number of rooms 3. Number of rooms _____ Useful living area (m2) _____ Total living area (m2) _____ Number of households _____ Number of residents _____ Households living in houses 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 NIU (not in universe) This variable indicates the number of rooms in the house in which the household lives. The criteria for determining the number of rooms is different depending upon whether or not the household is listed as the first household in the house. For households listed first, enumerators recorded the total number of rooms. For households listed subsequent to the first household, enumerators recorded only the number of rooms used by that household. IPUMS Useful living area (m2) Useful living area (m2) Useful living area (m2) Useful living area (m2) Useful living area (m2) 3. Number of rooms _____ Useful living area (m2) _____ Total living area (m2) _____ Number of households _____ Number of residents _____ Households living in houses 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 90 90 91 91 92 92 93 93 96 96 97 97 98 98 99 NIU (not in universe) This variable indicates the amount (in square meters) of useful living area in the house in which the household lives. The criteria for determining how to record the useful living area differs depending upon whether a household is listed as the first household in the house or a subsequent household. For households listed first, enumerators recorded the total useful living area of the entire house. For subsequent households, enumerators recorded only the useful living area is use by that household. IPUMS Total living area (m2) Total living area (m2) Total living area (m2) Total living area (m2) Total living area (m2) 3. Number of rooms _____ Useful living area (m2) _____ Total living area (m2) _____ Number of households _____ Number of residents _____ Households living in houses 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 62 62 63 63 64 64 65 65 66 66 67 67 68 68 70 70 71 71 74 74 80 80 85 85 93 93 99 NIU (not in universe) This variable indicates the total living area (in square meters) of the house in which the household lives. The criteria for determining how to record the total living area differs depending upon whether a household is listed as the first household in the house or a subsequent household. For households listed first, enumerators recorded the total living area of the entire house. For subsequent households, enumerators recorded only the total living area that was actually in use by that household. IPUMS Number of households Number of households Number of households Number of households Number of households 3. Number of rooms _____ Useful living area (m2) _____ Total living area (m2) _____ Number of households _____ Number of residents _____ Households living in houses NIU (not in universe) 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 This variable indicates the number of households living in the house in which the household lives if the household was listed as the first one in the house. For households listed second, third, fourth, etc., the number of households was recorded as 1. IPUMS Number of residents Number of residents Number of residents Number of residents Number of residents 3. Number of rooms _____ Useful living area (m2) _____ Total living area (m2) _____ Number of households _____ Number of residents _____ Households living in houses 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 99 NIU (not in universe) This variable indicates the number of residents living in the house in which the household resides if the household is listed as the first one in the house. For subsequent households, the variable indicates only the number of residents in that household. IPUMS Type of heating Type of heating Type of heating Type of heating Type of heating Type of heating: [] 01 Centralized [] 02 Non-centralized [] 03 Normal Households living in houses 1 Centralized 2 Non-centralized 3 Normal 9 NIU (not in universe) This variable indicates the type of heating used in the house in which the household lives. IPUMS Water supply Water supply Water supply Water supply Water supply Water supply: [] 04 Hot and cold water pipe [] 05 Cold water pipe [] 06 Public inside of house [] 07 Outside of house Households living in houses 1 Hot and cold water pipe 2 Cold water pipe 3 Public inside of house 4 Outside of house 9 NIU (not in universe) This variable indicates the type of water supply system in the house in which the household lives. IPUMS Sewage pipe for dirty water Sewage pipe for dirty water Sewage pipe for dirty water Sewage pipe for dirty water Sewage pipe for dirty water Sewage pipe for dirty water: [] 08 Inside of house [] 09 Public inside of house [] 10 Outside of house Households living in houses 1 Inside of house 2 Public inside of house 3 Outside of house 9 NIU (not in universe) This variable indicates the type of sewage system in the house in which the household lives. IPUMS Kitchen Kitchen Kitchen Kitchen Kitchen Kitchen: [] 11 Yes [] 12 No [] 13 Public Households living in houses 1 Yes 2 No 3 Public 9 NIU (not in universe) This variable indicates whether the house in which the household lives has a kitchen. IPUMS Bathroom/shower room Bathroom/shower room Bathroom/shower room Bathroom/shower room Bathroom/shower room Bathroom/Shower room: [] 14 Yes [] 15 No [] 16 Public Households living in houses 1 Yes 2 No 3 Public 9 NIU (not in universe) This variable indicates whether the house has a bathroom/shower room. IPUMS Disposal of household waste Disposal of household waste Disposal of household waste Disposal of household waste Disposal of household waste Disposal of household waste: [] 17 Through tube [] 18 No tube Households living in houses 1 Through tube 2 No tube 9 NIU (not in universe) This variable indicates how the household disposes of the household waste. IPUMS Electricity Electricity Electricity Electricity Electricity Electricity: [] 19 Yes [] 20 No Households living in houses 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the house in which the household resides has electricity. IPUMS Stove Stove Stove Stove Stove Stove: [] 21 Has stove [] 22 No stove Households living in houses 1 Has stove 2 No stove 9 NIU (not in universe) This variable indicates whether the house in which the household resides has a stove. IPUMS Stairs Stairs Stairs Stairs Stairs Stairs: [] 23 Has stairs [] 24 No stairs Households living in houses 1 Has stairs 2 No stairs 9 NIU (not in universe) This variable indicates whether the house in which the household resides has stairs. IPUMS Number of government-owned gers Number of government-owned gers Number of government-owned gers Number of government-owned gers Number of government-owned gers B. Ger Order of household in ger _ [] 1 Government Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in gers 1 1 2 2 3 3 9 NIU (not in universe) This variable indicates the number of government owned ger(s) in which the household resides. The household may also reside in other types of gers. IPUMS Number of walls (government-owned gers) Number of walls (government-owned gers) Number of walls (government-owned gers) Number of walls (government-owned gers) Number of walls (government-owned gers) B. Ger Order of household in ger _ [] 1 Government Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in government owned gers 4 4 5 5 6 6 7 7 9 NIU (not in universe) This variable indicates the number of walls in the government owned ger(s) in which the household resides. The household may also reside in other types of gers. IPUMS Number of households (government-owned gers) Number of households (government-owned gers) Number of households (government-owned gers) Number of households (government-owned gers) Number of households (government-owned gers) B. Ger Order of household in ger _ [] 1 Government Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in government owned gers 1 1 2 2 4 4 6 6 8 8 9 NIU (not in universe) This variable indicates the number of households living in the government owned ger(s) in which the household resides. The household may also reside in other types of gers. If the household is listed as the first household in the ger (for multi-household gers), the variable indicates the total number of households in the government owned ger. If the household is not the first one listed in the ger, this variable records 1 for the number of households. IPUMS Number of residents (government-owned gers) Number of residents (government-owned gers) Number of residents (government-owned gers) Number of residents (government-owned gers) Number of residents (government-owned gers) B. Ger Order of household in ger _ [] 1 Government Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in government owned gers 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 14 14 15 15 99 NIU (not in universe) This variable indicates the number of residents living in the government owned ger(s) in which the household resides. The household may also reside in other types of gers. If the household is listed as the first household in the ger (for multi-household gers), the variable indicates the total number of residents in the government owned ger. If the household is not the first one listed in the ger, this variable records only the number of residents for that household. IPUMS Has electricity (government-owned gers) Has electricity (government-owned gers) Has electricity (government-owned gers) Has electricity (government-owned gers) Has electricity (government-owned gers) B. Ger Order of household in ger _ [] 1 Government Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in government owned gers 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the government owned ger(s) in which the household resides has electricity. The household may also reside in other types of gers. IPUMS Number of cooperative-owned gers Number of cooperative-owned gers Number of cooperative-owned gers Number of cooperative-owned gers Number of cooperative-owned gers B. Ger Order of household in ger _ [] 2 Agricultural cooperative Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in gers 1 1 2 2 9 NIU (not in universe) This variable indicates the number of cooperative owned ger(s) in which the household resides. The household may also reside in other types of gers. IPUMS Number of walls (cooperative-owned gers) Number of walls (cooperative-owned gers) Number of walls (cooperative-owned gers) Number of walls (cooperative-owned gers) Number of walls (cooperative-owned gers) B. Ger Order of household in ger _ [] 2 Agricultural cooperative Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in cooperative owned gers 4 4 5 5 6 6 7 7 9 NIU (not in universe) This variable indicates the number of walls in the cooperative owned ger(s) in which the household resides. The household may also reside in other types of gers. IPUMS Number ofhouseholds (cooperative-owned gers) Number ofhouseholds (cooperative-owned gers) Number ofhouseholds (cooperative-owned gers) Number ofhouseholds (cooperative-owned gers) Number ofhouseholds (cooperative-owned gers) B. Ger Order of household in ger _ [] 2 Agricultural cooperative Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in cooperative owned gers 1 1 2 2 9 NIU (not in universe) This variable indicates the number of households in the cooperative owned ger(s) in which the household resides. The household may also reside in other types of gers. If the household is listed as the first household in the ger (for multi-household gers), the variable indicates the total number of households in the cooperative owned ger(s). If the household is not the first one listed in the ger, this variable records 1 for the number of households. IPUMS Number of residents (cooperative-owned gers) Number of residents (cooperative-owned gers) Number of residents (cooperative-owned gers) Number of residents (cooperative-owned gers) Number of residents (cooperative-owned gers) B. Ger Order of household in ger _ [] 2 Agricultural cooperative Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in cooperative owned gers 1 1 2 2 3 3 4 4 5 5 6 6 7 7 9 9 18 18 19 19 99 NIU (not in universe) This variable indicates the number of residents in the cooperative owned ger(s) in which the household resides. The household may also reside in other types of gers. If the household is listed as the first household in the ger (for multi-household gers), the variable indicates the total number of residents in the cooperative owned ger. If the household is not the first one listed in the ger, this variable records only the number of residents for that household. IPUMS Has electricity (cooperative-owned gers) Has electricity (cooperative-owned gers) Has electricity (cooperative-owned gers) Has electricity (cooperative-owned gers) Has electricity (cooperative-owned gers) B. Ger Order of household in ger _ [] 2 Agricultural cooperative Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in cooperative owned gers 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the cooperative owned ger(s) in which the household resides has electricity. The household may reside in other types of gers. IPUMS Number of private-owned gers Number of private-owned gers Number of private-owned gers Number of private-owned gers Number of private-owned gers B. Ger Order of household in ger _ [] 3 Private Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in gers 1 1 2 2 3 3 4 4 5 5 6 6 9 NIU (not in universe) This variable indicates the number of privately owned ger(s) in which the household resides. The household may reside in other types of gers. IPUMS Number of walls (private-owned gers) Number of walls (private-owned gers) Number of walls (private-owned gers) Number of walls (private-owned gers) Number of walls (private-owned gers) B. Ger Order of household in ger _ [] 3 Private Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in private gers 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 99 NIU (not in universe) This variable indicates the number of walls in the privately owned ger(s) in which the household resides. The household may reside in other types of gers. IPUMS Number of households (private-owned gers) Number of households (private-owned gers) Number of households (private-owned gers) Number of households (private-owned gers) Number of households (private-owned gers) B. Ger Order of household in ger _ [] 3 Private Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in private gers 1 1 2 2 3 3 4 4 9 NIU (not in universe) This variable indicates the number of households live in the privately owned ger(s) in which the household resides. The household may reside in other types of gers. If the household is listed as the first household in the ger (for multi-household gers), the variable indicates the total number of households in the privately owned ger(s). If the household is not the first one listed in the ger, this variable records 1 for the number of households. IPUMS Number of residents (private-owned gers) Number of residents (private-owned gers) Number of residents (private-owned gers) Number of residents (private-owned gers) Number of residents (private-owned gers) B. Ger Order of household in ger _ [] 3 Private Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in private gers 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 19 19 20 20 99 NIU (not in universe) This variable indicates the number of residents live in the privately owned ger(s) in which the household resides. The household may reside in other types of gers. If the household is listed as the first household in the ger (for multi-household gers), the variable indicates the total number of residents in the privately owned ger. If the household is not the first one listed in the ger, this variable records only the number of residents for that household. IPUMS Electricity (private-owned gers) Electricity (private-owned gers) Electricity (private-owned gers) Electricity (private-owned gers) Electricity (private-owned gers) B. Ger Order of household in ger _ [] 3 Private Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in private gers 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the privately owned ger(s) in which the household lives has electricity. The household may reside in other types of gers. IPUMS Number of otriin gers Number of otriin gers Number of otriin gers Number of otriin gers Number of otriin gers B. Ger Order of household in ger _ [] 4 Otriin Ger Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in gers 1 1 2 2 3 3 5 5 9 NIU (not in universe) This variable indicates the number of Otriin gers in which the household resides. The household may reside in other types of gers. IPUMS Number of walls (otriin gers) Number of walls (otriin gers) Number of walls (otriin gers) Number of walls (otriin gers) Number of walls (otriin gers) B. Ger Order of household in ger _ [] 4 Otriin Ger Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in otriin gers 3 3 4 4 5 5 8 8 9 NIU (not in universe) This variable indicates the number of walls in the Otriin ger(s) in which the household resides. The household may reside in other types of gers. IPUMS Number of households (otriin gers) Number of households (otriin gers) Number of households (otriin gers) Number of households (otriin gers) Number of households (otriin gers) B. Ger Order of household in ger _ [] 4 Otriin Ger Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in otriin gers 1 1 2 2 3 3 7 7 9 NIU (not in universe) This variable indicates the number of households living in the Otriin ger(s) in which the household resides. The household may reside in other types of gers. If the household is listed as the first household in the ger (for multi-household gers), the variable indicates the total number of households in the Otriin ger. If the household is not the first one listed in the ger, this variable records 1 for the number of households. IPUMS Number of residents (otriin gers) Number of residents (otriin gers) Number of residents (otriin gers) Number of residents (otriin gers) Number of residents (otriin gers) B. Ger Order of household in ger _ [] 4 Otriin Ger Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in otriin gers 1 1 2 2 3 3 4 4 5 5 6 6 7 7 9 9 10 10 13 13 15 15 16 16 19 19 20 20 22 22 32 32 99 NIU (not in universe) This variable indicates the number of residents in the Otriin ger(s) in which the household resides. The household may reside in other types of gers. If the household is listed as the first household in the ger (for multi-household gers), the variable indicates the total number of residents in the Otriin ger. If the household is not the first one listed in the ger, this variable records only the number of residents for that household. IPUMS Has electricity (otriin gers) Has electricity (otriin gers) Has electricity (otriin gers) Has electricity (otriin gers) Has electricity (otriin gers) B. Ger Order of household in ger _ [] 4 Otriin Ger Number of Gers _____ Number of walls of ger _____ Number of households _____ Number of residents _____ Has electricity _____ Households living in otriin gers 1 Yes 2 No 9 NIU (not in universe) This variable indicates whether the Otriin ger in which the household resides has electricity. The household may reside in other types of gers. IPUMS Household weight Household weight Household weight Household weight Household weight Household weight All households This variable indicates expansion factor (weight) for the case. This is a 5-digit numeric variable with 3 implied decimal places IPUMS Household weight Household weight Household weight Household weight Household weight HHWT indicates the number of households in the population represented by the household in the sample. For the samples that are truly weighted (see the comparability discussion), HHWT must be used to yield accurate household-level statistics. NOTE: HHWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. HHWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. IPUMS Mongolia, Province 1989 - 2000 [Level 1; consistent boundaries, GIS] Mongolia, Province 1989 - 2000 [Level 1; consistent boundaries, GIS] Mongolia, Province 1989 - 2000 [Level 1; consistent boundaries, GIS] Mongolia, Province 1989 - 2000 [Level 1; consistent boundaries, GIS] Mongolia, Province 1989 - 2000 [Level 1; consistent boundaries, GIS] 496001 Arkhangai 496002 Bayan-Ölgii 496003 Bayankhongor 496004 Bulgan 496005 Govi-Altai 496006 Dornogovi 496007 Dornod 496008 Dundgovi and Govisumber 496009 Zavkhan 496010 Övörkhangai 496011 Ömnögovi 496012 Sükhbaatar 496013 Selenge 496014 Töv 496015 Uvs 496016 Khovd 496017 Khövsgöl 496018 Khentii 496019 Darkhan-Uul 496020 Ulaanbaatar 496021 Orkhon GEO1_MN identifies the household's province (aimag) within Mongolia in all sample years. Provinces are the first level administrative units of the country. GEO1_MN is spatially harmonized to account for political boundary changes across census years. Some detail is lost in harmonization; see the comparability discussion. A GIS map (in shapefile format), corresponding to GEO1_MN can be downloaded from the GIS Boundary files page in the IPUMS International web site. The full set of geography variables for Mongolia can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. At the present moment, IPUMS International is only releasing integrated geography for the first level of geography for Mongolia. Year specific geography and maps will become available in the near future. IPUMS Mongolia, Province 1989 - 2000 [Level 1; inconsistent boundaries, harmonized by name] Mongolia, Province 1989 - 2000 [Level 1; inconsistent boundaries, harmonized by name] Mongolia, Province 1989 - 2000 [Level 1; inconsistent boundaries, harmonized by name] Mongolia, Province 1989 - 2000 [Level 1; inconsistent boundaries, harmonized by name] Mongolia, Province 1989 - 2000 [Level 1; inconsistent boundaries, harmonized by name] 1 Arkhangai 2 Bayan-Ölgii 3 Bayankhongor 4 Bulgan 5 Govi-Altai 6 Dornogovi 7 Dornod 8 Dundgovi and Govisumber 9 Zavkhan 10 Övörkhangai 11 Ömnögovi 12 Sükhbaatar 13 Selenge 14 Töv 15 Uvs 16 Khovd 17 Khövsgöl 18 Khentii 19 Darkhan-Uul 20 Ulaanbaatar 21 Orkhon 22 Erdenet GEO1_MNX identifies the household's province (aimag) within Mongolia in all sample years. Provinces are the first level administrative units of the country. GEO1_MNX is harmonized by name and does not account for boundary changes over time. The full set of geography variables for Mongolia can be found in the IPUMS International Geography variables list. For cross-national geographic analysis on the first and second major administrative level refer to GEOLEV1, and GEOLEV2. More information on IPUMS-International geography can be found here. At the present moment, IPUMS International is only releasing integrated geography for the first level of geography for Mongolia. Year specific geography and maps will become available in the near future. IPUMS Number of married couples in household Number of married couples in household Number of married couples in household Number of married couples in household Number of married couples in household No married couples in household 1 1 couple 2 2 couples 3 3 couples 4 4 couples 5 5 couples 6 6 couples 7 7 couples 8 8 couples 9 9 or more couples NCOUPLES is a constructed variable indicating the number of married/in-union couples within a household. NCOUPLES is constructed using the IPUMS-International pointer variable SPLOC (spouse's location in the household). IPUMS Number of mothers in household Number of mothers in household Number of mothers in household Number of mothers in household Number of mothers in household No mothers in household 1 1 mother 2 2 mothers 3 3 mothers 4 4 mothers 5 5 mothers 6 6 mothers 7 7 mothers 8 8 mothers 9 9 or more mothers in household NMOTHERS is a constructed variable indicating the number of mothers -- of persons of any age -- within a household. NMOTHERS is constructed using the IPUMS-International pointer variable MOMLOC (mother's location in the household). IPUMS Number of fathers in household Number of fathers in household Number of fathers in household Number of fathers in household Number of fathers in household No fathers in household 1 1 father 2 2 fathers 3 3 fathers 4 4 fathers 5 5 fathers 6 6 fathers 7 7 fathers 8 8 fathers 9 9 or more fathers in household NFATHERS is a constructed variable indicating the number of fathers -- of persons of any age -- within a household. NFATHERS is constructed using the IPUMS-International pointer variable POPLOC (father's location in the household). IPUMS Country Country Country Country Country 32 Argentina 40 Austria 50 Bangladesh 51 Armenia 68 Bolivia 76 Brazil 112 Belarus 116 Cambodia 120 Cameroon 124 Canada 152 Chile 156 China 170 Colombia 188 Costa Rica 192 Cuba 214 Dominican Republic 218 Ecuador 222 El Salvador 231 Ethiopia 242 Fiji 250 France 275 Palestine 276 Germany 288 Ghana 300 Greece 324 Guinea 332 Haiti 348 Hungary 356 India 360 Indonesia 364 Iran 368 Iraq 372 Ireland 376 Israel 380 Italy 388 Jamaica 400 Jordan 404 Kenya 417 Kyrgyz Republic 430 Liberia 454 Malawi 458 Malaysia 466 Mali 484 Mexico 496 Mongolia 504 Morocco 508 Mozambique 524 Nepal 528 Netherlands 558 Nicaragua 566 Nigeria 586 Pakistan 591 Panama 600 Paraguay 604 Peru 608 Philippines 620 Portugal 630 Puerto Rico 642 Romania 646 Rwanda 662 Saint Lucia 686 Senegal 694 Sierra Leone 704 Vietnam 705 Slovenia 710 South Africa 724 Spain 728 South Sudan 729 Sudan 756 Switzerland 764 Thailand 792 Turkey 800 Uganda 804 Ukraine 818 Egypt 826 United Kingdom 834 Tanzania 840 United States 854 Burkina Faso 858 Uruguay 862 Venezuela 894 Zambia COUNTRY gives the country from which the sample was drawn. The codes assigned to each country are those used by the UN Statistics Division and the ISO (International Organization for Standardization). IPUMS Electricity Electricity Electricity Electricity Electricity NIU (not in universe) 1 Yes 2 No 9 Unknown ELECTRIC indicates whether the household had access to electricity. IPUMS Living area in square meters Living area in square meters Living area in square meters Living area in square meters Living area in square meters LIVEAREA describes the total living area in the dwelling inhabited by the household. LIVEAREA is a 3-digit numeric variable. 000 = NIU (not in universe) 999 = Unknown Unless otherwise specified: 998+ Austria 1991-2001: 150+ Belarus 1999: 201+ Germany 1987: 361+ Hungary 2001: 260+ Iran 2006: 501+ Italy 2001: 150+ Romania 2002: 221+ Slovenia 2002: 101+ Spain 2001: 181+ Switzerland 1980-1990: 400+ Switzerland 2000: 500+ IPUMS Person number Person number Person number Person number Person number PERNUM numbers all persons within each household consecutively (starting with "1" for the first person record of each household). When combined with SAMPLE and SERIAL, PERNUM uniquely identifies each person in the IPUMS-International database. PERNUM is a 3-digit numeric variable. IPUMS Mother's location in household Mother's location in household Mother's location in household Mother's location in household Mother's location in household MOMLOC is a constructed variable that indicates whether or not the person's mother lived in the same household and, if so, gives the person number of the mother (see PERNUM). MOMLOC makes it easy for researchers to link the characteristics of children and their (probable) mothers. The method by which probable child-mother links are identified is described in PARRULE. The general design of MOMLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. Note: MOMLOC identifies social relationships (such as stepmother and adopted mother) as well as biological relationships. The variable STEPMOM is designed to identify some of these social relationships. MOMLOC is a 3-digit numeric variable. 0 = No mother of this person present in the household. 1 or higher = The person number of this person's mother IPUMS Father's location in household Father's location in household Father's location in household Father's location in household Father's location in household POPLOC is a constructed variable that indicates whether or not the person's father lived in the same household and, if so, gives the person number of the father (see PERNUM). POPLOC makes it easy for researchers to link the characteristics of children and their (probable) fathers. The method by which probable child-father links are identified is described in PARRULE. The general design of POPLOC and other constructed variables follows the methods developed for IPUMS-USA "Family Interrelationships," but the details vary significantly. Note: POPLOC identifies social relationships (such as stepfather and adopted father) as well as biological relationships. The variable STEPPOP is designed to identify some of these social relationships. POPLOC is a 3-digit numeric variable. 0 = No father of this person present in the household. 1 or higher = The person number of this person's father IPUMS Spouse's location in household Spouse's location in household Spouse's location in household Spouse's location in household Spouse's location in household SPLOC is a constructed variable that indicates whether or not the person's spouse lived in the same household and, if so, gives the person number (PERNUM) of the spouse. SPLOC makes it easy for researchers to link the characteristics of (probable) spouses. The method by which probable spouse-spouse links are identified is described in SPRULE. The general design of SPLOC and other constructed variables is modeled on the methods developed for IPUMS-USA "Family Interrelationships", but the details vary significantly. SPLOC is a 3-digit numeric variable. 0 = No spouse of this person present in the household. 1 or higher = The person number of this person's spouse IPUMS Rule for linking parent Rule for linking parent Rule for linking parent Rule for linking parent Rule for linking parent No parent of person in household 11 Link to head or spouse, unambiguous 12 Link to head or spouse, ambiguous 21 Child-Grandchild, within empirical child cap 22 Child-Grandchild, within constructed child cap 23 Child-Grandchild, exceeds child cap 31 Specified Other Relatives, within empirical child cap 32 Specified Other Relatives, within constructed child cap 33 Specified Other Relatives, exceeds child cap 41 Other Relatives, within empirical child cap 42 Other Relatives, within constructed child cap 51 Non-Relatives, within empirical child cap 52 Non-Relatives, within constructed child cap PARRULE describes the criteria by which the IPUMS-International variables MOMLOC and POPLOC linked the person to a probable mother and/or father. IPUMS-International establishes child-parent links according to five basic rules, and PARRULE gives the number of the rule that applied to the link in question. A link to any parent automatically generates a second link to that parent's spouse or partner, so only one rule is needed to describe both MOMLOC and POPLOC. The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology. IPUMS Rule for linking spouse Rule for linking spouse Rule for linking spouse Rule for linking spouse Rule for linking spouse No spouse present 1 Rule 1: strong relationship pairing, couple adjacent 2 Rule 2: strong relationship pairing, couple not adjacent 3 Rule 3: weak relationship pairing, couple adjacent 4 Rule 4: weak relationship pairing, couple not adjacent 5 Rule 5: weak consensual union pairings 6 Rule 6: sample-specific rules (usually child-to-child) SPRULE explains the criteria by which the IPUMS-International variable SPLOC linked the person to his/her probable spouse. IPUMS-International establishes spouse-spouse links according to five basic rules, and SPRULE gives the number of the rule that applied to the link in question. A sixth rule identifies sample-specific linking procedures only imposed in selected instances. The design of the interrelationship variables is described in this paper on IPUMSI family linking methodology. IPUMS Probable stepmother Probable stepmother Probable stepmother Probable stepmother Probable stepmother Biological mother or no mother present 1 Mother has no children borne or surviving 2 Child reports mother is deceased 3 Explicitly identified step relationship 4 Mother reports no children in the home 5 Age difference implausible 6 Child exceeds known fertility of mother STEPMOM indicates whether a person's mother, as identified by MOMLOC, was most probably not the person's biological mother. Non-zero values of STEPMOM explain why it is probable that the person's mother was a step- or adopted mother. A value of 0 indicates no likely stepmother because (1) the mother identified in MOMLOC was probably the biological mother or (2) there is no mother of this person present in the household. The codes for STEPMOM are as follows: 0 = Biological mother or no mother of this person present in household. 1 = Mother has no children borne or surviving. 2 = Child reports mother is deceased. 3 = Explicitly identified relationship (stepchild, adopted child, child of unmarried partner, stepchild/child-in-law). 4 = Mother reports no children in the home. 5 = Age difference between mother and child was less than 12 or greater than 54 years. 6 = Child exceeds known fertility of mother. See PARRULE for a description of the linking process. Users should note that there are many stepmothers and adopted mothers in the population that cannot be identified with information available in the censuses. Therefore, STEPMOM will always under-represent their actual number in the population. IPUMS Probable stepfather Probable stepfather Probable stepfather Probable stepfather Probable stepfather Biological father or no father present 1 Child reports father is deceased 2 Explicitly identified step relationship 3 Age difference implausible STEPPOP indicates whether a person's father, as identified by POPLOC , was most probably not the person's biological father. Non-zero values of STEPPOP explain why it is probable that the person's father was a step- or adopted father. A value of 0 indicates no likely stepfather because (1) the father identified in POPLOC was probably the biological father or (2) there is no father of this person present in the household. The codes for STEPPOP are as follows: 0 = Biological father or no father of this person present in household. 1 = Child reports father is deceased. 2 = Explicitly identified relationship (stepchild, adopted child, child of unmarried partner; stepchild/child-in-law). 3 = Age difference between father and child was less than 12 or greater than 54 years. See PARRULE for a description of the linking process. Users should note that there are many stepfathers and adopted fathers in the population that cannot be identified with information available in the censuses. Therefore, STEPPOP will always under-represent their actual number in the population. IPUMS Man with more than one wife linked Man with more than one wife linked Man with more than one wife linked Man with more than one wife linked Man with more than one wife linked No more than one wife linked via SPLOC 1 More than one wife linked via SPLOC POLYMAL indicates if a man had more than one wife linked to him in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The point of POLYMAL is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record. IPUMS Woman is second or higher order wife Woman is second or higher order wife Woman is second or higher order wife Woman is second or higher order wife Woman is second or higher order wife Person is not the 2nd or higher order wife linked via SPLOC 1 Person is the 2nd or higher order wife linked via SPLOC POLY2ND indicates if a woman was the second or higher order wife linked to a husband in the constructed IPUMS variable SPLOC -- Spouse's Location in Household. The variable does not suggest the actual marital order of wives, only their relative positions in the person order of the household as it was enumerated. The point of POLY2ND is to facilitate using SPLOC in samples that identify polygamy. Some statistical matching procedures expect to find only one matching record for each subject record. IPUMS Family unit membership Family unit membership Family unit membership Family unit membership Family unit membership FAMUNIT is a constructed variable indicating to which family within the household a person belongs. All persons related to the household head receive a 1 (see RELATE). Each secondary family or secondary individual receives a higher code. For purposes of FAMUNIT, secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). FAMUNIT is a 2-digit numeric variable. If there is only one group of related individuals within the household, all of them will be coded "1;" if there is a second, separate such group listed on the form, all of them will be coded "2," and so on. IPUMS Number of own family members in household Number of own family members in household Number of own family members in household Number of own family members in household Number of own family members in household 1 1 family member present 2 2 family members present 3 3 family members present 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95 96 96 97 97 98 98 99 99 or more persons FAMSIZE counts the number of the person's own family members living in the household with her/him, including the person her/himself. These include all persons related to the person by blood, adoption, or marriage as indicated by the census forms or inferred from them. FAMSIZE is calculated from the units identified in the IPUMS constructed variable FAMUNIT (family unit membebership). The primary family is defined as all persons related to the head in the RELATE variable. Secondary families are individuals or groups of persons linked together by the IPUMS constructed pointer variables SPLOC, MOMLOC, and POPLOC (location of spouse, mother, and father). IPUMS Number of own children in household Number of own children in household Number of own children in household Number of own children in household Number of own children in household 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 or more children in household NCHILD provides a count of the person's own children living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. IPUMS Number of own children under age 5 in household Number of own children under age 5 in household Number of own children under age 5 in household Number of own children under age 5 in household Number of own children under age 5 in household 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 or more own children under age 5 in household NCHLT5 provides a count of the person's own children under age five living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. IPUMS Age of eldest own child in household Age of eldest own child in household Age of eldest own child in household Age of eldest own child in household Age of eldest own child in household 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 99 No own child in household ELDCH gives the age of the person's oldest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. ELDCH is top-coded at age 50 or older. IPUMS Age of youngest own child in household Age of youngest own child in household Age of youngest own child in household Age of youngest own child in household Age of youngest own child in household 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 or older 99 No own child in household YNGCH gives the age of the person's youngest own child living in the household with her or him. These include all children linked to the person via the constructed IPUMS pointer variables MOMLOC or POPLOC -- mother's and father's location in the household. YNGCH is top-coded at age 50 or older. IPUMS Relationship to household head [general version] Relationship to household head [general version] Relationship to household head [general version] Relationship to household head [general version] Relationship to household head [general version] 1 Head 2 Spouse/partner 3 Child 4 Other relative 5 Non-relative 6 Other relative or non-relative 9 Unknown RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). IPUMS Relationship to household head [detailed version] Relationship to household head [detailed version] Relationship to household head [detailed version] Relationship to household head [detailed version] Relationship to household head [detailed version] 1000 Head 2000 Spouse/partner 2100 Spouse 2200 Unmarried partner 2300 Same-sex spouse/partner 3000 Child 3100 Biological child 3200 Adopted child 3300 Stepchild 3400 Child/child-in-law 3500 Child/child-in-law/grandchild 3600 Child of unmarried partner 4000 Other relative 4100 Grandchild 4110 Grandchild or great grandchild 4120 Great grandchild 4130 Great-great grandchild 4200 Parent/parent-in-law 4210 Parent 4211 Stepparent 4220 Parent-in-law 4300 Child-in-law 4301 Daughter-in-law 4302 Spouse/partner of child 4310 Unmarried partner of child 4400 Sibling/sibling-in-law 4410 Sibling 4420 Stepsibling 4430 Sibling-in-law 4431 Sibling of spouse/partner 4432 Spouse/partner of sibling 4500 Grandparent 4510 Great grandparent 4600 Parent/grandparent/ascendant 4700 Aunt/uncle 4800 Other specified relative 4810 Nephew/niece 4820 Cousin 4830 Sibling of sibling-in-law 4900 Other relative, not elsewhere classified 4910 Other relative with same family name 4920 Other relative with different family name 4930 Other relative, not specified (secondary family) 5000 Non-relative 5100 Friend/guest/visitor/partner 5110 Partner/friend 5111 Friend 5112 Partner/roommate 5113 Housemate/roommate 5120 Visitor 5130 Ex-spouse 5140 Godparent 5150 Godchild 5200 Employee 5210 Domestic employee 5220 Relative of employee, n.s. 5221 Spouse of servant 5222 Child of servant 5223 Other relative of servant 5300 Roomer/boarder/lodger/foster child 5310 Boarder 5311 Boarder or guest 5320 Lodger 5330 Foster child 5340 Tutored/foster child 5350 Tutored child 5400 Employee, boarder or guest 5500 Other specified non-relative 5510 Agregado 5520 Temporary resident, guest 5600 Group quarters 5610 Group quarters, non-inmates 5620 Institutional inmates 5900 Non-relative, n.e.c. 6000 Other relative or non-relative 9999 Unknown RELATE describes the relationship of the individual to the head of household (sometimes called the householder or reference person). IPUMS Age Age Age Age Age Less than 1 year 1 1 year 2 2 years 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95 96 96 97 97 98 98 99 99 100 100+ 999 Not reported/missing AGE gives age in years as of the person's last birthday prior to or on the day of enumeration. IPUMS Age, grouped into intervals Age, grouped into intervals Age, grouped into intervals Age, grouped into intervals Age, grouped into intervals 1 0 to 4 2 5 to 9 3 10 to 14 4 15 to 19 5 15 to 17 6 18 to 19 7 18 to 24 8 20 to 24 9 25 to 29 10 30 to 34 11 35 to 39 12 40 to 44 13 45 to 49 14 50 to 54 15 55 to 59 16 60 to 64 17 65 to 69 18 70 to 74 19 75 to 79 20 80+ 98 Unknown AGE2 gives computed years of age grouped into intervals. IPUMS Sex Sex Sex Sex Sex 1 Male 2 Female 9 Unknown SEX reports the sex (gender) of the respondent. IPUMS Marital status [general version] Marital status [general version] Marital status [general version] Marital status [general version] Marital status [general version] NIU (not in universe) 1 Single/never married 2 Married/in union 3 Separated/divorced/spouse absent 4 Widowed 9 Unknown/missing [program universe for et,mz samples. MARST describes the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. Census instructions rarely explicitly limit marital status to strictly legal unions. Note regarding universe: The lowest age at which a person can be anything but "never married" varies among samples. IPUMS Marital status [detailed version] Marital status [detailed version] Marital status [detailed version] Marital status [detailed version] Marital status [detailed version] NIU (not in universe) 100 Single/never married 110 Engaged 111 Never married and never cohabited 200 Married or consensual union 210 Married, formally 211 Married, civil 212 Married, religious 213 Married, civil and religious 214 Married, civil or religious 215 Married, traditional/customary 216 Married, monogamous 217 Married, polygamous 220 Consensual union 300 Separated/divorced/spouse absent 310 Separated or divorced 320 Separated or annulled 330 Separated 331 Separated legally 332 Separated de facto 333 Separated from marriage 334 Separated from consensual union 335 Separated from consensual union or marriage 340 Annulled 350 Divorced 360 Married, spouse absent 400 Widowed 410 Widowed or divorced 411 Widowed from consensual union or marriage 412 Widowed from marriage 413 Widowed from consensual union 420 Widowed, divorced, or separated 999 Unknown/missing [program universe for et,mz samples. MARST describes the person's current marital status according to law or custom. Individuals who remarried should report the status relevant to their most recent marriage. Census instructions rarely explicitly limit marital status to strictly legal unions. Note regarding universe: The lowest age at which a person can be anything but "never married" varies among samples. IPUMS Month of birth Month of birth Month of birth Month of birth Month of birth 1 January 2 February 3 March 4 April 5 May 6 June 7 July 8 August 9 September 10 October 11 November 12 December 98 Unknown 99 NIU (not in universe) BIRTHMO indicates the person's month of birth. IPUMS Children ever born Children ever born Children ever born Children ever born Children ever born No children 1 1 child 2 2 children 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) CHBORN reports the number of children ever born to each woman of whom the question was asked. In most samples, women were to report all live births by all fathers, whether or not the child was still living. IPUMS Children surviving Children surviving Children surviving Children surviving Children surviving No children 1 1 child 2 2 children 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30+ 98 Unknown 99 NIU (not in universe) CHSURV reports the number of children born to a woman who were still living at the time of the census. IPUMS Province of birth, Mongolia Province of birth, Mongolia Province of birth, Mongolia Province of birth, Mongolia Province of birth, Mongolia 1 Arkhangai 2 Bayan-Ölgii 3 Bayankhongor 4 Bulgan 5 Govi-Altai 6 Dornogovi 7 Dornod 8 Dundgovi 9 Govisumber 10 Zavkhan 11 Övörkhangai 12 Ömnögovi 13 Sükhbaatar 14 Selenge 15 Töv 16 Uvs 17 Khovd 18 Khövsgöl 19 Khentii 20 Darkhan-Uul 21 Ulaanbaatar 22 Erdenet 23 Orkhon 98 Foreign country 99 Unknown BPLMN indicates the person's province (aimag) of birth within Mongolia. IPUMS Citizenship Citizenship Citizenship Citizenship Citizenship 1 Citizen, not specified 2 Citizen by birth 3 Naturalized citizen 4 Not a citizen 5 Without citizenship, stateless 8 Unknown 9 NIU (not in universe) CITIZEN indicates the person's citizenship status within the country in which they were enumerated. IPUMS Country of citizenship Country of citizenship Country of citizenship Country of citizenship Country of citizenship NIU (not in universe) 10000 Africa 11000 Eastern Africa 11010 Burundi 11020 Comoros 11030 Djibouti 11040 Eritrea 11050 Ethiopia 11060 Kenya 11070 Madagascar 11080 Malawi 11090 Mauritius 11100 Mozambique 11110 Reunion 11120 Rwanda 11130 Seychelles 11140 Somalia 11150 Uganda 11160 Tanzania 11170 Zambia 11180 Zimbabwe 11999 Eastern Africa, n.s. 12000 Middle Africa 12010 Angola 12020 Cameroon 12030 Central African Republic 12040 Chad 12050 Congo (Republic of) 12060 Democratic Republic of Congo 12070 Equatorial Guinea 12080 Gabon 12090 Sao Tome and Principe 12999 Middle Africa, n.s. 13000 Northern Africa 13010 Algeria 13011 Algeria/Tunisia 13020 Egypt/United Arab Rep. 13021 Egypt/Sudan 13030 Libya 13040 Morocco 13050 Sudan 13060 Tunisia 13070 Western Sahara 13999 Northern Africa, n.s. 14000 Southern Africa 14010 Botswana 14020 Lesotho 14030 Namibia 14040 South Africa 14050 Swaziland 14999 Southern Africa, n.s. 15000 Western Africa 15010 Benin 15020 Burkina Faso 15030 Cape Verde 15040 Ivory Coast 15050 Gambia 15060 Ghana 15070 Guinea 15080 Guinea-Bissau 15090 Liberia 15100 Mali 15110 Mauritania 15120 Niger 15130 Nigeria 15140 St. Helena and Ascension 15150 Senegal 15160 Sierra Leone 15170 Togo 15991 Burkina-Faso, Niger, Ivory-Coast, Benin, Togo 15992 Liberia, Sierra-Leone, Nigeria, Ghana 15999 West Africa, n.s. 19990 Africa, n.s. 19991 Central and South Africa 19992 Arab African countries 19993 Non-Arab African countries 19994 Other Arab countries 19995 East, Central and South Africa 20000 Americas 21000 Caribbean 21010 Anguilla 21020 Antigua-Barbuda 21030 Aruba 21040 Bahamas 21050 Barbados 21060 British Virgin Islands 21070 Cayman Isles 21080 Cuba 21090 Dominica 21100 Dominican Republic 21110 Grenada 21120 Guadeloupe 21130 Haiti 21140 Jamaica 21150 Martinique 21160 Montserrat 21170 Netherlands Antilles 21180 Puerto Rico 21190 St. Kitts-Nevis 21200 St. Lucia 21210 St. Vincent 21220 Trinidad and Tobago 21230 Turks and Caicos 21999 Caribbean, n.s. 22000 Central America 22010 Belize/British Honduras 22020 Costa Rica 22030 El Salvador 22040 Guatemala 22050 Honduras 22060 Mexico 22070 Nicaragua 22080 Panama 22081 Panama Canal Zone 22999 Central America, n.s. 23000 South America 23010 Argentina 23020 Bolivia 23030 Brazil 23040 Chile 23050 Colombia 23060 Ecuador 23070 Falkland Islands 23080 French Guiana 23090 Guyana/British Guiana 23100 Paraguay 23110 Peru 23120 Suriname 23130 Uruguay 23140 Venezuela 23990 South America, n.s. 24000 North America 24010 Bermuda 24020 Canada 24030 Greenland 24040 United States 24041 U.S. Outlying Areas and Territories 24090 U.S. and Canada 24999 North America, n.s. 29900 Americas, n.s. 29901 America/Oceania 29902 Central/South America, n.s. 29903 Central-America and Carribean 29904 Central/South America and Caribbean 29905 North and Central America, n.s. 30000 Asia 31000 Eastern Asia 31010 China 31011 Hong Kong 31012 Macau 31013 Taiwan 31020 Japan 31030 Korea 31031 Korea, DPR (North) 31032 Korea, RO (South) 31040 Mongolia 31999 Eastern Asia, n.s. 32000 South-Central Asia 32010 Afghanistan 32020 Bangladesh 32030 Bhutan 32040 India 32041 India/Pakistan 32050 Iran 32060 Kazakhstan 32070 Kyrgyzstan 32080 Maldives 32090 Nepal 32100 Pakistan 32110 Sri Lanka (Ceylon) 32120 Tajikistan 32130 Turkmenistan 32140 Uzbekistan 32990 Burma, India, Pakistan, Ceylon 32999 South-Central Asia, n.s. 33000 South-Eastern Asia 33010 Brunei 33020 Cambodia (Kampuchea) 33030 East Timor 33040 Indonesia 33050 Laos 33060 Malaysia 33070 Myanmar (Burma) 33080 Philippines 33090 Singapore 33100 Thailand 33110 Vietnam 33991 Laos and Cambodia 33992 Malaysia and Singapore 33999 South-Eastern Asia, n.s. 34000 Western Asia 34010 Armenia 34020 Azerbaijan 34030 Bahrain 34040 Cyprus 34050 Georgia 34060 Iraq 34070 Israel 34080 Jordan 34090 Kuwait 34100 Lebanon 34110 Palestine 34120 Oman 34130 Qatar 34140 Saudi Arabia 34150 Syria 34151 Syria/Lebanon 34160 Turkey 34170 United Arab Emirates 34180 Yemen 34999 Western Asia, n.s. 39900 Asia, n.s. 39901 South-East/South Asia, n.s. 39902 West Central/Middle East Asia 39903 Arab Countries 39904 Non-Arab Asian countries 39905 Former Soviet Republics, Asia 40000 Europe 41000 Eastern Europe 41010 Belarus 41020 Bulgaria 41021 Bulgaria/Greece 41030 Czech Republic/Czechoslovakia 41040 Hungary 41050 Poland 41060 Moldova 41070 Romania 41080 Russia/USSR 41090 Slovakia 41100 Ukraine 41999 Eastern Europe, n.s. 42000 Northern Europe 42010 Denmark 42020 Estonia 42030 Faroe Islands 42040 Finland 42050 Iceland 42060 Ireland 42070 Latvia 42080 Lithuania 42090 Norway 42100 Svalbard and Jan Mayen Islands 42110 Sweden 42120 United Kingdom 42990 Nordic countries 42999 Northern Europe, n.s. 43000 Southern Europe 43010 Albania 43020 Andorra 43030 Bosnia and Herzegovina 43040 Croatia 43050 Gibraltar 43060 Greece 43070 Italy 43071 Vatican 43080 Malta 43090 Portugal 43100 San Marino 43110 Slovenia 43120 Spain 43130 Macedonia 43140 Yugoslavia 43141 Montenegro 43142 Serbia 43143 Kosovo 43144 Serbia and Montenegro 43999 Southern Europe, n.s. 44000 Western Europe 44010 Austria 44020 Belgium 44030 France 44040 Germany 44041 West Germany 44042 East Germany 44050 Liechtenstein 44060 Luxembourg 44070 Monaco 44080 Netherlands 44090 Switzerland 44999 Western Europe, n.s. 49990 Europe, n.s. 49991 Central-Eastern Europe 49992 European Union (Original 15) 49993 Other European Union 49994 Former Soviet Republics, Europe 49995 EEA, Switzerland, associated microstates 50000 Oceania 51000 Australia and New Zealand 51010 Australia 51020 New Zealand 51030 Norfolk Islands 51999 Australia and New Zealand, n.s. 52000 Melanesia 52010 Fiji 52020 New Caledonia 52030 Papua New Guinea 52040 Solomon Islands 52050 Vanuatu (New Hebrides) 52999 Melanesia, n.s. 53000 Micronesia 53010 Kiribati 53020 Marshall Islands 53030 Nauru 53040 Northern Mariana Isls. 53050 Palau 53999 Micronesia, n.e.c. 54000 Polynesia 54010 Cook Islands 54020 French Polynesia 54030 Niue 54040 Pitcairn Island 54050 Western Samoa 54060 Eastern Samoa 54070 Tokelau 54080 Tonga 54090 Tuvalu 54100 Wallis and Futuna Isls. 54999 Polynesia, n.s. 59999 Oceania, n.s. 60000 Asia n.s. or Oceania n.s. 70000 Other Countries 70010 Europe, Australia and New Zealand 70020 Australia, New Zealand, and stateless 99997 No citizenship/nationality 99998 Foreign, country unknown 99999 Unknown NATION indicates the person's country of citizenship. IPUMS Literacy Literacy Literacy Literacy Literacy NIU (not in universe) 1 No, illiterate 2 Yes, literate 9 Unknown/missing LIT indicates whether or not the respondent could read and write in any language. A person is typically considered literate if he or she can both read and write. All other persons are illiterate, including those who can either read or write but cannot do both. IPUMS Educational attainment, Mongolia Educational attainment, Mongolia Educational attainment, Mongolia Educational attainment, Mongolia Educational attainment, Mongolia Less than primary 1 Less than primary, illiterate 2 Less than primary, literate 10 Primary 20 Secondary 21 Lower secondary (grades 4-8) 22 Upper secondary (grades 9-10) 30 Technical vocational, unspecified 31 Post-primary technical 32 Secondary or post-secondary technical 40 Higher education 41 Some higher education 42 Completed higher education 99 NIU (not in universe) EDUCMN indicates the person's educational attainment in terms of the level of schooling completed. IPUMS Year of birth Year of birth Year of birth Year of birth Year of birth NIU (not in universe) 1843 1843 1845 1845 1850 1850 1853 1853 1854 1854 1856 1856 1858 1858 1859 1859 1860 1860 1861 1861 1862 1862 1863 1863 1864 1864 1865 1865 1866 1866 1867 1867 1868 1868 1869 1869 1870 1870 1871 1871 1872 1872 1873 1873 1874 1874 1875 1875 1876 1876 1877 1877 1878 1878 1879 1879 1880 1880 1881 1881 1882 1882 1883 1883 1884 1884 1885 1885 1886 1886 1887 1887 1888 1888 1889 1889 1890 1890 1891 1891 1892 1892 1893 1893 1894 1894 1895 1895 1896 1896 1897 1897 1898 1898 1899 1899 1900 1900 1901 1901 1902 1902 1903 1903 1904 1904 1905 1905 1906 1906 1907 1907 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013 9999 Unknown BIRTHYR gives the person's year of birth. IPUMS Residence status: de facto, de jure Residence status: de facto, de jure Residence status: de facto, de jure Residence status: de facto, de jure Residence status: de facto, de jure 1 Present resident 2 Absent resident 3 Visitor/non-resident 4 De facto population (present persons) 9 Unknown/missing RESIDENT identifies whether an enumerated person is a household resident or a visitor and whether she or he was present at the time of enumeration. This variable is available only in samples that enumerated both de facto and de jure residents. It can be used to eliminate the double-counting of persons who were enumerated both at their permanent residence and at the residence they were visiting on census night. De jure population: present residents and absent residents. De facto population: present residents and visitors/non-residents. IPUMS Person number (within household) Person number (within household) Person number (within household) Person number (within household) Person number (within household) Person number (within household) All persons Household record 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 This variable indicates the person number (within household). IPUMS Person number Person number Person number Person number Person number Person number All persons 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 This variable indicates the person number. IPUMS Relationship to household head Relationship to household head Relationship to household head Relationship to household head Relationship to household head 1. Relationship to household head: [] 01 Household head [] 02 Wife/husband [] 03 Daughter/son [] 04 Parents [] 05 Sister/brother [] 07 Daughter/son-in-law [] 08 Grandparents [] 09 Grandchild [] 10 Other relatives [] 11 Single [] 12 Separated from household All persons 1 Household head 2 Wife/husband 3 Daughter/son 4 Parents 5 Sister/brother 6 Father/mother-in-law 7 Daughter/son-in-law 8 Grandparent 9 Grandchild 10 Other relative 11 Single 12 Non-relative This variable indicates the person's relationship to the household head. IPUMS Resident type Resident type Resident type Resident type Resident type 2. [Residency status] [] 1 Resident [] 2 Temporary absent [] 3 Visitor All persons 1 Resident 2 Temporarily absent 3 Visitor This variable indicates the person's residency status. IPUMS Visitor: aimag Visitor: aimag Visitor: aimag Visitor: aimag Visitor: aimag 2. [Residency status] [] 1 Resident [] 2 Temporary absent [] 3 Visitor Persons who are visitors 1 Arkhangai 2 Bayan-Ulgii 3 Bayankhongor 4 Bulgan 5 Govi-Altai 6 Dornogovi 7 Dornod 8 Dundgovi 9 Zavkhan 10 Uvurkhangai 11 Umnugovi 12 Sukhbaatar 13 Selenge 14 Tuv 15 Uvs 16 Khovd 17 Khuvsgul 18 Khentii 19 Darkhan 20 Ulaanbaatar 21 Erdenet 98 Unknown 99 NIU (not in universe) This variable indicates the visitor's usual province (aimag) of residence. IPUMS Sex Sex Sex Sex Sex 3. Sex: [] 1 Male [] 2 Female All persons 1 Male 2 Female This variable indicates the person's sex. IPUMS Year of birth Year of birth Year of birth Year of birth Year of birth 4. Date of birth: Year ____ Month ____ Day ____ Age _ _ Aimag (province) _____ Soum (district) _____ All persons 1884 1884 1887 1887 1888 1888 1890 1890 1892 1892 1893 1893 1894 1894 1895 1895 1896 1896 1897 1897 1898 1898 1899 1899 1900 1900 1901 1901 1902 1902 1903 1903 1904 1904 1905 1905 1906 1906 1907 1907 1908 1908 1909 1909 1910 1910 1911 1911 1912 1912 1913 1913 1914 1914 1915 1915 1916 1916 1917 1917 1918 1918 1919 1919 1920 1920 1921 1921 1922 1922 1923 1923 1924 1924 1925 1925 1926 1926 1927 1927 1928 1928 1929 1929 1930 1930 1931 1931 1932 1932 1933 1933 1934 1934 1935 1935 1936 1936 1937 1937 1938 1938 1939 1939 1940 1940 1941 1941 1942 1942 1943 1943 1944 1944 1945 1945 1946 1946 1947 1947 1948 1948 1949 1949 1950 1950 1951 1951 1952 1952 1953 1953 1954 1954 1955 1955 1956 1956 1957 1957 1958 1958 1959 1959 1960 1960 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 This variable indicates the person's year of birth. IPUMS Month of birth Month of birth Month of birth Month of birth Month of birth 4. Date of birth: Year ____ Month ____ Day ____ Age _ _ Aimag (province) _____ Soum (district) _____ All persons 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 99 Unknown This variable indicates the person's month of birth. IPUMS Age Age Age Age Age 4. Date of birth: Year ____ Month ____ Day ____ Age _ _ Aimag (province) _____ Soum (district) _____ All persons Less than 1 year old 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 65 65 66 66 67 67 68 68 69 69 70 70 71 71 72 72 73 73 74 74 75 75 76 76 77 77 78 78 79 79 80 80 81 81 82 82 83 83 84 84 85 85 86 86 87 87 88 88 89 89 90 90 91 91 92 92 93 93 94 94 95 95 96 96 98 98 99 99 100 100 101 101 104 104 This variable indicates the person's age. IPUMS Province (aimag) of birth Province (aimag) of birth Province (aimag) of birth Province (aimag) of birth Province (aimag) of birth 4. Date of birth: Year ____ Month ____ Day ____ Age _ _ Aimag (province) _____ Soum (district) _____ All persons 1 Arkhangai 2 Bayan-Ulgii 3 Bayankhongor 4 Bulgan 5 Govi-Altai 6 Dornogovi 7 Dornod 8 Dundgovi 9 Zavkhan 10 Uvurkhangai 11 Umnugovi 12 Sukhbaatar 13 Selenge 14 Tuv 15 Uvs 16 Khovd 17 Khuvsgul 18 Khentii 19 Darkhan 20 Ulaanbaatar 21 Erdenet 98 Abroad 99 Unknown This variable indicates the person's province (Aimag) of birth. IPUMS Ethnicity Ethnicity Ethnicity Ethnicity Ethnicity 5. Ethnicity _____ All persons 1 Khalkh 2 Kazakh 3 Dorvod 4 Buriad 5 Bayad 6 Dariganga 7 Uriankhai 8 Zakhchin 9 Darkhad 10 Torguud 11 Uuld 12 Khoton 13 Myangad 14 Barga 15 Uzemchin 16 Kharchin 17 Tsakhar 18 Khotgoid 21 Russian /Mongolian citizens 22 Chinese /Mongolian citizens 23 Other ethnicity /Mongolian citizens 24 Russian /Russian citizens 25 Chinese /Citizens of PRC 26 Other ethnicity /Foreign citizens 99 Unknown This variable indicates the person's ethnicity. IPUMS Citizenship Citizenship Citizenship Citizenship Citizenship 6. Citizenship _____ All persons 1 Mongolia 2 Soviet Union 3 Bulgaria 4 Vietnam 5 Germany 6 Cuba 7 Poland 8 Romania 9 Korea 11 China 12 Czechoslovakia 13 Cambodia 14 Laos 15 Japan 16 Other This variable indicates the person's citizenship. IPUMS Social status of origin Social status of origin Social status of origin Social status of origin Social status of origin 9. Social origin: [] 1 Employee [] 2 Civil servant (intellectual) [] 3 Herder [] 4 Member of cooperatives [] 5 Member of craftsman [] 6 Other All persons 1 Employee 2 Civil servant (intellectual) 3 Herder 4 Member of cooperative 5 Member of craftsmen cooperative 6 Other This variable indicates the person's social status of origin based upon the working status of the person's parent at the time of birth. IPUMS Social group Social group Social group Social group Social group 10. Social group: [] 1 Employee [] 2 Civil servant (intellectual) [] 3 Member of cooperatives [] 4 Other All persons 1 Employee 2 Civil servant (intellectual) 3 Member of cooperative 4 Other This variable indicates the person's social group. IPUMS Income source Income source Income source Income source Income source 11. Income source: [] 1 Industry, enterprise, official organization [] 2 Agricultural cooperative [] 3 Pension [] 4 Student stipend [] 5 Other kind of pension, benefits [] 6 Under care of others [] 7 Own farm, private labor [] 8 Society for labor, work (cooperative) [] 9 Other All persons 1 Industry, enterprise, official organization 2 Agricultural cooperative 3 Pension 4 Students stipend 5 Other kind of pension benefits 6 Under care of others 7 Own farm, private labour 8 Society for labour, work (cooperative) 9 Other This variable indicates the person's income source. IPUMS Education level Education level Education level Education level Education level 12. Education: [] 1 Completed high [] 2 Non completed high [] 3 Technical vocational [] 4 General education Grade 9-10 [] 5 General education Grade 4-8 [] 6 Primary [] 7 Literate [] 8 Illiterate Persons age 7+ 1 Completed high 2 Non-completed high 3 Technical vocational 4 General education, grade 9-10 5 General education, grade 4-8 6 Primary 7 Literate 8 Illiterate 9 NIU (not in universe) This variable indicates the person's education level. IPUMS Marital status Marital status Marital status Marital status Marital status 14. Marital status: [] 1 Married [] 2 Widowed [] 3 Divorced [] 4 Never married Persons age 15+ 1 Married 2 Widowed 3 Divorced 4 Never married 9 NIU (not in universe) This variable indicates the person's marital status. IPUMS Number of children ever born Number of children ever born Number of children ever born Number of children ever born Number of children ever born [Question 15 was asked only of women.] 15. Number of children ever born _ _ Of which: number of living children _ _ Females age 15+ 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 22 22 98 Unknown 99 NIU (not in universe) This variable indicates the number of children ever born to a person. IPUMS Number of living children Number of living children Number of living children Number of living children Number of living children [Question 15 was asked only of women.] 15. Number of children ever born _ _ Of which: number of living children _ _ Females age 15+ 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 98 Unknown 99 NIU (not in universe) This variable indicates the number of children who are still alive. IPUMS Person weight Person weight Person weight Person weight Person weight Person weight All persons This variable indicates the expansion factor (weight) for the case. This is a 5-digit numeric variable with 3 implied decimal places IPUMS Person weight Person weight Person weight Person weight Person weight PERWT indicates the number of persons in the actual population represented by the person in the sample. For the samples that are truly weighted (see the comparability discussion), PERWT must be used to yield accurate statistics for the population. NOTE: PERWT has 2 implied decimal places. That is, the last two digits of the eight-digit variable are decimal digits, but there is no actual decimal in the data. PERWT is an 8-digit numeric variable with 2 implied decimal places. See the variable description. IPUMS Educational attainment, international recode [general version] Educational attainment, international recode [general version] Educational attainment, international recode [general version] Educational attainment, international recode [general version] Educational attainment, international recode [general version] NIU (not in universe) 1 Less than primary completed 2 Primary completed 3 Secondary completed 4 University completed 9 Unknown EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. IPUMS Educational attainment, international recode [detailed version] Educational attainment, international recode [detailed version] Educational attainment, international recode [detailed version] Educational attainment, international recode [detailed version] Educational attainment, international recode [detailed version] NIU (not in universe) 100 Less than primary completed (n.s.) 110 No schooling 120 Some primary completed 130 Primary (4 yrs) completed 211 Primary (5 yrs) completed 212 Primary (6 yrs) completed 221 Lower secondary general completed 222 Lower secondary technical completed 311 Secondary, general track completed 312 Some college completed 320 Secondary or post-secondary technical completed 321 Secondary, technical track completed 322 Post-secondary technical education 400 University completed 999 Unknown/missing EDATTAIN records the person's educational attainment in terms of the level of schooling completed (degree or other milestone). The emphasis on level completed is critical: a person attending the final year of secondary education receives the code for having completed lower secondary only -- and in some samples only primary. EDATTAIN does not necessarily reflect any particular country's definition of the various levels of schooling in terms of terminology or the number of years of schooling. EDATTAIN is an attempt to merge -- into a single, roughly comparable variable -- samples that provide degrees, ones that provide actual years of schooling, and those that have some of both. In addition to EDATTAIN, a country-specific education classification is provided which loses no information and reflects the particular educational system of that country (for example EDUCBR for Brazil, EDUCCL for Chile, and EDUCUS for the United States). As always, users can refer to the original education source variables for each sample, if they wish. Many samples also give single years of schooling completed, recorded in YRSCHOOL. Some samples provide educational information in a form that could not be incorporated into EDATTAIN. IPUMS Ethnicity, Mongolia Ethnicity, Mongolia Ethnicity, Mongolia Ethnicity, Mongolia Ethnicity, Mongolia 1 Khalkh 2 Kazak 3 Dorvod 4 Buriad 5 Bayad 6 Dariganga 7 Uriankhai 8 Zakhchin 9 Darkhad 10 Torguud 11 Oold 12 Khoton 13 Myangad 14 Barga 15 Uzemchin 16 Kharchin 17 Tsakhar 18 Khotgoid 21 Khamnigan 23 Sartuul 24 Tuva 26 Uzbek 30 Other ethnic group (Mongolian citizen) 31 Russian (Mongolian citizen) 32 Chinese (Mongolian citizen) 40 Russian (Russian citizen) 50 Chinese (PRC citizen) 60 Other ethnic group (foreign citizen) 98 Unknown 99 NIU (not in universe) ETHNICMN indicates the person's ethnicity in Mongolia. IPUMS Nativity status Nativity status Nativity status Nativity status Nativity status NIU (not universe) 1 Native-born 2 Foreign-born 9 Unknown/missing NATIVITY indicates whether the person was native- or foreign-born. IPUMS Year [person version] Year [person version] Year [person version] Year [person version] Year [person version] [This file is just a placeholder. See the household version of the variable.] This is a 4-digit numeric variable with 0 implied decimal places IPUMS IPUMS sample identifier [person version] IPUMS sample identifier [person version] IPUMS sample identifier [person version] IPUMS sample identifier [person version] IPUMS sample identifier [person version] [This file is just a placeholder. See the household version of the variable.] This is a 9-digit numeric variable with 0 implied decimal places IPUMS Household serial number [person version] Household serial number [person version] Household serial number [person version] Household serial number [person version] Household serial number [person version] [This file is just a placeholder. See the household version of the variable.] This is a 10-digit numeric variable with 0 implied decimal places IPUMS Country [person version] Country [person version] Country [person version] Country [person version] Country [person version] [This file is just a placeholder. See the household version of the variable.] This is a 3-digit numeric variable with 0 implied decimal places IPUMS Record type [person version] Record type [person version] Record type [person version] Record type [person version] Record type [person version] [This file is just a placeholder. See the household version of the variable.] This is a 1-digit numeric variable with 0 implied decimal places IPUMS